Academic Press is an imprint of Elsevier 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA 225 Wyman Street, Waltham, MA 02451, USA 32, Jamestown Road, London NW1 7BY, UK First edition 2011 Copyright # 2011 Elsevier Inc. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email:
[email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made ISBN: 978-0-12-387046-9 ISSN: 0065-2164 For information on all Academic Press publications visit our website at www.elsevierdirect.com Printed and bound in the USA 11 12 13 14 10 9 8 7 6 5 4
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CONTRIBUTORS
Bahram Bahrami Microbiology and Gut Biology Group, University of Dundee, Dundee, United Kingdom Gesche Braker Max Planck Institute for Terrestrial Microbiology, Karl-von-Frisch-Strasse 10, Marburg, Germany Steven J. Burgess Department of Life Sciences, Imperial College London, London, United Kingdom Ralf Conrad Max Planck Institute for Terrestrial Microbiology, Karl-von-Frisch-Strasse 10, Marburg, Germany Klaus Hellgardt Department of Chemical Engineering and Chemical Technology, Imperial College London, London, United Kingdom George T. Macfarlane Microbiology and Gut Biology Group, University of Dundee, Dundee, United Kingdom Sandra Macfarlane Microbiology and Gut Biology Group, University of Dundee, Dundee, United Kingdom Peter J. Nixon Department of Life Sciences, Imperial College London, London, United Kingdom Bojan Tamburic Department of Chemical Engineering and Chemical Technology, Imperial College London, London, United Kingdom
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Contributors
David E. Whitworth Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, Ceredigion, United Kingdom Fessehaye Zemichael Department of Chemical Engineering and Chemical Technology, Imperial College London, London, United Kingdom
CHAPTER
1 Myxobacterial Vesicles: Death at a Distance? David E. Whitworth1
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Contents
I. Introduction II. Outer Membrane Vesicles A. Natural roles of OMVs B. Applications of OMVs III. Myxobacteria A. Biotechnological importance B. Myxobacterial sociobiology C. Predation D. Multicellular development E. Motility F. Extracellular biology IV. Myxobacterial Vesicles A. OMVs of M. xanthus B. OMVs in M. xanthus biofilms C. OMVs in predation D. OMVs and motility E. Cargo of myxobacterial OMVs V. Concluding Remarks Acknowledgments References
Abstract
Outer membrane vesicles (OMVs) are produced from the outer membrane (OM) of myxobacterial cells and are found in large quantities within myxobacterial biofilms. It has been proposed that OMVs are involved in several of the social behaviors exhibited
Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, Ceredigion, United Kingdom 1 Corresponding author: e-mail address:
[email protected] Advances in Applied Microbiology, Volume 75 ISSN 0065-2164, DOI: 10.1016/B978-0-12-387046-9.00001-3
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2011 Elsevier Inc. All rights reserved.
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by the myxobacteria, including motility and predation. Proteomic data suggest that specific proteins are either selectively incorporated into or excluded from myxobacterial OMVs, as observed for OMVs of other organisms. Hydrolases are found in large numbers in OMVs, which then transport them to target bacteria. Fusion of OMVs with the OM of Gram-negative cells, or lysis of OMVs next to Gram-positive bacteria, is thought to deliver hydrolases to target cells, causing their lysis. The model myxobacterium Myxococcus xanthus is a predator of other bacteria, and OMVs are likely employed as predatory agents by this organism. The transfer of motility proteins between cells of M. xanthus has been documented, and OMV-mediated transfer provides a convenient mechanism to explain this phenomenon. This review describes the general principles of OMV biology, provides an overview of myxobacterial behavior, summarizes what is currently known about myxobacterial OMVs, and discusses the potential involvement of OMVs in many features of the myxobacterial life-cycle.
I. INTRODUCTION It has long been appreciated that many Gram-negative bacteria produce vesicles, which are formed by budding off portions of the cell outer membrane (OM). These outer membrane vesicles (OMVs) may be the unavoidable consequence of possessing a double cell membrane, being the passive by-products of a mechanism to balance the relative amounts of inner and OMs (Wensink and Witholt, 1981). However, a wide range of biomolecules seem to be specifically targeted to (or excluded from) OMVs, implying that OMV biogenesis has evolved additional functions associated with the secretion or trafficking of proteins/DNA/metabolites. OMVs participate in a variety of processes in diverse bacteria, including nutrient acquisition, pathogenesis, signaling and biofilm formation. Recently, it has been shown that the Deltaprotobacterium Myxococcus xanthus, a model myxobacterium, produces OMVs and it is likely that OMVs play important roles in some of the social behaviors for which myxobacteria are renowned. This review provides overviews of OMV and myxobacterial biology, before discussing what is known about myxobacterial OMVs, the possible roles of OMVs in the myxobacterial lifecycle, and important areas for further research.
II. OUTER MEMBRANE VESICLES Secreted/excreted lipopolysaccharide (LPS) complexes were first identified in Escherichia coli cultures in the 1960s, and it was eventually recognized that these complexes were actually membrane-bound vesicles
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derived primarily from the OM (Bishop and Work, 1965; Hoekstra et al., 1976; Katsui et al., 1982). OMVs are now known to be produced by a large number of Gram-negative bacteria including Pseudomonas, Lysobacter, Burkholderia, Helicobacter, Proteus, Morganella, and many others (Allan et al., 2003; Fiocca et al., 1999; Kadurugamuwa and Beveridge, 1995; Li et al., 1998; Vasilyeva et al., 2009). No Gram-negative bacteria have failed to produce OMVs when investigated, and it therefore seems likely that OMV production is a common feature of all Gram-negative bacteria. OMVs derive from the OM by budding, whereby a region of membrane bulges outwards and ultimately pinches off from the parent membrane, encapsulating a portion of the internal solution (periplasm in the case of Gram-negative bacteria). Resulting OMVs thus contain lipids characteristic of the OM such as LPS, integral and peripheral OM proteins, soluble periplasmic proteins, and other periplasmic components such as peptidoglycan (Hoekstra et al., 1976; Horstman and Kuehn, 2000; Kaparakis et al., 2010; Loeb and Kilner, 1979). However, while OMVs clearly derive from the OM, they are not just spherical fragments shed passively from the OM. Several studies have shown that some biomolecules are enriched in OMVs, while others are apparently excluded from OMVs (Haurat et al., 2011; Kato et al., 2002; Wensink and Witholt, 1981), suggesting the existence of a sorting mechanism which loads budding OMVs with cargo. Recently, there have been several reviews of OMV biology (Ellis and Kuehn, 2010; Kuehn and Kesty, 2005; Kulp and Kuehn, 2010; Lee et al., 2008; Mashburn-Warren and Whiteley, 2006), which in addition to providing an overview of OMV research, serve to highlight the current lack of understanding regarding many fundamental features of vesicle biology. In particular, there is little information currently available regarding the mechanisms of vesicle formation, the genetic basis of vesiculation, how specific molecules are recruited or excluded from vesicles and how membrane fission/fusion occurs. Proteomic approaches have been used to identify the protein components of vesicles (Lee et al., 2007; Sidhu et al., 2008) in attempts to provide clues to the mechanisms of vesicle production and cargo loading. However, without a quantitative analysis, it is impossible to determine whether proteins found in vesicles have been specifically incorporated into them or whether they have been incorporated passively into OMVs (Kulp and Kuehn, 2010). The secretion of biomolecules within vesicles, as opposed to secretion directly into the supernatant, is thought to have several important consequences; for instance, vesicles can transport insoluble material, protect their contents from the environment, maintain a high effective concentration even at a distance from the vesicle-producing cell, and can be targeted to fuse with specific recipient membranes (Kadurugamuwa and Beveridge, 1996, 1999). Such properties make OMVs potentially useful
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agents to mediate many physiological processes, and accordingly, OMVs have been shown to be involved in diverse prokaryotic behaviors.
A. Natural roles of OMVs OMVs are agents for the transport of material beyond the producing cell, and transported molecules can even end up within target cells. Descriptions of the physiological roles of OMVs are thus preoccupied with what cargo the OMVs carry, their final destination, and what effect cargo molecules have at their site of action. The OMVs of pathogenic bacteria have received the greatest amount of study, and several facets of pathogenesis have been found to involve OMVs (reviewed by Amano et al., 2010; Ellis and Kuehn, 2010; Kuehn and Kesty, 2005). Biofilm formation is an important behavior of many pathogenic Gram-negative bacteria, and OMVs have been found to nucleate biofilm formation in several systems; for instance, OMVs from Porphyromonas gingivalis have been shown to promote cell–cell adhesion, stimulating dental biofilm formation and host cell invasion (Grenier and Mayrand, 1987; Inagaki et al., 2006), and the presence of OMVs has been found to stimulate biofilm formation by Helicobacter pylori (Yonezawa et al., 2009). Biofilm formation promotes the entry of OMVs from P. gingivalis into epithelial cells, which has been documented to cause impairment of epithelial cell function (Furuta et al., 2009). Another important feature of OMVs from pathogens is the presence of toxins. OMVs from E. coli O157:H7 and Pseudomonas aeruginosa have been shown to contain toxins (Kadurugamuwa and Beveridge, 1997; Kolling and Matthews, 1999), and OMVs from enterotoxigenic E. coli are known to traffic enterotoxin into host cells (Kesty et al., 2004). As well as providing a route for the trafficking of toxins to host cell membranes, packaging of toxins into OMVs can result in vesicle-specific activation of toxins; for instance, the cytotoxin ClyA of E. coli forms active oligomers upon packaging into OMVs (Wai et al., 2003). In addition to trafficking virulence factors into eukaryotic cells during infection, OMVs possess activities which can detrimentally affect bacteria. OMVs of various species have been shown to contain lytic enzymes and antibacterial metabolites and are capable of causing bacterial lysis (Kadurugamuwa et al., 1998; Li et al., 1998); for instance, P. aeruginosa OMVs can convey gentamicin to recipient cells (Allan and Beveridge, 2003) and they also contain b-lactamase and antimicrobial quinolones (Ciofu et al., 2000; Mashburn and Whiteley, 2005). Lytic activity has led OMVs to be described as ‘‘predatory’’ (Beveridge et al., 1997, MashburnWarren and Whiteley, 2006), though whether lysis of other ‘‘prey’’ bacteria is a mechanism for competition reduction or a truly predatory behavior is currently unclear. OMVs can trigger the lysis of both Gram-negative
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and Gram-positive prey bacteria (Kadurugamuwa and Beveridge, 1996; Li et al., 1998). For Gram-negative prey, cellular lysis is thought to be mediated by fusion of OMVs with the OM of the prey, unloading OMV cargoes such as murein hydrolases directly into the periplasm of the recipient cell (Fig. 1.1; Kadurugamuwa and Beveridge, 1996; Li et al., 1998). Gram-positive bacteria lack the OM of Gram-negative bacteria, and therefore, OMVs must lyse Gram-positive bacteria through an alternative mechanism. It has been suggested that triggered lysis of OMVs next to Gram-positive bacteria releases hydrolases immediately adjacent to prey cells where they can degrade peptidoglycan directly (Fig. 1.1; Kadurugamuwa and Beveridge, 1996; Li et al., 1998). Intercellular trafficking by OMVs is not restricted to proteins, OMVs are also capable of carrying DNA (Dorward and Garon, 1990; Renelli et al., 2004) and transferring it into recipient cells (Dorward et al., 1989; Kolling and Matthews, 1999; Yaron et al., 2000). As a consequence, transformation of the recipient can occur, and this mechanism has been shown to allow the transfer of virulence genes between strains (Yaron et al., 2000). While DNA is found packaged within OMVs released from the cell, purified OMVs also seem to be able to associate with free DNA, and to take up exogenous DNA directly, protecting the DNA from DNAse treatment (Renelli et al., 2004). Extracellular DNA is an important component of bacterial biofilms and thus DNA-binding and stimulation of biofilm formation may be related properties of OMVs (Kulp and Kuehn, 2010). A role for OMVs in signaling has also been proposed recently (Mashburn and Whiteley, 2005). Many organisms produce an extracellular signal, which accumulates and acts as an indicator of the number of cells present in the vicinity. Acyl homoserine lactones (AHLs) are commonly used as such ‘‘quorum signals’’ by Gram-negative bacteria, and the production/ signaling of AHLs is particularly well understood ( Joint et al., 2007). P. aeruginosa produces three quorum signals—a quinolone (PQS or Pseudomonas Quinolone Signal, which also possesses antimicrobial activity) and two AHLs. The PQS of P. aeruginosa is packaged into OMVs, although the AHLs are not, and OMV formation is also dependent on the PQS molecule (Mashburn and Whiteley, 2005). It has been proposed that the packaging of quorum signals into OMVs may protect them from degradation while in the extracellular milieu (Mashburn-Warren and Whiteley, 2006). A summary of OMV-mediated transport processes is presented in Fig. 1.1. OMVs are able to specifically package many types of biomolecules and can then use different ‘‘delivery’’ mechanisms to ensure the transport of cargo molecules to particular destinations. Although not OMVs, extracellular vesicles have recently been described for some Gram-positive organisms, including Bacillus anthracis, Staphylococcus aureus, and Streptomyces coelicolor (Lee et al., 2009; Rivera et al., 2010; Schrempf et al., 2011). These vesicles seem to fulfil similar roles to the OMVs of Gram-negative
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IM PP OM
OMV
FIGURE 1.1 Vesicle-mediated transport between bacteria. OMVs form by budding from the OM of a Gram-negative bacterium (top) and can contain a subset of OM and periplasmic proteins, potentially with peptidoglycan fragments (gray). Some OM and periplasmic proteins are excluded from OMVs (purple triangles, orange circles). Production of OMVs may be particularly associated with regions of peptidoglycan weakness/remodeling (Kulp and Kuehn, 2010). OMVs can then lyse (bottom left), in this case adjacent to the peptidoglycan layer (gray) of a Gram-positive bacterium, or instead fuse with a recipient membrane (bottom right), here the OM of a Gram-negative bacterium. Lysis or fusion results in the release of cargo proteins/molecules, such as murein hydrolases (blue triangles), whose action can result in target cell lysis. IM: Inner Membrane, PP: Periplasm.
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bacteria, including toxin transport and trafficking of bacteriocides (Lee et al., 2009; Rivera et al., 2010; Schrempf et al., 2011).
B. Applications of OMVs Some pathogenic bacteria specifically package toxins and virulence factors into OMVs, which are then internalized by host cells. Such OMVs can be highly immunogenic (Alaniz et al., 2007; Ellis et al., 2010). As they seem ‘‘on the surface’’ to be very similar to their parent cells, and yet are incapable of replication, OMVs have been investigated as potential components in several vaccines. The results of OMV vaccines against meningococcal disease have proved very encouraging, and their use has been reviewed recently (Bernardini et al., 2007; Holst et al., 2009). OMV vaccines were first used to target serogroup B meningococci in the 1980s (Wedege and Fr holm, 1986) and were shown to enhance bacteriocidal activity of sera against Neisseria meningitidis. Although work has focused on meningococcal vaccines, OMVs from Bordetella pertussis, Francisella novicida, and Vibrio cholerae/vulnificus have also been studied for potential use in vaccines (Asensio et al., 2011; Bishop et al., 2010; Kim et al., 2010; Pierson et al., 2011; Roberts et al., 2008). As well as trafficking toxins and virulence factors, OMVs can contain antimicrobial enzymes/metabolites, including antibiotics and digestive hydrolases (Kadurugamuwa and Beveridge, 1995, 1996). The ability of OMVs to lyse bacteria has led to the proposition that they could be used as novel antibiotics (Kadurugamuwa and Beveridge, 1996) or as delivery systems for antibiotics (Allan and Beveridge, 2003, Kadurugamuwa and Beveridge, 1998). OMV production in P. aeruginosa and Shigella flexneri is enhanced by the addition of gentamicin, which is then packaged into the OMVs (Kadurugamuwa and Beveridge, 1998; MacDonald and Beveridge, 2002). Through uptake by host cells, gentamicin-laden OMVs can then deliver the gentamicin to eukaryotic cells infected with intracellular pathogens, reducing the amount of intracellular pathogen (Kadurugamuwa and Beveridge, 1998). Packaging gentamicin within vesicles was found to increase the MIC of gentamicin 2.5-fold, suggesting a synergistic effect between the antibiotic and other vesicular components (Kadurugamuwa and Beveridge, 1996). However, OMVs are known to be able to carry virulence factors, toxins, and drug-resistance-conferring proteins such as beta-lactamase (Bomberger et al., 2009; Kolling and Matthews, 1999), so there are potential risks that therapeutic OMVs might increase pathogenicity. OMVs also have the potential to be utilized as delivery devices by transporting specific biomolecules to particular targets, and/or modulating the activity of their cargo; for instance, Chen et al. (2010) showed that poorly immunogenic antigens could generate a greater immune response
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if delivered through vesicles. A nonimmunogenic protein (green-fluorescent protein, GFP) was fused with the OMV-targeted hemolysin ClyA and found to elicit high titers of anti-GFP antibodies. Engineering antigens into OMVs also increases the ease with which they could be purified for inclusion in vaccines (Chen et al., 2010). Perhaps when more is known about the mechanisms of OMV cargo selection, biogenesis, and recipient membrane targeting, it may become possible to rationally engineer OMVs to fulfil a variety of therapeutic and/or biotechnological uses.
III. MYXOBACTERIA Myxobacteria (order Myxococcales) are Gram-negative bacteria belonging to the Delta-subgroup of the Proteobacteria (Shimkets and Woese, 1992). They form rod-shaped cells that are capable of moving by gliding motility and are found abundantly in most environments, although they are particularly numerous in cultivated temperate topsoil (Dawid, 2000). Myxobacteria can broadly be divided into two groups, depending on their preferred nutrient sources (Dawid, 2000). The bacteriolytic myxobacteria are typified by M. xanthus (Kaiser, 2008; Kaplan, 2003), which can replicate by predating upon other members of the soil microfauna. In contrast, cellulolytic myxobacteria, such as Sorangium cellulosum (Gerth et al., 2003), are saprophytes, capable of degrading cellulose and other complex plant materials. For several decades, myxobacteria have been researched in tens of laboratories across the world, and diverse aspects of myxobacterial biology have been the focus of recent reviews and a collected volume (Berleman and Kirby, 2009; Kaiser et al., 2010; Mauriello et al., 2010; Velicer and Vos, 2009; Weissman and Mu¨ller, 2010; Whitworth, 2008). Lately, complete genome sequences have become available for several myxobacteria, including M. xanthus (Goldman et al., 2006), S. cellulosum (Schneiker et al., 2007), Stigmatella aurantiaca (Huntley et al., 2011), Anaeromyxobacter dehalogenans (Thomas et al., 2008) and Haliangium ochraceum (Ivanova et al., 2010), revolutionizing investigations into the biology of those organisms. Myxobacteria are best known for their production of secondary metabolites and for their social behaviors, and it is likely that OMVs are involved with both of these phenomena.
A. Biotechnological importance Myxobacteria are prolific producers of secondary metabolites with research into biosynthesis of these compounds focusing on members of the genus Sorangium. Myxobacteria are capable of producing secondary metabolites of several chemical classes, many with unique features,
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exhibiting a wide spectrum of bioactivities, often with novel modes of action (Reichenbach, 2001; Weissman and Mu¨ller, 2009). A selection of myxobacterial secondary metabolites are shown in Fig. 1.2. Of particular O S
O
OMe
OH
N
N
HN
Ixabepilone
O
N H
O
OH
O
Leupyrrin A1 O
O
O HO
O O
OH
O OH
HO O
N
OH OH O
S
H2N
O S
Thuggacin A (1)
N O O
H3C H3C
O
H 3C
N
O
S
Myxothiazol
CH3 O
N H NH N H O H 3C N H N H3 C
O
O NH2
Myxochromide
O
CH3 O
H3C
O
CH3
O N
C OH H3
CH3
H3C OH
O
OH
O
H3 C
Myxochelin
CH3 OH
OH HO
Chivosazole
R
O N H
O N H
OH OH
FIGURE 1.2 A selection of secondary metabolites produced by myxobacteria. Ixabepilone, leupyrrins, and thuggacins are mentioned in the text. Myxothiazol is a mitochondrial electron transport chain inhibitor from M. fulvus, myxochromide is a nonribosomal polypeptide from S. aurantiaca, chivosazoles are cytostatic polyketides from S. cellulosum, while myxochelin is an iron-chelating siderophore.
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note are the epothilones and disorazoles, which are novel classes of antineoplastic drugs (Hopkins and Wipf, 2009; Reichenbach and Ho¨fle, 2008). Epothilones A and B are microtubule-stabilizing agents, with potent cytotoxicity, even against paclitaxel-resistant cells. A lactam analogue of epothilones with increased metabolic longevity (ixabepilone) has been approved by the Food and Drug Administration for the treatment of aggressive forms of breast cancer (Hunt, 2009). Disorazoles have also been shown to possess anticancer activity through the disruption of microtubule polymerization (Hopkins and Wipf, 2009). In fact, 10% of myxobacterial secondary metabolites affect cytoskeleton function (Weissman and Mu¨ller, 2009). As well as anticancer activities, myxobacterial secondary metabolites have been isolated that demonstrate potent antifungal activity (e.g., leupyrrins) and antibacterial activity (e.g., thuggacins and antibiotic TA). Leupyrrins are complex metabolites with a structure including a g-butyrolactone ring, with pyrrole and oxazolinone functionalities (Kopp et al., 2011). The thuggacins are novel thiozole-containing macrolides with activity against Gram-positive bacteria, including Mycobacterium tuberculosis (Steinmetz et al., 2007), while antibiotic TA is a surface-adherent metabolite with activity against E. coli (Simhi et al., 2000). Unusual features of myxobacterial secondary metabolite synthesis include the production of ‘‘rare’’ bacterial metabolites, such as sterols, and a large number of ‘‘hybrid’’ polyketide/nonribosomal polypeptide metabolites (Weissman and Mu¨ller, 2009). The ability to produce particular metabolites is generally strain-specific, suggesting that investigation of secondary metabolism has only scratched the surface of true metabolite diversity in the Myxococcales. Studies of secondary metabolism have developed methods to uncover cryptic production, and provided strategies for yield optimization, while screening efforts are ongoing to test multitudes of novel isolates for novel bioactive compounds (Weissman and Mu¨ller, 2009; Wenzel and Mu¨ller, 2009). Complex metabolites of myxobacteria have also been described (the DKxanthene family and stigmolone), which play an essential role during development, a social behavior exhibited by most myxobacteria (Meiser et al., 2006; Plaga et al., 1998).
