Current Perspectives in microRNAs (miRNA)

Current Perspectives in microRNAs (miRNA)

Shao-Yao Ying Editor

Current Perspectives in microRNAs (miRNA)

Editor Shao-Yao Ying University of Southern California Los Angeles, CA USA

ISBN 978-1-4020-8532-1

e-ISBN 978-1-4020-8533-8

Library of Congress Control Number: 2008930759 © 2008 Springer Science + Business Media B.V. No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed on acid-free paper 9 8 7 6 5 4 3 2 1 springer.com

Contents

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Structures of MicroRNA Precursors ..................................................... Piotr Kozlowski, Julia Starega-Roslan, Marta Legacz, Marcin Magnus, and Wlodzimierz J. Krzyzosiak

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Small RNA Technologies: siRNA, miRNA, antagomiR, Target Mimicry, miRNA Sponge and miRNA Profiling ...................... Guiliang Tang, Yu Xiang, Zhensheng Kang, Venugopal Mendu, Xiaoyun Jia, Qi-Jun Chen, Xiaohu Tang, and Xiaoqing Tang

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RNA Interference Expression Vectors Based on miRNAs and RNA Splicing ................................................................................ Akua N. Bonsra, Joshua Yonekubo, and Guangwei Du

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Recent Application of Intronic MicroRNA Agents in Cosmetics ......................................................................................... Shi-Lung Lin, David T.S. Wu, and Shao -Yao Ying

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MicroRNA Profiling in CNS Tissue Using Microarrays .................. Reuben Saba and Stephanie A. Booth

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MicroRNA and Erythroid Differentiation ......................................... Mei Zhan and Chao-Zhong Song

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Homeotic miRNAs: From Development to Pathologies ....................... Maya Ameyar-Zazoua, Irina Naguibneva, Linda Pritchard, and Annick Harel-Bellan

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MicroRNA in Muscle Development and Function ............................... Zhongliang Deng and Da-Zhi Wang

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MicroRNAs and Regenerative Medicine ............................................... Ji Wu and Zhaojuan Yang

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Role of mir-302 MicroRNA Family in Stem Cell Pluripotency and Renewal .................................................................... Shi-Lung Lin and Shao-Yao Ying

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Epigenetic Regulation of miRNA in Stem Cells ................................. Keith Szulwach, Xuekun Li, Xinyu Zhao, and Peng Jin

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Identification of Cellular Targets for Virally-Encoded miRNAs by Ectopic Expression and Gene Expression Profiling ...... Mark A. Samols, Rebecca L. Skalsky, and Rolf Renne

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MicroRNA in Neuropsychiatric Diseases ............................................ Evgeny I. Rogaev, Denis V. Islamgulov, and Anastasia.P. Grigorenko

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Role of Repeat-Associated MicroRNA(ramRNA) in Fragile X Syndrome (FXS) ............................................................... Shi-Lung Lin and Shao -Yao Ying

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miRNA and Schizophrenia ................................................................... Diana O. Perkins and Clark D. Jeffries

16 SNPs in microRNA and microRNA Target Sites Associated with Human Cancers ................................................... Shi-Hsiang Shen and Zhenbao Yu 17

Expression and Function of microRNAs in Chronic Myeloid Leukemia ................................................................................. Michaela Scherr, Letizia Venturini, and Matthias Eder

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MicroRNAs in Vascular Neointimal Lesion Formation .................... Chunxiang Zhang

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microRNA in Cutaneous Wound Healing ........................................... Chandan K. Sen and Sashwati Roy

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CpG Island Hypermethylation, miRNAs, and Human Cancer .............................................................................. Amaia Lujambio and Manel Esteller

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Microarray Profiling of microRNA Changes in Cells That Express HIV-1 Proteins ............................................................... Man Lung Yeung and Kuan-Teh Jeang

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microRNA-Associated Therapies ......................................................... Anne Saumet, Guillaume Vetter, Nicolas Cougot, Manuella Bouttier, Florence Rage, Khalil Arar, and Charles-Henri Lecellier

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The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants ............................................................. George J. Wagner and Antoaneta B. Kroumova

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Index ................................................................................................................

461

Chapter 1

Structures of MicroRNA Precursors Piotr Kozlowski**, Julia Starega-Roslan**, Marta Legacz, Marcin Magnus, and Wlodzimierz J. Krzyzosiak*

Abstract MicroRNAs are single-stranded regulatory RNAs of 18–25 nucleotide length generated from endogenous transcripts that form local hairpin structures. The processing of microRNA transcripts involves the activities of two RNase III enzymes Drosha and Dicer. In this study we analyzed structural features of human microRNA precursors that make these transcripts Drosha and Dicer substrates. The structures of minimal functional primary precursors (pri-microRNAs) and secondary precursors (pre-microRNAs) were predicted. The frequency, nucleotide sequence content and the localization of various structure destabilizing motifs was analyzed. We identified numerous pri-microRNAs which structures strongly depart from the consensus structure and their processing is hard to explain by the existing model of the Microprocessor complex. We also found a biased distribution of symmetric and asymmetric motifs along the pre-microRNA hairpin stem and an overrepresentation of bulges on its 5′ arm (p < 0.000001), which may have considerable functional implications. Keywords miRNA biogenesis, Dicer, Drosha, RNA structure prediction, pri-miRNAs, pre-miRNA structural motifs

1.1

Introduction

MicroRNAs (miRNAs) are a family of short single-stranded noncoding RNAs identified in many eukaryotes from simple organisms to humans [1, 8]. It is anticipated that hundreds of miRNAs regulate the expression of thousands of human genes [20]. MiRNAs regulate gene expression at the posttranscriptional

Laboratory of Cancer Genetics, Institute of Bioorganic Chemistry, Polish Academy of Science, Noskowskiego 12/14, 61-704 Poznan, Poland * Corresponding author: E-mail: [email protected] ** These authors contributed equally to this work.

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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level by programming the RNA induced silencing complex (miRISC) which interacts with the complementary sequences of mRNAs causing their translational inhibition or cleavage [25, 33]. Specific miRNAs were shown to be engaged in the variety of processes such as development, cell proliferation, differentiation and apoptosis [12]. The detailed cellular function of the majority of miRNAs still remains unknown. The primary transcripts of miRNA genes (pri-miRNAs) are generated by either RNA polymerase II [19] or RNA polymerase III [4]. The pri-miRNAs, which harbor a long stem and loop structure, are processed in the nucleus to shorter, approximately 60-nt hairpin precursors (pre-miRNAs) (Fig. 1.1A). The nuclear processing enzyme is ribonuclease Drosha [18] which acts together with the DGCR8 protein [17] within the Microprocessor complex [5, 7]. Drosha which is the RNaseIII enzyme usually leaves a 2 nt overhang at the 3′-end of pre-miRNA and defines one end of mature miRNA [2]. The pre-miRNAs are then exported to cytoplasm by Exportin-5 [22] and further processed to miRNA duplexes by another RNaseIII enzyme Dicer [3, 26, 34] which defines the other miRNA end. Thus, the two RNA processing steps reduce the stem of the primary precursor hairpin into its internal portion, which usually is the imperfect duplex containing a functional miRNA strand (Fig. 1.1B). The presence of structure imperfection within this duplex facilitates its non-miRNA strand to be later disposed from the miRISC using the “bypass” rather than the cleavage mechanism [6]. It is clear that the structures of miRNA precursors are instrumental for their proper recognition and correct cleavages by the processing complexes containing Drosha and Dicer. Therefore, to analyze the structural aspects of both the nuclear and cytoplasmic steps of miRNA biogenesis the structures of the primary and secondary miRNA precursors need to be established. This can be done either by experiment or computational structure prediction. The latter approach gives the reliable structures of miRNA precursors that were confirmed in most of the investigated cases by experimental analysis [13]. The computational approach is also much faster thus better suited for structure analysis on a large scale. In order to predict the secondary structures of miRNA precursors their nucleotide sequences need to be known first. These sequences, however, are not available in the existing miRNA databases. For the purpose of this study the sequences of pre-miRNAs were reconstructed from the sequences of mature miRNAs as described earlier [14]. To analyze the pri-miRNA sequences the concept of a “minimal” functional precursor was adapted [9]. The pri-miRNA precursors may be very long and as such they are not amenable for a detailed structure analysis. Therefore, we analyzed minimal pri-miRNAs which were considered to be the shortest fragments of primary precursors that contain all sequence and structure elements required to be functional substrates for a Microprocessor. The difference between our approach and that described earlier [9] was that not a single length but several different lengths of sequences harboring miRNA were analyzed. Both the reconstructed sequences of pre-miRNAs and arbitrarily selected sequences of minimal pri-miRNAs were then subjected to structure prediction and a detailed analysis of their secondary structures. We intended to learn more about the occurrence and localization of different types of secondary structure

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Fig. 1.1 Biogenesis of miRNA. (A) Steps of miRNA biogenesis. Proteins involved in substrate recognition and precursor processing are shown. (B) Schemes of the Microprocessor complex and RNase Dicer interacting with their substrates, pri-miRNA and pre-miRNA, respectively. Arrows indicate Drosha and Dicer cleavage sites. RIIIa and RIIIb indicate the RNase domains responsible for cleavage. dsRBD denotes the double-stranded RNA binding domain. The fragment which corresponds to miRNA is marked in gray. (C) Scheme of minimal precursor pri-miRNA. The SD (single-stranded–double-stranded) and SL (stem-loop) junctions, internal distances and analyzed region are indicated. SD is postulated to be the DGCR8 protein binding site

motifs within the precursor hairpin. A comprehensive inventory of such motifs was generated and analyzed in relevance to the Drosha and Dicer steps of miRNA biogenesis.

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1.2 1.2.1

P. Kozlowski et al.

Materials and Methods Analysis of Pri-miRNA Structures

The sequences of minimal pri-miRNAs of the four length variants 110, 130, 150 and 300 nt were precut from longer sequences withdrawn from the GenBank for all 461 miRNAs deposited in the miRBase database version 8.2. [8]. To obtain the minimal pri-miRNA sequence of selected length, the natural sequence extensions of the required and equal length were added to each end of the pre-miRNA. These 1,844 sequences were subjected to secondary structure prediction by free energy minimization using the Mfold program [36]. The suboptimality parameter was set at 5% which means that all structures that have the free energy of the formation (∆G) 5% higher than the lowest energy structure were also shown. For further analysis only the lowest energy structures were taken. The critical parameter analyzed in the predicted structures was the length of the base-paired region in which only minor structure distorting motifs were allowed to exist. Only those minimal pri-miRNAs were taken for further analysis which had the same structure of the analyzed fragment in at least the 150 and 300 nt length variants. There were 246 such precursors, and among them were 180 pri-miRNAs which had the same structure of the fragment of interest in all four length variants.

1.2.2

Analysis of Pre-miRNA Structures

Prior to the structure analysis of pre-miRNAs their nucleotide sequences were reconstructed following the rules described earlier [14]. Briefly, a one arm terminus of the precursor hairpin was defined by one end of the miRNA sequence and the second arm terminus was defined either by the miRNA* end or assuming the existence of the 2 nt 3′ overhang at the Drosha cleavage site. The secondary structures of the pre-miRNAs were predicted using Mfold as described above for pri-miRNAs. All secondary structure motifs present in the lowest free energy structures were catalogued in the format that included the number and sequence of nucleotides present in the specific motif, the motif orientation and its localization within the precursor structure. These motifs were classified into two major groups: symmetric internal loops (SL) and asymmetric internal loops (AL). The first group includes both single nucleotide mismatches SL1:1 and longer symmetric loops SL2:2, SL3:3 etc. The second group includes bulges of different length AL0:1, AL0:2, AL0:3 etc. and asymmetric internal loops ALX:Y where both X and Y are different from 0. Thus, each motif is denoted by two numbers separated by the colon. The number or sequence before and after the colon denotes nucleotides from the precursor 5′ precursor arm and 3′ arm, respectively. For example, the single nucleotide bulge “a” located in the 5′ arm is denoted either AL1:0 or a:0. The localization of the motif was numbered counting from the terminal nucleotide at the 5′ arm of the

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pre-miRNA. To unify the position numbering system for all types of structural motifs the position of nucleotide directly preceding any specific motif was assigned as the motif position.

1.2.3

Statistical Methods

For asymmetric motifs their equal distribution between two pre-miRNA arms was assumed (null hypothesis). To assess the potential deviation from this distribution the chi2-squared test was applied using Statistica (StatSoft, Tulsa, OK) or Prism v. 4.0 (GraphPad Software, San Diego, CA). To compare the distribution of symmetric vs. asymmetric loops in pre-miRNAs having a moderate and high number of stem structure distorting motifs the Fisher exact test was used for the 2 × 2 contingency table analysis (programs as above). Where applicable, the Bonferroni adjustment for multiple comparisons was used.

1.3 1.3.1

Results Pri-miRNA Structure and Drosha Step of miRNA Biogenesis

In agreement with the recently proposed model of the Microprocessor structure the DGCR8 protein binds to the base of the pri-miRNA hairpin stem and forms a platform for Drosha binding and precursor cleavage [9] (Fig. 1.1B). DGCR8 anchors to the single strand-double strand (SD) junction in the structure of pri-miRNA. The consensus structure of minimal pri-miRNA was established based on the analysis of the predicted structures of numerous human primary precursors and the structure prediction was performed using the 110 nt long sequence for each pri-miRNA [9]. In light of the fact that human pre-miRNAs span the length range of 42–82 nt [14], the length of 110 nt seemed insufficient for the reliable minimal pri-miRNA structure prediction. To minimize the risk of taking an incorrect structure into consideration besides the 110 nt also three longer sequences harboring miRNAs were used for structure prediction in our study. Such an approach was undertaken because the structures generated by computer programs used for RNA structure prediction by free energy minimization are more trusted if the same critical domains are predicted from the sequences of different lengths. The detailed analysis of the predicted structures of minimal pri-miRNA precursors was focused on the fragment localized between the pre-miRNA ends and SD junction (Fig. 1.1C), which was proposed to play a critical role in pri-miRNA recognition by the Microprocessor [9]. In the consensus minimal pri-miRNA structure this region spanned 11 bp, which equals to one helical turn of A-RNA. We wanted to find out whether the consensus minimal

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Fig. 1.2 Pri-miRNA stem length distribution. The length distribution of base-paired stems having either full base complementarity or only minor disruptions (small internal loops, bulges) within the analyzed fragment in 243 minimal pri-miRNA precursors. Above the graph schematic structures representing three classes of such precursors are shown. They differ in the length of the analyzed fragment

pri-miRNA structure is correct and find the most deviant structures which still remain substrates for the Microprocessor. It turned out from this analysis that there are indeed pri-miRNAs which secondary structures ideally fit to the consensus structure e.g. pri-miR-33 but there are also precursors which have the analyzed region either much shorter e.g. pri-miR-656 or much longer e.g. pri-miR-607. However, in the majority of the analyzed structures (62.6%) the SD junction was located 9–13 nt below the Drosha cleavage site which is in rough agreement with the consensus structure proposed by Han et al. [9] and confirmed by Saetrom et al. [28]. This region was shorter in 13% of the analyzed precursors and longer in 19.5% of the precursors (Fig. 1.2). It is difficult to fit such precursors, especially their extreme examples, into the presently accepted model of pri-miRNA processing by the Microprocessor complex (Fig. 1.1C). This may suggest that either some alternative models of Microprocessor architecture need to be considered or precursors having structures most deviant from the consensus are processed in an entirely different way.

1.3.2

Pre-miRNA Structure and Dicer Step of miRNA Biogenesis

The structural insights into Dicer function came from both biochemical studies [35] and crystallography [23, 24]. In Fig. 1.1B the commonly accepted model of a Dicer single processing center is shown [35]. Human Dicer is composed of several

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functional domains: the PAZ domain, which is used for high-affinity binding to the 3′ overhanging nucleotides of pre-microRNA, the helicase domain, the DUF283 subunit, the dsRNA binding domain and two catalytic RNase III domains that form the intramolecular dimer during pre-miRNA cleavage [24, 35]. Thus, Dicer functions as a molecular ruler and cleaves the pre-miRNA hairpin about two helical turns away from the hairpin base to produce duplexes containing 18–24 nt long miRNAs. It is intuitively understood that the length diversity of miRNAs has its source in the structural features of pre-miRNA hairpins which rarely contain perfectly base paired stems. Usually the single nucleotide mismatches, the larger symmetric internal loops, bulges and the asymmetric internal loops break the regularity of the pre-miRNA double helical stem structure and may influence both the efficiency of Dicer binding and specificity of precursor cleavage. Therefore, a detailed analysis of the predicted secondary structures of pre-miRNAs was performed to search for such structure distortions. Out of the 461 nucleotide sequences of human pre-miRNAs which were subjected to structure prediction nearly all (456) formed hairpins as the lowest free energy structures. In these precursor hairpins as many as 1,243 secondary structure motifs destabilizing stem structures were found altogether and the occurrence of various types of motifs in each arm of the hairpin stem is shown in Fig. 1.3. These motifs include 631 symmetric internal loops of various sizes including single nucleotide mismatches (SL) and a similar number (612) of asymmetric internal loops including bulges (AL) (Fig. 1.3B). This means that 2.73 motifs (0.97 mismatches,

Fig. 1.3 The frequency of structural motifs in stems of 456 analyzed pre-miRNAs. (A) The chessboard-like table shows in numbers the occurrences of each type of structural motifs identified in the predicted structures of miRNAs. These motifs are shown as pairwise combinations of unpaired nucleotides present in precursor 5′ and 3′ arm. E.g. symmetric loops SL are located diagonally and bulges along the 0 column. In this and the subsequent figures the motifs under consideration are shadowed. (B) The total number of symmetric loops (SL) including mismatches (SL1:1) and asymmetric loops (AL) including all types of bulges

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0.42 symmetric loops of different length (2–5), 0.96 bulges and 0.38 asymmetric internal loops) occur, on average, per analyzed pre-miRNA.

1.3.3

Symmetric Loops Including Single Nucleotide Mismatches in Pre-miRNA Structures

In cataloguing the structural motifs present in pre-miRNAs we have looked not only at their type and size but also at their nucleotide sequence and orientation within the precursor hairpin. This allowed us to count symmetric internal loops containing a different number of nucleotides and divide them into sequence and orientation- specific subgroups. Figure 1.4A shows the number of occurrences of single nucleotide mismatches and 2–5 nt long symmetric internal loops as well as the number of occurrences of different nucleotides and sequences present in these motifs. It is apparent that the frequency of symmetric loops decreases with their size. The single nucleotide mismatches are most frequent and account for almost 2/3 of the total number of symmetric internal loops. The largest is the 5 nt long loop identified only once in hsa-mir-196a-1. As shown in Fig. 1.4A all ten possible base combinations of single nucleotide mismatches are represented in the pre-miRNAs and 61 different combinations of 2 nt long internal loops. For the 3–5 nt long internal loops the number of different sequence classes is almost equal to the total number of such loops. This means that almost every symmetric internal loop formed by more than two adjacent nucleotides has a different sequence and there is no preference of any specific sequence within such loops. For the single nucleotide mismatches and 2 nt long internal loops we analyzed their distribution between different sequence classes (Figs. 1.4B, C, respectively). It turned out that the a:c and c:u are most frequent among the former and the least frequent is the c:c mismatch (Fig. 1.4B). The orientation analysis of single nucleotide mismatches shows that most of them are rather equally distributed in both orientations with the exception of the c:u in which u is more frequent on the 5′ arm and c on the 3′ arm (36 and 58 c:u and u:c mismatches, respectively). However, this distribution is only marginally significant (ch2; p-val = 0.02) and not significant after Bonferroni correction. The 2 nt internal loops are almost randomly distributed among sequence subclasses and clear ug:ug overrepresentation is only observed (19 occurrences) (Fig. 1.4C).

1.3.4

Asymmetric Internal Loops Including Bulges in Pre-miRNA Structures

As many as 437 bulges account for the majority of asymmetric loops identified in the analyzed pool of pre-miRNAs. These bulges vary in size from 1 nt (293 occurrences) to 11 nt (single occurrence) (Fig. 1.5A). The frequency of bulges decreases with bulge

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Fig. 1.4 The symmetric loops in pre-miRNAs. (A) The number of single nucleotide mismatches and symmetric loops containing different numbers of unpaired nucleotides within the loop. The number of different nucleotide combinations in symmetric loops (dark gray), and total number of symmetric loops (light gray). (B) The number of different types of mismatches with their orientation taken into account and cumulative number (inset). (C) As in (B) but for 2 nt symmetric loops

size with almost a perfect exponential correlation (r2 = 0.97). The distribution of the most frequent bulges (1–3 nt) between the precursor hairpin arms shows their overrepresentation in the 5′ arm (Fig. 1.5A). Testing the null hypothesis that bulges are equally distributed between the 5′ and 3′ arms we showed that the total overrepresentation of bulges in the 5′ arm is very significant (chi2 p-val < 0.000001). Individual chi2 p-values for the 1-, 2- and 3 nt bulges are 0.00002, 0.014 and 0.23 respectively. The nucleotides present in the single nucleotide bulges and sequences present in the

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Fig. 1.5 The bulges in pre-miRNAs. (A) (center) The total number of bulges containing a different number of nucleotides (1–11 nt). (right) For the most frequent 1–3 nt bulges the total number of bulges was split between two orientations 0:X and X:0 for bulges in the 3′ and 5′ arm of pre-miRNA, respectively. (B) The number of different nucleotides in single-nucleotide bulges. The 0:1 and 1:0 orientations are shown separately. (C) As in (B) but for different combinations of nucleotides in 2 nt bulges

2 nt bulges are shown in Fig. 1.5B, C, respectively. Among the former the most frequent is u and least frequent is g (Fig. 1.5B). The 2 nt bulges are almost equally distributed over sequence variants and almost all combinations of 2 nt sequences occur (except for gc) (Fig. 1.5C). The asymmetric internal loops containing a different number of unpaired nucleotides on each side constitute a smaller and more heterogenous group (177 occurrences). In this group the small motifs such as AL1:2 and AL2:1 are most frequent but single cases of large motifs e.g. AL6:4 and AL3:10 were also found. The analysis of their sequence contents did not reveal any significant preferences.

1 Structures of MicroRNA Precursors

1.3.5

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Localization of Structural Motifs Within the Pre-miRNA Hairpin Stem

The proper localization of structural motifs in pre-miRNAs may facilitate the adaptation of precursor structures to the interacting proteins of miRNA biogenesis machinery. It may create a suitable environment for interaction with the specific RNA binding motifs of proteins and serve as a code for structure-specific RNA recognition. Therefore we looked in this study also at the localization of structural motifs in the pre-miRNA hairpin stem. As shown in Fig. 1.6 there is no specific position in which the single nucleotide mismatches and symmetric internal loops would be either over represented or under represented (Fig. 1.6A, B). However, a clear trend is observed to decrease the frequency of these motifs in going from the precursor base towards the terminal loop. This trend is most clear for single nucleotide mismatches and 2 nt long symmetric internal loops. The number of longer symmetric loops (4 and 5 nt) is too low to see any trend (Fig. 1.6A). Interestingly, the opposite trend is observed for asymmetric motifs the frequency of which increases in the same direction (Fig. 1.6C).

1.4

Discussion

The bioinformatics survey of miRNA precursor structures which was performed in this study provides a comprehensive insight into the structural variety of both pri-miRNAs and pre-miRNAs. This insight may be considered as next step towards a better understanding of the role of RNA structure in miRNA biogenesis. The obtained gallery of predicted structures of miRNA precursors will guide the selection of specific precursors for a more detailed experimental analysis of their structures and studies of their interactions with Drosha and Dicer protein complexes. The structural features of the precursors of numerous known miRNAs will also help to refine algorithms used for the identification of novel miRNA genes in genomes. In addition, the structural information gathered in this study may be relevant to the process of RISC loading by miRNA/miRNA* duplexes that may retain the structure imperfections present within miRNA precursors. We catalogued the rich repertoire of secondary structure motifs destabilizing and distorting the stem structures of pre-miRNAs paying attention to the nucleotide sequences present within these motifs and motif localization. The detailed analysis of this data collection revealed that with some exceptions there are only minor preferences for specific sequences in the destabilizing motifs present in pre-miRNA structures. This means that protein complexes involved in miRNA biogenesis use structure rather than sequence code for precursor recognition. As shown in this study there are about 2.7 stem structure destabilizing motifs in the average pre-miRNA hairpin. The number of pre-miRNAs containing a different number of such motifs is almost normally distributed with extreme numbers being 0 and 7 motifs per premiRNA (Fig. 1.7A). Taking into account this distribution and assuming somehow

12 Fig. 1.6 The localization of structural motifs in the pre-miRNA hairpin structure. (A) The localization of mismatches SL1:1 and symmetric internal loops having a different number of nucleotides SL2:2 – SL5:5 within precursor structure. (B) The cumulative number of mismatched nucleotides along the pre-miRNA hairpin. (C) Localization of bulges within the precursor structure

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arbitrarily the ~5% threshold of pre-miRNAs with extreme numbers of structural motifs we divided all the analyzed pre-miRNAs into three classes: (1) having 0 structure destabilizing motifs (2%), (2) containing a moderate number (1–4) of such motifs (93%), and (3) harboring high number (5–7) motifs (5%). The analysis of the symmetric and asymmetric loops distribution revealed a gradual increase of asymmetric motifs with the total number of motifs in pre-miRNAs. When we compared the frequency of SL vs. AL in pre-miRNAs with a moderate and high number of motifs it showed significant excess of AL in pre-miRNAs containing a high total number of motifs (p-val = 0.0005) (Fig. 1.7B). This could reflect the compensatory effect to balance the structure distortion introduced by one bending motif by another. The biased distribution of bulges observed in this study consisted of their overrepresentation in the 5′arm of pre-miRNA. To validate this result we analyzed the distribution of bulges also in the group of “prototypical” pre-miRNAs recently distinguished by Tuschl’s group [16] on the basis of the precise miRNA 5′ end processing, sequence conservation and high number of putative target sites [16]. We have shown that in the “prototypical” group the overrepresentation of bulges in the 5′ arm is even higher than that revealed in the group of pre-miRNAs analyzed in our study (compare results shown in Fig. 1.8A with those in Fig. 1.5A). Although the number of “prototypical” miRNA precursors is smaller (266) than the total number of pre-miRNAs analyzed by us (456) the statistical significance of the disproportional distribution of bulges is even higher for the “prototypical” group. Contrary to that group the observed bias completely disappears in the group of

Fig. 1.7 Statistics of pre-miRNAs containing a high number, moderate number and no structure destabilizing motifs. (A) The number and frequency (inset) of pre-miRNAs having a different number of structure distortions in the hairpin stem. Assuming the ~5% threshold we distinguished three groups of miRNA precursors with a high number (5–7), moderate number (1–4) and no (0) stem distortion. (B) Distribution of SL and AL motifs in precursors containing a different number of structural motifs and frequency of SL and AL motifs in precursors having a moderate and high number of structural motifs (inset)

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“repeat-derived” miRNAs. Also the distribution of internal asymmetric loops observed in this study is in line with a lower tolerance of excessive nucleotides in the 3′ arm of pre-miRNA. Our analysis shows an overrepresentation of loops having a higher number nucleotides in the 5′ arm (Fig. 1.3A). However, the number of asymmetric internal loops is relatively small and this effect is not statistically significant. To find out whether the bulges overrepresented in the 5′ arm of pre-miRNA are equally distributed along the hairpin structure we compared the localization of the 5′ and 3′ arm bulges (Fig. 1.8B). It appears from this comparison that bulges in the 5′arm are not equally distributed but they tend to be clustered at two sites with maxima at nucleotide positions 11 and 18. These sites could be involved in the bending of the pre-miRNA structures and/or in interactions with specific protein domains. Comprehensive information on the distribution of various structural motifs in miRNA precursors will be also useful to fine-tune the algorithms used for the ab initio prediction of miRNA genes. Numerous algorithms have been developed to distinguish miRNA precursors from other hairpin structures encoded by genomes [10, 21, 30, 31]. These algorithms use different conservation, thermodynamic, sequence and structure parameters. The latter include some general parameters such as the length of the longest fully base-paired stem, terminal loop size, the number of nucleotides in the symmetric and asymmetric loops including bulges [15, 27, 29] as well as more specific structural characteristics such as frequency of triplet structure elements [11, 27, 32]. The results of our study show that there are also other highly

Fig. 1.8 The overrepresentation of bulges in the 5′-arm of prototypical pre-miRNAs. (A) As in (Fig. 1.5A) but separately for prototypical and repeat-derived classes of miRNA [16]. (B) Localization of bulges in the 5′-arm (black) or 3′-arm (gray) of pre-miRNA structure

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significant features of pre-miRNA structure that might facilitate miRNA gene prediction. These parameters include: strong overrepresentation of bulges in the 5′ arm of pre-miRNA, the opposite polarity of symmetric and asymmetric motifs distribution along the hairpin stem and increased contribution of asymmetric motifs when the total number of stem structure destabilizing motifs in pre-miRNAs increases. Acknowledgement This work was supported by funding under the Sixth Research Framework Programme of the European Union, Project RIGHT (LSHB-CT-2004-005276) and by the Ministry of Science and Higher Education, Grant No. N301 112 32/3910.

References 1. Bartel, D. P. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116, 281–297. 2. Basyuk, E., Suavet, F., Doglio, A., Bordonne, R., and Bertrand, E. (2003). Human let-7 stemloop precursors harbor features of RNase III cleavage products. Nucleic Acids Res 31, 6593–6597. 3. Bernstein, E., Caudy, A. A., Hammond, S. M., and Hannon, G. J. (2001). Role for a bidentate ribonuclease in the initiation step of RNA interference. Nature 409, 363–366. 4. Borchert, G. M., Lanier, W., and Davidson, B. L. (2006). RNA polymerase III transcribes human microRNAs. Nat Struct Mol Biol 13, 1097–1101. 5. Denli, A. M., Tops, B. B., Plasterk, R. H., Ketting, R. F., and Hannon, G. J. (2004). Processing of primary microRNAs by the microprocessor complex. Nature 432, 231–235. 6. Gregory, R. I., Chendrimada, T. P., Cooch, N., and Shiekhattar, R. (2005). Human RISC couples microRNA biogenesis and posttranscriptional gene silencing. Cell 123, 631–640. 7. Gregory, R. I., Yan, K. P., Amuthan, G., Chendrimada, T., Doratotaj, B., Cooch, N., and Shiekhattar, R. (2004). The microprocessor complex mediates the genesis of microRNAs. Nature 432, 235–240. 8. Griffiths-Jones, S., Grocock, R. J., van Dongen, S., Bateman, A., and Enright, A. J. (2006). miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 34, D140–144. 9. Han, J., Lee, Y., Yeom, K. H., Nam, J. W., Heo, I., Rhee, J. K., Sohn, S. Y., Cho, Y., Zhang, B. T., and Kim, V. N. (2006). Molecular basis for the recognition of primary microRNAs by the Drosha-DGCR8 complex. Cell 125, 887–901. 10. Huang, T. H., Fan, B., Rothschild, M. F., Hu, Z. L., Li, K., and Zhao, S. H. (2007). MiRFinder: an improved approach and software implementation for genome-wide fast microRNA precursor scans. BMC Bioinformatics 8, 341. 11. Jiang, P., Wu, H., Wang, W., Ma, W., Sun, X., and Lu, Z. (2007). MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features. Nucleic Acids Res 35, W339–344. 12. Kim, V. N., and Nam, J. W. (2006). Genomics of microRNA. Trends Genet 22, 165–173. 13. Krol, J., Sobczak, K., Wilczynska, U., Drath, M., Jasinska, A., Kaczynska, D., and Krzyzosiak, W. J. (2004). Structural features of microRNA (miRNA) precursors and their relevance to miRNA biogenesis and small interfering RNA/short hairpin RNA design. J Biol Chem 279, 42230–42239. 14. Krol, J., Starega-Roslan, J., Milanowska, K., Nowak, D., Kubiaczyk, E., Nowak, M., Majorek, K., Kaminska, K., and Krzyzosiak, W. J. (2006). Structural Features of microRNAs and Their Precursors, In microRNA: Biology, Function & Expression, N. Clarke, and P. Sanseau, eds. (DNA Press), Eagleville, PA, pp. 95–110. 15. Lai, E. C., Tomancak, P., Williams, R. W., and Rubin, G. M. (2003). Computational identification of Drosophila microRNA genes. Genome Biol 4, R42.

16

P. Kozlowski et al.

16. Landgraf, P., Rusu, M., Sheridan, R., Sewer, A., Iovino, N., Aravin, A., Pfeffer, S., Rice, A., Kamphorst, A. O., Landthaler, M., et al. (2007). A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 129, 1401–1414. 17. Landthaler, M., Yalcin, A., and Tuschl, T. (2004). The human DiGeorge syndrome critical region gene 8 and its D. melanogaster homolog are required for miRNA biogenesis. Curr Biol 14, 2162–2167. 18. Lee, Y., Ahn, C., Han, J., Choi, H., Kim, J., Yim, J., Lee, J., Provost, P., Radmark, O., Kim, S., and Kim, V. N. (2003). The nuclear RNase III Drosha initiates microRNA processing. Nature 425, 415–419. 19. Lee, Y., Kim, M., Han, J., Yeom, K. H., Lee, S., Baek, S. H., and Kim, V. N. (2004). MicroRNA genes are transcribed by RNA polymerase II. EMBO J 23, 4051–4060. 20. Lewis, B. P., Burge, C. B., and Bartel, D. P. (2005). Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120, 15–20. 21. Lim, L. P., Glasner, M. E., Yekta, S., Burge, C. B., and Bartel, D. P. (2003). Vertebrate microRNA genes. Science 299, 1540. 22. Lund, E., Guttinger, S., Calado, A., Dahlberg, J. E., and Kutay, U. (2004). Nuclear export of microRNA precursors. Science 303, 95–98. 23. Macrae, I. J., Zhou, K., and Doudna, J. A. (2007). Structural determinants of RNA recognition and cleavage by Dicer. Nat Struct Mol Biol 14, 934–940. 24. Macrae, I. J., Zhou, K., Li, F., Repic, A., Brooks, A. N., Cande, W. Z., Adams, P. D., and Doudna, J. A. (2006). Structural basis for double-stranded RNA processing by Dicer. Science 311, 195–198. 25. Pillai, R. S., Bhattacharyya, S. N., Artus, C. G., Zoller, T., Cougot, N., Basyuk, E., Bertrand, E., and Filipowicz, W. (2005). Inhibition of translational initiation by Let-7 MicroRNA in human cells. Science 309, 1573–1576. 26. Provost, P., Dishart, D., Doucet, J., Frendewey, D., Samuelsson, B., and Radmark, O. (2002). Ribonuclease activity and RNA binding of recombinant human Dicer. EMBO J 21, 5864–5874. 27. Ritchie, W., Legendre, M., and Gautheret, D. (2007). RNA stem-loops: to be or not to be cleaved by RNAse III. RNA 13, 457–462. 28. Saetrom, P., Snove, O., Nedland, M., Grunfeld, T. B., Lin, Y., Bass, M. B., and Canon, J. R. (2006). Conserved microRNA characteristics in mammals. Oligonucleotides 16, 115–144. 29. Sewer, A., Paul, N., Landgraf, P., Aravin, A., Pfeffer, S., Brownstein, M. J., Tuschl, T., van Nimwegen, E., and Zavolan, M. (2005). Identification of clustered microRNAs using an ab initio prediction method. BMC Bioinformatics 6, 267. 30. Sheng, Y., Engstrom, P. G., and Lenhard, B. (2007). Mammalian MicroRNA prediction through a support vector machine model of sequence and structure. PLoS ONE 2, e946. 31. Wang, X., Zhang, J., Li, F., Gu, J., He, T., Zhang, X., and Li, Y. (2005). MicroRNA identification based on sequence and structure alignment. Bioinformatics 21, 3610–3614. 32. Xue, C., Li, F., He, T., Liu, G. P., Li, Y., and Zhang, X. (2005). Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. BMC Bioinformatics 6, 310. 33. Yekta, S., Shih, I. H., and Bartel, D. P. (2004). MicroRNA-directed cleavage of HOXB8 mRNA. Science 304, 594–596. 34. Zhang, H., Kolb, F. A., Brondani, V., Billy, E., and Filipowicz, W. (2002). Human Dicer preferentially cleaves dsRNAs at their termini without a requirement for ATP. EMBO J 21, 5875–5885. 35. Zhang, H., Kolb, F. A., Jaskiewicz, L., Westhof, E., and Filipowicz, W. (2004). Single processing center models for human Dicer and bacterial RNase III. Cell 118, 57–68. 36. Zuker, M. (2003). Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 31, 3406–3415.

Chapter 2

Small RNA Technologies: siRNA, miRNA, antagomiR, Target Mimicry, miRNA Sponge and miRNA Profiling Guiliang Tang1*, Yu Xiang2, Zhensheng Kang3, Venugopal Mendu1, Xiaohu Tang1, Xiaoyun Jia1, Qi-Jun Chen1, and Xiaoqing Tang4

Abstract The breakthrough discovery of RNA interference (RNAi) by Fire and Mello in 1998 has ushered in a new wave of RNA-based technological advances in the life sciences. Small RNAs, namely small interfering RNA (siRNA) and microRNA (miRNA), not only play key roles in down regulating gene expression, controlling growth and development, stress response, and various diseases, but also serve as essential tools for the study of gene functions. In this chapter, we provide an overview of the technological aspects of siRNAs and miRNAs and common methods for studying their functions. Keywords siRNA, miRNA, antagomiR, target mimicry, miRNA sponge, miRNA profiling

2.1

Introduction

RNA interference (RNAi) was the 2006 Nobel Prize winning discovery [135], although related research is still at an early stage and continuing at a rapid pace. RNAi technology has become one of the most important technological tools and is

1

Gene Suppression Laboratory, Department of Plant and Soil Sciences and KTRDC, University of Kentucky, Lexington, KY 40546, USA

2 Pacific Agri-Food Research Centre, Agriculture and Agri-Food Canada, Box 5000, 4200 Highway 97, Summerland, BC V0H1Z0, Canada 3 College of Plant Protection, Shaanxi Provincial Key Lab of Molecular Biology for Agriculture, Northwest Agriculture and Forestry (A & F) University, Yangling, 712100, China 4 Department of Molecular and Cellular Biochemistry, University of Kentucky College of Medicine, 741 South Limestone, Lexington, KY 40536, USA

* Corresponding author: Phone: 856 257 1594; Fax: 859 323 1077; E-mail: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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now widely applied in almost every research aspect of modern biology. The key elements in RNAi are the small RNAs of ∼21 nucleotides (nt), termed small interfering RNAs (siRNAs) [22–24, 39, 138]. SiRNAs regulate their target genes by binding in a sequence-specific manner to target gene transcripts (e.g. mRNAs), and inducing degradation of target RNAs or blocking their translations [20, 138]. The simple structure of siRNAs allows them to be easily generated in large quantities by chemical synthesis [22]. Synthetic siRNAs, as powerful reagents, bypass their biogenesis steps in RNAi and induce potent and specific silencing of any gene of interest in cells [22]. MicroRNA (miRNA), the siRNA cousin, is produced by RNAi-like mechanisms or miRNA pathways [3], and plays a key role in gene regulation, cell developmental control and various disease development [7]. More than 450 miRNAs encoded by the human genome have been identified and are predicated to regulate the expression of about one third of human coding genes [71, 130]. The development of many types of cancers or diseases is related to the abnormal expression or loss of certain miRNAs [11, 12, 17]. The global miRNA expression patterns of specific organs, tissues or cells can serve as an miRNA atlas or as biomarkers for the study of miRNA functions [65]. As a result, one can potentially reverse metastatic cancers by blocking the abnormally-expressed miRNAs or by reintroducing the lost miRNAs during cancer progression [80]. Much evidence indicates that many miRNAs function not only individually but also coordinately in gene regulation or in specific disease development [41]. Thus, this creates a new direction for studying a specific disease at the cellular level by simultaneously manipulating multiple miRNAs. Based on the study of the structures of miRNAs, artificial miRNAs have been developed as powerful tools for potently silencing genes in plants and animals [1, 89, 94, 101, 139, 140]. Compared to previous RNAi technologies, artificial miRNAs more accurately and specifically silence genes of interest and reduce off-target effects. More than 5,000 miRNAs have been identified from various organisms (http://microrna.sanger.ac.uk/) [32, 33], but very few of them have been functionally analyzed. It remains a big challenge to discover the functions of most miRNAs currently stored in the database. The emergence of new technologies, such as highthroughput miRNA array, antagomiR [59], miRNA target mimicry and miRNA sponge [18, 21, 30] provide new tools to understand how, where and when miRNAs are generated and function in specific tissues, cells and organisms. This chapter gives an overview of these different small RNA technologies and their applications.

2.2

The Basic Biology and Chemistry of siRNAs and miRNAs and Their Related Working Mechanisms

SiRNA and miRNA are ~21–23 nt small RNAs produced in cells via a series of enzymatic steps. Long double-stranded RNA (dsRNA) or stem-loop structured RNAs introduced or transcribed in cells are first processed into siRNA or miRNA duplexes by a dsRNA specific RNase-III family of enzymes termed Dicers [137].

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The small RNA duplexes are characterized by 2-nt overhangs at the 3′ ends with specific chemical end structures of a monophosphate at the 5′ end and a hydroxyl group at the 3′ end [44, 115]. In addition to differences in biogenesis, the siRNA duplex is a perfect duplex of Watson-Crick base pairs while the miRNA duplex is often an imperfect duplex with mismatches or bulges [114]. Both RNA duplexes need unwinding to form effector complexes: RNA-induced silencing complexes (RISCs) for their functionality. The key protein component of the effector complex is the Argonaute (AGO) protein of an evolutionally conserved protein super family [14]. The end structures of the small RNA duplex play a pivotal role in the assembly of the effectors or RISCs [76, 108]. After RISC assembly and maturation, specific gene transcripts, or messenger RNAs (mRNAs), are recognized and bound by the small RNAs on the RISCs based on sequence complementarities, leading to site-specific cleavage or translational repression of the mRNAs [28]. The elucidation of siRNA or miRNA chemical structures provides chemical approaches to generate them in large quantities for RNAi applications. Although single-stranded siRNA can be assembled into RISCs [81], synthetic siRNAs or miRNAs usually need to be double-stranded to be recognized by Dicer for initiating effective RISC assembly [77]. Thus, two short complementary RNA strands need to be synthesized and annealed to form siRNA or miRNA duplex characteristics with bona fide siRNA or miRNA end structures. In Drosophila, structurally distinct siRNA and miRNA duplexes are recognized by different Dicer proteins (DCR-1 and DCR-2) and sorted into distinct AGO proteins (AGO-1 and AGO-2) [29, 69, 91, 117]. DCR-2 sorts the siRNA duplex to be assembled into AGO-2 while DCR-1 sorts the miRNA duplex into the AGO-1 protein complex. Sometimes the two sorting systems are interchangeable based on siRNA or miRNA duplex structures or nucleotide compositions [29, 117]. SiRNA or miRNA duplexes can be divided into two types according to their end structures and thermodynamic stability: symmetric and asymmetric siRNA or miRNA [114]. A symmetric siRNA or miRNA assembles into two kinds of RISCs with either a sense strand or an antisense strand and can potentially interact with two different complementary target mRNAs for regulation [114]. However, siRNAs or artificial miRNAs are normally designed to target one specific gene transcript rather than two. Thus, symmetric siRNAs or miRNAs have a higher chance of targeting unwanted mRNAs due to their ability to target two different gene transcripts, leading to off-target effects. In contrast, asymmetric siRNAs or miRNAs preferentially favor only one specific strand of the small RNA duplex assembled into a RISC while the other strand is excluded from RISCs and is subsequently degraded [102]. This allows a maximum assembly of one specific strand of small RNA duplex into RISC components, considerably reducing off-target effects coming from the RISC assembled by the unwanted strand. Intriguingly, a major fraction of endogenous miRNAs are structurally asymmetric and display high specificity in the regulation of their target genes [50, 102], although a substantial number of miRNAs seem to have dual functions coming from each strand of the miRNA duplex (personal communication with Eric Lai). The asymmetric character seems a result of natural selection to reduce unwanted

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off-target effects for fine control of development during evolution. The asymmetric structure of endogenous miRNAs has been successfully adopted to design highly efficient artificial miRNAs to target genes of interest in plants and animals [1, 89, 94, 101, 139, 140]. Specific programs have also been developed to help design highly specific artificial miRNAs [101]. How can asymmetric siRNAs or miRNAs ensure that one specific strand is going into the RISC and excluding the other strand to prevent off-target effects? Recent research results indicate that RISC assembly and activation involve strand selection and exclusion by the RISCs. In the case of siRNAs, guide strand-associated RISCs exclude the passenger strand by guide-associated RISC directed cleavage of the passenger [70, 82, 95]. This cleavage has the same characteristics of RISCdirected target mRNA cleavage. That is, the cleavage site on the passenger strand is between the bases 10 and 11 from the 5′ end of the guider siRNA strand [24]. However, this cleavage depends on several prerequisites [82]. First, the AGO protein on the RISC must have “slicer” (endonuclease) activity. Second, there must be no mismatches or bulges between the guide strand and the passenger strand around the cleavage site. Thus, miRNA duplexes, which naturally have bulges or mismatches around the potential cleavage sites, likely employ other mechanisms to exclude and eliminate the passenger strand. This mechanism should be also true for RISCs on which the slicer activity is missing. In such cases, it remains unknown how the passenger strands are degraded after their exclusion from the RISCs, rather than cleaved by the slicer.

2.3

MiRNA Functional Analysis and miRNA Inhibitors

Like transcription factors, miRNA-directed regulation of post-transcriptional gene expression is wide-ranging [41]. First, the expression of many transcription factors themselves are regulated by miRNAs in plants and animals. Second, miRNAdirected gene regulation seems more extensive in animals than in plants due to distinct working mechanisms. One third of the human protein-coding genes are predicted to be regulated by different miRNAs [71, 130], but relatively very few miRNA-target interactions have been experimentally validated. Most identified or predicted miRNAs are functionally unknown. Thus, the study of miRNA functions constitutes a unique aspect of miRNA genomics. Due to the small size of miRNAs and their functions associated with specific target genes, functional analysis of miRNAs is substantially different from coding genes and as a result, various methods have been developed. An earlier approach to the study of miRNA targets was focused on computational predications based on the base-pairing conditions between miRNAs and their target genes [16, 51, 56, 96, 100, 106, 123, 124, 131, 134, 141]. The completion of the whole genome sequencing of various organisms expedited the discovery of new miRNA genes and their targets by a computational approach. The regulatory roles of miRNAs are reflected in the cellular functions of miRNA target genes.

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The prediction that one-third of human protein-coding genes are miRNA targets was mainly based on the assumption that a short stretch of “seed” region (~7 base pairs of the position 2 to 8 from the 5′ end of the miRNAs) between miRNAs and the 3′ untranslated region (UTR) of their targets is sufficient for regulation [71, 72, 130]. In contrast, regulation of target gene transcripts in plants by miRNAs seems predominantly reliant on extensive sequence complementarities between the miRNAs and their target genes. Thus, the number of predicted miRNA targets in plants is much more limited [98]. The outcomes of the interactions between plant miRNAs and their targets, in most cases, are the cleavage and degradation of the target mRNAs. Thus, validation of plant miRNA targets is relatively simple and can be done by assaying for target cleavage in vitro and in vivo. The first validations of miRNA-target interactions were reported in plants [78, 115]. Two experimental approaches were established for these validations: direct visualization of the target cleavage in vitro and cloning of the target cleavage products in vivo by 3′ or 5′ RACE-PCR. Traditional wheat germ extracts or newly established maize germ extracts (G. Tang, 2007) are convenient cell-free systems for miRNA target validation. Both systems contain abundant endogenous miRNAs that have already been loaded on the RISCs, and exogenous target mRNAs are readily cleaved by the existing miRNA-associated RISCs. However, these cell-free systems have limitations when validating miRNA-target interactions whose corresponding miRNAs do not exist in wheat or maize germ extracts. In vitro programming of active RISCs by synthetic miRNA duplexes in plant systems needs further exploration [83, 93, 115]. In contrast, Drosophila embryo extracts are capable of RISC assembly programmed by various kinds of small RNAs and can thus serve as a platform for animal miRNA target validations, as well as a useful heterologous system for validation of plant miRNA targets [38]. The validation of animal miRNA-target interactions is not trivial. First, most miRNA targets in animals are not directly cleaved but rather translationally repressed by miRNA-associated RISCs. Therefore, the validation needs to be conducted at the protein level. Detection of the change in protein expression of the target genes using specific antibodies is preferred for such validation [143]. Alternatively, reporter genes are often fused with the 3′ UTR of the target mRNAs for the purpose of validating translational repression by miRNAs [58]. A mammalian cell-free system was recently developed to recapitulate let-7 miRNA-directed translational repression in vitro, which will be useful in the validation of animal miRNA-target interactions [121]. This in vitro system was established with extracts from HEK293F cells transfected with expression vectors that contain genes encoding various miRNA pathway components, such as Dicer, TRBP2, Argonaute2 and GW182. This system is capable of processing chemically synthesized let-7 miRNA precursors into mature let-7 that is likely to be further assembled into RISC to direct translational repression. Based on this system, Wakiyama et al. found that let-7 miRNP complexes induced the deadenylation of the let-7 target mRNAs and the abolishment of cap-poly(A) synergy, leading to target mRNA translation blockage [121]. These in vivo and in vitro approaches are often used together to validate animal miRNA targets.

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Approaches to inducing a loss of function of miRNAs represent a powerful functional genomics tool. Traditional screening for mutation of miRNA genes has not proved very successful. This is because miRNAs are often encoded by multigene family members and the loss of function of one miRNA member is often obscured by redundant functions of other miRNA members that have almost identical sequences and the ability to bind and regulate the same target gene transcripts. Fortunately, different methods and strategies have been developed to block the regulatory functions of all members of any miRNA family. In vitro chemically modified miRNA inhibitors, such as ‘antagomirs’, or in vivo target mimicry in planta and miRNA sponge in mammalian cells have recently proved to be effective in blocking functions of specific miRNA families [21, 30, 59]. Chemically modified oligonucleotides have been widely used in the study of the loss-of-function of miRNAs. Based on antisense strategy, oligonucleotides complementary to the miRNAs act as competitive inhibitors of endogenous target mRNA binding to the miRNAs, leading to a suppression of miRNA functions. These have been developed and demonstrated to be very specific and potent inhibitors of targeted miRNAs [45, 59]. The major modification in antagomirs is 2′-O-methylation of the ribose, sometimes combined with other kinds of modifications such as phosphorothioate linkage near 5′ and 3′ ends and a cholesterol-moiety conjugated at 3′ end. Antagomir, usually 21–33 nt in length, sequence-specifically binds to specific target miRNAs through base-pairing [45, 59]. A traditional modified antisense oligo, such as morpholino that was previously used to knock down the expression of protein coding gene transcripts, also successfully knocked down specific miRNAs by binding to the miRNAs or their precursors [54]. These chemically modified miRNA antisense RNAs can effectively compete with miRNA target mRNAs by a stronger bind to their specific target miRNAs on the miRISCs, resulting in inhibition of the miRNA activities. Antagomirs also induced the degradation of the targeted miRNAs with as of yet unknown mechanisms [57, 59]. Antagomirs were delivered to mouse tissues via intravenous injections, absorbed by tissues, and were highly resistant to various RNases in cells. It was shown that antagomirs specifically inactivated multiple target miRNAs in various mouse tissues for over 20 days following a single intravenous injection, resulting in changes in the abundance of distinct target mRNAs [57, 59]. The introduction of antagomirs against specific miRNAs in cells will release the repression of the bona fide miRNA target mRNAs from translation into proteins, thus indirectly validating the miRNA targets. The strategy of target mimicry to block miRNA functions was enlightened by a study of the interactive relationships between the phosphate (Pi) starvation-induced miR-399 and its naturally occurring target RNA transcripts from IPS1 gene in Arabidopsis thaliana [30]. IPS1 contains a 23-nucleotide motif that is almost complementary to miR-399 but with a mismatched loop at the expected miRNAdirected cleavage site. Over-expressed IPS1 RNAs can bind to mature miR-399 associated RISCs, and prevent miR-399 mediated cleavage of the target mRNAs, including PHO mRNA. Mutation of the IPS1 motif to be perfectly complementary to miR-399 abolished IPS1 inhibitory activity on miR-399, indicating that miR-399 associated RISCs are highly efficient and multiple-turnover enzymes to cleave their

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perfectly complementary targets, but may be stuck in the interaction between RISCs and their non-cleavable targets. This research not only revealed the phenomenon that miRNA activity in planta can be regulated by its mimic non-coding RNA, but also provided a genetic tool for the miRNA functional analysis. That is, introduction of an artificial non-cleavable miRNA target mimic is capable of knocking down complementary miRNA activity in vivo. Using this strategy and the IPS gene backbone [30], successfully inhibited the activities of the miR-156 and miR-319 separately by over-expressing target mimics with non-cleavable sites for these miRNAs, respectively, in Arabidopsis thaliana. The principle of ‘miRNA sponges’ developed by [21] is similar to target mimicry of miRNAs described in plants. Artificial target RNAs are designed to contain several tandem complementary binding sites to the miRNA of interest, but with a bulge or mismatch in the RISC cleavage site, and are genetically engineered to be stably expressed in mammalian cells. These artificial RNAs, like sponges, absorb a high level of their complementary miRNAs and release the translational repression of the bona fide targets by the miRNA-associated RISCs (miRISCs). The mismatch in the cleavage site prevents the decoy RNA from being degraded by miRISCs, but binds more firmly to the target miRNA loaded in RISC, sequestering it away from its bona fide mRNA targets in the cell. These miRNA sponges are experimentally proven to function as highly competitive miRNA inhibitors and depress miRNA targets effectively in mammalian cells. In addition, the sponges can be designed to bind effectively to multiple miRNAs that contain the same “seed’ region (position 2–8 from the 5′ end of the miRNA) [21].

2.4

SiRNA and miRNA Vectors and Their Application in Gene Silencing

Various siRNA vectors have been developed for knocking down genes in plants and animals since the discovery of RNAi [2, 26, 49, 68, 85, 97, 109, 110, 126, 128]. SiRNA vectors are able to generate siRNAs transiently or consistently from doublestranded RNAs or hairpin/stem-loop structure via Dicer enzymes targeting specific gene transcripts in various tissues or cells. However, not all siRNA vectors work well for both plants and animals. For example, the most popular siRNA vectors for gene silencing in plants are inverted repeat sequences coupled with a linker or a spliceable intron between the two repeats to form long (>100 bp) RNA hairpins [27, 62, 107, 125]. Yet, these vectors are not applicable in animal cells because the long doublestranded RNAs (dsRNA) generated from these vectors trigger cellular interferon pathways and lead to non-specific programmed cell death. Consequently, vectors that produce short hairpin RNAs (shRNAs) but which rarely trigger the interferon pathway were developed and have become widely used in animal studies [110, 129]. Similar shRNA vectors were also successfully applied toward directing gene silencing in plants [79]. Most shRNA vectors currently use an RNA polymerase III (Pol III) promoter, usually U6 or H1, and a pol III terminator (a stretch of thymidines)

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to transcribe a short hairpin structure with a stem of 19–29 bp and a short loop of 4–10 nt. The shRNA structures are further recognized and cleaved by Dicers to produce a large amount of siRNAs in cells to target specific gene transcripts. Later on, with the discovery of miRNA genes that produce highly specific short miRNAs, earlier vectors that produce short hairpin structured siRNAs were further modified by using miRNA backbones [9]. The new vectors adapted the flanking and loop regions of endogenous miRNAs to express miRNA-like primary transcripts (pri-miRNA-like RNAs) using pol-II promoters and terminators. These modified miRNA-like small RNA vectors have been demonstrated to be more effective in gene knock-down by many folds, indicating the miRNA backbones are structurally predisposed to produce more effective small RNAs for gene silencing [9]. The most significant discovery that helped to revolutionize small RNA vector technology was the discovery of the asymmetric structures of siRNAs [50, 102]. The realization that most endogenous miRNAs are structurally asymmetric immediately prompted the birth of second-generation RNAi vectors, artificial miRNA vectors [1, 89, 94, 101, 139, 140]. The major difference between miRNA backboned siRNA vectors and artificial miRNA vectors is found on the stem region of the stem-loop structured RNAs produced by both kinds of vectors. While the stem regions of the stem-looped structured RNAs produced by the miRNA backboned siRNA vectors are perfect Watson-Crick base pairs, the ones from the miRNA vectors are often designed to be imperfectly matched with mismatches, GU wobbles, and bulges. The biogenesis of artificial miRNAs produced by miRNA vectors strictly follows the miRNA pathways distinct from the RNAi pathways in cells. Thus, artificial miRNA vectors can be used not only to silence most protein coding genes, but also to knock down genes encoding the enzymes/proteins of RNAi pathways. Today, artificial miRNAs are widely used for gene silencing in both plants and animals. Compared to siRNA vectors, artificial miRNA vectors have significant advantages, including high specificity, fewer off-target effects, tissue-specific expression and almost no side effects. In contrast to the vectors that are used to silence individual genes, various modified vectors that direct simultaneous silencing of multiple genes have also been developed. For example, modified multi-hairpin structures of miR-30 have successfully knocked down multi-genes in a single construct [111]. We expect future gene silencing vectors to be more powerful in fine-tuning silencing of genes with subtle differences for various therapeutic purposes.

2.5

MiRNA Profiling and miRNA Biomarkers

Over 5,000 miRNAs from 44 organisms have been identified/predicted and stored in the miRBase registry (http://microrna.sanger.ac.uk/) [32, 33]. Most of them are not characterized by function. Determination of miRNA functions and miRNA-target interactions is therefore a long-term objective. Roles of miRNAs in post-transcriptional gene regulation are presumed to be extensive. In humans, an individual miRNA is predicted to regulate hundreds of coding gene transcripts [10, 71, 130]. Furthermore,

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transcripts from a single gene can be regulated by multiple miRNAs in a coordinated manner [25, 42, 48]. Analysis of miRNA expression profile is thus important in elucidating roles of specific miRNA or miRNA cohorts in the regulation of their target gene transcripts. Like the expression of mRNAs, the expression of miRNAs varies considerably from different cells, tissues, organs and species [63, 64]. The big challenge of studying miRNAs is how to effectively analyze thousands of miRNAs simultaneously for a limited amount of given samples. Traditional microarray technology has succeeded in analyzing entire protein-coding gene transcriptomes in various organisms. Similarly, various laboratories and companies have adopted the traditional mRNA array platform for the analysis of miRNAs over the last few years, allowing thousands of miRNAs to be analyzed from samples including plants and animals [6, 13, 15, 36, 47, 55, 67, 73–75, 84, 86, 87, 103–105, 113, 116, 122, 142]. The technologies to be used for miRNA array are not trivial. Compared to array analysis for mRNA expression, miRNA arrays usually involve much more complicated procedures due to the small size of the miRNAs and the lack of a conserved 3′ end for easy sample labeling. These complicated steps include the ligation of RNA adapters to the miRNAs, RT-PCR amplification and T7 RNA polymerase transcription [19, 87]. Current non-isotope miRNA array platforms involve these complicated techniques and require special skills; moreover, process-related systematic biases are unavoidable [19]. To simplify these steps, we have recently optimized the conditions for an earlier version of an isotope labeled miRNA array platform [55, 86], and further developed this system demonstrating its use in mouse miRNA analysis [116]. This optimized miRNA array platform is characterized by several unique features: (1) a careful selection of miRNAs for probe design to reduce potential cross-hybridization between different probes; (2) isolation of small RNAs of 15–28 nt using a 15% sequencing gel to avoid interference of signals between pre-miRNAs and pri-miRNAs; (3) direct labeling of the isolated small RNAs at their 5′end by introducing isotope-labeled phosphates to avoid using adaptors and biased PCR amplification, and directly hybridizing the labeled small RNAs to the membrane containing arrayed miRNA probes. Results can be output as a visual miRNA atlas reflecting the bona fide level of miRNAs in cells; and (4) introduction of a new way of data normalization by using Northern blot analysis of a constitutively expressed miRNA for initial data adjustment, and by a set of external controls for the evaluation of process-related loss of signal and quantification of endogenous miRNAs. Application of various miRNA array platforms reveals numerous miRNA biomarkers for a variety of human diseases including various kinds of cancers. The expression changes of these miRNA biomarkers indicate changes from normal to abnormal genetic and physiological conditions. For example, a specific spectrum of miRNAs including miR-23, -24, -26, -27, -103, -107, -181, -210, and -213 were induced in neoplastic cells under a hypoxic environment compared to normal conditions [61]. Similarly, comparisons of miRNA profiles of tumor and normal tissues have revealed distinct miRNA biomarkers for various tumor cells over the last a few years [11, 12, 46, 60, 112, 120, 132]. Exploration of these miRNA biomarkers will be particularly useful in early diagnostics of human diseases such as cancers,

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diabetes, and Alzheimer’s disease. Eventually, detailed miRNA atlases of humans, animals and plants will be available with the help of small RNA deep sequencing and miRNA array platforms for a wide variety of applications.

2.6

Conclusions and Perspectives

In conclusion, the study of RNAi and miRNAs has led to a number of small RNA technologies that are and will continue to be extremely useful in the study of small RNAs, individual gene functions, functional genomics, and various biological questions in both plants and animals. The dissection of RNAi, miRNA, and other small RNA pathways is only the beginning. For most organisms, the detailed maps or atlases of small RNAs have not been completed or even started. The small RNA networks in gene regulation are still obscure, and the entire picture of gene regulation by small RNAs and their detailed regulatory steps is a long-term goal. With a deeper understanding of the roles and mechanisms of small RNA-directed gene regulation, new technologies of using small RNAs will continue to be developed and established. We expect that such small RNA technologies will be expanded from the current siRNA or artificial miRNA directed post-transcriptional gene regulation to transcriptional gene regulation, for example, small RNA directed chromatin modifications or DNA methylation, to modulate the expression of any gene of interest. Small RNA technologies will not only used as tools to silence genes of various pathways but also genes of small RNA pathways themselves. For example, since RNAi and miRNA generally belong to different pathways that composed of different sets of enzymes, we expect that RNAi technology will be used to study functions of genes of the miRNA pathway, and vice versa. In addition to siRNAs and miRNAs, other kinds of small RNAs, such as trans-acting siRNAs (ta-siRNAs) [31, 40, 43, 90, 119, 127], repeat-associated small interfering RNAs (rasiRNAs) [37, 52, 53, 92, 118], and piwi-associated siRNAs (piRNAs) [4, 5, 8, 34, 35, 66, 88, 99, 133, 136], may also be able to be used for silencing of genes of interests. Acknowledgements G.T. is supported by the Kentucky Tobacco Research and Development Center (KTRDC), the USDA-NRI grants 2006-35301-17115 and 2006-35100-17433, and the NSF grant MCB-0718029, Subaward No. S-00000260.

References 1. Alvarez, J.P., Pekker, I., Goldshmidt, A., Blum, E., Amsellem, Z., and Eshed, Y. (2006). Endogenous and synthetic microRNAs stimulate simultaneous, efficient, and localized regulation of multiple targets in diverse species. Plant cell 18, 1134–1151. 2. Amarzguioui, M., Rossi, J.J., and Kim, D. (2005). Approaches for chemically synthesized siRNA and vector-mediated RNAi. FEBS Lett 579, 5974–5981. 3. Ambros, V. (2001). microRNAs: tiny regulators with great potential. Cell 107, 823–826.

2 Small RNA Technologies

27

4. Aravin, A.A., Hannon, G.J., and Brennecke, J. (2007a). The Piwi-piRNA pathway provides an adaptive defense in the transposon arms race. Science (New York, NY) 318, 761–764. 5. Aravin, A.A., Sachidanandam, R., Girard, A., Fejes-Toth, K., and Hannon, G.J. (2007b). Developmentally regulated piRNA clusters implicate MILI in transposon control. Science (New York, NY) 316, 744–747. 6. Babak, T., Zhang, W., Morris, Q., Blencowe, B.J., and Hughes, T.R. (2004). Probing microRNAs with microarrays: tissue specificity and functional inference. RNA (New York, NY) 10, 1813–1819. 7. Bartel, D.P. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116, 281–297. 8. Betel, D., Sheridan, R., Marks, D.S., and Sander, C. (2007). Computational analysis of mouse piRNA sequence and biogenesis. PLoS Comput Biol 3, e222. 9. Boden, D., Pusch, O., Silbermann, R., Lee, F., Tucker, L., and Ramratnam, B. (2004). Enhanced gene silencing of HIV-1 specific siRNA using microRNA designed hairpins. Nucleic Acids Res 32, 1154–1158. 10. Brennecke, J., Stark, A., Russell, R.B., and Cohen, S.M. (2005). Principles of MicroRNA– Target Recognition. PLoS Biol 3, e85. 11. Calin, G.A., and Croce, C.M. (2006). MicroRNA signatures in human cancers. Nature Rev 6, 857–866. 12. Calin, G.A., Ferracin, M., Cimmino, A., Di Leva, G., Shimizu, M., Wojcik, S.E., Iorio, M.V., Visone, R., Sever, N.I., Fabbri, M., et al. (2005). A MicroRNA signature associated with prognosis and progression in chronic lymphocytic leukemia. New Engl J Med 353, 1793–1801. 13. Calin, G.A., Liu, C.G., Sevignani, C., Ferracin, M., Felli, N., Dumitru, C.D., Shimizu, M., Cimmino, A., Zupo, S., Dono, M., et al. (2004). MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias. Proc Natl Acad Sci USA 101, 11755–11760. 14. Carmell, M.A., Xuan, Z., Zhang, M.Q., and Hannon, G.J. (2002). The Argonaute family: tentacles that reach into RNAi, developmental control, stem cell maintenance, and tumorigenesis. Gene Dev 16, 2733–2742. 15. Castoldi, M., Schmidt, S., Benes, V., Noerholm, M., Kulozik, A.E., Hentze, M.W., and Muckenthaler, M.U. (2006). A sensitive array for microRNA expression profiling (miChip) based on locked nucleic acids (LNA). RNA (New York, NY) 12, 913–920. 16. Chaudhuri, K., and Chatterjee, R. (2007). MicroRNA detection and target prediction: integration of computational and experimental approaches. DNA Cell Biol 26, 321–337. 17. Chen, C.Z. (2005). MicroRNAs as oncogenes and tumor suppressors. New Engl J Med 353, 1768–1771. 18. Chitwood, D.H., and Timmermans, M.C. (2007). Target mimics modulate miRNAs. Nat Genet 39, 935–936. 19. Davison, T.S., Johnson, C.D., and Andruss, B.F. (2006). Analyzing micro-RNA expression using microarrays. Methods Enzymol 411, 14–34. 20. Doench, J.G., Petersen, C.P., and Sharp, P.A. (2003). siRNAs can function as miRNAs. Gene Dev 17, 438–442. 21. Ebert, M.S., Neilson, J.R., and Sharp, P.A. (2007). MicroRNA sponges: competitive inhibitors of small RNAs in mammalian cells. Nat Methods 4, 721–726. 22. Elbashir, S.M., Harborth, J., Lendeckel, W., Yalcin, A., Weber, K., and Tuschl, T. (2001a). Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells. Nature 411, 494–498. 23. Elbashir, S.M., Lendeckel, W., and Tuschl, T. (2001b). RNA interference is mediated by 21- and 22-nucleotide RNAs. Gene Dev 15, 188–200. 24. Elbashir, S.M., Martinez, J., Patkaniowska, A., Lendeckel, W., and Tuschl, T. (2001c). Functional anatomy of siRNAs for mediating efficient RNAi in Drosophila melanogaster embryo lysate. EMBO J 20, 6877–6888. 25. Enright, A.J., John, B., Gaul, U., Tuschl, T., Sander, C., and Marks, D.S. (2003). MicroRNA targets in Drosophila. Genome Biol 5, R1.

28

G. Tang et al.

26. Fewell, G.D., and Schmitt, K. (2006). Vector-based RNAi approaches for stable, inducible and genome-wide screens. Drug Discov Today 11, 975–982. 27. Filichkin, S.A., DiFazio, S.P., Brunner, A.M., Davis, J.M., Yang, Z.K., Kalluri, U.C., Arias, R.S., Etherington, E., Tuskan, G.A., and Strauss, S.H. (2007). Efficiency of gene silencing in Arabidopsis: direct inverted repeats vs. transitive RNAi vectors. Plant Biotechnol J 5, 615–626. 28. Filipowicz, W. (2005). RNAi: the nuts and bolts of the RISC machine. Cell 122, 17–20. 29. Forstemann, K., Horwich, M.D., Wee, L., Tomari, Y., and Zamore, P.D. (2007). Drosophila microRNAs are sorted into functionally distinct argonaute complexes after production by dicer-1. Cell 130, 287–297. 30. Franco-Zorrilla, J.M., Valli, A., Todesco, M., Mateos, I., Puga, M.I., Rubio-Somoza, I., Leyva, A., Weigel, D., Garcia, J.A., and Paz-Ares, J. (2007). Target mimicry provides a new mechanism for regulation of microRNA activity. Nat Genet 39, 1033–1037. 31. Gasciolli, V., Mallory, A.C., Bartel, D.P., and Vaucheret, H. (2005). Partially redundant functions of Arabidopsis DICER-like enzymes and a role for DCL4 in producing trans-acting siRNAs. Curr Biol 15, 1494–1500. 32. Griffiths-Jones, S. (2006). miRBase: the microRNA sequence database. Method Mol Biol (Clifton, NJ) 342, 129–138. 33. Griffiths-Jones, S., Grocock, R.J., van Dongen, S., Bateman, A., and Enright, A.J. (2006). miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 34, D140–D144. 34. Grivna, S.T., Pyhtila, B., and Lin, H. (2006). MIWI associates with translational machinery and PIWI-interacting RNAs (piRNAs) in regulating spermatogenesis. Proc Natl Acad Sci USA 103, 13415–13420. 35. Grosshans, H., and Svoboda, P. (2007). miRNA, piRNA, siRNA – Kleine Wiener Ribonukleinsauren. Bioessays 29, 940–943. 36. Grundhoff, A., Sullivan, C.S., and Ganem, D. (2006). A combined computational and microarraybased approach identifies novel microRNAs encoded by human gamma-herpesviruses. RNA (New York, NY) 12, 733–750. 37. Gunawardane, L.S., Saito, K., Nishida, K.M., Miyoshi, K., Kawamura, Y., Nagami, T., Siomi, H., and Siomi, M.C. (2007). A slicer-mediated mechanism for repeat-associated siRNA 5′ end formation in Drosophila. Science (New York, NY) 315, 1587–1590. 38. Haley, B., Tang, G., and Zamore, P.D. (2003). In vitro analysis of RNA interference in Drosophila melanogaster. Methods (San Diego, CA) 30, 330–336. 39. Hamilton, A.J., and Baulcombe, D.C. (1999). A species of small antisense RNA in posttranscriptional gene silencing in plants. Science (New York, NY) 286, 950–952. 40. Henderson, I.R., Zhang, X., Lu, C., Johnson, L., Meyers, B.C., Green, P.J., and Jacobsen, S.E. (2006). Dissecting Arabidopsis thaliana DICER function in small RNA processing, gene silencing and DNA methylation patterning. Nat Genet 38, 721–725. 41. Hobert, O. (2004). Common logic of transcription factor and microRNA action. Trends Biochem Sci 29, 462–468. 42. Hon, L., and Zhang, Z. (2007). The roles of binding site arrangement and combinatorial targeting in microRNA repression of gene expression. Genome Biol 8, R166. 43. Howell, M.D., Fahlgren, N., Chapman, E.J., Cumbie, J.S., Sullivan, C.M., Givan, S.A., Kasschau, K.D., and Carrington, J.C. (2007). Genome-wide analysis of the RNA-DEPENDENT RNA POLYMERASE6/DICER-LIKE4 pathway in Arabidopsis reveals dependency on miRNA- and tasiRNA-directed targeting. Plant Cell 19, 926–942. 44. Hutvagner, G., McLachlan, J., Pasquinelli, A.E., Balint, E., Tuschl, T., and Zamore, P.D. (2001). A cellular function for the RNA-interference enzyme Dicer in the maturation of the let-7 small temporal RNA. Science (New York, NY) 293, 834–838. 45. Hutvagner, G., Simard, M.J., Mello, C.C., and Zamore, P.D. (2004). Sequence-specific inhibition of small RNA function. PLoS Biol 2, E98. 46. Iorio, M.V., Ferracin, M., Liu, C.G., Veronese, A., Spizzo, R., Sabbioni, S., Magri, E., Pedriali, M., Fabbri, M., Campiglio, M., et al. (2005). MicroRNA gene expression deregulation in human breast cancer. Cancer Res 65, 7065–7070.

2 Small RNA Technologies

29

47. Jiang, J., Lee, E.J., Gusev, Y., and Schmittgen, T.D. (2005). Real-time expression profiling of microRNA precursors in human cancer cell lines. Nucleic Acids Res 33, 5394–5403. 48. John, B., Enright, A.J., Aravin, A., Tuschl, T., Sander, C., and Marks, D.S. (2004). Human MicroRNA targets. PLoS Biol 2, e363. 49. Kasahara, H., and Aoki, H. (2005). Gene silencing using adenoviral RNAi vector in vascular smooth muscle cells and cardiomyocytes. Method Mol Med 112, 155–172. 50. Khvorova, A., Reynolds, A., and Jayasena, S.D. (2003). Functional siRNAs and miRNAs exhibit strand bias. Cell 115, 209–216. 51. Kim, S.K., Nam, J.W., Rhee, J.K., Lee, W.J., and Zhang, B.T. (2006). miTarget: microRNA target gene prediction using a support vector machine. BMC Bioinformatics 7, 411. 52. Klattenhoff, C., Bratu, D.P., McGinnis-Schultz, N., Koppetsch, B.S., Cook, H.A., and Theurkauf, W.E. (2007). Drosophila rasiRNA pathway mutations disrupt embryonic axis specification through activation of an ATR/Chk2 DNA damage response. Dev Cell 12, 45–55. 53. Klenov, M.S., Lavrov, S.A., Stolyarenko, A.D., Ryazansky, S.S., Aravin, A.A., Tuschl, T., and Gvozdev, V.A. (2007). Repeat-associated siRNAs cause chromatin silencing of retrotransposons in the Drosophila melanogaster germline. Nucleic Acids Res 35, 5430–5438. 54. Kloosterman, W.P., Lagendijk, A.K., Ketting, R.F., Moulton, J.D., and Plasterk, R.H. (2007). Targeted inhibition of miRNA maturation with morpholinos reveals a role for miR-375 in pancreatic islet development. PLoS Biol 5, e203. 55. Krichevsky, A.M., King, K.S., Donahue, C.P., Khrapko, K., and Kosik, K.S. (2003). A microRNA array reveals extensive regulation of microRNAs during brain development. RNA (New York, NY) 9, 1274–1281. 56. Kruger, J., and Rehmsmeier, M. (2006). RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res 34, W451–W454. 57. Krutzfeldt, J., Kuwajima, S., Braich, R., Rajeev, K.G., Pena, J., Tuschl, T., Manoharan, M., and Stoffel, M. (2007). Specificity, duplex degradation and subcellular localization of antagomirs. Nucleic Acids Res 35, 2885–2892. 58. Krutzfeldt, J., Poy, M.N., and Stoffel, M. (2006). Strategies to determine the biological function of microRNAs. Nat Genet 38 Suppl, S14–S19. 59. Krutzfeldt, J., Rajewsky, N., Braich, R., Rajeev, K.G., Tuschl, T., Manoharan, M., and Stoffel, M. (2005). Silencing of microRNAs in vivo with ‘antagomirs’. Nature 438, 685–689. 60. Kulshreshtha, R., Ferracin, M., Negrini, M., Calin, G.A., Davuluri, R.V., and Ivan, M. (2007a). Regulation of microRNA expression: the hypoxic component. Cell Cycle 6, 1426–1431. 61. Kulshreshtha, R., Ferracin, M., Wojcik, S.E., Garzon, R., Alder, H., Agosto-Perez, F.J., Davuluri, R., Liu, C.G., Croce, C.M., Negrini, M., et al. (2007b). A microRNA signature of hypoxia. Mol Cell Biol 27, 1859–1867. 62. Lacomme, C., Hrubikova, K., and Hein, I. (2003). Enhancement of virus-induced gene silencing through viral-based production of inverted-repeats. Plant J 34, 543–553. 63. Lagos-Quintana, M., Rauhut, R., Meyer, J., Borkhardt, A., and Tuschl, T. (2003). New microRNAs from mouse and human. RNA (New York, NY) 9, 175–179. 64. Lagos-Quintana, M., Rauhut, R., Yalcin, A., Meyer, J., Lendeckel, W., and Tuschl, T. (2002). Identification of tissue-specific microRNAs from mouse. Curr Biol 12, 735–739. 65. Landgraf, P., Rusu, M., Sheridan, R., Sewer, A., Iovino, N., Aravin, A., Pfeffer, S., Rice, A., Kamphorst, A.O., Landthaler, M., et al. (2007). A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 129, 1401–1414. 66. Lau, N.C., Seto, A.G., Kim, J., Kuramochi-Miyagawa, S., Nakano, T., Bartel, D.P., and Kingston, R.E. (2006). Characterization of the piRNA complex from rat testes. Science (New York, NY) 313, 363–367. 67. Lee, E.J., Gusev, Y., Jiang, J., Nuovo, G.J., Lerner, M.R., Frankel, W.L., Morgan, D.L., Postier, R.G., Brackett, D.J., and Schmittgen, T.D. (2007). Expression profiling identifies microRNA signature in pancreatic cancer. Int J Cancer 120, 1046–1054. 68. Lee, Y.S., and Carthew, R.W. (2003). Making a better RNAi vector for Drosophila: use of intron spacers. Methods (San Diego, CA) 30, 322–329.

30

G. Tang et al.

69. Lee, Y.S., Nakahara, K., Pham, J.W., Kim, K., He, Z., Sontheimer, E.J., and Carthew, R.W. (2004). Distinct roles for Drosophila Dicer-1 and Dicer-2 in the siRNA/miRNA silencing pathways. Cell 117, 69–81. 70. Leuschner, P.J., Ameres, S.L., Kueng, S., and Martinez, J. (2006). Cleavage of the siRNA passenger strand during RISC assembly in human cells. EMBO Rep 7, 314–320. 71. Lewis, B.P., Burge, C.B., and Bartel, D.P. (2005). Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120, 15–20. 72. Lewis, B.P., Shih, I.H., Jones-Rhoades, M.W., Bartel, D.P., and Burge, C.B. (2003). Prediction of mammalian microRNA targets. Cell 115, 787–798. 73. Liang, R.Q., Li, W., Li, Y., Tan, C.Y., Li, J.X., Jin, Y.X., and Ruan, K.C. (2005). An oligonucleotide microarray for microRNA expression analysis based on labeling RNA with quantum dot and nanogold probe. Nucleic Acids Res 33, e17. 74. Lim, L.P., Lau, N.C., Garrett-Engele, P., Grimson, A., Schelter, J.M., Castle, J., Bartel, D.P., Linsley, P.S., and Johnson, J.M. (2005). Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature 433, 769–773. 75. Liu, C.G., Calin, G.A., Meloon, B., Gamliel, N., Sevignani, C., Ferracin, M., Dumitru, C.D., Shimizu, M., Zupo, S., Dono, M., et al. (2004a). An oligonucleotide microchip for genome-wide microRNA profiling in human and mouse tissues. Proc Natl Acad Sci USA 101, 9740–9744. 76. Liu, J., Carmell, M.A., Rivas, F.V., Marsden, C.G., Thomson, J.M., Song, J.J., Hammond, S.M., Joshua-Tor, L., and Hannon, G.J. (2004b). Argonaute2 is the catalytic engine of mammalian RNAi. Science (New York, NY) 305, 1437–1441. 77. Liu, X., Jiang, F., Kalidas, S., Smith, D., and Liu, Q. (2006). Dicer-2 and R2D2 coordinately bind siRNA to promote assembly of the siRISC complexes. RNA (New York, NY) 12, 1514–1520. 78. Llave, C., Xie, Z., Kasschau, K.D., and Carrington, J.C. (2002). Cleavage of Scarecrow-like mRNA targets directed by a class of Arabidopsis miRNA. Science (New York, NY) 297, 2053–2056. 79. Lu, S., Shi, R., Tsao, C.C., Yi, X., Li, L., and Chiang, V.L. (2004). RNA silencing in plants by the expression of siRNA duplexes. Nucleic Acids Res 32, e171. 80. Ma, L., Teruya-Feldstein, J., and Weinberg, R.A. (2007). Tumour invasion and metastasis initiated by microRNA-10b in breast cancer. Nature 449, 682–688. 81. Martinez, J., Patkaniowska, A., Urlaub, H., Luhrmann, R., and Tuschl, T. (2002). Singlestranded antisense siRNAs guide target RNA cleavage in RNAi. Cell 110, 563–574. 82. Matranga, C., Tomari, Y., Shin, C., Bartel, D.P., and Zamore, P.D. (2005). Passenger-strand cleavage facilitates assembly of siRNA into Ago2-containing RNAi enzyme complexes. Cell 123, 607–620. 83. Matranga, C., and Zamore, P.D. (2004). Plant RNA interference in vitro. Cold Spring Harbor Sym 69, 403–408. 84. Mattie, M.D., Benz, C.C., Bowers, J., Sensinger, K., Wong, L., Scott, G.K., Fedele, V., Ginzinger, D., Getts, R., and Haqq, C. (2006). Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies. Mol Cancer 5, 24. 85. Mellits, K.H., Pe’ery, T., Manche, L., Robertson, H.D., and Mathews, M.B. (1990). Removal of double-stranded contaminants from RNA transcripts: synthesis of adenovirus VA RNAI from a T7 vector. Nucleic Acids Res 18, 5401–5406. 86. Monticelli, S., Ansel, K.M., Xiao, C., Socci, N.D., Krichevsky, A.M., Thai, T.H., Rajewsky, N., Marks, D.S., Sander, C., Rajewsky, K., et al. (2005). MicroRNA profiling of the murine hematopoietic system. Genome Biol 6, R71. 87. Nelson, P.T., Baldwin, D.A., Scearce, L.M., Oberholtzer, J.C., Tobias, J.W., and Mourelatos, Z. (2004). Microarray-based, high-throughput gene expression profiling of microRNAs. Nat Methods 1, 155–161. 88. Nishida, K.M., Saito, K., Mori, T., Kawamura, Y., Nagami-Okada, T., Inagaki, S., Siomi, H., and Siomi, M.C. (2007). Gene silencing mechanisms mediated by Aubergine piRNA complexes in Drosophila male gonad. RNA (New York, NY) 13, 1911–1922.

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89. Niu, Q.W., Lin, S.S., Reyes, J.L., Chen, K.C., Wu, H.W., Yeh, S.D., and Chua, N.H. (2006). Expression of artificial microRNAs in transgenic Arabidopsis thaliana confers virus resistance. Nat Biotechnol 24, 1420–1428. 90. Nogueira, F.T., Sarkar, A.K., Chitwood, D.H., and Timmermans, M.C. (2006). Organ polarity in plants is specified through the opposing activity of two distinct small regulatory RNAs. Cold Spring Harbor Sym 71, 157–164. 91. Okamura, K., Ishizuka, A., Siomi, H., and Siomi, M.C. (2004). Distinct roles for Argonaute proteins in small RNA-directed RNA cleavage pathways. Gene Dev 18, 1655–1666. 92. Pelisson, A., Sarot, E., Payen-Groschene, G., and Bucheton, A. (2007). A novel repeatassociated small interfering RNA-mediated silencing pathway downregulates complementary sense gypsy transcripts in somatic cells of the Drosophila ovary. J Virol 81, 1951–1960. 93. Qi, Y., Denli, A.M., and Hannon, G.J. (2005). Biochemical specialization within Arabidopsis RNA silencing pathways. Mol Cell 19, 421–428. 94. Qu, J., Ye, J., and Fang, R. (2007). Artificial microRNA-mediated virus resistance in plants. J Virol 81, 6690–6699. 95. Rand, T.A., Petersen, S., Du, F., and Wang, X. (2005). Argonaute2 cleaves the anti-guide strand of siRNA during RISC activation. Cell 123, 621–629. 96. Rehmsmeier, M., Steffen, P., Hochsmann, M., and Giegerich, R. (2004). Fast and effective prediction of microRNA/target duplexes. RNA (New York, NY) 10, 1507–1517. 97. Reichhart, J.M., Ligoxygakis, P., Naitza, S., Woerfel, G., Imler, J.L., and Gubb, D. (2002). Splice-activated UAS hairpin vector gives complete RNAi knockout of single or double target transcripts in Drosophila melanogaster. Genesis 34, 160–164. 98. Rhoades, M.W., Reinhart, B.J., Lim, L.P., Burge, C.B., Bartel, B., and Bartel, D.P. (2002). Prediction of plant microRNA targets. Cell 110, 513–520. 99. Ro, S., Park, C., Song, R., Nguyen, D., Jin, J., Sanders, K.M., McCarrey, J.R., and Yan, W. (2007). Cloning and expression profiling of testis-expressed piRNA-like RNAs. RNA (New York, NY) 13, 1693–1702. 100. Saetrom, O., Snove, O., Jr., and Saetrom, P. (2005). Weighted sequence motifs as an improved seeding step in microRNA target prediction algorithms. RNA (New York, NY) 11, 995–1003. 101. Schwab, R., Ossowski, S., Riester, M., Warthmann, N., and Weigel, D. (2006). Highly specific gene silencing by artificial microRNAs in Arabidopsis. Plant Cell 18, 1121–1133. 102. Schwarz, D.S., Hutvagner, G., Du, T., Xu, Z., Aronin, N., and Zamore, P.D. (2003). Asymmetry in the assembly of the RNAi enzyme complex. Cell 115, 199–208. 103. Sempere, L.F., Freemantle, S., Pitha-Rowe, I., Moss, E., Dmitrovsky, E., and Ambros, V. (2004). Expression profiling of mammalian microRNAs uncovers a subset of brainexpressed microRNAs with possible roles in murine and human neuronal differentiation. Genome Biol 5, R13. 104. Shingara, J., Keiger, K., Shelton, J., Laosinchai-Wolf, W., Powers, P., Conrad, R., Brown, D., and Labourier, E. (2005). An optimized isolation and labeling platform for accurate microRNA expression profiling. RNA (New York, NY) 11, 1461–1470. 105. Sioud, M., and Rosok, O. (2004). Profiling microRNA expression using sensitive cDNA probes and filter arrays. BioTechniques 37, 574–576, 578–580. 106. Smalheiser, N.R., and Torvik, V.I. (2006). Complications in mammalian microRNA target prediction. Method Mol Biol (Clifton, NJ) 342, 115–127. 107. Smith, N.A., Singh, S.P., Wang, M.B., Stoutjesdijk, P.A., Green, A.G., and Waterhouse, P.M. (2000). Total silencing by intron-spliced hairpin RNAs. Nature 407, 319–320. 108. Song, J.J., Smith, S.K., Hannon, G.J., and Joshua-Tor, L. (2004). Crystal structure of Argonaute and its implications for RISC slicer activity. Science (New York, NY) 305, 1434–1437. 109. Sui, G., and Shi, Y. (2005). Gene silencing by a DNA vector-based RNAi technology. Method Mol Biol (Clifton, NJ) 309, 205–218. 110. Sui, G., Soohoo, C., Affar el, B., Gay, F., Shi, Y., Forrester, W.C., and Shi, Y. (2002). A DNA vector-based RNAi technology to suppress gene expression in mammalian cells. Proc Natl Acad Sci USA 99, 5515–5520.

32

G. Tang et al.

111. Sun, D., Melegari, M., Sridhar, S., Rogler, C.E., and Zhu, L. (2006). Multi-miRNA hairpin method that improves gene knockdown efficiency and provides linked multi-gene knockdown. BioTechniques 41, 59–63. 112. Szafranska, A.E., Davison, T.S., John, J., Cannon, T., Sipos, B., Maghnouj, A., Labourier, E., and Hahn, S.A. (2007). MicroRNA expression alterations are linked to tumorigenesis and non-neoplastic processes in pancreatic ductal adenocarcinoma. Oncogene 26, 4442–4452. 113. Tang, F., Hajkova, P., Barton, S.C., Lao, K., and Surani, M.A. (2006). MicroRNA expression profiling of single whole embryonic stem cells. Nucleic Acids Res 34, e9. 114. Tang, G. (2005). siRNA and miRNA: an insight into RISCs. Trends Biochem Sci 30, 106–114. 115. Tang, G., Reinhart, B.J., Bartel, D.P., and Zamore, P.D. (2003). A biochemical framework for RNA silencing in plants. Gene Dev 17, 49–63. 116. Tang, X., Gal, J., Zhuang, X., Wang, W., Zhu, H., and Tang, G. (2007). A simple array platform for microRNA analysis and its application in mouse tissues. RNA (New York, NY) 13, 1803–1822. 117. Tomari, Y., Du, T., and Zamore, P.D. (2007). Sorting of Drosophila small silencing RNAs. Cell 130, 299–308. 118. Vagin, V.V., Sigova, A., Li, C., Seitz, H., Gvozdev, V., and Zamore, P.D. (2006). A distinct small RNA pathway silences selfish genetic elements in the germline. Science (New York, NY) 313, 320–324. 119. Vaucheret, H. (2005). MicroRNA-dependent trans-acting siRNA production. Sci STKE 2005, pe43. 120. Volinia, S., Calin, G.A., Liu, C.G., Ambs, S., Cimmino, A., Petrocca, F., Visone, R., Iorio, M., Roldo, C., Ferracin, M., et al. (2006). A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci USA 103, 2257–2261. 121. Wakiyama, M., Takimoto, K., Ohara, O., and Yokoyama, S. (2007). Let-7 microRNAmediated mRNA deadenylation and translational repression in a mammalian cell-free system. Gene Dev 21, 1857–1862. 122. Wang, H., Ach, R.A., and Curry, B. (2007). Direct and sensitive miRNA profiling from lowinput total RNA. RNA (New York, NY) 13, 151–159. 123. Wang, X., and Wang, X. (2006). Systematic identification of microRNA functions by combining target prediction and expression profiling. Nucleic Acids Res 34, 1646–1652. 124. Watanabe, Y., Tomita, M., and Kanai, A. (2007). Computational methods for MicroRNA target prediction. Methods Enzymol 427, 65–86. 125. Wesley, S.V., Helliwell, C.A., Smith, N.A., Wang, M.B., Rouse, D.T., Liu, Q., Gooding, P.S., Singh, S.P., Abbott, D., Stoutjesdijk, P.A., et al. (2001). Construct design for efficient, effective and high-throughput gene silencing in plants. Plant J 27, 581–590. 126. Wielopolska, A., Townley, H., Moore, I., Waterhouse, P., and Helliwell, C. (2005). A highthroughput inducible RNAi vector for plants. Plant Biotechnol J 3, 583–590. 127. Williams, L., Carles, C.C., Osmont, K.S., and Fletcher, J.C. (2005). A database analysis method identifies an endogenous trans-acting short-interfering RNA that targets the Arabidopsis ARF2, ARF3, and ARF4 genes. Proc Natl Acad Sci USA 102, 9703–9708. 128. Wu, M.T., Wu, R.H., Hung, C.F., Cheng, T.L., Tsai, W.H., and Chang, W.T. (2005). Simple and efficient DNA vector-based RNAi systems in mammalian cells. Biochem Biophys Res Commun 330, 53–59. 129. Xia, X.G., Zhou, H., Ding, H., Affar el, B., Shi, Y., and Xu, Z. (2003). An enhanced U6 promoter for synthesis of short hairpin RNA. Nucleic Acids Res 31, e100. 130. Xie, X., Lu, J., Kulbokas, E.J., Golub, T.R., Mootha, V., Lindblad-Toh, K., Lander, E.S., and Kellis, M. (2005). Systematic discovery of regulatory motifs in human promoters and 3′ UTRs by comparison of several mammals. Nature 434, 338–345. 131. Yan, X., Chao, T., Tu, K., Zhang, Y., Xie, L., Gong, Y., Yuan, J., Qiang, B., and Peng, X. (2007). Improving the prediction of human microRNA target genes by using ensemble algorithm. FEBS Lett 581, 1587–1593. 132. Yanaihara, N., Caplen, N., Bowman, E., Seike, M., Kumamoto, K., Yi, M., Stephens, R.M., Okamoto, A., Yokota, J., Tanaka, T., et al. (2006). Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell 9, 189–198.

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133. Yin, H., and Lin, H. (2007). An epigenetic activation role of Piwi and a Piwi-associated piRNA in Drosophila melanogaster. Nature 450, 304–308. 134. Yoon, S., and De Micheli, G. (2005). Prediction of regulatory modules comprising microRNAs and target genes. Bioinformatics (Oxford, England) 21 Suppl 2, ii93–ii100. 135. Zamore, P.D. (2006). RNA interference: big applause for silencing in Stockholm. Cell 127, 1083–1086. 136. Zamore, P.D. (2007). RNA silencing: genomic defence with a slice of pi. Nature 446, 864–865. 137. Zamore, P.D., and Haley, B. (2005). Ribo-gnome: the big world of small RNAs. Science (New York, NY) 309, 1519–1524. 138. Zamore, P.D., Tuschl, T., Sharp, P.A., and Bartel, D.P. (2000). RNAi: double-stranded RNA directs the ATP-dependent cleavage of mRNA at 21 to 23 nucleotide intervals. Cell 101, 25–33. 139. Zeng, Y., Cai, X., and Cullen, B.R. (2005). Use of RNA polymerase II to transcribe artificial microRNAs. Methods Enzymol 392, 371–380. 140. Zeng, Y., Wagner, E.J., and Cullen, B.R. (2002). Both natural and designed micro RNAs can inhibit the expression of cognate mRNAs when expressed in human cells. Mol Cell 9, 1327–1333. 141. Zhang, Y. (2005). miRU: an automated plant miRNA target prediction server. Nucleic Acids Res 33, W701–704. 142. Zhao, J.J., Hua, Y.J., Sun, D.G., Meng, X.X., Xiao, H.S., and Ma, X. (2006). Genome-wide microRNA profiling in human fetal nervous tissues by oligonucleotide microarray. Childs Nerv Syst 22, 1419–1425. 143. Zhu, S., Si, M.L., Wu, H., and Mo, Y.Y. (2007). MicroRNA-21 targets the tumor suppressor gene tropomyosin 1 (TPM1). J Biol Chem 282, 14328–14336.

Chapter 3

RNA Interference Expression Vectors Based on miRNAs and RNA Splicing Akua N. Bonsra, Joshua Yonekubo, and Guangwei Du*

Abstract RNA interference (RNAi) has emerged as a powerful tool in basic research and therapeutics by silencing the expression of specific target genes. RNAi occurs naturally within cells to regulate gene expression at the post-transcriptional level. The development of reliable RNAi vectors encoding artificial and natural miRNAs would be useful tools for many RNAi applications. Here, we describe two new RNAi vectors, designated pSM155 and pSM30, that take into consideration of miRNA processing and RNA splicing by placing the miRNA-based artificial miRNA expression cassettes inside of synthetic introns. These vectors significantly improved the expression of a co-expressed enhanced green fluorescent protein (EGFP) marker and also provide a simplified cloning method. We discuss the advantages of these vectors, their potential applications, and concerns in using miRNA-based vectors. Keywords microRNA, mRNA, small-hairpin RNA, RNA interference, RNA splicing, intron

Abbreviations RNA interference, RNAi; small interfering RNAs, siRNAs; smallhairpin RNAs, shRNAs; microRNA, miRNA; primary miRNAs, pri-miRNAs; miRNA precursor, pre-miRNA; nucleotide, nt; enhanced green fluorescent protein, EGFP; oligonucleotide, oligo.

Department of Integrative Biology and Pharmacology, University of Texas Health Science Center at Houston, Houston, Texas 77030, U.S.A. * Corresponding author: E-mail: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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Introduction

RNA interference (RNAi) has emerged as a powerful research tool for the silencing of specific target genes and shown great potentials in therapeutics [4]. RNAi occurs naturally within cells to regulate gene expression at the post-transcriptional level. Scientists are able to mimic and manipulate this process in mammalian cells by introducing small interfering RNAs (siRNAs) or by transfecting DNAbased vectors encoding short hairpin RNAs (shRNAs) [1, 10]. Recent strategies for gene silencing come from new RNAi vectors based on microRNAs (miRNAs) [2, 11, 12]. In eukaryotes, primary miRNAs (pri-miRNAs) are transcribed by RNA polymerase II in the nucleus, capped at the 5′ end and polyadenylated at the 3′ end [3, 7]. Pri-miRNA is processed by the nuclear microprocessor complex where an RNase III enzyme, Drosha, cleaves it at specific cites surrounding the hairpin [3, 7]. The resultant 70–90 nt hairpin has a distinct 2 nt 3′ overhang that is recognized by Exportin-5, which transports this precursor miRNA (premiRNA) out of the nucleus. A cytolasmic RNase III enzyme, Dicer, then acts on the pre-miRNA to produce a ∼22 nt double-stranded miRNA. The duplex separates into single-stranded mature miRNAs and enters the RNA-induced silencing complex (RISC). The miRNA within the complex guides it to the target mRNA, which it binds then, depending on complementarity, triggers for degradation or translation inhibition [3, 7]. Because of the growing need for understanding of the functions of miRNAs and the many beneficial uses of RNAi in scientific research and therapeutic applications, the development of reliable vectors encoding artificial and natural miRNAs has become critical. This chapter will describe the development of new miRNA/ shRNA expression vectors designed by our group which takes advantage of naturally occurring mechanisms, summarize protocols on using these vectors [6], and discuss their potential applications in basic research and therapeutics.

3.2 3.2.1

Materials and Methods General Reagents and Antibodies

Cell culture media, Dulbecco’s Modified Eagle Medium (DMEM), Opti-MEM-I, and LipofectAMINE Plus were from Invitrogen (Carlsbad, CA, USA). The GeneRuler 1 kb DNA Ladder Plus was from Fermentas (Glen Burnie, MD). All other reagents were of analytical grade unless otherwise specified. The rabbit polyclonal anti-PLD2 was kindly provided by Y. Banno (Gifu University of Tokyo, Gifu, Japan). Rabbit anti-green fluorescent protein (GFP) was from Abcam (Cambridge, MA, USA). Monoclonal anti-α-tubulin was from Sigma-Aldrich (St Louis, MO, USA). Goat anti-mouse and anti-rabbit IgG conjugated to Alexa

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680 were from Invitrogen. Goat anti-mouse and anti-human IgG conjugated to IRDye 800 were from Rockland Immunochemicals (Gilbertsville, PA, USA).

3.2.2

Construction of pSM155 and pSM30

The construction of pcDNA3.1-mCherry, pSM155, and pSM30 have been described [6]. Briefly, a synthetic exon and intron is placed between the cytomegalovirus (CMV) promoter and EGFP in the pEGFP-N1 vector (Clontech, Pal Alto, CA), to generate pEGFP-N1-Intron. The expression cassettes for miR155 or miR30 were then cloned into pEGFP-N1-Intron to get pSM155 and pSM30. Two inverted BsmBI sites were introduced into both vectors to facilitate subsequent insertion of artificial miRNAs. The oligos for candidate sequences also contained cohesive ends for a simplified cloning strategy. The plasmid maps were generated using VectorNTI from Invitrogen.

3.2.3

Synthesis of Oligos

3.2.3.1

Synthesis of Oligos for pSM155 (An Example Is Shown in Fig. 3.3A)

A. Generating the top oligo sequence. To generate the top oligo sequence, combine these elements (from 5′ end to 3′ end): start with 5′ TGCTG, reverse complement of the 21 nt sense target sequence (this is the mature miRNA sequence), add GTTTTGGCCACTGACTGAC (terminal loop), and add nucleotides 1–8 (5′-3′) of sense target sequence and nucleotides 11–21 (5′-3′) of the sense target sequence. B. To generate the bottom oligo sequence, perform the following steps: Remove 5′ TGCT from the top oligo sequence (new sequence starts with G), take the reverse complement of the sequence from step 1 and add CCTG to the 5′ end of the sequence from step 2.

3.2.3.2

Synthesis of Oligos for pSM30 (An Example Is Shown in Fig. 3.3B)

A. To generate the top oligo sequence, combine these elements (from 5′ end to 3′ end): start with 5′ AGCG, add a 22 nt sense target sequence, change the first nt to one which does not anneal to the last nt in the anti-sense, e.g. C to A, add TAGTGAAGCCACAGATGTA (terminal loop) and add nucleotides of the antisense target sequence. B. To generate the bottom oligo sequence, perform the following steps: remove 5′ AGCG from the top oligo sequence (new sequence starts with G), take the reverse complement of the sequence from step 1 (this is the mature miRNA sequence, and add GGCA to the 5′ end of the sequence from step 2.

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Cloning of Artificial miRNAs

1. Preparation of vectors: Cut 1–2 µg of pSM155 or pSM30 in 15 µl NEB (New England Biolabs) restriction Buffer 3 and BsmB I at 55 °C for 1 h. Run the digested vectors on 0.8% agarose gel and purify them using QIAEX II gel extraction kit following the manufacturer’s instructions (Qiagen, Valencia, CA). 2. Annealing of oligos (25 uM final concentration): Dissolve oligos with distilled water (100 uM stock concentration). Take 5 µl from each oligo (top and bottom) and add 8 µl water and 2 µl 10 × NEB restriction buffer (we usually use Buffer 3). Boil the oligos for 4 min. Leave the denatured oligos at room temperature for 15 min and then move them to 4 °C for 10–15 min. Dilute 2,500-fold to get 10 nM double-stranded oligos (250-fold dilution with water, quickly followed by 10-fold with 1 × NEB Buffer 3; or add 0.2 µl of annealed oligos to 500 µl 1 × NEB Buffer 3). 3. Ligation using Rapid Ligation Kit (Roche Diagnostics, Indianapolis, IN): Mix 2 µl of the annealed oligos with 2 µl vector and H2O (~5 ng) (oligos: vector, ~15:1). Add 1 µl DNA dilution buffer, mix well, briefly spin down. Add 5 µl ligation buffer and mix. Add 0.5 µl T4 DNA ligase, mix well, spin down briefly. Incubate 5 min at RT. 4. Transform into a suitable cloning bacterial strain using standard transformation protocols.

3.2.5

Cell Culture and Transfection

HeLa cells were maintained in DMEM supplemented with 10% (v/v) calf serum, 100 µg/ml penicillin, and 100 µg/ml streptomycin. For transfections, cells were grown in 6-well or 12-well plates and then switched into Opti-MEM I media before being transfected with 1 or 0.5 µg of DNA per well using LipofectAMINE Plus. Four hours post transfection, the media was replaced with fresh growth medium and the cells incubated for an additional 48 h (the time for collecting cells depends on the half-life of target genes).

3.2.6

Western Blotting

Twenty micrograms of total cell lysates were separated using 8% (w/v) SDS/PAGE, transferred to a nitrocellulose membrane, blocked with 1% casein, probed overnight with primary antibodies, washed, and incubated with secondary antibody conjugated to Alexa 680 or IRDye 800. Fluorescent signals were detected with an Odyssey infrared imaging system from LI-COR Biosciences – Biotechnology (Lincoln, NE, USA). Alexa 680 and IRdye 800-labeled secondary antibodies are scanned at 700 and 800 channels, respectively.

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3.3 3.3.1

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Results Generation of Vectors for Expressing Artificial miRNAs from a Synthetic Intron

Understanding the delicate chemistry of the RNAi machinery is perhaps the most important aspect of designing miRNA-based RNAi vectors. There are several key enzymes and complexes involved in the miRNA pathway, each recognizing a specific structural element within the RNA [3, 7]. The more recent miRNA vectors sandwiched artificial miRNA expression cassettes between an RNA polymerase II promoter and a fluorescent protein reporter gene [5, 12]. For example, the miR155 and miR30-based vectors coexpressed the miRNAs and EGFP segments as a combined exonic transcript [5, 12] (Fig. 3.1A). These vectors were designed to suppress the target gene expression by mature miRNAs and also provide an EGFP marker to indicate which cells had been successfully transfected. However, the EGFP signal that can be generated from these vectors arise only from the very low number of pri-miRNAs that are exported into the cytoplasm prior to Drosha cleavage (Fig. 3.1A). As a result of this flaw in the design, many cells, although transfected with the miRNA silencer, may not express a detectable level of the EGFP marker. Our group has generated a new miRNA expression strategy that is based on the endogeneous splicing mechanism of pri-miRNAs to overcome the original flaw in the miRNA vector design [6]. Instead of inserting a miRNA cassette into an exon, we have placed the miRNA-expressing cassette into a chimeric intron containing the 5′ intron donor site of the human β-globin gene and the branch and 3′ intron acceptor sites from an immunoglobulin gene (Fig. 3.1B). Two such vectors, pSM155 and pSM30, were derived from miR155 and miR30, respectively (Fig. 3.2). Based on our current understanding of miRNA processing, the new strategy would allow Drosha processing of the pri-miRNA to produce both a functional pre-miRNA and EGFP mRNA that can both be transported to the cytoplasm and perform their functions [3, 6, 7]. Indeed, these two vectors successfully downregulated expression of exogenously expressed luciferase and an endogenous phospholipase D2 (PLD2) gene while also generating a bright EGFP signal in transfected cells [6].

3.3.2

Cloning of miRNAs

The cloning of artificial miRNAs follows the common steps of cloning: oligo synthesis, vector preparation, oligo annealing, ligation, transformation, and characterization. Selection of miRNA oligos is based on the general guidelines for siRNA, which take into account miRNA stability and structure [9, 14]. An effective artificial miRNA must meet most of the following guidelines: overall low to medium G/C content (30–50%), low internal stability at the 5′ antisense strand, high internal stability at the 5′ sense strand, absence of internal repeats or palindromes, A-form

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Fig. 3.1 Strategies for miRNA-based RNAi vector. (A) Original miRNA-based vectors contained a miRNA-expressing cassette, such as miR155, sandwiched between a CMV promoter and EGFP as a combined exonic transcript. Upon processing, the EGFP gene segment is left uncapped and will be degraded quickly. Only a low number of unprocessed pri-mRNAs escape the nucleus and can be translated to generate the EGFP protein. Because expression of the EGFP marker is significantly decreased, it no longer serves as a reliable marker for miRNA-expressing cells. (B) The design of the new pSM155 vector. Placing the miRNA cassette into a synthetic intron is predicted to increase the reliability of the EGFP marker expression in miRNA-expressing cells since both functional miRNA and EGFP can be efficiently exported into the cytoplasm and expressed

3 RNA Interference Expression Vectors Based on miRNAs and RNA Splicing

Fig. 3.2 Plasmid maps for pSM155 and pSM30. These vectors are designed to express artificial miRNAs for RNAi experiments by incorporating the sequences of the human miR155 and miR30 miRNA precursors into a synthetic intron. The maps were generated using VectorNTI (Full sequences and digital files are available upon request)

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helix between miRNA and target mRNA, presence of an A at position 3 and 19 of sense strand, absence of a G or C at position 19 of sense strand, presence of a U at position 10 of sense strand, absence of a G at position 13 of sense strand, etc. To enhance specificity, a miRNA also needs to have minimal homology with non-target RNAs and avoid low-stringency sequences. A pair of oligos includes cohesive ends and a specific sequence matching target mRNA for each artificial miRNA (64 nucleotides for the pSM155-based system and 67 nucleotides for the pSM30-based system). For each gene, we usually test four to five target sequences and choose at least two constructs for our experiments. To simplify the cloning of artificial miRNAs without substantially altering the miRNA arm sequences, inverted BsmBI sites were placed internal to the arms of pSM30 and pSM155 (Fig. 3.3). A pair of oligonucleotide primers with appropriate 4 nt overhangs can be easily ligated to the cohesive sites of the vector generated by BsmB I digestion. Examples for the oligo sequences and their cloning in pSM155 and pSM30 are illustrated in Fig. 3.3. miR-203.1 miR-221/222 miR-200/429

Human FMR1 3
UTR

miR-148/152 miR-181

miR-124.2/506 miR-130/301 miR-23

miR-125/351 miR-141/200a

miR-9 miR-19

miR-205

miR-490

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UTR length:2248

miR-15/16/195/424/497 miR-153 miR-93.hd/291-3p/294/295/302/372/373/520 miR-101 miR-383 miR-17-5p/20/93.mr/106/519.d

miR-101

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miR-25/32/92/363/367 miR-194 miR-23 miR-194 miR-130/301 miR-101 miR-153

miR-19

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miR-9

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Human LEPR 3
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Key:

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0 Conservation

Site conserved in Human, Mouse, Rat, Dog,Chiken 8mer 7mer-m8 7mer-1a

Less conserved site 8mer 7mer-m8

7mer-1a

Fig. 3.3 Strategy for cloning specific artificial miRNA sequences into the targeting vectors. Two inverted BsmB I restriction sites are used for cloning a pair of oligos into pSM155 (A) and pSM30 (B) vectors. BsmB I digestion leaves the miRNA arms unchanged and generates two different cohesive ends into which a synthetic DNA duplex can be inserted to replace the original miR155 or miR30 sequences. The cloning of artificial miRNA sequences against luciferase (underlined) is shown as an example. The central black font indicates the loop region

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After ligation, the candidate recombinant clones need to be confirmed by restriction digestion and sequencing. The cloning efficiency of our current strategy is excellent and there is very low empty vector background. We often purify plasmids from two colonies for further characterization. For the pSM155 vector, the plasmid DNA is digested with Msc I. A linearized parental vector is 5,114 bp, and recombinant construct generates a 2,784 bp and a 2,368 bp fragment (Fig. 3.4A). For pSM30 vector, the plasmid DNA is digested with Xho I/Nhe I (Fig. 3.4B). The empty pSM30 vector is used as control. The recombinant clone and the vector release a 239 bp and 200 bp fragment, respectively. Finally, the candidate recombinant clones need to be confirmed by sequencing because the error rate of long oligos from commercial sources is often very high. Both pSM155 and pSM30 can also be used to express natural miRNAs, and thus label cells transfected with exogenously introduced natural miRNAs. A full-length miRNA can be amplified by PCR using a top primer with a 5′ flanking Sal I restriction site and a bottom primer with a 5′ flanking Nhe I, EcoR V or Mlu I restriction site. The PCR product digested with restriction enzymes is then cloned into pSM155 or pSM30 previously cut with the same enzymes (see maps in Fig. 3.2).

3.3.3

Conforming the Expression of EGFP Marker

As discussed above, directly linking the marker ORF to a miRNA-based artificial miRNA expression cassette as shown in Fig. 3.1A may lead to inefficient translation of the marker protein [3, 7]. We have shown efficient expression of the artificial miRNA and marker from a single RNA transcript in our vectors [6], suggesting that

Fig. 3.4 Characterization of the recombinant constructs. (A) Cutting of the parental vector with Msc I generates a 5,114 bp fragment (lane 2), whereas the recombinant pSM155 construct generates a 2,784 bp and a 2,368 bp fragments (lane 3). (B) Cutting of the pSM30 vector (lane 2) and the recombinant construct (lane 3) with Xho I/Nhe I releases a 200 and 239 bp fragment, respectively. Lane 1 in A and B shows the GeneRuler 1 kb DNA Ladder Plus

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RNA processing in our design is as predicted in Fig. 3.1B. We describe here our methods used to determine the expression of the EGFP marker in miRNA expression constructs generated from pSM155 and pSM30 vectors. To ensure that some miRNAs do not interfere with the expression of EGFP, the validation of efficient EGFP expression in the transfected cells is important before further functional analysis is done. Two methods can be used to evaluate EGFP expression: Western blotting or immunofluorescent microscopy. We prefer to use the latter since it allows us to compare the expression of EGFP with a second red fluorescent protein such as mCherry in the same cells. In summary, EGFP and mCherry fluorescent signals are compared in cells cotransfected with artificial miRNAs directed against genes of interest and pcDNA3.1-mCherry, which encodes a red fluorescent protein and serves as a marker for transfected cells. Such analysis was described earlier in our study to demonstrate that EGFP was efficiently expressed from the pSM155 and pSM30 vectors expressing the artificial miRNAs directed against firefly luciferase or PLD2, but poorly in the original miRNA expression vectors, pmiR155 and pmiR30 [6] (Fig. 3.5).

3.3.4

Determination of the Inhibition of Target Gene Expression

Knockdown efficiency is often determined by Western blotting. An irrelevant artificial miRNA construct such as that targeting luciferase can be used as a control. In some cases, immunofluorescent microscopy can also be used. If an antibody for the gene of interest is not available, reverse transcription-PCR is then the preferred method. Figure 3.6 illustrates PLD2 knockdown by Western blot analysis using the Odyssey Infrared Imaging System from LI-COR Biosciences – Biotechnology. One key to get reliable results is getting high transfection efficiency. We only perform Western blotting when more than 80–90% cells are transfected, as judged by the expression of EGFP. However, the functions of many genes have to be studied in particular cell types, which are sometimes hard to transfect. If these genes do not express or express at low levels in highly transfectable cell lines, determining the knockdown efficiency of each construct would be problematic. In this case, we usually determine which constructs are able to suppress the expression of exogenously expressed target genes. The cells are co-transfected with the miRNA constructs and the gene of interest tagged with an epi-tag such as Flag or Myc which can be detected by an antibody against the epi-tag using Western blotting. This method is very fast and reliable, especially when many constructs need to be tested. However, every candidate construct has to be tested for its ability in downregulating the expression of endogenous cognate genes before functional experiments are performed.

pre-miR-130b Chr 22 P13

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DGCR8 q11.21 q11.22 q11.23 q12.1 q12.2

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Stimulating protein 1, ubiquitous zinc finger transcription factor Pleomorphic adenoma gene (PLAG) 1, a developmentally regulated C2H2 zinc finger protein

gtcagagggcaccctttccccccgggcagaggcccCgccccagccagcctgcattccaggtctcagatcc

Core promoter-binding protein (CPBP) with 3 Krueppel-type zinc fingers

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mature miR-130b

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b C-allele

MYC-associated zinc finger protein related transcription factor EGR1, early growth response 1

G-allele Neural-restrictive-silencer-element

gtcagagggcaccctttccccccgggcagaggcccGgccccagccagcctgcattccaggtctcagatcc c

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Fig. 3.5 Determining the expression of EGFP marker proteins in artificial miRNA-expressing cells. miRNAs designed to target luciferase (luc) and PLD2 are used as examples. HeLa cells were cotransfected with pmiR155-luc, pmiR155-PLD2, pSM155-luc, or pSM155-PLD2, and pcDNA3.1/mCherry, which encodes a red fluorescent protein and is used to identify transfected cells. Both pmiR155 and pSM155 constructs contain an EGFP marker as illustrated in Fig. 3.1. Whereas EGFP is expressed in all cells expressing mCherry when the pSM155 vector is used, it is only expressed in a few cells when pmiR155 is used. Similar results were seen using the miR30-based vectors, pmiR30 and pSM30 (not shown here) (Modified and reproduced from [6]. With permission from Wiley-Blackwell Publishing Ltd.)

3 RNA Interference Expression Vectors Based on miRNAs and RNA Splicing

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Fig. 3.6 Determination of knockdown of PLD2 using Western blotting. HeLa cells were transfected with artificial miRNAs against luciferase (control) and PLD2 in pmiR155 and pSM155. Cell lysates were collected for Western blotting 2 days after transfection. PLD2 and α-tubulin were detected by a polyclonal antibody and a mouse monoclonal antibody, respectively, followed by goat anti-rabbit secondary IgG conjugated to Alexa 680 and goat anti-mouse conjugated to IRDye 800. Fluorescence was recorded using an Odyssey infrared imaging system from LI-COR Bioscience-Biotechnology (Lincoln, NE, USA) (Reproduced from [6]. With permission from Wiley-Blackwell Publishing Ltd.)

3.4

Discussion

We have shown that insertion of the miRNA-based artificial miRNA expression cassette into an intron significantly increased expression of the marker protein. A similar strategy for expressing the artificial miRNA from an intron was also recently reported by other groups [2, 8, 15]. In these studies, the miRNA expression cassettes were placed into the introns of an endogenous gene, i.e., the first intron of the human ubiquitin C gene [2, 15]. In our work, we utilized a synthetic intron to maximalize mRNA processing and directly compared the efficiencies of RNAi and marker gene expression in the original and our modified vectors [6]. Our results demonstrate that incorporation of an intronic strategy offers a modest, at best, improvement in the efficiency of RNAi yet generates a dramatic improvement in marker gene expression. This result suggests that Drosha processing of the pri-miRNA is relatively efficient even when the miRNA cassette is in an exon, however, most of the marker protein expression is lost through degradation of the resulting unstable mRNA that lacks a 5′ CAP structure (Fig. 3.1A). The success of vectors using a synthetic intron also indicates that the conserved sequences for mRNA splicing (5′ donor, branch, and 3′ acceptor sites) suffice for the efficient processing of pri-miRNAs. In summary, the miRNA expression vectors we describe here, pSM155 and pSM30, which are designed based on knowledge of miRNA and RNA splicing, provide a better approach to achieve efficient expression of both the RNAi cassette and the marker gene for transiently transfected cell experiments. The miRNA-based RNAi vectors also offer some technical advantages that may be useful in multiple applications. Dual shRNA and/or miRNA expression vectors can be prepared by subcloning a vector carrying the miRNA cassette for one miRNA into another vector carrying a different miRNA cassette (Fig. 3.7A).

3 RNA Interference Expression Vectors Based on miRNAs and RNA Splicing

Fig. 3.7 Some potential technical applications of pSM155 and pSM30 vectors. (A) Generation of constructs expressing two artificial miRNAs. Two constructs carrying two different miRNAs or shRNAs can be combined together to generate one construct containing both miRNA cassettes. To do so, construct 1 can be cut with restriction enzymes Xba I and Mlu I, and construct 2 with Nhe I and Mlu I. Because Xba I and Nhe I generate the same sticky ends, these two miRNA cassettes can be ligated into one vector using the standard ligation protocol. *Xba I (1793) site in pSM155 vector is methylated in Dam + E. coli strains and can’t be cut. Xba I cuts the plasmids purified from Dam + E. coli strains only at the Xba I (827) site. (B) Expression of miRNA and an antibiotic selection marker from the same mRNA transcript. An antibiotic selection marker can be cloned into the RNAi vector in place of EGFP. When generating stable cell lines, the antibiotic-resistant clones should all express miRNAs. (C) Performing RNAi and rescue experiments using a single construct. Rescue miRNA vectors can be generated within the same construct by replacing the EGFP cDNA for that of the gene of interest containing wobble mutations at the site targeted by the miRNA. The siRNA expressed from this construct is able to inhibit the expression of the mRNA from the endogenous locus but not that from the same construct

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Strategically placed restriction enzymes allow generation of one modified RNAi vector carrying two miRNAs. This can be a powerful technique with two major applications. In one case, both shRNAs can target different regions of the same target mRNA to increase silencing efficiency. In another case, the vector can comprise of two shRNAs that target two different genes for silencing. This application could then be used to silence related or opposing genes in one experiment. The latter application would be a beneficial technique especially for those studying multiple signal pathways as well as systems biology, since shRNA-expressing cells would be labeled even in tissues or whole animals. Expression of two miRNA cassettes that target different regions of the same gene can also avoid ineffectivity caused by selective mutations (or highly occurring mutations) of target sequences in some diseases. The ability to effectively express two synthetic miRNAs from a single transcript has been shown in a similar design [2]. The pSM155 and pSM30 vectors can also be used as a method to select true clones when used to generate stable cell lines expressing artificial miRNAs. For this case, the EGFP marker can be replaced by antibiotic selection markers (Fig. 3.7B). Since both miRNA and selection marker are expressed from a single mRNA, only cells expressing the artificial miRNA will be able to grow in growth media containing appropriate antibiotics. Another advantage of our vectors lies in the fact that RNAi and rescue experiments can be performed using the same vector. This would allow for more reliable and conclusive RNAi experiments. To do this, for example, the cDNA for the target mRNA can be cloned into the vector in place of or in addition to the EGFP gene (Fig. 3.7C). The cDNA should carry a wobble mutation so that the miRNA can no longer target it. This technique is useful to ensure the phenotype of the cell is due to direct silencing of the target gene and not a result of nonspecific targeting of the miRNA to other genes. Furthermore, this strategy can also be used to remove the mutated genes causing aberrant signaling in human diseases such as cancer, and replace them with their wild-type copies, which are often required to mediate normal physiological functions. Since the expression of miRNAs is driven by pol II promoters, the major therapeutic advantage of our vectors and other miRNA-based RNAi vectors is the ability to modify the vector for tissue specificity. Conjugated delivery methods for synthetic siRNAs can target only limited tissues and organs [4]. Introducing tissuespecific promoters into miRNA-based vectors will allow targeting to specific diseased tissues to reduce affecting normal cells and tissues. A promoter inducibly controlled by small molecules can also be adapted to drive miRNAs expression to avoid chronic toxicity of miRNA expression. Finally, while miRNA-based RNAi vectors including our design offer several advantages discussed above, it is not without its own limitations. One such limitation is that expression of miRNAs using retroviral vectors may suffer from low viral titers. As with miRNAs, viral RNA molecules are first processed and degraded by Drosha in the nuclei prior to moving to the cytoplasm. Only few unprocessed viral RNA can be transported to the cytoplasm as in Fig. 3.1A, resulting in low viral titer.

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In an intronic transcript (Fig. 3.1B), the miRNA expression cassette will be removed from mature viral RNAs, which will not packed into the retroviral particles. The second concern is that miRNA-based RNAi may not be as efficient as synthetic siRNAs and the traditional shRNAs driven by pol III promoters in some cell types and tissues. Maturation of siRNAs from the more complex miRNA structure requires at least one more processing step catalyzed by Drosha, which may eventually lead to generating less mature siRNAs. In fact, it has been reported that many miRNA primary transcripts are present at high levels but are not processed by the enzyme Drosha in early mouse development and human primary tumors [13]. This finding implies that we need to be more cautious in using miRNA-based vectors in some applications. Acknowledgements The authors thank Dr. Yoshiko Banno for the PLD2 antibody, Dr. Greg Hannon for the pSM2 vector, and Dr. Roger Y. Tsien for pRSET-B-mCherry. We also thank Dr. Michael Frohman for scientific discussion. This work was supported by a Scientist Development Grant from the American Heart Association (0430096 N) and research grants from National Institutes of Health (GM071475) to GD.

References 1. Brummelkamp, T.R., Bernards, R., and Agami, R. (2002). A system for stable expression of short interfering RNAs in mammalian cells. Science 296, 550–553. 2. Chung, K.H., Hart, C.C., Al-Bassam, S., Avery, A., Taylor, J., Patel, P.D., Vojtek, A.B., and Turner, D.L. (2006). Polycistronic RNA polymerase II expression vectors for RNA interference based on BIC/miR-155. Nucleic Acids Res 34, e53. 3. Cullen, B.R. (2004). Transcription and processing of human microRNA precursors. Mol Cell 16, 861–865. 4. de Fougerolles, A., Vornlocher, H.P., Maraganore, J., and Lieberman, J. (2007). Interfering with disease: a progress report on siRNA-based therapeutics. Nat Rev Drug Discov 6, 443–453. 5. Dickins, R.A., Hemann, M.T., Zilfou, J.T., Simpson, D.R., Ibarra, I., Hannon, G.J., and Lowe, S.W. (2005). Probing tumor phenotypes using stable and regulated synthetic microRNA precursors. Nat Genet 37, 1289–1295. 6. Du, G., Yonekubo, J., Zeng, Y., Osisami, M., and Frohman, M.A. (2006). Design of expression vectors for RNA interference based on miRNAs and RNA splicing. FEBS J 273, 5421–5427. 7. Kim, V.N. (2005). MicroRNA biogenesis: coordinated cropping and dicing. Nat Rev Mol Cell Biol 6, 376–385. 8. Lin, S.L., and Ying, S.Y. (2006). Gene silencing in vitro and in vivo using intronic microRNAs. Methods Mol Biol (Clifton, NJ) 342, 295–312. 9. Mittal, V. (2004). Improving the efficiency of RNA interference in mammals. Nat Rev Genet 5, 355–365. 10. Paddison, P.J., Caudy, A.A., Bernstein, E., Hannon, G.J., and Conklin, D.S. (2002). Short hairpin RNAs (shRNAs) induce sequence-specific silencing in mammalian cells. Genes Dev 16, 948–958. 11. Silva, J.M., Li, M.Z., Chang, K., Ge, W., Golding, M.C., Rickles, R.J., Siolas, D., Hu, G., Paddison, P.J., Schlabach, M.R., et al. (2005). Second-generation shRNA libraries covering the mouse and human genomes. Nat Genet 37, 1281–1288.

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12. Stegmeier, F., Hu, G., Rickles, R.J., Hannon, G.J., and Elledge, S.J. (2005). A lentiviral microRNA-based system for single-copy polymerase II-regulated RNA interference in mammalian cells. Proc Natl Acad Sci USA 102, 13212–13217. 13. Thomson, J.M., Newman, M., Parker, J.S., Morin-Kensicki, E.M., Wright, T., and Hammond, S.M. (2006). Extensive post-transcriptional regulation of microRNAs and its implications for cancer. Genes Dev 20, 2202–2207. 14. Ui-Tei, K., Naito, Y., Takahashi, F., Haraguchi, T., Ohki-Hamazaki, H., Juni, A., Ueda, R., and Saigo, K. (2004). Guidelines for the selection of highly effective siRNA sequences for mammalian and chick RNA interference. Nucleic Acids Res 32, 936–948. 15. Zhou, H., Xia, X.G., and Xu, Z. (2005). An RNA polymerase II construct synthesizes shorthairpin RNA with a quantitative indicator and mediates highly efficient RNAi. Nucleic Acids Res 33, e62.

Chapter 4

Recent Application of Intronic MicroRNA Agents in Cosmetics Shi-Lung Lin1*, David T.S. Wu2, and Shao-Yao Ying1

Abstract Utilization of gene silencing effectors, such as microRNA (miRNA) and small hairpin RNA (shRNA), provides a powerful new strategy for human skin care in vivo, particularly for hyperpigmentation treatment and aging prevention. For example, tyrosinase (Tyr), a melanocytic membrane-bound glycoprotein, is the rate-limiting enzyme critical for melanin (black pigment) biosynthesis in skins and hairs. There are over 54 native microRNA capable of targeting human tyrosinase for skin whitening and lightening. In this study, we have designed a mir-434-5p homologue and used it to successfully demonstrate the feasibility of miRNA-mediated skin whitening in vitro and in vivo. Under the same experimental condition in trials, Pol-II-directed intronic mir-434-5p expression did not cause any detectable sign of cytotoxicity, whereas siRNAs targeting the same sequence induced certain non-specific mRNA degradation as previously reported. Because the intronic miRNA-mediated gene silencing pathway is tightly regulated by multiple intracellular surveillance systems, including Pol-II transcription, RNA splicing, exosome digestion and NMD processing, the current findings underscore the fact that intronic miRNA agents, such as mir-434-5p homologues, are effective, target-specific and safe to be used for skin whitening without any overt cytotoxic effect. Given that the human skins also express a variety of native miRNAs, we may re-design these miRNAs based on their individual functions for skin care, which will provide significant insights into areas of opportunity for new cosmetic interventions. Keywords microRNA (miRNA), intronic microRNA (Id-miRNA), mir-434-5p, tyrosinase (Tyr), hyaluronidase (Hyal), RNA interference (RNAi), skin whitening, antiaging, cosmetics.

1

Department of Cell and Neurobiology, Keck School of Medicine, University of Southern California, 1333 San Pablo Street, BMT-302, Los Angeles, CA 90033, USA

2

Mello Biotech Ltd, Taipei, Taiwan, R.O.C.

* Corresponding author: Phone: 002-1-323-442-1658; Fax: 002-1-323-442-3466; E-mail: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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Introduction

Prevention of hyperpigmentation (i.e. sun-burn) and aging is the key means for having healthy skins. However, many of the skin pigmentation and aging processes are associated with personal gene activities. For example, tyrosinase (Tyr), a melanocytic membrane-bound glycoprotein, is the rate-limiting enzyme critical for melanin (black pigment) biosynthesis in skins and hairs, while hyaluronidase (Hyal) often causes skin wrinkle by degrading subcutaneous hyaluronan (HA), the major anti-aging extracellular matrix in skins. Therefore, a good skin care can be achieved by suppressing these unwanted gene activities. Among a variety of currently available skin whitening and lightening products, many chemical and naturally extracted agents have been applied to inhibit tyrosinase function, using materials such as hormone-derived inhibitory oligopetides, hydroxytetronic acid derivatives, benzoyl compounds, hydroquinone compositions, alcohol diol and triol analogues, kojic acid derivatives, ascomycete-derived enzymes, and plant extracts. Although these cosmetic agents may work well in vitro, only a few of them, such as hydroquinone and its derivatives, are able to induce good hypopigmenting effects in clinical trials [25]. Nevertheless, all hydroquinone derivatives leading to a reactive quinone are putative cytotoxic agents. Thus, the gap between in-vitro and in-vivo studies suggests that innovative strategies are needed for validating their safety and efficacy. With the advance of recent RNA interference (RNAi) technologies, novel small RNA agents have been found to provide more potent effects in targeted gene suppression, including the utilization of double-stranded short interfering RNA (e.g. dsRNA/siRNA) [3, 4] and deoxyribonucleotidylated-RNA interfering molecules (e.g. D-RNAi) [12]. Conceivably, these small RNA agents may be used to develop new cosmetic designs and products for skin care. In principle, the RNAi mechanism elicits a post-transcriptional gene silencing (PTGS) phenomenon capable of inhibiting specific gene function with high potency at a few nanomolar dosage, which has been proven to be effective longer and much less toxic than conventional gene-knockout methods using antisense oligonucleotides or small molecule chemical inhibitors [12]. As reported in many previous studies [3, 6, 12, 14], the siRNA-induced gene silencing effects may last over one week, while the D-RNAi effects can even sustain up to one month after one treatment. These siRNA/D-RNAi agents evoke a series of intracellular sequence-specific mRNA degradation and/or translational suppression processes, affecting all highly homologous gene transcripts, namely co-suppression. It has been observed that such co-suppression results from the generation of small RNA products (21–25 nucleotide bases) by the enzymatic activities of RNaseIII endoribonucleases (Dicer) and/or RNA-directed RNA polymerases (RdRp) on aberrant RNA templates, which are usually the derivatives of foreign transgenes or viral genomes [3, 6, 12].

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Limitations of SiRNA/ShRNA-Based Gene Silencing Agents

Although the modern RNAi technologies may offer a new avenue for suppressing unwanted gene function in skins, the applications thereof have not been demonstrated to work constantly and safely in higher vertebrates, including fish, avian, mammal and human. For example, almost all of the current siRNA agents are based on a double-stranded RNA (dsRNA) conformation, which has been shown to cause interferon-mediated non-specific RNA degradation in vertebrates [3, 26]. Such an interferon-mediated cytotoxic response reduces the target specificity of siRNAinduced gene silencing effects and often results in global RNA degradation in vertebrate cells. Particularly in mammalian cells, it has been noted that the RNAi effects are disturbed when the siRNA/dsRNA size is longer than 25 base-pairs (bp) [3]. Transfection of siRNA or small hairpin RNA (shRNA) sized less than 25 bp may not completely overcome such a problem, because both [24] and [15] have reported that the high dosage of siRNAs and shRNAs (such as >250 nM in human T cells) is able to cause strong cytotoxic effects similar to those of long dsRNAs. This toxicity is due to their double-stranded RNA conformation, which activates the interferon-mediated non-specific RNA degradation and programmed cell death through the activation of cellular PKR and 2–5A signaling pathways. It is well known that interferon-activated protein kinase PKR can trigger cell apoptosis, while the activation of interferon-induced 2′,5′-oligoadenylate synthetase (2–5A) system leads to extensive cleavage of single-stranded RNAs, such as mRNAs [26]. Both PKR and 2-5A systems contain dsRNA-binding motifs, which possess high affinity to the double-stranded RNA conformation. Further, the most difficult problem is that these small siRNA/shRNA agents are not stable enough to be maintained at an optimal dose in vivo due to the abundant RNase activities in higher vertebrates [1]. As the RNAi effects are naturally caused by the production of small RNA products (21–25 nucleotide bases) from a transcriptional template derived from foreign transgenes or viral genomes [6, 12], the recent utilization of Pol-III-directed siRNA/ shRNA expression vectors has shown to offer relatively stable RNAi efficacy in vivo [27]. Although previous studies [9, 20, 22] using such a vector-based siRNA approach have succeeded in maintaining constant gene silencing effects, their strategies fail to focus the RNAi effects on a targeted cell or tissue population because of the ubiquitous existence of type III RNA polymerase (Pol-III) activity. Pol-III promoters, such as U6 and H1, are activated in almost all cell types, making tissue-specific gene silencing impossible. Moreover, because the leaky read-through activity of Pol-III transcription often occurs on a short DNA template in the absence of pr oper termination, large RNA products longer than desired 25 bp can be synthesized and cause unexpected interferon cytotoxicity [8, 23]. Such a problem can also result from the competitive conflict between the Pol-III promoter and another vector promoter (i.e. LTR and CMV promoters). Furthermore, it is recently noted that high

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siRNA/shRNA concentrations generated by the Pol-III-directed RNAi systems can over-saturate the cellular native microRNA (miRNA) pathway and thus cause global miRNA inhibition and cell death [7]. These disadvantages discourage the use of Pol-III-based RNAi vector systems in health care. In order to improve the delivery stability, targeting specificity and safety aspects of modern RNAi technologies for healthy skin care, a better transduction and maintenance strategy is highly desired.

4.3

Intronic MicroRNA-Mediated RNAi Mechanism

Research based on gene transcript (e.g. mRNA), an assembly of protein-coding exons, is fully described throughout the literature, taking the fate of spliced non-coding introns to be completely digested for granted [21]. Is it true that the intron portion of a gene is destined to be a genetic waste without function or there is a function for it, however, which has not yet been discovered? Recently, this misconception was corrected by the observation of intronic microRNA (miRNA) [13, 29, 30]. Intronic miRNA is a new class of small single-stranded regulatory RNAs derived from the gene introns, which are spliced out of the precursor messenger RNA (pre-mRNA) of the encoding gene and further processed into small mature miRNAs. MiRNA is usually about 18–27 nucleotides (nt) in length and is capable of either directly degrading its messenger RNA (mRNA) target or suppressing the protein translation of its targeted mRNA, depending on the complementarity between the miRNA and its target. In this way, the intronic miRNA is functionally similar to previously described siRNA/shRNA, but differs from them in the requirement of intracellular type II RNA polymerase (Pol-II) transcription and RNA splicing processes for its biogenesis [13]. Also, because introns naturally contain multiple translational stop codons for recognition by the intracellular nonsense-mediated decay (NMD) system [11, 31], most of the unstructured intron sequences can be quickly degraded after RNA splicing to prevent excessive accumulation, which is toxic to the cells. It has been measured that approximately 10–30% of a spliced intron is preserved after the exosome and NMD digestion in cytoplasm with a relatively long half-life, indicating the cellular origin of native intronic miRNAs [2]. Natural intronic miRNA biogenesis relies on the coupled interaction between nascent Pol-II-mediated pre-mRNA transcription and intron splicing/excision (Fig. 4.1), occurring within certain nuclear regions proximal to genomic perichromatin fibrils [5, 14]. In eukaryotes, protein-coding gene transcripts, such as mRNAs, are produced by type-II RNA polymerases (Pol-II). The transcription of a genomic gene generates precursor messenger RNA (pre-mRNA), which contains four major parts including 5′-untranslated region (UTR), protein-coding exon, non-coding intron and 3′-UTR. Broadly speaking, both 5′- and 3′-UTR can be seen as a kind of intron extension. Introns occupy the largest proportion of non-coding sequences in the pre-mRNA. Each intron can be ranged up to 30 or so kilo-bases and is required to be excised out of the pre-mRNA content before mRNA maturation. This process of pre-mRNA excision and intron removal is called RNA splicing, which is executed by intracellular

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Fig. 4.1 Biogenesis of native intronic microRNA (miRNA). Intronic miRNA is co-transcribed with precursor messenger RNA (pre-mRNA) by Pol-II and cleaved out of the pre-mRNA by RNA splicing, while the ligated exons become a mature messenger RNA (mRNA) for protein synthesis. The spliced intronic miRNA with a high secondary structure (i.e. hairpin and/or stem-loop) is further processed into mature miRNA capable of triggering RNAi-related gene silencing effects

spliceosomes. After RNA splicing, some of the intron-derived RNA fragments are further processed to form microRNA (miRNA) derivative molecules, which can effectively silence their targeted genes, respectively, through an RNA interference (RNAi)-like mechanism, while exons of the pre-mRNA are ligated together to form a mature mRNA for protein synthesis.

4.4

Differences Between miRNA and siRNA Biogenesis Pathways

We have demonstrated that effective mature miRNAs can be generated from the introns of vertebrate genes, of which the biogenetic process is different from those of siRNA and intergenic miRNA [13, 16]. To demonstrate their differences, Fig. 4.2 shows the comparison of native biogenesis and RNAi mechanisms among siRNA, intergenic (exonic) miRNA and intronic miRNA. Presumably, siRNA is formed by two perfectly complementary RNAs transcribed by two reversely positioned promoters from one DNA template, then hybridized and further processing into 20–25 bp duplexes by RNaseIII endoribonucleases, namely Dicer. Different from this siRNA model, the biogenesis of intergenic miRNA, e.g. lin-4 and let-7, involves a long non-coding precursor RNA transcript (pri-miRNA), which is directly transcribed from a Pol-II or Pol-III RNA promoter, whereas intronic miRNA is co-transcribed with its encoding gene by only Pol-II and released after

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Fig. 4.2 Comparison of biogenesis and RNAi mechanisms among siRNA, intergenic (exonic) miRNA and intronic miRNA. SiRNA is likely formed by two perfectly complementary RNAs transcribed from two different promoters (remains to be determined) and further processing into 19–22 bp duplexes by RNaseIII-familial endonucleases, Dicer. The biogenesis of intergenic (exonic) miRNA, e.g. lin-4 and let-7, involves a long transcript precursor (pri-miRNA), which is probably generated by a Pol-II or Pol-III RNA promoter, whereas intronic miRNA is mainly transcribed by the Pol-II promoter of its encoded gene and co-expressed in the intron region of the gene transcript (pre-mRNA). After pre-mRNA splicing, the spliced intron functions as a primiRNA for intronic miRNA generation. In the nucleus, the pri-miRNA is excised by either Drosha-like RNases (intergenic miRNA) or spliceosomal components (intronic miRNA) to form a hairpin-like pre-miRNA template and then exported to cytoplasm for further processing by Dicer* to form mature miRNAs. The Dicers for siRNA and miRNA pathways are different. For instance, some exosome and NMD components are likely involved in the process of intronic miRNA maturation. All three small regulatory RNAs are finally incorporated into a RNA-induced silencing complex (RISC), which contains either strand of siRNA or the single-strand of miRNA. The effect of miRNA is considered to be more specific and less adverse than that of siRNA because only one strand is involved. On the other hand, siRNAs primarily trigger mRNA degradation, whereas miRNAs can induce either mRNA degradation or suppression of protein synthesis depending on the sequence complementarity to the target gene transcripts

RNA splicing as a spliced intron. The spliced intron is then served as a pri-miRNA for processing into an intronic precursor miRNA (pre-miRNA) or a multipre-miRNA cluster. In the cell nucleus, the pri-miRNA is further excised by either Drosha-like RNases (for intergenic miRNA) or spliceosomal components (for intronic miRNA) to form a hairpin-like stem-loop precursor or a cluster of multiple

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stem-loop structures, termed pre-miRNA, and then exported to cytoplasm for final processing into mature miRNA by a miRNA-associated Dicer (Dicer*). Subsequently, all three small regulatory RNAs are incorporated into a RNA-induced silencing complex (RISC), which contains either strand of siRNA or the mature strand of miRNA. The Dicers and RISCs for siRNA and miRNA pathways are known to be different [28]. For example, some enzymes of the nonsense-mediated decay (NMD) system may play the role of Dicer* in intronic miRNA maturation. As a result, the effect of miRNA is generally more specific and less adverse than that of siRNA because only one strand is involved. On the other hand, siRNAs primarily trigger mRNA degradation, whereas miRNAs can induce either mRNA degradation or suppression of protein synthesis, or both, depending on the sequence complementarity to their targeted gene transcripts. Because the intronic miRNA pathway is well coordinated by multiple intracellularly regulatory systems, including Pol-II transcription, RNA splicing and NMD processing, the gene silencing effects of intronic miRNAs are considered to be effective, specific and safe [19].

4.5

Development of miRNA-Based Gene Silencing Agents

Based on the intronic RNA splicing and processing mechanisms (Figs. 3A, B), we designed and developed a Pol-II-mediated recombinant gene expression system containing at least a splicing-competent intron, namely SpRNAi, which is able to inhibit the function of a unwanted gene with high complementarity to the intron sequence. The SpRNAi is co-transcribed with the precursor mRNA (pre-mRNA) of the recombinant gene by Pol-II RNA polymerases (P) and cleaved out of the premRNA by RNA splicing. Subsequently, the spliced SpRNAi was further processed into mature gene silencing agents, such as shRNA and miRNA, capable of triggering RNAi-related gene silencing. After intron removal, the exons of the recombinant gene transcript are linked together to form a mature mRNA molecule for translational synthesis of a marker or functional protein. As shown in Fig. 4.3A, the essential components of the SpRNAi intron include several consensus nucleotide elements, consisting of a 5′-splice site, a branch-point motif (BrP), a poly-pyrimidine tract (PPT), and a 3′-splice site. In addition, a hairpin RNA-like pre-miRNA sequence is inserted inside the SpRNAi intron located between the 5′-splice site and the branch-point motif (BrP). This portion of the intron would normally form a lariat structure during RNA splicing and processing. We have observed that spliceosomal U2 and U6 snRNPs, both helicases, are involved in the unwinding and excision of the lariat RNA fragment into pre-miRNA; however, the detailed processing remains to be elucidated. Further, the 3′-end of the SpRNAi construct contains a multiple translational stop codon region (T codon) in order to increase the accuracy of intronic RNA splicing and NMD processing. When presented in a cytoplasmic mRNA, this T codon would signal the activation of the nonsense-mediated decay (NMD) pathway to degrade any unstructured RNA accumulation in the cell. However, the highly secondary structured hairpin RNA and

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Fig. 4.3 Structural composition of the SpRNAi-incorporated recombinant RGFP gene (SpRNAiRGFP) in an expression-competent vector (A), and the strategy (B) of using this composition to generate man-made microRNA, mimicking the biogenesis of the natural intronic miRNA. In vivo tests of an SpRNAi-RGFP expression composition directed against green EGFP in fish show an over 85% knockdown effect specifically on the targeted EGFP gene expression, as determined by Western blot analysis (C). The intron-derived anti-EGFP microRNA and its spliced precursor can be observed on a 1% formaldehyde agarose gel electrophoresis after Northern blot analysis (D)

pre-miRNA insert will be preserved for further Dicer cleavage, so as to form mature siRNA and miRNA, respectively. Moreover, for intracellular expression, we manually incorporate the SpRNAi construct in the DraII restriction site of a red fluorescent protein (RGFP) gene isolated from mutated chromoproteins of the coral reef Heteractis crispa, so as to form a recombinant SpRNAi-RGFP gene. The cleavage of RGFP at its 208th nucleotide site by the restriction enzyme DraII generates an AG– GN nucleotide break with three recessing nucleotides in each end, which will form 5′- and 3′-splice sites respectively after the SpRNAi insertion. Because this intronic insertion disrupts the structure of a functional RGFP protein, which can be recovered by intron splicing, we can determine the release of intronic shRNA/miRNA and RGFP-mRNA maturation through the appearance of red RGFP around the affected

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cells. The RGFP gene also provides multiple exonic splicing enhancers (ESEs) to increase RNA splicing accuracy and efficiency. In this intronic miRNA expression system (Fig. 4.3B), we provides a genetic engineering method for using synthetic RNA splicing and processing elements, such as 5′-splice site, branch-point motif (BrP), poly-pyrimidine tract (PPT), and 3′-splice site, to form an artificial SpRNAi intron containing at least a desired RNA insert for antisense RNA, small hairpin RNA (shRNA) and/or microRNA (miRNA) production. A DNA synthesizer can chemically produce and link these elements. Alternatively, the linkage of these elements can be achieved by enzymatic restriction and ligation. The intron so obtained can be used directly for transfection into cells of interest or further incorporated into a cellular gene for co-expression along with the gene transcript (i.e. pre-mRNA) by Pol-II. During RNA splicing and mRNA maturation, the desired RNA insert will be excised and released by intracellular spliceosome, exosome and NMD mechanisms and then triggers a desired gene silencing effect on specific gene transcripts with high complementarity to the inserted RNA sequence, while the exons of the recombinant gene transcript are linked together to form mature mRNA for expression of a desirable gene function, such as translation of a reporter or marker protein selected from the group of red/green fluorescent protein (RGFP/EGFP), luciferase, lac-Z, and their derivative homologues. The presence of the reporter/marker protein is useful for locating the production of the inserted shRNA/miRNA molecules in affected cells, facilitating the identification of the desired gene silencing/RNAi effects. In accordance with the biogenesis of intronic miRNA, mature mRNA formed by the linkage of exons can also be useful in conventional gene therapy to replace impaired or missing gene function, or to increase specific gene expression. Alternatively, this method provides novel compositions and means for inducing cellular production of gene silencing molecules through intronic RNA splicing and processing mechanisms to elicit either antisense-mediated gene knockout or RNA interference (RNAi) effects, which are useful for inhibiting targeted gene function. The intron-derived gene silencing molecules so obtained may include antisense RNA, ribozyme, short temporary RNA (stRNA), double-stranded RNA (dsRNA), small interfering RNA (siRNA), tiny non-coding RNA (tncRNA), short hairpin RNA (shRNA), microRNA (miRNA), and RNAi-associated precursor RNA constructs (pri-/pre-miRNA). The use of these intronic RNA-derived gene silencing agents is a powerful tool for targeting and silencing unwanted genes selected from the group consisting of pathogenic transgenes, viral genes, mutant genes, oncogenes, disease-related small RNA genes and any other types of protein-coding as well as non-coding genes. Using this novel Pol-II-mediated SpRNAi-RGFP expression system, we have successfully generated mature shRNA and miRNA molecules with full gene silencing capacity in human prostate cancer LNCaP, human cervical cancer HeLa and rat neuronal stem HCN-A94–2 cells [17] as well as in zebrafish, chicken and mouse in vivo [18]. We have tested different pre-miRNA insert constructs targeting against green EGFP and other cellular gene expression in zebrafish and various human cell lines, and have learned that effective gene silencing miRNAs are

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derived from the 5′-proximity of the intron sequence between the 5′-splice site and the branching point. As shown in Fig. 4.3C, a strong gene silencing effect occurs only in the transfection of anti-EGFP pre-miRNA insert (lane 4), whereas no effect can be detected in those of other inserts indicated by lanes from left to right: 1, blank vector control (Ctl); 2, pre-miRNA insert targeting HIV-p24 (mock); 3, antisense EGFP insert without the hairpin loop structure (anti); and 5, reverse premiRNA sequence which is completely complementary to the anti-EGFP pre-miRNA (miR*). No effect was detected on off-target genes, such as marker RGFP and house-keeping β-actin, suggesting that such intronic miRNA-mediated RNA interference (RNAi) is highly target-specific. To further confirm the role of RNA splicing in this intronic RNAi effect, we have also tested three different SpRNAi-RGFP expression systems as shown in Fig. 4.3D by lanes from left to right: (1) vector expressing intron-free RGFP without any pre-miRNA insert; (2) vector expressing RGFP with an intronic anti-EGFP pre-miRNA insert; and (3) vector similar to the 2 construct but with a defective 5′-splice site in the SpRNAi intron. As a result of this, Northern bolt analysis shows that mature miRNA is released only from the spliced intron of the vector 2 construct, which is exactly identical to the SpRNAi vector construct with the anti-EGFP pre-miRNA insert in the Fig. 4.3C, indicating the requirement of cellular RNA splicing for intronic miRNA biogenesis.