B. Myxobacterial sociobiology In the vegetative state myxobacteria typically obtain nutrients either from other soil microorganisms, or from the degradation of plant material. When nutrients are scarce though, the myxobacterial population aggregates, forming a three-dimensional structure called a fruiting body, within which sporulation occurs (Kaiser et al., 2010). The resulting myxospores are relatively resistant to environmental stresses and germinate upon the addition of nutrients. Myxospores are not as tough as the spores
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of Bacillus subtilis and related organisms, and potentially the fruiting body helps provide extra protection to the myxospores while also acting as a dispersal structure. A striking feature of the life-cycle of M. xanthus is the co-operative nature of most stages of the cycle (Fig. 1.3). Myxobacteria are motile
FIGURE 1.3 The life cycle of M. xanthus. Vegetative cells (brown rods) are able to replicate through the co-operative digestion of prey (white rods), shown at the top of the figure. Upon starvation, a population of cells undergoes a series of co-ordinated changes in behavior, resulting in rippling (right hand side), streaming (bottom), and then aggregation (left). As the aggregate matures into a fruiting body, sporulation occurs, producing myxospores (green circles). Red arrows denote the directions of motion of groups of cells.
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organisms, and motility is required throughout their life-cycle. M. xanthus possess two motility systems (see below), one of which is ‘‘social’’ (S-motility), requiring the close proximity of multiple cells to power cell movement (Wall and Kaiser, 1999). During vegetative growth, myxobacteria predate upon other soil microorganisms, and this activity is undertaken by small groups of cells, exhibiting co-operative ‘‘wolf-pack-like’’ behavior (Berleman and Kirby, 2009). The secretion of digestive enzymes and antibiotics causes prey cells to lyse, releasing nutrients into the extracellular milieu, which can then be consumed by the myxobacteria, providing resources necessary for replication. However, when nutrients are exhausted, the starving cells within a population organize themselves into a series of patterns, culminating in development of the fruiting body. Initially, cells become arranged side-by-side, forming a ridge. Multiple ridges give a striated pattern on a substrate, and over time, the ridges move and reflect off one another, giving rise to a dynamic behavior known as rippling (Welch and Kaiser, 2001). As development progresses, ripples break down into streams of cells where the constituent cells predominantly move in the same direction. It is thought that colliding streams then form relatively stationary mounds of cells, which grow in size as streams bring more and more cells to join the aggregate (Kaiser, 2003). Ultimately, the aggregate may contain sufficient cells to form a fruit, and within the structure, sporulation then occurs. When nutrients subsequently become available again, a population of germinants are released from the fruit, which are immediately able to engage in cooperative predation once more. Thus myxobacteria are truly multicellular organisms and exhibit behaviors typically associated with metazoans, such as development, cellular differentiation, and co-ordinated activity. As commonly observed in social systems, cheating phenotypes are found in myxobacteria, with some individuals increasing their proportion in the population at the expense of the co-operative majority (Velicer and Vos, 2009).
C. Predation Predation by M. xanthus is thought to be mediated by the secretion of extracellular hydrolases and antibiotics, which then act on nearby prey cells causing their lysis. M. xanthus is able to predate upon various Gramnegative and Gram-positive bacteria, as well as fungi, with predatory range and efficiency seemingly species and strain-dependent (Morgan et al., 2010; Pham et al., 2005; Rosenberg and Varon, 1984). Many degradative enzymatic activities have been identified in myxobacterial culture supernatants, including protease, lysozyme, amidase, glucosaminidase, and endopeptidase activities (reviewed by Berleman and Kirby, 2009). Predation by M. xanthus has often been compared to the hunting behavior
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of wolf-packs, with groups of cells co-operatively hunting prey. Evidence for co-operative predation has been provided using shaken cultures containing a protein nutrient source (casein). Growth rate was found to depend upon the cell density, which correlated with protease activity in the culture supernatant (Rosenberg et al., 1977). This implied that macromolecule degradation was enhanced by high-cell densities, indicative of a co-operative process. However, more recently, single cells of M. xanthus have been shown to engage in effective predation, suggesting that cooperativity is not absolutely required for predation (McBride and Zusman, 1996), although it may enhance the efficiency of predation in certain situations. An intriguing link between predation and starvation-induced development has been provided by Pham et al. (2005). Using an assay of M. xanthus predatory efficiency, it was shown that mutations in genes responsible for regulating early developmental (and thus potentially nutrient-dependent) events, significantly reduced predatory efficiency, whereas mutations of late-acting developmental genes did not affect predatory ability. Presumably, predatory activity is somehow regulated in response to nutrient (prey) availability. The availability of prey also affects the motility behavior of M. xanthus. During predation of prey colonies, M. xanthus forms rippling patterns, which are a consequence of altered motility behavior and cause enhanced predation efficiency (Berleman et al., 2006). Changes in the availability of prey also affect multicellular development, with a decrease in prey availability enhancing fruiting body formation (Berleman and Kirby, 2007). Thus, nutrition, predation, motility, and development are highly interdependent behaviors of M. xanthus, depending not only on the presence/absence of prey but also on the relative location of predator and prey cells and the local cell density of each cell type.
D. Multicellular development During development, a population of around 105 cells undergoes a series of regulated changes, resulting in the formation of myxospores within a fruiting body. Progression through the developmental program is dependent on cell density, cell–cell interactions, and the signaling state of individuals within the developing population. Development is triggered by starvation, mediated largely by the stringent response which is activated as a consequence of amino acid deprivation (Diodati et al., 2008). An important early intercellular signal of starvation in M. xanthus is A-signal—a mixture of secreted proteins and proteases, which give rise to extracellular peptides and free amino acids (the active components which stimulate A-signal-dependent pathways). The secretion of A-signal acts as a quorum signaling system, with the levels of extracellular amino
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acids being sensed as a proxy for cell number/density (Kaplan and Plamann, 1996). The other particularly important cell–cell signal involved with the regulation of development is C-signal, which is a cell-surface associated protein that is thought to bind to a putative receptor also on the surface of the cell. C-signaling is brought about by cell–cell contact, and therefore, levels of C-signaling are thought to correlate with cell density (S gaard-Andersen et al., 2003). Through a positive feedback loop, C-signaling causes the further expression of C-signal, and therefore, as development progresses at high cell densities within the developing fruit, the level of C-signaling steadily increases. Different behaviors are manifested at different levels of C-signaling (S gaard-Andersen et al., 2003), resulting in an ordered temporal hierarchy of processes within development (i.e., it is the progressive increase in C-signaling which causes rippling, streaming, aggregation, and sporulation to occur in that order during development). C-signal is actually produced as a cell-surface associated proprotein, and proteolytic activation is performed through the regulated secretion of the protease PopC (Rolbetzki et al., 2008). The signaling pathway responsible for multicellular development branches early during starvation (Diodati et al., 2008; Evans and Whitworth, 2010; Pollack and Singer, 2001), with one branch sensing/ regulating intracellular events (cellular pathway) and the other branch sensing/responding to extracellular signals (population pathway). In addition, myxobacteria are able to sporulate outside of a fruit, if exposed to toxic compounds such as glycerol (Dworkin and Gibson, 1964), and this ‘‘emergency’’ sporulation pathway seems to share common components with fruiting body sporulation (Licking et al., 2000). Generally, the regulation of development is extraordinarily complex, with more than 100 genes known to be involved. Many of these genes encode members of the two-component system family of signaling proteins, which are found encoded abundantly in myxobacterial genomes (Whitworth and Cock, 2008). Myxobacterial genomes also have large numbers of genes encoding Ser/Thr kinases/phosphatases which are more typical of eukaryotic signaling pathways. Many of these proteins are also known to play important roles in regulating myxobacterial development (Pe´rez et al., 2008; Treuner-Lange, 2010). An intriguing feature of myxobacterial development is that not all cells that enter a fruit are destined to become myxospores. Around 65% of cells entering the fruit instead lyse during development (Wireman and Dworkin, 1977). Presumably the lysis of such cells provides nutrients for the remaining cells, enabling them to complete the developmental program and differentiate into myxospores. Developmental autolysis thus appears to be a supremely altruistic behavior. Cheating phenotypes are found associated with development (Velicer et al., 2000), where a cheater increases its frequency within the population of spores as compared to the
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original population of vegetative cells. A reduced tendency to autolyse is a simple example of a mechanism whereby a mutant strain could exhibit a cheating phenotype.
E. Motility Myxobacteria are able to move across surfaces by gliding motility, with motion occurring in the direction of the long axis of the cell, accompanied by periodic reversals of direction. Early genetic analyses suggested that M. xanthus possessed two motility systems, implying two modes of motion and two engines (Hodgkin and Kaiser, 1979). One engine was required for ‘‘adventurous’’ movements of individual cells (A-motility), while the second gave rise to ‘‘social’’ movements of groups of cells (Smotility). S-motility appears to be the result of the repeated extension and retraction of Type-IV pili (Tfp) at the leading pole of the cell. Tfp are thought to be extended and to anchor onto the EPS (extracellular polysaccharide) of neighboring cells. Such anchoring triggers retraction of the Tfp, which results in the Tfp-retracting cell dragging itself toward the other ‘‘anchor’’ cells (Li et al., 2003). The molecular mechanism of Amotility is currently contentious. While early data suggested that Amotility was powered by the hydration of slime extruded from the lagging cell pole (Wolgemuth et al., 2002), it now seems more likely that motility is somehow achieved by the translocation of helical cytoskeletal filaments relative to foci mediating adhesion between the cell and underlying substrate (Nan et al., 2011). The genome of M. xanthus includes several chemosensory gene clusters (Zusman et al., 2007), and while some of these seem to have no role in regulating chemotaxis per se, evidence of the directed motion of cells has accumulated in the literature over several years (Curtis et al., 2006; Shi et al., 1993; Tieman et al., 1996). M. xanthus is able to move up a gradient of phosphatidylethanolamine (PE), with activity toward PE with specific fatty acyl chains, in a fibril-dependent fashion (Curtis et al., 2006; Kearns et al., 2000; Kearns and Shimkets, 1998). Myxobacteria also exhibit a behavior called elasticotaxis, which is a directional motion in response to elastic forces in the substrate; thus, M. xanthus can move toward chemically inert latex beads (Dworkin, 1983). It has been suggested that such behavior would allow M. xanthus to track down prey cells purely because of the forces that prey cells would impose on their substrate (Fontes and Kaiser, 1999). Finally, as mentioned previously, myxobacteria exhibit predataxis, in which the individual motions of cells within a predating M. xanthus population are regulated in such a way as to give rippling structures, which enhance predatory efficiency (Berleman et al., 2008).
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F. Extracellular biology The myxobacteria are profoundly social organisms and interact with one another physically as well as through the release and sensation of secreted diffusible factors. There are two important intercellular signals during development—diffusible A-signal, and surface associated C-signal whose activation depends on the regulated secretion of a protease. While any role of slime extrusion in powering A-motility is contentious, cells moving by A-motility certainly leave behind a trail of secreted slime, and following cells preferentially follow those slime-trails. S-motility also requires the secretion of macromolecules, with the repeated extension and retraction of pili, while predation is linked with the secretion of hydrolases and possibly antibiotics. Thus, every aspect of myxobacterial sociobiology is linked with the secretion of specific biomolecules. An early review of protein secretion by myxobacteria (Guespin-Michel et al., 1993) highlighted the technical difficulties in distinguishing between true secretion and the release of cellular proteins as a consequence of cell lysis. This is a particularly important consideration for myxobacteria as they are known to engage in high rates of autolysis (Berleman et al., 2006). A recent and very thorough review of the extracellular biology of M. xanthus included a genomic picture of protein secretion (Konovalova et al., 2009). All the genes required for Sec and Tat pathway secretion of protein and lipoproteins are found in the M. xanthus genome, including signal peptidases. To transport proteins across the OM, M. xanthus has all the genes for a functional type II secretion system. Type I, III, and VI secretion systems are able to transport proteins directly across both the inner membrane and the OM, and M. xanthus has the genes for these three secretion systems as well (Konovalova et al., 2009). In silico analysis of signal sequences within predicted proteins showed unusually large proportions of lipoprotein genes in the M. xanthus genome, consistent with the identification of four type II signal peptidases involved in lipoprotein translocation (Konovalova et al., 2009).
IV. MYXOBACTERIAL VESICLES Considering the predatory life-style of some myxobacteria, production of OMVs by all Gram-negative bacteria and the known ‘‘predatory’’ activity of OMVs, it is perhaps surprising that myxobacterial OMVs were first documented only 2 years ago. Using electron microscope tomography, Palsdottir et al. (2009) undertook an investigation of the structure of M. xanthus biofilms. They observed that in thin biofilms the space between cells was filled with vesicles, and that in thicker biofilms, vesicles were predominantly found surrounding cells. Vesicles were observed to have a fairly uniform size, varying between 30 and 60 nm in diameter, and
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some of the vesicles appeared to be tethered to cells by filaments assumed to be formed by proteins (Palsdottir et al., 2009). Staining of material within vesicles was also observed, suggesting that the vesicles were carrying cargo. A second study employed proteomic approaches to identify proteins within purified OMVs and proteins of the OM (Kahnt et al., 2010). This study was qualitative rather than quantitative, so care must be taken in interpreting its results. Nevertheless, a large number of proteins were identified within the M. xanthus OMVs, including several proteins with predicted hydrolase activities.
A. OMVs of M. xanthus Using electron microscopy, structures reminiscent of OMVs can be readily seen coating the surface of M. xanthus cells (Fig. 1.4). OMVs of M. xanthus vary between 30 and 100 nm in diameter (Kahnt et al., 2010; Palsdottir et al., 2009), which is at the smaller end of the scale observed for Gram-negative OMVs (Kulp and Kuehn, 2010). Small ring-like structures have also been observed on the surface of larger M. xanthus OMVs, and it has been suggested that these rings represent OM porins (Kahnt et al., 2010). When purifying OMVs from cultures of M. xanthus, there are some points to note. First, M. xanthus produces OMVs in large amounts, but starvation significantly stimulates vesicle formation (Kahnt et al., 2010). While starvation increases the yield of vesicles, it is probable that the protein content of starvation-induced OMVs will be different to those of vegetative OMVs. Indeed Kahnt et al. (2010) observed significant differences in protein complement on comparing developmental and
FIGURE 1.4 Low resolution electron micrographs of M. xanthus cells with putative OMVs. Cells growing exponentially were washed and deposited on the surface of a filter before air-drying and imaging. Structures reminiscent of vesicles can be seen on the surface of the rod-shaped cells, and such vesicle-like structures accumulate free of cells in culture supernatants. Bar ¼ 0.5 mm. Images courtesy of S. Wade.
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vegetative OMVs. Second, autolysis occurs at a significant rate in some strains of M. xanthus, particularly during starvation (Berleman et al., 2006), and therefore, preparations of OMVs can become contaminated with membrane fragments arising from cell lysis. For the wild-type strain DK1622, autolysis does not occur significantly until after 20 h of starvation (Berleman et al., 2006), so harvesting cells after 18 h reduces the problem of autolysis and membrane fragments are not then observed by electron microscopy in OMV preparations (Kahnt et al., 2010). Third, M. xanthus is known to produce large protein complexes beyond the OM, such as Tfp. Recovery of OMVs from culture supernatant by ultracentrifugation could conceivably coprecipitate pili with OMVs, although this was not observed by Kahnt et al. (2010) using strain DK1622. If contamination with large protein complexes is a problem with other strains, density-gradient centrifugation can be used to separate protein complexes from OMVs (Kulp and Kuehn, 2010). In a review of protein secretion by myxobacteria, it was noted that while myxobacteria up- or down-regulated the secretion of particular proteins depending on growth conditions, the rate of overall protein secretion remained at a relatively constant rate (Guespin-Michel et al., 1993). Such constancy could be the natural consequence of OMV production if the majority of secreted protein is packaged within vesicles rather than secreted freely into the extracellular medium. Supporting this scenario, the profile of soluble extra-vesicular proteins in M. xanthus culture supernatant is virtually identical to that of the soluble fraction of lysed cells, with both profiles being very different from that of OMVs (H. Currinn, G. Cooke-Fox, A. Evans and D.E. Whitworth, unpublished observation). One class of mutants has been isolated (Exc mutants), which generally hyper- or hypo-secrete protein in M. xanthus (Guespin-Michel et al., 1993), and it would be interesting to determine whether changes in overall protein secretion rates correlate with hyper- or hypo-vesiculation in these mutants.
B. OMVs in M. xanthus biofilms OMVs are found to constitute a large proportion of the extracellular space in biofilms formed by M. xanthus (Palsdottir et al., 2009). The function, if any, of OMVs in myxobacterial biofilms is not clear. Palsdottir et al. (2009) have suggested a role in the cell-to-cell transfer of proteins and in intercellular signaling, while Kahnt et al. (2010) have argued for a role in predation as well as a role in intercellular signaling. OMVs from cultures engaged in planktonic and biofilm growth are known to be significantly different, implying different functional roles (Schooling and Beveridge, 2006). As the biofilms characterized by Palsdottir et al. were single-species
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biofilms, it is unlikely that the OMVs were actively engaged in predation, and it is unclear what signal might be being trafficked by the vesicles. However, a proteomics analysis of M. xanthus OMVs has demonstrated the presence of two protein components of a BCKAD (Branchedchain keto-acid dehydrogenase) complex (Kahnt et al., 2010). These are ‘‘E-signal’’ proteins, which were identified initially in a screen for developmental mutants that could be rescued by codevelopment with wildtype cells (Toal et al., 1995). The observation of E-signal within OMVs suggests a mechanism for the intercellular complementation which first led to E-signal identification. Presumably, E-signal-containing OMVs can fuse with M. xanthus cells, delivering functional BCKAD subunits to cells which lack them genetically (Kahnt et al., 2010). However, such complementation is not necessarily indicative of true signaling (S gaardAndersen, 2008). BCKAD complexes provide a metabolic activity required for the production of long branched-chain fatty acids (Toal et al., 1995), and in this case, intercellular complementation may be more akin to cross-feeding than true intercellular signaling. As vesicles are known to nucleate biofilm formation (e.g., Yonezawa et al., 2009), it is quite possible that OMVs only play a structural role in M. xanthus biofilms. Indeed if vesicles are produced constitutively as a necessary by-product of living with a double-membrane (Wensink and Witholt, 1981), then their occurrence in biofilms would be expected and not necessarily indicative of a biological function. Biofilms are well documented as survival structures, rendering their cellular components relatively resistant to environmental stresses, such as antibiotics and bacteriophage (Gilbert et al., 2002). This property of biofilms could be in part due to the mere presence of vesicles, in much the same way that the grouping together of cells can generally be beneficial to a community to mitigate stress (Velicer and Vos, 2009). Vesicles are pinched-off portions of the OM, and thus, at the cellular level, resemble their parent cell in most outward appearances. As such, OMVs could act as cellular decoys and in doing so protect surrounding cells; for instance, within a vesicle-rich biofilm, a bacteriophage might be more likely to ‘‘infect’’ an OMV than a cell, resulting in relative bacteriophage resistance for the biofilm.
C. OMVs in predation Given the above observations, it seems highly likely that the OMVs of myxobacteria are predatory and myxobacterial predation is mediated, at least in part, by vesicles (Kahnt et al., 2010). Indeed, purified OMVs from M. xanthus do possess lytic activity against E. coli, although significant additional lytic activity is also found in culture supernatants from which vesicles have been removed (H. Currinn and D.E. Whitworth, unpublished observation). Kahnt et al. (2010) identified several proteins
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with predicted hydrolase activities packaged within the OMVs of M. xanthus, including peptidase, chitinase, phosphatase, murein hydrolase, lipase, and phytase activities. There are several advantages to the packaging of lytic factors into OMVs. Active ingredients are protected from environmental stresses, such as degradative enzymes, and OMV components are maintained within OMVs at high concentrations even when at a distance from the producing cell (Kulp and Kuehn, 2010). Myxobacteria move slowly compared to other motile microorganisms and extremely slowly in comparison to the diffusion of small molecules (Koch, 1999). Therefore, there are two problems facing predatory myxobacteria, both of which are caused by diffusion. First, when released into the environment, lytic factors made by the myxobacterium will become increasingly dilute with time and at an increasing distance from the producing cell. This problem is offset slightly by encapsulating lytic factors into OMVs, assuming that a single ‘‘hit’’ from an OMV is sufficient to trigger prey cell lysis. However, if multiple ‘‘hits’’ are required, then the dilution of OMVs into the environment by diffusion will still have a significantly detrimental effect on predatory activity. In addition, when a prey cell lyses, nutrients are released, primarily in the form of macromolecules. These nutrients will then diffuse generally in a direction away from the myxobacterial cell. By consuming nutrients rapidly, a myxobacterium might be able to establish a concentration gradient which favors diffusion of nutrients toward itself, but regardless, the distance between predator and prey cell will determine the efficiency of nutrient capture by the predatory myxobacterium, and diffusion will necessarily reduce predatory efficiency (Fig. 1.5). Therefore, in general terms, it would be better for a myxobacterium to limit lysis of prey to its immediate vicinity as this would be most efficient in terms of both the production of lytic activity and the effectiveness of nutrient capture. In reality, myxobacterial lysis of prey appears to be almost contact-dependent, supporting such a notion of proximal killing (Berleman and Kirby, 2009). An unappreciated feature of packaging lytic factors into OMVs is that the effective size of lytic factors such as hydrolases will be dramatically increased upon being incorporated into OMVs. This would result in a reduction in the rate of migration of vesicle-bound hydrolases compared to that of hydrolases secreted directly into the medium, further restricting lytic activity to the immediate vicinity of the OMV-producing cell. Such behavior would presumably be enhanced further if vesicles are truly tethered to cells by protein filaments as proposed by Palsdottir et al. (2009). A large number of questions remain regarding the mechanisms of OMV-mediated predation by myxobacteria. It would be interesting to determine whether the specificity of myxobacterial OMVs for the cells of particular target species correlates with the predatory range exhibited
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OMVs
[2] Concentration of lytic factors [1] Threshold
Distance
Zone of killing Concentration of released nutrients
FIGURE 1.5 Spatial aspects of predation. Predation by myxobacterial cells (yellow rods) is achieved through the secretion of hydrolases and other lytic factors. Considering growth on a surface, the concentration of secreted lytic factors will decrease as a function of distance from the producing cells, due to degradation and diffusion, resulting in a concentration profile [line 1]. It is thought that for each prey organism, there will be a certain threshold concentration of lytic factors that must be exceeded in order to lyse the prey. Presumably, if the number of myxobacterial cells at a point were doubled, the concentration profile of lytic factors would also increase [line 2]. This would extend the area over which prey cell lysis occurred (pink circle), while for tougher prey requiring higher concentration thresholds for lysis, a greater numbers of cells might be required to give any prey lysis at all. Nutrients released by lysis of prey (white rods, green concentration profile) would be more accessible to the myxobacteria, the closer they were to the prey. Vesicles are very large macromolecular aggregates with dimensions of only 1–2 orders of magnitude smaller than their parent cells. The mobility of OMVs across a surface would be much lower than that of free lytic factors, and OMVs would be expected to exhibit a very steep concentration profile (pale blue), focusing potent killing in the immediate vicinity of OMV-producing myxobacteria.
by the myxobacterial strain; for instance, is prey range a consequence of the ability of OMVs to fuse with prey organisms’ membranes or due to the specificity of cargo hydrolases or a combination of both? An extension of
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this question considers the relationship between OMV-producing cells and produced OMVs. Can OMVs re-fuse with parental membranes, and if so, do producing cells lyse upon OMV-fusion? Does a producing cell have ‘‘antifusion’’ proteins on its surface or does it lack an ‘‘OMV receptor’’ required for fusion? If OMVs can fuse with target cells, why can’t OMVproducing cells fuse with other cells?
D. OMVs and motility Over the years, many mutants of M. xanthus have been isolated which exhibit defects in A-motility or S-motility. A subset of nonmotile mutants are able to be rescued by coculturing with wild-type cells, and this phenomenon is referred to as stimulation. Stimulation of motility has been shown to be due to the transfer of proteins from wild-type to mutant cells, and it was assumed that transfer arose as a consequence of transient cell–cell fusion (Nudleman et al., 2005). In microscopic studies of M. xanthus biofilms, there was no evidence of cell–cell fusion, however, the transfer of vesicles between cells provides a plausible mechanism for the trafficking of proteins between cells in stimulation (Palsdottir et al., 2009), as proposed for the transfer of E-signal proteins (Kahnt et al., 2010). Proteins known to be transferred during stimulation include the A-motility protein CglB and the S-motility protein Tgl (Nudleman et al., 2005). In a proteomic survey of the OM and OMVs of M. xanthus, CglB and Tgl were both detected in the OM, however, neither were found to be present in OMVs (Kahnt et al., 2010). It is possible that CglB and Tgl are found in vesicles, but below the detection limit of the proteomic approach employed. Consistent with this suggestion, some known OM proteins of M. xanthus were not identified in OM fractions by Kahnt et al. (2010), including the well-described C-signal protein CsgA, which was not found in the OM of developing cells. Changes in motility that manifest as rippling in the presence of prey have been described as a predatory behavior (Berleman et al., 2006). Such behavior was also shown to occur in the absence of prey, if instead purified macromolecules such as protein, DNA, and peptidoglycan were provided. As OMVs are agglomerations of macromolecules, it is quite conceivable that vesicles might also stimulate predatory rippling in lieu of macromolecules, which if true might imply a role in predation beyond merely trafficking lytic factors.
E. Cargo of myxobacterial OMVs Evidence from proteomic comparisons between the OM proteome and that of OMVs suggests that some proteins might be preferentially packaged into OMVs by M. xanthus (Kahnt et al., 2010). However, as the study
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was not quantitative, and the method used to probe the OM proteome was different from that used to characterize the OMV proteome, it is not possible to know whether apparent differences are truly due to selective cargo loading or are instead technical artefacts. Nevertheless, biochemical analyses of hydrolase activities has provided supporting evidence for the selective incorporation of enzymes into vesicles; for instance, under certain conditions, around 95% of the pNPP-hydrolysing phosphatase activity within a culture of M. xanthus can be found within OMVs (A. Evans and D.E. Whitworth, unpublished observations), suggesting either selective incorporation or activation/ stimulation of enzymatic activity within vesicles. A predicted phosphatase protein (MXAN1389) has been observed in M. xanthus OMVs, and it is tempting to speculate that this protein is responsible for observed phosphatase activity. Further, a large proportion of OMV proteins with predicted functions were found to be putative hydrolases (Kahnt et al., 2010), consistent with selective cargo loading and a role in predation. The set of proteins within OMVs have been found to depend on whether cells producing the vesicles were growing vegetatively or were developing (Kahnt et al., 2010). This observation may merely reflect the presence of different proteins in the OM of developing cells and the nonspecific leakage of those into OMVs. However, of 31 OMV proteins which were found in vesicles derived from developing cells but not vesicles from vegetative cells, only seven were also found in the OM proteome of developing cells. This suggests that there is selective incorporation of developmentally regulated gene products into vesicles, which in turn implies that vesicles may have a mechanistic role to play in the progression of development. Such a role might involve signaling or transport between cells, efficient cannibalism of nutrients released from developmental lysis, altered motility behavior, or a combination of several properties. Certainly, elucidating the roles of myxobacterial OMVs promises to yield many interesting insights over the coming years, not only into OMV biology but also into the social biology of the myxobacteria.
V. CONCLUDING REMARKS Our current understanding of OMVs in myxobacterial biology is frustratingly limited. In the sections above, it was discussed how the general properties of OMVs might apply to well-studied features of myxobacterial biology. However, a greater understanding of myxobacterial OMVs also has the potential to shed light on fundamental features of OMV biology, many of which are still poorly understood. For instance:
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Do OMVs traffic peptidoglycan signals?
OMVs are known to carry components of peptidoglycan such as muropeptides (Kaparakis et al., 2010), and peptidoglycan fragments potentially act as signals of membrane stress or resumed growth in bacteria (Kana and Mizrahi, 2010; Paget et al., 1999). It has been established that peptidoglycan delivered through OMVs can trigger responses in eukaryotic cells, but can OMVs traffic peptidoglycan signals between bacteria? In M. xanthus, there is abundant but indirect evidence, that peptidoglycan and/or its components act as important signals during early development (reviewed by Yang et al., 2008). Can OMVs re-fuse with OMV-producing cells?
Although an OMV-producing cell would presumably need a resistance mechanism to prevent lysis from its own OMVs, it is possible that released OMVs might end up fusing with their parental cell or one of its clones. Such a phenomenon would allow the ‘‘sharing’’ of molecules between cells within a population, and as such, might have consequences for social behavior. Could the transfer of molecules between the cells within a population improve the fitness of the population as a whole by nurturing less able individuals within the society and in doing so maintain diversity? Or perhaps, such sharing might compensate for transient shortfalls in the OM/periplasmic protein complement of individuals? It would be nice to imagine that such charitable behaviors might be found among bacteria, made possible by OMVs. What powers membrane fission to release OMVs?
As explained by Kulp and Kuehn (2010), membrane fission events are often energy dependent, but there are no obvious energy sources available in the bacterial periplasm to power OMV release. However, bacteria do have mechanisms to power processes occurring at the OM, using energy from the inner membrane. TonB-dependent transporters enable the active transport of small molecules/complexes across the OM (Noinaj et al., 2010). The ExbB/ExbD/TonB inner membrane complex is able to transduce energy, in the form of proton motive force, to TonB-dependent transporters. Eleven TonB-dependent receptors have been identified in the M. xanthus OM (Kahnt et al., 2010). Features of these TonB-dependent proteins suggest that the majority have no role in signaling or transport, and there are few clues to their function (Kahnt et al., 2010). Could TonBdependent complexes provide the energy for membrane fission in M. xanthus, and in bacteria more generally? Thus, myxobacteria may represent model organisms for studies into OMV biology, potentially providing insights into both the mechanisms and the functional consequences of OMV production.
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ACKNOWLEDGMENTS Many thanks to Alun Evans, Heather Currinn, and Gillian Cooke-Fox for sharing unpublished observations, and to Stephen Wade for the images in Fig. 1.4.
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CHAPTER
2 Diversity, Structure, and Size of N2O-Producing Microbial Communities in Soils—What Matters for Their Functioning? Gesche Braker1 and Ralf Conrad
Contents
I. Introduction II. Global Importance of N2O Emissions III. Processes Leading to N2O Production A. Nitrification B. Denitrification C. Other biological N2O-generating processes D. Chemodenitrification IV. Exploring Ammonia Oxidizer and Denitrifier Communities in Soil A. Ammonia oxidizer communities B. Denitrifier communities V. Importance of Diversity, Structure, and Size of Nitrifier and Denitrifier Communities for N2O Production in Soil A. Diversity of nitrifier communities B. Structure of nitrifier communities C. Size of nitrifier communities D. Diversity of denitrifier communities and N2O emission E. Structure of denitrifier communities and N2O emission
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Max Planck Institute for Terrestrial Microbiology, Karl-von-Frisch-Strasse 10, Marburg, Germany 1 Corresponding author: e-mail address:
[email protected] Advances in Applied Microbiology, Volume 75 ISSN 0065-2164, DOI: 10.1016/B978-0-12-387046-9.00002-5
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2011 Elsevier Inc. All rights reserved.
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F. Size of denitrifier communities and N2O emission VI. Conclusion Acknowledgments References
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Nitrous oxide (N2O) is mainly generated via nitrification and denitrification processes in soils and subsequently emitted into the atmosphere where it causes well-known radiative effects. How nitrification and denitrification are affected by proximal and distal controls has been studied extensively in the past. The importance of the underlying microbial communities, however, has been acknowledged only recently. Particularly, the application of molecular methods to study nitrifiers and denitrifiers directly in their habitats enabled addressing how environmental factors influence the diversity, community composition, and size of these functional groups in soils and whether this is of relevance for their functioning and N2O production. In this review, we summarize the current knowledge on community–function interrelationships. Aerobic nitrification (ammonia oxidation) and anaerobic denitrification are clearly under different controls. While N2O is an obligatory intermediate in denitrification, its production during ammonia oxidation depends on whether nitrite, the end product, is further reduced. Moreover, individual strains vary strongly in their responses to environmental cues, and so does N2O production. We therefore conclude that size and structure of both functional groups are relevant with regard to production and emission of N2O from soils. Diversity affects on function, however, are much more difficult to assess, as it is not resolved as yet how individual nitrification or denitrification genotypes are related to N2O production. More research is needed for further insights into the relation of microbial communities to ecosystem functions, for instance, how the actively nitrifying or denitrifying part of the community may be related to N2O emission.
I. INTRODUCTION Nitrous oxide (N2O) is a trace gas of global relevance, which contributes significantly to the anthropogenic greenhouse gas effect (Crutzen, 1970; Dickinson and Cicerone, 1986). Most of the anthropogenic greenhouse gas effect is due to agricultural land use and increasing fertilizer application (EPA, 2010; IPCC, 2007). A significant fraction of the N-fertilizers applied is converted to N2O by the action of a suite of microbiological processes among which nitrification and denitrification are predominating.
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Although we also briefly introduce other microbial pathways that generate N2O, in this review, we focus on nitrification and denitrification as the main pathways leading to the fluxes of N2O from soils. The two groups of microbiota responsible for these processes, autotrophic nitrifiers and heterotrophic denitrifiers, were characterized based on culture-based studies in the past. The activity of these two functional groups in the soil has intensively been studied and applied to mechanistic models of N2O emission from soils (Chen et al., 2008; Hergoualc’h et al., 2009; Li et al., 2000). Further, the relative contribution of each group to N2O emission from soil has been frequently studied (Baggs, 2008; Wrage et al., 2001). However, these studies all neglected that functional groups are composed of more than one microorganism and may encompass a complex community of different species. The advent of molecular techniques in microbial ecology during the past two decades has enabled studying their diversity, community composition, and abundance by using functional marker genes involved in basically every single step of the nitrification and denitrification pathways. Although these methods are also prone to bias, they allowed more comprehensive insights into the community structure of nitrifiers and denitrifiers due to the fact that high numbers of samples could be processed without effort. Application of molecular techniques enabled more extensive research on environmental factors that shape microbial communities as mediators of nutrient cycling, and large efforts have been made to advance our understanding of the relationship between microbial community structure and ecosystem functioning. However, results on how community diversity, composition, and abundance of nitrifier and denitrifiers control nitrification and denitrification processes in the environment are at least in part conflicting. This has been attributed to ecosystem differences (Rich and Myrold, 2004) and to the impact of environmental factors which are not yet understood (Wallenstein et al., 2006). In this review, we aim at summarizing the current knowledge on the relevance of diversity, structure, and size of soil ammonia oxidizer and denitrifier communities for community functioning and how this may relate to N2O fluxes from terrestrial ecosystems.
II. GLOBAL IMPORTANCE OF N2O EMISSIONS N2O, also called laughing gas, is the third most important greenhouse gas after CO2 and methane (CH4) due to its long atmospheric lifetime of approximately 120 years and its global warming potential, which is about 310 times more powerful than CO2 on a 100-year time frame. N2O, which accumulates in the troposphere, is transparent to the incoming short-wave solar radiation but absorbs the outgoing long-wave
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terrestrial radiation (infrared radiation). This increases the kinetic energy of the gas molecules causing the temperature of the atmosphere, and subsequently the Earth’s surface, to rise. The upper atmosphere acts as a sink for N2O (Prather et al., 1995). During destruction of N2O, nitric oxide (NO) is formed, which destroys the stratospheric ozone layer protecting the Earth against UV light (Crutzen, 1970; IPCC, 2007). N2O has both natural- and human-related sources among which the natural sources account for over 60% of the annually emitted N2O (EPA, 2010). Soils covered by natural vegetation (6.6 Tg y1) and oceans (5.4 Tg y1) account for over 90% of the natural N2O sources. Tropical rainforest soils are the single most important source of atmospheric N2O (Werner et al., 2007) with a contribution of 75% from wet forests soils and 25% from dry savannahs (EPA, 2010; Fig. 2.1). Anthropogenic sources include not only primarily cultivated soils but also biomass burning, feedlots, and industry (e.g., production of nylon). Global atmospheric concentrations of N2O have on the average increased from background levels of about 270 parts per billion by volume (ppbv) in preindustrial times (till 1750) to about 319 ppbv in 2005 (IPCC, 2007). This equates to a 16% increase for the past 250 years and accounts for about 6% of the anthropogenically enhanced greenhouse gas effect. The atmospheric increase is largely attributed to agricultural land use and input of N fertilizers (IPCC, 2007; Mosier et al., 1998). From 1960 to 1995, the amount of fertilizers globally applied increased sevenfold (Fixen and West, 2002;
N2O soil
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FIGURE 2.1 Annual N2O production from soils under natural vegetation and fertilized agricultural fields (in tons N2O-N y 1) (from Geia, global emissions inventory activity, www.geiacenter.org).
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Tilman et al., 2002), resulting in about 1.5 Tg N2O y 1 released to the atmosphere (Mosier et al., 1998). Currently, the global N2O budget is imbalanced, as the total source strength of about 17.7 Tg N2O y 1 is larger than the total sink strength of about 14 Tg N2O y 1 (Fowler et al., 1998; IPCC, 2007). Therefore, the atmospheric concentration of N2O continues to increase with a rate of 0.26% per year. However, it has to be noted that large uncertainties exist with regard to the global budget. For instance, several reports showed that soils can also act as an occasional sink for N2O (Chapuis-Lardy et al., 2007; Fowler et al., 2009).
III. PROCESSES LEADING TO N2O PRODUCTION N2O emissions are predominantly biogenic in origin, and N2O is formed by a wide range of mostly microbiological processes involved in nitrogen cycling. Primary sources are microbial nitrification and denitrification that utilize the inorganic N compounds, ammonium and nitrate, respectively (Firestone and Davidson, 1989). However, several other microbial processes such as heterotrophic nitrification (Blagodatsky et al., 2006; Papen et al., 1989), codenitrification (Kumon et al., 2002; Tanimoto et al., 1992), and dissimilatory nitrate reduction to ammonia (DNRA; Bleakley and Tiedje, 1982; Smith, 1982, 1983; Smith and Zimmerman, 1981) also involve production of N2O. In natural and managed soils, nitrification and denitrification processes are the major sources of N2O (Barnard et al., 2005) and both contribute 70% to the global N2O emissions (Conrad, 1996; IPCC, 2001). Under most soil conditions, nitrification and denitrification occur simultaneously and the net flux to the atmosphere is the result of both processes together (Fowler et al., 2009). In structured aerobic soils, both processes even occur linked as coupled nitrification–denitrification allowing N2 production from NH4þ (Kremen et al., 2005). However, not only the rates of N2O production vary but also the relative contribution of both processes to N2O fluxes (Go¨dde and Conrad, 2000). Denitrification rates are temporally and spatially variable which is presumably due to denitrification ‘‘hot spots’’ and ‘‘hot moments’’ meaning that small areas of soil cores, ecosystems, and landscapes account for a very high percentage of areal denitrification within a given time period (Groffman et al., 2006; McClain et al., 2003; Parkin, 1987). Whether denitrification or nitrification dominates depends on many different factors, for example, soil type (Ambus et al., 2006; Go¨dde and Conrad, 2000), fertilizer applications (Senbayram et al., 2009), O2 availability (Bollmann and Conrad, 1998), irrigation (Panek et al., 2000), season (Kester et al., 2011; Wolf and Brumme, 2002), pH (Baggs et al., 2010), and competition between fungi and denitrifying bacteria for nitrate (Siciliano et al., 2009). A particular regulator of both processes is soil water content, as nitrification is an aerobic process
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while denitrification is anaerobic and oxygen partial pressures depend on the soil water content. Hence nitrification is the preferential source of N2O fluxes from well-aerated soils (water-filled pore space, WFPS < 60%; Bateman and Baggs, 2005; Mathieu et al., 2006) while N2O production in wet soils (WFPS 60–90%) is predominantly derived from anaerobic denitrification (Bateman and Baggs, 2005; Skiba et al., 1997).
A. Nitrification 1. Autotrophic nitrification a. Ammonia oxidation Autotrophic nitrification is the oxidation of
ammonium (NH4þ) or ammonia (NH3) to nitrate via nitrite in a two-step process by chemolithoautotrophic ammonia and nitrite oxidizers (Fig. 2.2). During ammonia oxidation, N2O can be formed by chemical decomposition of hydroxylamine (Frame and Casciotti, 2010; Hooper and Terry, 1979; Wrage et al., 2005). However, formation of nitrite is always the main pathway, and levels of NO and N2O produced are several orders of magnitude lower (103–106) than those of nitrite (Arp and Stein, 2003).
b. Nitrifier denitrification Nitrifier denitrification is an alternative pathway (Fig. 2.2). It is distinct from coupled nitrification–denitrification processes and involves the oxidation of ammonia to nitrite and its subsequent reduction via NO to N2O by the same autotrophic ammonia-oxidizing bacterium (Colliver and Stephenson, 2000; Poth and Nitrification
Ammonia monooxygenase (amoABC)
NH3
NO3– Nitrate oxidoreductase (nxr)
Hydroxylamine oxidoreductase (hao)
NH2OH
NO2–
NO3– Nitrite oxidation
Nitrate reductase (GH/napA)
NO2– Nitrite reductase (nirK/nirS)
NO
NO
NO NO reductase (qnorB/norCB)
N2O-pool
N2O
N2O
N 2O N2O reductase (nosZ)
N2
N2
FIGURE 2.2 Biological reactions of the nitrogen cycle producing N2O.
Denitrification
Ammonia oxidation
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Focht, 1985; Schmidt et al., 2004; Shaw et al., 2006; Wrage et al., 2001). Occasionally, nitrite may be even completely reduced to N2 (Poth, 1996), but N2O is the more common end product of nitrifier denitrification. Nitrifier denitrification may be a common trait among bacterial ammonia oxidizers (Shaw et al., 2006). Nitrifier denitrification can be ecologically important under conditions of high N, low organic C, and low oxygen pressure, and more recent studies have suggested that the process may contribute considerably to N2O fluxes from soil (Ma et al., 2007; SanchezMartı´n et al., 2008; Webster and Hopkins, 1996; Wrage et al., 2004). The most comprehensive study on the importance of nitrifier denitrification comes from Kool et al. (2010). These authors could show that although fertilizer-derived denitrification is predominating, nitrifier denitrification contributes significantly to total N2O fluxes at least in grassland and arable soils albeit not in forest soils (Kool et al., 2010). In contrast, N2O from ammonia oxidation contributed only marginally to the total N2O flux from these soils. The study also suggested that nitrification-derived N2O in the soil may be limited by low O2 partial pressure at high moisture levels resulting from a suppression of the first step in ammonia oxidation in the aerobic organisms. Additional factors that were shown to impact the relative significance of these N2O-producing processes are pH and organic C (Wrage et al., 2001). Besides autotrophic ammonia oxidizers, several nitrite-oxidizing bacteria were shown to produce N2O from nitrate during anoxic growth. However, basically nothing is known about the role of N2O production by nitrite-oxidizing bacteria to total N2O production in soil (Freitag et al., 1987).
2. Heterotrophic nitrification Heterotrophic nitrification also produces N2O by a type of nitrification– denitrification process and is carried out by a large variety of phylogenetically unrelated bacteria and fungi that use organic compounds as C and energy source (Arts et al., 1995; Blagodatsky et al., 2006; Hayatsu et al., 2008; Laughlin et al., 2008; Matsuzaka et al., 2003; Otte et al., 1996; Papen et al., 1989). Although the relevance of heterotrophic nitrification was shown for some soils, most of the current knowledge is based on studying strains of Alcaligenes spp. These organisms oxidize ammonia or the reduced nitrogen in organic compounds to hydroxylamine, nitrite, and nitrate while they are using organic compounds in heterotrophic metabolism. In contrast to autotrophic nitrification, oxidation of ammonium in heterotrophic nitrification is not coupled to energy conservation, and the enzymes responsible for the pathway differ from those of autotrophic nitrifiers. The specific nitrification rates are usually significantly lower in heterotrophic than in autotrophic nitrifiers (Kuenen and Robertson, 1994). Blagodatsky et al. (2006) proposed that the nitrite produced by heterotrophic nitrification is subsequently reduced to N2 via denitrification (Blagodatsky et al., 2006). Thus, similar to
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nitrifier denitrification in autotrophic nitrifiers, N2O can be produced by the concerted action of two pathways in a single organism. It is a process that simultaneously uses oxygen and oxidized nitrogen compounds as electron acceptors (Blagodatsky et al., 2006). Cell-specific N2O production was much higher in heterotrophic than in autotrophic nitrifiers (Cofman Anderson et al., 1993; Papen et al., 1989). Heterotrophic denitrification is generally an aerobic process. With the current knowledge, at least some of the N2O reported to originate from aerobic denitrification can be attributed to heterotrophic nitrification. Although it is widely accepted that autotrophic nitrification in soils is the prevalent nitrification process contributing to N2O fluxes (Tortoso and Hutchinson, 1990), high nitrification rates in acidic soils suggest that heterotrophic nitrification may be significant under certain conditions because it is less impacted by low pH than autotrophic nitrification (Islam et al., 2007). Such conditions are found in acidic forest soils where heterotrophic nitrification was the dominant nitrification pathway (Cai et al., 2010; Pedersen et al., 1999; Schimel et al., 1984).
B. Denitrification Denitrification is an anaerobic respiration including the stepwise reduction of nitrate or nitrite to N2 via the intermediates NO and N2O (Fig. 2.2). It is the major biological process in soils that returns fixed nitrogen to the atmosphere and thereby closes the nitrogen cycle (Philippot et al., 2009b). In contrast to nitrification, N2O is an obligatory intermediate of the denitrification process and may even be the end product of the pathway (Cofman Anderson and Levine, 1986). Denitrification accounts for a loss of up to 30% of fertilizers applied, thereby limiting the nitrogen availability to plants (Ambus and ZechmeisterBoltenstern, 2007; De Klein and Logtestijn, 1994; Mogge et al., 1999). Such loss is common even when ammonium instead of nitrate is used as fertilizer, as the nitrate produced by nitrification of ammonium is often directly denitrified. The process of ‘‘denitrification coupled to nitrification’’ involves distinct microorganisms (Arth et al., 1998; Avrahami et al., 2002; Carrasco et al., 2004; Kool et al., 2010). However, denitrification may also act as a sink for N2O, as N2O can be further reduced to N2 under conditions of complete denitrification. The flux of N2O at the soil/atmosphere interface is the result of dynamic production and consumption processes in the soil (Conrad, 1994). Whether denitrification acts as a sink or source strongly depends not only on the biological factors (activity of denitrification enzymes and the microbial communities) but also on the diffusion of N2O in the soil and its dissolution in water (Chapuis-Lardy et al., 2007; Smith et al., 2003). For instance, under anoxic conditions due to high water content or by
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compaction of fine textured soil, the probability that denitrification gases are reconsumed within the soil is greatly enhanced (Fowler et al., 2009).