4.6

Optimization of Intronic miRNA Designs

After the above understanding, we have further determined the optimal structural design of the pre-miRNA inserts for inducing maximal gene silencing effects and learned that a strong structural bias exists in the cellular selection of a mature miRNA strand during assembly of the RNAi effector, the RNA-induced gene silencing complex (RISC) [16]. RISC is a protein–RNA complex that directs either target gene transcript degradation or translational repression through the RNAi mechanism. Formation of siRNA duplexes plays a key role in assembly of the siRNA-associated RISC. The two strands of the siRNA duplex are functionally asymmetric, but assembly into the RISC complex is preferential for only one strand. Such preference is determined by the thermodynamic stability of each 5′-end base-pairing in the strand. Based on this siRNA model, the formation of miRNA and its complementary miRNA (miRNA*) duplexes was thought to be an essential step in the assembly of miRNA-associated RISC. If this were true, no functional bias would be observed in the stem-loop structure of a pre-miRNA. Nevertheless, we observed that the stemloop orientation of the intronic pre-miRNA is involved in the strand selection of a mature miRNA for RISC assembly in zebrafish. To find the correct miRNA structures for RISC assembly, we have constructed two different intronic pre-miRNA-inserted SpRNAi-RGFP expression vectors containing a pair of symmetric pre-miRNA constructs, respectively, namely miRNA*-stemloop-miRNA [1] and miRNA-stemloop-miRNA* [2], as shown in Fig. 4.4A. Both pre-miRNAs contain the same double-stranded stem-arm structure,

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which is directed against the EGFP nucleotide 280–302 sequence. In definition here, miRNA refers the exactly complete sequence of a mature microRNA, while miRNA* refers the reverse nucleotide sequence complementary to the mature microRNA sequence. After liposomal transfection of these miRNA-expressing SpRNAi-RGFP vectors (60 µg each) into two-week-old zebrafish larvae for 24 hours [16], we have isolated the zebrafish small RNAs using mirVana miRNA isolation columns (Ambion, Austin, TX) and then precipitated all the potential miRNAs matched to the targeted EGFP region by latex beads containing the target sequence. After sequencing, one effective miRNA identity, miR-EGFP(280–302),

Fig. 4.4 Different designs of intronic RNA inserts in an SpRNAi-RGFP construct for effective microRNA biogenesis. Gene silencing of a targeted green fluorescent protein (EGFP) expression in Tg(actin-GAL4:UAS-gfp) zebrafish demonstrates the asymmetric preference of RISC assembly between the transfection of [1] 5′-miRNA*-stemloop-miRNA-3′ and that of [2] 5′-miRNAstemloop-miRNA*-3′ hairpin RNA structures, respectively (A). In vivo gene silencing is only observed in the transfection of the [2] pre-miRNA construct, but not the [1] construct. Since the color combination of EGFP and RGFP displays more red than green (as shown in deep orange), the expression level of target EGFP (green) is significantly reduced in the [2] pre-miRNA transfection, while vector indicator RGFP (red) is evenly present in all vector transfections (B). Western blot analysis of the EGFP protein levels confirms the specific silencing result of the [2] premiRNA transfection (C). No detectable gene silencing is observed in fish with other treatments, such as liposome only (Lipo), empty vector without any insert (Vctr), and siRNA (siR)

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is identified to be active in the transfections of the 5′-miRNA-stemloop-miRNA*-3′ construct [2], as shown in Fig. 4.4A (gray-shading sequences). Since the mature miRNA is detected only in the zebrafish transfected by the [2] construct, the miRNA-associated RISC must preferably interact with the construct [2] rather than the [1] pre-miRNA, demonstrating the existence of a structural bias for intronic miRNA–RISC assembly. In this experiment, we use an actin-promoter-driven Tg(UAS:gfp) strain zebrafish, namely Tg(actin-GAL4:UAS-gfp), which constitutively express a green fluorescent EGFP protein in almost all cell types of the fish body. As shown in Fig. 4.4B, transfection of the SpRNAi-RGFP vector in these zebrafish silences the targeted EGFP and co-expresses a red fluorescent marker protein RGFP, serving as a positive indicator for intronic miRNA generation in the affected cells. The gene silencing effect in the gastrointestinal (GI) tract is somehow lower than other tissues, probably due to the high RNase activity in this region. Based on further Western blot analysis (Fig. 4.4C), the indicator RGFP protein expression is detected in both of the fish transfected with either 5′-miRNA*-stemloop-miRNA-3′ [1] or 5′-miRNA-stemloop-miRNA*-3′ [2] pre-miRNA, whereas gene silencing of the target EGFP expression (green) only occurs in the fish transfected with the [2] premiRNA construct, confirming the result of Fig. 4.4B. Because thermostability of the 5′-end stem-arm of both pre-miRNA constructs is the same, we conclude that the stem-loop of the intronic pre-miRNA is involved in the strand selection of a mature miRNA sequence during RISC assembly. Given that the cleavage site of Dicer in the stem-arm is known to determine the strand selection of mature miRNA [10], the stem-loop of an intronic pre-miRNA may function as a determinant for the recognition of the special cleavage site. In this early design, because the over sizes of many native pre-miRNA stemloop structures cannot fit in the SpRNAi-RGFP expression vector for efficient expression, we must use a short tRNAmet loop (i.e. 5′-(A/U)UCCAAGGGGG-3′) to replace the native pre-miRNA loops. The tRNAmet loop has been shown to efficiently facilitate the export of designed miRNAs from nucleus to cytoplasm through the same Ran-GTP and Exportin-5 transporting mechanisms [16]. Later, we use a pair of manually improved pre-mir-302 loops (i.e. 5′-GCTAAGCCAGGC3′ and 5′-GCCTGGCTTAGC-3′), which provide the same nuclear export efficiency as the native pre-miRNAs but not interfere with the tRNA exportation. The design of these new pre-miRNA loops is based on a mimicking modification of short stem-loops of mir-302s, which are highly expressed in embryonic stem cells but not in other differentiated tissue cells. Thus, the use of these man-made pre-miRNA loops will not interfere with the native miRNA pathway in the adult human body. For different pre-miRNA generation, because the intronic insertion site of the recombinant SpRNAi-RGFP gene is flanked with a PvuI and an MluI restriction site at its 5′- and 3′-ends, respectively, the primary intronic insert can be easily removed and replaced by various gene-specific pre-miRNA inserts (e.g. anti-EGFP and anti-Tyr pre-miRNA) possessing matched cohesive ends. By changing the pre-miRNA inserts directed against different gene transcripts, this intronic miRNA generation

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system can be served as a powerful tool for inducing targeted gene silencing in vitro and in vivo. For confirming the correct insert size, the pre-miRNA-inserted SpRNAirGFP gene (10 ng) can be amplified by a polymerase chain reaction (PCR) with a pair of oligonucleotide primers (i.e. 5′-CTCGAGCATG GTGAGCGGCC TGCTGAA-3′ and 5′-TCTAGAAGTT GGCCTTCTCG GGCAGGT-3′) for 25 cycles at 94 °C, 52 °C and then 70 °C each for one minute. The resulting PCR products are fractionated on a 2% agarose gel, and then extracted and purified by gel extraction kit (Qiagen, Valencia, CA) for sequencing confirmation.

4.7

Evaluation of Natural Anti-tyrosinase miRNA Agents

We adopt the proof-of-principle design of the Pol-II-mediated SpRNAi-RGFP expression system and use it for developing new cosmetic products for skin care. In this new approach, we apply skins a non-naturally occurring intron capable of being processed into hairpin-like precursor microRNA (pre-miRNA) molecules by the skin cells and thus inducing specific gene silencing effects on epidermal pigment-related genes and/or aging-causing genes. In this case, the RNA splicing- and processing-generated gene silencing molecule is the hairpin-like pre-miRNA insert located within the intron area of the recombinant gene and is capable of silencing a targeted gene, such as tyrosinase (Tyr), hyaluronidase (Hyal), hyaluronan receptors CD44 and CD168, and other pigmentation-related and/or aging-related genes and oncogenes. Alternatively, such a pre-miRNA insert can also be artificially incorporated into the intron region of a cellular gene in the skin. In general, this kind of intronic insertion technology includes plasmid-like transgene transfection, homologous recombination, transposon delivery, jumping gene integration and retroviral infection. In the present design, the recombinant SpRNAi-RGFP gene expresses an intronic insert construct reminiscent of a hairpin-like pre-mRNA structure. The recombinant gene is consisted of two major different parts: exon and intron. The exon part is ligated after RNA splicing to form a functional mRNA and protein for identification of the intronic RNA release, while the intron part is spliced out of the recombinant gene transcript and further processed into a desired intronic RNA molecule, serving as a gene silencing effector, including antisense RNA, miRNA, shRNA, siRNA, dsRNA and their precursors (i.e. pre-miRNA and piRNA). These desired intronic RNA molecules may comprise a hairpin-like stem-loop structure containing a sequence motif homologous to 5′-GCTAAGCCAG GC-3′ or 5′-GCCTGGCTTA GC-3′, which facilitates not only accurate excision of the desired RNA molecule out of the intron but also nuclear exportation of the desired RNA molecule to the cell cytoplasm. Also, the stem-arms of these intron-derived RNA molecules contain homology or complementarity, or both, to a targeted gene or a coding sequence of the targeted gene transcript. The homologous or complementary sequences of the desired RNA molecules are sized from about 18 to about 27 nucleotide bases. The homology and/or complementarity rate of the desired

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intronic RNA molecule to the targeted gene sequence is ranged from about 30–100%, more preferably 35–49%, for a desired hairpin-like intronic RNA and 90–100% for a linear intronic RNA molecule. In addition, the 5′-end of the non-naturally occurring intron contains a donor splice site homologous to 5′-GTAAGAGK-3′ motifs, while its 3′-end is a acceptor splice site that is homologous to 5′-GWKSCYRCAG-3′ motifs. Moreover, a branch point sequence is located between the 5′- and 3′-splice sites, containing homology to 5′-TACTWAY-3′ motifs. The adenosine “A” nucleotide of the branch-point sequence forms a part of (2′–5′)-linked lariat intron RNA by cellular (2′-5′)-oligoadenylate synthetases and spliceosomes in almost all spliceosomal introns. Furthermore, a poly-pyrimidine tract is closely located between the branch-point and 3′-splice site, containing a high T or C content oligonucleotide sequence homologous to either 5′-(TY)m(C/−)(T)nS(C/−)-3′ or 5′(TC)nNCTAG(G/−)-3′ motifs. The symbols of “m” and “n” indicate multiple repeats ≥1; most preferably, the m number is equal to 1~3 and the n number is equal to 7~12. The symbol “–” refers an empty nucleotide in the sequence. There are also some linker nucleotide sequences for the connection of all these intron components. In definition, the symbol W refers to an adenine (A) or thymine (T)/uracil (U), the symbol K refers to a guanine (G) or thymine (T)/uracil (U), the symbol S refers to a cytosine (C) or guanine (G), the symbol Y refers to a cytosine (C) or thymine (T)/uracil (U), the symbol R refers to an adenine (A) or guanine (G), and the symbol N refers to an adenine (A), cytosine (C), guanine (G) or thymine (T)/uracil (U).” Based on the above design, we have tested an optimized SpRNAi-RGFP gene construct expressing either anti-Tyr or anti-Hyal pre-miRNA directed against the unwanted pigmentation-related gene Tyr or aging-related gene Hyal in mouse skins (Fig. 4.3A). These pre-miRNAs target a highly conserved region (>98% homology) in both human and mouse Tyr and Hyal genes, respectively. In nature, there are 54 native miRNAs capable of targeting human tyrosinase (Tyr; 2082 bp) for pigmentation gene silencing, including mir-1, mir-15a, mir-16, mir-31, mir-101, mir-129, mir-137, mir-143, mir-154, mir-194, mir-195, mir-196b, mir-200b, mir200c, mir-206, mir-208, mir-214, mir-221, mir-222, mir-292-3p, mir-299-3p, mir-326, mir-328, mir-381, mir-409-5p, mir-434-5p, mir-450, mir-451, mir-452, mir-464, mir-466, mir-488, mir-490, mir-501, mir-522, mir-552, mir-553, mir-570, mir-571, mir-582, mir-600, mir-619, mir-624, mir-625, mir-633, mir-634, mir-690, mir-697, mir-704, mir-714, mir-759, mir-761, mir-768-5p, and mir-804. According to the miRNA-target database of the miRBase:: Sequences program (http://microrna.sanger.ac.uk), all these anti-Tyr miRNAs are directed against a region within the first 300 nucleotides of the Tyr gene transcript (NCBI accession number NM000372). Moreover, there are 9 native miRNAs capable of targeting hyaluronidase (Hyal; 2518 bp; NCBI accession number NM007312) for aging gene silencing, including mir-197, mir-349, mir-434-5p, mir-549, mir-605, mir-618, mir-647, mir-680, mir-702, and mir-763. In these native miRNAs, the mir-434-5p is the only one targets both Tyr and Hyal genes in human and also it is one of the most efficient miRNAs targeting the least off-target genes other

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than Tyr and Hyal. However, because almost all native miRNAs have several to over fifty targets and they tend to bind with some of the target genes more strongly than others, the use of these native miRNAs is likely not specific and safe enough for the skin care purpose. To test the feasibility of miRNA-mediated skin whitening, we have utilized the SpRNAi-RGFP expression system to express native pre-mir-434-5p in mouse skin. As shown in Fig. 4.5, patched albino (white) skins of melanin-knockdown mice (W-9 black) can be created by a succession of intra-cutaneous (i.c.) injections of the pre-mir-434-5p expression vector (50 µg) directed against tyrosinase (Tyr) for four days (total 200 µg). The Tyr, a type-I membrane protein and copper-containing enzyme, catalyzes the critical and rate-limiting step of tyrosine hydroxylation in the biosynthesis of melanin (black pigment) in skins and hairs. Starting from about two

Fig. 4.5 Depigmentational effects of RNAi-mediated tyrosinase (Tyr) gene silencing on mouse skins and hairs, indicating the feasibility of targeted gene knockdown in epidermal tissues using subcutaneous transfection of the recombinant SpRNAi-RGFP gene vector expressing a native mir434 pre-miRNA insert. Transfection of this mir-434-5p expression construct induces a strong and specific gene silencing effect on Tyr but not house-keeping GAPDH expression, whereas that of a U6 promoter-based siRNA expression vector against the same Tyr target sequence triggers nonspecific RNA degradation of both Tyr and GAPDH gene transcripts. Because Tyr plays an essential role in melanin (black pigment) production, the successful Tyr gene silencing can be observed by a significant loss of the black color in mouse skins and hairs. The circles indicate the location of i.c. injections. Small windows show the Northern blotting of Tyr mRNA knockdown in local hair follicles, confirming the effectiveness of the mir-434-mediated gene silencing effect

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weeks after the first i.c. injection, we observe that skin and hair pigments was significantly lost only in the pre-miRNA transfections. On the contrary, the blank control and the Pol-III (U6)-directed siRNA transfections present no significant effect. Northern blot analysis using mRNAs isolated from the hair follicles of the pre-mir-434-5p transfections show a 76.1% ± 5.3% reduction of Tyr expression two days post-transfection, whereas mild, non-specific degradation of random gene transcripts is detected in the siRNA-transfected skins (seen from the smearing patterns of both house-keeping control GAPDH and targeted Tyr mRNAs). Since [7] have reported that high siRNA/shRNA concentrations generated by the Pol-IIIdirected RNAi systems can over-saturate the cellular microRNA pathway and cause global miRNA dysregulation, this result indicates that the siRNA pathway is incompatible with the native miRNA pathway in skin tissues. Thus, the use of miRNA will likely provide a more effective, compatible and safe means for skin care. However, because the native mir-434-5p also targets five other cellular genes for silencing, including TRPS1, PITX1, LCOR, LYPLA2 and Hyal, the off-target effect of this native pre-mir-434-5p transfection remains to be determined.

4.8 Re-design of mir-434-5p for Skin Whitening Use in Human In order to improve the target-specificity and safety of anti-Tyr miRNA agents, we have re-designed the seed sequence of the mir-434-5p to form a highly matched region binding to either Tyr nucleotides 3–25 (namely miR-Tyr) or Hyal nucleotides 459–482 (namely miR-Hyal). The pre-miRNA insert sequence for Tyr gene silencing (pre-miR-Tyr) is 5′-GTCCGATCGT CGCCCTACTC TATTGCCTAA GCCGCTAAGC CAGGCGGCTT AGGCAATAGA GTAGGGCCGA CGCGTCAT-3′, which will form a hairpin-like RNA after splicing and will be further processed into a mature miR-Tyr microRNA (miRNA) sequence containing or homologous to 5′GCCCTACTCT ATTGCCTAAG CC-3′. Alternatively, the pre-miRNA insert for Hyal gene silencing (pre-miR-Hyal) is 5′-GTCCGATCGT CAGCTAGACA GTCAGGGTTT GAAGCTAAGC CAGGCTTCAA ACCCTGACTG TCTAGCTCGA CGCGTCAT-3′, which will form a different kind of hairpin-like RNA after splicing and will be further processed into a mature miR-Hyal miRNA sequence containing or homologous to 5′-AGCTAGACAG TCAGGGTTTG AA-3′. Although both pre-miR-Tyr and pre-miR-Hyal constructs are re-designed based on the same mir-434-5p backbone and mir-302 stem-loop, the mature miR-Tyr and miR-Hyal so obtained are totally different from each other. As shown in Fig. 4.6, the transfective expressions of miR-Tyr and miR-Hyal in mouse skins specifically knock down the targeted Tyr (reduction >90%) and Hyal genes (reduction > 67%), respectively, without any crossover off-target effect. The expression levels of mature miR-Tyr and miR-Hyal microRNAs are directly measured by Northern blot analysis, while the knockdown rates of the targeted Tyr and Hyal gene products (proteins) are determined by Western blot analysis.

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Fig. 4.6 Improvement of Tyr gene silencing using a man-made anti-Tyr pre-miRNA (miR-Tyr) insert expressed by the recombinant SpRNAi-RGFP gene vector in mouse skins, showing a more specific and less off-target gene silencing effect on the targeted tyrosinase (Tyr) gene. Neither offtarget (hyaluronidase) nor house-keeping (ß-actin) genes are affected by the transfection of this man-made intronic miR-Tyr microRNA

After understanding the optimized gene silencing effects of the re-designed miRTyr and miR-Hyal miRNAs in mice, we continue to test their efficacy, target specificity and safety in human skins. For efficient vector transfection into the human epidermal cell layers, a 1 µg/ml SpRNAi-RGFP vector solution is made by mixing 100 µg of the purified SpRNAi-RGFP vector in 1 ml of autoclaved ddH2O with 99 ml of 100% DNase-free glycerin (or called glycerol). DNase-free glycerin is used to encapsulate miR-Tyr for deep skin delivery and cell membrane penetration. This forms the major ingredient base for skin whitening and lightening products. Based on this, more other cosmetic ingredients may be added to increase the color, fragrance, effectiveness and/or stability of the final cosmetic products. As shown in Fig. 4.7A, Asian male arm skins treated with 2 ml of this major ingredient base expressing the aforementioned miR-Tyr (right site) versus empty SpRNAi-RGFP vector without any miRNA insert (glycerin control, left site) are compared. The result of skin whitening (loss of the black pigment–melanin) by the miR-Tyr treatment can be clearly observed in three days after two single treatments per day, as shown in this figure.

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Fig. 4.7 Human trial results of the improved anti-Tyr pre-miRNA (miR-Tyr) insert expressed by the recombinant SpRNAi-RGFP gene vector, identical to the Fig. 4.6 approach but in the human arm skins (A) and primary skin cell cultures (B and C), showing an over 50% knockdown rate in tyrosinase (Tyr) expression as determined by Western blot analysis

Then, primary skin cell culture is obtained by trypsin-dissociated skin explants from the tested donor with personal consent. The SpRNAi-RGFP vector transfection (final 6 µg/ml) in the primary skin culture is performed using a FuGene liposomal reagent (Roche Biochemicals, Indianapolis, IN), as described previously [13, 2006a]. Figure 4.7B shows that Western blot analyses of the loss of the targeted tyrosinase proteins and its substrate melanin are biostatistically significant (p > 0.001). The reduction amounts of tyrosinase proteins and its substrate melanin in skins is proportional to the treated concentrations of the miR-Tyr expression vector, indicating the positive correlation between the increase of the miR-Tyr treatment and the loss of the targeted tyrosinase proteins and its substrate melanin. No effect is found in other treatments, such as an empty SpRNAi-RGFP vector without any miRNA insert (glycerin) and an SpRNAi-RGFP vector expressing an anti-EGFP pre-miRNA insert (miR-gfp). At the concentration of 1 µg/ml of the miR-Tyr expression vector transfection, the optimal Tyr gene silencing rate is approximately 55–60% for tyrosinases and 30–45% for melanin, while the expression of non-target house-keeping control ß-actin is not affected by the miR-Tyr treatment, indicating the high target-specificity of this man-made microRNA molecule. Figure 4.7C further shows that the skin melanin levels are significantly reduced as shown in bright-field (BF) photographs of the primary skin cell culture (upper

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panels), while melanin (black dots around the cell nuclei) is highly expressed in the normal skin cells without the miR-Tyr treatment (i.e. blank and glycerin only). The miR-Tyr-treated skin cells present very limited melanin accumulation, demonstrating an effective skin-whitening effect in vivo. In regard to this loss of skin melanin, the targeted tyrosinase expression is concurrently reduced in the miR-Tyr-treated skin cells, as determined by immunocytochemical (ICC) staining analysis (Fig. 4.7C, lower panels). Therefore, based on these results, the re-designed miR-Tyr microRNA can be used to knock down the tyrosinase expression and successfully blocks melanin production in the human skins in vivo.

4.9

Microarray Analyses of Target Specificity and Safety

After establishing the gene silencing efficacy of the miR-Tyr in human skins, we use gene microarray analysis (Human GeneChip U133A&B arrays, Affymetrix, Santa Clara, CA) to assess the changes of approximately 32,668 human gene expression in the above miR-Tyr-transfected versus non-treated primary skin cell cultures, showing a much more target-specific and less offtarget gene silencing effect than the use of native mir-434. Total RNAs from each tested cell culture is isolated using RNeasy spin columns (Qiagen, CA). As shown in Fig. 4.8A (left), the result of microarray analysis in non-treated (miR–) versus miR-Tyr-transfected (miR+) primary skin cell cultures shows that there are only two genes altered more than 1.5 fold (>50% change of gene expression), including the targeted tyrosinase (Tyr) and its associated TRP1 gene (Fig. 4.8B), indicating that the miR-Tyr-mediated gene silencing effect is highly specific to the targeted Tyr. Furthermore, no gene related to either cytotoxicity or interferon-mediated PKR/2-5A pathways is affected, suggesting that this gene silencing effect is safe for skin care treatments. We have also used Northern blot analysis to compare and assess the gene expression levels of these microarray-identified genes (Fig. 4.8C), confirming the results of Figs. 4.8A, B. In further comparison with the result of the native mir-434-5p transfection (Fig. 4.8A, right), the correlation coefficiency (CC) rate clearly indicates that a high 99.8% population of the 32,668 tested human genes remains to be unchanged in the miR-Tyr-transfected (miR+) cells, while a low 77.6% CC rate is found in the mir-434-5p-transfected cells. This means that the expression patterns of at most only 65 cellular genes are altered by the redesigned miR-Tyr transfection, whereas those of over 7,317 genes may be changed by the native mir-434-5p transfection. Because it is a well-known fact that almost all native microRNAs (miRNAs) target multiple cellular genes due to their mismatched stem-arms, our present study demonstrates that the redesign of these stem-arm regions is required for the safe use of these miRNAs in target-specific gene silencing applications.

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Fig. 4.8 Gene microarray analysis (Affymetrix human GeneChip U133A&B, CA) of altered gene expression in the above human primary skin cell cultures with or without anti-Tyr pre-miRNA transfection, showing a much more target-specific and less off-target gene silencing effect than the use of native microRNAs, such as mir-434-5p

4.10

Conclusion

In sum, utilization of intronic hairpin-like microRNA (miRNA) expression provides a powerful new strategy for human skin care in vivo, particularly for hyperpigmentation treatment and aging prevention. Under the same treatment in animal trials, Pol-II-directed intronic miRNA expression does not cause any detectable cytotoxicity, whereas Pol-III-directed siRNAs induced non-specific mRNA degradation as previously reported [15, 24]. This underscores the fact that the intronic miRNA agent is effective, target-specific and safe in vivo. Because the intronic miRNAmediated gene silencing pathway is regulated by multiple intracellular surveillance systems, including Pol-II transcription, RNA splicing, exosome digestion and NMD processing, the gene silencing of intronic miRNA is considered to be the most effective, specific and safe approach among all three currently known RNAi

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pathways. Advantageously, using this intronic miRNA expression strategy, many cosmetic applications can be designed and developed for skin care, offering more long-term effectiveness, better target-specificity and higher safety in skin gene manipulation, which prevents the unspecific off-target cytotoxicity as commonly seen in the conventional siRNA methods.

References 1. Brantl S. (2002). Antisense-RNA regulation and RNA interference. Biochimica et Biophysica Acta 1575: 15–25. 2. Clement JQ, Qian L, Kaplinsky N, Wilkinson MF. (1999). The stability and fate of a spliced intron from vertebrate cells. RNA 5: 206–220. 3. Elbashir SM, Harborth J, Lendeckel W, Yalcin A, Weber K, Tuschl T. (2001). Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells. Nature 411: 494–498. 4. Fire A, Xu S, Montgomery MK, Kostas SA, Driver SE, Mello CC. (1998). Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 391: 806–811. 5. Ghosh S, Garcia-Blanco MA. (2000). Coupled in vitro synthesis and splicing of RNA polymerase II transcripts. RNA 6: 1325–1334. 6. Grant SR. (1999). Dissecting the mechanisms of posttranscriptional gene silencing: divide and conquer. Cell 96: 303–306. 7. Grimm D, Streetz KL, Jopling CL, et al. (2006). Fatality in mice due to oversaturation of cellular microRNA/short hairpin RNA pathways. Nature 441: 537–541. 8. Gunnery S, Ma Y, Mathews MB. (1999). Termination sequence requirements vary among genes transcribed by RNA polymerase III. J Mol Biol 286: 745–757. 9. Lee NS, Dohjima T, Bauer G, et al. (2002). Expression of small interfering RNAs targeted against HIV-1 rev transcripts in human cells. Nat Biotechnol 20: 500–505. 10. Lee Y, Ahn C, Han J, et al. (2003). The nuclear RNase III Drosha initiates microRNA processing. Nature 425: 415–419. 11. Lewis BP, Green RE, Brenner SE. (2003). Evidence for the widespread coupling of alternative splicing and nonsense-mediated mRNA decay in humans. Proc Natl Acad Sci USA 100: 189–192. 12. Lin SL, Ying SY. (2001). D-RNAi (messenger RNA-antisense DNA interference) as a novel defense system against cancer and viral infections. Curr Cancer Drug Targets 1: 241–247. 13. Lin SL, Chang D, Wu DY, Ying SY. (2003). A novel RNA splicing-mediated gene silencing mechanism potential for genome evolution. Biochem Biophys Res Commun 310: 754–760. 14. Lin SL, Ying SY. (2004a). Novel RNAi therapy – intron-derived microRNA drugs. Drug Des Rev 1: 247–255. 15. Lin SL, Ying SY. (2004b). Combinational therapy for HIV-1 eradication and vaccination. Int J. Oncol 24: 81–88. 16. Lin SL, Chang D, Ying SY (2005). Asymmetry of intronic pre-microRNA structures in functional RISC assembly. Gene 356: 32–38. 17. Lin SL, Ying SY. (2006a). Gene silencing in vitro and in vivo using intronic microRNAs. Methods Mol Biol 342: 295–312. 18. Lin SL, Chang SJE, Ying SY. (2006b). Transgene-like animal model using intronic microRNAs. Methods Mol Biol 342: 321–334. 19. Lin SL, Kim H, Ying SY. (2008). Intron-mediated RNA interference and microRNA (miRNA). Front Biosci 13: 2216–2230.

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20. Miyagishi M, Taira K. (2002). U6 promoter-driven siRNAs with four uridine 3′ overhangs efficiently suppress targeted gene expression in mammalian cells. Nat Biotechnol 20: 497–500. 21. Nott A, Meislin SH, Moore MJ. (2003). A quantitative analysis of intron effects on mammalian gene expression. RNA 9: 607–617. 22. Paul CP, Good PD, Winer I, Engelke DR. (2002). Effective expression of small interfering RNA in human cells. Nat Biotechnol 20: 505–508. 23. Schramm L, Hernandez N. (2002). Recruitment of RNA polymerase III to its target promoters. Genes Dev 16: 2593–2620. 24. Sledz, CA, Holko M, de Veer MJ, Silverman RH, Williams BR. (2003). Activation of the interferon system by short-interfering RNAs. Nat Cell Biol 5: 834–839. 25. Solano F, Briganti S, Picardo M, Ghanem G. (2006). Hypopigmenting agents: an updated review on biological, chemical and clinical aspects. Pigment Cell Res 19: 550–571. 26. Stark GR, Kerr IM, Williams BR, Silverman RH, Schreiber RD. (1998). How cells respond to interferons. Annu Rev Biochem 67: 227–264. 27. Tuschl T. (2002). Expanding small RNA interference. Nat Biotechnol 20: 446–448. 28. Tang G. (2005). siRNA and miRNA: an insight into RISCs. Trends Biochem Sci 30: 106–114. 29. Ying SY, Lin, SL. (2004). Intron-derived microRNAs–fine tuning of gene functions. Gene 342: 25–28. 30. Ying SY, Lin SL. (2005). Intronic microRNAs. Biochem Biophys Res Commun 326: 515–520. 31. Zhang G, Taneja KL, Singer RH, Green MR. (1994). Localization of pre-mRNA splicing in mammalian nuclei. Nature 372: 809–812.

Chapter 5

MicroRNA Profiling in CNS Tissue Using Microarrays Reuben Saba1,2 and Stephanie A. Booth1,2*

Abstract MicroRNAs (miRNAs) are important regulators of gene expression in virtually all eukaryotic cell types including the diverse cell types found in the CNS. They are involved in repressing gene expression by complementary hybridization to cognate protein-coding mRNAs. The likely involvement of miRNAs in disease processes requires both accurate detection and expression analysis strategies. In comparison to conventional methodologies to study miRNA expression, microarrays offer an advantage in terms of throughput, sensitivity and specificity. Although microarrays are almost routinely used in laboratories for the analysis of mRNA, the small size of miRNAs presents challenges for their analysis in terms of probe design, target labeling and hybridization conditions. We discuss these issues in this chapter as well as highlighting the emerging perspectives in this field. Keywords miRNA, central nervous system, microarray, oligonucleotide linker, probe design, direct-labelling, indirect-labelling, normalization, qRT-PCR, laser capture microdissection

5.1

Introduction to miRNAs

MicroRNAs (miRNAs) are ~18–25 nt long post-transcriptional regulators of gene expression in both plants and animals [7]. MiRNAs are genome encoded and are derived from a much larger transcript called a pri-miRNA. Pri-miRNAs are processed in the nucleus by the enzyme Drosha to generate ~70 nt long, stem-loop transcripts known as pre-miRNAs. These are exported through a nuclear-pore complex into the cytoplasm and subsequently processed by the enzyme Dicer to generate mature miRNAs. Mature miRNAs are incorporated into an RNA-induced silencing complex 1

Department of Medical Microbiology, University of Manitoba, Winnipeg, MB, R3E 0W3, Canada

2

Prion Diseases Program, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, R3E 3R2, Canada * Corresponding author: E-mail: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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(RISC), which either suppresses the translation and/or promotes the degradation of cognate protein-coding mRNA molecule(s) through complementary hybridization to the 3′-UTR. Among vertebrates, miRNAs are only partially complementary to their gene targets and only nucleotides 2–7 from the 5′-end of the miRNA, a region often referred to as the “seed sequence”, is predicted to bind to the target mRNA [40]. This imperfect complimentarity between the miRNA and its target site on the mRNA means that it is possible for any given miRNA to regulate hundreds of potential targets [34, 41]. It has been suggested that up to ~30% or more of the protein coding genes in the vertebrate genome are under miRNA regulation [40].

5.2

MiRNAs in the CNS

MicroRNAs have been implicated in several important biological functions in the CNS including neurogenesis [71], dendrite formation [59], brain morphogenesis [23], and silencing of non-neuronal transcripts [16, 64, 72]. One of the most abundant miRNAs identified in the adult mammalian brain is miR-124a which can account for up to 48% of the total miRNAs content of the brain [37]. Fascinatingly, this miRNA has been shown to play a putative role in modulating cell lineage fate. In one study, injection of miR-124a into HeLa cells (human carcinoma cell line) resulted in alterations in expression of over 100 different mRNA transcripts to generate a gene expression profile resembling that of a mature neuron [43]. Possibly, the binding motif of miR-124a, which is one of the most prevalent miRNA recognition elements (MREs) in the 3′-UTR of mammalian transcripts, is an important regulatory motif for the expression of neuronal genes and the maintenance of neuronal identity [76]. Due to the abundance of miRNAs in the CNS, as well as their regulatory and pleiotrophic properties, the involvement of these molecules in neurological disease processes is not surprising. The evidence for miRNA dysfunction in CNS disorders has been steadily accumulating including roles in Tourette’s syndrome [1], DiGeorge syndrome [38], fragile X mental retardation [30] and schizophrenia [26, 53]. More recently, evidence for the role of miRNA deregulation in neurodegenerative diseases including Alzheimer’s [47] and Parkinson’s [32] was also reported. In the latter, miR-133b was shown to work in an autoregulatory feedback loop with the transcription factor PitX3 to promote the maturation and survival of dopaminergic neurons in the brain. In patients with Parkinson’s disease and also in mouse models where there is a deficiency of dopaminergic neurons there is decreased expression of miR-133b [32]. Moreover, the deregulation of miRNAs in tumours of the CNS has been extensively studied (for a relevant review see [21]). Despite the fact that miRNAs have only recently been detected and characterized in the CNS, there exists a substantial amount of experimental evidence for their importance in the proper development and maintenance of this tissue. Furthermore, emerging evidence linking miRNA expression to dysfunctions of the CNS, advocates the targeting of these molecules as potential points of therapeutic intervention.

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Transcriptional Profiling of miRNAs Using Microarrays

The adaptation of genomic technologies to the study of miRNAs will ensure a rapid explosion in knowledge in this area over the next few years. Interestingly, in most publications that have laid down the groundwork for miRNA microarrays, the principal tissue studied was from the CNS. In this chapter, we describe the current trends, challenges and opportunities in the field of miRNA profiling using microarrays and other emerging technologies. We have examined a number of aspects of this methodology such as choice of array platform, the design of probes, miRNA isolation/enrichment options, target labelling strategies, hybridization conditions, and data processing. In several instances, novel strategies are presented that may be readily applied to the analysis of miRNAs from CNS tissues. Microarrays consist of addressable complimentary immobilized probes of DNA, RNA, or protein on a planar solid support, usually a glass slide [58]. The number of probes can vary from a few hundred in macro-projects to tens of thousands in large scale micro-projects. In this chapter, the word ‘probe’ refers to the reporter sequence, which is placed at a particular position on the microarray as it interrogates the sample for the presence of its reverse complement. The word ‘target’ refers to the molecule being interrogated in the sample. The probes on a microarray are arranged so that their specific location is known and can be referenced later on. Most of the current array experiments utilize fluorescent-tags to label targets that are subsequently detected by laser confocal microscopy. A quantitative inference of the abundance of the hybridized target from the original sample is determined from the intensity of the fluorescent signal on the array. Specifically, the relationship between the intensity of the signal to that of the abundance of the target is proportional.

5.3.1

MiRNA Array Platforms

The type of microarray platform utilized for profiling miRNAs plays a central role on the experimental design and type of analysis that can be performed. The user must choose between either custom or commercially available microarrays. Since commercial miRNA microarrays have only become available very recently, and the identification of miRNAs is still in progress, the use of custom manufactured microarrays is often the preferred option. The earliest prototype microarrays used for profiling miRNAs from CNS tissue were on filter or nylon membranes spotted with oligonucleotide sequences for mature miRNAs in either the sense [63] or antisense [35, 67] orientation. The predominant choice of microarray platform at present is planar glass; although the emerging use of liquid-phase bead-based microarrays is an interesting innovation [5] and will be discussed later in the chapter. The choices of immobilization chemistry for the attachment of probes to glass are wide-ranging. The most common are chemical coatings on the glass surface, such as aldehyde, epoxy, or poly-L-lysine,

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which interact either covalently or non-covalently with the DNA probe. A number of novel slide surfaces also show promise for the attachment of miRNA probes. The use of slides with three-dimensional surface matrices such CodeLink activated slides (GE Health Care, Piscataway, NJ, USA), Genopal® slides (Mitsubishi Rayon Co., Ltd., Yokohama, Japan) and slides that rely on evanescent resonator (ER) technology (UnaxisAG, Balzers, Liechtenstein) are emerging in the field. CodeLink Activated Slides are coated with a proprietary 3-D surface chemistry comprised of a long-chain, hydrophilic polymer containing amine-reactive groups. This polymer is covalently crosslinked to itself and to the surface of the slide. The crosslinked polymer, combined with end-point attachment, orients the immobilized DNA, and holds it upright from the surface of the slide. This combination means that the DNA is more readily available for hybridization and eliminates the need for stilts to hold up the capture probe. Additionally, the hydrophilic nature of the polymer provides a passive effect once the DNA has been immobilized. The overall result is a substantially lower background. A similar 3-D surface is used for miRNA probes spotted on Genopal® slides. In this instance it is plastic hollow fibers arranged in a block like fashion on the slide surface, initially cut from a large block of resin hardened fibers, which provides the 3-D space for attaching the probes [28]. Planar glass slides that employ Evanescent Resonance (ER) technology have greater sensitivity than conventional microarray slides due to their unique optical features [11] and have recently been introduced into miRNA research [9]. The distinguishing feature of these slides is a uniformly corrugated surface coated with a highly refractive index material, such as Ta2O5, that reduces background fluorescence and abnormal reflection patterns which may contribute to fluorescence cross talk. The overall effect of the ER platform is the improvement in the sensitivity of microarray detection which is imperative for low abundance miRNAs.

5.3.2

Probe Design

5.3.2.1

Probe Sequence

An invaluable resource for probe design is the freely available miRBase (http:// microrna.sanger.ac.uk) formerly known as the Sanger Registry [25]. This database houses the most up-to-date collection of miRNA sequences of both the pre-miRNAs (~60–70 nt) and mature miRNAs. It is possible to design microarrays to interrogate either pre-miRNAs or the mature species. Profiling the primary transcript (hairpin precursor) may provide valuable complementary information, however, most studies seek to understand the regulatory properties of mature miRNAs on protein expression, and so detection of mature miRNAs is generally the method of choice. Several strategies have been proposed to minimize cross-hybridization between closely related miRNAs on an array platform. In a recent publication it was shown that capture probes for miRNAs that have ~18–19 consecutive identical nucleotides show cross-hybridzation in comparison to probes for miRNAs that have less than

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18–19 consecutive identical nucleotides [67]. Therefore, it was suggested that probes should only be designed for miRNAs that have less than 18 consecutive identical bases. For example, within the let-7 family, probes should only be designed for let-7b, 7d, 7e, 7f, 7g, and 7i since they satisfy the criteria. However, probes for let-7a or let-7c would show cross-reactivity. In this case it may be possible to use other methods of identifying miRNAs that differ by a few nucleotides, such as qRT-PCR. In an alternate strategy, the large range of Tm values across all known miRNAs was curtailed in order to minimize the cross reactivity among closely related miRNAs. This was done by trimming the probes in a successive and alternating fashion from both the 3′- and 5′-ends, 1 nt at a time, until the Tm range between the probes was minimal [24]. Additional weight was given to trimming at the 5′-end of the probes which contains the highly conserved seed region so as to preserve the more variable 3′-end for better discrimination between closely related miRNAs.

5.3.2.2

Probe Immobilization via ‘Linker’ Addition

Determining optimal probe length for targets that are only ~18–25 nt long offers a unique challenge in the design of miRNA capture probes. Longer probe sequences offer more sensitivity with compromised specificity [54, 55], whereas short oligonucleotides provide greater specificity at the expense of sensitivity. Specificity of the probe also appears to be affected by steric hinderance caused by the proximity of the array surface. Nucleotide mismatches near the end of the probe that is tethered to the slide, can influence the specificity of a given probe to a greater extent than if the mismatch is towards the free end of the probe [5, 57]. The addition of ‘linker’ sequences to the probe overcomes these obstacles by holding the capture sequence away from the slide surface, thus reducing steric hinderence in the hybridization step, and allowing for a short, specific capture sequence to be used. The directional orientation of the nucleotide probes with respect to their binding to the microarray is not an issue in the design of probes which can be linked by either their 3′- or 5′-ends. Often, the technique used to generate the labeled target dictates the orientation of the probes and vice versa. A number of linkers, both nucleotide and chemical, have been described. These include using the pre-miRNA sequence (in which the miRNA capture sequence is embedded within the miRNA precursor sequence) [5], random ‘words’ that are absent in genomes [5], poly(T) tracts [57], and most often 5′-amino (6-carbon) linkers have been used when printing onto amine-coated slides (for example CodeLink slides) [8, 45, 48]. Another chemical linker that shows promise for the immobilization of miRNA capture probes is the addition of 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC). EDC cross linking likely proceeds via a 5′-terminal phosphate to form a phosphoramidate bond between the RNA and the nylon membrane. To date, EDC has only been used to immobilize size fractionated RNA on nylon membranes for Northern blot analysis of miRNAs [52]. In this case, EDC immobilized RNA was shown to be more amenable to hybridization with target, than probes covalently linked to the membrane by other means such as UV cross-linking.

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Chemical Modification of Probes

A number of probe modifications, independent from the addition of a ‘linker’, have been found to positively influence the specificity and sensitivity of target detection. Most of these probe modifications involve the incorporation, during synthesis, of nucleotide analogs that demonstrate more favourable hybridization characteristic than standard DNA-based probes. The most promising is the incorporation of locked nucleic acid (LNA) monomers into the probe sequence [14, 50, 69]. LNA nucleotides contain a methylene bridge that connects the 2′-oxygen of the ribose with the 4′-carbon [10, 69]. This bridge effectively locks the furnose ring in the sugar phosphate backbone and thereby reduces the conformational flexibility of the ribose. This results in an increase in the melting temperature (Tm) of the hybrid by +1−8 °C per LNA monomer for DNA hybrids and +2−10 °C per monomer in RNA hybrids [69], which in turn increases the affinity between probe and target, improves mismatch discrimination, and increases metabolic stability. One major outcome is that by adding varying amounts of LNA to array probes it is possible to design microarray capture probes with uniform Tm. In unmodified probes, the Tms can range between 45–74 °C thus compromising probe specificity and sensitivity during hybridization [14]. LNA modified probes have been used to improve the detection of CNS specific/enriched miRNAs by Northern blotting [69, 70], in situ detection [33, 50, 51] and by microarrays [11]. Another miRNA capture probe modification that has been investigated is the substitution at the 2′-postion of the ribose by O-(2-methoxyethyl) (MOE) side chain [9]. The addition of this moiety was shown to increase the affinity and specificity of binding to native RNA [44]. However, this was accompanied by a rather high false positive rate for the resulting microarray that was attributed to subjecting all probes on the array to identical hybridization temperatures; unlike LNA monomers which can be used to design a uniform Tm for the probes on an array. Though other promising oligonucleotide analogs exist, such as peptide nucleic acid (PNA), phosphoramidate DNA, hexitol nucleic acid (HNA) and morpholino based oligomers, they have not yet been tested in the design of capture probes for miRNA microarrays.

5.3.2.4

Probes for Use as Positive and Negative Controls

In miRNA microarray analysis, various control probes (positive, negative, and mismatch probes) serve to validate the sensitivity and specificity of the methodology. The most common positive controls used for analysis are other abundant small RNA species that are isolated alongside the miRNA from a biological sample. These include transfer RNAs (tRNAs), ribosomal RNAs (such as 5S RNA, 5.8S RNA), and U6 RNA species. The possibility of using these small RNA species as positive controls is only feasible when size fractionated mature RNAs are not used as starting material, as these control RNAs are significantly longer than the mature miRNA. If fractionated mature miRNAs are used then the only choice of positive control may be

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synthetic small RNAs spiked into the target; complementary probes to the spikes must be spotted on the array. To date, miRNA(s) that are ubiquitously expressed across all tissue types have not been identified, however, a number of miRNAs are known to be expressed at high levels in a tissue specific manner. In the case of CNS tissues, miR-124a may be an ideal positive control as this miRNA has been identified to be abundant in the majority of miRNA microarray analysis of this tissue [4, 5, 8, 9, 28, 35, 48, 57, 62, 77]. It is worth mentioning, however, that miR-124a has been recently shown to be present in abundance in the spinal cord [67], heart [67], and pancreas [6] suggesting that miRNAs may not be absolutely tissue specific. The most commonly utilized negative controls in vertebrate miRNA microarray research are plant miRNAs, as these miRNAs are predicted to be absent in the animal kingdom [57]. The main concern with using known animal miRNAs as negative controls is the extensive tissue tropism that is shown by animal miRNAs [60]. Another negative control that has been described is a trimer consisting of a random stretch of sequences (NHG-sequences; 10mer) that is very rare in the human genome [5]. Mismatch probes fulfill a further role in the determination of probe specificity; this is especially important in the validation of miRNA arrays as these molecules are often closely related, some differing by only a single nucleotide. Probes containing mismatches are often spotted alongside miRNA capture probes for at least a selection of miRNA probes on an array. Hybridization to mismatch probes has revealed that these probes generally tolerate 1–3 nucleotide differences between probe and target sequences. The extent of tolerance to mismatches, however, depends upon the location along the length of the probe. If the mismatch is in close proximity to the end of the probe that is tethered to the surface of the platform, then it is tolerated to a greater extent than if it was at the furthest end [5, 57, 67]. Tolerance, in this case, may be due to the limited accessibility of the wash buffer, during post hybridization processing of the arrays, or as result of increased steric hinderence conferred by the close proximity of the mismatch to the platform surface. Mismatch probes are useful to determine which miRNAs are especially prone to cross-hybridization on a given array platform, and therefore require further validation by a different method, such qRT-PCR.

5.3.3

MiRNA Preparation from CNS Tissues for Microarray Analysis

Central to all microarray experiments is the ability to isolate good quality RNA and microarray analysis of miRNAs is no exception. Many RNA isolation methods exist but they have all been optimized for capturing longer transcripts (mRNA) as short RNA species were considered unimportant. Since the discovery of miRNAs and other biologically relevant small RNA species, such as siRNAs, piwiRNAs and rasiRNA, conventional isolation methods have been re-designed or new methods of isolation implemented.

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Most early studies relied on total RNA extraction in Trizol to yield miRNAs for microarray analysis [4, 35, 45]. However, due to issues arising from non-specific interaction as a result of hybridization to pre-miRNAs, homologuos regions on target mRNA, and other RNA species a size fractionation step is generally employed to isolate or enrich for small RNA species. In early studies fractionation was carried out using 12–15% denaturing-PAGE [8, 48, 60, 68] or by filtration through size restriction columns such as the Amicon YM-100 (Millipore, Bedford, MA, USA) [5]. However, the need to isolate large numbers of highly reproducible samples for array analysis has driven the development and marketing of several commercial kits and instruments designed specifically for miRNA isolation. One of the most widely used commercial kits for isolating miRNAs is the mirVana™ miRNA isolation kit (Ambion, Autin, Texas, USA) that employs a combination of both chemical extraction and solid-phase extraction [62]. Specifically, organic extraction is followed by immobilization of RNA on glass-fiber filters to purify either total RNA or small RNA species (≤200 nt). Organic extraction involves disruption of the sample in a denaturing lysis buffer followed by acid-phenol:chloroform extraction of the total RNA from other contaminating bio-molecules including DNA. Solid-phase extraction relies on salt and alcohol to decrease the affinity of the RNA for water and increases its affinity for the solid support used (glass-fiber). Small RNA species are then enriched from total RNA by two sequential additions of 100% ethanol followed each time by passage through the solid support. Upon the addition of ethanol the concentration of the alcohol in the preparations increases from 25% to 55%. In the final step, the RNA is washed several times and eluted in low ionic strength solution. MiRNA isolation from CNS tissues by the mirVana kit for microarray analysis has been used in several studies [28, 57, 62]. Some commercial vendors offering miRNA isolation/enrichment kits include Invitrogen’s PureLink™ miRNA isolation kit from (Carlsbad, CA, USA), Qiagen’s miRNeasy Mini Kit (Valencia, CA, USA), Kreatech Diagnostics miRacULS II miRNA isolation and labelling kit (Amsterdam, Netherlands). Denaturing-polyacrylamide gel electrophoresis is a robust, although timeconsuming, methodology for the isolation of small RNAs. Ambion has automated this methodology and introduced the flashPAGE fractionator system that can rapidly and reproducibly fractionate total RNA. Gel fractionation enriches the RNA population ranging between ∼15–40 nucleotides in length by ~10,000-fold. The advantage of this over chemical/solid phase-extraction is that mature miRNAs can be specifically isolated whereas the chemical/solid phase-extraction extraction results in the enrichment of many small RNAs under ~200 nt, not just mature miRNAs.

5.3.4

Labelling miRNAs for Detection via Microarrays

Due to the small size of miRNAs, the lack of common sequence feature(s) and the relatively low amounts present in biological samples, specialized labelling methods are required to achieve consistent and representative labeling of miRNA targets. Most of the methodologies in use have been developed for the analysis of larger transcripts

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such as mRNA and adapted for use with small RNAs. The methodologies currently widely used for labeling miRNAs for array analysis can be classified into two major categories. Either miRNAs are isolated and labeled directly, or an intermediate step, for example reverse transcription or amplification, is employed and results in indirect labeling of the target. Following indirect labeling methodologies the resulting labeled species may be in either the sense or the antisense orientation. Additionally, a number of novel labeling techniques have been developed recently to specifically address the challenges of working with very small and rare targets; these will be described also.

5.3.4.1

Direct Labelling of miRNAs

Several different types of direct labelling strategies have been reported in studies to profile miRNAs from CNS tissues. These strategies either involve the direct labelling of nucleotides within the mature miRNA, or the addition of a labelled-tag to either the 3′- or 5′-terminus of the miRNA. Labelling of the 5′-end of miRNAs with the sensitive radioisotope 32P (γ 33P dATP) using T4 polynucleotide kinase has been used in a number of experiments [35, 67]. In these cases, the labeled-miRNAs were hybridized to nylon membrane arrays, and although relatively large amounts of RNA were used as starting material (5–50 µg), the method allowed the detection of <5 fmol of labelled miRNA. Though radioisotope labeling may offer a high degree of sensitivity, it does not allow competitive hybridization of a treated and untreated sample to be performed. Moreover, as with mRNA arrays it is unlikely that this methodology can be adapted to a planar glass microarray platform on which most robust microarray experiments are currently being performed. The incorporation of a fluorescent modified ribodinucleotide to the 3′-OH termini of miRNAs using T4 RNA ligase is a second direct labeling methodology that has been successfully used in CNS miRNA profiling [68]. The modified ribodinucleotide in question is termed pSEEp [29]. It is a ribodinucleotide with a 5′-phosphate and a 3′-terminal aliphatic amino group that is ideal for direct labelling of miRNAs for several reasons. Firstly, the reaction requires the presence of a 3′-OH group, which is a primary feature of miRNAs and therefore non-specific labelling of degradation products isolated alongside miRNAs is minimal. Secondly, all chemical reactions required to attach the label occur at the level of the ribodinucleotide and therefore do not compromise the miRNA. Thirdly, the reaction required to attach the labelled-ribodinucleotide to the miRNA occurs very efficiently as the bulky label is far removed from the site of enzymatic catalysis. Fourthly, the enzymatic reaction required to couple the labelledtag to the miRNA is very mild (reaction proceeds at 0–4 °C) and finally, different types of labels may be coupled to the ribodinuceliotide allowing competitive hybridization to be performed. The labelling reaction requires ~25 µg of total RNA which is initially size fractionated, although highly abundant miRNAs can still be detected when the amounts of starting material are lowered to ~50 ng of RNA. Direct covalent labelling of nucleotides within the miRNA is also possible. In one method G residues of the miRNA are covalently labelled at the N7 position with a fluorescent molecule bound to platinum (II) [4]. This type of labelling is based on the stable, coordinative binding properties of platinum (II) atoms to RNA,

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DNA, and proteins (Ulysis Alexa Fluor, Molecular Probes/Invitrogen, Carlsbad, CA, USA; Universal Labelling System (ULS), Kreatech Diagnostics, Amsterdam, Netherlands) [27, 74]. There are several advantages to this methodology in miRNA profiling, namely it is quick and reliable, does not require extensive manipulation of the miRNA and can be used in competitive hybridizations. Additionally, large amounts of starting material are not required for labelling (~7 µg RNA). However, the uneven presence of G residues in the mature miRNA may lead to disparate labelling and therefore provide an erroneous account of miRNA abundance. Furthermore, this technique does not consider genomic residuals isolated alongside the miRNAs that may also be labelled and interfere with the hybridization. An interesting miRNA labelling methodology that has been used in the analysis of miRNAs from plants, but could be readily applied for use in the analysis of vertebrate miRNAs has recently been described. This is labeling with quantum dots [42]. In this method, size fractionated miRNA is oxidized with sodium periodate to convert the 3′-hydroxyl groups, at the 2′- and 3′-positions of the ribose, into dialdehyde. The dialdehyde is then biotinylated by condensation with biotin-X-hydrazide. Streptavidin-conjugated quantum dots are then used for detection after the hybridization of the biotinylated miRNA to its complementary immobilized probe. Alternatively, streptavidin-conjugated gold followed by silver enhancement can also be used for the detection of biotinylated miRNA post hybridization [42]. In the case of the latter, gold nanoparticles catalyze the reduction of silver ions to form metallic silver that further autocatalyzes the conversion of silver ions to metallic silver that precipitates out on the gold particles. The direct labeling strategy provides a very low sensitivity of detection threshold, 0.4 fmol (at 633 nm excitation laser light) to 0.05–0.1 fmol (488 nm laser light). Additionally, the requirement of the 3′-hydroxyl group for the condensation reaction is a key feature of miRNAs. The primary drawback to this labelling method may be that it does not permit comparative analysis of miRNAs from more than one sample. Appending a 3′-tail to the miRNA which is then labelled with fluorescent dyes has also been used successfully in miRNA analysis [62] (mirVANA™ miRNA labeling kit, Ambion, Inc, Austin, TX, USA). Unmodified and amine-modified mixture of nucleotides are initially used to add ~20–50 nt long tail to the 3′-end of miRNAs using template independent E. coli poly(A) polymerase (PAP). Amine-reactive, fluorescently labeled moieties are then used to label miRNA tails, thus permitting the addition of multiple fluorescent label and increasing the sensitivity of detection. DNA dendrimers have also been used for the direct labelling of miRNAs (FlashTag™ RNA Labelling Kit, Genisphere, Hatfield, PA, USA; NCode™ miRNA Labelling System, Invitrogen). DNA dendrimers are complexes of partially double-stranded oligonucleotides that form a speherical structure via complementary hybridization with their free ends. Application specific capture sequences may be added to the free ends of dendrimers that enable it to hybridize to oligonucleotides [65]. A DNA dendrimer has on average 250 arms enabling the binding of ∼200 labels. The miRNA labeling process initially involves adding a tail to the 3′-end of the miRNA followed by a bridging ligation using an oligonucleotide sequence that is both complementary to the tail of the miRNA at one end as well as the capture sequence of

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the DNA dendrimer at the other. The use of DNA dendrimers can result in tremendous signal amplification by attaching numerous fluorescent dyes per molecule of miRNA, additionally, this method permits dual color competitive hybridization to be performed. A recently reported method is the LabelIT method (Mirus Bio Corporation, Madison, WI, USA) [20] in which an alkylating reactive group is covalently bound to fluoropores (Cy3 or Cy5) via a positively charged linker sequence. The alkylating moiety shows strong nucleic acid binding capabilities facilitated by electrostatic interaction. With this chemical labelling reagent, direct covalent modification of the miRNA takes place at any reactive heteroatom of the polynucleotide. Preferred binding sites include N7 of guanine, N3 of adenine, and N3 of cytosine. Another recently described method likely to be widely used in the future relies on the use of modification of probes on the array itself as well as a unique labeling strategy for the miRNA target [73] (Agilent miRNA Microarray System, Agilent Inc, Santa Clara, CA, USA). A single cyanine dye (Cy3 or Cy5) is added to the 3′-phosphate of 3′,5′-cytidine bisphosphate (pCp-Cy3 or pCp-Cy5) which is then ligated to the 3′-end of the miRNA using T4 RNA ligase to generate a modified miRNA which has an additional 3′-cytidine residue and one cyanine dye at the end. The oligonucleotide capture probe has a guanine residue at its 5′-end which is tethered to the slide by a T10 stilt. The guanine residue is complementary to the cytosine residue added to the 3′-end of the miRNA during the labelling reaction. The addition of the guanine residue serves two purposes. Initially, it stabilizes the probe/target interaction. Secondly, it raises the Tm of the miRNA above that of the hybridization temperature (∼55 °C). A hairpin structure is also added to the 5′-end of the probe so that it directly impinges on the 3′-end of the hybridizing labeled-miRNA. The hairpin structure serves to minimize sporadic signals generated by the binding of larger, non-miRNA species, as well as stabilizing the probe/target interaction. This labelling methodology, as well as being highly specific, shows an impressive degree of sensitivity as to the detection of <0.2 amol miRNAs has been reported.

5.3.4.2

Indirect Labelling of miRNAs

Indirect labelling of miRNAs for microarray hybridization can have two different connotations. It may either refer to the labelling of cDNA reverse transcribed from the mature miRNA sequence, subsequently used for hybridization, or it may refer to labelled-products obtained from the PCR amplification of the reverse transcribed product. In this section, we will discuss these two topics separately.

Labelled cDNA as Targets The ability to prime small RNA species, such as miRNAs and siRNAs for the generation of cDNA has been demonstrated [63]. Upon priming small RNA species, there is preferential binding of the primer to the 3′-end of the RNA template, which

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may be a novel property of reverse transcriptase when short RNA species are used as templates [63]. Random hexamers [63, 66] and random octamers [77] have both been used to prime mature miRNAs. The primer itself can carry a fluorescent label [45, 77] or the label can be added during cDNA synthesis by the incorporation of modified nucleotides containing a label, or having the ability to bind a label, [63, 66]. The main drawback for these methods is that there is a possibility of generating incomplete fragments that can bind in a non-specific manner to the capture probes. Nevertheless, it has been reported that the signal arising from this type of non-specific hybridization is minimal in relation to the signal generated from full-length, labelled targets [63]. It is also possible to add an adapter to one or both ends of the RNA in order to aid in the efficient priming of the small RNA. Adapter ligation to miRNAs is reminiscent of the early cloning strategies that were used for the identification and expression profiling of miRNAs (for example see [39]). In reports that have utilized this strategy, the adapter most often consists of a poly(A) tail ligated to the 3′-end of the RNA and the primer is oligo d(T) [63, 66]. Alternatively, a capture probe may be appended on to the 5′-end of the oligo d(T) primer which in turn may bind a fluorescent tag, such as a highly fluorescent DNA dendrimer (Array900 miRNA Direct Kit, Genisphere Inc, Hatfield, PA, USA) [24, 57]. This type of labeling for microarray hybridization may be considered a form of amplification where the signal intensity, rather than the genetic content, is augmented.

Labelled Amplified Products as Targets MicroRNA expression levels have been reported to span over four orders of magnitude [17], therefore a strategy that linearly amplifies the initial miRNA content may be advantageous, or even necessary to allow detection of low abundance miRNA species. Probably the simplest approach involves the ligation of adapters to both the 3′- and 5′-ends of the miRNA followed by reverse transcription of the ligation products. The cDNA is then PCR amplified using sense strand primers that have a fluoropore attached to it at the 5′-end, thereby labeling the sense strand of the PCR products [48]. In a very similar approach the labeled strand of the PCR reaction can be isolated and used for hybridization to the microarray, which removes any interference by hybridization involving the non-labeled strand. In one study, the products of the initial RT-PCR were further amplified using a set of modified primers [8]. The modifications involved adding a fluoropore to the end of one of the primers, and artificially lengthening the other [8, 75]. Upon resolution on a denaturing polyacrylamide gel, the labeled primer could be purified from the lengthened primer by gel excision, with the former being used in microarray detection. In another miRNA amplification strategy, a T7 RNA polymerase promoter sequence is incorporated into an adapter sequence to facilitate the labeling reaction [5]. Both 3′- and 5′-adapters are ligated to the miRNA with the 3′ adapter containing the T7 RNA polymerase promoter sequence. Subsequent reverse transcription using a primer specific for the 3′-adpater sequence, followed by second

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strand synthesis, generates a double stranded cDNA library of miRNAs. PCR amplification of this library using primers designed for the adapter sequences followed by in vitro transcription with T7 RNA polymerase, during which labeled nucleotides are incorporated, generates the labeled targets for hybridization. Labeled targets are in the same orientation as the mature miRNAs; however they now possess a modified nucleotide which has the capacity to accept a label. The microarray capture probes for the labelled targets should therefore be in the sense orientation relative to the mature miRNAs. Concurrently, a T7 RNA polymerase promoter may be introduced into the adapter added to the 5′-end of the miRNA; the microarray capture probes would be in antisense orientation relative to the mature miRNA. Using these amplification strategies it is possible to perform two-color, competitive hybridization analysis and the method is specific enough to discern miRNAs that differ by only a few nucleotides. Despite the benefits offered by miRNA amplification strategies, specifically in the analysis of low abundance transcripts, the introduction of amplification biases can be very problematic. The main biases most likely arise during the relatively large number of enzymatic steps that have to be performed in order to generate the labeled targets. Any bias introduced early on in the protocol is magnified at a later stage. The central bias arising from a random priming strategy [8, 48] is the likelihood of non-random labeling. Furthermore, there is also tendency for the amplification of non-specific products that could arise from a reverse transcription reaction. The latter, upon amplification, could obstruct the binding of perfectly complementary, full length-products [57].

5.3.4.3

Alternative Labeling Strategies

Several labeling strategies that are distinct from the direct and in-direct labeling methodologies described thus far have been utilized for the profiling of miRNAs by microarrays. RNA-primed, array-based Klenow enzyme (RAKE) assay offers several advantages to existing labeling strategies in that it eliminates systematic biases arising from reverse transcription, PCR amplification, ligation reactions, and enzymatic labeling [50]. The RAKE assay is performed on-slide. The DNA oligonucleotide probes spotted onto glass slides contain a 3′-terminus that is antisense to the mature miRNA, while the 5′-end possess a spacer sequence that is used to crosslink the probe to the glass surface. Connecting the miRNA capture sequence to the spacer sequence is a stretch of three consecutive thymidine residues. Initially, the RNA sample containing the miRNA sequence is hybridized to the array, followed by treatment with exonuclease I, which specifically degrades single stranded, unhybridized DNA probes. Next, the Klenow fragment of DNA polymerase I, along with biotin conjugated dATPs, are added to the reaction. The Klenow enzyme uses the miRNA as a primer and the unhybridized portion of the oligonucleotide probe as the template to incorporate the biotin-conjugated dATPs at thymidine residues. In the final step, streptavidin-conjugated fluoropores are

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used to visualize probes that have undergone Klenow based primer extension. RAKE has the ability to distinguish between paralogous miRNAs and also offers a high degree of sensitivity (1–2 fmol range). The ability of this methodology to distinguish between closely related miRNAs lies in the primer extension step where perfect complementarity at the 3′-end is paramount. Another advantage of this technique is that the enzymes employed in the methodology, Klenow and exonuclease I, work in an unbiased and sequence independent manner. The primary disadvantage of this method, however, is the inability to utilize the procedure for dual color, competitive hybridization. MiRNA detection and profiling system based on padlock probes and rolling circle amplification have also been reported [31], and can be easily adapted for microarray analysis. Padlock probes are linear DNA probes in which the terminal sequences of the probes are designed to hybridize to the two adjacent sequences of the target. In the case of miRNAs, the padlock probes recognize sequences at the 3′- and 5′-ends of the RNA and in the process the probes circularize. Upon the addition of DNA ligase (phi29 DNA polymerase), the termini of the padlock probe bound to a perfectly matched target ligate, thereby accurately distinguishing matched and mismatched miRNAs. This method has high specificity for closely related miRNAs, especially if they differ towards the middle. The miRNA that served as the template would now be used as the primer for rolling circle amplification; the overall outcome is linear amplification of the miRNA. By incorporating modified nucleotides capable of binding fluorescent moieties, linear amplified labeled targets can be generated for hybridization to a microarray containing probes that are antisense to the mature miRNA. The sensitivity of this method is estimated at ~1 fmol [31]. We summarize all of the labelling strategies that have been used to generate labelled-targets for miRNA microarray analysis in Fig. 5.1.

miRNA labelling

Direct labelling Chemical labelling

Indirect labelling

Enzymatic labelling

Labelled-cDNA

Random priming

Priming of miRNA ligated adapters

Alternative labelling Labelled amplified products

PCR amplification

RAKE assay

In vitro transcription of ds DNA Padlock probes and rolling circle amplification strategy

Fig. 5.1 Flowchart illustrating the miRNA labelling strategies that have been utilized in literature for labelled-target preparation for hybridization to miRNA microarrays. Refer to the text for detailed explanation about each methodology

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Hybridization Conditions for miRNA Microarrays

The temperature for hybridization is an important consideration in optimizing sensitivity and specificity of miRNA arrays. To date, there are only a limited number of publications that have examined this variable in detail [14, 24]. MiRNAs have widely variable Tms approximately between 45 °C and 74 °C. This variation along with the short length of these molecules, the variety of capture platforms utilized and differences in labeling strategy may have contributed to an overall neglect of this important parameter. To date, a uniform, optimal temperature for miRNA microarray hybridization has not been reported. A limited number of publications have examined the role played by hybridization temperature in the context of probe/ target mismatch discrimination [48, 57]. Hybridization temperatures of 42 °C and 50 °C are most commonly used in published studies. Several attempts have been made to identify a uniform hybridization temperature [14, 24, 69]. In these attempts, the authors focused their efforts in altering the nucleotide composition of the capture probes in order to achieve their goals. The incorporation of LNA monomers into the design of capture probes (reviewed earlier) can be used to harmonize the Tms of most of the miRNAs to a common value so as to identify a suitable hybridization temperature [14, 69]. A simple pattern that has been followed to generate LNA-modified probes involves the substitution of nucleotides with LNA monomers at every third position along the entire length of a probe (LNA3 pattern) [69]. The similarity in LNA-monomer electrostatic properties to that of nucleotide monomers and the compatibility of the LNA chemistry with the DNA phosphoramidite chemistry permits these modified nucleotides to seamlessly fit into the nucleotide sequence of the probe at desired positions and abundance. The ultimate goal of this is to obtain a uniform miRNA Tm (~75 °C) in order to allow for high stringency binding to achieve increased sensitivity and accuracy during hybridization (55 °C) [14, 69]. A second strategy employing probe trimming in order to achieve a uniform miRNA Tm has also been reported [24]. This strategy involved truncating nucleotides from 3′- and 5′-ends of probes with high Tm in an alternating fashion. Preference was given to trimming from the 5′-end so as to preserve the more variable 3′-end which would allow better discrimination between closely related miRNAs. The resulting Tm was approximately 66.97 °C with the hybridization temperature being 47 °C [24].

5.3.6

Processing miRNA Microarray Data

As with mRNA microarray profiling, the processing of data from miRNA experiments is important to produce accurate results. Most pertinent issues related to this area are covered in reviews on microarray analysis [3, 49], however, there are a number of issues that are specifically associated with miRNA arrays [18]. First, consideration must be given to the fact that during processing, related miRNA sample loss is inevitable and presently there is no foolproof way of quantifying total amount

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of miRNA in total RNA. This is further complicated by the fact that not all miRNAs are presently known and only a fraction of them may be detected by current miRNA microarray platforms. Secondly, unlike mRNA microarrays where the majority of genes do not show expression changes, a significant proportion of the miRNAs on an array may change relative to the context in which they are examined [4, 5, 12]. These issues create problems in the choice of method used to normalize miRNA array data. Normalization is a process of removing the source of systematic variation thus enabling data comparison across different samples and arrays. In the analysis of highdensity, whole genome, mRNA arrays this generally means adjusting data based on the null hypothesis, this assumption cannot necessarily be applied to the analysis of miRNAs. One option for miRNA analysis is to use a number of ubiquitously expressed small RNAs as normalization controls on the array in the same way that ‘housekeeping’ genes are used in some mRNA normalization procedures. Recently, an interesting miRNA microarray normalization technique was reported that utilizes an independently performed Northern blot analysis of a ubiquitously expressed miRNA, compared to external control RNAs, for array normalization [67]. The ubiquitously expressed miRNA in the report was let-7b where as the external controls were 5S and U6 RNAs. This method aims to correct for sample bias during isolation/enrichment and labeling procedures [67]. A possible drawback to using this method is all arrayed samples are normalized to a single miRNA whose expression may not be ubiquitous in all situations. Though 5S and U6 RNA species are regular normalization controls their expression and relative abundances may also vary depending on the conditions under which they are examined. More data from miRNA array analysis will be required before a consensus for miRNA array normalization can be reached.

5.4

Perspectives on the Future of High-Throughput miRNA Expression Profiling

MicroRNA profiling has so far focused on defining the miRNA complement of different tissues and in cell culture models. The uniqueness of miRNA expression profiles from tissue to tissue and the involvement of miRNAs in the determination of cell fate is one of the most interesting findings to date. CNS tissue is one of the most studied tissues so far, and also one of the most complex; the major challenge of miRNA research for the next decade is to unravel the molecular complement of individual cell types and cells within this tissue. One way of doing this is to compare miRNA profiles from cultured cells from different lineages, to miRNA profiles from whole tissue in order to predict the cell type in which individual miRNAs are expressed. We have used this approach in our laboratory to show that cell lines originating from different CNS lineages have unique expression profiles. Using a custom miRNA microarray platform [57] we profiled the expression of miRNAs from cultured cells of a number of neuronal cell lines (N2A, NB41A3, SKNFI, IMR32, NIE115, HCN2, HCN1A, CATH.a) and glial cell lines (EOC13.31, EOC20, C8B4, C8D30, C8S, C8D1A, A172, C6/LacZ). Principal component analysis

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(PCA) (Fig. 5.2) and hierarchical clustering (Fig. 5.3) of the miRNA expression profiles revealed robust separations of these cell types into distinct clusters. A number of miRNAs showed highly specific expression in either cell of neuronal or glial origin. These data highlight the importance of determining the cell specific expression profiles in order to understand different biological processes. The advent of laser capture microdissection (LCM) to isolate individual cells, and technologies that allow the detection of extremely small amounts of miRNA mean that this goal is now achievable. In the next section we describe some of the emerging technologies likely to make an impact on our understanding of miRNAs in the CNS.

5.4.1

Single Cell miRNA Profiling

Laser capture technology can be performed in two basic ways, either by cutting out individual cells or regions using a laser or by the activation of a thermoplastic membrane by a laser, which in turn cause specific adherence of the membrane to visually selected cell(s) or tissue fragments (LCM) [19]. The selected cells are then transferred to microcentrifuge tubes for subsequent molecular analysis. The application of LCM to miRNA analysis is a recent development with only one publication describing results to date. In this study, cell bodies and dendritic compartments were microdissected

Fig. 5.2 Principal component analysis (PCA) plot of CNS derived cell lines based on global miRNA expression using a custom miRNA microarray platform containing probes for ~557 nonredundant miRNAs. For each cell line four to six replicates were performed. Non-CNS cells (adrenal cells) were used for comparison

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Fig. 5.3 Hierarchical clustering illustrating miRNAs preferentially expressed in (A) neuronal and (B) glial cell types. Results were based on four to six separate hybridizations for each cell type

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and qRT-PCR assessment of multiple miRNAs performed. This process revealed a nuanced somatodendritic gradient distribution of miRNAs across E19 rat hippocampal neurons [36]. It was additionally revealed that some neuron enriched/specific miRNAs have unique spatial distribution patterns. For example, miR-124a which is renowned for its high abundance in neurons, is many-fold more abundant in the cell body compartments than in dendritic compartments. Albeit qRT-PCR assessment was performed with this set of isolated miRNAs, microarray assessment would have also been equally effective upon linear amplification, and potentially array analysis of the miRNAs isolated from microdissected tissue.

5.4.2

qRT-PCR Technologies

Although array analysis is becoming a standard laboratory procedure, the necessity for accurate validation of data requires a complementary method to be used. In miRNA analysis this is often the Northern Blot, however, several qRT-PCR methodologies have been reported for the analysis of mature miRNAs [2, 22, 56, 61]. Some of these methodologies involve the ligation of an adapter sequence to the miRNA (primarily a poly(A) tail to the 3′-end of the mature miRNA) followed by cDNA synthesis utilizing a primer complementary to the adapter sequence. Subsequent PCR amplification using a forward primer that is miRNA-specific and a reverse primer complementary to the adapter sequence enables the detection of the miRNA. An alternate qRT-PCR methodology that is widely used does not involve the ligation of adapters but uses a set of uniquely designed primers (TaqMan® MicroRNA Assay, Applied Biosystems, Foster City, CA, USA) [15]. In this TaqMan® MicroRNA Assay, the RT-primer is stem-looped with a protruding ~6 nt long 3′-end that is complementary to the 3′-end of the mature miRNA. Reverse transcription using the primer generates the cDNA. The RT product is then quantified using the conventional TaqMan® PCR approach, which includes a miRNA-specific forward primer, a reverse primer that targets the RT-primer derived sequence of the cDNA, and the dye-labeled TaqMan® probe. The unique design of the RT-primer is believed to enhance the thermal stability of the RT-primer/RNA duplex, which may be required for successful reverse transcription from a short primer. Furthermore, the modification of the forward primer to include a tail is to increase its Tm depending on the sequence composition of the miRNAs. All of the qRT-PCR methodologies that have been reported are able to detect low abundance miRNAs and are able to discriminate miRNAs that differ by as few as a single nucleotide.

5.4.3

Bead-Based miRNA Arrays

Liquid-phase arrays are an attractive option for miRNA profiling. Because hybridization takes place in solution, faster kinetics apply than with planar arrays, and modified probes, for example those containing LNAs, can also be readily

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used. To date, two different types of bead-based approaches have been reported for the analysis of miRNAs. The Luminex xMAP® technology (Luminex Corporation, Austin, TX, USA) utilizes ~5.6 µm polystyrene beads that are dyed using two different fluorescent dyes in different combinations to create ~100 microspheres each with its own unique color. Each microsphere can then be coated with a single miRNA capture oligonucleotide sequence targeting the entire length of the miRNA. Therefore, this approach permits multiplexing in the analysis of miRNAs. The labeled-targets for the array are prepared by ligating 3′- and 5′-adapters to the miRNA followed by reverse transcription. PCR amplification of the reverse transcribed miRNA using a set of primers complementary to the adapters and where one of the primers is also biotinylated allows one strand of the PCR products to be detected with staining by streptavidinphycoerythrin once complementary hybridization to the capture probes has occurred. The microbeads are then analyzed using a flow cytometric detector. The detector analyzes two properties of the beads: (1) detection of the bead color which designates miRNA identity, (2) measurement of phycoerythin intensity which is an assessment of miRNA abundance. For increased sensitivity, the capture probes on the microspheres can be LNA-modified (FlexmiR™ MicroRNA Assay, Luminex Corporation, Austin, TX, USA). The liquid-phase, bead-based microarray approach has been used to classify human cancers based on their miRNA expression profile [46]. Using this methodology, it was shown that profiling a modest number of miRNAs (217 in total) resulted in a more accurate classification of 334 human tumor samples than profiling the mRNA content of these tumors [46]. The second bead-based miRNA microarray approach that has been described in literature is the miRMASA technology which utilizes the Luminex xMAP® technology [5]. The capture probes are LNA based and only ~10–12 nt long. The probes target approximately half of the mature miRNA (beginning from the 3′-end). Once targets are bound, they are detected by an oligonucleotide sequence labeled with biotin, which binds to the free half of the miRNA. Similar to the FlexmiR™ MicroRNA Assay, two separate readings were made by the detector, an initial reading for the identity of the miRNA, and a second reading for the abundance of the miRNA. In contrast to the former bead-based approach, the miRMASA technology does not require the amplification of the miRNA sample and the possibility of a bias arising from unequal adaptor ligation. The sensitivity, specificity and rapidity of analysis may well make bead arrays the method of choice for focused studies on a particular target subset of miRNAs.

5.5

Discussion

The microarray platform is the method of choice for global miRNA expression analysis. In this chapter, we examined options for the design of array probes, and the enrichment and labeling techniques that are currently in use for miRNA profiling

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with reference to current literature. A number of challenges exist in regards to miRNA microarray applications: (1) their small size and the fact that they often differ by only a few nucleotides requires arrays to be highly specific, (2) the complete complement of miRNAs are as yet undefined and the number of experimentally verified miRNAs is growing and will be in excess of more than a thousand but could possibly reach tens of thousands and (3) many miRNAs are present in low abundance and require amplification for detection which may introduce bias. The recent explosion of interest for miRNAs has driven the rapid development of products and technologies which address these issues. The next few years will see a rapid expansion in the data produced from miRNA and a consensus on optimal techniques and quality control issues reached. Profiling of CNS tissues is one of the most active areas of research in the field of miRNA biology. The evidence presented to date suggests that miRNAs undoubtedly have key roles in neuronal development and likely their deregulation is an important factor in disease of the CNS. Microarray technology will be invaluable in the next few years in establishing links between miRNA expression and disease. One key emerging technology vital to this process will be the implementation of microdissection techniques to allow specific cell types and regions in the brain to be studied in isolation. MiRNA isolation and amplification technologies have reached a stage where this type of experimentation is possible and we expect a rapid expansion in the number of reports using LCM over the next few years. We anticipate the broadening of this technology in the molecular analysis of the CNS, specifically in miRNA expression analysis of complex diseases of the CNS where these molecules may serve as prognostic and diagnostic markers.

References 1. Abelson JF, Kwan KY, O’Roak BJ et al (2005) Sequence variants in SLITRK1 are associated with Tourette’s syndrome. Science 310:317-320 2. Allawi HT, Dahlberg JE, Olson S et al (2004) Quantitation of microRNAs using a modified Invader assay. RNA 10:1153-1161 3. Allison DB, Cui X, Page GP et al (2006) Microarray data analysis: from disarray to consolidation and consensus. Nat Rev Genet 7:55-65 4. Babak T, Zhang W, Morris Q et al (2004) Probing microRNAs with microarrays: tissue specificity and functional inference. RNA 10:1813-1819 5. Barad O, Meiri E, Avniel A et al (2004) MicroRNA expression detected by oligonucleotide microarrays: system establishment and expression profiling in human tissues. Genome Res 14:2486-2494 6. Baroukh N, Ravier MA, Loder MK et al (2007) MicroRNA-124a regulates Foxa2 expression and intracellular signaling in pancreatic beta-cell lines. J Biol Chem 282:19575-19588 7. Bartel DP (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116:281-297 8. Baskerville S, Bartel DP (2005) Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes. RNA 11:241-247

94

R. Saba, S.A. Booth

9. Beuvink I, Kolb FA, Budach W et al (2007) A novel microarray approach reveals new tissuespecific signatures of known and predicted mammalian microRNAs. Nucleic Acids Res 35: e52 10. Braasch DA, Corey DR (2001) Locked nucleic acid (LNA): fine-tuning the recognition of DNA and RNA. Chem Biol 8:1-7 11. Budach W, Neuschafer D, Wanke C et al (2003) Generation of transducers for fluorescencebased microarrays with enhanced sensitivity and their application for gene expression profiling. Anal Chem 75:2571-2577 12. Calin GA, Ferracin M, Cimmino A et al (2005) A MicroRNA signature associated with prognosis and progression in chronic lymphocytic leukemia. N Engl J Med 353:1793-1801 13. Castoldi M, Benes V, Hentze MW et al (2007) miChip: a microarray platform for expression profiling of microRNAs based on locked nucleic acid (LNA) oligonucleotide capture probes. Methods 43:146-152 14. Castoldi M, Schmidt S, Benes V et al (2006) A sensitive array for microRNA expression profiling (miChip) based on locked nucleic acids (LNA). RNA 12:913-920 15. Chen C, Ridzon DA, Broomer AJ et al (2005) Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res 33:e179 16. Conaco C, Otto S, Han JJ et al (2006) Reciprocal actions of REST and a microRNA promote neuronal identity. Proc Natl Acad Sci U S A 103:2422-2427 17. Cummins JM, He Y, Leary RJ et al (2006) The colorectal microRNAome. Proc Natl Acad Sci U S A 103:3687-3692 18. Davison TS, Johnson CD, Andruss BF (2006) Analyzing micro-RNA expression using microarrays. Methods Enzymol 411:14-34 19. Emmert-Buck MR, Bonner RF, Smith PD et al (1996) Laser capture microdissection. Science 274:998-1001 20. Enos JM, Duzeski JL, Roesch PL et al (2007) MicroRNA labeling methods directly influence the accuracy of expression profiling detection. Biotechniques 42:378-382 21. Esquela-Kerscher A, Slack FJ (2006) Oncomirs - microRNAs with a role in cancer. Nat Rev Cancer 6:259-269 22. Fu HJ, Zhu J, Yang M et al (2006) A novel method to monitor the expression of microRNAs. Mol Biotechnol 32:197-204 23. Giraldez AJ, Cinalli RM, Glasner ME et al (2005) MicroRNAs regulate brain morphogenesis in zebrafish. Science 308:833-838 24. Goff LA, Yang M, Bowers J et al (2005) Rational Probe Optimization and Enhanced Detection Strategy for MicroRNAs Using Microarrays. RNA Biol 2:93-100 25. Griffiths-Jones S (2006) miRBase: the microRNA sequence database. Methods Mol Biol 342:129-138 26. Hansen T, Olsen L, Lindow M et al (2007) Brain Expressed microRNAs Implicated in Schizophrenia Etiology. PLoS ONE 2:e873 27. Heetebrij RJ, Talman EG, v Velzen MA et al (2003) Platinum(II)-based coordination compounds as nucleic acid labeling reagents: synthesis, reactivity, and applications in hybridization assays. Chembiochem 4:573-583 28. Hohjoh H, Fukushima T (2007) Expression profile analysis of microRNA (miRNA) in mouse central nervous system using a new miRNA detection system that examines hybridization signals at every step of washing. Gene 391:39-44 29. Igloi GL (1996) Nonradioactive labeling of RNA. Anal Biochem 233:124-129 30. Jin P, Zarnescu DC, Ceman S et al (2004) Biochemical and genetic interaction between the fragile X mental retardation protein and the microRNA pathway. Nat Neurosci 7:113-117 31. Jonstrup SP, Koch J, Kjems J (2006) A microRNA detection system based on padlock probes and rolling circle amplification. RNA 12:1747-1752 32. Kim J, Inoue K, Ishii J et al (2007) A MicroRNA feedback circuit in midbrain dopamine neurons. Science 317:1220-1224 33. Kloosterman WP, Wienholds E, de Bruijn E et al (2006) In situ detection of miRNAs in animal embryos using LNA-modified oligonucleotide probes. Nat Methods 3:27-29

5 MicroRNA Profiling in CNS Tissue Using Microarrays

95

34. Krek A, Grun D, Poy MN et al (2005) Combinatorial microRNA target predictions. Nat Genet 37:495-500 35. Krichevsky AM, King KS, Donahue CP et al (2003) A microRNA array reveals extensive regulation of microRNAs during brain development. RNA 9:1274-1281 36. Kye MJ, Liu T, Levy SF et al (2007) Somatodendritic microRNAs identified by laser capture and multiplex RT-PCR. RNA 13:1224-1234 37. Lagos-Quintana M, Rauhut R, Yalcin A et al (2002) Identification of tissue-specific microRNAs from mouse. Curr Biol 12:735-739 38. Landthaler M, Yalcin A, Tuschl T (2004) The human DiGeorge syndrome critical region gene 8 and Its D. melanogaster homolog are required for miRNA biogenesis. Curr Biol 14:2162-2167 39. Lee RC, Ambros V (2001) An extensive class of small RNAs in Caenorhabditis elegans. Science 294:862-864 40. Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120:15-20 41. Lewis BP, Shih IH, Jones-Rhoades MW et al (2003) Prediction of mammalian microRNA targets. Cell 115:787-798 42. Liang RQ, Li W, Li Y et al (2005) An oligonucleotide microarray for microRNA expression analysis based on labeling RNA with quantum dot and nanogold probe. Nucleic Acids Res 33:e17 43. Lim LP, Lau NC, Garrett-Engele P et al (2005) Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature 433:769-773 44. Lind KE, Mohan V, Manoharan M et al (1998) Structural characteristics of 2’-O(2-methoxyethyl)-modified nucleic acids from molecular dynamics simulations. Nucleic Acids Res 26:3694-3799 45. Liu CG, Calin GA, Meloon B et al (2004) An oligonucleotide microchip for genome-wide microRNA profiling in human and mouse tissues. Proc Natl Acad Sci U S A 101: 9740-9744 46. Lu J, Getz G, Miska EA et al (2005) MicroRNA expression profiles classify human cancers. Nature 435:834-838 47. Lukiw WJ (2007) Micro-RNA speciation in fetal, adult and Alzheimer’s disease hippocampus. Neuroreport 18:297-300 48. Miska EA, Alvarez-Saavedra E, Townsend M et al (2004) Microarray analysis of microRNA expression in the developing mammalian brain. Genome Biol 5:R68 49. Mocellin S, Rossi CR (2007) Principles of gene microarray data analysis. Adv Exp Med Biol 593:19-30 50. Nelson PT, Baldwin DA, Kloosterman WP et al (2006) RAKE and LNA-ISH reveal microRNA expression and localization in archival human brain. RNA 12:187-191 51. Obernosterer G, Martinez J, Alenius M (2007) Locked nucleic acid-based in situ detection of microRNAs in mouse tissue sections. Nat Protoc 2:1508-1514 52. Pall GS, Codony-Servat C, Byrne J et al (2007) Carbodiimide-mediated cross-linking of RNA to nylon membranes improves the detection of siRNA, miRNA and piRNA by northern blot. Nucleic Acids Res 35:e60 53. Perkins DO, Jeffries CD, Jarskog LF et al (2007) microRNA expression in the prefrontal cortex of individuals with schizophrenia and schizoaffective disorder. Genome Biol 8:R27 54. Ramdas L, Cogdell DE, Jia JY et al (2004) Improving signal intensities for genes with lowexpression on oligonucleotide microarrays. BMC Genomics 5:35 55. Relogio A, Schwager C, Richter A et al (2002) Optimization of oligonucleotide-based DNA microarrays. Nucleic Acids Res 30:e51 56. Ro S, Park C, Jin J et al (2006) A PCR-based method for detection and quantification of small RNAs. Biochem Biophys Res Commun 351:756-763 57. Saba R, Booth SA (2006) Target labelling for the detection and profiling of microRNAs expressed in CNS tissue using microarrays. BMC Biotechnol 6:47 58. Schena M. (2003) Microarray Analysis. John Wiley & Sons, Inc., Hoboken, New Jersey

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R. Saba, S.A. Booth

59. Schratt GM, Tuebing F, Nigh EA et al (2006) A brain-specific microRNA regulates dendritic spine development. Nature 439:283-289 60. Sempere LF, Freemantle S, Pitha-Rowe I et al (2004) Expression profiling of mammalian microRNAs uncovers a subset of brain-expressed microRNAs with possible roles in murine and human neuronal differentiation. Genome Biol 5:R13 61. Shi R, Chiang VL (2005) Facile means for quantifying microRNA expression by real-time PCR. BioTechniques 39:519-525 62. Shingara J, Keiger K, Shelton J et al (2005) An optimized isolation and labeling platform for accurate microRNA expression profiling. RNA 11:1461-1470 63. Sioud M, Rosok O (2004) Profiling microRNA expression using sensitive cDNA probes and filter arrays. BioTechniques 37:574-6, 578-80 64. Smirnova L, Grafe A, Seiler A et al (2005) Regulation of miRNA expression during neural cell specification. Eur J Neurosci 21:1469-1477 65. Stears RL, Getts RC, Gullans SR (2000) A novel, sensitive detection system for high-density microarrays using dendrimer technology. Physiol Genomics 3:93-99 66. Sun Y, Koo S, White N et al (2004) Development of a micro-array to detect human and mouse microRNAs and characterization of expression in human organs. Nucleic Acids Res 32:e188 67. Tang X, Gal J, Zhuang X et al (2007) A simple array platform for microRNA analysis and its application in mouse tissues. RNA 13:1803-1822 68. Thomson JM, Parker J, Perou CM et al (2004) A custom microarray platform for analysis of microRNA gene expression. Nat Methods 1:47-53 69. Valoczi A, Hornyik C, Varga N et al (2004) Sensitive and specific detection of microRNAs by northern blot analysis using LNA-modified oligonucleotide probes. Nucleic Acids Res 32: e175 70. Varallyay E, Burgyan J, Havelda Z (2007) Detection of microRNAs by Northern blot analyses using LNA probes. Methods 43:140-145 71. Visvanathan J, Lee S, Lee B et al (2007) The microRNA miR-124 antagonizes the anti-neural REST/SCP1 pathway during embryonic CNS development. Genes Dev 21:744-749 72. Vo N, Klein ME, Varlamova O et al (2005) A cAMP-response element binding proteininduced microRNA regulates neuronal morphogenesis. Proc Natl Acad Sci U S A 102:16426-16431 73. Wang H, Ach RA, Curry B (2007) Direct and sensitive miRNA profiling from low-input total RNA. RNA 13:151-159 74. Wiegant JC, van Gijlswijk RP, Heetebrij RJ et al (1999) ULS: a versatile method of labeling nucleic acids for FISH based on a monofunctional reaction of cisplatin derivatives with guanine moieties. Cytogenet Cell Genet 87:47-52 75. Williams KP, Bartel DP (1995) PCR product with strands of unequal length. Nucleic Acids Res 23:4220-4221 76. Xie X, Lu J, Kulbokas EJ et al (2005) Systematic discovery of regulatory motifs in human promoters and 3’ UTRs by comparison of several mammals. Nature 434:338-345 77. Zhao JJ, Hua YJ, Sun DG et al (2006) Genome-wide microRNA profiling in human fetal nervous tissues by oligonucleotide microarray. Childs Nerv Syst 22:1419-1425

Chapter 6

MicroRNA and Erythroid Differentiation Mei Zhan and Chao-Zhong Song*

Abstract MicroRNAs (miRNAs) regulate diverse cellular functions by acting as sequence-specific regulators of gene expression. We have investigated miRNA expression profiles in erythroid cells at different stages of maturation and the regulation of erythroid differentiation by specific miRNAs. We found that more than one hundred miRNAs were expressed in erythroid cells. The majority of them showed changes in their expression levels during erythroid differentiation. Further analysis revealed that the overall miRNA expression levels are increased in more mature erythroid cells compared with less mature erythroid cells. Among the miRNAs that are expressed in erythroid cells, miR-451 was most significantly upregulated during erythroid maturation. Functional studies using gain of function and loss of function approaches showed that miR-451 is associated with both human and mouse erythroid maturation. In conclusion, dynamic changes in miRNA expression occurred during erythroid differentiation, with an overall increase in the levels of miRNAs upon terminal differentiation of erythroid cells. MiR-451 may play a role in promoting erythroid differentiation. Keywords Erythroid differentiation, erythropoiesis, miRNA expression profile

6.1

Introduction

MiRNAs were first discovered in C. elegans as heterochronic genes that control larval development [41, 59, 74]. It is now recognized that miRNAs are an abundant class of small non-coding RNAs that function as sequence-specific regulators of gene expression in diverse species ranging from worms, flies, plants to humans [3, 4, 7,

Box 357720, Division of Medical Genetics, Department of Medicine University of Washington, Seattle 1705 NE Pacific Street, Seattle, WA 98195, USA * Correspondence author: Phone: 206 616-2814; Fax: 206 666-4527; E-mail: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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23, 27, 31, 66]. Currently, nearly 600 human/mouse miRNAs are in the miRNA Registry, miRBase, http://microrna.sanger.ac.uk/. The total number of microRNAs in the human genome has been estimated to be near a thousand, accounting for >3% of all human genes [9, 10]. Bioinformatic predictions suggested that about 20–30% of human genes may be regulated by miRNAs [42, 75]. As more miRNAs are discovered and their targets are identified, the pervasiveness and importance of miRNA regulation are coming into focus. It is now established that miRNAs constitute an important layer of the gene regulatory network that controls most, if not all, aspects of cellular functions including cell growth, differentiation and development across most eukaryotic genomes [3, 4, 7, 27, 30, 56, 63, 66]. MiRNAs are transcribed as long primary miRNAs (pri-miRNAs) that are processed sequentially by two RNase-III enzymes, Drosha and Dicer, into a small, imperfect double strand RNA duplex (miRNA:miRNA*) that contains both the mature miRNA strand and its incompletely complementary passenger strand (miRNA*). First, Drosha cleavage of pri-miRNAs in the nucleus releases the stemloop to generate precursor miRNAs (pre-miRNAs). The pre-miRNAs are exported to cytoplasm where they are further processed by Dicer to produce an approximately 22 nt duplex miRNA:miRNA* intermediate [4, 7, 23]. One strand of the duplex, the mature miRNA, is loaded into the effecter complex called RISC (RNAinduced silencing complex) [7, 23, 31]. MiRNAs in RISC function as guides through Watson-Crick rules for base paring to deliver the effecter complex to target mRNAs. MiRNAs generally repress gene expression through translational inhibition, although miRNA-mediated target RNA cleavage and degradation have been reported [55]. Recent studies indicated that miRNAs may play important roles in hematopoiesis [21, 38]. For example, miR-221 and miR-222 were shown to regulate erythropoiesis and angiogenesis through targeting c-kit [26, 57]. MiR-223 forms a regulatory network with transcription factors NFI-A and C/EBPα to regulate human granulopoiesis [25]. MiR-181 is preferentially expressed in B-lymphoid cells of mouse bone marrow and its overexpression in hematopoietic stem/progenitor cells increased the number of B-lineage cells in vitro and in vivo with a decrease in the number of CD8+ T cells [20]. It was thus suggested that miR-181 might play a role in the normal development of B-cell and T-cell lineages in the mouse. MiRNA expression profiling of in vitro differentiated megakaryocytes derived from CD34+ cells revealed dynamic expression of miRNAs during megakaryocytic differentiation. For example, the expression of miR-223 and the miR-15a-miR-16-1 cluster was initially down-regulated during megakaryocytic differentiation, but after 14 days in culture, their expression returned to the levels comparable to that of CD34+ progenitors, whereas miR-181b, miR-155, miR-106a, miR-17 and miR-20 were down-regulated during megakaryocytopoiesis [29]. Conditional dicer knockout in T cells also demonstrated a general role of miRNAs in T cell differentiation [22, 50]. In addition to regulating normal hematopoiesis, deregulation of miRNA expression has been associated with hematopoietic malignancies [15]. For example, miR-155

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was deregulated in Burkitt lymphoma [48] and other B-cell lymphomas [24, 37]. MiR-15a and miR-16-1 cluster is located at chromosome 13q14.3, which is a commonly deleted region in chronic lymphocytic leukemia [13]. One cluster of microRNAs, the mir-17-92 polycistron, is located in a region of DNA that is amplified in human B-cell lymphomas. The expression of microRNAs derived from the mir-17-92 locus is often substantially increased in B-cell lymphoma [32]. A miRNA signature is associated with prognosis and progression in chronic lymphocytic leukemia [14]. MiR-15 and miR-16 induced apoptosis by repressing BCL2 in leukemia cells, and enforced expression of the miR-17-92 cluster acted with c-myc to accelerate tumor development in a mouse B-cell lymphoma model [32]. Therefore, miRNAs can function as both tumor suppressors and oncogenes. Taken together, accumulating data suggest that miRNAs play important roles in normal hematopoiesis and their deregulation contributes to the development of leukemia. Erythropoiesis, the formation of red blood cells, is a dynamic process that occurs sequentially during development and erythroid cell maturation. During ontogeny, embryonic, fetal and adult erythropoiesis occurs in different anatomic sites. During erythroid differentiation, commitment of hematopoietic stem cells (HSCs) to erythroid lineage initiates the process of erythroid maturation which involves a concerted progression from committed erythroid progenitors consisting of erythroid burst-forming units (BFU-Es) and erythroid colony-forming units (CFU-Es) to morphologically distinct erythroid precursors of proerythroblasts, basophilic erythroblasts, polychromatophilic erythroblasts and orthochromatophilic erythroblasts sequentially. Orthochromatophilic erythroblasts extrude nucleus to give rise to reticulocytes [54]. Erythroid cells at different stages of development and differentiation are different in many respects such as morphology, gene expression and growth factor dependence. For example, erythropoietin signaling becomes essential during terminal erythroid differentiation. As erythroid terminal differentiation progresses, cells showed a gradual decrease in cell volume, increase in chromatin condensation and hemoglobinization. The cell-surface erythroid-specific Ter119 antigen is expressed by terminally differentiating erythroblasts [36]. Although the stages of erythroid cell differentiation are well characterized, the molecular mechanisms that orchestrate the coordinated changes from erythroid lineage commitment to terminal maturation remain largely unknown. As a new class of sequence-specific regulators of gene expression, miRNAs may form a regulatory network with growth factors and transcription factors to control erythroid lineage commitment and differentiation. To study the regulation of erythropoiesis by miRNAs, we examined the expression profile of miRNAs in erythroid cells at different stages of differentiation using miRNA microarray analysis [76]. Our studies show that, of the 295 miRNAs assayed, more than a hundred are detected in erythroid cells with varied abundances. Of interest, the overall expression levels of miRNAs are increased during erythroid differentiation. A single miRNA, miR-451, was most significantly upregulated in differentiating erythroid cells. Functional studies revealed that increased levels of miR-451 promote erythroid differentiation.

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Materials and Methods Cells

MEL cells were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum and 100 units/ml of penicillin and streptomycin, in a humidified incubator at 37 °C in the presence of 5% CO2. Erythroid differentiation of MEL cells was induced by adding dimethyl sulfoxide (DMSO, 2% final concentration, Sigma, St. Louis, MO, USA), or N,N’ hexamethylene bisacetamide (HMBA, 5 mM final concentration; Sigma) to the culture media. The cells were collected at 96 and 120 h after DMSO or HMBA treatment respectively. Cord blood (CB) was obtained from healthy, full-term placentas at the obstetrical unit of the University of Washington. CB CD34+ cell isolation and erythropoietic (E) culture of CB CD34+ cells were as described [28, 67]. Human ES cell (hESC) culture and generation of erythroid cells from hESCs were as described [18]. CCE cells were cultured on gelatin coated plates in Dulbecco’s modified Eagle’s medium (DMEM) containing 15% ES-Cult™ Fetal Bovine Serum (#0695, StemCell technologies Inc, 5.5 × 10−2 mM ß-mercaptoethanol and 103 U/ml leukemia inhibitory factor (LIF) (StemCell technologies Inc). Forty-eight hours before primary embryoid body (EB) formation, CCE cells were transferred to Iscove’s modified Dulbecco’s medium (IMDM; Gibco BRL) with 15% FCS, 5.5 × 10−2 mM ß-mercaptoethanol and 103 U/ml LIF. For primary differentiation assays, CCE cells were plated in Petri dishes at 1,000 to 2,000 cells per ml in 1% methylcellulose-based differentiation medium (Cat #06900, StemCell Technologies Inc.) that contains IMDM, 15% Fetal Bovine Serum, L-Glutamine 2 mM, MTG 150 µM, murine Stem Cell Factor 40 ng/ml. The cells were incubated for 5–7 days at 37 °C with 5% CO2. The formation of EBs was examined under phase contrast microscopy. To generate erythroblast cells, single cells from day-7 EBs were plated at 1 × 105 cells per ml in IMDM-based media containing 15% Fetal Bovine Serum, L-Glutamine 2 mM, MTG 150 µM, BIT 9500 (StemCell Technologies, Cat #09500) murine Stem Cell Factor 40 ng/ml, and human EPO (3 U/ml). The cells were analyzed 10 days later for Ter119 and CD71 expression using FACS. Mouse fetal liver cells were prepared from day 14 mouse embryos. Briefly, fetal livers were separated into single cells with a 21-gauge needle in cell culture medium and washed twice with the medium. Mature erythrocytes were removed using the lysing procedure as described [11] with modifications. Briefly, fetal liver cells were suspended in a solution containing 155 mM NH4Cl, 10 mM KHCO3, and 1 mM EDTA for 15 min at 4 °C to allow the lysis of mature erythroid cells, and then washed once with the same buffer. Erythroblasts at different stages of differentiation were isolated from the spleens of phenylhydrazine hydrochloride (PHZ) treated mice. PHZ solution in PBS was injected into mouse peritoneal cavity at 60 mg/kg body weight on each of days 0, 1, and 3. On the first day after the third injection, mice were euthanized and spleens were removed under sterile conditions for further analysis. Animal experiments were performed in compliance with the University of Washington Institutional Animal Care and Use Committee and NIH guidelines.

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Experiments using human CB cells and hESCs have been reviewed and approved by the IRB and appropriate Committees of the University of Washington.

6.2.2

Reagents

miRCURY™ LNA Knockdown probes for miR-451 and the control miRCURY™ LNA scrambled probes were purchased from Exiqon, Inc. (Vedbaek, Denmark). The miRIDIAN miR-451 mimic and miRIDIAN miR-451 mimic negative control oligonucleotides were purchased from Dharmacon (Lafayette, CO, USA). Mouse monoclonal antibody to c-Myc (9E10, sc-40), goat anti-mouse IgG-HRP (sc-2005) and goat anti-rabbit IgG-HRP (sc-2004) were purchased from Santa Cruz Biotechnology, Inc. (Santa Cruz, CA, USA). Anti β-actin antibody (ab8227) was purchased from Abcam, Inc (Cambridge, MA, USA). TaqMan® MicroRNA Reverse Transcription Kit and TaqMan® MicroRNA Assays kit were purchased from Applied Biosystems (Foster City, CA, USA).

6.2.3

RNA Isolation and miRNA Microarray

Total RNA was isolated using Trizol reagent (Invitrogen, CA, USA) and further purified using RNeasy mini kit (QIAGEN Valencia, CA, USA). MiRNA microarray including labeling, hybridization, scanning, noralization and data analysis was carried out by EXIQON. Briefly, RNA Quality Control is performed using Bioanalyser 2100. The samples were labeled using the miRCURY™ Hy3™/Hy5™ labeling kit and hybridized on the miRCURY™ LNA (locked nucleic acid) Array (v.8.0). Three independent hybridizations for each sample were performed on chips with each miRNA spotted in quadruplicate. Labeling efficiency was evaluated by analyzing the signals from control spike-in capture probes. LNA-modified capture probes corresponding to human, mouse, and rat mature sense miRNA sequences were spotted on slides. This set of LNA-modified oligonucleotides was designed to have uniform melting temperatures (Tm) of 72 °C against their complementary targets. Spotted microarray slides were processed using an automated hybridization station (Lucidea Slide Processor; GE Healthcare). The resulting signal intensity values were normalized to per-chip median values and then used to obtain geometric means and standard deviations for each miRNA. Triplicate arrays were performed under each treatment condition.

6.2.4

Real-Time RT-PCR Quantification of miRNAs

Real-time RT-PCR quantification of miRNA expression was carried out using TaqMan MicroRNA Assay kits according to the manufacturer’s protocol (Applied Biosystems,

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Foster City, CA, USA). The real-time RT-PCR assay is based on a stem-loop RT primer design [19]. Briefly, cDNAs were synthesized from total RNA using gene-specific primers. Reverse transcriptase reactions contained 10 ng of RNA samples, 50 nM stem-loop RT primer, 1 × RT buffer, 0.25 mM each of dNTPs, 3.33 U/µl MultiScribe reverse transcriptase and 0.25 U/µl RNase Inhibitor. The 15 µl reactions were incubated for 30 min at 16 °C, 30 min at 42 °C, 5 min at 85 °C and then held at 4 °C. Realtime PCR was performed using an Applied Biosystems 7300 Sequence Detection system. The 20 µl PCR reaction included 1.33 µl RT product, 1× TaqMan universal PCR master mix and 1 µl of primers and probe mix of the Taq-Man MicroRNA Assay kit. The reactions were incubated in a 96-well optical plate at 95 °C for 10 min, followed by 45 cycles of 95 °C for 15 s and 60 °C for 10 min. The threshold cycle (Ct) was determined using default threshold settings. The Ct value is defined as the fractional cycle number at which the fluorescence passes the fixed threshold. All experiments were done in triplicates each, and were repeated three times. U6 small nuclear RNA was used as an internal control to normalize RNA input in the real-time RT-PCR assay. The assay was carried out using the TaqMan® Endogenous Control, RNU6B kit.

6.2.5

RT-PCR

Total RNA was isolated as described above. Semi-quantitative RT-PCR was carried out using the SuperScript. III One-Step RT-PCR System (Invitrogen, Carlsbad, CA, USA). Each PCR cycle included 94 °C for 30 s, 60 °C for 30 s and 72 °C for 1 min. GAPDH was used as control for RNA quality and quantity.

6.2.6

Cell Transfection with Oligonucleotides

Stability-enhanced miR 451oligonucleotides and control nontargeting scrambled oligonucleotide were purchased from Dharmacon (Lafayette, CO, USA). MiR-451 antisense oligonucleotides and scrambled control oligonucleotides were purchased from (Exiqon, Vedbaek, Denmark). One day before transfection, the MEL was seeded into 24-well plates. Transfection of miR-451 mimic oligonucleotides, miR451 antisense oligonucleotides (ASO) or scrambled oligonucleotides (SO) control was carried out in triplicate using Lipofectamine™ 2000 (Invitrogen) according to the manufacturer’s instructions.

6.2.7

Benzidine Staining

Cells were smeared on glass slides and air-dried. Then they were fixed in 100% Methanol for 5 min, stained in 1% Benzidine solution for 5 min and subsequently

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incubated in 30% H2O2 for 2 min. Benzidine positivity was indicated by golden brown color.

6.2.8

Flow Cytometry

Flow cytometry analysis of mouse spleen erythroblasts was carried out as described [65]. Briefly, spleens were mechanically dissociated by pushing with a syringe plunger through a 70 µm strainer in the presence of phosphate-buffered saline and 0.5% bovine serum albumin (PBS/0.5% BSA). Cell viability was examined by trypan blue exclusion and was always greater than 95%. Cells (1 × 106) were incubated with anti-CD16/CD32 antibodies (BD Biosciences) to block Fc receptors prior to staining for flow cytometry. Then they were immunostained with phycoerythrin (PE)–conjugated anti-TER119 (1:200) (BD Pharmingen, San Diego, CA, USA) and fluorescein isothiocyanate (FITC)–conjugated anti-CD71 (1:200) (BD Pharmingen) antibodies. Propidium iodide was added to exclude dead cells from analysis. Erythroid cells at different stages of differentiation were sorted using a FACS Moflo machine (Cytomation, Fort Collins, CO, USA).

6.3 6.3.1

Results and Discussion MiRNA Expression Array and Design

Different methodologies have been developed to profile miRNA expression. The most common methods include Northern blot [61, 72], microarray-based approaches [5, 6, 8, 16, 39, 43, 44, 49, 52, 64, 69, 70] and quantitative PCR-based approaches [19, 33, 60, 62]. Other methods such as a bead-based profiling method [45], a single-molecule method for miRNA quantitation [51] and an invader assay [1] are also been reported. Northern blot was the first described method used by Ambros’ group to analyze lin-4 miRNA, the first miRNA identified in C. elegans [41]. Northern blot is still widely used for analysis of miRNA expression. However, it requires large amounts of RNA and is relatively insensitive for measuring miRNAs that are expressed at low levels. Therefore, it cannot be used for miRNA expression analysis when the starting material is limited. As more miRNAs are discovered, microarray-based approaches become popular choices for miRNA expression profiling. Microarray based approaches have several advantages over northern blot hybridization such as higher throughput, better normalization and increased sensitivity. In contrast to conventional mRNA expression profiling, accurate miRNA profiling is technically challenging due to the small size of mature miRNAs (about 22 nucleotides) and the sequence similarity between

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miRNA family members. For example, the short nature of miRNAs imposes limitation on the design of hybridization probes and optimization of hybridization condition for their detection. The calculated melting temperatures (Tms) toward the complementary DNA strand among the miRNAs assayed in this study vary from 45 °C to 74 °C due to differences in their GC content. For example, miR-324-3p is 73% G-C and miR-369 is 24% G-C. Consequently, very different hybridization conditions are required for accurate detection of their expression. In addition, although most of the human and mouse miRNAs differ by four or more nucleotides, some members of the miRNA families differ only by one or two nucleotides. Therefore, cross-hybridization of related miRNAs has been a problem facing many microarray platforms. Extensive research efforts have been made to the development of methods that permit moralization of experimental conditions for equal detection of miRNA expression. Recently, a new microarray platform (miChip) using locked nucleic acid (LNA)-modified capture probes showed increased sensitivity and specificity [17]. LNA modification increases the binding affinities for complementary RNA and DNA sequences [12]. In this microarray platform, the capture probes were designed to consist of a defined combination of unmodified and LNA-modified nucleotide analogs [71]. The LNA modification raises the thermal stability of nucleic acid duplex 3–8 °C per nucleotide depending on the sequence context and whether the complementary strand is DNA or RNA [12, 53]. By achieving uniform hybridization condition, LNA-modified probes offer higher sensitivity, specificity and equality for miRNA detection. Therefore, the miRNA expression analysis was carried out using the miRCURY™ LNA array, which has a normalized 72 °C Tm. Three pairs of RNA samples from independent cultures of MEL cells with or without DMSO treatment were subjected to miRNA expression profiling analysis. Normalization involved background subtraction and normalization with a global Lowess (LOcally WEighted Scatterplot Smoothing) regression algorithm. This within-slide normalization was performed to minimize differences between the colors in an intensity-dependent manner. Median Normalized Data contain normalized data where replicated measurements of quadruplicate spots of the same miRNA probe on each slide have been averaged. Median of ratio Hy5/Hy3 (sample/common reference) was median ratios of quadruplicate spots within each slide. Fold changes in miRNAs expression levels from three independent arrays under each experimental condition were calculated and presented as mean ± SD.

6.3.2

MiRNA Expression Profile During Erythroid Differentiation

MEL cells are derived from Friend virus transformed mouse spleen erythroid precursors that are blocked at about the pronormoblast stage of differentiation [46, 47]. Terminal erythroid differentiation into cells resembling orthochromatophilic normoblasts can

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be induced by treatment of MEL cells with chemical inducers such as DMSO. The percentage of benzidine stain positive cells and the level of β globin reach maximum after 96 h following DMSO treatment, recapitulating the normal process of erythroid differentiation from pronormoblast to later stages of erythrocytes. MEL cells have been used extensively as a cell model for studying erythroid differentiation. Therefore, analysis of miRNA expression status in MEL cells with or without induction of erythroid terminal differentiation should reveal miRNA expression profiles associated with erythroid differentiation. The identification of erythroid- and differentiation stage-specific miRNAs and the elucidation of their roles in erythropoiesis will provide important clues on the molecular control of erythroid differentiation. MiRNA expression in MEL cells with or without DMSO treatment was assayed using the miRCURY™ LNA Array (v.8.0), which contains 295 known murine miRNAs. Terminal erythroid differentiation of MEL cells following DMSO treatment was confirmed by benzidine staining and β globin expression analyses. More than a hundred miRNAs were detected in MEL cells with or without DMSO induction. Their expression levels, however, varied significantly with hybridization signals ranging from several ten thousands to a few hundreds. Of the miRNAs on the array, miR-298 was the most abundant miRNA with signals of about 50,000 in uninduced MEL cells. MiR-320 was the second most abundant miRNA in uninduced MEL cells. Since uninduced and induced MEL cells represent erythroid cells at pronormoblast and orthochromatophilic normoblast stages of differentiation, respectively, the results of the miRNA expression array should represent the miRNA expression profiles of erythroid cells at these two different stages of maturation. Significant changes in the levels of many miRNAs upon induction of erythroid differentiation were observed (Fig. 6.1). For example, miR-29b, miR-140*, miR-193, miR-382 and miR-434-5p which were undetectable in untreated MEL cells, became detectable following induction of erythroid differentiation by DMSO. In contrast, the levels of both miR-298 and miR-320, the two most abundant miRNAs in untreated MEL cells, decreased upon induction of erythroid maturation with DMSO. The level of miR-451 is the most significantly increased (more than seven fold), whereas the levels of several miRNAs, such as miR-29a, miR-26a, miR-22, miR144, miR-15b, miR-292-5p and miR-30a-5p, increased more than two fold upon induction of erythroid differentiation. The microarray results were validated using real-time RT-PCR analysis of several selected miRNAs. Recently, it was reported that miR-221 and miR-222 are down-regulated in E culture of human CB CD34+ cells [26]. Since miR-221 and miR-222 produced hybridization signals below the background level using the current array platform, we analyzed their expression using real-time RT-PCR. This assay showed that both miR-221 and miR-222 are expressed in MEL cells and mouse spleen primary erythroblasts. The level of miR-221 and 222 in MEL cells is very low since the ct value of both miRNAs are higher than a control miRNA which generated a hybridization signal that is near the threshed level for detection using the microarray platform. Therefore, the failure to detect miR-221 and miR-222 in the microarray maybe due to their relatively low levels in MEL cells. However,

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Fig. 6.1 Dynamic changes in miRNA expression during erythroid differentiation. Total RNAs were purified from MEL cells with or without DMSO treatment for 96 h. MicroRNA profiling was carried out using miRCURY™ LNA array. Three independent arrays were performed under each treatment condition. Relative miRNA levels (fold) in MEL cells with and without induction of erythroid differentiation by DMSO are shown (mean ± SD)

the levels of miR-221 and miR-222 decreased following DMSO or HMBA induction of MEL cells and as primary spleen erythroblast maturation progresses from early to later stages. These data are consistent with the observation that miR-221 and miR-222 levels decreased during erythroid cell maturation of E cultures of CB CD34+ cells by Felli et al. [26]. HMBA, another inducer of erythroid differentiation of MEL cells, induced similar to DMSO levels of erythroid differentiation of MEL cells, as judged by the percentage of benzidine-positive cells and the level of β globin expression. As similar levels of up-regulation of miR-15b, miR-16, miR-22, miR-26a, miR-29a and miR451 were also observed following HMBA treatment for 5 days, they confirmed the fact that the changes in miRNA expression are erythroid differentiation-specific rather than inducer-specific.

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Overall Increase in miRNA Levels During Erythroid Maturation

Box plot analysis revealed that overall miRNA expression increased upon induction of erythroid differentiation (Fig. 6.2). The biological implications of overall increase in miRNA expression following erythroid differentiation remain to be determined. Nevertheless, it is likely that the elevated levels of miRNAs during erythroid differentiation may play a role in inhibiting target genes whose downregulation is required for erythroid differentiation. Studies on miRNA expression in undifferentiated mESCs, day 11 EBs and mature somatic tissues also revealed an overall trend of increasing miRNA expression from immature to mature cells [68].

Fig. 6.2 Overall increase in miRNA expression level during erythroid differentiation. Box plot shows the distribution of hybridization signals in all capture probes on each array. RNAs from each sample (Hy5) and common reference pool (Hy3) are labeled using the miRCURY™ Hy3™/ Hy5™ labelling kit and hybridized on the miRCURY™ LNA Array (v.8.0). Capture probes with a Log2 median ratio of “0” on the Y-axis correspond to miRNAs that are equally expressed in MEL cells with or without DMSO induction of erythroid differentiation. Slide 1, 3 and 5 are data from untreated MEL cells. Slide 2, 4 and 6 are data from MEL cells that are treated with DMSO for 96 h. The lower boundary of the box indicates the 25th percentile, the line within the box shows the median, and the upper edge of the box marks the 75th percentile. Whiskers above and below each box indicate the 95th and 5th percentiles. All data points that lie outside the 5th and 95th percentiles are shown as symbols. This analysis revealed that there is an overall up-regulation of miRNA expression during erythroid differentiation

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A general upregulation of miRNAs in normal tissues compared with tumors was also observed [45]. These studies together with our results suggest that the increased miRNA levels in differentiated cells may play a role in the restricted gene expression in differentiated cells.

6.3.4

Association of miR-451 Expression with Human Erythroid Maturation

Our miRNA expression analysis revealed that miR-451 is the most significantly upregulated miRNA upon terminal erythroid differentiation of MEL cells. Therefore, we performed further analysis on its expression during erythroid differentiation using different erythroid culture and differentiation systems. Real-time RT-PCR analysis of RNAs from MEL cells at different time points following DMSO induction of erythroid differentiation showed that miR-451 level increases significantly at 12 h, reaches a peak level at 24 h, and remains at significantly high levels thereafter (Fig. 6.3A). These data demonstrated that the levels of miR-451

Fig. 6.3 Up-regulation of miR-451 during erythroid differentiation of MEL cells at different time point following DMSO treatment (A); in human CB CD34+ cells at day 0, 4, 8, 15 and 20 of E culture (B); in mESCs, day 10 EBs and day 7 E culture of day 10 EB cells (C); and in hESCs, day 7 EBs and 15 day expansion culture of erythroid differentiation of EB cells (D). MiR-451 levels were analyzed using real-time RT-PCR analysis as described in materials and methods and represented as fold changes

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begin to rise at relatively early time points and remain elevated throughout terminal erythroid differentiation of MEL cells. Recently, it was reported that human miR-451 is abundant in human red blood cells [58]. The same study also found that miR-451 was not detectable using Northern blot analysis in the cell lines J2E, F4N, BW5147, J558L and 416B, representing progenitors of fetal liver erythroid, bone marrow erythroid, T cell, B cell and multipotent precursor stages, respectively. To determine the expression status of miR-451 during human erythroblast differentiation and maturation, we carried out E culture of CB CD34+ progenitor cells. Erythroblast differentiation and maturation during E culture of human CB CD34+ cells were monitored by FACS analysis of glycophorin A expression and cell size distribution using FACS forward scatter. MiR-451 was expressed at very early stages of erythroid differentiation and its level increased near eight fold at day 4 of the E culture (Fig. 6.3B). MiR-451 level increased near 20 fold at day 8 of E culture when glycophorin A+ cells increased to 60%. At day 15 and day 20 of E culture, erythroblasts maturate into late erythroblasts as indicated by increases in the percentage of glycophorin A+ cells with reduced cell size. As shown in Fig. 6.3B, miR-451 remained at the peak level (near 20 fold) throughout the assay period up to 20 days in which the majority of the erythroblasts are late erythroblasts. The in vitro hematopoietic differentiation of mESCs is a useful tool to study the molecular control of hematopoiesis [35, 73]. The mESC line CCE cells efficiently undergo differentiation into mesoderm and hematopoietic cells in vitro. The in vitro differentiation system recapitulates early hematopoietic development of mice [34]. We next examined the expression of miR-451 during erythroid differentiation of CCE cells in erythroid culture in vitro. As shown in Fig. 6.3C, miR-451 levels increased near eight fold in day 10 EBs. The levels of miR-451 increased to 23 fold after 7-day E cultures of cells derived from day 10 EBs. Definitive-like erythroid cells have been efficiently derived from hESCs in culture [18] and references therein. Therefore, we also examined the expression of miR-451 during erythroid differentiation of hESCs. As shown in Fig. 6.3D, miR-451 levels increased to four fold in day 7 EBs and to 16 fold in cells from day 15 expansion cultures. These results demonstrated that miR-451 levels increased during in vitro erythroid differentiation of hESCs, mESCs and adult erythroid progenitors. We next analyzed the expression of miR-451 in vivo in primary erythroid cells at different stages of their maturation. Erythroblasts at different stages of maturation including proerythroblasts (Ter119medCD71high), basophilic erythro-blasts Ter119highCD71high), late basophilic and polychromatophilic erythroblasts (Ter119highCD71med), and orthochromatic erythroblasts (Ter119highCD71low), were isolated from mouse spleen as described [65]. Figure 6.4A shows a representative flow cytometry density plot. Real-time RT-PCR analysis revealed that the levels of miR-451 increased significantly during erythroid differentiation (Fig. 6.4B). The level of miR-451 increased more than ten fold when erythroid differentiation proceeds from proerythroblasts to basophilic erythroblasts, and maintained at high levels throughout the subsequent stages of erythroid maturation. These studies demonstrated that miR-451 upregulation is associated with erythroid cell maturation in vivo.

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Fig. 6.4 Expression of miR-451 in murine erythroblasts at different stages of erythroid differentiation. (A) flow cytometry density plot of spleen cells from PHZ treated mice. Spleen cells were immunostained with PE–conjugated anti-TER119 and FITC–conjugated anti-CD71 antibodies. X and y axes indicate the fluorescence units for PE and FITC respectively. Selected regions are proerythroblasts (P4), basophilic erythroblasts (P5), late basophilic and polychromatophilic erythroblasts (P6), and orthochromatic erythroblasts (P7). (B) Real-time RT-PCR assay of miR-451 levels in each erythroblast cell population as depicted. Data are shown as fold changes in miR-451 levels relative to proerythroblasts (P4), which is set as 1 (mean ± SD)

Mouse miR-451 and miR-144 genes are in a cluster [2]. Consistent with this, the levels of both miR-451 and miR-144 are significantly increased upon induction of erythroid differentiation, although the latter is not increased as significantly as the former. In agreement with the microarray results, RT-PCR analysis confirmed that the level of miR-144 increased in a similar pattern as that of miR-451 but at a lower magnitude, in MEL cells upon induction by DMSO or HMBA as well as in primary spleen erythroblasts at different stages of maturation. This result indicates that their levels may also be regulated posttranscriptionally.

6.3.5

Regulation of Erythroid Maturation by miR-451

We next tested whether the increase in miR-451 level plays a role in erythroid differentiation. As shown in Fig. 6.5A, the levels of miR-451 were further elevated following transfection of miR-451 oligonucleotides, compared with SO or mock transfected cells. The transfected miR-451 sustained the elevated levels of miR-451 in MEL cells up to 96 h post-transfection. Increased expression of β-globin and hemoglobinization have been used as markers of erythroid differentiation. The levels of β-globin and benzidine stain positive cells gradually increase during DMSO-induced erythroid differentiation and reach maximum by day 4 following DMSO treatment. We first determined whether increased levels of miR-451 affect globin expression. The levels of β globin were analyzed using RT-PCR at day 2 and day 4 following transfection of miR-451 oligonucleotides. As shown in Fig. 6.5B, increased level of β-globin was

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Fig. 6.5 Overexpression of miR-451 induced erythroid differentiation of MEL cells. (A) miR451 levels increased following DMSO induction of erythroid differentiation. miR-451 level was further elevated following transfection of miR-451 oligonucleotides. MEL cells were treated with DMSO and transfected with miR-451 oligonucleotides (451), scrambled oligonucleotides (SO) as control or mock transfected as indicated. Total RNA was prepared at different time points as indicated after transfection and DMSO treatment. MiR-451 levels were analyzed using real-time RT-PCR. Assays were carried out in triplicate for each RNA sample. Data are normalized using U6 small nuclear RNA as an endogenous control for RNA input. Fold changes in miR-451 levels are shown as mean ± SD. (B) MEL cells were transfected as in (A) without DMSO treatment. β globin expression was analyzed using RT-PCR at day 2 and 4 following transfection. GAPDH was used as a control for RNA input. (C) Hemoglobinization was analyzed by benzidine staining 48 h after transfection and DMSO treatment as in (A). *, p < 0.05 compared with SO and mock transfection controls

observed at day 2 and further increased at day 4 after miR-451 transfection, indicating the progression of erythroid differentiation of the cells following overexpression of miR-451. This result demonstrates that forced increase of miR-451 level in MEL cells can partially remove the blockade of erythroid differentiation. At day 2 after DMSO treatment, 7% of MEL cells that are transfected with SO oligonucleotides or mock transfected are benzidine stain positive. However, 11% of the cells that are transfected with miR-451 oligonucleotides are benzidine stain

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Fig. 6.6 Inhibition of miR-451 using miR-451 antisense oligonucleotides (ASO) blocks erythroid differentiation of MEL cells. (A) Dose-dependent decrease in miR-451 levels by miR-451 ASO (ASO). MEL cells were treated with DMSO and transfected with different amounts of miR-451 ASO or SO oligonucleotides as indicated for 48 h. MiR-451 levels were analyzed using real-time RT-PCR. (B) Time course of miR-451 inhibition by ASO. MEL cells were treated with DMSO and transfected with 50 nM of ASO or SO control oligonucleotides as indicated. The levels of miR-451 were analyzed using real-time RT-PCR at different time points as depicted. (C) Inhibition of endogenous miR-451 blocks DMSO-induced β globin expression. MEL cells were treated with DMSO and transfected with ASO, SO oligonucleotides or mock transfected as indicated. β-globin levels were analyzed using RT-PCR at day 2 and day 4 post-transfection and induction as indicated. GAPDH was used as control for RNA input. (D) Inhibition of endogenous miR-451 blocks DMSO-induced hemoglobinization. Hemoglobinization was analyzed using benzidine staining on day 0, day 2 and day 4 following transfection as in C. *, p < 0.05 compared with SO and mock transfection controls

positive (Fig. 6.5C). This significant increase in hemoglobinization indicated that increased levels of miR-451 promote erythroid differentiation. The induction of erythroid differentiation is miR-451 specific since transfection with SO or mock transfection had no effects on β-globin expression and hemoglobinization. These results together demonstrated that miR-451 levels increased significantly during erythroid maturation and elevated level of miR-451 in MEL cells promotes erythroid differentiation. If an increase in miR-451 level is required for erythroid differentiation, inhibition of its upregulation or activity should have inhibitory effects on erythroid differentiation. Therefore, we also tested the effects of inhibition of miR-451 on erythroid differentiation. ASOs against miRNAs have been shown to be very

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effective inhibitors of miRNA activity [40]. MEL cells were treated with DMSO and transfected with different amounts of ASO targeting miR-451, SO control or mock transfected for 2 days. MiR-451 ASO significantly and dose-dependently decrease in endogenous miR-451 levels in MEL cells (Fig. 6.6A) and the inhibitory effects of transfected miR-451 ASO on endogenous miR-451 lasted throughout the experimental period (Fig. 6.6B). This inhibition is highly specific since SO control oligonucleotides showed no effects on endogenous miR-451 levels (Figs. 6.6A, B). To determine whether inhibition of miR-451 using miR-451 ASO blocks erythroid differentiation, MEL cells were transfected with miR-451 ASO and treated with DMSO to induce erythroid differentiation. RT-PCR analysis showed increased levels of β-globin in cells transfected with SO and in mock transfected cells at day 2 following DMSO treatment (Fig. 6.6C). The levels of β-globin further increased at day 4, indicating the progression of erythroid differentiation. However, no increase in the levels of β-globin was observed at day 2 following DMSO induction in cells transfected with miR-451 ASO (Fig. 6.6C). The levels of β-globin increased to a lesser degree at day 4 after DMSO induction in cells transfected with miR-451 ASO (Fig. 6.6C). Benzidine staining also demonstrated that inhibition of miR-451 using miR-451 ASO significantly reduced the levels of hemoglobinization of MEL cells (Fig. 6.6D). These studies using gain of function and loss of function approaches demonstrated that miR-451 positively regulates erythroid differentiation. Future studies on the roles of other differentiation stage-specific miRNAs in erythroid differentiation as well as the identification of the targets of their regulation will shed lights on our understanding of the molecular control of erythropoiesis. Acknowledgements The authors acknowledge the Kai-Hsin Chang for experiments involving the use of human ES cells. This work was supported by grants from National Institute of Health (HL20899, GS; HL-01-013, CZS).

References 1. Allawi, H. T., Dahlberg, J. E., Olson, S., Lund, E., Olson, M., Ma, W. P., Takova, T., Neri, B. P., and Lyamichev, V. I. (2004). Quantitation of microRNAs using a modified invader assay. RNA 10, 1153–1161. 2. Altuvia, Y., Landgraf, P., Lithwick, G., Elefant, N., Pfeffer, S., Aravin, A., Brownstein, M. J., Tuschl, T., and Margalit, H. (2005). Clustering and conservation patterns of human microRNAs. Nucleic Acids Res 33, 2697–2706. 3. Alvarez-Garcia, I., and Miska, E. A. (2005). MicroRNA functions in animal development and human disease. Development 132, 4653–4662. 4. Ambros, V. (2004). The functions of animal microRNAs. Nature 431, 350–355. 5. Babak, T., Zhang, W., Morris, Q., Blencowe, B. J., and Hughes, T. R. (2004). Probing microRNAs with microarrays: tissue specificity and functional inference. RNA 10, 1813–1819. 6. Barad, O., Meiri, E., Avniel, A., Aharonov, R., Barzilai, A., Bentwich, I., Einav, U., Gilad, S., Hurban, P., Karov, Y., et al. (2004). MicroRNA expression detected by oligonucleotide microarrays: system establishment and expression profiling in human tissues. Genome Res 14, 2486–2494.

114

M. Zhan, C.-Z. Song

7. Bartel, D. P. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116, 281–297. 8. Baskerville, S., and Bartel, D. P. (2005). Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes. RNA 11, 241–247. 9. Bentwich, I., Avniel, A., Karov, Y., Aharonov, R., Gilad, S., Barad, O., Barzilai, A., Einat, P., Einav, U., Meiri, E., et al. (2005). Identification of hundreds of conserved and nonconserved human microRNAs. Nat Genet 37, 766–770. 10. Berezikov, E., Guryev, V., van de Belt, J., Wienholds, E., Plasterk, R. H., and Cuppen, E. (2005). Phylogenetic shadowing and computational identification of human microRNA genes. Cell 120, 21–24. 11. Boyle, W. (1968). An extension of the 51Cr-release assay for the estimation of mouse cytotoxins. Transplantation 6, 761–764. 12. Braasch, D. A., and Corey, D. R. (2001). Locked nucleic acid (LNA): fine-tuning the recognition of DNA and RNA. Chem Biol 8, 1–7. 13. Calin, G. A., Dumitru, C. D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., Aldler, H., Rattan, S., Keating, M., Rai, K., et al. (2002). Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc Natl Acad Sci USA 99, 15524–15529. 14. Calin, G. A., Ferracin, M., Cimmino, A., Di Leva, G., Shimizu, M., Wojcik, S. E., Iorio, M. V., Visone, R., Sever, N. I., Fabbri, M., et al. (2005). A MicroRNA signature associated with prognosis and progression in chronic lymphocytic leukemia. N Engl J Med 353, 1793–1801. 15. Calin, G. A., Garzon, R., Cimmino, A., Fabbri, M., and Croce, C. M. (2006). MicroRNAs and leukemias: how strong is the connection? Leuk Res. 30, 653–655. 16. Calin, G. A., Liu, C. G., Sevignani, C., Ferracin, M., Felli, N., Dumitru, C. D., Shimizu, M., Cimmino, A., Zupo, S., Dono, M., et al. (2004). MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias. Proc Natl Acad Sci USA 101, 11755–11760. 17. Castoldi, M., Schmidt, S., Benes, V., Noerholm, M., Kulozik, A. E., Hentze, M. W., and Muckenthaler, M. U. (2006). A sensitive array for microRNA expression profiling (miChip) based on locked nucleic acids (LNA). RNA 12, 913–920. 18. Chang, K. H., Nelson, A. M., Cao, H., Wang, L., Nakamoto, B., Ware, C. B., and Papayannopoulou, T. (2006). Definitive-like erythroid cells derived from human embryonic stem cells coexpress high levels of embryonic and fetal globins with little or no adult globin. Blood 108, 1515–1523. 19. Chen, C., Ridzon, D. A., Broomer, A. J., Zhou, Z., Lee, D. H., Nguyen, J. T., Barbisin, M., Xu, N. L., Mahuvakar, V. R., Andersen, M. R., et al. (2005). Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res 33, e179. 20. Chen, C. Z., Li, L., Lodish, H. F., and Bartel, D. P. (2004). MicroRNAs modulate hematopoietic lineage differentiation. Science 303, 83–86. 21. Chen, C. Z., and Lodish, H. F. (2005). MicroRNAs as regulators of mammalian hematopoiesis. Semin Immunol 17, 155–165. 22. Cobb, B. S., Nesterova, T. B., Thompson, E., Hertweck, A., O’Connor, E., Godwin, J., Wilson, C. B., Brockdorff, N., Fisher, A. G., Smale, S. T., and Merkenschlager, M. (2005). T cell lineage choice and differentiation in the absence of the RNase III enzyme Dicer. J Exp Med 201, 1367–1373. 23. Du, T., and Zamore, P. D. (2005). microPrimer: the biogenesis and function of microRNA. Development 132, 4645–4652. 24. Eis, P. S., Tam, W., Sun, L., Chadburn, A., Li, Z., Gomez, M. F., Lund, E., and Dahlberg, J. E. (2005). Accumulation of miR-155 and BIC RNA in human B cell lymphomas. Proc Natl Acad Sci USA 102, 3627–3632. 25. Fazi, F., Rosa, A., Fatica, A., Gelmetti, V., De Marchis, M. L., Nervi, C., and Bozzoni, I. (2005). A minicircuitry comprised of microRNA-223 and transcription factors NFI-A and C/EBPalpha regulates human granulopoiesis. Cell 123, 819–831. 26. Felli, N., Fontana, L., Pelosi, E., Botta, R., Bonci, D., Facchiano, F., Liuzzi, F., Lulli, V., Morsilli, O., Santoro, S., et al. (2005). MicroRNAs 221 and 222 inhibit normal erythropoiesis and erythro-

6 MicroRNA and Erythroid Differentiation

27. 28.

29.

30. 31. 32.

33. 34. 35. 36.

37.

38. 39.

40. 41. 42. 43.

44.

45.

46.

115

leukemic cell growth via kit receptor down-modulation. Proc Natl Acad Sci USA 102, 18081–18086. Filipowicz, W., Jaskiewicz, L., Kolb, F. A., and Pillai, R. S. (2005). Post-transcriptional gene silencing by siRNAs and miRNAs. Curr Opin Struct Biol 15, 331–341. Gabbianelli, M., Testa, U., Massa, A., Pelosi, E., Sposi, N. M., Riccioni, R., Luchetti, L., and Peschle, C. (2000). Hemoglobin switching in unicellular erythroid culture of sibling erythroid burst-forming units: kit ligand induces a dose-dependent fetal hemoglobin reactivation potentiated by sodium butyrate. Blood 95, 3555–3561. Garzon, R., Pichiorri, F., Palumbo, T., Iuliano, R., Cimmino, A., Aqeilan, R., Volinia, S., Bhatt, D., Alder, H., Marcucci, G., et al. (2006). MicroRNA fingerprints during human megakaryocytopoiesis. Proc Natl Acad Sci USA 103, 5078–83. Harfe, B. D. (2005). MicroRNAs in vertebrate development. Curr Opin Genet Dev 15, 410–415. He, L., and Hannon, G. J. (2004). MicroRNAs: small RNAs with a big role in gene regulation. Nat Rev Genet 5, 522–531. He, L., Thomson, J. M., Hemann, M. T., Hernando-Monge, E., Mu, D., Goodson, S., Powers, S., Cordon-Cardo, C., Lowe, S. W., Hannon, G. J., and Hammond, S. M. (2005). A microRNA polycistron as a potential human oncogene. Nature 435, 828–833. Jiang, J., Lee, E. J., Gusev, Y., and Schmittgen, T. D. (2005). Real-time expression profiling of microRNA precursors in human cancer cell lines. Nucleic Acids Res 33, 5394–5403. Keller, G., Kennedy, M., Papayannopoulou, T., and Wiles, M. V. (1993). Hematopoietic commitment during embryonic stem cell differentiation in culture. Mol Cell Biol 13, 473–486. Keller, G. M. (1995). In vitro differentiation of embryonic stem cells. Curr Opin Cell Biol 7, 862–869. Kina, T., Ikuta, K., Takayama, E., Wada, K., Majumdar, A. S., Weissman, I. L., and Katsura, Y. (2000). The monoclonal antibody TER-119 recognizes a molecule associated with glycophorin A and specifically marks the late stages of murine erythroid lineage. Br J Haematol 109, 280–287. Kluiver, J., Haralambieva, E., de Jong, D., Blokzijl, T., Jacobs, S., Kroesen, B. J., Poppema, S., and van den Berg, A. (2006a). Lack of BIC and microRNA miR-155 expression in primary cases of Burkitt lymphoma. Gene Chromosome Cancer 45, 147–153. Kluiver, J., Kroesen, B. J., Poppema, S., and van den Berg, A. (2006b). The role of microRNAs in normal hematopoiesis and hematopoietic malignancies. Leukemia 20, 1931–1936. Krichevsky, A. M., King, K. S., Donahue, C. P., Khrapko, K., and Kosik, K. S. (2003). A microRNA array reveals extensive regulation of microRNAs during brain development. RNA 9, 1274–1281. Krutzfeldt, J., Rajewsky, N., Braich, R., Rajeev, K. G., Tuschl, T., Manoharan, M., and Stoffel, M. (2005). Silencing of microRNAs in vivo with ‘antagomirs’. Nature 438, 685–689. Lee, R. C., Feinbaum, R. L., and Ambros, V. (1993). The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75, 843–854. Lewis, B. P., Burge, C. B., and Bartel, D. P. (2005). Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120, 15–20. Liang, R. Q., Li, W., Li, Y., Tan, C. Y., Li, J. X., Jin, Y. X., and Ruan, K. C. (2005). An oligonucleotide microarray for microRNA expression analysis based on labeling RNA with quantum dot and nanogold probe. Nucleic Acids Res 33, e17. Liu, C. G., Calin, G. A., Meloon, B., Gamliel, N., Sevignani, C., Ferracin, M., Dumitru, C. D., Shimizu, M., Zupo, S., Dono, M., et al. (2004). An oligonucleotide microchip for genomewide microRNA profiling in human and mouse tissues. Proc Natl Acad Sci USA 101, 9740–9744. Lu, J., Getz, G., Miska, E. A., Alvarez-Saavedra, E., Lamb, J., Peck, D., Sweet-Cordero, A., Ebert, B. L., Mak, R. H., Ferrando, A. A., et al. (2005). MicroRNA expression profiles classify human cancers. Nature 435, 834–838. Marks, P. A., and Rifkind, R. A. (1978). Erythroleukemic differentiation. Annu Rev Biochem 47, 419–448.

116

M. Zhan, C.-Z. Song

47. Marks, P. A., Sheffery, M., Ramsay, R., Ikeda, K., and Rifkind, R. A. (1987). Induction of transformed cells to terminal differentiation. Ann NY Acad Sci 511, 246–255. 48. Metzler, M., Wilda, M., Busch, K., Viehmann, S., and Borkhardt, A. (2004). High expression of precursor microRNA-155/BIC RNA in children with Burkitt lymphoma. Gene Chromosome Cancer 39, 167–169. 49. Miska, E. A., Alvarez-Saavedra, E., Townsend, M., Yoshii, A., Sestan, N., Rakic, P., Constantine-Paton, M., and Horvitz, H. R. (2004). Microarray analysis of microRNA expression in the developing mammalian brain. Genome Biol 5, R68. 50. Muljo, S. A., Ansel, K. M., Kanellopoulou, C., Livingston, D. M., Rao, A., and Rajewsky, K. (2005). Aberrant T cell differentiation in the absence of Dicer. J Exp Med 202, 261–269. 51. Neely, L. A., Patel, S., Garver, J., Gallo, M., Hackett, M., McLaughlin, S., Nadel, M., Harris, J., Gullans, S., and Rooke, J. (2006). A single-molecule method for the quantitation of microRNA gene expression. Nat Methods 3, 41–46. 52. Nelson, P. T., Baldwin, D. A., Scearce, L. M., Oberholtzer, J. C., Tobias, J. W., and Mourelatos, Z. (2004). Microarray-based, high-throughput gene expression profiling of microRNAs. Nat Methods 1, 155–161. 53. Nielsen, J. T., Stein, P. C., and Petersen, M. (2003). NMR structure of an alpha-L-LNA:RNA hybrid: structural implications for RNase H recognition. Nucleic Acids Res 31, 5858–5867. 54. Papayannopoulou, T., D’Andrea, Alan D., Abkowitz, Janis L. and Migliaccio, Anna Rita (2006). Biology of Erythropoiesis, Erythroid Differentiation, and Maturation. In HematologyBasic principles and Practice, R. Hoffman, Benz, Jr., Edward J., Shattil, Sanford J., Furie, Bruce, Cohen, Harvey J. Silberstein, Leslie, E., McGlave, Philip, ed. (Elsevier), pp. 267–288. 55. Pillai, R. S., Bhattacharyya, S. N., and Filipowicz, W. (2006). Repression of protein synthesis by miRNAs: how many mechanisms? Trends Cell Biol 17, 118–26. 56. Plasterk, R. H. (2006). Micro RNAs in animal development. Cell 124, 877–881. 57. Poliseno, L., Tuccoli, A., Mariani, L., Evangelista, M., Citti, L., Woods, K., Mercatanti, A., Hammond, S., and Rainaldi, G. (2006). MicroRNAs modulate the angiogenic properties of HUVECs. Blood 108, 3068–3071. 58. Rathjen, T., Nicol, C., McConkey, G., and Dalmay, T. (2006). Analysis of short RNAs in the malaria parasite and its red blood cell host. FEBS Lett 580, 5185–5188. 59. Reinhart, B. J., Slack, F. J., Basson, M., Pasquinelli, A. E., Bettinger, J. C., Rougvie, A. E., Horvitz, H. R., and Ruvkun, G. (2000). The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature 403, 901–906. 60. Schmittgen, T. D., Jiang, J., Liu, Q., and Yang, L. (2004). A high-throughput method to monitor the expression of microRNA precursors. Nucleic Acids Res 32, e43. 61. Sempere, L. F., Freemantle, S., Pitha-Rowe, I., Moss, E., Dmitrovsky, E., and Ambros, V. (2004). Expression profiling of mammalian microRNAs uncovers a subset of brain-expressed microRNAs with possible roles in murine and human neuronal differentiation. Genome Biol 5, R13. 62. Shi, R., and Chiang, V. L. (2005). Facile means for quantifying microRNA expression by real-time PCR. Biotechniques 39, 519–525. 63. Shivdasani, R. A. (2006). MicroRNAs: regulators of gene expression and cell differentiation. Blood 108, 3646–3653. 64. Sioud, M., and Rosok, O. (2004). Profiling microRNA expression using sensitive cDNA probes and filter arrays. Biotechniques 37, 574–576, 578–580. 65. Socolovsky, M., Nam, H., Fleming, M. D., Haase, V. H., Brugnara, C., and Lodish, H. F. (2001). Ineffective erythropoiesis in Stat5a(-/-)5b(-/-) mice due to decreased survival of early erythroblasts. Blood 98, 3261–3273. 66. Sontheimer, E. J., and Carthew, R. W. (2005). Silence from within: endogenous siRNAs and miRNAs. Cell 122, 9–12. 67. Sposi, N. M., Zon, L. I., Care, A., Valtieri, M., Testa, U., Gabbianelli, M., Mariani, G., Bottero, L., Mather, C., Orkin, S. H., et al. (1992). Cell cycle-dependent initiation and lineage-dependent abrogation of GATA-1 expression in pure differentiating hematopoietic progenitors. Proc Natl Acad Sci USA 89, 6353–6357.

6 MicroRNA and Erythroid Differentiation

117

68. Strauss, W. M., Chen, C., Lee, C. T., and Ridzon, D. (2006). Nonrestrictive developmental regulation of microRNA gene expression. Mamm Genome 17, 833–840. 69. Sun, Y., Koo, S., White, N., Peralta, E., Esau, C., Dean, N. M., and Perera, R. J. (2004). Development of a micro-array to detect human and mouse microRNAs and characterization of expression in human organs. Nucleic Acids Res 32, e188. 70. Thomson, J. M., Parker, J., Perou, C. M., and Hammond, S. M. (2004). A custom microarray platform for analysis of microRNA gene expression. Nat Methods 1, 47–53. 71. Tolstrup, N., Nielsen, P. S., Kolberg, J. G., Frankel, A. M., Vissing, H., and Kauppinen, S. (2003). OligoDesign: optimal design of LNA (locked nucleic acid) oligonucleotide capture probes for gene expression profiling. Nucleic Acids Res 31, 3758–3762. 72. Valoczi, A., Hornyik, C., Varga, N., Burgyan, J., Kauppinen, S., and Havelda, Z. (2004). Sensitive and specific detection of microRNAs by northern blot analysis using LNA-modified oligonucleotide probes. Nucleic Acids Res 32, e175. 73. Weiss, M. J., and Orkin, S. H. (1996). In vitro differentiation of murine embryonic stem cells. New approaches to old problems. J Clin Invest 97, 591–595. 74. Wightman, B., Ha, I., and Ruvkun, G. (1993). Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans. Cell 75, 855–862. 75. Xie, X., Lu, J., Kulbokas, E. J., Golub, T. R., Mootha, V., Lindblad-Toh, K., Lander, E. S., and Kellis, M. (2005). Systematic discovery of regulatory motifs in human promoters and 3′ UTRs by comparison of several mammals. Nature 434, 338–345. 76. Zhan, M., Miller, C. P., Papayannopoulou, T., Stamatoyannopoulos, G., and Song, C. Z. (2007). MicroRNA expression dynamics during murine and human erythroid differentiation. Exp Hematol 35, 1015–1025.

Chapter 7

Homeotic miRNAs: From Development to Pathologies Maya Ameyar-Zazoua, Irina Naguibneva, Linda Pritchard, and Annick Harel-Bellan

Abstract Hox genes are key elements for anterio-posterior morphogenesis. Hox genes are tightly regulated at the transcriptional level. This level of regulation, however, is by far not unique, and non-coding RNAs, and in particular microRNAs, provide an important supplementary level of regulation. This review recapitulates what is known about Hox-related microRNAs, describes a technique that can be used to address miRNA function and attempts to speculate on the function of regulation by miRNAs and how it may impact on medicine.

Keywords miRNA, Hox, LNA

7.1

Materials and Methods

All details on the antisense technique can be found in [25, 26].

7.2

Hox Genes

The establishment of the antero-posterior axis is triggered at the gastrula stage and is largely orchestrated by the Hox protein family for a review see [16]. Hox genes are highly conserved and are found in both vertebrates and invertebrates. At the genomic level, their overall organization is also highly conserved: they are organized in clusters, with various levels of redundancy depending on the species. Hox genes control subsets of genes involved in tissue morphogenenesis for review see [30]. Hox genes are expressed in a sequential manner, collinear with their position in the cluster, 3′ genes being expressed first. Morphogenesis starts at the anterior

Centre National de la Recherche Scientifique (CNRS) FRE 2944, Institut André Lwoff, Villejuif F-94801, France; Université Paris-Sud, Villejuif F-94801, France

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end, and the embryo extends from there toward the tail. Thus, 3′Hox genes begin to be expressed in the anterior part and, more 5′ genes start to be expressed sequentially as more posterior segments are added by continuous gastrulation. HOX proteins are transcription factors that regulate a number of different targets involved in tissue morphogenesis. Posterior and anterior Hox genes can be transcribed in the same embryonic areas, and the identity of the cells in these areas results from combinatorial gene expression. Analysis of various mutants in the Hox cluster supports a hypothesis known as “posterior prevalence”. Indeed, deletion of all paralogs in a group does not create a phenotype in the whole region of expression, but rather affects only the most anterior region of expression. Thus cell fate is dictated by the most posterior Hox genes when co-expressed with more anterior Hox genes [6]. Hox gene activation is primarily regulated at the transcriptional level, by mechanisms that may vary during development. Several transcription factors have been linked to establishment of the Hox gene expression pattern, including members of the drosophila caudal family (cdx in mouse), Krox 20 for review see [5] and the retinoic acid receptor RAR/RXR, the anterior boundary of some Hox genes (HoxB) being controlled by retinoic acid [29]. On the other hand, the maintenance of Hox expression patterns is epigenetically controlled, with two families of factors involved, the Trithorax proteins (trithorax in drosophila; mll in mouse) being involved in Hox gene activation and the Polycomb proteins being involved in Hox gene repression [10]. There is, however, strong evidence for additional post-transcriptional mechanisms regulating the level of at least some of the HOX proteins. In chicken, the pattern of expression of HOXB4 protein does not entirely match that of the corresponding mRNA [27]. Similar observations have been made for HOXB4 in mouse [2]. The discrepancy between mRNA and protein levels might be attributed to various causes including protein accessibility, stability etc. In recent years, however, an ancient mode of regulation of gene expression acting at the post-transcriptional level has been unraveled, which involves short non-coding RNAs, the microRNAs (miRNAs).

7.3

MiRNAs

MiRNAs are processed from long RNA precursors by the sequential action of two endonucleases, Drosha and Dicer [4]. MiRNAs influence gene expression by guiding, in a sequence-specific manner, a complex of proteins with which they form the “RISC” complex and which includes a member of the Argonaute family of proteins [15]. A similar complex is used in the RNA interference pathway by siRNAs, which induce the cleavage of the target messenger. In animals, in many instances, the RISC complex does not induce the cleavage of the target but rather inhibits target mRNA translation. The mechanism seems to depend on the degree of homology between the miRNA and its target sequence; in animals, the vast majority of miRNAs are not fully homologous to the target and thus repress translation, either at the level of initiation or at the level of elongation [7]. However, it is certainly not an absolute rule, and in some cases, miRNA also (or sometimes instead) induces cleavage or degradation of the target RNA [17]. The miRNA pathway is remarkably conserved. Moreover, the system is also highly redundant, with, for a number of miRNAs, several isoforms and several loci

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encoding each of these isoforms, underscoring the functional importance of the pathway. Indeed, a body of arguments indicates that miRNAs are essential molecules during development.

7.4

MiRNAs and Development

MiRNAs were first characterized in genetic screens searching for sequences governing the timing of development in C. elegans [23]. Since then, many other studies document the idea that some of the most essential functions for miRNAs take place during development, although it is also clear that their role continues throughout adult life, for example in the endocrine system [3]. MiRNAs are involved in a number of pathways that are important for correct development. In various organisms, they control the timing (C. elegans), the size of tissues (drosophila) and many other processes. Although much less is known in mammals, it is clear that the miRNA pathway is also essential for mammalian embryogenesis, since ubiquitous inactivation of Dicer is embryonic lethal at very early stages [1, 18], and tissue specific inactivation of Dicer is generally harmful for the targeted tissue see for example [24, 37]. Moreover, despite the important redundancy in the system, inactivation of a single locus of miR-1 also has important consequences for the embryo [37]. Thus, miRNAs are particularly important during embryogenesis. In theory, maternal miRNAs could provide an efficient means for controlling gene expression at early stages, when there is no transcription going on. In particular, miRNAs could be distributed non-homogenously in the oocyte cytoplasm, thus providing an initial intracellular pattern from which subsequent patterning could derive. This hypothesis remains to be demonstrated. At later stages, when gene expression is primarily controlled at the transcriptional level, miRNAs provide a supplementary level of control that seems adapted to help in achieving pattern formation, provided that the target controls an entire genetic program. Indeed, expression of a given miRNA in a specific region of the embryo will prevent both the activity of the target transcription factor (Fig. 7.1) and the activation of the genetic

target TF activity target TF mRNA expression miRNA expression

Fig. 7.1 MiRNAs and patterning. A transcription factor (TF) is expressed throughout an embryonic region; a miRNA that targets this TF is expressed in a defined area of this region; as a net result, the transcription factor activity is restricted to the remaining area, resulting in the formation of a pattern of activity

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program in this specific region, resulting in the formation of a pattern. Hox genes represent key transcription factors that control important genetic programs.

7.5

MiRNAs Encoded Within the Hox Cluster

It became quite clear very rapidly that miRNAs were involved in regulating Hox gene expression. The first evidence came with the observation that two families of miRNAs, miR-10 and miR-196, were encoded inside of the Hox cluster [36]. Both are expressed with a Hox-like pattern in mouse [21]: using a sensor reporter, in which a sequence complementary to the miRNA is inserted into the 3′-UTR of a reporter gene, McManus and collaborators found that miR-10 and miR-196 were highly expressed in the central and/or posterior part of the embryo but were not detected in the head and anterior trunk, suggesting that the miRNAs are regulated by the same mechanisms as the surrounding Hox genes. However, the expression pattern of Hox9, the gene closest to the miR-196 precursor, is not entirely superimposable on that of the miRNA, indicating that the mechanisms of regulation of the two Hox cluster components are not completely identical.

7.6

miR-196

MiR-196 precursors are located upstream of Hox9 genes in the A, B and C clusters (Fig. 7.1). MiR-196a miRNA is almost fully complementary to a sequence in the 3′UTR of Hox-B8, and miR-196a is able to direct the cleavage of Hox-B8 mRNA in transfected cells. In the embryo, Hox-B8 mRNA is highly expressed in the central part of the embryo and less strongly in the caudal trunk [8, 10], whereas miR196a is predominantly expressed in the most posterior region [21]. MiR-196 and Hox-B8 patterns of expression, thus, fit the general rule for Hox cluster order of expression, with the most 5′ sequences being expressed late and in the most posterior parts of the body. Little is known, however, about the molecular mechanism through which miR-196 miRNAs are activated and repressed in the embryo. Horsnstein et al. analyzed the function of miR-196 in limb buds, using limb buds that were cultured in vitro [14]. They demonstrated that miR-196 contributes, at specific stages of embryogenesis, to Hox-B8 down-regulation in the hind limb. In this study, HoxB8 was induced by retinoic acid, an important morphogen, in in vitro cultured forelimbs but not in hindlimbs under the same conditions. In the absence of Dicer, however, HoxB8 mRNA was also induced in the hindlimb, a phenotype that was corrected by ectopic expression of miR-196a. MiR-196 might contribute to “posterior prevalence”: by down-regulating the more anterior HoxB8 gene, miR-196 allows more posterior HOX proteins to control gene programs in the posterior areas; thus in the hindlimb, miR-196 controls the expression of an essential target of HoxB8, the transcription factor sonic hedgehog (shh).

7 Homeotic miRNAs: From Development to Pathologies 3'

Chr 6

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1 2 3 4 5 6 7 8 9 10 11 12 13

5' predicted targets validated targets

11

A

miR-196b

8

Chr 11 B

miR-196a1

miR-10a

Chr 15 C miR-196a2

Chr 2

10

D

miR-10b

miR-181 a, miR-181b

early (anterior)

late (posterior) Transcription

Chr 1

A

miR-181 a, miR-181b

Ubx

B

miR-10

miR-iab

Fig. 7.2 The mouse Hox cluster (A) and the drosophila Hox cluster (B); chr: chromosome; the position of miRNAs and of their targets are depicted in red; predicted targets are depicted in orange

The results of Hornstein et al., however, are in contradiction with a paper by Harfe et al., whose data suggest that Dicer is not required for proper shh expression in the limb buds [13]. Interestingly, the miR-196/Hox-B8 pathway is certainly very ancient, and a highly similar pathway also exists in drosophila (Fig. 7.2b), in which the miRNA iab-4 represses the Hox protein Ultrabithorax. The physiological function, however, is different, since the miRNA iab-4 controls the choice between wing and haltere (a balancing organ) in the Drosophila embryo [31].

7.7

MiR-10

Attention was drawn to MiR-10b with the discovery that miR-10b was overexpressed in metastatic breast cancer cells [20]. Ectopic expression of miR10b was sufficient to convert a non-metastatic breast cancer cell line to a metastatic one. Hox D-10 is a predicted target for miR-10b, and indeed in tissue culture cells, ectopic expression of miR-10b reduced the level of HoxD10. However, miR-10 targets during development have not been identified. If Hox-D10 is among the targets, then this particular miRNA/target system would not fit the posterior prevalence rule, since miR10b is located in a more anterior region as compared to HoxD10. Notably, in zebra fish, miR-10

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represses Hox B1 and Hox B2, more consistent with the posterior prevalence [33]. In mouse, ectopic expression of miR-10b was accompanied by increased RhoC, a protein of the Rho family that is required for cell migration/invasion. It is not clear that RhoC is also a target for miR-10 in the embryo. RhoC is required for tumor cell metastasis, but is fully dispensable for embryogenesis and development [12]. Also, in cancer cells, the expression of miR-10b was induced by a bHLH transcription factor, Twist. The extent to which this pathway of induction is not restricted to cancer cells but also operates during development is not clear. Twist had been previously linked to metastasis [32, 35]. However, and although Twist has an essential function during embryogenesis [28], Twist has not been linked to Hox gene control. Moreover, its pattern of expression during embryogenesis is strikingly different from that of Hox genes, Twist being expressed in specific tissues throughout the embryo [9]. Thus, it is most likely that miR-10b is not under the control of Twist during embryogenesis, and the mechanism through which miR-10b transcription is controlled remains to be discovered. MiR-10 is not only over-expressed in breast cancer, but has also been proven to be actively involved in the formation of metastases [20]: the ectopic expression of miR-10 converts a non-metastatic breast tumor cell line into a metastatic one. Thus, miR-10b is an interesting diagnostic (and prognostic) tool for breast cancer therapies. Moreover, miR-10b also potentially represents a target for anti-metastatic treatments. Indeed, highly specific and efficient loss-of-function assays for miRNAs are available [22, 25]. These assays are based on the use of antisense oligonucleotides, either RNA or DNA, which are chemically modified. In one of these approaches, the antisense can be a DNA oligonucleotide that includes a few Locked Nucleic Acid (LNA) nucleotides [19] (Fig. 7.3). The LNA antisense has a very high affinity for the microRNA [25], efficiently blocking the incorporation of the miRNA into the RISC complex and thereby repressing the miRNA function. This technique provides a means for miRNA inhibition in vitro and in vivo, and potentially represents a new therapeutic tool to fight various diseases. For example, if miR-10 is involved in human tumor metastasis formation as it is in mouse, then such a loss-of-function assay might be useful in new targeting therapies.

miRNA:miRNA* RISC miRNA:antisense*

A

B

Fig. 7.3 A loss-of-function assay for miRNAs; (a) structure of LNA (b) the LNA antisense replaces the strand complementary to the miRNA in the natural short double stranded RNA, the miRNA*, and inhibits miRNA incorporation into the RISC complex

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MiRNAs Encoded Outside of the Hox Cluster

Hox genes can also be controlled by miRNAs that are encoded outside of the Hox cluster. In particular, Hox-A11 is controlled by miR-181 [26]. The human and murine miR-181 family of miRNAs includes four isoforms, among which two are encoded as clusters on chromosomes 1 and 2 (Fig. 7.2). Both clusters are outside of the Hox gene cluster, even though one set of miRNA precursors is on the same chromosome as the Hox D subset. Hox A 11 is a strong inhibitor of terminal differentiation in muscle cells [34]. Mir-181a (but not b) represses HoxA11 in adult muscle precursor cells, thereby allowing terminal differentiation. The pattern of expression of miR-181 during embryogenesis is not known, and the relevance of this observation for embryogenesis remains to be elucidated.

7.8

Conclusion

At least three miRNAs are involved in Hox gene regulation, either during development or in adults. It is likely, however, that other miRNAs also participate in Hox gene control. Indeed, target prediction algorithms predict that most mammalian Hox genes are targets for miRNAs (see Fig. 7.2), with the exception of Hox C12 and Hox D12. The number of miRNAs that potentially control each of the Hox genes varies from 2 to 20 or more, depending on the locus. Most of these miRNAs are encoded outside of the Hox cluster. Not all predictions will turn out to be correct, but certainly some of them will, implying that more remains to be discovered in this area. Given their importance during mammalian development, it is likely that miRNAs are important players in some human pathologies. MiRNA implication in cancer is thoroughly documented, and miRNA can be tumor suppressors or oncogenes [11]. In particular, miR-10b, which is encoded inside of the Hox cluster, is a pro-metastatic miRNA and is a potentially important target in cancer therapy. It is likely that other miRNAs involved in development also function under pathological conditions and represent potential targets for future therapies. The antisense technology described here could thus be of prime importance in the fight against various diseases including cancer. Acknowledgements The authors’ experimental work has been supported by grants from the European Union’s 6th Framework Program (LSHB-CT-2004-005276 and LSHG-CT-2006037900), and from the ANR and from the ARC.

References 1. Bernstein, E., Kim, S.Y., Carmell, M.A., Murchison, E.P., Alcorn, H., Li, M.Z., Mills, A.A., Elledge, S.J., Anderson, K.V., and Hannon, G.J. (2003). Dicer is essential for mouse development. Nat Genet 35, 215–217.

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2. Brend, T., Gilthorpe, J., Summerbell, D., and Rigby, P.W. (2003). Multiple levels of transcriptional and post-transcriptional regulation are required to define the domain of Hoxb4 expression. Development 130, 2717–2728. 3. Cuellar, T.L., and McManus, M.T. (2005). MicroRNAs and endocrine biology. J Endocrinol 187, 327–332. 4. Cullen, B.R. (2004). Transcription and processing of human microRNA precursors. Mol Cell 16, 861–865. 5. Deschamps, J., van den Akker, E., Forlani, S., De Graaff, W., Oosterveen, T., Roelen, B., and Roelfsema, J. (1999). Initiation, establishment and maintenance of Hox gene expression patterns in the mouse. Int J Dev Biol 43, 635–650. 6. Duboule, D. (1991). Patterning in the vertebrate limb. Curr Opin Genet Dev 1, 211–216. 7. Filipowicz, W., Bhattacharyya, S.N., and Sonenberg, N. (2008). Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat Rev Genet 9, 102–114. 8. Forlani, S., Lawson, K.A., and Deschamps, J. (2003). Acquisition of Hox codes during gastrulation and axial elongation in the mouse embryo. Development 130, 3807–3819. 9. Fuchtbauer, E.M. (1995). Expression of M-twist during postimplantation development of the mouse. Dev Dyn 204, 316–322. 10. Fujimura, Y., Isono, K., Vidal, M., Endoh, M., Kajita, H., Mizutani-Koseki, Y., Takihara, Y., van Lohuizen, M., Otte, A., Jenuwein, T., et al. (2006). Distinct roles of Polycomb group gene products in transcriptionally repressed and active domains of Hoxb8. Development 133, 2371–2381. 11. Hagan, J.P., and Croce, C.M. (2007). MicroRNAs in carcinogenesis. Cytogen Genome Res 118, 252–259. 12. Hakem, A., Sanchez-Sweatman, O., You-Ten, A., Duncan, G., Wakeham, A., Khokha, R., and Mak, T.W. (2005). RhoC is dispensable for embryogenesis and tumor initiation but essential for metastasis. Genes Dev 19, 1974–1979. 13. Harfe, B.D., McManus, M.T., Mansfield, J.H., Hornstein, E., and Tabin, C.J. (2005). The RNaseIII enzyme Dicer is required for morphogenesis but not patterning of the vertebrate limb. Proc Natl Acad Sci USA 102, 10898–10903. 14. Hornstein, E., Mansfield, J.H., Yekta, S., Hu, J.K., Harfe, B.D., McManus, M.T., Baskerville, S., Bartel, D.P., and Tabin, C.J. (2005). The microRNA miR-196 acts upstream of Hoxb8 and shh in limb development. Nature 438, 671–674. 15. Hutvagner, G., and Simard, M.J. (2008). Argonaute proteins: key players in RNA silencing. Nat Rev Mol Cell Biol 9, 22–32. 16. Iimura, T., and Pourquie, O. (2007). Hox genes in time and space during vertebrate body formation. Dev Growth Differ 49, 265–275. 17. Jackson, R.J., and Standart, N. (2007). How do microRNAs regulate gene expression? Sci STKE 2007, re1. 18. Kanellopoulou, C., Muljo, S.A., Kung, A.L., Ganesan, S., Drapkin, R., Jenuwein, T., Livingston, D.M., and Rajewsky, K. (2005). Dicer-deficient mouse embryonic stem cells are defective in differentiation and centromeric silencing. Genes Dev 19, 489–501. 19. Koshkin, A.A., Nielsen, P., Meldgaard, M., Rajwanshi, V. K., Singh, S. K., and Wengel, J (1998). LNA (Locked Nucleic Acid): an RNA mimic forming exceedingly stable LNA:LNA duplexes. J Am Chem Soc 120, 13252–13260. 20. Ma, L., Teruya-Feldstein, J., and Weinberg, R.A. (2007). Tumour invasion and metastasis initiated by microRNA-10b in breast cancer. Nature 449, 682–688. 21. Mansfield, J.H., Harfe, B.D., Nissen, R., Obenauer, J., Srineel, J., Chaudhuri, A., FarzanKashani, R., Zuker, M., Pasquinelli, A.E., Ruvkun, G., et al. (2004). MicroRNA-responsive ‘sensor’ transgenes uncover Hox-like and other developmentally regulated patterns of vertebrate microRNA expression. Nat Genet 36, 1079–1083. 22. Meister, G., Landthaler, M., Dorsett, Y., and Tuschl, T. (2004). Sequence-specific inhibition of microRNA- and siRNA-induced RNA silencing. RNA 10, 544–550. 23. Moss, E.G., Lee, R.C., and Ambros, V. (1997). The cold shock domain protein LIN-28 controls developmental timing in C. elegans and is regulated by the lin-4 RNA. Cell 88, 637–646.

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24. Muljo, S.A., Ansel, K.M., Kanellopoulou, C., Livingston, D.M., Rao, A., and Rajewsky, K. (2005). Aberrant T cell differentiation in the absence of Dicer. J Exp Med 202, 261–269. 25. Naguibneva, I., Ameyar-Zazoua, M., Nonne, N., Polesskaya, A., Ait-Si-Ali, S., Groisman, R., Souidi, M., Pritchard, L.L., and Harel-Bellan, A. (2006a). An LNA-based loss-of-function assay for micro-RNAs. Biomed Pharmacother 60(9), 633–638. 26. Naguibneva, I., Ameyar-Zazoua, M., Polesskaya, A., Ait-Si-Ali, S., Groisman, R., Souidi, M., Cuvellier, S., and Harel-Bellan, A. (2006b). The microRNA miR-181 targets the homeobox protein Hox-A11 during mammalian myoblast differentiation. Nat Cell Biol 8, 278–284. 27. Nelson, C.E., Morgan, B.A., Burke, A.C., Laufer, E., DiMambro, E., Murtaugh, L.C., Gonzales, E., Tessarollo, L., Parada, L.F., and Tabin, C. (1996). Analysis of Hox gene expression in the chick limb bud. Development 122, 1449–1466. 28. O’Rourke, M.P., and Tam, P.P. (2002). Twist functions in mouse development. Int J Dev Biol 46, 401–413. 29. Oosterveen, T., Niederreither, K., Dolle, P., Chambon, P., Meijlink, F., and Deschamps, J. (2003). Retinoids regulate the anterior expression boundaries of 5′ Hoxb genes in posterior hindbrain. Embo J 22, 262–269. 30. Pearson, J.C., Lemons, D., and McGinnis, W. (2005). Modulating Hox gene functions during animal body patterning. Nat Rev Genet 6, 893–904. 31. Ronshaugen, M., Biemar, F., Piel, J., Levine, M., and Lai, E.C. (2005). The Drosophila microRNA iab-4 causes a dominant homeotic transformation of halteres to wings. Genes Dev 19, 2947–2952. 32. Thiery, J.P., and Morgan, M. (2004). Breast cancer progression with a Twist. Nat Med 10, 777–778. 33. Woltering, J.M., and Durston, A.J. (2008). MiR-10 Represses HoxB1a and HoxB3a in Zebrafish. PLoS ONE 3, e1396. 34. Yamamoto, M., and Kuroiwa, A. (2003). Hoxa-11 and Hoxa-13 are involved in repression of MyoD during limb muscle development. Dev Growth Differ 45, 485–498. 35. Yang, J., Mani, S.A., Donaher, J.L., Ramaswamy, S., Itzykson, R.A., Come, C., Savagner, P., Gitelman, I., Richardson, A., and Weinberg, R.A. (2004). Twist, a master regulator of morphogenesis, plays an essential role in tumor metastasis. Cell 117, 927–939. 36. Yekta, S., Shih, I.H., and Bartel, D.P. (2004). MicroRNA-directed cleavage of HOXB8 mRNA. Science 304, 594–596. 37. Zhao, Y., Ransom, J.F., Li, A., Vedantham, V., von Drehle, M., Muth, A.N., Tsuchihashi, T., McManus, M.T., Schwartz, R.J., and Srivastava, D. (2007). Dysregulation of cardiogenesis, cardiac conduction, and cell cycle in mice lacking miRNA-1–2. Cell 129, 303–317.

Chapter 8

MicroRNA in Muscle Development and Function Zhongliang Deng1,3 and Da-Zhi Wang1,2*

Abstract microRNAs (miRNAs) are a class of highly conserved small non-coding RNAs of ∼22-nucleotides that negatively regulate gene expression post-transcriptionally. The emerging field of miRNA biology has begun to unravel roles for these regulatory molecules in a range of biological functions, including cell proliferation, differentiation and development. The molecular events that regulate cardiac and skeletal muscle development, as well as in muscle-related disease processes have bee well-established at transcriptional level. In this chapter, we review the role of miRNAs in muscle biology. The expression of several miRNAs was found specifically in cardiac and skeletal muscles. Most importantly, genetic studies have demonstrated that miRNAs are required for muscle gene expression, muscle development and function. Furthermore, dysregulated miRNA expression has been correlated to certain muscle-related diseases, including cardiac hypertrophy, cardiac arrhythmias, and muscular dystrophy. Keywords microRNA, skeletal muscle, gene expression, cardiovascular disease

8.1

Introduction

microRNAs (miRNAs or miRs) are an increasingly important class of small noncoding RNAs that negatively regulate gene expression post-transcriptionally. Their discovery and subsequent analysis has produced another layer of complex mechanisms appearing to modulate protein dosages of key regulators in a variety of biological

1

Carolina Cardiovascular Biology Center

2

Department of Cell & Developmental Biology, University of North Carolina, Chapel Hill, NC 27599, USA 3

Department of Orthopaedic Surgery, The Second Affiliated Hospital, Chongqing University of Medical Sciences, Chongqing 400010, P.R. China * Corresponding author: Phone: 919-843-4590; Fax: 919-966-6012; E-mail: [email protected]

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processes. Recent studies have shown that muscle miRNAs regulate the expression of transcription factors and signaling mediators important for muscle biology, including such fundamental processes as the regulation of proliferation and differentiation during myogenesis. Aberrant miRNA expression has been observed during muscle diseases, including cardiac hypertrophy as well as in muscular dystrophy. Genetics studies demonstrate that some of these dysregulated miRNAs are sufficient to induce hypertrophy, while others are required for the process. Here, we review the wide range of emerging roles for miRNAs in muscle development and function (Table 8.1).

Table 8.1 Known miRNAs in muscle development and function Expression microRNA pattern miR-1

miR-21

miR-133

miR-181

miR-195 miR-206 miR-208 miR-214

Heart, skeletal muscle

Biological roles

Regulated targets

Apoptosis, cardiogen- Cdk9, Delta, esis, conduction, Fibronectin, GDF8, myogenesis, GJA1, Hand2, Irx5, skeletal muscle KCNJ2, HDAC4, hypertrophy HSP60, HSP70, KCNE1, nPTB, RasGAP, Rheb Heart, spleen, Apoptosis, cardiac PTEN, TPM1 small intestine, hypertrophy, colon tumorigenesis Heart, skeletal Apoptosis, conducCaspase-9, Cdc42, muscle tion, myogenesis, ERG, KCNQ1, skeletal muscle nPTB, RhoA, SRF, hypertrophy WHSC2 Brain, heart, lung, Myogenesis and Hox-A11 kidney, skeletal regeneration, muscle, bone hematopoiesis marrow, spleen, thymus Heart, lung, Cardiac hypertrophy None reported kidney, skin Skeletal muscle Myogenesis Cx43, GDF8, Fstl1, nPTB, Pola1, Utrn Heart Cardiac hypertrophy Thrap1 Somites Myogenesis Su(fu)

References [28–31, 52, 54, 58, 68, 80, 81]

[82, 83]

[28, 29, 54, 58, 81, 84]

[66, 67]

[38, 85] [32, 57, 61, 68, 81] [33] [64]

Cdc42, Cell division cycle 42; Cdk9, Cyclin-dependent kinase 9; ERG, Ether-a-go-go potassium channel; GDF8, myostatin; GJA1, Gap junction protein alpha 1; Hand2, Heart and neural crest derivatives expressed 2; HSP60, heat-shock protein 60; HSP70, heat-shock protein 70; HDAC4, Histone deacetylase 4; Irx5, iroquois homeobox protein; KCNE1, Potassium voltage-gated channel, Isk-related family, member 1; KCNJ2, Potassium inwardly-rectifying channel, subfamily J, member 2; KCNQ1, Potassium voltage-gated channel, KQT-like subfamily, member 1; nPTB, polypyrimidine tract-binding protein 2; PTEN, phosphatase and tensin homolog; RasGAP, Ras GTPase-activating protein; Rheb, Ras homolog enriched in brain; RhoA, Ras homolog A; SRF, Serum response factor; Su(fu), suppressor of fused; Thrap1, thyroid hormone receptor associated protein 1; TPM1, tropomyosin 1; WHSC2, Wolf-Hirschhorn syndrome candidate 2

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Mammalian Muscle Development and Regulation of Muscle Gene Expression

There are three major muscle types: cardiac, skeletal, and smooth. All of them are derived from the embryonic mesoderm layer during early embryogenesis in vertebrates. The heart is the first functioning organ to form during mammalian development and cardiac precursor cells come from a population of cells in the anterior lateral plate mesoderm in early embryos [1]. Skeletal muscle arises from paraxial mesoderm that gives rise to the somites along the anteroposterior axis of the embryo [2]. Somites become compartmentalized into the myotome, sclerotome, and dermatome, which give rise to skeletal muscle, axial skeleton, and dermis, respectively [2, 3]. In contrast to cardiac and skeletal muscle cells, which exit cell cycle and undergo terminal differentiation, smooth muscle cells (SMCs) are highly plastic and can modulate their phenotypes between proliferative and differentiated states in response to extracellular cues [4, 5]. Much of our current understanding of muscle gene expression regulation during development is at the level of transcription. The embryologic events associated with cardiac morphogenesis and the underlying molecular mechanisms that control this process were well investigated at the transcriptional level [6, 7]. Several such transcription factors have been implicated in activation of cardiac muscle gene expression during cardiomyocyte differentiation. NKX2.5, a homeobox protein, is expressed specifically in the heart and has been shown to bind a regulatory element in several cardiac gene control regions [8]. MEF2C, a member of myocyte enhance factor-2 (MEF2) family of MADS-box transcription factors, binds to a conserved A/T-rich DNA sequence in the control regions of the majority of cardiac, skeletal and smooth muscle genes [9, 10]. GATA4, a GATA family zinc finger protein, is expressed in the cardiac lineage throughout embryonic development and in adulthood [11]. GATA4 can directly bind to the DNA sequence element (A/T)GATA(A/G), which is present in the regulatory region of numerous genes, including cardiac-specific atrial natriuretic factor (ANF) and cardiac α-actin [12]. SRF is a MADS-box transcription factor that regulates target genes by binding the DNA consensus sequence CC(A/T)6GG, known as a CArG box, or serum response element (SRE). CArG boxes have been found in many muscle-specific genes, such as cardiac α-actin [13]. The important roles of SRF in cell proliferation and muscle cell differentiation have been documented by gain- and loss-of-function experiments in cultured cells. Recently, the in vivo function of SRF during muscle development was clearly documented when SRF was conditionally knocked out in cardiac and skeletal muscle lineages [14–16]. One of the molecular mechanisms for SRF function is that SRF can associate with tissue-specific transcription factors, such as myocardin, to activate muscle gene expression [17, 18]. The molecular mechanisms that control skeletal muscle development are starting to become understood. The MyoD family of myogenic bHLH transcription factors, including MyoD, myogenin, Myf5 and MRF4, function as master regulators that control the specification and differentiation of skeletal muscle cells [19].

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The Myocyte Enhancer Factor 2 (MEF2) family of transcription factors and serum response factor (SRF) are also suggested to regulate myogenesis [20]. MEF2 and MyoD were shown to synergistically transactivate muscle gene expression through direct protein-protein interaction [21]. It has become clear that exploring how muscle is formed and muscle gene expression is regulated is the key to understanding muscle-related human diseases.

8.3

miRNA Biogenesis and Their Expression in Animals

miRNAs arise endogenously from independent transcriptional units or from within the introns of messenger RNA (mRNA) transcripts [22]. It is now known that miRNA genes are initially transcribed by RNA polymerase II, the same enzyme used for the transcription of most protein-encoding genes. miRNAs are initially part of immature primary transcripts that undergo extensive posttranscriptional processing to yield mature miRNAs, whose lengths are approximately 18 to 24 nucleotides. The lengths of the primary transcripts range from several hundred to several thousand nucleotides and may harbor a single miRNA or sometimes several (miRNA polycistrons) [23]. Mature miRNAs become part of the RNA-induced silencing complex (RISC) that facilitates miRNA-mediated regulation of gene expression through complementary base-pairing between a miRNA and sequence(s) within the 3′ untranslated region (UTR) of targeted mRNAs [24, 25]. The majority of animal miRNAs base pair imperfectly to their targeted mRNAs, which generally results in suppression of translation [22]. Interestingly, miRNAs have also been shown to affect stability of targeted mRNAs and mediate their degradation [26]. To date, more than 600 human miRNA genes have been identified, of which many are evolutionarily conserved, present in worm, fly, fish, mouse, and human [27]. Many miRNA genes cluster into families based on their sequence similarity, with special weight given to the second through eighth 5′ nucleotides termed the ‘seed region.’ The base pairing between the seed region of a miRNA and its mRNA target site is generally perfectly complementary, thus miRNAs with identical seed regions may target the same sets of genes. For example, miR-1, a cardiac and skeletal muscle miRNA, and miR-206, found only in skeletal muscle, both belong to the same miRNA family, a potential caveat for their genetic analysis since they have overlapping expression patterns and may regulate the same mRNA targets. Whereas the majority of miRNAs are ubiquitously expressed, some miRNAs are expressed in a spatial- and/or temporal-restricted manner. For example, miR-122 is specifically expressed in the liver and miR-124 is enriched in brain. During animal development, more miRNAs are expressed in late than early developmental stages when most of organs/tissues are formed. Interestingly, the expression of several miRNAs is limited to muscle lineages. The expression of miR-1 and miR-133 are only detected in cardiac and skeletal muscle. Whereas miR-206 is restricted to skeletal muscle, miR-208 expression is only detected in cardiac muscle. Currently, how the expression of most miRNAs is regulated remains elusive.

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133

Regulation of miRNA Expression in Cardiac and Skeletal Muscle Tissues

The expression of muscle-specific miRNAs miR-1, miR-133, miR-206, and miR208, appears largely regulated by well-established and evolutionarily conserved muscle transcriptional networks involving SRF, MyoD, Twist, MEF2, and myocardin [28–31]. For example, miR-1 was highly conserved during evolution and, in addition to mouse and human, it is found in the genomes of organisms as diverse as worm, fly, zebrafish, and chicken. The pathways controlling miR-1 expression also appear highly conserved: Drosophila miR-1 expression in the presumptive and early mesoderm occurs downstream of Twist and MEF2, two transcription factors that are major regulators of mammalian muscle development [30, 31]. In vertebrates, there are two polycistronic genes that encode miR-1 along with miR-133 [28]. Accordingly, the expression of miR-1 and miR-133 mirror one another in skeletal and cardiac muscle, where they are solely expressed. Their muscle-specific expression pattern is explained by promoter analyses demonstrating that both miR1/miR-133 loci have upstream enhancers with SRF binding sites, and that myocardin activity increases the expression of those promoters in the heart, whereas as their skeletal muscle expression is controlled by MyoD [28, 30]. Similarly, MyoD, a transcription factor sufficient to activate the program of skeletal muscle differentiation, stimulates the skeletal muscle-specific expression of miR-206 [32]. In contrast to miR-1, miR-133, and miR-206, which are expressed as independent transcriptional units, miR-208 is encoded by an intron of its host gene alpha myosin heavy chain (aMHC) [33]. More than 127 human miRNAs have been identified within the introns of protein-coding genes, and findings support the idea that these intronic miRNAs are generally co-expressed with their host genes [23, 33– 35]. In agreement, both miR-208 and aMHC are heart-specific and concurrently expressed during development, suggesting that their expression is controlled by a common regulatory element. The promoter region of the aMHC gene contains several binding elements important for muscle-specific gene expression, such Nkx2.5, GATA4, MEF2 and SRF sites, and thyroid hormone signaling is also known to play an important role in controlling aMHC expression. Collectively, these studies indicate that muscle miRNA expression is under tight spatial and temporal regulation by transcriptional networks important for muscle gene expression.

8.5

Dysregulation of miRNA Expression in Pathological Cardiac and Skeletal Muscle Condition

In addition to their normal expression during development, several reports, using miRNA microarrays, have found the global miRNA expression profile regulated in models of physiological and pathological cardiac hypertrophy [36–38]. Interestingly, several groups document that expression of only a relatively small fraction of

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miRNAs were changed in response to cardiac hypertrophy [37, 38], while another group reports expression level changes for more than half of the miRNAs in the heart [36]. Furthermore, dysregulated miRNA expression has been shown in human patients with failing hearts [38–41]. In addition, it has been reported that miRNA expression is altered in patients with primary muscular disorders [42]. Together, those studies strongly suggest that miRNAs may contribute to cardiovascular and other muscle-related disease by mediating pathological changes in gene expression.

8.6

Requirement of miRNAs for Proper Animal Development

One approach to determine the potential function of miRNAs in animal development has been to create mutations in Dicer, an upstream enzyme required for the processing miRNAs to their mature, active form. Vertebrates have only a single copy of Dicer, which is likely required to fully process all vertebrate miRNAs [43, 44]. In mice, ablation of Dicer function resulted in lethality by embryonic day 7.5 (E7.5). The Dicer null mice did not express primitive streak marker T (brachyury), indicating that development was likely arrested during gastrulation [44, 45]. Results from Dicer conditional knockout mouse studies further support the view that miRNAs are critical for normal development [46, 47]. Completely blocking miRNA formation in zebrafish by making maternal-zygotic Dicer mutants revealed that loss of miRNAs did not affect axis formation or patterning of many cell types in the embryos [48]. However, morphogenesis during gastrulation, brain formation, somitogenesis, and heart development all proved abnormal, and resulted in lethality [48]. Circumventing the early lethality of Dicer deletion in mice, conditional Dicer knockout studies using the Cre-loxP system have demonstrated that Dicer, therefore miRNAs, is required for the morphogenesis of the limb [46], skin [49], lung [50], and heart [51]. Although these Dicer deletion studies do not provide insight into the precise functions of specific miRNAs, collectively, the genetic analyses of Dicer function suggest that mature miRNAs are required for proper animal development.

8.7

miR-1 and miR-133 Are Essential for Muscle Development and Function

Recent genetic studies of miR-1 in Drosophila and mouse provide convincing evidences about the function of this miRNA in muscle development [31, 51, 52]. Genetic deletion revealed Drosophila miR-1 as an essential gene for viability [31, 52]. Homozygous miR-1 mutant larvae exhibit decreased locomotion that ultimately progressed to death accompanied by severe gross disruption of the larval musculature [31], supporting the view that miR-1 plays a critical role in muscle development

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and function. A subset of severely affected miR-1 null embryos exhibited an enlarged pool of cardiac progenitors, suggesting that miR-1 may modulate differentiation of heart [52]. The miR-1 loss-of-function phenotype could be partially rescued by re-introduction of miR-1 into mutant embryos, strongly supporting a muscle-specific role for miR-1 [31, 52]. Consistent with the role for miR-1 in muscle differentiation, overexpression of miR-1 in the developing mouse heart resulted in reduced ventricular myocyte expansion and decreased the number of proliferating myocytes [30]. This phenotype was explained in part by the presence of a miR-1 target site in the 3' UTR of the Hand2 gene, an important cardiac transcription factor [30], whose genetic ablation in the mouse produced a similar failure in ventricular myocyte expansion [53]. Similarly, introduction of miR-1 into Xenopus embryos interfered with cardiac and skeletal muscle development [28]. In vertebrates, the genes miR-1-1 and miR-1-2 both produce the mature miR-1 product and appear to have largely overlapping expression patterns [28, 51]. Nevertheless, genetic deletion of miR-1-2 in mouse caused half of miR-1-2 null animals die by weaning age and suffer defects indicative of abnormal cardiac morphogenesis, including incomplete ventricular septation and pericardial edema [51]. This distinct phenotype suggests that miR-1-2 plays non-redundant roles with miR-1-1 in the heart despite their overlapping expression patterns and/or that a particularly fine balance of miR-1 levels is required for proper cardiac development. Interestingly, miR-1-2 deletion did not appear to affect skeletal muscle development, which may reflect a difference in the gene affected by miR-1 in cardiac versus skeletal muscle. Most recently, miR-1 and miR-133 were shown to play regulatory a role in apoptosis in rat cardiomyocytes: miR-1 mediated a pro-apoptotic effect, while the effect of miR-133 was anti-apoptotic [54]. Thus, in addition to their role in regulating muscle cell proliferation and differentiation, miR-1 and miR-133 also seem to play opposing roles in regulating muscle cell apoptosis. The opposing effects of miR-1 and miR-133 during apoptosis are likely explained by which genes are targeted: miR-1 reduced protein levels of HSP60 and HSP70, while miR-133 repressed caspase-9 expression [54]. Though a clear picture of which genes are regulated by miRNAs is desperately needed to fully understand the roles of miRNAs in muscle biology, the main theme that has emerged thus far is that miRNAs indeed participate in regulatory networks to modulate muscle gene expression, muscle cell proliferation, differentiation, and apoptosis [28, 54, 55].

8.8

Role of Other miRNAs in Skeletal Muscle Proliferation, Differentiation and Development

Skeletal muscle cells arise from embryonic mesoderm during embryonic development, where they exist as proliferating myoblasts or terminally differentiated myotubes that have exited the cell cycle. Multiple regulatory factors, including

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those of transcription factors and cellular signaling molecules play a critical role in the control of muscle proliferation and differentiation [2]. Muscle proliferation and differentiation process can be faithfully mimicked in vitro in tissue-cultured cells. The C2C12 myoblast cell line will maintain an undifferentiated state and continue to proliferate when cultured in growth medium, where serum is provided. However, they rapidly differentiate into large multinucleated myotubes that express musclespecific marker proteins when they are switched to differentiation medium, in which serum is removed [56]. Interestingly, the expression of miR-1, miR-133 and miR-206 is significantly up-regulated when C2C12 myoblasts were induced to differentiate into myotubes [28, 57]; therefore the C2C12 cell line offers an excellent tool to study the biological function and molecular mechanism of miRNAs in regulating muscle development. Using the C2C12 model system, overexpression and knockdown experiments have been applied to study the function of those muscle miRNAs [28, 57]. While miR-1 and miR-206 enhanced myogenesis, overexpression of miR-133 repressed myoblast differentiation and promoted myoblast proliferation. Conversely, inhibition of endogenous miR-1, miR-133, or miR-206 led to opposite effects on skeletal muscle proliferation and differentiation. In further support of those in vitro results, injection of Xenopus embryos with miR-1 or miR-133 led to developmental defects: once again, miR-1 enhances muscle differentiation and inhibits cell proliferation, whereas introduction of miR-133 induces cell proliferation [28]. It is interesting to note that miR-1/-206 and miR-133 have opposing effects although miR-1 and miR-133 derive from the same miRNA polycistron and are transcribed together, which further support the view that miRNAs may play an important role in tipping the balance between cell proliferation and differentiation. Of further note, the expression levels of miR-1 and miR-133 were decreased in a functional model of skeletal muscle hypertrophy in the mouse [58]. Such altered expression of miR-1 and miR-133 suggests their involvement in the adaptive response to skeletal muscle overload. Among the experimentally verified targets for miR-1, histone deacetylase 4 (HDAC4) has been shown to inhibit muscle differentiation and skeletal muscle gene expression, mainly by repressing MEF2C, an essential muscle-related transcription factor [59, 60]. By contrast, miR-133 enhances myoblast proliferation, at least in part, by reducing protein levels of serum response factor (SRF), a critical factor for muscle proliferation and differentiation in vitro and in vivo [4]. Similar to miR-1, miR-206 has also been shown to promote myoblast differentiation [57, 61]. Importantly, gap junction protein connexin43 (Cx43) and the p180 subunit (Pola1) of DNA polymerase alpha have been identified as regulatory targets of miR-206 in those studies. Although Cx43 is required for the initial phase of myogenesis, it is rapidly downregulated post-transcriptionally after the induction of differentiation [62], thus miR-206 is suggested to decrease communication between developing muscle fibers by decreasing Cx43 expression [61]. Downregulation of Pola1 by miR-206 during early differentiation reduces DNA synthesis and contributes to the suppression of cell proliferation during myotube formation [57]. miR-206 is also suggested to mediate MyoD-dependent inhibition of follistatin-like 1 (Fstl1) and Utrophin (Utrn) genes in myoblasts [32]. In this case, MyoD activates the

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expression of miR-206, which in turn represses Fstl1 and Utrn gene expression post-transcriptionally. This study could presumably explain some of the previous observations in which MyoD, known as a transcriptional activator, repressed Fstl1 and Utrn gene expression. In support of a role for miR-206 in muscle pathophysiology, the expression level of miR-206 was elevated in the diaphragm muscle of mdx mice, a model of muscular dystrophy [63]. While Utrn expression was repressed by miR-206 during myoblast differentiation [32], its expression was upregulated in mdx diaphragm muscle [63]. This result is seemingly inconsistent with the increase of miR-206 expression found in mdx diaphragm muscle, however this phenomenon might reflect decreased efficiency of miRNA-mediated translational repression during a diseased state. miR-214 is expressed in skeletal muscle cell progenitors during zebrafish development and was shown to specify muscle cell type during somitogenesis by modulating the response of muscle progenitors to Hedgehog signaling [64]. Blocking miR-214 activity by injecting chemically-modified antisense oligonucleotides into zebrafish embryos decreased in the number of slow-muscle cell types present in the developing somites and distinctly changed the gross morphology of the somites in manner previously associated with attenuated Hedgehog signaling. This phenotype was attributed to relief of miR-214-mediated inhibition of suppressor of fused (su(fu) ) expression [64], a fine-tuner of Hedgehog signaling essential for proper specification of muscle cell types during somitogenesis [65]. It will be interesting to test whether miR-214 plays a similar role in mammalian skeletal muscle development. Collectively, these studies indicate that miRNAs function as regulators of gene expression important for myoblast proliferation and differentiation and may play decisive roles in specifying cell types during development. In contrast to other muscle miRNAs discussed, which are specifically expressed in a tissue-restricted manner, miR-181 is broadly expressed. Interestingly, the expression of miR-181 was increased in the regenerating muscle from an in vivo mouse model of muscle injury [66]. Further analysis using the C2C12 cell line demonstrated that miR-181 depletion reduced MyoD expression and inhibited myoblast differentiation. One of the genes targeted by miR-181 is homeobox protein Hox-A11, which in turn represses MyoD expression. The proposed mechanism underlying miR-181 function is that miR-181 becomes up-regulated upon differentiation and targets a repressor (Hox-A11) of the differentiation process to allow new muscle growth. This study suggests that miRNAs can play roles in establishing a differentiated phenotype and alludes to the potential role of miRNAs in skeletal muscle regeneration. In addition to myogenesis, miR-181 was shown to modulate hematopoietic lineage differentiation in another study [67], which suggests that individual miRNAs may play very diverse biological roles depending upon their cellular context. Intriguingly, a genetic link has recently connected miRNA function to muscular hypertrophy. In a study to identify the quantitative trait locus underlying the exceptional muscularity of Texel sheep, the quantitative trait locus responsible was finemapped to an interval on chromosome 2 containing the myostatin gene [68]. However no polymorphisms were detected in the open reading frame of myostatin,

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but surprisingly, a G to A transition in the 3′ UTR of the myostatin gene created a target site for miR-1 and miR-206. Both miR-1 and miR-206 are strongly expressed in muscle tissues, suggesting that a gain-of-function miRNA target site created by this polymorphism negatively regulates the expression of the Texel myostatin gene. Indeed, myostatin expression/translation was dramatically repressed in Texel sheep. Further supporting the involvement of miRNAs, the 3′ UTR containing the polymorphism conferred repression to a reporter gene in vitro when miR-1 or miR-206 was co-expressed. Since loss of myostatin in mice, cattle, and human leads to muscle doubling, decreased myostatin expression by miRNAs explained the molecular mechanism underlying the muscle hypertrophy in Texel sheep. The discovery that a mutation in the non-coding region of an important gene created a miRNA target site underscores that importance of miRNAs in diverse biological processes and disease status.

8.9

miRNAs Modulate Cardiac Hypertrophy, Heart Failure, Muscular Dystrophy and Other Cardiac- and Skeletal- Muscle-Related Human Disorders

Cardiac myocytes proliferate rapidly during embryogenesis, but adult cardiac myocytes lose their proliferative capacity and respond to mechanical and pathological stimuli by hypertrophic growth [69]. Hypertrophic growth helps to sustain cardiac output in the face of such stress and is defined by an increase in myocyte size and/or myofibrillar volume without a change in myocyte number. Cardiac hypertrophy is also accompanied by re-activation of fetal cardiac genes normally expressed in the heart before birth. The reactivation of cardiac fetal genes in post-natal cardiomyocytes suggests the molecular events that control cardiac gene expression during development are redeployed to regulate hypertrophic cardiac growth or heart regeneration [70]. Although cardiac hypertrophy induced by pathological stimuli is an adaptive mechanism that is beneficial in the short term, prolonged hypertrophy has adverse consequences associated with heart failure and sudden death. As such, much effort for understanding the complex genetic pathways required for myocardial hypertrophy has been made with the ultimate goal of improving heart patient prognosis. Recent studies have found miRNA expression profiles changes during cardiac hypertrophy and that specific miRNAs are able to modulate the cellular response to cardiac stress. Similarly, mature skeletal muscle cells (myotubes) are terminal differentiated, postmitotic cells which lose their potential to proliferate or regenerate [2]. Loss of skeletal muscle tissue regenerative capacity is generally acknowledged to be the underlying deficit in severe examples of muscle diseases such as Muscular Dystrophies, which include a diverse group of genetically heterogeneous disorders characterized by progressive muscle weakness and wasting that leads to severe disability and often premature death [71]. Several forms of muscular dystrophy are due to abnormalities of membrane proteins and protein complexes, whereas others, such as those due to dystrophin mutations, are due to abnormalities of protein

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complexes that are postulated to transduce signals from the extracellular matrix into the cell. However, the normal cellular mechanisms regulating cell survival that are disrupted in these diseases are not well understood. Consistent with the observation that miRNA expression is dynamically regulated in physiologically- and/or pathologically-induced cardiac hypertrophy, functional analyses using both gain- and loss-of-function approaches have established a correlation between miRNAs and cardiac hypertrophy [33, 36–38, 72, 73]. miR-1 and miR-133 are both down-regulated during cardiac hypertrophy and are proposed to be necessary for the expression of targeted growth-related genes and induction of hypertrophic growth [72, 73]. In support, ectopic expression of miR-1 or miR-133 inhibited target gene expression and the hypertrophic growth response in a tissue-culture model of cardiac hypertrophy [72, 73]. Conversely, blocking endogenous miR-133 function in isolated cardiomyocytes augmented agonist-induced hypertrophy [72]. Furthermore, prolonged inhibition of miR-133 in vivo using chemically-modified oligonucleotides antisense to miR-133 caused a marked hypertrophic response [72]. It should be pointed out that while the expression of miR-1 appears dysregulated in cardiac hypertrophy [73], there is not yet direct genetic evidence supporting a role for this miRNA in the regulation of hypertrophy. Instead, miR-1 was found to have arrhythmogenic potential when overexpressed in adult rat hearts [39], suggesting that miR-1 may play an essential role in cardiac electrophysiology, in addition to its role in heart development. Among the miRNAs with their expression altered in hypertrophy, miR-195 is up-regulated during cardiac hypertrophy and was found sufficient to induce hypertrophic growth in cultured cardiomyocytes as well as in transgenic mice [38]. In contrast, transgenic mice over-expressing miR-214, a miRNA also up-regulated during hypertrophy and important for modulating Hedgehog signaling during myogenesis, caused no detectable phenotypic effect in the heart [38]. Those studies indicate that some miRNAs, but not others, are sufficient to induce cardiac hypertrophy. It will be interesting to investigate whether those miRNAs are necessary for the hypertrophic response using a loss-of-function approach. In addition, how those miRNAs integrate into relevant genetic pathways to modulate the hypertrophic response warrants further investigation. Although genetic ablation of miR-208 did not identify a critical role in the developing mouse, a striking postnatal role for miR-208 was revealed [33]. Loss of miR-208 protects mice against cardiac hypertrophy and up-regulation of b-MHC induced by hyperthyroidism, activated calcineuron signaling and cardiac pressureoverload induced stress [33]. Those results suggest that the genetic pathways coordinating cardiac hypertrophy share a common component regulated by miR-208. One of such candidate is Thyroid hormone receptor associated protein 1 (Thrap1). Thrap1 is a co-factor of the thyroid hormone nuclear receptor that can positively and negatively influence the transcription of its regulatory target genes. Expression of Thrap1 mRNA is targeted by miR-208 at its 3′ UTR, therefore Thrap1 protein levels are elevated in miR-208 mutant hearts [33]. Those studies suggest that miR-208 may function to modulate cardiac hypertrophy, at least in part, by regulating the expression of a thyroid hormone signaling pathway component.

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miR-21, a miRNA implicated in tumor-related cell growth and apoptosis [74–76], is up-regulated in response to agonist-induced cardiac hypertrophy in cell culture experiments and in pressure-overload induced hypertrophy in vivo [36–38, 73]. Inhibition of endogenous miR-21 was found sufficient to induce hypertrophic growth in isolated rat cardiomyocytes [37], however another study reports that inhibition of miR-21 in an agonist-induced model of hypertrophy attenuated global protein synthesis and cell growth [36]. Interestingly, other reports on miR-21 function also appear contradictory: while one study documented that miR-21 inhibition provoked cell growth in HeLa cells [75], others showed that miR-21 inhibition led to activation of apoptosis and decreased cell proliferation [74, 76]. Clearly, further analysis of the molecular pathways modulated by miR-21 in different biological systems is needed to better understand the biological function of this miRNA. Collectively, these studies identify miR-1, miR-21, miR-133, miR-195, and miR-208 as a class of novel important regulators of cardiac hypertrophy. In addition, it is speculated that the identification of the hypertrophic miRNA expression signature will unveil many hitherto unrecognized players involved in cardiac hypertrophy, and those candidates are awaiting closer examination. Given the complexity of the cardiac remodeling occurring during hypertrophy, the identification of specific regulatory mRNA targets for those miRNAs involved in the hypertrophic response will provide more insight into the molecular mechanisms underlying this disease process.

8.10

Build Strong Muscle with miRNAs, Tiny Building Blocks?

The budding miRNA field has expanded our understanding of gene expression by adding a novel regulatory mechanism at the post-transcriptional level. With more than one-third of human protein-coding genes predicted as subject to miRNA regulation [77], there is great potential for miRNA involvement in many aspects of muscle biology. Although much progress has been made towards establishing miRNAs as important regulators in muscle biology, few target genes have been consummately verified relative to the hundreds of predicted target genes. In addition, the role for miRNAs in smooth muscle biology has not yet been carefully addressed. Smooth muscle cells lining the arterial walls are associated with numerous cardiovascular diseases and the mechanisms by which smooth muscle cells proliferate, differentiate, as well as dedifferentiate and reenter the cell cycle, are not fully understood. Given that miRNAs were recently found aberrantly expressed in injured vascular walls [78], it is of great interest to know what processes those miRNAs might be regulating. Beyond identifying targeted genes, fundamental questions remain about the activities of miRNAs in the cell: miRNAs are generally regarded as repressors of translation normally located in the cytoplasm, however miR-206 was found within the nucleoli of skeletal muscle myoblasts and myotubes [79]. What function(s) might miR-206 or other miRNAs be carrying out in the

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nucleolus? As the research in this field progresses, it will be interesting to see how many different ways and to what extent miRNAs are integrated into muscle biology. Acknowledgements We are grateful to Tom Callis for his stimulating discussion and critical reading of the manuscript. Research in the Wang lab is supported by the March of Dimes, National Institute of Health and Muscular Dystrophy Association of American. Dr. Wang is an Established Investigator of American Heart Association.

References 1. Srivastava, D., Making or breaking the heart: from lineage determination to morphogenesis. Cell, 2006. 126(6): pp. 1037–1048. 2. Buckingham, M., Myogenic progenitor cells and skeletal myogenesis in vertebrates. Curr Opin Genet Dev, 2006. 16(5): pp. 525–532. 3. Venuti, J.M. and P. Cserjesi, Molecular embryology of skeletal myogenesis. Curr Top Dev Biol, 1996. 34: pp. 169–206. 4. Miano, J.M., Serum response factor: toggling between disparate programs of gene expression. J Mol Cell Cardiol, 2003. 35(6): pp. 577–593. 5. Owens, G.K., M.S. Kumar, and B.R. Wamhoff, Molecular regulation of vascular smooth muscle cell differentiation in development and disease. Physiol Rev, 2004. 84(3): pp. 767–801. 6. Olson, E.N., A decade of discoveries in cardiac biology. Nat Med, 2004. 10(5): pp. 467–474. 7. Olson, E.N., Gene regulatory networks in the evolution and development of the heart. Science, 2006. 313(5795): pp. 1922–1927. 8. Harvey, R.P., et al., Homeodomain factor Nkx2–5 in heart development and disease. Cold Spring Harb Symp Quant Biol, 2002. 67: pp. 107–114. 9. Black, B.L. and E.N. Olson, Transcriptional control of muscle development by myocyte enhancer factor-2 (MEF2) proteins. Annu Rev Cell Dev Biol, 1998. 14: pp. 167–196. 10. McKinsey, T.A., C.L. Zhang, and E.N. Olson, MEF2: a calcium-dependent regulator of cell division, differentiation and death. Trends Biochem Sci, 2002. 27(1): pp. 40–47. 11. Holtzinger, A. and T. Evans, Gata4 regulates the formation of multiple organs. Development, 2005. 132(17): pp. 4005–4014. 12. Bisping, E., et al., Gata4 is required for maintenance of postnatal cardiac function and protection from pressure overload-induced heart failure. Proc Natl Acad Sci USA, 2006. 103(39): pp. 14471–14476. 13. Wang, D., et al., Regulation of cardiac growth and development by SRF and its cofactors. Cold Spring Harb Symp Quant Biol, 2002. 67: pp. 97–105. 14. Miano, J.M., et al., Restricted inactivation of serum response factor to the cardiovascular system. Proc Natl Acad Sci USA, 2004. 101(49): pp. 17132–17137. 15. Li, S., et al., Requirement for serum response factor for skeletal muscle growth and maturation revealed by tissue-specific gene deletion in mice. Proc Natl Acad Sci USA, 2005. 102(4): pp. 1082–1087. 16. Parlakian, A., et al., Targeted inactivation of serum response factor in the developing heart results in myocardial defects and embryonic lethality. Mol Cell Biol, 2004. 24(12): pp. 5281–5289. 17. Wang, D., et al., Activation of cardiac gene expression by myocardin, a transcriptional cofactor for serum response factor. Cell, 2001. 105(7): pp. 851–862. 18. Wang, Z., et al., Myocardin and ternary complex factors compete for SRF to control smooth muscle gene expression. Nature, 2004. 428(6979): pp. 185–189. 19. Berkes, C.A. and S.J. Tapscott, MyoD and the transcriptional control of myogenesis. Semin Cell Dev Biol, 2005. 16(4–5): pp. 585–595.

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20. Bassel-Duby, R. and E.N. Olson, Signaling pathways in skeletal muscle remodeling. Annu Rev Biochem, 2006. 75: pp. 19–37. 21. Molkentin, J.D., et al., Cooperative activation of muscle gene expression by MEF2 and myogenic bHLH proteins. Cell, 1995. 83(7): pp. 1125–1136. 22. Bartel, D.P., MicroRNAs: genomics, biogenesis, mechanism, and function. Cell, 2004. 116(2): pp. 281–297. 23. Griffiths-Jones, S., et al., miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res, 2006. 34(Database issue): pp. D140–D144. 24. Doench, J.G. and P.A. Sharp, Specificity of microRNA target selection in translational repression. Genes Dev, 2004. 18(5): pp. 504–511. 25. Pillai, R.S., C.G. Artus, and W. Filipowicz, Tethering of human ago proteins to mRNA mimics the miRNA-mediated repression of protein synthesis. RNA, 2004. 10(10): pp. 1518–1525. 26. Bagga, S., et al., Regulation by let-7 and lin-4 miRNAs results in target mRNA degradation. Cell, 2005. 122(4): pp. 553–563. 27. Griffiths-Jones, S., The microRNA registry. Nucleic Acids Res, 2004. 32(Database issue): pp. D109–D111. 28. Chen, J.F., et al., The role of microRNA-1 and microRNA-133 in skeletal muscle proliferation and differentiation. Nat Genet, 2006. 38(2): pp. 228–233. 29. Rao, P.K., et al., Myogenic factors that regulate expression of muscle-specific microRNAs. Proc Natl Acad Sci USA, 2006. 103(23): pp. 8721–8726. 30. Zhao, Y., E. Samal, and D. Srivastava, Serum response factor regulates a muscle-specific microRNA that targets Hand2 during cardiogenesis. Nature, 2005. 436(7048): pp. 214–220. 31. Sokol, N.S. and V. Ambros, Mesodermally expressed Drosophila microRNA-1 is regulated by twist and is required in muscles during larval growth. Genes Dev, 2005. 19(19): pp. 2343–2354. 32. Rosenberg, M.I., et al., MyoD inhibits Fstl1 and Utrn expression by inducing transcription of miR-206. J Cell Biol, 2006. 175(1): pp. 77–85. 33. van Rooij, E., et al., Control of stress-dependent cardiac growth and gene expression by a microRNA. Science, 2007. 316(5824): pp. 575–579. 34. Baskerville, S. and D.P. Bartel, Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes. RNA, 2005. 11(3): pp. 241–247. 35. Kim, Y.K. and V.N. Kim, Processing of intronic microRNAs. Embo J, 2007. 26(3): pp. 775–783. 36. Cheng, Y., et al., MicroRNAs are aberrantly expressed in hypertrophic heart: do they play a role in cardiac hypertrophy? Am J Pathol, 2007. 170(6): pp. 1831–1840. 37. Tatsuguchi, M., et al., Expression of microRNAs is dynamically regulated during cardiomyocyte hypertrophy. J Mol Cell Cardiol, 2007. 42(6): pp. 1137–1141. 38. van Rooij, E., et al., A signature pattern of stress-responsive microRNAs that can evoke cardiac hypertrophy and heart failure. Proc Natl Acad Sci USA, 2006. 103(48): pp. 18255–18260. 39. Yang, B., et al., The muscle-specific microRNA miR-1 regulates cardiac arrhythmogenic potential by targeting GJA1 and KCNJ2. Nat Med, 2007. 13(4): pp. 486–491. 40. Ikeda, S., et al., Altered microRNA expression in human heart disease. Physiol Genomics, 2007. 31: pp. 367–373. 41. Thum, T., et al., MicroRNAs in the human heart: a clue to fetal gene reprogramming in heart failure. Circulation, 2007. 116(3): pp. 258–267. 42. Eisenberg, I., et al., Distinctive patterns of microRNA expression in primary muscular disorders. Proc Natl Acad Sci USA, 2007. 104(43): pp. 17016–17021. 43. Ambros, V., MicroRNA pathways in flies and worms: growth, death, fat, stress, and timing. Cell, 2003. 113(6): pp. 673–676. 44. Wienholds, E., et al., The microRNA-producing enzyme Dicer1 is essential for zebrafish development. Nat Genet, 2003. 35(3): pp. 217–218. 45. Bernstein, E., et al., Dicer is essential for mouse development. Nat Genet, 2003. 35(3): pp. 215–217.

8 MicroRNA in Muscle Development and Function

143

46. Harfe, B.D., et al., The RNaseIII enzyme Dicer is required for morphogenesis but not patterning of the vertebrate limb. Proc Natl Acad Sci USA, 2005. 102(31): pp. 10898–10903. 47. Yi, R., et al., Morphogenesis in skin is governed by discrete sets of differentially expressed microRNAs. Nat Genet, 2006. 38(3): pp. 356–362. 48. Giraldez, A.J., et al., MicroRNAs regulate brain morphogenesis in zebrafish. Science, 2005. 308(5723): pp. 833–838. 49. Andl, T., et al., The miRNA-processing enzyme dicer is essential for the morphogenesis and maintenance of hair follicles. Curr Biol, 2006. 16(10): pp. 1041–1049. 50. Harris, K.S., et al., Dicer function is essential for lung epithelium morphogenesis. Proc Natl Acad Sci USA, 2006. 103(7): pp. 2208–2213. 51. Zhao, Y., et al., Dysregulation of cardiogenesis, cardiac conduction, and cell cycle in mice lacking miRNA-1-2. Cell, 2007. 129(2): pp. 303–317. 52. Kwon, C., et al., MicroRNA1 influences cardiac differentiation in Drosophila and regulates notch signaling. Proc Natl Acad Sci USA, 2005. 102(52): pp. 18986–18991. 53. Srivastava, D., et al., Regulation of cardiac mesodermal and neural crest development by the bHLH transcription factor, dHAND. Nat Genet, 1997. 16(2): pp. 154–160. 54. Xu, C., et al., The muscle-specific microRNAs miR-1 and miR-133 produce opposing effects on apoptosis by targeting HSP60, HSP70 and caspase-9 in cardiomyocytes. J Cell Sci, 2007. 120(Pt 17): pp. 3045–3052. 55. Wang, D.Z., Micro or mega: how important are MicroRNAs in muscle? Cell Cycle, 2006. 5(10): pp. 1015–1016. 56. Yaffe, D. and O. Saxel, Serial passaging and differentiation of myogenic cells isolated from dystrophic mouse muscle. Nature, 1977. 270(5639): pp. 725–727. 57. Kim, H.K., et al., Muscle-specific microRNA miR-206 promotes muscle differentiation. J Cell Biol, 2006. 174(5): pp. 677–687. 58. McCarthy, J.J. and K.A. Esser, MicroRNA-1 and microRNA-133a expression are decreased during skeletal muscle hypertrophy. J Appl Physiol, 2007. 102(1): pp. 306–313. 59. Lu, J., et al., Regulation of skeletal myogenesis by association of the MEF2 transcription factor with class II histone deacetylases. Mol Cell, 2000. 6(2): pp. 233–244. 60. Lu, J., et al., Signal-dependent activation of the MEF2 transcription factor by dissociation from histone deacetylases. Proc Natl Acad Sci USA, 2000. 97(8): pp. 4070–4075. 61. Anderson, C., H. Catoe, and R. Werner, MIR-206 regulates connexin43 expression during skeletal muscle development. Nucleic Acids Res, 2006. 34(20): pp. 5863–5871. 62. Proulx, A., P.A. Merrifield, and C.C. Naus, Blocking gap junctional intercellular communication in myoblasts inhibits myogenin and MRF4 expression. Dev Genet, 1997. 20(2): pp. 133–144. 63. McCarthy, J.J., K.A. Esser, and F.H. Andrade, MicroRNA-206 is over-expressed in the diaphragm but not the hindlimb muscle of mdx mouse. Am J Physiol Cell Physiol, 2007. 239(1): pp. 451–457. 64. Flynt, A.S., et al., Zebrafish miR-214 modulates hedgehog signaling to specify muscle cell fate. Nat Genet, 2007. 39(2): pp. 259–263. 65. Wolff, C., S. Roy, and P.W. Ingham, Multiple muscle cell identities induced by distinct levels and timing of hedgehog activity in the zebrafish embryo. Curr Biol, 2003. 13(14): pp. 1169–1181. 66. Naguibneva, I., et al., The microRNA miR-181 targets the homeobox protein Hox-A11 during mammalian myoblast differentiation. Nat Cell Biol, 2006. 8(3): pp. 278–284. 67. Chen, C.Z., et al., MicroRNAs modulate hematopoietic lineage differentiation. Science, 2004. 303(5654): pp. 83–86. 68. Clop, A., et al., A mutation creating a potential illegitimate microRNA target site in the myostatin gene affects muscularity in sheep. Nat Genet, 2006. 38(7): pp. 813–818. 69. Frey, N. and E.N. Olson, Cardiac hypertrophy: the good, the bad, and the ugly. Annu Rev Physiol, 2003. 65: pp. 45–79. 70. Heineke, J. and J.D. Molkentin, Regulation of cardiac hypertrophy by intracellular signalling pathways. Nat Rev Mol Cell Biol, 2006. 7(8): pp. 589–600.

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Z. Deng, D-Z. Wang

71. Amack, J.D. and M.S. Mahadevan, Myogenic defects in myotonic dystrophy. Dev Biol, 2004. 265(2): pp. 294–301. 72. Care, A., et al., MicroRNA-133 controls cardiac hypertrophy. Nat Med, 2007. 13(5): pp. 613–618. 73. Sayed, D., et al., MicroRNAs play an essential role in the development of cardiac hypertrophy. Circ Res, 2007. 100(3): pp. 416–424. 74. Chan, J.A., A.M. Krichevsky, and K.S. Kosik, MicroRNA-21 is an antiapoptotic factor in human glioblastoma cells. Cancer Res, 2005. 65(14): pp. 6029–6033. 75. Cheng, A.M., et al., Antisense inhibition of human miRNAs and indications for an involvement of miRNA in cell growth and apoptosis. Nucleic Acids Res, 2005. 33(4): pp. 1290–1297. 76. Si, M.L., et al., miR-21-mediated tumor growth. Oncogene, 2006. 26(19): pp. 2799–2803. 77. Lewis, B.P., C.B. Burge, and D.P. Bartel, Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell, 2005. 120(1): pp. 15–20. 78. Ji, R., et al., MicroRNA expression signature and antisense-mediated depletion reveal an essential role of MicroRNA in vascular neointimal lesion formation. Circ Res, 2007. 100(11): pp. 1579–1588. 79. Politz, J.C., F. Zhang, and T. Pederson, MicroRNA-206 colocalizes with ribosome-rich regions in both the nucleolus and cytoplasm of rat myogenic cells. Proc Natl Acad Sci USA, 2006. 103(50): pp. 18957–18962. 80. Lagos-Quintana, M., et al., Identification of tissue-specific microRNAs from mouse. Curr Biol, 2002. 12(9): pp. 735–739. 81. Boutz, P.L., et al., MicroRNAs regulate the expression of the alternative splicing factor nPTB during muscle development. Genes Dev, 2007. 21(1): pp. 71–84. 82. Meng, F., et al., MicroRNA-21 regulates expression of the PTEN tumor suppressor gene in human hepatocellular cancer. Gastroenterology, 2007. 133(2): pp. 647–658. 83. Zhu, S., et al., MicroRNA-21 targets the tumor suppressor gene tropomyosin 1 (TPM1). J Biol Chem, 2007. 282(19): pp. 14328–14336. 84. Xiao, J., et al., MicroRNA miR-133 represses HERG K + channel expression contributing to QT prolongation in diabetic hearts. J Biol Chem, 2007. 282(17): pp. 12363–12367. 85. Lagos-Quintana, M., et al., New microRNAs from mouse and human. RNA, 2003. 9(2): pp. 175–179.

Chapter 9

MicroRNAs and Regenerative Medicine Ji Wu* and Zhaojuan Yang

Abstract Regenerative medicine is a multidisciplinary field that aims to repair, replace or regenerate cells, tissues or organs. MicroRNAs are regulators of gene expression that were identified only decades ago and recently have been shown potential therapeutic value for diverse diseases. Thus, combination of microRNAs and regenerative medicine become an emerging interdisciplinary medical field that may yield new exciting possibilities for clinical medicine. In this chapter, we review the therapeutic prospects of microRNAs in regenerative medicine. On one hand, microRNAs have important functions in the differentiation and proliferation of stem cells, which have a key function in the regeneration and transplantation of organs, and are involved in mammalian development, understanding of which will benefit tissue engineers. On the other hand, microRNAs are identified as potential therapeutic target for diverse diseases, especially for cancers. Even more, some indirect evidences show that the initiation and maintenance of cancer stem cells may be under their controls. Thus accumulated understanding of microRNAs functions in different biological processes will bring new approaches for regeneration medicine.

Keywords microRNA, regenerative medicine, stem cell, tissue engineering, cancer, cancer stem cell

9.1

Introduction

Regenerative medicine is a new interdisciplinary field that strives to repair, replace or regenerate cells, tissues or organs. This must be accomplished under disease, injury, or ageing. Regenerative medicine is very different from the more conventional

School of Life Science and Biotechnology, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, Shanghai 200240, China *Corresponding author: Phone: 86-21-34204933; Fax: 86-21-34204051; E-mail: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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approach of administering chemically based drugs. Proteins, cDNA, genes, cells, and tissues are all used as regenerative medicines. Based on that, regenerative medicines are classified into four broad types according to their characteristics: human substances (proteins, genes etc.), cells and tissues (a form of tissue engineering), embryonic stem (ES) cells, and novel materials [1]. Recent advances in regenerative medicine have been influenced by our understanding in multiple areas, including tissue engineering, stem cell biology, tissue turnover and replacement in adult mammals, and embryonic development [2–7]. MicroRNAs, a kind of short non-coding RNAs, are negative regulators that recognized not far long ago. Since the fist microRNAs (lin-4 and let-7) identified a crucial role in development of C. elegans [8], more and more biological processes in mammals are found affected by microRNAs, including development, metabolism, cell proliferation, apoptosis, and cell regeneration [9, 10]. Therefore, this kind of small RNAs will undoubtedly enhance new approaches to regenerative medicine.

9.2

MicroRNAs and Stem Cell

Owing to mammalian regeneration being mostly based on embryonic and adult stem cells, these special cells have recently been used in therapy and emerge at the center of expectations of regenerative medicine. Since 1959, hematopoietic stem cells (HSCs) have been used clinically and routinely for transplantations, even almost in a non-pure form [11–13]. From that time on, various kinds of stem cells have been under investigation for repairing injuries in multiple organs: the spinal cord, bone, brain and other organs [1, 14]. To scientists, there are generally two ways to apply discoveries of these stem cells. First, researchers isolate stem cells, culture and harvest them in vitro. They, then, transplant them into certain tissues of patients and let the endogenous signals to differentiate the stem cells into needed cells. Second, scientists use those factors identified to activate the patient’s own stem cells to repair damage occurred. Furthermore, tissue regenerative potential has an age-related decline due to an inhibition of the local signaling pathways that can activate stem cell in normal young tissues [15]. Therefore, the signals that can control stem cell proliferation and differentiation are very essential for stem cells in therapeutic approaches. Emerging works have showed that microRNAs are key regulators in proliferation and differentiation of stem cells [16]. Hatfield SD et al. found that germline stem cells from Drosophila with deletion of dicer-1, a gene encoding an enzyme that is essential for the maturation of microRNAs [17], exhibited a defect in cell cycle control and were delayed in the G1 to S transition [18]. This implies that microRNAs have crucial functions in stem cells. The first microRNAs reported involving in stem cells may be lin-4 and let-7. These microRNAs have been shown to control cell division of hypodermal blast cell lineage, a stem cell lineage [19–22]. The product of lin-14, one of lin-4’s target genes, presents at high levels in this stem cell lineage from newly hatched L1 animals

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and then decreases by the L2 stage [19–21]. In both lin-4 loss-of-function and lin14 gain-of-function mutants, the stem cell fails to differentiate and reiterates the L1 stage. The microRNA let-7 is expressed in the hypodermal seam cells at late L3 and early L4 stages [22]. Similar to lin-4 loss-of-function mutants, let-7 loss of function causes a failure of differentiation in this stem cell lineage. In recent years, other let-7 microRNA family members have also been found to have the same function in hypodermal cells [23, 24]. MiR-181 seems to be involved in the differentiation of hematopoietic stem cells [25]. Over-expression of miR-181 in these stem cells from bone marrow leads to an excess of B cells and fewer CD8+ T cells, which suggests that miR-181 directs bone-marrow progenitors along the B-cell differentiation pathway. MiR-150 is another microRNA that contributes to hematopoietic cell development [26]. Overexpression of miR-150 in hematopoietic stem cells leads to decreased formation of mature B cells but has little effect on T cell formation; the transition from pro-B to pre-B cell stage will be blocked when miR-150 expresses prematurely. This result suggests that miR-150 is essential for B cell development. MiR-124 has crucial function in the differentiation of progenitor cells to mature neurons [27]. During the neuronal differentiation, miR-124 regulates stage-specific alternative pre-mRNA splicing patterns, repressing PTBP1 to correctly splice PTBP2 mRNAs and accumulate PTBP2 protein, to promote nervous system development. In ES cells, microRNAs have been also found playing important roles. Knocking-out Dicer-1 in mouse ES cells results in severe differentiation defects [28] or a significant temporary proliferation defect [29]. Knocking out DGCR8, an RNA-binding protein that involves in the microRNA processing [30], leads to loss the ability of cell self-renewal and induces cell differentiation in mouse ES cells [31]. Even these results are contradictory, but all of them suggest that microRNAs have key function in ES cell fate control. In addition, miR-296 has been shown to have ES cell-specific functions in mouse; a mammalian hairpin cluster encoding six related microRNA genes for miR-290 to miR-295 has been found to be expressed specifically in ES cells but not in adult mouse organs; miR-21 and miR-22 cloned from undifferentiated ES cells have been indicated a increased expression upon differentiation [32]. Suh MR et al. identified 36 microRNAs by cDNA cloning from human ES (hES) cells; of these, 14 microRNAs are specifically expressed in ES cells only, miR-154*, miR200c, -d, miR371-373 and miR367-368 [33]. All of these data implicate a specific function of microRNAs in ES cells. As a result, microRNAs may have key functions in the proliferation and differentiation of stem cells, including ES cells. If we can clearly understand the regulative functions of microRNAs in the maintenance and differentiation of stem cells, such as which microRNAs control self-renewal and which regulate differentiation and how, we may enhance the healing rate of patients treated with stem cells. Therefore, there are a number of benefits of using microRNAs. First, a large number of stem cells may be obtained from few stem cells by using microRNAs as regulators. Thus, it will become much easier to realize transplantation of stem cells in clinic. Second, using microRNAs to activate the differentiation or proliferation of endogenous

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stem cells to repair damage tissues or regenerate aged ones. Third, through applying knowledge of microRNAs in stem cells, we will be able to freely control when and how target stem cells differentiation in a patient’s body (this may be called inducible differentiation). For example, expression of miR-181 results in an increase in the number of cells entering the B-lymphoid lineage and no significant change in the number entering the T-lymphoid lineage, whereas ectopic expression of miR142s or miR-223 has the opposite effect [25]. This suggests that selective gene silencing might be an essential event during subsequent cell line differentiation.

9.3

MicroRNAs and Tissue Engineering

Conventional approaches to harvest tissues are from patient themselves or donors, or using artificial ones. Even though all of these have significant medical impact, newer technologies are emerged seeking to overcome the limitations of these ‘conventional’ ones. One newer approach is to seed biodegradable scaffolds with donor cells and/or growth factors, culture them together, and then implant the scaffolds into human body to restore, maintain or improve the function of diseased or damaged tissues. Recently, some researches are trying another approach: developing human ES cells to harvest functional 3D tissues on demand. In both strategies, however, how to control the proliferation and oriented differentiation of seed cells is the main problem for tissue engineers. To solution this problem relies on our fundamental understanding of mammalian natural development process. Since the first microRNAs identified in development of C. elegans, this kind of non-coding small RNA in developmental control, as a new area of biology, consequentially impacts tissue engineers. Zebrafish miR-214 regulates muscle cell fate in embryonic development by targeting su(fu), encoding a negative regulator of Hedgehog signaling [34]. MiR-196 can direct cleavage of HoxB8 (one of Hox genes) mRNA in mouse embryos and up-regulate Sonic hedgehog (Shh) in the induction of mouse limb development [35–37]. In addition, miR-223 has been reported as a key factor in mouse osteoclast precursor cells affecting osteoclast differentiation [38]. All of these suggest that different microRNAs have their specific functions in different cell types during development. In some cases, however, different microRNAs are with distinct functions in the same cell type. MiR-1 and miR-133 are clustered and transcribed together in skeletal muscle during embryonic development, but their functions are very different [39]. Chen JF et al. indicated that miR-1 may regulate the expression of histone deacetylase 4 (HDAC4), a transcriptional repressor of muscle gene expression, to promote myoblast differentiation. While miR-133 represses serum response factor (SRF) to enhance myoblast proliferation [39]. Besides that, Xu C et al. reported a novel function of miR-1 and miR-133 on cardiomyocyte apoptosis, in response to oxidative stress in rat embryonic ventricular cell line, h9c2 [40]. MiR-1 promotes cell apoptotic by repressing the post-transcription of HSP60 and HSP70

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(heat shock proteins that are anti-apoptotic factors); whereas miR-133 produces an opposing effect by repressing the expression of caspase-9. Taking together, microRNAs may have key roles in controlling cell fate. Thus microRNAs are potentially a useful tool to regulate cell development for tissue engineers. As we all know, transplanted tissues are of multi-cellular. How to control the differentiated orientation of seed cells used by tissue engineers just become a fundamental problem. Recent researches imply that microRNAs are useful tools to solve this problem. Yi R et al. cloned more than 100 microRNAs from skin and found a different expression profile in epidermis and hair follicles [41]. MiR-200a, miR200b, miR-200c, miR-141, miR-429, miR-19b, miR-20, miR-17-5p and miR-93 are exclusively expressed in epidermis, whereas miR-199a and miR-199b are expressed preferentially in hair follicles. In epidermal-specific-Dicer-deleted mutant mice, hair follicles are stunted and their proliferation is decreased; in addition, no normal hair shafts are produced [42]. In the mutant mice, however, proliferation in the epidermis did appear to be increased [42]. This suggests that microRNAs influence the pattern of differentiation in skin epithelial stem cells and have critical roles in epidermal and hair-follicle development. To understand functions of these microRNAs in skin will make it more easily to generate this complex structure. In fact, to create a scaffold-guided tissue that is different from creating whole 3D organs, the seed cells should be controlled in a certain development stage before implantation. So, how to control the development of these seed cells become very important. Giraldez AJ et al. found that miR-430 targets hundreds of maternal mRNAs and can promote their deadenylation to control the maternal-zygotic transition during zebrafish embryogenesis [43]. Moreover, in mice with Dicer-specific deletion, the growing oocytes fail to process the first cell division [44]. These founding suggest that it is potential to hold cells in a particular developmental state by using microRNAs in the future, which is essential for tissue engineers.

9.4

MicroRNAs as Potential Therapeutic Targic in Diseases

Since microRNAs have been found various essential functions in diverse biologic process, it is potential that microRNAs are involved in pathogenesis of diseases. Recently, abnormal expression of microRNAs is identified to disrupt signaling networks in cells and leads to pathological changes. MiR-124 is a brain–specific microRNA. Transfecting this microRNA into HeLa cells causes a shift in their expression profile towards that of brain [45], and 1,100 putative and 174 annotated transcripts are suggested under the control of miR-124 [45, 46]. This indicates that miR-124 plays crucial role in brain function. Whether does its abnormal expression link brain disease? A recent report gives the answer. Lukiw WJ compared the expression patterns of microRNAs in normal brain and disease brain, finding that expression level of miR-124 changes in aged brain and Alzheimer’s disease brain [47]. This suggests that pathogenesis of disease is related with the expression of microRNAs that play crucial roles in cells. In fact, there are many researches having

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reported aberrant expression of microRNAs in diverse diseases. Here, we review some listing as following (summarized in Table 9.1).

9.4.1

MicroRNAs in Metabolic Diseases

So far, there are a few microRNAs that have been shown to regulate the fat metabolism pathway [48]. MiR-14 is the first microRNA reported to be involved in fat metabolism. Inhibiting miR-14 expression results in increased levels of triacylglycerol and diacylglycerol in Drosophila [49]. Krützfeldt J et al. used antagomirs (short RNA molecules designed to silence microRNAs) to study the precise molecular function of microRNAs in mice, and found that cholesterol biosynthesis genes are affected by miR-122 [50]. By inhibiting the expression of miR-122 in a diet-induced obese mouse, Esau C et al. also observed a decrease in plasma cholesterol levels and considerable improvement in hepatic steatosis [51]. MiR-278 is another one that is involved in energy homeostasis in Drosophila [52].

Table 9.1 Diverse functions of microRNAs in different biologic processes and some identified in diseases microRNA Function or disease involved Reference miR-122 miR-278 miR-375 miR-206 miR-181 miR-1, miR-133 miR-1 miR-1 miR-195 miR-208 miR-430 miR-9, miR-124a, miR-125b, miR-128, miR-132, miR-219 miR-133b

miR-181a miR-155 miR-155 let-7i miR-32 miR-17-92 hcmv-miR-UL112 miR-21

Cholesterol biosynthesis Energy homeostasis Insulin secretion Skeletal muscle differentiation Muscle differentiation Myogenesis Cardiomyocyte apoptosis Cardiogenesis Coronary artery disease Cardiac hypertrophy and heart failure Cardiac growth Zebrafish brain morphogenesis Ageing or Alzheimer’s disease

[51] [52] [53] [56] [58] [39] [40] [59] [60] [61] [62] [64] [47]

Maturation and function of midbrain dopamine neurons, related with Parkinson’s disease T cell sensitivity and selection Inflammation Immunodeficient Cholangiocyte immune response Inhibiting PFV-1 replication Inhibiting HIV-1 replication Viral microRNA, evading host immune defense Proliferative vascular diseases

[66]

[67] [68] [69, 70] [74] [75] [76] [78] [80]

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Mutants lacking miR-278 are lean. The reason for this may be that miR-278 mutants have elevated insulin production and sugar circulation mobilized from adipose-tissue glycogen stores. These researches suggest a potential role for microRNAs as attractive pharmacological agents for metabolic diseases, such as obesity. Of course, to determine whether or not these microRNAs are useful in the treatment of metabolic diseases, and how to use these microRNAs for this purpose, will require further studies.

9.4.2

MicroRNAs in Diabetes

MiR-375 is an evolutionarily-conserved, pancreatic islet-specific microRNA [53]. It has been shown that this molecule might control insulin secretion. Excess miR-375 inhibits glucose-induced insulin secretion, whereas repression of its expression improves insulin secretion. Thus, miR-375 might be a novel potential therapeutic target to cure diabetes.

9.4.3

MicroRNAs in Muscle-Related Human Diseases

MicroRNAs in skeletal muscle have been identified and seem to influence the formation of muscle tissue, suggesting that they have potential medical benefit in the treatment of muscle-related human diseases [54]. Detected by Northern blot analysis, MiR-1 is specifically expressed in cardiac and skeletal muscle and can promote myogenesis [39]. Lim LP et al. showed that ectopic miR-1 expression could change the transcriptional profile of Hela cells to shift towards a more muscle-like profile [45]. In Drosophila, miR-1 knock-out mutant larvae become paralyzed and die as small second instar larvae with severely disrupted musculatures [55]. MiR-206, together with miR-1, has effect on skeletal muscle development [56]. Repressing the expression of miR-206 may inhibit cell cycle withdrawal and muscle differentiation. P180, a subunit of DNA polymerase alpha, has been shown to be a direct target of miR-206 [57]. It is possible that miR-206 inhibits DNA synthesis, leading to down-regulation of p180 and thereby repressing the differentiation of muscle. A microRNA presented in the same cluster with miR-1, miR-133, also has an essential role in skeletal muscle proliferation and differentiation in vitro and in vivo [39]. In an addition, miR-181, a microRNA that is significantly up-regulated during muscle differentiation, is reported to participate in the establishment of muscle phenotype by targeting the homeobox protein Hox-A11, a repressor of this differentiation process [58]. Taking together, all these data suggest that microRNAs are potential therapeutic target for muscle-related human diseases.

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MicroRNAs in Heart Diseases

Zhao Y et al. pointed out that miR-1 expression in mouse embryo is regulated by SRF and myocardin (that negatively regulate ventricular cardiomyocyte proliferation) as well as Hand2 (that is necessary for cardiac differentiation) is one of its targets, suggesting that miR-1 is in the centre of balance regulation between differentiation and proliferation during cardiogenesis [59]. Moreover, the adult heart lacking miR-1 may reduce heart rate and prolong ventricular depolarization [59]. Over-expression of miR-1 has also been found in humans with coronary artery disease [60]. This research shows that miR-1 can exacerbate arrhythmogenesis by repressing both genes, KCNJ2 (encoding the K+ channel subunit Kir2.1) and GJA (encoding connexin 43). Knockdown of miR-1 may prevent heart arrhythmia. Thus, miR-1 is a potential target for antiarrhythmic. In mouse heart, overexpression of miR-195 leads to pathological cardiac growth and heart failure [61]. Recently, Van Rooij et al. have reported another microRNAs (miR-208) linking heart disease [62]. MiR-208 is a cardiac-specific microRNA, encoded by an intron of the α-myosin heavy chain (MHC) gene. MiR-208 has effect on cardiac growth and gene expression in response to stress and hupothyroidism. MiR-208-deficient mice resemble hyperthyroid hearts, which fail to undergo stress-induced β-MHC up-regulation as well as protect against pathological hypertrophy and fibrosis. Besides that, van Rooij et al. described more microRNAs that are up- or down-regulated during cardiac hypertrophy and heart failure; many of these microRNAs have similar expressive profit in failing hearts of human [61]. In addition, Ikeda S et al. pointed out distinct changes of microRNAs expression profile in different type of heart disease [63]. All of these findings suggest the possibility of microRNAs as therapeutic targets in heart disease.

9.4.5

MicroRNAs in Brain Diseases

In zebrafish, injection of miR-430, one member of a superfamily that includes the mammalian miR-17-miR-20 families, can rescue the defects in brain morphogenesis in maternal-zygotic dicer (MZdicer) mutants [64]. However, whether the function of miR-430 is conserved in mammals remains to be determined. Recently, a few research groups report the mutation of microRNAs in some brain diseases: aberrant expression of miR-9, miR-124a, miR-125b, miR-128, miR-132 and miR-219 in aged brain and Alzheimer’s disease brain [47], and mutation of some X-chromosomal microRNA genes in brain in patients with non-syndromic X-linked mental retardation [65]. Kim J et al. described the essential role of feedback circuit between miR-133b and paired-like homeodomain transcription factor Pitx3 in the maturation and function of midbrain dopamine neurons, and the deficient of miR-133b detected in midbrain tissue from patients with Parkinson’s disease [66]. These data suggest that microRNAs represent a key point of intervention in efforts to repair diseased brain cells.

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MicroRNAs in Infectious Diseases

Pathogenesis of infectious disease relies on function of host immune system and source of infection. An immune system with strong function will efficiently defense pathogen invasion. Up to date, there are a few microRNAs having been shown key roles in mammalian immune system. Li QJ et al. reported that miR-181a is important for T cell sensitivity and selection [67]; miR-155 plays key role in inflammation and deletion of miR-155 leads to animal immunodeficient [68–70]. Recently, more and more research works have demonstrated that microRNAs have essential function in viral replication and pathogenesis [71, 72]. Some papers indicated that host cells use microRNA-mediated post-transcriptional pathways to defense against virus replication [73] and prevent microbial infection [74]: mammalian miR-32 efficiently inhibits the propagation of primate foamy virus type-1 (PFV-1) [75]; miR-17-92 is essential for inhibiting efficient HIV-1 replication [76]; and let-7i contributes to preventing infection of Cryptosporidium parvum [74]. In fact, microRNAs have been identified not only in mammals, but also in virus, suggesting they have effect on viral pathogenesis. Marshall V et al. just found conserved, virally encoded microRNAs in patients with kaposi sarcoma or multicentric Castleman disease [77]. More intriguingly, Stern-Ginossar N et al. indicated that virus encode microRNAs, such as hcmv-miR-UL112, to evade host immune defense [78]. So, for host cells or even for virus, microRNAs are crucial regulators and may be useful in therapeutics for infectious disease. Taking together, more and more evidences show the crucial role of microRNAs in diverse biologic process and their potential medical prospects. Accumulated understanding on regulative role of microRNAs certainly serves to expand our knowledge of various disease pathogenesis and offer novel therapeutic approaches, such as microRNAs or antagomirs as one kind of regenerative medicines. However, the question is how to locally transfect specific microRNAs into patient bodies, for the same microRNA will have distinct function in different cell types. Fortunately, recent research has shown that a single vector for microRNA-based conditional RNA interference (RNAi) can be tightly regulated to knock-down multiple genes in mammalian cells; and tissue-specific, regulatable RNAi may be available using a replacement promoter that restrict the expression of RNAi to a particular cell lineage [79]. Thus, this approach raises the potential of microRNAs as regenerative medicine.

9.5 9.5.1

MicroRNAs in Cancer Potential Role in Oncogenisis

Cancer is one of the leading causes of death in the world. More and more people died of cancer, mostly for its metastasis and recurrence as well as no timely and efficient treatment. Whether can microRNAs help us resolve these problems? The answer may be yes. Kumar MS et al. repressed the maturation of microRNAs in

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cancer cells, leading to enhance cellular transformation and tumorigenesis [81]. Calin GA et al. performed a systematic search for the location of 186 representative microRNAs in the human genome, and found that 98 of 186 microRNA genes (52.5%) are present in cancer-associated genomic regions or in fragile sites; 35 of these are located in, or are very close to, fragile sites and common breakpoint regions [82]. Using a new bead-based flow cytometric method for microRNA expression profiling, Lu J et al. analyzed 217 microRNAs from 334 tissue samples, including multiple types of human cancers, and found that microRNAs are generally down-regulated in tumors compared with normal tissues. Besides that, more and more evidences have indicated that microRNAs are mutated or poorly expressed in most human cancers, including lymphoid, lung, liver, brain, breast, colorectal, prostate, cervical and testicular germ cell cancers, uterine leiomyoma, neuroblastoma [83–95] (summarized in Table 9.2). Table 9.2 MicroRNAs with cancers microRNA involved miR-15, miR-16 miR-142 miR-155 miR-17-19b miR-21, miR-155 miR-106-363 miR-15a, miR-15b, miR-16-1, let7a-3, let-7c, let-7d, miR-223, miR-342, miR-107 miR-181c miR-17-92 let-7 miR-34a-c miR-122 miR-21 let-7c miR-34a miR-181a-c miR-9, miR-125a, miR-125b miR-221, miR-222 miR-125b, miR-145, miR-21, miR-155 miR-21 miR-24, miR-98 miR-26a, miR-212 miR-143, miR-145 miR-221, miR-222 miR-30d, miR-125b, miR-26a, miR-30a-5p let-7, miR-21, miR-23b, miR-29b, miR-197 miR-372, miR-373

Cancer type

Reference

B cell chronic lymphocytic leukemia9 B-cell leukemia B-cell lymphomas B-cell lymphomas Chronic lymphocytic leukemia T-cell leukemia Acute promyelocytic leukemia

[100] [97] [98] [104] [99] [101, 102] [136]

Lung cancer Lung cancer Non-small cell lung cancer Hepatocellular carcinoma Hepatocellular cancinoma Liver carcinomas Neuroblastoma Brain cancer (glioblastoma multiforme) Primary neuroblastoma tumors Glioblastomas Breast tumor

[103] [106] [132] [107, 108] [109] [128] [94] [111, 134] [135] [137] [111]

Breast tumor Pituitary adenomal

[123] [85]

Colorectal neoplasia Prostate cancer Thyroid anaplastic carcinomas

[112] [124] [92]

Human uterine leiomyomas

[93]

Testicular germ cell tumors

[91]

9 MicroRNAs and Regenerative Medicine

155

A t[8, 17] translocation has been shown to cause an aggressive B-cell leukemia due to the over-expression of Myc [96]. The gene encoding the microRNA miR-142 is just located at this breakpoint junction [97]. The translocation results in a translocated myc gene at the 3′ end of the miR-142 precursor, with only 4-nt in between, resulting in the formation of a fusion protein, furthermore, the absence of an ~20 nt conserved sequence downstream of the miR-142 hairpin prevents the maturation of this microRNA. This may be the reason resulting to the accumulation of fusion transcripts and the up-regulation of myc and causing tumorgenesis. MiR-155 also is found accumulating in human B cell lymphomas [98, 99]; whereas, the genes that encode miR-15 and miR-16 are frequently deleted in B cell chronic lymphocytic leukemia (CLL) [100]. In an addition, the over-expression of mir-106-363 is reported in T cell tumorigenesis [101, 102]. A microRNA cluster, miR-17-92, has been found over-expressing in B cell lymphomas and lung cancer [103–105]. Takamizawa J et al. reported reduced expression of let-7 in human lung cancers [106]. Kutay H et al. showed changes in the microRNA expression profile in hepatocellular carcinomas (HCCs) [107]. It includes that down-regulation of hepatic miR-122, a liver-specific microRNA, is frequently found in HCC in both rodents and humans [107, 108]. Five other microRNAs, miR-199a*, miR-195, miR-199a, miR-200a, and miR-125a, have also been indicated to be down-regulated in HCC tissues [84]. In an addition, miR-21 is found up-regulated in human hepatocellular cancer [109]. MiR-34a is found lower expression in neuroblastoma (NB) cells [94]; lower expression levels of miR-181a, miR-181b and miR-181c have been shown in glioblastoma cell lines and in samples from the brains of patients with glioblastoma multiforme (GBM), a kind of highly invasive and very aggressive brain cancer, compared with normal brain control samples [110]. A significant decrease in the expression levels of miR-125b, miR-145, miR-21, and miR-155 has been observed in human breast tumor compared with normal breast tissue using microRNA microarrays and Northern blot analyses [111]. In colorectal neoplasia, the levels of miR-143 and miR-145 are significantly decreased, even though the levels of their hairpin precursors are similar in both normal and neoplastic organs [112]. Reduced accumulation of miR-143 and miR-145 is also detected in cancer cells of breast, prostate, cervical and lymphoid cancers [112]. All of these indicate that microRNAs may have crucial roles in oncogenesis. Then, what is their regulative mechanism to trigger oncogenesis? Next we will discuss the potential role of microRNAs in cancer stem cell; it may be the reason that microRNAs have function in oncogenesis.

9.5.2

Potential Role in Cancer Stem Cells

In most kinds of cancers, including both blood cell cancers and solid tumors, there are a small proportion of cells that possess the capacity to proliferate and form new tumors; these have been called cancer stem cells [113–115]. Normal stem cells are

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prevented from forming tumors by restrictions on the expansion of the stem cell pool, which is under the control of multiple genes. Normal stem cells are nichedependent. Indeed, stem cells’ niches regulate stem cell maintenance and the balance between self-renewal and initiation of differentiation [116–118]. However, cancer stem cells seem to overcome all of these obstacles. The indefinite proliferation of cancer stem cells initiates the formation of new tumors in distant sites. Cancer stem cells may originate from normal stem cells. In the case of acute myeloid leukemia (AML), normal primitive cells are thought to be the target cell that is susceptible to leukemic transformation [114]. Furthermore, cancer stem cells share many properties with normal stem cells, such as self-renewal. Recent research has indicated that the same signaling pathway controls the self-renewal of both normal and cancer stem cells. Bmi-1, a molecule that is essential for the maintenance of normal stem cells, is required for the proliferation and self-renewal of leukemia stem cells [119]. Cells lacking Bmi-1 fail to undergo leukemic transformation. These data indicate that the signals participating in the proliferation and self-renewal of normal stem cells possibly influence the formation and transfer of tumors. Since microRNAs have important function in proliferation and differentiation of stem cells (mentioned above), do they have function in the generation and maintenance of cancer stem cells and participate in the formation and transfer of human cancers? Abnormal expression of microRNAs has been identified in most human cancers and some of these microRNAs appear to have the characteristics of stem cell microRNAs (seen in Table 9.3), for the proliferation of cancer cells seems to be driven by cancer stem cells. MiR-17-92, has found essential role in lung development [120]. Over-expression of this cluster in embryonic lung epithelium increases number of proliferative epithelial cells, while inhibits the differentiation of proximal epithelial cells [120]. This suggests that miR-17-92 enhances the proliferation and inhibits differentiation of lung epithelial progenitor cell. Intriguingly, miR-17-92 is also able to enhance lung cancer cell growth [103–105]. This implicates that the microRNA cluster has most probably key functions in cancer stem cells. Some reports show that the oncogene c-myc (function in regulating cell proliferation, growth and apoptosis) activate the expression of this microRNA cluster [105]. Tumors with c-myc over-expression alone have high rates of apoptosis, but the cooperation between c-myc and miR-1719b (a portion of miR-17-92) results in highly malignant and disseminated lymphomas [104]. The reason may be as following: on one hand, E2F transcription factors, which participate in Myc signaling to regulate cell cycle and apoptosis, activate miR-17-92 transcription by binding its promoter; on the other hand, miR-17-92 negatively regulates the expression of E2F1, a factor to promote cell proliferation [105, 121, 122]. The aberrant expression of miR-17-92 in cancer cells maybe shift the balance of E2F factors from pro-apoptotic E2F1 to proliferative E2F3 network [121, 122]. Besides that, the phosphatase and tensin homolog (PTEN), a tumor suppressor, is also a predicted target of miR-17-92 [105]. Thus, the crucial function of miR-17-92 seems to evade Myc-induced apoptosis and cause inappropriate proliferation in tumors. MiR-21, an up-regulated microRNA found in human

9 MicroRNAs and Regenerative Medicine Table 9.3

Regulative mechanism of microRNAs in cancer cell

microRNA

Regulator

miR-17-92

c-myc, E2F factors

miR-21

Target of microRNA Function in cancer

miR-221 and miR-222 let-7

Enhance cancer cell growth

[104, 105, 121, 122]

PTEN

Increase cancer cell proliferation, mig ration and invasion Promote cancer cell proliferation Promote cancer cell proliferation Repress cancer cell growth Induce cancer cell apoptosis Inhibit growth and induce apoptosis of cancer cells Inhibit growth and increase apoptosis of cancer cells

[109, 123]

p27(Kip1) RAS, c-myc, HmgA2 Bcl2

miR-15 and miR-16 miR-34 family

p53

Reference

E2F1, PTEN

miR-155

miR-181c

157

E2F3

PCAF

[98] [124, 125] [126–129] [130] [94, 132, 133] [134]

hepatocellular cancer, is another example [109]. PTEN is also its direct target, and regulation of miR-21 can modify the expression profile of downstream mediators of PTEN (matrix metalloproteases 2 and 9), which involve in cell migration and invasion. This may be the reason why over-expression of miR-21 increases the proliferation, migration and invasion of tumor cells. The aberrant expression of miR-21 is also found in breast tumors, and knocking down miR-21 inhibits tumor growth [123]. Besides that, miR-155, miR-221 and miR-222 are also reported to promote cancer cell proliferation [98, 124, 125]. By contrast, some microRNAs are found to suppress the proliferation of cancer cells or even induce their apoptosis. Over-expression of let-7 represses the growth of lung cancer cells [106, 126]. Some oncogenes, such as RAS [127], c-myc [128], High Mobility Group A2 (HmgA2) [129], have been shown to be targets of let-7, and many genes in cell cycle and cell division are also reported to be directly or indirectly regulated by let-7 [126], implying that let-7 has crucial negative role in regulative network of cancer cell growth. Disrupting the relationship between HmgA2 and let-7 promotes oncogenic transformation [129]. Moreover, c-myc is also the target of let-7c; the induction of c-myc via inhibiting expression of let-7c will over-express oncogenic miR-17-92 cluster, and leads to hepatocellular proliferation and tumorigenesis [128]. In leukemic cells, miR-15 and miR-16 seem able to induce apoptosis by repressing the protein antiapoptotic B cell lymphoma 2 (Bcl2) [130]. Moreover, Jing Q et al. indicated that miR-16 contains an UAAAUAUU sequence that is complementary to AU-rich elements (AREs) [131]. Interestingly,

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AREs are normally found in some transcripts that encode cell proliferation factors such as c-fos, GM-CSF, TNF-α, IL-6, and IL-8, suggesting that miR-16 contributes to the control of cell proliferation [131]. MiR-34 family (miR-34a-c) is another example. They are the direct targets of p53; their over-expression can inhibit growth of non-small cell lung cancer cells by down-regulating a group of genes that promote cell cycle progress [132, 133]. Moreover, Welch C et al. found that miR-34a can reduce the expression of E2F3 protein and induce NB cell apoptosis [94]. Besides that, there are more examples. In glioma cells, miR-181c has a negative effect on cell growth, possibly for the positive correlation of miR-181c with PCAF and p53 (two tumor suppressor genes) [134]; three neuronal miRNAs (9, 125a, and 125b), which are found low lever in primary neuroblastoma tumors, can repress human neuroblastoma cell growth by down-regulating the truncated isoform of neurotrophin receptor tropomyosin-related kinase C [135]. Taking together, these microRNAs probably form a signaling network with some regulative factors to control proliferation of cancer cells, implying that they potentially have essential functions in cancer stem cell. If the roles of microRNAs in cancer stem cells are clearly defined, we will be able to exploit this information to develop new therapeutic strategies for cancer healing, such as using microRNA as a type of regenerative medicine to repress the growth of cancer stem cells or trigger their apoptosis. Interestingly, some researchers have suggested that cancer stem cells originate from Mature cells [138, 139]. If this is true, it will indicate that mature cells can be turned into stem cells. Understanding the regulatory mechanism of this transformation will launch a new era of research in regenerative medicine. This will be an attractive program to cure those diseases that are due to the abnormal functions of stem cells.

9.6

Perspectives

In-depth study of microRNAs is revealing more and more evidence of the potential roles of microRNAs in regenerative medicine. (1) MicroRNAs may potentially be used as medicines or therapeutic targets to cure various diseases, especially cancer. (2) MicroRNAs may be integrated in stem cells to induce them to differentiate in order to repair or regenerate damaged cells, structures, or tissues. (3) MicroRNAs may be as useful regulators to control cell development in tissue engineering. Besides that (4) microRNA expression profiles are able to be as diagnostic and prognostic markers of cancers [140–142]. (5) Moreover, microRNA-based shRNA libraries might be used to rapidly identify effective therapy targets, or to study the formation of diseases. Despite the huge potential for microRNAs in regenerative medicine, there are some obstacles to the clinical utilization of microRNAs including: how to make microRNA therapy efficient, specific and inducible; whether or not this therapeutic strategy has side effects; and whether or not microRNA therapeutics can lead to cancer. Regardless, with the emergence of more fascinating discoveries, all of these problems will be resolved and the medical potential of microRNAs should be realized.

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Acknowledgments The work was supported by Key Program of National Natural Scientific Foundation of China (No. 30630012; to J.W.) and Sponsored by Shanghai Pujiang Program, China (No: 06PJ14058; to J.W.).

References 1. Haseltine, W.A. (2003). Regenerative medicine: a future healing art. Brookings Rev 21, 38–43. 2. Alonso, L., and Fuchs, E. (2003). Stem cells of the skin epithelium. Proc. Natl. Acad. Sci. USA 100, 11830–11835. 3. Harada, S., and Rodan, G.A. (2003). Control of osteoblast function and regulation of bone mass. Nature 423, 349–355. 4. Dor, Y., Brown, J., Martinez, O.I., and Melton, D.A. (2004). Adult pancreatic beta-cells are formed by self-duplication rather than stem-cell differentiation. Nature 429, 41–46. 5. Leor, J., Amsalem, Y., and Cohen, S. (2005). Cells, scaffolds, and molecules for myocardial tissue engineering. Pharmacol. Ther. 105, 151–163. 6. Radtke, F., and Clevers, H. (2005). Self-renewal and cancer of the gut: two sides of a coin. Science 307, 1904–1909. 7. Sage, C., Huang, M., Karimi, K., Gutierrez, G., Vollrath, M.A., Zhang, D.S., GarciaAnoveros, J., Hinds, P.W., Corwin, J.T., Corey, D.P., and Chen, Z. (2005). Proliferation of functional hair cells in vivo in the absence of the retinoblastoma protein. Science 307, 1114–1118. 8. Lee, R.C., Feinbaum, R.L., and Ambros, V. (1993). The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75, 843–854. 9. Bartel, D.P. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116, 281–297. 10. Tsonis, P.A., Call, M.K., Grogg, M.W., Sartor, M.A., Taylor, R.R., Forge, A., Fyffe, R., Goldenberg, R., Cowper-Sal Lari, R., and Tomlinson, C.R. (2007). MicroRNAs and regeneration: let-7 members as potential regulators of dedifferentiation in lens and inner ear hair cell regeneration of the adult newt. Biochem. Biophys. Res. Commun. 362, 940–945. 11. Horowitz, M.M. (1999). Uses and growth of hematopoietic cell transplantation. In: Forman SJ, ed. Hematopoietic cell transplantation. Second ed. Malden, MA: Blackwell Science, pp. 12–18. 12. Santos, G.W. (2000). Historical background to hematopoietic stem cell transplantation. In: Atkinson K, ed. Clinical bone marrow and blood stem cell transplantation. Cambridge: Cambridge University Press, pp. 1–12. 13. Domen, J., Wagers, A., and Weissman, I.L. (2006). Bone marrow (hematopoietic) stem cells. In: Regenerative medicine. Washington, DC: Department of Health and Human Services, pp. 13–34. 14. Barberi, T., Klivenyi, P., Calingasan, N.Y., Lee, H., Kawamata, H., Loonam, K., Perrier, A.L., Bruses, J., Rubio, M.E., Topf, N., Tabar, V., Harrison, N.L., Beal, M.F., Moore, M.A., and Studer, L. (2003). Neural subtype specification of fertilization and nuclear transfer embryonic stem cells and application in parkinsonian mice. Nat. Biotechnol. 21, 1200–1207. 15. Rao, M.S., and Mattson, M.P. (2001). Stem cells and aging: expanding the possibilities. Mech. Ageing Dev. 122, 713–734. 16. Zhang, B., Pan, X., and Anderson, T.A. (2006). MicroRNA: a new player in stem cells. J. Cell Physiol. 209, 266–269. 17. Lee, Y.S., Nakahara, K., Pham, J.W., Kim, K., He, Z., Sontheimer, E.J., and Carthew, R.W. (2004). Distinct roles for Drosophila Dicer-1 and Dicer-2 in the siRNA/miRNA silencing pathways. Cell 117, 69–81.

160

J. Wu, Z. Yang

18. Hatfield, S.D., Shcherbata, H.R., Fischer, K.A., Nakahara, K., Carthew, R.W., and RuoholaBaker, H. (2005). Stem cell division is regulated by the microRNA pathway. Nature 435, 974–978. 19. Chalfie, M., Horvitz, H.R., and Sulston, J.E. (1981). Mutations that lead to reiterations in the cell lineages of C. elegans. Cell 24, 59–69. 20. Ambros, V., and Horvitz, H.R. (1984). Heterochronic mutants of the nematode Caenorhabditis elegans. Science 226, 409–416. 21. Ruvkun, G., and Giusto, J. (1989). The Caenorhabditis elegans heterochronic gene lin-14 encodes a nuclear protein that forms a temporal developmental switch. Nature 338, 313–319. 22. Reinhart, B.J., Slack, F.J., Basson, M., Pasquinelli, A.E., Bettinger, J.C., Rougvie, A.E., Horvitz, H.R., and Ruvkun, G. (2000). The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature 403, 901–906. 23. Abbott, A.L., Alvarez-Saavedra, E., Miska, E.A., Lau, N.C., Bartel, D.P., Horvitz, H.R., and Ambros, V. (2005). The let-7 MicroRNA family members mir-48, mir-84 and mir-241 function together to regulate developmental timing in Caenorhabditis elegans. Dev. Cell 9, 403–414. 24. Lin, M., Jones-Rhoades, M.W., Lau, N.C., Bartel, D.P., and Rougvie, A.E. (2005). Regulatory mutations upstream of mir-48, a C. elegans let-7 family microRNA cause developmental timing defects. Dev. Cell 9, 415–422. 25. Chen, C.Z., Li, L., Lodish, H.F., and Bartel, D.P. (2004). MicroRNAs modulate hematopoietic lineage differentiation. Science 303, 83–86. 26. Zhou, B., Wang, S., Mayr, C., Bartel, D.P., and Lodish, H.F. (2007). miR-150, a microRNA expressed in mature B and T cells, blocks early B cell development when expressed prematurely. Proc. Natl. Acad. Sci. USA 104, 7080–7085. 27. Makeyev, E.V., Zhang, J., Carrasco, M.A., and Maniatis, T. (2007). The MicroRNA miR-124 promotes neuronal differentiation by triggering brain-specific alternative pre-mRNA splicing. Mol. Cell. 27, 435–448. 28. Kanellopoulou, C., Muljo, S.A., Kung, A.L., Ganesan, S., Drapkin, R., Jenuwein, T., Livingston, D.M., and Rajewsky, K. (2005). Dicer-deficient mouse embryonic stem cells are defective in differentiation and centromeric silencing. Genes Dev. 19, 489–501. 29. Murchison, E.P., Partridge, J.F., Tam, O.H., Cheloufi, S., and Hannon, G.J. (2005). Characterization of Dicer-deficient murine embryonic stem cells. Proc. Natl. Acad. Sci. USA 102, 12135–12140. 30. Han, J., Lee, Y., Yeom, K.H., Nam, J.W., Heo, I., Rhee, J.K., Sohn, S.Y., Cho, Y., Zhang, B.T., and Kim, V.N. (2006). Molecular basis for the recognition of primary microRNAs by the Drosha-DGCR8 complex. Cell 125, 887–901. 31. Wang, Y., Medvid, R., Melton, C., Jaenisch, R., and Blelloch, R. (2007). DGCR8 is essential for microRNA biogenesis and silencing of embryonic stem cell self-renewal. Nat. Genet. 39, 380–385. 32. Houbaviy, H.B., Murray, M.F., and Sharp, P.A. (2003). Embryonic stem-cell-specific microRNAs. Dev. Cell 5, 351–358. 33. Suh, M.R., Lee, Y., Kim, J.Y., Kim, S.K., Moon, S.H., Lee, J.Y., Cha, K.Y., Chung, H.M., Yoon, H.S., Moon, S.Y., Kim, V.N., and Kim, K. (2004). Human embryonic stem cells express a unique set of microRNAs. Dev. Biol. 270, 488–498. 34. Flynt, A.S., Li, N., Thatcher, E.J., Solnica-Krezel, L., and Patton, J.G. (2007) Zebrafish miR214 modulates Hedgehog signaling to specify muscle cell fate. Nat. Genet. 39, 259–263. 35. Cobb, J., and Duboule, D. (2004). Tracing microRNA patterns in mice. Nat. Genet. 36, 1033–1034. 36. Yekta, S., Shih, I.H., and Bartel, D.P. (2004). MicroRNA-directed cleavage of HOXB8 mRNA. Science 304, 594–596. 37. Hornstein, E., Mansfield, J.H., Yekta, S., Hu, J.K., Harfe, B.D., McManus, M.T., Baskerville, S., Bartel, D.P., and Tabin, C.J. (2005). The microRNA miR-196 acts upstream of Hoxb8 and Shh in limb development. Nature 438, 671–674.

9 MicroRNAs and Regenerative Medicine

161

38. Sugatani, T., and Hruska, K.A. (2007). MicroRNA-223 is a key factor in osteoclast differentiation. J. Cell Biochem. 101, 996–999. 39. Chen, J.F., Mandel, E.M., Thomson, J.M., Wu, Q., Callis, T.E., Hammond, S.M., Conlon, F.L., and Wang, D.Z. (2006). The role of microRNA-1 and microRNA-133 in skeletal muscle proliferation and differentiation. Nat. Genet. 38, 228–233. 40. Xu, C., Lu, Y., Pan, Z., Chu, W., Luo, X., Lin, H., Xiao, J., Shan, H., Wang, Z., and Yang, B. (2007). The muscle-specific microRNAs miR-1 and miR-133 produce opposing effects on apoptosis by targeting HSP60, HSP70 and caspase-9 in cardiomyocytes. J. Cell Sci. 120, 3045–3052. 41. Yi, R., O’Carroll, D., Pasolli, H.A., Zhang, Z., Dietrich, F.S., Tarakhovsky, A., and Fuchs, E. (2006). Morphogenesis in skin is governed by discrete sets of differentially expressed miRNAs. Nat. Genet. 38, 456–462. 42. Andl, T., Murchison, E.P., Liu, F., Zhang, Y., Yunta-Gonzalez, M., Tobias, J.W., Andl, C.D., Seykora, J.T., Hannon, G.J., and Millar, S.E. (2006). The miRNA-processing enzyme dicer is essential for the morphogenesis and maintenance of hair follicles. Curr. Biol. 16, 1041–1049. 43. Giraldez, A.J., Mishima, Y., Rihel, J., Grocock, R.J., Van Dongen, S., Inoue, K., Enright, A.J., and Schier, A.F. (2006). Zebrafish MiR-430 promotes deadenylation and clearance of maternal mRNAs. Science 312, 75–79. 44. Tang, F., Kaneda, M., O’Carroll, D., Hajkova, P., Barton, S.C., Sun, Y.A., Lee, C., Tarakhovsky, A., Lao, K., and Surani, M.A. (2007). Maternal microRNAs are essential for mouse zygotic development. Genes Dev. 21, 644–648. 45. Lim, L.P., Lau, N.C., Garrett-Engele, P., Grimson, A., Schelter, J.M., Castle, J., Bartel, D.P., Linsley, P.S., and Johnson, J.M. (2005). Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature 433, 769–773. 46. Lewis, B.P., Burge, C.B., and Bartel, D.P. (2005). Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA rargets. Cell 120,15–20. 47. Lukiw, W.J. (2007). Micro-RNA speciation in fetal, adult and Alzheimer’s disease hippocampus. Neuroreport 18, 297–300. 48. Wilfred, B.R., Wang, W.X., and Nelson, P.T. (2007). Energizing miRNA research: a review of the role of miRNAs in lipid metabolism, with a prediction that miR-103/107 regulates human metabolic pathways. Mol. Genet. Metab. 91, 209–217. 49. Xu, P., Vernooy, S.Y., Guo, M., and Hay, B.A. (2003). The Drosophila miRNA Mir-14 suppresses cell death and is required for normal fat metabolism. Curr. Biol. 13, 790–795. 50. Krützfeldt, J., Rajewsky, N., Braich, R., Rajeev, K.G., Tuschl, T., Manoharan, M., and Stoffel, M. (2005). Silencing of microRNAs in vivo with ‘antagomirs’. Nature 438, 685–689. 51. Esau, C., Davis, S., Murray, S.F., Yu, X.X., Pandey, S.K., Pear, M., Watts, L., Booten, S.L., Graham, M., McKay, R., Subramaniam, A., Propp, S., Lollo, B.A., Freier, S., Bennett, C.F., Bhanot, S., and Monia, B.P. (2006). miR-122 regulation of lipid metabolism revealed by in vivo antisense targeting. Cell Metab. 3, 87–98. 52. Teleman, A.A., Maitra, S., and Cohen, S.M. (2006). Drosophila lacking miRNA miR-278 are defective in energy homeostasis. Genes Dev. 15, 417–422. 53. Poy, M.N., Eliasson, L., Krutzfeldt, J., Kuwajima, S., Ma, X., Macdonald, P.E., Pfeffer, S., Tuschl, T., Rajewsky, N., Rorsman, P., and Stoffel, M. (2004). A pancreatic islet-specific miRNA regulates insulin secretion. Nature 432, 226–230. 54. Callis, T.E., Chen, J.F., and Wang, D.Z. (2007). MicroRNAs in skeletal and cardiac muscle development. DNA Cell Biol. 26, 219–225. 55. Sokol, N.S., and Ambros, V. (2005). Mesodermally expressed Drosophila miRNA-1 is regulated by Twist and is required in muscles during larval growth. Genes Dev. 19, 2343–2354. 56. Anderson, C., Catoe, H., and Werner, R. (2006). MIR-206 regulates connexin43 expression during skeletal muscle development. Nucleic. Acids. Res. 34, 5863–5871. 57. Kim, H.K., Lee, Y.S., Sivaprasad, U., Malhotra, A., and Dutta, A. (2006). Muscle-specific microRNA miR-206 promotes muscle differentiation. J. Cell Biol. 174, 677–687.

162

J. Wu, Z. Yang

58. Naguibneva, I., Ameyar-Zazoua, M., Polesskaya, A., Ait-Si-Ali, S., Groisman, R., Souidi, M., Cuvellier, S., and Harel-Bellan, A. (2006). The miRNA miR-181 targets the homeobox protein Hox-A11 during mammalian myoblast differentiation. Nat. Cell Biol. 8, 278–284. 59. Zhao, Y., Samal, E., and Srivastava, D. (2005). Serum response factor regulates a muscle-specific miRNA that targets Hand2 during cardiogenesis. Nature 436, 214–220. 60. Yang, B., Lin, H., Xiao, J., Lu, Y., Luo, X., Li, B., Zhang, Y., Xu, C., Bai, Y., Wang, H., et al. (2007). The muscle-specific micromicroRNA miR-1 regulates cardiac arrhythmogenic potential by targeting GJA1 and KCNJ2. Nat. Med. 13, 486–491. 61. van Rooij, E., Sutherland, L.B., Liu, N., Williams, A.H., McAnally, J., Gerard, R.D., Richardson, J.A., and Olson, E.N. (2006). A signature pattern of stress-responsive microRNAs that can evoke cardiac hypertrophy and heart failure. Proc. Natl. Acad. Sci. USA 103, 18255–18260. 62. van Rooij, E., Sutherland, L.B., Qi, X., Richardson, J.A., Hill, J., and Olson, E.N. (2007). Control of stress-dependent cardiac growth and gene expression by a MicroRNA. Science 316, 575–579. 63. Ikeda, S., Kong, S.W., Lu, J., Bisping, E., Zhang, H., Allen, P.D., Golub, T.R., Pieske, B., and Pu, W.T. (2007). Altered microRNA expression in human heart disease. Physiol. Genomics. 31, 367–373. 64. Giraldez, A.J., Cinalli, R.M., Glasner, M.E., Enright, A.J., Thomson, J.M., Baskerville, S., Hammond, S.M., Bartel, D.P., and Schier, A.F. (2005). MicroRNAs regulate brain morphogenesis in zebrafish. Science 308, 833–838. 65. Chen, W., Jensen, L.R., Gecz, J., Fryns, J.P., Moraine, C., de Brouwer, A., Chelly, J., Moser, B., Ropers, H.H., and Kuss, A.W. (2007). Mutation screening of brain-expressed X-chromosomal miRNA genes in 464 patients with nonsyndromic X-linked mental retardation. Eur. J. Hum. Genet. 15, 375–378. 66. Kim, J., Inoue, K., Ishii, J., Vanti, W.B., Voronov, S.V., Murchison, E., Hannon, G., and Abeliovich, A. (2007). A MicroRNA Feedback Circuit in Midbrain Dopamine Neurons. Science 317, 1220–1224. 67. Li, Q.J., Chau, J., Ebert, P.J., Sylvester, G., Min, H., Liu, G., Braich, R., Manoharan, M., Soutschek, J., Skare, P., Klein, L.O., Davis, M.M., and Chen, C.Z. (2007). miR-181a is an intrinsic modulator of T cell sensitivity and selection. Cell 129, 147–161. 68. O’Connell, R.M., Taganov, K.D., Boldin, M.P., Cheng, G., and Baltimore, D. (2007). MicroRNA-155 is induced during the macrophage inflammatory response. Proc. Natl. Acad. Sci. USA 104,1604–1609. 69. Rodriguez, A., Vigorito, E., Clare, S., Warren, M.V., Couttet, P., Soond, D.R., van Dongen, S., Grocock, R.J., Das, P.P., Miska, E.A., Vetrie, D., Okkenhaug, K., Enright, A.J., Dougan, G., Turner, M., and Bradley, A. (2007). Requirement of bic/microRNA-155 for normal immune function. Science 316, 608–611. 70. Thai, T.H., Calado, D.P., Casola, S., Ansel, K.M., Xiao, C., Xue, Y., Murphy, A., Frendewey, D., Valenzuela, D., Kutok, J.L., Schmidt-Supprian, M., Rajewsky, N., Yancopoulos, G., Rao, A., and Rajewsky, K. (2007). Regulation of the germinal center response by microRNA-155. Science 316, 604–608. 71. Sullivan, C.S., and Ganem, D. (2005). MicroRNAs and viral infection. Mol. Cell 20, 3–7. 72. Dykxhoorn, D.M. (2007). MicroRNAs in viral replication and pathogenesis. DNA Cell Biol. 26, 239–249. 73. Kumar, A. (2007). The silent defense: micro-RNA directed defense against HIV-1 replication. Retrovirology 4, 26. 74. Chen, X.M., Splinter, P.L., O’hara, S.P., and Larusso, N.F. (2007). A cellular miRNA, let-7i, regulates toll-like receptor 4 expression and contributes to cholangiocyte immune responses against Cryptosporidium parvum infection. J. Biol. Chem. 282, 28929–28938. 75. Lecellier, C.H., Dunoyer, P., Arar, K., Lehman-Che, J., Eyquem, S., Himber, C., et al. (2005). A cellular MicroRNA mediates antiviral defense in human cells. Science 308, 557–560. 76. Triboulet, R., Mari, B., Lin, Y.L., Chable-Bessia, C., Bennasser, Y., Lebrigand, K., Cardinaud, B., Maurin, T., Barbry, P., Baillat, V., Reynes, J., Corbeau, P., Jeang, K.T., and Benkirane, M. (2007).

9 MicroRNAs and Regenerative Medicine

77.

78.

79.

80.

81. 82.

83.

84.

85.

86.

87.

88.

89.

90. 91.

92.

163

Suppression of microRNA-silencing pathway by HIV-1 during virus replication. Science 315, 1579–1582. Marshall, V., Parks, T., Bagni, R., Wang, C.D., Samols, M.A., Hu, J., Wyvil, K.M., Aleman, K., Little, R.F., Yarchoan, R., Renne, R., and Whitby, D. (2007). Conservation of virally encoded microRNAs in Kaposi sarcoma – associated herpesvirus in primary effusion lymphoma cell lines and in patients with Kaposi sarcoma or multicentric Castleman disease. J. Infect. Dis. 195, 645–659. Stern-Ginossar, N., Elefant, N., Zimmermann, A., Wolf, D.G., Saleh, N., Biton, M., Horwitz, E., Prokocimer, Z., Prichard, M., Hahn, G., Goldman-Wohl, D., Greenfield, C., Yagel, S., Hengel, H., Altuvia, Y., Margalit, H., and Mandelboim, O. (2007). Host immune system gene targeting by a viral miRNA. Science 317, 376–381. Shin, K.J., Wall, E.A., Zavzavadjian, J.R., Santat, L.A., Liu, J., Hwang, J.I., Rebres, R., Roach, T., Seaman, W., Simon, M.I., and Fraser, I.D. (2006). A single lentiviral vector platform for microRNA-based conditional RNA interference and coordinated transgene expression. Proc. Natl. Acad. Sci. USA 103, 13759–13764. Ji, R., Cheng, Y., Yue, J., Yang, J., Liu, X., Chen, H., Dean, D.B., and Zhang, C. (2007). MicroRNA expression signature and antisense-mediated depletion reveal an essential role of MicroRNA in vascular neointimal lesion formation. Circ. Res. 100, 1579–1588. Kumar, M.S., Lu, J., Mercer, K.L., Golub, T.R., and Jacks, T. (2007). Impaired microRNA processing enhances cellular transformation and tumorigenesis. Nat. Genet. 39, 673–677. Calin, G.A., Sevignani, C., Dumitru, C.D., Hyslop, T., Noch, E., Yendamuri, S., Shimizu, M., Rattan, S., Bullrich, F., Negrini, M., and Croce, C.M. (2004). Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proc. Natl. Acad. Sci. USA 101, 2999–3004. Lu, J., Getz, G., Miska, E.A., Alvarez-Saavedra, E., Lamb, J., Peck, D., Sweet-Cordero, A., Ebert, B.L., Mak, R.H., Ferrando, A.A., Downing, J.R., Jacks, T., Horvitz, H.R., and Golub, T.R. (2005). MicroRNA expression profiles classify human cancers. Nature 435, 834–838. Murakami, Y., Yasuda, T., Saigo, K., Urashima, T., Toyoda, H., Okanoue, T., and Shimotohno, K. (2006). Comprehensive analysis of microRNA expression patterns in hepatocellular carcinoma and non-tumorous tissues. Oncogene 25, 2537–2545. Bottoni, A., Zatelli, M.C., Ferracin, M., Tagliati, F., Piccin, D., Vignali, C., Calin, G.A., Negrini, M., Croce, C.M., and Degli Uberti, E.C. (2007). Identification of differentially expressed microRNAs by microarray: a possible role for microRNA genes in pituitary adenomas. J. Cell Physiol. 210, 370–377. Lanza, G., Ferracin, M., Gafa, R., Veronese, A., Spizzo, R., Pichiorri, F., Liu, C.G., Calin, G.A., Croce, C.M., and Negrini, M. (2007). mRNA/microRNA gene expression profile in microsatellite unstable colorectal cancer. Mol. Cancer 6, 54. Looijenga, L.H., Gillis, A.J., Stoop, H., Hersmus, R., and Oosterhuis, J.W. (2007). Relevance of microRNAs in normal and malignant development, including human testicular germ cell tumours. Int. J. Androl. 30, 304–315. Marsh, E.E., Lin, Z., Yin, P., Milad, M., Chakravarti, D., and Bulun, S.E. (2007). Differential expression of microRNA species in human uterine leiomyoma versus normal myometrium. Fertil. Steril. doi:10.1016/j.fertnstert.2007.05.004. Muralidhar, B., Goldstein, L.D., Ng, G., Winder, D.M., Palmer, R.D., Gooding, E.L., BarbosaMorais, N.L., Mukherjee, G., Thorne, N.P., Roberts, I., Pett, M.R., and Coleman, N. (2007). Global microRNA profiles in cervical squamous cell carcinoma depend on Drosha expression levels. J. Pathol. 212, 368–377. Porkka, K.P., Pfeiffer, M.J., Waltering, K.K., Vessella, R.L., Tammela, T.L., and Visakorpi, T. (2007). MicroRNA expression profiling in prostate cancer. Cancer Res. 67, 6130–6135. Voorhoeve, P.M., le Sage, C., Schrier, M., Gillis, A.J., Stoop, H., Nagel, R., Liu, Y.P., van Duijse, J., Drost, J., Griekspoor, A., et al. (2007). A genetic screen implicates miRNA-372 and miRNA-373 as oncogenes in testicular germ cell tumors. Adv. Exp. Med. Biol. 604, 17–46. Visone, R., Pallante, P., Vecchione, A., Cirombella, R., Ferracin, M., Ferraro, A., Volinia, S., Coluzzi, S., Leone, V., Borbone, E., et al. (2007). Specific microRNAs are downregulated in human thyroid anaplastic carcinomas. Oncogene 26, 7590–7595.

164

J. Wu, Z. Yang

93. Wang, T., Zhang, X., Obijuru, L., Laser, J., Aris, V., Lee, P., Mittal, K., Soteropoulos, P., and Wei, J.J. (2007). A micro-RNA signature associated with race, tumor size, and target gene activity in human uterine leiomyomas. Gene. Chromosome. Cancer 46, 336–347. 94. Welch, C., Chen, Y., and Stallings, R.L. (2007). MicroRNA-34a functions as a potential tumor suppressor by inducing apoptosis in neuroblastoma cells. Oncogene 26, 5017–5022. 95. Negrini, M., Ferracin, M., Sabbioni, S., and Croce, C.M. (2007). MicroRNAs in human cancer: from research to therapy. J. Cell Sci. 120, 1833–1840. 96. Gauwerky, C.E., Huebner, K., Isobe, M., Nowell, P.C., and Croce, C.M. (1989). Activation of MYC in a masked t(8;17) translocation results in an aggressive B-cell leukemia. Proc. Natl. Acad. Sci. USA 86, 8867–8871. 97. Lagos-Quintana, M., Rauhut, R., Yalcin, A., Meyer, J., Lendeckel, W., and Tuschl, T. (2002). Identification of tissue-specific microRNAs from mouse. Curr. Biol. 12, 735–739. 98. Eis, P.S., Tam, W., Sun, L., Chadburn, A., Li, Z., Gomez, M.F., Lund, E., and Dahlberg, J.E. (2005). Accumulation of miR-155 and BIC RNA in human B cell lymphomas. Proc. Natl. Acad. Sci. USA 102, 3627–3632. 99. Fulci, V., Chiaretti, S., Goldoni, M., Azzalin, G., Carucci, N., Tavolaro, S., Castellano, L., Magrelli, A., Citarella, F., Messina, M., et al. (2007). Quantitative technologies establish a novel microRNA profile of chronic lymphocytic leukemia. Blood 109, 4944–4951. 100. Calin, G.A., Dumitru, C.D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., Aldler, H., Rattan, S., Keating, M., Rai, K., Rassenti, L., Kipps, T., Negrini, M., Bullrich, F., and Croce, C.M. (2002). Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc. Natl. Acad. Sci. USA 99, 15524–15529. 101. Landais, S., Landry, S., Legault, P., and Rassart, E. (2007). Oncogenic potential of the miR106–363 cluster and its implication in human T-cell leukemia. Cancer Res. 67, 5699–5707. 102. Lum, A.M., Wang, B.B., Li, L., Channa, N., Bartha, G., and Wabl, M. (2007). Retroviral activation of the mir-106a microRNA cistron in T lymphoma. Retrovirology 4, 5. 103. Hayashita, Y., Osada, H., Tatematsu, Y., Yamada, H., Yanagisawa, K., Tomida, S., Yatabe, Y., Kawahara, K., Sekido, Y., and Takahashi, T. (2005). A polycistronic microRNA cluster, miR-17–92, is overexpressed in human lung cancers and enhances cell proliferation. Cancer Res. 65, 9628–9632. 104. He, L., Thomson, J.M., Hemann, M.T., Hernando-Monge, E., Mu, D., Goodson, S., Powers, S., Cordon-Cardo, C., Lowe, S.W., Hannon, G.J., and Hammond, S.M. (2005). A microRNA polycistron as a potential human oncogene. Nature 435, 828–833. 105. O’Donnell, K.A., Wentzel, E.A., Zeller, K.I., Dang, C.V., and Mendell, J.T. (2005). c-Mycregulated microRNAs modulate E2F1 expression. Nature 435, 839–843. 106. Takamizawa, J., Konishi, H., Yanagisawa, K., Tomida, S., Osada, H., Endoh, H., Harano, T., Yatabe, Y., Nagino, M., Nimura, Y., Mitsudomi, T., and Takahashi, T. (2004). Reduced expression of the let-7 microRNAs in human lung cancers in association with shortened postoperative survival. Cancer Res. 64, 3753–3756. 107. Kutay, H., Bai, S., Datta, J., Motiwala, T., Pogribny, I., Frankel, W., Jacob, S.T., and Ghoshal, K. (2006). Downregulation of miR-122 in the rodent and human hepatocellular carcinomas. J. Cell Biochem. 99, 671–678. 108. Gramantieri, L., Ferracin, M., Fornari, F., Veronese, A., Sabbioni, S., Liu, C.G., Calin, G.A., Giovannini, C., Ferrazzi, E., Grazi, G.L., Croce, C.M., Bolondi, L., and Negrini, M. (2007). Cyclin G1 is a target of miR-122a, a microRNA frequently down-regulated in human hepatocellular carcinoma. Cancer Res. 67, 6092–6099. 109. Meng, F., Henson, R., Wehbe-Janek, H., Ghoshal, K., Jacob, S.T., and Patel, T. (2007). MicroRNA-21 regulates expression of the PTEN tumor suppressor gene in human hepatocellular cancer. Gastroenterology 133, 647–658. 110. Ciafre, S.A., Galardi, S., Mangiola, A., Ferracin, M., Liu, C.G., Sabatino, G., Negrini, M., Maira, G., Croce, C.M., and Farace, M.G. (2005). Extensive modulation of a set of microRNAs in primary glioblastoma. Biochem. Biophys. Res. Commun. 334, 1351–1358. 111. Iorio, M.V., Ferracin, M., Liu, C.G., Veronese, A., Spizzo, R., Sabbioni, S., Magri, E., Pedriali, M., Fabbri, M., Campiglio, M., Menard, S., Palazzo, J.P., Rosenberg, A., Musiani, P., Volinia, S.,

9 MicroRNAs and Regenerative Medicine

112.

113.

114. 115.

116. 117.

118.

119. 120.

121. 122.

123. 124.

125.

126.

127.

128.

129.

165

Nenci, I., Calin, G.A., Querzoli, P., Negrini, M., and Croce, C.M. (2005). MicroRNA gene expression deregulation in human breast cancer. Cancer Res. 65, 7065–7070. Michael, M.Z., O’Connor, S.M., van Holst Pellekaan, N.G., Young, G.P., and James, R.J. (2003). Reduced accumulation of specific microRNAs in colorectal neoplasia. Mol. Cancer Res. 1, 882–891. Lapidot, T., Sirard, C., Vormoor, J., Murdoch, B., Hoang, T., Caceres-Cortes, J., Minden, M., Paterson, B., Caligiuri, M., and Dick, J. (1994). A cell initiating human acute myeloid leukaemia after transplantation into SCID mice. Nature 367, 645–648. Bonnet, D., and Dick, J. (1997). Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat. Med. 3, 730–737. Al-Hajj, M., Wicha, M.S., Benito-Hernandez, A., Morrison, S.J., and Clarke, M.F. (2003). Prospective identification of tumorigenic breast cancer cells. Proc. Natl. Acad. Sci. USA 100, 3983–3988. Spradling, A., Drummond-Barbosa, D., and Kai, T. (2001). Stem cells find their niche. Nature 414, 98–104. Calvi, L.M., Adams, G.B., Weibrecht, K.W., Weber, J.M., Olson, D.P., Knight, M.C., Martin, R.P., Schipani, E., Divieti, P., Bringhurst, F.R., Milner, L.A., Kronenberg, H.M., and Scadden, D.T. (2003). Osteoblastic cells regulate the haematopoietic stem cell niche. Nature 425, 841–846. Zhang, J., Niu, C., Ye, L., Huang, H., He, X., Tong, W.G., Ross, J., Haug, J., Johnson, T., Feng, J.Q., Harris, S., Wiedemann, L.M., Mishina, Y., and Li, L. (2003). Identification of the haematopoietic stem cell niche and control of the niche size. Nature 425, 836–841. Lessard, J., and Sauvageau, G. (2003). Bmi-1 determines the proliferative capacity of normal and leukaemic stem cells. Nature 423, 255–260. Lu, Y., Thomson, J.M., Wang, H.Y., Hammond, S.M., and Hogan, B.L. (2007). Transgenic over-expression of the microRNA miR-17-92 cluster promotes proliferation and inhibits differentiation of lung epithelial progenitor cells. Dev. Biol. 310, 442–453. Woods, K., Thomson, J.M., and Hammond, S.M. (2007). Direct regulation of an oncogenic micro-RNA cluster by E2F transcription factors. J. Biol. Chem. 282, 2130–2134. Sylvestre, Y., De Guire, V., Querido, E., Mukhopadhyay, U.K., Bourdeau, V., Major, F., Ferbeyre, G., and Chartrand, P. (2007). An E2F/miR-20a autoregulatory feedback loop. J. Biol. Chem. 282, 2135–2143. Si, M.L., Zhu, S., Wu, H., Lu, Z., Wu, F., and Mo, Y.Y. (2007). miR-21-mediated tumor growth. Oncogene 26, 2799–2803. Galardi, S., Mercatelli, N., Giorda, E., Massalini, S., Frajese, G.V., Ciafre, S.A., and Farace, M.G. (2007). miR-221 and miR-222 expression affects the proliferation potential of human prostate carcinoma cell lines by targeting p27Kip1. J. Biol. Chem. 282, 23716–23724. le Sage, C., Nagel, R., Egan, D.A., Schrier, M., Mesman, E., Mangiola, A., Anile, C., Maira, G., Mercatelli, N., Ciafre, S.A., Farace, M.G., and Agami, R. (2007). Regulation of the p27(Kip1) tumor suppressor by miR-221 and miR-222 promotes cancer cell proliferation. EMBO J. 26, 3699–3708. Johnson, C.D., Esquela-Kerscher, A., Stefani, G., Byrom, M., Kelnar, K., Ovcharenko, D., Wilson, M., Wang, X., Shelton, J., Shingara, J., Chin, L., Brown, D., and Slack, F.J. (2007). The let-7 MicroRNA represses cell proliferation pathways in human cells. Cancer Res. 67, 7713–7722. Johnson, S.M., Grosshans, H., Shingara, J., Byrom, M., Jarvis, R., Cheng, A., Labourier, E., Reinert, K.L., Brown, D., and Slack, F.J. (2005). RAS is regulated by the let-7 microRNA family. Cell 120, 635–647. Shah, Y.M., Morimura, K., Yang, Q., Tanabe, T., Takagi, M., and Gonzalez, F.J. (2007). Peroxisome proliferator-activated receptor alpha regulates a microRNA-mediated signaling cascade responsible for hepatocellular proliferation. Mol. Cell Biol. 27, 4238–4247. Mayr, C., Hemann, M.T., and Bartel, D.P. (2007). Disrupting the pairing between let-7 and Hmga2 enhances oncogenic transformation. Science 315, 1576–1579.

166

J. Wu, Z. Yang

130. Cimmino, A., Calin, G.A., Fabbri, M., Iorio, M.V., Ferracin, M., Shimizu, M., Wojcik, S.E., Aqeilan, R.I., Zupo, S., Dono, M., Rassenti, L., Alder, H., Volinia, S., Liu, C.G., Kipps, T.J., Negrini, M., and Croce, C.M. (2005). miR-15 and miR-16 induce apoptosis by targeting BCL2. Proc. Natl. Acad. Sci. USA 102, 13944–13949. 131. Jing, Q., Huang, S., Guth, S., Zarubin, T., Motoyama, A., Chen, J., Di Padova, F., Lin, S.C., Gram, H., and Han, J. (2005). Involvement of MicroRNA in AU-rich element-mediated mRNA instability. Cell 120, 623–634. 132. Bommer, G.T., Gerin, I., Feng, Y., Kaczorowski, A.J., Kuick, R., Love, R.E., Zhai, Y., Giordano, T.J., Qin, Z.S., Moore, B.B., Macdougald, O.A., Cho, K.R., and Fearon, E.R. (2007). p53-Mediated Activation of miRNA34 candidate tumor-suppressor genes. Curr. Biol. 17, 1298–1307. 133. He, L., He, X., Lim, L.P., de Stanchina, E., Xuan, Z., Liang, Y., Xue, W., Zender, L., Magnus, J., Ridzon, D., Jackson, A.L., Linsley, P.S., Chen, C., Lowe, S.W., Cleary, M.A., and Hannon, G.J. (2007). A microRNA component of the p53 tumour suppressor network. Nature 447, 1130–1134. 134. Liu, T., Papagiannakopoulos, T., Puskar, K., Qi, S., Santiago, F., Clay, W., Lao, K., Lee, Y., Nelson, S.F., Kornblum, H.I., Doyle, F., Petzold, L., Shraiman, B., and Kosik, K.S. (2007). Detection of a microRNA signal in an in vivo expression set of mRNAs. PLoS ONE. 2, e804. 135. Laneve, P., Di Marcotullio, L., Gioia, U., Fiori, M.E., Ferretti, E., Gulino, A., Bozzoni, I., and Caffarelli, E. (2007). The interplay between microRNAs and the neurotrophin receptor tropomyosin-related kinase C controls proliferation of human neuroblastoma cells. Proc. Natl. Acad. Sci. USA 104, 7957–7962. 136. Garzon, R., Pichiorri, F., Palumbo, T., Visentini, M., Aqeilan, R., Cimmino, A., Wang, H., Sun, H., Volinia, S., Alder, H., Calin, G.A., Liu, C.G., Andreeff, M., and Croce, C.M. (2007). MicroRNA gene expression during retinoic acid-induced differentiation of human acute promyelocytic leukemia. Oncogene 26, 4148–4157. 137. Gillies, J.K., and Lorimer, I.A. (2007). Regulation of p27Kip1 by miRNA 221/222 in glioblastoma. Cell Cycle 6, 2005–2009. 138. Guo, W., Lasky, J.L., 3rd, and Wu, H. (2006). Cancer stem cells. Pediatr. Res. 59, 59R–64R. 139. Zhang, P., Zuo, H., Ozaki, T., Nakagomi, N., and Kakudo, K. (2006). Cancer stem cell hypothesis in thyroid cancer. Pathol. Int. 56, 485–489. 140. Yanaihara, N., Caplen, N., Bowman, E., Seike, M., Kumamoto, K., Yi, M., Stephens, R.M., Okamoto, A., Yokota, J., Tanaka, T., Calin, G.A., Liu, C., Croce, C.M., and Harris, C.C. (2006). miRNA signature in lung cancer diagnosis and prognosis. Cancer Cell 9, 189–198. 141. Gaur, A., Jewell, D.A., Liang, Y., Ridzon, D., Moore, J.H., Chen, C., Ambros, V.R., and Israel, M.A. (2007). Characterization of microRNA expression levels and their biological correlates in human cancer cell lines. Cancer Res. 67, 2456–2468. 142. Waldman, S.A., and Terzic, A. (2007). Translating MicroRNA discovery into clinical biomarkers in cancer. JAMA 297, 1923–1925.

Chapter 10

Role of mir-302 MicroRNA Family in Stem Cell Pluripotency and Renewal Shi-Lung Lin* and Shao-Yao Ying

Abstract Recent research in human embryonic stem (hES) cells has shown a highly promising potential in transplantation therapy. Nevertheless, it is very difficult to maintain the purity and pluripotency of these hES cells. In a fertilized egg, maternal materials naturally maintain stem cell renewal and totipotency before the 128-cell stage of embryonic development. Mouse oocytes lacking Dicer, a conserved ribonuclease required for microRNA (miRNA) biogenesis, arrest in the division phase of meiosis I, indicating that miRNAs play a critical role in oogenesis. We have observed that mir-302 familial microRNAs (mir-302s) were expressed at extremely high levels in mouse oocytes and human embryonic stem cells, and gradually decreased after cell differentiation. Therefore, we proposed that the mir-302 family is one of the key maternal materials essential for maintenance and renewal of the hES cell pluripotency. For this, we developed a Pol-II-based intronic miRNA expression system to transgenically express the mir-302s in several human epidermal and cancerous cell lines. Surprisingly, these mir-302s-transfected cells, namely miRNA-induced pluripotent stem (mirPS) cells, were shown to not only express all sorts of hES markers, such as Oct3/4, SSEA-3, SSEA-4, Sox2 and Nanog, but also have a highly demethylated genome similar to the reprogrammed genome of a fertilized egg. Microarray analyses further revealed that genomewide gene expression patterns of these mirPS cells shared over 86% similarity with those of hES H1 and H9 cell lines. With certain molecular guidance ex vivo, these mirPS cells could differentiate into distinct tissue cell types, such as neuron-, chondrocyte-, fibroblast- and spermatogonia-like primordial cells. Based on these findings, we suggest that the function of mir-302s is able to not only maintain the hES cell renewal and pluripotency but also to reprogram differentiated cells into a hES-like pluripotent state, which may provide insights into areas of opportunity for therapeutic intervention.

Department of Cell and Neurobiology, Keck School of Medicine, University of Southern California, 1333 San Pablo Street, BMT-403, Los Angeles, CA 90033, USA *Corresponding author: E-mail: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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Keywords human embryonic stem (ES) cell, induced pluripotent stem (iPS) cell, stem cell renewal, totipotency, maternal materials, microRNA (miRNA), mir-302, feeder-free culture, epigenetic reprogramming, cell differentiation.

10.1

Introduction

Ever since the first isolation of human embryonic stem (hES) cell line from human blastocysts [33], there were concerns about destruction of human embryos, contamination of feeder cell antigens, and formation of teratomas. Recent reports on induced pluripotent stem (iPS) cells have opened up a new avenue for generating hES-like pluripotent cells directly from adult body cells, bypassing the use of human embryos as starting materials [30, 31]. Using retroviral delivery of four transcription factor genes (Oct3/4, Sox2, c-Myc, Klf4) into mouse embryonic fibroblasts, the iPS cells so obtained were similar in many genetic and behavioral properties to mouse embryonic stem cells [20, 34]. Additional iPS cell lines have continued to be developed from human embryonic fibroblasts and primary dermal fibroblast cultures using a similar approach [21, 37]. This approach may provide a potential patient-friendly therapy if is used in conjunction with the somatic cell nuclear transfer (SCNT) technology [17]. Indeed, such an iPS-based SCNT therapy has been shown to be useful for treating sickle cell anemia in a transgenic mouse model [6]. Yet, there are two problems emerging from the processes of iPS cell generation; one is the use of retroviral transgenes and the other the use of oncogenes (e.g. c-Myc and Klf4). Retroviral transfection is the only effective means to simultaneously and transgenically deliver the four full-length genes into a targeted somatic cell, whereas the random insertion of retroviral vectors into the transfected cell genome may also affect other non-targeted genes and produce unexpected results. This is problematic because simultaneous delivery of four large transgenes into one single cell is difficult to control, particularly when one or more of the genes are oncogenes. For generating therapy-grade pluripotent cell lines, the iPS approach may eventually work but is not natural. In natural fertilized eggs, maternal materials are responsible for the regulation of stem cell maintenance and renewal. That is why embryonic cells before the 128-cell stage are almost the same and all totipotent. Therefore, the secret of stem cell maintenance and renewal must reside in maternal materials rather than the transcription factors involved in early embryonic development, which is actually shown up later than the totipotent embryo stage. In a mouse oocyte, RNAs occupy a large volume of maternal materials, corresponding to about 45% of the whole genomic transcriptome [28]. During maternal–zygotic transition, these maternal RNAs are quickly degraded and the transcription of zygotic genes starts as early as at the two-cell stage to produce signals for embryonic development [19]. It is conceivable that many of the maternal RNAs are inhibitors of the zygotic gene products in order to prevent developmental signals and maintain the totipotent/pluripotent cell division at the most early embryonic stage.

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169

Role of MicroRNA in Stem Cell Maintenance and Renewal

MicroRNA (miRNA) is one of the key maternal materials essential for embryonic stem (ES) cell maintenance and renewal. MiRNA is a group of small inhibitory RNAs about 18–27 nucleotides (nt) in length and is capable of either directly degrading its messenger RNA (mRNA) targets or suppressing the protein translation of its targeted mRNAs, depending on the complementarity between the miRNA and its targets. Mouse oocytes lacking Dicer, a conserved ribonuclease required for miRNA biogenesis, arrest in the division phase of meiosis I, indicating that miRNAs play critical role in oogenesis [18]. It is also noted that mir-302 familial miRNAs (mir-302s) are expressed at extremely high levels in mouse oocytes and human ES cells as compared to other differentiated cells [29, 32]. The mir-302s are expressed together as a cluster in a long non-coding RNA transcript containing mir302b, mir-302c mir-302a, mir–302d and mir-367 in a 5′ to 3′ sequential order [29]. All of the mir-302s share an identical sequence in their 5′-end first 17 nucleotides, including the whole seed motif, and an overall 89% homology in their 23-nucleotide-long miRNA sequences. Based on the current databases from the miRBase:: Sequences program (http://microrna.sanger.ac.uk/), they are highly conserved in mammals from mouse to human and target almost the same cellular genes, including over 445 conserved genes in human and mouse. Many of these target genes are actually developmental signals involved in initiation and/or facilitation of lineagespecific cell differentiation during early embryonic development. For example, insulin-like growth factors (IGF) are potent developmental signals for the neuronspecific stem and progenitor cell lineage via either the Ras/Raf/mitogen-activated protein kinase (MAPK) or the phosphatidylinositol 3-kinase (PI3K)/Akt signal transduction pathway [35]. Some recent reports even suggest their roles in human ES cell renewal; however, this part of research remains to be determined because the current human ES cells are all isolated at a relatively late blastocyst stage. We found that over eighteen members of the IGF receptor (IGFR)–Ras/PI3K signaling pathways are strong targets for mir-302s, indicating that there is an extremely tight blockade of neuron-specific cell differentiation in mammalian oocytes and ES cells. Similar inhibitory effects of mir-302s on many other tissue cell lineages are also observed. In view of these evidences, it is very likely that the mir-302 family plays a critical role in ES cell maintenance and renewal. One of the closest mir-302 homologues in non-mammalian animals is the mir-430 family (mir-430s), which shares the same first six-nucleotide seed sequence with mir-302s. Nevertheless, there are three major differences between mir-430s and mir-302s. First, the mir-430 family targets a very different set of cellular genes in zebrafish [5], showing that over 84% of its target genes are totally different from those of mir-302s. Second, the function of mir-430s, but not mir-302s, is observed to degrade the wide variety of maternal RNA messages coincident with zygotic transcription at the mid-blastula stage. Last, the mir-430 expression initiates at the maternal–zygotic transition, not during oogenesis like maternal mir-302s. According

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to these differences, mir-430s and mir-302s are very likely to be evolutionally distinct species rather than evolutional derivatives. As a result, mir-403s function as a developmental initiator by degrading maternal inhibitors, whereas mir-302s act as a maternal inhibitor to prevent the activation of many developmental signals.

10.3

Design and Development of a Transgenic mir-302s Expression System

Based on the above observations, we hypothesize that the mir-302 family is one of the key maternal materials essential for pluripotent stem cell maintenance and renewal. To test the function of a specific miRNA, we have developed a Pol-IIbased intronic miRNA expression system and successfully used it to generate several transgenic miRNA-expressing cell lines and animals [13]. Our previous studies have shown that effective miRNAs can be derived from the intron regions of mammalian genes, namely intronic miRNA [10, 36]. Intronic miRNA expression is a prevalent event in mammals because approximately 50% of mammalian miRNAs are encoded within the introns of protein-coding genes [22]. As shown in Fig. 10.1A, intronic miRNA biogenesis relies on a coupled interaction between nascent Pol-II-mediated pre-mRNA transcription and intron splicing/excision, occurring within certain nuclear regions proximal to genomic perichromatin fibrils [4, 11]. These miRNAs are transcribed by type-II RNA polymerases (Pol-II) and excised by spliceosomes and other RNaseIII endonucleases to form mature miRNAs [3, 10]; however, Drosha may be not required for this process [24]. Because the intronic miRNA pathway is tightly regulated by multiple intracellular surveillance systems, including Pol-II transcription, spliceosomal splicing, exosomal digestion and nonsense-mediated decay (NMD) processing, its resulting gene silencing effect is considered to be most effective, specific and safest on targeted genes of interest [16]. Using this strategy, we have first demonstrated the specific RNA interference (RNAi) effects of numerous man-made miRNAs in several mouse and human cell lines in vitro [10, 11] and mouse skin, chicken embryo and zebrafish in vivo [12, 13, 14]. Further methods similar to ours have also been reported by Zhou et al. [38] and Chung et al. [2], who found that both intergenic and intronic miRNAs possess the same RNAi efficacy while the intronic miRNA expression methods allow coexpression of a marker protein with the miRNA(s). Given that there are currently over 1,000 native miRNAs found in vertebrates and many more new miRNA species continue to be identified, it is conceivable that this intronic miRNA expression system can be readily used as a transgenic tool for generating miRNA-mediated gene-knockout or -knockdown cell lines and/or loss-of-gene-function animals for evaluating the miRNA function of interest. Using the Pol-II-based intronic miRNA expression system, we have transgenically expressed mir-302s in several human epidermal and cancerous cell lines, such as human primary epidermal skin culture (hpESC), prostate carcinoma PC3 and LNCaP, breast adenocarcinoma MCF7 and melanoma Colo cells. Strategy for

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Fig. 10.1 Mechanism of intronic miRNA biogenesis and its relative RNAi effects. (A) Intronic miRNA is generated as a part of precursor messenger RNA (pre-mRNA), containing protein-coding exons and non-coding introns. The introns are spliced out of pre-mRNA and further excised into small miRNA-like molecules capable of triggering targeted gene silencing, while the exons are ligated together to form a mature mRNA for marker protein synthesis. (B) Transfection of a pre-designed intronic miRNA into a Tg(actin-GAL4:UAS-gfp) strain zebrafish elicits a strong gene-specific silencing effect on targeted green EGFP expression (>80% suppression, left lane 4), whereas other off-target RNA inserts, i.e. empty intron RGFP(–) (lane 1), intron with a HIV-p24 pre-miRNA insert (lane 2), with an integrin β1 pre-miRNA insert (lane 3) and 5′-splice site-defective intron RGFP(∆) (lane 5), present no effect. The anti-EGFP miRNA is inserted in the 5′proximal intron region of a red-shifted fluorescent marker (RGFP) gene. Northern blot analyses (right) show that mature miRNAs are generated only from the spliced products of the miRNAinserted RGFP, but not the empty RGFP(–) or the defective RGFP(∆), indicating the involvement of RNA splicing in the intronic miRNA biogenesis mechanism

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triggering intronic miRNA-mediated gene silencing in vitro and in vivo has been tested, using either Pol-II or CMV promoter-directed transcription of a recombinant RGFP gene, namely SpRNAi-RGFP, which contains an artificial splicing-competent intron (SpRNAi) for producing intron-derived gene silencing RNA effectors, such as native microRNA (miRNA) and man-made small hairpin RNA (shRNA). Incorporation of the SpRNAi intron into the red-shifted fluorescent protein gene (RGFP) is genetically engineered by sequential ligation of several synthetic DNA sequences as reported [10, 13, 14]. The SpRNAi intron comprises a precursor miRNA or shRNA insert, which can be released by intracellular RNA splicing and processing machineries, such as components of spliceosomes, exosomes and NMD systems, and then triggers an intronic miRNA-mediated gene silencing mechanism through the production of mature miRNA or shRNA gene silencing effectors. As shown in Fig. 10.1B, transfection of a pre-designed intronic miRNA into a Tg(actin-GAL4:UAS-gfp) strain zebrafish elicits a strong gene-specific silencing effect on targeted green EGFP expression (>80% suppression, left lane 4), whereas other off-target RNA inserts, including an intron-free RGFP(–) (lane 1), the intron with an anti-HIV-p24 miRNA insert (lane 2), with an anti-integrin b1 miRNA insert (lane 3), and with a 5′-splice site-defective intron RGFP(∆) (lane 5), present no detectable effects. The anti-EGFP miRNA is inserted in the 5′-proximal region of the SpRNAi intron. Northern blot analyses (right) show that mature miRNAs are generated only from the spliced products of the miRNA-inserted RGFP, but not the empty RGFP(–) or the defective RGFP(∆), indicating the involvement of RNA splicing in the intronic miRNA biogenesis mechanism. Based on this proof-of-principle design and strategy, we have constructed and tested an optimized SpRNAi-RGFP transgene vector expressing either a synthetic mir-302a–mir-302b–mir-302c–mir-302d (mir-302s) pre-miRNA cluster insert or a manually re-designed mir-302s pre-miRNA homologue insert. Both designs have been shown to present the same RNAi efficacy. The success of mir-302s transfection also co-expressed a red fluorescent protein (RGFP) marker, useful for identification of the mir-302s-expressing cells. All synthetic sequences used for construction of the intronic mir-302s pre-miRNA insert were made by following the databases of the miRBase::Sequences program. In experiments, we modified a VSV-G-positive pantropic retroviral vector, namely pLNCX2-rT, to transgenically deliver the mir302s-encoded SpRNAi-RGFP transgene. The pLNCX2-rT vector was derived from a modified pseudotype Moloney Murine Leukemia virus, pLNCX2 (Clontech, Palo Alto, CA). As shown in Fig. 10.2, we first incorporated the mir-302s pre-miRNA construct into the intronic insertion site (MluI–PvuI restriction site) of the SpRNAiRGFP transgene [10, 13, 14], and then inserted the SpRNAi-RGFP transgene into the multiple cloning site (XhoI–ClaI restriction site) of the pLNCX2-rT vector, so as to form a retroviral pLNCX2-rT-SpRNAi transgene vector. After that, the pLNCX2-rT-SpRNAi vector was co-transfected with a pVSV-G vector into GP2-293 packaging cells (Clontech, CA) to produce infectious but not replicable pLNCX2rT-SpRNAi retrovirus. The pLNCX2-rT-SpRNAi vector can be directly microinjected into the tested cell genomes or used to prepare high-titer retrovirus for infecting the tested cells [13, 14]. Positively transfected cells were isolated and

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Fig. 10.2 Schematic procedure for producing mir-302s-mediated transgenic mirPS cell lines. A retroviral vector delivery approach is used to transfect a cytomegalovirus (CMV) promoterdriven SpRNAi-RGFP transgene into the tested cell lines for steady expression of a pre-designed mir-302s pre-miRNA cluster

collected 24 hours later for sub-culturing, using flow cytometry selection with anti-RGFP monoclonal antibody (Clontech, CA) as reported [15].