C. Other biological N2O-generating processes 1. Codenitrification Codenitrification can be distinguished from respiratory denitrification by isotope-labeling experiments (Laughlin and Stevens, 2002). It is performed by fungi and bacteria and involves the formation of N2 or N2O by synproportionation of oxidized nitrogen (e.g. nitrite) with reduced nitrogen, for example, the nitrogen in amino acids, aniline, or azide (Kumon et al., 2002; Shoun et al., 1992; Tanimoto et al., 1992). The mechanisms of this process differ, for example, among fungal species, as different end products are produced and the molecular mechanism and physiological significance remain to be elucidated. That codenitrification may account for as much as 92% of the flux of labeled N2 in grassland soils was shown in a comprehensive 15N-labeling study on N2O- and N2producing processes. However, N2O predominantly originated from denitrification, and its flux was always greater than the flux of N2 (Laughlin and Stevens, 2002).
2. Dissimilatory nitrate reduction to ammonia DNRA by bacteria, for example, isolated from soil, results in nitrate reduction to ammonia, but besides NH4þ can also lead to the production of N2O (Satoh et al., 1983; Smith, 1982). The process occurs under strictly anaerobic conditions and is thought to be favored over denitrification by a high C/N ratio (Tiedje, 1988). Both DNRA and denitrification, however, can also occur simultaneously (Paul and Beauchamp, 1989). DNRA was found to be relevant in some soils, for example, in tropical and paddy soil (Silver et al., 2001; Yin et al., 2002). For instance, in a tropical upland soil, DNRA rates were three times higher than rates of denitrification, and DNRA accounted for up to 75% of the nitrogen pool turnover (Silver et al., 2001).
3. Nitrate assimilation Smart and Bloom showed that N2O emission was correlated with nitrate assimilation in wheat leaves and was not due to microbial activity (Smart and Bloom, 2001). N2O was produced in vitro by the leaves during photoassimilation of nitrite in the chloroplast. Although the N2O fluxes from nitrate were among the smallest trace gas emissions by any higher plant ever measured, the authors calculated that photoassimilation alone could produce from 0.03 to 0.9 Tg N2O-N y 1. Hence, given the large quantities of nitrate assimilated by plants in the
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terrestrial biosphere, N2O formation during nitrite photoassimilation could be an important global biogenic source of N2O.
D. Chemodenitrification Chemodenitrification describes either the chemical decomposition of hydroxylamine and nitrite during nitrification or the chemical reactions in which nitrite is reduced by organic (e.g., amines) or inorganic (e.g., Fe2þ or Cu2þ) molecules (Wrage et al., 2001). The chemical decomposition of nitrite, which is very common in soil under acidic conditions, produces mainly NO but also N2O and N2 (Tiedje, 1988). Chemodenitrification occurs in soils only at low pH (van Cleemput and Baert, 1984; van Cleemput and Samater, 1995), for example, in acid forest at pH < 5.0 (Tiedje, 1994). This abiotic process is not considered to be important on a global scale because it becomes significant only in the presence of high nitrite concentrations (> 1 mM), a condition which is not common in natural environments (Yoshinari, 1990).
IV. EXPLORING AMMONIA OXIDIZER AND DENITRIFIER COMMUNITIES IN SOIL Pure cultures are necessary and well suited to study the physiology, genetics, and biochemistry in single organisms. However, as only 0.3% of the soil microbiota is susceptible to cultivation, culture-based studies lead to a significant underestimation of microbial diversity which strongly limits studies on the structure of natural microbial communities (Amann et al., 1995). To circumvent this limitation, molecular, primarily PCR-based, approaches have been developed to detect nitrifiers and denitrifiers in environmental samples and to analyze the diversity, composition, and abundance of these functional groups. These approaches are not only targeting the genes of ribosomal RNA for phylogenetic affiliation but also targeting the genes, transcripts, and proteins that are functionally involved in nitrification and/or denitrification and ideally are specific for the particular type of metabolism.
A. Ammonia oxidizer communities The functional group of ammonia-oxidizing bacteria (AOB) is represented by organisms affiliated with the b- and g-proteobacteria (Purkhold et al., 2000). While the g-proteobacterial AOB are marine Nitrosococcus spp., b-proteobacterial AOB consist of the genera Nitrosospira and Nitrosomonas (Prosser, 2007). Nitrosospira and Nitrosomonas spp. comprise a monophyletic group of organisms belonging to at least nine distinct
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lineages some of which are specific for a given habitat (Bernhard and Bollmann, 2010). For instance, albeit being less readily cultivated from soils than Nitrosomonas spp., Nitrosospira spp. (clusters 2, 3, and 4) represent the most abundant AOB communities from terrestrial habitats (Bruns et al., 1999; Kowalchuk and Stephen, 2001; Stephen et al., 1996). The ability to oxidize ammonia was long believed to occur exclusively among autotrophic bacterial ammonia oxidizers (AOB), but archaeal ammonia oxidizers (AOA) were identified as new players in the N-cycle during the past 5 years. First evidence that archaea carry the genetic potential for ammonia oxidation, that is, an amoA gene with homology to its bacterial counterparts, came from the analysis of Sargasso Sea and soil metagenomes (Treusch et al., 2005; Venter et al., 2004). The genome sequences indicated that the respective organisms were affiliated to the mesophilic Crenarchaeota recently proposed as new phylum of Thaumarcheaota (Brochier-Armanet et al., 2008; Spang et al., 2010). Meantime, pure cultures were confirmed of carrying archaeal amoA, that is, Nitrosopumilus maritimus (Ko¨nneke et al., 2005) and Nitrososphaera gargensis (Hatzenpichler et al., 2008). The amoA gene was also found in the genome of uncultured Crenarchaeum symbiosum, the symbiont of a marine sponge (Hallam et al., 2006). Novel comprehensive data sets underline their environmental relevance and show that they are ubiquitous and constitute the dominant fraction of ammonia oxidizers in many terrestrial habitats (Erguder et al., 2009; Leininger et al., 2006). The amoA gene codes for a subunit of the key enzyme in bacterial and archaeal ammonia oxidation, the enzyme ammonia monooxygenase (AMO) which is encoded by the amoABC operon. AmoA is the subunit with the site of ammonia oxidation. Two to three copies of the AMO operon are present in ammonia oxidizers belonging to the b-proteobacteria which are all functional and sustain growth while g-proteobacteria contain only one copy (Norton et al., 2002). AMO is a versatile enzyme as it does not only oxidize ammonia but also a suite of other substrates, for example, CH4. Moreover, the enzyme as well as the amoA gene shows similarity to particulate CH4 monooxygenase and the respective gene pmoA (Arp and Stein, 2003). Interestingly, AMO from heterotrophic nitrifiers seems to share partial sequence similarities with AMO from autotrophic nitrifiers (Hayatsu et al., 2008). The amoA gene has been used extensively as a functional gene marker to study bacterial ammonia oxidizers (Rotthauwe et al., 1997). Its phylogeny generally agrees with that of b-proteobacterial ammonia oxidizers defined based on 16S rRNA genes (Aakra et al., 2001; Purkhold et al., 2000, 2003) and allows a specific finescale resolution of closely related populations (Rotthauwe et al., 1997). Putative homologs of amoABC also occur in ammonia-oxidizing archaea (AOA) albeit showing only low similarity (38–51% amino acid sequence similarity) to their bacterial counterparts (Ko¨nneke et al., 2005).
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The second step, the oxidation of hydroxylamine to nitrite, is catalyzed by the hao gene-encoded hydroxylamine oxidoreductase (HAO). Similar to amoABC, hao is also present in three copies in ammonia oxidizers; in contrast, however, this enzyme is unique to autotrophic AOB sharing no similarity with those found in heterotrophic nitrifiers ( Jetten et al., 1997; Moir et al., 1996) and seems to be lacking in AOA (Walker et al., 2010). In addition to the enzymes involved in the oxidation of ammonia to nitrite, ammonia-oxidizing bacteria may also contain enzymes involved in nitrite reduction, thus allowing nitrifier denitrification. Homologs of nirK and norB genes occur in Nitrosomonas spp. and Nitrosospira spp. as well as in Nitrosococcus spp., species capable of nitrifier denitrification. Moreover, nirK was also found among AOA (Bartossek et al., 2010; Treusch et al., 2005). However, the nirK transcript copy number of AOA in soils was uncoupled from denitrification activity (Bartossek et al., 2010), and no gene-encoding NO reductase was found by genome sequencing (Walker et al., 2010). Therefore, it is unclear whether AOA can produce N2O at all.
B. Denitrifier communities Denitrifiers constitute a polyphyletic group of mostly heterotrophic microorganisms which share the ability to denitrify and seem to have acquired this trait via a suite of evolutionary mechanisms ( Jones et al., 2008). This may explain why on one hand organisms denitrify which are phylogenetically only distantly related while on the other hand not all closely related species of a given genus share this ability. To date, the ability to denitrify was described for microorganisms belonging to more than 60 genera, which are listed by Philippot et al. (2007) in the most comprehensive compendium to date. Although most denitrifiers belong to the proteobacteria (a-, b-, g-, and e-proteobacteria), denitrification is also found among the Firmicutes, Actinomycetes, Bacteroidetes, and Aquificaceae as well as among the archaea. Denitrification was further shown to be widespread among Foraminifera and Gromiida (Pin˜a-Ochoa et al., 2010; Risgaard-Petersen et al., 2006). Another group impacting N2O fluxes, that has long been neglected, are fungi. Fungi are capable of denitrification, and they were even shown to be responsible for most of the N2O production from some soils (Laughlin and Stevens, 2002; Ma et al., 2008b; McLain and Martens, 2006). Since fungal biomass dominates in many ecosystems relative to bacterial biomass with a proportion of up to 96% in some cases (Ruzicka et al., 2000), its potential activity may be the dominant process resulting in N2O flux from soil (Ma et al., 2008b). Further ecological significance originates from the fact that the final product of fungal denitrification is N2O, as knowledge to date indicates that fungi generally lack N2O
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reductase (Kim et al., 2009; Shoun et al., 1992). The fungal denitrification pathway has long been considered as unique, but recent results indicate that at least NarGHI and NirK of the fungal denitrifying system which is located in the mitochondria resembles its bacterial counterparts and is involved in denitrification (Kim et al., 2010; Kobayashi and Shoun, 1995; Kobayashi et al., 1996; Uchimura et al., 2002). However, most of the denitrifier diversity in soils is not covered by cultured denitrifiers, and thus molecular analyses based on functional marker genes for denitrification as mentioned above are commonly applied. Due to the polyphyletic origin of denitrification, it is impossible to apply the commonly used 16S rRNA gene-based approach and hence, research has focused on targeting functional marker genes for the process. In the complete reduction of nitrate to dinitrogen, denitrification displays four respective dissimilatory reductases, that is, nitrate reductase, nitrite reductase, NO reductase, and N2O reductase, encoded by the genes narGH/napA, nirK/nirS, norB, and nosZ, respectively. Genes encoding the structurally distinct but functionally equivalent forms of copperand cytochrome cd1-containing nitrite reductase as well as N2O reductase were primary targets. Every denitrifier community survey, however, targeting an individual gene of the denitrification pathway will likely reflect distinctively composed communities but potentially also provide different insight into the functional diversity of the denitrifier community. Detection of denitrifiers via nitrite reductase genes requires analysis of two distinct genes, nirK and nirS, and sequences belonging to the recently defined and only distantly related class II of nirK genes are not even targeted by the commonly used primer sets (Ellis et al., 2007). This may change in the future because just recently class II nirK genes were published generated by newly developed primer sets (Bartossek et al., 2010; Green et al., 2010; Kim et al., 2010). Targeting nir genes also allows detecting nitrifiers and denitrifiers involved in N2O production via nitrifier denitrification and heterotrophic nitrification, respectively, as well as even genes of fungal denitrifiers. However, a specific detection of these different groups might be restricted to a few subgroups, as, for example, nirK genotypes of nitrifiers are dispersed over the nirK gene tree (Cantera and Stein, 2007; Casciotti and Ward, 2001, 2005; Garbeva et al., 2007). In summary, the analysis of denitrifier communities based on nitrite reductase genes will probably reflect the most complex picture of denitrifier community structure. Evidence is growing that nirK- and nirS-type denitrifiers respond differentially to environmental conditions (Hallin et al., 2009; Jones and Hallin, 2010; Liu et al., 2003). Such a niche differentiation of denitrifiers cannot be resolved by norB and nosZ, although both genes encode enzymes that are directly involved in N2O metabolism. Three different forms of NO reductase are known (cNorB, qNorB, and CuANorB) that
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differ in their electron donors (Suharti and de Vries, 2005; Zumft, 2005). For unknown reasons, the norB genes were never practically used as functional marker genes. Surprisingly, only one form of N2O reductase is known to date, and N2O reduction in prokaryotes constitutes a unique process that biologically forms N2. In contrast to nirK and nirS distribution among microbial species, phylogenies based on the nosZ gene generally show a high degree of congruency with 16S rRNA gene-based phylogenies, so that a recent horizontal gene transfer of nosZ seems unlikely (Dandie et al., 2007; Jones et al., 2008). This promoted the proposal of using an 80% similarity threshold for nosZ genes to define species-level operational taxonomic units for denitrifiers in environmental samples (Palmer et al., 2009). However, besides complete denitrification to N2, several truncated forms of the process exist. For instance, the process of N2O reduction can function as an autonomous process (Zumft, 1997). These denitrifiers are using only N2O but not nitrate, nitrite, or NO as electron acceptor (Shapovalova et al., 2008; Simon et al., 2004). However, pure culture studies as well as genome-sequencing data indicate that a relatively large fraction of denitrifiers (30%) lack N2O reductase and thus obligately produce N2O as end product ( Jones et al., 2008).
V. IMPORTANCE OF DIVERSITY, STRUCTURE, AND SIZE OF NITRIFIER AND DENITRIFIER COMMUNITIES FOR N2O PRODUCTION IN SOIL The control of N2O production by nitrification and denitrification is complex. The conceptual ‘‘hole-in-the-pipe’’ model gives a simplified view of the situation (Firestone and Davidson, 1989). In this model, the rate of nitrification or of denitrification is conceptualized as a pipe, while the relative ratio of N2O to the product produced or the substrate consumed is conceptualized as a hole. The relative ratio of N2O in turn is mainly a factor of the relative enzyme activities producing and consuming it, which are the activities of nitrite reductase plus NO reductase producing N2O and of N2O reductase consuming it. The activity of these enzymes controls the net production of N2O in denitrification and also in nitrification (nitrifier denitrification). It has been assumed the N2O production can be modeled by simply accounting for the proximate environmental controls of nitrification and denitrification, which are supply of the substrates (ammonia, nitrate, carbon substrates), O2, and soil pH (Robertson, 1989). The regulation of the activity of N2O-producing nitrifiers and denitrifiers by environmental factors has intensively been studied and implemented in process-based models. However, since ammonia oxidation and denitrification are achieved by not only one microbial species and since enzyme expression and regulation is likely
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different in different species, it is worthwhile considering how diversity, size, and structure of the nitrifier and denitrifier communities could affect N2O production rates.
A. Diversity of nitrifier communities Diversity of nitrifiers in soil can more or less be equated with species richness. A soil with high diversity would contain more different species of ammonia-oxidizing bacteria and/or archaea than a soil with low diversity. Diversity can, for example, be estimated by counting the number of amoA sequences that are dissimilar by a certain number of nucleotides or amino acids. For bacterial amoA, such dissimilarity is on the order of about 80% and 85%, respectively (Purkhold et al., 2000). Determination of the diversity of amoA does not require any phylogenetic affiliation of the recorded sequences, as the occurrence of amoA is restricted to ammonia oxidizers. Similar to the diversity of amoA, it is in principle possible to determine the diversity of other genes, for example, those coding for HAO, nitrite reductase, and NO reductase. Then, however, only those sequences that typically cluster with AOB can be considered for diversity estimates. Clearly, transcription and translation of such genes would be crucial for regulating the release of N2O. However, would it make a difference for N2O production whether the same gene would be transcribed of 1, 2, 10, or 50 different species, and if it would make a difference, would N2O production rates increase or decrease with diversity? Primary production of plants increased with the diversity in a meadow ecosystem (Tilman et al., 1996). The diversity of heterotrophic bacteria exhibited a unimodal relationship with productivity in heterogenous environments (Kassen et al., 2000). However, microbial diversity may be affected by many other environmental factors (Kassen and Rainey, 2004). Therefore, it is hard to predict how N2O production would respond to diversity. A study of the diversity of bacterial amoA genes across environmental gradients in a marine sediment found no single physical or chemical parameter explaining the diversity patterns (Francis et al., 2003). In terrestrial ecosystems, the relationship between amoA diversity and environmental parameters, N2O production in particular, has to our knowledge not been studied. Since AMO is the key enzyme of ammonia oxidation, while nitrite reductase is the key enzyme of denitrification, and both are required for N2O production in nitrifiers, it might also be interesting to consider the relative diversity of the genes coding for both enzymes. Perhaps, there are many ammonia oxidizer species that do not contain a nitrite reductase. Hence it might be possible that the number of amoA genes is high, but that of nitrifier nirK genes is low, meaning that there are more ammonia oxidizers potentially producing nitrite than ammonia oxidizers
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potentially reducing nitrite to N2O. The opposite case, however, should not exist. We presently do not know whether all of the uncultured ammonia oxidizers really have the genes required to reduce nitrite and potentially produce N2O. Finally, there is no guarantee that the relationship between the nitrifier communities and N2O production can be described by the general diversity of nitrifier species and their genes. Perhaps, we better know the explicit composition (structure) of the nitrifier community for being able to make a prediction with respect to N2O flux.
B. Structure of nitrifier communities Structure defines the percentage composition of a nitrifier community by different species. In contrast to diversity, it is not only species richness, but it also combines the relative abundance with the identity of the different species. Knowledge of identity would ideally allow conclusions with regard to life history and/or metabolism of these species. With such knowledge, it should be possible to correlate N2O production rates with specific patterns of community structure, in particular, if the structure not only of species but also of species-specific enzyme expression (e.g., mRNA of amoA and nirK) would be known. Hence, phylogenetic information is very helpful to define the structure of a community. Niche differentiation of sediment nitrifiers has been studied with respect to low ammonium concentrations and starvation (Bollmann et al., 2002) and O2 partial pressure and salinity (Bollmann and Laanbroek, 2002). Unfortunately, there is only rudimentary knowledge of the physiological characteristics of nitrifiers with respect to N2O production, as most of the ammonia oxidizers present in soil are not yet cultured. Nevertheless, several strains of Nitrosomonas and Nitrosospira have been assayed ( Jiang and Bakken, 1999; Shaw et al., 2006). They have all a remarkably constant ratio of N2O/nitrite when ammonia oxidation was not restricted ( Jiang and Bakken, 1999). However, ratios of N2O/nitrite increased dramatically in Nitrosomonas europaea and Nitrosospira multiformis, but not in other Nitrosospira strains, when ammonium oxidation was restricted ( Jiang and Bakken, 1999). Unfortunately, there is presently no culture of a soil-inhabiting ammonia-oxidizing archaeon, and also many of the different Nitrosospira species in soil are only known from their amoA sequences, but have not been isolated and phenotypically characterized. However, there are full genome sequences available for the bacteria N. europaea (Chain et al., 2003), Nm. eutropha (Stein et al., 2007), Nitrosococcus oceanus (Klotz et al., 2006), and Ns. multiformis (Norton et al., 2008). This knowledge could be used for theoretical analysis of potential N2O production in the different genera of AOB. Full genome sequence is also available for the AOA Nm. maritimus (Walker et al., 2010).
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However, since no gene-encoding NO reductase was found, AOA probably do not produce N2O and thus are not further considered in this review. Further, there is ample evidence that specific phylogenetic clusters of bacterial amoA are preferentially found under particular environmental conditions, that is, that the structure of soil AOB communities is related to environmental conditions, including ammonium concentration (Kowalchuk and Stephen, 2001; Kowalchuk et al., 2000), pH (de Boer and Kowalchuk, 2001), temperature (Avrahami and Conrad, 2005; Avrahami et al., 2003; Fierer et al., 2009), and soil moisture (Hastings et al., 2000). The soil AOB communities usually consist of different Nitrosospira species, while Nitrosomonas species are uncommon in soil. Nitrosomonas seems to be restricted to soil sites that have been improved by fertilization with large amounts of ammonium, compost, or waste water (Hastings et al., 1997; Kowalchuk et al., 1999; Oved et al., 2001; Webster et al., 2002). Thus, Nm. europaea and Nitrosospira cluster 3b were found to be particularly tolerant toward high ammonium concentrations (Webster et al., 2005). Similarly, several groups of soil AOB responded positively to simultaneous increase of atmospheric CO2, precipitation, temperature, and nitrogen deposition (Horz et al., 2004). However, the effect of soil AOB structure on N2O emission has hardly been investigated (Avrahami and Bohannan, 2009). The study by Avrahami and Bohannan (2009) indicated that manipulation of soil on the ecosystem level can result in complex interrelationships involving enhancement of particular groups of AOB. These groups may have direct or indirect effects on the potential nitrification activity and production of N2O as determined by multiple linear regression and path analysis (Fig. 2.3). However, more such studies are required to find out how N2O emission is affected by the community structure of AOB. Presently, nothing is known about the importance of AOA for N2O emission from soil.
C. Size of nitrifier communities Size of nitrifier communities in soil can be equated with number of microbial cells oxidizing ammonia. The maximum cell-specific rates of ammonia oxidation are typically on the order of 0.9–83 and 0.08–0.59 fmol cell 1 h 1 for AOB (Belser, 1979; Ward et al., 1989) and AOA (de la Torre et al., 2008; Ko¨nneke et al., 2005), respectively. The maximum cell-specific rates of N2O production are probably 2–3 orders of magnitude lower ( Jiang and Bakken, 1999). It is likely that rates of nitrifier-dependent N2O emission scale with the number of nitrifier cells, provided that supply with ammonia and O2 is sufficient for activity. In fact, if supply of energy substrate (i.e., ammonia and O2) is not limiting in soil and if nutrients (P, S, trace elements, pH) are also not limiting, one would expect
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NH3 F 0.07
G –0.46
A 0.78
H –0.90
SAC10
SAC9
SAC3a
D
C B
NitN2O
FIGURE 2.3 Path analysis of the hypothesized models of N2O emission rates due to nitrification in high fertilizer treatments of Californian meadow soil. SAC3a, SAC9, and SAC10 are the scaled abundance of amoA cluster 3a, 9, and 10, respectively. The absolute magnitude of the path coefficients indicates the strength of the causal path (adapted from Avrahami and Bohannan, 2009).
that nitrifier populations would proliferate until they reach a size, at which one of these substrates becomes limiting for growth. As long as the limiting substrate is ammonia or O2, the size of the nitrifier community should reflect that supply of these energy substrates and community size would not be an additional control of the rates of ammonium oxidation and N2O production. However, if a nutrient (e.g., P) is limiting proliferation, ammonia oxidation rates may be limited by the size of the nitrifier populations and N2O production would scale with size. Growth of nitrifiers in soil has frequently been observed. For example, it was found that the abundance of bacterial amoA gene increased when soil was supplemented with ammonium or manure ( Jia and Conrad, 2009; Schauss et al., 2009), or when soil was incubated at different temperatures (Saad and Conrad, 1993; Szukics et al., 2010). It was also found that soil AOB (Nitrosospira spp.) incorporated CO2 into their DNA indicating population growth ( Jia and Conrad, 2009). Unfortunately, there are only few studies that relate population size of ammonia oxidizers to N2O production. However, none of these studies found that N2O production rates correlated with the population size of autotrophic ammonia oxidizers ( Jumadi et al., 2005, 2008; Ma et al., 2008a; Siciliano et al., 2009). Rates of N2O emission increased with gross rates of nitrification in tropical rainforest soil, but the dominant populations of nitrifiers were heterotrophic rather than autotrophic ones (Kiese et al., 2008).
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D. Diversity of denitrifier communities and N2O emission Studies on higher organisms have indicated that diversity may play a significant role in controlling ecosystem processes and overall ecosystem functioning (Hector et al., 2005; Hooper and Vitousek, 1997), and studies on assembled bacterial communities agree with these findings (Bell et al., 2005; Wohl et al., 2004). That functionality of a system correlates with diversity is based on two principles, complementarity and positive selection, that is, diverse communities are believed to be functionally more efficient since their members occupy slightly different niches and they are more likely to contain species that exert a more pronounced effect on ecosystem functioning, respectively. With regard to denitrifiers, implications from the large phylogenetic and functional variability suggest that denitrifiers can occupy a large number of possible ecological niches resulting in a high level of functional diversity of this community in soils. However, to hypothesize that a more diverse soil denitrifier community will produce higher levels of N2O is a simplistic view. N2O is an intermediate of the process in most cultured denitrifier strains. Consequently, it may be more likely produced but also consumed by a more diverse community. For instance, cocultures of strains with complementary capabilities, that is, strains reducing nitrate to nitrite and others reducing nitrite to N2 interacted to completely denitrify but interactions in natural communities are of unknown complexity (Sorokin et al., 2003; van de Pas-Schoonen et al., 2005). First insights came from assembled model denitrifier communities of up to 16 species where species richness exerted a small and indirect effect on denitrification (Salles et al., 2009). However, potential denitrification was most significantly impacted by community niche, and community niche was positively correlated to diversity (Fig. 2.4). Diversity effects were also experimentally assessed via eroded diversity, that is, by reinoculating sterile soil with serially diluted soil suspensions (Wertz et al., 2006, 2007). Surprisingly, reduced denitrifier community richness did not cause impaired functioning, either due to sufficient species richness of the remaining denitrifier community to maintain functioning (functional redundancy) or due to loss of numerically and functionally less important species (Wertz et al., 2006). Moreover, the community responded to a disturbance (heating to 42 C for 24 h) only by a short-term reduction in denitrification activity after which function recovered (Wertz et al., 2007). These effects were unrelated to diversity although the level of diversity within functional groups is generally assumed being crucial for resistance and resilience (recovery from disturbances) of a system upon disturbances. At least some minimum number of species would be expected of being essential for ecosystem functioning, and this number may be larger for maintaining
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160
Denitrification (µgN-N2O ml–1 h–1)
140 120 100 80 60 40 20 0 0
0.1
0.2
0.3
All data points: R 2 = 0.42 P =0.0001
0.4 0.5 0.6 Community niche
0.7
0.8
0.9
1.0
Species richness 4 species 1 species 2 species 8 species All data points
FIGURE 2.4 Relationship between denitrifier community functioning (N2O production) and community niche. Community niche of individual denitrifiers was first defined according to monoculture ability to perform denitrification on six individual carbon sources. For assemblages, community niche was defined as the sum over all carbon sources of the maximal performance of a given species on an individual carbon source. The relative performance of an assemblage as shown here by dividing community niche of an assemblage by the maximum value observed for all communities. Different symbols correspond to different levels of species richness. The graph shows that communities with low richness but large community niche perform better than communities with high richness but small community niche (from Salles et al., 2009).
the stability of ecosystem processes in changing environments (Loreau et al., 2001). However, in this respect, denitrifiers may be a particular case among the various functional groups of microorganisms, as they are expected to show a high level of functional redundancy and diversity, for example, with respect to temperature optima, due to the wide range of organisms conducting the process (Wertz et al., 2007).
E. Structure of denitrifier communities and N2O emission Structure, that is, the presence of specific groups or differences within a functional group may be decisive for the stability of ecosystem functioning. This applies, in particular, for functional groups of microorganisms with a narrow physiology, and denitrifiers are an example for such a group due to the limited number of enzymes involved in denitrification
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(Schimel, 1995). In simple model communities, that is, in mixtures of two denitrifying species, the presence of specialized species resulted mostly in enhanced denitrification activity compared to the performance of each monoculture, but functioning was also impaired in some cases (Salles et al., 2009). Although low oxygen tension and the presence of a nitrogen oxide are the prevailing exogenous signals that induce the synthesis of the denitrification system (van Spanning et al., 2007), considerable variability exists among strains in their response to these signals and thus in N2O production (Bergaust et al., 2008; Ferguson, 1994; Ka et al., 1997; Miyahara et al., 2010; Saleh-Lakha et al., 2008; Zumft, 1997). N2O production in a denitrifier will likely also be influenced by other functional traits of the organisms apart from denitrification, for example, an obligate chemolithoautotrophic versus heterotrophic lifestyle. Hence, positive effects, where denitrification activity is enhanced in mixed communities, are likely due to occupation of different niches while negative interactions between members of the community may result from antibiotics or inhibitory compounds production (Salles et al., 2009). Denitrifiers are also variable in their ability to completely denitrify nitrate to N2. While many strains produce N2, others accumulate N2O as the end product because they lack N2O reductase (Hashimoto et al., 2009; Jones et al., 2008). Recently, the abundance of nosZ-containing organisms relative to the total soil microbial community or to denitrifiers which completely denitrify to N2 was suggested to significantly influence N2O metabolism (Cuhel et al., 2010; Morales et al., 2010; Philippot et al., 2009a). Indeed, potential denitrification and N2O emissions were positively correlated to the relative abundance of nosZ in a soil inoculated with serial dilutions of an obligate N2O-producing strain (Fig. 2.5), but this soil had a low N2O uptake capacity (Philippot et al., 2011). In contrast, numbers of nosZ-lacking denitrifiers were irrelevant to N2O metabolism in two soils with high N2O uptake capacity indicating that the indigenous nosZ-containing soil denitrifier community may act as a sink for N2O and can thus compensate for the higher N2O production rates. These findings agree with potential denitrification activity appearing uncoupled from community composition in many soils (Enwall et al., 2005; Hallin et al., 2009; Rich and Myrold, 2004). In some cases, the composition of only part of the community, for example, the nirS- but not nirK-type denitrifiers, was related to activity, suggesting that the assembly of communities responds to distinct environmental gradients (Enwall et al., 2010). Evidence is indeed growing that both types are ecologically nonredundant and occupy distinct ecological niches as community composition of soil nirK- and nirS-type denitrifiers responded differently to environmental factors (Enwall et al., 2010; Hallin et al., 2009; Jones and Hallin, 2010). For instance, along a short-term chronosequence, nirK-type denitrifier communities showed more habitat
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1.2
N2O/(N2O + N2)
1 0.8 0.6 0.4 0.2 0 NI
1/300 1/30 1/10 1/3 1 Dilution series of A. tumefaciens C58 inocula
FIGURE 2.5 N2O/(N2 þ N2O) ratio of three soils from Sweden in dependence of inoculation with increasing relative amounts of obligate N2O producing Agrobacterium tumefaciens C58. Increasing relative N2O production from Ekhaga soil (white) correlates with inoculum size, while the end product ratio from Lo¨vsta (gray) was unaffected by inoculum size and Ullera˚ker (black) showed a trend albeit nonsignificant toward increasing N2O/(N2 þ N2O) ratio with increasing inoculum size. NI, noninoculated soil; values are means SE (n ¼ 3) (from Philippot et al., 2010).
selectivity than nirS-type denitrifiers (Smith and Ogram, 2008), and they were more sensitive to long-term fertilization (Chen et al., 2010). Generally, apart from selective pressure of global regulators such as salinity, communities seem primarily shaped by habitat-specific factors ( Jones and Hallin, 2010), but how environmental factors influence community development is still poorly understood. However, since individual strains express significant differences in the induction of the process and activity, community structure would be strongly expected to result in ecosystem level differences in functioning (Schimel and Gulledge, 1998). Accordingly, under conditions where denitrification was not substrate-limited, intrinsic differences in denitrifier community composition were suggested of being responsible for differences in N2O metabolism in soils that were exposed to environmental stresses (Cavigelli and Robertson, 2000; Do¨rsch and Bakken, 2004; Holtan-Hartwig et al., 2000, 2002). Molecular analyses showed that structure and denitrification potential of soil denitrifier communities were indeed linked in some soils (Bremer et al., 2009; Rich et al., 2003), but these functional differences could not be attributed to specific genotypes. As far as currently known, a link of denitrification genotype to function is unlikely because the physiology of denitrification, that is, denitrification rate and end product ratios, is variable even in strains with very similar denitrification genotypes or in closely related organisms (Falk et al., 2010; Fesefeldt et al., 1998; Hashimoto et al., 2009).
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However, in an acidic fen, in particular, nosZ genotypes dominated habitat-specific denitrification and the respective low pH-adapted denitrifiers seemed responsible for complete denitrification and even consumption of atmospheric N2O (Palmer et al., 2010). Generally, assuming structure–function relationships based on the genetic potential for denitrification of a community confounds that denitrification in nature likely results from the activity of only parts of the denitrifier community. Accordingly, the active nirK-type denitrifier community in a potato cropping system represented only a subset of the overall community whose structure shifted relative to time and location (Wertz et al., 2009). Although the function of denitrifier communities may be linked much more tightly to these genotypes expressed under given environmental conditions, studies on how denitrification gene expression responds to changing environmental conditions in soils and how the structure of the active community is related to its function are still scarce. In a potato cropping system, changes in the expression of a few specific genotypes were related to variations in denitrification rates while a high basal level of denitrification was presumably supported by only a few ubiquitous and abundant denitrification genotypes that were invariantly expressed (Wertz et al., 2009). Likewise, the most diverse active denitrifier community exposed to freeze–thaw stress corresponded with the time point of the highest gene expression and N2O emission (Sharma et al., 2006).
F. Size of denitrifier communities and N2O emission Estimates of the size of denitrifiers communities based on cultivationdependent and -independent approaches can be as high as 5% of the total soil microbiota (Henry et al., 2004, 2006; Tiedje, 1988). Overall, denitrifiers represent a successful and abundant group of soil microorganisms as their abundance in soil is higher than that of other microbial groups involved in N-cycling such as nitrifiers and diazotrophs (Philippot et al., 2007; To¨we et al., 2010). Alterations in community size would be expected to result from actively denitrifying microorganisms able to generate energy for growth as long as nutrients are nonlimiting. Major proximal regulators of denitrification activity are the availability of nitrogen oxides and carbon under oxygen limitation (Tiedje, 1988), but only the concurrent availability of both substrates enhances denitrification process rates, for instance, in the rhizosphere (Philippot et al., 2007). In the field, cow slurry application increased N2O formation compared to soil amended with nitrate due to the surplus of organic matter (Christensen, 1985). Moreover, enhanced N2O production was accompanied by community growth and agreed with community size, suggesting that denitrification activity was not limited by resource supply. Potential denitrification activity and denitrifier community size were also correlated in a number
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of other studies (Hallin et al., 2009; Morales et al., 2010; Szukics et al., 2010; Throba¨ck et al., 2007), leading to the suggestion that community size may be used as a proxy to predict community functioning which, however, is probably too much of a generalization. As for structure–function relationships, there are also studies showing the contrary, namely that denitrification activity and N2O emissions were unrelated to the growth of the denitrifier community and to denitrification gene mRNA levels (Henderson et al., 2010). Size and function were also uncoupled in other studies (Dandie et al., 2008; Miller et al., 2008a,b; Morales et al., 2010). As outlined above, the absolute abundance of individual denitrification genes per se is probably not generally decisive for N2O production. Recent studies further suggest that even the size of the denitrification gene transcript pool cannot be used to ultimately predict production of gaseous denitrification products (Liu et al., 2010). Additional regulation at the posttranscriptional level seems to affect the translation, the assembly of N2O reductase, or enzyme activity directly which may exert a significant impact on N2O fluxes at the ecosystem level.
VI. CONCLUSION The importance to know whether N2O production in a particular soil is caused by nitrification or denitrification has been acknowledged since quite some time. Much effort has been spent to elaborate methods which allow the distinction between the N2O produced by either of these processes. The reason is the completely different catabolism with different regulation mechanisms, which affects both the process rate and the activity of nitrite reductase plus NO reductase relative to N2O reductase that determine the extent of N2O production. Whereas nitrification is an aerobic chemolithoautotrophic process, denitrification is an anaerobic organoheterotrophic one. Clearly, nitrification and denitrification respond to different proximal and distal regulators in soil (Robertson, 1989). While differences in the process are obviously of importance for N2O production, it was disputed whether microbial species matter (e.g., Schimel and Gulledge, 1998). Is it important for the N2O flux that nitrification or denitrification is brought about by a particular microbial species? In the present review, we have summarized knowledge on the effects that diversity, structure, and size of nitrifying and denitrifying soil microbial communities can have on rates of nitrification and denitrification and on N2O production. Although the literature is at least in part conflicting, it became quite clear that size and species composition of nitrifying and denitrifying microbial communities cannot be dismissed when assessing the environmental regulation of production and emission of N2O from
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soil. Hence, N2O emission cannot simply be modeled from knowledge of soil variables, and even knowledge on the relative contribution of nitrification and denitrification to N2O production is not sufficient. Diversity, structure, and size of the microbial communities apparently are also important. However, this conclusion is mainly based on circumstantial evidence and is presently only a qualitative one. It will be difficult to implement microbial community effects into explicit mathematical models of N2O production. For this purpose, we will need more and systematic studies, in which the effects of diversity, structure, and size of nitrifiers and denitrifiers on process rates and on N2O production are quantified. Even more comprehensive insights may be expected from exploring how the actively nitrifying and denitrifying soil microbial communities and their functioning are interrelated. However, an unambiguous concept of the interdependence of diversity, structure, size, and functioning of the microbial communities may be confounded by the fact that additional regulation on the level of gene transcription, translation, and enzyme activity is likely occurring. We believe that knowledge about the structure of the nitrifier and denitrifier communities will be of particular importance as a first step into the direction of a mechanistic theory of N2O production. This is because structure by definition encompasses information about phylogeny and functional genes of individual groups as well as information about their relative abundance. If knowledge on the structure of genotypes will eventually be expanded to that of transcripts and proteins, that is, the transcriptome and proteome of nitrifier and denitrifier communities in soil, the potential activity of individual groups of nitrifiers and denitrifiers will be accessible. Finally, however, it will also be necessary obtaining knowledge on molecular mechanisms of regulation by environmental cues to fully understand the mechanism of microbial N2O production in situ.
ACKNOWLEDGMENTS We are grateful to Annette Bollmann for critically reading this chapter and to the German Federal Ministry for Education and Research within the BIOLOG Biodiversity Program (01LC0021) for financial support.
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CHAPTER
3 Solar-Driven Hydrogen Production in Green Algae Steven J. Burgess,*,1 Bojan Tamburic,† Fessehaye Zemichael,† Klaus Hellgardt,† and Peter J. Nixon*
Contents
I. Introduction A. The hydrogen economy II. Biophotolytic H2 Production III. H2 Production in Green Algae A. Sources of reductant for hydrogen production in C. reinhardtii B. Sulfur depletion IV. Improving H2 Production in C. reinhardtii A. Choice of WT strain B. Improving the genetic tools C. Engineering an O2-tolerant hydrogenase D. Hydrogenase–ferredoxin interactions E. Dissipating the thylakoid proton gradient F. Targeting auxiliary electron transport pathways G. Targeting fermentative pathways H. Modifying the photosynthetic apparatus I. Creating anoxic conditions V. Engineering Challenges: Photobioreactors A. Overview B. Photobioreactors VI. Conclusions and Future Prospects References
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* Department of Life Sciences, Imperial College London, London, United Kingdom {
1
Department of Chemical Engineering and Chemical Technology, Imperial College London, London, United Kingdom Corresponding author: e-mail address:
[email protected]
Advances in Applied Microbiology, Volume 75 ISSN 0065-2164, DOI: 10.1016/B978-0-12-387046-9.00004-9
#
2011 Elsevier Inc. All rights reserved.
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Abstract
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The twin problems of energy security and global warming make hydrogen an attractive alternative to traditional fossil fuels with its combustion resulting only in the release of water vapor. Biological hydrogen production represents a renewable source of the gas and can be performed by a diverse range of microorganisms from strict anaerobic bacteria to eukaryotic green algae. Compared to conventional methods for generating H2, biological systems can operate at ambient temperatures and pressures without the need for rare metals and could potentially be coupled to a variety of biotechnological processes ranging from desalination and waste water treatment to pharmaceutical production. Photobiological hydrogen production by microalgae is particularly attractive as the main inputs for the process (water and solar energy) are plentiful. This chapter focuses on recent developments in solar-driven H2 production in green algae with emphasis on the model organism Chlamydomonas reinhardtii. We review the current methods used to achieve sustained H2 evolution and discuss possible approaches to improve H2 yields, including the optimization of culturing conditions, reducing light-harvesting antennae and targeting auxiliary electron transport and fermentative pathways that compete with the hydrogenase for reductant. Finally, industrial scale-up is discussed in the context of photobioreactor design and the future prospects of the field are considered within the broader context of a biorefinery concept.
I. INTRODUCTION Global energy consumption in 2008 was estimated at 16TW-years (5.1 1020 J) and is predicted to rise by 44% to 23TW-years (7.4 1020 J) by 2030 (IEA, 2010). Concomitantly, 60–80% cuts in total CO2 emissions relative to 1990 levels are thought to be required by 2050 to avoid the worst impacts of climate change (Stern, 2006). Therefore, bridging the energy gap without increasing CO2 emissions will require radical changes to the way energy is produced and consumed.
A. The hydrogen economy One possible solution is a carbon-free, ‘‘hydrogen economy’’ (Blanchette, 2008; Lattin and Utgikar, 2007; Marba´n and Valde´s-Solı´s, 2007; McDowall and Eames, 2007). However, unlike oil, gas, or coal, hydrogen is a secondary energy carrier and must therefore be generated from alternate sources. The majority of hydrogen is currently created from fossil fuels which would make any change in energy supply unsustainable (Bartels et al., 2010), but can also be generated from renewable sources
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including hydroelectric, wave, wind, solar, geothermal, biomass (Bartels et al., 2010), or biological approaches, which can be classified as dark fermentative (Das, 2009; Guo et al., 2010; Hallenbeck and Ghosh, 2010), photofermentative (Akkerman et al., 2002; Kars and Gu¨ndu¨z, 2010), or biophotolytic (Bothe et al., 2010; Ghirardi et al., 2009; Kruse et al., 2005b).
II. BIOPHOTOLYTIC H2 PRODUCTION By far the most abundant renewable energy supply available on earth is in the form of solar radiation, which totals 5 1024 J/annum (Miyamoto, 1997). This is 11,000 more than the total energy demand in 2008, making solar-driven H2 production processes an attractive prospect. Biophotolytic H2 production is the process whereby the light-driven oxidation of water by the photosystem II (PSII) complex of oxygenic photosynthesis Eq. (3.1) is coupled to the enzymatic reduction of protons to H2 Eq. (3.2) to give the net reaction shown in Eq. (3.3). 2H2 O ! 4Hþ þ O2 þ 4e
(3.1)
2Hþ þ 2e ! H2
(3.2)
2H2 O ! 2H2 þ O2
(3.3)
The formation of hydrogen gas is catalyzed in green algae by a ferredoxin-dependent [FeFe]-hydrogenase (Forestier et al., 2003; Happe and Kaminski, 2002), in unicellular cyanobacteria via a NADPHdependent [NiFe]-H2ase (Volbeda et al., 1995) and in nitrogen-fixing cyanobacteria in the absence of N2 via a nitrogenase (Benemann, 1996; Bothe et al., 2010; Nath and Das, 2004). The advantage of biophotolytic processes over conventional photovoltaic technologies includes absolving the need for expensive rare metals and the potential for coupling to a range of processes such salt or waste water treatment, carbon capture (Sheehan et al., 1998), human and animal food provision, production of health supplements, biopolymers, cosmetics, highvalue molecules (Spolaore et al., 2006; Stephens et al., 2010), or therapeutic proteins such as vaccines and antibodies (Rasala et al., 2010). Here, we highlight recent advances in understanding the molecular basis of hydrogen production in green algae, in particular, the model alga Chlamydomonas reinhardtii, and possible strategies to improve the yield both in terms of development of new strains and bioreactor design. Cyanobacterial H2 production has been reviewed elsewhere (Angermayr et al., 2009; Bothe et al., 2010; Lopes Pinto et al., 2002; Sakurai and Masukawa, 2007).
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III. H2 PRODUCTION IN GREEN ALGAE The presence of H2 metabolism in green algae has been known since the 1930s (Gaffron, 1939), although extensive screening of culture collections has since shown that it is not a universal trait (Ben-Amotz et al., 1975; Brand et al., 1989; Greenbaum et al., 1983; Healey, 1970; Meuser et al., 2009; Skja˚nes et al., 2008; Stuart and Gaffron, 1972; Timmins et al., 2009a). C. reinhardtii is currently the main model organism for studying algal H2 production (Hemschemeier et al., 2009). A typical C. reinhardtii cell is 10 mm in diameter and possesses a single large chloroplast in addition to a nucleus containing a 121 Mbp genome, multiple mitochondria, and two flagella for motility and mating (Merchant et al., 2007). Strains exist as either mating type positive (mtþ) or mating type minus (mt), which together are capable of sexual reproduction, allowing for classic genetic analysis. Additionally fully sequenced and transformable mitochondrial, chloroplast, and nuclear genomes (Boynton et al., 1988; Maul et al., 2002; Mayfield and Kindle, 1990; Merchant et al., 2007; Randolph-Anderson et al., 1993; Vahrenholz et al., 1993), microarrays (Gonzalez-Ballester et al., 2010; Nguyen et al., 2008), and a large collection of expressed sequence tags (Asamizu et al., 1999) and mutants are available to facilitate genetic analysis.