10.4

Generation of hES-Like mir-302s-Induced Pluripotent Stem Cell Lines

We have generated several mir-302s-induced pluripotent stem (mirPS) cell lines derived from human epidermal and cancerous cells, such as human primary epidermal skin culture (hpESC), prostate carcinoma PC3 and LNCaP, breast adenocarcinoma MCF7, and melanoma Colo cells. The hES-like cell properties of these mirPS lines

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have been assessed in six areas: First, the cell morphology and proliferation rate were significantly changed by the mir-302s transfection in hpESC, PC3 and Colo cells. These new mirPS cell lines were named as “cell name + mir-302” as shown in Fig. 10.3. Second, the elevated expression of the complete mir-302 familial miRNAs (mir-302s) has been confirmed, using microRNA microarray analyses in these mirPS cell lines (Fig. 10.4). Third, the formation of embryoid bodies and the elevated expression of standard embryonic stem (ES) cell markers have been observed, including Oct3/4, SSEA-3, and SSEA-4 (Fig. 10.5). Fourth, global genomic demethylation has been detected, similar to the reprogramming status of an oocyte genome (Fig. 10.6). Fifth, genome-wide gene expression patterning of these mir302-expressing cells has been performed, showing over 86% similarity in the expression patterns of 32,668 cellular genes of the human ES H1 and H9 cells (Fig. 10.8). Last, the mir-302s-transfected cells can be guided into different tissue cell types, such as neuron-, chondrocyte-, fibroblast-, and spermatogonia-like cells, using various treatments of hormones and growth factors in vitro (Fig. 10.9). These findings provide strong evidence that our intronic mir-302s expression strategy is able to not only reprogram and transform somatic cells into ES-like pluripotent cells but also to maintain the renewal and pluripotency of these mirPS cells under a feeder-free culture condition in vitro. For in vitro isolation of primary culture cells from normal tissues, the dissected tissues (>1 mm3) are incubated at 37 °C under 5% CO2 for 15 minutes in digest buffer (0.1% collagenase IV, 0.2% hyaluronidase and 50 U/ml DNase (Sigma, CA), and then dissociated using cell dissociation buffer (Invitrogen). After that, the predesigned mir-302s expression vector was transgenically transfected into the dissociated cells. Approximately 95–98% of the mir-302s-transfected cells will undergo apoptosis, whereas 2–5% of the survival cells will be transformed into ES-like mirPS cells. All currently established mirPS cell lines were able to grow in 1x DMEM medium supplemented with charcoal-stripped 10% fetal bovine serum (FBS) with 4 mM L-glutamine, 1 mM sodium pyruvate, 5 ng/ml activin, 5 ng/ml noggin, and some other growth factor inhibitors, at 37 °C under 5% CO2. Under this feeder-free culture condition, the average cell cycle of the mirPS cells takes about 20–24 hours, indicating a very slow cell division rate. As shown in Fig. 10.3A–C, the tested somatic cells after the mir-302s transfection have changed their morphologies (lower panels) from spindle or asterisk-like outlooks to a more round shape, indicating that they may have lost the ability for cell migration. Flow cytometry analyses (upper panels) of their DNA contents (y axis) to different cell cycle stages (x axis) showed an over 67% reduction in their mitotic cell population, suggesting that the cell proliferation rates are much slower than those of their original cell types. The first (left) and second (right) peaks of the flow cytometry charts represented the levels of resting G0/G1 and mitotic M phase cell populations in the entire tested cell population, respectively. The mitotic cell population (M phase) was decreased from 36.1% to 10.9% in hpESC, from 38.4% to 12.6% in PC3, and from 36.5% to 11.5% in Colo cells after the mir-302 transfection, whereas there were no significant changes in either cell morphology or cell proliferation after transfection with an empty SpRNAi-RGFP vector (cell + vector)

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Fig. 10.3 Changes of cell morphology and cell proliferation rate after transgenic mir-302 transfection into human primary epidermal skin culture (hpESC), human prostatic carcinoma PC3, and human primary melanoma culture Colo cells. The cells with positive mir-302 expression were labeled as hpESC + mr-302 (A), PC3 + mir-302 (B), and Colo + mir-302 (C), respectively

or a vector encoding mir-gfp pre-miRNA insert (cell + mir-gfp). The mir-gfp miRNA was designed to target against a firefly green fluorescent protein EGFP gene, which shared no homology to known human and mouse genes. Based on these findings, we have demonstrated that transgenic mir-302 expression is sufficient

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Fig. 10.4 microRNA microarray analyses using the Colo cell samples, confirming that all mir-302 familial members (mir-302s) were highly expressed in the SpRNAi-RGFP transgenetransfected Colo + mir-302 cells (p < 0.01)

to reprogram and transform human primary culture cells and cancerous cells into a more embryonic stem (ES)-like morphology and rate of cell division. To confirm the transgenic mir-302s expression in the mirPS cells, we performed microRNA (miRNA) microarray analysis. At about 70% confluency, small RNAs from each cell culture line were isolated using a mirVana™ miRNA isolation kit (Ambion, Inc., Austin, TX), following the manufacturer’s suggestion. The purity and quantity of the isolated small RNAs were assessed using 1% formaldehydeagarose gel electrophoresis and spectrophotometer measurement (Bio-Rad, Hercules, CA), and then immediately submitted to LC Sciences (San Diego, CA) for microarray analyses. In the Cy3 and Cy5 intensity images (blue background), as signal intensity increases from level 1 to level 65,535 the corresponding color changes from blue to green, to yellow, and to red. In the Cy5/Cy3 ratio image (black background), when Cy3 level is higher than Cy5 level the color is green; when Cy3 level is equal to Cy5 level the color is yellow; and when Cy5 level is higher than Cy3 level the color is red. For example, as shown in Fig. 10.4, Cy3 refers to cells without any treatment (i.e. Colo) while Cy5 refers to cells with the transgenic mir-302 transfection (i.e. Colo + mir-302). In the Cy5/Cy3 ratio image (most right), all mir-302 familial members (mir-302s, white circles) were highly expressed after the transfection, indicating that our intronic mir-302s expression approach is able to transgenically express the whole mir-302 familial miRNAs in the mirPS cells.

10.5

Identification of hES Cell Marker Expression in mirPS Cells

At very high cell culture confluency (>85–90%), the mir-302-transfected mirPS cells tended to form compact colonies reminiscent of embryoid bodies (EB) derived from human embryonic stem (hES) cells, as shown in Fig. 10.5A. However, in the absence of proper guidance by any hormone or growth factor, these EB-like bodies

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would fall apart and differentiate into neuron-like primordial cells during subculturing. To further test the hES- and EB-like gene properties of these mirPS cell lines, we evaluated their ES marker gene expression. For example, as shown in Fig. 10.5B, the Colo + mir-302 cells strongly expressed a full category of hES cell markers, such as Oct3/4, SSEA-3, SSEA-4 and Sox2, whereas none of these markers were detected in the control Colo cells and the Colo cells transfected with an empty SpRNAi-RGFP vector (Colo + vector), a vector expressing mir-gfp miRNA (Colo + mir-gfp), or a vector expressing mir-434-5p miRNA (Colo + mir-434-5p). It is known that mir434-5p shares no homologous target gene with mir-302s. Since Colo is a primarily cultured human melanoma cell line, this result shows that the SpRNAi-RGFP transgenemediated mir-302 transfection is able to reprogram somatic cancer cells into an ES-like state, which is very similar to those of hES cell lines. Oct3/4 (also termed Oct-3 or Oct-4) is one of the POU transcription factors, whose expression is mainly in totipotent embryonic stem and germ cells [23, 25]. A critical level of Oct3/4 expression is required to maintain stem cell self-renewal and pluripotency. Down-regulation of Oct3/4 results in differentiation of embryonic stem cells into divergent developmental programs. SSEA proteins, SSEA-1, -3 and -4, are originally identified by monoclonal antibodies recognizing lacto- and globoglycolipids on the surface of pre-implantation-stage murine embryos and teratocarcinoma stem cells, but not on their differentiated derivatives [27]. Undifferentiated primate embryonic stem (ES) cells, human embryonic cancer (EC) and ES cells

Fig. 10.5 Embryoid body formation and the relative ES makers. (A) Different embryoid bodies (EB) derived from mir-302-transfected hpESC + mir-302, PC3 + mir-302 and Colo + mir-302 cells. In the absence of proper guidance under a feeder-free condition, these EB cells tend to differentiate into neuron-like cell types (bottom right). (B) Western blotting showing the expression of embryonic stem (ES) cell markers in the Colo + mir-302 cells, including Oct3/4, SSEA-3, SSEA-4 and Sox2, but not oncogenic Klf4 (n = 4, p < 0.01)

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all express SSEA-3 and SSEA-4, but not SSEA-1 [33]. SSEA-3 and SSEA-4 are synthesized during oogenesis and mainly presented in the membranes of oocytes, zygotes and early cleavage-stage embryos [26]. Sox2 functions as a core transcription factor in maintaining pluripotency, but this function is not specific to embryonic stem cells [1]. Therefore, based on the current understanding of these ES cell markers, the mirPS cells we established carry all characteristics of these markers.

10.6

Assessment of Genomic Demethylation and Loss of Cell Migration

Change of epigenetic modification is another unique feature of pluripotent ES cells, particularly genomic demethylation [7, 8]. In order to reprogram a somatic cell into an ES state, many embryonic genes need to be re-activated for inhibiting the activation of developmental and differentiation-related signals. DNA methylation plays a key role in regulating the on and off switch of these genes. Because methylation in the upstream promoter region often interferes with the assembly of transcriptional machineries essential for embryonic gene expression, a demethylation process must occur in order to re-activate the embryonic marker genes, such as Oct3/4, SSEA-3, and SSEA-4. To assess the DNA methylation alterations between Colo and Colo + mir-302 cells, we first isolated the cell genomes (DNA isolation kit, Roche, IN) and performed genome digestion with a CCGG-cutting restriction enzyme HpaII, which was sensitive to CpG methylation and cleaved only an unmethylated CCGG site, but not a methylated CCGG site. Figure 10.6A shows that the digested genomic fragments from control Colo cells were in average twice lager than those from hES-like Colo + mir-302 cells, indicating that a highly demethylation status

Fig. 10.6 CpG demethylation patterns observed in the Colo + mir-302 cells at the genome-wide scale (A) and in the 5′-upstream region of Oct3/4 promoter (B)

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indeed occurs in the Colo + mir-302 genome. The original sizes of Colo and Colo + mir-302 genomes are almost identical. Figure 10.6B further shows the changes of CpG methylation patterns in the Oct3/4 gene promoter region of the hES-like hpESC + mir-302, PC3 + mir-302 and Colo + mir-302 cell genomes as compared to those from their cancerous origins. To determine the CpG demethylation sites in this region, we treated the isolated genomic DNA with bisulfite (CpGenome DNA modification kit, Chemicon, CA), which converted all unmethylated cytosine to uracil, and then isolated the Oct3/4 5′-upstream promoter region using PCR (long template PCR extension kit, Roche, IN). Then, the PCR products were collected by a PCR purification kit (Qiagen, CA) and digested with an equal mixture (5U each) of multiple ACGT-cutting restriction enzymes, containing AclI (AACGTT), BmgBI (CACGTC), PmlI (CACGTG), SnaBI (TACGTA) and HpyCH4IV (ACGT). Because the unmethylated ACGT sites in this region were changed into AUGT sites by bisulfite, which could no longer be cleaved by the above restriction enzyme mixture, this result demonstrates that at least four methylated ACGT sites in the control hpESC, PC3 and Colo cells were reprogrammed to become demethylated in the mir-302s-transfected cells. This mir-302s-mediated demethylation of the Oct3/4 gene promoter region may also contribute to the re-activation of Oct3/4 gene expression in the mir-302s-transfected cells, such as Colo + mir-302. In addition, loss of cell migration was often observed in the metastatic cancer cells after the mir-302s transfection, such as metastatic PC3 cells. The PC3 cell line was originated from a bone metastasis of hormone-refractory prostate cancer. Given that ES cells tend to rest in one place and often form an embryoid body in situ, this may explain why the PC3 + mir-302 cells lost their migration capability. As shown in Fig. 10.7, when placing a PC3 cell next to a PC3 + mir-302 cell, we could clearly observe that the metastatic PC3 cell quickly migrated along one side of the PC3 + mir-302 cell in just about 30 seconds. This result suggests a potential therapeutical application for the intronic mir-302s transfection in cancer cells, which may not only reprogram the cancer cells into useful pluripotent ES cells but also reduce the chance of cancer metastasis. More advantageously, since the mir-302stransfected cancerous cells are still immune-compatible to the patients, the pluripotent ES cells so obtained may be directly used for transplantation therapy without the risk of immune rejection.

Fig. 10.7 Loss of cell migration ability observed in PC3 + mir-302 mirPS cells. Black arrows indicate the direction of metastatic PC3 cell movement

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Microarray Analysis of Genome-Wide Gene Expression

After the correlation between hES cell marker and transgenic mir-302s expression was confirmed, we performed microarray analysis to screen the changes of genome-wide gene expression profiles in the tested cells before and after the mir-302s transfection as well as between the mir-302s-transfected cells and other hES cells. Affymetrix gene microarrays (GeneChip U133A&B arrays, Santa Clara, CA) were used to assess the changes of over 32,668 human gene expression patterns between Colo and Colo + mir-302 cells as well as between Colo + mir-302 and other hES cell lines, such as H1 and H9. Total RNAs from each tested cell culture were isolated, using RNeasy spin columns (Qiagen, Valencia, CA). To clearly identify the most variable targets in the background, we first duplicated the microarray tests using the same Colo + mir-302 sample and selected two hundred genes (white dots), which were slightly presented in one side of the tests for more detailed comparison. As shown in Fig. 10.8, the changes of expression of these selected genes were all far less than one fold in the duplicated tests of Colo + mir-302, indicating that the background variation was very limited. Based on the scattering patterns of all microarray-identified genes, we then calculated the correlation coefficiency (CC) between the results of two compared transcriptome libraries. A CC rate was given to show the percentage of similarity in the expression patterns of 32,668 human genes with a threshold of only one-fold change. As a result of such stringent CC rates obtained, we found that the gene expression patterns of Colo + mir-302 cells shared a very high 89% and 86% similarity to those of hES H1 and H9 cells, whereas only a low 53% CC rate was shown between Colo and Colo + mir-302 cells. This strong genetic correlation between hES and mirPS cells suggests that the mir-302s transfection may directly and indirectly change up to 15,354 cellular gene expression patterns, which are associated with the reprogramming processes of a cancerous Colo cell into a hES-like Colo + mir-302 cell. Thus, our mir-302s transfection approach offers a simple, effective and safe shortcut for not only generating novel hES-like pluripotent cells but also facilitating the maintenance of hES cell pluripotency and self-renewal under a feeder-free cell culture

Fig. 10.8 Gene microarray analyses of altered gene expression patterns in the Colo + mir-302 compared to Colo cells, showing a significant increase of expression of many embryonic marker genes and a marked decrease of expression of cancer markers and developmental signal genes, which were very similar to the gene expression patterns of hES H1 and H9 cell lines (n = 3, p < 0.01)

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condition, preventing the tedious retroviral insertion of four large transcription factor genes into one single cell as used in the previous iPS methods.

10.8

Molecular Guidance of mirPS Cell Differentiation

Pluripotent differentiation defines the key characteristic of an embryonic stem (ES) cell. Through the guidance of different growth factors and/or hormones, human ES cells can differentiate into the three embryonic germ layers (ectoderm, mesoderm and definitive endoderm) – the founders of all adult tissues [9]. In the absence of any treatment except the feeder-free culture medium, xenograft implantation of the Colo + mir-302 mirPS cells into the uterus, but not other tissues, of a female pseudopregnant immunocompromised SCID-beige mouse formed embryo-like teratoma structures, particularly rich in neuronal and epithelial lineages. The pseudopregnant mice were made by intraperitoneally injection of 1 IU human menopausal gonadotrophin (HMG) for 2 days and then human chorionic gonadotrophin (hCG) for one more day. Without any external stimulation, the mirPS cells rarely grew in the subcutaneous region of mouse dorsal flanks. It seems that there is a self-regulation mechanism limiting the random growth of the mirPS cells. In present experiments, we have established four useful protocols for generating relatively pure populations of several differentiated cell types, such as neuron, fibroblast, chondrocyte and spermatogonia-like primordial cells. The mirPS cells were first cultivated in phenol red-free DMEM supplemented with 10% charcoalstripped FBS, 4 mM L-glutamine, 1 mM sodium pyruvate, 5 ng/ml activin, 5 ng/ml noggin, and some other growth factor inhibitors, at 37 °C under 5% CO2. At 70% confluency in a 75 ml culture flask (about five million cells), the noggin and growth factor inhibitors were removed and different hormones and/or growth factors were added into the medium of the cell culture, respectively, such as 50 ng/ml DHT, 100 ng/ml TGF-ß1, and/or 100 ng/ml BMP4. After 6 to 12 hour incubation, the treated cells were trypsinized, washed with 1x PBS, and collected in four aliquots of chilled Matrigel (100 µl each) and one aliquots of 100 µl 1x PBS, and immediately injected into the hind limb muscle, peritoneum, uterus, subcutaneous neck skin (with Matrigel) and tail vein (with PBS) regions of 6-week-old athymic immunocompromised SCID-beige nude mice in vivo. The nude mice were anesthetized with diethyl ether during experimental processing. By this means, we have confirmed the pluripotency, or even totipotency, of our Colo + mir-302 mirPS cells, which were able to form primordial neuron, fibroblast, chondrocyte and spermatogonia-like tissue cells (Fig. 10.9). We have also found the expression of embryonic fibroblast (EF) marker type-I collagen, cartilage marker type-II collagen, and germ cell marker THY-1 but not c-kit in these mirPS-derived fibroblasts, chondrocytes, and spermatogonia-like cells, respectively. Furthermore, we have shown the default neuronspecific lineage in Fig. 10.5A. It is conceivable that many more tissue cell types may be induced from the mirPS cells, using molecular guidance with various hormones and growth factors in vitro. In vitro guidance of stem cell differentiation into

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Fig. 10.9 Pluripotent differentiation of the Colo + mir-302 mirPS cells into various tissue cell types, such as primordial fibroblasts, chondrocytes and even spermatogonia-like germ cells, after xenotransplantation into immunocompromised SCID-beige nude mice, demonstrating their pluripotency in guided stem cell differentiation. Differentiated tissue cells derived from the mirPS cells were marked by the co-expression of a red fluorescent protein, RGFP (middle panels)

pure, feeder-free tissue cell types for use in transplantation therapy is the ultimate goal for current stem cell research.

10.9

Conclusion

Unlike the previous iPS cell technology using elevated expression of four full-length transcription factor genes (i.e. either Oct4–Sox2–c-Myc–Klf4 or Oct4–Sox2–Nanog– Lin28), each member of the mir-302 family is able to simultaneously regulate over 445 cellular genes and they all share almost the same target genes based on the databases of the miRBase::Sequences program (http://microrna.sanger.ac.uk/). Many of the mir-302 targeted genes are actually developmental signals involved in initiation or facilitation of lineage-specific cell differentiation during early embryonic

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development. Thus, the function of mir-302s is more likely to shut down or attenuate the global production of developmental signals rather than to create a counteracting balance among certain embryonic signaling pathways. By inhibiting the cellular genes essential for embryonic development and cell differentiation, mir-302s may be used not only to reprogram and transform differentiated somatic cells into ES-like pluripotent cells but also to maintain the long-term pluripotent and renewal properties of the ES cells under a feeder-free culture condition. Utilization of our intronic mir-302s expression strategy provides a safe and powerful new tool for ES-like pluripotent cell generation, particularly derived from primarily cultured somatic cells and cancerous cells. Because the pathway of intronic miRNA-mediated gene silencing is tightly regulated by multiple intracellular surveillance systems, including components of gene transcription, RNA splicing, exosomal digestion and NMD processing mechanisms, it is considered to be much more effective, specific and safe than the Pol-III-based siRNA/shRNA pathway. Advantageously, there are three breakthroughs in this intronic mir-302s expression strategy. First, the transfection of a single mir-302s-expressing transgene offers a very simple, efficient and safe method for generating ES-like pluripotent cells, preventing the tedious retroviral insertion of all four large transcription factor genes into one single cell as used in the previous iPS methods. Second, because the size of the mir-302s-expressing transgene is just about 1 kilo-bases, the transfection efficiency is extremely high (almost 100%) and the selection of positively transfected cells can be easily carried out by passing once through flow cytometry, which is a very time-saving process. Third, the transfection process can be completed under a feeder-free condition without the risk of feeder antigen contamination and the ES-like pluripotent cells so obtained can continue to grow in a feeder-free culture condition. Fourth, mir-302s are transcribed as part of maternal materials, which are more natural and compatible to the pluripotent conditions of mouse oocytes and human embryonic stem cells. Fifth, no oncogene is needed in the process of mir-302s-mediated ES cell generation. Last, we may use homologous DNA insertion in place of retroviral transfection to deliver the mir-302sexpressing transgene into a specific, desired region of the cell genome, preventing the risk of random insertion. Given that these advantages have solved most of the problems found in current stem cell research, learning how to use these mirPS cells for exploiting their potentials in transplantation therapy will be a forthcoming challenge in the near future.

References 1. Boyer LA, Lee TI, Cole MF, Johnstone SE, Levine SS, Zucker JP, Guenther MG, Kumar RM, Murray HL, Jenner RG, Gifford DK, Melton DA, Jaenisch R, Young RA. (2005) Cell 122: 947–956. 2. Chung KH, Hart CC, Al-Bassam S, Avery A, Taylor J, Patel PD, Vojtek AB, Turner DL. (2006) Polycistronic RNA polymerase II expression vectors for RNA interference based on BIC/miR155. Nucleic Acid Res. 34: e53.

184

S.-L. Lin, S.-Y. Ying

3. Danin-Kreiselman M, Lee CY, Chanfreau G. (2003) RNAse III-mediated degradation of unspliced pre-mRNA and lariat introns. Mol. Cell 11: 1279–1289. 4. Ghosh S, Garcia-Blanco MA. (2000) Coupled in vitro synthesis and splicing of RNA polymerase II transcripts. RNA 6: 1325–1334. 5. Giraldez AJ, Mishima Y, Rihel J, Grocock RJ, Van Dongen S, Inoue K, Enright AJ, Schier AF. (2006) Zebrafish MiR-430 promotes deadenylation and clearance of maternal mRNAs. Science 312: 75–79. 6. Hanna J, Wernig M, Markoulaki S, Sun CW, Meissner A, Cassady JP, Beard C, Brambrink T, Wu LC, Townes TM, Jaenisch R. (2007) Treatment of sickle cell anemia mouse model with iPS cells generated from autologous skin. Science 318: 1920–1923. 7. Harikrishnan KN, Chow MZ, Baker EK, Pal S, Bassal S, Brasacchio D, Wang L, Craig JM, Jones PL, Sif S, El-Osta A. (2005) Brahma links the SWI/SNF chromatin-remodeling complex with MeCP2-dependent transcriptional silencing. Nat. Genet. 37: 254–64. 8. Hochedlinger K, Jaenisch R. (2006) Nuclear reprogramming and pluripotency. Nature 441: 1061–1067. 9. Jiang J, Au M, Lu K, Eshpeter A, Korbutt G, Fisk G, Majumdar AS. (2007) Generation of insulin-producing islet-like clusters from human embryonic stem cells. Stem Cell 25: 1940–1953. 10. Lin SL, Chang D, Wu DY, Ying SY. (2003) A novel RNA splicing-mediated gene silencing mechanism potential for genome evolution. Biochem. Biophys. Res. Commun. 310: 754–760. 11. Lin SL, Ying SY. (2004) Novel RNAi therapy – intron-derived microRNA drugs. Drug Design Rev. 1: 247–255. 12. Lin SL, Chang D, Ying SY. (2005) Asymmetry of intronic pre-microRNA structures in functional RISC assembly. Gene 356: 32–38. 13. Lin SL, Ying SY. (2006a) Gene silencing in vitro and in vivo using intronic microRNAs. ShaoYao Ying (Ed.) MicroRNA protocols. pp295–312, Humana press, Totowa, NJ. 14. Lin SL, Chang SJE, Ying SY. (2006b) Transgene-like animal model using intronic microRNAs. Methods Mol. Biol. 342: 321–334. 15. Lin SL, Chang D, Ying SY. (2007) Hyaluronan stimulates transformation of androgenindependent prostate cancer. Carcinogenesis 28: 310–320. 16. Lin SL, Kim H, Ying SY. (2008) Intron-mediated RNA interference and microRNA (miRNA). Front. Biosci. 13: 2216–2230. 17. Meissner A, Jaenisch R. (2006) Generation of nuclear transfer-derived pluripotent ES cells from cloned Cdx2-deficient blastocysts. Nature 439: 212–215. 18. Murchison EP, Stein P, Xuan Z, Pan H, Zhang MQ, Schultz RM, Hannon GJ. (2007) Critical roles for Dicer in the female germline. Genes Dev. 21: 682–693. 19. O’Farrell PH, Stumpff J, Su TT. (2004) Embryonic cleavage cycles: how is a mouse like a fly? Curr. Biol. 14: R35–R45. 20. Okita K, Ichisaka T, Yamanaka S. (2007) Generation of germline-competent induced pluripotent stem cells. Nature 448: 313–317. 21. Park IH, Zhao R, West JA, Yabuuchi A, Huo H, Ince TA, Lerou PH, Lensch MW, Daley GQ. (2008) Reprogramming of human somatic cells to pluripotency with defined factors. Nature 451: 141–146. 22. Rodriguez A, Griffiths-Jones S, Ashurst JL, Bradley A. (2004) Identification of mammalian microRNA host genes and transcription units. Genome Res. 14: 1902–1910. 23. Rosner MH, Vigano MA, Ozato K, Timmons PM, Poirier F, Rigby PW, Staudt LM. (1990) A POU-domain transcription factor in early stem cells and germ cells of the mammalian embryo. Nature 345: 686–692. 24. Ruby JG, Jan CH, Bartel DP. (2007) Intronic microRNA precursors that bypass Drosha processing. Nature 448: 83–86. 25. Schöler HR, Hatzopoulos AK, Balling R, Suzuki N, Gruss P. (1989) A family of octamerspecific proteins present during mouse embryogenesis: evidence for germline-specific expression of an Oct factor. EMBO J. 8: 2543–2550.

10 Role of mir-302 MicroRNA Family in Stem Cell Pluripotency and Renewal

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26. Shevinsky LH, Knowles BB, Damjanov I, Solter D. (1982) Monoclonal antibody to murine embryos defines a stage-specific embryonic antigen expressed on mouse embryos and human teratocarcinoma cells. Cell 30: 697–705. 27. Solter D, Knowles BB. (1978) Monoclonal antibody defining a stage-specific mouse embryonic antigen (SSEA-1). Proc. Natl. Acad. Sci. USA 75: 5565–5569. 28. Stitzel ML, Seydoux G. (2007) Regulation of the oocyte-to-zygote transition. Science 316: 407–408. 29. Suh MR, Lee Y, Kim JY, Kim SK, Moon SH, Lee JY, Cha KY, Chung HM, Yoon HS, Moon SY, Kim VN, Kim KS. (2004) Human embryonic stem cells express a unique set of microRNAs. Dev. Biol. 270: 488–498. 30. Takahashi K, Yamanaka S. (2006) Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 126: 663–676. 31. Takahashi K, Tanabe K, Ohnuki M, Narita M, Ichisaka T, Tomoda K, Yamanaka S. (2007) Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 131: 861–872. 32. Tang F, Kaneda M, O’Carroll D, Hajkova P, Barton SC, Sun YA, Lee C, Tarakhovsky A, Lao K, Surani MA. (2007) Maternal microRNAs are essential for mouse zygotic development. Genes Dev. 21: 644–648. 33. Thomson JA, Itskovitz-Eldor J, Shapiro SS, Waknitz MA, Swiergiel JJ, Marshall VS, Jones JM. (1998) Embryonic stem cell lines derived from human blastocysts. Science 282: 1145–1147. 34. Wernig M, Meissner A, Foreman R, Brambrink T, Ku M, Hochedlinger K, Bernstein BE, Jaenisch R. (2007) In vitro reprogramming of fibroblasts into a pluripotent ES-cell-like state. Nature 448: 318–324. 35. Ye P, D’Ercole AJ. (2006) Insulin-like growth factor actions during development of neural stem cells and progenitors in the central nervous system. J. Neurosci. Res. 83: 1–6. 36. Ying SY, Lin SL. (2004) Intron-derived microRNAs – fine tuning of gene functions. Gene 342: 25–28. 37. Yu J, Vodyanik MA, Smuga-Otto K, Antosiewicz-Bourget J, Frane JL, Tian S, Nie J, Jonsdottir GA, Ruotti V, Stewart R, Slukvin II, Thomson JA. (2007) Induced pluripotent stem cell lines derived from human somatic cells. Science 318: 1917–1920. 38. Zhou HSL, Xia XG, Xu Z. (2005) An RNA polymerase II construct synthesizes short hairpin RNA with a quantitative indicator and mediates high efficient RNAi. Nucleic Acid Res. 33: e62.

Chapter 11

Epigenetic Regulation of miRNA in Stem Cells Keith Szulwach1, Xuekun Li2, Xinyu Zhao2, and Peng Jin1

Abstract The ability of stem cells to maintain the necessary potency to differentiate into unique progeny, as well as the process of differentiation itself, exemplifies the critical role of epigenetic regulation in modulating the expression of common genomes so as to link cellular genotype with phenotype. Various types of epigenetic regulation in the context of stem cells, and in particular that of epigenetic regulation of non-coding microRNA, hold significance during neurogenesis from a stem cell state. Potential mechanisms and discussion on the role of epigenetic regulation of miRNA expression during stem cell epigenesis and function will be put forth. Additionally, descriptions of current techniques enabling identification of key regulatory pathways involving miRNA via comprehensive expression profiling are provided.

Keywords Epigenetics, stem cells, neuron, high-throughput miRNA profiling

11.1 11.1.1

Introduction Epigenetics, Non-coding RNA and Stem Cells

In many multicellular organisms, common genomes have the ability to express the information of those genomes in different ways. Fundamentally, the study of such a phenomenon is epigenetics. Differences in the function of genetic elements without changes in the actual genetic or underlying DNA sequence of those elements

1 Department of Human Genetics and Graduate Program in Genetics and Molecular Biology, Emory University School of Medicine, Atlanta, GA, USA 2

Department of Neurosciences, University of New Mexico School of Medicine, Albuquerque, NM, USA

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allows for cells to differentiate and take on distinct roles, linking cellular genotype with phenotype. The epigenetic regulation of genomes in mammalian systems has allowed for the unique ability of particular cells to not only produce differential progeny but to maintain the ability to self renew, continually retaining the potency to produce unique cell types in subsequent cell divisions. Cells having these characteristics are formally known as stem cells. In mammalian systems, the molecular mechanisms contributing to stem cell function and epigenetic regulation of genomic information are quite varied and are still not completely understood. Such mechanisms include but may not necessarily be limited to those directly influencing DNA accessibility and gene expression in the context of chromatin, like covalent and non-covalent chemical modifications of DNA and histones. Other mechanisms, including those indirectly influencing the information flow from DNA to protein, like alternative splicing and poly-adenylation of mRNA transcripts, post-translational modifications of proteins, and posttranscriptional regulation of transcribed RNA may also be considered epigenetic under strict definitions. Perhaps one of the most intriguing of the mechanisms that have been described as influencing epigenetic processes is that involving some non-coding RNA transcripts. Reports of epigenetic influence by non-coding RNA, that is itself encoded in the genome, offers the possibility that these RNAs may be both subjected to and directing epigenetic regulation [43, 46, 47]. The obvious implication of such observations is the potential for such non-coding RNAs as ideal molecular links between cellular genotype and phenotype. Indeed non-coding RNAs are known to be involved in direct and indirect epigenetic regulation of genetic information in the context of stem cells as well. As a result, we have hypothesized that the epigenetic regulation of non-coding RNA, as well as the epigenetic influence of that non-coding RNA on cellular phenotype, contribute to stem cell function. Here, we will discuss various epigenetic mechanisms related to stem cell function emphasizing the potential for epigenetic regulation of non-coding RNA, particularly microRNA (miRNA). Through this, we will provide a framework for how epigenetic regulation of and by miRNA may influence the function of stem cells and differentiation of stem cells toward neuronal lineages.

11.1.2

DNA Methylation, Methyl DNA Binding Proteins, and an Example of MBD Function in Neurogenesis

DNA methylation is a covalent modification of cytosine at the position C-5 in CpG dinucleotides. In mammals, over 70% of CpG dinucleotides are methylated and nearly all DNA methylation occurs on CpG dinucleotides. Concentrations of unmethylated CpG dinucleotides are usually found in the promoters and the first exons of active protein coding genes, termed CpG islands [17]. Conversely, methylated CpG islands are generally associated with a condensed chromatin state that is repressive toward transcription of associated DNA. As a consequence, differential states of DNA methylation may modulate the expression of underlying genetic

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information and so are considered epigenetic in nature. DNA methylation is catalyzed by three DNA methyltransferase proteins (DNMTs). The de novo establishment of DNA methylation relies on DNMT3a and DNMT3b, whereas the maintenance of DNA methylation depends on DNMT1, which specifically recognizes hemi-methylated DNA and methylates the remaining strand [15]. Mammalian DNA methylation has been implicated in a diverse range of cellular functions, including tissue-specific gene expression, cell differentiation, genomic imprinting, and X chromosome inactivation [5]. DNA methylation represses gene expression by either directly blocking the binding of transcription factors [54] or by recruiting a family of methylated-CpG binding proteins (MBDs) many of which share homology only in their methyl-CpG binding (MBD) domains [5]. Therefore, DNA methylation is thought to be a critical factor in regulating the expression of common genomes in certain cellular or environmental contexts and so also in regulating the potency of stem cells. The MBD protein family includes MBD1, MBD2, MBD3, MBD4, MeCP2, Keiso, and several newly discovered members [22]. MBD1/Mbd1 is a multifunctional protein that is localized to both euchromatin and heterochromatin with influence in neural stem cell function. MBD1 has two DNA-binding domains which specifically recognize methylated CpGs and a zinc finger (CXXC3) domain that specifically binds unmethylated CpGs. The presence of two DNA binding domains in MBD1 may contribute to higher affinity and specificity in binding DNA sequences [18]. Transcriptional repression by MBD1 can be facilitated by several putative cofactors [11], and it is likely that MBD1 represses transcription through various mechanisms, depending on the particular gene and cell type. However, despite great effort, few MBD1 target genes have been identified. Moreover, although recent literature suggests that each MBD protein may have its own preferred binding sites in the genome [23], currently available structure-function data have not provided sequence specificity other than CpGs. Extensive in vitro analyses have suggested a role for MBD1 in transcriptional repression [12], chromatin assembly [12, 48], and heterochromatin structure maintenance: however, the biological function of MBD1 remains relatively unknown [50]. Despite the relative lack of data on Mbdl’s role in chromatin function, Mbd1 has been found localized in both neurons and a subset of Nestin-positive immature cells in the germinal zone of the hippocampus (SGZ) of adult mice [63]. This suggests that Mbd1 may regulate functions of adult neural stem/progenitor cells (NSPCs) via modulating epigenetic control of gene expression. Mbd1 mutant (Mbd1-/-) mice develop normally into adulthood, with no detectable developmental defects, except for mild reduction in forebrain weight, indicating that early development of the brain may be suboptimal in the absence of Mbd1. In the Mbd1-/- hippocampus, cell proliferation is normal, but the survival of newborn cells is significantly reduced along with decreased neuronal differentiation capacity of NSPCs. As a possible consequence, the dentate gyrus in Mbd1-/- mice has reduced cell density. In addition, adult Mbd1-/- mice have spatial learning deficits and markedly reduced dentate gyrus-specific long term potentiation, a proposed cellular mechanism for learning and memory [63]. Recently, we have found that these mice also exhibit

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increased anxiety, depression, and reduced social interaction [1], suggesting that Mbd1 is involved in multiple brain pathways and functions. At the cellular level, NSPCs isolated from adult Mbd1-/- mice have a reduced neuronal differentiation capacity in vitro, consistent with our in vivo findings [63]. In addition, Mbd1-/NSPCs have increased genomic instability and increased expression of endogenous stem cell mitogen fibroblast growth factor (Fgf-2). Fgf-2 is a potent growth factor for a large number of cell types and its over-expression has been found in many transformed tumor cells including glioma cells with possible NSC origin [57]. In fact, we found that Mbd1 regulates the expression of endogenous Fgf-2 level in adult NSPCs and, therefore, affects the neuronal differentiation of adult NSPCs (X Li and X Zhao, 2008). These studies on the function of Mbd1 in NSPCs provide a key example concerning the influence epigenetic modulation may have on stem cell function and neurogenesis.

11.1.3

Histone Modification

In eukaryotic cells, the basic unit of chromatin is formed by 146 base pairs of DNA wrapped around the histone octamer. The core histones H2A, H2B, H3, and H4 are subject to numerous and varied modifications, including acetylation, methylation, and phosphorylation. Among these modifications, lysine (K) acetylation and methylation are the best-understood [4]. Initial histone modification studies focused largely on acetylation, which is catalyzed by two opposing enzymes, histone acetyltransferease (HAT) and histone deacetylase (HDAC). At least eight HATs and nine HDACs have been identified in mammals [37]. The activities of HATs and HDACs can directly affect adult NSCs and adult neurogenesis. For example, neuronspecific genes share the conserved 21–23-basepair DNA response element, RE-1 (repressor element 1). Neuronal restricted silencing factor (NRSF or REST) binds to RE-1 and forms a repressing complex that represses neuronal gene expression in non-neuronal cells by recruiting HDAC1/2 and Sin3A [2, 32, 33, 53]. Treatment of adult NSPCs by volporic acid (VPA), a HDAC inhibitor and antiepileptic medicine, leads to reduced proliferation, increased neuronal differentiation, and decreased astrocyte and oligodendrocyte differentiation through activating a panneuronal transcription factor NeuroD1 [24]. More recently, Jessberger et al. further confirmed that VPA treatment attenuates seizure-induced aberrant neurogenesis through regulating NRSF and HDACs [16]. In the developing brain, VPA administration also induces significant hypomyelination and delay in the differentiation of oligodendrocytes through inhibiting the activity of HDACs [52]. Histone methylation plays important roles in embryonic stem cell (ESC) development, cell fate determination, and X chromosome inactivation [43, 56]. Patterns of histone H3K4 methylation (an active chromatin mark), H3K27 methylation (a temporarily inactive chromatin mark), and H3K9 methylation (a long term repressive chromatin mark) define the chromatin state of NSCs [35]. Mutation of Bmi-I, a component of polycomb group proteins with H3K27 methylase activity, results

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in reduced self-renewal of adult NSCs [39]. The chromatin state of NSCs is distinct from those of ESCs or differentiated cell types [35]. It is likely that during NSC differentiation, the chromatin state that defines the NSC signature shifts towards a state corresponding to those of more differentiated cell types. Therefore, the temporal epigenetic landscape of NSCs could in fact be a much more precise marker for stem cell signature than the expression patterns of single genes.

11.1.4

Adult Neural Stem Cells: Primary Isolation and Culture

In adults, stem cells exist in many tissues throughout life and may play critical roles in tissue regeneration and repair. Here we are concerned with a particular type of adult stem cell, neural stem cells (NSCs). These are multipotent cells that are characterized by their abilities to self-renew and to generate differentiated cells specifically in the central nervous system. Neurogenesis is defined as the process of generating new neurons from NSCs, which consists of the proliferation and fate determination of NSCs, migration and survival of young neurons, and maturation and integration of newly matured neurons [36]. Since the discovery of adult neurogenesis, neuroscientists and developmental biologists have been exploring the regulatory mechanisms and functions of this fascinating process. Our current knowledge supports the model that adult neurogenesis is regulated by both intrinsic programs and extrinsic modulators. Intrinsic programs include genes, genetic background, and epigenetic modifications that are essential for controlling NSC selfrenewal and multipotency. Extrinsic factors include both the microenvironment where NSCs physically reside and the stimuli that NSCs receive due to endocrinal, physiological and pathological changes (see a recent review by [62]). Although many significant advances have been made, more challenges are ahead of us in understanding how these regulatory mechanisms coordinately modulate neurogenesis and define neurogenic niche in adult mammalian brains. In particular, the potential epigenetic regulation of miRNA driven regulatory pathways may be crucial in understanding the molecular mechanisms contributing to neural stem cell epigenesis and production of new neurons throughout adulthood.

11.1.5

miRNA Function in Stem Cells and Neurogenesis

miRNA were originally discovered in genetic screens identifying heterochronic developmental regulators in C. elegans [30, 59]. More recent observations continue to support roles for miRNA in determining and maintaining developmental cell fates both spatially and temporally. In particular, miRNA are known to act in a cell type specific manner and, furthermore, have been found to be expressed at especially high levels in the central nervous system acting critically during neurogenesis

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and neuronal patterning [1, 3, 20, 26, 38, 49]. It has also been shown that the expression patterns of small RNA undergo dynamic changes during the differentiation of human ESCs into neuronal progenitors and mature neurons [27, 60]. One of the most well characterized examples of a miRNA having influence on neural development from the stem cell state is that of mir-124a, a miRNA with preferentially high expression in brain. Exogenous expression of the neuronalenriched mir-124a, as well another highly neuronal enriched miRNA, mir-9, in ESCs has been found to inhibit their differentiation into astrocytes by modulating the STAT3 pathway that is critical for astrocyte differentiation [20]. In addition, mir-124a has been found to down-regulate the expression of the small C-terminal domain phosphatase 1 (an anti-neuronal phosphatase) and promote pro-neuronal RNA splicing and thus neurogenesis [34, 58]. In fact there is also precedence for the involvement of epigenetic regulation of mir-124a in the context of neurogenesis from the stem cell state, further indicating the potential for epigenetic regulation of miRNA critical to the proper function of stem cells and neurogenesis. mir-124a has been shown to be regulated by a transcriptional regulatory complex that also happens to be associated with an epigenetic effector and DNA methyl CpG binding protein of the same family as MBD1, methyl CpG binding protein 2 (MeCP2), during neurogenesis from P19 embryonic carcinoma cells [10]. P19 cells have stem cell character in that they are able to maintain a certain amount of potency in culture and can be induced to differentiate into neuronal cell types with the treatment of retinoic acid. MeCP2 has been shown to recruit the histone lysine methyltransferase, SUV39H1, as part of the co-repressor complex specific for neuronal genes that was previously mentioned, REST or NRSF [40, 51]. REST has itself been shown to directly bind regions proximal to a family of miRNAs including mir-9, mir-124a, and mir-132. Reduced expression of REST during retinoic acid induced neuronal differentiation of P19 cells was shown to correlate with increased expression of mir-124a and decreased expression of non-neuronal mRNAs, thus revealing the potential for reciprocal epigenetic action of REST and mir-124a in P19 derived neurogenesis [10]. This example, similar to that of MBD1, again emphasizes a critical role for epigenetic regulation in neural stem cell function and further implicates the potential for epigenetic regulation of miRNA expression in such processes. We will further discuss the potential for epigenetic regulation of particular miRNA as well as the practicality for the use of specific techniques that may be applied toward assessing alterations in miRNA expression in the context of stem cells. Broad profiling of miRNA expression allows for determination of the potential contributions of miRNA to stem cell function and may also be useful for assessing any changes from wildtype levels of miRNA expression when epigenetic regulators, such as methyl-DNA binding proteins, are disrupted. Beyond mir-124a, there is also intriguing evidence for critical epigenetic regulation of miRNA in the context of stem cells. This evidence comes from genomewide scans of binding sites for key transcriptional and epigenetic regulators in embryonic stem cells. These studies have identified core transcriptional regulatory networks involving the factors Oct4, Sox2 and Nanog as well as binding sites for

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the epigenetic regulatory Polycomb proteins. Sox2, in particular, has itself been shown to play a critical role in differentiation of neuronal stem cells specifically toward the neuronal lineage. In both studies, the above transcriptional and epigenetic regulators were found to directly interact with genomic regions proximal to specific miRNA in ES cells [6, 7, 31]. This strongly indicates the importance of these miRNA in either the maintenance or differentiation of stem cells. The implications for epigenetic regulation of miRNA expression in the context of stem cells are potentially far reaching. Reports on the abilities of individual miRNA to target multiple mRNA transcripts simultaneously and the potential of individual mRNA transcripts to be regulated by multiple different miRNA simultaneously may in fact allow for the potential of particular miRNA or subsets of miRNA to drive regulatory pathways during cellular, multicellular, and organism development via their impact on translation of target mRNA. Indeed this has been shown to be the case for some miRNA in oncogenic and tumor suppressor networks as well in dopaminergic neurons and Parkinson’s Disease [8, 13, 14, 21, 42]. Furthermore, recent reports on the ability of miRNA to fine tune expression of their targets to biologically critical levels also indicate the potential importance of such mechanisms in stem cells [19, 61]. Epigenetic regulation of a single miRNA, therefore, could potentially set in motion the regulation or fine tuning of multiple mRNA targets whose downstream expression and function is critical toward either the self-renewal or differentiation of a stem cell. By regulating the expression of a single miRNA at the epigenetic level a cell could thereby more efficiently, dynamically, and accurately regulate the expression levels of downstream target mRNAs at critical temporal and spatial thresholds required for proper stem cell function (see Figs. 11.1, 11.2). Again, we will further discuss the practicality of assessing alterations in miRNA expression in the context of stem cells in order to determine potential contributions of key miRNA to stem cell function as well assessing any changes from wildtype levels of miRNA expression when epigenetic regulators critical to the function of many stem cells, such as the described methyl-DNA binding proteins, are disrupted. This approach works towards establishing a general framework in which critical epigenetic-miRNA regulatory pathways driving stem cell epigenesis and differentiation from the stem cell state may be identified.

11.2

Results

In order to fully address the potential for epigenetic regulation of miRNA in the context of stem cell function we have chosen to take the approach of isolating and culturing primary adult NSPCs and subsequently performing differentiation of those cells in culture (summarized in Fig. 11.3) so as to enable detection of any potential alterations in miRNA expression in the context of neurogenesis. As an additional experimental variable, cells may be isolated from any type of genetically engineered and viable mouse in order to determine the associated affects on NSPC function and miRNA expression. For instance, isolating cells from mice in which a null allele for

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Repressor Complex

X Translation

Epigenetic suppression

mRNA translation

Cell Fate

miRNA expression

miRNA expression

Target mRNA

Translation

Fig 11.1 Generalized model for epigenetic regulation of miRNA determining cell fate. A miRNA may be epigenetically silenced in the undifferentiated cell state by the combination of a methylDNA binding protein and associated chromatin modifying repressor complex. In this state, the expression of the repressed miRNA is low while the expression of target mRNA transcript or protein coded for by the target transcript is high relative to the differentiated state. Upon an extrinsic or intrinsic signal cue for cellular differentiation epigenetic repression of the target miRNA is released and miRNA expression increases. The increase in miRNA expression then correlates with decreased stability or translation of target mRNAs. By epigenetically regulating one miRNA the cell can thereby direct and fine tune expression of multiple miRNA targeted mRNA transcripts during cell fate determination. The illustrated example provides a single direction in which this mechanism may potentially function and it may be equally likely that the mechanism contributes to cell fate determination in the opposite manner. In this case, miRNA expression may become epigenetically silenced during differentiation. Subsequently, target mRNA translation would increase and proteins important to the differentiating cell would be expressed at higher levels than in the undifferentiated cell

an epigenetic effector protein has been generated by gene targeting and subsequently assaying miRNA expression would work toward identifying miRNA potentially under the influence of that particular epigenetic effector. miRNA expression itself may be assayed by the use of multiple complementary and comprehensive approaches including miRNA specific stem-loop reverse transcription followed by TaqMan realtime quantitative PCR as well as high-throughput sequencing based expression profiling on the Solexa 1G platform (summarized in Fig. 11.4). The combination of these two complementary and powerful approaches allows for both single base pair

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Fig 11.2 Potential action of multiple interacting and epigenetically influenced miRNA regulatory circuits involved in neuronal differentiation and/or stem cell function. Epigenetic regulation of various miRNA to different levels of expression, as represented by the different size of the “miRNA dots,” may work simultaneously to fine tune the expression levels of multiple mRNA targets, represented by the “mRNA spokes” overlapping the “miRNA dots.” Meanwhile, multiple protein products from connected “mRNA spokes” may work together within pathways, as represented by the central core connecting the “spokes,” driving stem cell function and/or neuronal differentiation. Also illustrated here, is the potential for overlap between these pathways themselves, or overlap of “spokes”. Therefore, the proper modulation of miRNA expression at an epigenetic level becomes critical to the proper simultaneous fine tuning of multiple mRNA targets within interacting pathways driving neuronal differentiation and influencing stem cell function

distinction of mature miRNA expression as well as detection of miRNA with very low abundance as a result of the high sensitivity of PCR based approaches and use of deep sequencing of cloned small RNA. As a demonstration of the use and practicality of such approaches we have examined the alterations in mir-124a expression in proliferating, undifferentiated NSPCs as well as NSPCs subjected to a neuronal differentiation protocol (Figs. 11.3, 11.5). As can be seen in Fig. 11.5 cells can be efficiently isolated, cultured, and differentiated as assessed by the presence or absence of cell type specific markers. After collecting both undifferentiated and differentiated cells and isolating total RNA we could observe clear increases in mir-124a expression by TaqMan miRNA specific real-time PCR. This correlates quite well with previously published data and provides evidence for the practicality of using such technologies and primary cell culture techniques in determining the epigenetic and miRNA components of stem cell function.

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Fig 11.3 Scheme for isolation of NSPCs from adult mouse brains and analysis of neurogenesis in vitro and in vivo. A.) Schematic drawing demonstrating the protocol for isolation, culture, and in vitro analyses of adult NSPCs. We use both bulk culture and clonal assays to determine the two basic properties of adult NSPCs: self renewal and multipotency. B.) Experimental setup for in vivo cell proliferation analyses (Group I), single dose of BrdU was injected into adult mice (about 10 weeks of age), and mice will be analyzed at 6 hours post-injection. For in vivo newborn cell survival and differentiation analysis (Group II), mice will be given daily BrdU injections for 7 days and analyzed at 4 weeks after the last injection

11.3

Discussion

Establishment of cell type specific systems is imperative toward understanding epigenetic mechanisms contributing to control and function of stem cells. Here we have described previously established procedures for isolating and culturing adult neural stem cells in order to assay epigenetic regulation associated with neurogenesis. Furthermore, within this particular context the application of determining miRNA expression profiles in order to identify key miRNA involved in the maintenance/selfrenewal and differentiation of adult NSPCs was provided. Using this framework, we propose that it may then be possible to overlay additional molecular and genetic variables, in particular those concerned with epigenetic mechanisms, in order to further identify epigenetic and miRNA related regulatory pathways critical to proper stem cell function. Identification of such regulatory pathways may in fact prove to be central to stem cell biology since the epigenetic regulation miRNA, which themselves can regulate multiple mRNA transcripts, would provide an efficient means by which stem cells may efficiently, dynamically, and accurately fine tune their own function. Additionally,

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~15-30nt PAGE purified small RNA

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8 Pools of 4848-Plex RT

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3’ adaptor ligation Reverse transcription and minimal PCR amplification

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Application to flow cell surface and cluster formation by bridge amplification

~365 assays

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Sequence individual clusters within flow cell using reversibly terminated fluorescently labeled nucleotides

Fig 11.4 miRNA expression profiling. A.) miRNA specific TaqMan assays are characterized by the use of miRNA specific stem-loop reverse transcription primer followed by miRNA specific TaqMan real-time PCR. This allows for full coverage of mature miRNA sequence in a highly sensitive PCR based assay. The reverse transcription reaction has currently been adapted to a 48plex, where pools of 48 miRNA specific reverse transcription primers are used within a single reaction to simultaneously reverse transcribe 48 miRNA. Using multiple pools of 48-plex reverse transcription allows for the throughput to then be scaled up. cDNA may subsequently be loaded into inidividual miRNA specific TaqMan assays. Current technology provides 8 pools of 48-plex reverse transcription primers that are followed by ~365 miRNA specific assays. B.) High-throughput sequencing based expression profiling of small RNA on the Solexa 1G platform. 5’ and 3’ RNA adaptors are ligated sequentially to gel purified ~15-30nt small RNA. Small RNA with adaptors ligated are reverse transcribed using primers complementary to the known adaptor sequence and subsequently amplified by PCR at a low cycle number in order to maintain relative abundance of individual cDNA molecules. PCR amplified cDNA molecules are then attached to the surface of a flowcell on which DNA oligos complementary to the adaptor sequences are already attached. The presence of these complementary oligos allows for the amplification of individual cDNA molecules in clusters through a process called bridge amplification. After generation of clusters, sequencing reactions are processed directly on the surface of the flowcell in a directional manner based upon the known adaptor sequence and using reversibly terminated fluorescently labeled nucleotides. Currently, flowcells contain 8 individual lanes in which independent experiments may be performed. Current read lengths are of ~27-32 bases on this platform, making it ideal for sequencing of small RNA in the 15-30nt range

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A

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relative quantity (2^-ddCt)

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5.5 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0

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Fig 11.5 Analysis of neurogenesis in vitro and in vivo with TaqMan based miRNA expression determination. A.) A primary neurosphere derived from NSPC of adult mouse brain; B.) NSPCsderived neurospheres contain mostly nestin+ immature cells. Green, nestin; blue: DAPI; scale bar=50 µm; C.) A single neurosphere can be differentiated into both TuJI+ immature neurons (red) and S100β+ astrocytes (not shown); D.) An example of using BrdU-labeling for assessing proliferation levels of bulk cultured NSPCs. Red, BrdU; Blue, DAPI; scale bar=10 µm. E.) Primary adult mouse NSPCs can be differentiated into both neurons (TuJ1+, green) and astrocytes (GFAP+, red) (Blue, DAPI). F.) Use of TaqMan base miRNA real-time PCR for a representative microRNA, mir124a, found to have increased expression upon differentiation of cultured NSPCs. G-J.) Sample confocal images from neurogenesis analyses of adult mice using immunofluorescent staining (red, BrdU; green: NeuN; Blue, GFAP). H.) A new neuron that is BrdU+ and NeuN+; I.) A new astrocyte that is BrdU+ and GFAP+; J.) Proliferating cells in adult DG that are Ki67+ (red). (Blue, DAPI) (Scale bars in g=200 µm, in h-j: 10 µm)

employing mechanisms of epigenetic control may also provide a means by which stem cells could respond to extrinsic or environmental cues to respond, transfer, and fix information onto the genome so that proper function may be carried out.

11.4

Materials and Methods

11.4.1

Stem Cell Systems/Adult Neural Stem Cells

11.4.1.1

In Vitro and In Vivo Cell Proliferation Assay

Proliferation may be analyzed with BrdU and Ki67 labeling in vivo and in vitro. The thymidine analog bromodeoxyuridine (BrdU) is able to incorporate into DNA during the S-phase of the cell cycle, and therefore is detectable by immunohistochemistry [55].

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Ki67 is a protein expressed during all active phases of the cell cycle, late G1 to M phase, but is undetectable in quiescent cells (G0 phase). Total cell number can be determined with 4′, 6-diamidino-2-phenylindole (DAPI) staining. For in vitro study, BrdU can be administrated into culture medium for several hours, for example, 5 µM for 16 h. For in vivo assay, BrdU is dissolved in 0.9% sodium chloride/7 mM NaOH, and injected intraperitoneally. The dose and administration time should be decided by the goals of study. For example, animals could be pulsed with three consecutive BrdU injections with 2 h interval and then sacrificed at 12 h post-BrdU injection to determine in vivo cell proliferation.

11.4.1.2

In Vivo NSC Differentiation Analyses

To determine differentiation of new cells in adult brains, animals receive multi-day injections for 4–7 days, followed by analyses at 4-weeks post-injection due to the 2–4 weeks normally were required for new neurons to become mature.

11.4.1.3

In Vitro NSC Self-Renewal Analyses

Self-renewal properties of NSPCs can be determined using a clonal assay [41, 44, 45]. Briefly, single primary neurospheres derived from adult brains are dissociated into single cells by trituration with a fire-polished Pasteur pipette in the presence of small amount of trypsin-EDTA and filtered through a 40 µm cell filter. Cells are then diluted and plated at one cell/well in a 96 well tissue culture plate in DMEM/ F12 medium supplemented with 20 ng/ml FGF-2 and EGF and 25% conditioned medium. Conditioned medium is obtained by collecting and filtering the culture medium from confluent bulk culture of adult NSPCs. The numbers of wells with cells that are able to proliferate and generate secondary spheres can be quantified under a bright field microscope. The self-renewal ability of subsequent generations of neuropheres can then be determined using the similar method. The proliferation index of each clone is then analyzed (see proliferation assay).

11.4.1.4

In Vitro Multipotency and Fate Analyses

Multipotency can be assessed with in vitro differentiation [63]. Briefly, cultured NSPCs are plated onto Polyornithine and laminin coated coverslips in a 24-well plate at a density of 5 × 104 cells/coverslip in DMEM/F-12 medium containing 5 µM Forskolin, 1 µM Retinoic acid and differentiated for 4–7 days. To perform the immunocytochemistry, cells are fixed with 4% paraformaldehyde for 30 min and washed with Phosphorylated Buffered Saline pH 7.4 PBS for 30 min. After washing with PBS, cells are then blocked using PBS with 5% normal goat serum, 0.1% Triton X-100 for 30 min, followed by overnight incubation with different primary antibodies at 4 °C. To detect neurons, the markers should be neuron-specific type III-tubulin (Tuj1) and Doublecortin (DCX). Glial fibrillary acidic protein (GFAP)

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and O4 could be used to label astrocytes and oligodendrocytes, respectively. On the second day, appropriate secondary antibodies are applied to the cells, and the total cell number is determined with a nuclear dye, such as DAPI.

11.4.2

miRNA Expression Profiling

11.4.2.1

miRNA Specific Reverse Transcription and Taqman Real-Time PCR

The method described is based upon protocols provided by Applied Biosystems, Inc. and are as described in [9]. Generally, total RNA can be isolated from wildtype proliferating and differentiated NSPCs using TRIzol reagent, washed well in 70% ethanol and resuspended in RNase free H2O. However, it also common to use any one of a number of methods that enrich for small RNA populations <100 nts so as to potentially increase the sensitivity of miRNA detection in the assay. Enrichment may allow for the possibility of introducing the loss of some quantitative information during the additional isolation procedure. Ten nanograms of total RNA is reverse transcribed using miRNA specific stem-loop reverse transcription primers. Current technology also allows for the multiplexing of the reverse transcription step, where pools of 48 miRNA specific reverse transcription primers are used to simultaneously reverse transcribe each of the 48 miRNA in a single reaction. cDNA is then loaded equally into individual miRNA specific TaqMan assays. Samples to be compared for relative expression are run in parallel with each TaqMan assay run in triplicate. Cts are normalized to U6 snRNA and relative quantities for each miRNA are calculated using the ∆∆Ct method.

11.4.2.2

Solexa 1G Sequencing Based Small RNA Expression Profiling

This method begins similarly to that originally described by multiple groups for cloning miRNA [25, 28, 29] and is then adapted for use of cloned small RNA in a high-throughput sequencing reaction. Greater than or equal to 10 ug TRIzol isolated total RNA is used to clone PAGE size fractionated small RNA (∼15–30 nt) by sequential ligation of 5′ and 3′ RNA adaptors using T4 RNA ligase. Adaptor ligated small RNA are reverse transcribed, PCR amplified for ∼15 cycles, and sequenced using a primer complementary to the 5′ adaptor sequence and reversibly terminated fluorescently labeled nucleotides on the Solexa 1G platform by Illumina, Inc. All sequence tags used in expression analysis are comprised completely of bases with a quality score of ≥ 10 (phred score equivalent). Reads of unique tags are collapsed and trimmed of sequence corresponding to the 3′ adaptor. Sequences matching ≥ 6 nt of the 5′ adaptor may also be removed from further consideration so as to eliminate sequences obtained from cloning of the 5′ adaptor. The remaining unique tags ≥ 15 nt long having ≥ 3 reads are mapped to the most recent NCBI Build of the

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mouse genome sequence and are also compared to all Mus musculus stem-loop miRNA sequences in the latest version of miRBase using the BLAST algorithm. Sequences may be compared to any annotated sequence database in a similar manner. Those sequences that are read ≥ 3 times and having full-length ungapped perfect matches to a reference sequence set may then be used for identification of differentially expressed small RNA.

References 1. Allan AM, Liang X, Luo Y, Pak C, Li X, Szulwach KE, Chen D, Jin P, Zhao X (2008) The loss of methyl-CpG binding protein 1 leads to autism-like behavioral defects. Human and Molecular Genetics, Advance Access doi:10.1093/hmg/ddn102. 2. Babak T, Zhang W, Morris Q, Blencowe BJ, Hughes TR (2004) Probing microRNAs with microarrays: tissue specificity and functional inference. RNA 10:1813–1819. 3. Ballas N, Grunseich C, Lu DD, Speh JC, Mandel G (2005) REST and its corepressors mediate plasticity of neuronal gene chromatin throughout neurogenesis. Cell 121:645–657. 4. Barad O, Meiri E, Avniel A, Aharonov R, Barzilai A, Bentwich I, Einav U, Gilad S, Hurban P, Karov Y, Lobenhofer EK, Sharon E, Shiboleth YM, Shtutman M, Bentwich Z, Einat P (2004) MicroRNA expression detected by oligonucleotide microarrays: system establishment and expression profiling in human tissues. Genome Res 14:2486–2494. 5. Bernstein BE, Meissner A, Lander ES (2007) The mammalian epigenome. Cell 128:669–681. 6. Bird A (2002) DNA methylation patterns and epigenetic memory. Genes Dev 16:6–21. 7. Boyer LA, Lee TI, Cole MF, Johnstone SE, Levine SS, Zucker JP, Guenther MG, Kumar RM, Murray HL, Jenner RG, Gifford DK, Melton DA, Jaenisch R, Young RA (2005) Core transcriptional regulatory circuitry in human embryonic stem cells. Cell 122:947–956. 8. Boyer LA, Plath K, Zeitlinger J, Brambrink T, Medeiros LA, Lee TI, Levine SS, Wernig M, Tajonar A, Ray MK, Bell GW, Otte AP, Vidal M, Gifford DK, Young RA, Jaenisch R (2006) Polycomb complexes repress developmental regulators in murine embryonic stem cells. Nature 441:349–353. 9. Chang TC, Wentzel EA, Kent OA, Ramachandran K, Mullendore M, Lee KH, Feldmann G, Yamakuchi M, Ferlito M, Lowenstein CJ, Arking DE, Beer MA, Maitra A, Mendell JT (2007) Transactivation of miR-34a by p53 broadly influences gene expression and promotes apoptosis. Mol Cell 26:745–752. 10. Chen C, Ridzon DA, Broomer AJ, Zhou Z, Lee DH, Nguyen JT, Barbisin M, Xu NL, Mahuvakar VR, Andersen MR, Lao KQ, Livak KJ, Guegler KJ (2005) Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res 33:e179. 11. Conaco C, Otto S, Han JJ, Mandel G (2006) Reciprocal actions of REST and a microRNA promote neuronal identity. Proc Natl Acad Sci USA 103:2422–2427. 12. Fujita N, Watanabe S, Ichimura T, Ohkuma Y, Chiba T, Saya H, Nakao M (2003a) MCAF mediates MBD1-dependent transcriptional repression. Mol Cell Biol 23:2834–2843. 13. Fujita N, Watanabe S, Ichimura T, Tsuruzoe S, Shinkai Y, Tachibana M, Chiba T, Nakao M (2003b) Methyl-CpG binding domain 1 (MBD1) interacts with the Suv39h1-HP1 heterochromatic complex for DNA methylation-based transcriptional repression. J Biol Chem 278:24132–24138. 14. He L, Thomson JM, Hemann MT, Hernando-Monge E, Mu D, Goodson S, Powers S, CordonCardo C, Lowe SW, Hannon GJ, Hammond SM (2005) A microRNA polycistron as a potential human oncogene. Nature 435:828–833. 15. He L, He X, Lim LP, de Stanchina E, Xuan Z, Liang Y, Xue W, Zender L, Magnus J, Ridzon D, Jackson AL, Linsley PS, Chen C, Lowe SW, Cleary MA, Hannon GJ (2007) A microRNA component of the p53 tumour suppressor network. Nature 447:1130–1134.

202

K. Szulwach et al.

16. Jaenisch R, Bird A (2003) Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat Genet 33 Suppl:245–254. 17. Jessberger S, Nakashima K, Clemenson GD, Jr., Mejia E, Mathews E, Ure K, Ogawa S, Sinton CM, Gage FH, Hsieh J (2007) Epigenetic modulation of seizure-induced neurogenesis and cognitive decline. J Neurosci 27:5967–5975. 18. Jones PA, Takai D (2001) The role of DNA methylation in mammalian epigenetics. Science 293:1068–1070. 19. Jorgensen HF, Ben-Porath I, Bird AP (2004) Mbd1 is recruited to both methylated and nonmethylated CpGs via distinct DNA binding domains. Mol Cell Biol 24:3387–3395. 20. Karres JS, Hilgers V, Carrera I, Treisman J, Cohen SM (2007) The conserved microRNA miR8 tunes atrophin levels to prevent neurodegeneration in Drosophila. Cell 131:136–145. 21. Kim J, Krichevsky A, Grad Y, Hayes GD, Kosik KS, Church GM, Ruvkun G (2004) Identification of many microRNAs that copurify with polyribosomes in mammalian neurons. Proc Natl Acad Sci USA 101:360–365. 22. Kim J, Inoue K, Ishii J, Vanti WB, Voronov SV, Murchison E, Hannon G, Abeliovich A (2007) A MicroRNA feedback circuit in midbrain dopamine neurons. Science 317:1220–1224. 23. Klose RJ, Bird AP (2006) Genomic DNA methylation: the mark and its mediators. Trends Biochem Sci 31:89–97. 24. Klose RJ, Sarraf SA, Schmiedeberg L, McDermott SM, Stancheva I, Bird AP (2005) DNA binding selectivity of MeCP2 due to a requirement for A/T sequences adjacent to methyl-CpG. Mol Cell 19:667–678. 25. Kuwabara T, Hsieh J, Nakashima K, Taira K, Gage FH (2004) A small modulatory dsRNA specifies the fate of adult neural stem cells. Cell 116:779–793. 26. Lagos-Quintana M, Rauhut R, Lendeckel W, Tuschl T (2001) Identification of novel genes coding for small expressed RNAs. Science 294:853–858. 27. Lagos-Quintana M, Rauhut R, Yalcin A, Meyer J, Lendeckel W, Tuschl T (2002) Identification of tissue-specific microRNAs from mouse. Curr Biol 12:735–739. 28. Landgraf P, Rusu M, Sheridan R, Sewer A, Iovino N, Aravin A, Pfeffer S, Rice A, Kamphorst AO, Landthaler M, Lin C, Socci ND, Hermida L, Fulci V, Chiaretti S, Foa R, Schliwka J, Fuchs U, Novosel A, Muller RU, Schermer B, Bissels U, Inman J, Phan Q, Chien M, Weir DB, Choksi R, De Vita G, Frezzetti D, Trompeter HI, Hornung V, Teng G, Hartmann G, Palkovits M, Di Lauro R, Wernet P, Macino G, Rogler CE, Nagle JW, Ju J, Papavasiliou FN, Benzing T, Lichter P, Tam W, Brownstein MJ, Bosio A, Borkhardt A, Russo JJ, Sander C, Zavolan M, Tuschl T (2007) A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 129:1401–1414. 29. Lau NC, Lim LP, Weinstein EG, Bartel DP (2001) An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science 294:858–862. 30. Lee RC, Ambros V (2001) An extensive class of small RNAs in Caenorhabditis elegans. Science 294:862–864. 31. Lee RC, Feinbaum RL, Ambros V (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75:843–854. 32. Lee TI, Jenner RG, Boyer LA, Guenther MG, Levine SS, Kumar RM, Chevalier B, Johnstone SE, Cole MF, Isono K, Koseki H, Fuchikami T, Abe K, Murray HL, Zucker JP, Yuan B, Bell GW, Herbolsheimer E, Hannett NM, Sun K, Odom DT, Otte AP, Volkert TL, Bartel DP, Melton DA, Gifford DK, Jaenisch R, Young RA (2006) Control of developmental regulators by Polycomb in human embryonic stem cells. Cell 125:301–313. 33. Lunyak VV, Rosenfeld MG (2005) No rest for REST: REST/NRSF regulation of neurogenesis. Cell 121:499–501. 34. Lunyak VV, Burgess R, Prefontaine GG, Nelson C, Sze SH, Chenoweth J, Schwartz P, Pevzner PA, Glass C, Mandel G, Rosenfeld MG (2002) Corepressor-dependent silencing of chromosomal regions encoding neuronal genes. Science 298:1747–1752. 35. Makeyev EV, Zhang J, Carrasco MA, Maniatis T (2007) The MicroRNA miR-124 promotes neuronal differentiation by triggering brain-specific alternative pre-mRNA splicing. Mol Cell 27:435–448.

11 Epigenetic Regulation of miRNA in Stem Cells

203

36. Mikkelsen TS, Ku M, Jaffe DB, Issac B, Lieberman E, Giannoukos G, Alvarez P, Brockman W, Kim TK, Koche RP, Lee W, Mendenhall E, O’Donovan A, Presser A, Russ C, Xie X, Meissner A, Wernig M, Jaenisch R, Nusbaum C, Lander ES, Bernstein BE (2007) Genomewide maps of chromatin state in pluripotent and lineage-committed cells. Nature 448:553–560. 37. Ming GL, Song H (2005) Adult neurogenesis in the mammalian central nervous system. Annu Rev Neurosci 28:223–250. 38. Miremadi A, Oestergaard MZ, Pharoah PD, Caldas C (2007) Cancer genetics of epigenetic genes. Hum Mol Genet 16 Spec No 1:R28–49. 39. Miska EA, Alvarez-Saavedra E, Townsend M, Yoshii A, Sestan N, Rakic P, Constantine-Paton M, Horvitz HR (2004) Microarray analysis of microRNA expression in the developing mammalian brain. Genome Biol 5:R68. 40. Molofsky AV, He S, Bydon M, Morrison SJ, Pardal R (2005) Bmi-1 promotes neural stem cell self-renewal and neural development but not mouse growth and survival by repressing the p16Ink4a and p19Arf senescence pathways. Genes Dev 19:1432–1437. 41. Moretti P, Zoghbi HY (2006) MeCP2 dysfunction in Rett syndrome and related disorders. Curr Opin Genet Dev 16:276–281. 42. Muotri AR, Chu VT, Marchetto MC, Deng W, Moran JV, Gage FH (2005) Somatic mosaicism in neuronal precursor cells mediated by L1 retrotransposition. Nature 435:903–910. 43. O’Donnell KA, Wentzel EA, Zeller KI, Dang CV, Mendell JT (2005) c-Myc-regulated microRNAs modulate E2F1 expression. Nature 435:839–843. 44. Plath K, Fang J, Mlynarczyk-Evans SK, Cao R, Worringer KA, Wang H, de la Cruz CC, Otte AP, Panning B, Zhang Y (2003) Role of histone H3 lysine 27 methylation in X inactivation. Science 300:131–135. 45. Reynolds BA, Weiss S (1996) Clonal and population analyses demonstrate that an EGFresponsive mammalian embryonic CNS precursor is a stem cell. Dev Biol 175:1–13. 46. Reynolds BA, Weiss, S. (1992) Generation of neurons and astrocytes from isolated cells of the adult mammalian central nervous system. Science 255:1646. 47. Rinn JL, Kertesz M, Wang JK, Squazzo SL, Xu X, Brugmann SA, Goodnough LH, Helms JA, Farnham PJ, Segal E, Chang HY (2007) Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs. Cell 129:1311–1323. 48. Sanchez-Elsner T, Gou D, Kremmer E, Sauer F (2006) Noncoding RNAs of trithorax response elements recruit Drosophila Ash1 to Ultrabithorax. Science 311:1118–1123. 49. Sarraf SA, Stancheva I (2004) Methyl-CpG binding protein MBD1 couples histone H3 methylation at lysine 9 by SETDB1 to DNA replication and chromatin assembly. Mol Cell 15:595–605. 50. Sempere LF, Freemantle S, Pitha-Rowe I, Moss E, Dmitrovsky E, Ambros V (2004) Expression profiling of mammalian microRNAs uncovers a subset of brain-expressed microRNAs with possible roles in murine and human neuronal differentiation. Genome Biol 5: R13. 51. Setoguchi H, Namihira M, Kohyama J, Asano H, Sanosaka T, Nakashima K (2006) MethylCpG binding proteins are involved in restricting differentiation plasticity in neurons. J Neurosci Res 84:969–979. 52. Shahbazian MD, Zoghbi HY (2002) Rett syndrome and MeCP2: linking epigenetics and neuronal function. Am J Hum Genet 71:1259–1272. 53. Shen S, Li J, Casaccia-Bonnefil P (2005) Histone modifications affect timing of oligodendrocyte progenitor differentiation in the developing rat brain. J Cell Biol 169:577–589. 54. Stanfield BB, Trice JE (1988) Evidence that granule cells generated in the dentate gyrus of adult rats extend axonal projections. Exp Brain Res 72:399–406. 55. Takizawa T, Nakashima K, Namihira M, Ochiai W, Uemura A, Yanagisawa M, Fujita N, Nakao M, Taga T (2001) DNA methylation is a critical cell-intrinsic determinant of astrocyte differentiation in the fetal brain. Dev Cell 1:749–758.

204

K. Szulwach et al.

56. Tang X, Falls DL, Li X, Lane T, Luskin MB (2007) Antigen-retrieval procedure for bromodeoxyuridine immunolabeling with concurrent labeling of nuclear DNA and antigens damaged by HCl pretreatment. J Neurosci 27:5837–5844. 57. Torres-Padilla ME, Parfitt DE, Kouzarides T, Zernicka-Goetz M (2007) Histone arginine methylation regulates pluripotency in the early mouse embryo. Nature 445:214–218. 58. Ueba T, Kaspar B, Zhao X, Gage FH (1999) Repression of human fibroblast growth factor 2 by a novel transcription factor. J Biol Chem 274:10382–10387. 59. Visvanathan J, Lee S, Lee B, Lee JW, Lee SK (2007) The microRNA miR-124 antagonizes the anti-neural REST/SCP1 pathway during embryonic CNS development. Genes Dev 21:744–749. 60. Wightman B, Ha I, Ruvkun G (1993) Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans. Cell 75:855–862. 61. Wu H, Xu J, Pang ZP, Ge W, Kim KJ, Blanchi B, Chen C, Sudhof TC, Sun YE (2007) Integrative genomic and functional analyses reveal neuronal subtype differentiation bias in human embryonic stem cell lines. Proc Natl Acad Sci USA 104:13821–13826. 62. Xiao C, Calado DP, Galler G, Thai TH, Patterson HC, Wang J, Rajewsky N, Bender TP, Rajewsky K (2007) MiR-150 controls B cell differentiation by targeting the transcription factor c-Myb. Cell 131:146–159. 63. Zhao X, Schaffer D, Gage F (2004) Neurogenesis in adult brain: understanding the mechanism and regulation. In: Stem cells in the Nervous System: Functional and Clinical Implications. Berlin, Heidelberg: Springer. 64. Zhao X, Ueba T, Christie BR, Barkho B, McConnell MJ, Nakashima K, Lein ES, Eadie BD, Willhoite AR, Muotri AR, Summers RG, Chun J, Lee KF, Gage FH (2003) Mice lacking methyl-CpG binding protein 1 have deficits in adult neurogenesis and hippocampal function. Proc Natl Acad Sci USA 100:6777–6782.

Chapter 12

Identification of Cellular Targets for Virally-Encoded miRNAs by Ectopic Expression and Gene Expression Profiling Mark A. Samols1, Rebecca L. Skalsky1, and Rolf Renne1*

Abstract Since the first report in 2005, more than 120 microRNAs (miRNAs) have been identified in many double stranded DNA viruses-mainly herpesviruses and polyomaviruses [12, 68, 69, 82, 92]. MiRNAs are short 22 ± 3 nt RNA molecules that post-transcriptionally regulate gene expression by binding to 3′ UTRs of target mRNAs thereby inducing translational silencing and/or mRNA degradation [1, 3]. Because miRNAs require only limited complementarity, miRNA targets are difficult to determine [24]. Indeed, to date targets have only been experimentally verified for miRNAs of three viruses. SV40 encodes a miRNA which targets viral large T antigen expression [92]. Several KSHV miRNAs target Thrombospondin 1, a potent inhibitor of angiogenesis [82]. In addition, one KSHV miRNA, miRK122-11, mimics a human miRNA, hsa-miR-155, involved in hematopoiesis and tumorigenesis. CMV miRNAs target both cellular and viral gene expression [31, 90]. Thus, virally encoded miRNAs regulate fundamental biological processes such as immune recognition, promotion of cell survival, and angiogenesis and may contribute to tumorigenesis. First, we briefly summarize our current knowledge on identification and expression of viral miRNAs with special emphasis on herpesviruses. Next, we will discuss our work on KSHV-encoded miRNAs to illustrate how viral miRNAs provide a unique opportunity for target identification, and the challenges lying ahead in deciphering their potential roles in viral biology, and pathogenesis.

Keywords KSHV, CMV, SV40, herpes simplex virus, viral miRNAs, miR-155, seed sequence, ectopic miRNA expression, gene expression profiling, 3′UTR cloning, B cell development

1 Department of Molecular Genetics and Microbiology and University of Florida Shands Cancer Center, University of Florida, 1613 Mowry Road, Gainesville, FL 32610, USA

*Corresponding author: Phone: (352) 273-8204; Fax: (352) 273-8299; E-mail: [email protected]

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Introduction MicroRNAs Regulate Fundamental Cell Processes in All Metazoans

The first miRNA, lin-4 of C. elegans, was found through analysis of a strong developmental timing defect. The responsible gene, lin-4, did not contain an ORF, and instead only expressed two short transcripts of 60 and 24 nucleotides in length. It was subsequently shown that the lin-4 RNA was involved in translationally silencing of the lin-14 transcript by binding to complementary sequences within the lin14 3′UTR [45, 79, 97, 98]. This novel RNA based inhibition was specific to C. elegans until the discovery of the let-7 miRNA, which was found to be conserved in many metazoan cells, including humans and flies [65, 75, 89]. Currently, over 600 different human miRNAs are known (http://microrna.sanger.ac.uk/ sequences/) [32]. MiRNAs have been isolated from every metazoan and plant species tested thus far, and according to estimates, around 30% of all metazoan miRNAs are conserved between species [48]. The major function of miRNAs appears to be regulation of cellular gene expression through translational inhibition and mRNA degradation. However, recent examples have been described by which miRNAs act as positive regulators when bound together with other 3′UTR binding complexes [47]. To date, relatively few metazoan miRNAs have been functionally characterized, most of them by forward genetics. Of the known human miRNAs, only 66 have experimentally verified targets [87] – however, the few examples where functions are known and the rapidly ongoing identification of new targets show that miRNAs regulate fundamental processes during development and differentiation and that miRNA expression is tightly regulated in both a spatial and temporal manner [1, 3].

12.1.2

MicroRNA Biogenesis and Function

MiRNAs, expressed from pol II transcripts can occur individually or be organized into clusters and they can exist as stand-alone genes or embedded within the introns and exons of protein coding transcripts (for review see [1, 3, 64]). Biogenesis of metazoan miRNAs begins with formation of an imperfect stem loop that forms in one RNA transcript termed the pri-miRNA (Fig. 12.1) [35, 46]. The dsRNA region of the pri-miRNA is recognized by DGCR8 (Pasha in flies) which recruits the endonuclease Drosha to cleave and release a 60 to 80 nt long hairpin [46, 103]. This pre-miRNA is then exported to the cytoplasm by the Exportin 5/RAN-GTPase pathway, where it is recognized by Dicer and cleaved to leave a short dsRNA molecule [46]. One strand of this dsRNA product is loaded by Dicer and the dsRNA binding protein TRBP (also known as R2D2 in flies and RDE-4 in nematodes) into the RNA-induced silencing complex (RISC) [42, 53]. RISC functions by binding to semi-complementary sites

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Degradation (siRNA like) Fig. 12.1 Biogenesis pathway for metazoan miRNAs. MiRNA precursors begin as hairpin loops in pol II or pol III transcripts in introns or exons. After Pasha binding (not depicted), Drosha cleaves leaving a ~80 bp stem loop which is exported into the cytoplasm. Dicer cleaves off the loop structure leaving a 21–24 nt dsRNA molecule. The miRNA is incorporated into the RISC where it binds to the 3′UTR of target transcripts and induces either translational silencing or transcriptional degradation depending on the level of complementarity. The seed sequence of the miRNA, nts 2 through 8, is known to be a critical component of target recognition and binding [1, 34, 48, 49]

within the 3′UTRs of target transcripts and induces translational silencing and/or siRNA-like degradation [24]. Critically important for binding is seed sequence complementarity of nts 2 to 7 of the mature miRNA – as a consequence a single miRNA can target multiple targets with varying affinity. After binding of RISC to the 3′UTR

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of the target transcript, silencing is accomplished through a yet not fully deciphered mechanism(s). Current evidence suggest several different mechanisms: inhibition of translational initiation by interfering with the interaction of eIF4E, eIF6E, and the poly A binding protein [37, 70], premature termination of translation by inducing ribosomal drop off following initiation [56, 67], and messenger RNA degradation by translocation of RISC-associated mRNAs to cytoplasmic Processing (P)-bodies which contain the RNA degradation machinery [17, 27, 86].

12.1.3

Interactions of Viruses and miRNAs

Plants express several classes of siRNAs some of which are dedicated to confer strong anti-viral immunity. Two of the four isoforms of the Dicer (DCL) proteins in plants are responsible for generating anti-viral siRNAs during viral infections [6, 101]. Similar pathways have been found in D. melanogaster and C. elegans [55, 96, 99]. All of these pathways involve the use of an RNA-dependent RNA polymerase (RDRP) to generate double stranded RNA that, after cleavage by Dicer, produces siRNAs to degrade viral sequences. Not surprisingly, viruses have learned to evade these mechanisms by evolving proteins that potently inhibit the siRNA pathway. For example, the B2 protein of Flock house virus (FHV), an insect nodavirus, binds to dsRNA with high affinity thereby preventing cleavage by Dicer and the generation of siRNA [51]. Alternatively, P38 of the Turnip crinkle virus (TCV) directly inhibits a Dicer isoform (DCL4) [71]. In contrast, mammalian cells contain single copies for both Drosha and Dicer and do not encode RDRPs. There has been one report showing that human miR-32 can inhibit the replication of primate foamy virus type 1 (PFV-1) through binding to the F11 sequence of the virus [44]. However, this is probably not a dedicated anti-viral mechanism in mammalian cells as the miR-32 ability to bind and target PFV-1 is thought to be fortuitous and is not the primary role of miR-32 [44]. Conversely, there has also been one report of positive regulation of virus replication by a cellular miRNA. Rather than suppression, miR-122, a liver-specific miRNA, enhances replication of hepatitis C virus (HCV) [41]. Two miR-122 binding sites are located in the HCV genome, one in the 3′non-coding region (NCR) and the other in the 5′NCR. Mutation of the 5′NCR binding site abolished HCV replication, indicating that binding of miR-122 to the HCV genome is required for replication, presumably by preventing formation of a specific secondary structure within the HCV genome [44]. Additionally, a recent report by Pedersen et al. showed that HCV sensitivity to IFN-β may in part be conveyed by up-regulation of cellular miRNAs directly targeting HCV RNA [66].

12.1.4

DNA Viruses, such as Herpesviruses, Encode miRNAs

In 2004, Pfeffer et al. opened a new field in virology by reporting the cloning and identification of five miRNAs from Epstein Barr virus (EBV). Three miRNAs are

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located in the BHRF region and two miRNAs in the BART region of EBV [69]. The possibility that viral miRNAs could regulate hundreds of target genes suggests a novel and extremely complex level of host/virus interaction. To date, more than 110 miRNAs have been identified in 12 different DNA viruses (Table 12.1, Fig. 12.2). In 2005, three independent groups cloned miRNAs from Kaposi’s sarcomaassociated herpesvirus (KSHV)-infected primary effusion lymphoma cells (PEL), and identified 11 miRNA genes [12, 68, 82]. Surprisingly, all KSHV miRNAs are located within the major latency-associated region of the genome with 10 miRNA genes organized in a single cluster. Two additional miRNAs are located within K12 open reading frame [33]. A combination of tiled arrays and cloning identified 15 additional EBV miRNAs, located within the 12 kb deletion specific to the B95-8 strain analyzed in the previous study [72] and 3 more within the BART region outside of the B95-8 deletion [13, 33]. Cai et al. also reported 16 miRNAs within the EBV-related Rhesus lymphocryptovirus (LCV), 8 of which are conserved to EBV [13]. Recently, Schafer et al. reported seven miRNAs within the Rhesus Rhadinovirus (RRV), a γ-herpesvirus closely related to KSHV [84]. Like KSHV, RRV miRNAs are located within the latency-associated region of RRV; however, their sequences seem not to be evolutionary conserved. Murine γ-herpesvirus type 68 (MHV68) encodes nine miRNAs which are located within transfer RNA-like genes at the 5′end of the genome [68]. In α-herpesviruses, 13 miRNAs have been predicted and 1 verified in Herpes simplex virus (HSV-1) [9, 18]. Burnside et al. used 454 deep sequencing to identify eight miRNAs from Marek’s disease virus type 1 (MDV-1), which map to the inverted repeat short and long regions (IRs and IRL). Five of these miRNAs flank the meq oncogene and the remaining three map to the LAT region of MDV-1 [9]. Conventional miRNA cloning revealed 17 miRNAs within the closely related MDV2 virus, 16 of which were clustered [102]. Within β-herpesviruses, nine miRNAs were identified from human cytomegalovirus (HCMV), scattered throughout the viral

Table 12.1 Verified known viral miRNAs. *HSV-1 miRNAs have been predicted or demonstrated by Northern blotting but have not been molecularly cloned Viral family Virus pre-miRNA hairpins Reference α-Herpesviruses* β-Herpesvirsues γ-Herpesviruses

Polyomaviruses Hepadnaviruses

HSV-1 MDV-1 MDV-2 HCMV EBV LCV RRV KSHV MHV-68 SV40 SA12 HBV

1 *(8–13) 8 17 12 17 15 7 12 9 1 1 1

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Fig. 12.2 Schematic representation of miRNAs found for several herpesviruses. Genomes are represented for HSV-1, MDV, HCMV, EBV, LCV, RRV, KSHV and MHV-68 with black arrows for ORFs, black triangles for tRNA genes, and black bars or rectangles for repeat sequences. MiRNA locations are indicated with orange arrows. Genomes are not drawn to scale. MDV-1 is depicted, MDV-2 contains nine additional miRNAs within its IRs and IRL region [102]. Figure was compiled from [9-33, 68, 69, 82, 102]. *Indicates that no HSV-1 miRNAs have been cloned, only one has be verified by Northern blot analysis [18]

genome [68]. Dunn et al. cloned a previously unreported miRNA and Grey et al. used a bioinformatics approach to predict conserved hairpins between HCMV and chimpanzee CMV [25, 30]. They predicted and confirmed two new HCMV miRNAs for a current total of 12 HCMV miRNAs. These studies also illustrate that bioinformatics approaches alone are not reliable tools for the identification of miRNAs. Outside the herpesvirus family, two miRNAs resulting from a single hairpin were identified within the 3′UTR of the SV40 late transcript [92]. Positional homologues of these SV40 miRNAs were also isolated from SA12 infected cells, and furthermore, have been predicted to exist in BK and JC viruses [15]. One additional miRNA was predicted in hepatitis B virus (HBV) within the

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precore/core gene; however, robust expression data or cloning approaches have not been presented [38]. Human Papillomavirus 31 (HPV31) was examined by Cai et al. but no miRNAs were identified through cloning attempts [11]. Hence, while common in herpesviruses, miRNA-encoding genes appear to be rare in other virus families. Currently, there are somewhat conflicting reports on whether Retroviruses encode miRNAs and/or whether they encode proteins which inhibit the RNAi machinery. The Nef gene of HIV has been hypothesized to encode a miRNA [62, 63]. However, these small RNAs may originate from Dicer processing of the overlap between the Nef transcript and the U3-R end of the viral genome, as no valid hairpin structure has been demonstrated for the proposed miRNA [5, 62, 63, 68]. In addition to encoding miRNAs, it was also suggested that the HIV Tat protein inhibits the RNAi pathway through binding and inactivation of Dicer [4]. However, a recent study by the Cullen lab could not confirm the anti siRNA activity of HIV tat nor could detect similar activities associated with transcriptional regulators of other retroviruses, such as HTLV-1 and PFV-1 [52]. However, Sullivan and Ganem demonstrated that Nodumura virus (NoV), a small RNA virus, which infects insects and vertebrates, encodes a protein, which in analogy to many plant viruses, strongly inhibits RNA interference. The NoV B2 protein binds to Dicer substrate RNAs and interacts with RISC, thereby completely blocking Dicer-dependent siRNA and miRNA formation both in vivo and in vitro [91]. Together, these findings suggest that the RNA silencing machinery is detrimental to RNA virus replication which makes it unlikely that HIV encodes miRNAs. Accordingly, Pfeffer et al. were unable to clone miRNAs from cells infected with either hepatitis C virus, yellow fever virus, or HIV [68], and there have been no other reports of miRNAs being predicted and verified in other RNA viruses. Thus it appears as if miRNAs are a DNA virusspecific phenomenon.

12.1.4.1

KSHV miRNA Are Expressed from a Single Genomic Location During Latent and Lytic Replication

KSHV miRNAs are clustered in one location, the KSHV latency-associated region (KLAR), which encodes four genes expressed from multiple promoters during latent and lytic replication [12, 68, 82]. The latency-associated nuclear antigen (LANA), v-Cyclin, v-Flip, and Kaposin (K12) all contribute to viral latency by regulating viral and cellular gene expression and supporting DNA replication and episomal maintenance. Additionally, some of these genes are expressed during lytic replication [2, 28, 29, 59, 60, 72, 76]. KSHV miRNAs are readily detectable by Northern blot analysis in KSHV latently infected and lytically reactivated PEL cells [12, 33, 68, 82] implying that KSHV miRNAs are expressed during both stages of the virus life cycle. Interestingly, transcripts originating from the beginning of this loci have been shown to over-read a polyA signal thereby producing primary transcripts which can give rise to protein expression as well as miRNA expression [10]. The complexity of this genomic loci is depicted in Fig. 12.3.

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Fig. 12.3 The KSHV latency-associated region (KLAR) expresses miRNAs from multiple transcripts. Orange lines represent hn-pre-mRNAs expressed from all four promoters within the KLAR region. *The polyA-side downstream of v-Flip is frequently over-read, which leads to transcripts encompassing the entire region [10]. These transcripts originate from either LANAp or LTi during latent and lytic replication (J. Hu and R. Renne, 2007). Below shown in black are latency-associated transcripts mapped prior to the identification of KSHV miRNAs. Figure was compiled from [10, 21, 50, 57, 80, 93]

12.2 12.2.1

Results After Identifying KSHV miRNAs, the “Big” Question Is: What Do They Regulate?

During the last two years, we have concentrated on experimental, rather than bioinformatics-based strategies to identify a set of human genes that are targeted by these novel regulators of gene expression. In the following section, we will summarize these data and discuss both opportunities and challenges associated with these experiments. Viral miRNAs provide a unique opportunity to examine miRNA targets and functions in mammalian cells. Compared with the more than 600 miRNAs known in humans, the number of virally encoded miRNAs is relatively small (10 to 20 per herpesvirus). The fact that they are not expressed in non-infected cells provides a model system in which the overall complexity of the viral miRNA regulatory network is greatly reduced, thus being more amenable to biochemical analysis. Since most viral miRNAs are not highly conserved or related to their metazoan counterparts, viral miRNAs can be ectopically expressed without having to otherwise mutate or genetically modify cells. Viral miRNAs are also unique in that there are two potential groups of targets: (i) cellular transcripts to modulate the host cellular environment, or (ii) viral transcripts. We choose initially to concentrate on identifying cellular target genes by ectopic viral miRNA expression (Fig. 12.4). This simple strategy provides a perfect negative control (cells not expressing viral miRNAs) and importantly results are not hampered by the numerous known viral gene products that modulate host cellular gene expression such as LANA, v-cyclin, and v-Flip [2].

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Fig. 12.4 Ectopic expression of miRNAs and gene expression profiling to identify targets. (A) Schematic diagram of the latency associated region in the KSHV genome. The black bar indicates the miRNA cluster containing 10 KSHV miRNA genes that were inserted into expression vector. (B) Northern blot analysis of KSHV miRNAs in 293 pmiRNA cluster cells versus 293 pcDNA control cells and BCBL-1 cells. Thirty micrograms of total RNA was loaded and hybridized to a probe for miR-K12-1. Ribosomal RNA shown as a loading control. (C) miRNA responsive gene expression profiles. Colors represent changes in variance normalized gene expression differences for individual genes represented by the probe sets as indicated on the color scale. The dendrogram denotes the relative relationship among the significant probe sets (p < 0.001) among the eight samples (Modified from [83])

12.2.2

Techniques to Determine miRNA Targets

There are two main approaches to determine miRNA targets: predicting targets using bionformatics, or experimentally identifying miRNA targets. Several algorithms have been developed to predict miRNA binding sites through scanning of 3′UTR libraries [8, 48, 49, 81]. Predicting miRNA targets is complicated by the fact that miRNAs require only limited complementarity for 3′UTR binding [3, 7, 49]. Consequently, a single miRNA can modulate expression of multiple genes. Analysis of the entire human transcriptome in silico in combination with experimental verification mostly by gene expression profiling has revealed that binding of a miRNA to a specific 3′UTR is critically dependent on 5′ nucleotides 2 to 7 of the mature miRNA. Recently, Grimson et al. reported on a set of criteria, which further contribute to the affinity by which a miRNAs bind to target mRNAs [34]. It is also important to note that many 3′UTRs contain multiple binding sites for a specific miRNA, and a single mRNA can be targeted by multiple miRNAs [7, 26, 49]. As a result, miRNAs constitute a large post-transcriptional regulatory network with the ability to control complex processes such as development and cell differentiation [48, 49].

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John et al. used miRanda with 218 human miRNAs and predicted over 2,000 potential targets [40]. Thus computer-based target predictions provide a useful start, but clearly need to be experimentally validated by directly demonstrating either mRNA degradation or translational silencing. Using microarrays for gene expression profiling provides an efficient method to determine which cellular transcripts are up- or down-regulated in response to miRNA expression. In addition, either microarrays containing viral probe sets or genome wide qRT-PCR assays, which have been developed for all human herpesviruses [22, 23], are available to investigate whether viral miRNAs target viral gene expression. Observed transcriptional repression or decreased protein levels may be due to secondary effects. Therefore, for target verification, miRNA binding should be functionally confirmed within a 3′UTR of each candidate target gene. The most commonly used method is to introduce 3′UTRs downstream of a luciferase reporter and demonstrate miRNA-dependent repression. This can be confirmed through mutational analysis of identified seed-match binding sites. Based on these criteria to date, targets for about 70 out of more than 600 described human miRNAs have been identified (http://microrna.sanger.ac.uk/cgi-bin/targets/ v5/known_targets.pl).

12.2.3

Few Targets for Virally-Encoded miRNAs Have Been Identified

To date, only few studies have reported on virally encoded miRNA-dependent silencing of target genes (Table 12.2). First, the SV40 miRNAs, located within the 3′UTR of the late transcript, target and efficiently degrade early transcripts encoding the large T antigen [92]. As a result large T antigen expression is down-regulated after DNA replication has been completed. Furthermore, Sullivan et al. showed that cells were more efficiently lysed in cytotoxic T-cell assays when infected with a genetically engineered miRNA-minus virus, strongly suggesting that these miRNAs function to reduce immune recognition.

Table 12.2 Experimentally verified viral miRNA targets Virus Targets Reference SV40 HCMV KSHV

Large-T antigen MICB Viral IE genes SPP1 PRG1 THBS1 BACH-1 LDOC1 MATR3 TM6SF1

[92] [90] [31] [83] [83] [83] [88] [88] [88] [88]

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Unlike “classical” miRNAs the SV40-encoded small RNAs have 100% sequence complementarities towards their target, hence they function like siRNAs, which induce rapid mRNA degradation. While there are still many open questions with respect to the mechanism(s) by which miRNAs regulate gene expression, recent work clearly indicates that translational inhibition in many cases is followed by mRNA decay. Hence, genome-wide transcriptional profiling in miRNA gain of function or loss of function mutants provides an efficient first step in identifying miRNA targets (for review [61, 100]). Stern-Ginossar et al. used bioinformatics prediction to identify the major histocompatibility complex class I-related chain B (MICB) as major target for hcmv-miR-UL112 which was confirmed by 3′UTR cloning and mutagenesis. Importantly, it was shown that HCMV infection results in potent down-regulation of MICB which represents a novel T cell immune evasion mechanism [90].

12.2.4

Identification of Host Genes Targeted by KSHV-Encoded miRNAs

Recently, our laboratory stably expressed the KSHV miRNA cluster, encoding 10 of the 12 KSHV miRNA genes, in 293 cells and performed gene expression profiling [83]. Sixty-five genes (80%) out of 81 affected were down-regulated in the presence of KSHV miRNAs. While the majority of changes were below twofold, eight genes were down-regulated between 4- and 20-fold. MiRNAs were expressed from CMV promoters using puromycin selectable plasmids. To avoid effects of integration, we performed the analysis on cell populations rather than single cell clones. After performing both biological and experimental replicates observed gene changes were highly consistent across arrays. Importantly, experiments were performed under conditions where miRNAs are expressed at physiological copy numbers. The latter can be problematic when using miRNA mimics, which also can trigger innate immune responses, instead of endogenous expression strategies using either plasmid vectors or retroviral transduction. To distinguish direct from down-stream targets a confirmatory analysis is required. Using bioinformaticsbased target prediction can be used to identify putative miRNA binding sites within 3′UTRs of altered genes. Additionally, miRNA-regulation can be studied by luciferase reporters containing 3’UTR sequences of candidate genes. Finally, observed targets should also be regulated at the protein level. In our study, SPP1, PRG1 and THBS1 were verified to be targets of the viral miRNAs using luciferase reporter constructs containing the 3′UTRs of these three genes. Additionally, protein levels of THBS1 were decreased >10-fold in KSHV miRNA expressing cells. THBS1 has previously been reported to be down-regulated in KS lesions and is known to be a strong tumor suppressor and anti-angiogenic factor, exerting its anti-angiogenic effect in part by activating the latent form of TGF-β [19, 43, 85, 94]. Reduced THBS1 expression in the presence of viral miRNAs also translated into decreased TGF-β activity.

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Additional targets, SPP1 and PRG1, are known to be involved with cell-mediated immunity and apoptosis, respectively [73, 74, 78]. While these findings need to be confirmed in additional cell types relevant to KSHV biology, such as endothelial or lymphoid cells, they strongly suggest that KSHV-encoded miRNAs may contribute to viral pathogenesis by promoting angiogenesis (a hallmark of KS tumors) and by inhibition of cellular immunity and apoptosis. Interestingly, genes altered in the presence of KSHV miRNAs harbor seedsequence matches for multiple viral miRNAs in their 3′UTRs, suggesting that viral miRNA clusters coordinately regulate host cellular target genes [82, 83]. These initial studies suggested that KSHV miRNAs, like their metazoan relatives, modulate cellular target genes with varying complementarity in their 3′UTRs; whether KSHV miRNAs may also target viral transcripts in a miRNA-mediated manner is not yet known. However, Grey et al. demonstrated that two HCMVencoded miRNAs target immediate early transcripts whose regulation is likely involved in the transition from latent to lytic replication [31].

12.2.5

KSHV Encodes an Ortholog of miR-155

Yet another theme on how virally-encoded miRNAs may function to manipulate host cells is to mimic cellular miRNAs. With this respect, several groups including us have realized that a small set of virally-encoded miRNAs show seed sequence homology with human miRNAs. Intriguingly, the highest conservation was observed between the KSHV miR-K12-11, and hsa-miR-155 and EBV-BART5 and hsa-miR-18a, a member of the 17/92 miRNA cluster. Both miR-155 and the miR17/92 cluster have been reported to be overexpressed in a variety of human malignancies including lymphomas. Additionally, both were the first miRNAs for which a direct role in transformation was demonstrated in transgenic mice [16, 36]. Furthermore, miR-155 is an important regulator for hematopoiesis and in particular, was shown to be a central regulator of B cell development [77, 95]. Hence, we hypothesized that miR-K12-11 may regulate a common set of target genes in latently infected B cells. First, we tested four different PEL-derived cell lines and found that none expressed detectable levels of miR-155; however, all expressed high levels of miR-K12-11 [88]. Using three different target prediction algorithms, we predicted Bach-1 whose 3′UTR has four seed sequence matches as possible target (Fig. 12.5). Using a Bach-1 3′UTR-containing reporter, we showed that both miR-155 and miR-K12-11 efficiently down-regulated luciferase expression. Furthermore, both miRNAs when ectopically expressed, down-regulate Bach-1 protein levels in a Burkitt’s lymphoma cell line. In addition, we generated 293 cells which stably express each miRNA and performed comparative gene expression profiling. We found that both miR-155 and miR-K12-11 target a common set of 64 genes, many of which play known roles in apoptosis, cell proliferation, and hematopoiesis. These data, which were reported by us and the Cullen lab, strongly suggest that KSHV miR-K12-11 is an ortholog of miR-155. Both the pre-blast

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Fig. 12.5 KSHV encodes an ortholog of miR-155. BACH-1 is targeted by miR-K12-11 and miR-155. (A) The BACH-1 3′UTR contains four seed match sites (black bars) based on three target prediction programs (miRanda, PicTar, TargetScan). (B) and (C) A region of the BACH-1 3′UTR (nt 658–2,495) encompassing the predicted miRNA binding sites was cloned downstream of luciferase (pGL3-BACH1). 293 cells were co-transfected with 40 ng pGL3-BACH-1 and increasing amounts (100, 200, 400, 800 ng) pmiR-155 or pmiR-K12-11. Ratios on the X-axis indicate the amount of miRNA vector to reporter. pcDNA3.1 was used as filler. Light units (RLU) are normalized to total protein determined by BCA (Pierce). Shown is the average of three independent transfections. (D) Transient expression of miR-155 or miR-K12-11 affects BACH-1 protein levels. BJAB cells were transfected with 2 µg miRNA expression vector or pcDNA3.1 control (nucleofection, Amaxa, inc.). Lysates were harvested at 72 h and probed for endogenous BACH-1 or actin. (E) Expression of either miR-155 or miR-K12-11 predicts BACH-1 expression in lymphomas. PEL cells expressing miR-K12-11, and BL cells expressing miR-155, express low amounts of BACH-1 protein. Lysates from 1 × 105 VG1, RAJI, or BJAB cells were probed for endogenous BACH-1 and actin

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phenotype of KSHV-infected PEL tumors and the now known roles for miR-155 in germinal center B cell differentiation [77, 95] suggest that miR-K12-11 contributes to lymphomagenesis by mimicking de-regulated miR-155 activity. Clearly, this attractive model will need to be addressed in appropriate in vitro and in vivo B cell differentiation models.

12.3 12.3.1

Discussion and Outlook Viral miRNAs as Oncogenes?

Recently, a large number of epidemiological studies suggest that metazoan miRNAs can have both oncogenic as well as tumor suppressor activity (for review see [14]). As described above, miR-155 is aberrantly expressed in many lymphomas and when overexpressed in transgenic animals induces lymphoproliferative disease [16]. The human miR-17-92 cluster was first shown to be highly expressed in transformed cells, and interestingly, in the context of the above described KSHV data, miR-19 also targets thrombospondin-1 [20]. In contrast, the let-7 family members act as tumor suppressors by down-regulating the Ras pathway [39] and recently, polymorphisms in 3′UTRs of oncogenes have been proposed as novel mechanisms of transformation [58]. These observations, together with the fact that the human DNA tumor viruses EBV and KSHV encode viral miRNAs, raise the question whether they directly contribute to viral oncogenesis. Thus far, no direct role for viral miRNAs in transformation has been reported. Identified targets for KSHV miRNAs involve genes regulating key pathways such as apoptosis, cell proliferation, and immune evasion [83], believed to be critically important for the establishment of latency and/or persistence within the infected host. For KSHV, such function would be in congruence with the latency-associated genes that are expressed from the same genomic location. It is also feasible that EBV and KSHV miRNA expression during latency, in the context of additional viral gene products and/or external genotoxic stress, may indirectly contribute to tumorigenesis.

12.3.2

What’s Next for Viral microRNAs?

With respect to miRNAs, metazoan viruses have clearly diverged from plant viruses. While many plant viruses encode potent inhibitors of RNA interference against miRNA-dependent innate immunity, animal viruses have evolved to utilize miRNAs as a mechanism to post-transcriptionally regulate and modulate the host cellular environment. A growing number of viral miRNAs are still being identified, but thus far only in DNA viruses, and predominantly in herpesviruses.

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There are currently 12 DNA viruses known to encode and express a total of 101 miRNA genes (Table 12.1), causing the total number of herpesvirus genes to increase by over 10% since the identification of the first miRNA. However, very little is known about targets and functions for viral miRNAs and as of this writing, experimentally verified miRNA targets for only three viruses have been reported which highlight two different mechanisms (Table 12.2). First, miRNAs can target their own viral transcripts in a siRNA-mediated fashion as demonstrated by degradation of the SV40 large T mRNA [92] and proposed for the EBV DNA pol gene by EBV miR-BART-2 [69]. Second, miRNAs target cellular transcripts in a miRNA-mediated fashion as shown for KSHV [83, 88]. Based on these initial experiments that identified genes involved in important signaling pathways such as apoptosis and angiogenesis, it is tempting to hypothesize that viral miRNAs function primarily by down-regulating specific genes to create a favorable cellular environment for viral replication. Deciphering miRNAdependent phenotypes will critically depend on genetic systems to create viral mutants in combination with robust animal models for viral infection and importantly, pathogenesis. These tools can similarly be applied to further investigate whether viral genes are targeted by miRNAs. Herpesviruses, with their large genomes and complex life cycles, are characterized by tightly orchestrated gene expression programs during both latent and lytic replication. Hypothetically, viral miRNAs may contribute to this regulation by targeting viral genes. For example, inhibiting immediate early gene expression, as shown for CMV-encoded miRNAs [31, 90] could contribute to the establishment and/or maintenance of latency. Such a role would be analogous to the role of many metazoan miRNAs that regulate crucial steps during development and differentiation by expressing specific miRNA repertoires in both a spatial and temporal manner. Finally, virally-encoded miRNAs may function in ways different from our current model which focusses on determining miRNA mRNA target relations. Since miRNAs generally inhibit gene expression, we could imagine a scenario by which a burst of viral miRNA expression (i.e. after primary infection) could temporarily lead to an inhibition of cellular miRNA activity causing a general de-repression of cellular gene expression and as a result, lead to activation of the infected cell. Such a general mode of action would account for the fact that even closely related viruses, such as KSHV and RRV [84] or MDV-1 and MDV-2 [9, 102] have conserved the genome localization and presumably, the expression kinetics of miRNA genes but not their primary sequences. Although not miRNA-related, a similar mechanism has been demonstrated for the Adenovirus non-coding VA1 RNAs that inhibit RNA interference by both competing for the Exportin 5 nuclear factors and by inhibiting Dicer activity [54]. While these scenarios are speculative at this time, it is fair to say that the identification of miRNA genes within DNA viruses already forces us to revise our current understanding of viral and host cellular gene expression by integrating a new and highly complex layer of post-transcriptional regulation.

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References 1. Ambros, V. 2004. The functions of animal microRNAs. Nature 431:350–5. 2. An, F. Q., N. Compitello, E. Horwitz, M. Sramkoski, E. S. Knudsen, and R. Renne. 2005. The latency-associated nuclear antigen of Kaposi’s sarcoma-associated herpesvirus modulates cellular gene expression and protects lymphoid cells from p16 INK4A-induced cell cycle arrest. J Biol Chem 280:3862–74. 3. Bartel, D. P. 2004. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116: 281–97. 4. Bennasser, Y., S. Y. Le, M. Benkirane, and K. T. Jeang. 2005. Evidence that HIV-1 encodes an siRNA and a suppressor of RNA silencing. Immunity 22:607–19. 5. Bennasser, Y., S. Y. Le, M. L. Yeung, and K. T. Jeang. 2004. HIV-1 encoded candidate microRNAs and their cellular targets. Retrovirology 1:43. 6. Borsani, O., J. Zhu, P. E. Verslues, R. Sunkar, and J. K. Zhu. 2005. Endogenous siRNAs derived from a pair of natural cis-antisense transcripts regulate salt tolerance in Arabidopsis. Cell 123:1279–91. 7. Brennecke, J., A. Stark, R. B. Russell, and S. M. Cohen. 2005. Principles of microRNA-target recognition. PLoS Biol 3:e85. 8. Burgler, C., and P. M. Macdonald. 2005. Prediction and verification of microRNA targets by MovingTargets, a highly adaptable prediction method. BMC Genomics 6:88. 9. Burnside, J., E. Bernberg, A. Anderson, C. Lu, B. C. Meyers, P. J. Green, N. Jain, G. Isaacs, and R. W. Morgan. 2006. Marek’s disease virus encodes MicroRNAs that map to meq and the latency-associated transcript. J Virol 80:8778–86. 10. Cai, X., and B. R. Cullen. 2006. Transcriptional origin of Kaposi’s sarcoma-associated herpesvirus microRNAs. J Virol 80:2234–42. 11. Cai, X., G. Li, L. A. Laimins, and B. R. Cullen. 2006. Human papillomavirus genotype 31 does not express detectable microRNA levels during latent or productive virus replication. J Virol 80:10890–3. 12. Cai, X., S. Lu, Z. Zhang, C. M. Gonzalez, B. Damania, and B. R. Cullen. 2005. Kaposi’s sarcoma-associated herpesvirus expresses an array of viral microRNAs in latently infected cells. Proc Natl Acad Sci USA 102:5570–5. 13. Cai, X., A. Schafer, S. Lu, J. P. Bilello, R. C. Desrosiers, R. Edwards, N. Raab-Traub, and B. R. Cullen. 2006. Epstein-Barr virus microRNAs are evolutionarily conserved and differentially expressed. PLoS Pathog 2:e23. 14. Calin, G. A., and C. M. Croce. 2006. MicroRNA signatures in human cancers. Nat Rev Cancer 6:857–66. 15. Cantalupo, P., A. Doering, C. S. Sullivan, A. Pal, K. W. Peden, A. M. Lewis, and J. M. Pipas. 2005. Complete nucleotide sequence of polyomavirus SA12. J Virol 79:13094–104. 16. Costinean, S., N. Zanesi, Y. Pekarsky, E. Tili, S. Volinia, N. Heerema, and C. M. Croce. 2006. Pre-B cell proliferation and lymphoblastic leukemia/high-grade lymphoma in E(mu)-miR155 transgenic mice. Proc Natl Acad Sci USA 103:7024–9. 17. Cougot, N., S. Babajko, and B. Seraphin. 2004. Cytoplasmic foci are sites of mRNA decay in human cells. J Cell Biol 165:31–40. 18. Cui, C., A. Griffiths, G. Li, L. M. Silva, M. F. Kramer, T. Gaasterland, X. J. Wang, and D. M. Coen. 2006. Prediction and identification of herpes simplex virus 1-encoded microRNAs. J Virol 80:5499–508. 19. de Fraipont, F., A. C. Nicholson, J. J. Feige, and E. G. Van Meir. 2001. Thrombospondins and tumor angiogenesis. Trends Mol Med 7:401–7. 20. Dews, M., A. Homayouni, D. Yu, D. Murphy, C. Sevignani, E. Wentzel, E. E. Furth, W. M. Lee, G. H. Enders, J. T. Mendell, and A. Thomas-Tikhonenko. 2006. Augmentation of tumor angiogenesis by a Myc-activated microRNA cluster. Nat Genet 38:1060–5. 21. Dittmer, D., M. Lagunoff, R. Renne, K. Staskus, A. Haase, and D. Ganem. 1998. A cluster of latently expressed genes in Kaposi’s sarcoma-associated herpesvirus. J Virol 72:8309–15.

12 Identification of Cellular Targets for Virally-Encoded miRNAs

221

22. Dittmer, D. P. 2003. Transcription profile of Kaposi’s sarcoma-associated herpesvirus in primary Kaposi’s sarcoma lesions as determined by real-time PCR arrays. Cancer Res 63:2010–5. 23. Dittmer, D. P., C. M. Gonzalez, W. Vahrson, S. M. DeWire, R. Hines-Boykin, and B. Damania. 2005. Whole-genome transcription profiling of rhesus monkey rhadinovirus. J Virol 79:8637–50. 24. Doench, J. G., and P. A. Sharp. 2004. Specificity of microRNA target selection in translational repression. Genes Dev 18:504–11. 25. Dunn, W., P. Trang, Q. Zhong, E. Yang, C. van Belle, and F. Liu. 2005. Human cytomegalovirus expresses novel microRNAs during productive viral infection. Cell Microbiol 7:1684–95. 26. Enright, A. J., B. John, U. Gaul, T. Tuschl, C. Sander, and D. S. Marks. 2003. MicroRNA targets in Drosophila. Genome Biol 5:R1. 27. Eystathioy, T., E. K. Chan, S. A. Tenenbaum, J. D. Keene, K. Griffith, and M. J. Fritzler. 2002. A phosphorylated cytoplasmic autoantigen, GW182, associates with a unique population of human mRNAs within novel cytoplasmic speckles. Mol Biol Cell 13:1338–51. 28. Friborg, J., Jr., W. Kong, M. O. Hottiger, and G. J. Nabel. 1999. p53 inhibition by the LANA protein of KSHV protects against cell death. Nature 402:889–94. 29. Fujimuro, M., F. Y. Wu, C. ApRhys, H. Kajumbula, D. B. Young, G. S. Hayward, and S. D. Hayward. 2003. A novel viral mechanism for dysregulation of beta-catenin in Kaposi’s sarcoma-associated herpesvirus latency. Nat Med 9:300–6. 30. Grey, F., A. Antoniewicz, E. Allen, J. Saugstad, A. McShea, J. C. Carrington, and J. Nelson. 2005. Identification and characterization of human cytomegalovirus-encoded microRNAs. J Virol 79:12095–9. 31. Grey, F., H. Meyers, E. A. White, D. H. Spector, and J. Nelson. 2007. A human cytomegalovirus-encoded microRNA regulates expression of multiple viral genes involved in replication. PLoS Pathog 3:e163. 32. Griffiths-Jones, S. 2004. The microRNA registry. Nucleic Acids Res 32:D109–11. 33. Grundhoff, A., C. S. Sullivan, and D. Ganem. 2006. A combined computational and microarray-based approach identifies novel microRNAs encoded by human gamma-herpesviruses. RNA 12:733–50. 34. Grimson, A., K. K. Farh, W. K. Johnston, P. Garrett-Engele, L. P. Lim, D. P. Bartel. 2007. MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol Cell 27(1):91–105. 35. Han, J., Y. Lee, K. H. Yeom, J. W. Nam, I. Heo, J. K. Rhee, S. Y. Sohn, Y. Cho, B. T. Zhang, and V. N. Kim. 2006. Molecular basis for the recognition of primary microRNAs by the Drosha-DGCR8 complex. Cell 125:887–901. 36. He, L., J. M. Thomson, M. T. Hemann, E. Hernando-Monge, D. Mu, S. Goodson, S. Powers, C. Cordon-Cardo, S. W. Lowe, G. J. Hannon, and S. M. Hammond. 2005. A microRNA polycistron as a potential human oncogene. Nature 435:828–33. 37. Humphreys, D. T., B. J. Westman, D. I. Martin, and T. Preiss. 2005. MicroRNAs control translation initiation by inhibiting eukaryotic initiation factor 4E/cap and poly(A) tail function. Proc Natl Acad Sci USA 102:16961–6. 38. Jin, W. B., F. L. Wu, D. Kong, and A. G. Guo. 2007. HBV-encoded microRNA candidate and its target. Comput Biol Chem. 31(2):124–26. 39. Johnson, S. M., H. Grosshans, J. Shingara, M. Byram, R. Jarvis, A. Cheng, E. Labourier, K. L. Reinert, D. Brown, and F. J. Slack. 2005. Ras is regulated by the let.7 microRNA family. Cell 120(5):635–47. 40. John, B., A. J. Enright, A. Aravin, T. Tuschl, C. Sander, and D. S. Marks. 2004. Human MicroRNA targets. PLoS Biol 2:e363. 41. Jopling, C. L., M. Yi, A. M. Lancaster, S. M. Lemon, and P. Sarnow. 2005. Modulation of hepatitis C virus RNA abundance by a liver-specific MicroRNA. Science 309:1577–81. 42. Lau, N. C., L. P. Lim, E. G. Weinstein, and D. P. Bartel. 2001. An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science 294:858–62. 43. Lawler, J. 2002. Thrombospondin-1 as an endogenous inhibitor of angiogenesis and tumor growth. J Cell Mol Med 6:1–12.

222

M.A. Samols et al.

44. Lecellier, C. H., P. Dunoyer, K. Arar, J. Lehmann-Che, S. Eyquem, C. Himber, A. Saib, and O. Voinnet. 2005. A cellular microRNA mediates antiviral defense in human cells. Science 308:557–60. 45. Lee, R. C., R. L. Feinbaum, and V. Ambros. 1993. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75:843–54. 46. Lee, Y., C. Ahn, J. Han, H. Choi, J. Kim, J. Yim, J. Lee, P. Provost, O. Radmark, S. Kim, and V. N. Kim. 2003. The nuclear RNase III Drosha initiates microRNA processing. Nature 425:415–9. 47. Leung, A. K. and P. A. Sharp. 2007. microRNAs: a safeguard against turmoil? Cell 130(4): 581–85. 48. Lewis, B. P., C. B. Burge, and D. P. Bartel. 2005. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120:15–20. 49. Lewis, B. P., I. H. Shih, M. W. Jones-Rhoades, D. P. Bartel, and C. B. Burge. 2003. Prediction of mammalian microRNA targets. Cell 115:787–98. 50. Li, H., T. Komatsu, B. J. Dezube, and K. M. Kaye. 2002. The Kaposi’s sarcoma-associated herpesvirus K12 transcript from a primary effusion lymphoma contains complex repeat elements, is spliced, and initiates from a novel promoter. J Virol 76:11880–8. 51. Li, H., W. X. Li, and S. W. Ding. 2002. Induction and suppression of RNA silencing by an animal virus. Science 296:1319–21. 52. Lin, J., and B. R. Cullen. 2007. Analysis of the interaction of primate retroviruses with the human RNA interference machinery. J Virol 81:12218–26. 53. Liu, Q., T. A. Rand, S. Kalidas, F. Du, H. E. Kim, D. P. Smith, and X. Wang. 2003. R2D2, a bridge between the initiation and effector steps of the Drosophila RNAi pathway. Science 301:1921–5. 54. Lu, S. and B. R. Cullen. 2004. Adenovirus VA1 noncoding RNA can inhibit small interfering RNA and MicroRNA biogenesis. J Virol 78(23):12868–76. 55. Lu, R., M. Maduro, F. Li, H. W. Li, G. Broitman-Maduro, W. X. Li, and S. W. Ding. 2005. Animal virus replication and RNAi-mediated antiviral silencing in Caenorhabditis elegans. Nature 436:1040–3. 56. Maroney, P. A., Y. Yu, J. Fisher, and T. W. Nilsen. 2006. Evidence that microRNAs are associated with translating messenger RNAs in human cells. Nat Struct Mol Biol 13:1102–7. 57. Matsumura, S., Y. Fujita, E. Gomez, N. Tanese, and A. C. Wilson. 2005. Activation of Kaposi’s sarcoma-associated Herpesvirus major latency locus by the lytic switch protein RTA (ORF50). J Virol 79(13):8493–505. 58. Mayr, C., M. T. Hemann, and D. P. Bartel. 2007. Disrupting the pairing between let-7 and Hmga2 enhances oncogenic transformation. Science 315:1576–9. 59. McCormick, C., and D. Ganem. 2005. The kaposin B protein of KSHV activates the p38/MK2 pathway and stabilizes cytokine mRNAs. Science 307:739–41. 60. Moore, P. S., L. A. Kingsley, S. D. Holmberg, T. Spira, P. Gupta, D. R. Hoover, J. P. Parry, L. J. Conley, H. W. Jaffe, and Y. Chang. 1996. Kaposi’s sarcoma-associated herpesvirus infection prior to onset of Kaposi’s sarcoma. Aids 10:175–80. 61. Nilsen, T. W. 2007. Mechanisms of microRNA-mediated gene regulation in animal cells. Trends Genet 23:243–9. 62. Omoto, S., and Y. R. Fujii. 2005. Regulation of human immunodeficiency virus 1 transcription by nef microRNA. J Gen Virol 86:751–5. 63. Omoto, S., M. Ito, Y. Tsutsumi, Y. Ichikawa, H. Okuyama, E. A. Brisibe, N. K. Saksena, and Y. R. Fujii. 2004. HIV-1 nef suppression by virally encoded microRNA. Retrovirology 1:44. 64. Pasquinelli, A. E., S. Hunter, and J. Bracht. 2005. MicroRNAs: a developing story. Curr Opin Genet Dev 15:200–5. 65. Pasquinelli, A. E., B. J. Reinhart, F. Slack, M. Q. Martindale, M. I. Kuroda, B. Maller, D. C. Hayward, E. E. Ball, B. Degnan, P. Muller, J. Spring, A. Srinivasan, M. Fishman, J. Finnerty, J. Corbo, M. Levine, P. Leahy, E. Davidson, and G. Ruvkun. 2000. Conservation of the sequence and temporal expression of let-7 heterochronic regulatory RNA. Nature 408:86–9. 66. Pedersen, I. M., G. Cheng, S. Wieland, S. Volinia, C. M. Croce, F. V. Chisari, and M. David. 2007. Interferon modulation of cellular microRNAs as an antiviral mechanism. Nature 449:919–22.

12 Identification of Cellular Targets for Virally-Encoded miRNAs

223

67. Petersen, C. P., M. E. Bordeleau, J. Pelletier, and P. A. Sharp. 2006. Short RNAs repress translation after initiation in mammalian cells. Mol Cell 21:533–42. 68. Pfeffer, S., A. Sewer, M. Lagos-Quintana, R. Sheridan, C. Sander, F. A. Grasser, L. F. van Dyk, C. K. Ho, S. Shuman, M. Chien, J. J. Russo, J. Ju, G. Randall, B. D. Lindenbach, C. M. Rice, V. Simon, D. D. Ho, M. Zavolan, and T. Tuschl. 2005. Identification of microRNAs of the herpesvirus family. Nat Methods 2:269–76. 69. Pfeffer, S., M. Zavolan, F. A. Grasser, M. Chien, J. J. Russo, J. Ju, B. John, A. J. Enright, D. Marks, C. Sander, and T. Tuschl. 2004. Identification of virus-encoded microRNAs. Science 304:734–6. 70. Pillai, R. S., S. N. Bhattacharyya, C. G. Artus, T. Zoller, N. Cougot, E. Basyuk, E. Bertrand, and W. Filipowicz. 2005. Inhibition of translational initiation by Let-7 MicroRNA in human cells. Science 309:1573–6. 71. Qu, F., T. Ren, and T. J. Morris. 2003. The coat protein of turnip crinkle virus suppresses posttranscriptional gene silencing at an early initiation step. J Virol 77:511–22. 72. Radkov, S. A., P. Kellam, and C. Boshoff. 2000. The latent nuclear antigen of Kaposi sarcoma-associated herpesvirus targets the retinoblastoma-E2F pathway and with the oncogene Hras transforms primary rat cells. Nat Med 6:1121–7. 73. Raja, S. M., B. Wang, M. Dantuluri, U. R. Desai, B. Demeler, K. Spiegel, S. S. Metkar, and C. J. Froelich. 2002. Cytotoxic cell granule-mediated apoptosis. Characterization of the macromolecular complex of granzyme B with serglycin. J Biol Chem 277:49523–30. 74. Rangaswami, H., A. Bulbule, and G. C. Kundu. 2006. Osteopontin: role in cell signaling and cancer progression. Trends Cell Biol 16:79–87. 75. Reinhart, B. J., F. J. Slack, M. Basson, A. E. Pasquinelli, J. C. Bettinger, A. E. Rougvie, H. R. Horvitz, and G. Ruvkun. 2000. The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature 403:901–6. 76. Renne, R., C. Barry, D. Dittmer, N. Compitello, P. O. Brown, and D. Ganem. 2001. Modulation of cellular and viral gene expression by the latency-associated nuclear antigen of Kaposi’s sarcoma-associated herpesvirus. J Virol 75:458–68. 77. Rodriguez, A., E. Vigorito, S. Clare, M. V. Warren, P. Couttet, D. R. Soond, S. van Dongen, R. J. Grocock, P. P. Das, E. A. Miska, D. Vetrie, K. Okkenhaug, A. J. Enright, G. Dougan, M. Turner, and A. Bradley. 2007. Requirement of bic/microRNA-155 for normal immune function. Science 316:608–11. 78. Rollo, E. E., S. J. Hempson, A. Bansal, E. Tsao, I. Habib, S. R. Rittling, D. T. Denhardt, E. R. Mackow, and R. D. Shaw. 2005. The cytokine osteopontin modulates the severity of rotavirus diarrhea. J Virol 79:3509–16. 79. Ruvkun, G., B. Wightman, and I. Ha. 2004. The 20 years it took to recognize the importance of tiny RNAs. Cell 116:S93–6, 2 p following S96. 80. Sadler, R., L. Wu, B. Forghani, R. Renne, W. Zhong, B. Herndier, and D. Ganem. 1999. A complex translational program generates multiple novel proteins from the latently expressed kaposin (K12) locus of Kaposi’s sarcoma- associated herpesvirus. J Virol 73:5722–30. 81. Saetrom, O., O. Snove, Jr., and P. Saetrom. 2005. Weighted sequence motifs as an improved seeding step in microRNA target prediction algorithms. RNA 11:995–1003. 82. Samols, M. A., L. Skalsky, and R. Renne. 2005. Cloning and identification of a microRNA cluster within the latency-associated region of Kaposi’s sarcoma-associated herpesvirus. J Virol 79:9301–5. 83. Samols, M. A., R. L. Skalsky, A. M. Maldonado, A. Riva, M. C. Lopez, H. V. Baker, and R. Renne. 2007. Identification of cellular genes targeted by KSHV-encoded microRNAs. PLoS Pathog 3(5):e65 84. Schafer, A., X. Cai, J. P. Bilello, R. C. Desrosiers, and B. R. Cullen. 2007. Cloning and analysis of microRNAs encoded by the primate gamma-herpesvirus rhesus monkey rhadinovirus. Virology 364:21–7. 85. Schultz-Cherry, S., H. Chen, D. F. Mosher, T. M. Misenheimer, H. C. Krutzsch, D. D. Roberts, and J. E. Murphy-Ullrich. 1995. Regulation of transforming growth factor-beta activation by discrete sequences of thrombospondin 1. J Biol Chem 270:7304–10. 86. Sen, G. L., and H. M. Blau. 2005. Argonaute 2/RISC resides in sites of mammalian mRNA decay known as cytoplasmic bodies. Nat Cell Biol 7:633–6.

224

M.A. Samols et al.

87. Sethupathy, P., B. Corda, and A. G. Hatzigeorgiou. 2006. TarBase: a comprehensive database of experimentally supported animal microRNA targets. RNA 12:192–7. 88. Skalsky, R. L., M. A. Samols, K. B. Plaisance, I. W. Boss, A. Riva, M. C. Lopez, H. V. Baker, and R. Renne. 2007. Kaposi’s sarcoma-associated herpesvirus encodes an otholog of miR-155. J Virol 81(23):12836–45. Epub 2007 Sept 19. 89. Slack, F. J., M. Basson, Z. Liu, V. Ambros, H. R. Horvitz, and G. Ruvkun. 2000. The lin-41 RBCC gene acts in the C. elegans heterochronic pathway between the let-7 regulatory RNA and the LIN-29 transcription factor. Mol Cell 5:659–69. 90. Stern-Ginossar, N., N. Elefant, A. Zimmermann, D. G. Wolf, N. Saleh, M. Biton, E. Horwitz, Z. Prokocimer, M. Prichard, G. Hahn, D. Goldman-Wohl, C. Greenfield, S. Yagel, H. Hengel, Y. Altuvia, H. Margalit, and O. Mandelboim. 2007. Host immune system gene targeting by a viral miRNA. Science 317:376–81. 91. Sullivan, C. S., and D. Ganem. 2005. A virus-encoded inhibitor that blocks RNA interference in mammalian cells. J Virol 79:7371–9. 92. Sullivan, C. S., A. T. Grundhoff, S. Tevethia, J. M. Pipas, and D. Ganem. 2005. SV40encoded microRNAs regulate viral gene expression and reduce susceptibility to cytotoxic T cells. Nature 435:682–6. 93. Talbot, S. J., R. A. Weiss, P. Kellam, and C. Boshoff. 1999. Transcriptional analysis of human herpesvirus-8 open reading frames 71, 72, 73, K14, and 74 in a primary effusion lymphoma cell line. Virology 257:84–94. 94. Taraboletti, G., R. Benelli, P. Borsotti, M. Rusnati, M. Presta, R. Giavazzi, L. Ruco, and A. Albini. 1999. Thrombospondin-1 inhibits Kaposi’s sarcoma (KS) cell and HIV-1 Tatinduced angiogenesis and is poorly expressed in KS lesions. J Pathol 188:76–81. 95. Thai, T. H., D. P. Calado, S. Casola, K. M. Ansel, C. Xiao, Y. Xue, A. Murphy, D. Frendewey, D. Valenzuela, J. L. Kutok, M. Schmidt-Supprian, N. Rajewsky, G. Yancopoulos, A. Rao, and K. Rajewsky. 2007. Regulation of the germinal center response by microRNA-155. Science 316:604–8. 96. Wang, X. H., R. Aliyari, W. X. Li, H. W. Li, K. Kim, R. Carthew, P. Atkinson, and S. W. Ding. 2006. RNA interference directs innate immunity against viruses in adult Drosophila. Science 312:452–4. 97. Wightman, B., T. R. Burglin, J. Gatto, P. Arasu, and G. Ruvkun. 1991. Negative regulatory sequences in the lin-14 3′-untranslated region are necessary to generate a temporal switch during Caenorhabditis elegans development. Genes Dev 5:1813–24. 98. Wightman, B., I. Ha, and G. Ruvkun. 1993. Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans. Cell 75:855–62. 99. Wilkins, C., R. Dishongh, S. C. Moore, M. A. Whitt, M. Chow, and K. Machaca. 2005. RNA interference is an antiviral defence mechanism in Caenorhabditis elegans. Nature 436:1044–7. 100. Wu, L., and J. G. Belasco. 2008. Let me count the ways: mechanisms of gene regulation by miRNAs and siRNAs. Mol Cell 29:1–7. 101. Xie, Z., L. K. Johansen, A. M. Gustafson, K. D. Kasschau, A. D. Lellis, D. Zilberman, S. E. Jacobsen, and J. C. Carrington. 2004. Genetic and functional diversification of small RNA pathways in plants. PLoS Biol 2:E104. 102. Yao, Y., Y. Zhao, H. Xu, L. P. Smith, C. H. Lawrie, A. Sewer, M. Zavolan, and V. Nair. 2007. Marek’s Disease Virus Type 2 (MDV-2)-encoded MicroRNAs show no sequence conservation with those encoded by MDV-1. J Virol 81:7164–70. 103. Zeng, Y., R. Yi, and B. R. Cullen. 2003. MicroRNAs and small interfering RNAs can inhibit mRNA expression by similar mechanisms. Proc Natl Acad Sci USA 100:9779–84.

Chapter 13

MicroRNA in Neuropsychiatric Diseases Evgeny I. Rogaev1,2,3*, Denis V. Islamgulov1, and Anastasia P. Grigorenko1,2

Abstract Up to 30% of protein encoding genes are regulated by microRNAs (miRNAs). The miRNAs are abundantly expressed in the brain, and, in particular, during brain development stages. Some miRNAs are essential regulators of left/ right neuronal asymmetry in an invertebrate and brain development in vertebrates. Transfection of some microRNA (miR-124) in human cells changed the expression pattern of mRNAs towards brain-like profiles. It may be expected, therefore, that miRNA-related mechanisms are involved in certain aspects of neuropsychiatric pathologies. The data have been obtained suggesting that depletion of cellular components controlling miRNA processing and biogenesis severely affects brain functions implicated in pathogenesis of neurodegenerative or behavior diseases. Partial or conditional loss of function for Dicer causes loss of dopamine neurons and degeneration of Purkinje cells – mechanisms implicated in Parkinson disease; or enhance neurodegeneration in Drosophila model induced by proteins implicated in polyQ neurodegenerative pathologies. Loss of FMPR protein function is a cause of common mental retardation syndrome (FXS) and function of FMRP or FMPR-related protein in Drosophila (Dfmr1) was linked to RNA-induced silencing complex (RISC). Mutation in putative target for miRNA in SLITRK1 gene is associated with Tourette’s neuropsychiatric disorder- the most direct known to date example of linkage between behavior disease and specific miRNA. The pilot studies demonstrated that despite the tiny size miRNAs are quite stable in postmortem tissues and that convergent approach in study of expression and genetic variability of miRNAs in neuropsychiatric pathology is a conceivable goal. It is anticipated that comprehensive studies of miRNA regulators and their targets using innovative genomic technologies may shed a light on unknown aspects in pathogenesis of 1 Department of Psychiatry, Brudnick Neuropsychiatric Research Institute, University of Massachusetts Medical School, 303 Belmont Street, Worcester, MA 01604, USA 2

Research Center of Mental Health, RAMS, Moscow

3

Vavilov Institute of General Genetics, RAS, Moscow

* Corresponding author: Department of Psychiatry, Brudnick Neuropsychiatric Research Institute, University of Massachusetts Medical School, 303 Belmont Street, Worcester, MA 01604, USA; E-mail: [email protected]

S.-Y. Ying, (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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common neurodegenerative disorders (Alzheimer’s disease) and mental disorders (schizophrenia) in a nearest future.

Keywords miRNA, neuropsychiatric diseases, CNS, schizophrenia, Alzheimer’s disease

Abbreviations ADHD, attention deficit hyperactivity disorder; AGO2, Argonaute 2; APP, Amyloid Precursor Protein; BDNF, brain-derived neurotrophic factor; CNS, central nervous system; CNV, copy number variation; CRE, calcium responsive elements; DGCR8, DiGeorge syndrome critical region gene 8; DN, dopaminergic neurons; DRD3, dopamine receptor D3; dsRNA, double-stranded RNA; EIF2C2, eukaryotic translation initiation factor 2C; ES, embryonic cells; FMR1, fragile X mental retardation 1; FMRP, fragile X mental retardation protein; FXS, Fragile X syndrome; GABRA4, gamma-aminobutyric acid (GABA) A receptor, alpha 4; MAP1B, microtubule-associated protein 1B; MECP2, methyl CpG binding protein 2; miRNA, microRNA; MM, mismatch; MSC, mesenchymal cells; OCD, obsessivecompulsive disorder; Pcp2, Purkinje cell protein 2, PM, perfect match; PTBP1, polypyrimidine tract binding protein 1; PTBP2, polypyrimidine tract binding protein 1; RISC, RNA-induced silencing complex; RVG, rabies virus glycoprotein; SCN, suprachiasmatic nuclei; siRNA, small interfering RNA; SLITRK1, Slit and Trk-like family member 1; SNP, single nucleotide polymorphism; SP, substance P; STAT3, signal transducer and activator of transcription 3; Tac1, tachykinin, precursor 1; TNFα, tumor necrosis factor alpha; TS, Tourette’s syndrome; UTR, untranslated region

13.1

Introduction

The study of microRNA (miRNA) in human disease, and especially in neurological or psychiatric disorders, is still at the embryonic stage. To date much indirect data has been accumulated suggesting a general role of miRNA in controlling CNS development and maintenance. There is no doubt that primary research on miRNA biogenesis will be greatly expanded in the coming years to functional studies of miRNAs in human brain and behavioral pathologies. The etiology of many common neuropsychiatric illnesses, such as age-related cognitive and memory decline in dementias and neurodevelopment abnormalities in autism and mental retardation is not yet completely understood or, in the case of common schizophrenia and depression disorders, is largely unknown. A simple bioinformatics search for miRNA targets in human genes identified that genes involved in neurological and psychiatric disorders (FMR1 gene and genes

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for ubiquitin-proteasome system controlling misfolded proteins toxic to neurons) are ranked in the top of genes with the largest number of predicted targets for miRNAs [20]. Early studies demonstrated that the exogenous application of small interfering RNA (siRNAs) to neurons seems to be difficult. This observation implied the existence of natural mechanisms for relative resistance of neurons to RNA interference (RNAi). Indeed, in C. elegans, the endogenous product (ERI-1) with putative exonuclease properties expressed in neurons was identified [23]. Mutations of the gene for this protein result in accumulation of siRNAs demonstrating that small RNAs are under strong negative control in neurons. C.elegans gene rrf-3, encoding RNA-directed RNA polymerase, is also expressing in neurons and regulates RNAi response [43].These initial observations along with currently available data which we discuss here indicate that miRNAs may be an intriguing and often missed type of cellular regulators contributing to normal and abnormal brain function [39]. At least 9%-30% of protein encoding genes are predicted to be regulated by miRNAs [20, 29, 47] and miRNAs are abundant and presented in developing and adult brains [26, 32] (Fig. 13.1). It would not be surprising, therefore, that miRNArelated mechanisms are indeed involved in certain aspects of neuropsychiatric pathologies.

13.2 13.2.1

Results and Discussion Small RNAs in Brain and Neurons

MiRNAs are a class of small of regulatory RNAs that control a cellular level of transcript or protein products of encoding genes. Mature miRNAs are endogenous ~19–24 nt RNAs derived from longer RNA precursors (~70–100 nt) with a stem loop structure. There are ~350 well described and, including very rare and evolutionary novel and non-conserved forms, perhaps up to 1,000 or more miRNA species in human tissues (databases websites). The miRNAs, as an imperfect complement to one or several different mRNA targets, may promote degradation of these mRNAs or, more often, suppress translation of corresponding protein in mammalian cells. The role of small regulatory RNA in psychiatric diseases has been hypothesized but has yet to be elucidated [37, 39]. We believe there are several reasons to study miRNAs in the etiology of neuropsychiatric diseases. They are abundantly expressed in the brain, and, in particular, during brain development stages [24]. These genes are probably critical regulators of development. Specific endogenous miRNAs are essential regulators of left/right neuronal asymmetry in an invertebrate animal model and of brain development in vertebrates [12, 21]. While viral hypotheses have been implicated in schizophrenia etiology, there is also evidence that small RNA may confer intracellular immunity in human cells against replicating RNA viruses [13]. On the other hand, miRNAs were predicted in viral genomes, including the herpes virus family [38].

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138-1 488 137 9-1 124-1 297 218 33 744 186 872 708

m iR hs -12 5 hs a-le b a- tm 7a iR hs -2 a- 6a le hs t-7 c a hs -let a- -7f hs let hs a-m -7b a- iR m iR -9* h 12 hs sa- 4a a- let m -7 iR d hs -1 a 2 hs -m 5a a iR hs -m -9 a- iRm 23 hs iR a- -1 b 2 hs miR 8a a- -1 m 28 iR - b hs 18 a- 1a l hs eths a-l 7e a- etm hs iR 7g a- -1 hs miR 03 a- -2 hs miR 9a a- -1 m 9 hs iR 1 a- -3 4 hs miR 2 a- -1 hs m 07 a- iRm 23 i hs R- a a- 18 m 1 hs iR- b a 1 hs -mi 26 a- Rm 16 hs iRa 13 hs -mi 2 a- Rm 2 hs iR 4 a- -1 hs miR 00 a- -3 m 6 iR 1 hs -99 hs a-l b a- etm hs iR 71 a- -2 m hs iR 22 a- -9 hs miR 9a a- -3 m 0 hs iR c a- -1 m 9 hs iR 5 a- -2 2 hs miR 1 a- -1 m hs iR 45 a- -2 m 7b hs iR a- -26 m i b hs R-1 hs a-m 27 a- iR m -7 hs iR a- -1 m 4 hs iR 3 a- -3 hs miR 0d a- -3 m hs iR 20 a- -3 m 0b iR -1 85

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hs a hs -m a iR hs -m -1 a iR 4 hs -m -3 3 a i 3 hs -m R-2 1 a- iR 7a m h iR 38 hs sa- -1 2 a m 2 h -m iR 9 hs sa- iR -7 a- mi -15 m R hs iR -431 hs a-m17- 2 a- iR 5p h hs sa miR -93 a- -m -3 hs m iR 0 i a- R -3 b m -4 3 hs iR- 09 0 a 30 -3 hs hsa -miRa-5 p a- -m -4 p m iR 2 hs iR- -2 5 3 hs a-m 24 0a a- iR -5 p m hs iR -45 hs a-m-10 1 6 a hs -m iR- a i 2 hsa-m R-1 2 a- iR 39 hs mi -21 hs a-mR-1 4 5 a hs -mi iR-92 R hsa-m -4 8 a- iR 95 h m hs sa iR 34 a- -m -3 a m iR 2 i 3 h R- -3 hs sa- 485 46 a- mi -5 m R- p i 1 hs hsa R-1 34 a- -m 30 hs miR iR- b 3 a hs -m -18 1 hs a-miR- 1c a- i 38 hs miRR-3 3 a- -1 28 hs miR 30 hs a-m -2 a hs a-m iR 24 a- iR -2 hs miR -1 8 5 a hs -m -42 b a iR 2 hs -m -1 b a iR 5 hs -m -4 0 hs a-m iR-391 hs a-m iR- 29 a iR 37 hs-miR -14 0 a 6 h -m -10 b hs sa- iR- 6b hs a- mi 21 a- m R- 2 m iR 49 i hs R- 19 4 a 3 3 hs -m 24- b a iR 3 hs -m -2 p i 0 hsa-m R-3 b a i 7 hs -m R-1 9 a- iR 84 hs m -1 i a hs -m R- 38 a- iR 19 7 m hs iR -21 hs a-m-14 0 6 a hs -m iR- a a- iR 25 hs m -4 a iR 2 hs -m -3 3 a iR 4 hs -m -33 5 iR hsa-m -1 5 5 hs a-miR-1 a a- iR 3 m -4 7 iR 89 -4 22 a

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Fig. 13.1 Expression of miRNAs in the human adult brain. (A) Relative level of expression of different miRNA species in human parietal brain neocortex detected by hybridization with the human miRNA chips (LC Science). Highly expressed miRNAs (intensity higher than 1,000) and moderate or low expressed miRNAs (intensity higher than 100 and lower than 1,000) are shown (O. Burmistrova and E. Rogaev, 2006). (B) MiRNA predominantly expressed in brain tissues. The relative level of expression of brain enriched miRNA in comparison to other tissues (Modified from data presented [26]). (C) The relative abundance of the brain specific miRNAs (below histogram) estimated by analysis of RNA extracted from human brain neocortex of 15 individuals (Control set, brain specimens from Stanley Medical Research Institute, our unpublished data). Each sample was analyzed by RT-TaqMan PCR (Applied Biosystems) and average mean and individual diversity in a level of expression is shown

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There are a number of miRNAs specifically expressed in the brain (Fig. 13.1). One of the most abundant brain-specific miRNAs, miR-124, is essential in brain development. Interestingly, over-expression of miR-124 leads to the formation of neuronal-like expression pattern of other genes. For example, transfection of miR124 in human cells changed the expression pattern of mRNAs towards brain-like profiles [30]. Moreover, the overexpression of miR-124 in neuroblastoma cells also changed the pattern of spliced RNA transcripts. It was shown that during differentiation of progenitor cells to mature neurons, miR-124 reduced PTBP1 mRNA encoding a repressor of alternative pre-mRNA splicing in non-neuronal cells. This effect is associated with significantly increased PTBP2 protein resulting in a transition from non-neuronal to neuronal like- alternative splicing in RNAs [31]. There is yet little data on what genes controlling behavior may be directly regulated by miRNAs. In one instance, in order to elucidate the role of miRNA in neurotransmitter synthesis, miRNA expression profiles were analyzed in neuronal differentiated and non-differentiated mesenchymal cells (MSC). Tac1 gene encodes neurotransmitter P substance which is not produced in the MSC-derived neuronal cells unless stimulated with inflammatory factor IL-1α. Creco and Rameshwar identified miRNAs in these cells downregulated by IL-1α and showed that inhibition of two such miRNAs, miR-130a and miR-206, which have presumable targets on Tac1, led to SP translation and its release in neuronal cells [14]. In another important report focusing on the search for miRNAs specifically localized to synapto-dendritic neuronal compartments, the miR-134 was identified that potentially inhibit LimK1 translation, the protein that regulates dendritic spine structure [42]. In a comprehensive line of experiments, Dr. Greenberg’s group first identified miR-134 as a miRNA with gradually increased expression in development reaching maximum at the time of synaptic maturation. Next, by in situ hybridization the expression of miR-134 was detected within dendrites. Upregulation of miR-134 showed a decrease in spine volume and, in contrast, inhibition of the miR-134 increased the spine volume of cultured neuronal hippocampal cells. All together these experiments demonstrated the importance of miRNAs in neuronal differentiation, synaptic plasticity and neurotransmission – the processes thought to be impaired in a number of psychiatric and neurological diseases.

13.2.2

MiRNA in Neurodegenerative Disorders

Although the role of miRNA in development is quite well established, their role in postmitotic neurons was less clear. Knockout of Dicer protein, essential for the processing of miRNAs, produces a lethal phenotype in the early embryo characterized by a depletion of stem cells [4]. Therefore, the conditional knockout has to be employed to address whether disruption in processing of miRNA will disturb the neuronal function. In one recent study, the system with Purkinje cell-specific Pcp2 promoter-driven Cre recombinase [41] was used to inactivate Dicer alleles in Purkinje cells. The Dicer deficiency seems to have no effect on morphology or the

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number of the Purkinje cells in the cerebellum of 8–10 week-old mice. However, degeneration of Purkinje cells was observed in 13–17 week-old Dicer-deficient mice. This gradual progression of degeneration of Purkinje cells resembles, in part, the neurodegenerative process in Parkinson’s disease. In another recent study, conditional knockout of Dicer enzyme was employed to study the role of miRNA in specialized dopaminergic neurons (DN) [50]. The role of midbrain dopaminergic neurons was described in reward and addiction behavior and their loss leads to Parkinson’s disease. The murine embryonic cells (ES) with conditionally expressed Dicer were differentiated to midbrain neurons. Since Crerecombinase was expressed under the regulation of dopamine transporter transcriptional regulators, activation of the Cre-enzyme resulted in deletion of Dicer in postmitotic DN. Reduced locomotion was found in the Dicer-deficient mice. The authors further addressed the question of what miRNA may be specifically important in DN maintenance. The miR-133b was identified as miRNA particularly enriched in midbrain and reduced in midbrain specimens depleted of DN. Interestingly, this miRNA was also reduced in Parkinson’s disease patients. Given the essential role of miRNA in the survival of DN the following experiments for over-expression and inactivation of miR-133b resulted in quite unexpected and controversial data. Inhibiting miR-133b by a 2′-O-methyl-modified RNA homologous oligonucleotide induced expression of DN markers, dopamine transporter and tyrosine hydroxylase, whereas overexpression of miR-133b resulted in reduction of these DN markers. The transcriptional factor Pitx3 is a potential target for miR133b and authors argue that miR-133b may be a part of a negative feed back circuit that includes Pitx3 in control of dopaminergic-related behavior. The relevance of miR-133b to neurodegeneration remains ambiguous and other miRNAs have to be tested. However, these two conditional-knock-out studies demonstrate an apparent role of miRNA in neuron survival. The role of Dicer in other types of neurons and brain regions (e.g., affected in Alzheimer’s disease) would also be interesting to clarify using the conditional knock-out approaches. It would be critically important to accompany such studies by direct testing of specific miRNA in neurodegeneration cell models since the role of Dicer in other molecular pathways unrelated to miRNA processing has been described. Research is also shedding light on the importance of miRNA in modulation of neurodegeneration directly linked to human diseases. In one elegant study the Drosophila model was used to test whether neurodegenerative polyQ pathologies are modulated by miRNAs. PolyQ-neurodegenerative diseases are caused by the expansion of CAG tandem repeats within the open reading frame of some proteins culminating in progressive neurodegeneration. The severity of the process during the life-span depends on the length of CAG tract in a mutant allele. Several forms of ataxia and among them the ataxia 3 were linked to this type of molecular-genetic mechanisms. What downstream elements are triggered by polyQ- mutations leading to cell death have yet to be clarified. However, it is already clear that the ubiquitin-proteasome system and neurotoxic misfolded proteins are involved as it has been described for many neurodegenerative disorders [33]. Bilen et al. described how Drosophila Dicer (dcr-1) mutation enhances degeneration in the eye, caused

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by Ataxin-3 truncated protein (SCA3tr-Q78). The authors also showed that in the hypomorphic mutant for R3D1/loquacious (dsRNA binding protein) with downregulated miRNA processing, the SCA3tr- Q78-induced neural degeneration is significantly enhanced. The authors next sought to find genes that may modify the ataxin-3-induced neurodegeneration in the Drosophila eye. A genetic screen identified that some of the upregulated allele modifiers are located in the genomic region of the miRNA gene miR-14 or ban. It was previously shown that in Drosophila, the miRNAs ban/miR-14 may modulate the genes involved in programmed cell death [6, 28, 48]. Upregulation of ban restored internal retinal structure and inhibited external pigmentation loss associated with neurodegeneration whereas even partial loss of function of ban enhanced the neurodegeneration caused by CA3tr-Q78 [5]. It is worth noting that in flies, a loss of dcr-1 (specifically involved in miRNA processing), but not a loss of dcr-2 (specific to siRNA pathways), attenuated the neurodegeneration process [5]. This finding clearly demonstrated that specific miRNAs rather than siRNAs control cell survival in neurodegeneration. Finally, Bilen and co-authors showed that reduced or enhanced activity of R3D1 and bin also modulate neurodegeneration caused by tau-protein [5]. Tau- pathology is a hallmark for several forms of dementia. Thus these data may open a new avenue in the study of miRNA in tau-pathologies, including Alzheimer’ disease. Apparently, such studies should be addressed not only in invertebrate but mammalian animal or neuronal cell models. Alzheimer’s disease is quantitative pathology linked to accumulation of Aβ-fibrillogenic peptides. It would be of interest, therefore, to directly test the role of certain miRNAs with putative targets on APP or proteins involved in processing of APP on modulation of neurodegenerative process mediated-by cascade mechanisms that include APP processing, Aβ40, 42 generation and modification of tau-proteins (Fig. 13.2).