A. Sources of reductant for hydrogen production in C. reinhardtii 1. PSII-dependent pathways In this process, PSII catalyzes the photolysis of water, producing O2 and releasing electrons into the photosynthetic electron transport (PET) chain, ultimately generating reduced ferredoxin that can be used by hydrogenase to reduce protons to hydrogen (Fig. 3.1; Greenbaum et al., 1983). This process offers the maximum theoretical efficiency of converting solar to H2 energy (Kruse et al., 2005a), but because [FeFe]-hydrogenases are irreversibly inactivated by O2 (Stripp et al., 2009b), as soon as cells begin to produce oxygen at high rates, hydrogen evolution rapidly stops (Ghirardi et al., 1997), meaning it is not currently a viable process under standard conditions.
2. PSII-independent pathways Starch reserves accumulated through photosynthetic activity can undergo autofermentation to produce NADH and pyruvate, both of which can be oxidized to provide electrons for hydrogen production. In the case of pyruvate, a chloroplast-located pyruvate:ferredoxin oxidoreductase (PFOR) is likely to be involved in reducing ferredoxin in the dark, and
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Starch Cytoplasm
2ATP
Glycolysis
2ADP
14H+ 2H+
H2
HYD NAD+
NADH Stroma
8H+ e-
NDA2 PSII
Thylakoid
e-
PQ
e-
e-
Lumen
2H2O
O2 + 4H+
PSI
Cytb6f
8H+
PC
3ATP
3ADP + 3Pi PYR
Fd PFOR e-
AcCoA CO2
ATPase
2ATP 2ATP NADH PYR
e14H+
FIGURE 3.1 Schematic representation of potential sources of reductant for hydrogen production during (1) transient illumination of dark-adapted cultures, (2) dark fermentation, and (3) sulfur depletion. Abbreviations: Cytb6f, cytochrome b6f complex; Fd, ferredoxin; HYD, [FeFe]-hydrogenase; NDA2, type II NADH dehydrogenase; PFOR, pyruvate:ferredoxin oxidoreductase; PSI, photosystem I; PSII, photosystem II; PC, plastocyanin; PQ, plastoquinone. For simplicity, the Q cycle at the Cytb6f complex is not shown.
possibly the light, with the concomitant production of CO2 and acetylCoA (Atteia et al., 2006; Mus et al., 2007; Fig. 3.1). Oxidation of NAD(P)H occurs in the light via NDA2, a thylakoid-associated type II NADH dehydrogenase (Desplats et al., 2008; Jans et al., 2008) which feeds electrons into the PET at the point of the plastoquinone (PQ) pool (Fig. 3.1).
B. Sulfur depletion The most commonly used protocol for achieving sustained H2 evolution in the light involves starving cultures of sulfur (Melis et al., 2000), which can be described as passing through five phases: aerobic, oxygen consumption, anaerobic, hydrogen production, and termination (Kosourov et al., 2002). Aerobic and O2 consumption phases last between 20 and 30 h (Kosourov et al., 2002) but are strain (Chochois et al., 2009, 2010) and condition dependent (Kosourov et al., 2002). Initially, cells continue to evolve oxygen (Ghirardi et al., 2000; Kosourov et al., 2002; Melis et al., 2000) and accumulate energy reserves in the form of starch (Timmins et al., 2009b; Zhang et al., 2002) and triacylglycerides (TAGs; Timmins et al., 2009b), which is a well-characterized response to nutrient limitation
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and can also be seen during nitrogen starvation (Ball et al., 1990) and salt stress (Siaut et al., 2011). These changes are followed by the rapid degradation of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) suggesting a decline in CO2 fixation rates (Zhang and Melis, 2002; Zhang et al., 2002) and cultures enter a phase of oxygen consumption, as by depriving cells of sulfur, synthesis of the PSII reaction center protein D1 is impaired, reducing the cell’s ability to repair PSII (Nixon et al., 2010; Wykoff et al., 1998). Taken together, the lack of Calvin cycle activity leading to the overreduction of PQ (Antal et al., 2003), and impaired D1 turnover, causes a decrease in the number of active PSII centers to about 5–10% of normal levels (Zhang et al., 2002), as determined by chlorophyll fluorescence measurements (Antal et al., 2003; Zhang et al., 2002) and the rate of photosynthetic oxygen evolution (Wykoff et al., 1998). Initially, respiratory activity in the mitochondrion remains largely unimpaired (Zhang et al., 2002) causing the rate of photosynthesis to drop below respiration and sealed cultures to go anaerobic (Melis et al., 2000). These changes are accompanied by a decrease in photorespiratory and TCA cycle intermediates (Timmins et al., 2009b), as O2 and CO2 become limiting, and a decline in chlorophyll levels as cells seek to limit photodamage (Melis et al., 2000; Zhang and Melis, 2002). A brief lag period ensues where cells consume dissolved oxygen and induce hydrogenase expression, followed by hydrogen evolution which lasts several days (Melis et al., 2000). In the absence of CO2 fixation, H2 production acts to allow continued PET for the generation of ATP by photophosphorylation albeit at a reduced rate (Melis, 2007). Additionally, limited O2 availability causes reduced rates of oxidative phosphorylation in the mitochondria; resultantly, glycolysis and anaerobic fermentation also become major pathways for ATP formation (Timmins et al., 2009b). This suggestion is supported by the decrease in starch concentration during the hydrogen production phase (Zhang et al., 2002) and the excretion of formate (Hemschemeier et al., 2008b; Timmins et al., 2009b; Tsygankov et al., 2002) and ethanol (Hemschemeier et al., 2008b; Kosourov et al., 2003; Timmins et al., 2009b) along with minor amounts of succinate and amino acids with the exception of glutamate (Timmins et al., 2009b) which allows for the reoxidation of NADH formed by glycolysis. The amino acids excreted are found to originate at least partly from de novo synthesis (Timmins et al., 2009b), which coupled to the uptake of ammonium via the glutamine synthetase/glutamate synthase cycle also oxidizes one molecule of NADPH. In the final period, hydrogen production gradually declines to a stop despite the continuing presence of energy reserves in the form of starch, TAGs, and acetate, which could be due to the toxic nature of the accumulated metabolites or as a result of the long-term consequences of sulfur depletion (Timmins et al., 2009b).
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1. Contribution of PSII to H2 production during sulfur starvation The precise contribution of the PSII-dependent and -independent pathways to hydrogen production is still unclear and a range of values have been proposed (Antal et al., 2009; Chochois et al., 2009; Kosourov et al., 2003) with the most recent suggestion of up to 90% of electrons coming from residual water splitting (Chochois et al., 2009, 2010), but this value is likely to be strain and condition dependent, which could provide an explanation for the differences reported (Chochois et al., 2009). The importance of PSII activity for the process was first discerned by the inability of mutants lacking PSII to evolve H2 (Hemschemeier et al., 2008a; Zhang et al., 2002). Similarly, addition of the PSII inhibitor 3-(3,4dichlorophenyl)-1,1-dimethylurea (DCMU) at the beginning of sulfur depletion led to an inhibition of H2 evolution (Hemschemeier et al., 2008a). However, if PSII inhibition was delayed until after the aerobic and oxygen consumption phases, hydrogen evolution was observed, although at a vastly reduced level ( 10% uninhibited; Chochois et al., 2009) indicating that, as with light-induced hydrogen production, there is a PSII-independent source of reductant for the hydrogenase. This indirect pathway is dependent on PSII activity during the initial stages of sulfur depletion, suggesting it is based on degradation of the energy reserves formed in the aerobic phase (Chochois et al., 2009; Hemschemeier et al., 2008a). In addition, the indirect pathway was found to be absent in starchdeficient mutants, indicating carbohydrate reserves are the sole source of reductant for PSII-independent H2 production and not protein or TAGs (Hemschemeier et al., 2008a). Further evidence for this theory came from mutants affected in starch catabolism, which showed a general decrease in the amount of PSII-independent H2 production, and those with a reduced rate of starch degradation which showed delayed H2 evolution (Chochois et al., 2010).
2. Role of starch and acetate during H2 production NADH produced from starch breakdown plays a dual role in hydrogen production: it is oxidized via the mitochondrial respiratory chain, to keep oxygen levels sufficiently low to allow expression of active hydrogenase for the PSII-dependent pathway (Melis, 2007), and it feeds electrons into the PET chain in the indirect pathway (Bamberger et al., 1982; Melis, 2007). However, experiments using the ADP-glucose pyrophosphorylase deficient mutant, sta6, which is unable to accumulate starch, found wild-type levels of H2 evolution during sulfur depletion (Chochois et al., 2009). This result suggests that starch is dispensable for PSII-dependent hydrogen production and can be explained by the fact that, unlike wt cultures, sta6 consumes acetate during the hydrogen production phase, which could act as a replacement for carbohydrate in maintaining respiration (Chochois et al., 2009).
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Similarly, although acetate is usually included in the growth medium (Melis et al., 2000), it is dispensable for H2 production when cultures are grown under a defined light regime, with CO2 bubbling to promote starch accumulation (Kosourov et al., 2007; Tolstygina et al., 2009; Tsygankov et al., 2006). This suggests the role of starch or acetate in the maintenance of respiration is interchangeable, although CO2 bubbling and acetate are required for maximum H2 yields (Kosourov et al., 2007).
IV. IMPROVING H2 PRODUCTION IN C. REINHARDTII It has been calculated that if coupled to the production of high-value products, biophotolytic energy conversion efficiencies of around 5% will be required for economic viability (Kruse et al., 2005b). Currently achievable light to hydrogen conversion efficiencies, as demonstrated in a laboratory environment, are in the region of 1% postsulfur deprivation for C. reinhardtii mutant stm6 (Kruse et al., 2005b). Therefore, as with dark and photofermentative processes (Hallenbeck and Ghosh, 2010), further increases in efficiency are still required.
A. Choice of WT strain Different laboratory strains of C. reinhardtii display a great variation in rates of hydrogen production; thus it is important to choose the right strain to work with. Long-term maintenance in culture collections has presumably allowed for the accumulation of mutations—with strains supposedly of the same genotype from different laboratories displaying markedly different phenotypes (ranging from 55 to 95 ml/l H2 reported for different CC-124 isolates; Chochois et al., 2010). The precise reasons why strains differ in their ability to produce hydrogen are unknown, and careful genetic analysis may be a means of identifying mutations important for the process. The choice of strain for study is important not only for H2 production but will also determine the ease of genetic analysis. The best H2 production rates have been reported using derivatives of the 137c strain (CC-124, CC-125), which possess a cell wall that can be transformed by biolistic bombardment (Debuchy et al., 1989; Kindle et al., 1989) or electroporation, but transformation efficiencies are low (Brown et al., 1991). Alternatively, wild-type strains treated with autolysin, which degrades the cell wall, or cell-wall-deficient strains of C. reinhardtii (cw) can be easily transformed by glass beads (Kindle and Sodeinde, 1994) or electroporation (Brown et al., 1991; Shimogawara et al., 1998).
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B. Improving the genetic tools Although C. reinhardtii possesses many genetic advantages, the lack of effective, reproducible methods for generating targeted mutants via homologous recombination (HR; Zorin et al., 2009) makes the construction of knockout mutants time consuming. Reverse genetic analysis can be performed through isolation of knockout mutants by PCR screening random mutagenesis libraries created by marker gene insertion (Pootakham et al., 2010). However, this requires the labor-intensive screening and maintenance of 50,000 transformants to provide complete genome coverage. Alternatives include the creation of knockdown mutants by RNA interference ( Jans et al., 2008; Mussgnug et al., 2007; Petroutsos et al., 2009; Rohr et al., 2004) or artificial microRNA technology (Molnar et al., 2009; Schmollinger et al., 2010; Zhao et al., 2009), but the stability of the knockdown of expression needs to be carefully evaluated. Additionally, some approaches to improving H2 production might require the induction or repression of particular genes at specific stages of growth (see Section IV.E). A number of inducible promoter systems are currently available (Kucho et al., 1999; Ohresser et al., 1997; Quinn et al., 2003; Schroda et al., 2000), but each has drawbacks which could be detrimental for use in H2 production systems, variously including lack of tight control (Quinn et al., 1998) and use causing physiological stress (Schroda et al., 2000) or repression by ammonium (Ohresser et al., 1997)—which is required for optimum H2 production. Alternative possibilities include utilizing the potential of other controllable expression systems such as riboswitches (Croft et al., 2007) or promoters that are switched on by anoxia (Chen et al., 2010; Nguyen et al., 2008; Terashima et al., 2010).
C. Engineering an O2-tolerant hydrogenase As previously stated, maximum efficiencies are achieved through direct photolysis; therefore, the ultimate goal is to engineer an O2-tolerant hydrogenase. There are a few known examples found in nature of the [NiFe] type (Burgdorf et al., 2005), but they tend to favor H2 uptake (Maroti et al., 2009). C. reinhardtii contains two highly similar, differentially regulated, oxygen-sensitive [FeFe]-hydrogenases, HYDA1 and HYDA2 (Forestier et al., 2003), of which only HYDA1 is thought to play a role in H2 production (Godman et al., 2010). The assembly and proper functioning of [FeFe]-hydrogenases is an O2-sensitive process dependent on accessory factors HydE, HydF, and HydG (Nicolet et al., 2010; Posewitz et al., 2004). The active site H-cluster is a [4Fe–4S] cubane linked to a 2Fe subcluster via cysteine (Adams, 1990; Peters, 1999). The mechanism of assembly is not fully characterized, but HydE and HydG belong
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to the radical SAM class of enzymes involved in radical based catalysis (Sofia et al., 2001) and are proposed to play a role in H-cluster synthesis (Rubach et al., 2005) while HydF possess GTPase activity (Brazzolotto et al., 2006) and is thought to act as a scaffold for assembly (McGlynn et al., 2008). Three main approaches can be taken to modify the O2 tolerance of the enzyme, but any modified hydrogenase would also require a means of assembly in the presence of oxygen: (1) Random mutagenesis. The C. reinhardtii [FeFe]-hydrogenase can be expressed heterologously in E. coli using the Clostridium acetobutylicum hydrogenase assembly factors HydE, HydF, and HydG (King et al., 2006). In principle, such a system is amenable to a highthroughput mutagenesis screen, although ideally the species-specific ferredoxin donor should be used in assays as the ability for ferredoxin–hydrogenase electron transfer can vary widely between different isoforms ( Jacobs et al., 2009). Examples of research on the algal hydrogenase include random gene shuffling (Nagy et al., 2007) and directed evolution (Stapleton and Swartz, 2010), the latter of which managed to identify a version of C. reinhardtii HydA1 with a fourfold increase in catalytic activity but none yet with improved O2 tolerance. (2) Intelligent design. In contrast to high-throughput random mutagenesis approaches, it may be possible to use existing structural and mechanistic information to mutate specific amino acid residues within the hydrogenase structure to improve catalytic properties. For example, it has been suggested that narrowing gas channels leading to the active site (Posewitz et al., 2009) or potentially modifying the protein environment around the H-cluster itself (Stripp et al., 2009b) may be means of preventing inhibition by O2. There are now a number of X-ray crystal structures of [FeFe]-hydrogenases (Cohen et al., 2005; Peters et al., 1998; Shima et al., 2008) including the partially assembled C. reinhardtii enzyme (Mulder et al., 2010). A homology model of the C. reinhardtii HYDA2 has been constructed (Chang et al., 2007) and HYDA1 has been isolated and characterized by electron paramagnetic resonance (EPR) spectroscopy (Kamp et al., 2008) as well as by X-ray absorption spectroscopy (XAS) which has revealed the structure of the active site H-cluster (Stripp et al., 2009a), and the means by which O2 inhibition occurs (Stripp et al., 2009b). However, these data have not yet been successfully applied to making beneficial mutations to reduce the O2 sensitivity of the algal hydrogenase. (3) Bioprospecting. The vast diversity of hydrogenase sequences remains underrepresented in databases (Beer et al., 2009), and there may yet be a suitable sequence present in nature. The establishment of metagenomics has allowed for identification of novel hydrogenases from the
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environment including analysis of termite gut microbiota (Warnecke et al., 2007) and through the Craig Venter Institute’s Global Ocean Sequencing program (Maroti et al., 2009; Rusch et al., 2007), but as yet the oxygen tolerance of these enzymes is unknown.
D. Hydrogenase–ferredoxin interactions Ferredoxins play a central role in allocating high energy electrons in the chloroplast and are involved in distributing electrons to CO2 fixation (Kitayama et al., 1994), nitrite (Ferna´ndez et al., 1989; Hirasawa et al., 2009) and sulfite reduction (Gonzalez-Ballester et al., 2009), glutamate synthesis (Garcı´a-Sa´nchez et al., 2000), cyclic electron flow (CEF; Finazzi et al., 2002; Rochaix, 2011), and reduction of thioredoxins for regulation of biosynthetic pathways (Lemaire et al., 2003) in addition to the role in hydrogen production. C. reinhardtii encodes six differentially regulated [Fe2S2] ferredoxins: PetF (the dominant Fd reduced in the light reactions) and Fdx2–Fdx5 (Mus et al., 2007; Terauchi et al., 2009; Winkler et al., 2010) of which Fdx5 was found to be induced by anoxia as well as copper stress ( Jacobs et al., 2009; Lambertz et al., 2010; Mus et al., 2007; Terauchi et al., 2009) but which is unable to donate electrons to HYDA1 ( Jacobs et al., 2009). PetF is thought likely to be the substrate for H2 production in vivo, although the Fd specificity of the hydrogenases, HydA1 and HydA2, has yet to be fully evaluated (Happe and Naber, 1993; Lambertz et al., 2010). In principle, hydrogen production could be enhanced by increasing the specificity of electron transfer from the ferredoxin to the hydrogenase over other competing pathways. Progress has been made in identifying potentially important residues involved in the interaction between the Fd and the hydrogenase (Chang et al., 2007; Long et al., 2008; Winkler et al., 2009, 2010) which opens up the possibility of manipulating the affinity of binding and kinetics of electron transfer.
E. Dissipating the thylakoid proton gradient Disrupting the transthylakoid proton gradient (DpH) through heterologous expression of a proton channel in the thylakoid membrane is another potential way of increasing supply of reductant to the hydrogenase. DpH is thought to limit H2 production by causing a decrease in proton concentration in the stroma and a reduction in electron transport at the point of the Cytb6f complex (Antal et al., 2009; Kramer and Crofts, 1993). The proton gradient uncoupler carbonylcyanide-p-trifluoromethoxyphenylhydrazone (FCCP) does indeed stimulate H2 evolution (Antal et al., 2009; Cournac et al., 2002; Lee and Greenbaum, 2003); however, addition
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prior to anaerobic induction abolished H2ase activity in vivo (Chochois et al., 2009), suggesting that the proton gradient is also important for hydrogenase expression. Therefore, although a potential means of increasing yields, any attempts at decoupling electron transport from DpH, such as integration of a proton channel in the thylakoid membrane (Lee and Greenbaum, 2003), will likely require an inducible element to allow for hydrogenase expression.
F. Targeting auxiliary electron transport pathways Switching off auxiliary electron transport pathways offers another way of increasing the supply of electrons to the hydrogenase, as they dissipate excess reducing pressure in competition with H2 production. Pathways include nonphotochemical reduction of electron carriers in a process known as chlororespiration, the oxidation of PQ or photosystem I (PSI) electron acceptors by O2 in a process known as the Mehler reaction and CEF around PSI (Fig. 3.2; Peltier et al., 2010; Rochaix, 2011). The precise effect of the Mehler reaction or chlororespiration on H2 production is Mito-respiration
FTR GOGAT
CEF
FNR
PGRL1/ PGR5
NAD(P)H NAD+ O 2
Stroma
NDA2
Thylakoid
PSII
e-
PQ
H2O 8H+ e-
e-
e-
Lumen 2H2O
O2
+ 4H+
PSI
Cytb6f
8H+
PC
NII1
?
14H+ 3ATP
3ADP + 3Pi 2H+
PTOX e-
SIR
PetF HYD e-
H2
Fdx2 Fdx5
ATPase
Fermentation products
e14H+
FIGURE 3.2 Schematic representation of processes that potentially compete with the hydrogenase for reductant. Abbreviations: Cytb6f, cytochrome b6f complex; Fd, ferredoxin; FNR, ferredoxin-NADPþ reductase; FTR, ferredoxin–thioredoxin reductase; GOGAT, ferredoxin-dependent glutamate reductase; HYD, [FeFe]-hydrogenase; NDH-2, type II NADH dehydrogenase; NII2, ferredoxin-dependent nitrate reductase; PFOR, pyruvate:ferredoxin oxidoreductase; PGR5, proton gradient regulator protein 5; PGRL1, proton gradient regulator-like protein 1; PSI, photosystem I; PSII, photosystem II; PC, plastocyanin; PQ, plastoquinone; PTOX, plastid or plastoquinol terminal oxidase; SIR, ferredoxin-dependent sulfate reductase. Note: during linear electron transport, eight protons are pumped per four electrons coming from the oxidation of one molecule of H2O. However, the operation of both cyclic and linear electron flow will increase the relative number of protons pumped at Cytb6f complex (figure based on Winkler et al., 2010).
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unclear, but several studies have indicated that competition for reductant occurs between CEF and H2 production (Antal et al., 2009).