13.2.3

MiRNA in Mental Disorders

13.2.3.1

Tourette’s Syndrome

To date at least one study has provided quite convincing genetic evidence for the possible involvement of miRNA regulating process in human behavioral pathology. Abelson et al. in a search for gene variations contributing to Tourette’s syndrome (TS) identified three rare mutations in a gene Slit and Trk-like family member 1 (SLITRK1) [2]. TS is a common neuropsychiatric disorder (∼1% in human populations) characterized by vocal and motor ticks often associated with obsessive-compulsive disorder (OCD), attention deficit hyperactivity disorder (ADHD) and depression. The SLITRK1 was, initially, implied as a candidate-gene because its location on chromosome 13q13 proximal to a de novo chromosomal inversion. This inversion was found in a single individual with TS suggesting that this genomic rearrangement may alter regulation of the gene. Further analysis of 174 unrelated probands found one frameshift mutation and identical mutation in

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Neurodevelopmental genes; neurotransmitter genes

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FMR1 gene /loss-of-function/ Fragile X mental retardation syndrome miRNA processing miRNA binding (complex with RISC)

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Fig. 13.2 Potential role of miRNA and components of miRNA processing system in pathways underlying neuropsychiatric disorders

two unrelated individuals in the putative binding site for miR-189 within the 3′untranslated region (UTR) of SLITRK1. Although the data have to be confirmed in other cohorts of TS subjects, the authors demonstrated that the mutation resides on distinct haplotypes of these two affected subjects providing evidence that this mutation arose independently. On the basis of thermodynamic properties and experimental test of the mutant 3′-UTR sequence variant versus that of wild type expressed with luciferase reporter gene in Neuro2 cells, the authors concluded that the mutation strengthens affinity of the SLITRK1 3′-UTR- target site to miR-189. Therefore, translation of the SLITRK1 mutant allele transcript may be repressed to a greater degree than a wild type [2] and, partial loss of function of SLITRK1, implicated in neurite outgrowth, may explain at least some cases of TS.

13.2.3.2

Mental Retardation and Autism

Not only mutations in miRNA targets but dysfunction of miRNA or RNA interference pathway itself may lead to crucial pathogenic process in CNS. Fragile X syndrome (FXS) is a very common form of mental retardation with an incidence rate of 1 in 4,000 men and 1 in 8,000 women [1]. The common molecular cause of FXS is an expansion of CGG tri-nucleotide repeats located in the 5′-untranslated region

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of the FMR1 gene eventually resulting in the suppression of expression of FMR1 protein (FMRP). Although much research has been done, it is still unclear exactly what molecular pathway is disrupted by the loss of function of FMRP. FMRP contains RNA binding domains and probably acts as a translational repressor for some neuronal mRNAs. Three well established activities were associated with FMRP: control of mRNA translation, regulation of mRNA localization in dendrites and control of mRNA stability. For example, FMRP interacts with 3′-region of PSD-95 mRNA increasing its stability. PSD-95 is essential for learning and cortical plasticity. The regulation of PSD-95 by FMRP may depend on mGluR signaling [44, 49]. The FMRP represses MAP1B translation required for active synaptogenesis and control of cytoskeleton organization during neuronal development control. Many mRNA or even non-coding RNA (BC1 and BC200) were implicated as putative binding targets for FMRP. Several groups provided data suggesting the association of FMRP with components critical for siRNA-mediated gene silencing or miRNA processing and pathway, including Dicer activity and mammalian Argonaute protein (EIF2C2). FMRP-related protein in Drosophila (Dfmr1) is associated with Argonaute 2 (AGO2) and with the RNA-induced silencing complex (RISC) [8, 17, 19, 35]. It must be noted, however, that loss of function of FMRP does not disrupt siRNA machinery. It is conceivable that FMRP binds to certain mRNA and recruit RISC and miRNA complex for regulation of protein synthesis required for synaptic plasticity [19]. Interestingly, there are numerous putative targets for miRNA in FMRP transcript itself (Fig. 13.3), suggesting that feedback circuit mechanisms may be involved in miRNA-FMRP-mediated activity in neurons.

13.2.3.3

Other Pathways in Behavior and Brain Homeostasis

Circadian clocks and sleep. Feedback regulatory loops in transcription and posttranscription processes is a central dogma in the explanation of how circadian clocks keep time. The circadian maker in the brain is suprachiasmatic nuclei (SCN). Cheng et al. identified that miR-219 and miR-132 genes have calcium responsive elements (CRE) enhancers and expressed rhythmically in normal SCN but not in circadian mutants. Interestingly, miR-132, appears to be induced by light. Inhibition of these miRNA in vivo by antagomirs resulted in alteration of behavioral periods. As for many other miRNAs the exact action of such mRNAs in vivo remain to be speculative since quantitative alterations in spatio-temporal manner of combinations of multiple endogenous targets may underlie the clockwork [10, 36]. The current conception of sleep is that the sleep process is initiated by prior neuronal activity promoting expression of sleep regulatory proteins. Sleep and sleep impairments alter gene expression of sleep regulatory substances and thereby change input-output oscillations. In this regard, the activity of miRNAs in the translation processes make them attractive candidates for regulatory molecules contributing to control of sleep homeostasis. In primary experiments miRNA profiles were analyzed in sleep-deprived rats in different brain regions [11]. About 50 miRNAs

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Fig. 13.3 MiRNAs and their targets in genes for behavioral disorders. Evolutionary-conserved sites in 3′-UTR- gene regions. Conserved sites for miRNA families in Human, Mouse, Rat, Dog and Chicken are shown (TargetScan prediction; http://www.targetscan.org)

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changed their expression. The most significant changes were observed in the hippocampus where up to 49 miRNAs were upregulated in sleep-deprived animals with statistical significance. It is interesting to note that, except miR-128a and miR29a, in this study the miRNAs that were down-regulated in the cortex were upregulated in the hippocampus. Thus it seems that sleep homeostasis is associated with a process in alteration of miRNAs which is brain area-dependent. It is still unclear what specific targets and molecules are affected via the alteration of miRNAs. The let-7s, a member of an abundantly expressed family of miRNA-let-7, has a predicted complementary target to tumor necrosis factor alpha (TNFα) which is a key sleep regulatory substance. MiRNAs highly expressed in the brain (e.g., miR-125b) or miRNA implicated in synaptic plasticity (miR-132) show prominent alteration after sleep loss [11]. Their targets and pathway in a regulation of sleep related proteins have yet to be found. It is possible that multiple changes in miRNA in different brain areas, if proved to be specific, reflect the complex processes in neuronal ensembles in brain regions during sleep homeostasis or sleep impairment. In addition to circadian regulation, it would be interesting to investigate the role of miRNA in neurons of the hypothalamic arcuate nucleus acting as primary sensors of alteration of energy stores and controlling appetite in response to circulating adipocyte-derived hormone leptin. The leptin – LPLR (OB-R receptor) – activation of STAT3 transcriptional factor is a key signaling system regulating appetite and feeding behavior and loss-of-function in this system results in hyperphagia and obesity [45]. It would be of interest to elucidate whether the level of STAT3-regulating transcripts and production of anorectic melanocyte stimulating hormone aMSH and orexigen neuropeptide Y may depend on miRNA regulators. Interestingly, the number of very conserved microRNA targets seems to be depleted in these genes and it may be speculated that limited number of specific miRNAs may play a role in the regulation of this system (Fig. 13.3). The miRNA network may be changed by an alteration of physiological conditions in the hypothalamus. For example, chronic drinking of 2% of saline (hyperosmolarity) in a mouse increases the level of highly expressed miRNAs miR-7b and miR-9 in mouse paraventricular and supraoptic nuclei. MiR-7b inhibits in vitro translation of inducible Fos transcription factor. For future perspective it is reasonable to hypothesize that one of the functions of miRNA in the brain is to keep in check the gene products which normally must have a low level of expression or activity but induced in response to neurophysiological or behavioral conditions.

13.2.4

Alcohol and miRNA

Ethanol is a very common factor critically changing behavior, and currently alcoholism is regarded as a psychiatric illness. Alcohol may be teratogenic to the fetal brain, inducing mitosis and stem cell maturation. Recently, a study employing fetal mouse cerebral cortex-derived neurosphere culture model showed that ethanol in a dose attained by alcoholics down-regulates the expression of miR-21, -335, -9, and -153,

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and at a dose comparable to the concentration during social drinking upregulates miR-335. Suppression of miR-21 expression leads to apoptosis whereas suppression of miR-335 facilitated cell proliferation and, interestingly, prevented death induced by concurrent downregulation of miR-21. Moreover, the authors showed that simultaneous suppression of miR-335, -21, and -153 significantly increased the level of Jagged-1 mRNA [40]. This study illuminated the effect which may be quite common in miRNA function: coordinately induced miRNAs may show both synergetic and antagonistic pathways toward each other depending on the strength of the inducing factor and spatial-temporal conditions.

13.2.5

Schizophrenia

13.2.5.1

Expression of miRNAs

Using hybridization array assays containing ∼350 miRNA samples and as a probe pooled small RNA extracted from schizophrenia and control cortex brain specimens we were able to identify miRNAs profiles in schizophrenic and control subjects ([39] and E.I. Rogaev, 2006). Since real-time PCR profiling is a more robust method for quantification we directly analyzed ~157 miRNAs in cohorts of schizophrenic in comparison to control individuals and found only a few microRNA with altered expression reached statistical significance in schizophrenia versus control (unpublished). This pilot study has implied that it is unlikely to expect significantly altered miRNA profiles in schizophrenia as it was demonstrated in cancer. A recent study by other groups using hybridization array in a limited cohorts of schizophrenia and control individuals identified 12 miRNAs altering expression in schizophrenia. However, except miR-106b exhibiting 1.77 dowregulation in schizophrenia, all other miRNAs showed very modest 0.63–0.82 alteration in expression in schizophrenia vs. normal subjects. Among them miR-26b, -30e, -92, -24 were confirmed in RT-PCR assay in a larger cohort of individuals with statistically significant down-regulation in schizophrenia versus control individuals (p < 0.05). In our RT-PCR profiling of 157 miRNAs we found no evidence for alteration in expression of mir-26b,-30e, -92 in parietal schizophrenic cortex using our cohorts of 15 patients and 15 control individuals. There are many confounding effects in quantification of expression of genes in postmortem material broadly discussed for protein-encoding genes requiring stringent criteria in controls and quality of RNA material. The same assumptions must be applied to miRNA analysis. Importantly, however, by testing ~160 postmortem specimens from subjects with psychiatric and control individuals we found that miRNAs are surprisingly stable and seem less dependant on pH and the postmortem interval as described for mRNAs (Fig. 13.4). It is noteworthy to indicate that miRNA has been efficiently detected by array hybridization assay and in situ hybridization even in archival formalin-fixed, paraffin-embedded brain tissues [34]. These data give opportunity to undertake a more comprehensive analysis of expression of miRNAs in particular brain regions

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Fig. 13.4 High quality RNA isolated from postmortem human brain neocortex specimens. (A) Agilent analysis of three samples from schizophrenia subjects. (B) Representative region of miRNA array (LC Science) hybridization with Cy3- and Cy5- labeled small brain RNA fractions from schizophrenia and control subjects. The bracket refers to 5S-rRNA probes; in the left column probes with perfect match (PM) and mismatch (MM) for controls are spotted

in large collections of specimens which may be combined with genetic analysis of the miRNA genes in the same subjects.

13.2.5.2

Genetics of miRNA

There is little knowledge about genetic variability in the structure or expression of miRNAs in the human genome. The comprehensive genetic analysis of miRNA in common forms of neurodegenerative (e.g., Alzheimer’s disease) and mental disorders (e.g., bipolar depression and schizophrenia) have yet to be undertaken. A few considerations would be useful to keep in mind in any design of such studies. First, many miRNAs are located within transcriptional units of protein-encoding genes (“host” genes), therefore transcriptional regulation of these micro RNA would correlate with the transcription of the “host” gene. The SNPs (single nucleotide polymorphisms) in promoter regulatory regions for the “host” gene or multiple SNPs (haplotypes) covering large genomic interval (e.g., >50–100 kb) for this gene may contribute to individual variability in a level of miRNA in CNS. On the other hand, independent transcription regulation for miRNA located in introns or in intergenic regions is predicted for many miRNA genes. Thus variations in regulatory elements in immediate 5′-region of miRNA precursor may potentially affect the transcription of the miRNA gene.

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Second, mutations in precursor miRNA or mature miRNA may directly affect the efficiency of RNA:RNA binding and interaction of miRNA and target mRNA. We predict, however, that given the tiny size of the mature miRNA (~22 nt) and short sequences for precursor miRNA (~70–90 nt), the miRNA genes are relatively small targets for stochastic mutational process in comparison with larger protein encoding genes. Thus the frequency of population SNPs or de novo mutations in miRNA genes is anticipated to be relatively low. Nevertheless, direct sequencing of 173 human pre-miRNA regions in 96 unrelated individuals identified 10 polymorphisms [18] in 10 miRNAs including species (e.g., miR-146, miR-149, miR-138) expressed in adult brain [7]. Most of these mutations do not disrupt the integrity of the predicted stems of precursor miRNA. In our pilot study, we analyzed miRNA located in schizophrenia-susceptible loci. MiR-130b is expressed in the brain and is located in the most consistently reported susceptibility locus for schizophrenia (22q11). Micro-deletions in 22q11 occur at a frequency of 0.5–3% of individuals with schizophrenia; that is 30-fold more than in non-schizophrenic cohort strongly demonstrating that this region harbors one or more genes contributing to schizophrenia pathway [3, 16, 22]. The putative target for miR-130b was found in the 3′UTR of the MECP2 gene. MECP2 gene mutations cause disorders with autistic condition (Rett syndrome) and the contribution of MECP2 gene variation was implicated in the case of schizophrenia. We found a common single nucleotide polymorphism (C/G) at the -63 bp position from the start of the precursor miR-130b (rs861843) disrupting and generating potential regulatory elements (Fig. 13.5) [7]. No statistically significant prevalence of the C allele was found in the total group of paranoid schizophrenics (Ms cohort) (P = 0.960, OR = 1.012, C.I. = 0.737–1.391). Expression analysis was undertaken using Real-Time PCR and TaqMan MiRNA Assays (Applied Biosystems). On average, there was no strong difference in the expression of miR130b between schizophrenia and normal groups (12 normal individuals and 12 individuals with schizophrenia). No correlation of expression of miR-130b and the -63 C/G genotypes was observed in postmortem brain specimens. This first genetic study, coupled with expression analysis of miRNA genes, although producing negative results, implicates the feasibility of convergent miRNA analysis in psychiatric diseases. Other miRNAs located in this region must be tested. In addition to miRNA genes this region also contains DiGeorge syndrome critical region gene 8 (DGCR8). DGCR8 forms complex with Drosha that cleaves primary microRNA substrates into precursor miRNA and is involved in maturation of the microRNA transcripts [27]. Thus, it is conceivable, that in addition to miRNA analysis, the search for mutations in genes essential for miRNA biogenesis may also lead to the identification of genetic factors for psychiatric pathologies. In another recent study the bioinformatics search for SNPs within the mature miRNA sequence and in the flanking sequences (~100 bp upstream or downstream) of 101 miRNA genes expressed in brain identified 46 putative SNPs. Among them 18 SNPs were informative for a genetic association study. Three groups of schizophrenia-control Scandinavian subjects (Danish, Swedish and Norwegian) were tested in this study. Neither of the SNPs showed consistent association with

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Fig. 13.5 Population polymorphism in 5′-putative regulatory region for miR130b gene: (A) chromosomal location miR130b gene; (B) precursor gene structure and polymorphism found in 5′-upstream region; (C) putative regulatory regions for two allelic variants

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schizophrenia in all three groups [15]. However, SNP rs17578796 in miR-206 showed statistically significant association in the joint sample (p = 0.041) and in the Danish sample (p = 0.002) even after correction for multiple testing. It must be noted that the frequency of the polymorphic allele in these groups was very low and varied from 0.4% to 1.6%. Thus given the number of patients in these groups (from 163 to 420 individuals) the nominally significant positive association may be a result of Type I error. The significance of population variations in mature miRNA which would affect the efficiency of mRNA targeting has yet to be investigated in large population cohorts. We hypothesize that another type of polymorphism, copy number variation (CNV) may be a more common type of genetic variability for miRNA genes. Massive analysis of the miRNA genes for CNV in population studies and case-control cohorts would be interesting and novel approach towards finding the genomic variations underlying neuropsychiatric pathologies. A genomic search for CNVs on a relatively wide genomic scale has identified putative CNV and duplicated genomic regions harboring some miRNA genes [46]. Location of many miRNA overlapped with putative loci implicated schizophrenia and autism (Fig. 13.6). The SNPs in putative neurogene targets for miRNAs have also to be tested in case-control of family studies. Some SNPs in 3 -UTR sequences complementary to miRNAs can be predicted already from available SNPs data bases, e.g., for dopamine receptor D3 (DRD3), BDNF, GABRA4 and other neurogenes implicated in schizophrenia molecular pathways ([9]; and our unpublished observations). These putative targets would need to be tested experimentally for interactions of both alleles with corresponding miRNAs and, if the interaction was confirmed, the polymorphisms would be worthy of further analysis in a genetic association study in psychiatric disease-control groups.

13.2.6

Perspectives

To gain better understanding of the role of miRNA and other small RNA in neuropsychiatric pathologies a combination of approaches needs to be undertaken. The invertebrate or rodent and primate animal models have been designed for Alzheimer’s disease, other brain neurodegenerative disorders, affective disorders or, in part, even for schizophrenia–related behavioral phenotypes. The down- or up-regulation of miRNAs in such models may clarify their function and identify new pathways modulating these pathologies. The brain is a very complex organ with multilayered morphological and functional neural and non-neural cell networks altering during ontogenesis and in response to environmental conditions. Thus miRNA-mediated regulation may be a very dynamic spatio-temporal process which has to be studied within specific neural network connections. The comparative miRNA gene expression analysis of cohorts of patients and control individuals using hybridization chip arrays may have some confounding effects well known for protein encoding gene expression profiles. Thus careful

13 MicroRNA in Neuropsychiatric Diseases Fig. 13.6 Synthetic map for the susceptibility loci for schizophrenia and autism and miRNA genes. There are more than 30 miRNAs genes/clusters located in putative schizophrenia and autism loci

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design in miRNA gene expression study that would include large numbers of casecontrol samples should be considered. The positive sign is that miRNA seems to be very stable in postmortem brain tissues and the limited number of miRNA genes existing in the human genome allows for the use of an accurate RT-PCR quantitative analysis of all miRNAs (Applied Biosystem/Ambion assays) in a large cohort of postmortem specimens. We believe that in the near future ultra-deep sequencing will be a most promising technology for the identification of small RNA species expressed in the brain at a low level and for accurate quantification of the RNA transcripts, e.g., in schizophrenia versus control. The most appropriate system for such analysis have recently emerged. (1) Massive parallel “pyrosequencing” by 454 Life Science system (Genome Sequence 20 tm DNA sequencing System: GS20, Roche/454 Life Science) that enables the analysis of up to 25 million neucleotides in a single reaction (<250–400 bp in average) and (2) Solexa technology (in the latest version Illumina Genome Analyzer) that produces one billion bases in a single run but for short 30–40 base sequence reads. Given the small size of miRNAs these systems must be particularly effective for identification of novel miRNA transcripts and quantitative expression profiling of small RNA in brain specimens of cohort of patients with neurological or psychiatric disease in comparison to control individuals.

13.2.6.1

Delivery of Small RNA to the Brain

What practical application of specific miRNAs might there be if their role in the modulation of brain pathology is proven? The number of small antisense inhibitors for miRNA and application of miRNA in cultured cells has become available. However, the major obstacle in the therapy for neuropsychiatric diseases is the blood-brain barrier that prevents intravenous administration of many putative molecules with therapeutic effects including small RNAs. Very encouraging data were reported recently showing that small neurotropic peptide derived from rabies virus glycoprotein (RVG) can efficiently deliver small interfering RNA to the brain after intravenous injection in mice. Remarkably, the peptide binds to acetylcholine receptors in neurons [25]. We can speculate that since the loss of acetylcholine neurons is a primary hallmark of Alzheimer’s disease pathogenesis this system may be particularly promising in delivery of miRNA regulators to susceptible neurons implicated in Alzheimer’s disease neurodegeneration. The endogenous miRNAs targeting a particular set of neurogenes along with siRNAs may be potentially an attractive new type of therapeutic molecules to be developed for interfering with neurological and mental pathologies. Acknowledgements The authors were supported by the Stanley Research Medical Institute, and, in part, by NIH NINDS (E.I.R.) and NIH NIDDK (E.I.R.), Alzheimer’s Association, RFBR, Russian Ministry of Science and Technology and Presidium of the Russian Academy of Sciences. The frozen tissue specimens were donated by the Stanley Medical Research Institute Brain collection courtesy of Drs. Michael B. Knable, E. Fuller Torrey, Maree J. Webster, and Robert H. Yolken.

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References 1. American College of Obstetricians and Gynecologists Committee on Genetics (2006) ACOG committee opinion. No. 338: Screening for fragile X syndrome. Obstet Gynecol 107:1483–1485 2. Abelson JF, Kwan KY, O’Roak BJ et al. (2005) Sequence variants in SLITRK1 are associated with Tourette’s syndrome. Science 310:317–320 3. Bassett AS, Chow EW, AbdelMalik P et al. (2003) The schizophrenia phenotype in 22q11 deletion syndrome. Am J Psychiatr 160:1580–1586 4. Bernstein E, Kim SY, Carmell MA et al. (2003) Dicer is essential for mouse development. Nat Genet 35:215–217 5. Bilen J, Liu N, Bonini NM (2006) A new role for microRNA pathways: modulation of degeneration induced by pathogenic human disease proteins. Cell Cycle 5:2835–2838 6. Brennecke J, Hipfner DR, Stark A et al. (2003) Bantam encodes a developmentally regulated microRNA that controls cell proliferation and regulates the proapoptotic gene hid in Drosophila. Cell 113:25–36 7. Burmistrova OA, Goltsov AY, Abramova LI et al. (2007) MicroRNA in schizophrenia: genetic and expression analysis of miR-130b (22q11). Biochemistry (Mosc) 72:578–582 8. Caudy AA, Myers M, Hannon GJ et al. (2002) Fragile X-related protein and VIG associate with the RNA interference machinery. Genes Dev 16:2491–2496 9. Chen K, Rajewsky N (2006) Deep conservation of microRNA-target relationships and 3∋ΥΤΡ motifs in vertebrates, flies, and nematodes. Cold Spring Harb Symp Quant Biol 71:149–156 10. Cheng HY, Papp JW, Varlamova O et al. (2007) microRNA modulation of circadian-clock period and entrainment. Neuron 54:813–829 11. Davis CJ, Bohnet SG, Meyerson JM et al (2007) Sleep loss changes microRNA levels in the brain: a possible mechanism for state-dependent translational regulation. Neurosci Lett 422:68–73 12. Giraldez AJ, Cinalli RM, Glasner ME et al. (2005) MicroRNAs regulate brain morphogenesis in zebrafish. Science 308:833–838 13. Gitlin L, Karelsky S, Andino R (2002) Short interfering RNA confers intracellular antiviral immunity in human cells. Nature 418:430–434 14. Greco SJ, Rameshwar P (2007) MicroRNAs regulate synthesis of the neurotransmitter substance P in human mesenchymal stem cell-derived neuronal cells. Proc Natl Acad Sci USA 104:15484–15489 15. Hansen T, Olsen L, Lindow M et al. (2007) Brain expressed microRNAs implicated in Schizophrenia etiology. PLoS ONE 2:e873 16. Horowitz A, Shifman S, Rivlin N et al. (2005) A survey of the 22q11 microdeletion in a large cohort of schizophrenia patients. Schizophr Res 73:263–267 17. Ishizuka A, Siomi MC, Siomi H (2002) A Drosophila fragile X protein interacts with components of RNAi and ribosomal proteins. Genes Dev 16:2497–2508 18. Iwai N, Naraba H (2005) Polymorphisms in human pre-miRNAs. Biochem Biophys Res Commun 331:1439–1444 19. Jin P, Alisch RS, Warren ST (2004) RNA and microRNAs in fragile X mental retardation. Nat Cell Biol 6:1048–1053 20. John B, Enright AJ, Aravin A et al. (2004) Human MicroRNA targets. PLoS Biol 2:e363 21. Johnston RJ, Hobert O (2003) A microRNA controlling left/right neuronal asymmetry in Caenorhabditis elegans. Nature 426:845–849 22. Karayiorgou M, Gogos JA (2004) The molecular genetics of the 22q11-associated schizophrenia. Brain Res Mol Brain Res 132:95–104 23. Kennedy S, Wang D, Ruvkun G (2004) A conserved siRNA-degrading RNase negatively regulates RNA interference in C. elegans. Nature 427:645–649 24. Krichevsky AM, King KS, Donahue CP et al. (2003) A microRNA array reveals extensive regulation of microRNAs during brain development. RNA 9:1274–1281 25. Kumar P, Wu H, McBride JL et al. (2007) Transvascular delivery of small interfering RNA to the central nervous system. Nature 448:39–43

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E.I. Rogaev et al.

26. Landgraf P, Rusu M, Sheridan R et al. (2007) A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 129:1401–1414 27. Landthaler M, Yalcin A, Tuschl T (2004) The human DiGeorge syndrome critical region gene 8 and Its D. melanogaster homolog are required for miRNA biogenesis. Curr Biol 14:2162–2167 28. Leaman D, Chen PY, Fak J et al. (2005) Antisense-mediated depletion reveals essential and specific functions of microRNAs in Drosophila development. Cell 121:1097–1108 29. Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120:15–20 30. Lim LP, Lau NC, Garrett-Engele P et al. (2005) Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature 433:769–773 31. Makeyev EV, Zhang J, Carrasco MA et al. (2007) The MicroRNA miR-124 promotes neuronal differentiation by triggering brain-specific alternative pre-mRNA splicing. Mol Cell 27:435–448 32. Miska EA, Varez-Saavedra E, Townsend M et al. (2004) Microarray analysis of microRNA expression in the developing mammalian brain. Genome Biol 5:R68 33. Muchowski PJ, Wacker JL (2005) Modulation of neurodegeneration by molecular chaperones. Nat Rev Neurosci 6:11–22 34. Nelson PT, Baldwin DA, Kloosterman WP et al. (2006) RAKE and LNA-ISH reveal microRNA expression and localization in archival human brain. RNA 12:187–191 35. Okamura K, Ishizuka A, Siomi H et al. (2004) Distinct roles for Argonaute proteins in small RNA-directed RNA cleavage pathways. Genes Dev 18:1655–1666 36. O’Neill JS, Hastings MH (2007) Circadian clocks: timely interference by MicroRNAs. Curr Biol 17:R760–R762 37. Perkins DO, Jeffries C, Sullivan P (2005) Expanding the ‘central dogma’: the regulatory role of nonprotein coding genes and implications for the genetic liability to schizophrenia. Mol Psychiatr 10:69–78 38. Pfeffer S, Sewer A, Lagos-Quintana M et al. (2005) Identification of microRNAs of the herpesvirus family. Nat Methods 2:269–276 39. Rogaev EI (2005) Small RNAs in human brain development and disorders. Biochemistry (Mosc) 70:1404–1407 40. Sathyan P, Golden HB, Miranda RC (2007) Competing interactions between micro-RNAs determine neural progenitor survival and proliferation after ethanol exposure: evidence from an ex vivo model of the fetal cerebral cortical neuroepithelium. J Neurosci 27:8546–8557 41. Schaefer A, O’Carroll D, Tan CL et al. (2007) Cerebellar neurodegeneration in the absence of microRNAs. J Exp Med 204:1553–1558 42. Schratt GM, Tuebing F, Nigh EA et al. (2006) A brain-specific microRNA regulates dendritic spine development. Nature 439:283–289 43. Simmer F, Tijsterman M, Parrish S et al. (2002) Loss of the putative RNA-directed RNA polymerase RRF-3 makes C. elegans hypersensitive to RNAi. Curr Biol 12:1317–1319 44. Todd PK, Mack KJ, Malter JS (2003) The fragile X mental retardation protein is required for type-I metabotropic glutamate receptor-dependent translation of PSD-95. Proc Natl Acad Sci USA 100:14374–14378 45. Vaisse C, Halaas JL, Horvath CM et al. (1996) Leptin activation of Stat3 in the hypothalamus of wild-type and ob/ob mice but not db/db mice. Nat Genet 14:95–97 46. Wong KK, DeLeeuw RJ, Dosanjh NS et al. (2007) A comprehensive analysis of common copy-number variations in the human genome. Am J Hum Genet 80:91–104 47. Xie X, Lu J, Kulbokas EJ et al. (2005) Systematic discovery of regulatory motifs in human promoters and 3′ UTRs by comparison of several mammals. Nature 434:338–345 48. Xu P, Vernooy SY, Guo M et al. (2003) The Drosophila microRNA Mir-14 suppresses cell death and is required for normal fat metabolism. Curr Biol 13:790–795 49. Zalfa F, Eleuteri B, Dickson KS et al. (2007) A new function for the fragile X mental retardation protein in regulation of PSD-95 mRNA stability. Nat Neurosci 10:578–587 50. Kim J, Inoue K, Ishii J et al. (2007) A MicroRNA feedback circuit in midbrain dopamine neurons. Science 317:1220–1224

Chapter 14

Role of Repeat-Associated MicroRNA (ramRNA) in Fragile X Syndrome (FXS) Shi-Lung Lin* and Shao-Yao Ying

Abstract A large portion of the genome is non-coding DNA, which frequently contains redundant microsatellite-like trinucleotide repeats with function not yet to be known. Recent studies have shown that many of these trinucleotide repeats are involved in triplet repeat expansion diseases (TREDs), such as fragile X syndrome (FXS), Huntington’s disease (HD), myotonic dystrophy (DM), and a number of spinocerebellar ataxias (SCAs). The trinucleotide repeats can fold into RNA hairpins and are further processed by Dicer to form microRNA (miRNA)like molecules, capable of triggering targeted gene-silencing effects in the TREDs; however, the pathogenic mechanism of these repeat-associated miRNAs (ramRNAs) is unclear. To resolve this question, we have identified the first native ramRNAs in FXS and successfully developed a ramRNA-mediated transgenic zebrafish model for studying the role of the ramRNAs in FXS-related neurodegeneration. Based on this model, we found that ramRNA-induced DNA methylation of the FMR1 5′-UTR CGG trinucleotide repeat expansion is central to FXS etiology. This epigenetic modification leads to physical, neurocognitive and emotional characteristics linked to the transcriptional FMR1 gene inactivation and the deficiency of its protein product. FMR1 deficiency often causes synapse deformity in the neurons essential for cognition and memory activities. Furthermore, the metabotropic glutamate receptor (mGluR)-activated long-term depression (LTD) is augmented after the FMR1 inactivation, suggesting that exaggerated LTD may be responsible for aspects of abnormal neuronal responses in FXS, such as autism. Therefore, the establishment of this ramRNA-mediated transgenic animal model provides a new avenue to dissect the physiopathological and epigenetic alterations of TREDs affected by the microsatellite-like trinucleotide repeat expansions, with the hope of providing insights into areas of opportunity for therapeutic intervention. Keywords microRNA (miRNA), repeat-associated miRNA (ramRNA), microsatellite nucleotide repeat, triplet repeat expansion disease (TRED), fragile X mental Department of Cell and Neurobiology, Keck School of Medicine, University of Southern California, 1333 San Pablo Street, BMT-403, Los Angeles, CA 90033, USA * Corresponding author: Phone: 002-1-323-442-1658; Fax: 002-1-323-442-3466; E-mail: [email protected]

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retardation syndrome (FXS), transcriptional gene silencing, epigenetic modification, DNA methylation, FMR1, autism.

14.1

Introduction

Over 97% of the human genome is the non-coding DNA, which varies from one species to another, and changes in these sequences are frequently noticed to manifest biological and clinical dysfunction. Many non-coding DNA sequences encode microRNA (miRNA) genes, which are involved in a wide variety of physiological and developmental events, including, but not limited, developmental timing, embryonic patterning, cell fate determination, cell lineage differentiation, cell proliferation, apoptosis, organogenesis, growth control and metabolism [2, 3]. MicroRNAs (miRNAs) are small single-stranded RNA molecules of about 18 to 27 nucleotides in length that regulate the expression of other protein-coding genes through an intracellular gene silencing mechanism, namely RNA interference (RNAi). After transcribed from the non-coding DNA, instead of being translated, the primary miRNA transcript (pri-miRNA) is processed to a hairpin-like stem-loop precursor, termed pre-miRNA, and finally to a mature miRNA. The mature miRNA molecule binds complementarily to matched sequences of one or more messenger RNAs (mRNAs) for executing targeted gene silencing through either direct mRNA degradation or translational suppression. Intron occupies the largest proportion of non-coding sequences in a gene. Gene transcription generates precursor messenger RNA (pre-mRNA), which contains four major parts including 5′-untranslational region (UTR), protein-coding exon, non-coding intron and 3′-UTR. In a broad definition, both 5′- and 3′-UTR are a kind of intron extension. The intron can be as big as several ten-kilo-base nucleotides and was thought to be a huge genetic waste in gene transcripts; however, this misconception is changed after the first discovery of intronic miRNA [1, 30]. Rodriguez et al. [45] have performed a computational analysis of 161 vertebrate miRNAs and found that 30 are located in an exon of a non-coding gene, 27 in an intron of a non-coding gene, 90 in an intron of a protein-coding gene, and 14 in both exonic and intronic locations, depending on the alternative splicing pattern of the encoded gene. The majority of miRNAs located in the intron region of a gene suggests that expression of these intronic miRNAs may be coordinately regulated with their flanking mRNAs. In this way, an intronic miRNA differs from the previously found intergenic miRNA in its unique requirement of RNA splicing for miRNA processing and maturation [30, 64]. Also, because introns often contain multiple translational stop codons recognized by the intracellular nonsense-mediated decay (NMD) system [28, 65], most of the unstructured intron parts can be quickly degraded after RNA splicing to prevent excessive RNA accumulation, which is toxic to the cells. It has been measured that approximately 10% of a spliced intron is preserved after the NMD digestion in cytoplasm with a moderate half-life long enough for further functioning [6]. This provides a cellular source for intronic miRNA biogenesis.

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14.2

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Biogenesis of Intronic MicroRNA (miRNA)

Intronic miRNA is a new class of small regulatory RNAs derived from the noncoding DNA regions of a gene, such as intron, 5′- and 3′-UTR. Many introns and UTRs contain tri-or tetra-nucleotide repeat expansions, capable of being transcribed and processed into repeat-associated microRNAs (ramRNAs) [15, 26]. In vertebrates, the biogenesis of intronic miRNAs conceivably involves five steps (Fig. 14.1). First, miRNA is generated, as a part of a long primary precursor microRNA (pri-miRNA) located in the intron or UTR of a primary gene transcript (pre-mRNA), by type II RNA polymerases (Pol-II) [30]. Second, after intron splicing, the long pri-miRNA is excised by spliceosomal components and/ or maybe further processed by other Drosha-like RNaseIII endonucleases/microprocessors to form precursor microRNA (pre-miRNA) [23, 30, 34]. Ruby et al. [46] have recently shown that intronic miRNA precursors can bypass Drosha processing. Third, the pre-miRNA is then exported out of the cell nucleus, probably by Ran-GTP and a receptor for exportins [41, 63]. Fourth, once in the cytoplasm, a Dicer-like nuclease cleaves the pre-miRNA to form mature miRNA. Lastly, the mature miRNA is assembled into a ribonuclear particle (RNP) to form a RNA-induced silencing complex (RISC) or RNA-induced transcriptional silencing (RITS) complex for executing RNA interference (RNAi)-related gene silencing mechanisms [22, 47]. Although the biogenic pathways of siRNA and miRNA are thought to be relatively comparable, many characteristics of the mechanistic components are distinctly different from each other [27, 53]. In zebrafish, we have observed that the stem-loop structure of intronic pre-miRNA is involved in strand selection for mature miRNA during miRNA-associated RISC (miRISC) assembly [34]. Furthermore, unlike the siRNA/shRNA pathway, excessive RNA accumulation can be prevented by the intracellular NMD mechanism, a specific RNA degradation system for unstructured spliceosomal introns. These findings indicate that the siRNA/shRNA pathway is likely lack of some advanced properties required for the regulation of intronic miRNA generation and functioning. Given that natural evolution gives raise to more complexity and more variety of introns in higher animals and plants for coordinating their vast gene expression volumes and interactions, any intronic repeat expansion or deletion may cause dysregulation of certain miRNA biogenesis or miRNA–target interaction and thus lead to triplet repeat expansion diseases (TREDs). As shown in Table 14.1, TREDs include dentarubral-pallidoluyian atrophy (DRPLA), fragile X mental retardation syndrome (FXS), Friedreich ataxia (FRDA), Huntington’s disease (HD), myotonic dystrophy (DM), spinobulbar muscular atrophy (SBMA), and a number of spinocerebellar ataxias (SCAs). These TREDs all express mutant genes with elevated expansion of either CGG/CCG (FXS/FXTAS) or CAT/CTG (others) repeats; however, the correlation between the intron-encoded repeat-associated microRNA (ramRNA) and its related TRED remains to be determined. In order to understand the role of a specific ramRNA in the pathogenic mechanism of a TRED, we must first identify its RNA molecular structure and function. Nevertheless, although the

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Fig. 14.1 Biogenesis of intronic microRNA (miRNA). Intronic miRNA is generated as a part of precursor messenger RNA (pre-mRNA), containing protein-coding exons and non-coding introns. The introns include in-frame intron, 5′- and 3′-untranslational region (UTR). The introns are spliced out of a pre-mRNA to form miRNA precursors (pri- and pre-miRNA) by intracellular spliceosomes and further excised by RNaseIII Dicer to generate small mature miRNAs, which are capable of inducing RNA interference (RNAi) against complementary gene expression, while the exons are ligated to form a mature messenger RNA (mRNA) for protein translation Table 14.1 List of triplet repeat expansion diseases (TREDs) in human TRED disorders Pathogene, site Expansion Dentarubral-pallidoluyian atrophy (DRPLA) Fragile X syndrome (FXS) Fragile X tremor ataxia syndrome (FXTAS) Fragile X syndrome E (FRAXE) Friedreich ataxia (FRDA) Myotonic dystrophy type 1 (DM1) Myotonic dystrophy type 2 (DM2) Huntington’s disease (HD) Huntington’s disease-like 2 (HDL2) Spinobulbar muscular atrophy (SBMA) Spinal cerebellar ataxia (SCA) types 1–3, 7 SCA type 8 (SCA8) SCA type 17 (SCA17) ND = not defined yet

Repeat number

Atrophin-1, exons

CAG

49–88

FMR1, 5′-UTR FMR1, 5′-UTR

CGG CGG

>200 70–120

FMR2, 5′-UTR Frataxin, intron DMPK, 3′-UTR ZNF9, intron 1 Huntingtin, exon 1 JPH3, intron, exon, or 3′-UTR Androxgen receptor, intron Ataxin 1–3, 7, exons

CCG GAA CTG CCTG CAG CTG

200–900 200–1,700 50–1,000 75–11,000 40–121 66–78

CAG

38–62

CAG

37–300

ND (ncRNA) TBP, exon

CTG CAG

>74 47–63

existence of ramRNA has been proposed for several years [15, 21, 26], there is no solid evidence for its identity in nature yet. In this chapter, we will demonstrate how we discover the first ramRNA identity and use it as a tool to establish a transgenic animal model for studying its function in vivo.

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Identification of Repeat-Associated MicroRNA (ramRNA)

Recently, we have successfully detected and isolated the first native ramRNA identity in zebrafish, namely miR-fmr1, which is involved in the pathogenesis of fragile X syndrome (FXS). Two primary miR-fmr1 isoforms, miR-fmr1-27 and miR-fmr1-42, are found in the fmr1 5′-UTR CGG repeat region approximately 65-nucleotide upstream of the translational start codon (accession number NM152963). Both ramRNAs contain the same seed and core sequence to interact with the zebrafish fmr1 gene or gene transcript. As shown in Fig. 14.2, we can clearly observe the tissue-specific expression pattern of both miR-fmr1 in the zebrafish brain, using fluorescent in-situ hybridization (FISH) with a locked nucleic acid (LNA) probe directed against the miR-fmr seed and core sequence. The LNA-modified DNA oligonucleotide is a high-affinity RNA analogue with a bicyclic furanose unit locked in an RNA-mimicking sugar conformation, which results in unprecedented hybridization affinity towards complementary single-stranded RNA molecules. Furthermore, to screen the exact miRNA sequence in a defined fmr1 5′-UTR region, we have also developed a nucleotide-shift probing technology for isolating and sequencing the specific miRNA, as described in our previous report [35]. In brief, we first synthesize a series of 20-nucleotide antisense DNA probes with two base intervals franking across the defined gene region, label each probe with fluorescein, and then use them, respectively, to precipitate the targeted miRNA(s) from an isolated total small RNA library. The total small RNAs are extracted by mirVana filter columns, following the manufacture’s suggestion (Ambion, Austin, TX). By this way, the probe-bound miRNA can be easily purified and collected by 15,000 × g centrifugation with a bead-conjugated antibody directed against the fluorescein. After sequencing, the result is shown in Fig. 14.2J. Figure 14.2 shows that the normal expression pattern of miR-fmr1 is limited in the neuronal bodies and nuclei but not the dendrites of the hippocampal-cortical junction (A–C), hippocampal stratum radiatum (D–F), and cerebellum (G–I) neurons, which are exactly opposite to the normal fmr1 expression pattern in these neurons. Figures 14.2K, K′ further indicate that over-expression of the miR-fmr1 can expand their distribution from the bodies to the dendrites, resulting in ramRNAmediated fmr1 gene silencing in the whole neurons (Fig. 14.3A). This distributional difference may serve as a marker for FXS diagnosis. To demonstrate the previously proposed transcriptional gene silencing effect on fmr1 [15, 21, 36], we have performed analysis of methylation-specific restriction enzyme cleavage in an isolated genomic fmr1 5′-UTR CGG repeat expansion region ranged from the – 1,103rd to +48th nucleotide flanking the translational start codon site (accession number NM152963). This isolated region is then digested with two different C*CGG-cutting restriction enzymes, HpaII (CpG methylation-blocking) and MspI (CpG methylation-cutting), respectively. Figure 14.3B shows that the neurons with miR-fmr1 over-expression often present approximately five to seven methylated sites in this isolated region, whereas only one to two methylated sites are found in

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Fig. 14.2 Expression patterns of native miR-fmr1 in wild-type zebrafish, as shown in lateral pallium-neocortical sections 1 and 2 (A–F) and cerebellar section 3 (G–I). J shows the sequence conformation f the miR-fmr1. (K and K′) show the comparison between normal (WT) and FXS (fmr1 KO) miR-fmr1 expression patterns in zebrafish pallium-neocortical neurons

Fig. 14.3 r(CGG)-derived ramRNA-mediated fmr1 gene silencing. (A) Fluorescent in-situ hybridization (FISH) analysis of fmr1 mRNA and anti-fmr1 miRNA (miR-fmr1) expressions in the brains of 7-day post-fertilization wild-type versus transgenic loss-of-fmr1-function (fmr1 KO) zebrafish. Fluorescent labels are shown in neurons (green EGFP), miRi-fmr1 miRNA (red RGFP) and fmr1 mRNA (blue DAPI). Gray arrows indicate the dendro-dendritic contacts between lateral pallium and neocortical neurons. (B) Methylation site cleavage assay with HpaII (CpG methylation-blocking) and MspI (CpG methylation-cutting) restriction enzymes shows the changes of CpG methylation patterns in the fmr1 5′-UTR r(CGG) expansion region of the wild-type versus fmr1 KO zebrafish brains

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that of the wild-type neurons. Therefore, the ramRNA-mediated gene silencing mechanism can occur at the transcriptional level through DNA methylation. Moreover, using a gene-knockout method with modified morpholino antisense oligonucleotides directed against some RNAi-associated genes, we have observed that this ramRNA-mediated fmr1 silencing mechanism may require Rad54-like protein (Rad54l) and methyl-CpG binding protein (MeCP2) activities. Both protein activities are essential for the CpG methylation of repetitive chromatin sequences in mammalian cells [10]. We particularly noted that the miR-fmr1-42 is specially characterized by its unique pre-miRNA structure consisting of (a) multiple loops and short matched stems in a relatively long hairpin precursor, (b) a nuclear import signal (NIS) motif probably to allow the re-entry of the mature ramRNA into the cell nucleus, and (c) a C/G-rich gene binding motif to recruit the DNA methylation machinery. These findings support a novel disease model in which mature ramRNAs originating from the trinucleotide repeat expansion of a gene can reversely bind back to the corresponding triplet repeat regions of the gene. More trinucleotide repeats in the gene generate more mature ramRNAs. With more ramRNAs binding back to the targeted gene, DNA methylation of the triplet repeat regions of the gene then takes place, consequently leading to targeted gene inactivation. This model would be most suitable for studying TREDs involving epigenetic alterations.

14.4

Intronic ramRNA and Fragile X Mental Retardation Syndrome (FXS)

FXS is one of the most common mental retardation and neuropsychiatric disorders in humans, affecting approximately one in 2,000 males and one in 4,000 females [14]. The characteristic features of FXS in boys include a long face, prominent ears, large testes, delayed speech, hyperactivity, tactile defensiveness, gross motor delays, and autistic behaviors. Much less is known about girls with FXS. This disease is caused by a dynamic mutation [expansion of microsatellite-like trinucleotide – (cytosine-guanine-guanine) – repeats or termed r(CGG)] at an inherited fragile site on the long-arm of the X chromosome, where locates the FMR1 gene. Because this mutation is dynamic, it can change in length and hence in severity from generation to generation, from person to person, and even within a given person. Patients with FXS have an increased number of r(CGG) >200 copies in the 5′-UTR of the FMR1 gene [9, 19, 20]. This CpG-rich r(CGG) expansion region is often heavily methylated, as shown in Fig. 14.3B. That means, the hydrogen atom of cytosine (C) is replaced with a methyl group and thus the cytosine is conversed to 5-methylcytosine in the FMR1 5′-UTR. Such r(CGG) expansion and methylation leads to physical, neurocognitive and emotional characteristics linked to the FMR1 inactivation and the deficiency of its protein product. FMR1 encodes an RNA-binding protein, FMR1 or FMRP, which is associated with polyribosome assembly in an RNP-dependent manner and capable of suppressing

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translation through an RNAi-like pathway that is important for neuronal development and plasticity. FMR1 also contains a nuclear localization signal (NLS) and a nuclear export signal (NES) for shuttling certain mRNAs between nucleus and cytoplasm [7, 52]. Therefore, excessive expression of r(CGG)-derived ramRNAs during embryonic brain development may cause early FMR1 gene inactivation, leading to the pathogenesis of FXS. Two theories have been proposed to explain this FMR1 inactivation mechanism in FXS. First, [15] found that non-coding RNA transcripts transcribed from the FMR1 r(CGG) expansion can fold into RNA hairpins and are further processed by RNaseIII Dicer to suppress the FMR1 expression. Second, [21] suggested that miRNA-mediated gene methylation may occur in the CpG regions of the FMR1 r(CGG) expansion, which are targeted by hairpin RNAs derived from the 3′-end of the FMR1 expanded allele transcript. Conceivably, we proposed that the Dicer-processed hairpin RNAs may trigger the formation of RITS assembly on the homologous r(CGG) sequences and result in transcriptional repression of the FMR1 chromatin locus.

14.5

Design of a Vector-Based ramRNA Expression System

Ongoing neuroscience research on FXS in animal models like the FMR1-deleted mouse and fly provides a wealth of information of subcellular, cellular, and intercellular networks or circuits – to delineate the neurobiology of this disorder, but none is closely related to the pathogenic role of non-coding RNAs playing in the FXS etiology. To overcome this barrier, we have developed and established the first ramRNA-mediated loss-of-FMR1-function zebrafish strain as a viable animal model for studying the aforementioned r(CGG)-derived miRNA-induced FXS theory [34, 36]. This novel in vivo model can also be used to develop and test drugs or therapies for the cure of this disease. Our previous studies have shown that effective mature miRNAs can be generated from an artificial intron inserted in a vertebrate gene (Fig. 14.4) [30, 64]. As demonstrated in Fig. 14.5A, the intron containing certain pre-miRNA structures is co-transcribed with its encoding gene by a type-II RNA polymerase (Pol-II) and further excised by spliceosomal components to form mature miRNAs. Because this intronic miRNA biogenesis pathway is coordinately regulated by intracellular Pol-II transcription, RNA splicing and NMD mechanisms, the resulting miRNA effector is safe, effective and powerful as a new genetic tool for regulating targeted gene function of interest [31, 32]. Using this Pol-IImediated intronic miRNA expression system, we have tested and observed the target-specific RNAi effects of various man-made miRNAs in mouse and human cell lines in vitro [30, 31, 32, 37, 38] as well as mouse skin, chicken embryo and zebrafish in vivo [34, 36, 37]. These man-made miRNAs differ from native miRNAs in their pre-miRNA hairpin-like structures containing a tRNAMet loop instead of the large miRNA loop for facilitating their nuclear export by the exportin-5. Furthermore, using the same design system, [5, 66] have also observed that both native intergenic and intronic miRNAs possess the same RNAi effectiveness, while

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Pre-mRNA construct with SpRNAi: 5’-promoter – exon 1 – artificial intron 5’splice site – pre-miRNA insert After intronic insert is spliced:

(SpRNAi) – exon 2 – 3’ T codons

– BrP – PPT –3’ T codons – 3’ splice site

5’-UTR – exon1 – exon 2 (mRNA) – 3’-UTR + Intronic microRNAs

Fig. 14.4 Schematic construct of the artificial SpRNAi intron in a recombinant gene, SpRNAiRGFP, for intracellular expression and processing. The major components of SpRNAi include several consensus nucleotide elements, consisting of a 5′-splice site, a branch-point motif (BrP), a poly-pyrimidine tract (PPT), a 3′-splice site and a pre-miRNA insertion site located between the 5′-splice site and the BrP motif. The SpRNAi is co-expressed with its encoding SpRNAi-RGFP gene under the regulation of either a eukaryotic Pol-II RNA promoter or a compatible viral promoter for cell-type- or tissue-specific transcription. After RNA splicing, mature miRNAs are released from the SpRNAi intron by spliceosomal cleavage and further Dicer processing. Simultaneously, the exons are linked together to form a mature mRNA for translating red RGFP, which is a reporter protein used for indicating the production of the mature miRNAs

the use of intronic miRNA allows co-expression of a protein marker with the miRNA at a defined expression ratio. Given that there are currently over 1,000 native miRNA species found in vertebrates and many more new miRNA homologs continue to be identified, we are able to utilize this intronic miRNA expression system as a transgenic tool for generating target-specific loss-of-gene-function animal strains or cell lines for evaluating the gene function of interest. Previously, several kinds of vector-based RNAi systems have been developed based on a directly exonic shRNA expression mechanism, using type-III RNA polymerases (Pol-III) [43, 44, 56]. Some of these studies have succeeded in maintaining constant gene silencing effects in vivo [42, 61]; nevertheless, they failed to provide tissue-specific RNAi efficacy in a certain cell population due to the ubiquitous existence of Pol-III activities. Moreover, because the Pol-III machinery often reads through a short DNA template in the absence of proper termination, large dsRNA products (e.g. >30 base-pairs) may be synthesized to cause unexpected interferon cytotoxicity, particularly in the vertebrates [13, 48]. Such a problem may also result from the competitive conflict between the Pol-III promoter and another vector promoter (i.e. LTR and CMV promoters). Sledz et al. [51] and [33] have reported that high concentrated siRNAs/shRNAs (e.g., >250 nM in human T cells) can cause strong cytotoxicity similar to that of long dsRNAs. Recently, [12] further demonstrated that the Pol-III-directed RNAi systems often generate high concentrated siRNAs/shRNAs to over-saturate the cellular microRNA pathway, resulting in global miRNA inhibition and cell death. In view of these problems, a Pol-II-mediated intronic miRNA expression system has the advantage of its auto-regulation by the cellular RNA splicing and NMD mechanisms [36, 62], both of which degrade excessive RNA accumulation to prevent cytotoxicity.

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Fig. 14.5 Design of an intronic microRNA (miRNA) expression system. (A) The principal design is based on the mechanism of native intronic miRNA biogenesis, as described in Fig. 14.1. A hairpin-like pre-miRNA construct is inserted in the intron region of a gene, such as the SpRNAiRGFP gene shown in Fig. 14.4. After gene transcription, the intron is co-expressed, spliced out of the gene transcript and then further excised into small miRNAs for triggering a desired RNAi effect, while the exons are ligated to form a mature mRNA for translating the gene-encoded reporter protein (e.g. RGFP). (B) Ectopic transfection of a pre-designed intronic miRNA expression system into the enhanced green fluorescent protein (EGFP)-positive Tg(actin-GAL4:UASgfp) zebrafish was found to elicit a strong silencing effect on the targeted EGFP gene (>80% suppression, left lane 4). The pre-miRNA was directed against EGFP and placed in the intron region of a mutant coral reef red fluorescent reporter protein (RGFP). Northern blot analysis (right) showed that the spliced miRNAs were only generated by correct intronic insertion, but not empty RGFP(–) or defective RGFP∆

The core design of the Pol-II-mediated intronic miRNA expression system is relied on a recombinant gene construct containing one or more splicing-competent RNA introns, namely SpRNAi [30]. Structurally, the SpRNAi consists of several consensus nucleotide elements such as 5′-splice site, branch-point motif (BrP), poly-pyrimidine tract (PPT) and 3′-splice site (Fig. 14.4). In addition, a pre-miRNA or pre-miRNA cluster insert is placed within the SpRNAi intron sequence between the 5′-splice site and the branch-point motif. This portion of an intron would normally form a lariat structure during RNA splicing and processing. The spliceosomal U2 and U6 snRNPs, both helicases, may be involved in the unwinding and excision of the lariat RNA fragment into pre-miRNA; however, the detailed processing

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mechanism remains to be elucidated. Moreover, the SpRNAi contains a multiple translational stop codon motif (T codons) in its 3′-proximal region, which if presented in a pre-mature mRNA, will signal diversion of the pre-mature mRNA processing to the nonsense-mediated decay (NMD) pathway and thus eliminates excess RNA accumulation in the cell. This feature guarantees the safety of the intronic miRNA biogenesis pathway. The SpRNAi intron can be incorporated into a gene or vector for co-expression in a cell or an organism. After co-expression, the SpRNAi is released by RNA splicing and then its encoded pre-miRNA insert can be processed into mature miRNA for triggering the desired gene silencing effect, while the exon transcripts of the gene are linked together to form a mature messenger RNA (mRNA) for protein synthesis. For example, we can insert the SpRNAi intron into the DraII restriction site of a redshifted fluorescent protein (RGFP) gene, which is derived from the mutated chromoprotein of coral reef Heteractis crispa. This step forms a recombinant SpRNAi-RGFP gene [30]. Technically, DraII cleavage at the RGFP 208th nucleotide site generates an AG–GN nucleotide break with three recessing nucleotides in each end, which can serve as 5′- and 3′-splice sites, respectively, for the SpRNAi insertion. Because this intronic insertion disrupts the fluorescent protein function of RGFP, it becomes possible to determine the occurrence of intron splicing and RGFP mRNA maturation through the appearance of red fluorescent light emission in the transfected cells. The RGFP gene sequence also contains seven exonic splicing enhancers (ESEs), which are essential for intron splicing efficiency. Using this SpRNAi-RGFP gene, we have tested various hairpin-like miRNA precursors (pre-miRNAs), many of which result in mature miRNAs with full capacity for triggering RNAi-associated gene silencing effects in mouse, rat and human cell lines in vitro [30, 31, 32, 38, 39] and in mouse, chicken embryo and zebrafish in vivo [34, 36, 37, 38]. As determined by Western blot analysis, Fig. 14.5B shows that the expression of intron-derived hairpin RNAs triggers the most strong suppression effect on the targeted EGFP gene product (lane 4), whereas off-target hairpin RNA inserts, i.e. empty intron RGFP(–) (lane 1), HIV-p24 intron (lane 2), integrin b1 intron (lane 3) and splicing-defective intron RGFP(∆) (lane 5), present no effects. No miRNA production from the splicing-defective intron RGFP(∆), indicating the necessity of spliceosomal splicing for intronic miRNA biogenesis. In addition, no silencing effect can be detected on off-target genes, such as RGFP, GAPDH and β-actin, suggesting that this gene silencing effect is highly specific to the target EGFP. The intronic miRNAs isolated by guanidinium-chloride ultracentrifugation can also elicit a strong, but short-term, gene silencing effect on the target genes, indicating their special RNAi inducibility and target specificity. More recent advances in the intronic miRNA expression system have been reported in mice. Chung et al. [5] successfully performed ectopic expression of a cluster of polycistronic miRNAs, which were processed into multiple miRNAs via the cellular miRNA pathway. This new RNAi approach has several advantages over the conventional Pol-III-directed shRNA expression systems. First, Pol-II expression can be tissue-specific, whereas Pol-III expression cannot. Second, Pol-II expression is compatible with the native miRNA pathway, while [12] have reported

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some incompatibility in the Pol-III-directed shRNA expression systems. Third, excessive RNA accumulation and cytotoxicity can be prevented by the NMD mechanism of a cellular intronic expression system, but not an exonic expression system [50]. Lastly, one Pol-II is able to express a large cluster (>10 kb) of polycistronic shRNAs, which can be further excised into multiple shRNAs via the native miRNA pathway, so as to prevent the promoter conflict that often occurs in a vector system containing multiple promoters. For instance, in many commercial U6directed shRNA expression systems, a self-inactivated vector promoter must be used to enhance the U6 promoter activity.

14.6

Transgenic Animal Model of ramRNA-Induced FXS

Animal models mimicking the human developmental events and diseases are essential for all sorts of biomedical research. Zebrafish (Danio rerio), a tropical fresh water fish, has set an impressive record as an in vivo viable model for studies of mechanisms involving in embryogenesis, organogenesis, physiology and behavior. One of the areas that stand to benefit most from the zebrafish model is developmental neuroscience. Advantages of using zebrafish include low cost, easy maintenance, rapid life cycle, small size, embryonic transparency, quick development (i.e. nervous system precursors presented by 6–7 hour post-fertilization (hpf); first neuron formed by 18–24 hpf), large generation number (i.e. clutch sizes from a single mating pair range between 100 to 200 embryos), and the fact that phenotypes can be easily assessed in many high-throughput assays [24, 58]. Ultimately, screening genetic suppressors is likely to add great value to the understanding of loss-of-gene-function phenotypes that are related to certain diseases, with the genes becoming logical drug target candidates. Also, screening for morphological or behavioral mutants is often more timeand cost-effective than the equivalent assays in mouse. These advantages have provided great advances in understanding the detailed pathological mechanisms underlying brain disorders that may lead to functional and behavioral defects. For example, zebrafish possess three FMRP-related genes, fmr1, fxr1 and fxr2; these genes are completely orthologous to the human FMR1, FXR1 and FXR2 genes, respectively [55]. The expression patterns of these genes in zebrafish are also consistent with those in mouse and human [55, 60], suggesting that zebrafish is one of the excellent models for studying human FMRP-related disorders. To investigate the molecular mechanism of r(CGG)-derived ramRNA-mediated FMR1 inactivation, we have developed a transgenic FXS model in zebrafish, of which fish fmr1 is silenced by over-expression of an isolated r(CGG) expansion from the fmr1 5′-UTR [36]. As shown in Fig. 14.6, we modified a VSV-G-positive pantropic retroviral vector, namely pLNCX2-rT, to deliver a recombinant SpRNAi-RGFP transgene expressing the precursor miR-fmr1 into a ubiquitous actin promoter-driven EGFP-expressing Tg(UAS:gfp) strain zebrafish, namely Tg(actin-GAL4:UAS-gfp). We first incorporated an isolated fmr1 5′-UTR r(CGG) expansion region (accession number NW001511047 from the 124,001st to 124,121st nucleotide) into the pre-miRNA

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insertion site (MluI–PuvI restriction site) of the SpRNAi-RGFP transgene [34, 37]. The pLNCX2-rT vector is derived from a modified pseudotype Moloney Murine Leukemia virus, pLNCX2 (Clontech, Palo Alto, CA), by insertion of a heart-specific ICML1-rT promoter in the original CMV promoter site [37]. Following the same protocol, we replaced the ICML1 promoter with an isolated fish GABA R2 promoter and then inserted the SpRNAi-RGFP transgene into the multiple cloning site (XhoI–ClaI restriction site) of the pLNCX2 construct, so as to form a transgenic pGABAR2-rT-SpRNAi retroviral vector. The GABA R2 and FMR1 genes are closely co-expressed in many brain areas, particularly in cortex, hippocampus, and cerebellum [40, 49]. After that, the pGABAR2-rT-SpRNAi vector was co-transfected with a pVSV-G vector into GP2-293 packaging cells (Clontech) to produce infectious but not replicable pGABAR2-rT-SpRNAi retrovirus. The pGABAR2-rT-SpRNAi vector can be directly injected into one-cell-stage fertilized eggs or used to prepare high-titer retrovirus for infecting the 1–10 hpf-stage zebrafish embryos [36, 37]. Transgenic F0 zebrafish so obtained were selectively separated into four groups based on their different fmr1 knockdown levels, as determined by Western blot analysis, including <50%, 50–75%, 75–90%, and >90% knockdown of fmr1 expression (Fig. 14.7). The zebrafish showing above 90% fmr1 knockdown were too defective to be raised into a transgenic line, while we had difficulty but succeeded in raising the fish with 75–90% fmr1 knockdown to sexual maturity and mated them to each other to generate the F1 founder line with a stable 75–85% fmr1 knockdown rate. After genome typing and transgene sequencing analyses, the F1 and F2 transgenic lines were show to possess two copies of the transgene in a consistent genomic insertion site located in the chromosome 18 close to the 3′proximity of the LOC565390 locus region, where encodes no gene. We have also measured that the fish with >90% fmr1 knockdown possess average three to five copies of the transgene located in two to three genomic insertion sites. Concomitant insertion is known to frequently occur in high-titer retroviral infection. The principle of this loss-of-fmr1-function zebrafish model (fmr1 KO) and human FXS are based on the same molecular interaction between the r(CGG)derived ramRNA and the FMR1 5′-UTR r(CGG) expansion. Both mechanisms are triggered by ramRNA-mediated FMR1 inactivation and result in similar pathological defects in relation to FMR1 deficiency. By transgenically increasing the fmr1 5′-UTR r(CGG) RNA expression, we have shown that the miR-fmr1 concentration is concurrently increased over sixfold in the transgenic zebrafish with 75–90% fmr1 knockdown (Fig. 14.7A). In comparison with the weak FMR1 promoter (100–1,000 copies of mRNA per cell), we used a fish GABA R2 promoter (5,000–15,000 copies of mRNA per cell) to boost the expression of the isolated fmr1 5′-UTR r(CGG) expansion and successfully detected the specific fmr1 silencing effect in the transgenic zebrafish, as determined by Northern blot (Fig. 14.7B) and Western blot (Fig. 14.7C, D) analyses. Because we only isolated 30% of the whole fmr1 5′-UTR r(CGG) expansion region, each transgene, after GABA R2 promoter-driven transcription, would approximately create a total two- to fourfold increase in the miRfmr1 production. As a result, the zebrafish with 75–90% fmr1 knockdown express sixfold more miR-fmr1 than the wild-type zebrafish, similar to the difference

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Fig. 14.6 Schematic procedure of ramRNA-mediated transgene delivery in zebrafish. A transgenic pGABAR2-rT-SpRNAi retroviral vector was used to infectively integrate the pre-designed SpRNAiRGFP transgene into the genome of the Tg(actin-GAL4:UAS-gfp) zebrafish for steady expression. An isolated fmr1 r(CGG)-derived ramRNA precursor, i.e. the fmr1 5′-UTR r(CGG) expansion, was inserted in the SpRNAi intron region and co-expressed with the transgene. The transgene expression was driven by a neuron-specific fish GABA(A) receptor bZ2 (GABA R2) promoter. Following the procedure listed in the right panel site, we selectively raised and cross-mated the RGFP-positive, miRNA-expressing zebrafish for establishing a stable transgenic FXS fish line

between human FXS (>200 copies) and normal (<50 copies) r(CGG) expansion expression. During native embryonic development, excessive expression of r(CGG)-derived ramRNAs over fourfold is sufficient to inactivate FMR1 gene transcription [36]. We also found that both human and fish FXS models present similar pathological abnormalities in synaptic connectivity and neuronal plasticity. To a less extent of the miR-fmr1 expression, the fish with 50–75% fmr1 knockdown may represent the case of fragile X tremor/ataxia syndrome (FXTAS), which expresses a moderate increase of r(CGG) expansion (~120 copies) and often displays elevated fmr1 mRNA but decreased fmr1 protein levels, as shown in Fig. 14.7B, C, lanes 2, respectively.

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Fig. 14.7 Transgenic zebrafish with different levels of miR-fmr1 expression and fmr1 knockdown can be generated using different concentrated pGABAR2-rT-SpRNAi vectors expressing the fmr1 5′-UTR r(CGG) expansion. (A) Strategy used in development of these transgenic FXS zebrafish models is described in Fig. 14.6. Instead of increasing the r(CGG) expansion number in the fmr1 5′-UTR, we directly over-express the r(CGG)-derived ramRNA precursor to trigger the desired fmr1 inactivation. Knockdown levels of the fmr1 mRNA and fmr1 protein were determined by Northern blot (B) and Western blot (C) analyses, respectively. The line chart (D) indicates the Western blotting results of (C). Arrows indicate the two compared groups: one is wild-type (WT) and the other is the transgenic FXS zebrafish line with 75–90% fmr1 knockdown (fmr1 KO), as shown in Figs. 14.8 and 14.9

In addition, we have used fluorescent in-situ hybridization (FISH) assays to determine the distinct fmr1 mRNA expression patterns in the wild-type (WT) and fmr1 KO (FXS) zebrafish brains (Fig. 14.3A). In wild-type zebrafish, abundant fmr1 mRNA expression was shown in the junction (upper row, dot lines) of pallium and neocortical neurons and the dendritic projection of neocortical granule neurons adjacent to the granular layer (yellow arrows), where resides the purkinje cells. In fmr1 KO zebrafish, no fmr1 mRNA is detected in these areas (red + green = yellow; no blue), indicating that the fmr1 gene is largely inactivated in the fmr1 KO neurons.

14.7

Similar Abnormalities in Human and Fish FXS Neurons

Despite some notable differences in the sizes, the overall organization of major brain components in zebrafish is highly conserved with that of the human brain [54, 59]. As in other vertebrates, zebrafish possess all of the classical sense modalities such as vision, hearing, olfaction, taste, tactile, balance, and their sensory pathways,

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sharing an overall homology with humans. We have compared the phenotypes between human and fish FXS in detail to provide an informative groundwork for the use of this novel r(CGG)-derived ramRNA-mediated animal model for FXSrelated research and drug development. As shown in Fig. 14.8, fluorescent threedimension (3D)-micrograph shows abnormal neuron morphology and connectivity in the embryonic brains of the fmr1 KO fish, reminiscent of those in human FXS. In fish lateral pallium (similar to human hippocampal-neocortical junction), wildtype neurons present normal dendrite outlines and are well connected to each other (yellow arrows), whereas the fmr1 KO transgenics exhibit thin, strip-shape neurons, similar to the abnormal dendritic spine neurons in human FXS [16, 18]. Synaptic deformity frequently occurs in the fmr1 KO neurons (red arrows), indicating the functional role of FMR1 in neuronal plasticity. Altered synaptic plasticity has been reported to be a major physiological damage in human and fish FXS, particularly in the hippocampal stratum radiatum, layer IV/V cortex and sometimes cerebellum of severe cases [8, 18]. FMR1 mRNA is present in dendritic spines and translated in response to activation of the type 1 metabotropic glutamate receptors (mGluR-1) in synaptoneurosomes [25, 57]. The activation of mGluR1 stimulates a phosphorylation cascade, triggering rapid association of some mRNAs with translation machinery near synapses, and leading to protein synthesis of the mRNAs [57]. FMR1 protein is, however, a translational inhibitor that binds with the mRNA species involved in regulation of microtubule-dependent synapse growth and function, including its own mRNA [4, 19, 29]. Such translational suppression in dendritic spines is though to be crucial for eliminating immature synapses and enhancing synaptic strength during brain development. Changes in spine shape are often coupled to the absence of FMR1 function in FXS patients [17]. Thus, an increased density of long, immature dendritic spines found in the fmr1 KO neurons (Fig. 14.8, most right panel) may provide new insights into the role of FMR1 in synaptic maturation and pruning. Based on the present evidence, not only FMR1 protein but also miR-fmr1 ramRNA can modulate the expression of certain neural genes involved in synaptic development and maturation. In male, 3-month-old fmr1 KO zebrafish, excitatory synapses in slices of the pallium-neocortical junction are found to exhibit diminished long-term potentiation (LTP), as compared with wild-type controls (Fig. 14.9A). LTP in hippocampus is a learning-related form of synaptic plasticity, highly involved in dendritic spine shape changes [11]. Thus, this result suggests that deficits in hippocampalcortical LTP mechanisms may contribute to cognitive impairments in FXS disorders. On the other hand, post-synaptic stimulation of mGluR increases neural protein synthesis and subsequently triggers internalization of α-amino-3hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptors. This process is crucial for the expression of long-term depression (LTD), which refers to a longlasting decrease in synaptic strength to below the normal baseline level. Given that FMR1, a stimulated gene by mGluR, serves to quench this process, fmr1 KO neurons may likely display over-amplification of this LTD response. As shown in Fig. 14.9B, the pallium neuron LTD is augmented in the absence of fmr1, sug-

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Fig. 14.8 Morphological changes of lateral pallium neurons in the transgenic zebrafish with fmr1-knockdown (fmr1 KO) (middle row) and Nurr1-knockdown (Nurr1 KO) (bottom row), in comparison to the wild-types (top row). Fluorescent 3D-micrograph shows distinct neuronal morphology and connectivity between the wild-type and fmr1 KO Tg(actin-GAL4:UAS-gfp) zebrafish. Because the entire zebrafish body expresses an actin promoter-driven EGFP protein (green) and the miR-fmr1 ramRNA expression is marked by a RGFP reporter protein (red), we can easily observe the normal dendritic neurons (green) versus the fmr1 KO neurons (yellow) under a fluorescent microscope. This fmr1 ramRNA-mediated FXS model is consistent with the neurodegenerative mechanism of human FXS, in which the native miR-FMR1 prevents synaptic strengthening and blocks local protein-synthesis-dependent synaptic connections, a cascade of events for which FMR1 has been strongly implicated. As a comparison control, the Nurr1 KO transgenics display a totally different phenotype, indicating that these changes specifically correspond with the expression of different ramRNAs. Abbreviations indicate: Pa, pallium; sP, subpallium; Te, tectum; H, hypothalamus

gesting that exaggerated LTD may be responsible for aspects of abnormal neuronal responses in FXS, such as autism. This exaggerated LTD can be inhibited by treating the brain slices of the fmr1 KO fish with mGluR-specific agonists, such as 3,5-dihydroxyphenyglycine (DHPG). These findings raise a possibility in FXS-associated autism, which is supported by other evidence that induction of mGluR1-dependent LTD is enhanced in pyramidal cells of the hippocampus in FMR1-deleted mice [16]. Thus, altered LTP and LTD in FXS hippocampal neurons may explain how and why such FMR1 inactivation hinders the normal learning and cognition process in the brain, which is important for the development of human intelligence quotient (IQ).

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Fig. 14.9 The responsiveness of hippocampal-neocortical LTP is decreased (A), whereas that of hippocampal LTD is augmented (B) in the loss-of-fmr1-function zebrafish (fmr1 KO). Both changes in neuronal activities reflect the abnormality of certain synaptic circuits, which are crucial for learning and cognitive brain functions

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Conclusion

The list of developmental and degenerative diseases that are caused by expansion of microsatellite-like genomic repeats continues to grow. Many of the trinucleotide repeats are predicted to encode miRNAs; nevertheless, none of the repeat-associated miRNA (ramRNA) has ever been identified. We have recently established three important breakthroughs in the study of r(CGG)-derived ramRNA function in FXS, which is one of the most prevalent neurodegenerative diseases in men. First, mature ramRNAs, namely miR-fmr1, can be generated from the 5′-UTR r(CGG) expansion region of the fmr1 gene in zebrafish, matching the previously predicted epigenetic disease model of FXS. Second, the ramRNA-mediated FXS zebrafish can be raised and maintained to show the same neural defects as human FXS. And last, the normal expression pattern of miR-fmr1 in wild-type zebrafish is limited within the neuronal body, whereas the FXS-associated ramRNA expression can extend into the nucleus and dendrites, consequently leading to transcriptional fmr1 inactivation. These findings confirm the feasibility of using this novel FXS animal model for studying ramRNA-mediated pathogenesis and neuropathology, which may be common in human patients but difficult to be evidenced in the FMR1-deleted animals. This animal model may also provide insights into the molecular mechanism of brain-specific trinucleotide repeats for understanding how a ramRNA affects human intelligence. Given that there are still many more microsatellite-like nucleotide repeats in the human genome, which may encode a variety of ramRNAs, as might be expected, learning how to use the newly established intronic miRNA expression system for exploiting the functional roles of these ramRNAs in vivo will be a forthcoming challenge.

References 1. Ambros V, Lee RC, Lavanway A, Williams PT, Jewell D. (2003). MicroRNAs and other tiny endogenous RNAs in C. elegans. Curr Biol 13:807–818. 2. Ambros V. (2004). The functions of animal microRNAs. Nature 431:350–355. 3. Bartel DP. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116:281–297. 4. Brown V, Jin P, Ceman S, Darnell JC, et al. (2001). Microarray identification of FMRP-associated brain mRNAs and altered mRNA translational profiles in fragile X syndrome. Cell 107:477–487. 5. Chung KH, Hart CC, Al-Bassam S, et al. (2006). Polycistronic RNA polymerase II expression vectors for RNA interference based on BIC/miR-155. Nucleic Acid Res 34:e53. 6. Clement JQ, Qian L, Kaplinsky N, Wilkinson MF. (1999). The stability and fate of a spliced intron from vertebrate cells. RNA 5:206–220. 7. Eberhart DE, Malter HE, Feng Y, Warren ST. (1996). The fragile X mental retardation protein is a ribonucleoprotein containing both nuclear localization and nuclear export signals. Hum Mol Genet 5:1083–1091. 8. Galvez R, Gopal AR, Greenough WT. (2003). Somatosensory cortical barrel dendritic abnormalities in a mouse model of the fragile X mental retardation syndrome. Brain Res 971:83–89.

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9. Genc B, Muller-Hartmann H, Zeschnigk M, et al. (2000). Methylation mosaicism of 5′-(CGG)(n)3′ repeats in fragile X, premutation and normal individuals. Nucleic Acids Res 28:2141–2152. 10. Gibbons RJ, McDowell TL, Raman S, et al. (2000). Mutations in ATRX, encoding a SWI/SNFlike protein, cause diverse changes in the pattern of DNA methylation. Nat Genet 24:368–371. 11. Godfraind JM, Reyniers E, De Boulle K, et al. (1996). Long-term potentiation in the hippocampus of fragile X knockout mice. Am J Med Genet 64:246–251. 12. Grimm D, Streetz KL, Jopling CL, et al. (2006). Fatality in mice due to oversaturation of cellular microRNA/short hairpin RNA pathways. Nature 441:537–541. 13. Gunnery S, Ma Y, Mathews MB. (1999). Termination sequence requirements vary among genes transcribed by RNA polymerase III. J Mol Biol 286:745–757. 14. Hagerman RJ, Staley LW, O’Conner R, et al. (1996). Learning-disabled males with a fragile X CGG expansion in the upper premutation size range. Pediatrics 97:122–126. 15. Handa V, Saha T, Usdin K. (2003). The fragile X syndrome repeats form RNA hairpins that do not activate the interferon-inducible protein kinase, PKR, but are cut by Dicer. Nucleic Acids Res 31:6243–6248. 16. Huber KM, Gallagher SM, Warren ST, Bear MF. (2002). Altered synaptic plasticity in a mouse model of fragile X mental retardation. Proc Natl Acad Sci USA 99:7746–7750. 17. Irwin SA, Patel B, Idupulapati M, et al. (2001). Abnormal dendritic spine characteristics in the temporal and visual cortices of patients with fragile-X syndrome: a quantitative examination. Am J Med Genet 98:161–167. 18. Irwin SA, Christmon CA, Grossman AW, et al. (2005). Fragile X mental retardation protein levels increase following complex environment exposure in rat brain regions undergoing active synaptogenesis. Neurobiol Learn Mem 83:180–187. 19. Jin P, Zarnescu DC, Zhang F, et al. (2003). RNA-mediated neurodegeneration caused by the fragile X premutation rCGG repeats in Drosophila. Neuron 39:739–747. 20. Jin P, Zarnescu DC, Ceman S, et al. (2004a). Biochemical and genetic interaction between the fragile X mental retardation protein and the microRNA pathway. Nat Neurosci 7:113–117. 21. Jin P, Alisch RS, Warren ST. (2004b). RNA and microRNAs in fragile X mental retardation. Nat Cell Biol 6:1048–1053. 22. Khvorova A, Reynolds A, Jayasena SD. (2003). Functional siRNAs and miRNAs exhibit strand bias. Cell 115:209–216. 23. Danin-Kreiselman M, Lee CY, Chanfreau G. (2003). RNAse III-mediated degradation of unspliced pre-mRNAs and lariat introns. Mol. Cell 11:1279–1289. 24. Kimmel CB, Ballard WW, Kimmel SR, et al. (1995). Stages of embryonic development of the zebrafish. Dev Dyn 203:253–310. 25. Koekkoek SK, Yamaguchi K, Milojkovic BA, et al. (2005). Deletion of FMR1 in Purkinje cells enhances parallel fiber LTD, enlarges spines, and attenuates cerebellar eyelid conditioning in Fragile X syndrome. Neuron 47:339–352. 26. Krol J, Fiszer A, Mykowska A, et al. (2007). Ribonuclease dicer cleaves triplet repeat hairpins into shorter repeats that silence specific targets. Mol Cell 25:575–586. 27. Lee YS, Nakahara K, Pham JW, et al. (2004). Distinct roles for Drosophila Dicer-1 and Dicer2 in the siRNA/miRNA silencing pathways. Cell 117:69–81. 28. Lewis BP, Green RE, Brenner SE. (2003). Evidence for the widespread coupling of alternative splicing and nonsense-mediated mRNA decay in humans. Proc Natl Acad Sci USA 100:189–192. 29. Li Z, Zhang Y, Ku L, et al. (2001). The fragile X mental retardation protein inhibits translation via interacting with mRNA. Nucleic Acids Res 29:2276–2283. 30. Lin SL, Chang D, Wu DY, Ying SY. (2003). A novel RNA splicing-mediated gene silencing mechanism potential for genome evolution. Biochem Biophys Res Commun 310:754–760. 31. Lin SL, Ying SY. (2004a). New drug design for gene therapy – taking advantage of introns. Lett Drug Design Discov 1:256–262. 32. Lin SL, Ying SY. (2004b). Novel RNAi therapy – intron-derived microRNA drugs. Drug Design Rev 1:247–255. 33. Lin SL and Ying SY. (2004c). Combinational therapy for HIV-1 eradication and vaccination. Int J Oncol 24:81–88.

14 Role of Repeat-Associated MicroRNA (ramRNA) in Fragile X Syndrome (FXS)

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34. Lin SL, Chang D, Ying SY (2005). Asymmetry of intronic pre-microRNA structures in functional RISC assembly. Gene 356:32–38. 35. Lin SL, Chang D, Ying SY. (2006a). Isolation and identification of gene-specific microRNAs. Methods Mol Biol 342:313–320. 36. Lin SL, Chang SJE, Ying SY. (2006b). First in vivo evidence of microRNA-induced fragile X mental retardation syndrome. Mol Psychiatr 11:616–617. 37. Lin SL, Chang SJE, Ying SY. (2006c). Transgene-like animal model using intronic microRNAs. Methods Mol Biol 342:321–334. 38. Lin SL, Ying SY. (2006d). Gene silencing in vitro and in vivo using intronic microRNAs. Methods Mol Biol 342:295–312. 39. Lin SL, Chang D, Ying SY. (2007). Hyaluronan stimulates transformation of androgen-independent prostate cancer. Carcinogenesis 28:310–320. 40. Lopez-Bendito G, Shigemoto R, Kulik A, et al. (2004). Distribution of metabotropic GABA receptor subunits GABAB1a/b and GABAB2 in the rat hippocampus during prenatal and postnatal development. Hippocampus 14:836–848. 41. Lund E, Guttinger S, Calado A, et al. (2004). Nuclear export of microRNA precursors. Science 303:95–98. 42. McCaffrey AP, Meuse L, Pham TT, et al. (2002). RNA interference in adult mice. Nature 418:38–39. 43. Miyagishi M, Taira K. (2002). U6 promoter-driven siRNAs with four uridine 3′ overhangs efficiently suppress targeted gene expression in mammalian cells. Nat Biotechnol 20:497–500. 44. Paul CP, Good PD, Winer I, Engelke DR. (2002). Effective expression of small interfering RNA in human cells. Nat Biotechnol 20:505–508. 45. Rodriguez, A, Griffiths-Jones, S, Ashurst JL, Bradley A. (2004). Identification of mammalian microRNA host genes and transcription units. Genome Res 14:1902–1910. 46. Ruby JG, Jan CH, Bartel DP. (2007). Intronic microRNA precursors that bypass Drosha processing. Nature 448:83–86. 47. Schwarz DS, Hutvagner G, Du T, et al. (2003). Asymmetry in the assembly of the RNAi enzyme complex. Cell 115:199–208. 48. Schramm L, Hernandez N. (2002). Recruitment of RNA polymerase III to its target promoters. Genes Dev 16:2593–2620. 49. Selby L, Zhang C, Sun QQ. (2007). Major defects in neocortical GABAergic inhibitory circuits in mice lacking the fragile X mental retardation protein. Neurosci Lett 412:227–232. 50. Sheth U, Parker R. (2006) Targeting of aberrant mRNAs to cytoplasmic processing bodies. Cell 125:1095–1109. 51. Sledz, CA, Holko M, de Veer MJ, et al. (2003). Activation of the interferon system by shortinterfering RNAs. Nat Cell Biol 5:834–839. 52. Tamanini F, Van Unen L, Bakker C, et al. (1999). Oligomerization properties of fragile-X mental-retardation protein (FMRP) and the fragile-X-related proteins FXR1P and FXR2P. Biochem J 343 Pt 3:517–523. 53. Tang G. (2005). siRNA and miRNA: an insight into RISCs. Trends Biochem Sci 30:106–114. 54. Tropepe V, Sive HL. (2003). Can zebrafish be used as a model to study the neurodevelopmental causes of autism? Genes Brain Behav 2:268–281. 55. Tucker B, Richards R, Lardelli M. (2004). Expression of three zebrafish orthologs of human FMR1-related genes and their phylogenetic relationships. Dev Genes Evol 214:567–574. 56. Tuschl, T, Borkhardt, A. (2002). Small interfering RNAs: a revolutionary tool for the analysis of gene function and gene therapy. Mol Interv 2:158–167. 57. Weiler IJ, Greenough WT. (1999). Synaptic synthesis of the Fragile X protein: possible involvement in synapse maturation and elimination. Am J Med Genet 83:248–252. 58. Westerfield M. (2003). The Zebrafish Book. Sprague J, Clements D, Conlin T, et al. The Zebrafish Information Network (ZFIN): the zebrafish model organism database. Nucleic Acids Res. 31:241–243. 59. Wullimann MF. (1998). The central nerve system. In Evans DH (Ed) The physiology of fishes, 2nd. CRC press, New York, pp. 245–281.

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60. van ‘t Padje S, Engels B, Blonden L, et al. (2005). Characterization of Fmrp in zebrafish: evolutionary dynamics of the fmr1 gene. Dev Genes Evol 215:198–206. 61. Xia H, Mao Q, Paulson HL, Davidson BL. (2002). siRNA-mediated gene silencing in vitro and in vivo. Nat Biotechnol. 20:1006–1010. 62. Xia XG, Zhou H, Samper E, Melov S and Xu Z. (2006). Pol II-expressed shRNA knocks down Sod2 gene expression and causes phenotypes of the gene knockout in mice. PLoS Genet 2:e10. 63. Yi R, Qin Y, Macara IG, Cullen BR. (2003). Exportin-5 mediates the nuclear export of premicroRNAs and short hairpin RNAs. Genes Dev. 17:3011–3016. 64. Ying SY, Lin, SL. (2004). Intron-derived microRNAs–fine tuning of gene functions. Gene 342:25–28. 65. Zhang G., Taneja KL, Singer RH, Green MR. (1994). Localization of pre-mRNA splicing in mammalian nuclei. Nature 372:809–812. 66. Zhou HSL, Xia XG, Xu Z. (2005). An RNA polymerase II construct synthesizes short hairpin RNA with a quantitative indicator and mediates high efficient RNAi. Nucleic Acid Res. 33:e62.

Chapter 15

miRNA and Schizophrenia Diana O. Perkins1* and Clark D. Jeffries2

Keywords miRNA, schizophrenia, Neurodevelopmental origins, Altered synaptic plasticity, neurodevelopment, synaptogenesis, synaptic function, post-mortem, cortex

15.1

Introduction

Schizophrenia is a common disorder, affecting about 1% of the general population. The diagnosis of schizophrenia requires the presence of psychosis, including hallucinations, delusional beliefs, and/or disorganization of thought processes or behavior. Psychotic symptoms typically fluctuate over time in response to medication, stressful life events, marijuana use, or unknown causes. Impairments of other aspects of brain function, including cognition (memory skills, attentiveness, and ability to manipulate and organize complex information) are stable core features of the illness. In addition patients often experience deficits in social cognition, emotional responsiveness, and motivation. These symptoms usually result in significant disability, and schizophrenia ranks among the top ten causes of disability worldwide [67]. The evidence that schizophrenia is in large part a genetically based illness is overwhelming, but the genes and regulatory mechanisms that underlie symptoms are poorly understood and likely involve multiple genetic alterations with small effect, as well as epistatic and environmental interactions [45, 66]. Regarding protein-coding genes, it is now apparent that altered regulatory control of transcription, post-transcriptional message modification, or translation and post-translational protein modification contribute to disease risk [78]. Post-mortem studies find altered levels of numerous mRNAs or their cognate proteins most consistently in frontal cortical, thalamic, and temporal lobe regions, but as yet no defective protein has emerged as etiologic. However, there are examples where a mismatch of mRNAs and the cognate protein

1

Professor of Psychiatry, University of North Carolina at Chapel Hill

2

Professor of Pharmacy, University of North Carolina at Chapel Hill

* Corresponding author: Phone: 919-966-3813; E-mail: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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levels are found, consistent with a pathological process involving post-transcriptional dysregulation of gene expression [29, 59]. Finally, the gene sequences implicated by genetic association studies are often located in segments that are non-coding but potentially regulatory, that is, in the 3′ or 5′ untranslated regions (UTRs) or introns (http:// www.schizophreniaforum.org/res/sczgene/). Given the evidence that altered regulation of gene expression contributes to schizophrenia risk, microRNAs (miRNAs) with their pivotal and widespread role as regulators of gene expression, are genes of interest. Several investigators have hypothesized a role of miRNAs in the etiology of schizophrenia [15, 34, 57, 64].

15.2

Schizophrenia: Neurodevelopmental Origins

Converging evidence indicates that schizophrenia has a neurodevelopmental diathesis that involves dysregulation of neuroplasticity, evident both in early brain development and in adulthood. Cell replication, migration, and growth of neural processes can be considered elements of brain development and neuroplasticity [17]. These include in particular processes involving dendrite and dendritic spine formation and removal. Evidence that early brain development is altered in schizophrenia comes from ecological and case-control studies. Ecological studies find that a variety of perinatal insults, including infection, malnutrition, severe maternal stress, and anoxic birth trauma, increase risk of developing schizophrenia later in life, presumably by altering brain development [60]. In one investigation serologically confirmed in utero exposure to rubella increases schizophrenia risk 20-fold, to influenza threeto sevenfold, and to toxoplasmosis twofold [19]. There is evidence that maternal cytokine response to infection is a common pathway of increased risk; exposure in utero to elevated levels of the proinflammatory cytokine interleukin-8 and tumor necrosis factor during pregnancy are associated with elevated incidence of schizophrenia during early adulthood [20, 21]. As well, animal studies find cytokines impact fetal brain development [31]. Consistent with a neurodevelopmental diathesis, clinical schizophrenia studies consistently find characteristic premorbid developmental and behavioral deficits, including delayed achievement of motor milestones, a variety of social and academic difficulties, deficits in motor function (e.g. “soft” neurological signs), and deficits in cognitive functioning (e.g. attention, verbal and working memory) [54]. Minor physical anomalies affecting ectodermal structures that develop during the late second and third trimesters are also common (e.g. dermatoglyphic and facial structure asymmetries) [25]. Neuropathological studies do not find obvious neurodevelopmental alterations that could explain the consistent findings of premorbid deficits. A few studies have found regionally specific disordered organization of cortical subplate neurons, abnormal distribution of neurons in entorhinal regions, reduced neuron numbers in thalamic structures, and reduced glial cell numbers in cortical regions [5]. However, more consistent findings point to alterations in synaptic structures.

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15.3

269

Schizophrenia: Altered Synaptic Plasticity

Converging evidence that schizophrenia is related to altered synaptic plasticity comes from brain imaging, genetic, and post-mortem studies. Brain imaging studies consistently find decreased volume of cortical gray matter structures and increased (likely compensatory) ventricular volume in schizophrenia patients compared with unaffected persons [74]. Recent longitudinal studies suggest that alteration of cortical gray matter volume occurs at about the same time as the onset of psychosis, and subsequent changes parallel symptomatic progression [80, 77]. To a large extent the loss of gray matter is most likely related to loss of neuropil (dendrites and axons) and reduced cell body size. Post-mortem studies examining gray matter consistently find alterations in the density of neuropil in frontal cortical regions, with limited evidence that striatal and hippocampal regions may also be affected. In the frontal cortex of schizophrenia patients, neuronal density is increased, interneuronal space decreased, and the number of neurons unchanged [69, 70]. Ultrastructure studies find decreased number and length of dendrites and decreased density of dendritic spines, most prominent in pyramidal neurons in cortical layer III [30, 32, 42], with one study [16] finding reduced dendritic arborization in cortical layer V [42]. These neurons are part of brain circuits implicated in schizophrenia in other lines of research. In particular, layer III neurons receive afferents from medial dorsal thalamic neurons, and both layer III and layer V neurons project efferents to other cortical association areas and to the striatum [42]. There are provocative but less consistent findings for dendritic alterations in the striatum and hippocampus. In the striatum there are reports of increased density of axospinous synapses in schizophrenia subjects, greatest for subjects who were not taking antipsychotics at the time of death [62, 63], and altered morphology of dendritic spines [61]. These changes were restricted anatomically; in the anterior putamen to the “patch” (receiving efferents from limbic regions), and in the caudate to the “matrix” components of the patch matrix compartment (receiving efferents from the dorsolateral frontal cortex, most likely from cortical gluamateric neurons). In hippocampal regions, including CA4, CA3, the subiculum, and the entorhinal cortex, the protein spinophilin, predominantly (although not exclusively) localized to dendritic spines, was decreased [46]. Reduced spinophilin levels suggest reductions in dendritic spine number or activity. Decreased dendritic length in the subiculum has also been reported ([65]. However, for the protein MAP2, considered a marker for dendritic tree size, findings are variable [4, 46]. Post-mortem studies find altered levels of mRNA and proteins involved in NMDA-mediated activity-dependent dendritic plasticity, and the most implicated schizophrenia risk genes regulate this process, including neuregulin 1 (NRG1), regulator of G protein signaling 4 (RGS4), dysbindin (DNTP1), D-amino acid oxidase activator (DAOA) and catecholamine-methyl-transferase (COMT) [13, 75]. There is direct experimental evidence linking several of these genes to plasticity; for example disruption of NRG1 signaling results in loss of dendritic spines [49].

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In addition, the risk gene disrupted in schizophrenia (DISC1) codes for a protein involved in microtubule cytoskeletal dynamics key to dendritic plasticity. Decreased DISC1 results in impaired neurite outgrowth [37]. Another risk gene critical to neurite outgrowth is the v-akt murine thymoma viral oncogene homolog 1 (PI3/ Akt1) [13].

15.4

miRNA Roles in Neurodevelopment, Synaptogenesis, and Synaptic Function

miRNAs are highly expressed in the nervous system with their potential importance indicated by marked regional and developmental expression patterns in the brain [38]. miRNAs are implicated in the regulation of neurodevelopment, synaptogenesis, and synaptic function, and there are now several examples where the role of specific miRNAs in these processes is known. In olfactory neuroepithelium, the loss of Dicer (and thus loss of mature miRNAs) has been associated with reduced neuronal progenitor cell population and lowered rate of neuronal progenitor maturation into mature neurons [24]. Interestingly, in this study initial developmental patterning (cell fate specification) was not affected. In addition, loss of miR-200 family members (miR-200a, miR-200b, miR-200c, miR-429, and miR-141) was found to disrupt terminal differentiation of olfactory neuronal progenitors. Through gain and loss of function studies in mouse embryonic stem cells, miR-124 and miR-9 have been shown to regulate differentiation determination of progenitors into neuronal or glial pathways [43, 52, 79]. Furthermore depletion of miR-124 in cultured mouse neuronal cells led to increased transcription of numerous non-neuronal transcripts, while over expression of miR-124 led to a decrease of the same. This suggests that miR-124 has a role in regulation of the neuronal phenotype [26]. In C. elegans it was shown that the miRNA lys-6 regulates chemosensory neuron specification [23], and in Drosophila miR-7 inhibits Yan protein expression permitting photoreceptor cells to differentiate [50]. In neonatal rodent cortical neuronal cell culture, overexpression of miR-132 was associated with increased number and length of neurite processes, while reduction of the same inhibited neurite development [81]. miR-133b was found to regulate dopamine neuron differentiation and function [41]. In summary, it appears certain that miRNAs play key regulatory functions in brain development and function, although understanding of these functions is far from complete. In the adult brain, synaptic structures are plastic, insomuch as they are remodeled in response to neuronal activity. Machinery needed to translate mRNA into protein is located in dendrites, and it is now known that this machinery includes miRNAs and associated proteins [6, 10, 44]. Moreover, correlations of neuronal activity with protein synthesis localized to the synapse suggest a role for control of translation rates in modification and stability of synaptic plasticity [6]. Details about the precise mechanisms involved in miRNA regulation of dendritic protein translation are emerging. In a conditional learning paradigm in Drosophila,

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presentation of two stimuli (shock and odor) led in the dendrite to degradation of the protein Armitage, a component of the RISC, and liberation of CaMKII mRNA from translational repression resulted in local protein synthesis [7]. In this study degradation of Armitage was accompanied by translational suppression of Kinesin heavy chain and Staufen in the neuronal cell body; this could enhance function of the dendritic mRNA transport mechanism. In a second study Lugli et al. [51] reported that in mouse, Dicer and the RISC component eIF2c were expressed in the somatodendritic compartment of neurons. They advanced a model in which acute neuronal stimulation at excitatory synapses increases intracellular calcium, activating calpain, and in turn liberating Dicer and eIF2c. Moreover, Schratt et al. [68] found in rat that brain-specific miR-134 is localized to dendrites of hippocampal neurons, inhibits translation of mRNA of protein kinase Limk1, and thereby contributes to regulation of the morphology of dendritic spines.

15.5

Investigation of miRNAs in Schizophrenia

A plausible theoretical rationale for miRNA involvement in the etiology or the pathology of schizophrenia can include neurodevelopment, dendritic plasticity, and gene expression, all regulated in part by miRNAs. However, there are presently only a handful of studies. The available studies described below investigate postmortem miRNA expression or investigate associations of single nucleotide polymorphisms in miRNA or miRNA target sites. Polymorphisms in miRNA binding sites may increase disease vulnerability by altering RNA binding energy and hence translational regulation or rate of mRNA degradation.

15.5.1

Post-mortem Prefrontal Cortical miRNA Expression in Schizophrenia

A post mortem study [58] used a custom miRNA microarray to measure the expression of 264 miRNAs in prefrontal cortical tissue from 15 individuals with schizophrenia and 21 persons who were psychiatrically healthy at time of death. After controlling for multiple comparisons and specifying a 5% false discovery rate, 16 miRNAs were differentially expressed in PFC from schizophrenia subjects, with 15 expressed at lower levels (fold change 0.63–0.89) and 1 at higher level (fold change 1.77) than in the controls (Table 15.1). The relatively modest differences in miRNA expression are consistent with the magnitude of changes found in mRNA expression in schizophrenia and other brain disorders associated with subtle neuropathological changes [3, 35]. miRNA expression can be regulated at by modulation of the rate of transcription and the mechanisms of post-transcriptional processing of the primary miRNA transcript to the precursor miRNA transcript [76]. In some instances, the reported

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D.O. Perkins, C.D. Jeffries Table 15.1 Summary of differentially expressed miRNAs in postmortem brains of schizophrenia compared to psychiatrically healthy subjectsa miRNA Fold-change Tissue hsa-miR-7 0.70 PFCb hsa-miR-9-3p 0.77 PFC hsa-miR-20b 0.81 PFC hsa-miR-24 0.79 PFC hsa-miR-26b 0.63 PFC hsa-miR-29a 0.82 PFC hsa-miR-29b 0.69 PFC hsa-miR-29c 0.82 PFC hsa-miR-30a-5p 0.79 PFC hsa-miR-30b 0.68 PFC hsa-miR-30d 0.80 PFC hsa-miR-30e 0.89 PFC hsa-miR-92 0.76 PFC hsa-miR-106b 1.77 PFC hsa-miR-195 0.73 PFC hsa-miR-212 0.82 PFC hsa-miR-181b 1.5 STGc a As reported in [55] and [15], see text for details b Prefrontal cortex c Superior temporal gyrus

differential expression of miRNAs is related to altered miRNA processing rather than altered transcription rates of the primary miRNAs. Affymetrix U133A mRNA arrays were available for these subjects and include one or more probes for 52 of primary miRNA transcripts, including 6 of the differentially expressed miRNAs. Thus the Affy probes were fortuitously designed to hybridized to sequences in host genes (hosting in the sense that the precursor miRNA hairpins are located in introns). After correction for multiple comparisons, there was no difference in expression levels of the primary miRNAs as measured by the Affy probes between schizophrenia and psychiatrically healthy subjects. The ratio of mature miRNA expression (measured by an in-house microarray) and primary miRNA expression (measured by the U33A array) can be considered an indicator of biogenesis “efficiency” [76]. Biogenesis efficiency was lower for all five of the evaluable, differentially expressed miRNAs in the schizophrenia versus control comparisons, and significantly lower for three of the five (hsa-miR-26b, p = 0.009; hsa-miR-9-3p, p = 0.002; hsa-miR-24, p = 0.037; hsa-miR-7, p > 0.05; hsa-miR-30e, p > 0.05). For the one miRNA that was expressed at a significantly higher level in schizophrenia subjects, hsa-miR-106b, the ratio was significantly higher (p = 0.003 for one Affymetrix mRNA probe and 0.006 for the other). In the remaining 46 miRNAs with at least one host gene probe, the ratio of mature to primary miRNA was significantly lower for two miRNA (hsa-miR-218, p = 0.021) and significantly higher for five miRNAs (hsa-miR-482, p = 0.015; hsa-miR-190, p = 0.018; hsa-miR-105, p = 0.02; hsa-miR-148b, p = 0.027; hsa-miR-218, p = 0.02). Thus for the evaluable

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differentiated miRNAs, 67% had significantly different biogenesis efficiency in schizophrenia versus comparison subjects, in contrast with only 15% of the nondifferentially expressed probes (p = 0.012, Fisher’s exact test). Further bioinformatic investigations revealed the existence of motif TGAGNCTT upstream of pre-miRNAs miR-26b, -30a, 30b, and -7-1, and motif GTCNCTTC upstream of pre-miRNAs -9-1, -9-2, -9-3, -7-3, and -30e. The first motif was found by custom program and the second was found by application of Weeder to the 500 base flanks that are 5′ of the pre-miRNAs [56]. Weeder motifs of length 8 nucleotides were examined for pairs that differ in exactly one position. The same search was applied to 20 other selections of pre-miRNAs that are also isolated (not in clusters), including selections with subsets of related mature regions analogous to the miR-7 and miR-9 subsets here. None of the other 20 produced motifs that “covered” the set of pre-miRNAs as well. (Incidentally, the six 500 base flanking regions of miR-7 and miR-9 pre-miRNAs seem no more related than random sequences, as measured by ClustalW.) These and other simple tests suggest possible significance. More importantly, the distances upstream of the nine motif instances are clustered at ~100 and ~400 bases. However, bioinformatic observations of this type do not prove or disprove that the motifs are functional. Perhaps a good guess, considering the remarkable commonality of distances, is that they are involved but only among other motifs and structures that together determine regulation. Experimental validation is needed, for example experiments enforcing RNAi directed against putative motifs in the nucleus in vivo. Dysregulation of miRNA levels, as suggested above for schizophrenia, would be anticipated to affect the translation of multiple protein coding genes. Available bioinformatic strategies to identify miRNA:mRNA target relationships provide initial guidance. However, only a few of these potential target sites have been verified as potent, mainly in vitro [71]. With the caveat that putative miRNA target genes are at this point speculative, the miRNAs differentiated in this study were found to target genes over-represented in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (http://www.genome.jp/kegg/pathway.html) involved in the regulation of synaptic plasticity, especially involving regulation of the actin cytoskeleton.

15.5.2

Temporal Cortical miRNA Expression in Schizophrenia

A post-mortem study using a custom microarray [15] determined the expression of 262 human miRNAs in the superior temporal gyrus of seven schizophrenia and seven matched, psychiatrically healthy subjects. Seventy-six miRNAs were expressed above background levels, with two miRNAs significantly elevated in schizophrenia; hsa-miR-181b (2.8-fold, p = .001) and hsa-let-7 g (1.8-fold, p = .008). Northern blotting confirmed a significantly higher expression of miR-181b (1.5-fold, p = .04), but the hsa-let-7g expression was not significantly different (p = .12).

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A follow-up study was done with these subjects plus an additional 28 subjects (21 subjects in each group). Using qRT-PCR the authors confirmed elevated expression of hsa-miR-181b (1.24-fold, p = .049). Precursor transcript levels for hsa-miR-181b did not differ between groups, consistent with altered biogenesis regulation. Primary miRNA levels were not reported. Beveridge and colleagues used the on-line target prediction service TargetCombo [71] to determine potential targets, followed by functional annotational clustering to determine over-represented pathways. Consistent with the evidence regarding schizophrenia etiopathology, the potential targets were over-represented in the following Gene Ontology categories: development, nervous system development, neurogenesis, and differentiation. Over-represented KEGG pathways included long term potentiation, MAPK signalling, and axon guidance. The expression of potential miRNA target genes was investigated in a parallel mRNA microarray study. Two potential hsa-miR-181b targets, the ionotropic glutamate/AMPA receptor gene (GRIA2) and visinin-like 1 (VSNL1) were expressed at significantly lower levels in schizophrenia. The lower expression levels were confirmed with qRT-PCR (VSNL1 at 0.52-fold, p = .037 and GRIA2 at 0.69-fold, p = .047). Furthermore, in HEK293 and SY5Y cells transfected with synthetic miR-181b the expression of both VSNL1 and GRIA2 was suppressed, and a luciferase reporter gene assay study confirmed the potency of miR-181b to down-regulate VSNL1 and GRIA2 expression. Both genes are implicated in regulation of synaptic plasticity. VSNL1 is a calcium sensor protein, with decreased levels associated with schizophrenia in a previous study [14]. The investigators also point out that VSNL1 is a double stranded RNA binding protein potentially involved in activity-dependent trafficking of dendritically regulated mRNAs. GRIA2 is an ionotropic glutamate receptor subunit and has a role in synaptic plasticity, with experimentally demonstrated impact on growth and density of dendritic spines [55].

15.5.3

Associations of Single Nucleotide Polymorphisms in miRNA or miRNA Target Sites

A DNA gene association study compared the frequency of 18 polymorphic single nucleotide genetic variants in miRNA genes in three separate Scandinavian samples (a total of 840 schizophrenia and 1,476 healthy comparison subjects) using a GoldenGate assay on a custom designed Illumina Bead Array [34]. The investigated miRNAs included hsa -206. There was a nominal association of the rare allele in hsa-miR-206 and one other miRNA, with hsa-miR-206 still significant after correction for multiple testing. Consistent with these results, examination of hsamiR-206 expression in the postmortem comparison reported by [58] reveals that hsa-miR-206 was under expressed in the schizophrenia subjects using a false discovery rate of 10%, with a fold-change of 0.88.

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15.5.4

275

DiGeorge Critical Region 8 (DGCR8) and Schizophrenia

Hemizygosity for a 1.5 mb region in chromosomal region 22q11.21 is associated with a greater than 12-fold elevated risk of schizophrenia. The microdeletion is found in 0.3–2% of persons with schizophrenia, compared to the population prevalence of 0.025% [2, 36, 39]. Linkage studies have also implicated the 22q11.21 region in the etiology of schizophrenia [8, 48, 83]. In addition, 22q11 microdeletions are associated with Velocardiofacial Syndrome (VCFS), a syndrome marked by cleft palate, heart defects, dysmorphic facial characteristics, and a pattern of cognitive deficits that is very similar to that found in schizophrenia. About a third of VCFS patients will experience psychotic symptoms consistent with a diagnosis of schizophrenia [11, 27, 47], and up to half may have transient psychotic symptoms [9, 12, 53]. For these reasons genes in the 22q11 region represent high priority schizophrenia risk genes. Included is the gene DiGeorge critical region 8 (DGCR8). DGCR8 is critical for processing of the primary miRNA transcript to the precursor miRNA. The impact of DGCR8 haploinsufficiency on mature miRNA levels has not been well studied, however. Notably, one investigation found no difference in mature miRNA levels in wild type and DGCR8 knockdown mouse embryonic stem cells [82]. In embryonic stem cells miRNA levels are thought to be generally low, with miRNA biogenesis occurring as cell differentiation occurs. In an engineered mouse hemizygous for a region that included DGCR8 miRNA expression for certain miRNAs was altered in the prefrontal cortex and hippocampus, including miRNA 212 and 106b [73], which were also altered in schizophrenia prefrontal cortex [56]. Interestingly, these mice also exhibited dendritic spine density changes and sensorimotor deficits similar to deficits found in schizophrenia.

15.5.5

22q11 and hsa-miR-130b

A second gene located in the 22q11 critical region codes for hsa-miR-130b. A bioinformatic investigation of this gene identified a SNP in the 5 UTR in a putative promoter region potentially impacting transcription, and the investigators hypothesized a role for this polymorphism in schizophrenia [22]. In this same report there was no relationship between the alternative alleles and miR-130b expression in human brain tissue as measured by qRT-PCR. In addition a genetic association study of 300 schizophrenia and 316 healthy control subjects found no significant association of the miR-130b allelic variants [22].

15.5.6

Putative miRNA Target Sites in a Schizophrenia Risk Gene

There are emerging examples where polymorphisms in miRNA target sites affect gene expression and influence disease risk. For example a rare polymorphism in a

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SNP rs9332380 = G with frequency .988

SNP rs9332380 = A with frequency .012

3’cttgtccatcagac_ttgtgaccc5’ mir-199a-5p : |: ||| |||||||| ...CCTCTCTGAACTGCAACACTGGATT... COMT 3’UTR 3’UTR

3’cttgtccatcagac_ttgtgaccc5’ mir-199a : |: || |||||||| ...CCTCTCTGAACTACAACACTGGATT... COMT

total energy of shown bonds: -24.5 Kcal/mole

-21.3 Kcal/mole

Fig. 15.1 The SNP rs9332380 is shown in blue, and seed bonds are highlighted in yellow. Minor allele A bond leads to a predicted bonding energy that is weaker by 3.2 kcal/mol than the common G bond, a 13% difference

target site for hsa-miR-189 in the Tourette’s syndrome candidate gene Slit and Trklike 1 (SLITRK1) was shown to affect SLITRK1 levels and to impact dendritic growth in neuronal cell cultures [1]. However, subsequent genetic association studies failed to find the rare polymorphism in Tourette’s syndrome patients, suggesting that this variant may not contribute to disease risk in a significant number of Tourette’s syndrome patients [28, 40]. Relevant to schizophrenia is the putative schizophrenia risk gene catecholamine methyltransferase (COMT), located on chromosome 22q11. A COMT haplotype that spans the 3′ UTR (rs737865-rs4680-rs165599) is associated with schizophrenia [33, 72]. The SNP rs165599 is located in the 3′UTR of COMT and rs165599 polymorphisms are associated with decreased expression of COMT [18]. Bioinformatic investigation finds one potential human miRNA target site for hsa-miR-199a or hsa-miR-199b located in the 3′UTR of COMT and only 354 base pairs from the linkage SNP rs165599. Using a modification of the mfold program [84] to model binding energy, we predicted that the target with the minor A allele will have about 13% less binding affinity for hsa-miR-199a miRNAs than the common G allele (Fig. 15.1). Thus the minor A allele would theoretically result in reduced translational inhibition of COMT, possibly leading to increased COMT activity (theoretically associated with increased schizophrenia risk). One theoretical explanation for the relationship of rs165599 and schizophrenia is that this allele is in linkage disequilibrium with the hsa-miRNA-199a target, and that the relationship to schizophrenia is due to altered regulation of COMT expression by hsa-miRNA-199a. A melting point study confirmed the higher binding energy of the G compared to the A allele (Tm 49.6 vs 42.9, respectively), and a gel migration study of confirmed stronger miRNA hybridization with G as compared with the A allele (unpublished data).

15.6

Summary and Discussion

The etiology of schizophrenia is likely to be highly complex, with epistatic, epigenetic, and environmental factors interacting with an underlying genetic vulnerability. Current evidence is consistent with the view that gene expression regulation

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will be important in disease risk. The evidence is particularly strong that genetic dysregulation of neurodevelopment and synaptic plasticity are involved and may be a final common pathway. How this dysregulation of gene expression occurs is not understood, but miRNAs are cogent subjects for further research. One basic problem is the general absence of a type of control theory appropriate to gene regulation (notwithstanding the existence of several research articles with promising titles). It seems possible that miRNA data, particularly time series of miRNA, mRNA, and protein levels, could provide information leading to a breakthrough system approach that captures feedforward and feedback mechanisms with sufficient clarity and reliability to enable translation into practical drug platforms. In particular, miRNA expression in peripheral tissues might yield dynamic clues, collected, for example, post-treatment with an antipsychotic. Regarding schizophrenia, the coordination of excision of several isolated (not clustered) pre-miRNAs with similar or identical mature regions would seem an especially worthy target of research effort. Figure 15.2 summarizes the concepts of this chapter. It shows how the (as yet sparse) results from schizophrenia studies may be organized to suggest avenues for future study. Several groups are now actively investigating a potential role for miRNAs in schizophrenia and other serious mental disorders. With increasing understanding of how gene expression regulation is altered in schizophrenia may come novel diagnostic and treatment strategies.

Altered miRNA expression in schizophrenia Causal: Dysregulation of miRNA expression or target binding results in altered expression of etiologic proteins.

Examples: • Altered DGCR8 levels affecting miRNA biogenesis o Copy number variation (e.g. 22q11 hemizygosity) o General regulation of DGCR8 expression • Altered miRNA levels o Variable levels of various factors that regulate pri-miRNA transcription o Polymorphisms in or near miRNA transcription factor binding sites o Splicing regulation relative to miRNAs in introns o miRNA copy number variation (e.g. hsa-miR-130b) o Altered function of factors that coordinate initiation of biogenesis of sets of isolated miRNAs (not in clusters) o Altered function of factors that select miRNAs for processing from within miRNA clusters • Altered miRNA target binding o Polymorphisms in mature miRNAs o Polymorphisms in target binding sites (e.g. potential hsa-miR-199a binding site SNP in COMT) Compensatory: miRNA expression regulatory mechanisms respond to altered expression of etiologic protein.

Examples: • hsa-miR-212 potentially targets DGCR8, so ↓ DGCR8 (e.g. related to CNV) → (compensatory) ↓ hsamiR-212

Fig. 15.2 Potential mechanisms of dysregulation of miRNA expression that might contribute to schizophrenia risk

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References 1. Abelson, J. F., K. Y. Kwan, et al. (2005). “Sequence variants in SLITRK1 are associated with Tourette’s syndrome.” Science 310(5746): 317–20. 2. Arinami, T., T. Ohtsuki, et al. (2001). “Screening for 22q11 deletions in a schizophrenia population.” Schizophr Res 52(3): 167–70. 3. Arion, D., T. Unger, et al. (2007). “Molecular evidence for increased expression of genes related to immune and chaperone function in the prefrontal cortex in schizophrenia.” Biol Psychiatr 62(7): 711–21. 4. Arnold, S. E., V. M. Lee, et al. (1991). “Abnormal expression of two microtubule-associated proteins (MAP2 and MAP5) in specific subfields of the hippocampal formation in schizophrenia.” Proc Natl Acad Sci USA 88(23): 10850–4. 5. Arnold, S. E., K. Talbot, et al. (2005). “Neurodevelopment, neuroplasticity, and new genes for schizophrenia.” Prog Brain Res 147: 319–45. 6. Ashraf, S. I. and S. Kunes (2006). “A trace of silence: memory and microRNA at the synapse.” Curr Opin Neurobiol 16(5): 535–9. 7. Ashraf, S. I., A. L. McLoon, et al. (2006). “Synaptic protein synthesis associated with memory is regulated by the RISC pathway in Drosophila.” Cell 124(1): 191–205. 8. Badner, J. A. and E. S. Gershon (2002). “Meta-analysis of whole-genome linkage scans of bipolar disorder and schizophrenia.” Mol Psychiatr 7(4): 405–11. 9. Baker, K. D. and D. H. Skuse (2005). “Adolescents and young adults with 22q11 deletion syndrome: psychopathology in an at-risk group.” Br J Psychiatr 186: 115–20. 10. Barbee, S. A., P. S. Estes, et al. (2006). “Staufen- and FMRP-containing neuronal RNPs are structurally and functionally related to somatic P bodies.” Neuron 52(6): 997–1009. 11. Bassett, A. S., E. W. Chow, et al. (2003). “The schizophrenia phenotype in 22q11 deletion syndrome.” Am J Psychiatr 160(9): 1580–6. 12. Bassett, A. S., E. W. Chow, et al. (2005). “Clinical features of 78 adults with 22q11 deletion syndrome.” Am J Med Genet A 138(4): 307–13. 13. Bellon, A. (2007). “New genes associated with schizophrenia in neurite formation: a review of cell culture experiments.” Mol Psychiatr 12(9): 882. 14. Bernstein, H. G., K. H. Braunewell, et al. (2002). “Hippocampal expression of the calcium sensor protein visinin-like protein-1 in schizophrenia.” Neuroreport 13(4): 393–6. 15. Beveridge, N. J., P. A. Tooney, et al. (2008). “Dysregulation of miRNA 181b in the temporal cortex in schizophrenia.” Hum Mol Genet 17(8): 1156–68. 16. Black, J. E., I. M. Kodish, et al. (2004). “Pathology of layer V pyramidal neurons in the prefrontal cortex of patients with schizophrenia.” Am J Psychiatr 161(4): 742–4. 17. Blitzer, R. D., R. Iyengar, E. M. Landau. (2005). Postsynaptic signaling networks: cellular cogwheels underlying long-term plasticity. Biol Psychiatry 57(2): 113–9. 18. Bray, N. J., P. R. Buckland, et al. (2003). “A haplotype implicated in schizophrenia susceptibility is associated with reduced COMT expression in human brain.” Am J Hum Genet 73(1): 152–61. 19. Brown, A. S. (2006). “Prenatal infection as a risk factor for schizophrenia.” Schizophr Bull 32(2): 200–2. 20. Brown, A. S., J. Hooton, et al. (2004). “Elevated maternal interleukin-8 levels and risk of schizophrenia in adult offspring.” Am J Psychiatr 161(5): 889–95. 21. Buka, S. L., M. T. Tsuang, et al. (2001). “Maternal cytokine levels during pregnancy and adult psychosis.” Brain Behav Immun 15(4): 411–20. 22. Burmistrova, O. A., A. Y. Goltsov, et al. (2007). “MicroRNA in schizophrenia: genetic and expression analysis of miR-130b (22q11).” Biochemistry (Mosc) 72(5): 578–82. 23. Chang, S., R. J. Johnston, Jr., et al. (2004). “MicroRNAs act sequentially and asymmetrically to control chemosensory laterality in the nematode.” Nature 430(7001): 785–9. 24. Choi, P. S., L. Zakhary, et al. (2008). “Members of the miRNA-200 Family Regulate Olfactory Neurogenesis.” Neuron 57(1): 41–55.

15 miRNA and Schizophrenia

279

25. Compton, M. T., A. M. Bollini, et al. (2007). “Neurological soft signs and minor physical anomalies in patients with schizophrenia and related disorders, their first-degree biological relatives, and non-psychiatric controls.” Schizophr Res 94(1–3): 64–73. 26. Conaco, C., S. Otto, et al. (2006). “Reciprocal actions of REST and a microRNA promote neuronal identity.” Proc Natl Acad Sci USA 103(7): 2422–7. 27. Debbane, M., B. Glaser, et al. (2006). “Psychotic symptoms in children and adolescents with 22q11.2 deletion syndrome: Neuropsychological and behavioral implications.” Schizophr Res 84(2–3): 187–93. 28. Deng, H., W. D. Le, et al. (2006). “Examination of the SLITRK1 gene in Caucasian patients with Tourette syndrome.” Acta Neurol Scand 114(6): 400–2. 29. Dracheva, S., S. L. Elhakem, et al. (2004). “GAD67 and GAD65 mRNA and protein expression in cerebrocortical regions of elderly patients with schizophrenia.” J Neurosci Res 76(4): 581–92. 30. Garey, L. J., W. Y. Ong, et al. (1998). “Reduced dendritic spine density on cerebral cortical pyramidal neurons in schizophrenia.” J Neurol Neurosurg Psychiatr 65(4): 446–53. 31. Gilmore, J. H. and L. F. Jarskog (1997). “Exposure to infection and brain development: cytokines in the pathogenesis of schizophrenia.” Schizophr Res 24(3): 365–7. 32. Glantz, L. A. and D. A. Lewis (2000). “Decreased dendritic spine density on prefrontal cortical pyramidal neurons in schizophrenia.” Arch Gen Psychiatr 57(1): 65–73. 33. Handoko, H. Y., D. R. Nyholt, et al. (2005). “Separate and interacting effects within the catechol-O-methyltransferase (COMT) are associated with schizophrenia.” Mol Psychiatr 10(6): 589–97. 34. Hansen, T., L. Olsen, et al. (2007). “Brain expressed microRNAs implicated in schizophrenia etiology.” PLoS ONE 2(9): e873. 35. Hashimoto, T., D. Arion, et al. (2007). “Alterations in GABA-related transcriptome in the dorsolateral prefrontal cortex of subjects with schizophrenia.” Mol Psychiatr 13(2): 147–61. 36. Horowitz, A., S. Shifman, et al. (2005). “A survey of the 22q11 microdeletion in a large cohort of schizophrenia patients.” Schizophr Res 73(2–3): 263–7. 37. Kamiya, A., T. Tomoda, et al. (2006). “DISC1-NDEL1/NUDEL protein interaction, an essential component for neurite outgrowth, is modulated by genetic variations of DISC1.” Hum Mol Genet 15(22): 3313–23. 38. Kapsimali, M., W. P. Kloosterman, et al. (2007). “MicroRNAs show a wide diversity of expression profiles in the developing and mature central nervous system.” Genome Biol 8(8): R173. 39. Karayiorgou, M., M. A. Morris, et al. (1995). “Schizophrenia susceptibility associated with interstitial deletions of chromosome 22q11.” Proc Natl Acad Sci USA 92(17): 7612–6. 40. Keen-Kim, D., C. A. Mathews, et al. (2006). “Overrepresentation of rare variants in a specific ethnic group may confuse interpretation of association analyses.” Hum Mol Genet 15(22): 3324–8. 41. Kim, J., K. Inoue, et al. (2007). “A MicroRNA feedback circuit in midbrain dopamine neurons.” Science 317(5842): 1220–4. 42. Kolluri, N., Z. Sun, et al. (2005). “Lamina-specific reductions in dendritic spine density in the prefrontal cortex of subjects with schizophrenia.” Am J Psychiatr 162(6): 1200–2. 43. Krichevsky, A. M., K. C. Sonntag, et al. (2006). “Specific microRNAs modulate embryonic stem cell-derived neurogenesis.” Stem Cells 24(4): 857–64. 44. Kye, M. J., T. Liu, et al. (2007). “Somatodendritic microRNAs identified by laser capture and multiplex RT-PCR.” RNA 13(8): 1224–34. 45. Lang, U. E., I. Puls, et al. (2007). “Molecular mechanisms of schizophrenia.” Cell Physiol Biochem 20(6): 687–702. 46. Law, A. J., C. S. Weickert, et al. (2004). “Reduced spinophilin but not microtubule-associated protein 2 expression in the hippocampal formation in schizophrenia and mood disorders: molecular evidence for a pathology of dendritic spines.” Am J Psychiatr 161(10): 1848–55.

280

D.O. Perkins, C.D. Jeffries

47. Lewandowski, K. E., V. Shashi, et al. (2007). “Schizophrenic-like neurocognitive deficits in children and adolescents with 22q11 deletion syndrome.” Am J Med Genet B Neuropsychiatr Genet 144(1): 27–36. 48. Lewis, C. M., D. F. Levinson, et al. (2003). “Genome scan meta-analysis of schizophrenia and bipolar disorder, part II: Schizophrenia.” Am J Hum Genet 73(1): 34–48. 49. Li, B., R. S. Woo, et al. (2007). “The neuregulin-1 receptor erbB4 controls glutamatergic synapse maturation and plasticity.” Neuron 54(4): 583–97. 50. Li, X. and R. W. Carthew (2005). “A microRNA mediates EGF receptor signaling and promotes photoreceptor differentiation in the Drosophila eye.” Cell 123(7): 1267–77. 51. Lugli G., J. Larson, M. E. Martone, Y. Jones, N. R. Smalheiser. (2005). Dicer and eIF2c are enriched at postsynaptic densities in adult mouse brain and are modified by neuronal activity in a calpain-dependent manner. J Neurochem 94(4): 896–905. 52. Makeyev, E. V., J. Zhang, et al. (2007). “The MicroRNA miR-124 promotes neuronal differentiation by triggering brain-specific alternative pre-mRNA splicing.” Mol Cell 27(3): 435–48. 53. Murphy, K. C., L. A. Jones, et al. (1999). “High rates of schizophrenia in adults with velocardio-facial syndrome.” Arch Gen Psychiatr 56(10): 940–5. 54. Niemi L. T., J. M. Suvisaari, A. Tuulio-Henriksson, J. K. Lonnqvist (2003). Childhood developmental abnormalities in schizophrenia: evidence from high-risk studies. Schizophr Res 60(2–3): 239–58. 55. Passafaro, M., T. Nakagawa, et al. (2003). “Induction of dendritic spines by an extracellular domain of AMPA receptor subunit GluR2.” Nature 424(6949): 677–81. 56. Pavesi, G., P. Mereghetti, et al. (2004). “Weeder web: discovery of transcription factor binding sites in a set of sequences from co-regulated genes.” Nucleic Acids Res 32: W199–203. 57. Perkins, D. O., C. Jeffries, et al. (2005). “Expanding the ‘central dogma’: the regulatory role of nonprotein coding genes and implications for the genetic liability to schizophrenia.” Mol Psychiatr 10(1): 69–78. 58. Perkins, D. O., C. D. Jeffries, et al. (2007). “microRNA expression in the prefrontal cortex of individuals with schizophrenia and schizoaffective disorder.” Genome Biol 8(2): R27. 59. Prabakaran, S., J. E. Swatton, et al. (2004). “Mitochondrial dysfunction in schizophrenia: evidence for compromised brain metabolism and oxidative stress.” Mol Psychiatr 9(7): 684–97, 643. 60. Rapoport, J. L., A. M. Addington, et al. (2005). “The neurodevelopmental model of schizophrenia: update 2005.” Mol Psychiatr 10(5): 434–49. 61. Roberts, R. C., R. Conley, et al. (1996). “Reduced striatal spine size in schizophrenia: a postmortem ultrastructural study.” Neuroreport 7(6): 1214–8. 62. Roberts, R. C., J. K. Roche, et al. (2005). “Synaptic differences in the patch matrix compartments of subjects with schizophrenia: a postmortem ultrastructural study of the striatum.” Neurobiol Dis 20(2): 324–35. 63. Roberts, R. C., J. K. Roche, et al. (2005). “Synaptic differences in the postmortem striatum of subjects with schizophrenia: a stereological ultrastructural analysis.” Synapse 56(4): 185–97. 64. Rogaev, E. I. (2005). “Small RNAs in human brain development and disorders.” Biochemistry (Mosc) 70(12): 1404–7. 65. Rosoklija, G., G. Toomayan, et al. (2000). “Structural abnormalities of subicular dendrites in subjects with schizophrenia and mood disorders: preliminary findings.” Arch Gen Psychiatr 57(4): 349–56. 66. Ross, C. A., R. L. Margolis, et al. (2006). “Neurobiology of schizophrenia.” Neuron 52(1): 139–53. 67. Rossler, W., H. J. Salize, et al. (2005). “Size of burden of schizophrenia and psychotic disorders.” Eur Neuropsychopharmacol 15(4): 399–409. 68. Schratt, G. M., F. Tuebing, et al. (2006). “A brain-specific microRNA regulates dendritic spine development.” Nature 439(7074): 283–9. 69. Selemon, L. D. (2004). “Increased cortical neuronal density in schizophrenia.” Am J Psychiatr 161(9): 1564.

15 miRNA and Schizophrenia

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70. Selemon, L. D., J. Mrzljak, et al. (2003). “Regional specificity in the neuropathologic substrates of schizophrenia: a morphometric analysis of Broca’s area 44 and area 9.” Arch Gen Psychiatr 60(1): 69–77. 71. Sethupathy, P., M. Megraw, et al. (2006). “A guide through present computational approaches for the identification of mammalian microRNA targets.” Nat Methods 3(11): 881–6. 72. Shifman, S., M. Bronstein, et al. (2002). “A highly significant association between a COMT haplotype and schizophrenia.” Am J Hum Genet 71(6): 1296–302. 73. Stark K. L., B. Xu, A. Bagchi, W. S. Lai, H. Liu, R. Hsu, X. Wan, P. Pavlidis, A. A. Mills, M. Karayiorgou, and J. A. Gagos (2008). Altered brain microRNA biogenesis contributes to phenotypic deficits in a 22q11-deletion mouse model. Nat Genet [epub ahead of print]. 74. Steen, R. G., C. Mull, et al. (2006). “Brain volume in first-episode schizophrenia: systematic review and meta-analysis of magnetic resonance imaging studies.” Br J Psychiatr 188: 510–8. 75. Stephan, K. E., T. Baldeweg, et al. (2006). “Synaptic plasticity and dysconnection in schizophrenia.” Biol Psychiatr 59(10): 929–39. 76. Thomson, J. M., M. Newman, et al. (2006). “Extensive post-transcriptional regulation of microRNAs and its implications for cancer.” Genes Dev 20(16): 2202–7. 77. van Haren, N. E., H. E. Hulshoff Pol, et al. (2007). “Focal gray matter changes in schizophrenia across the course of the illness: a 5-year follow-up study.” Neuropsychopharmacology 32(10): 2057–66. 78. Vawter, M. P., M. E. Atz, et al. (2006). “Genome scans and gene expression microarrays converge to identify gene regulatory loci relevant in schizophrenia.” Hum Genet 119(5): 558–70. 79. Visvanathan, J., S. Lee, et al. (2007). “The microRNA miR-124 antagonizes the anti-neural REST/SCP1 pathway during embryonic CNS development.” Genes Dev 21(7): 744–9. 80. Vita, A., L. De Peri, et al. (2006). “Brain morphology in first-episode schizophrenia: a metaanalysis of quantitative magnetic resonance imaging studies.” Schizophr Res 82(1): 75–88. 81. Vo, N., M. E. Klein, et al. (2005). “A cAMP-response element binding protein-induced microRNA regulates neuronal morphogenesis.” Proc Natl Acad Sci USA 102(45): 16426–31. 82. Wang, Y., R. Medvid, et al. (2007). “DGCR8 is essential for microRNA biogenesis and silencing of embryonic stem cell self-renewal.” Nat Genet 39(3): 380–5. 83. Williams, N. M., N. Norton, et al. (2003). “A systematic genomewide linkage study in 353 sib pairs with schizophrenia.” Am J Hum Genet 73(6): 1355–67. 84. Zuker, M. (2003). “Mfold web server for nucleic acid folding and hybridization prediction.” Nucleic Acids Res 31(13): 3406–15.

Chapter 16

SNPs in microRNA and microRNA Target Sites Associated with Human Cancers Shi-Hsiang Shen1,2 and Zhenbao Yu1

Abstract MicroRNAs (miRNAs) are small non-coding RNAs that play an important role in gene regulatory network. They regulate gene expression at the posttranscriptional level by base-pairing to the 3′-untraslated region (3′-UTR) of their target messenger RNAs (mRNAs), thus leading to mRNA degradation or repressed protein production. The expression of miRNA is deregulated in many types of cancers. However, whether miRNA mutations and single nucleotide polymorphisms (SNPs) are associated with cancers remains obscure. We have systematically screened mutations and SNPs of both miRNAs and their targets in human cancers by mining public databases and genotyping. We identified several mutations/SNPs of miRNA genes in human colon and prostate cancer tissues and cell lines. These mutations/SNPs are located either at regions of mature miRNAs, or of miRNA precursors (pre-miRNAs) or of primary transcripts (pri-miRNAs). MiRNA mutations/SNPs might disrupt miRNA functions by affecting miRNA transcription, miRNA bio-processing or miRNA-target interaction. We found that the density of SNPs at miRNA-binding sites of miRNA targets is significantly lower than that of SNPs located in the 3′-UTRs of human genes, suggesting that miRNA target SNPs underwent a purifying selection during evolution. This result further indicates important biological functions and therefore potential pathological functions of human miRNAs. Indeed, we found that the allele frequencies of several miRNA target SNPs is aberrant in human cancers. Some SNPs might affect miRNA-target interaction and thus target expression. The contribution of these mutations/SNPs of miRNAs and miRNA targets to carcinogenesis is currently under investigation. Keywords microRNA, microRNA target, cancer, mutation, single nucleotide polymorphism

1 Health Sector, Biotechnology Research Institute, National Research Council of Canada, 6100 Royalmount Avenue, Montréal, Québec, Canada, H4P 2R2 2

Department of Medicine, McGill University, Montréal, Québec, Canada, H3G 1A4

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Introduction

MicroRNAs are small RNAs of 18–25 nucleotides that regulate gene expression by targeting messenger RNAs (mRNAs) through hybridization to their 3′-untranslated regions (3′-UTRs), resulting in RNA degradation and/or translational repression. MiRNAs are generated from hairpin-shaped precursor RNAs that are transcribed from genomic DNA. It is now known that there are several hundreds of miRNAs in animals and plants. To date, 533 human miRNA sequences have been reported at the Sanger Institute miRBase (http://microrna.sanger.ac.uk/sequences/index.shtml). Although only a few miRNAs have been functionally characterized since their discovery, a growing body of evidence reveals that miRNAs are associated with the carcinogenesis of many human cancers. For example, over half of all known human miRNA genes are located at fragile sites and genomic regions involved in cancers [9]. Similarly, mouse miRNA genes are also frequently located near mouse cancer susceptibility loci [78]. High-resolution array-based comparative genomic hybridization (aCGH) revealed that the copy numbers of miRNAs are quite frequently abnormal in human cancers; for example, the numbers are 37.1%, 72.8% and 85.9% in ovarian cancer, in breast cancer and in melanoma, respectively [99]. Global repression of miRNA maturation promotes cellular transformation and tumorigenesis, suggesting that some miRNAs are potential tumor suppressors [41]. However, miRNAs can also function in an oncogenic manner. Indeed, miRNA profiling studies have revealed that many miRNAs are up- or down-regulated in different types of human cancers (Tables 16.1, 16.2) and that most of them are down-regulated [51]. Yet, the carcinogenic function and mechanisms of only a few miRNAs have been studied in more detail (Table 16.3 shows the experimentally identified miRNA targets associated with cancers). Among others, miR-21 is overexpressed in glioblastoma [10], hepatocellular carcinoma [42], breast cancer [36, 81], pancreatic cancer [46, 71], cervical cancer [52], malignant cholangiocyte [57] and chronic lymphocyte leukemia [25]. Its expression is also greatly induced in transforming growth factor-β (TGF-β)-induced epithelial-mesenchymal transition (EMT) in human keratinocytes, a key step during changes in the cell phenotype of epithelial tumors [98]. The suppression of miR-21 inhibits cell and tumor growth probably through the induction of apoptosis [10, 81]. The tumor suppressor tropomyosin 1 (TPM1) is a miR-21 target [100]. The mir-21 gene contains two Stat3 binding site and its expression is controlled by Stat3 [49]. The induction of miR-21 might contribute to the oncogenic potential of Stat3 in myeloma cells [49]. MiR-29b is downregulated in B cell chronic lymphocytic leukemia [67, 87], cholangiocarcinoma [62] and uterine leiomyoma [92]. T-cell leukemia/lymphoma 1(Tcl1) is a direct target of miR-29b. The expression of Tcl1 in B cell chronic lymphocytic leukemia is inversely correlated with miR-29b expression [67]. In cholangiocarcinoma cells, miR-29b targets Mcl-1, an anti-apoptotic protein of the Bcl-2 family. MiR-29b expression reduces the Mcl-1 level and increases the sensitivity of cholangiocarcinoma cells to apoptosis [62].

16 SNPs in microRNA and microRNA Target Sites Associated with Human Cancers Table 16.1 MiRNAs up-regulated in human cancers miRNAs Cancers miR-17-92 cluster

miR-21

miR-125b miR-155

miR-221

miR-222 miR371-372-373 cluster

B cell chronic lymphocytic leukemia B cell lymphoma Mantle cell lymphoma A few solid cancers Glioblastoma Hepatocellular carcinomas Breast cancer Pancreatic cancer Cervical cancer Cholangiocarcinoma Chronic lymphocyte leukemia Stomach cancer Pancreas cancer Primary mediastinal B-cell Lymphoma Diffuse large B-cell lymphoma Hodgkin’s lymphoma Chronic lymphocyte leukemia Lung cancer Pancreatic cancer Papillary thyroid carcinoma Primary glioblastoma Aggressive prostate carcinoma Activated B cell-like subtype of diffuse large B cell lymphoma Papillary thyroid carcinoma Testicular germ cell tumor

Table 16.2 MiRNAs down-regulated in human cancers miRNAs Cancers Let-7

miR-15a-16-1 cluster miR-29b

miR-34a miR-122 miR-125b miR-127 mR-143 miR-145

Lung cancer Ovarian cancer Uterine leiomyoma B-cell chronic lymphocytic leukemia Pituitary adenoma B cell chronic lymphocytic leukemia Cholangiocarcinoma Uterine leiomyoma Pancreatic cancer Neuroblastoma Hepatocellular carcinoma Breast cancer Thyroid anaplastic carcinoma Prostate and bladder cancers Colon cancer Breast cancer Cervical cancer

References [8] [33] [70] [30, 89] [10] [42] [36, 81] [46, 71] [52] [57] [25] [89] [89] [22, 39] [22, 39] [39, 87], [25] [95] [46, 71] [31, 66] [14] [26] [44] [31, 66] [50, 90]

References [73, 85] [80] [92] [7] [4] [7, 8, 67] [62] [92] [12] [93] [29, 42] [36, 89] [88] [72] [1–3, 60] [36] [52]

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S.-H. Shen, Z. Yu Table 16.3 Experimentally confirmed targets of the miRNAs associated with cancers miRNA Targets Reference Ras

Let-7

mir-15a and miR-16 miR-17-92 cluster

miR-21 miR-29b miR-34a miR-122 miR-124a miR-125b miR-127 miR-221 miR-222 miR-143 miR-370 miR371–372–373 cluster

HMGA2 Neurofibromatosis2 (NF2) Myc BCL2 Arginyl-tRNA synthetase gene (RARS) E2F1, E2F2 and E3F3 Anti-angiogenic thrombospondin-1 (Tsp1) Connective tissue growth factor (CTGF) Acute myeloid leukaemia-1 (AML-1) AIB1 (amplified in breast cancer 1) Tropomyosin 1 T-cell leukemia/lymphoma 1(Tcl1) Mcl-1 E2F3 Cyclin E, CDK4, MET, Bcl2 and BIRC3 Cyclin G1 CDK6 ERBB2 and ERBB3 Lin-28 and Lin-41 BCL6 p27kip1 p27kip1 ERK5 MAP3K8 Large tumor suppressor homolog 2 (LATS2)

[56] [47] [80] [92] [58] [79], [15, 27] [4, 6] [64, 83] [20] [20] [24] [35] [100] [67]. [62] [93] [12, 32] [29] [53] [76] [75, 94] [72] [26, 45] [26, 45] [1, 2, 23] [59] [90]

MiR-122 that constitutes 70% of total liver miRNAs [11, 43], is frequently down-regulated in both human and rodent hepatocellular carcinomas [29, 42]. Cyclin G1 is a target of miR-122 and cyclin G1 expression is inversely correlated with that of miR-122 in primary liver carcinomas [29]. Interestingly, miR-125b is down-regulated in breast cancer [36, 89] and thyroid anaplastic carcinoma [88] but upregulated in stomach and pancreatic cancers [89]. The enforced expression of miR-125a or miR-125b could reduce the proliferation of FB-1 and FRO thyroid anaplastic carcinoma cells [88] and impair the anchoragedependent growth, migration and invasiveness of SKBR3 breast cancer cells [76], supporting their tumor suppressor function in these two types of cancers. However, a deletion of miR-125b in PC-3 prostate cancer cell line causes the inhibition of proliferation [48], indicating its oncogenic function in this cell line. The opposing functions of miR-125b in different types of cancers suggest that miR-125b targets different genes in different cells. For example, both miR-125a and miR-125b suppress ERBB2 and ERBB3 expression in breast cancer cells [76]. The reduced

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expression of miR-125b in breast cancer might lead to ERBB2 and ERBB3 upregulation. Lin-28 and Lin-41 are two important targets of miR-125a and miR125b. The miRNA regulation of Lin-28 and Lin-41 plays an important role during embryo development and neuronal differentiation [75, 94]. However, deletions of miR-125a and miR-125b do not change the level of either Lin-28 or Lin-14 in PC-3 cells, suggesting that the function of miR-125b in the proliferation of the prostate cancer cells is not associated with these two target proteins [48]. MiR-143 and miR-145 are significantly down-regulated in several solid cancers, including colon [1–3, 60], breast [36] and cervical cancers [52]. The increased expression of exogenous miR-143 causes significant growth inhibition [1] and caspase-independent apoptosis in colon cancer DLD-1 cells [63], indicating that it has a tumor suppressor function. ERK5, which is a downstream component of the MAP kinase signaling pathway and which promotes cell growth and proliferation, is the only experimentally confirmed target of miR-143 [1, 2, 23]. MiR-155 is produced from the bic gene that is a common site of viral DNA integration in lymphomas induced by avian leukosis virus [17]. It is expressed at high levels in various B-cell lymphomas, including primary mediastinal B-cell lymphoma [22, 39], diffuse large B-cell lymphoma [22, 39], Hodgkin’s lymphoma [39, 87], chronic lymphocyte leukemia [25], lung cancer [95] and pancreatic cancer [46, 71]. More significantly, high levels of miR-155 expression are closely correlated with poor survival among patients with lung cancer [95]. Consistently with its oncogenic function, transgenic mice with miR-155 initially exhibit a preleukemic pre-B cell proliferation, followed by high-grade B cell malignancies [18]. MiR-221 is over-expressed in papillary thyroid carcinoma [31, 66], primary glioblastoma [14], aggressive prostate carcinoma [26] and the activated B cell-like subtype of diffuse large B cell lymphoma [44] and miR-222 is over-expressed in papillary thyroid carcinoma. Both miR-221 and miR-222 directly suppress p27kip1 expression and promote cancer cell proliferation [26, 45]. The miR-371-372-373 cluster is selectively expressed in testicular germ cell tumor (TGCT) but not in the normal testis [50, 90]. A genetic screen of a miRNA library have revealed that both miR-372 and miR-373 promote cell proliferation [90]. They permit the tumorigenesis of primary human cells that harbor active wild type p53 and their expression is closely correlated with p53 active status in the tumors [50, 90], suggesting that both miRNA-372 and miRNA-373 exert their oncogenic properties by neutralizing p53 function. Indeed, miRNA-372 and miRNA-373 suppress the expression of the large tumor suppressor homology 2 (LATS2), an inhibitor of CDK, which ultimately prevents CDK inhibition by p53 [90]. The mechanism through which miRNA expression is deregulated in cancers is very complex. The deregulation can be caused by genomic amplification [30, 65, 70, 84], genomic deletion. [6], epigenetic alteration [5, 53, 59, 72], inappropriate activation or inhibition of the proteins that directly regulate miRNA expression [12, 32, 69, 86] and retroviral insertion mutagenesis [54, 82, 91]. More importantly, the deregulation of miRNA expression in cancers can be caused by a single nucleotide replacement resulting from a mutation or a single nucleotide polymorphism (SNP). Mutation or SNP at a miRNA gene region might

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affect the transcription of miRNA primary transcripts, the processing of miRNA precursors to mature miRNAs, or miRNA-target interactions. A germ-line mutation (C to T) at the +7 position after the 3-terminus of mir-16-1 has been identified in B-cell chronic lymphocytic leukemia [7]. This mutation significantly reduces the expression of both miR-15a and miR-16-1 [7]. Similarly, a single nucleotide mutation located in the immediate 3′-flanking region of mouse mir-16-1 (position +6 after mir-16-1) has been identified in a genome-wide linkage scan of the New Zealand black (NZB) loci associated with lymphoma [68]. This mutation led to reduced miR-16 expression in lymphoid tissues and the NZB-derived malignant Bcell line, LNC. The expression of exogenous miR-16 in NZB malignant B-1 cells induces apoptosis. An SNP located at nucleotide 8 of mature miR-125a [21] blocks pri-miR-125a processing to pre-miRNA and thus reduces suppression of its target expression [21]. Many other SNPs located in the regions of miRNA genes have been identified although most of them do not affect miRNA expression and miRNA function [37]. Intriguingly, the oncogenic effect of miRNAs can be caused by mutation of a miRNA target at miRNA-binding sites. For example, the chromosomal translocation of High Mobility Group A2 (Hmga2) in many types of cancers generate a truncated Hmga2 mRNA lacking the Let-7 binding sites of wild type mRNA [47, 56]. Hmga2 is a direct target of Let-7 [47, 56, 80] and deleting Let-7 binding sites leads to Hmga2 overexpression. Hmga2 is an architectural transcription factor that does not have transcriptional activity but can modulate transcription by affecting chromatin structure. Hmga2 is overexpressed in lung cancer [73], ovarian cancer [80] and in uterine leiomyomas [92], where Let-7 is reduced [85]. Interestingly, both the reduced expression of let-7 and the increased expression of Hmga2 are inversely associated with the survival of patients with lung cancer [73, 85] or ovarian cancer [80], suggesting a functional relationship between Let-7 and Hmga2 although Let-7 might also target other oncogenes such as RAS and NF2 [38, 58]. A loss of the 3′-UTR caused by chromosomal translocation might also abolish Hmga2 regulation by other miRNAs. For example, Hmga2 mRNA contains a few potential binding sites for miR-98. Notably, miR-98 can suppress Hmga2 expression in head and neck squamous carcinoma [34]. The human angiotensin II type 1 receptor + 1166 A/C polymorphism attenuates miR-155 binding [55, 77]. A mutation creating a target site of miR-1 and miR-206 found in the myostatin gene affects muscularity in sheep [16]. A loss of function of the same gene causes double-muscling in mouse, cattle and humans. An SNP (829C/T) near the miR-24 binding site at the 3′ UTR of human dihydrofolate reductase (DHFR) interferes with miR-24-regulated DHFR expression, resulting in drug resistance of the cells bearing the 829T allele [61]. Several SNPs located on miRNA gene regions and the miRNA-binding sites of miRNA targets have recently been identified by a bioinformatics approach and direct sequencing [13, 21, 37, 74, 97]. The effect of these SNPs on miRNA-target interaction and the potential biological functions of miRNAs and their targets remains to be determined. Here, we report the common research approaches used in this study and describe our recent progress.

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16.2 16.2.1

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Materials and Methods Materials

Freshly frozen cancer tissue specimens from Caucasian patients with various cancers were provided by the Cooperative Human Tissue Network (CHTN) in the USA. Mammalian cell lines were obtained from ATCC and cultured in the media as recommended. Genomic DNAs of normal subjects were obtained from the British 1958 birth cohort that is based on all persons born in Britain during one week in 1958, and Coriell Institute for Medical Research. Collection and use of the tissue and genomic DNA samples were approved by the National Research Council Canada. DNeasyR Tissue kit used for genomic DNA extraction was purchased from Qiagen. TRIZOLR Reagent used for RNA extraction was from Invitrogen. MinElute 96 UF plates for DNA purification were purchased from Qiagen. High capacity cDNA reverse transcription kit was purchased from Applied Biosystems.

16.2.2

Databases

Sequence and genomic location of human miRNAs were obtained from the Sanger Institute miRBase (http://microrna.sanger.ac.uk/sequences/index.shtml). The miRNA target dataset, developed by Kreb et al. [40], was obtained from the PicTar database located in the UCSC Genome browser (http://genome.ucsc. edu/cgi-bin/hgTables). A 3′-UTR dataset of human genes was also obtained from the UCSC Genome browser (http://genome.ucsc.edu/cgi-bin/hgTables). A human SNP dataset (NCBI dbSNP Build 126), including allele frequency data, was downloaded from NCBI databases (ftp://ftp.ncbi.nih.gov/snp). The human expressed sequence tag (EST) libraries and EST sequences were also obtained from NCBI databases (http://www.ncbi.nlm.nih.gov/projects/dbEST/). The libraries were sorted into cancer EST libraries and normal tissue EST libraries. A SNP dataset, that contains the allele frequency of the SNPs of cancer-related genes in the four populations, was obtained from SNP500Cancer database (http://snp500cancer. nci.nih.gov/home_1.cfm).

16.2.3

Identification of miRNA Mutations and SNPs by Sequencing Genomic DNA of miRNA Genes

Genomic DNA was extracted from freshly frozen tissue specimens and cultured cell lines using DNeasyR Tissue kit following the manufacturer’s protocol. An approximately 500 bp genomic DNA fragment of each miRNA gene, including 200–300 bp at each end of the mature mRNA was amplified by PCR. The amplified

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DNA was purified using MinElute 96 UF plates (Qiagen) and used for sequencing. The sequences of the primers used for genomic DNA amplification and sequencing of the miRNA genes studied are available upon request. Heterozygous sequences in each sequencing reaction were first automatically identified using a computer program and then confirmed by manual reading. The sequences of the PCR products, that can be homozygous or heterozygous, were compared with the corresponding genomic DNA sequences to identify mutations or SNPs.

16.2.4

Identification of miRNA Target SNPs Through Mining Public Database

The genomic locations (chromosome number and nucleotide position) on human chromosome of both the SNPs and the miRNA-binding regions of miRNA targets were extracted from the dbSNP database (ftp://ftp.ncbi.nih.gov/snp) and the PicTar miRNA target database (http://genome.ucsc.edu/cgi-bin/hgTables). A computer program was developed to search for the SNPs that are located in the miRNA-binding sites of miRNA targets. Simply, the nucleotide position (chromosome number and nucleotide number on the chromosome) of each SNP was mapped to the nucleotide position of each miRNA-binding site. The overlapping sites are miRNA target SNPs.

16.2.5

SNP Density Analysis

The SNPs located at the whole 3′-UTRs, each position of the miRNA-binding sites and the regions surrounding miRNA-binding sites of human genes were counted, respectively. The SNP density in a group was calculated by dividing the total number of SNPs found in the group with the total number of nucleotides used for the screen in the same group. The SNP density at the miRNA-binding sites was then compared with that at the whole 3′-UTRs and the surrounding regions of miRNA binding sites to determine if the SNPs at miRNA-binding sites are positively, negatively or neutrally selected through evolution.

16.2.6

Analysis of Allele Distribution in the Cancer EST Libraries Versus the dbSNP Database

The allele numbers and frequencies of each miRNA target SNP in different ethnic populations were obtained from the dbSNP database. The same information was also obtained from the cancer EST databases. The human EST libraries downloaded from the NCBI databases (http://www.ncbi.nlm.nih.gov/projects/dbEST/) were manually curated and cataloged into cancer EST libraries and normal tissue EST libraries. Totally, 5,731 EST libraries, of which 3,721 are cancer EST libraries,

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were downloaded. The 3,721 cancer EST libraries contain totally more than 2.2 millions of EST sequences. A computer program was developed to search for the EST fragments representing each allele of miRNA-targeting SNPs using a 30nucliotide sequence surrounding the SNP site. The sequences for both alleles were used separately for the searching. Only the sequences with 100% identity were picked up. For each SNP, the total number of ESTs corresponding to each allele identified from the cancer EST libraries was counted and compared with the allele number found in the dbSNP database. Fischer’s exact test was used to determine the significant difference of the allele frequency of each SNP by comparing cancer EST libraries with that of the dbSNP database.