1. Cyclic electron flow For optimal photosynthetic activity photosynthetic organisms must balance the amount of light energy absorbed by the PSII and PSI reaction centers through transfer of mobile light-harvesting complexes in a process known as state transitions (Lemeille and Rochaix, 2010). In C. reinhardtii, this process allows the switch between linear and CEF (Lemeille and Rochaix, 2010). CEF potentially occurs by two pathways in C. reinhardtii which can be distinguished by their sensitivity to antimycin A (Ravenel et al., 1994). a. Antimycin A-sensitive pathway. This involves the reduction of PQ using electrons from ferredoxin. The precise mechanism is unclear (Rochaix, 2011) but is mediated by a PSI-LHCI-LHCII-Cytb6f-FNR-PGRL1 supercomplex which has been implicated in CEF in C. reinhardtii (Iwai et al., 2010). b. Antimycin A-insensitive pathway. The second pathway is believed to be controlled by the activity of a type II NAD(P)H dehydrogenase, reducing PQ using NAD(P)H generated via the ferredoxin-dependent NADPþ reductase (Rumeau et al., 2007; Fig. 3.2). The efficacy of disrupting CEF as a means of increasing H2 yields was demonstrated in short-term inhibitor studies using antimycin A, which resulted in a doubling of H2 production as a result of antimycin A’s activity in blocking CEF (Antal et al., 2009). It is possible to screen for mutants affected in CEF through chlorophyll fluorescence video imaging, which has allowed the identification of mutants unable to switch between linear and cyclic electron transport (Depe`ge et al., 2003). This screen also led to the discovery a high hydrogen producing strain deficient in the mitochondrial transcription factor moc1 known as stm6 (state transition mutant 6; Kruse et al., 2005a; Table 3.1). stm6 is locked permanently in ‘‘state 1’’ meaning in the process of linear electron transport, thereby inhibiting CEF which was cited as one of the major factors contributing to the high hydrogen phenotype. stm6 is also able to accumulate more starch and has a higher respiratory rate due to an upregulated alternative oxidase (AOX) which is beneficial for H2 production because of more favorable rates of oxygen consumption (Kruse et al., 2005a). For targeted gene knockout, potential candidates in the antimycinsensitive pathway include protein gradient regulator protein 5 (PGR5; Munekage et al., 2002; Nandha et al., 2007) and PGRL1 (DalCorso et al., 2008). Knockout of these genes will also likely have the dual effect of disrupting DpH formation to help H2 evolution. However, identifying the
TABLE 3.1 Target gene
Summary of published mutations affecting H2 production in C. reinhardtii Effect on H2 production relative to parental strain
Function
Type of mutation
Mode of action
psbA
D1 subunit of PSII complex involved in water oxidation
Double point mutation L159I-N230Y
psbA
D1 subunit of PSII complex involved in water oxidation
Amino acid deletion Residues 239–240
hydEF
[FeFe]-hydrogenase assembly factor Light-harvesting complex
Knockout
15 increase Conditions: light, TAP-S Chl content: 12 mg/mla Total yield: 504 ml/l Maximum rate: 5.77 ml/l/h Duration: 285 h Light intensity: 70 mmol/m2/s Increase in photoinhibition 12–18 increase Conditions: light, TAP-S Prolonged H2 evolution phase Chl content: 12 mg/mla Reduced chlorophyll content Total yield: 475 ml/l Maximum rate: 2.6 ml/l/h Higher respiration-toDuration: 183 h photosynthesis ratio Light intensity: 70 mmol/m2/s Increased carbohydrate accumulation Higher synthesis of xanthophyll-cycle pigments Inhibition of hydrogenase No detectable H2 production synthesis 78% reduction in Not tested chlorophyll content
LHC
RNAi
Decrease in chlorophyll content Prolonged H2 production Higher respiration rate Higher photosynthetic capacity relative to quantum yield of PSII
Reference Torzillo et al. (2009)
Faraloni and Torzillo (2010)
Posewitz et al. (2004) Mussgnug et al. (2007)
moc1
Mitochondrial transcription factor
moc1 þ hup1
Mitochondrial Knockout þ transcription factor transgenic with hexose uptake expression protein
nab1
LHC RNA-binding protein Pyruvate decarboxylase Pyruvate formate lyase Pyruvate formate lyase
pdc3 pfl1 pfl1
pgrl1
pgrl1
Proton gradient regulator-like protein 1 Proton gradient regulator-like protein 1
Knockout
RNAi amiRNA amiRNA Knockout
5 increase Conditions: light, TAP-S Chl content: 25–30 mg/Chl/ml Total yield: 540 ml/l Maximum rate: 4 ml/ l/h Duration: 336 h Light intensity: 100 mmol/m2/s In addition to moc1 mutant 7.5 increase phenotype allows glucose Conditions: TAP-S þ 1 mM transport for use in H2 glucose production Data given as % of Kruse et al. (2005a) Decrease in antennae size Not tested 10–17% Altered fermentation Not tested Decrease in CEF, increased starch accumulation, prolonged H2 evolution phase
Decrease in formic acid production Decrease in formic acid production
RNAi
Potential alteration to CEF and DpH
amiRNAi
Potential alteration to CEF and DpH
No increase Conditions: TAP-S 1.5 increase Conditions: dark N2 purged 55% decrease Conditions: light N2 purged Not tested
Greater than twofold increase Conditions: TAP-S
Kruse et al. (2005a)
Doebbe et al. (2007)
Beckmann et al. (2009) Burgess and Nixon (unpublished) Burgess and Nixon (unpublished) Philipps et al. (2011)
Petroutsos et al. (2009) Burgess and Nixon (unpublished)
(continued)
TABLE 3.1 Target gene
a
Summary of published mutations affecting H2 production in C. reinhardtii (continued) Function
Effect on H2 production relative to parental strain
Type of mutation
Mode of action
hemH, lba Ferreochelatase (hemH) Leghemoglobin (lba)
Transgene expression
sulP
Chloroplast localized sulfate permease
RNAi
tla1
Control of lightharvesting antennae size
Knockout
Lower internal O2 levels due 4.5 increase Wu et al. (2010, to expression of soya bean Conditions: light, 2011) O2 scavenging proteins TAP-S (sparged N2 to induce anaerobiosis) Chl content: 12.5 mg/ml Total yield: 55 ml/l Maximum rate: 2.0 ml/ mgChl/h Light intensity: 50 mmol/m2/s Chen et al. (2005) Knockdown of chloroplast H2 production in sulfur-replete media, overall yields not given sulfate transporter. Triggering sulfur starvation response in replete media 48% decrease in 6 increase Berberoglu et al. chlorophyll content Conditions: light, (2008), Kosourov immobilized TAP-S et al. (2011), Maximum rate: 8.5 Mitra and Melis increase (2010), Polle et al. Duration: 250 h (2003) Light intensity: 350 mmol/m2/s
Similar number of cells was used in H2 measurements as in Kruse et al. (2005a).
Reference
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precise enzyme(s) responsible for the antimycin-insensitive CEF pathway in C. reinhardtii has been more difficult as the genome encodes six type II NADH dehydrogenases, including a plant type NDB (NDA2), a yeast type NDE (NDA3), one that grouped with plant type NDAs (NDA1), and three cyanobacterial type NDCs (NDA5, NDA6, and NDA7; Desplats et al., 2008; Jans et al., 2008). Arabidopsis also has multiple type II NADH dehydrogenases with differing physiological roles (Michalecka et al., 2003); six out of seven are targeted exclusively to the mitochondria (Elhafez et al., 2006; Michalecka et al., 2003), highlighting the importance of identifying the correct isoform or isoforms for study. In C. reinhardtii, RNA hybridization only detected transcripts for NDA2 and NDA6 under mixotrophic conditions and further analysis revealed NDA2 was located in the chloroplast. An RNAi study knocked down NDA2 showing a reduction in CEF and reduced ability for state II transition when oxidative phosphorylation was inhibited ( Jans et al., 2008). Despite this, the NDA2 knockdown resulted in an 50% decrease in H2 production under sulfur depletion ( Jans et al., 2008) which was proposed to occur as NDA2 may be acting as the point of entry for reductant from the breakdown of starch reserves, and therefore NDA2 overexpression may actually be a means of increasing the supply of reductant for H2 production ( Jans et al., 2008). It is unclear why NDA2 knockdown resulted in such a dramatic decrease in overall H2 yields when the indirect pathway is proposed only to contribute 10% of reductant to H2 production, but could perhaps be attributed to the knockdown of additional targets by siRNAs generated from the inverted repeated RNAi construct ( Jans et al., 2008).
G. Targeting fermentative pathways Switching off fermentative pathways is also a potential method of increasing flow of reductant to the hydrogenase (Doebbe et al., 2010; Mus et al., 2007; Timmins et al., 2009b). This is based on the assumption that eliminating sinks for NADH could potentially increase the amount of reductant fed into the PET by a type II NADH dehydrogenase, and redirecting carbon flux to a PFOR may be a means of increasing the amount of reduced ferredoxin available to the hydrogenase (Fig. 3.3). Key enzymes for targeting are thought to include pyruvate formate lyase (PFL1), bifunctional acetaldehyde/alcohol dehydrogenase (ADH1), and pyruvate decarboxylase (PDC; Mus et al., 2007). This is based on a working model of fermentative metabolism (Fig. 3.3) constructed from genomic (Grossman et al., 2007), biochemical (S.J. Burgess and P.J. Nixon, unpublished data; Kreuzberg et al., 1987), transcriptomic (Mus et al., 2007; Nguyen et al., 2008), metabolomic (Doebbe et al., 2010; Timmins et al., 2009b), and proteomic (Atteia et al., 2009; Chen et al., 2010; Terashima
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Starch
Glycolysis NAD+
2H+
NADH
LDH
LAC
PDC3
PYR CoASH
Fdox
HYD
CO2
PFL1
PFOR
Fdred
H2
AcALD NADH
ADH NAD+
CO2
FOR
AcCoA
Pi
EtOH
2NADH
PAT CoASH
ADH 2NAD+ + CoASH
AcP
EtOH
ADP
ACK ATP
Ac
FIGURE 3.3 Proposed pyruvate metabolism in C. reinhardtii (adapted from Grossman et al., 2007). Metabolites are labeled in red—AcALD, acetaldehyde; Ac, acetate; AcCoA, acetyl-CoA; EtOH, ethanol; Fd, ferredoxin; LAC, lactate; PYR, pyruvate. Enzymes present in the C. reinhardtii genome are in blue boxes—ACK, acetate kinase; ADH, alcohol dehydrogenase; HYD, [FeFe]-hydrogenase; LDH, lactate dehydrogenase; PTA, phosphotransacetylase; PDC, pyruvate decarboxylase; PFL1, pyruvate formate lyase; PFOR, pyruvate ferredoxin oxidoreductase. It must be noted that, in a hydrogenase knockout mutant, additional pathways are activated during anaerobic incubation, as reviewed (Grossman et al., 2010).
et al., 2010) analysis of anoxic pathways in C. reinhardtii (reviewed by Grossman et al., 2010). Pyruvate can be broken down to formate and acetyl-CoA by PFL1 (Atteia et al., 2006; Hemschemeier and Happe, 2005; Hemschemeier et al., 2008b), and the acetyl-CoA converted into acetate by a phosphate acetyltransferase (PAT)–acetate kinase (ACK) catalyzed pathway or potentially into ethanol by a bifunctional aldehyde/ADH consuming two molecules of NADH (Fig. 3.3). Additionally, pyruvate can be converted into lactate by a D-lactate dehydrogenase (LDH; Husic and Tolbert, 1985) with the
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cost of one molecule of NADH (Fig. 3.3), or into acetaldehyde by a pyruvate decarboxylase (PDC3) which could then be converted to ethanol by an ADH (Mus et al., 2007) catalyzed pathway, also consuming NADH (Atteia et al., 2003; Fig. 3.3). The feasibility of knocking down fermentative pathways as a means of increasing hydrogen evolution was recently demonstrated by studies of a PFL1 insertion line, which showed improved H2 evolution in the dark, suggesting flux was redirected toward PFOR providing reduced ferredoxin for hydrogen production (Philipps et al., 2011; Table 3.1). This additionally caused an increase in the production of lactic acid, meaning some carbon flux was directed to the LDH making it a good target for future efforts at genetic engineering. However, the link between fermentation and hydrogen production under varying circumstances is still not fully understood. While improving yields in the dark, PFL1 knockout actually decreased H2 evolution in the light, possibly due to reduced hydrogenase transcription (Philipps et al., 2011). Additionally, analysis of the hydrogen production ability of a PFL1 knockdown line during sulfur depletion revealed little change in overall yields (S.J. Burgess and P.J. Nixon, unpublished data). This suggests a greater understanding is required of the more complex metabolic response to nutrient starvation and hypoxia caused by sulfur starvation, as fermentative pathways interact with respiration, ammonium assimilation, and amino acid synthesis through metabolic intermediates (Doebbe et al., 2010; Timmins et al., 2009b).
H. Modifying the photosynthetic apparatus 1. Decreasing the light-harvesting antennae When exposed to high irradiances of light, C. reinhardtii dissipates up to 80% of absorbed photons as heat or fluorescence to protect against photodamage (Polle et al., 2002), in a process known as feedback de-excitation (Holt et al., 2004). This photoprotective mechanism automatically reduces the energy conversion efficiency of PET. Decreasing the light-harvesting capacity of the photosystems reduces excess light absorption by individual cells, thereby increasing photon and energy conversion efficiencies as well as light penetration in a culture (Melis et al., 1998; Mussgnug et al., 2007; Polle et al., 2002). Mutants with a truncated light-harvesting antennae (such as the tla mutants) have been identified on account of their pale phenotype (Berberoglu et al., 2008; Melis, 2009; Mitra and Melis, 2010; Polle et al., 2002) or through reverse genetic approaches, such as by downregulation of light-harvesting complexes through RNAi (Mussgnug et al., 2007) or overexpression of the RNA-binding protein, NAB1, known to block translation of light-harvesting subunits (Beckmann et al., 2009).
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Preliminary results have found that the tla1 mutant could not establish anaerobiosis after sulfur depletion in a bioreactor (Kosourov et al., 2011). However, recent results indicate that, when immobilized in an alignate film and deprived of both sulfur and phosphorous, H2 production rates are increased four to six times relative to the parental strain at light intensities ranging from 285 to 350 mE/m2/s, demonstrating the feasibility of this strategy for improving yields under the optimized conditions (Kosourov et al., 2011; Table 3.1).
2. Altering photosynthetic rates Decreasing O2-evolution rates further may have beneficial impacts in shortening the lag phase between sulfur deprivation and H2 evolution, as well as increasing hydrogenase expression and activity. This could potentially be achieved by targeting photoprotective mechanisms (Li et al., 2009), components of the PSII repair cycle (Nixon et al., 2010), or altering photosynthetic electron transfer rates. The efficacy of this approach is largely untested, but mutations in the QB-binding site of D1 which is responsible for optimal electron transport from PSII ( Johanningmeier et al., 2000; Lardans et al., 1998; Rose et al., 2008) resulted in substantial increases in hydrogen evolution compared to wild-type cultures (Faraloni and Torzillo, 2010; Torzillo et al., 2009; Table 3.1). The precise reason for the increase is unclear but is likely the result of a number of contributing factors (Table 3.1). However, not all photosynthetic mutations are likely to be beneficial. For example, directly targeting photosynthetic activity appeared to cause a decline in overall hydrogen yields (Makarova et al., 2007), possibly as a reduced water-splitting activity affected starch accumulation in the aerobic phase, and may represent a problem for this approach in certain cases.
I. Creating anoxic conditions 1. Improving upon sulfur starvation As mentioned in Section III.B, sulfur depletion is the commonly used process for downregulation of photosynthetic activity, but centrifugation, as used in laboratory protocols as a means of cycling cultures from sulfurreplete to sulfur-deplete media, is unfeasible for scale-up. One method to circumvent this problem is to restrict sulfate transport into the chloroplast. This was done by targeting the C. reinhardtii chloroplast sulfate transporter sulP using RNAi, resulting in the establishment of anaerobiosis in stationary phase cultures triggering H2 production (Chen et al., 2005; Table 3.1). Alternatively, optimization of the sulfate content in the growth media would allow cells to reach optimal density for H2 production at the point when sufficient sulfur is consumed during growth to trigger the starvation response.
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2. Optimizing culturing conditions Under standard conditions, sulfur-deprived cultures of C. reinhardtii CC124 produce H2 at maximum specific rates of 4–6 mmol/mgChl/ h (Kosourov et al., 2002). Since its establishment in 2000, experimental parameters have been optimized, although mainly in isolation, through synchronization of cultures (Tsygankov et al., 2002), re-addition of low levels of sulfate (Kosourov et al., 2002), optimization of pH (Kosourov et al., 2003), light intensity (Laurinavichene et al., 2004), medium composition ( Jo et al., 2006), and growth conditions (Kosourov et al., 2007), with maximum rates of up to 9.4 mmol/mgChl/h reported (Kosourov et al., 2003). The duration of hydrogen evolution has also been extended through cycling between sulfur-replete and -deprived media (Ghirardi et al., 2000; Kosourov and Seibert, 2009; Laurinavichene et al., 2006), the use of a two-staged bioreactor setup for continuous production (Fedorov et al., 2005) and immobilization of cells in an alignate film (Kosourov and Seibert, 2009; Laurinavichene et al., 2006). Immobilizing cells also provided a higher tolerance to O2, greater achievable cell densities, and better light utilization, leading to maximum recorded rates of H2 production at around 12.5 mmol/mgChl/h and an increase in light energy conversion efficiency from 0.24% in liquid cultures to 1% (Kosourov and Seibert, 2009).
3. Regulation of PSII activity through inducible promoters The disadvantages of sulfur depletion include that it ultimately results in cell death, is only suitable as a batch process, and requires continuous illumination over several days for maximum H2 production (Oncel and Sukan, 2011). Therefore, controllable expression of PSII could be used to reduce oxygen evolution to a rate below respiration and drive cultures anaerobic. Surzycki and colleagues used the copper-sensitive cytochrome c6 promoter to repress PSII assembly (Surzycki et al., 2007), thereby inducing anoxia and hydrogen production when cells were transferred from copper-free to copper-replete media. However, it was also found that the promoter used was stimulated by anoxia, even in the presence of copper and resultantly aerobic conditions were reestablished shortly after the initiation of H2 evolution, bringing the process to a stop (Surzycki et al., 2007). Despite this setback, this approach did demonstrate that controlling photosynthesis through inducible promoters is an effective method of stimulating H2 evolution.
4. Mutants with altered rates of photosynthesis to respiration A different approach could be taken to identify mutants with altered rates of photosynthesis to respiration (P/R) which would automatically go anaerobic when placed in sealed containers. A forward genetics screen
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was used to identify such strains based on a colorimetric analysis of dissolved oxygen concentrations, finding one which was named apr1 for attenuated photosynthesis to respiration, showing dramatically reduced photosynthetic rates and a slight increase in respiration (Ruhle et al., 2008). However, despite going anaerobic when placed in sealed containers, H2 was only produced in the light after the Calvin cycle was inhibited through the addition of glycoaldehyde (Ruhle et al., 2008). These results suggested downregulation of the Calvin cycle is a necessary step for stimulating H2 production which otherwise acts as a preferential electron sink (Ruhle et al., 2008).
5. Rubisco mutants Mutant CC-2803, which lacks Rubisco, a key enzyme of the Calvin cycle involved in the fixation of CO2, has a light-sensitive phenotype and a dramatically reduced rate of photosynthesis. Consequently, cultures go anaerobic and produce H2 in sealed containers even in the presence of sulfur (Hemschemeier et al., 2008a). Control of the Calvin cycle or Rubisco activity therefore represents a potentially novel method of inducing H2 production (Marı´n-Navarro et al., 2010) by removing the major sink of electrons for reduced ferredoxin generated by the light reactions. This could be achieved through inducible control of Rubisco or Calvin cycle enzyme expression or control of CO2 supply to carbon-concentrating mutants (Spalding, 2008). Rubisco may also make an interesting target to decrease the specificity of carboxylation to oxygenation reactions as has previously been demonstrated (Chen et al., 1988; Genkov et al., 2006; Satagopan and Spreitzer, 2004), which would result in a higher respiratory rate as well as reduced flux through the Calvin cycle.
6. Direct reduction in O2 levels In addition to altering the specificity of Rubisco to increase the respiratory rate, direct reduction of internal O2 levels without affecting PSII activity could be achieved by overexpressing O2 consuming enzymes, such as a plastid/plastoquinol terminal oxidase (PTOX) in the chloroplast or an AOX in the mitochondrion, although it remains to be seen whether the benefits of decreasing O2 levels would outweigh the loss of electrons which could potentially be fed to the hydrogenase. Another approach for the direct reduction of O2 levels has been demonstrated to improve yields where O2 scavenging proteins from soya bean root nodules were expressed in C. reinhardtii, causing a 4.5 increase in H2 production relative to the parental strain during sulfur depletion (Wu et al., 2010, 2011; Table 3.1).
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V. ENGINEERING CHALLENGES: PHOTOBIOREACTORS A. Overview In addition to improving yields through generation of novel strains, processes for production of hydrogen from algae or cyanobacteria will require scaled-up photobioreactor (PBR) systems (Giannelli et al., 2009; Morweiser et al., 2010; Posten, 2009). Inexpensive open systems such as natural ponds, circular ponds with a rotating arm for stirring, and raceway ponds have already been used for commercial growth of algal biomass, in particular of the green algae Chlorella and Dunaliella, grown for the pigmenting agent astaxanthin and b-carotene, respectively (Akkerman et al., 2002). The disadvantages of such outdoor systems include a lack of control of temperature and hydrodynamics, poor mass transfer and gas exchange within the algal culture, and a strong possibility of contamination and evaporative losses (Carvalho et al., 2006). Additionally, there is significant public concern about genetically manipulated algal species, particularly if the biomass cultivation is open to the environment. Open systems are particularly unsuitable for H2 production process due to the need to efficiently harvest a highly mobile and diffusive gaseous molecule. Enclosed PBR systems, however, feature more reproducible cultivation conditions, with better heat and mass transfer control. This increases biomass production rates and H2 yield, resulting in better product quality as well as providing an opportunity for more flexible technical design (Pulz, 2001). They can enable algal cultivation in arid regions, hence ensuring that algae do not need to compete for land area with food crops, while also opening new economic possibilities in desert countries (Ugwu et al., 2008). The main drawbacks of enclosed PBR systems are their high capital and operating costs (Melis, 2002).
B. Photobioreactors A PBR is best described as a complex, multiphase system, consisting of the gaseous H2 product, the liquid growth medium, and the solid algal cells, as well as the superimposed light radiation field (Borowitzka, 1999). Environmental parameters such as the light transfer and fluid dynamics within the PBR have a strong influence on the biohydrogen production reaction. To achieve optimal productivity, the PBR should be operated at appropriate illumination conditions, with an optimal surface-to-volume ratio and light–dark cycle, and with sufficient gaseous mass transfer through the algal culture (Posten, 2009). Both the intensity and wavelength of light incident on the PBR are equally important, along with the parameters that influence the light attenuation, light dilution, and light mixing in the system (Tsygankov, 2001). The types of PBR previously
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considered in the literature are the stirred-tank reactor (often with internal illumination), the vertical-column reactor, the horizontal tubular reactor, and the flat-plate reactor (Akkerman et al., 2002; Borowitzka, 1999; Carvalho et al., 2006; Dasgupta et al., 2010; Melis, 2002; Posten, 2009; Pulz, 2001; Tamburic et al., 2011; Ugwu et al., 2008). The different PBR geometries are compared in Table 3.2.
1. Stirred-tank reactors Stirred-tank fermenter-type reactors have regularly been used for laboratory measurements of biophotolytic H2 production (Berberoglu et al., 2008); nevertheless, these reactors are characterized by a high degree of back-mixing and poor light penetration through the culture (Pulz, 2001). Agitation is typically provided by means of a mechanical stirrer, which becomes a major source of energy consumption for large volumes. High sheer rates also induce substantial cell death. The possibility of providing internal illumination to stirred-tank systems has been explored as a means of increasing the functionality of these PBRs but becomes a significant engineering challenge for large-scale reactors (Pulz, 2001).