16.2.7

Analysis of the Effect of SNPs on miRNA Target Expression by Mining the dbSNP Database and dbEST Database

To determine if SNPs affect miRNA target expression, we compared the frequency of the two alleles of SNPs located in the miRNA-binding motifs of miRNA targets in the dbEST database and in the dbSNP database. Since the EST libraries were constructed with cDNAs derived from mRNAs, the relative allele frequency of the two alleles in the EST database should be different from that in the dbSNP database if a SNP affects gene expression. We termed the allele that is complimentary to the respective miRNA at the SNP position as “target allele” and the other that has a mismatch with the miRNA at the SNP position as “non-target allele”. We counted the total number of target allele and the total number of non-target allele of a miRNA target SNP in the dbEST database and in the dbSNP database, and calculated allele frequencies in each database. To determine if SNPs affect overall miRNA target expression, we counted the total number of SNPs that have a higher allele frequency of non-target allele in the dbEST database than in the dbSNP database. We also calculated and compared the average allele frequency of the non-target alleles of these miRNA target SNPs in the dbSNP database and in the dbEST database, respectively.

16.2.8

Analysis of the Effect of SNPs on miRNA Target Expression by Sequencing Genomic DNAs and cDNAs

The cancer patients that bear both the two alleles of a respective SNP were selected for the analysis. Genomic DNAs were extracted using DNeasyR Tissue kit and total RNAs were extracted using TriZOL regent from Invitrogen following the manufacturer’s protocols. cDNAs were synthesized using a high capacity cDNA reverse transcription kit from Applied Biosystems following the manufacturer’s instruction. An approximately 500bp fragment containing the interesting SNP was amplified from both genomic DNA and cDNA (no intron in the amplified region) with the same pair of primers. The PCR products were purified and subjected to sequencing. The relative copy numbers of the two alleles in the genomic DNA

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sample and the cDNA sample were calculated according to the intensity of the two nucleotides at the SNP position in the sequence reaction using “PeakPicker” software developed by Ge et al. [28]. All primers for PCR and sequencing, and all computer programs are available upon request. Statistical analysis methods were described in the previous studies [19, 96]

16.3 16.3.1

Results MiRNA Mutations and/or SNPs Identified from Human Cancer Patients and Cancer Cell Lines

To identify mutations and SNPs located in the regions of miRNA genes in human cancers, we determined the genomic DNA sequence of 288 miRNAs (http://microrna. sanger.ac.uk/sequences/index.shtml) and 48 miRNA candidates in a variety of human cancer tissues (86 colon cancers, 74 prostate cancers, 25 lung cancers, 9 breast cancers and 2 ovary cancers) and 20 cancer cell lines, including Jurkat, K562, MCF7, PC-3, MNNG/HOS 85, DLD-1, U-87MG, DU-145, A549, colo205, UACC-62, SF-295, LOX-1MV1, MDA-MB-435, LNCaP, SK-N-MC, 768-0, H1299, CCRF-CEM, BT-549. For each miRNA gene, we amplified a ~500 bp fragment of the genomic DNA containing mature miRNA and ~250 bp segments at each end of the mature miRNA, and then sequenced the amplified PCR product. We identified a total of 14 mutations, 1 of which is located in the mature miRNA region and 4 in the pre-miRNA region (Table 16.4). Further studies using un-affected nearby tissues of the same patients suggested that most of them are germ line mutations or SNPs. The effects of these mutations on miRNA expression, bioprocessing and miRNA-target interaction are under investigation.

16.3.2

MiRNA Target SNPs Identified by Mining Public Database

To identify SNPs located on the miRNA-binding sites of miRNA targets, we searched for the dbSNP database using the miRNA targets predicted by Kreb et al. [40].

Table 16.4 Summary of identification of MiRNA Mutations and/or SNPs in human cancer patients and cancer cell lines Total number of miRNAs and miRNA candidates studied 336 Total number of cancer patients studied 196 Total number of cell lines studied 20 Total number of mutations/SNPs identified 14 Total number of mutations/SNPs at mature miRNAs 1 Total number of mutations/SNPs at pre-miRNAs 4

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Table 16.5 SNPs located at the “seed” region of miRNA targets Total number of SNPs SNP positiona 1 263 2 276 3 265 4 234 5 231 6 250 7 252 8 274 a The position counted from the 5-terminus of the corresponding miRNAs

Each of the predicted miRNA-binding sites contains a 7-nucleotide segment (called the “seed” motif herein), which is complimentary to the seed (7 nucleotides at the 5′-terminus of mature miRNA from position 2 to position 8) of the respective miRNA. We identified a total of 1,245 miRNA target SNPs. Since the seed regions are crucial for the recognition of miRNA with its target, the SNPs located on these motifs are most likely to affect the miRNA-target interaction and thus target expression. Accordingly, we focused more on such regions. Table 16.5 shows the total number of SNPs located at each position of the seed motifs. We also calculated the density of the SNPs found in the seed motifs and compared it with that of the SNPs found in the 3′-UTRs. We found that the SNPs located on the seed motifs of miRNA targets were negatively selected under evolutional pressure [97], confirming the importance of the interaction of miRNA-target through the seed regions.

16.3.3 MiRNA Target SNPs with Aberrant SNP Allele Frequency in Human Cancer dbEST Database To identify miRNA target SNPs that might be associated with cancers, we initially compared the allele distribution of miRNA target SNPs in the dbSNP and human cancer dbEST databases. First, we downloaded 2.2 millions of human cancer EST sequences from 3,721 cancer EST libraries. We then searched for ESTs that corresponded to each SNP allele among those SNPs located in the miRNA-binding regions of miRNA targets. To determine whether the allele frequency of the SNPs in the miRNA-binding regions in cancer EST libraries is similar to or different from that found in the general population, we counted the number of ESTs of each SNP allele found in cancer EST libraries and compared it with that in the general population as described in the dbSNP database. We used Fisher’s exact test to determine the significance of the difference. We found that the allele frequency of 18 SNPs significantly differed between the cancer EST libraries and the dbSNP database (P < 0.01, Tables 16.6, 16.7). To further confirm this finding, we searched for the allele frequencies in the SNP500Cancer database (http://snp500cancer.nci.nih.gov/home 1.cfm) that contains

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Table 16.6 MiRNA-targeting SNPs with higher minor allele frequency in the cancer EST libraries Allele number Allele number in cancer EST Allele number in normal EST in dbSNP libraries libraries miRNA target

SNP

Major allele

Minor allele

Major allele

Minor allele

P value

Major allele

P value

0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0

1 1 1 1 1 1 1 0.06 0.06 1 1 0.07 1 1 1 1 1 1

S.-H. Shen, Z. Yu

18 NM_080423 rs9888470 420 0 17 4 3.8 × 10−6 18 NM_024536 rs1043901 184 0 24 6 4.7 × 10−6 8 NM_033389 rs1046243 416 0 9 3 1.7 × 10−5 11 NM_020467 rs1061804 194 0 13 4 3.6 × 10−5 7 NM_058187 rs1046762 184 0 5 3 4.8 × 10−5 34 NM_006164 rs1057092 818 0 34 3 5 × 10−5 5 NM_019848 rs1048969 184 0 6 3 7 × 10−4 10 NM_178126 rs1051166 184 0 12 3 3.5 × 10−4 11 NM_031232 rs1062954 184 0 12 3 3.5 × 10−4 NM_006516 rs3199358 408 1 49 3 0.0014 38 NM_024536 rs1043910 184 0 24 3 0.0019 18 NM_012158 rs1062733 184 1 8 2 0.0024 13 NM_014629 rs14375 398 20 15 5 0.0035 13 NM_000089 rs1061276 184 0 37 3 0.0053 31 NM_017432 rs1062942 184 0 12 2 0.0040 9 NM_004229 rs1128513 116 22 3 5 0.0058 5 NM_138440 rs3169377 184 0 15 2 0.0067 15 NM_002136 rs633540 184 0 148 6 0.0085 78 P value was calculated using Fischer’s Exact Test by comparing with the allele numbers in the dbSNP

Minor allele

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Table 16.7 Gene annotation and corresponding miRNA identity of the miRNA targets with higher SNP minor allele frequency in the cancer EST libraries SNP Gene ID Annotation miRNA rs9888470

NM_080423

rs1043901

NM_024536

rs1046243

NM_033389

rs1061804

NM_020467

rs1046762

NM_058187

rs1057092

NM_006164

rs1048969

NM_019848

rs1051166

NM_178126

rs1062954

NM_031232

rs3199358

NM_006516

rs1043910

NM_024536

rs1062733

NM_012158

rs14375

NM_014629

rs1061276 rs1062942

NM_000089 NM_017432

rs1128513

NM_004229

rs3169377 rs633540

NM_138440 NM_002136

Protein tyrosine phosphatase, non-receptor type 2 (PTPN2) Chondroitin polymerizing factor (CHPF) Slingshot homolog 2 (Drosophilae) (SSH2) Hypothetical protein from clone 643 (LOC57228) Chromosome 21 open reading frame 63 (C21orf63) Nuclear factor (erythroid-derived 2)-like 2 (NFE2L2) Solute carrier family 10, member 3 (SLC10A3), Hypothetical protein LOC162427 (LOC162427) Amyloid beta precursor proteinbinding, family A, member 2 binding protein (APBA2BP). Solute carrier family 2 glucose transporter-1 (SLC2A1). Chondroitin polymerizing factor (CHPF) F-box and leucine-rich repeat protein 3 (FBXL3) Rho guanine nucleotide exchange factor (GEF) 10 (ARHGEF10) Collagen, type I, alpha 2 (COL1A2) Prostate tumor overexpressed gene 1 (PTOV1) Cofactor required for Sp1 transcriptional activation, subunit 2 (CRSP2) Vasorin Heterogeneous nuclear ribonucleo protein A1 (HNRPA1)

miR-30a-5p miR-139 miR-23a mMiR-24 miR-205 miR-144 miR-182 miR-128a miR-125a

miR-328 miR-139 miR-106b miR-106b let-7a miR-331 miR-182

miR-205 miR-129

102 subjects from African/African American, Caucasian, Hispanic and Pacific Rim populations. We found two (rs1057092 and rs3199358) of the 18 SNPs in the SNP500Cancer database. Importantly, the frequency of the minor allele was zero in both SNPs in all of the four populations (Table 16.8). This result suggests that the allele frequencies of the two SNPs found in cancer EST libraries differ from the control populations regardless of the source of the EST libraries.

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Table 16.8 Comparison of SNP allele frequency in the cancer EST libraries and in the SNP500Cancer database Cancer EST SNP500cancer SNP

Major allele

Minor allele

Population

Afr/Afr American rs1057092 34 3 Caucasian Hispanic Pacific Rim Total number Afr/Afr American rs3199358 49 3 Caucasian Hispanic Pacific Rim Total number P value was calculated using Fischer’s Exact Test

Major allele

Minor allele

P value

48 62 44 46 200 48 62 46 48 204

0 0 0 0 0 0 0 0 0 0

0.078 0.049 0.091 0.084 0.0035 0.13 0.09 0.15 0.14 0.0080

Table 16.9 MiRNA target SNPs with aberrant allele frequency identified in human cancers Count in Count in control/dbSNP cancers miRNA Major Minor Major Minor MAF MAF Odds ratio target SNP allele allele allele allele (ctrl) (case) [95% CI] P value NM_ rs2292152 1,092 019072 NM_ rs8759 653 005347

16.3.4

10

386

16

3

368

12

0.0091 0.0398 4.53 [2.17, 3.8 × 9.41] 10−5 0.0046 0.0316 7.10 [2.37, 7.2 × 21.2] 10−4

MiRNA Target SNPs with Aberrant SNP Allele Frequency in Human Colon Tumors

To further identify miRNA target SNPs associated with human cancers, we genotyped genomic DNAs derived from cancer patients. We identified 14 SNPs with an aberrant allele frequency in colon cancer when compared with that in the dbSNP database. Twelve of them have been described in our previous report [97]. Table 16.9 shows the two most recently identified. Such SNPs with aberrant allele frequencies in cancer could be used as potential tumor markers and drug targets for early cancer detection and prevention.

16.3.5

SNPs Located at Seed Motifs Affect miRNA Target Expression

Since the 7-nucleotide seed regions of miRNAs are important for miRNA-target interaction and miRNA functions, we postulated that the SNPs located in the 7-nucleotide

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segments (miRNA-binding motifs) of miRNA targets complementary to the seed regions of miRNAs might affect target expression. To test this notion, we compared the frequency of the two alleles of the SNPs located in the miRNA-binding motifs of miRNA targets in the dbEST and dbSNP databases. For convenience, we termed the allele that is 100% complementary to the seed region of a miRNA as “the target allele” and the other with one mismatch as “the non-target allele”. We counted the total numbers of target alleles and the total numbers of non-target alleles of a miRNA target SNP in the dbEST and dbSNP databases respectively and calculated the allele frequencies. We found that the average non-target allele frequency of these SNPs was significantly higher in the dbEST database than in the dbSNP database (0.113 vs. 0.079) [97]. Since the SNP allele frequency found in the dbSNP database represents the distribution of the two alleles in the whole population and since the allele frequency found in the dbEST database represents the relative expression of the two alleles, the expression level of the allele at higher frequency in the dbEST database than in the dbSNP database is also very likely higher than that of the other allele. The higher average frequency of the non-target alleles in the dbEST database than in the dbSNP database suggests that the expression level of the non-target alleles is higher than that of the target alleles. This result indicates that the SNPs/mutations located in the miRNA-binding motifs of miRNA targets can disrupt miRNA-target interaction and lead to the up-regulation of miRNA target expression.

16.4

Discussion

During the past few years, miRNA expression in human cancers has been extensively profiled. The results revealed that many miRNAs are over- or down-regulated in various human cancers, strongly indicating that miRNAs are involved in carcinogenesis. Detailed studies have shown that miRNA deregulation in human cancers could have many causes such as genomic DNA amplification and deletion, unwanted epigenetic regulation and inappropriate activation of the transcription factors that regulate miRNA expression. However, compared with the comprehensive studies of miRNA expression profiling in cancers, little is understood about the associations between miRNA mutations and miRNA target mutations with cancers. Here, we identified several miRNA gene mutations in human cancer patients. The effects of these mutations on miRNA gene transcription, miRNA bio-processing and miRNA-target interaction are currently under investigation at our laboratory. Since miRNAs exert their functions by regulating the expression of their targets, we also studied mutations and SNPs of miRNA targets on miRNA-binding sites to demonstrate the association of miRNA functions with human cancers. Since the SNP frequency in human genome is very high (>1:1,000 base pairs throughout the genome) and due to limited resources and analytical tools, most researchers have focused on specific genes to search SNP-affected disease susceptibility and outcome. Moreover, nonsynonymous SNPs are of considerable interest because

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they shift codons and often change protein structures and functions. However, most SNPs in the genome are not nonsynonymous and they occur in untranslated regions, introns, or intergenic regions. These SNPs could also quantitatively contribute to complex diseases through their effect on gene expression. Unlike nonsynonymous SNPs, those SNPs that can affect gene regulation at the transcriptional level might not be easily identified because gene regulatory elements located in the promoter regions could not be accurately defined in a complicated gene regulation process. In contrast, based on the principle of miRNA-target interaction, the SNPs that affect miRNA-mediated gene regulation at the post-transcriptional level are relatively easy to predict. Accumulating empirical evidence has revealed that seven key nucleotides at the 5′-terminus of miRNAs from position 2 to position 8, called the seed region, are essential for knockdown of their target expression. Based on these discoveries, several computational methods have been developed to predict miRNA targets. The accuracy of these methods has been experimentally confirmed. For example, up to 90% of the randomly selected miRNA targets predicted by Krek et al. have been confirmed as true targets. Consequently, an SNP occurring in a miRNA seed region likely has a functional effect. Indeed, miRNA target SNPs undergo negative selection [13, 74, 97]. More importantly, the density of SNPs located in miRNA seed regions is even lower than that of nonsynonymous SNPs located in coding regions [13]. The strong negative selection of the seed SNPs confirms that interaction between miRNAs and their targets is important for the biological functions of miRNA targets and suggests that SNP-related deregulation of the expression of miRNA targets contributes to tumorigenesis. We performed a genome-wide search for SNPs located in the miRNA-binding sites of miRNA targets using the dbSNP database and comprehensively defined the display of each SNP in cancers vs. normal tissues through comparisons with dbEST extracts from corresponding cDNA libraries. We thus identified several miRNA target SNPs with apparent cancer-associated aberrant frequencies, and used genotyping to confirm that some SNPs are indeed aberrantly present in human tumors. Acknowledgments We thank our team members Zhen Li, Normand Jolicoeur, Linhua Zhang, Meiqun Wu, Yves Fortin and Denis L’Abbe for their contributions to this research project and our collaborator Dr. Edwin Wang for discussion on this manuscript. We acknowledge use of DNA from the British 1958 Birth Cohort collection, funded by the Medical Research Council grant G0000934 and the Wellcome Trust grant 068545/Z/02, and thank D. Strachan, R. Jones and all other members of the 1958 Cohor Biomedical Study Team. This work was supported in part by the Canadian Institute of Health Research Grant MOP82807.

References 1. Akao, Y., Nakagawa, Y., and Naoe, T. (2006). MicroRNAs 143 and 145 are possible common onco-microRNAs in human cancers. Oncol. Rep. 16, 845–850. 2. Akao, Y., Nakagawa, Y., and Naoe, T. (2007). MicroRNA-143 and -145 in colon cancer. DNA Cell Biol. 26, 311–320.

16 SNPs in microRNA and microRNA Target Sites Associated with Human Cancers

299

3. Bandres, E., Cubedo, E., Agirre, X., Malumbres, R., Zarate, R., Ramirez, N., Abajo, A., Navarro, A., Moreno, I., Monzo, M., and Garcia-Foncillas, J. (2006). Identification by Realtime PCR of 13 mature microRNAs differentially expressed in colorectal cancer and nontumoral tissues. Mol. Cancer 5, 29. 4. Bottoni, A., Piccin, D., Tagliati, F., Luchin, A., Zatelli, M.C., and gli Uberti, E.C. (2005). miR-15a and miR-16-1 down-regulation in pituitary adenomas. J. Cell Physiol. 204, 280–285. 5. Brueckner, B., Stresemann, C., Kuner, R., Mund, C., Musch, T., Meister, M., Sultmann, H., and Lyko, F. (2007). The human let-7a-3 locus contains an epigenetically regulated microRNA gene with oncogenic function. Cancer Res. 67, 1419–1423. 6. Calin, G.A., Dumitru, C.D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., Aldler, H., Rattan, S., Keating, M., Rai, K., Rassenti, L., Kipps, T., Negrini, M., Bullrich, F., and Croce, C.M. (2002). Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc. Natl. Acad. Sci. USA 99, 15524–15529. 7. Calin, G.A., Ferracin, M., Cimmino, A., Di, L.G., Shimizu, M., Wojcik, S.E., Iorio, M.V., Visone, R., Sever, N.I., Fabbri, M., Iuliano, R., Palumbo, T., Pichiorri, F., Roldo, C., Garzon, R., Sevignani, C., Rassenti, L., Alder, H., Volinia, S., Liu, C.G., Kipps, T.J., Negrini, M., and Croce, C.M. (2005). A MicroRNA signature associated with prognosis and progression in chronic lymphocytic leukemia. N. Engl. J. Med. 353, 1793–1801. 8. Calin, G.A., Liu, C.G., Sevignani, C., Ferracin, M., Felli, N., Dumitru, C.D., Shimizu, M., Cimmino, A., Zupo, S., Dono, M., Dell’Aquila, M.L., Alder, H., Rassenti, L., Kipps, T.J., Bullrich, F., Negrini, M., and Croce, C.M. (2004a). MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias. Proc. Natl. Acad. Sci. USA 101, 11755–11760. 9. Calin, G.A., Sevignani, C., Dumitru, C.D., Hyslop, T., Noch, E., Yendamuri, S., Shimizu, M., Rattan, S., Bullrich, F., Negrini, M., and Croce, C.M. (2004b). Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proc. Natl. Acad. Sci. USA 101, 2999–3004. 10. Chan, J.A., Krichevsky, A.M., and Kosik, K.S. (2005). MicroRNA-21 is an antiapoptotic factor in human glioblastoma cells. Cancer Res. 65, 6029–6033. 11. Chang, J., Nicolas, E., Marks, D., Sander, C., Lerro, A., Buendia, M.A., Xu, C., Mason, W.S., Moloshok, T., Bort, R., Zaret, K.S., and Taylor, J.M. (2004). miR-122, a mammalian liver-specific microRNA, is processed from hcr mRNA and may downregulate the high affinity cationic amino acid transporter CAT-1. RNA. Biol. 1, 106–113. 12. Chang, T.C., Wentzel, E.A., Kent, O.A., Ramachandran, K., Mullendore, M., Lee, K.H., Feldmann, G., Yamakuchi, M., Ferlito, M., Lowenstein, C.J., Arking, D.E., Beer, M.A., Maitra, A., and Mendell, J.T. (2007). Transactivation of miR-34a by p53 broadly influences gene expression and promotes apoptosis. Mol. Cell 26, 745–752. 13. Chen, K. and Rajewsky, N. (2006). Natural selection on human microRNA binding sites inferred from SNP data. Nat. Genet. 38, 1452–1456. 14. Ciafre, S.A., Galardi, S., Mangiola, A., Ferracin, M., Liu, C.G., Sabatino, G., Negrini, M., Maira, G., Croce, C.M., and Farace, M.G. (2005). Extensive modulation of a set of microRNAs in primary glioblastoma. Biochem. Biophys. Res. Commun. 334, 1351–1358. 15. Cimmino, A., Calin, G.A., Fabbri, M., Iorio, M.V., Ferracin, M., Shimizu, M., Wojcik, S.E., Aqeilan, R.I., Zupo, S., Dono, M., Rassenti, L., Alder, H., Volinia, S., Liu, C.G., Kipps, T.J., Negrini, M., and Croce, C.M. (2005). miR-15 and miR-16 induce apoptosis by targeting BCL2. Proc. Natl. Acad. Sci. USA 102, 13944–13949. 16. Clop, A., Marcq, F., Takeda, H., Pirottin, D., Tordoir, X., Bibe, B., Bouix, J., Caiment, F., Elsen, J.M., Eychenne, F., Larzul, C., Laville, E., Meish, F., Milenkovic, D., Tobin, J., Charlier, C., and Georges, M. (2006). A mutation creating a potential illegitimate microRNA target site in the myostatin gene affects muscularity in sheep. Nat. Genet. 38, 813–818. 17. Clurman, B.E. and Hayward, W.S. (1989). Multiple proto-oncogene activations in avian leukosis virus-induced lymphomas: evidence for stage-specific events. Mol. Cell Biol. 9, 2657–2664.

300

S.-H. Shen, Z. Yu

18. Costinean, S., Zanesi, N., Pekarsky, Y., Tili, E., Volinia, S., Heerema, N., and Croce, C.M. (2006). Pre-B cell proliferation and lymphoblastic leukemia/high-grade lymphoma in E(mu)-miR155 transgenic mice. Proc. Natl. Acad. Sci. USA 103, 7024–7029. 19. Cui, Q., Yu, Z., Purisima, E.O., and Wang, E. (2006). Principles of microRNA regulation of a human cellular signaling network. Mol. Syst. Biol. 2, 46. 20. Dews, M., Homayouni, A., Yu, D., Murphy, D., Sevignani, C., Wentzel, E., Furth, E.E., Lee, W.M., Enders, G.H., Mendell, J.T., and Thomas-Tikhonenko, A. (2006). Augmentation of tumor angiogenesis by a Myc-activated microRNA cluster. Nat. Genet. 38, 1060–1065. 21. Duan, R., Pak, C., and Jin, P. (2007). Single nucleotide polymorphism associated with mature miR-125a alters the processing of pri-miRNA. Hum. Mol. Genet. 16, 1124–1131. 22. Eis, P.S., Tam, W., Sun, L., Chadburn, A., Li, Z., Gomez, M.F., Lund, E., and Dahlberg, J.E. (2005). Accumulation of miR-155 and BIC RNA in human B cell lymphomas. Proc. Natl. Acad. Sci. USA 102, 3627–3632. 23. Esau, C., Kang, X., Peralta, E., Hanson, E., Marcusson, E.G., Ravichandran, L.V., Sun, Y., Koo, S., Perera, R.J., Jain, R., Dean, N.M., Freier, S.M., Bennett, C.F., Lollo, B., and Griffey, R. (2004). MicroRNA-143 regulates adipocyte differentiation. J. Biol. Chem. 279, 52361–52365. 24. Fontana, L., Pelosi, E., Greco, P., Racanicchi, S., Testa, U., Liuzzi, F., Croce, C.M., Brunetti, E., Grignani, F., and Peschle, C. (2007). MicroRNAs 17-5p-20a-106a control monocytopoiesis through AML1 targeting and M-CSF receptor upregulation. Nat. Cell Biol. 9, 775–787. 25. Fulci, V., Chiaretti, S., Goldoni, M., Azzalin, G., Carucci, N., Tavolaro, S., Castellano, L., Magrelli, A., Citarella, F., Messina, M., Maggio, R., Peragine, N., Santangelo, S., Mauro, F.R., Landgraf, P., Tuschl, T., Weir, D.B., Chien, M., Russo, J.J., Ju, J., Sheridan, R., Sander, C., Zavolan, M., Guarini, A., Foa, R., and Macino, G. (2007). Quantitative technologies establish a novel microRNA profile of chronic lymphocytic leukemia. Blood 109, 4944–4951. 26. Galardi, S., Mercatelli, N., Giorda, E., Massalini, S., Frajese, G.V., Ciafre, S.A., and Farace, M.G. (2007). miR-221 and miR-222 expression affects the proliferation potential of human prostate carcinoma cell lines by targeting p27kip1. J. Biol. Chem. 27. Garzon, R., Pichiorri, F., Palumbo, T., Visentini, M., Aqeilan, R., Cimmino, A., Wang, H., Sun, H., Volinia, S., Alder, H., Calin, G.A., Liu, C.G., Andreeff, M., and Croce, C.M. (2007). MicroRNA gene expression during retinoic acid-induced differentiation of human acute promyelocytic leukemia. Oncogene 26, 4148–4157. 28. Ge, B., Gurd, S., Gaudin, T., Dore, C., Lepage, P., Harmsen, E., Hudson, T.J., and Pastinen, T. (2005). Survey of allelic expression using EST mining. Genome Res. 15, 1584–1591. 29. Gramantieri, L., Ferracin, M., Fornari, F., Veronese, A., Sabbioni, S., Liu, C.G., Calin, G.A., Giovannini, C., Ferrazzi, E., Grazi, G.L., Croce, C.M., Bolondi, L., and Negrini, M. (2007). Cyclin G1 is a target of miR-122a, a microRNA frequently down-regulated in human hepatocellular carcinoma. Cancer Res. 67, 6092–6099. 30. Hayashita, Y., Osada, H., Tatematsu, Y., Yamada, H., Yanagisawa, K., Tomida, S., Yatabe, Y., Kawahara, K., Sekido, Y., and Takahashi, T. (2005). A polycistronic microRNA cluster, miR-17-92, is overexpressed in human lung cancers and enhances cell proliferation. Cancer Res. 65, 9628–9632. 31. He, H., Jazdzewski, K., Li, W., Liyanarachchi, S., Nagy, R., Volinia, S., Calin, G.A., Liu, C.G., Franssila, K., Suster, S., Kloos, R.T., Croce, C.M., and de la, C.A. (2005a). The role of microRNA genes in papillary thyroid carcinoma. Proc. Natl. Acad. Sci. USA 102, 19075–19080. 32. He, L., He, X., Lim, L.P., de, S.E., Xuan, Z., Liang, Y., Xue, W., Zender, L., Magnus, J., Ridzon, D., Jackson, A.L., Linsley, P.S., Chen, C., Lowe, S.W., Cleary, M.A., and Hannon, G.J. (2007). A microRNA component of the p53 tumour suppressor network. Nature 447, 1130–1134. 33. He, L., Thomson, J.M., Hemann, M.T., Hernando-Monge, E., Mu, D., Goodson, S., Powers, S., Cordon-Cardo, C., Lowe, S.W., Hannon, G.J., and Hammond, S.M. (2005b). A microRNA polycistron as a potential human oncogene. Nature 435, 828–833.

16 SNPs in microRNA and microRNA Target Sites Associated with Human Cancers

301

34. Hebert, C., Norris, K., Scheper, M.A., Nikitakis, N., and Sauk, J.J. (2007). High mobility group A2 is a target for miRNA-98 in head and neck squamous cell carcinoma. Mol. Cancer 6, 5. 35. Hossain, A., Kuo, M.T., and Saunders, G.F. (2006). Mir-17-5p regulates breast cancer cell proliferation by inhibiting translation of AIB1 mRNA. Mol. Cell Biol. 26, 8191–8201. 36. Iorio, M.V., Ferracin, M., Liu, C.G., Veronese, A., Spizzo, R., Sabbioni, S., Magri, E., Pedriali, M., Fabbri, M., Campiglio, M., Menard, S., Palazzo, J.P., Rosenberg, A., Musiani, P., Volinia, S., Nenci, I., Calin, G.A., Querzoli, P., Negrini, M., and Croce, C.M. (2005). MicroRNA gene expression deregulation in human breast cancer. Cancer Res. 65, 7065–7070. 37. Iwai, N. and Naraba, H. (2005). Polymorphisms in human pre-miRNAs. Biochem. Biophys. Res. Commun. 331, 1439–1444. 38. Johnson, S.M., Grosshans, H., Shingara, J., Byrom, M., Jarvis, R., Cheng, A., Labourier, E., Reinert, K.L., Brown, D., and Slack, F.J. (2005). RAS is regulated by the let-7 microRNA family. Cell 120, 635–647. 39. Kluiver, J., Poppema, S., de, J.D., Blokzijl, T., Harms, G., Jacobs, S., Kroesen, B.J., and van den, B.A. (2005). BIC and miR-155 are highly expressed in Hodgkin, primary mediastinal and diffuse large B cell lymphomas. J. Pathol. 207, 243–249. 40. Krek, A., Grun, D., Poy, M.N., Wolf, R., Rosenberg, L., Epstein, E.J., MacMenamin, P., da Piedade, I., Gunsalus, K.C., Stoffel, M., and Rajewsky, N. (2005). Combinatorial microRNA target predictions. Nat. Genet. 37, 495–500. 41. Kumar, M.S., Lu, J., Mercer, K.L., Golub, T.R., and Jacks, T. (2007). Impaired microRNA processing enhances cellular transformation and tumorigenesis. Nat. Genet. 39, 673–677. 42. Kutay, H., Bai, S., Datta, J., Motiwala, T., Pogribny, I., Frankel, W., Jacob, S.T., and Ghoshal, K. (2006). Downregulation of miR-122 in the rodent and human hepatocellular carcinomas. J. Cell Biochem. 99, 671–678. 43. Lagos-Quintana, M., Rauhut, R., Yalcin, A., Meyer, J., Lendeckel, W., and Tuschl, T. (2002). Identification of tissue-specific microRNAs from mouse. Curr. Biol. 12, 735–739. 44. Lawrie, C.H., Soneji, S., Marafioti, T., Cooper, C.D., Palazzo, S., Paterson, J.C., Cattan, H., Enver, T., Mager, R., Boultwood, J., Wainscoat, J.S., and Hatton, C.S. (2007). Microrna expression distinguishes between germinal center B cell-like and activated B cell-like subtypes of diffuse large B cell lymphoma. Int. J. Cancer 121, 1156–1161. 45. Le Sage, C., Nagel, R., Egan, D.A., Schrier, M., Mesman, E., Mangiola, A., Anile, C., Maira, G., Mercatelli, N., Ciafre, S.A., Farace, M.G., and Agami, R. (2007). Regulation of the p27(Kip1) tumor suppressor by miR-221 and miR-222 promotes cancer cell proliferation. EMBO J. 46. Lee, E.J., Gusev, Y., Jiang, J., Nuovo, G.J., Lerner, M.R., Frankel, W.L., Morgan, D.L., Postier, R.G., Brackett, D.J., and Schmittgen, T.D. (2007). Expression profiling identifies microRNA signature in pancreatic cancer. Int. J. Cancer 120, 1046–1054. 47. Lee, Y.S. and Dutta, A. (2007). The tumor suppressor microRNA let-7 represses the HMGA2 oncogene. Genes Dev. 21, 1025–1030. 48. Lee, Y.S., Kim, H.K., Chung, S., Kim, K.S., and Dutta, A. (2005). Depletion of human micro-RNA miR-125b reveals that it is critical for the proliferation of differentiated cells but not for the down-regulation of putative targets during differentiation. J. Biol. Chem. 280, 16635–16641. 49. Loffler, D., Brocke-Heidrich, K., Pfeifer, G., Stocsits, C., Hackermuller, J., Kretzschmar, A.K., Burger, R., Gramatzki, M., Blumert, C., Bauer, K., Cvijic, H., Ullmann, A.K., Stadler, P.F., and Horn, F. (2007). Interleukin-6-dependent survival of multiple myeloma cells involves the Stat3-mediated induction of microRNA-21 through a highly conserved enhancer. Blood. 110, 1330–1333. 50. Looijenga, L.H., Gillis, A.J., Stoop, H., Hersmus, R., and Oosterhuis, J.W. (2007). Relevance of microRNAs in normal and malignant development, including human testicular germ cell tumours. Int. J. Androl. 30, 304–314.

302

S.-H. Shen, Z. Yu

51. Lu, J., Getz, G., Miska, E.A., varez-Saavedra, E., Lamb, J., Peck, D., Sweet-Cordero, A., Ebert, B.L., Mak, R.H., Ferrando, A.A., Downing, J.R., Jacks, T., Horvitz, H.R., and Golub, T.R. (2005). MicroRNA expression profiles classify human cancers. Nature 435, 834–838. 52. Lui, W.O., Pourmand, N., Patterson, B.K., and Fire, A. (2007). Patterns of known and novel small RNAs in human cervical cancer. Cancer Res. 67, 6031–6043. 53. Lujambio, A., Ropero, S., Ballestar, E., Fraga, M.F., Cerrato, C., Setien, F., Casado, S., Suarez-Gauthier, A., Sanchez-Cespedes, M., Git, A., Spiteri, I., Das, P.P., Caldas, C., Miska, E., and Esteller, M. (2007). Genetic unmasking of an epigenetically silenced microRNA in human cancer cells. Cancer Res. 67, 1424–1429. 54. Lum, A.M., Wang, B.B., Li, L., Channa, N., Bartha, G., and Wabl, M. (2007). Retroviral activation of the mir-106a microRNA cistron in T lymphoma. Retrovirology. 4, 5. 55. Martin, M.M., Buckenberger, J.A., Jiang, J., Malana, G.E., Nuovo, G.J., Chotani, M., Feldman, D.S., Schmittgen, T.D., and Elton, T.S. (2007). The human angiotensin II type 1 receptor + 1166 A/C polymorphism attenuates MicroRNA-155 binding. J. Biol. Chem. 282, 24262–24269. 56. Mayr, C., Hemann, M.T., and Bartel, D.P. (2007). Disrupting the pairing between let-7 and Hmga2 enhances oncogenic transformation. Science 315, 1576–1579. 57. Meng, F., Henson, R., Lang, M., Wehbe, H., Maheshwari, S., Mendell, J.T., Jiang, J., Schmittgen, T.D., and Patel, T. (2006). Involvement of human micro-RNA in growth and response to chemotherapy in human cholangiocarcinoma cell lines. Gastroenterology 130, 2113–2129. 58. Meng, F., Henson, R., Wehbe-Janek, H., Smith, H., Ueno, Y., and Patel, T. (2007). The MicroRNA let-7a modulates interleukin-6-dependent STAT-3 survival signaling in malignant human cholangiocytes. J. Biol. Chem. 282, 8256–8264. 59. Meng, F., Wehbe-Janek, H., Henson, R., Smith, H., and Patel, T. (2008). Epigenetic regulation of microRNA-370 by interleukin-6 in malignant human cholangiocytes. Oncogene. 27, 378–386. 60. Michael, M.Z., O’ Connor, S.M., van Holst Pellekaan, N.G., Young, G.P., and James, R.J. (2003). Reduced accumulation of specific microRNAs in colorectal neoplasia. Mol. Cancer Res. 1, 882–891. 61. Mishra, P.J., Humeniuk, R., Mishra, P.J., Longo-Sorbello, G.S., Banerjee, D., and Bertino, J.R. (2007). A miR-24 microRNA binding-site polymorphism in dihydrofolate reductase gene leads to methotrexate resistance. Proc. Natl. Acad. Sci. USA 104, 13513–13518. 62. Mott, J.L., Kobayashi, S., Bronk, S.F., and Gores, G.J. (2007). mir-29 regulates Mcl-1 protein expression and apoptosis. Oncogene. 26, 6133–6140. 63. Nakagawa, Y., Iinuma, M., Naoe, T., Nozawa, Y., and Akao, Y. (2007). Characterized mechanism of alpha-mangostin-induced cell death: Caspase-independent apoptosis with release of endonuclease-G from mitochondria and increased miR-143 expression in human colorectal cancer DLD-1 cells. Bioorg. Med. Chem. 15, 5620–5628. 64. O’Donnell, K.A., Wentzel, E.A., Zeller, K.I., Dang, C.V., and Mendell, J.T. (2005). c-Mycregulated microRNAs modulate E2F1 expression. Nature 435, 839–843. 65. Ota, A., Tagawa, H., Karnan, S., Tsuzuki, S., Karpas, A., Kira, S., Yoshida, Y., and Seto, M. (2004). Identification and characterization of a novel gene, C13orf25, as a target for 13q31q32 amplification in malignant lymphoma. Cancer Res. 64, 3087–3095. 66. Pallante, P., Visone, R., Ferracin, M., Ferraro, A., Berlingieri, M.T., Troncone, G., Chiappetta, G., Liu, C.G., Santoro, M., Negrini, M., Croce, C.M., and Fusco, A. (2006). MicroRNA deregulation in human thyroid papillary carcinomas. Endocr-Relat Cancer 13, 497–508. 67. Pekarsky, Y., Santanam, U., Cimmino, A., Palamarchuk, A., Efanov, A., Maximov, V., Volinia, S., Alder, H., Liu, C.G., Rassenti, L., Calin, G.A., Hagan, J.P., Kipps, T., and Croce, C.M. (2006). Tcl1 expression in chronic lymphocytic leukemia is regulated by miR-29 and miR-181. Cancer Res. 66, 11590–11593. 68. Raveche, E.S., Salerno, E., Scaglione, B.J., Manohar, V., Abbasi, F., Lin, Y.C., Fredrickson, T., Landgraf, P., Ramachandra, S., Huppi, K., Toro, J.R., Zenger, V.E., Metcalf, R.A., and Marti, G.E. (2007). Abnormal microRNA-16 locus with synteny to human 13q14 linked to CLL in NZB mice. Blood 109, 5079–5086.

16 SNPs in microRNA and microRNA Target Sites Associated with Human Cancers

303

69. Raver-Shapira, N., Marciano, E., Meiri, E., Spector, Y., Rosenfeld, N., Moskovits, N., Bentwich, Z., and Oren, M. (2007). Transcriptional activation of miR-34a contributes to p53-mediated apoptosis. Mol. Cell 26, 731–743. 70. Rinaldi, A., Poretti, G., Kwee, I., Zucca, E., Catapano, C.V., Tibiletti, M.G., and Bertoni, F. (2007). Concomitant MYC and microRNA cluster miR-17-92 (C13orf25) amplification in human mantle cell lymphoma. Leukemia Lymphoma 48, 410–412. 71. Roldo, C., Missiaglia, E., Hagan, J.P., Falconi, M., Capelli, P., Bersani, S., Calin, G.A., Volinia, S., Liu, C.G., Scarpa, A., and Croce, C.M. (2006). MicroRNA expression abnormalities in pancreatic endocrine and acinar tumors are associated with distinctive pathologic features and clinical behavior. J. Clin. Oncol. 24, 4677–4684. 72. Saito, Y., Liang, G., Egger, G., Friedman, J.M., Chuang, J.C., Coetzee, G.A., and Jones, P.A. (2006). Specific activation of microRNA-127 with downregulation of the proto-oncogene BCL6 by chromatin-modifying drugs in human cancer cells. Cancer Cell 9, 435–443. 73. Sarhadi, V.K., Wikman, H., Salmenkivi, K., Kuosma, E., Sioris, T., Salo, J., Karjalainen, A., Knuutila, S., and Anttila, S. (2006). Increased expression of high mobility group A proteins in lung cancer. J. Pathol. 209, 206–212. 74. Saunders, M.A., Liang, H., and Li, W.H. (2007). Human polymorphism at microRNAs and microRNA target sites. Proc. Natl. Acad. Sci. USA 104, 3300–3305. 75. Schulman, B.R., Esquela-Kerscher, A., and Slack, F.J. (2005). Reciprocal expression of lin-41 and the microRNAs let-7 and mir-125 during mouse embryogenesis. Dev. Dyn. 234, 1046–1054. 76. Scott, G.K., Goga, A., Bhaumik, D., Berger, C.E., Sullivan, C.S., and Benz, C.C. (2007). Coordinate suppression of ERBB2 and ERBB3 by enforced expression of micro-RNA miR125a or miR-125b. J. Biol. Chem. 282, 1479–1486. 77. Sethupathy, P., Borel, C., Gagnebin, M., Grant, G.R., Deutsch, S., Elton, T.S., Hatzigeorgiou, A.G., and Antonarakis, S.E. (2007). Human microRNA-155 on chromosome 21 differentially interacts with its polymorphic target in the AGTR1 3¢ untranslated region: a mechanism for functional single-nucleotide polymorphisms related to phenotypes. Am. J. Hum. Genet. 81, 405–413. 78. Sevignani, C., Calin, G.A., Nnadi, S.C., Shimizu, M., Davuluri, R.V., Hyslop, T., Demant, P., Croce, C.M., and Siracusa, L.D. (2007). MicroRNA genes are frequently located near mouse cancer susceptibility loci. Proc. Natl. Acad. Sci. USA 104, 8017–8022. 79. Shah, Y.M., Morimura, K., Yang, Q., Tanabe, T., Takagi, M., and Gonzalez, F.J. (2007). Peroxisome proliferator-activated receptor alpha regulates a microRNA-mediated signaling cascade responsible for hepatocellular proliferation. Mol. Cell Biol. 27, 4238–4247. 80. Shell, S., Park, S.M., Radjabi, A.R., Schickel, R., Kistner, E.O., Jewell, D.A., Feig, C., Lengyel, E., and Peter, M.E. (2007). Let-7 expression defines two differentiation stages of cancer. Proc. Natl. Acad. Sci. USA 104, 11400–11405. 81. Si, M.L., Zhu, S., Wu, H., Lu, Z., Wu, F., and Mo, Y.Y. (2007). miR-21-mediated tumor growth. Oncogene 26, 2799–2803. 82. Slape, C., Hartung, H., Lin, Y.W., Bies, J., Wolff, L., and Aplan, P.D. (2007). Retroviral insertional mutagenesis identifies genes that collaborate with NUP98-HOXD13 during leukemic transformation. Cancer Res. 67, 5148–5155. 83. Sylvestre, Y., De Guire, V., Querido, E., Mukhopadhyay, U.K., Bourdeau, V., Major, F., Ferbeyre, G., and Chartrand, P. (2007). An E2F/miR-20a autoregulatory feedback loop. J. Biol. Chem. 282, 2135–2143. 84. Tagawa, H., Karube, K., Tsuzuki, S., Ohshima, K., and Seto, M. (2007). Synergistic action of the microRNA-17 polycistron and Myc in aggressive cancer development. Cancer Sci. 98, 1482–1490. 85. Takamizawa, J., Konishi, H., Yanagisawa, K., Tomida, S., Osada, H., Endoh, H., Harano, T., Yatabe, Y., Nagino, M., Nimura, Y., Mitsudomi, T., and Takahashi, T. (2004). Reduced expression of the let-7 microRNAs in human lung cancers in association with shortened postoperative survival. Cancer Res. 64, 3753–3756. 86. Tarasov, V., Jung, P., Verdoodt, B., Lodygin, D., Epanchintsev, A., Menssen, A., Meister, G., and Hermeking, H. (2007). Differential regulation of microRNAs by p53 revealed by

304

87.

88.

89.

90.

91.

92.

93. 94. 95.

96.

97.

98.

99.

100.

S.-H. Shen, Z. Yu massively parallel sequencing: miR-34a is a p53 target that induces apoptosis and G1-arrest. Cell Cycle 6, 1586–1593. van den, B.A., Kroesen, B.J., Kooistra, K., de, J.D., Briggs, J., Blokzijl, T., Jacobs, S., Kluiver, J., Diepstra, A., Maggio, E., and Poppema, S. (2003). High expression of B-cell receptor inducible gene BIC in all subtypes of Hodgkin lymphoma. Gene. Chromosome. Cancer 37, 20–28. Visone, R., Pallante, P., Vecchione, A., Cirombella, R., Ferracin, M., Ferraro, A., Volinia, S., Coluzzi, S., Leone, V., Borbone, E., Liu, C.G., Petrocca, F., Troncone, G., Calin, G.A., Scarpa, A., Colato, C., Tallini, G., Santoro, M., Croce, C.M., and Fusco, A. (2007). Specific microRNAs are downregulated in human thyroid anaplastic carcinomas. Oncogene 26, 7590–7595 Volinia, S., Calin, G.A., Liu, C.G., Ambs, S., Cimmino, A., Petrocca, F., Visone, R., Iorio, M., Roldo, C., Ferracin, M., Prueitt, R.L., Yanaihara, N., Lanza, G., Scarpa, A., Vecchione, A., Negrini, M., Harris, C.C., and Croce, C.M. (2006). A microRNA expression signature of human solid tumors defines cancer gene targets. Proc. Natl. Acad. Sci. USA 103, 2257–2261. Voorhoeve, P.M., le, S.C., Schrier, M., Gillis, A.J., Stoop, H., Nagel, R., Liu, Y.P., van, D.J., Drost, J., Griekspoor, A., Zlotorynski, E., Yabuta, N., De, V.G., Nojima, H., Looijenga, L. H., and Agami, R. (2006). A genetic screen implicates miRNA-372 and miRNA-373 as oncogenes in testicular germ cell tumors. Cell 124, 1169–1181. Wang, C.L., Wang, B.B., Bartha, G., Li, L., Channa, N., Klinger, M., Killeen, N., and Wabl, M. (2006). Activation of an oncogenic microRNA cistron by provirus integration. Proc. Natl. Acad. Sci. USA 103, 18680–18684. Wang, T., Zhang, X., Obijuru, L., Laser, J., Aris, V., Lee, P., Mittal, K., Soteropoulos, P., and Wei, J.J. (2007). A micro-RNA signature associated with race, tumor size, and target gene activity in human uterine leiomyomas. Gene. Chromosome. Cancer 46, 336–347. Welch, C., Chen, Y., and Stallings, R.L. (2007). MicroRNA-34a functions as a potential tumor suppressor by inducing apoptosis in neuroblastoma cells. Oncogene 26, 5017–5022. Wu, L. and Belasco, J.G. (2005). Micro-RNA regulation of the mammalian lin-28 gene during neuronal differentiation of embryonal carcinoma cells. Mol. Cell Biol. 25, 9198–9208. Yanaihara, N., Caplen, N., Bowman, E., Seike, M., Kumamoto, K., Yi, M., Stephens, R.M., Okamoto, A., Yokota, J., Tanaka, T., Calin, G.A., Liu, C.G., Croce, C.M., and Harris, C.C. (2006). Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell 9, 189–198. Yu, Z., Jian, Z., Shen, S.H., Purisima, E., and Wang, E. (2007a). Global analysis of microRNA target gene expression reveals that miRNA targets are lower expressed in mature mouse and Drosophila tissues than in the embryos. Nucleic Acids Res. 35, 152–164. Yu, Z., Li, Z., Jolicoeur, N., Zhang, L., Fortin, Y., Wang, E., Wu, M., and Shen, S.H. (2007b). Aberrant allele frequencies of the SNPs located in microRNA target sites are potentially associated with human cancers. Nucleic Acids Res. 35, 4535–4541. Zavadil, J., Narasimhan, M., Blumenberg, M., and Schneider, R.J. (2007). Transforming growth factor-beta and microRNA:mRNA regulatory networks in epithelial plasticity. Cells Tissues Organs 185, 157–161. Zhang, L., Huang, J., Yang, N., Greshock, J., Megraw, M.S., Giannakakis, A., Liang, S., Naylor, T.L., Barchetti, A., Ward, M.R., Yao, G., Medina, A., O’brien-Jenkins, A., Katsaros, D., Hatzigeorgiou, A., Gimotty, P.A., Weber, B.L., and Coukos, G. (2006). microRNAs exhibit high frequency genomic alterations in human cancer. Proc. Natl. Acad. Sci. USA 103, 9136–9141. Zhu, S., Si, M.L., Wu, H., and Mo, Y.Y. (2007). MicroRNA-21 targets the tumor suppressor gene tropomyosin 1 (TPM1). J. Biol. Chem. 282, 14328–14336.

Chapter 17

Expression and Function of microRNAs in Chronic Myeloid Leukemia* Michaela Scherr*, Letizia Venturini, and Matthias Eder*

Abstract Micro RNAs represent a class of small regulatory non-coding RNAs which are aberrantly expressed in some human malignancies. We here describe specific regulation of miRNA expression in chronic myeloid leukemia (CML) depending on BCR-ABL, the characteristic onco-protein of CML. Using microarray analysis (miCHIP) and miRNA-specific quantitative real-time RT-PCR from CML cell lines treated with either imatinib or anti BCR-ABL shRNAs to inhibit its tyrosine kinase activity or its protein expression, we found specific down-regulation of miRNAs encoded within the polycistronic miR-17-92 cluster (two- to fivefold). In addition, analysis of miR-17-92 expression in purified normal, early chronic phase and blast crisis CML CD34 + cells demonstrated increased expression in chronic phase but not in blast crisis CML. Lentivirus-mediated over-expression of miR-17-92 encoded miRNAs in K562 cells increases proliferation and enhances sensitivity to imatinib induced cell death. Furthermore, reporter assays using luciferase genes with specific miRNA binding sites in the 3′ untranslated region were used to specifically inhibit miRNA function by so called antagomirs. Finally, strategies to induce stable gain- and loss of function phenotypes for specific miRNAs based on lentiviral transfer of miRNA- and antagomir expression cassettes allow functional analysis for individual miRNAs. Such studies are required to determine whether altered miRNA expression may contribute to the pathophysiology of CML and if so how miRNAs may provide potential targets for therapeutic intervention.

Hannover Medical School, Department of Hematology, Hemostasis and Oncology, 30625 Hannover, Germany *Corresponding authors: Medizinische Hochschule Hannover, Zentrum Innere Medizin, Klinik für Hämatologie, Hämostaseologie, Onkologie und Stammzelltransplantation, Carl-Neuberg Strasse 1, D-30623 Hannover, Germany; Phone: (+49) 511 532 9207; Fax: (+49) 511 532 9242; E-mails: [email protected], [email protected] * Supported in part by grants of the “Deutsche Forschungsgemeinschaft” (SFB 566), H.W. & J. Hector-Stiftung, Wilhelm Sanders-Stiftung

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Keywords non-coding RNAs, miRNA microarray (miCHIP), chronic myeloid leukemia (CML), polycistronic, anti BCR-ABL shRNAs, tyrosine kinase, CD34, lentivirus-mediated, antagomir, therapeutic intervention

17.1

Introduction

Micro RNAs are a recently discovered class of short regulatory RNAs, which negatively regulate gene expression in a sequence-specific manner by translational repression, degradation or destabilization of target mRNAs [9, 17]. Through genetic screening in the nematode worm C. elegans, lin-4 and let-7, the first miRNAs to be discovered, were shown to function as regulators of developmental timing [14, 22]. Subsequent studies in vertebrates suggest that miRNAs play key roles in a variety of cellular pathways such as differentiation [5], proliferation [29] and apoptosis [6]. Moreover, an additional focus in the miRNA field developed as these small regulatory molecules are aberrantly expressed in many types of cancer [11–13], including haematological malignancies [4, 31]. miRNAs have been found to act similar to both tumor suppressor molecules (miR-15a, miR-16) in leukemias [3] and to oncogene products such as miR-155 and miR-17-92 in lymphomas [8, 11, 12, 20]. In addition, miRNA expression profiles can help to classify human cancer types [19]. miRNAs are processed in a regulated multi-step process [2]. As shown in Fig. 17.1A, miRNA biogenesis starts with the transcription of long primary transcripts (pri-miRNAs), either from individual miRNA genes, from polycistrons, or from introns of protein-coding genes. Pri-miRNAs are processed in the nucleus by Drosha, an RNaseIII-type nuclease, into ∼70 nt long precursor miRNAs (pre-miRNAs). Following export to the cytoplasm by Exportin-5, the pre-miRNA is further processed by Dicer, another RNaseIII-type enzyme to generate mature double-stranded miRNAs. Similar to siRNAs, one miRNA strand is then incorporated into a multi-enzyme complex RISC (RNA-induced silencing complex) which is required for recognition of its target mRNAs [10, 15]. As part of the RISC, miRNAs negatively regulate gene expression by two mechanisms namely translational inhibition or mRNA degradation, depending of the degree of complementarities between miRNA and target mRNA. Partial base pairing seems to mediate translational inhibition whereas perfect base pairing usually results in endonucleolytic cleavage [17]. miRNAs are often transcribed as polycistronic transcripts encoding multiple, often closely related miRNAs. As shown in Fig. 17.1B, seven miRNAs (miR-17-5p, miR-17-3p, miR-18a, miR-19a, miR-20a, miR-19b, miR-92-1) are annotated to and transcribed from an intron of the C13-25orf locus at 13q31-q32 [28]. It has been shown that this miR-17-92 polycistron is amplified and over-expressed in different types of B-cell lymphoma [21], promotes lymphomagenesis in a murine stem cell transplantation model [12], and is transcriptionally regulated by c-Myc [20]. Furthermore, miR-17-92 is over-expressed in an erythroleukemia model [7] and we recently demonstrated BCR-ABL and c-MYC dependent aberrant expression of the polycistronic miR17-92 miRNA cluster in early phase chronic myeloid leukaemia

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Fig. 17.1 (A) miRNA biogenesis. Pri-miRNAs are transcribed by RNA Polymerase II and processed in the nucleus by Drosha (RNAse III) into pre-miRNAs. The pre-miRNA is exported into the cytoplasm by Exportin-5 and further processed by Dicer, another RNAse III, into mature miRNAs (∼22 nt). Helicase can unwind the duplex into two separate strands. One strand is loaded into a multiprotein complex called RISC (RNA-induced silencing complex) and finally guides RISC to target mRNAs resulting either in translational attenuation or endonucleolytic cleavage of the target mRNA. (B) Schematic representation of the miR-17-19b cluster according to [28]

(CML) CD34 + cells [31]. CML is a myeloproliferative stem cell disorder characterized by the Philadelphia translocation t (9;22)(q34;q11) resulting in the generation of the oncogenic bcr-abl fusion gene. The corresponding BCR-ABL onco-protein is a constitutively active tyrosine kinase which activates intracellular signalling cascades. Recent evidence identifies miRNAs at least as indirect downstream targets of the BCR-ABL tyrosine kinase [31]. The function of and the targets regulated by individual miRNAs, in particular of those encoded on polycistronic transcripts, are largely unknown. The analysis of miRNA gain- and loss-of function phenotypes in cultured cells should allow the assignment of functions to individual miRNAs encoded on the polycistronic miR-17-92 miRNA cluster. Here we summarize our data on BCR-ABL-mediated expression of miR-17-92 miRNAs in early phase CML-CD34 + cells.

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Materials and Methods RNA Isolation and miR-qRT-PCR

Total RNA from human chronic myeloid leukemia cell lines K562, LAMA-84, and EM-2 and from purified normal peripheral blood CD34 + (purity >90%), peripheral blood CD34 + cells from newly diagnosed chronic phase CML (purity >98%), and from patients in blast crisis (purity >90%) was prepared using Trizol (Invitrogen) and analyzed using an Agilent 2100 bioanalyzer (Agilent Technologies). Expression of mature miRNAs was determined using miR-qRT-PCR (Applied Biosystems, Foster City, USA) and was normalized using the 2-∆∆CT method [18] relative to miR-16 miRNA, which was nearly equally expressed in normal CD34 + cells (i.e. <1.3-fold change in CD34 + and K562 cells in all conditions tested, data not shown). PCR was performed in duplicate using an ABI7500 cycler, and miRNAexpression of CML samples was normalized to the averaged ratio of 4 normal CD34 + samples.

17.2.2

Antagomirs, Sensor Plasmids, and Luciferase Assays

Antagomirs (AmiR-17.5p: 5′-ACUACCUGCACUGUAAGCACUUUG-3′ and scrambleAmiR: 5′-AAAACCUUUUGACCGAGCGUGUU-3′) were chemically synthesized as 2′-O-methyloligoribonucleotides by BioSpring (Frankfurt, Germany). The sensor and control luciferase plasmids pGL3-miR-17.5p-sensor and -control were kindly provided by Joshua Mendell [20]. The sensor plasmid has two sites complementary to miR17.5p and the control plasmid has the insert in reverse complement orientation. K562 cells (1 × 106) were electroporated (330 V, 10 ms) in 100 µl RPMI 1640/10% FCS containing either 1 µg pGL3-miR-17.5p-sensor or -miR-17.5p-control plasmid and 0.1 µg pBabe-Puro plasmid in a 4 mm electroporation cuvette using an EPI 2500 gene pulser (Fischer, Heidelberg, Germany). The cells were selected with 2 µg/µl puromycin to generate stable clones of K562-17.5p-sensor and K562-17.5p-control. The transfection of the antagomiRs into K562 cells stably expressing the 17.5p sensor or 17.5p-control cassette was carried out by electroporation. 1 × 106 cells were electroporated (330 V and 10 mA) in a volume of 100 µl medium containing 2 µg antagomiR and 0.25 µg pRLSV40 (Promega, Madison, USA). Luciferase assays were performed 24 h after transfection using the Dual Luciferase Reporter Assay System (Promega). Firefly luciferase activity was normalized to renilla luciferase activity for each reaction.

17.2.3

Lentiviral Over-Expression of the miR-17-19b Cluster

The retroviral vector MSCV-PIG-17-19b containing miR-17-19b-1 [12] was kindly provided by Gregory Hannon. To construct the lentiviral vector S-17-19b-IEW, the plasmid pHR’-SIN-SIEW-SnaBI was digested with BamHI followed by a DNA polymerase I

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fill-in reaction and gel purification. The miR-17-19b-1 cassette was excised from MSCVPIG-17-19b plasmid with XhoI/EcoRI, and the cohesive ends were filled in using Klenow. The blunt-end ∼790 nt fragment was ligated with the blunted BamHI vector fragment placing 17-19b-1 downstream of the SFFV promoter (S-17-19b-IEW). Lentiviral vector particles were produced by transient calcium phosphate cotransfection of 293T cells in a T175 flask with 60 µg lentiviral vector DNA together with 45 µg of packaging plasmid DNA, and 30 µg of VSV.G plasmid [24]. Viral supernatants were harvested 32 and 48 h after transfection, concentrated by low speed centrifugation at 10,000 rpm for 16 h at 10 °C, and titered as described [23]. The titers were averaged and typically ranged between 1–10 × 107 IU/ml. Parental K562 cells and K562 cells stably expressing SIEW or S-17/19b-IEW were transduced at an MOI of ∼1 as described [25], were sorted for GFP-expression using DakoCytomation MoFlo (Glostrup, Denmark), and individual clones were isolated.

17.2.4

Cloning of H1-Antagomir Expression Cassettes

Self-complementary DNA oligonucleotides (BioSpring, Frankfurt, Germany) encompassing the sequence of the miRNAs miR-18a, miR-19b, and miR-20a, as well as an irrelevant sequence (ant-ctrl) were chemically synthesized including overhang sequences from a 5′ Bgl II- and a 3′ Sal I- restriction site. Annealed oligonucleotides were directionally cloned into the Bgl II/Sal I-digested pBlueScript-derived pH1plasmid as described [24] to generate pH1ant-miR-18a, pH1ant-miR-19b, pH1ant-miR20a and pH1-ant-ctrl. pdc-SEW was used to generate lentiviral transgenic plasmids containing H1-antagomir expression cassettes located in the U3 region of the ∆3’long terminal repeat (LTR) [24]. To generate the lentiviral pdcH1-antagomir-SEW plasmid, the pH1ant-mir-18a, pH1ant-mir-19b, pH1ant-mir-20a and pH1-ant-ctrl plasmids were digested with SmaI and HincII and the resulting DNA fragments (∼320 nt) were blunt-end ligated into the SnaBI site of pdc-SEW to generate pdcH1-ant-18a-SEW, pdcH1-ant-19b-SEW, pdcH1-ant-20a-SEW, and pdcH1-ant-ctrl-SEW, respectively.

17.2.5

Lentiviral Over-Expression of miRNAs

The cloning of individual miRNAs into the lentiviral vector S-miR30miRNA-IEW has been previously described [26]. The correct sequence and insertion was confirmed by DNA sequencing for S-miR30miR-18a-IEW, S-miR30miR-19b-IEW, S-miR30miR-20a-IEW, and S-miR30-IEW (control), respectively.

17.2.6

Cell Proliferation of Transduced K562 Cells

Transduced K562 cells (5 × 104/ml) were cultured in 24-well plates and viable cells were counted from one to 7 days by trypan blue exclusion.

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Results miRNA Expression in CML Cell Lines

To study miRNA expression in CML cells, we used miRNA-specific quantitative real-time RT-PCR (miR-qRT-PCR). miR-qRT-PCR allows detection and quantification of individual mature miRNAs by the use of miRNA-specific looped primers for reverse transcription followed by quantitative PCR as schematically shown in Fig. 17.2. We used this method to validate miRNA expression patterns observed in miRNA-microarray analysis (miCHIP), initially employed to screen for differentially expressed miRNAs in the K562 CML cell line in the presence or absence of

Fig. 17.2 Quantification of miRNAs using miRNA-specific quantitative RT-PCR (miR-qRTPCR). The cDNA is first reverse transcribed from total RNA using specific miRNA stem-loop primers. In a second step, the ‘real-time’ qPCR, the amplicons are synthesized from cDNA using miRNA specific primers and probes

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BCR-ABL tyrosine kinase activity. Among the 210 miRNAs analyzed, miCHIP demonstrated BCR-ABL-dependent regulation of nine miRNAs more than twofold: miR-17-5p, miR-17-3p, miR-20a, miR-92, miR-106a, miR-106b, miR-142-3p and miR-212 were down- and miR-129 was up-regulated, respectively [31]. Noteworthy, four of these miRNAs (miR-17-5p, miR-17-3p, miR-20a and miR-92) are encoded within the miR-17-92 polycistronic cluster which further contains miR-18a, miR-19a and miR-19b (Fig. 17.1B). Furthermore, miR-106a and miR-106b are located in paralogue clusters of miR-17-92 [28]. We therefore performed miR-qRT-PCR on identical total RNA samples from K562 cells treated as described with 1 µM of the BCR-ABL specific tyrosine kinase inhibitor imatinib mesylate or with lentivirally expressed anti-bcr-abl-shRNAs [24]. As shown in Fig. 17.3, miR-qRT-PCR demonstrated specific down-regulation (between two- and five-fold) in both imatinib and shRNA treated cells as compared to the respective controls (untreated cells, or cells treated with an irrelevant shRNA) for all miRNAs encoded within the miR-17-92 cluster, except miR-17-3p and miR-92, for which no regulation was observed. In addition, down-regulation of miR-106a, miR-106b (except in the case of imatinib treatment), miR-142-3p, miR-142-5p and miR-212, as well as up-regulation of miR-129, was confirmed by miR-qRT-PCR (Fig. 17.3). To study whether the observed BCR-ABL-dependent miRNA expression was indeed BCR-ABL specific and not restricted to K562 cells, we analyzed two additional BCR-ABL positive CML cell lines, LAMA-84 and EM-2, by miR-qRT-PCR. After anti-BCR-ABL RNAi (Fig. 17.4A) and imatinib treatment (Fig. 17.4B), the miRNA expression pattern in both these cell lines was very similar to that observed in K562 cells, especially for the miRNAs belonging to the miR-17-92 cluster. Moreover, the observation that imatinib treatment did not effect miRNA expression in the BCR-ABL negative HL-60 cell line (data not shown) further supports the specificity of the observed miRNA regulation by BCR-ABL.

Fig. 17.3 miR-qRT-PCR of miRNAs regulated by BCR-ABL in K562 cells. miRNA expression in K562 cells treated with imatinib (light-grey bars) and lentivirally expressed anti-bcr-abl shRNA (dark-grey bars) was compared to parental or control shRNA transduced K562 cells. Mean and SD of two independent experiments. miR-16 served as an endogenous control

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Fig. 17.4 miR-qRT-PCR of miRNAs regulated by BCR-ABL. (A) miRNA expression in LAMA and EM-2 cells treated with imatinib was compared to parental LAMA-84 (dark-grey bars) and EM-2 cells (light-grey bars), respectively. (B) miRNA expression in cells treated with lentivirally expressed anti-bcr-abl shRNA was compared to control shRNA transduced LAMA-84 cells (darkgrey bars) and EM-2 cells (light-grey bars), respectively. miR-16 served as an endogenous control. Mean and SD of two independent experiments

17.3.2

miRNA Expression in CML Patients

miR-qRT-PCR was also used to analyze miRNA expression in CD34 + cells from CML patients in chronic phase (CP) and in blast crisis (BC) as well as in highly purified CD34 + cells from four healthy donors. As shown in Fig. 17.5, all the miRNAs found to be regulated in the CML cell lines, were over-expressed between two and six fold (mean of 24 patients is shown) in CP CD34 + primary samples as compared to normal CD34 + cells. In contrast, the miRNA expression in BC CD34 + cells was nearly unchanged or even down-regulated (mean of seven patients between 0.3 to 1.6 fold) except miR-212 which was consistently over-expressed. Presumably due to its low expression in primary cells, we were not able to detect the expression of miR-129 in primary CD34 + CML cells, which we found downregulated by BCR-ABL in CML cell lines.

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Fig. 17.5 miRNA expression in primary CML CD34 + cells as compared to normal CD34 + cells. Comparative analysis of miRNA expression from chronic phase CML CD34 + cells (dark-grey bars) and from blast crisis CML CD34 + cells (light-grey bars) as compared to normal CD34 + cells was determined by miR-qRT-PCR. miR-16 served as an endogenous control

17.3.3

mir-17-19b Function in K562 Cells

Since miRNA expression analysis revealed a specific up-regulation of miR-17-92 expression in CML cells depending on BCR-ABL tyrosine kinase activity, we performed functional analyses in K562 cells. miR-17-19b, a variant of the miR-17-92 polycistron selected for efficient transgenic miRNA expression which lacks the 3′-located miR-92 [12], was over-expressed in K562 cells by lentiviral gene-transfer (S-17/19b-IEW) (Fig. 17.6A). Three individual clones were isolated by limiting dilution with clones #1 and #3 showing higher expression as compared to #2 as determined by miR-qRT-PCR (Fig. 17.6B). As shown in Fig. 17.6C, K562 cells over-expressing the miR-17-19b exhibited enhanced cell proliferation as compared to K562 cells transduced with empty vector (SEW). This effect was more pronounced in clones #1 and #3 as compared to clone #2. Finally, we also studied the impact of miR-17-19b over-expression on the cytotoxicity of imatinib in K562 cells. As shown in Fig. 17.6D, PI staining demonstrated increased sensitivity to imatinib induced cell death in K562 cells over-expressing miR-17-19b as compared to controls. Again, clones #1 and #3 were more sensitive to imatinib treatment than clone #2.

17.3.4

Function of Endogenous miR-17-5p in K562 Cells

To analyze miRNA function in vivo, we used the luciferase reporter assay schematically represented in Fig. 17.7A. K562 cells were transfected with a construct

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Fig. 17.6 Lentiviral expression of miR-17-19b in K562 cells. (A) Schematic representation of miR-17-19b, a variant miR-17-92 cluster, inserted in the bicistronic lentiviral vector S-17-19bIEW. The miR-17-19b cluster is transcribed as a polycistronic transcript and expressed along with EGFP (reporter gene) from the viral SFFV-LTR promoter. (B) miR-17-19b expression levels in three independent lentivirally transduced K562 clones (#1–3) in comparison to K562 cells transduced with empty vector as determined by miR-qRT-PCR. (C) Cell proliferation of three miR-1719b lentivirally transduced K562 cell clones (#1–3) in comparison to K562 cells transduced with empty vector. K562 cells were lentivirally transduced, plated at 104 cells per well 2 days after transduction and the number of viable cells was counted using trypan blue exclusion assay. (D) Imatinib induced cell death in three miR-17-19b lentivirally transduced K562 cell clones (#1–3) in comparison to K562 cells transduced with empty vector. Ratio of PI positive cells in the presence of increasing concentrations of imatinib are shown

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Fig. 17.7 Endogenous miRNA function in K562 cells. (A) K562 cells expressing reporter constructs containing two perfectly complementary binding sites for miR-17-5p in the 3′-untranslated region of the firefly luciferase gene (called “miR-17-5p sensor” and “miR-20a sensor”). As shown in the cartoon, endogenous miRNAs bind to the reporter mRNA and suppress luciferase expression and activity (left site), whereas electroporation of specific antagomiR miR-17.5p relieves miRNA-mediated luciferase gene repression (right site). (B) Inhibition of miR-17-5p function by antagomiR miR-17.5p. K562 cells stably expressing miR-17-5p luciferase constructs were electroporated alone (mock), with a scrambled antagomiR or antagomiR-17.5p as shown. The ratio of normalized sensor to control luciferase activity is shown

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containing two perfectly complementary binding sites for miR-17-5p in the 3′-untranslated region of the firefly luciferase gene (called “miR-17-5p sensor”). A plasmid containing the reverse complement sequence of the miR-17-5p binding site served as control. In this assay, endogenous miRNAs are recruited to the corresponding binding sites in the 3′-untranslated region of the reporter mRNA and suppress luciferase expression and activity. In contrast, the inhibition of luciferase activity can be relieved by the presence of miRNA-complementary antisenseoligonucleotides (antagomiR) which are able to specifically interfere with miRNA function (Fig. 17.7A). As shown in Fig. 17.7B, co-transfection of the antagomiR-17-5p, but not scrambled oligonucleotides, increases normalized luciferase activity of about tenfold.

17.3.5

Generation of Stable Gain- and Loss-of-Function Phenotypes for Individual miRNAs

To investigate the function of individual miRNAs, particularly of those encoded on polycistrons like miR-17-92, the generation of stable gain- and loss-of-function phenotypes for individual miRNAs is of fundamental importance. To achieve stable loss-of-function phenotypes we recently generated antagomir-expressing lentiviral vectors as represented in Fig. 17.8A [26]. Antagomirencoding oligonucleotides are cloned downstream of an H1-promoter located in the U3 region of the 3′ LTR of lentiviral transgenic plasmids. These encode the

Fig. 17.8 (A) Cartoon of the lentiviral transgene-plasmid harbouring an antagomir expression cassette with a human H1-RNA promoter inserted into the U3 region of the ∆3’LTR. This location results in duplication during reverse transcription indicated as “double-copy” (dc) vector. (B) Cartoon of the lentiviral transgene-plasmid harbouring a miRNA-expression cassette. Specific miRNA-sequences are embedded within sequences derived from miR-30 as described. S:SFFVLTR, I: IRES, E:EGFP, W:WPRE

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EGFP reporter gene under control of the SFFV-LTR (spleen focus forming virus LTR) promoter to allow the identification and isolation of the transduced cells. Upon lentiviral transduction stable loss-of function phenotypes for individual miRNAs can be generated [26]. In contrast, gain-of-function can be achieved by lentivirally over-expression of individual miRNAs embedded into a miR-30 backbone as previously described [27]. We cloned self-complementary chemically synthesized oligonucleotides harboring a determined miRNA sequence into the

Fig. 17.9 (A) Cell proliferation of K562 cells after lentiviral transduction with anti-miR-18a, anti-miR-19b, and anti-miR-20a antagomirs as compared to anti-ctrl transduced cells. K562 cells were plated at 104 cells per well after transduction, and the number of trypan blue negative cells was counted. Mean and SD of two independent experiments are shown. The highest cell number on day 14 was set 100%. (B) Cell proliferation of K562 cells after lentiviral transduction with miR-30 control (control), the miR-17-19b cluster (miR17/19b), miR-18a (miR-30-18a), or miR-20a (miR30-20a), and the number of trypan-blue negative cells is indicated as described for Fig. 17.9A

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bicistronic plasmid SIEW to generate S-miR30-miRNA-IEW (Fig. 17.8B). In this system PolII-mediated miRNA-transcription is driven by the SFFV-LTR promoter. The IRES (internal ribosome entry site) element allows the concomitant expression of the EGFP reporter gene for the isolation of the transduced cells (Fig. 17.8B). To investigate the function of individual miRNAs encoded within the miR-17-92 polycistron in K562 cells, we generated stable gain- or loss-of function phenotypes by lentivirally-mediated expression of specific miRNAs and their corresponding antagomirs, respectively. K562 cells were initially transduced with lentiviruses encoding specific antagomirs against miR-18a, miR-19b, miR-20a or a control antagomir. As shown in Fig. 17.9A, lentivirally-mediated expression of anti-miR18a, but not anti-miR-19b, anti-miR-20a, or control antagomirs inhibit proliferation of K562 cells. Correspondingly, a slight positive impact on K562 cell proliferation has been observed for over-expression of miR-18a (Fig. 17.9B). In contrast, a strong inhibition of cell proliferation is induced by over-expression of miR-20a in K562 cells (Fig. 17.9B).

17.4

Discussion

Our data demonstrate BCR-ABL-mediated expression of miR-17-92 miRNAs in myeloid cell lines. Inhibition of both BCR-ABL tyrosine kinase activity and protein expression reduces miRNA-17-92 expression as determined by miCHIP and miRqRT-PCR in K562 cells. As described elsewhere, miR-17-92 expression is also regulated by c-Myc in K562 cells [31]. Finally, expression of the immature pri-miR-17-92 is also regulated by BCR-ABL [31] suggesting transcriptional activation of the miR-17-92 promoter downstream of BCR-ABL. However, since miRNA biogenesis is a highly regulated multistep process [1, 2, 15, 29], steady state miRNA levels can additionally be regulated at different levels, such as Droshadependent pre-miRNA processing, nuclear export, Dicer-dependent processing into mature miRNAs, incorporation into RISC, and miRNA turn-over. Expression of the miR-17-92 cluster is also enhanced in CML CD34 + cells from patients in chronic phase (CP) but not in blast crisis (BC) as compared to normal CD34 + cells (Fig. 17.5). In addition, miR-106a was found over-expressed in CP but not in BC CD34 + cells, whereas miR-212 was up-regulated in both CP and BC CML CD34 + cells as compared to normal controls. The reason for the differential miRNA expression in chronic phase CML and blast crisis is currently not known but the transition from the myeloproliferative chronic stage to blast crisis may be equivalent to the general reduction of miRNA expression observed in human malignancies [19]. In K562 cells, endogenous miR-17-92 miRNAs, namely miR-17-5p are functional as demonstrated by luciferase reporter experiments and by an increase in cell proliferation upon retroviral expression of miR-17-19b, a variant of miR-17-

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92 (Figs. 17.6A–C, 17.7). Interestingly, not only BCR-ABL driven proliferation but also cell death upon inhibition of BCR-ABL kinase activity by imatinib is enhanced upon over-expression of miR-17-19b (Fig. 17.6D). In the luciferase reporter experiments, repression of its activity depends on miRNA recognition sites in the luciferase 3′UTR to which endogenous miRNAs bind specifically [31]. Using specific antagomirs, we demonstrate relieve of miRNA-specific repression of luciferase activity which can be further enhanced by anti-c-myc-RNAi [31]. According to the expression data discussed above, the data on miRNA function place the miR-17-92 cluster down-stream of c-Myc in K562 cells. Although expression of E2F1, PTEN, and TGFβ receptor have recently been shown to be regulated by miR-17-92 encoded miRNAs [16, 20, 32] the number and identity of additional validated targets are currently not known. To assign specific functions to individual miRNAs encoded on polycistronic transcripts, tools to induce specific gain- and loss of function phenotypes for individual miRNAs are required. Using the lenitiviral transgene plasmids described in Fig. 17.8 we hold the tools in hand to over-express either specific miRNAs or miRNA-specific antagomirs for such analyses. Our data indicate a positive role of miR-18a (and correspondingly a negative impact of anti-18a antagomirs) on proliferation of K562 cells whereas miR-20a seems to inhibit proliferation. In summary, this data add miRNAs to the signaling network affected by the BCR-ABL onco-protein in chronic phase CML cells. Further studies are required to determine the miRNA targets and their functional role in the pathophysiology of CML. This kind of knowledge is required to determine any potential therapeutic impact of modulation of miRNA expression and function in CML. The tools to address these questions in cell culture models are now available using lentiviral transfer of miRNA or antagomir expression cassettes.

References 1. Ambros V. The functions of animal microRNAs. Nature. 2004; 431:350–355. 2. Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004; 116:281–297. 3. Calin GA, Dumitru CD, Shimizu M, Bichi R, Zupo S, Noch E, Aldler H, Rattan S, Keating M, Rai K, Rassenti L, Kipps T, Negrini M, Bullrich F, Croce CM. Frequent deletions and down-regulation of micro-RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc Natl Acad Sci USA. 2002 Nov 26; 99(24):15524–15529. 4. Calin GA, Liu CG, Sevignani C, et al. MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias. Proc Natl Acad Sci USA. 2004; 101:11755–11760. 5. Chen CZ, Li L, Lodish HF, Bartel DP. MicroRNAs modulate hematopoietic lineage differentiation. Science. 2004 Jan 2; 303(5654):83–86. 6. Cimmino A, Calin GA, Fabbri M, Iorio MV, Ferracin M, Shimizu M, Wojcik SE, Aqeilan RI, Zupo S, Dono M, Rassenti L, Alder H, Volinia S, Liu CG, Kipps TJ, Negrini M, Croce CM. miR-15 and miR-16 induce apoptosis by targeting BCL2. Proc Natl Acad Sci USA. 2005 Sept 27; 102(39):13944–13949.

320

M. Scherr et al.

7. Cui JW, Li YJ, Sarkar A, Brown J, Tan YH, Premyslova M, Michaud C, Iscove N, Wang GJ, Ben-David Y. Retroviral insertional activation of the Fli-3 locus in erythroleukemias encoding a cluster of microRNAs that convert Epo-induced differentiation to proliferation. Blood. 2007 Oct 1; 110(7):2631–2640. 8. Eis PS, Tam W, Sun L, Chadburn A, Li Z, Gomez MF, Lund E, Dahlberg JE. Accumulation of miR-155 and BIC RNA in human B cell lymphomas. Proc Natl Acad Sci USA. 2005 Mar 8; 102(10):3627–3632. 9. Farh KK, Grimson A, Jan C, Lewis BP, Johnston WK, Lim LP, Burge CB, Bartel DP. The widespread impact of mammalian MicroRNAs on mRNA repression and evolution. Science. 2005 Dec 16; 310(5755):1817–1821. 10. Gregory RI, Yan KP, Amuthan G, Chendrimada T, Doratotaj B, Cooch N, Shiekhattar R. The Microprocessor complex mediates the genesis of microRNAs. Nature. 2004 Nov 11; 432(7014):235–240. 11. Hayashita Y, Osada H, Tatematsu Y, et al. A polycistronic microRNA cluster, miR-17-92, is overexpressed in human lung cancers and enhances cell proliferation. Cancer Res. 2005; 65:9628–9632. 12. He L, Thomson JM, Hemann MT, et al. A microRNA polycistron as a potential human oncogene. Nature. 2005; 35:828–833. 13. Johnson SM, Grisshans H, Shingara J, et al. RAS is regulated by the let-7 microRNA family. Cell. 2005; 120:635–647. 14. Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993 Dec 3; 75(5):843–854. 15. Lee Y, Ahn C, Han J, et al. The nuclear RNase III Drosha initiates microRNA processing. Nature. 2003; 425:415–419. 16. Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burke CB. Prediction of mammalian micro RNA targets. Cell. 2003; 115:787–798. 17. Lim LP, Lau NC, Garrett-Engele P, Grimson A, Schelter JM, Castle J, Bartel DP, Linsley PS, Johnson JM. Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature. 2005 Feb 17; 433(7027):769–773. 18. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T) ) method. Methods. 2001; 25:402–408. 19. Lu J, Getz G, Miska EA, et al. MicroRNA expression profiles classify human cancers. Nature. 2005; 435:834–838. 20. O’Donnell KA, Wentzel EA, Zeller KI, et al. c-Myc-regulated microRNAs modulate E2F1 expression. Nature. 2005; 35:839–843. 21. Ota A, Tagawa H, Karnan S, et al. Identification and characterization of a novel gene, C13orf25, as a target for 13q31-q32 amplification in malignant lymphoma. Cancer Res. 2004; 64:3087–3095. 22. Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, Bettinger JC, Rougvie AE, Horvitz HR, Ruvkun G. The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature. 2000 Feb 24; 403(6772):901–906. 23. Scherr M, Battmer K, Blomer U, et al. Lentiviral gene transfer into peripheral blood-derived CD34 + NOD/SCID-repopulating cells. Blood. 2002; 99:709–712. 24. Scherr M, Battmer K, Ganser A, et al. Modulation of gene expression by lentiviral-mediated delivery of small interfering RNA. Cell Cycle. 2003; 2:251–257. 25. Scherr M, Battmer K, Schultheis B, et al. Stable RNA interference (RNAi) as an option for anti-bcr-abl therapy. Gene Ther. 2005; 12:12–21. 26. Scherr M, Venturini L, Battmer K, Schaller-Schoenitz M, Schaefer D, Dallmann I, Ganser A, Eder M. Lentivirus-mediated antagomir expression for specific inhibition of miRNA-function. Nucleic Acids Res. 2007; 35:e149. 27. Stegmeier F, Hu G, Rickles RJ, Hannon GJ, Elledge SJ. A lentiviral microRNA-based system for single-copy polymerase II-regulated RNA interference in mammalian cells. Proc Natl Acad Sci USA. 2005; 102:13212–13217.

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28. Tanzer A, Stadler PF. Molecular evolution of a microRNA cluster. J Mol Biol. 2004; 339:327–335. 29. Thompson BJ, Cohen SM. The Hippo pathway regulates the bantam microRNA to control cell proliferation and apoptosis in Drosophila. Cell. 2006 Aug 25; 126(4):767–774. 30. Thomson JM, Newman M, Parker JS, Morin-Kensicki EM, Wright T, Hammond SM. Extensive post-transcriptional regulation of microRNAs and its implications for cancer. Genes Dev. 2006; 20(16):2202–2207. 31. Venturini L, Battmer K, Castoldi M, Schultheis B, Hochhaus A, Muckenthaler MU, Ganser A, Eder M, Scherr M. Expression of the miR-17-92 polycistron in chronic myeloid leukemia (CML) CD34 + cells. Blood. 2007; 109:4399–4405. 32. Volinia S, Calin GA, Liu CG. A micro RNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci USA. 2006; 103:2257–2261.

Chapter 18

MicroRNAs in Vascular Neointimal Lesion Formation Chunxiang Zhang*

Abstract MicroRNAs (miRNAs) are a recently discovered class of endogenous, small, noncoding RNAs that regulate gene expression by either translational inhibition and/or mRNA degradation. However, the miRNA expression profile in vessels and their potential roles in vascular diseases are currently unknown. Therefore, we determined miRNA expression in rat carotid arteries using microarray analysis. Indeed, compared with other tissues, tissue-specific expression is one important characteristic of miRNA expression in the vascular wall. Neointimal formation is the common pathological lesion in atherosclerosis, restenosis, and transplant vascular disease. To determine the potential roles of miRNAs in vascular diseases, we selected a neointimal formation model in rat carotid artery induced via balloon angioplasty. Compared with non-injured control vessel, miRNAs are aberrantly expressed in the vascular walls with neointimal formation. Interestingly, modulating an aberrantly overexpressed miRNA, miR-21, via antisense-mediated depletion (knock-down) had a significant negative effect on neointimal lesion formation. Vascular smooth muscle cell (VSMC) is the major cellular component within the neointimal lesions. We found that miR-21 expression in VSMCs isolated from balloon-injured vessels was significantly higher than that from normal vessels. Depletion of miR-21 resulted in decreased cell proliferation and increased cell apoptosis in a dose-dependent manner. MiR-21-mediated cellular effects were further confirmed in vivo in balloon-injured rat carotid arteries. Western blot analysis demonstrated that PTEN and Bcl-2 were involved in miR-21-mediated cellular effects. The results suggest that miRNAs may be novel regulatory RNAs for neointimal lesion formation. Bioinformatics, proteomics, transgene and gene knockout approaches will be warranted to further identify the roles of these miRNAs in vascular neointimal formation and their molecular mechanisms. MiRNAs may be a new therapeutic target for proliferative vascular diseases such as atherosclerosis, postangioplasty restenosis, transplantation arteriopathy, and stroke.

RNA and Cardiovascular Research Laboratory, Department of Anesthesiology, New Jersey Medical School, University of Medicine & Dentistry of New Jersey, Newark, NJ 07101, USA *Correspondence author: E-mail: [email protected]

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Keywords MicroRNAs, vascular smooth muscle cells, proliferation, apoptosis, neointimal formation, vascular diseases

18.1

Introduction

Since the discovery of the DNA double-helix structure by Watson and Crick in 1953, the standard pathway of information flow in a cell from DNA to RNA to protein has been the dominant theme in molecular biology. In this standard information pathway, RNA was initially considered a mainly passive intermediary and has long stood in the shadow of DNA. It was thought that enzymes and other biological catalysts were exclusively proteins. Then, the scientist realized that this theory was not correct. Indeed, in the 1980s, Cech discovered the enzymatic activity of RNA, which represented the first RNA revolution [1]. In the past few years, developmental biologists working on the primitive earthworm Caenorhabditis elegans have discovered a novel protein expression regulatory mechanism via small noncoding RNAs named small interfering RNAs (siRNAs) and microRNAs (miRNAs). The discovery of these small regulatory, noncoding RNAs may represent the second RNA revolution [2]. MicroRNAs (miRNAs) are endogenous, noncoding, single-stranded RNAs of ∼22 nucleotides and constitute a novel class of gene regulators [3–6]. Although the first miRNA, lin-4, was discovered in 1993 [7, 8], their presence in vertebrates was confirmed only in 2001 [9]. MiRNAs are initially transcribed by RNA polymerase II (Pol II) in the nucleus to form large pri-miRNA transcripts [10]. The primiRNAs are processed by the RNase III enzymes, Drosha and Dicer, to generate 18- to 24-nucleotide mature miRNAs. The mature miRNAs negatively regulate gene expression in one of two ways that depend on the degree of complementarity between the miRNA and its target. MiRNAs that bind to 3′UTR of mRNA with imperfect complementarity block protein translation. In contrast, miRNAs that bind to mRNA with perfect complementarity induce targeted mRNA cleavage. Currently, more than 400 miRNAs have been cloned and sequenced in human, and the estimated number of miRNA genes is as high as 1,000 in the human genome [11, 12]. As a group, miRNAs are estimated to regulate at least 30% genes of the human genome [13]. To date, the biological roles of only a small fraction of identified miRNAs have been elucidated. In fact, we are just beginning to understand how this novel class of gene regulators is involved in biological functions. Although only a small number of the hundreds of identified miRNAs have been characterized, a growing body of exciting evidence suggests that miRNAs are important regulators for cell growth, differentiation, and apoptosis [14–16]. Therefore, miRNAs may be important for normal development and physiology. Consequently, dysregulation of miRNA function may lead to human diseases [17]. In this respect, the most exciting research area is the role of miRNAs in cancer, given that cell dedifferentiation, growth, and apoptosis are important cellular events in the development of cancer.

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Indeed, both basic and clinical studies have demonstrated that miRNAs are aberrantly expressed in diverse cancers [18–21]. miRNAs are currently thought to function as both tumor suppressors and oncogenes [22]. Cardiovascular disease has long been the leading cause of death in developed countries, and it is rapidly becoming the number one killer in developing countries [23]. Although miRNAs are highly expressed in heart tissue [24], there is no study that reports on the miRNA expression signature in vessel system. Emerging genetic evidence suggests an essential role of miRNAs in normal cardiogenesis and abnormal stress responses such as cardiac hypertrophy, heart failure and cardiac arrhythmogenesis [25–33]. Neointimal formation is a common pathological lesion in diverse cardiovascular diseases such as atherosclerosis, coronary heart diseases, postangioplasty restenosis, and transplantation arteriopathy. However, the roles of these miRNAs in vascular diseases are currently unknown. As neointimal lesion formation in proliferative vascular disease shares similar cellular events and molecular mechanisms with cancers [34], we therefore hypothesized that miRNAs might play important roles in neointimal lesion formation. To test this hypothesis, we applied the well-established rat carotid artery balloon-injury model to induce neointimal lesion formation, in which the cellular mechanisms are well documented [35–37]. The results demonstrated that miRNAs were aberrantly expressed in the vascular walls with neointimal formation. Among which, microRNA 21 (miR-21) was the most upregulated miRNAs in the vascular wall after angioplasty. Therefore, we selected miR-21 as our first experimental target to determine the potential role of miRNAs in vascular neointimal lesion formation. It is well established that miRNAs regulate biological function via modulating their gene expression. Based on the bioinformatics, we hypothesized that miR-21 might participate in vascular neointimal lesion formation via its target genes, tensin homology deleted from chromosome 10 (PTEN), transforming growth factor-beta (TGF-beta) or B-cell leukemia/lymphoma 2 (Bcl-2).

18.2 18.2.1

Materials and Methods Rat Carotid Artery Balloon Injury Model

Carotid artery balloon injury was induced in male Sprague-Dawley rats (250–300 g) as described in our previous studies [35, 36]. Briefly, rats were anesthetized with ketamine (80 mg/kg)/xylazine(5 mg/kg). Under a dissecting microscope, the right common carotid artery was exposed through a midline cervical incision. A 2F Fogarty catheter (Baxter Edwards) was introduced via an arteriotomy in the external carotid artery, and then the catheter was advanced to the proximal edge of the omohyoid muscle. To produce carotid artery injury, we inflated the balloon with saline and withdrew it three times from just under the proximal edge of the omohyoid

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muscle to the carotid bifurcation. After injury, the external carotid artery was permanently ligated with a 6-0 silk suture, and blood flow in the common carotid artery was restored. All protocols were approved by the Institutional Animal Care and Use Committee at the University of Tennessee and were consistent with the Guide for the Care and Use of Laboratory Animals (NIH publication 85-23, revised 1985).

18.2.2

Local Oligo Delivery

To deliver these miRNA inhibitors into injured vascular tissue and to avoid any potential systemic side effects, we applied an established local oligo delivery model via F-127 pluronic gel as previously described [38]. Briefly, 30 µg of these oligonucleotides were preloaded into the 200-µl, 30% F-127 pluronic gel (Sigma) at 4 °C. LipofectAMINE 2000 reagent (Invitrogen) was added at a final concentration of 1%. Immediately after balloon injury of the right common carotid artery, the F-127 pluronic gel loaded with these oligonucleotides was applied locally to the adventitia around injured artery segments. At the beginning of this set of experiments, these oligonucleotides were labeled with a fluorescent dye, 5′ Cal Fluor 610 (Integrated DNA Technologies), to determine the delivery efficacy.

18.2.3

Morphometric Analysis for Neointimal Lesion Formation

Morphometric analysis via computerized image analysis system (Scion Image CMS-800) was performed in sections stained with hematoxylin-eosin (H-E) as described in our previous studies [36, 37]. Six sections (5 µm thick) sectioned at equally spaced intervals of injured carotid arteries were used. The parameters for neointimal lesion formation and vascular remodeling were as follows: neointimal area, medial area, intimal to medial area ratio (I/M), luminal area, and the area defined by external elastic lamina (EEL). The average of the six sections was used as the parameter for one animal.

18.2.4

Cell Culture

Vascular smooth muscle cells (VSMCs) were obtained from the aortic media of male Sprague-Dawley rats (5 weeks old) by using an enzymatic dissociation method as described [37, 39]. To compare the expression levels of miR-21 in differentiated and dedifferentiated VSMCs, the freshly isolated differentiated VSMCs and dedifferentiated VSMCs cultured with 10% fetal bovine serum (FBS) for 3 days were used. The basic culture medium was DMEM.

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18.2.5

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Oligo Transfection, miR-21 Knockdown and miR-21 Overexpression in Cultured VSMCs

Oligo transfection was performed according to an established protocol [40, 41]. Briefly, cells were transfected using Transfection reagent (Qiagen) 24 h after seeding into the well plate. Transfection complexes were prepared according to the manufacturer’s instructions. For miR-21 knockdown, miR-21 inhibitor was added directly to the complexes to a final oligonucleotide concentration of 1, 3, 10, 30, and 100 nmol/l. For miR-21 overexpression, miR-21 (Proligo-Sigma) was added directly to the complexes to a final oligonucleotide concentration of 10 nmol/l. The transfection medium was replaced 4 h posttransfection by the regular culture medium. Two controls were applied. One was vehicle control. Another control was control oligos targeting EGFP.

18.2.6

VSMC Proliferation

VSMC proliferation in vitro was determined by cell counting and bromodeoxyuridine (BrdU) incorporation assay. For cell counting, the cells were detached by trypsinization and resuspended in PBS. The cells were then counted under a microscope. For BrdU incorporation assay, 10 mM BrdU was added to the culture medium for incorporation into the DNA of replicating cells. After 2 h of incubation, cells were fixed, and anti-BrdU antibody (In Situ Cell Proliferation Kit) was added to each well for 45 min. Finally, the proliferative cells were detected under a fluorescence microscope. To detect VSMC proliferation in the vascular wall in vivo, the animals received one injection of the thymidine analog BrdU. The injection was given 12 h (100 mg/kp, ip) before the animals were sacrificed. Proliferating cells were evaluated in vessel sections by using the BrdU labeling technique with a BrdU detection kit (BD PharMingen) [42]. The section was counterstained with hematoxylin. A VSMC proliferation index was calculated using the following formula: [the number of BrdU-labeled nuclei)/(total nuclei stained by hematoxylin) × 100] for each section. The average of the six sections was used as the parameter for one animal.

18.2.7

VSMC Apoptosis

VSMC apoptosis in cultured cells was measured by TUNEL staining and caspase-3 activation measurement. For TUNEL analysis, VSMCs cultured on coverslips in 24-well plates were fixed in 4% paraformaldehyde. TUNEL staining was done using the In Situ Cell Death Detection Kit (Roche) according to the manufacturer’s protocol. The number of TUNEL-positive cells was counted under a fluorescence microscope. A VSMC apoptosis index was calculated using the following formula: [the number of

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TUNEL-positive cells]/(total cells) × 100]. Caspase-3 activation was measured by enzyme-catalyzed release of pNA as described [43]. Detection of apoptotic cells in vivo was performed using the TUNEL method by immunohistochemistry [42]. The In Situ Cell Death Detection Kit (Roche) was used. Apoptotic cells were quantified by counting the percentage of TUNEL-positive cells against total nucleated cells in the tissue section. The average of the six sections was used as the parameter for one animal.

18.2.8

Cell Viability Assay

Cell viability was measured by bioreduction of 3-(4,5-dimethylthiazol-2-yl)-2, 5-diphenyl tetrazolium bromide (MTT) method as described [44]. Cells were washed with PBS and then incubated for 1 h (37 °C; CO2 5%) with MTT (0.5 mg/ml) in PBS containing CaCl2 (11 mM) and glucose (5.5 mM). After lysis of the cells in isopropanol–0.1 N HCl, absorbance was measured at 570 nm.

18.2.9

Gene Microarray Analysis for miRNA Expression

MiRNAs were isolated from rat carotid arteries by using the mirVana miRNA isolation kit (Ambion, Inc.). MiRNA expression profiling was determined by miRNA microarray analysis by using the rat miRNA array probes (LC Science, Chip ID miRat 7.1 version) that included 180 mature rat miRNAs. Every time point had six mice in each group.

18.2.10 MiRNA Levels Were Determined by Quantitative Reverse Transcriptase Polymerase Chain Reaction (qRT-PCR) Briefly, RNAs from VSMCs, carotid arteries and hearts were isolated with mirVana miRNA Isolation Kit (Ambion, Inc.). qRT-PCR was performed on cDNA generated from 200 ng of total RNA by using the protocol of mirVana qRT-PCR miRNA Detection Kit (Ambion, Inc). Amplification and detection of specific products were performed with the ABI PRISM 7700 Sequence Detection System with the cycle profile according to the mirVana qRT-PCR miRNA Detection Kit. As an internal control, U6 primers were used for RNA template normalization. Fluorescent signals were normalized to an internal reference, and the threshold cycle (Ct) was set within the exponential phase of the PCR. The relative gene expression was calculated by comparing cycle times for each target PCR. The target PCR Ct values were normalized by subtracting the U6 Ct value, which was given the ∆Ct value. The relative expression level between treatments was then calculated using the following equation: relative gene expression = 2-(∆Ctsample-∆Ctcontrol) [43].

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Northern Blot Analysis of miRNA

Ten micrograms of total RNA from snap-frozen tissues and VSMCs were loaded onto a precast 15% denaturing polyacrylamide gel (Bio-Rad). The RNA was then electrophoretically transferred to Bright-Star blotting membranes (Ambion, Inc.). Probes were end-labeled with [γ-32P]ATP by T4 polynucleotide kinase. Prehybridization and hybridization were carried out in Ultrahyb Oligo solution (Ambion, Inc.) containing 106 cpm/ml probes overnight at 37 °C. The most stringent wash was with 2× SSC and 1% SDS at 37 °C. For reuse, blots were stripped by boiling and reprobed. U6 was used as a loading control to normalize expression levels.

18.2.12

Western Blot Analysis

VSMCs at 70% confluence transfected with vehicle (PBS), Control oligos, miR-21 inhibitor 2′OMe-miR-21 (30 nM) or mature miR-21 (10 nM) were cultured with 10% DMEM for 24 h, and then cell proteins were isolated for Western blot analysis. PTEN, Akt, phosphorylated Akt, TGF-beta and Bcl-2 levels were determined by Western blot analysis. Briefly, VSMCs were lysed at 4 °C in lysis buffer, and equal amounts of protein were subjected to SDS-PAGE. Standard Western blot analysis was conducted using PTEN, Akt, phosphorylated Akt (p-Akt), TGF-beta and Bcl-2 (1:1,000; Cell Signaling) antibodies. Anti-β-actin antibody (1:5,000 dilution; Sigma) was used as a loading control.

18.2.13

Statistics

All data are presented as mean ± standard error. For relative gene expression, the mean value of vehicle control group is defined as 100%. Two-tailed unpaired Student’s t tests and ANOVA were used for statistical evaluation of the data. Sigma Stat Statistical Analysis Program was used for data analysis. A p value < 0.05 was considered significant.

18.3 18.3.1

Results MiRNA Expression Signature in Normal Rat Carotid Artery

Tissue-specific expression is one important characteristic of miRNA expression [24]. To study the biological functions of miRNA in vascular disease, we determined the miRNA expression profile in rat carotid arteries through miRNA microarray analysis.

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Overall, 140 miRNAs out of the 180 arrayed were found in normal rat carotid arteries. Forty nine highly expressed miRNAs in rat vessels were listed in Table 18.1, while 49 highly expressed miRNAs in rat hearts were listed in Table 18.2. Indeed, the miRNA expression profile in vessels is different from that in heart tissue.

18.3.2

MiRNAs Are Aberrantly Expressed in Rat Carotid Arteries After Angioplasty

Compared with normal, uninjured arteries, microarray analysis demonstrated that aberrant miRNA expression was a remarkable characteristic in vascular walls after angioplasty. Seven days after balloon injury, 113 of the 140 artery miRNAs were differentially expressed with p-value <0.01; 60 miRNAs were upregulated, and 53 miRNAs were downregulated. At 14 days after injury, 110 of the 140 artery miRNAs were differentially expressed (63 up and 47 down), while 102 of the 140 artery miRNAs were differentially expressed (55 up and 47 down) at 28 days after angioplasty. Figure 18.1A shows the time course changes of miRNAs that were highly expressed in rat carotid artery and over one-fold upregulated after angioplasty. Figure 18.1B shows the time course changes of miRNAs that were highly expressed in rat carotid artery and over 50% downregulated after angioplasty. Microarray data should be verified by either qRT-PCR or Northern blot analysis. These miRNAs whose expression was significantly dysregulated based on microarray analysis were therefore selected for expression confirmation by qRT-PCR and/or Northern blot analysis. The Northern blot probe sequences of these miRNAs are shown in Table 18.3. In agreement with the results from microarray analysis, we found that miR-21, 146, 214, and 352 were highly upregulated, whereas miR-125a, Table 18.1 miRNAs highly expressed in normal rat carotid artery let-7a let-7b let-7c let-7d let-7e miR-10a miR-16 miR-21 miR-22 miR-23a miR-26a miR-26b miR-27a miR-27b miR-29a miR-30d miR-31 miR-30a-5p miR-98 miR-99a miR-103 miR-107 miR-125a miR-125b miR-126 miR-145 miR-146 miR-150 miR-152 miR-181a miR-195 miR-199a miR-214 miR-221 miR-320

Table 18.2 miRNAs highly expressed in normal rat heart miR-1 miR-26a miR-126 let-7a let-7f miR-23b miR-23a miR-30c miR-29a let-7d let-7i miR-30b miR-133a miR-26b miR-125b miR-24 miR-16 miR-21 miR-27a miR-195 miR-145 miR-125a let-7e miR-30d miR-146 miR-424 miR-29c miR-191 miR-22 miR-422b miR-152 miR-15b miR-98 miR-181a miR-99a

let-7f miR-23b miR-30b miR-99b miR-133a miR-181b miR-352

let-7c miR-499 miR-27b miR-150 miR-352 miR-185 miR-214

let-7i miR-24 miR-30c miR-100 miR-143 miR-191 miR-365

Let-7b miR-133b miR-30a-5p miR-143 miR-30e miR-451 miR-450

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700 uninjured control 7 days after injury 14 days after injury 28 days after injury

MiRNA expression

600 500

miR-125b

400 300

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miR-21

0 miR-21 miR-146 miR-352 miR-125a miR-125b miR-133a miR-143 miR-145

U6

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uninjured 7d injury 14d injury 28d injury

Fig. 18.1 Aberrant expression of miRNAs in rat carotid arteries after angioplasty. (A) Time course changes of miRNAs that are highly expressed in rat carotid artery and over one-fold upregulated after angioplasty as determined by microarray analysis. (B) Time course changes of miRNAs that are highly expressed in rat carotid artery and over 50% downregulated after angioplasty as determined by microarray analysis. (C) Confirmation of the aberrantly expressed miRNAs after angioplasty as determined by quantitative real-time polymerase chain reaction (qRT-PCR). (D) Confirmation of the aberrantly expressed miRNAs after angioplasty as determined by Northern blot. Note: Mean miRNA levels in uninjured arteries were defined as 100%.* p < 0.05 compared with those in uninjured arteries

125b, 133a, 143, 145, 347, and 365 were significantly downregulated during different time courses. Remarkably, miR-21 had more than a five-fold increase compared with the control. (Fig. 18.1C, D). Therefore, miR-21 was further studied using our in vitro and in vivo models to determine the potential biological function of these aberrantly expressed miRNAs.

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18.3.3

5′ TCAACATCAGTCTGATAAGCTA 3′ 5′CACAGGTTAAAGGGTCTCAGGGA3′ 5′CACAAGTTAGGGTCTCAGGGA3′ 5′AAGGGATTCCTGGGAAAACTGGAC3′ 5′ CTGCCTGTCTGTGCCTGCTGT3′ 5′TGGGCGACCCAGAGGGACA3′ 5′TACTATGCAACCTACTACTCT3′ 5′ATAAGGATTTTTAGGGGCATTA3′ 5′GCAGGGGCCATGCTAATCTTCTCTGTATCG3′

The Effect of miR-21 on Neointimal Lesion Formation in Rat Carotid Artery After Angioplasty

To determine the potential roles of aberrantly expressed miRNAs in neointimal lesion formation after angioplasty, we applied antisense oligonucleotide-mediated miRNA depletion to knock down an overexpressed miRNA, miR-21. The antisense oligonucleotide for miR-21 was modified at each nucleotide by an O-methyl moiety at the 2′-ribose position. The modified antisense oligonucleotide (2′OMe-miR-21) is also called miRNA inhibitor. 2′OMe-miR-21 is synthesized by Integrated DNA Technologies and has the following sequence and structure: 5′mUmCmAmAmCmAmUmCmAmGmUmCmUmGmAmUmAmAmGmCmUmA-3′ [26, 45, 46]. We used two controls for this study. The first control was a vehicle control (PBS), and the second control was the modified antisense oligonucleotide for enhanced green fluorescence protein (EGFP) mRNA (2′OMe-EGFP). EGFP gene is a mutant form of green fluorescence protein (GFP) gene [47]. Neither EGFP and GFP genes are expressed in rats and transfection of exogenous EGFP, and GFP has no effect on VSMC growth and vascular neointimal formation [48, 49]. Thus, 2′OMe-EGFP targeting EGFP mRNA is used as a negative oligonucleotide control [46]. 2′OMeEGFP is also synthesized by Integrated DNA Technologies and has the following sequence and structure: 5′-mAmAmGmGmCmAmAmGmCmUmGmAmCmCmCmUmGmAmAmGmU-3′ [45]. As shown in Fig. 18.2B, the fluorescent-marked 2′OMe-miR-21 and 2′OMeEGFP were successfully delivered into the vascular wall after injury by using the

Fig. 18.2 The effect of downregulation of overexpressed miR-21 on neointimal lesion formation in rat carotid artery after angioplasty. (A) Schematic diagram for local delivery of oligonucleotides into the injured carotid artery via pluronic gel. (B) Chronic delivery of miR-21 antisense oligonucleotide (2′OMe-miR-21) and control oligonucleotide (2′OMe-EGFP) labeled with a fluorescent dye, 5′ Cal Fluor 610, into the injured vascular walls. (C) Confirmation of the knockdown effect of locally delivered miR-21 inhibitor 2′OMe-miR-21 on miR-21 level in rat carotid arteries at 3 and 7 days after angioplasty as determined by qRT-PCR. (D) Representative H-E stained photomicrographs of rat carotid arteries from different treatment groups at 14 days after angioplasty. (E) Effect of 2′OMe-miR-21 on the area defined by external elastic lamina (EEL), luminal area (Lumen), intimal area (Intima), and medial area (Media) of rat carotid arteries at 14 days after angioplasty. (F)

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local oligo delivery system (Fig. 18.2A). Consistent with the fluorescent activity analysis, 2′OMe-miR-21 decreased miR-21 expression significantly in the vascular walls at 3 and 7 days after balloon injury (Fig. 18.2C). In contrast, 2′OMe-EGFP had no effect on miR-21 expression (Fig. 18.2C). To determine the effect of the miRNA inhibitor 2′OMe-miR-21 on neointimal lesion formation, the injured carotid arteries were isolated 14 days after treatment for morphometric analysis. We found that downregulation of the overexpressed miR-21 inhibited neointima formation in rat carotid artery after angioplasty (Fig. 18.2D–F). In contrast, 2′OMe-EGFP had no effect on neointima formation. Representative hematoxylin-eosin (H-E) stained photomicrographs of rat carotid arteries from different groups are shown in Fig. 18.2D. It should be noted that 2′OMe-miR-21-induced miRNA inhibition is miR-21 specific, as no inhibitory effect was found on other miRNAs such as miR-24 and miR-146 (Fig. 18.2G, H).

18.3.4

MiR-21 Expression Is Increased in VSMCs Isolated from Injured Artery

To determine the potential cellular mechanism in miR-21-mediated effect on the neointimal lesion formation, we isolated VSMCs, the major cells within the neointimal lesions from rat carotid arteries 7 days after balloon angioplasty. As shown in Fig. 18.3, compared with the VSMCs isolated from uninjured vessels, the expression of miR-21 in VSMCs from injured arteries is significantly higher.

Fig. 18.3 Upregulation of miR-21 in vascular smooth muscle cells isolated from injured artery. * p < 0.05 compared with that in vascular smooth muscle cells isolated from uninjured vessels

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Inhibition of miR-21 Decreases Proliferation of Cultured VSMCs

VSMC proliferation is the key cellular event for neointimal lesion formation. We therefore determined the effect of miR-21 inhibitor 2′OMe-miR-21 on cell proliferation in cultured VSMCs in the following experiments. Firstly, we applied antisense oligonucleotide-mediated miRNA depletion to knock down the miR-21 overexpression by using its inhibitor, 2′OMe-miR-21. Oligonucleotide transfection was performed according to an established protocol [36]. As shown in Fig. 18.4A, fluorescentmarked 2′OMe-miR-21 and 2′OMe-EGFP were successfully transfected into the cultured VSMCs. Consistent with the transfection, 2′OMe-miR-21 decreased the miR-21 expression levels (Fig. 18.4B) in a dose-dependent manner, with a significant decrease observed at a concentration of 3 nM and the maximum effect at 100 nM. In contrast, the control oligo, 2′OMe-EGFP, had no effect on miR-21 level, even at the highest concentration (100 nM). In addition, 2′OMe-miR-21-induced miRNA inhibition in cultured cells is also miR-21 specific, as no inhibitory effect was found on other miRNAs such as miR-24 and miR-146 (Fig. 18.3C). In subsequent experiments, we determined the effect of 2′OMe-miR-21 on VSMC proliferation by using two different methods: cell counting and BrdU incorporation assay as described [41]. Consistent with the levels of miR-21 in Fig. 18.3C, 2′OMe-miR-21 significantly decreased cell numbers and BrdU incorporation at 48 h after culture with DMEM containing 10% FBS (Fig. 18.4D, E). Representative BrdU-stained photomicrographs (Fig. 18.4F, bottom panel) as well as their corresponding total cell photomicrographs (Fig. 18.4F, top panel) are shown in Fig. 18.4F. The result indicated that miR-21 has a pro-proliferative effect on cultured VSMCs. In contrast, 2′OMe-EGFP (100 nM) had no effect on VSMC proliferation.

18.3.6

Inhibition of miR-21 Increases Apoptosis of Cultured VSMCs

Neointimal growth is the balance between cell apoptosis and cell proliferation. Thus, apoptosis is also an important cellular event in neointimal lesion formation. Recent reports demonstrated that miR-21 had an anti-apoptosis effect on glioblastoma cells, but had no anti-apoptosis effect on HeLa cells [45, 46]. To determine the role of miR-21 in VSMC apoptosis, we applied a VSMC apoptosis model in which apoptosis was measured after 48 h in serum-free culture [43]. The VSMCs were divided into the following groups: vehicle control, antisense oligo control 2′OMe-EGFP, and miR-inhibitor 2′OMe-miR-21. Apoptosis was evaluated by TUNEL assay and caspase-3 activity measurement. We found that 2′OMe-miR-21 increased TUNEL-positive cells (Fig. 18.5A), accompanied by increasing caspase-3 activity (Fig. 18.5B). Representative TUNEL-stained photomicrographs (Fig. 18.5C, bottom panel), as well as their corresponding total cell

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Fig. 18.4 The effect of miR-21 inhibitor 2′OMe-miR-21 on cell proliferation in cultured VSMCs. (A) Transfection of miR-21 inhibitor 2′OMe-miR-21 and control oligonucleotide (2′OMe-EGFP) labeled with a fluorescent dye (red color) into the cultured VSMCs. (B) The effects of miR-21 inhibitor 2′OMe-miR-21 on the expression levels of miR-21, miR-24 and miR-146. (C) The effect of miR-21 inhibitor 2′OMe-miR-21 on VSMC proliferation as determined by cell counting. (D) The effect of miR-21 inhibitor 2′OMe-miR-21 on VSMC proliferation as determined by BrdU incorporation. (E) Representative BrdU-stained photomicrographs (bottom panel), as well as their corresponding total cell photomicrographs (top panel). Note: Two controls were used in the experiment. The first control was a vehicle control (PBS), and the second control was 2′OMe-EGFP(100 nM). *P < 0.05 compared with controls

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photomicrographs (Fig. 18.5C, top panel), are shown in Fig. 18.4C. In contrast, 2′OMe-EGFP (100 nM) had no effect on apoptosis. The results revealed that miR-21 had an anti-apoptotic effect in cultured VSMCs. To avoid of nonspecific cellular toxicity of miR-21 inhibition, the following two approaches were applied in addition to control oligo 2′OMe-EGFP application. First, we determined the cellular viability using MTT method after transfection of

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Fig. 18.5 The effect of miR-21 inhibitor 2′OMe-miR-21 on cell apoptosis in cultured VSMCs. (A) The effect of miR-21 inhibitor 2′OMe-miR-21 on VSMC apoptosis with serum deprivation for 48 h as determined by TUNEL assay. (B) The effect of miR-21 inhibitor 2′OMe-miR-21 on VSMC apoptosis with serum deprivation for 48 h as determined by caspase-3 activity measurement. (C) Representative TUNEL-stained photomicrographs (bottom panel), as well as their corresponding total cell photomicrographs (top panel). (D) The effect of miR-21 inhibitor 2′OMe-miR-21 on cell viability as measured by bioreduction of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) method. (E) The effect of miR-21 inhibitor 2′OMe-miR-21 on VSMC apoptosis without serum deprivation for 48 h as determined by TUNEL assay. Note: Two controls were used in the experiment. The first control was a vehicle control (PBS), and the second control was 2′OMe-EGFP(100 nM). *P < 0.05 compared with controls

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antisense oligonucleotides but prior to the onset of apoptosis induction. No nonspecific toxicity was found at our experimental concentration range (Fig. 18.5D). Second, we determined the effect of miR-21 inhibition on cell apoptosis without serum deprivation. As shown in Fig. 18.4E, under 10% serum culture condition, few cells underwent apoptosis in the vehicle and 2′OMe-EGFP-treated groups. 2′OME-miR-21 increased the apoptosis rate in a dose-dependent manner. The maximal effect occurred at 100 nM with an apoptosis rate at about 12%. The results indicate that the apoptosis effect is not a nonspecific toxicity. However, miR-21 knockdown and serum deprivation may have a synergetic effect on apoptosis, although the mechanism is currently not clear (Fig. 18.5A–C).

18.3.7

Inhibition of miR-21 Modulates Cell Proliferation and Apoptosis In Vivo in Injured Rat Carotid Artery

To further determine the cellular effects of miR-21 in vivo, we used immunohistochemistry to determine the proliferation and apoptosis in injured vascular walls as described in our previous publications [42, 50, 51]. Injured rat carotid arteries treated with vehicle, 2′OMe-EGFP, or 2′OMe-miR-21 were isolated at 7 days after balloon injury. We found that miR-21 inhibitor 2′OMe-miR-21 decreased cell proliferation (Fig. 18.6) and increased apoptosis (Fig. 18.7) in injured vascular walls. In contrast, the control oligo 2′OMe-EGFP had no effect on either proliferation or apoptosis (Figs. 18.6, 18.7).

18.3.8

PTEN and Bcl-2 Are Involved in 2′OME-miR-21-Mediated Cellular Effects on VSMCs

To identify the potential molecular targets of miR-21 that may contribute to miR21-mediated cellular effects, bioinformatics programs such as microrna.sanger.ac.uk, genes.mit.edu/cgi-bin/targetscn, and microran.org were used. Based on the known genes that are involved in smooth muscle cell growth and apoptosis and these potential miR-21 target genes from bioinformatics databases, we propose that PTEN, TGFbeta and Bcl-2 might be potential targets for miR-21. As shown in Fig. 18.8, miR-21 inhibition has no effect on TGF-beta expressing, suggesting that TGF-beta is not the gene target for miR-21 in VSMCs. Interestingly, 2′OMe-miR-21 increased PTEN expression (Fig. 18.9) but decreased Bcl-2 expression (Fig. 18.10). To further confirm the effects of miR-21 on PTEN and Bcl-2, miR-21 expression was upregulated via transfection of miR-21 (Proligo-Sigma) using the method as described in a recent report [32]. We found that miR-21 expression had a six-fold increase in miR-21 (10 nM) transfected VSMCs compared with those in vehicle and control oligo-treated VSMCs as determined by qRT-PCR. Contrary to miR-21 inhibition, miR-21 overexpression decreased PTEN expressed (Fig. 18.9) but increased Bcl-2 expression (Fig. 18.10). Akt is a downstream signal molecule of PTEN. To further confirm

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Fig. 18.6 The effect of miR-21 inhibitor 2′OMe-miR-21 on VSMC proliferation in vivo in rat carotid arteries at 7 days after angioplasty. (A) Representative BrdU immunostaining sections of rat carotid arteries from different groups. (B) Quantitative analysis of BrdU-positive cells in rat carotid arteries at 7 days after angioplasty. Note: The dose of 2′OMe-miR-21 used was 30 µg per carotid artery. Two controls were used in the experiment. The first control was a vehicle control (PBS), and the second control was 2′OMe-EGFP (30 µg per carotid artery). BrdU-positive cells are displayed with DAB as brown color. *P < 0.05 compared with vehicle control

the involvement of PTEN in miR-21-mediated effects, Akt activity was determined. Consistent with the expression changes of PTEN (Fig. 18.8), miR-21 inhibition decreased, but miR-21 overexpression increased Akt activity (Fig. 18.8).

18.4

Discussion

Although miRNA expression profile in the heart has recently been described [24], the expression signature for miRNAs in vessel is currently uncovered. In the current study, miRNA expression was identified using microarray analysis for the first

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Fig. 18.7 The effect of miR-21 inhibitor 2′OMe-miR-21 on VSMC apoptosis in vivo in rat carotid arteries at 7 days after angioplasty. (A) Representative TUNEL staining sections of rat carotid arteries from different groups. (B) Quantitative analysis of TUNEL-positive cells in rat carotid arteries at 7 days after angioplasty. Note: The dose of 2′OMe-miR-21 used was 30 µg per carotid artery. Two controls were used in the experiment. The first control was a vehicle control (PBS), and the second control was 2′OMe-EGFP (30 µg per carotid artery). TUNEL-positive cells are displayed as red color. *P < 0.05 compared with vehicle control

time. Indeed, miRNA expression profile in artery is different from that in heart (Tables 18.1 and 18.2). For example, the most abundant miRNAs in heart are miR-1, let-7, miR-126, miR-30c, miR-133, miR-26a, miR-23 and miR-30c. However, in artery the most abundant miRNAs are miR-145, let-7, miR-125b, miR-125a, miR-23, and miR-143. MiR-1 is not an abundant miRNA in artery. The different expression signature was also well documented in other tissue system [24]. The different expression profiles in different tissues indicate that the physiological functions of miRNAs in different tissues could be different. Identifying these tissue-specific miRNAs and their physiological functions could be important for future studies. As a novel class of gene regulators, miRNAs play important roles not only in normal development and physiological conditions, but also in disease status. In this respect, both basic and clinical studies have demonstrated that miRNAs are aberrantly expressed in diverse cancers [18–22]. As proliferative vascular diseases share similar

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Fig. 18.8 The effect of miR-21 inhibitor 2′OMe-miR-21 on expression level of transforming growth factor-beta (TGF-beta) in cultured VSMCs. Up panel: Representative immunoblots of TGF-beta from cells treated with vehicle (PBS), 2′OMe-EGFP (30 nM), and 2′OMe-miR-21 (30 nM). Down panel: quantitative analysis of TGF-beta expression

cellular events and molecular mechanisms with cancer [34], we hypothesized that miRNAs might also play important roles in these vascular diseases. It is well known that neointimal lesion formation is the pathological basis of these proliferative vascular diseases; we therefore applied a well-established neointimal lesion formation model in balloon-injured rat carotid artery. We demonstrated for the first time that multiple miRNAs were aberrantly expressed in the vascular wall after angioplasty. The multiple miRNA dysregulation and the time course changes of these aberrantly expressed miRNAs match the complex process of neointimal lesion formation, in which multiple genes have been dysregulated. Our results indicate that multiple miRNAs are involved in neointimal lesion formation, although their roles may be diverse. Identifying these aberrantly expressed miRNAs and their physiological functions will be important direction in this novel research area. As the first experimental target, miR-21 was selected for the following reasons: First, miR-21 is an abundant miRNA in artery. Second, miR-21 was one of the most upregulated miRNAs in the vascular wall after balloon injury. Third, miR-21 was

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Fig. 18.9 The effect of miR-21 inhibitor 2′OMe-miR-21 on expression levels of PTEN, Akt, p-Akt and Bcl-2 in cultured VSMCs. (A) Up panel: Representative immunoblots of phosphatase and tensin homology deleted from chromosome 10 (PTEN), phosphorylated Akt (p-Akt) and total Akt from cells treated with vehicle (PBS), 2′OMe-EGFP (30 nM), and 2′OMe-miR-21 (30 nM). Down panel: Quantitative analysis of PTEN, p-Akt and Akt expression. (B). Up panel: Representative immunoblots of PTEN, p-Akt and total Akt from cells treated with vehicle (PBS), control oligonucleotide (sense sequence of 2′OMe-EGFP, 10 nM), and miR-21 (10 nM). Down panel: Quantitative analysis of PTEN, p-Akt and Akt expression. Note: *P < 0.05 compared with vehicle control

also overexpressed in cancers [22, 45]. The upregulated miR-21 is not limited in balloon-injury induced acute neointimal lesions, as our unpublished data also demonstrated that the expression levels of miR-21 was also increased in atherosclerotic mouse arteries and human arteries with neointimal lesion formation. We demonstrated that inhibition of miR-21 expression via antisense oligonucleotide-mediated miRNA depletion significantly decreased neointima formation after angioplasty. Our results strongly indicate that miR-21 is an important regulator for neointimal hyperplasia. However, there are two limitations for this in vivo study. One important limitation is the relative low efficiency (30–40% inhibition) for miR-21 knockdown by 2′OMe-miR-21. To improve the efficiency, the dose-response study for 2′OMemiR-21 should be performed to choose the best doses. In addition, the luminal delivery approach described in our recent study could be used to further improve the inhibitory efficiency [50, 51]. Definitely, miR-21 conditional knockout mouse targeting VSMCs will be provide additional information in the future studies. The second limitation is that the current experiment can not establish whether changes in miR-21 expression are the cause or result of arterial injury. Mature miR-21 direct delivery into the injured vascular walls is not a good approach due to its

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Fig. 18.10 The effect of miR-21 inhibitor 2′OMe-miR-21 on expression level of Bcl-2 in cultured VSMCs. (A) Up panel: Representative immunoblots of B-cell leukemia/lymphoma 2 (Bcl-2) from cells treated with vehicle (PBS), 2′OMe-EGFP (30 nM), and 2′OMe-miR-21 (30 nM). Down panel: Quantitative analysis of Bcl-2 expression. (B) Up panel: Representative immunoblots of B-cell leukemia/lymphoma 2 (Bcl-2) from cells treated with vehicle (PBS), control oligonucleotide (sense sequence of 2′OMe-EGFP, 10 nM), and miR-21 (10 nM). Down panel: Quantitative analysis of Bcl-2 expression. Note: *P < 0.05 compared with vehicle control

instability within the vascular tissue. miR-21 transgenic animal model will be needed for this purpose. VSMC is the major cellular component within the neointimal lesions. Neointimal growth is the balance between VSMC proliferation and apoptosis. The increased VSMC proliferation and/or the relative decreased VSMC apoptosis are responsible for neointimal formation. We have found that miR-21 expression was increased in VSMCs isolated from injured arteries, compared with that from normal, control vessels. To further determine the cellular mechanism of miR-21-mediated effect on neointimal lesion formation, we applied cultured cell models for VSMC proliferation and apoptosis. The results suggest that miR-21 is a pro-proliferative and anti-apoptotic regulator for VSMCs. MiR-21 inhibitor 2′OMe-miR-21-mediated cellular effects on proliferation and apoptosis are miR-21 specific and are not mediated by nonspecific toxic effects; because, a high dose of control oligonucleotide, 2′OMe-EGFP (100 nM), had no such cellular effects. In addition, cellular viability experiment using MTT method after transfection of 2′OMe-miR-21 revealed no nonspecific toxicity prior to the onset of apoptosis (Fig. 18.5D). Furthermore, apoptosis at the highest dose of 2′OMe-miR-21 (100 nM) without serum deprivation was only about 12% after 48 h miR-21 inhibition (Fig. 18.4E). However, high and disproportionate

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apoptosis under both miR-21 knockdown and serum deprivation (Fig. 18.5) indicates that a synergetic effect of miR-21 knockdown and serum deprivation on apoptosis may exist, although the mechanism is currently not clear. The anti-apoptotic effect is consistent with the effect of miR-21 on glioblastoma cells [45]. However, the anti-apoptotic effect was not found in HeLa cells [46]. The different effects of miR-21 on different cells suggest that the physiological effect of miRNAs may be cell-type dependent. We finally confirmed the cellular mechanisms of miR-21-mediated effect on neointimal lesion formation in vivo in the vascular wall after angioplasty by modulating the levels of miR-21 with miR-21 inhibitor. The gain-of-function experiment such as adenovirus-mediated miR-21 expression will be needed to further confirm these cellular effects both in vitro and in vivo. The mRNA targets of miRNAs are very complex as miRNAs are able to bind to their mRNA targets with either perfect or imperfect complementarity. Thus, one miRNA may have multiple mRNA targets. The detailed mRNA targets responsible for miR-21-mediated effects on VSMC proliferation and apoptosis are currently unclear. Although we found the activity of caspase-3 was increased in 2′OMemiR-21-treated VSMCs, the effect may not be the direct effect of miR-21, because there is no direct binding site for miR-21 in the 3′ UTR of caspase-3 mRNA. With the help of the currently available bioinformatics, we propose that PTEN and Bcl-2, two important signal molecules associated with VSMC growth and apoptosis, might be miR-21 targets. Our results from Western blot analysis indicate that PTEN and Bcl-2 are indeed involved in miR-21-mediated cell proliferation and apoptosis. PTEN could be a direct target of miR-21, because miR-21 inhibition up-regulates and miR-21 overexpression down-regulates its expression. However, the extent of PTEN express changes was much smaller than that we expected. We think that there are two possible reasons: First, PTEN is only one of the multiple target genes of miR-21. Thus, downregulation of miR-21 can only partially reduce PTEN expression; Second, mature miRNA-mediated decrease in its target gene expression is also miRNA-associated multiprotein RNA-induced silencing complex (miRISC) dependent. For example, the binding of mature miRNA with its target mRNA may require miRISC. Therefore, exogenous transfected miR-21 may only partially reduce PTEN expression due to the limited availability of miRISC. To further confirm the involvement of PTEN in miR-21-mediated effects, we have then determined the effect of miR-21 on its downstream signal molecule Akt using both loss-of-function and gain-of-function approaches. The effects of miR-21 on Akt activity are consistent with the expression changes of PTEN. In contrast to PTEN, miR-21 inhibition decreases and overexpression increases Bcl-2 expression. Although the results suggest that Bcl2 is involved in miR-21-mediated effects, the molecular mechanism is unclear. We think there are two possibilities. First, Bcl-2 might be an indirect target of miR-21 in VSMCs. miR-21 may suppress expression of a gene(s) that negatively regulates Bcl-2 expression. Another possibility could be that miR-21 might be able to directly affect Bcl-2 expression, but perhaps not via binding to the 3′ UTR. Other potential targets should be verified using both loss-of-function and gain-of-function approaches.

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In summary, miRNAs are aberrantly expressed in the vascular wall after angioplasty. The miRNA expression signature and antisense-mediated depletion reveal an essential role of miRNAs in vascular neointimal lesion formation. miRNAs may be a new therapeutic target for proliferative vascular diseases such as atherosclerosis, postangioplasty restenosis, transplantation arteriopathy, and stroke. However, it is clear that we are only at the very early stage in identifying the potential targets in miRNA-mediated effects on neointimal lesion formation. Bioinformatics, proteomics, transgene and gene knockout approaches, as well as clinical studies will be warranted to further identify the roles of these miRNAs in vascular neointimal formation and their molecular mechanisms. Acknowledgments This work was supported by a National Institutes of Health Grant HL080133, an American Heart Association Grant 0530106N, and an American Diabetes Association Grant 105JF60. The authors thank Dr. Kimberly Louis in our department for editing assistance.

References 1. Zaug AJ, Cech TR. The intervening sequence RNA of Tetrahymena is an enzyme. Science. 1986; 231:470–475. 2. Kong Y, Han JH. MicroRNA: biological and computational perspective. Genom. Proteom. Bioinform. 2005; 3:62–72. 3. Ambros V. MicroRNA pathways in flies and worms: growth, death, fat, stress, and timing. Cell. 2003; 113:673–676. 4. Farh KK, Grimson A, Jan C, Lewis BP, Johnston WK, Lim LP, Burge CB, Bartel DP. The widespread impact of mammalian MicroRNAs on mRNA repression and evolution. Science. 2005; 310:1817–1821. 5. Pasquinelli AE, Hunter S, Bracht J. MicroRNAs: a developing story. Curr Opin Genet Dev. 2005; 15(2):200–205. 6. Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004; 116:281–297. 7. Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993; 75:843–854. 8. Wightman B, Ha I, Ruvkun G. Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans. Cell. 1993; 75:855–862. 9. Lagos-Quintana M, Rauhut R, Lendeckel W, Tuschl T. Identification of novel genes coding for small expressed RNAs. Science. 2001; 294:853–858. 10. Kim VN. MicroRNA biogenesis: coordinated cropping and dicing. Nat Rev Mol Cell Biol. 2005; 6:376–385. 11. Bentwich I, Avniel A, Karov Y, Aharonov R, Gilad S, Barad O, Barzilai A, Einat P, Einav U, Meiri E, Sharon E, Spector Y, Bentwich Z. Identification of hundreds of conserved and nonconserved human microRNAs. Nat Genet. 2005; 37:766–770. 12. Berezikov E, Guryev V, van de Belt J, Wienholds E, Plasterk RH, Cuppen E. Phylogenetic shadowing and computational identification of human microRNA genes. Cell. 2005; 120:21–24. 13. Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005; 120:15–20. 14. Ambros V. The functions of animal microRNAs. Nature. 2004; 431:350–355. 15. Hwang HW, Mendell JT. MicroRNAs in cell proliferation, cell death, and tumorigenesis. Br J Cancer. 2006; 94:776–780.

346

C. Zhang

16. Wienholds E, Plasterk RH. MicroRNA function in animal development. FEBS Lett. 2005; 579:5911–5922. 17. Alvarez-Garcia I, Miska EA. MicroRNA functions in animal development and human disease. Development. 2005; 132:4653–4662. 18. Hammond SM. MicroRNAs as oncogenes. Curr Opin Genet Dev. 2006; 16:4–9. 19. Esquela-Kerscher A, Slack FJ. Oncomirs - microRNAs with a role in cancer. Nat Rev Cancer. 2006; 6:259–269. 20. Meng F, Henson R, Lang M, Wehbe H, Maheshwari S, Mendell JT, Jiang J, Schmittgen TD, Patel T. Involvement of human micro-RNA in growth and response to chemotherapy in human cholangiocarcinoma cell lines. Gastroenterology. 2006; 130:2113–21129. 21. Borkhardt A, Fuchs U, Tuschl T. MicroRNA in chronic lymphocytic leukemia. N Engl J Med. 2006; 354:524–525. 22. Chen CZ. MicroRNAs as oncogenes and tumor suppressors. N Engl J Med. 2005; 353:1768–1771. 23. Van Herck PL, Vrints CJ, Carlier SG. Coronary circulation and interventional cardiology. Ann Biomed Eng. 2005; 33:1735–1742. 24. Lagos-Quintana M, Rauhut R, Yalcin A, Meyer J, Lendeckel W, Tuschl T. Identification of tissue-specific microRNAs from mouse. Curr Biol. 2002; 12:735–739. 25. van Rooij E, Olson EN. MicroRNAs: powerful new regulators of heart disease and provocative therapeutic targets. J Clin Invest. 2007; 117:2369–2376. 26. Cheng Y, Ji R, Yue J, Yang J, Liu X, Chen H, Dean DB, Zhang C. MicroRNAs are aberrantly expressed in hypertrophic heart: do they play a role in cardiac hypertrophy? Am J Pathol. 2007; 170:1831–1840. 27. Chien KR. Molecular medicine: microRNAs and the tell-tale heart. Nature. 2007; 447:389–390. 28. Tatsuguchi M, Seok HY, Callis TE, Thomson JM, Chen JF, Newman M, Rojas M, Hammond SM, Wang DZ. Expression of microRNAs is dynamically regulated during cardiomyocyte hypertrophy. J Mol Cell Cardiol. 2007; 42:1137–1141. 29. Care A, Catalucci D, Felicetti F, Bonci D, Addario A, Gallo P, Bang ML, Segnalini P, Gu Y, Dalton ND, Elia L, Latronico MV, Hoydal M, Autore C, Russo MA, Dorn GW 2nd, Ellingsen O, Ruiz-Lozano P, Peterson KL, Croce CM, Peschle C, Condorelli G. MicroRNA-133 controls cardiac hypertrophy. Nat Med. 2007; 13:613–618. 30. Yang B, Lin H, Xiao J, Lu Y, Luo X, Li B, Zhang Y, Xu C, Bai Y, Wang H, Chen G, Wang Z. The muscle-specific microRNA miR-1 regulates cardiac arrhythmogenic potential by targeting GJA1 and KCNJ2. Nat Med. 2007; 13:486–491. 31. van Rooij E, Sutherland LB, Qi X, Richardson JA, Hill J, Olson EN. Control of stress-dependent cardiac growth and gene expression by a microRNA. Science. 2007; 316:575–579. 32. Thum T, Galuppo P, Wolf C, Fiedler J, Kneitz S, van Laake LW, Doevendans PA, Mummery CL, Borlak J, Haverich A, Gross C, Engelhardt S, Ertl G, Bauersachs J. MicroRNAs in the human heart: a clue to fetal gene reprogramming in heart failure. Circulation. 2007; 116:258–267. 33. Mann DL. MicroRNAs and the failing heart. N Engl J Med. 2007; 356:2644–2645. 34. Ross JS, Stagliano NE, Donovan MJ, Breitbart RE, Ginsburg GS. Atherosclerosis: a cancer of the blood vessels? Am J Clin Pathol. 2001; 116:S97–S107. 35. Zhang C, Yang J, Jennings LK. Attenuation of neointima formation through the inhibition of DNA repair enzyme PARP-1 in balloon-injured rat carotid artery. Am J Physiol Heart Circ Physiol. 2004; 287: H659–666. 36. Zhang C, Chaturvedi D, Jaggar L, Magnuson D, Lee JM, Patel TB. Regulation of vascular smooth muscle cell proliferation and migration by human sprouty 2. Arterioscler Thromb Vasc Biol. 2005; 25: 533–538. 37. Holm J, Hansson GK. Cellular and immunologic features of carotid artery disease in man and experimental animal models. Eur J Vasc Surg. 1990; 4:49–55.

18 MicroRNAs in Vascular Neointimal Lesion Formation

347

38. Forte A, Galderisi U, De Feo M, Gomez MF, Esposito S, Sante P, Renzulli A, Agozzino L, Hellstrand P, Berrino L, Cipollaro M, Cotrufo M, Rossi F, Cascino A. C-Myc antisense oligonucleotides preserve smooth muscle differentiation and reduce negative remodelling following rat carotid arteriotomy. J Vasc Res. 2005; 42:214–225. 39. Zhang C, Baker DL, Yasuda S, Makarova N, Balazs L, Johnson LR, Marathe GK, McIntyre TM, Xu Y, Prestwich GD, Byun HS, Bittman R, Tigyi G. Lysophosphatidic acid induces neointima formation through PPARgamma activation. J Exp Med. 2004; 199:763–774. 40. Caplen NJ, Parrish S, Imani F, Fire A, Morgan RA. Specific inhibition of gene expression by small double-stranded RNAs in invertebrate and vertebrate systems. Proc Natl Acad Sci USA. 2001; 98:9742–9747. 41. Poliseno L, Tuccoli A, Mariani L, Evangelista M, Citti L, Woods K, Mercatanti A, Hammond S, Rainaldi G. MicroRNAs modulate the angiogenic properties of HUVECs. Blood. 2006; 108: 3068–3071. 42. Yang J, Cheng Y, Ji R, Zhang C. A novel model of inflammatory neointima formation reveals a potential role of myeloperoxidase in neointimal hyperplasia. Am J Physiol Heart Circ Physiol. 2006; 291:H3087–H3093. 43. Li H, Telemaque S, Miller RE, Marsh JD. High glucose inhibits apoptosis induced by serum deprivation in vascular smooth muscle cells via upregulation of Bcl-2 and Bcl-xl. Diabetes. 2005; 54:540–545. 44. Schaeffer C, Vandroux D, Thomassin L, Athias P, Rochette L, Connat JL. Calcitonin gene-related peptide partly protects cultured smooth muscle cells from apoptosis induced by an oxidative stress via activation of ERK1/2 MAPK. Biochim Biophys Acta. 2003; 1643:65–73. 45. Chan JA, Krichevsky AM, Kosik KS. MicroRNA-21 is an antiapoptotic factor in human glioblastoma cells. Cancer Res. 2005; 65:6029–6033. 46. Cheng AM, Byrom MW, Shelton J, Ford LP. Antisense inhibition of human miRNAs and indications for an involvement of miRNA in cell growth and apoptosis. Nucleic Acids Res. 2005; 33:1290–1297. 47. Tsien RY. The green fluorescent protein. Annu Rev Biochem. 1998; 67:509–544. 48. Liu Z, Zhang C, Dronadula N, Li Q, Rao GN. Blockade of nuclear factor of activated T cells activation signaling suppresses balloon injury-induced neointima formation in a rat carotid artery model. J Biol Chem. 2005; 280:14700–14708. 49. Dourron HM, Jacobson GM, Park JL, Liu J, Reddy DJ, Scheel ML, Pagano PJ. Perivascular gene transfer of NADPH oxidase inhibitor suppresses angioplasty-induced neointimal proliferation of rat carotid artery. Am J Physiol Heart Circ Physiol. 2005; 288:H946–953. 50. Chang Y, Ceacareanu B, Zhuang D, Zhang C, Pu Q, Ceacareanu AC, Hassid A. Counter-regulatory function of protein tyrosine phosphatase 1B in platelet-derived growth factor- or fibroblast growth factor-induced motility and proliferation of cultured smooth muscle cells and in neointima formation. Arterioscler Thromb Vasc Biol. 2006; 26: 501–507. 51. Liu Z, Zhang C, Dronadula N, Li Q, Rao GN. Blockade of nuclear factor of activated T cells activation signaling suppresses balloon injury-induced neointima formation in a rat carotid artery model. J Biol Chem. 2005; 280: 14700–14708.

Chapter 19

microRNA in Cutaneous Wound Healing Chandan K. Sen* and Sashwati Roy

Abstract Repair of a defect in the human skin is a highly orchestrated physiological process involving numerous factors that act in a temporally resolved synergistic manner to re-establish barrier function by regenerating new skin. The inducible expression and repression of genes represents a key component of this process. MicroRNAs (miRNAs) are powerful regulators of gene expression yet their significance in tissue repair remains largely unknown. Recent estimates suggest that the number of unique miRNA genes in humans exceeds 1000, and may be as high as 20,000. miRNAs are functionally versatile, with the capacity to specifically inhibit translation initiation or elongation, as well as, induce mRNA destabilization, through predominantly targeting the 3’-untranslated regions of mRNA. In this chapter, we address the potential significance of miRNA in cutaneous wound healing. The following specific areas related to cutaneous wound healing are addressed: skin structure and function, stem cell biology, infection, immunity, inflammation, angiogenesis and extracellular matrix. Furthermore, we discuss opportunities for miRNA-based therapeutics in addressing chronic wounds as a major public health concern in the United States and globally.

Keywords wound healing, non-coding RNA, skin, Dicer, stem cell, infection, immunity, Inflammation, angiogenesis, miRNA-based therapeutics

19.1

Introduction

The public health impact of chronic wounds is staggering. An estimated 1.3 to 3 million US individuals are believed to have pressure ulcers; and as many as 10–15% of the 20 million individuals with diabetes are at risk of developing diabetic ulcers. Many more have had venous ulcers or wounds that result from arterial disease. Treating Laboratory of Molecular Medicine, Department of Surgery, 512 Davis Heart and Lung Research Institute, The Ohio State University Medical Center, 473 W. 12th Ave., Columbus, OH 43210, USA *Corresponding author: E-mail: [email protected]

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these wounds costs an estimated $5–10 billion each year [40]. Repair of a defect in the human skin is a highly orchestrated physiological process involving numerous factors that act in a temporally resolved synergistic manner to re-establish barrier function by regenerating new skin. The inducible expression and repression of genes represents a key component of this regenerative process [7, 8, 72]. The central dogma in molecular biology has been that DNA replicates its information and transcribes to RNA where it codes for the production of mRNA. Processing of mRNA essentially by splicing and translocation from nucleus to the cytoplasm and its function is to carry coded information from the ribosomes. Ribosomes translate the code for protein synthesis. The synthesis of specific proteins and their proper functionality at the correct temporal phase of healing is central to wound healing. Do all RNA carry the code to synthesize protein? No. However, almost all means of gene identification assume that genes encode proteins. An important aspect of the central dogma remained under veils for a long time. Non-coding RNA (ncRNA) genes produce functional RNA molecules rather than encoding proteins. Several different systematic screens have identified a surprisingly large number of ncRNA genes. Non-coding RNAs seem to be particularly abundant in roles that require highly specific nucleic acid recognition without complex catalysis, such as in directing post-transcriptional regulation of gene expression or in guiding RNA modifications. Although it has been generally assumed that most genetic information is transacted by proteins, recent evidence suggests that the majority of the genomes of mammals and other complex organisms is in fact transcribed into ncRNAs, many of which are alternatively spliced and/or processed into smaller products [47]. These RNAs (including those derived from introns) appear to comprise a hidden layer of internal signals that control various levels of gene expression in physiology and development, including chromatin architecture/epigenetic memory, transcription, RNA splicing, editing, translation and turnover. This hidden layer of internal signals is now emerging to be of such critical significance that lack of consideration of that layer poses the serious risk of clouding our ability to understand the molecular basis of health and disease [27, 47, 61, 87]. In all forms of life, ncRNA includes ribosomal RNA (rRNA), transfer RNA (tRNA), small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), interference RNA (RNAi), short interfering RNA (siRNA), and micro RNA (miRNA). miRNAs are powerful regulators of gene expression. A miRNA is approximately 22 ribonucleotides-long, non-coding RNAs, with a potential to recognize multiple mRNA targets guided by sequence complementarity and RNA-binding proteins. Recent evidence suggests that the number of unique miRNA genes in humans exceeds 1,000, and may be as high as 20,000 [58]. Recent data claim that the numbers of miRNAs and their targets are much greater than what we previously thought [64]. miRNAs are functionally versatile, with the capacity to specifically inhibit translation initiation or elongation, as well as, induce mRNA destabilization, through predominantly targeting the 3′-untranslated regions of mRNA. Briefly, miRNA are transcribed in the nucleus by conventional mechanisms and are exported to the cytoplasm [94], where after biological processing they form the mature miRNA that can interact with matching mRNAs by RNA-RNA binding. This binding, with the

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assistance of the RNA induced silencing complex (RISC) leads to modes of action, resulting in mRNA degradation or translational inhibition [85]. This mechanism of action is termed as post-transcriptional gene regulation (PTGS). In animals, in contrary to plants, there is not 100% nt match between miRNA and its target mRNA, leading to a mode of action causing mRNA translational inhibition and not mRNA degradation [11]. The interaction between the miRNA and its matching mRNA occurs between the 5′ UTR of the miRNA to the 3′ UTR region of the mRNA by a matching seed element in the miRNA. Utilizing this data in computational prediction approaches estimates that miRNAs can target 30% of the human genome [36, 42, 75]. Furthermore, one miRNA can regulate more than one gene, and one gene can be regulated by a number of miRNAs. One of the outcomes of this is the fact that there is tissue specificity for miRNA expression that contributes to the tissue specificity of the mRNAs, adding to the role of miRNA in developmental biology and to cell and tissue phenotyping [51, 77, 79]. The complexities underlying tissue-dependent miRNA biogenesis and target selection process is being gradually understood [64]. miRNAs have been implicated in the regulation of developmental timing and pattern formation, restriction of differentiation potential, regulation of insulin secretion, resistance to viral infection, and in genomic rearrangements associated with carcinogenesis or other genetic disorders, such as fragile X syndrome. Broadly, there are three basic phases of wound healing: inflammation, proliferation, and maturation [9]. The first inflammatory phase is characterized by hemostasis and inflammation. The next phase consists mainly of epithelialization, angiogenesis, granulation tissue formation, and collagen deposition. The final phase includes maturation and remodeling. In this phase mainly there is deposition of collagen in an organized and well-mannered network [8]. The complexity of wound healing is augmented by the influence of local factors such as ischemia, edema and infection, and systemic factors such as diabetes, age, hypothyroidism, nutrition and more [29]. The objective of this review article is to explore the potential significance of miRNA in cutaneous wound healing (Fig. 19.1) in light of the current literature.

19.2 19.2.1

miRNA Regulation of the Skin The Cutaneous Architecture

The skin is the largest organ of the body, accounting for about 15% of the total body weight in adult humans [31, 32]. Broadly, the skin is made up of three layers: epidermis, dermis and hypodermis. The mammalian epidermis is a stratified epithelium layer that retains the ability to self renew under both homeostatic and injury conditions by maintaining a population of mitotically active cells in the hair follicles and innermost basal layer [71]. It is populated by keratinocytes (80%), dendritic cells (20%), melanocytes, Langerhans and Merkel cells. The dermis consists of collagenous and elastic fibers embedded into an amorphous

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Skin Development

Response to Bacterial Infection Response to Viral Infection Neutrophil Function Monocyte Differentiation Macrophage Function Fibroblast Proliferation Endothelial Function Angiogenic Response Redox Signaling Stem Cell Renewal Cytokine Expression & Function Blood Cell Renewal ECM Expression

Hair Follicle Development

Fig. 19.1 microRNA regulated processes that are relevant to wound healing

ground substance. It is inhabited by fibroblasts, macrophages, mast cells and lymphocytes. The hypodermis is composed of adipocyte lobules defined by fibrous connective tissue septa. In addition, the skin contains hair follicles which developmentally represents an outgrowth of the primitive epidermis [80]. The hair follicle has a complex structure with more than 20 different cell types distributed into six main compartments, namely the connective tissue sheath, the dermal papilla, the outer root sheath, the inner root sheath, the shaft and the sebaceous gland. These compartments span between the dermis and the epidermis [4]. Of note, the hair follicle has a reservoir of pluripotent stem cells that can also regenerate the epidermis [41, 46].

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19.2.2

353

miRNA Regulation of Skin Morphogenesis and Barrier Function

Functionally, the skin has multiple roles including serving as an epidermal barrier, immune surveillance, UV protection, thermoregulation, sweating, lubrication, pigmentation, the sensations of pain and touch, and the protection of various stem cell niches in its domain [67]. However, the primary role of the skin is to defend the body by serving as an interface between the internal organs and the environment. This barrier function of the skin is critical in newborn animals, as shown by transgenic animal models with barrier defects that die shortly after birth from transepidermal water loss [70]. Some of earliest works examining the role of miRNA on skin biology have therefore focused on the regulation of barrier function [93]. Examination of the functional significance of miRNAs murine skin epidermis and hair follicle led to the observation that skin morphogenesis is governed by discrete sets of differentially expressed microRNAs. Skin miRNAs were noted to be differentially expressed by cells of epidermal and hair follicle lineages. There were distinctive expression patterns of miRNAs in these two tissue compartments of the skin. The miRNA mmu-miR-16, abundantly present in all tissues [38], was noted to be also present at high levels in cells of epidermal and hair follicle lineages. On the basis of analogy in 5′-seed sequences, skin miRNAs could be classified into discrete groups [93]. The RNase III enzyme Dicer processes RNA into siRNAs and miRNAs, which direct a RNA-induced silencing complex (RISC) to cleave mRNA or block its translation. Dicer represents a key enzyme that regulates miRNA biogenesis [53, 76]. Thus, dicer knock down represents a reasonable approach to deplete tissue miRNA pool. Generation of the conditional knockdown mouse where Dicer can be specifically knocked down from skin epithelial progenitor cells represents a landmark progress that should be instrumental in understanding the significance of miRNA biology in the skin [93]. Interestingly, these conditional knockout mice were born intact but began losing weight within 1–2 days after birth. The neonatal conditional knockout mice appeared dehydrated and did not survive past postnatal days 4–6. The most striking histological finding was that in the skin instead of invaginating downwards into the dermis, hair germs appeared to evaginate into the epidermis. With age, hair germ–like cysts became prevalent, markedly distorting the overlying epidermis. In addition, the conditional knockout skin showed signs of apoptosis although the number of cells in the hair follicles was higher. The continual upward proliferation of follicle cells grossly perturbed the integrity of the skin of the mutant mice. The cystinduced epidermal perturbations were held accountable for the loss of body weight, dehydration and eventual death of the Dicer1 conditional knockout mice [93]. Dicer is present in both epidermis and hair-follicle outer root sheath [2]. To determine whether Dicer is required for development of the hair follicles or epidermis, a mouse line containing epidermal-specific deletion of the Dicer gene has been generated [2]. This was achieved by crossing Dicerflox mice with a transgenic mouse line in which Cre recombinase is expressed under the control of a keratin 14 (K14) promoter.

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In agreement with the former study described above [93], newborn Dicer mutant mice were initially grossly indistinguishable from control littermates. However, by postnatal day 7 the mutant mice were stunted, lacked external hair growth and started to die. Evaginations of the epidermis by hair follicles were noted. In addition, the hair follicles were also replaced by cyst structures or disorganized clumps of epithelial cells within the dermis. Of note, the expression of the progenitor cell marker, Keratin 15 was absent from the skin of newborn Dicer mutants. Keratin 15 is a specific marker for hair-follicle stem cells, although its significance remains mostly unknown [5]. In contrast to the findings in the mutant hair follicles, the Dicer mutant epidermis displayed a marked elevation in the numbers of both basal and suprabasal cell layers compared with control littermate epidermis. Notch proteins are important in binary cell-fate decisions and inhibiting differentiation in many developmental systems. Notch1 functions as a tumor-suppressor gene in mammalian skin [54]. Both Notch1 and Notch2 receptors contribute to the maintenance of melanoblasts and melanocyte stem cells, and are essential for proper hair pigmentation [69]. Interestingly, the expression of Notch1 was reduced in Dicer mutant epidermis as well as in the hair follicles. Deletion of Notch1 in the epidermis causes hyperproliferation and tumor development suggesting that the observed decrease in Notch1 expression in the Dicer mutant could contribute to the epidermal phenotype [60]. The observation that Notch1 is essential for postnatal hair follicle development and homeostasis [89] leads to the hypothesis that Notch 1 is the key protein that is affected in the Dicer knockouts causing hair follicle abnormalities leading to impairments in skin morphogenesis resulting in compromised barrier function, loss of water and death. Another striking observation in the skin of these mutant mice was the appearance of clusters of dermal cells, apparently in the process of being surrounded by epidermal cells. Because K14-Cre does not cause recombination of the Dicerflox allele in dermal cells this phenotype is likely secondary to Dicer deficiency in the epidermis or the epithelium of hair follicle. The above-described two murine models contributed by the groups of Elaine Fuchs and Sarah E. Millar provide first evidence supporting the fundamental roles of miRNAs in skin tissue morphogenesis.

19.3

miRNA Regulation of Stem Cell Biology

Stem cell self-renewal and differentiation are defined by the dynamic interplay between transcription, epigenetic control, and posttranscriptional regulators, including microRNAs, whose key role in stem cell biology is just emerging [15, 92]. One of the key characteristics of stem cells is their capacity for self-renewal for long periods of time. In this respect, stem cells are similar to cancer cells, which also have the ability to escape cell cycle stop signals. Some miRNAs are specifically expressed in stem cells, control stem cell self-renewal, and differentiation through negatively regulating the expression of certain key genes in stem cells [74]. miRNAs are implicated in the proper control of germline stem cell (GSC) division in Drosophila melanogaster. Analysis of GSCs mutant for dicer-1 (dcr-1), the

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double-stranded RNaseIII essential for miRNA biogenesis, revealed a marked reduction in the rate of germline cyst production. These dcr-1 mutant GSCs exhibit normal identity but are defective in cell cycle control. On the basis of cell cycle markers and genetic interactions, it may be understood that dcr-1 mutant GSCs are delayed in the G1 to S transition, which is dependent on the cyclin-dependent kinase inhibitor Dacapo, suggesting that miRNAs are required for stem cells to bypass the normal G1/S checkpoint. Hence, the miRNA pathway might be part of a mechanism that makes stem cells insensitive to environmental signals that normally stop the cell cycle at the G1/S transition [30]. In addition, miRNAs signal cell fate [62] and stem cell phenotype [1]. miRNAs are components of the molecular circuitry that controls mouse hematopoiesis. In one of the earlier studies three miRNAs that are specifically expressed in hematopoietic cells were identified. The expression of these miRNAs was dynamically regulated during early hematopoiesis and lineage commitment. One of these miRNAs, miR-181, was preferentially expressed in the B-lymphoid cells of mouse bone marrow, and its ectopic expression in hematopoietic stem/progenitor cells led to an increased fraction of B-lineage cells in both tissue-culture differentiation assays and adult mice [13]. Some human miRNAs are linked to leukemias: the miR-15a/miR-16 locus is frequently deleted or down-regulated in patients with B-cell chronic lymphocytic leukemia and miR-142 is at a translocation site found in a case of aggressive B-cell leukemia [14]. miRNAs 221 and 222 inhibit normal erythropoiesis and erythroleukemic cell growth via kit receptor down-modulation [20]. miRNA-155 transduction greatly reduces both myeloid and erythroid colony formation of normal human CD34+ hematopoietic stem-progenitor cells [25]. In sum, miRNA-mediated post-transcriptional regulation influences the development and function of blood cells. miRNAs target megakaryocytic transcription factors and regulate megakaryocytopoiesis. Megakaryocytic differentiation is associated with down-regulation of miR-10a, miR-126, miR-106, miR-10b, miR-17 and miR-20. miR-130a targets the transcription factor MAFB, which is involved in the activation of the GPIIB promoter, a key protein for platelet physiology. In differentiated megakaryocytes, miR10a expression is inverse to that of HOXA1, a direct target of miR-10a [24]. Challenging mice with lentiviral vectors encoding target sequences of endogenous miRNAs it has been found that the efficiency of miRNA is sharply segregating gene expression among different tissues. Transgene expression from vectors incorporating target sequences for mir-142-3p was effectively suppressed in intravascular and extravascular hematopoietic lineages, whereas expression was maintained in nonhematopoietic cells [10]. The regulation of monocytic differentiation and maturation by miRNA is discussed in the section on inflammation.

19.4

miRNA Regulation of Infection

The anti-viral function of RNA silencing was first discovered in plants as a natural manifestation of the artificial ‘co-suppression’, which refers to the extinction of endogenous gene induced by homologous transgene. Replication of mammalian

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viruses is regulated by RNAi. miRNAs, rather than virus-derived small interfering (si)RNAs like in other organisms, are involved. In fact, these recent studies even suggest that RNA silencing may be beneficial for viral replication. Accordingly, several large DNA mammalian viruses have been shown to encode their own miRNAs. RNAi is directly implicated in HIV replication [33]. Dicer mutant mice are hypersusceptible to infection by the RNA virus vesicular stomatitis virus [57]. Contrary to the hypothesis that RNAi is an antiviral pathway in mammals, as has been reported for subgenomic hepatitic C virus (HCV) replicons, siRNAs that target Dicer inhibited HCV replication. Furthermore, siRNAs that target several other components of the RNAi pathway also inhibit HCV replication. miRNA-based immunoevasion mechanism is exploited by human cytomegalovirus [81]. MicroRNA profiling of human liver, human hepatoma Huh-7.5 cells, and Huh-7.5 cells that harbor replicating HCV demonstrated that miR-122 is the predominant miRNA in each environment. miR-122 has been also implicated in positively regulating the replication of HCV genotype 1 replicons. It is now known that 2′’-O-methyl antisense oligonucleotide depletion of miR-122 also inhibits HCV genotype 2a replication and infectious virus production. These findings define 26 host genes that modulate HCV infection and indicate that the requirement for functional RNAi for HCV replication is dominant over any antiviral activity this pathway may exert against HCV [63]. Virus infection and viral proteins influence miRNA balance without affecting posttranscriptional gene silencing and contributes to the hypothesis that viruses exploit miRNA pathways during pathogenesis [3]. The involvement of miRNAs in bacterial infection remains more poorly appreciated. siRNAs corresponding to transferred-DNA oncogenes initially accumulate in virulent Agrobacterium tumefaciens-infected tissues and RNA interference-deficient plants are hypersusceptible to the pathogen. Successful infection relies on a potent antisilencing state established in tumors whereby siRNA synthesis is specifically inhibited. This inhibition has only modest side effects on the miRNA pathway, shown here to be essential for disease development [18]. Arabidopsis, the bacterial component, flagellin, induces the expression of a specific microRNA, which in turn leads to the down-regulation of the signaling pathways that are implicated in disease susceptibility [22]. The involvement of miRNAs in the lipopolysaccharide (LPS) pathway is discussed below under the section on inflammation.

19.5

miRNA Regulation of Immunity

MicroRNAs (miRNAs) are found in most metazoan organisms as well as in viruses and are implicated in immunity [16, 84]. miRNA dependent mRNA decay influences innate immunity against microbes and T cell activation as a model of the adaptive response [35]. The first highly specific knockouts of a miRNA, miR155, in mice resulted in multiple defects in adaptive immunity [50]. Recently, miRNA has been directly involved in innate immunity and transduction signalling by Tolllike receptors and the ensuing cytokine response [23]. The innate immune response

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can be initiated by the binding of various pathogen-associated compounds or cytokines to receptors on the surfaces of dendritic cells. These interactions result in the activation of many genes and gene products. Several different pathways converge to raise the abundance of specific miRNAs. In particular, activation of the transcription factors AP-1 and NF-kappaB results in an increase in the amount of miR-155. High levels of this miRNA are associated with several types of cancer. However, the mRNAs that may be targeted by miR-155 in the innate immune response remain to be fully characterized. Mice deficient for bic/microRNA-155 are immunodeficient and display increased lung airway remodeling. bic/microRNA-155 are required for the function of B and T lymphocytes and dendritic cells. Transcriptome analysis of bic/microRNA-155-deficient CD4+ T cells identified a wide spectrum of miRNA-155-regulated genes, including cytokines, chemokines, and transcription factors. bic/microRNA-155 plays a key role in the homeostasis and function of the immune system [66]. T cell sensitivity to antigen is intrinsically regulated during maturation to ensure proper development of immunity and tolerance, but the response to how this is accomplished includes miRNAs as a central player. Increasing miR-181a expression in mature T cells augments the sensitivity to peptide antigens, while inhibiting miR-181a expression in the immature T cells reduces sensitivity and impairs both positive and negative selection. Moreover, quantitative regulation of T cell sensitivity by miR-181a enables mature T cells to recognize antagonists-the inhibitory peptide antigens-as agonists. These effects are in part achieved by the downregulation of multiple phosphatases, which leads to elevated steady-state levels of phosphorylated intermediates and a reduction of the T cell receptor signaling threshold. Importantly, higher miR-181a expression correlates with greater T cell sensitivity in immature T cells, suggesting that miR-181a acts as an intrinsic antigen sensitivity “rheostat” during T cell development [43].

19.6

miRNA Regulation of Inflammation

The mammalian inflammatory response involves the induction of several hundred genes, a process that must be carefully regulated to achieve the right microenvironment to facilitate wound healing. Emergent results point to the general direction that miRNAs may regulate inflammation at multiple levels. miRNAs regulate monocytic differentiation and maturation [21]. Monocytopoiesis is controlled by a circuitry involving sequentially miRNA 17-5p-20a-106a, AML1 and M-CSFR, whereby miRNA 17-5p-20a-106a function as a master gene complex interlinked with acute myeloid leukaemia-1 (AML1) in a mutual negative feedback loop. In unilineage monocytic culture generated by haematopoietic progenitor cells these miRNAs are downregulated, whereas the transcription factor (AML1; also known as Runt-related transcription factor 1, Runx1) is upregulated at protein but not mRNA level. As miRNAs 17-5p, 20a and 106a bind the AML1 mRNA 3′UTR, their decline seem to unblock AML1 translation. Accordingly, transfection with miRNA 17-5p-20a-106a suppresses AML1 protein expression, leading to M-CSF

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receptor (M-CSFR) downregulation, enhanced blast proliferation and inhibition of monocytic differentiation and maturation. Treatment with anti-miRNA 17-5p, 20a and 106a causes opposite effects. Knockdown of AML1 or M-CSFR by short interfering RNA (siRNA) mimics the action of the miRNA 17-5p-20a-106a, confirming that these miRNAs target AML1, which promotes M-CSFR transcription. In addition, AML1 binds the miRNA 17-5p-92 and 106a-92 cluster promoters and transcriptionally inhibits the expression of miRNA 17-5p-20a-106a [21]. LPS-induced innate immune response is associated with widespread, rapid and transient increases in miRNA expression which might be involved in the regulation of the inflammatory response. The LPS-induced increases in miRNA expression are not mediated via classical inflammatory transcription factors [52]. miR-155 is emerging as a common target of a broad range of inflammatory mediators [55]. Both miR-155 and miR-125b play a role in innate immune response [86]. LPS stimulation of mouse Raw 264.7 macrophages resulted in the up-regulation of miR-155 and down-regulation of miR-125b levels. The same changes also occurred when C57BL/6 mice were i.p. injected with LPS. Furthermore, the levels of miR-155 and miR-125b in Raw 264.7 cells displayed oscillatory changes in response to TNF-alpha. These changes were impaired by pretreating the cells with the proteasome inhibitor MG-132, suggesting that these two miRNAs may be at least transiently under the direct control of NF-kappaB transcriptional activity. There is suggestive evidence demonstrating that miR-155 directly targets transcript coding for several proteins involved in LPS signaling such as the Fas-associated death domain protein (FADD), IkappaB kinase epsilon (IKKepsilon), and the receptor (TNFR superfamily)interacting serine-threonine kinase 1 (Ripk1) while enhancing TNF-alpha translation. In contrast, miR-125b targets the 3′-untranslated region of TNF-alpha transcripts; therefore, its down-regulation in response to LPS may be required for proper TNF-alpha production. Emu-miR-155 transgenic mice produce higher levels of TNF-alpha when exposed to LPS and were hypersensitive to LPS/d-galactosamine-induced septic shock. Thus, LPS/TNF-alpha-dependent regulation of miR-155 and miR-125b may be implicated in the response to endotoxin shock, thus offering new targets for drug design. Exposure of primary murine macrophages to polyriboinosinic:polyribocytidylic acid or the cytokine IFN-beta caused induction of miR-155. miR-155 is also induced by several Toll-like receptor ligands through myeloid differentiation factor 88- or TRIF-dependent pathways, whereas up-regulation by IFNs was shown to involve TNF-alpha autocrine signaling. Pharmacological inhibition of the kinase JNK blocked induction of miR-155 in response to either polyriboinosinic:polyribocytidylic acid or TNF-alpha, suggesting that miR-155-inducing signals use the JNK pathway [55]. In the area of cytokine function, miR let-7a modulates interleukin-6-dependent STAT-3 survival signaling [48]. Not only is interleukin-6 signaling subject to miRNA regulation but interleukin-6 itself can cause epigenetic regulation of miRNA-370 [49]. Such observations underscore the complexities involved in miRNA-dependent regulation of cytokine biology. Psoriasis is the most prevalent chronic inflammatory skin disease in adults. Recently it has been demonstrated that psoriasis-affected skin has a specific microRNA expression profile when compared with healthy

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human skin or with another chronic inflammatory skin disease, atopic eczema [78]. Psoriasis-specific microRNAs included leukocyte-derived microRNAs and one keratinocyte-derived microRNA, miR-203. In a panel of 21 different human organs and tissues, miR-203 showed a highly skin-specific expression profile. Among the cellular constituents of the skin, miR-203 was exclusively expressed by keratinocytes. The up-regulation of miR-203 in psoriatic plaques was concurrent with the down-regulation of an evolutionary conserved target of miR-203, suppressor of cytokine signaling 3 (SOCS-3), which is involved in inflammatory responses and keratinocyte functions. These findings suggest that microRNAs are involved in the pathogenesis of psoriasis and contributes to the dysfunction of the cross talk between resident and infiltrating cells [78]. miRNAs also regulate transforming growth factor-beta1 (TGF-beta)-induced epithelial-mesenchymal transition (EMT) in human keratinocytes, a model of epithelial cell plasticity underlying epidermal injury. A novel EMT-specific miRNA signature that includes induction of miR-21 has been described. Integration of the miRNA screen results with target prediction algorithms and gene expression profiling data have resulted in a framework for TGF-beta-directed microRNA:messenger RNA (mRNA) regulatory circuitry [95].

19.7

miRNA Regulation of Angiogenesis

Angiogenesis represents a critical component of successful wound healing process [44]. It is marked by endothelial cell migration and capillary formation where the migration of capillaries into the wound bed is critical for proper wound healing. The granulation phase and tissue deposition require nutrients supplied by the capillaries. Failed wound angiogenesis causes a chronic wound. In the study of embryonic angiogenesis it has been reported that Dicer gene is significantly expressed in 11-day embryos and remains constant through 17-day, evenly expressed throughout the embryonic tissues [91]. The dicerex1/2 mutant mouse lacking the first two exons of dicer that are essential for the function of the protein represents a tool that has shed light on embryonic angiogenesis. Homozygous mutant mice were not viable, therefore the embryos were examined. Starting from embryonic day 11.5, virtually all dicerex1/2 embryos were growth and developmentally retarded as compared with their wild type or heterozygous litter mates. The embryos that were still viable at this stage had thin and sub-optimally developed blood vessels providing first evidence for the involvement of miRNAs levels in angiogenesis [91]. Microscopic examination of the yolk sacs from the mutant embryos revealed that there were fewer blood vessels in the dicerex1/2 yolk sacs and that these vessels were thin, small, and less organized than those of control yolk sacs. These observations indicate that Dicer-dependent biogenesis of miRNA is required for blood vessel development during embryogenesis. miRNAs also regulate tumor angiogenesis [17]. C-myc is a leucin zipper transcription factor that has a role in neo-vascularization of neoplasms [6]. Myc directly activates the microRNA cluster miR-17-92 in human lymphocytes [56].

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In addition, it induces miR-18 and miR-19 which are the cleavage products of miR-17-92 cluster [17]. Induced by Myc, miR-18 and miR-19 antagonizes thrombospondin 1 and connective tissue growth factor, respectively. These findings represent the first evidence for the involvement of specific miRNAs in angiogenesis. Support for the involvement of miR in angiogenesis comes from in vitro studies as well [59]. Large-scale analysis of miRNA expression in human umbilical vein endothelial cells (HUVEC) led to the observation that among the 15 highly expressed miRNAs have the receptors of angiogenic factors as putative targets. In particular, miR-221 and miR-222 was identified as regulating cKit expression as well as the angiogenic properties of its ligand Stem Cell Factor. The miR-221/2 and c-Kit interaction represents an integral component of a complex circuit that controls the ability of endothelial cells to form new capillaries [59]. Inhibition of c-kit results in reduced VEGF expression [45]. Furthermore, we know that c-kit is involved in neovascularization [65, 82]. Dicer and Drosha are the miRNA processing enzymes that are required for the maturation of miRNAs. The maintenance and regulation of endogenous miRNA levels via Dicer mediated processing is critical for endothelial cell gene expression and functions in vitro [83]. The significance of both Dicer and Drosha in driving angiogenesis in vitro have been reported [39, 83]. Silencing of Dicer and Drosha significantly reduced capillary sprouting of endothelial cells and tube forming activity. Migration of endothelial cells was significantly decreased in Dicer siRNA-transfected cells, whereas Drosha siRNA had no effect. Silencing of Dicer but not of Drosha reduced angiogenesis in vivo. The let-7 family and mir-27b were identified as key regulators of the angiogenic responses of endothelial cells. Several studies have demonstrated a central role of NADPH oxidase derived reactive oxygen species (ROS) as signaling messengers in driving angiogenesis [12, 68, 73, 88]. Whether such redox control of angiogenesis is subject to regulation by miRNA remain unknown. A recent study in our laboratory presents first evidence that cellular redox state, a key driver of cell signaling, is regulated by miRNAs. Specifically, p47phox of the NADPH oxidase complex was identified as one target that regulates the angiogenic properties of endothelial cells [26].

19.8

miRNA Regulation of Other Aspects of Wound Healing Related Biology

Extracellular matrix (ECM) represents an essential component of wound healing. First evidences pointing towards a regulatory role of miRNAs in ECM biology is starting to accumulate. For example, miR-192 regulates TGF-betainduced Col1a2 expression by down-regulating E-box repressors [34]. In fibroblasts, let7 and other miRNAs with similar expression profiles seem to be involved in regulating the transcriptional program in response to proliferative signals [28].

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19.9

361

miRNA-Based Therapeutics

The discovery of miRNAs as new regulators in the mechanism of gene expression opened new options for the design of new therapeutic agents that could modify gene expression in disease. The ability to modulate miRNAs activity in vivo may have tremendous impact on disease therapy and on in vivo research opportunities. The direction towards this has been actually set. Two options, over-expression or silencing of the prospective miRNA exist. For the former, delivery of corrective synthetic miRNAs in the form of (siRNA-like) dsRNA will be beneficial. If a disease phenotype is derived from abnormal inhibition of mRNAs caused by, for example, excessive expression of miRNAs, or shutting down a miRNA will be positive, oligonucleotides complementary to either the mature miRNA or its precursors can be designed, so that the miRNAs will be arrested and will not be able to compliment the target mRNA. The fundamental properties of such oligonucleotides (for either up or down-regulation of miRNA activity) will be delivery in vivo, degradation avoidance, specificity and high binding affinity to RNA. This can be achieved by modification of the nucleotides, especially the addition of chemical groups to the 2′-hydroxyl group of them has been shown to be effective. Three forms of chemically modified oligonucleotides may be used to silence miRNAs [90]. These include 2′-O-methyl-group (OMe)-modified oligonucleotides, 2′-O-Methoxyethyl (MOE)-modified oligonucleotides that show to have higher affinity and specificity to RNA than their OMe-analogs and locked nucleic acid (LNA)-modified oligonucleotides in which the 2′-O-oxygen is bridged to the 4′-position via a methylene linker to form a rigid bicycle, locked into a C3′-endo (RNA) sugar conformation. Most of the data so far has been gathered from in vitro experiments, though; there are some works that have been done in in vivo studies. Both genetic as well as nongenetic approaches may be adopted to manipulate miRNAs [37]. Specific miRNA silencing is achieved by antisense targeting. The genetic approaches include knockout of miRNA genes in mice, mutation of miRNA target sites in protein-encoding genes and conditional alleles of the miRNA-processing gene Dicer1, leading to deficiency of all mature miRNAs. The non-genetic approaches utilize the (OMe)modified oligonucleotides that go through further modifications to be compatible for in vivo delivery. This method was successfully demonstrated in vivo using modified oligonucleotides named “antagomirs” [38]. Chemically modified, cholesterolconjugated single-stranded RNA analogues complementary to miRNAs, antagomirs, have been designed. They were synthesized starting from a hydroxyprolinol-linked cholesterol solid support and 2′-OMe phosphoramidites. Indeed, i.v. injection of antagomir-122 decreased miR-122 levels specifically. Antagomir-122 resulted in a complete loss of miR-122 signal and levels of miR-122 were undetectable for as long as 23 days after injection. Antagomir-16 silences miR-16 in all body tissues besides the brain. Therefore, when using antagomirs one can silence efficiently miRNAs in vivo in almost all body tissues. In this case, silencing miR-122 resulted in changes in cholesterol-biosynthesis genes with down-regulation of 3-hydroxy3-methylglutaryl-CoA-reductase (Hmgcr), a rate-limiting enzyme of endogenous cholesterol biosynthesis. Plasma cholesterol levels were decreased more than 40%

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in antagomir-122 treated animals. Moreover, antagomir injection did not seem to have any toxic effect. These lines of evidence support that antagomirs may represent a productive tool to silence miRNAs in vivo. Another form of modified oligonucleotides, 2′-O-methoxyethyl (2′-MOE) phosphorothioate-modified antisense oligonucleotide (ASO), has been proven to succeed in in vivo silencing of miRNAs [19]. Using this approach, miR-122 was successfully silenced, by mere intrperitoneal injection of ASO. Verification of miR-122 silencing was additionally proven by the increase of mRNA levels of four target genes of miR-122, while no target mRNA changes were observed in mice treated with control ASO, demonstrating specific inhibition of miR-122 activity in the liver. This study has taken another step forward by applying this technique in a disease model of obesity in mice. C57Bl/6 mice that had been fed a high-fat diet for 19 weeks were treated with miR-122 ASO. Blocking miR-122 resulted in 35% decrease of plasma cholesterol levels compared to control mice, although the authors explained that there was a maximal relief threshold from the effect of silencing miR-122. Over-expression of miRNAs in vivo can be achieved [96]. pre-miR-1 plus flanking sequence was sub-cloned into α-MHCclone26 or β-MHCclone32 vectors and introduced into mice. Northern blots of the transgenic mice confirmed that they expressed miR-1. Next, Western blots of transgenic heart were performed. A significant decrease in Hand2 protein levels compared with non-transgenic littermates were observed, with no change in mRNA levels of Hand2. These observations confirmed that Hand2 is a miR-1 target in vivo and that up-regulation of a single miRNA using its precursor can elevate specific proteins levels. Ongoing studies in our laboratory have identified specific changes in miRNA expression in the woundedge tissue as a function of time. We hypothesize that such changes are functionally important with respect to orchestrating the healing cascade. Approaches such as those that are described above and other emergent techniques may be used to modulate miRNA expression in the healing wound at specific phases. Such studies should lead to novel therapeutic strategies aimed at healing the problem wound under conditions such as aging, obesity and diabetes. Acknowledgments Supported by NIH awards RO1 GM 077185 and GM 069589 to CKS, and by RO1 DK076566 to SR.

References 1. Wasta V and Mehl V Micro-RNA’s function to maintain stem cell phenotype. Cancer Biol Ther 6: 305, 2007. 2. Andl T, Murchison EP, Liu F, Zhang Y, Yunta-Gonzalez M, Tobias JW, Andl CD, Seykora JT, Hannon GJ, and Millar SE. The miRNA-processing enzyme dicer is essential for the morphogenesis and maintenance of hair follicles. Curr Biol 16: 1041–1049, 2006. 3. Bazzini AA, Hopp HE, Beachy RN, and Asurmendi S. Infection and coaccumulation of tobacco mosaic virus proteins alter microRNA levels, correlating with symptom and plant development. Proc Natl Acad Sci USA 104: 12157–12162, 2007. 4. Bernard BA. The biology of hair follicle. J Soc Biol 199: 343–348, 2005.

19 microRNA in Cutaneous Wound Healing

363

5. Bieniek R, Lazar AJ, Photopoulos C, and Lyle S. Sebaceous tumours contain a subpopulation of cells expressing the keratin 15 stem cell marker. Br J Dermatol 156: 378–380, 2007. 6. Brandvold KA, Neiman P, and Ruddell A. Angiogenesis is an early event in the generation of myc-induced lymphomas. Oncogene 19: 2780–2785, 2000. 7. Branski LK, Pereira CT, Herndon DN, and Jeschke MG. Gene therapy in wound healing: present status and future directions. Gene Ther 14: 1–10, 2007. 8. Broughton G, 2nd, Janis JE, and Attinger CE. The basic science of wound healing. Plast Reconstr Surg 117: 12S–34S, 2006. 9. Broughton G, 2nd, Janis JE, and Attinger CE. Wound healing: an overview. Plast Reconstr Surg 117: 1e-S–32e-S, 2006. 10. Brown BD, Venneri MA, Zingale A, Sergi Sergi L, and Naldini L. Endogenous microRNA regulation suppresses transgene expression in hematopoietic lineages and enables stable gene transfer. Nat Med 12: 585–591, 2006. 11. Carrington JC and Ambros V. Role of microRNAs in plant and animal development. Science 301: 336–338, 2003. 12. Cave AC, Brewer AC, Narayanapanicker A, Ray R, Grieve DJ, Walker S, and Shah AM. NADPH oxidases in cardiovascular health and disease. Antioxid Redox Signal 8: 691–728, 2006. 13. Chen CZ, Li L, Lodish HF, and Bartel DP. MicroRNAs modulate hematopoietic lineage differentiation. Science 303: 83–86, 2004. 14. Chen CZ and Lodish HF. MicroRNAs as regulators of mammalian hematopoiesis. Semin Immunol 17: 155–165, 2005. 15. Croce CM and Calin GA. miRNAs, cancer, and stem cell division. Cell 122: 6–7, 2005. 16. Cullen BR. Immunology. Outwitted by viral RNAs. Science 317: 329–330, 2007. 17. Dews M, Homayouni A, Yu D, Murphy D, Sevignani C, Wentzel E, Furth EE, Lee WM, Enders GH, Mendell JT, and Thomas-Tikhonenko A. Augmentation of tumor angiogenesis by a Myc-activated microRNA cluster. Nat Genet 38: 1060–1065, 2006. 18. Dunoyer P, Himber C, and Voinnet O. Induction, suppression and requirement of RNA silencing pathways in virulent Agrobacterium tumefaciens infections. Nat Genet 38: 258–263, 2006. 19. Esau C, Davis S, Murray SF, Yu XX, Pandey SK, Pear M, Watts L, Booten SL, Graham M, McKay R, Subramaniam A, Propp S, Lollo BA, Freier S, Bennett CF, Bhanot S, and Monia BP. miR-122 regulation of lipid metabolism revealed by in vivo antisense targeting. Cell Metab 3: 87–98, 2006. 20. Felli N, Fontana L, Pelosi E, Botta R, Bonci D, Facchiano F, Liuzzi F, Lulli V, Morsilli O, Santoro S, Valtieri M, Calin GA, Liu CG, Sorrentino A, Croce CM, and Peschle C. MicroRNAs 221 and 222 inhibit normal erythropoiesis and erythroleukemic cell growth via kit receptor down-modulation. Proc Natl Acad Sci USA 102: 18081–18086, 2005. 21. Fontana L, Pelosi E, Greco P, Racanicchi S, Testa U, Liuzzi F, Croce CM, Brunetti E, Grignani F, and Peschle C. MicroRNAs 17-5p-20a-106a control monocytopoiesis through AML1 targeting and M-CSF receptor upregulation. Nat Cell Biol 9: 775–787, 2007. 22. Fritz JH, Girardin SE, and Philpott DJ. Innate immune defense through RNA interference. Sci STKE 2006: pe27, 2006. 23. Gantier MP, Sadler AJ, and Williams BR. Fine-tuning of the innate immune response by microRNAs. Immunol Cell Biol 85: 458–462, 2007. 24. Garzon R, Pichiorri F, Palumbo T, Iuliano R, Cimmino A, Aqeilan R, Volinia S, Bhatt D, Alder H, Marcucci G, Calin GA, Liu CG, Bloomfield CD, Andreeff M, and Croce CM. MicroRNA fingerprints during human megakaryocytopoiesis. Proc Natl Acad Sci USA 103: 5078–5083, 2006. 25. Georgantas RW, 3rd, Hildreth R, Morisot S, Alder J, Liu CG, Heimfeld S, Calin GA, Croce CM, and Civin CI. CD34+ hematopoietic stem-progenitor cell microRNA expression and function: a circuit diagram of differentiation control. Proc Natl Acad Sci USA 104: 2750– 2755, 2007. 26. Goldberg S, Roy S, Khanna S, and Sen CK. Evidence for the involvement of miRNA in redox regulated angiogenic response of human microvascular endothelial cells. Atheroscler Thromb Vasc Biol 28: 471–477, 2008.

364

C. K. Sen, S. Roy

27. Goodrich JA and Kugel JF. Non-coding-RNA regulators of RNA polymerase II transcription. Nat Rev Mol Cell Biol 7: 612–616, 2006. 28. Gu J and Iyer VR. PI3K signaling and miRNA expression during the response of quiescent human fibroblasts to distinct proliferative stimuli. Genome Biol 7: R42, 2006. 29. Harvey C. Wound healing. Orthop Nurs 24: 143–157; quiz 158–149, 2005. 30. Hatfield SD, Shcherbata HR, Fischer KA, Nakahara K, Carthew RW, and Ruohola-Baker H. Stem cell division is regulated by the microRNA pathway. Nature 435: 974–978, 2005. 31. Healy B. Skin deep. As the body’s largest organ, skin is a powerful yet unappreciated veneer. US News World Rep 139: 66–68, 2005. 32. Kanitakis J. Anatomy, histology and immunohistochemistry of normal human skin. Eur J Dermatol 12: 390–399; quiz 400–391, 2002. 33. Kanzaki LI, Ornelas SS, and Arganaraz ER. RNA interference and HIV-1 infection. Rev Med Virol, 18: 5–18, 2008. 34. Kato M, Zhang J, Wang M, Lanting L, Yuan H, Rossi JJ, and Natarajan R. MicroRNA-192 in diabetic kidney glomeruli and its function in TGF-beta-induced collagen expression via inhibition of E-box repressors. Proc Natl Acad Sci USA 104: 3432–3437, 2007. 35. Khabar KS. Rapid transit in the immune cells: the role of mRNA turnover regulation. J Leukoc Biol 81: 1335–1344, 2007. 36. Kruger J and Rehmsmeier M. RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res 34: W451–W454, 2006. 37. Krutzfeldt J, Poy MN, and Stoffel M. Strategies to determine the biological function of microRNAs. Nat Genet 38 (Suppl): S14–S19, 2006. 38. Krutzfeldt J, Rajewsky N, Braich R, Rajeev KG, Tuschl T, Manoharan M, and Stoffel M. Silencing of microRNAs in vivo with ‘antagomirs’. Nature 438: 685–689, 2005. 39. Kuehbacher A, Urbich C, Zeiher AM, and Dimmeler S. Role of Dicer and Drosha for endothelial microRNA expression and angiogenesis. Circ Res 101: 59–68, 2007. 40. Kuehn BM. Chronic wound care guidelines issued. Jama 297: 938–939, 2007. 41. Lavker RM, Sun TT, Oshima H, Barrandon Y, Akiyama M, Ferraris C, Chevalier G, Favier B, Jahoda CA, Dhouailly D, Panteleyev AA, and Christiano AM. Hair follicle stem cells. J Investig Dermatol Symp Proc 8: 28–38, 2003. 42. Lewis BP, Burge CB, and Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120: 15–20, 2005. 43. Li QJ, Chau J, Ebert PJ, Sylvester G, Min H, Liu G, Braich R, Manoharan M, Soutschek J, Skare P, Klein LO, Davis MM, and Chen CZ. miR-181a is an intrinsic modulator of T cell sensitivity and selection. Cell 129: 147–161, 2007. 44. Lingen MW. Role of leukocytes and endothelial cells in the development of angiogenesis in inflammation and wound healing. Arch Pathol Lab Med 125: 67–71, 2001. 45. Litz J and Krystal GW. Imatinib inhibits c-Kit-induced hypoxia-inducible factor-1alpha activity and vascular endothelial growth factor expression in small cell lung cancer cells. Mol Cancer Ther 5: 1415–1422, 2006. 46. Ma DR, Yang EN, and Lee ST. A review: the location, molecular characterisation and multipotency of hair follicle epidermal stem cells. Ann Acad Med Singapore 33: 784–788, 2004. 47. Mattick JS and Makunin IV. Non-coding RNA. Hum Mol Genet 15 Spec No 1: R17–R29, 2006. 48. Meng F, Henson R, Wehbe-Janek H, Smith H, Ueno Y, and Patel T. The MicroRNA let-7a modulates interleukin-6-dependent STAT-3 survival signaling in malignant human cholangiocytes. J Biol Chem 282: 8256–8264, 2007. 49. Meng F, Wehbe-Janek H, Henson R, Smith H, and Patel T. Epigenetic regulation of microRNA370 by interleukin-6 in malignant human cholangiocytes. Oncogene, 27: 378–386, 2007. 50. Moffett HF and Novina CD. A small microRNA makes a Big difference. Genome Biol 8: 221, 2007. 51. Monticelli S, Ansel KM, Xiao C, Socci ND, Krichevsky AM, Thai TH, Rajewsky N, Marks DS, Sander C, Rajewsky K, Rao A, and Kosik KS. MicroRNA profiling of the murine hematopoietic system. Genome Biol 6: R71, 2005. 52. Moschos SA, Williams AE, Perry MM, Birrell MA, Belvisi MG, and Lindsay MA. Expression profiling in vivo demonstrates rapid changes in lung microRNA levels following lipopolysac-

19 microRNA in Cutaneous Wound Healing

53. 54. 55.

56. 57.

58. 59.

60.

61. 62. 63.

64. 65.

66.

67. 68. 69.

70. 71. 72. 73.

365

charide-induced inflammation but not in the anti-inflammatory action of glucocorticoids. BMC Genomics 8: 240, 2007. Muller S and Imler JL. Dicing with viruses: microRNAs as antiviral factors. Immunity 27: 1–3, 2007. Nicolas M, Wolfer A, Raj K, Kummer JA, Mill P, van Noort M, Hui CC, Clevers H, Dotto GP, and Radtke F. Notch1 functions as a tumor suppressor in mouse skin. Nat Genet 33: 416–421, 2003. O’Connell RM, Taganov KD, Boldin MP, Cheng G, and Baltimore D. MicroRNA-155 is induced during the macrophage inflammatory response. Proc Natl Acad Sci USA 104: 1604– 1609, 2007. O’Donnell KA, Wentzel EA, Zeller KI, Dang CV, and Mendell JT. c-Myc-regulated microRNAs modulate E2F1 expression. Nature 435: 839–843, 2005. Otsuka M, Jing Q, Georgel P, New L, Chen J, Mols J, Kang YJ, Jiang Z, Du X, Cook R, Das SC, Pattnaik AK, Beutler B, and Han J. Hypersusceptibility to vesicular stomatitis virus infection in Dicer1-deficient mice is due to impaired miR24 and miR93 expression. Immunity 27: 123–134, 2007. Perera RJ and Ray A. MicroRNAs in the search for understanding human diseases. BioDrugs 21: 97–104, 2007. Poliseno L, Tuccoli A, Mariani L, Evangelista M, Citti L, Woods K, Mercatanti A, Hammond S, and Rainaldi G. MicroRNAs modulate the angiogenic properties of HUVEC. Blood 108: 3068–3071, 2006. Proweller A, Tu L, Lepore JJ, Cheng L, Lu MM, Seykora J, Millar SE, Pear WS, and Parmacek MS. Impaired notch signaling promotes de novo squamous cell carcinoma formation. Cancer Res 66: 7438–7444, 2006. Racz Z and Hamar P. Can siRNA technology provide the tools for gene therapy of the future? Curr Med Chem 13: 2299–2307, 2006. Raftopoulou M. microRNA signals cell fate. Nat Cell Biol 8: 112, 2006. Randall G, Panis M, Cooper JD, Tellinghuisen TL, Sukhodolets KE, Pfeffer S, Landthaler M, Landgraf P, Kan S, Lindenbach BD, Chien M, Weir DB, Russo JJ, Ju J, Brownstein MJ, Sheridan R, Sander C, Zavolan M, Tuschl T, and Rice CM. Cellular cofactors affecting hepatitis C virus infection and replication. Proc Natl Acad Sci USA 104: 12884–12889, 2007. Ro S, Park C, Young D, Sanders KM, and Yan W. Tissue-dependent paired expression of miRNAs. Nucleic Acids Res 35: 5944–5953, 2007. Roboz GJ, Giles FJ, List AF, Cortes JE, Carlin R, Kowalski M, Bilic S, Masson E, Rosamilia M, Schuster MW, Laurent D, and Feldman EJ. Phase 1 study of PTK787/ZK 222584, a small molecule tyrosine kinase receptor inhibitor, for the treatment of acute myeloid leukemia and myelodysplastic syndrome. Leukemia 20: 952–957, 2006. Rodriguez A, Vigorito E, Clare S, Warren MV, Couttet P, Soond DR, van Dongen S, Grocock RJ, Das PP, Miska EA, Vetrie D, Okkenhaug K, Enright AJ, Dougan G, Turner M, and Bradley A. Requirement of bic/microRNA-155 for normal immune function. Science 316: 608–611, 2007. Ross FP and Christiano AM. Nothing but skin and bone. J Clin Invest 116: 1140–1149, 2006. Roy S, Khanna S, Nallu K, Hunt TK, and Sen CK. Dermal wound healing is subject to redox control. Mol Ther 13: 211–220, 2006. Schouwey K, Delmas V, Larue L, Zimber-Strobl U, Strobl LJ, Radtke F, and Beermann F. Notch1 and Notch2 receptors influence progressive hair graying in a dose-dependent manner. Dev Dyn 236: 282–289, 2007. Segre J. Complex redundancy to build a simple epidermal permeability barrier. Curr Opin Cell Biol 15: 776–782, 2003. Segre JA. Epidermal barrier formation and recovery in skin disorders. J Clin Invest 116: 1150–1158, 2006. Sen CK. The general case for redox control of wound repair. Wound Repair Regen 11: 431– 438, 2003. Sen CK, Khanna S, Babior BM, Hunt TK, Ellison EC, and Roy S. Oxidant-induced vascular endothelial growth factor expression in human keratinocytes and cutaneous wound healing. J Biol Chem 277: 33284–33290, 2002.

366

C. K. Sen, S. Roy

74. Shi Y, Sun G, Zhao C, and Stewart R. Neural stem cell self-renewal. Crit Rev Oncol Hematol’ 65: 43–53, 2008. 75. Smalheiser NR and Torvik VI. Complications in mammalian microRNA target prediction. Methods Mol Biol 342: 115–127, 2006. 76. Soifer HS, Rossi JJ, and Saetrom P. MicroRNAs in disease and potential therapeutic applications. Mol Ther 15: 2070–2079, 2007. 77. Song L and Tuan RS. MicroRNAs and cell differentiation in mammalian development. Birth Defects Res C Embryo Today 78: 140–149, 2006. 78. Sonkoly E, Wei T, Janson PC, Saaf A, Lundeberg L, Tengvall-Linder M, Norstedt G, Alenius H, Homey B, Scheynius A, Stahle M, and Pivarcsi A. MicroRNAs: novel regulators involved in the pathogenesis of Psoriasis? PLoS ONE 2: e610, 2007. 79. Sood P, Krek A, Zavolan M, Macino G, and Rajewsky N. Cell-type-specific signatures of microRNAs on target mRNA expression. Proc Natl Acad Sci USA 103: 2746–2751, 2006. 80. Stenn KS. Molecular insights into the hair follicle and its pathology: a review of recent developments. Int J Dermatol 42: 40–43, 2003. 81. Stern-Ginossar N, Elefant N, Zimmermann A, Wolf DG, Saleh N, Biton M, Horwitz E, Prokocimer Z, Prichard M, Hahn G, Goldman-Wohl D, Greenfield C, Yagel S, Hengel H, Altuvia Y, Margalit H, and Mandelboim O. Host immune system gene targeting by a viral miRNA. Science 317: 376–381, 2007. 82. Strumberg D. Preclinical and clinical development of the oral multikinase inhibitor sorafenib in cancer treatment. Drugs Today (Barc) 41: 773–784, 2005. 83. Suarez Y, Fernandez-Hernando C, Pober JS, and Sessa WC. Dicer dependent microRNAs regulate gene expression and functions in human endothelial cells. Circ Res 100: 1164–1173, 2007. 84. Taganov KD, Boldin MP, and Baltimore D. MicroRNAs and immunity: tiny players in a big field. Immunity 26: 133–137, 2007. 85. Tang G. siRNA and miRNA: an insight into RISCs. Trends Biochem Sci 30: 106–114, 2005. 86. Tili E, Michaille JJ, Cimino A, Costinean S, Dumitru CD, Adair B, Fabbri M, Alder H, Liu CG, Calin GA, and Croce CM. Modulation of miR-155 and miR-125b Levels following Lipopolysaccharide/TNF-{alpha} stimulation and their possible roles in regulating the vresponse to endotoxin shock. J Immunol 179: 5082–5089, 2007. 87. Tomaru Y and Hayashizaki Y. Cancer research with non-coding RNA. Cancer Sci 97: 1285– 1290, 2006. 88. Ushio-Fukai M. VEGF signaling through NADPH oxidase-derived ROS. Antioxid Redox Signal 9: 731–739, 2007. 89. Vauclair S, Nicolas M, Barrandon Y, and Radtke F. Notch1 is essential for postnatal hair follicle development and homeostasis. Dev Biol 284: 184–193, 2005. 90. Weiler J, Hunziker J, and Hall J. Anti-miRNA oligonucleotides (AMOs): ammunition to target miRNAs implicated in human disease? Gene Ther 13: 496–502, 2006. 91. Yang WJ, Yang DD, Na S, Sandusky GE, Zhang Q, and Zhao G. Dicer is required for embryonic angiogenesis during mouse development. J Biol Chem 280: 9330–9335, 2005. 92. Yang Z and Wu J. MicroRNAs and regenerative medicine. DNA Cell Biol 26: 257–264, 2007. 93. Yi R, O’Carroll D, Pasolli HA, Zhang Z, Dietrich FS, Tarakhovsky A, and Fuchs E. Morphogenesis in skin is governed by discrete sets of differentially expressed microRNAs. Nat Genet 38: 356–362, 2006. 94. Yi R, Qin Y, Macara IG, and Cullen BR. Exportin-5 mediates the nuclear export of pre-microRNAs and short hairpin RNAs. Genes Dev 17: 3011–3016, 2003. 95. Zavadil J, Narasimhan M, Blumenberg M, and Schneider RJ. Transforming growth factor-beta and microRNA:mRNA regulatory networks in epithelial plasticity. Cells Tissues Organs 185: 157–161, 2007. 96. Zhao Y, Samal E, and Srivastava D. Serum response factor regulates a muscle-specific microRNA that targets Hand2 during cardiogenesis. Nature 436: 214–220, 2005.

Chapter 20

CpG Island Hypermethylation, miRNAs, and Human Cancer Amaia Lujambio and Manel Esteller*

Abstract The importance of microRNAs (miRNAs) has rapidly increased in molecular biology in recent years due to their key role in several malignancies, including cancer. For this reason, it is crucial to unravel the physiological and disease-related mechanisms of regulation of these small, single-stranded RNAs. In cancer, aberrant DNA hypermethylation of tumor-suppressor genes, global genomic-DNA hypomethylation and disruption of histone-modification patterns are the main epigenetic alterations, and have consequently been widely studied. Some miRNAs are downregulated in cancer and act as bona fide tumor-suppressor genes, and this knowledge has led to the proposal of the hypothesis that miRNAs could be silenced by epigenetic mechanisms in transformed cells. It has recently been shown that miR-127 and miR-124a, two putative tumor-suppressor miRNAs, are methylated in tumor cells. Therefore, epigenomic tools can be effectively used in the search for new methylated tumor-suppressor miRNAs. From a clinical standpoint, this aberrant methylation can be reversed by epigenetic drugs, such as DNA demethylating agents and histone deacetylase inhibitors, restoring miRNA-expression levels and reverting the tumoral phenotype. Now that epigenetics and miRNAs have come together, the expectations are high. Keywords miRNAs, DNA methylation, epigenetics, histone modifications, cancer.

20.1

The Epigenetic Landscape of Healthy Cells

Epigenetics is defined as the inheritance of changes in gene expression without changes in the DNA sequence [16]. The two main epigenetic processes are DNA methylation and histone modifications, and these have critical roles in gene regulation, development, and carcinogenesis [36].

Cancer Epigenetics Laboratory, Molecular Pathology Programme, Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro, 3, E-28029, Madrid, Spain *Corresponding author: Phone: 34-91-2246949; Fax: 34-91-2246923; E-mail: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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In humans, the most widely studied epigenetic modification is the cytosine methylation of DNA that occurs in a CpG dinucleotide context. This process is largely mediated by three DNA methyltransferases (DNMTs) [37]. DNMT3A and DNMT3B are de novo methyltransferases while DNMT1 is the maintenance methyltransferase, which ensures that methylation patterns are transmitted faithfully through each cell division [40]. Around 3–6% of all cytosines are methylated in normal human DNA [18]. Interestingly, CpG sites are roughly depleted in the genome and are asymmetrically distributed, leading to CpG-poor and CpG-dense regions, the latter known as CpG islands [69, 70]. These CpG-rich regions, which are often located in the 5′ end region of almost half of all protein-coding genes, are usually unmethylated in normal cells. However, the majority of the genome is rather CpG-poor due to the mutagenicity of a methylated cytosine that can spontaneously undergo deamination to become a guanine [27]. In general, CpG islands normally remain unmethylated, whereas sporadic CpG sites in the rest of the genome are usually methylated [20]. DNA methylation is used by mammalian cells to maintain an appropriate gene-expression pattern and is involved in the establishment of imprinting and X-chromosome inactivation [14, 37]. Moreover, DNA methylation is required for the germline-specific expression of some genes like those of the MAGE family [5] and the tissue-specific gene silencing in cell types in which they should not be expressed [26]. Furthermore, repetitive genomic sequences are heavily methylated and this could have a role in the protection of chromosomal integrity by preventing translocations, chromosomal instability, and gene disruption through the reactivation of endoparasitic sequences [75]. DNA methylation occurs in the context of other epigenetic modifications. Histones are now recognized as dynamic regulators of gene activity that can undergo many post-translational modifications, including acetylation, methylation, phosphorylation, ubiquitylation, and sumoylation [16, 76]. Some modifications, such as histone acetylation, are associated with active gene transcription, while others, such as the methylation of lysine 9 of histone H3, are an indicator of silenced and condensed chromatin [56]. Overall, histone hypoacetylation and hypermethylation are representative of DNA sequences that are methylated and repressed in normal cells, such as the inactive X chromosome in females, and silenced, imprinted, and tissue-specific genes (Fig. 20.1). However, the “histone code” hypothesis postulates that each specific combination of histone modifications determines the expression status of a particular region of chromatin [62]. For this reason, deciphering this code has become one of the most exciting challenges in the field. Finally, it is essential to clarify the relationship between DNA methylation and histone modifications because the two mechanisms cooperate in controlling gene expression. Thus, there is a precise cross-talk between DNA methylation and histone modifications [2]. DNMTs, histone methyltransferases, histone deacetylases, methyl-cytosine-binding proteins, and many other components are involved in the complexes that ensure this interplay [24, 25, 50]. Taking all this into account, the disruption of the epigenetic patterns of a healthy cell will lead to various dysfunctions, including cancer. For this reason, the knowledge

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Fig. 20.1 DNA-methylation and histone-modification patterns in normal and cancer cells. At the DNA methylation level, hypermethylation of tumor-suppressor genes is a common alteration in transformed cells, leading to transcriptional inactivation and loss of function, contributing to cancer. Also, there is global hypomethylation of repetitive sequences and tissue-specific and imprinted genes, which contributes to genomic instability. At the histone level, in tumor-suppressor genes, acetylation of H3 and H4 lysine residues and trimethylation of K4 of H3 are the main marks, while DNA repeats and heterochromatic regions are characterized by the methylation of K20 and K9 of H3 and trimethylation of K20 of H4. In cancer cells, there is a loss of active histone marks on tumorsuppressor genes and loss of repressive marks in tissue-specific and imprinted genes and repetitive sequences. Black circle: methylated CpG; green circle: acetylation; red circle, methylation

of epigenetic alterations linked to cancer has emerged as one of the most powerful weapons against tumoral cells.

20.2

Epigenetic Contribution to Cancer

Cancer is simultaneously a genetic and an epigenetic disease. In the last 30 years, cancer research has focused on the study of classical oncogenes and tumor-suppressor genes. However, since DNA methylation and histone modifications have entered the scene, epigenetics has been in the spotlight [19]. The most important epigenetic alterations in human cancer are the hypermethylation of tumor-suppressor genes, global DNA hypomethylation, and specific histone changes. The contribution of each alteration to carcinogenesis is highly important, and they all constitute key hallmarks of cancer.

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Aberrant Hypermethylation of Tumor-Suppressor Genes

In cancer cells, the transcriptional silencing of tumor-suppressor genes by aberrant CpG-island-promoter hypermethylation is a significant process (Fig. 20.1), contributing to all the typical hallmarks of a cancer cell arising from the inactivation of tumor-suppressor genes [30]. Thus, genes with critical roles in cancer biology, such as the cell-cycle inhibitor p16INK4a and the DNA-repair genes MLH1 and BRCA1, are repressed by methylation in cancer [18, 33]. By this mechanism of silencing, the expression of these tumor-suppressor genes in the cancer cell can be reduced or abolished, as an alternative to genetic mutation. Tumor-suppressor-gene hypermethylation is itself a common hallmark of all types of human cancer, affecting genes involved in all cellular pathways [18, 33]. Interestingly, each tumor type can be defined by a CpG island hypermethylation profile [13, 21, 54] in a similar way to the characterization enabled by genetic and cytogenetic markers, and this has important diagnostic and prognostic implications. Not all epigenetically silenced genes present genetic mutations [33, 36], so more genes might suffer loss of function through epigenetic modifications than through genetic defects. The precise number of promoter hypermethylated CpG islands in a given tumor has not yet been determined, but preliminary results [3, 22, 38, 54, 68, 78] point to a range of 100–400 genes. These numbers might change as epigenomic studies are carried out across a wider range of tumor types. Furthermore, the recent demonstration that miRNAs with tumor-suppressor behavior can also undergo DNA methylation-associated silencing in tumor cells [45, 61] might indicate an additional contribution of DNA hypermethylation events to cancer development, increasing the potential number of methylated genes in cancer.

20.2.2

Global Genomic Hypomethylation

At the same time that CpG islands become hypermethylated, cancer cell genomes undergo global hypomethylation [16, 18, 33], with a reduction of 20–60% of genomic 5-methylcytosine content compared to their normal counterparts (Fig. 20.1). The drop in DNA methylation could contribute to the large-scale genetic changes that are a feature of tumorigenesis [18]. This loss is accomplished mainly by hypomethylation of the body of the genes (the coding region and introns) and through demethylation of repetitive DNA sequences, which accounts for 20–30% of the human genome. This latter event could promote cancer, allowing chromosome instability and the re-expression of pathogenic sequences [75]. In addition, genes methylated in normal cells can undergo demethylation, giving rise to their inappropriate expression. This aberrant demethylation could account for genes or miRNAs with oncogenic properties, such as let-7-a3 in lung cancer [7].

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Cancer-Linked Histone Changes

So far, little is known about the patterns of histone modification disruption in human tumors. At the single-gene level, promoter CpG-island hypermethylation in cancer cells is accompanied by a particular combination of histone marks: deacetylation of histones H3 and H4, loss of histone H3 lysine K4 trimethylation, and gain of H3K9 methylation and H3K27 trimethylation [3] (Fig. 20.1). It is also known that certain genes with tumor-suppressor-like features, such as p21WAF1, are silent at the transcriptional level in the absence of CpG island hypermethylation, due to the presence of hypoacetylated and hypermethylated histones H3 and H4 [59]. At the genomic level, a profile of histone modifications and their locations for any transformed cell type has recently been assembled. In a considerable number of normal human tissues, cancer cell lines, and primary tumors, the post-translational modifications of histone H4 have been profiled at a global level [23]. In this study, cancer cells were shown to exhibit a loss of monoacetylated and trimethylated forms of histone H4 (Fig. 20.1). Interestingly, these changes appear early and accumulate during the tumorigenic process, as shown in a mouse model of multistage skin carcinogenesis [23]. Mass spectrometry showed these losses to occur predominantly at the acetylated K16 and trimethylated K20 residues of histone H4, and to be associated with the well characterized hypomethylation of repetitive DNA sequences. As has been accepted for global DNA hypomethylation and CpG-island hypermethylation, it seems that the global loss of monoacetylation and trimethylation of histone H4 might be a common hallmark of human tumor cells; these observations have been confirmed in other studies [57, 73]. Some recent papers have shown that genes methylated in cancer cells are specifically packaged with nucleosomes containing histone H3 trimethylated on Lys27. This chromatin mark is established on these unmethylated genes early in development and then maintained in differentiated cell types by the presence of an EZH2-containing Polycomb complex. In cancer cells, the presence of this complex leads to de novo methylation. These results suggest that tumor-specific targeting of de novo methylation is pre-programmed by an established epigenetic system that normally has a role in marking embryonic genes for repression. These findings are consistent with a stem-cell origin for cancer in which reversible gene repression is replaced by permanent silencing, locking the cell into a perpetual state of self-renewal and thereby predisposing it to subsequent malignant transformation [53, 64, 79].

20.3

MicroRNAs and Cancer

As we gain further insight into cancer, new players in the game have been recognized. The most recently identified participants are miRNAs, peculiar molecules with a small size but a big role in cancer.

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miRNAs are small non-coding RNAs, about 22 nucleotides long, that repress gene expression in a variety of eukaryotic organisms [31]. In animals, these small RNAs bind to specific target mRNAs through an almost perfect complementarity with sequences located in the 3′-untranslated region (UTR), inducing translational inhibition or mRNA degradation carried out by the RNA-induced silencing complex (RISC) [4]. miRNAs play important roles in numerous cellular processes such as proliferation, differentiation, apoptosis, and development, by simultaneously controlling the expression levels of hundreds of genes [31]. In cancer, recent studies have shown that miRNA expression profiles are perturbed, leading to the development of various malignancies [43]. Some miRNAs are downregulated while others are overexpressed, suggesting that miRNAs can act as tumor-suppressor genes or oncogenes, respectively [43]. Several studies corroborating this evidence have been published. In 2002, the downregulation of a cluster of two miRNAs, miR-15a and miR-16-1, located in chromosome 13, was closely associated with chronic lymphocytic leukemia (CLL) [9]. Subsequently, the inverse correlation between miR-15a and miR-16-1 expression and BCL2 protein levels revealed that the oncogene was inhibited at the post-transcriptional stage [11]. Other examples of miRNAs with tumor-suppressor features have been described in recent years. It was shown that let-7 expression in lung cancer was lower than that in normal tissues, suggesting a tumor-suppressor role [71]. Thereafter, it was found that let-7 inhibited lung-tumor growth and repressed oncogene Ras, confirming the initial hypothesis [35]. Although miRNA downregulation is more frequent in cancer than miRNA upregulation, these single-stranded RNAs can act as oncogenes by targeting tumor-suppressor genes [28]. In glioblastomas, miR-21 was found to be overexpressed and this miRNA inhibition led to the activation of caspases and cell death in vivo, suggesting a role for miR-21 in malignant glioblastoma through its action on genes involved in apoptosis [10]. The complexity of miRNAs is strikingly illustrated by the case of miR-155, located within the human BIC locus [72]. Either BIC or miR-155 are known to be involved in different malignancies, such as Burkitt’s lymphomas, in which there is a drastic increase in precursor miR-155 levels [49] or B-cell lymphomas, characterized by miR-155 and BIC RNA accumulation [17]. However, the miR-17-92 cluster, also known as OncomiR-1, is the best example of mammalian oncogenic miRNA. Thus, tumors overexpressing this oncomiR present low rates of apoptosis, contributing to the development of cancer [32]. The regulatory circuits involved in the regulation of this cluster have not yet been fully identified, but the preliminary results already indicate the existence of a complex mechanism [28]. Briefly, oncomiR-1 seems to inhibit Myc-induced apoptosis while Myc is simultaneously a transactivator of the miR-17-92 host gene [28]. Moreover, miR-17 and miR-20 target E2F1, a transcription factor with a key role in the cell cycle [51]. Therefore, the correct understanding of miRNA regulation is critical to extending our knowledge of tumorigenesis.

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Epigenetic Tools in the Search for New Tumor-Suppressor miRNAs

The fact that miRNAs act as tumor suppressors in cancer has led to the proposal that they could be aberrantly methylated and silenced in cancer. Therefore, the study of the methylation status of miRNAs could represent a powerful strategy for identifying miRNAs with an important role in cancer. The increasing recognition of the importance of epigenetic changes in cancer pathogenesis has given rise to a shift in the approaches used to identify genes that are affected in this malignancy. The field has moved from studying the effects of silencing on classic tumor-suppressor genes to searching for candidate tumorsuppressor genes on the basis of the hypermethylation of promoter regions. Thus, the discovery of genes that are specifically hypermethylated (and silenced) or hypomethylated (and overexpressed) has provided us with a new set of factors involved in tumor initiation and progression [20]. Different routes may be taken in the search for methylated tumor-suppressor miRNAs. The first one, the pharmacological unmasking of miRNAs, is based on the ability of epigenetic drugs, such as DNA demethylating agents and HDAC inhibitors, to reverse the silencing mediated by DNA methylation and accompanied by inactive histone marks. This treatment forces the release of methylated miRNAs that can be detected by miRNA quantification methods, such as miRNA microarrays and Q-RT-PCR. The miRNAs upregulated after treatment and embedded in a CpG island can be pinpointed using bisulfite genomic sequencing in a given cell line and in normal counterpart tissues (Fig. 20.2A). The second approach relies on a genetic model in which DNA methylation has been erased by disrupting the activity of DNA methyltransferases. As in the case of epigenetic drugs, hypomethylated miRNAs experience increased expression, which can be detected by the previously mentioned methods (Fig. 20.2B). The third approach is an in silico model that uses bioinformatic tools to find miRNAs embedded in CpG islands that might be susceptible to becoming methylated (Fig. 20.2C) [44]. The most convenient technique for studying the methylation status of miRNAs is the bisulfite treatment, which changes unmethylated cytosines to uracils, leaving methylated cytosines unchanged. The combination of this DNA modification and genomic sequencing [12] or amplification by methylation-specific PCR (MSP) [34] has enabled any laboratory to study DNA methylation. More recently developed quantitative techniques, such as the bisulfite treatment followed by MethyLight [15] or pyrosequencing [74], can give results with extremely small samples. Restriction-enzyme-based techniques can also be used [39] although suitable controls are necessary. As some of these methods are restricted to a few CpG sites, the bisulfite treatment followed by genomic sequencing may be considered to be the best alternative. To confirm the histone modifications that are present in the promoter of a given miRNA, the most powerful technique is chromatin immunoprecipitation (ChIP)

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Fig. 20.2 Methods for finding methylated miRNAs in cancer. (A) Pharmacological unmasking. This approach is based on RNA extraction, before and after treatment with a DNA demethylating agent (DAC), followed by miRNA microarray expression analysis. (B) Genetic unmasking. The procedure is similar, unless the starting material, in which a cell line with disrupted DNA methyltransferases is used. (C) In silico unmasking. This method is based on the use of bioinformatic tools to colocalize miRNAs with CpG islands. Additional database information, related to miRNA expression levels in tumors, can be very useful. In the three approaches, bisulfite sequencing is performed in normal and cancer cells

with antibodies against specific histone modifications and subsequent PCR with specific primers against the promoter region of the candidate miRNA gene [52]. By coupling DNA methylation and histone modification studies it is possible to unmask epigenetically silenced miRNAs in cancer. The approaches described above have been used with some variations in the following examples in the search for epigenetically regulated miRNAs in cancer.

20.4.1

Pharmacological Unmasking

In bladder cancer cells, it was observed that 5% of human miRNAs were upregulated after treatment with 5-aza-2′-deoxycytidine, a DNA demethylating agent, and HDAC inhibitor 4-phenylbutyric acid (PBA). Seventeen miRNAs were upregulated by a factor of more than three, and among them, miR-127 was the most

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differentially expressed. This miRNA is embedded in a CpG island and the treatment strongly induced miRNA expression by decreasing DNA methylation levels around the promoter region of the gene, while the proto-oncogene BCL6, a potential target of miR-127, was translationally downregulated after treatment [61]. Moreover, miR-127 is located on chromosome 14q32, a region that is involved in several types of translocations in hematological malignancies and is deleted by LOH in solid tumors [9]. This supports the hypothesis that miR-127 is a bona fide tumor-suppressor gene. This work reveals a miRNA that is methylated in normal and tumoral tissues, i.e., in a tissue-specific manner, and that exhibits tumor-suppressor activity.

20.4.2

Genetic Unmasking

The second approach involves a genetic model, which has been used in three independent studies. All of these used a cell line in which DNMT1 and DNMT3b, the two main DNA methyltransferases, had been disrupted by homologous recombination. These cells showed a drastic reduction of DNMT activity and 5-methylcytosine DNA content leading to a release of gene silencing associated with CpG island hypermethylation [58]. In the first report [45], after comparing the miRNA expression levels in the double knockout cell line (DKO) and its wild type counterpart (HCT116), 18 miRNAs were found to be significantly upregulated. Among them, miR-124a, miR-373, and miR-517c were methylated in cancer cells. On one hand, the latter two miRNAs were also methylated in normal cells, showing tissue-specific methylation in a similar manner to miR-127. On the other hand, miR-124a was unmethylated in normal tissues and specifically methylated in cancer cells, suggesting a tumor-suppressor role [45]. Thus, the epigenetic silencing of miR-124a led to the activation of cyclin D kinase 6 (CDK6), a bona fide oncogenic factor, and the phosphorylation of the retinoblastoma (Rb) tumorsuppressor gene [45]. Besides DNA methylation, it is reasonable to think that miRNA genes will be surrounded by certain histone modifications, because DNA methylation is closely linked to histone modifications through the cross-talk mediated by the transcriptional repressors methyl-CpG-binding domain proteins (MBDs) [45]. Interestingly, miR-124a silencing by DNA methylation was accompanied by the absence of active histone markers, such as acetylation of histone H3, acetylation of histone H4, trimethylation of histone H3-lysine 4, and occupancy by MBDs such as MeCP2 and MBD2 [45]. In addition, these active markers were recovered, and the binding of MBDs was released upon DNA hypomethylation events arose from the genetic disruption of the DNMTs or from pharmacological treatment with DNA demethylating agent (5-aza-2′deoxycytidine) [45]. Some of these results were also confirmed in the miR-127 promoter by chromatin immunoprecipitation studies [61].

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Similar results have been achieved in another study [29] employing the same genetic model. Using the DKO cell line, the expression of about 10% of the miRNAs (13/135) was increased with respect to the wild type cell line, suggesting that this re-expression could be directly or indirectly related to DNA methylation. In contrast, neither 5-aza-2′-deoxycytidine treatment nor deletion of DNMT1 alone recapitulated the miRNA expression profile seen in the DKO cell line, implying that miRNA expression was tightly controlled by DNA methylation and that partial methylation reduction was not sufficient for miRNA re-expression. They found that the two miRNAs with the greatest expression increased in DKO cells, miR-10a and miR-200 (miR-200a and miR-200b share the same CpG island), were methylated in the wild type cell line whilst unmethylated in DKO cells. They also found that HOXA3 and HOXD10 were putative targets of miR-10a, one of the differentially expressed miRNAs that is located in the HOX gene cluster [29]. Unfortunately, they did not measure the methylation status of these miRNAs in normal cells, so it remains unclear whether or not this methylation is exclusive to cancer cells. The different results obtained using apparently the same model could be due to the distinct objectives of the two studies; the first [45] focused on the discovery of miRNAs specifically methylated in cancer cells, while the second [29] was concerned with the contribution of DNA methylation to the regulation of miRNAs. The third example [7] showed that let-7a-3, located on chromosome 22q13.31 and associated with a CpG island, was heavily methylated in normal human tissues but hypomethylated in some lung adenocarcinomas. Hypomethylation of let-7a-3 allowed epigenetic reactivation of the gene and increased the expression of the miRNA in a human lung cancer cell line resulting in an enhanced tumor phenotype and oncogenic changes in transcription profiles. Consistent with that, overexpression of let-7a-3 in lung cancer cells caused deregulation of roughly 200 genes, of which those involved in cell adhesion, proliferation, and differentiation were significantly over-represented, which further strengthened the connection between altered miRNA expression and tumorigenesis.

20.4.3

In Silico Studies

CpG islands are defined as regions of DNA enriched in CpG dinucleotides that can be potentially methylated [69, 70]. It has been proposed that almost 70% of promoters in the human genome are associated with CpG islands [63]. Even the miRNA genes are closely related to CpG islands [7, 29, 45, 61]. Weber et al. [77] found that 155 out of 332 human miRNA genes (47%) were associated with CpG islands. To reach this conclusion, CpG islands were defined as regions of at least 200 DNA base pairs with a G + C content greater than or equal to 55% and an observed:expected CpG ratio in excess of 0.65. In addition, the CpG islands had to be located within 2,000 bp upstream or downstream of the DNA sequence encoding the corresponding miRNA sequence.

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To demonstrate experimentally the methylation status of miRNA gene-associated CpG islands COBRA assays of nine miRNA genes were performed in five cell lines [77]. All the miRNAs showed methylation in some of these cell lines although were unmethylated in the DKO cell line, which was used as a control to check that the bisulfite reaction had taken place correctly and to validate the COBRA analysis. The percentage of methylated miRNA genes was higher than that of protein-encoding genes, indicating that miRNA gene methylation is frequent in human cells [77].

20.5 20.5.1

Applying the Acquired Knowledge Potential Use of miRNAs as Markers

Epigenetic markers, such as DNA methylation of tumor-suppressor genes, are highly interesting from the clinical standpoint, as they can be used for the early detection of cancer or for prognostic purposes [18]. Furthermore, epigenetic techniques, such as methylation-specific PCR, are extremely sensitive, allowing cancer cells to be detected in all types of biological fluids and biopsies [41]. In some cases, such as prostate cancer, a single hypermethylated marker, glutathione S-transferase 1 (GSTP1), is informative in 80–90% of cases [8, 42]. Unfortunately, this is not commonly the case and a large panel is usually necessary. In the majority of cases, a given malignancy is characterized by a unique profile of several hypermethylated CpG islands [13, 21, 54]. In any case, a good DNA methylation marker should be unmethylated in normal ‘healthy’ cells. On the other hand, a tumor suppressor that undergoes methylation-associated silencing is a potential candidate for testing as a predictor of tumor prognosis. For example, death-associated protein kinase (DAPK), p16INK4a, and epithelial membrane protein 3 (EMP3) hypermethylation have been linked to tumor aggressivity in lung, colorectal, and brain cancer patients, respectively [18]. Further candidates awaiting analysis include genes related to increased metastatic potential (such as members of the cadherin and ADAMs families) and angiogenesis (for example, the thrombospondin family). These epigenomic profiles are complementary to profiles of gene-expression patterns and genetic alterations, but have the advantage that they can be assayed using DNA that has been extracted from archived material [18]. The discovery of tumor-suppressor miRNA methylation in cancer enlarges the perspectives of the field. Some miRNAs with tumor-suppressor features and which are aberrantly methylated in cancer could be used for these clinical purposes. miRNA expression profiles have been presented as an alternative to conventional gene-expression profiles with promising results [43]. This suggests that DNA methylation profiles of tumor-suppressor miRNAs could be an excellent tool

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for classifying tumor types and for their early detection. To achieve this, new methylated miRNAs need to be discovered and characterized.

20.5.2

Restoration of miRNA Expression in Cancer

Several studies have established the potential usefulness of miRNA-based therapy in cancer. Some representative examples of this are the induction of apoptosis by miR-15a and miR-16-1 in CLL [11], the inhibition of growth of cancer cells by let-7 [1], the reduced migration and invasion capacities induced by miR-125 in breast cancer cells [65], and the use of anti-miR-21 oligonucleotides (AMOs) to elicit the proapoptotic response in glioblastoma and breast cancer cells [66]. Furthermore, the use of the anti-miR-21 AMO increases susceptibility of colangiocarcinoma cells to gemcitabine [48], which suggests that miRNA-based therapy can be effectively combined with chemotherapy. One of the main obstacles to translating this into effective therapies is the efficiency of delivery of miRNAs/AMOs to the target cells in vivo. Moreover, several side-effects have been described for RNAi. First, immunostimulatory effects, such as the interferon response, may be triggered by both shRNAs and siRNAs [6, 47, 67]. Second, the reintroduced RNAs uses the same cellular factors as endogenous miRNAs, competing for and saturating critical enzymes and protein complexes needed for biogenesis and targeting. Therefore, an alternative method for restoring tumor-suppressor miRNA expression is needed. Thus, epigenetic therapy based on chromatin-modifying drugs such as inhibitors of DNA methylation and HDACs, could be used to reactivate hypermethylated tumor-suppressor miRNAs in cancer. Unlike genetic changes in cancer, epigenetic changes are potentially reversible. In cultured cancer cell lines, it has been possible for years to re-express genes that had been silenced by methylation by using DNA-demethylating agents [46]. When given to patients at low doses, these drugs have shown a significant antitumoral activity, and the US Food and Drug Administration (FDA) has approved the use of two agents, 5-azacytidine and 5-aza-2′-deoxycytidine, as elective treatments for the pre-leukemic disease, myelodysplastic syndrome [46]. On the other hand, HDAC inhibitors are another promising group of agents for the epigenetic therapy of cancer. However, the pleiotropic nature of these inhibitors raises the possibility that their well known abilities to induce differentiation, cell-cycle arrest and apoptosis are accompanied by other, less desirable outcomes. Despite these concerns, many phase-I clinical trials indicate that HDAC inhibitors are well tolerated and, recently, the first drug of this type, suberoylanilide hydroxamic acid (SAHA), has been approved by the FDA for the treatment of cutaneous T-cell lymphoma [46]. The newly discovered link between miRNAs and epigenetics opens up a new seam to be mined for therapeutic targets of cancer. Thus, epigenetic therapy with chromatinmodifying drugs can activate both protein-coding and non-coding genes, including

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miRNAs; that function as tumor suppressors. Activation of tumor-suppressor miRNA genes could subsequently cause downregulation of target oncogenes, as shown for miR-127 and BCL6 [61] and miR-124a and CDK6 [45]. Since the number of miRNA genes is increasing and the expression of many miRNAs is reduced in cancer, there could be a large number of potential targets. Further studies are necessary to verify the possibility that epigenetic regulation of miRNAs by chromatin-modifying drugs can be a novel strategy for prevention and treatment of human cancer.

20.6 The Exciting Present and Promising Future of miRNAs The demonstration of miRNA hypermethylation in tumors considerably expands our knowledge of the human cancer epigenome. The observation that miRNA genes can become aberrantly methylated in tumors adds an additional layer of complexity to the effects of epigenetic deregulation in cancer [77]. The methylation of CpG islands associated with miRNA promoters is an essential mechanism for the regulation of these single-stranded RNAs. Thus, the repertoire of different DNA methylation patterns observed from the study of normal and cancer cells is diverse and resembles that seen in the 5′ regulatory regions of protein-encoding genes [44] (Fig. 20.3). Whether or not miRNA genes become embedded in CpG islands determines the contribution of DNA methylation to the transcriptional status of the miRNA. If they are, miRNAs can be depleted in DNA methylation, either in normal or tumoral tissues (Fig. 20.3A). When the promoter of a miRNA is methylated in normal tissues we can talk about tissuespecific methylation (Fig. 20.3C, D). This methylation can be maintained in cancer (Fig. 20.3C), as in the case of miR-127 [61], or diminished (Fig. 20.3D), as in the case of let-7a-3 [7, 77]. The two cases have a contrary functional significance. miR-127 seems to act as a tumor suppressor and so its methylation is maintained in cancer, while let-7a-3 is thought to act as an oncogene, so its demethylation would contribute to the tumor phenotype. Furthermore, one of the most interesting patterns of DNA methylation known from the biomedical field is the cancer-specific methylation (Fig. 20.3B), exemplified by miR-124a, that is unmethylated in normal tissues and aberrantly methylated in cancer [45]. The study of this latter pattern can help us identify new miRNAs with hitherto unknown tumor-suppressor roles in cancer [45] and will provide us with excellent, new targets for DNA demethylating agents [60, 80]. Epigenetic approaches, such as the bisulfite treatment combined with miRNA microarrays, are a useful tool for discovering new miRNAs with tumor-suppressor properties. Once methylated miRNAs have been described, miRNA methylation profiles could be used for classifying tumors and for the early detection of cancer, expanding the current possibilities. Finally, the restoration of miRNA expression with epigenetic drugs opens up new possibilities for cancer treatment, avoiding the problems that arise from the delivery of miRNAs.

380

Normal cell

-

-

miRNA with CpG island promoter unmethylated A

Cancer cell

B

A

Aberrant CpG island hypermethylation C

B

D

-DNA hypomethylation D

No significant changes

A

Examples

C

No significant changes

Cancer cell treated with DAC

miRNA with CpG island promoter methylated

miR-200c miR-130b

No significant changes

Reactivation

B

C

miR-373 miR-124a

miR-517c

-3

D

let-7-a3

Fig. 20.3 Repertory of different DNA methylation patterns of miRNAs in normal and cancer cells. (A) miRNAs located in a CpG island that is not methylated either in normal or in cancer cells. (B) Cancer-specific methylation. Tumor-suppressor miRNAs, like miR-124a, are unmethylated in normal cells but may undergo methylation in cancer cells. These miRNAs are susceptible to demethylation by DNA demethylating agents, leading to miRNA expression and downregulation of oncogenic targets. (C) Tissue-specific methylation unchanged in cancer cells. The CpG island of the miRNA is methylated in both normal and tumoral cells, such as miR-127. As with cancer-specific methylated miRNAs, these miRNAs can be reactivated by epigenetic drugs. (D) Tissue-specific methylation lost in cancer cells that might be related to oncogenic activity. Black circle: methylated CpG

A. Lujambio, M. Esteller

miR-127

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References 1. Akao Y, Nakagawa Y, Naoe T (2006) let-7 microRNA functions as a potential growth suppressor in human colon cancer cells. Biol Pharm Bull 29:903–906 2. Ballestar E, Esteller M (2002) The impact of chromatin in human cancer: linking DNA methylation to gene silencing. Carcinogenesis 23:1103–1109 3. Ballestar E, Paz MF, Valle L, et al. (2003) Methyl-CpG binding proteins identify novel sites of epigenetic inactivation in human cancer. EMBO J 22:6335–6345 4. Bartel DP (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116:281–297 5. Bodey B (2002) Cancer-testis antigens: promising targets for antigen directed antineoplastic immunotherapy. Expert Opin Biol Ther 2:577–584 6. Bridge AJ, Pebernard S, Ducraux A, et al. (2003) Induction of an interferon response by RNAi vectors in mammalian cells. Nat Genet 34:263–264 7. Brueckner B, Stresemann C, Kuner R, et al. (2007) The human let-7a-3 locus contains an epigenetically regulated microRNA gene with oncogenic function. Cancer Res 67:1419–1423 8. Cairns P, Esteller M, Herman JG, et al. (2001) Molecular detection of prostate cancer in urine by GSTP1 hypermethylation. Clin Cancer Res 7:2727–2730 9. Calin GA, Sevignani C, Dumitru CD, et al. (2004) Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proc Natl Acad Sci USA 101:2999–3004 10. Chan JA, Krichevsky AM, Kosik KS (2005) MicroRNA-21 is an antiapoptotic factor in human glioblastoma cells. Cancer Res 65:6029–6033 11. Cimmino A, Calin GA, Fabbri M, et al. (2005) miR-15 and miR-16 induce apoptosis by targeting BCL2. Proc Natl Acad Sci USA 102:13944–13949 12. Clark SJ, Harrison J, Paul CL, et al. (1994) High sensitivity mapping of methylated cytosines. Nucleic Acids Res 22:2990–2997 13. Costello JF, Frühwald MC, Smiraglia DJ, et al. (2000) Aberrant CpG-island methylation has non-random and tumor-type-specific patterns. Nat Genet 24:132–138 14. Csankovszki G, Nagy A, Jaenisch R (2001) Synergism of Xist RNA, DNA methylation, and histone hypoacetylation in maintaining X chromosome inactivation. J Cell Biol 153:773–784 15. Eads CA, Danenberg KD, Kawakami K, et al. (2000) MethyLight: a high-throughput assay to measure DNA methylation. Nucleic Acids Res 28:e32 16. Egger G, Liang G, Aparicio A, et al. (2004) Epigenetics in human disease and prospects for epigenetic therapy. Nature 429:457–463 17. Eis PS, Tam W, Sun L, et al. (2005) Accumulation of miR-155 and BIC RNA in human B cell lymphomas. Proc Natl Acad Sci USA 102:3627–3632 18. Esteller M (2005) Aberrant DNA methylation as a cancer inducing mechanism. Annu Rev Pharmacol Toxicol 45:629–656 19. Esteller M (2006) Epigenetics provides a new generation of oncogenes and tumor-suppressor genes. Br J Cancer 94:179–183 20. Esteller M (2007) Cancer epigenomics: DNA methylomes and histone-modification maps. Nat Rev Genet 4:286–298 21. Esteller M, Corn PG, Baylin SB, et al. (2001) A gene hypermethylation profile of human cancer. Cancer Res 8:3225–3229 22. Fraga MF, Herranz M, Espada J, et al. (2004) A mouse skin multistage carcinogenesis model reflects the aberrant DNA methylation patterns of human tumors. Cancer Res 64:5527–5534 23. Fraga MF, Ballestar E, Villar-Garea A, et al. (2005) Loss of acetylation at Lys16 and trimethylation at Lys20 of histone H4 is a common hallmark of human cancer. Nat Genet 37:391–400 24. Fuks F, Burgers WA, Brehm A (2000) DNA methyltransferase Dnmt1 associates with histone deacetylase activity. Nat Genet 24:88–91

382

A. Lujambio, M. Esteller

25. Fuks F, Hurd PJ, Wolf D (2003) The methyl-CpG binding protein MeCP2 links DNA methylation to histone methylation. J Biol Chem 278:4035–4040 26. Futscher BW, Oshiro MM, Wozniak RJ, et al. (2002) Role for DNA methylation in the control of cell type specific maspin expression. Nat Genet 31:175–179 27. Gardiner-Garden M, Frommer M (1987) CpG islands in vertebrate genomes. J Mol Biol 196:261–282 28. Hammond SM (2006) MicroRNAs as oncogenes. Curr Opin Genet Dev 16:4–9 29. Han L, Witmer PD, Casey E, et al. (2007) DNA methylation regulates microRNA expression. Cancer Biol Ther (epub ahead of print) 30. Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100:57–70 31. He L, Hannon GJ (2004) MicroRNAs: small RNAs with a big role in gene regulation. Nat Rev Genet 5:522–531 32. He L, Thomson JM, Hemann MT, et al. (2005) A microRNA polycistron as a potential human oncogene. Nature 435:828–833 33. Herman JG, Baylin SB (2003) Gene silencing in cancer in association with promoter hypermethylation. N Engl J Med 349:2042–2054 34. Herman JG, Graff JR, Myohanen S, et al. (1996) Methylation-specific PCR: a novel PCR assay for methylation status of CpG islands. Proc Natl Acad Sci USA 93:9821–9826 35. Johnson SM, Grosshans H, Shingara J, et al. (2005) RAS is regulated by the let-7 microRNA family. Cell 120:635–647 36. Jones PA, Laird PW (1999) Cancer epigenetics comes of age. Nat Genet 21:163–167 37. Kaneda M, Okano M, Hata K, et al. (2004) Essential role for de novo DNA methyltransferase Dnmt3a in paternal and maternal imprinting. Nature 429:900–903 38. Keshet I, Schlesinger Y, Farkash S, et al. (2006) Evidence for an instructive mechanism of de novo methylation in cancer cells. Nat Genet 38:149–153 39. Khulan B, Thompson RF, Ye K, et al. (2006) Comparative isoschizomer profiling of cytosine methylation: the HELP assay. Genome Res 16:1046–1055 40. Klose RJ, Bird AP (2006) Genomic DNA methylation: the mark and its mediators. Trends Biochem Sci 31:89–97 41. Laird PW (2003) The power and the promise of DNA methylation markers. Nat Rev Cancer 3:253–266 42. Lee WH, Morton RA, Epstein JI, et al. (1994) Cytidine methylation of regulatory sequences near the pi-class glutathione S-transferase gene accompanies human prostatic carcinogenesis. Proc Natl Acad Sci USA 91:11733–11737 43. Lu J, Getz G, Miska EA, et al. (2005) MicroRNA expression profiles classify human cancers. Nature 435:834–838 44. Lujambio A, Esteller M (2007) CpG Island hypermethylation of tumor suppressor microRNAs in human cancer. Cell Cycle 6:1455–1459 45. Lujambio A, Ropero S, Ballestar E, et al. (2007) Genetic unmasking of an epigenetically silenced microRNA in human cancer cells. Cancer Res 67:1424–1429 46. Mack GS (2006) Epigenetic cancer therapy makes headway. J Natl Cancer Inst 98:1443–1444 47. Marques JT, Williams BR (2005) Activation of the mammalian immune system by siRNAs. Nat Biotechnol 23:1399–1405 48. Meng F, Henson R, Lang M, et al. (2006) Involvement of human micro-RNA in growth and response to chemotherapy in human cholangiocarcinoma cell lines. Gastroenterology 130:2113–2129 49. Metzler M, Wilda M, Busch K, et al. (2004) High expression of precursor microRNA155/BIC RNA in children with Burkitt lymphoma. Gene Chromosome Cancer 39: 167–169 50. Nan X, Ng HH, Johnson CA (1998) Transcriptional repression by the methyl-CpG-binding protein MeCP2 involves a histone deacetylase complex. Nature 393:386–389 51. O’Donnell KA, Wentzel EA, Zeller KI, et al. (2005) c-Myc-regulated microRNAs modulate E2F1 expression. Nature 435:839–843

20 CpG Island Hypermethylation, miRNAs, and Human Cancer

383

52. O’Neill LP, Vermilyea MD, Turner BM (2006) Epigenetic characterization of the early embryo with a chromatin immunoprecipitation protocol applicable to small cell populations. Nat Genet 38:835–841 53. Ohm JE, McGarvey KM, Yu X, et al. (2007) A stem cell-like chromatin pattern may predispose tumor suppressor genes to DNA hypermethylation and heritable silencing. Nat Genet 39:37–42 54. Paz MF, Fraga MF, Avila S, et al. (2003) A systematic profile of DNA methylation in human cancer cell lines. Cancer Res 63:1114–1121 55. Paz MF, Wei S, Cigudosa JC, et al. (2003) Genetic unmasking of epigenetically silenced tumor suppressor genes in colon cancer cells deficient in DNA methyltransferases. Hum Mol Genet 12:2209–2219 56. Peters AH, Mermoud JE, O’Carroll D (2002) Histone H3 lysine 9 methylation is an epigenetic imprint of facultative heterochromatin. Nat Genet 30:77–80 57. Pogribny IP, Ross SA, Tryndyak VP, et al. (2006) Histone H3 lysine 9 and H4 lysine 20 trimethylation and the expression of Suv4–20h2 and Suv-39h1 histone methyltransferases in hepatocarcinogenesis induced by methyl deficiency in rats. Carcinogenesis 27:1180–1186 58. Rhee I, Bachman KE, Park BH, et al. (2002) DNMT1 and DNMT3b cooperate to silence genes in human cancer cells. Nature 416:552–556 59. Richon VM, Sandhoff TW, Rifkind RA, et al. (2000) Histone deacetylase inhibitor selectively induces p21WAF1 expression and gene-associated histone acetylation. Proc Natl Acad Sci USA 97:10014–10019 60. Saito Y, Jones PA (2006) Epigenetic activation of tumor suppressor microRNAs in human cancer cells. Cell Cycle 5:2220–2222 61. Saito Y, Liang G, Egger G, et al. (2006) Specific activation of microRNA-127 with downregulation of the proto-oncogene BCL6 by chromatin-modifying drugs in human cancer cells. Cancer Cell 9:435–443 62. Sanders SL, Portoso M, Mata J, et al. (2004) Methylation of histone H4 lysine 20 controls recruitment of Crb2 to sites of DNA damage. Cell 119:603–614 63. Saxonov S, Berg P, Brutlag DL (2006) A genome-wide analysis of CpG dinucleotides in the human genome distinguishes two distinct classes of promoters. Proc Natl Acad Sci USA 103:1412–1417 64. Schlesinger Y, Straussman R, Keshet I, et al. (2007) Polycomb-mediated methylation of Lys27 of histone H3 pre-marks genes for de novo methylation in cancer. Nat Genet 39:232–236 65. Scott GK, Goga A, Bhaumik D, et al. (2007) Coordinate suppression of ERBB2 and ERBB3 by enforced expression of micro-RNA miR-125a or miR-125b. J Biol Chem 282:1479–1486 66. Si ML, Zhu S, Wu H, et al. (2007) miR-21-mediated tumor growth. Oncogene 26:2799–2803 67. Sledz CA, Holko M, de Veer MJ, et al. (2003) Activation of the interferon system by shortinterfering RNAs. Nat Cell Biol 5:834–839 68. Suzuki H, Gabrielson E, Chen W, et al. (2002) A genomic screen for genes upregulated by demethylation and histone deacetylase inhibition in human colorectal cancer. Nat Genet 31:141–149 69. Takai D, Jones PA (2002) Comprehensive analysis of CpG islands in human chromosomes 21 and 22. Proc Natl Acad Sci USA 99:3740–3745 70. Takai D, Jones PA (2003) The CpG island searcher: a new WWW resource. In Silico Biol 3:235–240 71. Takamizawa J, Konishi H, Yanagisawa K, et al. (2004) Reduced expression of the let-7 microRNAs in human lung cancers in association with shortened postoperative survival. Cancer Res 64:3753–3756 72. Tam W (2001) Identification and characterization of human BIC, a gene on chromosome 21 that encodes a noncoding RNA. Gene 274:157–167 73. Tryndyak VP, Kovalchuk O, Pogribny IP (2006) Loss of DNA methylation and histone H4 lysine 20 trimethylation in human breast cancer cells is associated with aberrant expression of

384

74.

75. 76. 77. 78.

79. 80.

A. Lujambio, M. Esteller DNA methyltransferase 1, Suv4–20h2 histone methyltransferase and methyl-binding proteins. Cancer Biol Ther 5:65–70 Uhlmann K, Brinckmann A, Toliat MR, et al. (2002) Evaluation of a potential epigenetic biomarker by quantitative methyl-single nucleotide polymorphism analysis. Electrophoresis 23:4072–4079 Walsh CP, Chaillet JR, Bestor TH (1998) Transcription of IAP endogenous retroviruses is constrained by cytosine methylation. Nat Genet 20:116–117 Wang Y, Fischle W, Cheung W, et al. (2004) Beyond the double helix: writing and reading the histone code. Novartis Found Symp 259:3–17 Weber B, Streseman C, Brueckner B, et al. (2007) Methylation of human microRNA genes in normal and neoplastic cells. Cell Cycle 6:1001–1005 Weber M, Davies JJ, Wittig D, et al. (2005) Chromosome-wide and promoter-specific analyses identify sites of differential DNA methylation in normal and transformed human cells. Nat Genet 37:853–862 Widschwendter M, Fiegl H, Egle D, et al. (2007) Epigenetic stem cell signature in cancer. Nat Genet 39:157–158 Yoo CB, Jones PA (2006) Epigenetic therapy of cancer: past, present and future. Nat Rev Drug Discov 5:37–50

Chapter 21

Microarray Profiling of microRNA Changes in Cells That Express HIV-1 Proteins Man Lung Yeung and Kuan-Teh Jeang*

Abstract Mammalian microRNAs (miRNAs) are small RNAs of 18–25 nucleotides (nt) in length that are transcribed from the genome and serve a variety of regulatory functions. Recent studies have verified that miRNAs in addition to playing antipathogen roles in plants and lower eukaryotes also serve important roles in defending mammalian cells against endogenous and exogenous viral infection. In a setting where miRNAs may act to restrict viral infection, it stands to reason that viruses may have a vested interest to change the miRNA expression profile of infected cells. Here, we describe our experience in establishing a microarray for measuring 327 human miRNAs. We illustrate an example whereby this microarray approach was used to measure miRNA changes in human cells transfected to express human immunodeficiency virus proteins.

Keywords HIV, RNAi, Tat, TAR, TRBP

21.1

Introduction

The latest release of the human miRNA database indicates that there are now 678 discretely characterized human miRNAs (http://microrna.sanger.ac.uk/). Current predictions suggest that the human genome may encode 800 to 1,000 miRNAs [4, 5]. MiRNAs are small RNAs of 18–25 nucleotides (nt) in length that regulate developmental timing, signal transduction, apoptosis, cell proliferation and tumorigenesis, amongst other activities [6, 10, 19, 38]. Recent studies indicate that mammalian cellular miRNAs generally function to inhibit [22, 28], and in a rare instance can

Molecular Virology Section, Laboratory of Molecular Microbiology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Building 4, Room 306, 9000 Rockville Pike, Bethesda, MD 20892-0460, USA *Corresponding author: Phone: 301-496-6680; Fax: 301-480-3686; E-mail: KTJ: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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promote [18, 23, 37], virus replication. In turn, mammalian viruses employ a variety of stratagems which include the synthesis of RNA-binding proteins [2, 15, 33] or decoy RNAs [1, 3, 27] to suppress the cell’s anti-pathogen RNA interference (RNAi) defense. MiRNAs in higher eukaryotes function primarily to silence post-transcriptional gene expression through imperfect base-pairing with cognate transcripts. The processing of primary miRNA transcripts by Drosha in the nucleus and pre-miRNAs by Dicer in the cytoplasm have been extensively reviewed elsewhere [12]. While it remains debated what are the gamut of mechanisms used by processed mature miRNA for post-transcriptional gene silencing, some of the proposed miRNA-action include inhibition of translational initiation and sequestration of miRNA-mRNA complexes in ribosome-free cytoplasmic P bodies [17]. MiRNA-mRNA matching is dictated by imperfect sequence base-pairing with require-complementarity largely centered over positions 2 to 8 of a mRNA’s seed sequence [13]. Because its action requires relatively relaxed base complementarity, one miRNA can target multiply different (up to 100) mRNAs [25]. Currently, it is considered that approximately 30% of all human genes are regulated through a miRNA-mediated mechanism [24]. Recent bioinformatics analyses have further suggested that many mammalian viruses are restricted for replication by human miRNAs [35]. The latter finding frames a rationale for why viruses may wish to act in order to alter the cell’s miRNA milieu. The human immunodeficiency virus (HIV) encodes a small highly secondary structured leader RNA, TAR, which is recognized by a viral RNA-binding protein Tat for activated transcription [7]. TAR RNA is processed by human Dicer into a miRNA-guide sequence [20]. Sixteen years ago, a human TAR-RNA-binding protein (TRBP) was identified and was originally suggested to act in regulating the expression of HIV-1 transcripts [11]. Intriguingly, one and one-half decades later, consistent with the finding that TAR is processed as a miRNA, TRBP was discovered to be a critical cellular co-factor used by mammalian Dicer for processing pre-miRNAs into mature miRNAs [9, 14]. Both TAR and Tat when over expressed have been suggested to have RNAi suppressive properties [2, 3, 15], although the specificity of Tat for RNAi–suppression has been questioned [26]. However, recent findings from in vivo infected PBMCs have provided evidence that certain human miRNAs are changed during the natural course of HIV-1 infection [16, 34].

21.2

A Human microRNA Microarray – RAKE Assay

Based on the above results, there is an impetus in HIV-research for achieving an understanding of how miRNA profiles in human cells may be altered by virus infection. Below, we outline in detail, a microarray approach developed in our laboratory to measure rapid changes in the profile of fully processed mature miRNAs human cells.

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The microarray platform we used is called RNA-primed Array-based Klenow Enzyme (RAKE) assay. It was originally described by Nelson and colleagues who detected the mature form of miRNAs without the need of RNA amplification [30]. Purified small RNAs (≤200 nt) are first hybridized with specially designed DNA oligonucleotide probes printed on a microarray glass slide (Fig. 21.1). These probes comprised three different elements: a 3′ anti-miRNA variable element which has a nucleotide sequence that is complementary to a specific miRNA; a poly-thymidine region which allows labeling of hybridized miRNAs through the process of primer extension; a 5′ linker region which provides sufficient spaces for the enzymatic reactions to take place. In addition, a 5′ amino-modified end allows effective linkage of the probe to the slide. In this assay, cognate miRNAs are captured by the 3′ anti-miRNA variable element of the probes. After extensive washing, unhybridized single-stranded DNA probes (ssDNA probes) are digested and removed by exonuclease I. Thereafter, primer extension labeling of the hybridized miRNAs can take place on the poly-thymidines region by the action of Klenow (3′ → 5′ exo) in the presence of biotinylated-dATP. Signal detection is facilitated by addition of streptavidin-Alexa fluor 555 which recognize the biotin group in the polymerized biotinylated-dATPs. It should be noted that a number of different microarray platforms have been reported. Most, if not all, of these platforms require a step of sample amplification which involves addition of linkers on both ends of the sample. However, the enzyme (RNA ligase) used in this step varies in its activity depending on the substrate sequences [31, 32]. This may lead to an inaccurate representation of the original starting population. RAKE, on the other hand, bypasses this problem by skipping the sample amplification step. It is also worth noting that the enzymes (Klenow and exonuclease I) employed in this assay work in an unbiased, substrate sequence-independent way [8]. Unlike most miRNA microarray platforms which have limited power to distinguish precursor from mature miRNAs, the absolute requirement of the 3′ end in the primer extension step of RAKE provides a specificity advantage as many of the mature miRNAs differs from their precursor forms in the 3′ end. Recent identification of the polymorphism of miRNAs, mainly on the 3′ end, raised a sensitivity concern for RAKE and other miRNA-detecting microarray platforms [21, 29, 36]. Perhaps the only way to solve this problem is to perform more labor-intensive, time-consuming direct cloning of miRNAs.

21.3

HIV-1 Alters miRNA Expression Profile in Human Cells

We used the above microarray approach to ask if HIV-1 can alter the expression profile of host cell miRNAs. We compared miRNA profiles in mock-transfected HeLa cells versus HeLa cells transfected with an infectious HIV-1 molecular clone, pNL4-3.

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Fig. 21.1 A schematic representation of the RAKE microarray assay. (A) Small RNAs (≤200 nt) isolated from cells are hybridized to the microarray slide. Cognate miRNA (miRNA1) and its precursor (pre-miRNA1) are then captured by the variable region (anti-miRNA1) of the probes. (B) After washing, unhybridized single-stranded DNA probes (ssDNA probes) are digested by exonuclease I. (C) With the aid of Klenow (3′ → 5′ exo−), addition of biotinylated-dATP to the 3′ OH group of the hybridized mature miRNA1 is facilitated. On the other hand, extra sequence on the 3′ end of pre-miRNA1 prevents the primer extension to occur and hence will not be labeled. (D) Fluorescent labeling of the hybridized miRNA1 can be achieved by addition of StreptavidinAlexa fluor 555 which binds to the biotin group

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Fig. 21.2 Assessment of the sensitivity of the RAKE assay. We determined the sensitivity of RAKE assay by hybridizing different concentration of “spike-in” oligo (ath-miR-157a). Signal intensity from each of the known concentration of “spike-in” oligo was collected and converted into log2 scale. The log2 values are proportional to the “spike-in” oligos concentration at the range of 10−8 to 10−6 M. An estimated minimum detection limit of about 10−7 M was determined. Error bars represent the standard deviation of the values from the four replicated spottings of each probe

We evaluated the sensitivity of our RAKE readout. A typical analysis is shown in Fig. 21.2 which verified that our assay provided a sufficiently robust signal when the miRNA substrate was as low as 10−7 M, and offered linear readouts in log2 scale for substrates in the 10−8 to 10−6 M range. We next compared microarray readouts from small RNAs (20 µg per slide) isolated from mock-transfected HeLa or HeLa cells transfected with infectious HIV-1 molecular clone, pNL4-3 (Fig. 21.3) [39]. Clear differences were seen in comparing mock-transfected HeLa cells to pNL4-3-transfected HeLa cells. Table 21.1 tabulates the quantifications of all of the human miRNAs that were changed by more than two fold between the HeLa-mock and the HeLa-pNL4-3 samples. It is significant to note that ∼43% of all of the miRNAs were more than two-fold downregulated with most of the remaining 57% of miRNAs being largely unchanged in expression level. Only a small handful of human miRNAs were found to be up regulated by viral gene expression. Currently, it is unclear whether this uni-modal direction (down regulated expression) is a result of high viral protein expression due to transfection of

Fig. 21.3 Analysis the miRNA expression profile after transfection of HeLa cells with HIV-1 pNL4-3. A representative experiment comparing the miRNA expression profiles of mock- and pNL4-3-transfected HeLa cells is shown. Each colored block represents the expression of a single miRNA (labeled on the left) in the indicated sample. Signals acquired from the microarray are converted into color (high signal = red; medium signal = black; low/no signal = green). Only miRNAs with greater than two fold changes after comparing with the two samples are shown

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Table 21.1 Changes in human miRNA expression after HIV pNL4-3 transfection Values in log2 (Units) miRNAs

Mock infected HeLa

pNL4-3 transfected HeLa

Fold change

hsa-miR-93 hsa-miR-221 hsa-miR-148b hsa-miR-34a hsa-let-7i hsa-miR-181a hsa-miR-18b hsa-miR-186 hsa-miR-301 hsa-miR-7 hsa-miR-130b hsa-let-7b hsa-miR-196a hsa-miR-126 hsa-miR-128a hsa-miR-107 hsa-miR-26b hsa-miR-17-3p hsa-miR-222 hsa-miR-224 hsa-miR-128b hsa-miR-27b hsa-miR-29b hsa-miR-92 hsa-miR-342 hsa-mir-452 hsa-miR-18a hsa-miR-182 hsa-miR-20b hsa-miR-320 hsa-miR-29c hsa-miR-15b hsa-miR-103 hsa-let-7g hsa-miR-151 hsa-miR-185 hsa-miR-96 hsa-miR-146b hsa-miR-210 hsa-miR-106a hsa-miR-25 hsa-miR-125b hsa-miR-95 hsa-miR-99b hsa-miR-335 hsa-let-7e hsa-miR-194 hsa-miR-183 hsa-miR-497

13.69717 12.29471 12.49783 12.17716 11.65101 10.93157 12.99769 11.34747 11.9391 11.23054 12.41341 13.10612 11.60949 12.31534 11.49703 12.91814 11.86322 11.01943 10.21726 12.22912 10.90223 12.53995 14.19081 12.71245 12.29607 12.19808 12.95946 12.04113 12.06622 11.7551 12.26552 12.76099 13.56076 12.07938 11.32907 10.50798 11.51342 9.437754 10.83302 12.85463 10.05186 12.07991 8.675488 10.71111 11.54034 11.04971 11.71718 10.28429 9.363925

8.422064781 7.383704185 7.592456818 7.513543129 7.169925213 6.686501026 9.066088676 7.426264763 8.092757225 7.459432125 8.682994843 9.451210976 7.97728014 8.744817734 8.033423424 9.49185276 8.51570034 7.754888058 7.066089153 9.095396996 7.800899982 9.481799126 11.15291977 9.679479599 9.280771255 9.209452629 10.03205013 9.174925804 9.306061745 9.014019966 9.525521278 10.06070042 10.88263988 9.473706245 8.768183708 8.011226654 9.060695648 6.988685131 8.392316818 10.45018005 7.651051998 9.702173233 6.303781033 8.339850426 9.172428131 8.754887581 9.426264763 8.046544075 7.139551163

−5.275105219 −4.911005815 −4.905373182 −4.663616871 −4.481084787 −4.245068974 −3.931601324 −3.921205237 −3.846342775 −3.771107875 −3.730415157 −3.654909024 −3.63220986 −3.570522266 −3.463606576 −3.42628724 −3.34751966 −3.264541942 −3.151170847 −3.133723004 −3.101330018 −3.058150874 −3.03789023 −3.032970401 −3.015298745 −2.988627371 −2.92740987 −2.866204196 −2.760158255 −2.741080034 −2.739998722 −2.70028958 −2.67812012 −2.605673755 −2.560886292 −2.496753346 −2.452724352 −2.449068869 −2.440703182 −2.40444995 −2.400808002 −2.377736767 −2.371706967 −2.371259574 −2.367911869 −2.294822419 −2.290915237 −2.237745925 −2.224373837

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HIV-molecular clone into cells. Further verification of profile changes after infection of human peripheral blood mononuclear cells is being conducted. Acknowledgements We also thank Drs. Mourelatos and Le for the discussion of RAKE assay technique and bioinformatics.

References 1. Andersson MG, Haasnoot PC, Xu N, Berenjian S, Berkhout B, Akusjarvi G: Suppression of RNA interference by adenovirus virus-associated RNA. J Virol 2005, 79: 9556–9565. 2. Bennasser Y, Le SY, Benkirane M, Jeang KT: Evidence that HIV-1 encodes an siRNA and a suppressor of RNA silencing. Immunity 2005, 22: 607–619. 3. Bennasser Y, Yeung ML, Jeang KT: HIV-1 TAR RNA subverts RNA interference in transfected cells through sequestration of TAR RNA-binding protein, TRBP. J Biol Chem 2006, 281: 27674–27678. 4. Bentwich I, Avniel A, Karov Y, Aharonov R, Gilad S, Barad O, et al.: Identification of hundreds of conserved and nonconserved human microRNAs. Nat Genet 2005, 37: 766–770. 5. Berezikov E, Guryev V, van de BJ, Wienholds E, Plasterk RH, Cuppen E: Phylogenetic shadowing and computational identification of human microRNA genes. Cell 2005, 120: 21–24. 6. Berkhout B, Jeang KT: RISCy business: MicroRNAs, pathogenesis, and viruses. J Biol Chem 2007, 282: 26641–26645. 7. Berkhout B, Silverman RH, Jeang KT: Tat trans-activates the human immunodeficiency virus through a nascent RNA target. Cell 1989, 59: 273–282. 8. Brody RS, Doherty KG, Zimmerman PD: Processivity and kinetics of the reaction of exonuclease I from Escherichia coli with polydeoxyribonucleotides. J Biol Chem 1986, 261: 7136–7143. 9. Chendrimada TP, Gregory RI, Kumaraswamy E, Norman J, Cooch N, Nishikura K, et al.: TRBP recruits the Dicer complex to Ago2 for microRNA processing and gene silencing. Nature 2005, 436: 740–744. 10. Croce CM, Calin GA: miRNAs, cancer, and stem cell division. Cell 2005, 122: 6–7. 11. Gatignol A, Buckler-White A, Berkhout B, Jeang KT: Characterization of a human TAR RNA-binding protein that activates the HIV-1 LTR. Science 1991, 251: 1597–1600. 12. Gregory RI, Chendrimada TP, Shiekhattar R: MicroRNA biogenesis: isolation and characterization of the microprocessor complex. Methods Mol Biol 2006, 342: 33–47. 13. Grimson A, Farh KK, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP: MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol Cell 2007, 27: 91–105. 14. Haase AD, Jaskiewicz L, Zhang H, Laine S, Sack R, Gatignol A, et al.: TRBP, a regulator of cellular PKR and HIV-1 virus expression, interacts with Dicer and functions in RNA silencing. EMBO Rep 2005, 6: 961–967. 15. Haasnoot J, de VW, Geutjes EJ, Prins M, de HP, Berkhout B: The Ebola virus VP35 protein is a suppressor of RNA silencing. PLoS Pathog 2007, 3: e86. 16. Huang J, Wang F, Argyris E, Chen K, Liang Z, Tian H, et al.: Cellular microRNAs contribute to HIV-1 latency in resting primary CD4(+) T lymphocytes. Nat Med 2007, 13: 1241–1247. 17. Jackson RJ, Standart N: How do microRNAs regulate gene expression? Sci STKE 2007, 2007: re1. 18. Jopling CL, Yi M, Lancaster AM, Lemon SM, Sarnow P: Modulation of hepatitis C virus RNA abundance by a liver-specific MicroRNA. Science 2005, 309: 1577–1581. 19. Kim VN: Small RNAs: classification, biogenesis, and function. Mol Cells 2005, 19: 1–15.

21 Microarray Profiling of microRNA Changes in Cells That Express HIV-1 Proteins

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20. Klase Z, Kale P, Winograd R, Gupta MV, Heydarian M, Berro R, et al.: HIV-1 TAR element is processed by Dicer to yield a viral micro-RNA involved in chromatin remodeling of the viral LTR. BMC Mol Biol 2007, 8: 63. 21. Lagos-Quintana M, Rauhut R, Yalcin A, Meyer J, Lendeckel W, Tuschl T: Identification of tissue-specific microRNAs from mouse. Curr Biol 2002, 12: 735–739. 22. Lecellier CH, Dunoyer P, Arar K, Lehmann-Che J, Eyquem S, Himber C, et al.: A cellular microRNA mediates antiviral defense in human cells. Science 2005, 308: 557–560. 23. Leung AK, Sharp PA: microRNAs: a safeguard against turmoil? Cell 2007, 130: 581–585. 24. Lewis BP, Burge CB, Bartel DP: Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 2005, 120: 15–20. 25. Lim LP, Lau NC, Garrett-Engele P, Grimson A, Schelter JM, Castle J, et al.: Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature 2005, 433: 769–773. 26. Lin J, Cullen BR: Analysis of the interaction of primate retroviruses with the human RNA interference machinery. J Virol 2007, 81: 12218–12226. 27. Lu S, Cullen BR: Adenovirus VA1 noncoding RNA can inhibit small interfering RNA and MicroRNA biogenesis. J Virol 2004, 78: 12868–12876. 28. Meister G: miRNAs get an early start on translational silencing. Cell 2007, 131: 25–28. 29. Neilson JR, Zheng GX, Burge CB, Sharp PA: Dynamic regulation of miRNA expression in ordered stages of cellular development. Genes Dev 2007, 21: 578–589. 30. Nelson PT, Baldwin DA, Scearce LM, Oberholtzer JC, Tobias JW, Mourelatos Z: Microarraybased, high-throughput gene expression profiling of microRNAs. Nat Methods 2004, 1: 155–161. 31. Ohtsuka E, Nishikawa S, Fukumoto R, Tanaka S, Markham AF: Joining of synthetic ribotrinucleotides with defined sequences catalyzed by T4 RNA ligase. Eur J Biochem 1977, 81: 285–291. 32. Romaniuk E, McLaughlin LW, Neilson T, Romaniuk PJ: The effect of acceptor oligoribonucleotide sequence on the T4 RNA ligase reaction. Eur J Biochem 1982, 125: 639–643. 33. Sullivan CS, Ganem D: A virus-encoded inhibitor that blocks RNA interference in mammalian cells. J Virol 2005, 79: 7371–7379. 34. Triboulet R, Mari B, Lin YL, Chable-Bessia C, Bennasser Y, Lebrigand K, et al.: Suppression of microRNA-silencing pathway by HIV-1 during virus replication. Science 2007, 315: 1579–1582. 35. Watanabe Y, Kishi A, Yachie N, Kanai A, Tomita M: Computational analysis of microRNAmediated antiviral defense in humans. FEBS Lett 2007, 581: 4603–4610. 36. Wu H, Neilson JR, Kumar P, Manocha M, Shankar P, Sharp PA, et al.: miRNA profiling of naive, effector and memory CD8 T Cells. PLoS ONE 2007, 2: e1020. 37. Yeung ML, Benkirane M, Jeang KT: Small non-coding RNAs, mammalian cells, and viruses: regulatory interactions? Retrovirology 2007, 4: 74. 38. Yeung ML, Bennasser Y, Le SY, Jeang KT: siRNA, miRNA and HIV: promises and challenges. Cell Res 2005, 15: 935–946. 39. Yeung ML, Bennasser Y, Myers TG, Jiang G, Benkirane M, Jeang KT: Changes in microRNA expression profiles in HIV-1-transfected human cells. Retrovirology 2005, 2: 81.

Chapter 22

microRNA-Associated Therapies Anne Saumet1, Guillaume Vetter2, Nicolas Cougot3, Manuella Bouttier3, Florence Rage3, Khalil Arar4, and Charles-Henri Lecellier3*

Abstract The micro(mi)RNA pathway play crucial roles in the regulation of our genome and is implicated in fundamental aspects of our physiology. Therefore, deregulations of miRNA expression are often associated with human malignancies including cancers, neuronal diseases or viral infections. They can even be considered as excellent diagnostic or prognostic markers. Several biotechnological tools are now available to measure miRNA expression in patient samples and to reproduce or inhibit the miRNA action on translation repression. We present here these different miRNA-based techniques and discuss their potential applications in the clinical management of several human diseases. Keywords microRNA deregulation, cancer, neuronal disease, metabolism, immunity, virus, therapy

22.1

Introduction

The vital function of miRNAs in mammalian biology is illustrated by the observation that disruption of the dicer gene stops the mouse embryo development [9]. In fact, it is now admitted that each cell type produces a specific miRNA repertoire regulating cellular processes as essential as differentiation, proliferation and apoptosis [7].

1

Institut de Genetique Humaine- CNRS UPR1142, 141, rue de la Cardonille, 34396 Montpellier Cedex 5, France 2

University of Luxembourg, 162A, ave de la Faïencerie, L-1511 Luxembourg

3

Institute of Molecular Genetics of Montpellier, CNRS UMR 5535 – IFR 122, 1919 Route de Mende, 34293 Montpellier Cedex 5, France 4

Sigma-Aldrich Proligo, Genopole Campus 1, 5 rue Desbrueres, 91030 Evry cedex, France

*Corresponding author: Phone: 33 (0) 4 67 61 36 54; Fax: 33 (0) 4 67 04 02 31; E-mail: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

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For instance, enforced expression of the miR-181 in hematopoietic progenitors is sufficient to induce B cell maturation [24]. The miR-181, which is strongly upregulated during myoblast differentiation, also participates in establishing the muscle phenotype by repressing the translation of the homeobox protein Hox-A11 (a repressor of the differentiation process) [108]. The miR-223 expression has been implicated in granulopoiesis [42]. Hence, due to the apparent fundamental functions of miRNAs, the idea that mis-regulation of the miRNA repertoire could be linked to oncogenesis rapidly arose and numerous reports now support this proposal. In that sense, miRNAs may represent novel and promising targets of therapeutic strategies. Although no clear evidence for the curative potential of miRNA modulations has been provided yet, current researches are aimed at getting a better understanding of their implication in human diseases and at developing valuable tools to inhibit or reproduce their action. Here, we present possible strategies aimed at exploiting miRNAs in clinical practice and review our current knowledge on their implication in human disorders.

22.2 22.2.1

Materials and Methods Detection of miRNAs for Diagnosis and Prognosis

Determining miRNA profiles might be indicative of the existence or the severity of a particular pathology. Two techniques can be envisaged to measure miRNA expression in patient samples.

22.2.1.1

Quantitative Real-Time PCR

A novel miRNA quantification method has been developed based on a specific Reverse Transcriptase (RT) followed by Polymerase Chain Reaction (PCR) amplification (Fig. 22.1) [23]. Stem–loop RT primers are designed to bind to the 3′ region of miRNA molecules which are reverse transcribed with regular reverse transcriptase. The stem–loop RT primers are better than conventional ones in terms of RT efficiency and specificity. The RT product is quantified using conventional quantitative PCR using miRNA-specific forward primer and a reverse primer complementary to the stem-loop oligonucleotide used for the RT. These miRNA assays are specific for mature miRNAs and can discriminate related miRNAs that differ by one nucleotide. These assays are not affected by genomic DNA contamination. Precise quantification is achieved routinely with as little as 250 ng of total RNA for most miRNAs. This method enables fast, accurate and sensitive miRNA expression profiling and can identify and monitor potential biomarkers specific to tissues or diseases [45, 48, 76, 117, 119].

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Fig. 22.1 Schematic description of the Real-time quantifaction of miRNAs. Real-time quantification of miRNAs includes two steps, stem–loop RT (Step 1) and real-time PCR (Step 2). Stem–loop RT primers are complementary to 6 nucleotides at the 3′ end of a miRNA and are reverse transcribed with conventional reverse transcriptase. The RT product is quantified using quantitative PCR (all available technologies are suitable) that includes a miRNA-specific forward primer, complementary to the 5′ end of the miRNA, and a reverse primer comlementary to the stem-loop RT primer

Example and Brief Procedure: Total RNA are extracted using conventional purification methods. First-strand cDNA synthesis is carried out with 250 ng of total RNAs in 7.5 µl of final volume containing 50 nM stem-loop primer, 1X RT buffer, dNTPs, RT and RNase inhibitor (Fig. 22.1). The mix is incubated in PCR tubes at 16 °C for 30 min, 42 °C for 30 min, 85 °C for 5 min, and then held at 4 °C. Real-Time PCR is next performed and the 10 µl PCR reactions included 2 µl of RT products, 1.5 µM forward primer and 0.7 µM reverse primer. The reactions are incubated at 95 °C for 10 min, followed by 42 cycles of 95 °C for 30 s, 58 °C for 1 min, and 72 °C for 1 min. All reactions are performed in triplicate. The threshold cycle (TC) is defined as the fractional cycle number at which the fluorescence passes the fixed threshold.

22.2.1.2

In Situ Hybridization

After discovery of miRNAs, a major limitation for understanding miRNA function was the difficulty in determining spatial expression patterns. However, two similar approaches for detection of mature miRNAs by in situ hybridization (ISH) have been recently described: one ISH method is based on Locked Nucleic Acid (LNA) oligonucleotide probes (DNA probes) [4, 109, 120, 165], and the second is based on RNA oligonucleotide probes [32, 152]. These methods were used for detection of mature miRNAs in embryos, in tissue sections from embryonic and adult mice, as well as from human brain sections. The LNA-based miRNA ISH method ensures a high degree of sequence specificity from the base-pairing properties of digoxigenin (DIG) or fluorescein-labeled LNA probes. The miRNA ISH using RNA probes, labelled with either fluorescein or 33P (5’ end), uses high-stringency wash conditions based on tetramethylammonium chloride (TMAC) in combination with RNase A treatment to remove unhybridized probe and to generate highly sequence specific conditions. Both methods appear to generate similar results based on the comparison of published expression patterns.

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Example and Brief Procedure: Sections of fresh-frozen tissues are prepared using standard protocols (e.g fixation in 4% paraformaldehyde (PFA), treatment with proteinase K, re-fixation with 4% PFA). Slides are incubated in hybridization buffer for 1–3 h before the addition of the probe (500,000 cpm of 33P-labeled RNA probe or DIG-labeled LNA probe and 1 µg/ml of fluorescein-labeled RNA probe). Slides are then washed in SSC buffer, dehydrated through a graded series of 50–100% ethanol, air dried, and exposed to X-ray film for several days (exposure times can vary depending upon the relative abundance of each miRNA within tissue areas). For the detection of fluorescein-labeled probes, a supplemental step with incubation of slides with an anti-fluorescein antibody is needed.

22.2.2

Pharmacological Modulations of miRNAs

Although no data on curative modulations of miRNAs has been published yet, several leads can be envisaged. One of these is conventional pharmacological treatments. In fact, cellular miRNAs are modulated by diverse stimuli, in particular pharmacological treatments, and are thought to participate in their integration, as illustrated in the cases of human cholangiocarcinoma or acute promyelocytic leukaemia chemotherapies [48, 100]. Hence, miRNA expression could be adjusted by conventional chemotherapies. For instance, Rossi et al. showed that the antineoplastic 5-fluorouracil (5-FU), widely used in clinical practice, was able to specifically modulate miRNA expression in colon cancer cell lines [130]. 19 miRNAs were found up-regulated by 5-FU while the miR-200b, -210 and -224 were found down-regulated [130]. A comparable strategy might be to directly modulate the transcriptional status of miRNA genes. In fact, in cancer, aberrant DNA hypermethylation of tumor suppressor genes, global genomic DNA hypomethylation, and disruption of the histone modification patterns are the main epigenetic alterations [41]. The miRNA genes are no exception and expression profiling of human bladder cancer cells revealed that 17 out of 313 human miRNAs were upregulated more than three-fold by simultaneous treatment with the chromatin-modifying drugs 5-aza-2′-deoxycytidine and 4-phenylbutyric acid [131]. One of these, the miR-127, is embedded in a CpG island and is highly induced after treatment. The miR-127 is usually detectable in normal cells but not in cancer cells, suggesting that, in these cells, it is subject to epigenetic silencing [131]. Other reports showed that the miR-127, as well as the miR-124a, are methylated in tumor cells [91, 92]. Importantly, this aberrant methylation can be reversed by epigenetic drugs, such as DNA demethylating agents and hydroxamic acid histone deacetylase (HDAC) inhibitors, restoring microRNA expression levels and reverting the tumoral phenotype [91]. Using miRNA array analyses, Scott et al. reported rapid alteration of the miRNA levels in response to the potent HDAC inhibitor LAQ824 in the breast cancer cell line SKBr3 [134]. A proapoptotic dose of LAQ824 down-regulated 22 miRNAs while 5 miRNAs were found up-regulated upon 5 h of drug exposure [134].

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In human malignant cholangiocytes, Meng et al. have identified seven miRNAs that were significantly upregulated by the methylation inhibitor 5-aza-2′-deoxycytidine and downregulated by Interleukin-6 (IL-6) [102]. Among those, the miR-370, whose gene is embedded in a CpG island, targets the oncogene mitogen-activated protein kinase kinase kinase 8 (MAP3K8). Overexpression of IL-6 reduced miR-370 expression and restored MAP3K8 expression in vitro as well as in tumor cell xenografts [102]. Interestingly, IL-6 is also able to increase the expression of the oncogenic miR-21 [89]. The corresponding gene is indeed controlled by an upstream enhancer containing two binding sites for the signal transducer and activator of transcription 3. These studies not only showed that IL-6 may contribute to tumor growth by modulation of expression of selected miRNAs, such as miR-370 and miR-21, but also define a mechanism by which inflammation-associated cytokines can epigenetically modulate miRNA expression, a strategy that could find application in miRNA-targeting therapies.

22.2.3

Inhibition of miRNAs

As mature miRNAs are short oligonucleotides, it is difficult to imagine inhibiting a specific miRNA without using Watson-Crick base pairing. Oligonucleotides analogs are the natural choice of therapeutic class to correct the aberrant activity of any miRNA which is involved in a specific disease. These synthetic anti-miRNA oligonucleotides called Antagomirs [79] or AMOS (Anti-miRNA oligonucleotides) [163] are useful tools to specifically inhibit individual miRNAs. Similar to the antisense oligonucleotides, these anti-miRNAs may have the potential to progress into a new class of therapeutic agents. The earliest report of miRNA inhibition using oligonucleotides describes the microinjection of DNA oligonucleotides of the same length and complementary to the target miRNA into Drosophila embryos [13]. Unmodified DNA oligonucleotides were later found to be ineffective as inhibitors of let-7 miRNA in C. elegans, consistent with the known instability of unmodified DNA in vivo [64]. Fully chemically modified oligonucleotides have been shown to be effective inhibitors of both coding and noncoding RNAs in vitro and in vivo [33]. From years of antisense research, a number of nucleoside modifications emerged, which increases binding affinity for RNA. In particular, the addition of chemical groups to the 2’-hydroxyl end has been rather fruitful and a number of derivative oligonucleotides are pursued in clinical development. Therefore, these chemical modifications may also be applicable as therapeutic tools against miRNAs [61]. The potential utility of oligonucleotides anti-miRNAs will depend on whether effective concentrations of oligonucleotides reach the target site of action in vitro and in vivo. Although the naturally occurring antisense phosphodiester oligonucleotides have displayed activities against some targets in vitro [142], they are rapidly degraded when used in vivo. Thus, the key to the future value of oligonucleotides anti-miRNAs resides in the development of modified oligonucleotides.

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There are several modifications that have been used to improve the performances of oligonucleotides (Fig. 22.2): Phosphorotioates, 2’ Ome, morpholino, 2-fluoro (2’-F) and Locked Nucleic Acids (LNAs) were the main modifications used. Another strategy is to prepare mixed-backbone oligonucleotides or second generation of oligonucleotides, capitalizing on the ideal aspects of each type of nucleotide analog.

22.2.3.1

Locked Nucleic Acids (LNA) Modified Oligonucleotides

It has been demonstrated that mixed LNA/DNA oligonucleotides abolished miR-32 and miR-23 functions in Hela cells [84]. The anti-miR-23 used was a gapmer of 4 LNA bases added at each end of the oligonucleotides and the central part were natural phosphodiester bases: 5’-*g*g*a*aatccctggcaatg*t*g*a*t – 3’ (the modified nucleotides are indicated by*). LNAs are characterized by a methylene bridge connecting the 2’-oxygen of ribose with the 4’-carbon of the ribose ring [67]. This bridge results in a locked 3’-endo conformation, reducing the conformational flexibility of the ribose and increasing the local organization of the phosphate backbone. Oligonucleotides containing such locked nucleotides are assembled using conventional phosphoramidite chemistry allowing locked nucleotides to be easily interspersed among standard DNA nucleotides. These chemical modifications increase the stability of nucleic acid duplexes formed between LNAs and other nucleic acids: usually, LNA/DNA duplexes have increased thermal stability (3–8 °C per

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modified base in the oligonucleotide) compared to similar duplexes formed by DNA. This feature allowed the use of LNAs as antisense inhibitors of mRNA translation or to target chromosomal DNA [8]. Orom et al. also demonstrated the efficiency of LNAs in specifically inhibiting microRNA function [113]. They showed that LNA-modified oligonucleotides were able to inhibit exogenously introduced miRNAs with high specificity using a heterologous reporter assay and they further confirmed their ability to inhibit an endogenous miRNA in Drosophila cells, leading to up-regulation of the target protein [113].

22.2.3.2

2’-O-Me Modified Oligonucleotides

The 2’-O-methyl group (2’Ome) is one of the oldest, simplest and most often used modifications of oligonucleotides. The methyl group increases nuclease resistance and improves binding affinity to RNA. Fully modified or Ome/DNA mixed oligonucleotides can be equally used with similar efficiency. In December 2005, Krützfeldt et al. showed that a novel class of chemically engineered oligonucleotides, termed Antagomirs, are efficient and specific silencers of endogenous microRNAs in mice [79]. In this study, the authors designed chemically modified, cholesterolconjugated, single strand RNAs complementary to miRNAs. They synthesised an antagomir directed against the miR-122, an abundant liver-specific miRNA, by using 2’Ome phosphoramidites and by adding a cholesterol molecule to the 3’ end. Intravenous administration of antagomirs resulted in a marked reduction of corresponding miRNA levels in liver accompanied with reduced plasma cholesterol concentration. These findings show that antagomirs are powerful tools to silence specific miRNAs in vivo and may represent a therapeutic strategy to silence miRNAs in human diseases. Likewise, Chan et al. have successfully applied 2’-Omethyl and DNA/LNA mixed oligonucleotides to specifically knockdown the miR-21 in glioblastoma cell lines [21].

22.2.3.3

Others Modifications

The 2’-O-Methoxyethyl (MOE) modified oligonucleotides have higher affinity and specifity to RNA than their 2’-O-Me-analogs [40]. Esau et al. transfected distinct MOE oligonucleotides targeting 86 human miRNAs into cultured human preadipocytes [40]. Following gene expression profiles of five marker genes, they found that the miR-143 was involved in adipocyte differentiation through regulation of ERK protein levels. Kloosterman et al. used morpholino oligonucleotides to inhibit the miR-375 in pancreatic islet development [75]. They introduce a quick and versatile method to interfere with miRNA function during zebrafish embryonic development. Morpholino oligonucleotides targeting the mature miRNA or the miRNA precursor specifically and temporally knock down miRNAs. Morpholinos can block processing of the miRNA precursor and can inhibit the activity of the mature miRNA.

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Other modifications including 2-fluoro (2’-F), as well as phosphorothioate backbone modification can also be envisaged to inhibit miRNAs. Overall, oligonucleotides against miRNAs have the potential to become powerful tools in interfering with miRNA pathways thereby allowing the development of alternative therapies aimed at specifically inhibiting miRNA functions.

22.2.4

Artificial Over-Expression of miRNAs

Several strategies aimed at restoring down-regulated miRNAs are feasible. Among those, the simplest strategy is to directly introduce the miRNA precursor, the Drosha product, into cells. This pre-miRNA will further be processed by Dicer to produce the desired miR/miR* duplex. Although this approach is highly efficient and widely used in vitro, its in vivo application would face all the difficulties linked to the introduction of naked nucleic acids in animals. The 2’ sugar chemical modifications (Phosphorotioates, 2’ O-Me, morpholino, 2-fluoro and LNA) should be considered in order to improve resistance to nuclease degradation and prevent rapid renal clearance from the blood. Hence, to improve the distribution of these pre-miRNAs, strategies initially used with small interfering (si)RNAs might be considered. In fact, systemic delivery of naked siRNAs have been shown to be efficient in mice, wherein the expression of a transgene can be suppressed by synthetic siRNAs and by small-hairpin RNAs transcribed in vivo from DNA templates [99]. Zimmermann et al. have shown that siRNAs, when delivered systemically in a liposomal formulation, can silence the apolipoprotein B (APOB) in non-human primates [176]. APOB-specific siRNAs were encapsulated in stable nucleic acid lipid particles and administered by intravenous injection to monkeys at doses of 1 or 2.5 mg per kg. A single siRNA injection resulted in dose-dependent silencing of APOB messenger RNA expression in the liver 48 h after administration. Biological signs of ApoB depletion (serum cholesterol and low-density lipoprotein levels) were observed 24 h after treatment and lasted for 11 days [176]. Another strategy could be based on the conjugation to peptides, able to improve RNA delivery. For instance, Kumar et al. showed that a short peptide derived from rabies virus glycoprotein (RVG) enables the transvascular delivery of siRNA to the brain of mice [80]. This 29-amino-acid RVG peptide specifically binds to the acetylcholine receptor expressed by neuronal cells. The RVG peptide can be modified by adding nine arginine residues able to bind siRNA. This modification does not alter neuronal cell recognition nor RNAi reaction. RVG-bound siRNAs can be intravenously delivered into mice and are able to trigger RNA silencing within the brain. Importantly, these siRNAs can protect mice against fatal viral encephalitis and do not induce inflammatory cytokines or anti-peptide antibodies [80]. Finally, the development of particular gene therapy vectors encoding miRNAs could be considered. This strategy would benefit all the advances made in gene therapy including cell specificity, long-lasting and stable expression of one or several

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miRNAs. However, it would also meet all its limitations (among those immunity and transcription maintenance) [160]. It is in fact possible to clone the DNA sequence of a miRNA precursor under the control of RNA polymerase II or III promoters. Pol III promoters are usually preferred for the expression of a single miRNA (similarly to short hairpin RNA encoding vectors), while pol II promoters can be used to express one or several clustered miRNAs [38, 88] and our own unpublished data. However, caution should be taken when using small RNA expressing vectors because Grimm et al. showed that overexpression of short hairpin RNAs from Adeno-Associated Virus vectors in mice could saturate the miRNA pathway and cause severe liver toxicity [54]. The limiting factor was identified as being the nuclear karyopherin Exportin-5, shared by the shRNA and the miRNA pathways, which could be saturated by the small RNA over-expression leading to a drop in miRNA production [54]. However, John et al., showed that effective target-gene silencing in the mouse and hamster liver can be achieved by systemic administration of synthetic siRNA without significant changes in the levels of three hepatocyteexpressed miRNAs (miR-122, miR-16 and let-7a) nor an effect on miRNA activity [68]. Thus, controlling intracellular pri-miRNA expression levels will be imperative for the development of miRNA-expressing therapeutic vectors in animals.

22.3

Results and Discussion: microRNAs in Human Diseases

22.3.1

Cancers

22.3.1.1

MicroRNA Expression Profiling Classify Human Cancers

The first evidence of a direct link between miRNAs and human cancer came from the observations that two miRNAs genes, miR-15 and miR-16, are located in a genomic region that is deleted in chronic lymphocytic leukaemia (CLL), and that the expression of these two miRNAs is frequently downregulated in CLL [15]. Further works revealed that many miRNAs are indeed found at chromosomal breakpoints and genomic regions associated with cancer [17, 173]. Likewise, several studies have found that the miR-34a is a direct transcriptional target of the p53 tumour suppressor protein, which is a critical regulator of the cellular response to genotoxic stress [22, 126, 150]. The miR-34 activation can recapitulate elements of p53 activity, including induction of cell-cycle arrest and promotion of apoptosis, whereas loss of miR-34 can impair p53-mediated cell death [22, 126, 150]. Because of their potential implication in cancer, numerous efforts have been made to profile miRNA expression in various cancers such as lymphoma [2, 34, 60, 76, 77, 103, 147], colorectal cancer [34, 69, 104, 158], breast cancer [3, 62, 65, 95, 137, 158], myeloids and lymphoids leukemias [3, 15, 17, 27, 42, 45, 48, 83, 155, 172], prostate cancer [116, 124, 158], lung cancer [59, 69, 148, 158, 169], ovarian cancer [65], and testicular germ cell cancer [159]. To date, miRNA profiling of tumours from different

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origin has shown significantly different miRNA profiles compared with normal cells from the same tissue (Table 22.1). Two extensive miRNA profiling studies using diverse tumours have been realised [90, 158]: a miRNA microarray analysis from solid tumours, including colon, lung, breast, stomach, prostate and pancreatic tumours, allowed the identification of several overexpressed miRNAs that might contribute to the oncogenic phenotype [158]. In a second large-scaled study, the authors performed a systematic expression analysis on human cancers [90]. They found that miRNAs are widely downregulated in tumors cells and that miRNA expression profiles reflect the developmental lineage and differentiation state of the tumours. Furthermore, they were able to classify poorly differentiated tumours based on miRNA profiles, while messenger RNA profiles were not such informative when applied to the same samples [90]. These observations illustrate the diagnostical and the prognostical potential of miRNAs in cancer.

22.3.1.2

Several miRNAs Are Similarly Deregulated in Various Cancers

As miRNAs are vital regulators of gene expression, misregulation of miRNA expression may promote tumour by modulating the functional expression of critical genes involved in cell proliferation and/or survival. For example, a high accumulation of

Table 22.1 Cancer-associated miRNAs (*1): the miR-17-92 cluster contains six miRNA genes, i.e. miR-17, miR-18a, miR-19a, miR-20a, miR-19b-1 and miR-92-1 (*2): a relative high expression of miR-155/BIC in pediatric Burkitt lymphoma is reported by Mezler et al. However, Kluiver et al. demonstrated that compared to Hodgkin’s lymphoma and normal lymphoid tissues pediatric/ young Burkitt lymphoma patients have a low miR-155/BIC expression. (*3): Ma et al. demonstrated that miR-10b is highly expressed in metastatic breast cancer cells and positively regulates cell migration and invasion. (*4): miR-155 was expressed in healthy pancreas but not, or to a lesser extent, in pancreatic endocrine tumours and pancreatic acinar cell carcinomas, whereas in pancreatic adenocarcinomas miR-155 was found to be overexpressed Cancer type

microRNA downregulated microRNA upregu(Tumor suppressor) lated (Oncogene)

References

LEUKEMIAS ALL

B-CLL miR-143 miR-145 miR-15a/16-1 cluster T-cell leukemia

miR-128b miR-204 miR-218 miR-331 miR-181b miR-17-92 cluster (*1) miR-21 miR-92 miR-150 miR-155 miR-106/363 cluster

[162]

[42, 15, 17, 2, 25]

[77] (continued)

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Table 22.1 (continued) Cancer type

microRNA downregulated microRNA upregu(Tumor suppressor) lated (Oncogene)

References

APL (AML3)

miR-181b

miR-15a

[45]

miR-15b miR-16-1 miR-342 let-7a-3 let-7c let-7d miR-107 miR-223 miR-17-92 cluster

[40]

CML TUMORS Malignant lymphoma

miR-17-92 cluster miR-155/BIC

Burkitt lymphoma

miR-155/BIC (*2) miR-143, 145

Breast cancer

miR-10b (*3) miR-17-5p miR-125b miR-143 miR-145

Cholangiocarcinoma

Colorectal cancer

let-7 family miR-133b miR-143 miR-145

Follicular thyroid carcinoma

miR-21 miR-29b miR-146 miR-155/BIC

miR-21 miR-141 miR-200b miR-10a miR-17-92 cluster miR-20a miR-24-1 miR-29b miR-31 miR-96 miR-135b miR-183 miR-197

[148] [55] [34] [71] [140] [103] [70] [2] [57] [2] [150] [60] [89] [130] [94] [150] [63] [3] [5] [32] [98]

[161]

miR-125a

miR-346 miR-21 miR-221 miR-222 miR-18

[49] [26] [21] [101, 102]

miR-195 miR-199a

miR-21 miR-224

[53] [107]

Glioblastoma

miR-128 miR-181 a-c

Hepatocellular carcinoma

miR-200a miR-122a (continued)

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Table 22.1 (continued) Cancer type Neuroblastoma Non-small cell lung cancer

microRNA downregulated microRNA upregu(Tumor suppressor) lated (Oncogene)

References

miR-34a miR-184 let-7 family

[27] [162] [150]

miR-126

Ovarian cancer

miR-199a miR-140 miR-145 miR-125b-1

Pancreatic cancer

Papillary thyroid carcinomas

Pituitary adenomas Prostate cancer

Stomach cancer

miR-15a/16-1 miR-128b miR-125b-1 miR-145 let-7c mir-218-2

Testicular germ cell tumours

miR-21 miR-17-92 cluster miR-155/BIC miR-200b miR-205 miR-210 miR-21 miR-203 miR-205 miR-200a-c miR-141 miR-21 miR-24-2 miR-100 miR-103-1,2 miR-107 miR-125b-1 miR-155/BIC (*4) miR-146b

[141] [159] [63] [54]

miR-181b miR-221 miR-222

[43] [117]

let-7d miR-195 miR-203 miR-223 miR-21 miR-103-2 miR-372

[66]

[150] [79] [122]

[55]

[12] [109] [117] [150] [150]

[151]

miR-373 Thyroid anaplastic carcinomas

miR-30d

[156]

miR-125b miR-26a miR-30a-5p ALL, Acute Lymphoid Leukemia; APL, Acute Promyelocytic leukemia; AML, Acute Myeloid Leukemia; CML, Chronic Myeloid Leukemia; CLL, Chronic Lymphoid Leukemia

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a miRNA that targets a tumour suppressor gene diminishes the expression of this protective factor. In contrast, reduced accumulation of a miRNA that targets the mRNA of a proto-oncogene increases the quantity of the oncogenic protein. The miRNA profiling revealed that, among all miRNAs deregulated in several tumour types, some are similarly deregulated (Table 22.1). For instance, the miR15a-16 cluster, the let-7 family and the miR-143/145 are downregulated in many cancers, whereas the miR17-92 cluster, the miR-21 or the miR-155/BIC are often found upregulated in cancerous tissues. These particular miRNAs are usually found to be located in genomic regions that are amplified (for oncogenic miRNAs), deleted or mutated (for tumour-suppressor miRNAs) in cancers cells [14].

22.3.1.3

Causes of Abnormal miRNA Expression

The causes of deregulations of miRNA expression and/or action observed in tumour cells are only partially known and various abnormalities can explained these deregulations in each tumour type. So far, several mechanisms have been described that may not be exclusive: (i) miRNA loci are frequently found at chromosomal breakpoint and genomic regions associated with cancer. For instance, the miR-15a-16 cluster, located at 13q14.3, a region frequently deleted in B-CLL and pituitary tumours, was shown to be downregulated in the majority of patients with these diseases [12, 15]. The miR-17-92 cluster is located in a genomic region amplified in B-cell lymphomas and lung cancers and is overexpressed in these cancers [59, 147, 159]. (ii) The miRNA expression can also be affected by epigenetic silencing regulation, like methylation or histone-modification losses [131, 134]. (iii) Although miRNA deregulations are often associated with transcriptional deregulation of the corresponding promoter, post-transcriptional deregulations have also been observed [153]. An analysis of gene expression in primary tumours has indicated that the widespread down-regulation of miRNAs observed in cancer is due to a failure of the Drosha processing step [153]. This observation is consistent with the findings that the nuclear processing of the pri-miRNAs by Drosha is antagonised by the pri-miRNA editing by the Adenosine Deaminases Acting on RNA (ADARs) [170]. (iv) The miRNA processing can also be affected by a single point mutation of the miRNA precursor [16]. For instance, Calin et al., identified a germ-line mutation in the miR-16-1-miR-15a primary precursor, which caused low levels of microRNA expression [16]. Importantly, germ-line or somatic mutations were found in 5 of 42 sequenced microRNAs in 11 of 75 patients with CLL, but no such mutations were found in 170 subjects without cancer. (v) The miRNA action can be impaired by the introduction of mutation in the targeted sequence [98]. Mayr et al., have reported that chromosomal translocations previously associated with human tumours disrupt the pairing between the High Mobility Group A2 (Hmga2) mRNA and the let-7 miRNA, promoting anchorage-independent growth [98].

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MiRNAs with Tumour Suppressing Activity

miR15a-16 Cluster Two of the best characterised examples of miRNA with tumour suppressor activity are the miR-15a and miR-16, which are downregulated in the majority of CLL cases [15]. The tumour suppressor activities of theses two miRNAs are supported by the fact that they negatively regulate the expression of the anti-apoptotic BCL2 [27]. Hence, downregulation of miR-15a and miR-16 results in higher BCL2 protein level and, consequently, higher anti-apoptotic activity [27]. The downregulation of miR15a/16 was also described in pituitary adenomas wherein it is inversely correlated with tumour diameter [12]. Let-7 Family Examination of miRNA expression pattern in lung cancers identified a drastic reduction of the let-7 miRNA [148, 169]. Its role as tumour suppressor is supported by experiments showing that let-7 negatively regulates expression of RAS protooncogenes [69]. As reduction of let-7 expression was also found to be associated with other cancers, like colorectal [3, 5] and prostate cancers [116, 124], it will be interesting to determine if impaired let-7 regulation of RAS is also a step required for the development of these cancers as demonstrated for lung cancer [69]. miR143/145 First discovered in adenomatous and cancer stages of colorectal neoplasia [5, 104, 158], the downregulation of miR-143 and miR-145 expression was also found in a large number of other cancers, including breast cancer [158], ovarian cancer [65] and prostate cancer [158, 124, 116]. More recently, the expression of the miR-143 and miR-145 was also found decreased in most of the B-cell malignancies examined, including chronic lymphocytic leukemias (CLL), B-cell lymphomas, Epstein-Barr virus (EBV)-transformed B-cell lines, and Burkitt lymphoma cell lines [2]. The mitogen-activated protein (MAP) kinase ERK5, which promotes cell growth, was identified as a target of the miRNA-143, supporting the classification of this miRNA as tumour suppressor [2]. 22.3.1.5

MiRNAs with Oncogenic Potential

miR-17/92 Cluster The miR-17/92 cluster encodes six distincts miRNAs: miR-17, miR-18a, miR19a, miR-20a, miR-19b-1 and miR-92-1 [114]. The implication of the mir-17/92 in tumour development was first demonstrated in haematopoietic stem cells derived

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from foetal liver of myc transgenic mice [60]. It was shown that co-expression of the miRNA cluster and c-Myc resulted in the accelerated formation of highly malignant lymphomas, indicating, for the first time, that miRNAs can promote oncogenesis [60]. Concomittantly, O’Donnell et al. presented evidences that the transcription factor c-myc regulates the miR-17/92 transcription [110]. The miR-17-5p and miR-20a were shown to downregulate the expression of the E2F1 transcription factor, known to play an essential role in the regulation of cell cycle progression [110, 147]. Interestingly, transcription of the miR-17/92 cluster is also driven by the E2F transcription factor family (E2F1-3), illustrating the complexity of miRNA regulation by autoregulatory feedback loops [145, 166]. Finally, the anti-angiogenic thrombospondin-1 and related proteins, such as connective tissue growth factor (CTGF), were identified as targets of the miR-17/92 cluster [34]. This might illustrate the implication of the miR-17/92 cluster in angiogenesis, which is a fundamental process of tumour growth [34]. miR-21 The miR-21 is highly expressed in numerous cancers like breast cancer [65, 137], B-CLL [45], stomach [158], pancreatic [85, 129], ovarian [65] or lung cancers [169], as well as glioblastoma [21] and cholangiocarcinoma [100]. Inhibition of the miR21 action results in a reduction of both cell growth in vitro and tumour growth in vivo [21, 137]. This reduction is associated with the activation of a caspase-dependent apoptosis, suggesting that the miR-21 functions as an oncogene by inhibiting proapoptotic genes [21, 137]. In that sense, further studies indicate that the tumour suppressor phosphatase PTEN, antagonising the survival or growth pathway, is directly targeted by the miR-21 [101]. In another work, the tumor suppressor tropomyosin 1 (TPM1) was identified as a potential target of the miR-21 [174]. These results may explain why the suppression of the miR-21 can inhibit the breast tumour growth and support the notion that miR-21 functions as an oncogene. miR-155/BIC The up-regulation of the miR-155, which is processed from the non-coding RNA BIC [149], is associated with B cell lymphoma [36, 77, 103], as well as other tumour types including, lung and breast cancers [65, 158, 169]. A transgenic mouse model, overexpressing the miR-155 specifically in B-cells, revealed that miR-155 overexpression first induces preleukaemic pre-B cell proliferation, evident in spleen and bone marrow, and subsequently B-cell malignancies [29]. 22.3.1.6

MicroRNA Profiling Might Aid Cancer Diagnosis and Prognosis

The miRNA expression profiles can be used to classify tumours according to their differentiation state and developmental origin, and may therefore be useful for

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diagnosis and prognosis [31, 90, 158]. Researchers are now using miRNA-signatures to predict favourable prognosis, e.g. high progression risk, poor survival or presence of metastases, and to reduce aggressive therapies [16, 17, 21, 60, 65, 95, 118, 129, 136, 148, 169], as best exemplified by the correlation between let-7 and miR-155 levels of expression (i.e. high miR-155 and low let-7a) and post-operative survival in patients with lung cancer [136, 148, 169]. Bloomston et al. showed that pancreatic cancer may have a distinct miRNA expression pattern that differentiate cancerous pancreas from normal pancreas and chronic pancreatitis [11]. They identified 15 overexpressed and 8 underexpressed miRNAs that can be used to distinguish pancreatic cancer from chronic pancreatitis [11]. Similarly, a subgroup of six miRNAs (miR-339, miR-409-3p, miR-483, miR-494, miR-497 and miR-96) distinguishes long- and short-term survivors [11]. Another example of miRNA-based prognosis is provided by CLL. As the prognosis of most cases of CLL is relatively good, treatment after diagnosis is started only if poor prognosis markers are evident (e.g. high expression levels of ZAP70 and absence of mutations in the immunoglobulin heavychain variable-region gene (IgVH)) [16, 17]. Comparing miRNA profiles in three types of CLL (indolent CLL, aggressive CLL, and aggressive CLL associated with 11q deletion), Calin et al. observed that a unique signature of 13 miRNAs (miR-15a, miR-195, miR-221, miR-23b, miR-155, miR-223, miR-29a-2, miR-24-1, miR-29b-2, miR-146, miR-16-1, miR-16-2, miR-29c) discriminates the prognosis of CLL (good or bad prognosis and presence or absence of disease progression) [16, 17]. Specific miRNAs signatures were also characterised in breast cancer which correlated with specific breast cancer biopathologic features, such as estrogen and progesterone receptor expression, tumor stage, vascular invasion or proliferation index [65]. Moreover, it was recently demonstrated that the miR-10b initiates tumour invasion and metastasis of breast cancer [95]. The miR-10b is highly expressed in metastatic breast cancer cells wherein it is thought to positively regulates cell migration and invasion [95]. Moreover, overexpression of miR-10b in non-metastatic breast tumours is sufficient to initiate robust invasion and metastasis [95].

22.3.2

Neuronal Diseases

22.3.2.1

Contribution of miRNAs in Brain Physiology

Several miRNAs specifically expressed in brain have been characterised [81, 135] and there is now an increasing number of studies showing the importance of miRNA pathway in brain development, neuronal maturation, and synapse development [50, 78, 105, 135]. For instance, the miR-124 is one of the most conserved and abundant brain specific miRNA [82]: its expression is neuron specific and increases during neural development [78, 105, 140]. Three possible targets were identified. The first factor identified was Small C-terminal domain phosphatase 1 (SCP1) [157]. This factor is an anti-neural factor expressed in non neuronal cells which is recruited to the neural genes and repress their expression [171]. Another study identified laminin

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γ1 and integrin β1 as miR-124 targets. Both proteins are highly expressed by neural progenitors but repressed upon neuronal differentiation [18]. In these three cases, miR-124 appears to block translation in neurons allowing differentiation to occur. Interestingly, it has also been shown that the expression of miR-124a, a member of this family, can be repressed by transcriptional repressor from the REST family [28]. This family of protein can bind 23 bp sequences on the target genes in non neuronal cells and inhibit their transcription through the recruitment of histone deacetylases. Thus, the process of neuronal differentiation seems to involve derepression of REST-regulated genes and posttranscriptional downregulation of non-neuronal transcripts by a miRNA that is also under the control of REST [28]. The let-7 miRNA, which is composed of 12 precursor genes encoding nine mature miRNAs, is also highly expressed in mouse brain and other primates [82, 105]. The potential role of let-7 in mouse brain has been addressed [167]: using in situ hybridization, the authors showed that let-7 shares similar properties with already described brain specific mir-124 and also that its processing is required for normal differentiation. However, its target mRNAs in these cells remain to be determined. The miR-128 was identified by cloning methods and described as a brain specific miRNA in mouse [82]. Two recent studies gave a more precise view of its possible role [74, 140]. First, a biochemical approach was developed to investigate the potential involvement of miRNAs in synaptic tagging [74]. Among miRNAs cloned from rat cerebellum, the miR-128 was found highly expressed in the cortex and cerebellum. By cell fractionation and density gradient, the authors showed that the miR-128 co-precipitates with polysomes and with mRNPs but was excluded from RNA granules. Interestingly, this study also showed that some miRNAs including miR-128 are highly expressed during neuronal differentiation. This allowed the authors to suggest that miR-128 could be involved in regulation of translation of mRNAs which are required for neuronal differentiation [74]. Another group has confirmed the potential role of miR-128 in neuron differentiation [140]. Using a reporter mRNA in which the target sequence of miR-128 was added in the 3’UTR of eGFP coding sequence, they showed that the miR-128 was inactive in astrocytes but four times more active in differentiated neurons [140]. Future work will certainly focus on the identification of miR-128 targets and on stimuli leading to the activation of this miRNA. The molecular function of miR-134 in brain was recently described [133]. Schratt et al., have shown that the miR-134 expression is restricted to the brain and that it increases when synaptic maturation occurs [133]. By in situ hybridization, the authors showed that the miR-134 accumulates in dendrites of rat neurons where it regulates the size of dendritic spines and controls neuronal plasticity via inhibition of Limk1 mRNA translation [133]. This study suggests a direct role for miR-134 in the transport of translationally repressed Limk1 mRNA to the dendritic spine and provides evidence for a molecular role of miRNA in local translation. In line with this, it has recently been shown, in Drosophila, that miRNAs can be transported in granules called processing bodies (P-bodies) together with their target mRNA [6]. These cytoplasmic foci are implicated in translation repression of messenger RNAs via the miRNA pathway [86, 120]. The observation that repressed mRNA can be

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released from these structures in somatic cells [10] and their presence in dendrites might be linked to the functions of the miR-134 in neurons.

22.3.2.2

miRNAs and Neuronal Diseases

The examples described above substantiate the crucial roles of miRNAs in different nervous processes. Their implication in neuron maturation or synaptic activation make them pivotal in neuronal pathologies. Human brain diseases related to impairment of consciousness, intellect, mood and memory can be subdivided into two groups: (i) diseases of nervous system’s development such as mental deficiency, autism, schizophrenia; and (ii) neurodegenerative diseases, such as Alzheimer’s and Parkinson’s diseases. The putative contribution of miRNAs in brain disorders might be illustrated by the findings that Dicer-deficient neurons slowly die in a manner similar to what is seen in human neurodegenerative disorders [132]. Several studies have now more accurately implicated miRNAs in neuronal pathologies. Alzheimer’s disease (AD) is a neurodegenerative disease that is found in people over 65, in its most common form. Approximately 24 million people worldwide have dementia of which the majority (~60%) is due to Alzheimer’s [44]. The molecular causes of Alzheimer’s are not precisely known. Some dominant mutations in different genes have been identified that account for the small number of cases of familial early-onset AD. Most cases of familial AD are caused by mutations in the Presenilin1 (PS1) gene. PS1 is a transmembrane protein localized to internal cell membranes and is involved in processing amyloid ß (Aß) precursor protein to produce Aß. Krichevsky et al. have shown that the miR-9 and miR-131 expression was reduced in the forebrains of embryonic E17.5 PS1-deficient mice [78]. Putative targets of these microRNAs are implicated in important neuronal functions. For example the miR-131 modulates the expression of calcineurin (a major phosphatase of the central nervous system) involved in a variety of neuronal signaling cascades [175]. Recently, Lukiw has observed alteration in the abundance of several miRNAs in Alzheimer hippocampus compared to fetal and normal aging hippocampus, including the miR-9, miR-124a, miR-125b and miR-128 expression [93]. Parkinson’s disease is a degenerative disorder of the central nervous system that often impairs the motor skills and speech. Recently, a number of specific genetic mutations causing Parkinson’s disease have been discovered [96]. The symptoms of Parkinson’s disease result from the loss of dopaminergic cells in the pars compacta region of the substantia nigra. Kim et al. have identified the miR133b as specifically enriched in the midbrain dopamine neurons and they have revealed that the midbrain of Parkinson’s patients lacked this particular miRNA [73]. Moreover, they showed that the Pitx3 transcription factor induces the expression of the miR-133b which in turn inhibits PitX3 expression and that this negative feedback loop regulates dopaminergic neuron differentiation [73]. Schizophrenia is a psychiatric diagnosis that describes a mental illness characterized by impairment of the perception or expression of reality, most commonly

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manifesting as auditory hallucinations, paranoid or bizarre delusions or disorganized speech and thinking in the context of significant social or occupational dysfunction. It is now suspected that non-coding RNAs could be involved in schizophrenia [128]. Some of the most consistent pathological findings in schizophrenia includes abnormal cyto-architecture, left-right asymmetry of brain hemispheres [58] as well as reductions in dendritic spine density and the number of synapses [51, 52]. With the current knowledge that miRNAs are involved in all these processes (see above the miR-134 and let-7) and that alterations in the interactions between miRNAs and their targets may form a potent source of phenotypic variation, brain-expressed miRNAs qualify as candidate genes for schizophrenia. In line with this idea, altered miRNA profiles were observed in postmortem prefrontal cortex from schizophrenia patients [119]. Tourette’s syndrome (TS) is an inherited neurological disorder with onset in childhood, characterized by the presence of multiple physical (motor) tics and at least one vocal (phonic) tic. One of the TS-associated proteins, SLITRK1, can bind extracellular signaling molecules and affects the growth of neurons. SLITRK1 is expressed in specific regions of the brain known to be affected in TS. Albeson et al. have found that one patient presenting TS exhibits a mutation in the 3’UTR of SLITK1 gene that corresponds to the predicted binding site of the miR-189 [1]. This mutant variant was not present in over than 3,600 control chromosomes [1]. Luciferase assays showed that the miR-189 significantly represses the expression of luciferase gene fused to SLITK1 3’UTR. Moreover, in situ hybridization demonstrates that expression of slitrk1 mRNA overlaps with miR-189 in the neuro-anatomical circuits commonly implicated in the TS [1]. Spinal Muscular Amyotrophy (SMA) is caused by deletions or loss-of-function mutations in the Survival of Motor Neuron (SMN) protein. This protein is part of a large ribonucleoprotein complex that contains numerous miRNAs, called miRNP [106]. Dostie et al. characterized several miRNAs associated with miRNPs isolated from neuronal cells [35]. Gemin3 and Gemin4 are also components of the miRNP complexes and it is thought that deletion or loss-of-function mutations of SMN in SMA also affect the activity of miRNPs due to possible redistribution or changes in the levels of Gemin3 and Gemin4 [35]. Thus, it is possible that specific or general changes in the activity of the miRNPs play a role in the development of SMA. In addition, the authors identified 53 novel miRNAs conserved from mouse to human neuronal cell lines, suggesting a potential role of these specific miRNAs in neurons [35]. A change or mutation in the fragile X mental retardation 1 (FMR1) gene, located on the X chromosome, causes the fragile X syndrome. This gene appears in three forms that are defined by the number of repeats of a pattern of DNA called CGG repeats. Individuals with over 200 repeats have a full mutation responsible for the fragile X syndrome. The full mutation causes transcriptional silencing of the FMR-1 gene and abolishes the production of the corresponding protein FMRP [47]. In mammalian cells, FMRP associates with Argonaute 2 (Ago2) and miRNAs [19, 20]. FMRP could play a crucial role in the regulation of miRNA-mediated protein translation [122, 123].

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Taken as a whole, these results clearly implicate miRNAs in neuronal disorders. Therefore they might be considered as valuable targets for therapeutic strategies.

22.3.3

Metabolism

The miRNA pathway is implicated in crucial steps of physiology and metabolism regulation. Implicitly, deregulation of vital miRNAs might contribute to metabolism disorders and miRNAs could also be considered as attractive therapeutic targets for metabolic diseases.

22.3.3.1

miRNAs and Lipid Metabolism

The first report suggestive of a role of miRNAs in metabolism came from experiments performed in Drosophila: testing existing collections of P element insertion lines for their ability to enhance a small-eye phenotype, Xu et al. observed that depletion of the miR-14 resulted in increased levels of triacylglycerol and diacylglycerol while the opposed phenotype was observed when the expression of the miR-14 was augmented [168]. Another example was provided by Teleman et al. who showed that miR-278-deficient flies have elevated insulin production and elevated circulating sugar, mobilized from adipose-tissue glycogen stores. [151]. In mammals, bioinformatics analyses have been used to dissect a potential role of miRNAs in the functions of pre-adipocytes and adipocytes. Hackl et al. performed high-throughput analyses of the 3’ UTR from ESTs expressed in pre-adipocyte cell line [56]. Studies of hundreds of ESTs showed that more than 70% of differentially expressed genes could be regulated by miRNAs. In fact, Esau et al. characterised a role for the miR-143 in adipocyte differentiation [40]: the level of this particular miRNA increases in differentiating adipocytes, and, accordingly, inhibition of miR-143 inhibits adipocyte differentiation. Likewise, the inhibition of the liver-specific miR-122 in the adult liver results in reduced plasma cholesterol levels, increased hepatic fatty-acid oxidation, and a decrease in hepatic fatty-acid and cholesterol synthesis rates [39]. Upon miR-122 inhibition, the RNA transcripts of many key genes regulating lipid metabolism were down-regulated. Among those, the ACC2 gene reduction correlated with increased fatty acid oxidation and decreased fatty acid and sterol synthesis [39]. The activity of the AMPK enzyme, promoting adenosine triphosphate-generating pathways such as fatty acid oxidation and inhibiting energy storage pathways such as fatty acid synthesis, increased more than two fold. [39]. The inhibition of the miR-122 in a diet-induced obesity mouse model resulted in decreased plasma cholesterol levels as well as a significant improvement in liver steatosis, accompanied by reductions in several lipogenic genes [39]. This phenotype was also obtained with a similar strategy by another laboratory [79]. In that later case, the lower cholesterol

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level was attributed to the reduced level of 3-hydroxy-3-methylglutaryl coenzymeA reductase, the rate limiting enzyme of the cholesterol biosynthesis pathway. Hence, it appears that the miR-122 is a key regulator of cholesterol and fatty-acid metabolism in the adult liver [39, 79]. These fundamental functions of miRNAs in lipid metabolism make them attractive candidates for novel therapeutic interventions aimed at regulating adipocyte biochemistry.

22.3.3.2

miRNAs and Diabetes

The miRNAs are implicated in the biology of pancreatic endocrine cells and the secretion of insulin. The miR-375 has been specifically characterised as an isletspecific miRNA [125]. The overexpression of this miRNA suppresses glucoseinduced insulin secretion, and conversely, inhibition of miR-375 function enhances insulin secretion. The miR-375 targets the Myotrophin (Mtpn) mRNA and inhibition of Mtpn by RNA interference recapitulates the effects of miR-375 on glucosestimulated insulin secretion and exocytosis [125]. In accordance with these results, using morpholino oligonucleotides targeting the mature miRNA or the miRNA precursor during zebrafish embryonic development, Klooterman et al. knocked down 13 miRNAs conserved between zebrafish and mammals. They observed that knockdown of miR-375 causes defects in the morphology of the pancreatic islet [75]. Another miRNA has been implicated in the biology of insulin-secreting cells: Plaisance et al. showed that overexpression of the miR-9 in insulin-secreting cells causes a reduction in exocytosis elicited by glucose or potassium. The miR-9 diminishes the expression of the transcription factor Onecut-2 and, in turn, increases the level of Granuphilin/Slp4, a Rab GTPase effector that exerts a negative control on insulin release [121]. Importantly, silencing of Onecut-2 by RNA interference increases Granuphilin expression and mimics the effect of miR-9 on stimulus-induced exocytosis [121]. In addition, to assess the overall contribution of miRNAs to pancreatic development, Lynn et al. conditionally deleted the dicer1 gene early in pancreas development [94]. Dicer null animals displayed gross defects in all pancreatic lineages and the number of endocrine cells, in particular the insulin-producing beta-cells, was particularly reduced, implicating miRNAs in pancreas development and in beta-cell formation [94]. Diabetic nephropathy (DN) is the most common cause of kidney failure in patients with diabetes. This pathology is associated with the accumulation of extracellular matrix proteins such as collagen 1-alpha 1 and -2 (Col1α1 and -2). The over-expression of Col1α1 and -2 is induced by the transforming growth factor beta1 (TGF-beta) through the decrease of two E-box repressors, deltaEF1 and Smadinteracting protein 1 (SIP1) [72]. SIP1 is in fact a target of the miR-192, a miRNA highly expressed in the kidney whose expression is induced by the TGF-beta [72]. Importantly, the miR-192 expression level is significantly enhanced in glomeruli isolated from streptozotocin-injected diabetic mice or diabetic db/db mice, while, in the same models, the expression levels of TGF-beta and Col1α2 increased [72].

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These studies indicate that miRNAs might be valuable targets of therapies aimed at controlling the secretion of insulin, including in the case of diabetes.

22.3.4

miRNAs, Immunity and Viral Infections

22.3.4.1

miRNAs as Regulators of Immunity

It is now admitted that the miRNA pathway is involved in the fine-tuning of innate immune responses [46]. For instance, Taganov et al., have observed that, in human monocytes, a cell type essential for the establishment of an efficient immune response, the miR-146a/b, miR-132, and miR-155 are endotoxin-responsive genes [146]. In particular, they found that the miR-146a and miR-146b are induced by a variety of microbial components and proinflammatory cytokines and that these miRNAs repress the translation of the TNF receptor-associated factor 6 as well as the IL-1 receptor-associated kinase 1, two key adapter molecules downstream of Toll-like and cytokine receptors. In addition, Rodriguez et al. have shown that mice deficient for the miR-155 are immunodeficient and display increased lung airway remodeling [127]. The miR-155 is required for the function of B and T lymphocytes as well as dendritic cells [127]. Together, these studies demonstrate that miRNAs play a key role in the homeostasis and function of the immune system. Their therapeutic regulation (e.g. inhibition of the miR-146a/b or over-expression of the miR-155) could potentiate the defense response and therefore be pivotal for the eradication of a given pathogen.

22.3.4.2

miRNA-Encoded Viruses

Among human pathogens, viruses are obligatory intracellular parasites and many, if not all, cellular pathways are hijacked during their replication. The miRNA pathway is no exception since several studies have now reported the existence of a complex interplay between several unrelated viruses and miRNAs. First, virusencoded miRNAs have been characterised for DNA viruses, which replicates in the nucleus, such as Herpesviruses (as Kaposi sarcoma herpesvirus, mouse gammaherpesvirus, human cytomegalovirus), Polyomaviruses (Simian Virus 40, Simian Agent 12) and Adenovirus [30]. The nuclear replication step seems to be mandatory for the generation of these viral miRNAs as it allows the processing by the nuclear RNase III Drosha. This viral mimicry is illustrated by the findings that some viral miRNAs can be considered as orthologs of their cellular counterparts [138]. Of note, one group have identified a miRNA encoded by the Human Immunodeficiency Virus type 1 (HIV-1) in persistently infected cells [111, 112]. The requirement of the nuclear step during the viral life cycle implies that the production of miRNAs by RNA viruses or cytoplasmic DNA viruses is very unlikely and experimental

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efforts to identify virus-encoded miRNAs in cells infected with such viruses support so far this supposition. The viral miRNAs are able to target both cellular and viral messengers. For instance, the SV40 miRNA mediates the degradation of the perfectly complementary transcript encoding the viral large T antigen [144]. The control of expression of a viral protein by a viral miRNA is thought to help the virus to escape the immune response, notably the cytotoxic T cells, by limiting the production of viral antigens [144]. Similarly, the Epstein-Barr virus (EBV) encodes the BART miRNAs which target the 3’ UTR of the EBV LMP1 mRNA and negatively regulate LMP1 protein expression. The LMP1 protein is believed to be a key factor in the development of nasopharyngeal carcinoma [87]. On the other hand, some cellular mRNAs have also been reported as targeted by viral miRNAs. The latency-associated transcript (LAT) of herpes simplex virus-1 (HSV-1) encodes a miRNA, miR-LAT, which exerts an anti-apoptotic effect by the downregulation of transforming growth factor (TGF)-beta 1 and SMAD3 expression, both of which are functionally linked to the TGF-beta pathway [55]. The authors proposed that the miR-LAT might contribute to the latency of HSV-1 in sensory neurons. In the case of human cytomegalovirus (HCMV), the hcmv-miR-UL112 targets the major histocompatibility complex class I-related chain B (MICB) messenger [143]. This leads to decreased binding of natural killer (NK) cell activating receptor NKG2D and reduced killing by NK cells. Hence, the modulation of virus-encoded miRNAs might represent alternative strategies to limit viral propagation. For instance, inhibition of the SV40-encoded miRNA or hcmv-miR-UL112 could increase the production of large T antigen and MICB respectively and, thus, help the immune system to eradicate infected cells. On the other hand, inhibition of miR-LAT could permit infected cells to engage in the apoptotic suicide program and protect surrounding cells from being infected.

22.3.4.3

Viruses and Cellular miRNAs

The miRNA-targeting therapies might also apply for viruses that do not have the miRNA-coding capacity of herpesvirus or polyomavirus genomes. In fact, it has been shown that such viruses can nonetheless impact on cellular messenger translation through the modulation of cellular miRNAs in order to create favourable environment for their replication. In the case of HIV-1, the expression of the polycistronic miRNA cluster miR-17/92 is actively suppressed by the viral transactivator Tat [154]. This suppression increases the expression of the miR-17 and miR-20-targeted p300/CBP-associated factor (PCAF) which is a positive cofactor of HIV Tat. Hence, over-expressing the polycistronic miRNA cluster, in particular miR-17 and miR-20, in HIV-infected cells should diminish the expression of PCAF and limit the transactivation capacities of Tat. Eventually, this gene therapy could limit viral production and propagation. Interestingly, in the same study, Triboulet et al. also provided evidence for a global role of the miRNA-silencing machinery in limiting HIV-1 replication. Type III RNAses Dicer and Drosha, responsible for miRNA processing, are able to

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inhibit virus replication as their extinction through RNA interference leads to an increase in virion production in both peripheral blood mononuclear cells from HIV-1infected donors and latently infected cells. Latency in resting memory CD4(+) T cells is a reversibly non-productive state of infection that allows HIV to evade host immune responses [57]. Therefore, targeting Dicer and Drosha through cellspecific RNAi vectors might represent a way to reactivate the viral replication. As a consequence, latently infected cells will turn into virus-producing cells, able to be eliminated by the immune system and/or anti-HIV pharmacological treatments. Another aspect of the complex interplay between viruses and cellular miRNAs is illustrated by the findings that some viral RNAs can be recognised by cellular miRNAs. In fact, viral mRNAs are highly similar to cellular mRNAs and one can easily imagine that viral messengers can be recognised and viral translation modulated by cellular miRNAs. This assumption has now been substantiated for several unrelated viruses. The first description of a virus whose mRNAs can be targeted by a cellular miRNA was made in the case of the Primate Foamy Virus type 1 (PFV-1), a complex non pathogenic retrovirus akin to HIV-1 [84]. The 3’UTR of the PFV-1 messengers harbours a sequence that can be recognised by the host-encoded miR-32. Although the effect of the miR-32 on viral protein translation has not been formally verified, this recognition leads to a limitation in viral replication as the inhibition of the miR-32 increases the virion production. In addition, the replication of a mutated virus harbouring a silent mutation that disrupts the recognition of the viral mRNAs by the miR-32 is increased compared to the replication of its wild type counterpart. Similarly, in the case of the Vesicular Stomatitis Virus (VSV), the miR-24 and miR-93 are able to recognise and to repress the expression of the viral proteins L and P. In accordance with the increase of HIV replication upon Drosha or Dicer RNAi, it has been shown that the 3′ ends of HIV-1 messenger RNAs are targeted by several cellular miRNAs including miR-28, miR-125b, miR-158, miR-223 and miR-382, which are enriched in resting CD4(+) T cells as compared to activated CD4(+) T cells [63]. Specific inhibitors of these miRNAs significantly counteract their effects on HIV mRNAs and increase HIV replication even in resting CD4(+) T cells isolated from HIV-1-infected individuals on suppressive highly active antiretroviral therapy [63]. These data indicate that cellular miRNAs are pivotal in HIV-1 latency and suggest that manipulation of cellular miRNAs could be a novel approach for purging the HIV-1 reservoir. Together, these findings suggest that a recognition of viral messengers by cellular miRNAs could occur for all types of viruses. In that scenario, the perturbation of the miRNA pathway (i.e. blockage of the miRNA action) should increase the replication of all types of viruses. The perturbation of the miRNA pathway readily increases the replication of PFV-1, HIV, VSV, Herpes Simplex Virus type 1 (HSV-1) and Influenza A virus [84, 97, 115, 154]. Of note, in contrast to PFV-1 and VSV, the HSV-1 susceptibility to Dicer depletion could merely be explained by the fact that this virus encodes the Dicer-processed miR-LAT which is required for HSV-1 survival. On the other hand, knocking down Dicer has slight or no effect on the replication of encephalomyocarditis virus, lymphocytic choriomemingitis virus, Coxsackievirus group B serotype 3, or vaccinia virus (VV) in vivo [115]. Although

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other anti-viral mechanisms, such as the interferon response, might mask the Dicermediated defense [97], these experiments suggest that the complex interplay between viruses and the miRNA pathway could be directly linked to the viral mode of replication. This proposal is exemplified by the findings that the replication of the Hepatitis C Virus (HCV) requires the expression of the miR-122, an abundant liver-specific miRNA, which hybridizes with the 5’ non coding region of the viral genome [70]. Studies with replication-defective RNAs suggest that miR-122 does not detectably affect mRNA translation or RNA stability. Although the exact role of the hybrid formed by the miR-122 and HCV mRNA is not completely unveiled, the authors proposed that the miR-122 may aid in RNA folding or RNA sequestration in replication complexes. Overall, it appears that the exact characterisation of the relationship existing between each type of pathogenic viruses and the cellular miRNAs is a prerequisite for the development of miRNA-associated anti-viral therapies.

22.4

Conclusion

No curative effect of miRNA modulation has been published yet and a better understanding of the implication of miRNAs in human pathologies is clearly required. Hence, it might, at first, appear premature to review the potential of miRNAs in clinical practice. In fact, a similar scenario occurred few years ago with the RNA interference triggered by siRNAs. For instance, the use of RNAi as therapeutic strategies, before a complete understanding of the process, was criticised by several findings showing that the use of siRNA might be deleterious [71, 139]. However, it appears that trials performed in animals are not only successful but accurate as no deleterious effect was associated with siRNA introduction by different strategies [141, 176]. And 4 years only after the discovery that siRNAs are sufficient to trigger RNA interference in vitro [37], the first clinical data for an RNAi-based drug was presented by Sirna Therapeutics (Boulder, CO, USA) in the case of age-related macular degeneration [164]. RNA interference is now certainly considered as a promising strategy to down-regulate undesirable gene activities in various diseases including cancers and viral infections. We may anticipate that the same development will apply to the miRNA-associated therapeutic strategies.

References 1. Abelson, J. F., Kwan, K. Y., O’Roak, B. J., Baek, D. Y., Stillman, A. A., Morgan, T. M., Mathews, C. A., Pauls, D. L., Rasin, M. R., Gunel, M., Davis, N. R., Ercan-Sencicek, A. G., Guez, D. H., Spertus, J. A., Leckman, J. F., Dure, L. S. t., Kurlan, R., Singer, H. S., Gilbert, D. L., Farhi, A., Louvi, A., Lifton, R. P., Sestan, N. & State, M. W. (2005). Sequence variants in SLITRK1 are associated with Tourette’s syndrome. Science 310, 317–20. 2. Akao, Y., Nakagawa, Y., Kitade, Y., Kinoshita, T. & Naoe, T. (2007). Downregulation of microRNAs-143 and -145 in B-cell malignancies. Cancer Sci. 98, 1914–20.

420

A. Saumet et al.

3. Akao, Y., Nakagawa, Y. & Naoe, T. (2006). let-7 microRNA functions as a potential growth suppressor in human colon cancer cells. Biol Pharm Bull 29, 903–6. 4. Ason, B., Darnell, D. K., Wittbrodt, B., Berezikov, E., Kloosterman, W. P., Wittbrodt, J., Antin, P. B. & Plasterk, R. H. (2006). Differences in vertebrate microRNA expression. Proc Natl Acad Sci USA 103, 14385–9. 5. Bandres, E., Cubedo, E., Agirre, X., Malumbres, R., Zarate, R., Ramirez, N., Abajo, A., Navarro, A., Moreno, I., Monzo, M. & Garcia-Foncillas, J. (2006). Identification by Real-time PCR of 13 mature microRNAs differentially expressed in colorectal cancer and non-tumoral tissues. Mol Cancer 5, 29. 6. Barbee, S. A., Estes, P. S., Cziko, A. M., Hillebrand, J., Luedeman, R. A., Coller, J. M., Johnson, N., Howlett, I. C., Geng, C., Ueda, R., Brand, A. H., Newbury, S. F., Wilhelm, J. E., Levine, R. B., Nakamura, A., Parker, R. & Ramaswami, M. (2006). Staufen- and FMRPcontaining neuronal RNPs are structurally and functionally related to somatic P bodies. Neuron 52, 997–1009. 7. Bartel, D. P. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116, 281–97. 8. Beane, R. L., Ram, R., Gabillet, S., Arar, K., Monia, B. P. & Corey, D. R. (2007). Inhibiting gene expression with locked nucleic acids (LNAs) that target chromosomal DNA. Biochemistry 46, 7572–80. 9. Bernstein, E., Kim, S. Y., Carmell, M. A., Murchison, E. P., Alcorn, H., Li, M. Z., Mills, A. A., Elledge, S. J., Anderson, K. V. & Hannon, G. J. (2003). Dicer is essential for mouse development. Nat Genet 35, 215–7. 10. Bhattacharyya, S. N., Habermacher, R., Martine, U., Closs, E. I. & Filipowicz, W. (2006). Relief of microRNA-mediated translational repression in human cells subjected to stress. Cell 125, 1111–24. 11. Bloomston, M., Frankel, W. L., Petrocca, F., Volinia, S., Alder, H., Hagan, J. P., Liu, C. G., Bhatt, D., Taccioli, C. & Croce, C. M. (2007). MicroRNA expression patterns to differentiate pancreatic adenocarcinoma from normal pancreas and chronic pancreatitis. JAMA 297, 1901–8. 12. Bottoni, A., Piccin, D., Tagliati, F., Luchin, A., Zatelli, M. C. & degli Uberti, E. C. (2005). miR-15a and miR-16–1 down-regulation in pituitary adenomas. J Cell Physiol 204, 280–5. 13. Boutla, A., Delidakis, C. & Tabler, M. (2003). Developmental defects by antisense-mediated inactivation of micro-RNAs 2 and 13 in Drosophila and the identification of putative target genes. Nucleic Acids Res 31, 4973–80. 14. Calin, G. A. & Croce, C. M. (2006). MicroRNA signatures in human cancers. Nat Rev Cancer 6, 857–66. 15. Calin, G. A., Dumitru, C. D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., Aldler, H., Rattan, S., Keating, M., Rai, K., Rassenti, L., Kipps, T., Negrini, M., Bullrich, F. & Croce, C. M. (2002). Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc Natl Acad Sci USA 99, 15524–9. 16. Calin, G. A., Ferracin, M., Cimmino, A., Di Leva, G., Shimizu, M., Wojcik, S. E., Iorio, M. V., Visone, R., Sever, N. I., Fabbri, M., Iuliano, R., Palumbo, T., Pichiorri, F., Roldo, C., Garzon, R., Sevignani, C., Rassenti, L., Alder, H., Volinia, S., Liu, C. G., Kipps, T. J., Negrini, M. & Croce, C. M. (2005). A MicroRNA signature associated with prognosis and progression in chronic lymphocytic leukemia. N Engl J Med 353, 1793–801. 17. Calin, G. A., Liu, C. G., Sevignani, C., Ferracin, M., Felli, N., Dumitru, C. D., Shimizu, M., Cimmino, A., Zupo, S., Dono, M., Dell’Aquila, M. L., Alder, H., Rassenti, L., Kipps, T. J., Bullrich, F., Negrini, M. & Croce, C. M. (2004). MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias. Proc Natl Acad Sci USA 101, 11755–60. 18. Cao, X., Pfaff, S. L. & Gage, F. H. (2007). A functional study of miR-124 in the developing neural tube. Genes Dev 21, 531–6. 19. Carthew, R. W. (2002). RNA interference: the fragile X syndrome connection. Curr Biol 12, R852–4. 20. Caudy, A. A., Myers, M., Hannon, G. J. & Hammond, S. M. (2002). Fragile X-related protein and VIG associate with the RNA interference machinery. Genes Dev 16, 2491–6.

22 microRNA-Associated Therapies

421

21. Chan, J. A., Krichevsky, A. M. & Kosik, K. S. (2005). MicroRNA-21 is an antiapoptotic factor in human glioblastoma cells. Cancer Res 65, 6029–33. 22. Chang, T. C., Wentzel, E. A., Kent, O. A., Ramachandran, K., Mullendore, M., Lee, K. H., Feldmann, G., Yamakuchi, M., Ferlito, M., Lowenstein, C. J., Arking, D. E., Beer, M. A., Maitra, A. & Mendell, J. T. (2007). Transactivation of miR-34a by p53 broadly influences gene expression and promotes apoptosis. Mol Cell 26, 745–52. 23. Chen, C., Ridzon, D. A., Broomer, A. J., Zhou, Z., Lee, D. H., Nguyen, J. T., Barbisin, M., Xu, N. L., Mahuvakar, V. R., Andersen, M. R., Lao, K. Q., Livak, K. J. & Guegler, K. J. (2005). Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res 33, e179. 24. Chen, C. Z., Li, L., Lodish, H. F. & Bartel, D. P. (2004). MicroRNAs modulate hematopoietic lineage differentiation. Science 303, 83–6. 25. Chen, Y. and Stallings, R. L. (2007). Differential patterns of microRNA expression in neuroblastoma are correlated with prognosis, differentiation, and apoptosis. Cancer Res, 67, 976–983. 26. Ciafre, S. A., Galardi, S., Mangiola, A., Ferracin, M., Liu, C. G., Sabatino, G., Negrini, M., Maria, G., Croce, C. M. and Farace, M. G. (2005). Extensive modulation of a set of microRNAs in primary glioblastoma. Biochem Biophys Res Commun, 334, 1351–1358. 27. Cimmino, A., Calin, G. A., Fabbri, M., Iorio, M. V., Ferracin, M., Shimizu, M., Wojcik, S. E., Aqeilan, R. I., Zupo, S., Dono, M., Rassenti, L., Alder, H., Volinia, S., Liu, C. G., Kipps, T. J., Negrini, M. & Croce, C. M. (2005). miR-15 and miR-16 induce apoptosis by targeting BCL2. Proc Natl Acad Sci USA 102, 13944–9. 28. Conaco, C., Otto, S., Han, J. J. & Mandel, G. (2006). Reciprocal actions of REST and a microRNA promote neuronal identity. Proc Natl Acad Sci USA 103, 2422–7. 29. Costinean, S., Zanesi, N., Pekarsky, Y., Tili, E., Volinia, S., Heerema, N. & Croce, C. M. (2006). Pre-B cell proliferation and lymphoblastic leukemia/high-grade lymphoma in E(mu)miR155 transgenic mice. Proc Natl Acad Sci USA 103, 7024–9. 30. Cullen, B. R. (2006). Viruses and microRNAs. Nat Genet 38 Suppl, S25–30. 31. Cummins, J. M., He, Y., Leary, R. J., Pagliarini, R., Diaz, L. A., Jr., Sjoblom, T., Barad, O., Bentwich, Z., Szafranska, A. E., Labourier, E., Raymond, C. K., Roberts, B. S., Juhl, H., Kinzler, K. W., Vogelstein, B. & Velculescu, V. E. (2006). The colorectal microRNAome. Proc Natl Acad Sci USA 103, 3687–92. 32. Deo, M., Yu, J. Y., Chung, K. H., Tippens, M. & Turner, D. L. (2006). Detection of mammalian microRNA expression by in situ hybridization with RNA oligonucleotides. Dev Dyn 235, 2538–48. 33. Devi, G. R., Beer, T. M., Corless, C. L., Arora, V., Weller, D. L. & Iversen, P. L. (2005). In vivo bioavailability and pharmacokinetics of a c-MYC antisense phosphorodiamidate morpholino oligomer, AVI-4126, in solid tumors. Clin Cancer Res 11, 3930–8. 34. Dews, M., Homayouni, A., Yu, D., Murphy, D., Sevignani, C., Wentzel, E., Furth, E. E., Lee, W. M., Enders, G. H., Mendell, J. T. & Thomas-Tikhonenko, A. (2006). Augmentation of tumor angiogenesis by a Myc-activated microRNA cluster. Nat Genet 38, 1060–5. 35. Dostie, J., Mourelatos, Z., Yang, M., Sharma, A. & Dreyfuss, G. (2003). Numerous microRNPs in neuronal cells containing novel microRNAs. RNA 9, 180–6. 36. Eis, P. S., Tam, W., Sun, L., Chadburn, A., Li, Z., Gomez, M. F., Lund, E. & Dahlberg, J. E. (2005). Accumulation of miR-155 and BIC RNA in human B cell lymphomas. Proc Natl Acad Sci USA 102, 3627–32. 37. Elbashir, S. M., Harborth, J., Lendeckel, W., Yalcin, A., Weber, K. & Tuschl, T. (2001). Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells. Nature 411, 494–8. 38. Epanchintsev, A., Jung, P., Menssen, A. & Hermeking, H. (2006). Inducible microRNA expression by an all-in-one episomal vector system. Nucleic Acids Res 34, e119. 39. Esau, C., Davis, S., Murray, S. F., Yu, X. X., Pandey, S. K., Pear, M., Watts, L., Booten, S. L., Graham, M., McKay, R., Subramaniam, A., Propp, S., Lollo, B. A., Freier, S., Bennett, C. F., Bhanot, S. & Monia, B. P. (2006). miR-122 regulation of lipid metabolism revealed by in vivo antisense targeting. Cell Metab 3, 87–98.

422

A. Saumet et al.

40. Esau, C., Kang, X., Peralta, E., Hanson, E., Marcusson, E. G., Ravichandran, L. V., Sun, Y., Koo, S., Perera, R. J., Jain, R., Dean, N. M., Freier, S. M., Bennett, C. F., Lollo, B. & Griffey, R. (2004). MicroRNA-143 regulates adipocyte differentiation. J Biol Chem 279, 52361–5. 41. Esteller, M. (2007). Epigenetic gene silencing in cancer: the DNA hypermethylome. Hum Mol Genet 16 Spec No 1, R50–9. 42. Fazi, F., Rosa, A., Fatica, A., Gelmetti, V., De Marchis, M. L., Nervi, C. & Bozzoni, I. (2005). A minicircuitry comprised of MicroRNA-223 and transcription factors NFI-A and C/EBPalpha regulates human granulopoiesis. Cell 123, 819–31. 43. Felli, N., Fontana, L., Pelosi, E., Botta, R., Ronci, D., Facchiano, F., Liuzzi, F., Lulli, V., Morsilli, O., Santoro, S., Valtieri, M., Calin, G. A., Liu, C. G., Sorrentino, A., Corce, C. M. and Peschle, C. (2005). MicroRNAs 221 and 222 inhibit normal erythropoiesis and erythroleukemic cell growth via kit receptor down-modulation. Proc Natl Acad Sci U S A, 102, 18081–6. 44. Ferri, C. P., Prince, M., Brayne, C., Brodaty, H., Fratiglioni, L., Ganguli, M., Hall, K., Hasegawa, K., Hendrie, H., Huang, Y., Jorm, A., Mathers, C., Menezes, P. R., Rimmer, E. & Scazufca, M. (2005). Global prevalence of dementia: a Delphi consensus study. Lancet 366, 2112–7. 45. Fulci, V., Chiaretti, S., Goldoni, M., Azzalin, G., Carucci, N., Tavolaro, S., Castellano, L., Magrelli, A., Citarella, F., Messina, M., Maggio, R., Peragine, N., Santangelo, S., Mauro, F. R., Landgraf, P., Tuschl, T., Weir, D. B., Chien, M., Russo, J. J., Ju, J., Sheridan, R., Sander, C., Zavolan, M., Guarini, A., Foa, R. & Macino, G. (2007). Quantitative technologies establish a novel microRNA profile of chronic lymphocytic leukemia. Blood 109, 4944–51. 46. Gantier, M. P., Sadler, A. J. & Williams, B. R. (2007). Fine-tuning of the innate immune response by microRNAs. Immunol Cell Biol 85, 458–62. 47. Garber, K., Smith, K. T., Reines, D. & Warren, S. T. (2006). Transcription, translation and fragile X syndrome. Curr Opin Genet Dev 16, 270–5. 48. Garzon, R., Pichiorri, F., Palumbo, T., Visentini, M., Aqeilan, R., Cimmino, A., Wang, H., Sun, H., Volinia, S., Alder, H., Calin, G. A., Liu, C. G., Andreeff, M. & Croce, C. M. (2007). MicroRNA gene expression during retinoic acid-induced differentiation of human acute promyelocytic leukemia. Oncogene 26, 4148–57. 49. Gillies, J. K. and Lorimer, I. A. (2007). Regulation fo p27Kip 1 by miRNA 221/222 in glioblastoma. Cell Cycle 6, 2005–9 50. Giraldez, A. J., Cinalli, R. M., Glasner, M. E., Enright, A. J., Thomson, J. M., Baskerville, S., Hammond, S. M., Bartel, D. P. & Schier, A. F. (2005). MicroRNAs regulate brain morphogenesis in zebrafish. Science 308, 833–8. 51. Glantz, L. A., Austin, M. C. & Lewis, D. A. (2000). Normal cellular levels of synaptophysin mRNA expression in the prefrontal cortex of subjects with schizophrenia. Biol Psychiatry 48, 389–97. 52. Glantz, L. A. & Lewis, D. A. (2000). Decreased dendritic spine density on prefrontal cortical pyramidal neurons in schizophrenia. Arch Gen Psychiatry 57, 65–73. 53. Gramantieri, L., Ferracin, M., Fornari, F., Veronese, A., Sabbioni, S., Liu, C. G., Calin, G. A., Giovannini, C., Ferrazzi, E., Grazi, G. L., Croce, C. M., Bolondi, L. and Negrini, M. (2007). Cyclin G1 is a target of miR-122a, a microRNA frequently down-regulated in human hepatocellular carcinoma. Cancer Res 67, 6092–99. 54. Grimm, D., Streetz, K. L., Jopling, C. L., Storm, T. A., Pandey, K., Davis, C. R., Marion, P., Salazar, F. & Kay, M. A. (2006). Fatality in mice due to oversaturation of cellular microRNA/ short hairpin RNA pathways. Nature 441, 537–41. 55. Gupta, A., Gartner, J. J., Sethupathy, P., Hatzigeorgiou, A. G. & Fraser, N. W. (2006). Antiapoptotic function of a microRNA encoded by the HSV-1 latency-associated transcript. Nature 442, 82–5. 56. Hackl, H., Burkard, T. R., Sturn, A., Rubio, R., Schleiffer, A., Tian, S., Quackenbush, J., Eisenhaber, F. & Trajanoski, Z. (2005). Molecular processes during fat cell development revealed by gene expression profiling and functional annotation. Genome Biol 6, R108.

22 microRNA-Associated Therapies

423

57. Han, Y., Wind-Rotolo, M., Yang, H. C., Siliciano, J. D. & Siliciano, R. F. (2007). Experimental approaches to the study of HIV-1 latency. Nat Rev Microbiol 5, 95–106. 58. Harrison, P. J. (2004). The hippocampus in schizophrenia: a review of the neuropathological evidence and its pathophysiological implications. Psychopharmacology (Berl) 174, 151–62. 59. Hayashita, Y., Osada, H., Tatematsu, Y., Yamada, H., Yanagisawa, K., Tomida, S., Yatabe, Y., Kawahara, K., Sekido, Y. & Takahashi, T. (2005). A polycistronic microRNA cluster, miR-17–92, is overexpressed in human lung cancers and enhances cell proliferation. Cancer Res 65, 9628–32. 60. He, L., Thomson, J. M., Hemann, M. T., Hernando-Monge, E., Mu, D., Goodson, S., Powers, S., Cordon-Cardo, C., Lowe, S. W., Hannon, G. J. & Hammond, S. M. (2005). A microRNA polycistron as a potential human oncogene. Nature 435, 828–33. 61. Henry, S. P., Geary, R. S., Yu, R. & Levin, A. A. (2001). Drug properties of second-generation antisense oligonucleotides: how do they measure up to their predecessors? Curr Opin Investig Drugs 2, 1444–9. 62. Hossain, A., Kuo, M. T. & Saunders, G. F. (2006). Mir-17–5p regulates breast cancer cell proliferation by inhibiting translation of AIB1 mRNA. Mol Cell Biol 26, 8191–201. 63. Huang, J., Wang, F., Argyris, E., Chen, K., Liang, Z., Tian, H., Huang, W., Squires, K., Verlinghieri, G. & Zhang, H. (2007). Cellular microRNAs contribute to HIV-1 latency in resting primary CD4(+) T lymphocytes. Nat Med 13, 1241–7. 64. Hutvagner, G., Simard, M. J., Mello, C. C. & Zamore, P. D. (2004). Sequence-specific inhibition of small RNA function. PLoS Biol 2, E98. 65. Iorio, M. V., Ferracin, M., Liu, C. G., Veronese, A., Spizzo, R., Sabbioni, S., Magri, E., Pedriali, M., Fabbri, M., Campiglio, M., Menard, S., Palazzo, J. P., Rosenberg, A., Musiani, P., Volinia, S., Nenci, I., Calin, G. A., Querzoli, P., Negrini, M. & Croce, C. M. (2005). MicroRNA gene expression deregulation in human breast cancer. Cancer Res 65, 7065–70. 66. Iorio, M. V., Visone, R., Di Leva, G., Donati, V., Petrocca, F., Casalini, P., Taccioli, C., Volinia, S., Liu, C. G., Alder, H., Calin, G. A., Menard, S. and Croce, C. M. (2007) MicroRNA Signatures in Human Ovarian Cancer. Cancer Res 67, 8699–8707. 67. Jepsen, J. S., Sorensen, M. D. & Wengel, J. (2004). Locked nucleic acid: a potent nucleic acid analog in therapeutics and biotechnology. Oligonucleotides 14, 130–46. 68. John, M., Constien, R., Akinc, A., Goldberg, M., Moon, Y. A., Spranger, M., Hadwiger, P., Soutschek, J., Vornlocher, H. P., Manoharan, M., Stoffel, M., Langer, R., Anderson, D. G., Horton, J. D., Koteliansky, V. & Bumcrot, D. (2007). Effective RNAi-mediated gene silencing without interruption of the endogenous microRNA pathway. Nature 449, 745–7. 69. Johnson, S. M., Grosshans, H., Shingara, J., Byrom, M., Jarvis, R., Cheng, A., Labourier, E., Reinert, K. L., Brown, D. & Slack, F. J. (2005). RAS is regulated by the let-7 microRNA family. Cell 120, 635–47. 70. Jopling, C. L., Yi, M., Lancaster, A. M., Lemon, S. M. & Sarnow, P. (2005). Modulation of hepatitis C virus RNA abundance by a liver-specific MicroRNA. Science 309, 1577–81. 71. Kariko, K., Bhuyan, P., Capodici, J. & Weissman, D. (2004). Small interfering RNAs mediate sequence-independent gene suppression and induce immune activation by signaling through toll-like receptor 3. J Immunol 172, 6545–9. 72. Kato, M., Zhang, J., Wang, M., Lanting, L., Yuan, H., Rossi, J. J. & Natarajan, R. (2007). MicroRNA-192 in diabetic kidney glomeruli and its function in TGF-beta-induced collagen expression via inhibition of E-box repressors. Proc Natl Acad Sci USA 104, 3432–7. 73. Kim, J., Inoue, K., Ishii, J., Vanti, W. B., Voronov, S. V., Murchison, E., Hannon, G. & Abeliovich, A. (2007). A MicroRNA feedback circuit in midbrain dopamine neurons. Science 317, 1220–4. 74. Kim, J., Krichevsky, A., Grad, Y., Hayes, G. D., Kosik, K. S., Church, G. M. & Ruvkun, G. (2004). Identification of many microRNAs that copurify with polyribosomes in mammalian neurons. Proc Natl Acad Sci USA 101, 360–5. 75. Kloosterman, W. P., Lagendijk, A. K., Ketting, R. F., Moulton, J. D. & Plasterk, R. H. (2007). Targeted inhibition of miRNA maturation with morpholinos reveals a role for miR-375 in pancreatic islet development. PLoS Biol 5, e203.

424

A. Saumet et al.

76. Kluiver, J., Haralambieva, E., de Jong, D., Blokzijl, T., Jacobs, S., Kroesen, B. J., Poppema, S. & van den Berg, A. (2006). Lack of BIC and microRNA miR-155 expression in primary cases of Burkitt lymphoma. Gene Chromosome Canc 45, 147–53. 77. Kluiver, J., Poppema, S., de Jong, D., Blokzijl, T., Harms, G., Jacobs, S., Kroesen, B. J. & van den Berg, A. (2005). BIC and miR-155 are highly expressed in Hodgkin, primary mediastinal and diffuse large B cell lymphomas. J Pathol 207, 243–9. 78. Krichevsky, A. M., King, K. S., Donahue, C. P., Khrapko, K. & Kosik, K. S. (2003). A microRNA array reveals extensive regulation of microRNAs during brain development. RNA 9, 1274–81. 79. Krutzfeldt, J., Rajewsky, N., Braich, R., Rajeev, K. G., Tuschl, T., Manoharan, M. & Stoffel, M. (2005). Silencing of microRNAs in vivo with ‘antagomirs’. Nature 438, 685–9. 80. Kumar, P., Wu, H., McBride, J. L., Jung, K. E., Kim, M. H., Davidson, B. L., Lee, S. K., Shankar, P. & Manjunath, N. (2007). Transvascular delivery of small interfering RNA to the central nervous system. Nature 448, 39–43. 81. Kye, M. J., Liu, T., Levy, S. F., Xu, N. L., Groves, B. B., Bonneau, R., Lao, K. & Kosik, K. S. (2007). Somatodendritic microRNAs identified by laser capture and multiplex RT-PCR. RNA 13, 1224–34. 82. Lagos-Quintana, M., Rauhut, R., Yalcin, A., Meyer, J., Lendeckel, W. & Tuschl, T. (2002). Identification of tissue-specific microRNAs from mouse. Curr Biol 12, 735–9. 83. Landais, S., Landry, S., Legault, P. & Rassart, E. (2007). Oncogenic potential of the miR106–363 cluster and its implication in human T-cell leukemia. Cancer Res 67, 5699–707. 84. Lecellier, C. H., Dunoyer, P., Arar, K., Lehmann-Che, J., Eyquem, S., Himber, C., Saib, A. & Voinnet, O. (2005). A cellular microRNA mediates antiviral defense in human cells. Science 308, 557–60. 85. Lee, E. J., Gusev, Y., Jiang, J., Nuovo, G. J., Lerner, M. R., Frankel, W. L., Morgan, D. L., Postier, R. G., Brackett, D. J. & Schmittgen, T. D. (2007). Expression profiling identifies microRNA signature in pancreatic cancer. Int J Cancer 120, 1046–54. 86. Liu, J., Valencia-Sanchez, M. A., Hannon, G. J. & Parker, R. (2005). MicroRNA-dependent localization of targeted mRNAs to mammalian P-bodies. Nat Cell Biol 7, 719–23. 87. Lo, A. K., To, K. F., Lo, K. W., Lung, R. W., Hui, J. W., Liao, G. & Hayward, S. D. (2007a). Modulation of LMP1 protein expression by EBV-encoded microRNAs. Proc Natl Acad Sci USA 104, 16164–9. 88. Lo, H. L., Chang, T., Yam, P., Marcovecchio, P. M., Li, S., Zaia, J. A. & Yee, J. K. (2007b). Inhibition of HIV-1 replication with designed miRNAs expressed from RNA polymerase II promoters. Gene Ther 14, 1503–2. 89. Loffler, D., Brocke-Heidrich, K., Pfeifer, G., Stocsits, C., Hackermuller, J., Kretzschmar, A. K., Burger, R., Gramatzki, M., Blumert, C., Bauer, K., Cvijic, H., Ullmann, A. K., Stadler, P. F. & Horn, F. (2007). Interleukin-6 dependent survival of multiple myeloma cells involves the Stat3mediated induction of microRNA-21 through a highly conserved enhancer. Blood 110, 1330–3. 90. Lu, J., Getz, G., Miska, E. A., Alvarez-Saavedra, E., Lamb, J., Peck, D., Sweet-Cordero, A., Ebert, B. L., Mak, R. H., Ferrando, A. A., Downing, J. R., Jacks, T., Horvitz, H. R. & Golub, T. R. (2005). MicroRNA expression profiles classify human cancers. Nature 435, 834–8. 91. Lujambio, A. & Esteller, M. (2007). CpG island hypermethylation of tumor suppressor microRNAs in human cancer. Cell Cycle 6, 1455–9. 92. Lujambio, A., Ropero, S., Ballestar, E., Fraga, M. F., Cerrato, C., Setien, F., Casado, S., Suarez-Gauthier, A., Sanchez-Cespedes, M., Git, A., Spiteri, I., Das, P. P., Caldas, C., Miska, E. & Esteller, M. (2007). Genetic unmasking of an epigenetically silenced microRNA in human cancer cells. Cancer Res 67, 1424–9. 93. Lukiw, W. J. (2007). Micro-RNA speciation in fetal, adult and Alzheimer’s disease hippocampus. Neuroreport 18, 297–300. 94. Lynn, F. C., Skewes-Cox, P., Kosaka, Y., McManus, M. T., Harfe, B. D. & German, M. S. (2007). MicroRNA expression is required for pancreatic islet cell genesis in the mouse. Diabetes 56, 2938–45. 95. Ma, L., Teruya-Feldstein, J. & Weinberg, R. A. (2007). Tumour invasion and metastasis initiated by microRNA-10b in breast cancer. Nature 449, 682–8.

22 microRNA-Associated Therapies

425

96. Mandemakers, W., Morais, V. A. & De Strooper, B. (2007). A cell biological perspective on mitochondrial dysfunction in Parkinson disease and other neurodegenerative diseases. J Cell Sci 120, 1707–16. 97. Matskevich, A. A. & Moelling, K. (2007). Dicer is involved in protection against influenza A virus infection. J Gen Virol 88, 2627–35. 98. Mayr, C., Hemann, M. T. & Bartel, D. P. (2007). Disrupting the pairing between let-7 and Hmga2 enhances oncogenic transformation. Science 315, 1576–9. 99. McCaffrey, A. P., Meuse, L., Pham, T. T., Conklin, D. S., Hannon, G. J. & Kay, M. A. (2002). RNA interference in adult mice. Nature 418, 38–9. 100. Meng, F., Henson, R., Lang, M., Wehbe, H., Maheshwari, S., Mendell, J. T., Jiang, J., Schmittgen, T. D. & Patel, T. (2006). Involvement of human micro-RNA in growth and response to chemotherapy in human cholangiocarcinoma cell lines. Gastroenterology 130, 2113–29. 101. Meng, F., Henson, R., Wehbe-Janek, H., Ghoshal, K., Jacob, S. T. & Patel, T. (2007a). MicroRNA-21 regulates expression of the PTEN tumor suppressor gene in human hepatocellular cancer. Gastroenterology 133, 647–58. 102. Meng, F., Wehbe-Janek, H., Henson, R., Smith, H. & Patel, T. (2007b). Epigenetic regulation of microRNA-370 by interleukin-6 in malignant human cholangiocytes. Oncogene 27, 378–86. 103. Metzler, M., Wilda, M., Busch, K., Viehmann, S. & Borkhardt, A. (2004). High expression of precursor microRNA-155/BIC RNA in children with Burkitt lymphoma. Gene Chromosome Canc 39, 167–9. 104. Michael, M. Z., SM, O. C., van Holst Pellekaan, N. G., Young, G. P. & James, R. J. (2003). Reduced accumulation of specific microRNAs in colorectal neoplasia. Mol Cancer Res 1, 882–91. 105. Miska, E. A., Alvarez-Saavedra, E., Townsend, M., Yoshii, A., Sestan, N., Rakic, P., Constantine-Paton, M. & Horvitz, H. R. (2004). Microarray analysis of microRNA expression in the developing mammalian brain. Genome Biol 5, R68. 106. Mourelatos, Z., Dostie, J., Paushkin, S., Sharma, A., Charroux, B., Abel, L., Rappsilber, J., Mann, M. & Dreyfuss, G. (2002). miRNPs: a novel class of ribonucleoproteins containing numerous microRNAs. Genes Dev 16, 720–8. 107. Murakami, Y., Yasuda, T., Saigo, K., Urashima, T., Toyoda, H., Okanoue, T. and shimatohno, K. (2006) Comprehensive analysis of microRNA expression patterna in hepatocellular carcinoma and non-tumorous tissues. Oncogene 25, 2537–2545. 108. Naguibneva, I., Ameyar-Zazoua, M., Polesskaya, A., Ait-Si-Ali, S., Groisman, R., Souidi, M., Cuvellier, S. & Harel-Bellan, A. (2006). The microRNA miR-181 targets the homeobox protein Hox-A11 during mammalian myoblast differentiation. Nat Cell Biol 8, 278–84. 109. Nelson, P. T., Baldwin, D. A., Kloosterman, W. P., Kauppinen, S., Plasterk, R. H. & Mourelatos, Z. (2006). RAKE and LNA-ISH reveal microRNA expression and localization in archival human brain. RNA 12, 187–91. 110. O’Donnell, K. A., Wentzel, E. A., Zeller, K. I., Dang, C. V. & Mendell, J. T. (2005). c-Mycregulated microRNAs modulate E2F1 expression. Nature 435, 839–43. 111. Omoto, S. & Fujii, Y. R. (2005). Regulation of human immunodeficiency virus 1 transcription by nef microRNA. J Gen Virol 86, 751–5. 112. Omoto, S., Ito, M., Tsutsumi, Y., Ichikawa, Y., Okuyama, H., Brisibe, E. A., Saksena, N. K. & Fujii, Y. R. (2004). HIV-1 nef suppression by virally encoded microRNA. Retrovirology 1, 44. 113. Orom, U. A., Kauppinen, S. & Lund, A. H. (2006). LNA-modified oligonucleotides mediate specific inhibition of microRNA function. Gene 372, 137–41. 114. Ota, A., Tagawa, H., Karnan, S., Tsuzuki, S., Karpas, A., Kira, S., Yoshida, Y. & Seto, M. (2004). Identification and characterization of a novel gene, C13orf25, as a target for 13q31-q32 amplification in malignant lymphoma. Cancer Res 64, 3087–95. 115. Otsuka, M., Jing, Q., Georgel, P., New, L., Chen, J., Mols, J., Kang, Y. J., Jiang, Z., Du, X., Cook, R., Das, S. C., Pattnaik, A. K., Beutler, B. & Han, J. (2007). Hypersusceptibility to

426

116. 117.

118.

119.

120. 121.

122.

123.

124. 125.

126.

127.

128. 129.

130.

131.

132.

A. Saumet et al. vesicular stomatitis virus infection in Dicer1-deficient mice is due to impaired miR24 and miR93 Expression. Immunity 27, 378–86. Ozen, M., Creighton, C. J., Ozdemir, M. & Ittmann, M. (2007). Widespread deregulation of microRNA expression in human prostate cancer. Oncogene 27, 1788–93. Pallante, P., Visone, R., Ferracin, M., Ferraro, A., Berlingieri, M. T., Troncone, G., Chiappetta, G., Liu, C. G., Santoro, M., Negrini, M., Croce, C. M. & Fusco, A. (2006). MicroRNA deregulation in human thyroid papillary carcinomas. Endocr Relat Cancer 13, 497–508. Pekarsky, Y., Santanam, U., Cimmino, A., Palamarchuk, A., Efanov, A., Maximov, V., Volinia, S., Alder, H., Liu, C. G., Rassenti, L., Calin, G. A., Hagan, J. P., Kipps, T. & Croce, C. M. (2006). Tcl1 expression in chronic lymphocytic leukemia is regulated by miR-29 and miR-181. Cancer Res 66, 11590–3. Perkins, D. O., Jeffries, C. D., Jarskog, L. F., Thomson, J. M., Woods, K., Newman, M. A., Parker, J. S., Jin, J. & Hammond, S. M. (2007). microRNA expression in the prefrontal cortex of individuals with schizophrenia and schizoaffective disorder. Genome Biol 8, R27. Pillai, R. S. (2005). MicroRNA function: multiple mechanisms for a tiny RNA? RNA 11, 1753–61. Plaisance, V., Abderrahmani, A., Perret-Menoud, V., Jacquemin, P., Lemaigre, F. & Regazzi, R. (2006). MicroRNA-9 controls the expression of Granuphilin/Slp4 and the secretory response of insulin-producing cells. J Biol Chem 281, 26932–42. Plante, I., Davidovic, L., Ouellet, D. L., Gobeil, L. A., Tremblay, S., Khandjian, E. W. & Provost, P. (2006). Dicer-derived MicroRNAs are utilized by the fragile X mental retardation protein for assembly on target RNAs. J Biomed Biotechnol 2006, 64347. Plante, I. & Provost, P. (2006). Hypothesis: a role for fragile X mental retardation protein in mediating and relieving MicroRNA-guided translational repression? J Biomed Biotechnol 2006, 16806. Porkka, K. P., Pfeiffer, M. J., Waltering, K. K., Vessella, R. L., Tammela, T. L. & Visakorpi, T. (2007). MicroRNA expression profiling in prostate cancer. Cancer Res 67, 6130–5. Poy, M. N., Eliasson, L., Krutzfeldt, J., Kuwajima, S., Ma, X., Macdonald, P. E., Pfeffer, S., Tuschl, T., Rajewsky, N., Rorsman, P. & Stoffel, M. (2004). A pancreatic islet-specific microRNA regulates insulin secretion. Nature 432, 226–30. Raver-Shapira, N., Marciano, E., Meiri, E., Spector, Y., Rosenfeld, N., Moskovits, N., Bentwich, Z. & Oren, M. (2007). Transcriptional activation of miR-34a contributes to p53mediated apoptosis. Mol Cell 26, 731–43. Rodriguez, A., Vigorito, E., Clare, S., Warren, M. V., Couttet, P., Soond, D. R., van Dongen, S., Grocock, R. J., Das, P. P., Miska, E. A., Vetrie, D., Okkenhaug, K., Enright, A. J., Dougan, G., Turner, M. & Bradley, A. (2007). Requirement of bic/microRNA-155 for normal immune function. Science 316, 608–11. Rogaev, E. I. (2005). Small RNAs in human brain development and disorders. Biochemistry (Mosc) 70, 1404–7. Roldo, C., Missiaglia, E., Hagan, J. P., Falconi, M., Capelli, P., Bersani, S., Calin, G. A., Volinia, S., Liu, C. G., Scarpa, A. & Croce, C. M. (2006). MicroRNA expression abnormalities in pancreatic endocrine and acinar tumors are associated with distinctive pathologic features and clinical behavior. J Clin Oncol 24, 4677–84. Rossi, L., Bonmassar, E. & Faraoni, I. (2007). Modification of miR gene expression pattern in human colon cancer cells following exposure to 5-fluorouracil in vitro. Pharmacol Res 56, 248–53. Saito, Y., Liang, G., Egger, G., Friedman, J. M., Chuang, J. C., Coetzee, G. A. & Jones, P. A. (2006). Specific activation of microRNA-127 with downregulation of the proto-oncogene BCL6 by chromatin-modifying drugs in human cancer cells. Cancer Cell 9, 435–43. Schaefer, A., O’Carroll, D., Tan, C. L., Hillman, D., Sugimori, M., Llinas, R. & Greengard, P. (2007). Cerebellar neurodegeneration in the absence of microRNAs. J Exp Med 204, 1553–8.

22 microRNA-Associated Therapies

427

133. Schratt, G. M., Tuebing, F., Nigh, E. A., Kane, C. G., Sabatini, M. E., Kiebler, M. & Greenberg, M. E. (2006). A brain-specific microRNA regulates dendritic spine development. Nature 439, 283–9. 134. Scott, G. K., Mattie, M. D., Berger, C. E., Benz, S. C. & Benz, C. C. (2006). Rapid alteration of microRNA levels by histone deacetylase inhibition. Cancer Res 66, 1277–81. 135. Sempere, L. F., Freemantle, S., Pitha-Rowe, I., Moss, E., Dmitrovsky, E. & Ambros, V. (2004). Expression profiling of mammalian microRNAs uncovers a subset of brain-expressed microRNAs with possible roles in murine and human neuronal differentiation. Genome Biol 5, R13. 136. Shell, S., Park, S. M., Radjabi, A. R., Schickel, R., Kistner, E. O., Jewell, D. A., Feig, C., Lengyel, E. & Peter, M. E. (2007). Let-7 expression defines two differentiation stages of cancer. Proc Natl Acad Sci USA 104, 11400–5. 137. Si, M. L., Zhu, S., Wu, H., Lu, Z., Wu, F. & Mo, Y. Y. (2007). miR-21-mediated tumor growth. Oncogene 26, 2799–803. 138. Skalsky, R. L., Samols, M. A., Plaisance, K. B., Boss, I. W., Riva, A., Lopez, M. C., Baker, H. V. & Renne, R. (2007). Kaposi’s Sarcoma-associated Herpesvirus Encodes an Ortholog of miR-155. J Virol 81, 12836–45. 139. Sledz, C. A., Holko, M., de Veer, M. J., Silverman, R. H. & Williams, B. R. (2003). Activation of the interferon system by short-interfering RNAs. Nat Cell Biol 5, 834–9. 140. Smirnova, L., Grafe, A., Seiler, A., Schumacher, S., Nitsch, R. & Wulczyn, F. G. (2005). Regulation of miRNA expression during neural cell specification. Eur J Neurosci 21, 1469–77. 141. Soutschek, J., Akinc, A., Bramlage, B., Charisse, K., Constien, R., Donoghue, M., Elbashir, S., Geick, A., Hadwiger, P., Harborth, J., John, M., Kesavan, V., Lavine, G., Pandey, R. K., Racie, T., Rajeev, K. G., Rohl, I., Toudjarska, I., Wang, G., Wuschko, S., Bumcrot, D., Koteliansky, V., Limmer, S., Manoharan, M. & Vornlocher, H. P. (2004). Therapeutic silencing of an endogenous gene by systemic administration of modified siRNAs. Nature 432, 173–8. 142. Stein, C. A. & Cheng, Y. C. (1993). Antisense oligonucleotides as therapeutic agents–is the bullet really magical? Science 261, 1004–12. 143. Stern-Ginossar, N., Elefant, N., Zimmermann, A., Wolf, D. G., Saleh, N., Biton, M., Horwitz, E., Prokocimer, Z., Prichard, M., Hahn, G., Goldman-Wohl, D., Greenfield, C., Yagel, S., Hengel, H., Altuvia, Y., Margalit, H. & Mandelboim, O. (2007). Host immune system gene targeting by a viral miRNA. Science 317, 376–81. 144. Sullivan, C. S., Grundhoff, A. T., Tevethia, S., Pipas, J. M. & Ganem, D. (2005). SV40encoded microRNAs regulate viral gene expression and reduce susceptibility to cytotoxic T cells. Nature 435, 682–6. 145. Sylvestre, Y., De Guire, V., Querido, E., Mukhopadhyay, U. K., Bourdeau, V., Major, F., Ferbeyre, G. & Chartrand, P. (2007). An E2F/miR-20a autoregulatory feedback loop. J Biol Chem 282, 2135–43. 146. Taganov, K. D., Boldin, M. P., Chang, K. J. & Baltimore, D. (2006). NF-kappaB-dependent induction of microRNA miR-146, an inhibitor targeted to signaling proteins of innate immune responses. Proc Natl Acad Sci USA 103, 12481–6. 147. Tagawa, H. & Seto, M. (2005). A microRNA cluster as a target of genomic amplification in malignant lymphoma. Leukemia 19, 2013–6. 148. Takamizawa, J., Konishi, H., Yanagisawa, K., Tomida, S., Osada, H., Endoh, H., Harano, T., Yatabe, Y., Nagino, M., Nimura, Y., Mitsudomi, T. & Takahashi, T. (2004). Reduced expression of the let-7 microRNAs in human lung cancers in association with shortened postoperative survival. Cancer Res 64, 3753–6. 149. Tam, W., Hughes, S. H., Hayward, W. S. & Besmer, P. (2002). Avian bic, a gene isolated from a common retroviral site in avian leukosis virus-induced lymphomas that encodes a noncoding RNA, cooperates with c-myc in lymphomagenesis and erythroleukemogenesis. J Virol 76, 4275–86.

428

A. Saumet et al.

150. Tarasov, V., Jung, P., Verdoodt, B., Lodygin, D., Epanchintsev, A., Menssen, A., Meister, G. & Hermeking, H. (2007). Differential regulation of microRNAs by p53 revealed by massively parallel sequencing: miR-34a is a p53 target that induces apoptosis and G1-arrest. Cell Cycle 6, 1586–93. 151. Teleman, A. A., Maitra, S. & Cohen, S. M. (2006). Drosophila lacking microRNA miR-278 are defective in energy homeostasis. Genes Dev 20, 417–22. 152. Thompson, R. C., Deo, M. & Turner, D. L. (2007). Analysis of microRNA expression by in situ hybridization with RNA oligonucleotide probes. Methods 43, 153–61. 153. Thomson, J. M., Newman, M., Parker, J. S., Morin-Kensicki, E. M., Wright, T. & Hammond, S. M. (2006). Extensive post-transcriptional regulation of microRNAs and its implications for cancer. Genes Dev 20, 2202–7. 154. Triboulet, R., Mari, B., Lin, Y. L., Chable-Bessia, C., Bennasser, Y., Lebrigand, K., Cardinaud, B., Maurin, T., Barbry, P., Baillat, V., Reynes, J., Corbeau, P., Jeang, K. T. & Benkirane, M. (2007). Suppression of MicroRNA-Silencing Pathway by HIV-1 During Virus Replication. Science 315, 1579–82. 155. Venturini, L., Battmer, K., Castoldi, M., Schultheis, B., Hochhaus, A., Muckenthaler, M. U., Ganser, A., Eder, M. & Scherr, M. (2007). Expression of the miR-17–92 polycistron in chronic myeloid leukemia (CML) CD34 + cells. Blood 109, 4399–405. 156 Visone, R., Pallante, P., Vecchione, A., Cirombella, R., Ferracin, M., Ferraro, A., Volinia, S., Coluzzi, S., Leone, V, Borbone, E., Liu, C. G., Petrocca, F., Troncone, G., Calin, G. A., Scarpa, A., Colato, C., Tallini, G., Santoro, M., Croce, C. M. and Fusco, A. (2007). Specific microRNAs are downregulated in human thyroid anaplastic carcinomas. Oncogene. 157. Visvanathan, J., Lee, S., Lee, B., Lee, J. W. & Lee, S. K. (2007). The microRNA miR-124 antagonizes the anti-neural REST/SCP1 pathway during embryonic CNS development. Genes Dev 21, 744–9. 158. Volinia, S., Calin, G. A., Liu, C. G., Ambs, S., Cimmino, A., Petrocca, F., Visone, R., Iorio, M., Roldo, C., Ferracin, M., Prueitt, R. L., Yanaihara, N., Lanza, G., Scarpa, A., Vecchione, A., Negrini, M., Harris, C. C. & Croce, C. M. (2006). A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci USA 103, 2257–61. 159. Voorhoeve, P. M., le Sage, C., Schrier, M., Gillis, A. J., Stoop, H., Nagel, R., Liu, Y. P., van Duijse, J., Drost, J., Griekspoor, A., Zlotorynski, E., Yabuta, N., De Vita, G., Nojima, H., Looijenga, L. H. & Agami, R. (2006). A genetic screen implicates miRNA-372 and miRNA-373 as oncogenes in testicular germ cell tumors. Cell 124, 1169–81. 160. Waehler, R., Russell, S. J. & Curiel, D. T. (2007). Engineering targeted viral vectors for gene therapy. Nat Rev Genet 8, 573–87. 161 Weber, F., Teresi, R. E., Broelsch, C. E., Frilling A. and Eng, C. (2006). A limited set of human MicroRNA is deregulated in follicular thyroid carcinoma. J Clin Endocrinol Matab 91, 3584–91. 162 Welch, C., Chen, Y. and Stallings, R. L., (2007) MicroRNA-34a functionas as a potential tumor suppressor by inducing apoptosis in neuroblastoma cells. Oncogene, 26, 5017–22. 163. Weiler, J., Hunziker, J. & Hall, J. (2006). Anti-miRNA oligonucleotides (AMOs): ammunition to target miRNAs implicated in human disease? Gene Ther 13, 496–502. 164. Whelan, J. (2005). First clinical data on RNAi. Drug Discov Today 10, 1014–5. 165. Wienholds, E., Kloosterman, W. P., Miska, E., Alvarez-Saavedra, E., Berezikov, E., de Bruijn, E., Horvitz, H. R., Kauppinen, S. & Plasterk, R. H. (2005). MicroRNA expression in zebrafish embryonic development. Science 309, 310–1. 166. Woods, K., Thomson, J. M. & Hammond, S. M. (2007). Direct regulation of an oncogenic micro-RNA cluster by E2F transcription factors. J Biol Chem 282, 2130–4. 167. Wulczyn, F. G., Smirnova, L., Rybak, A., Brandt, C., Kwidzinski, E., Ninnemann, O., Strehle, M., Seiler, A., Schumacher, S. & Nitsch, R. (2007). Post-transcriptional regulation of the let-7 microRNA during neural cell specification. Faseb J 21, 415–26. 168. Xu, P., Vernooy, S. Y., Guo, M. & Hay, B. A. (2003). The Drosophila microRNA Mir-14 suppresses cell death and is required for normal fat metabolism. Curr Biol 13, 790–5.

22 microRNA-Associated Therapies

429

169. Yanaihara, N., Caplen, N., Bowman, E., Seike, M., Kumamoto, K., Yi, M., Stephens, R. M., Okamoto, A., Yokota, J., Tanaka, T., Calin, G. A., Liu, C. G., Croce, C. M. & Harris, C. C. (2006). Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell 9, 189–98. 170. Yang, W., Chendrimada, T. P., Wang, Q., Higuchi, M., Seeburg, P. H., Shiekhattar, R. & Nishikura, K. (2006). Modulation of microRNA processing and expression through RNA editing by ADAR deaminases. Nat Struct Mol Biol 13, 13–21. 171. Yeo, M., Lee, S. K., Lee, B., Ruiz, E. C., Pfaff, S. L. & Gill, G. N. (2005). Small CTD phosphatases function in silencing neuronal gene expression. Science 307, 596–600. 172. Zanette, D. L., Rivadavia, F., Molfetta, G. A., Barbuzano, F. G., Proto-Siqueira, R. & Silva-Jr, W. A. (2007). miRNA expression profiles in chronic lymphocytic and acute lymphocytic leukemia. Braz J Med Biol Res 40, 1435–40. 173. Zhang, L., Huang, J., Yang, N., Greshock, J., Megraw, M. S., Giannakakis, A., Liang, S., Naylor, T. L., Barchetti, A., Ward, M. R., Yao, G., Medina, A., O’Brien-Jenkins, A., Katsaros, D., Hatzigeorgiou, A., Gimotty, P. A., Weber, B. L. & Coukos, G. (2006). microRNAs exhibit high frequency genomic alterations in human cancer. Proc Natl Acad Sci USA 103, 9136–41. 174. Zhu, S., Si, M. L., Wu, H. & Mo, Y. Y. (2007). MicroRNA-21 targets the tumor suppressor gene tropomyosin 1 (TPM1). J Biol Chem 282, 14328–36. 175. Zhuo, M., Zhang, W., Son, H., Mansuy, I., Sobel, R. A., Seidman, J. & Kandel, E. R. (1999). A selective role of calcineurin aalpha in synaptic depotentiation in hippocampus. Proc Natl Acad Sci USA 96, 4650–5. 176. Zimmermann, T. S., Lee, A. C., Akinc, A., Bramlage, B., Bumcrot, D., Fedoruk, M. N., Harborth, J., Heyes, J. A., Jeffs, L. B., John, M., Judge, A. D., Lam, K., McClintock, K., Nechev, L. V., Palmer, L. R., Racie, T., Rohl, I., Seiffert, S., Shanmugam, S., Sood, V., Soutschek, J., Toudjarska, I., Wheat, A. J., Yaworski, E., Zedalis, W., Koteliansky, V., Manoharan, M., Vornlocher, H. P. & MacLachlan, I. (2006). RNAi-mediated gene silencing in non-human primates. Nature 441, 111–4.

Chapter 23

The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants George J. Wagner* and Antoaneta B. Kroumova

Abstract RNA interference technology (RNAi, dsRNA-mediated gene silencing) has already had a major impact on the study and manipulation of plant secondary metabolites. To date RNAi has mainly been used as a readily available, rapid, reverse genetics tool to create plants with novel chemical phenotypes, and to determine the phenotypes of genes responsible for the synthesis of many different secondary metabolites. These manipulations have also greatly facilitated the identification and improvement of specific plant-insect and plant-pathogen interactions, and have set the stage for greater exploitation of plants to produce commercially-valuable, plant-derived drugs, flavoring agents, perfumes, etc. RNAi has been used to study and manipulate products that are representatives of all three main groups of plant secondary metabolites, the phenylpropanoids (and allied phenolics), alkaloids, and terpenoids. We predict that because there exists so much diversity in chemical structure among plant secondary metabolites, and RNAi is highly efficient, foreign gene expression together with RNAi will undoubtedly play an increasingly important role in enabling plants to produce renewable chemical feed stocks now obtained from petroleum. Thus, various forms of RNAi will be very important in the post “peak oil” future of agriculture, worldwide. After a brief general introduction to plant secondary metabolites, we will survey recent studies that have used RNAi for phenotyping of secondary metabolite related genes, and to generating novel chemical phenotypes, pointing out the advantages gained. A few examples will be highlighted to exemplify the powerful approach of gene knockdown combined with foreign gene overexpression as a means for creating new secondary-product-based phenotypes (e.g., the blue rose). Where data is available, we will compare knockdown efficiency and stability of antisense, co-suppression and dsRNAi. As a case study, we will describe in more detail how RNAi has been used to chart carbon flow among branch pathways of diterpenoid biosynthesis in trichome glands. Finally we will discuss the potential of artificial miRNAi for

Plant Physiology/Biochemistry/Molecular Biology Program, Plant and Soil Science Department, 200L KTRDC, University of Kentucky, Lexington, KY 40546–0091, USA *Corresponding author: E-mail: [email protected]

S.-Y. Ying (ed.) Current Perspectives in microRNAs (miRNA), © Springer Science + Business Media B.V. 2008

431

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enhancing the RNA-mediated gene silencing approach (particularly selectivity) in plants, and as a mutational tool. Keywords RNAi, Plant Secondary Metabolites, Gene Knockdown, Phenylpropanoids, Alkaloids, Terpenoids, Trichomes.

23.1

Background: RNA-Mediated Gene Suppression

The history of RNA mediated gene silencing dates back to the mid-1980s, but the “antisense effect” was first demonstrated in intact plants in 1987 by the silencing of an integrated nopaline synthase transgene in tobacco [47]. Until recently, antisense and sense (co-suppression) RNA mediated, single gene silencing, using a strong constitutive promoter, was the most widespread approach for initiating posttranscriptional gene silencing (PTGS) in plants. These approaches are shown to have low to moderate efficiency, generally resulting in a 5–20% knockdown of target gene mRNA accumulation [5, 72]. With these approaches mRNA suppression is variable from individual to individual transformant, ranging from 0–99% reduction in steady state mRNA, and is highly dependent on antisense RNA to mRNA homology. RNAi (dsRNA interference) employs complementary sense and antisense sequences (identity of ≥70%) separated by a non-homologous linker. RNAi, like its predecessors, is post-transcriptional, homology-dependent, and is associated with siRNA accumulation [15]. But, in contrast to antisense and sense suppression, RNAi is highly efficient. It is not uncommon that dsRNAi yields >90% near-absolute target gene suppression [15, 33]. An RNAi vector must possess a highly homologous dsRNA region of at least ∼100 nt to efficiently induce PTGS [72]. This is a common size for a cDNA with a sequence suggestive of an annotated sequence or an un-annotated cDNA, so RNAi can easily, quickly, and selectively be used to probe gene function of such early experimental entities as partial cDNAs prepared from EST libraries. Many popular and widely used protocols for using RNAi in plants have been developed [53, 58]. Generally, RNAi has been applied using a single DNA per construct, but as will be discussed later, artificial miRNA (amiRNA silencing) technology promises to allow multiple gene targeting using a single suppression construct. While the above description perhaps implies that dsRNAi has superseded antisense and sense suppression, we note that antisense may have advantages over RNAi for certain applications, such as clinical therapy applications where unintended down regulation or up regulation of non-target genes may have serious consequences [44]. And, antisense knockdown of lignin-related genes provides sufficient suppression to allow entry of antisensed plants into near commercial use [9]. The mechanisms underlying gene silencing in plants have been extensively studied [58], and chapters in this volume, and will not be considered in this chapter. Here we will focus on the application of dsRNAi to plant secondary metabolite research. Also, we will not consider alternative gene suppression methods ([48] and see other chapters

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 433

in this volume) such as antisense (except from an efficiency perspective), sense suppression, virus induced gene silencing, chimeric repressor silencing, reversible silencing using inducible promoters, transitive RNAi, transcriptional gene silencing, etc.

23.2 Plant Secondary Metabolites Plant secondary metabolites (sometimes called plant secondary products, or plant natural products) are generally distinguished from primary metabolites (D-sugars, L-amino acids, organic acids, nucleotides, fatty acids, etc.) by their roles and taxonomic distribution [10]. Primary metabolites serve essential roles as intermediates and polymer units (of e.g., cellulose, starch, triacyl glycerides) in general, essential biochemistry and are ubiquitous in plants and most other organisms. In contrast, most secondary metabolites are usually found in limited taxonomic groups and often appear to serve primarily at certain developmental stages and in certain cell types, in defensive roles against pests, pathogens or herbivores, or in reproduction (e.g., as pollinator attractants). However, the perhaps simplistic generalization that plant secondary metabolites serve primarily to defend the plant – that must live stationary in its environment – is becoming increasingly challenged as evidence for the role of classical defense compounds (e.g., phenolics) in preventing photo damage (plant cell damage control), in regulation of symbiotic interactions and in metabolic regulation emerges [59]. The older literature contains many suggestions that particular plant secondary metabolites may have roles in regulating metabolism, as well as participating in plant defense and reproduction [46]. Secondary metabolites cannot be distinguished from primary metabolites on the basis of their chemistry or metabolic origin. For example, the diterpene kaurenoic acid, the precursor to the ubiquitous and essential gibberellins (thus considered a primary metabolite) and abietic acid (defensive rosin component limited to members of the Fabaceae and Pinacae) are formed by similar enzymatic reactions. Another case perhaps is the occurrence of D-amino acids (glutamic, aspartic, γ-aminobutyric) in select plants, some of which are thought to effect plant growth and development (see [46]). Thus, while the division between primary and secondary metabolism is often indistinct, non-ubiquitous un-polymerized secondary metabolites that often accumulate to high levels in specific species are a key feature of many higher plants. The discussion thus far has focused on relatively low molecular weight, nonpolymerized molecules that are products of secondary metabolism. We will continue with this focus, but recognize that larger molecules that may be general ubiquitous in plants, or may be enriched in certain plants, and in specific tissues of plants, can also be considered to be natural products of a type. But, to refer to these as secondary products would not be consistent with the general use of this term. These include plant polymers built from primary metabolites such as: fibers, waxes, storage proteins, starches, etc. RNAi has also been successfully used to investigate and alter such compounds/products [29, 33, 57]. Examples are: allergenic peanut protein knockdown [14]; wheat grain gliadin knockdown [16]; production of low glutelin

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G.J. Wagner, A.B. Kroumova

rice, which was shown to be stable for 20 generations [28] manipulation of fiber elongation in cotton [31]; production of a high-amylose potato [3]. In the last case, antisense and RNAi knockdowns of two genes encoding starch branching enzymes were compared. These approaches resulted in 3% and 50% transgenic lines having the desired high amylose type, respectively. A 2006 review by [33] describes the successful use of RNAi for modifying stearic and oleic acid contents of cotton seed, down regulating pollen allergens in ryegrasses, improving productivity of oilseed rape, increasing arsenic contents of Arabidopsis shoots towards a phytoremediation purpose, and also some studies of secondary product modification. The role of RNAi in increasing resistance to viral, and bacterial pathogens, and nematodes, and in developing male sterility in plants is also discussed in that review. The 2004 review by Tang and Galili centered on the use of RNAi for improving the nutritional value of plant products, focusing on lysine and oil manipulation in seeds. These authors also discussed the mechanisms of RNA mediated gene suppression and provided a glimpse of how the next generation of knockdown tools may avoid undesirable effects of long dsRNAs produced by RNAi vectors on RNA-dependent protein kinase pathways. We make one more distinction regarding primary versus secondary metabolites. This relates to the lignins. These mostly ubiquitous, highly polymerized compounds are generally considered polymerized secondary products, perhaps because they are unique to plants and built from secondary product precursors. Secondary metabolites have been extensively exploited by man as flavorants, perfumes, drugs, etc. Some of the oldest known records indicate that medicinal recommendations for treating disease using plant products enriched in secondary metabolites were documented by the Chinese in 2735 BC in the writings of emperor Shen Nung, and the use of natural product drugs by the Chinese is thought to date back 5,000 years. Plant secondary metabolites have served as sources of modern drugs and drug leads for decades. A recent survey indicated that 61% of the 877 small molecule new chemicals introduced as drugs world-wide between 1981 and 2002 can be traced to, or were inspired by natural products [37]. These include natural products, 6%; natural product derivatives, 27%; and compounds synthetically designed after natural products. Many of these are higher plant products/product models [4]. Recent studies indicate that there is a greater similarity in the chemical diversity space (measure of structural properties) of successful drugs and natural products than successful drugs and combinatorial compounds, indicating that the diversity of chemistry found in nature continues to be superior for new drug discovery and that natural-product scaffolds may restore value to the combinatorial chemistry approach to drug discovery [42]. Given that there are about 250,000 species of flowering plants and only about 10% have been examined for pharmaceutical properties (many examined decades ago when techniques were relatively crude) there is much remaining potential for discovery of new drugs from plants. However, genomics based techniques are needed to explore this potential [45]. Multi-gene amiRNAi may well serve an important role in accelerating new drug discovery from plants

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 435

[8, 50]. If results of recent efforts to manipulate flower color are an indicator (see below), RNAi will certainly play a role in “re-tooling” plants that accumulate low levels of valuable secondary products into “factory” plants that can efficiently produce drugs and other valuable secondary compounds in quantity, and in a sustainable manner.

23.3 Survey of dsRNAi Use in Studying Plant Secondary Metabolism There are many studies in the literature describing the use of gene overexpression to alter plant secondary metabolism, some combined with antisense suppression (see reviews by [7, 13, 33, 43, 48, 56]. Here we survey only those papers in which RNAi has been employed. Tables 23.1–23.3 describe a survey (circa, late 2007) of papers in the recent literature that describe the use of RNAi for manipulating or phenotyping genes involved in plant secondary metabolism. It is noteworthy that the oldest of the published studies was published in 2003. Thus, the use of dsRNAi in plant secondary products research is recent, but growing rapidly. Much of the work thus far has centered on creating new phenotypes (altering flower color or fragrance, or reducing undesirable secondary products, e.g., lignin, gossypol). We apologize to authors of papers we may have missed, and authors of those in process that will appear before this volume is available, but we believe the papers cited adequately provide a view of the main advantageous outcomes of the dsRNAi approach over earlier gene knockdown methods. These outcomes are: 1. Generally, high efficiency of desired knockdown to allow facile DNA phenotyping or to allow substantial change in tissue phenotype, despite the use of various RNAi vectors or modified commercially obtained vectors, and the use of various small sized DNAs and cDNAs (≥300 nt) in different studies. Also, most studies produced several high knockdown plants allowing better confirmation of the phenotype concluded, or the product sought. 2. The not-uncommon observation of unexpected, additional phenotypes which may provide leads to understanding the targeted metabolism better. 3. The observation that knockdown of an enzyme efficiently competing for the same substrate as an introduced foreign enzyme can greatly enhance foreign gene product formation, particularly where the endogenous enzyme has a higher affinity for the substrate than the foreign enzyme. This represents a fine tuning/ optimization of metabolic engineering. Tables 23.1–23.3 are divided into papers related to the three groups of secondary products, the phenylpropanoids, the alkaloids, and the terpenoids. The studies are grouped according to similarity in objectives (e.g., lignin reduction, novel flower color or fragrance) and are numbered consecutively, to assist in their description only.

436

Table 23.1 A survey of studies involving RNAi knockdown of phenylpropanoid-related genes Study

Gene

1

Lignin reduction, functional analysis

Hydroxycinnamoyl transferase (HCT)

2

Lignin reduction, functional analysis

Hydroxycinnamoyl transferase (HCT)

3

Lignin reduction, functional analysis

Hydroxycinnamoyl transferase (HCT)

4

Lignin reduction, increase phenolics

Cinnamoyl-CoA reductase

5

Lignin reduction, improve the elastic properties

Cinnamyl alcohol dehydrogenase

Species and phenotype of primary trans- RNAi (%) Total # of genic plants efficiency TO Arabidopsis thaliana Most plants with severely reduced growth, darkgreen/purple coloration of leaves (flavonoid accumulation), and no floral stem Nicotiana bentamiana Changes in plant development, lignin content (15% reduction in stems), and structure (differential effect on G and S lignin units)b and susceptibility of the cell walls to enzymatic degradation. Pinus radiata (monterey pine) 42% reduction in lignin content in tracheary elements; increase of p-hydroxyphenyl units from trace amounts up to 31% Solanum lycopersicum L. (tomato) Reduced lignin content (20–37% lower than control), higher levels of soluble phenolic compounds in vegetative organs only; reduction of size; no fruits or limited number of small fruitsb, synthesis of hyroxycinnamate derivativesb Linum usitatissimum L. (flax)

Fragment length; RNAi vector

Ref.

Most

30,000 seeds

367-bp pFGC5941a

[22]

86

7

957-bp pTV00

[22]

78

56 callus lines

1302-bp pHF5 (pAH25 derivative)c

[65]

NG

16

420-bp pDV01 (pGreen0029 derivative)a

[62]

NG

11

506-bp pHellsgate2a

[73]

G.J. Wagner, A.B. Kroumova

Study focus

Novel color, functional analysis

Chalcone isomerase

7

Novel color

First, introduction of gerbera dihydroflavonol 4-reductase (DFR); Second, RNAi of the same plants with Flavonoid 3′5′-hydroxylase

8

Novel color

Result – accumulation of predominantly pelargonidin derivatives in flowers. Created orange hue. Anthocyanidin synthase Torenia hybrida (torenia) Dramatic decrease of anthocyanidins and some decrease of flavones;b paler or white novel colored flowers

89

12

543-bp pEBisHR35SintNtCHIira

[38]

100

5

544-bp pFGC 1008a

[51]

89

98

[35] 310 bp pSPB, (backbone from pBinPLUS)a

(continued)

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 437

6

Reduced total lignin (by 40%), pectin, and hemicelluloses;b improved elastic properties; decreased resistance to fungi (two-fold) N. tabacum Changed colors in flower petals and pollen; 25% reduction of anthocyanins in petals; accumulation of high levels of chalcone in pollen (yellow coloration) Osteospermum hybrida (osteospermum)

438

Table 23.1 (continued) Species and phenotype of primary trans- RNAi (%) Total # of genic plants efficiency TO

Study focus

Gene

9

Novel color

10

Novel color

11

Novel color

Knockdown of endogTorenia hybrida (torenia) Down regulaenous dihydroflation of anthocyanin biosynthesis vonol 4-reductase promotes flavonoid metabolic flux (DFR) or flavanonetoward aurusidin 6-O-glucoside in 3-hydroxylase and flowers (bright yellow). Unexpected coexpression of hetbiosynthetic pathwayb erologous chalcone 4′-O-glucosyltrasferase and auresidin synthase Knockdown of flavonol Nicotiana tabacum (tobacco) High synthase and flaamounts of pelargonidin and vanone-3-hydroxyreduced amounts of flavonols lase and expression of heterologous dihydroflavonol 4reductase (DFR) Knockdown of endogRosa hybrida Accumulation of delphienous dihydroflanidin in the petals (blue hues) with vonol 4-reductase absence of cyanidin and pelargo(DFR) and overnidin. expression of both iris DFR and viola flavonoid 3′5′hydroxylase

Fragment length; RNAi vector

Ref.

56

71

length not givenp SFL308a

[40]

45

> 10

500 bp pEBisBR35gerberaDFR35intFLS: Φ3′Ηιρ1α

[36]

67

NG

300-bp pSPB919

[27] G.J. Wagner, A.B. Kroumova

Study

13

14

15

16

Fragrance change, functional analysis

Benzoic acid/salicylic Petunia x hybrida 75–99% decrease in acid carboxyl methylbenzoate emission (reduced methyltransferase fragrance) PhBSMT1 and 2 Functional analysis, Phenylacetaldehyde syn- Petunia hybrida Complete suppression thase PAAS fragrance related of phenylacetaldehyde and 2-phenylethanol emission Functional analysis, Benzoyl-CoA:benzyl Petunia hybrida Complete to partial alcohol/2-phenylethfragrance related knockdown of BPBT transcripts and anol benzoyltranscorresponding BB emission (10– ferase BPBT 91% of control); 1.7 fold increased benzylaldehyde and 1.6-fold reduced methylbenzoate; changed overall morphology of knockout plantsb Functional analysis, Coniferyl alcohol acyl- Petunia x hybrida Decreased synthetransferase PhCFAT fragrance related sis and emission of isoeugenol and 5 other volatiles;b 5x and 10x increased coniferyl aldehyde and homovanillic acid in the petals. Functional analysis, R2R3 MYB-type tranfragrance related scription factor ODORANT1

Petunia hybrida Strong reduction of volatile benzenoids (12x reduced benzoic acid); downregulation of genes from the shikimate pathway; upregulation of BSMTb and stable methyl salicylate levelsb

NG

11

341-bpa

[60]

100

5

464-bp pART27a

[26]

100

30

350-bp pEF1.LISBEBTia

[41]

19

16

334 and 661-bpa

[12]

10

39

303-bp pK7GW IWG2(I)

[63]

(continued)

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 439

12

440

Table 23.1 (continued) Study

Study focus

Gene

17

Gene phenotyping

Chalcone synthase (CHS)

18

Gene phenotyping

19

To increase nutritional value

20

Root nodulation

Species and phenotype of primary trans- RNAi (%) Total # of genic plants efficiency TO

Ref.

303 bp pBI-CHSi (pBI121 derivative)a

[23]

100

21 Agrobacterium -infiltrated fruits 30 roots

521-bppCAM-sUbi: GFPd

[54]

75

117

520-bp pSVS297nosa

[11]

75

127

543-bp pHellsgate8d

[71]

100

G.J. Wagner, A.B. Kroumova

Fragaria x ananassa cv. Elsanta (strawberry fruit) Downregulated anthocyanin and a large increase in levels of (hydroxyl) cinnamoyl glucose esters; reduction of the transcript levels was 80%; white or chimeric fruits Isoflavone synthase Glycine Max (soybean) 60–95% reduction of isoflavone levels in roots; enhanced susceptibility to Phytophthora sojae in roots and nontransformed cotyledon tissues. Distal silencing was transient (5–7 days posttransformation) De-etiolated1 DET1 Solanum lycopersicum L. Significant increase in carotenoid and flavonoid contents of fruits. Chalcone synthase CHS Medicago truncatula No nodulation due to the deficiency in flavonoids, altered auxin transport

Fragment length; RNAi vector

22

a

Gene phenotyping

Eight separate RNAi Torenia fournieri (torenia) 1. Ubiquitin 100 for 6 NG experiments conjugating enzyme and Glutatione RNAi Glutatione SS-Transferase 2; Results: – no downexperiTransferase 1 and 2, regulation. 2. Anthocyanidin synments ubiquitin conjugating thase and Glutatione S-Transferase1; enzyme, putative Results: – low anthocyanin and low cullin, anthocyanidin chlophyll content; 3. Putative cullin, synthase, putative flowering-time gene, glutathione flowering-time gene, conjugate transporter, and GPTV; GPT and the gluResults: – low anthocyanin and high tathione conjugate chlorophyll level. transporter. 100 15 Study role of flavo- Chalcone synthase CHS Solanum lycopersicum L. Various noids in reprodegrees of reduced total flavonoid duction and fruit levels; fruit partenocarpyb and mordevelopment phological variabilityb

Transformations with A. tumefaciens Unexpected results c Biolistic particle bombardment with a plasmid d Transformations with A. rhizogenes NG: Not given Knockdown efficiency (suppressed lines/total lines analyzed × 100) b

544-bp pPANDA35HKa

[34]

801-bp pHEAP-20 (pFLAP50derived)a

[49]

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 441

21

442

Table 23.2 A survey of studies involving RNAi knockdown of alkaloid-related genes

Study

Study focus

Gene

23

Decafeination

Theobromine synthase

24

Nornicotine reduction Nornicotine reduction Narcotic reduction

25 26

Coffee Arabica and C. canephora Embryos and plantlets showed reduction of both theobromine and caffeine content (by 30–50%). Additional suppression of xanthosine methyltransferase 1 (50–80% that of the control) and caffeine synthaseb Nicotine NNicotiana tabacum Suppressed nicotine to nornicodemethylase nine conversion to 0.8% Nicotine NNicotiana tabacum Suppressed nicotine to nornicodemethylase nine conversion to very low levels Codeinone Papaver somniferum (opium poppy) High retireductase culine phenotype:b accumulation of reticuline and its methylated derivatives; no detectable morphine, codeine, oripavineb and thebaineb

Narcotic reduction

Salutaridinol 7-O-acetyltransferase

28

Narcotic reduction

Berberine bridge enzyme

Total # of TO

Fragment length; RNAi vectora

100

14

332-bp 139-bp pBIH1-IG

100

20

298-bp pKYLX71 [18]

84 (to ≤1% conversion) 76

NG

NG

18

336-bp Cor1 242-bp Cor2 pPLEX X002i Only abstract available

Papaver somniferum Accumulation of salutaridine NG at up to 23% of total alkaloids; reduction in salutaridinol 7-O-acetyltransferase transcript to 12% of control Eschscholzia californica cells (California poppy) 76 Accumulation of reticuline; considerable reduction of end products of the pathway (such as sanguinarine); the level of BBE transcript was 2% of control

Transformations with A. tumefaciens Unexpected phenotypes Knockdown efficiency (suppressed lines/total lines analyzed × 100)

b

Knockdown efficiency (%)

16

37 cell lines

1100-bp pART27

Ref. [39]

[Xu et al. 2007] [1]

[2]

[17]

G.J. Wagner, A.B. Kroumova

27

a

Species and phenotype of primary transgenic plants

Study

Study focus

29

Altered terpe- CBT-ol hydrones, insect xylase resistance

30

Altered terpe- CBT-ol cyclase nes

31

Cadinene Gossypol reduction synthase

32

Gene pheno- Dammarenediol typing synthase CarotenoidGene phenotyping associated proteinsa

33

34

a

Gene

Reduce cya- P450CYP79D1a nogenic P450CYglycosides P79D2a

Species and phenotype of primary transgenic plants Nicotiana tabacum (tobacco) High to moderate suppression of CBT-diol synthesis and corresponding increase of CBT-ols. Increased aphid resistance. Nicotiana tabacum Strong reduction of CBT-diols, appearance of labdendiol, and enhancement of cis-abienol G. hirsutum (cotton) Seeds have different levels of gossypol reduction, down to 1% of control Panax ginseng (ginseng) Reduction of ginsenoside down to 15.5% of control Lycopersicon esculentum (tomato) Flowers accumulated 30% less carotenoids/unit protein in corollas and were significantly more susceptible to Botrytis cinerea infectionc Manihot esculenta Crantz (cassava) Reduced cyanogenic glucoside content in leaves (<1– <25% of control) and tubers (8–50% of control)

Not terpenoid-related Transformations with A. tumefaciens c Unexpected phenotypes Knockdown efficiency (suppressed lines/total lines analyzed × 100) b

Knockdown efficiency (%)

Total # of TO

Fragment length; RNAi vectorb

45

11

1,025-bp pKYLX71–35S2

[69]

64

28

699-bp pKYLX71– 35S2

[69]

NG

26

[55]

14

37

NG

37

604-bp pAGP-iHPdCD (pATR27 derivative) 249-bp pK7GWIWG2 (I) 530 bp pART27

60

300

Ref.

[21] [30]

300-bp of CYP79D1 [25] 330-bp of CYP79D2 pPS48

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 443

Table 23.3 A survey of studies involving RNAi knockdown of terpenoid-related genes and other genesa

444

23.3.1

G.J. Wagner, A.B. Kroumova

Phenylpropanoid Metabolism

As already noted, to date many of the studies applying dsRNAi to secondary metabolism have targeted phenylpropanoid metabolism, and many of these have focused on reducing lignin contents of plants (to improve paper pulping, forage digestibility, stem elasticity, or fermentable sugar yields for biofuels production [9]; or for modifying flavonoid metabolism to alter flower color or fragrance to produce horticultural novelty [43, 56]. Most recent efforts to reduce lignin using RNAi were spurred by the discovery by Hoffmann et al. [6, 22] of the enzyme hydroxycinnamoyl-CoA:shikimate hydroxycinnamoyltransferase (HCT), a key enzyme in the biosynthesis of lignin in angiosperms. Knockdown of the HCT gene (studies 1, 2, 3 in Table 23.1) in Arabidopsis, N. bentamiana and Pinus radiate all led to the substantially reduced lignin content in lignified tissues. In Arabidopsis, a coincident, somewhat surprising, increase in flavonoids was reported. Alteration in growth was linked to flavonoid accumulation. Knockdown levels in tobacco and pine were reported to be 15% and 42% in stem and tracheary elements, respectively. Surprisingly, in the N. bentamiana study, differential effects on guaiacyl and syringyl units of lignin were found. In study 4, van der Rest et al. suppressed CCR (cinnamoyl-CoA reductase) in tomato in order to cause accumulation of soluble, health-related phenolics. They observed a 20–37% reduction in lignin, increased chlorogenic acid and rutin, but also, surprisingly, the appearance of N-caffeoyl putrescine and kaempferol rutinoside, compounds not found in the wild type. Antisense has been used to substantially suppress HCT and CCR [9, 64], respectively). While it is difficult to compare the efficiency of lignin reduction by the two approaches, both methods have been used to achieve substantial reduction. Since genetically engineered lignin reduction for improving forage digestibility, paper pulping, and bio-fuel production will undoubtedly reach commercial use rapidly, this case may provide a measure of the relative knockdown efficiency and stability of these two methods, at least when applied to lignin reduction. It will be interesting to see which approach proves best for achieving the ideal balance between retention of structural properties and reduced lignin level. In study 5, RNAi of cinnamyl alcohol reductase was used to reduce lignin contents of flax to modify fiber elastic properties. Lignin was reduced by 40%. Increased susceptibility to Fusarium oxysporum was expected and observed. However, the reduced pectin and hemicelluloses observed was not anticipated. Manipulation of the flavonoid branch of the phenylpropanoid pathway using RNAi has led to numerous novel flower colors (studies 6–11), reduced seed coat pigment, altered nodulation, and other effects (studies 12–17). Reduction in chalcone isomerase in N. tabacum (study 6) led to reduced petal pigment and accumulation of chalcone and yellow coloration in pollen. In the study by Seitz et al. (study 7) anthocyanin biosynthesis was redirected in Osteospermum towards pelargonidin derivatives to yield orange-hued flowers. In this study, like studies 9–11, the desired color change required overexpression of a gene conferring a novel color component in combination with knockdown of the endogenous enzyme, usually a dihydroflavonol-4-reductase (DFR) that competes for the common substrate of the

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 445

introduced enzyme. In study 7, the overexpression of a gene for a orange-conferring DFR from Gerbera hybrida in combination with RNAi suppression of endogenous flavonoid 3’, 5’-hydroxylase led to the desired flower color. A co-suppression experiment towards the same purpose was said to have largely failed. In study 8, white flowered Torenia was produced by suppression of anthocyanidin synthase, the enzyme that converts leucopelargonidin, lecuocyanidin, and lecuodelphinidin to their respective anthocyanidins. In this study antisense, sense and dsRNAi were compared. Antisense and sense suppression yielded few or no white flowers while about ½ of RNAi plant flowers were white, and 38% were variably paler in color. Variability in floral color is a valuable characteristic in the horticulture industry. Antisense and sense application were said to yield only 1% and 0% suppression, respectively. The white RNAi phenotype was said to be stable for 1 year in the greenhouse. The successful objective of study 9 was to produce yellow flowers in Torenia by down-regulation of anthocyanidin biosynthesis and overexpression of two key enzyme for synthesis of aurone flavonoids. Further, overexpressed proteins were localized as chimeric fusions with GFP. Results indicated that aurone 6-Oglucosides were formed in the vacuole from tonoplast transported 4’-O-glucosides, a novel and unexpected finding. Similarly, Nakatsuka et al., (study 10) suppressed two enzymes of flavanol synthesis and overexpressed a foreign DFR to increase pelargonidin pigment and produce a novel red flower color in tobacco. In this RNAi study a fusion construct containing three genes (two of these for dsRNAi suppression of flavonone synthase and flavanone-3-hydroxylase, and one for overexpression of DFR) was compared with a RNAi construct for suppression of flavonone synthase alone. The fusion was found to be less efficient than the single construct in suppression of cyanidin synthesis, perhaps due to structural properties of the (>1 kb) sequence of the fusion construct. amiRNA suppression could be effective in such a case where facile, multiple gene knockdown is desirable. In study 11, the elusive “blue” rose was obtained by introducing a viola flavonoid 3’5’-hydroxylase to cause delphinidin production, suppression of endogenous dihydroflavonol 4-reductase (DFR), and overexpression of Iris x hollandica DFR. The reduction of carbon flow towards pelargonidin and cyanidin synthesis due to reduction of endogenous DFR allowed efficient and lone blue pigment formation in certain lines. Like the study by Seitz et al., advantage was made of differences in substrate specificities of DFR enzymes from different species to direct carbon from dihydrokeampherol to different colored anthocyanidins. But in the Katsumoto study, a foreign DFR was substituted for the endogenous activity to avoid more efficient carbon flow towards cyanidin synthesis. This represents a fine tuning of the requirements for specific product production by substitution of a more suitable (for the purpose) enzyme than its endogenous counterpart. One would expect that such fine tuning would minimize possible unwanted alterations in flavonoid biosynthesis that could impact regulatory roles of flavonoids [59]. Studies 12–16 all relate to the production of volatile organic compounds (VOCs) of flowers that contribute to floral scent. In study 12, two 99% identical benzoic acid/salicylic acid carboxyl methyltransferase genes were suppressed in petunia using a knockdown construct targeting one of the genes. Transgenic flowers with

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reduced mRNA levels for both genes showed a 75–99% reduction in methylbenzoate emission, with minimal changes in other petunia VOCs. Human sensory panels were able to discriminate between fragrance of knockdown and control flowers. In study 13, the gene encoding phenylacetaldehyde synthase was suppressed in petunia to study its properties. RNAi knockdown led to complete suppression of phenylacetaldehyde and 2-phenylethanol emission by flowers, providing genetic evidence for the role of the synthase in phenylacetaldehyde formation, and indicating that this compound is a precursor to 2-phenylethanol. Study 14 focused on testing the hypothesis that benzylbenzoate is an intermediate in the synthesis of benzoic acid from phenylalanine. The enzyme benzoyl-CoA:benzyl alcohol/2-phenylethanol benzoyltransferase which catalizes formation of benzylbenzoate, was suppressed to yield 50% of transgenic plants with no benzybenzoate emission, and 50% with reduced emission. Benzylaldehyde was increased and methylbenzoate was decreased. Several knockdown lines had altered growth phenotypes that correlated with altered auxin transport capacity. As described in study 20, several flavonoids are known to impact auxin transport. In study 15, a petunia gene encoding an enzyme that apparently converts coniferyl alcohol to isoeugenol (PhCFAT, coniferyl alcohol acyltransferase) was isolated and its activity correlated (by tissue transcript localization and developmental stage of transcript occurrence) with VOC production. To provide genetic evidence for function, RNAi was employed. Isoeugenol emission was reduced by 90% in PhCFAT knockdown plants. Accumulation of coniferyl alcohol was not found, but high levels of its likely metabolic products (coniferyl aldehyde and homovanillic acid) were observed. Unexpectedly, emissions of several other VOCs were decreased. Further study is needed to determine if this result was due to knockdown of related genes, or uncharacterized metabolic responses. Study 16 stemmed from the recent discovery of a transcription factor (ODORANT1) that is shown to regulate fragrance in petunia flowers. ODORANT1 is apparently the first transcription factor discovered that controls fragrance formation in plants. Study 16 shows that ODORANT1 appears to specifically regulate the shikimate pathway towards benzenoid formation in petunia petals. Transcript levels of seven shikimate pathway genes were reduced by suppression of ODORANT1. But, surprisingly, its knockdown increased transcript levels of one pathway enzyme of shikimate biosynthesis and did not appear to substantially impact another. Flower pigment was not affected, likely because pigment and scent formation occur at different development stages. The studies of RNAi manipulation of the ODORANT1 and DET-1 (studies 16 and 19 [see below], respectively) are undoubtedly forerunners of many more efforts to study the functions of transcription factors that impact secondary metabolism. Suppression of transcription factors that are apparently quite specific (e.g., ODORANT1) and those having more pleiotropic impacts (e.g., DET-1) will undoubtedly reveal many new aspects of secondary metabolism and regulation. In study 17, chalcone synthase was suppressed in strawberry fruits that were injected with an RNAi construct targeting this gene. Anthocyanin biosynthesis was reduced and flavonoid metabolism was shunted towards production of the hydroxyl cinnamoyl glucose esters, caffeoyl glucose and feruloyl glucose. In contrast, in an

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 447

earlier study constitutive antisense suppression of this gene caused lower levels of flavonoids than control because flavonoids are synthesized early in fruit development. Thus, the RNAi construct injection approach served as an alternative to inducible, tissue-specific RNAi in this situation. Studies 18, 19, were made for the main purposes of phenotyping one or more genes in flavonoid pathways or to use RNAi reverse genetics to provide genetic evidence for gene function. In the first, isoflavone synthase, a key enzyme in isoflavone synthesis was silenced causing a breakdown in R-gene mediated resistance to Phytophthora sojoe in roots. Results provide molecular genetic evidence for the role of isoflavones in soybean disease resistance. Davuluri et al., (study 19) utilized RNAi to suppress, fruit-specifically, the endogenous photomorphogenesis gene DET1 in tomato. The objective was to increase tomato fruit nutritional value by enhancing flavonoids and carotenoids. These were increased substantially, without affecting other parameters of fruit quality, or presumably plant growth and development. Thus, RNAi of this light-responsive, pleiotropic, transcription regulating gene (transcription factor gene) was found to be highly selective in this case, perhaps because knockdown was highly restricted to fruits. In study 20, chalcone synthase, the first committed step in the flavonoid synthetic pathway, was silenced to determine effects on nodulation. Silenced roots were deficient in flavonoids, were unable to initiate nodulation, and showed increased auxin transport, consistent with known inhibitory effects of flavonols on auxin transport. Results provide genetic evidence that root flavonols are necessary for nodule formation and that they act as auxin transport regulators. Study 21 was designed to probe the mechanisms involved in anthocyanin and chlorophyll degradation induced by osmotic stress in Torenia. Suppression hybridization was used to enrich in cDNAs of genes related to osmotic stress induced reduction of anthocyanin synthesis and chlorophyll degradation. Eight cDNAs were selected for RNAi knockdown. Results identified several genes that may contribute to elucidating the mechanisms underlying stress induced effects on anthocyanin and chlorophyll. In study 22, Schijlen et al., suppressed chalcone synthase (both Chs1 and Chs2) and found that nearly completely suppressed lines developed parthenocarpic fruits. It is known that flavanoids are involved in male sterility by effecting pollen tube germination and growth. The suppression phenomenon was pollination-dependent. The parthenocarpy observed would probably not have been seen if suppression efficiency was less than near complete. This unexpected finding offers an approach for producing seedless fruits, a trait favorable for direct consumption and processing of certain fruits.

23.3.2

Alkaloid Metabolism

Recent studies that used RNAi to probe alkaloid metabolism are described in Table 23.2. In study 23, theobromine synthase was targeted in two Coffee species in an effort to reduce theobromine and caffeine levels of embryonic tissues and plantlets. The suppression of these isoquinoline alkaloid pathway end products

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was 30–50%. Surprisingly, activities of two other methyltransferase enzymes in the pathway to caffeine were also reduced (by 50–80%). It was suggested that this effect may be a result of a >90% similarity in the coding regions of the three genes involved. This explaination was favored over one that invoked interference at the metabolic regulatory level. Gavilano et al. (study 24) suppressed a nicotine N-demethylase gene in tobacco in order to reduce formation of the undesirable compound nornicotine from nicotine. An optimized RNAi construct reduced conversion from a control level of 98% to as low as 0.8%. Towards the same objective, Xu et al. (study 25), showed that RNAi knockdown of an independently isolated tobacco nicotine N-demethylase gene reduced nornicotine formation levels in two tobaccos – in one levels were reduced to 0–0.2% in 33% of plants, and 0.3–0.5% in 26% of plants. Thus reduction to <0.5% occurred in 59% of transgenic plants. The high suppression was said to be stable through advanced generations. In study 26, RNAi was used to enhance the production of non-narcotic precursors of codeine and morphine in the opium poppy, because these precursors (that have anti-malarial and other useful properties) are normally minor, transitory intermediates. The gene encoding codeinone reductase, the oxidoreductase enzyme penultimate in codeine and morphine synthesis, was targeted by Allen et al. (study 26). Surprisingly, the intermediate alkaloid (S)-reticuline (7 enzymatic steps upstream of codeine) accumulated in transformants at the expense of codeine, morphine and two other intermediates downstream of (S)-reticuline, a branch-point intermediate in isoquinoline alkaloid biosynthesis. Transcripts of genes encoding the seven preceding enzymes were unaffected in transgenics. Various metabolic regulatory possibilities were considered for the unexpected findings. Results suggest a number of questions that may lead to a better understanding of the morphinan-alkaloid branch pathway. In a continuation of their work on this general pathway (study 27), Allen et al. both overexpressed and RNAi suppressed the enzyme salutaridinol 7-O-acetyltransferase that produces the precursor to thebaine, three steps above codeine and morphine. Overexpressing plants had about 40% increased total alkaloids in independent trials over 3 years. RNAi suppression of this gene caused accumulation of the normally undetectable intermediate salutaridine, to 23% of total alkaloids. Salutaridine is not the precursor of the targerted enzyme, but of the enzyme preceding it, salutaridine reductase. This principal result, like that of study 26, exemplifies how RNAi can open new avenues of metabolic study. The last study of Table 23.2 (study 28) the gene encoding berberine bridge enzyme (BBE) was highly suppressed in California poppy cultured cells using RNAi. This enzyme provides for entry of carbon from (S)-reticuline to the benzophenanthridine branch of isoquinoline alkaloid biosynthesis. End products of this branch pathway were highly reduced, while reticuline was accumulated, and indeed secreted to the culture medium. A methylated derivative of reticuline, (S)-laudanine that occurs only in trace levels in control cells, was also found in transformants. The level of BBE transcript was 2% of control. As in many of the above studies, a number of observations made would likely have been missed if suppression level achieved had only been modest, or if only a few knockdown plants had been obtained.

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 449

23.3.3

Terpenoid Metabolism

The application of RNAi to terpenoid metabolism has not been as extensive as its use in studying and manipulating phenylpropanoid and alkaloid metabolism. However, its counterpart, antisense, has been successfully applied to manipulating, at least, monoterpenoid metabolism [32]. Efficiency of knockdown in that study was about 6%. Studies 29 and 30 will be discussed below as part of a case study of trichome diterpene modification, so these works will not be summarized at this point. In study 31, cadinene synthase, the first committed step in the synthesis of the cardio- and hepatotoxic, sesquiterpene gossypol, was suppressed in cotton seed. Seeds of several transformed lines were said to have 1% of control level gossypol. The use of a seed specific promoter allowed seed-specific gossypol suppression, allowing retention of this pest resistance conferring compound in leaves and flowers. The study by Han et al. (study 32) sought to demonstrate genetically that oxidosqualene cyclase, the first committed step enzyme in the synthesis of ginsenosides (triterpenoid saponins) of ginseng was key in the formation of these pharmacologically-active compounds. RNAi silencing of this gene led to ~85% reduction in ginsenoside production in roots. Study 33 was undertaken to assess the role of plastid lipid-associated protein LeCHRC in chromoplastogenesis and stress in tomato. This protein is involved in the sequestration/stabilization of hyperaccumulated carotenoids in developing flower and fruit chromoplasts. Flowers of transgenic plants accumulated ~30% less carotenoids than controls. Suppressed plants were also more susceptible to Botrytis cinerea infection. Since certain plastid lipid associated proteins are induced and accumulated by plant stresses, it was suggested that increased Botrytis sensitivity was due to reduced plastid lipid-associated protein. In study 34, RNAi was used to reduce the cyanogenic glucoside contents of cassava, an extremely important food crop, particularly in third world countries. The presence of potential-cyanide-generating cyanogenic glucosides in cassava requires careful processing during food preparation, which results in loss of nutritional value. The first committed steps in the biosynthesis of cassava cyanogenic glucosides are catalyzed by the P450 enzymes CYP79D1 and CYP79D2. A fusion RNAi construct was prepared to simultaneously knock down both genes and allow localization of gene expression via GUS. Of 300 independent transgenic lines, 180 were found to have <1% of wild type cassava cyanogenic glucosides.

23.4

The Use of RNAi to Study Diterpeniod Biosynthesis and Function in Tobacco Trichome Glands – A Case Study

Here we describe the tobacco trichome system used in our research (studies 29 and 30) as a case study because it can help to emphasize several of the advantages of dsRNAi application that have been reiterated throughout this review, namely that: dsRNAi generally results in highly efficient, and therefore easily observed gene

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knockdown, even when one begins with a partial cDNA; that dsRNAi often gives several lines in a knockdown population that are highly suppressed, multiple lines that can serve to add confidence-of-numbers to a phenotyping experiment that a single line, e.g., from a low efficiency knockdown approach cannot provide; that in some cases dsRNAi causes gene suppression or altered metabolism that is not entirely gene-specific, a situation that can lead to unexpected results and therefore additional discovery. Outstanding characteristics of the tobacco trichome system are that: the chemical composition of products produced by trichome glands is relatively simple and easily analyzed; that trichome gland specific genes can be easily isolated; that RNAi is easily applied to functional characterization of trichome-specific partial cDNAs obtained from trichome specific mRNAs; and that products of the genes involved are not essential to growth and development. Also, tobacco is easily and rapidly transformed using Agrobacterium tumefaciens (in T.I. 1068, about 1 month from Agro infection to shooted/rooted seedlings) using very well established procedures. Results obtained to date point out advantages and serendipity brought by dsRNAi in our efforts to characterize regulation of carbon flow between what are probably two different diterpenoid branch pathways from a common precursor. A general description of the biology and chemistry of the trichome system is in order at this point. Most tobaccos bear tall trichomes (hairs) on their aerial surfaces that have glands which produce copious exudates (secretions) that contain a limited number of diterpenoids, and also sugar esters. These exudates can reach levels of 17% of leaf dry weight in our model experimental tobacco (Nicotiana tabacum T.I. 1068). Exudates accumulate under the cuticle surrounding the gland, but can escape this containment and flow to the epidermal surface (like molten wax on a candle), then disperse on the epidermal surface via depressions between anticlinal walls of epidermal cells. Fungal spores, bacteria or insects contact exudate compounds at the plant surface, and inhibition of specific, susceptible microbes or insects may occur. Thus trichome exudates can serve as a first line of defense against certain exudate-compound-sensitive fungi, bacteria or insects. Also, in tobaccos producing abundant exudates, amphipathic components can physically entrap insects or occlude their feeding parts, and thereby reduce infestation and damage [66, 67]. The diterpenoids exudated by the experimental tobacco, N. tabacum, T.I. 1068, and the proposed pathways leading to their synthesis are shown in Fig. 23.1. The main components are the macrocyclic cembratriene diols (α and β isomers, only the α isomer is shown), their precursor cembratriene-ols, and the bicyclic compounds cis-abienol, and labdenediol. These compounds constitute at least ~60%, ~1.4%, ~9%, and ~0.6% of trichome exudate weight, respectively. Sucrose esters make up ~24%. Thus, these compounds comprise the bulk of T.I. 1068 trichome exudate. Total exudate can easily be recovered for direct, rapid analysis/use from aerial surfaces by washing with an appropriate solvent. Biosynthetically-competent trichomes can be physically removed in quantity and used for metabolic studies, enzyme isolation, and mRNA isolation. cDNA derived from mRNAs can be employed for cDNA/gene phenotyping using RNAi. An important advantage of the trichome system is that it is non-essential nature, so complete

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 451

Fig. 23.1 Working model for the synthesis of N. tabacum trichome exudate diterpenes. Enzyme A and B were phenotyped as CBT-ol cyclase and CYP71D16 (CBT-ol hydroxylase), respectively. Enzyme C is a putitative cis-abienol cyclase. Earlier biochemical studies are consistent with this scheme. The values in parentheses are the percentage of total wild type trichome exudate weight contributed by each compound shown

knockdowns do not effect plant growth and development or seed germination, obviating the need for the use of tissue specific or inducible promoters when manipulating exudate related genes. Also, much is known about the interactions between particular diterpenoids of T.I. 1068 trichome exudate and various insect and microbial pathogens of tobaccos [24]. We have exploited this system to explore the biochemistry of diterpenoid synthesis, for isolation of trichome genes involved in exudate chemical synthesis, and using dsRNAi, for the phenotyping of genes involved in order to study the regulation of carbon flow between the various diterpenoids produced. These characterizations led to studies of the relationship between trichome exudate chemistry and plant-aphid interactions. The working model for biosynthesis of tobacco trichome diterpenes from the common precursor GGPP is shown in Fig. 23.1. This model is constructed from biochemical studies [19, 20], and dsRNAi reverse genetics [69, 70], EW & GW, 2006.

452

23.4.1

G.J. Wagner, A.B. Kroumova

dsRNAi Efficiency

The efficiency of antisense, sense and dsRNAi suppression was compared directly for two tobacco trichome specific genes [69], the CBT-ol synthase (diterpenoid cyclase, reaction A, Fig. 23.1), and CBT-ol hydroxylase, CYP71D16 (P450, reaction B, Fig. 23.1: in this case two different hairpin loop sequences were tested). As shown in Table 23.4, suppression efficiency (suppressed lines/total lines analyzed × 100) of the P450 CYP71D16 gene using dsRNAi was ~45%, irrespective of the hairpin loop used while that using full-length sense or antisense constructs was ~20%. Partial length sense or antisense constructs gave very little suppression. A comparison of the CBT-ol synthase gene gave similar results in that suppression efficiency with dsRNAi was ~64%, while full-length antisense or sense suppression yielded 6% and 20% suppression, respectively. Partial length sense and antisense gave no suppression. dsRNAi efficiency obtained for these two genes is similar to the mean calculated efficiency (74.4% +/− 27.6%) for all studies surveyed in Tables 23.1–23.3 (calculated where data was available). As noted in discussion of survey results, certain critical serendipitous observations made using dsRNAi would likely have been missed if the method were less efficient (e.g., parthenocarpy observed in study 22).

23.4.2

Degree of Knockdown in Suppressed Populations

Another aspect of knockdown efficiency is the degree of knockdown among suppressed plants produced using dsRNAi. This aspect impacts the number of

Table 23.4 Suppression efficiencies of different RNAi silencing constructs for the P450 CYP71D16 gene and the CBT-ol cyclase gene. (A) PIHP intron hairpin, PGHP length antisense suppression, PPS partial sense co-suppression, PPAS partial antisense suppression. (B) CGHP GUS hairpin, CFS full-length sense co-suppression, CFAS full-length antisense suppression, CPS partial sense co-suppression, CPAS partial antisense suppression. Percent of suppressed plants relative to the total number of transgenic plants analyzed is shown in parentheses [69] A – P450 Constructs No of plants observed Suppression efficiency CGHP CFS CFAS CPS CPAS

28 20 16 30 30

18 (16.4%) 4 (20%) 1 (6%) 0 (0%) 0 (0%)

B – CBT-ol cyclase Constructs

No of plants observed

Suppression efficiency

PIHP PGHP PFS PFAS PPS PPAS

11 23 29 28 29 30

5 (45%) 10 (44%) 6 (21%) 5 (18%) 0 (0%) 1 (3%)

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 453

suppressed lines obtained in a study which can be further characterized to substantiate the principal findings of the study. Figure 23.2 shows the range of the degree of suppression in knockdown populations obtained in two studies. As shown for two genes of diterpene synthesis (Fig. 23.2A and 23.2B, reactions A and B, Fig. 23.1) and one for nicotine N-demethylase gene knockdown (Fig. 23.2C, see study 25) degrees of suppression were skewed towards the high end. This result is suggested in other studies surveyed as well (e.g., studies 8 and 14). We do not speculate on the mechanism involved but point out that this is a generally useful effect. However, as argued for the advantage of the antisense approach in animal therapeutics, a high degree of knockdown may not be acceptable for certain purposes [44].

23.4.3

From Reverse Genetics to Physiological Relevance

The ability to rapidly progress experimentally from a suspect cDNA, to functional characterization of the corresponding gene, to studies relating the involvement of the gene product’s (enzyme) product (secondary compound) involvement in complex interactions such as plant-insect interactions can be provided by RNAi, in no small part because of the efficiency and high degree of suppression this approach affords (discussed above). Our identification of the function of a tobacco trichome gland specific P450-like cDNA obtained via a subtraction EST library (pure trichome mRNA minus trichome-free leaf tissue mRNA) immediately presented the possibility of confirming and extending the observations of others that topical application (spraying) of CBT-ol (a main product of the P450 knockdown) on to leaves of a tobacco easily colonized by aphids inhibits colonization. The CBT-ol content of control and highly-suppressed P450 gene RNAi lines were ~1.4% and ~27% of trichome exudate weight, respectively. First we applied total exudates from a P450 knockdown line to the abdomen of aphids and observed an increase in LD50 relative to control. Then colonization tests in the greenhouse showed that P450 suppressed plants were highly resistant to colonization from adjacent colonized control plants [70]. In a final test of efficacy, we examined aphid resistance of P450 suppressed plants in the field. A statistically significant correlation was found between CBT-ol levels and degree of reduced aphid colonization [68].

23.4.4

Unexpected Results Can Lead to Deeper Questions

Analysis of the dsRNAi experiments surveyed showed that at least 35% of studies revealed unexpected results that suggested new avenues for research. While knockdown of the P450 gene described above and a CBT-ol cyclase (encoding enzyme A, Fig. 23.1) gave clear cut results that are consistent with the working model shown in Fig. 23.1 and earlier biochemical studies, suppression of another trichome gland cDNA (designated 3–8) with terpene cyclase characteristics gave somewhat

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p450 Knockdown 60

% of plants

50 40 30 20 10 0 0.1

0.2

0.4

Ratio α-Diols/α-Monols

CBT-ol Cyclase Knockdown 100

% of plants

80 60 40 20 0 0.0

0.7 Ratio α-Diol/cis-Abienol

Nicotine-N-demethylase Knockdown 60

% of plants

50 40 30 20 10 0

0-0.5

0.6-1

1.1-2.2

>2.2

% Conversion of Nicotine

Fig. 23.2 Degree of suppression in populations of RNAi knockdown plants found for three genes. A- Suppression of CYP71D16 (enzyme B, Fig. 23.1) expressed as the ratio of α-CBTdiol/ α-CBTol versus percentage of total number (10) of knockdown plants. B- Suppression of CBT-ol cyclase (enzyme A, Fig. 23.1) expressed as the ratio of α-CBT-diol/cis-abienol versus percentage of total number (17) of knockdown plants. C- Suppression of nicotine N-demethylase expressed as percentage conversion of nicotine versus percentage of total number (166) of knockdown plants (study 25). As shown, in all cases the degree of knockdown was heavily weighted towards very high knockdown

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 455

unexpected results. dsRNAi of this cDNA showed highly suppressed cis-abienol and greatly increased labdenediol, suggesting that carbon flow in the bicyclic branch pathway was diverted from cis-abienol to labdenediol. In control, cis-abienol comprises ~9% of exudate weight while labdenediol makes up ~0.5%. In 3–8 knockdown plants, formation of CBT-ols was also suppressed substantially, suggesting that 3–8 and CBT-ol cyclase sequences are sufficiently similar to cause suppression of both, or metabolic regulation was impacted. Recently, amiRNA suppression using a 21 nt sequence of 3–8 that is unique to 3–8 gave a similar suppression phenotype, perhaps suggesting regulatory crosstalk in modeled branch pathways. GW, GT, 2007 These results comparing dsRNAi and amiRNAi, though preliminary, suggest that further study is needed to elucidate the possible interactions between the macrocyclic versus bicyclic metabolic branches, if different branches do exist. We note that two diterpenes that are related to or produced by certain tobaccos are shown to be capable of regulating pathogen resistance in tobacco [52, 61], and others are shown to be alleopathic [24].

23.5

Summary

In this review we have attempted to provide a progress report on the use of dsRNAi for manipulating plant secondary metabolism in order to create new phenotypes, to perform reverse genetics phenotyping, or for probing metabolism. Common advantages that undoubtedly contribute to the success and rapidly growing use of the RNAi approach have been highlighted. These include the high efficiency of suppression obtained in many different studies of different secondary product metabolic pathways (average of ~74% in the 34 studies surveyed here) using many different RNAi vectors and gene sequence lengths from 139 to 1,302 bp. Another perhaps common experience (but relatively little data published) is that the degree of knockdown in a suppressed population is skewed towards high level knockdown, a consequence that serves most purposes well (reverse genetics phenotyping and new phenotype creation and verification). An additional characteristic of many dsRNAi studies (at least 35% of studies surveyed) is the occurrence of unexpected, additional phenotypes which can open new avenues of additional discovery. There appears to be relatively little data concerning the stability of dsRNAi gene suppression over several generations, however, stability in the T2 generation was shown in some cases (e.g., studies 25 and 31). In the future, amiRNAi may help to fine tune specificity of knockdown as well as facilitate multiple gene knockdown using one or a few constructs. And, it may be useful as a sequence-directed tool to dissect gene portions through RNAi phenotyping. Finally, some of the most elegant of the studies surveyed show how RNAi of an endogenous gene coupled with overexpression of foreign genes encoding both an ideal substitute for the suppressed endogenous gene as well as a downstream gene leading to the targeted product can fine tune a modification effort to very specifically tailor a new phenotype (e.g., the blue rose, study 11).

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References 1. Allen R, Millgate A, Chitty J, et al. (2004) RNAi-medated replacement of morphine with the nonnarcotic alkaloid reticuline in ipium poppy. Nature Biotechnol 22:1560–1566 2. Allen RS, Miller JA, Chitty JA, et al. (2008) Metabolic engineering of morphinan alkaloids by over-expression and RNAi suppression of salutaridinol 7-O-acetyltransferase in opium poppy. Plant Biotechnol J 5 6:22–30 3. Andersson M, Melander M, Pojmark P, et al. (2006) Targeted gene suppression by RNA interference: an efficient method for production of high-amylose potato lines. J Biotechnol 123:137–148 4. Barnes S, Prasain J (2005) Current progress in the use of traditional medicines and nutraceuticals. Curr Opin Plant Biol 8:324–328 5. Baulcombe DC (1996) RNAas an initiator of post-transcriptional gene silencing in transgenic plants. Plant Mol Biol 32:79–88 6. Besseau S, Hoffmann L, Geoffroy R, et al. (2007) Flavonoid accumulation in Arabidopsis repressed in lignin synthesis affects auxin transport and plant growth. Plant Cell 19:148–162 7. Capell T, Christou P (2004) Progress in plant metabolic engineering. Curr Opin Biotechnol 15:148–154 8. Carrington JC (2005) Small RNAs and arabidopsis. A fast forward look. Plant Physiol 138:565–566 9. Chen F, Dixon RA (2007) Lignin modification improves fermentable sugar yields for biofuel production. Nature Biotechnol 25:759–761 10. Croteau R, Kutchar TM, Lewis NG (2000) Natural products (secondary metabolites) In: Buchanan BB, Gruissem W, Jones RL (eds) Biochemistry and molecular biology of plants, American Society of Plant Physiologists, Rockville, MD 11. Davuluri GR, van Tuinen A, Fraser PD, et al. (2005) Fruit-specific RNAi-mediated suppression of DET1 enhanced carotenoid and flavonoid content in tomatoes. Nat Biotechnol 23:890–895 12. Dexter R, Qualley A, Kish CM (2007) Characterization of a petunia acetyltransferase involved in the biosynthesis of the floral volatile isoeugenol. Plant J 49:265–275 13. Dixon RA (2005) Engineering of plant natural product pathways. Curr Opin Plant Biol 8:329–336 14. Dodo HW, Konan KN, Chen FC, et al. (2007) Alleviating peanut allergy using genetic engineering: the silencing of the immunodominant allergen Ara h 2 leads to its significant reduction an a decrease in peanut allergenicity. Plant Biotechnol J, doi:10.1111/j.1467-7652.2007.00292.x 15. Escobar MA, Dandekar AM (2005) Post transcriptional gene silencing in plants. NCBI Bookshelf, Landes Bioscience, http://www.ncbi.nlm.nih.gov/books 16. Folck A, Wieser H, Knies P, et al. (2003) Silencing the α-gliadins in wheat www.vvgvg.org/ pdf/PosterWeizen%200803.pdf 17. Fujii N, Inui T, Iwasa K, et al. (2007) Knockdown of berberine bridge enzyme by RNAi accumulates (S)-reticuline and activates a silent pathway in cultured California poppy cells. Transgenic Res 16:363–375 18. Gavilano L, Coleman N, Burnley LE, et al. (2006) Genetic engineering of Nicotiana tabacum for reduced nornicotine content. J Agric Food Chem 54:9071–9078 19. Guo Z, Wagner GJ (1993) Biosynthesis of cis-abienol in cell free extracts of tobacco trichomes. Arch Biochem Biophys 308:103–108 20. Guo Z, Wagner GJ (1995) Biosynthesis of cembratrienols in cell-free extracts from trichomes of Nicotiana tabacum. Plant Sci 110:1–10 21. Han JY, Kwon YS, Yang DC, et al. (2006) Expression and RNA interference-induced silencing of the dammarenediol synthase gene in Panax ginseng. Plant Cell Physiol 47:1653–1662 22. Hoffmann L, Besseau S, Geoffroy P, et al. (2004) Silencing of hydroxycinnamoyl-coenzyme A shikimate/quinate hydroxycinnamoyltransferase affects phenylpropanoid biosynthesis. Plant Cell 16:1446–1465

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 457 23. Hoffmann T, Kalinowski G, Schwab W (2006) RNAi-induced silencing of gene expression in strawberry fruit (Fragaria x ananassa) by agroinfiltration: a rapid assay for gene function analysis. Plant J 48:818–826. http://www.vvgvg.org/pdf/Anne%20WEizen%20 Hamburg%202.pdf 24. Jackson DM, Danehower DA (1996) Integrated case study: nicotiana leaf-surface components and their effects on insect pests and diseases. In Kerstiens G (ed) Plant Cuticles, BIOS Scientific, Oxford 25. Jorgensen K, Bak S, Busk PK, et al. (2005) Cassava plants with a depleted cyanogenic glucoside content in leaves and tubers. Distribution of cyanogenic glucosides, their site of synthesis and transport, and blockage of the biosynthesis by RNA interference technology. Plant Physiol 139:363–374 26. Kaminaga Y, Schnepp J. Peel G, et al. (2006) Plant phenylacetaldehyde synthase is a bifunctional homotetrameric enzyme that catalyzed phenylalanine decarboxylation and oxidation. J Biol Chem 281:23357–23366 27. Katsumoto Y, Fukuchi-Mizutani M, Fukui Y, et al. (2007) Engineering of the rose flavonoid biosynthetic pathway successfully generated blue-hued flowers accumulating delphinidin. Plant Cell Physiol 48:1589–1600 28. Kusaba M, Miyahara K, Iida S, et al. (2003) Low glutelin content1: a dominant mutation that suppresses the glutelin multigene family via RNA silencing in rice. Plant Cell 15:1455–1467 29. Larkin P, Harrigan GG (2007) Opportunities and surprises in crops modified by transgenic technology: metabolic engineering of benzylisoquinoline alkaloid gossypol and lysine biosynthetic pathways. Metabolomics 3:371–382 30. Leitner-Dagan Y, Ovadis M, Shklarnam E, et al. (2006) Expression and functional analyses of the plastid lipid-associated protein CHRC suggest its role in chromoplastogenesis and stress. Plant Physiol 142:233–244 31. Li XB, Fan XP, Wand XL, et al. (2005) The cotton ACTIN1 gene is functionally expressed in fibers and participates in fiber elongation. Plant Cell 17:859–875 32. Mahmoud SS, Croteau RB (2003) Menthofuran regulates essential oil biosynthesis in peppermint by controlling a downstream monoterpene reductase. Proc Natl Acad Sci USA 100:14481–14486 33. Mansoor S, Amin I, Hussain M, et al. (2006) Engineering novel traits in plants through RNA interference. Trend Plant Sci 11:559–565 34. Nagira Y, Shimamura K, Hirai S, et al. (2006) Identification and characterization of genes induced for anthocyanin synthesis and chlorophyll degradation in regenerated torenia shoots using suppression subtractive hybridization, cDNA microarrays, and RNAi techniques. J Plant Res 119:217–230 35. Nakamura N, Fukuchi-Mizutani M, Miyazaki K, et al. (2006) RNAi suppression of the anthocyanidin synthase gene in Torenia hybrida yields white flowers with higher frequency and better stability than antisense and sense suppression. Plant Biotechnol 23:13–17 36. Nakatsuka T, Abe Y, Kakizaki Y, et al. (2007) Production of red-flowered plants by genetic engineering of multiple flavonoid biosynthetic genes. Plant Cell Rep, doi:10.1007/ s00299-007–0401–0 37. Newman DJ, Cragg GM, SNader KM (2003) Natural products and sources of new drugs over the period 1981–2002. J Nat Prod 66:1022–1037 38. Nishihara M, Nakatsuka T, Yamamura S (2005) Flavonoid components and flower color change in transgenic tobacco plants by suppression of chalcone isomerase gene. FEBS Lett 579:6074–6078 39. Ogita S, Uefuji H, Morimoto M, et al. (2004) Application of RNAi to confirm theobromine as the major intermediate for caffeine biosynthesis of coffee plants with potential for construction of decaffeinated varieties. Plant Mol Biol 54:931–941 40. Ono E, Fukuchi-Mizutani M, Nakamura N, et al. (2006) Yellow flowers generated by expression of the aurone biosynthetic pathway. Proc Natl Acad Sci USA 103:11075–11080

458

G.J. Wagner, A.B. Kroumova

41. Orlova I, Marshall-Colon A, Schnepp J, et al. (2006) Reduction of benzenoid synthesis in petunia flowers reveals multiple pathways to benzoic acid and enhancement in auxin transport. Plant Cell 18:3458–4375 42. Ortholand JY, Ganesan A (2004) Natural products and combinatorial chemistry: back to the future. Curr Opin Chem Biol 8:271–280 43. Pichersky E, Dudareva N (2007) Scent engineering: toward the goal of controlling how flowers smell. Trends Biotechnol 25:105–110 44. Potera C (2007) Antisense – down, but not out. Nature Biotechnol 25:497–499 45. Raikhel N, Pirrung M (2005) Adding precision tools to the plant biologists’ toolbox with chemical genomics. Plant Physiol 138:563–564 46. Robinson T (1991) The organic constituents of higher plants. Their chemistry and interrelationships. Cordus Press, North Amherst, MA 47. Rothstein SJ, DiMaio J, Strand M, et al. (1986) Stable and heritable inhibition of the expression of nopaline synthase in tobacco expressing anti sense RNA. Proc Natl Acad Sci USA 84:8439–8443 48. Sato F (2005) RNAi and functional genomics. Plant Biotechnol 22:431–442 49. Schijlen E, Ric de Vos CH, Martens S, et al. (2007) RNA interference silencing of chalcone synthase, the first step in the Flavonoid biosynthesis pathway, leads to parthenocarpic tomato fruits. Plant Physiol 144:1520–1530 50. Schwab R, Ossowski S, Riester M, et al. (2006) Highly specific gene silencing by artificial microRNAs in Arabidopsis. Plant Cell 18:1121–1133 51. Seitz C, Vitten M, Steinbach P, et al. (2007) Redirection of anthocyanin synthesis on Osteospermum hybrida by a two-enzyme manipulation strategy. Phytochemisty 68:824–833 52. Seo S, Seto H, Koshino H, et al. (2003) A diterpene as an endogenous signal for the activation of defense responses to infection with Tobacco mosaic virus and wounding in tobacco. Plant Cell 15:863–873 53. Small I (2007) RNAi for revealing and engineering plant gene functions. Curr Opin Biotechnol 18:1–6 54. Subramanian S, Graham MY, Yu O, et al. (2005) RNA interference of soybean isoflavone synthase genes leads to silencing I in tissues distal to the transformation site and to enhanced susceptibility to Phytophthora sojae. Plant Physiol 137:1345–1353 55. Sunilkumar G, Campbell LM, Puckhaber L, et al. (2006) Engineering cottonseed for use in human nutrition by tissue-specific reduction of toxic gossypol. Proc Natl Acad Sci USA 103:18054–18059 56. Tanaka Y, Katsumoto Y, Brugliera F, et al. (2005) Genetic engineering in floriculture. Plant Cell Tissue Org Cult 80:1–24 57. Tang G, Galili G (2004) Using RNAi to improve plant nutritional value: from mechanism to application. Trend Biotechnol, doi:10.1016/j.tibtech.2004.07.009 58. Tang G, Galili G, Zhuang X (2007) RNAi and microRNA: breakthrough technologies for the improvement of plant nutritional value and metabolic engineering. Metabolomics 3:357–369 59. Taylor LP, Grotewold E (2005) Flavonoid and developmental regulators. Curr Oppin Plant Biol 8:317–323 60. Underwood RB, Tieman DM, Shibuya K, et al. (2005) Ethylene-regulated floral volatile synthesis in petunia corollas. Plant Physiol 138:255–266 61. Van den Brule S, Muller A, Fleming AJ, et al. (2002) The ABC transporter SpTUR2 confers resistance to the antifungal diterpene sclareol. Plant J 30:649–662 62. Van der Rest B, Danoun S, Boudet AM, et al. (2006) Down-regulation of cinnamoyl-CoA reductase in tomato (Solanum lycopersicum L.) induces dramatic changes in soluble phenolic pools. J Exp Bot 57:1399–1411 63. Verdonk, JC, Haring MA, van Tunen AJ, et al. (2005) ODORANT1 regulates fragrance biosynthesis in petunia flowers. Plant Cell 17:1612–1624 64. Wadenback J, von Arnold S, Egertsdotter U, et al. (2007) Lignin biosynthesis in transgenic Norway spruce plants harboring an antisense construct for cinnamoyl CoA reductase (CCR). Transgenic Res, doi:10.1007/s11248-007-9113-z

23 The Use of RNAi to Elucidate and Manipulate Secondary Metabolite Synthesis in Plants 459 65. Wagner A, Ralph J, Akiyana T, et al. (2007) Exploring lignification in conifers by silencing hydroxycinnamoyl-CoA:shikimate hydroxycinnamoyltransferase in Pinus radiate. Proc Natl Acad Sci USA 104:11856–11861 66. Wagner GJ (1991) Secreting glandular trichomes: more than just hairs. Plant Physiol 96:675–679 67. Wagner GJ, Wang E, Shepherd RW (2004) New approaches for studying and exploiting an old protuberance, the plant trichome. Annals Bot 93:3–11 68. Wang E, Hall JT, Wagner GJ (2004) Transgenic Nicotiana tabacum L. with enhanced trichome exudates Cembratriene-ol has reduced aphid infestation in the field. Mol Breeding 13:49–57 69. Wang E, Wagner GJ (2003) Elucidation of the functions of genes central to diterpene metabolism in tobacco trichomes using PTGS. Planta 216:686–691 70. Wang E, Wang R, DeParasis J, et al. (2001) Metabolic engineering of plant trichome glands enhanced natural-product-based aphid resistance. Nature Biotechnol 19:371–374 71. Wasson AP, Pellerone FI, Mathesius U (2006) Silencing the flavonoid pathway in Mediago truncatula inhibits root nodule formation and prevents auxin transport regulation by Rhizobia. Plant Cell 18:1617–1629 72. Wesley SV, Helliwell CA, Smith NA, et al. (2001) Construct design for efficient, effective and high-throughput gene silencing in plants. Plant J 27:581–590 73. Wrobel-Kwiatkowska M, Starzycki M, Zebrowski J, et al. (2007) Lignin deficiency in transgenic flax resulted in plants with improved mechanical properties. J Biotechnol 128:919–934

Index

A aberrant DNA hypermethylation, 367, 398 alkaloids, 431, 435, 442, 447–449 altered synaptic plasticity, 260, 267, 269 Alzheimer’s disease, 26, 74, 149, 150, 152, 226, 230–232, 237, 240, 242, 412 angiogenesis, 98, 205, 216, 219, 349, 351, 359, 360, 369, 377, 409 antagomiR, 17, 18, 22, 150, 153, 233, 305, 306, 308, 309, 315–319, 361, 399, 401 anti BCR-ABL shRNAs, 305, 306, 311, 312 anti-aging, 52 apoptosis, 2, 53, 99, 130, 135, 140, 146, 148, 150, 156–158, 174, 216, 218, 219, 236, 246, 284, 287, 288, 306, 323, 324, 327, 335, 337, 338, 340, 343, 344, 353, 369, 372, 378, 385, 395, 403, 409 autism, 226, 232, 240, 241, 245, 246, 261, 412

B B cell development, 205, 216

C cancer, 18, 48, 59, 123–125, 153–158, 177, 179, 180, 236, 283–298, 306, 324, 341, 354, 356, 367–380, 395, 398, 403–410 cancer stem cells, 145, 155, 156, 158 cardiac and skeletal muscle, 129, 131–133, 135, 138, 151 CD34, 98, 100, 105, 106, 108, 109, 305–308, 312, 313, 318, 355 cell differentiation, 98, 99, 131, 147, 167–169, 181–183, 189, 213, 218, 275 cell proliferation, 2, 129, 131, 135, 136, 140, 146, 156–158, 174, 175, 189, 195, 197, 198, 216, 218, 236, 246, 287, 309, 313, 314, 317, 318, 323, 327, 335, 336, 338, 344, 385, 404, 409

central nervous system (CNS), 73–93, 191, 226, 232, 237, 412 CGG trinucleotide repeat expansion, 232, 245 chronic myeloid leukemia (CML), 305–320, 406 cytomegalovirus (CMV), 37, 40, 53, 172, 173, 205, 209, 210, 215, 219, 253, 257, 355, 416, 417 cortex, 235, 236, 257, 260, 267, 269, 272, 275, 411, 413 cosmetics, 51–71

D Dicer, 1–3, 6, 7, 11, 19, 21, 23, 36, 52, 55–58, 62, 73, 98, 120–123, 134, 146, 147, 149, 152, 167, 169, 206–208, 211, 219, 225, 230, 233, 245, 247, 248, 252, 253, 270, 271, 306, 307, 318, 324, 349, 353–355, 359, 360, 386, 395, 402, 412, 415, 417, 418 direct-labelling, 25, 73, 81, 82, 86 disruption of histone-modification paterns, 367, 371, 398 DNA demethylation, 369, 372, 375–377, 380–382, 400 DNA methylation, 26, 178, 188, 189, 192, 245, 246, 251, 367–370, 373–380 Drosha, 1–6, 11, 36, 39, 46, 48, 56, 73, 98, 120, 170, 206–208, 232, 238, 247, 306, 307, 318, 324, 359, 360, 386, 402, 407, 416–418

E Epstein Barr virus (EBV), 208–210, 216, 218, 219, 408, 417 ectopic miRNA expression, 205 embryonic stem cells (ES), 62, 146–148, 167–169, 174, 176–179, 181, 183, 190, 192, 193, 226, 230, 270, 275 461

462 epigenetic alterations, 245, 251, 287, 367, 369, 398 epigenetic drugs, 367, 373, 379, 380, 398 epigenetics, 187, 367, 369, 378 erythroid differentiation, 97–113 erythropoises, 97–99, 105, 113, 355 expression profile, 25, 74, 88, 89, 92, 97, 99, 105, 133, 138, 149, 152, 155, 157, 158, 180, 196, 213, 219, 229, 240, 306, 323, 329, 330, 339, 340, 323, 329, 330, 339, 340, 358, 360, 372, 376, 377, 385, 387, 390, 401, 404, 409

F FMR1, 226, 232, 233, 245, 246, 248–252, 255–263, 413 fragile X mental retardation syndrome (FXS), 226, 232, 245–263, 351, 413

G gene expression, 1, 17, 20, 35, 36, 39, 45, 46, 57–59, 69, 70, 73, 74, 97–99, 108, 120–122, 129, 131–140, 145, 148, 152, 167, 174, 177–180, 188–190, 205, 206, 211–215, 219, 233, 240, 242, 247, 248, 258, 268, 271, 275–277, 283, 284, 291, 298, 307, 324–326, 329, 330, 345, 351, 356, 360, 361, 369, 370, 374, 379, 388, 391, 403, 406, 409, 433, 451 gene expression profiling, 74, 205, 213–216, 359 global genomic-DNA hypomethylation, 369, 370, 400

H H1, 23, 53, 167, 174, 180, 310, 317 H9, 167, 174, 180 herpes simplex virus, 205, 209, 419, 420 HIV, 60, 150, 153, 171, 172, 211, 255, 356, 387–392, 416–418 Hox genes, 119, 120, 122–125, 148, 378 hyaluronidase (Hyal), 51, 52, 63–67, 174

I immunity, 208, 216, 218, 227, 350, 357, 397, 405, 418 indirect-labelling, 73, 81, 83, 85, 86 induced pluripotent stem cells (iPS), 168 infection, 63, 153, 208, 215, 219, 257, 268, 350, 352, 356, 357, 387, 388, 392, 397, 418, 420, 421, 445, 451, 452

Index inflammation, 150, 153, 350, 352, 356–358, 401 intron, 23, 35, 37, 39–41, 46, 54–60, 63, 64, 133, 152, 170–172, 207, 246–248, 252–255, 258, 291, 307, 454 intronic microRNA (Id-miRNA), 51–71, 247, 248, 253, 254

K Karposi’s sarcoma-associated herpesvirus (KSHV), 205, 209–219

L laser capture microdissection, 73, 89, 93 lentivirus-mediated, 307, 307 limb bud, 122, 123

M malignancies, 98, 216, 287, 306, 307, 319, 369, 374, 375, 377, 379, 397, 410, 411 metabolism, 146, 150, 246, 397, 416, 417, 435, 437, 446, 448, 449, 451, 452, 457 microarray platform, 75, 81, 88, 89, 92, 104, 105, 389 microRNA target, see miRNA target microRNA, see miRNA miR-1, 64, 121, 130, 132–136, 138–140, 148, 150–152, 288, 331, 341, 363 miR-124a, 74, 79, 91, 150, 152, 192, 194, 196, 286, 369, 377, 381, 382, 400, 413, 414 miR-127, 285, 286, 369, 376, 377, 381, 382, 400 miR-133, 130, 132–136, 139, 140, 148–151, 341 miR-155, 98, 150, 153–155, 157, 205, 216–218, 285, 287, 288, 307, 357, 358, 372, 404, 405, 408, 409, 411, 412, 418 mir-302, 62, 66, 167–183 mir-430, 149, 150, 152, 169 mir-434–5p, 51, 64–66, 69, 70, 105, 177 miR-451, 64, 97, 99, 101, 102, 105, 106, 108–113, 330 miRNA, 1–14, 17–26, 35–48, 54–71, 73–93, 97–113, 119–125, 129–141, 145–158, 167–183, 187–200, 205–219, 225–242, 245–263, 267–277, 281–298, 305–319, 323–345, 349–362, 367–380, 385–391, 395–419 miRNA biogenesis, 1–3, 5, 6, 11, 54, 60, 132, 167, 169–172, 226, 238, 246, 247, 252, 254, 255, 275, 277, 306, 318, 350, 353, 354

Index miRNA microarray (miCHIP), 75, 78, 79, 83, 86, 87, 88, 92, 93, 99, 101, 104, 133, 176, 226, 271, 306, 307, 310–312, 319, 328, 329, 375, 376, 381, 389, 406 miRNA profiling, 17, 24, 73–93, 103, 106, 187, 284, 355, 403, 404, 407, 409 miRNA sponge, 17, 18, 22, 23 miRNA-based therapeutics, 350, 361 miRNA-induced pluripotent stem cells (mirPS), 167, 173, 174, 176–183 miRNA target, 18, 20–24, 64, 80, 83, 123, 132, 138, 140, 205, 212–215, 219, 226, 227, 232, 235, 271, 273–277, 283–298, 319, 362 morphogenesis, 74, 119, 120, 1331, 134, 135, 150, 152, 353, 355 mRNA, 2, 18–23, 25, 35, 36, 39, 40, 42, 46–48, 51–59, 63, 65, 66, 70, 73, 74, 79–81, 87, 88, 92, 98, 103, 120–122, 132, 139, 147–149, 169–171, 188, 192–195, 197, 205–209, 212–215, 219, 225, 227, 229, 233, 236, 238, 240, 246, 250, 252–255, 257–260, 267, 269–274, 277, 283, 284, 288, 289, 291, 307, 308, 316, 317, 323, 324, 332, 344, 350, 353, 356, 357, 359–362, 372, 386, 401, 407, 411, 413, 415, 417–419, 432, 446, 450, 453 mutation, 22, 46–48, 134, 138, 152, 190, 208, 214, 225, 227, 230–232, 238, 251, 283, 287–290, 292, 297, 361, 370, 407, 410, 412, 413, 418, 432 myoblast, 135–137, 140, 148, 396 myotube, 135, 136, 138, 140

N Nanog, 167, 182, 192 natural products, 435, 436 neointimal formation, 323–325, 332, 343, 345 neural stem cells, 189, 191, 192, 196, 197 neurodevelopment, 226, 267, 270, 271, 277 neurodevelopmental origins, 268 neuron plasticity, 258, 260 neuronal disease, 397, 412, 414 neuropsychiatric diseases, 225–242 non-coding RNAs, 1, 23, 59, 97, 119, 120, 129, 146, 169, 187, 188, 233, 252, 283, 306, 307, 324, 325, 350, 351, 372, 401, 411, 413 nonsense-mediated decay (NMD), 51, 54, 56, 57, 59, 70, 170, 172, 183, 246, 247, 252, 253, 255, 256 normalization, 25, 73, 88, 103, 104, 329 nuclear import signal (NIS), 251

463 O Oct3/4, 167, 168, 174, 177–179 oligonucleotide linker, 73

P phenylpropanoids, 433, 434, 437, 438, 444, 446, 451 plant secondary products, 435, 437 polycistronic, 133, 255, 256, 305–307, 311, 314, 319, 419 post-mortem, 267, 269, 271, 273 pre-miRNA structural motifs, 1 pri-miRNAs, 1–15, 25, 35, 36, 39, 56–68, 70, 73, 76, 77, 80, 98, 171–173, 175, 206, 207, 209, 238, 243, 246–248, 251–256, 273, 277, 283, 288, 292, 306–308, 319, 388, 390, 404 probe design, 25, 73, 76 proliferation, 2, 129–131, 135–137, 140, 145–149, 151, 152, 156–158, 174, 175, 189, 190, 195, 197, 198, 216, 218, 236, 246, 286, 287, 306, 307, 310, 314, 315, 318–320, 324, 325, 328, 335–337, 339, 340, 344, 345, 352, 354, 358, 374, 378, 387, 397, 406, 411, 412

Q qRT-PCR, 73, 77, 79, 91, 214, 274, 275, 309, 311–315, 319, 329, 331–333, 339

R regenerative medicine, 145–159 repeat-associated microRNA (ramRNA), 245–263 RNA interference (RNAi), 17, 35–48, 51, 52, 55, 59, 60, 120, 153, 170, 211, 218, 219, 227, 232, 246–248, 350, 356, 386, 415, 418, 419, 433, 434 RNA splicing, 35–48, 51, 54–57, 59, 60, 63, 70, 171, 183, 192, 246, 252–255, 350 RNA structure prediction, 1, 5

S schizophrenia, 74, 226, 227, 232, 236–238, 240–242, 267–277, 412, 413, 415 seed sequence, 66, 74, 169, 205, 207, 216, 354, 386 single nucleotide polymorphism (SNP), 226, 237, 238, 240, 271, 274–277, 283–298

464 siRNA, 17–10, 23, 24, 26, 35, 36, 39, 47, 48, 51–61, 63, 65, 66, 70, 71, 79, 83, 120, 183, 207, 208, 211, 215, 219, 226, 227, 231, 233, 242, 247, 253, 307, 325, 351, 354, 356–358, 361, 380, 404, 405, 421, 432 skin, 51, 52, 54, 63, 65–71, 130, 134, 149, 170, 173, 175, 181, 252, 350, 352–355, 359, 373 skin whitening, 51, 52, 65–67, 69 small-hairpin RNA (shRNA), 23, 24, 35, 51–54, 57–59, 63, 66, 72, 158, 183, 247, 253, 255, 256, 305, 306, 311, 312, 378, 403 Sox2, 167, 168, 177, 178, 182, 192, 193 SSEA-3, 167, 174, 177, 178 SSEA-4, 167, 174, 177, 178 stem cells, 62, 99, 100, 145–149, 155, 156, 158, 167–183, 187–200, 229, 235, 270, 275, 307, 308, 350, 352–355, 360, 373, 410 SV40, 205, 209, 210, 214, 215, 219, 419 synaptic function, 267, 270 synaptogenesis, 233, 267, 270

T TAR, 387, 388 target mimicry, 17, 18, 22, 23 Tat, 211, 385, 386, 417 terpenoids, 433, 434, 437, 445, 451

Index therapeutic intervention, 74, 167, 245, 305, 306, 415 therapy, 59, 124, 125, 146, 158, 167, 168, 179, 182, 183, 242, 252, 361, 378, 380, 395, 397–409, 432 tissue engineering, 145, 146, 148, 158 TAR-RNA-binding protein (TRBP), 206, 385, 388 triplet repeat expansion disease (TRED), 245, 247, 248 tumor-suppressor genes, 158, 367, 369, 370, 372, 373, 375, 377, 398 tyrosinase (Tyr), 51, 52, 62–70 tyrosine kinase, 305–307, 311, 313, 318

U 3’UTR cloning, 205, 215

V vascular smooth muscle cells (VSMC), 323, 324, 326–330, 333–345 viral miRNAs, 212, 214, 216, 219, 417 virus, 104, 153, 172, 205, 208–211, 214, 218, 219, 226, 227, 242, 257, 287, 317, 355, 356, 357, 387, 388, 397, 402, 403, 408, 416–421, 433

W wound healing, 350–362