2. Vertical-column reactors Vertical-column reactors are simple systems consisting of a polyethylene or glass tube, agitated by means of an air-lift loop or a bubble column. They are compact, low cost, easy to operate, and consequently used for domestic (and laboratory) microalgal and plankton growth (Uyar et al., 2007). Due to the reactor orientation, artificial lighting is important; a high degree of turbulence is also required to produce sufficient mixing and light–dark cycling of the culture (Skja˚nes et al., 2008). The advantages of vertical-column reactors are the high mass transfer rates and good culture mixing with low shear stress on the algae. The main limitation is the relatively small surface-to-volume ratio compared with the flat-plate or stirred-tank reactors. Other drawbacks include the variable light attenuation through the algal culture, the need for sophisticated construction materials to keep the reactor H2 leak free, and the decrease in illumination surface area upon scale-up (Uyar et al., 2007).
3. Tubular reactors Tubular photobioreactors consist of straight, coiled, or looped transparent tubing laid out in a specific geometric arrangement designed to maximize light capture (Xu et al., 2002). They come in multiple reactor geometries including horizontal, helical, conical, and a-shape and can be made from a variety of materials ranging from glass capillaries to plastic bags. Tubular reactors are widely available because of the ease of manufacture, process scale-up, and suitability for outdoor use due to their large illumination surface area. Large surface areas are obtained by using thin tubes with a
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TABLE 3.2 A comparison of representative photobioreactor geometries used to facilitate green algal H2 production (adapted from Tamburic et al., 2011) Reactor geometry Stirredtanka
Illumination
Mass transfer
Scale-up
Economics
Poor light
High
Impractical
Cheap and
Verticalcolumnb
Low
Tubularc
surface-tovolume ratio Artificial illumination for efficient growth
Large
Flat-plated
penetration and diffusion Artificial illumination only
illumination surface area Conical/ alpha geometries for outdoor operation
Large
surface-tovolume ratio Inclined design for outdoor operation
degree of culture backmixing Energyintensive mechanical agitation
Air-lift/
bubble column provides good mixing Low shear stress on algal cells
High gas
gradients arise along tubes Algal clustering along tube surfaces
geometry Internal illumination required
Illumination Domestic
area decreases with volume Multiple reactor units required
Additional
sections added via manifolds Difficult to keep reactor H2 tight
Difficult to Two
control light dilution gradients Algal fouling possible
effective at laboratory scale Large applications prohibitively expensive
dimensions available for scale-up Multiple units required on industrial scale
microalgal and plankton growth Many largescale growth applications
Commercial
Chlorela growth Impractical for H2 production applications
Operational flexibility
Some largescale growth applications
Photographs are of a SolarBiofuels consortium stirred-tank reactor (http://www.solarbiofuels.org/consortium.php), b Aqua Medic Plankton Light Reactor, c Sartorius Biostat PBR 2s, and d Imperial College flat-plate reactor (Tamburic et al., 2011).
diameter of no more than 10 cm and illuminating the reactor from multiple directions. Horizontal tubular plastic bag reactors have achieved commercial success for the cultivation of Chlorella (Ugwu et al., 2008). Helical
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designs enclosing a central light source usually aim to attain high surfaceto-volume ratios, while conical and a-shape geometries create a better angle relative to the direction of sunlight but have so far proven difficult to scale up (Akkerman et al., 2002). The main disadvantage of tubular reactors is their poor axial mass transfer—long reactors are characterized by significant gas gradients along the tubes (Xu et al., 2002). Tubular reactors are scaled up by the incorporation of additional sections via manifolds (Borowitzka, 1999). However, each additional link increases the possibility of H2 diffusive losses and the requirement for a H2-tight reactor also reduces the number of potential tubular reactor materials.
4. Flat-plate reactors A flat-plate reactor features a rectangular compartment with a depth of 1– 5 cm, depending on the quality of agitation in the system (Skja˚nes et al. 2008). The height and width may be scaled up to a practical limit of 2–3 m (Borowitzka, 1999). Flat-plate reactors may be run in both batch and continuous modes and therefore provide operational flexibility. Artificially illuminated flat-plate reactors are typically vertical and the irradiation is incident on one of the large reactor surfaces, while outdoor flatplate reactors tend to be tilted at an angle corresponding to the mean solar irradiation angle (Akkerman et al., 2002). The reactor region adjacent to the illuminated surface is known as the photic zone. Within the photic zone, light saturation of the algal culture may result in photoinhibition of the cells (Skja˚nes et al., 2008). Light intensity decreases exponentially away from the photic zone, with a limiting light diffusion length of 0.8 mm for a fully grown culture of C. reinhardtii (Janssen et al., 2003). These light gradients may be minimized, and the light–dark cycles experienced by algal cells may be controlled, by introducing effective agitation into the system. Since the space between flat-plate reactor panels is restricted, the gaseous mass transfer rates tend to be low, which reduces the clearance efficiency of the dissolved oxygen produced by photosynthesis (Molina et al., 2000). Gas-lift agitation is therefore required to achieve significant algal biomass production rates. Other limitations for flat-plate reactors include the difficulty in controlling culture temperature and the requirement for multiple compartments and support materials when scaling up the reactors (Molina et al., 2000).
5. Artificial systems Alternatively, to avoid some of the problems outlined with biological systems, it may be possible to use bio-inspired processes as a solution to the energy problem. Various artificial approaches to harness solar energy using components of biological systems have been envisioned. These include the immobilization of hydrogenase and isolated PSII complexes onto electrodes, spatially separating oxygen evolution and hydrogen
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production (Esper et al., 2006) and the construction of hybrid systems ranging from coupling of photosystem complexes to Pt nanoparticles for H2 production (Grimme et al., 2008; Iwuchukwu et al., 2010; Lubner et al., 2010), attachment of bacterial reaction center complexes to carbon nanotubes for electricity generation (Ham et al., 2010), the coupling of hydrogenases to TiO2 nanoparticles (Reisner et al., 2009), or the use of viral particles as scaffolds for the assembly and repair of photocatalytic nanostructures (Nam et al., 2010). Efforts have also been directed at biomimetic design (Lewis and Nocera, 2006), creating novel water-splitting catalysts based on the [FeFe]-hydrogenase active site (Gloaguen et al., 2001; Kluwer et al., 2009; Ott et al., 2004). However, there are a number of disadvantages inherent in many of these processes including the short life span of many hybrid systems containing biological components that are rapidly damaged by light and during water oxidation, the requirement for expensive rare metals in the synthesis of many catalysts, and the requirement for energy input in some catalytic systems. Despite these problems, there have been significant advances in these fields over the past few years (Kanan and Nocera, 2008) and biologically inspired artificial systems represent an exciting prospect for future energy production
VI. CONCLUSIONS AND FUTURE PROSPECTS Current ideas suggest that the feasibility of algal H2 production should be considered in terms of the biorefinery concept (Kruse and Hankamer, 2010; Mussgnug et al., 2010) which aims to maximize the biotechnological potential of every fraction of biomass. Synergies exist between the production of a H2 and variety of algal fuels as the process of sulfur deprivation leads to increased lipid accumulation (Timmins et al., 2009b) and a lower sulfur content aiding biodiesel or biogas production (Mussgnug et al., 2010). Additionally, the economics of the process could be further improved by coupling to a range of biotechnological processes as described in Section II. The long-term future of society requires drastic changes in how we produce and consume energy, and biological hydrogen production offers one possible alternative to traditional fossil fuels. Knockout of competing processes, integration of dark fermentative, photofermentative, and biophotolytic modes of hydrogen production into a three-step process, and coupling to a range of biotechnological processes within a biorefinery offers promise for increasing efficiencies toward the levels required for economic viability. But much research is still required to improve yields and drive down the costs of culturing and bioreactor construction, in concert with economic and political drive toward a low carbon H2
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economy if the goal of generating clean energy through renewable means is to be achieved. It is possible, however, given the recent discovery that the marine cyanobacterium Cyanothecae can produce significant amounts of H2 under aerobic conditions via a nitrogenase (Bandyopadhyay et al., 2010), that the solution may lie beyond the limits of established research. This finding illustrates the limitation of using model organisms for biotechnological purposes and suggests the key to photolytic H2 production could yet lie in the largely untapped biodiversity of cyanobacteria and microalgae in the environment.
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4 Mucosal Biofilm Communities in the Human Intestinal Tract Sandra Macfarlane,1 Bahram Bahrami, and George T. Macfarlane
Contents
Abstract
I. Introduction II. Colonization of the Upper Gastrointestinal Tract A. Mucosal communities in the esophagus B. The gastric microbiota III. Mucosal-Associated Populations in the Large Bowel IV. Alterations in Intestinal Mucosal Communities in IBD V. Therapeutic Manipulation of Mucosal Biofilm Communities VI. Modeling Studies VII. Conclusions References
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Complex and highly variable site-dependent bacterial ecosystems exist throughout the length of the human gastrointestinal tract. Until relatively recently, the majority of our information on intestinal microbiotas has come from studies on feces, or from aspirates taken from the upper gut. However, there is evidence showing that mucosal bacteria growing in biofilms on surfaces lining the gut differ from luminal populations, and that due to their proximity to the epithelial surface, these organisms may be important in modulating the host’s immune system and contributing to some chronic inflammatory diseases. Over the past decade, increasing
Microbiology and Gut Biology Group, University of Dundee, Dundee, United Kingdom 1 Corresponding author: e-mail address:
[email protected] Advances in Applied Microbiology, Volume 75 ISSN 0065-2164, DOI: 10.1016/B978-0-12-387046-9.00005-0
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2011 Elsevier Inc. All rights reserved.
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interest in mucosal bacteria, coupled with advances in molecular approaches for assessing microbial diversity, has begun to provide some insight into the complexity of these mucosa-associated communities. In gastrointestinal conditions such as inflammatory bowel diseases (ulcerative colitis, Crohn’s disease), it has been shown that a dysbiosis exists in microbial community structure, and that there is a reduction in putatively protective mucosal organisms such as bifidobacteria. Therefore, manipulation of mucosal communities may be beneficial in restoring normal functionality in the gut, thereby improving the immune status and general health of the host. Biofilm structure and function has been studied intensively in the oral cavity, and as a consequence, mucosal communities in the mouth will not be covered in this chapter. This review addresses our current knowledge of mucosal populations in the gastrointestinal tract, changes that can occur in community structure in disease, and therapeutic modulation of biofilm composition by antibiotics, prebiotics, and probiotics.
I. INTRODUCTION Until recently, much of what we knew about the human gut microbiota came from work done on fecal material over many decades using a variety of culturing techniques. These studies demonstrated that anaerobic bacteria predominated in feces, with over 400 species being detected and total viable counts in the region of 1011–1012 g 1 (Finegold et al., 1974; Hentges, 1993; Holdeman et al., 1977; Moore and Holdeman, 1974). Largely due to the inaccessibility of the gut, and ethical problems in obtaining intestinal biopsy tissue, until relatively recently, few investigations were undertaken on bacteria inhabiting the colonic mucosa, and studies on biofilm formation have concentrated on pathogenic species such as Escherichia coli. However, over the past 10 years there has been increasing interest in mucosal populations, particularly in relation to their role in maintenance of gut health and potential involvement in gastrointestinal illnesses such as Barrett’s esophagus (BE), inflammatory bowel disease (IBD), and colon cancer (Hughes and Rowland, 2003; Macfarlane et al., 2004, 2009a,b; Swidsinski et al., 2005). Secretory intestinal epithelia in the gastrointestinal tract are covered in a largely continuous mucus coating secreted by goblet cells, between 100 and 200 mm thick (Pullan et al., 1994). This forms a viscoelastic gel (Allen, 1981) providing a barrier that protects against adhesion and invasion by pathogenic bacteria, microbial antigens, and other damaging agents in the gut lumen. Intestinal mucins are chemically and structurally diverse but usually contain galactose and hexosamines, lower amounts of fucose, and varying levels of neuraminic acid and sulfate (Macfarlane et al., 2005b; Quigley and Kelly, 1995), which increase their resistance to digestion by
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bacterial hydrolytic enzymes (Corfield et al., 1992). Mucins are important sources of carbohydrate for saccharolytic bacteria, while a variety of other substances such as proteins, peptides, nucleic acids, and partly digested plant cellular materials can also be found in the mucin layer, which are used as energy sources. Several hydrolytic enzymes are necessary for the complete degradation of mucin by gut microorganisms, and evidence suggests that this is a cooperative activity in the microbiota (Macfarlane and Macfarlane, 2000; Macfarlane et al., 1999). The spatial organization and composition of mucosal communities can also be influenced by a variety of factors, such as humoral and innate immunity, other host defenses, the type and amount of mucus glycoprotein in the microcosm, intestinal epithelial cell turnover, and gut motility. Early cultural studies indicated that intestinal mucosal populations were analogous to those in the gut lumen (Croucher et al., 1983; Edmiston et al., 1982; Nelson and Mata, 1970), and that there were similar communities along the length of the large bowel (Croucher et al., 1983); however, several unique bacteria were visualized on the mucosa which were not seen or cultured from fecal material (Lee et al., 1971), indicating the existence of distinct mucosal populations. Recent studies have shown that intestinal communities can be visualized growing as microcolonies or biofilms of sessile microorganisms attached to the mucosa or growing in the mucus layer in healthy and diseased individuals (Ahmed et al., 2007; Macfarlane et al., 2000, 2004). Currently, through the increasing interest in the physiologic significance of these mucosal biofilm communities in the health of the host, together with the development of new molecular approaches based on small subunit ribosomal RNA (Macfarlane and Macfarlane, 2004) and high-throughput sequence analysis, a more detailed picture of mucosal bacterial diversity is beginning to emerge.
II. COLONIZATION OF THE UPPER GASTROINTESTINAL TRACT A. Mucosal communities in the esophagus It is only in the past few years that bacterial colonization in the esophagus has begun to be investigated in any great depth. Until recently, it was thought that because of the rapid movement of material through the esophagus, little bacterial growth occurred, and that the esophageal microbiome was composed primarily of bacteria originating from the oral environment (Lau et al., 1981). In an early study, esophageal aspirates were found to consist mainly of streptococci, Haemophilus influenzae, Neisseria catarrhalis, yeasts such as Candida albicans, and anaerobic bacteria
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including peptococci, peptostreptococci, and bacteroides, and no differences in microbial populations existed in patients with and without esophageal carcinoma (Mannell et al., 1983). Over the past two decades, there have been unexplained increases in diseases such as BE and esophageal carcinoma, and because epithelial mucosal communities exist in close contact, and have more time to interact with the epithelium, this has led to several studies on bacterial colonization of the esophageal mucosae. These have increased our insight into the esophageal microbiota in health and disease, and have shown that the mucosal esophageal microbiome is much more diverse than was originally thought. BE is a complication of gastroesophageal reflux disease, in which the normal squamous mucosa found in the distal esophagus undergoes metaplastic changes, and is transformed into a more columner-lined epithelium. Patients with BE have an increased risk of development of adenocarcinoma, which is the seventh most common cause of cancer in the United Kingdom, with 5-year survival rates as low as 5% (Landis et al., 1999). Many of these patients receive proton pump inhibitors, which reduce gastric acid production, allowing bacterial proliferation. As a consequence, inflammation of the mucosa and the breakdown of normal defense processes may facilitate colonization by potentially more immunogenic or pathogenic microrganisms. Osias et al. (2004) examined stored esophageal tissue from Barrett’s patients microscopically and found that increased colonization by Gram-positive cocci occurred in BE compared to healthy controls; however, when the same group did aerobic culture on fresh biopsy material, no differences were detected. Macfarlane et al. (2007) used culturing to isolate facultatively anaerobic, anaerobic, and microaerophilic bacteria from the distal esophageal mucosa in aspirates taken from seven healthy controls, and seven patients with BE. The Barrett’s patients were found to have a higher numbers of bacteria and greater species diversity than the healthy controls. Direct microscopic analysis using live/dead staining of the mucosal epithelium to determine the spatial location of the microbiota demonstrated that the bacteria were viable, and were often present as microcolonies and in bio films (Fig. 4.1). Distinct mucosal communities were found to occur on the esophageal surface that were not simply due to contamination by bacteria present in gastric aspirates. Prevotellas were only detected on healthy and gastric mucosae, and greater numbers and species diversity of lactobacilli were found on the healthy mucosa. Helicobacter pylori was not observed in any of the samples. BE microbial communities were found to contain high numbers of putatively pathogenic bacteria such as Campylobacter rectus and C. concisus, which are able to reduce nitrate, but they were not detected in healthy subjects. Moreover, increased numbers of nitratereducing veillonellas were found in BE, which have also been detected in high levels in oral squamous cell carcinomas (Nagy et al., 1998). These
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FIGURE 4.1 Live/dead stains of mucosal tissue. (A) From a patient with Barrett’s esophagus showing a heterogeneous mixture of bacteria growing in aggregates. Yellow bacteria are living, red cells are dead. (B) Healthy esophageal tissue showing the presence of microcolonies and individual living cells on the mucosal surface.
organisms may have a role in disease etiology, due to the potential for nitrite produced by nitrate reduction in the mouth to be converted to N-nitroso compounds and nitric oxide, which have been shown to be involved in DNA damage and the induction of cancer (Liu et al., 2002; Mirvish, 1995). The principal site of nitrite production has been shown to be the gastroesophageal junction (Iijima et al., 2002), and the increased presence of these bacteria has been postulated to result in tissue damage due to high localized concentrations of toxic substances on the esophageal epithelium.
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Several culture-independent molecular analyses have also been done on the microbiome from the healthy esophagus, and as well as in BE patients. 16S rRNA gene sequencing of material from the healthy distal esophagus indicated the existence of six phyla, with the predominant bacteria identified as streptococci, followed by prevotellas and veillonellas. The bacterial communities were reported to be similar in composition to those detected in the oral environment (Pei et al., 2004). More recently, Yang et al. (2009) used 16S rRNA gene amplification, cloning and sequencing to identify the presence of bacteria in distal esophageal biopsies taken from 10 BE patients, 12 individuals with esophagitis, and 12 healthy controls. They detected nine phlya and 166 species, and observed that the predominant organisms in healthy people were streptococci, which accounted for 78% of healthy esophageal sequences, which they termed as a type I microbiome. The Barrett’s microbiome, similar to the earlier study based on cultural analysis, was found to be more diverse, with a lower number of streptococcal sequences (29%) and a greater presence of sequences for Gram-negative taxa such as prevotella, bacteroides, haemophilus, veillonella, and fusobacteria, which was labeled a type II microbiome. However, only a small number of clones were sequenced (200) per biopsy, and although the study provides some insight into microbial biodiversity in the distal esophagus, since 16S rRNA sequencing is not a quantitative molecular technique, the actual numbers of these bacteria on the esophageal mucosa is unclear.
B. The gastric microbiota Due to gastric acid, bile salts and the short retention time of digestive materials (ca. 2 h), the stomach is sparsely colonized by microorganisms, and they consist mainly of aciduric Gram-positive microorganisms (lactobacilli, streptococci, yeasts), with numbers less than 103 CFU/ml (Draser et al., 1969; Savage, 1977; Simon and Gorbach, 1986). Other bacteria such as H. pylori have been shown to occur in association with the gastric epithelium (Marshall, 1994). Flagella enable this bacterium to penetrate the gastric mucosa and protection from gastric acid is also afforded by the production of urease, which converts urea into ammonia. The presence of H. pylori can lead to inflammation, gastritis, peptic ulceration, and increased risk of developing gastric cancer. Treatment for H. pylori usually involves the use of proton pump inhibitors to reduce stomach acid in combination with antibiotics; however, this can also lead to overgrowth of bacteria in the stomach. The mucosal gastric microbiotas of eight patients with H. pylori-associated gastritis, and five controls with no histological evidence of gastritis were compared by Monstein et al. (2000). Using temperature gradient gel electrophoresis (TGGE) of PCRamplified 16S rRNA gene sequences, they were able to detect H. pylori
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specific DNA in gastric biopsies. Although they were unable to determine differences at species level, because of the small number of short (200 bp) 16S rRNA gene fragments obtained, the authors detected the presence of 11 bacterial genera, including Pseudomonas, Enterococcus, Streptococcus, Staphylococcus, and Stomatococcus. However, since TGGE is a nonquantitative technique, the actual differences in numbers of H. pylori and the other bacteria between the groups could not be determined. Li et al. (2009) used cloning and 16S rRNA sequencing to profile bacterial microbiotas in patients with gastritis, without H. pylori involvement, and compared them to healthy controls. They identified eight bacterial phyla composed of 133 phylotypes, and quantitative real-time PCR analysis of firmicutes and streptococci showed that they occurred in higher numbers in patients with antral gastritis than in normal controls. Bik et al. (2006) reported that the gastric mucosa contained distinct bacterial communities. They examined microbiotas associated with gastric biopsies from 23 healthy individuals, 12 of which were determined to be H. pylori positive. A 16S small subunit clone library approach was used that generated 1833 sequences, and identified 128 phylotypes with the main phyla being Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes, and Fusobacteria. Community structure was not found to be dependent on the presence of H. pylori. Fifty percent of the phylotypes obtained were from uncultivated bacteria, of which 67% were similar to those described in the oral environment. Limitations of the study were that the biopsies were obtained from individuals with different medical conditions, and that the different methods employed for amplification and DNA extraction may have affected the results. Although H. pylori has been implicated in gastric cancer, it has been found to be a poor coloniser of the atrophic stomach and is rarely found in intestinal metaplasia; however, it may create a more suitable environment for the presence of other bacteria that produce toxic substances such as N-nitroso compounds that may be linked to cancer development (Blaser and Atherton, 2004; Correa, 1992). Bacterial involvement in gastric cancer was evaluated in a recent study (Dicksved et al., 2009). Terminal restriction fragment length polymorphism (T-RFLP) in combination with 16S rRNA gene cloning and sequencing was used to compare the gastric microbiota of 10 patients with gastric cancer, compared to five controls with normal gastric mucosal morphology. T-RFLP analysis indicated that no significant differences occurred in diversity indices; however, cluster analysis indicated greater similarity between healthy controls. A total of 384 clones were obtained from clone libraries from six of the cancer patients, of which, on comparison with T-RFLP, 140 were sequenced. Based on T-RFLP relative abundances, complex communities of bacteria were identified clustering within five bacterial phyla Firmicutes (60%), Bacteroidetes (11%), Actinobacteria (7%), Proteobacteria (6%), and
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Fusobacteria (3%), with low abundance of H. pylori. However, the authors suggested that the results could have been influenced by a relatively old control group being used, that might have had a deficiency in acid production, and that the study was not able to provide quantitative information on the actual numbers of microrganisms present on the gastric mucosa.
III. MUCOSAL-ASSOCIATED POPULATIONS IN THE LARGE BOWEL Early studies on mucosal intestinal populations based on culturing indicated the presence of a diverse range of anaerobic bacteria, including bacteroides, bifidobacteria, clostridia, and fusobacteria and that they were basically similar in composition to luminal populations (Croucher et al., 1983; Edmiston et al., 1982; Nelson and Mata, 1970). Since then, more extensive investigations of mucosal populations involving both cultural and molecular analyses have provided more information, and have shown that differences in community structure occur along the length of the large intestine. Moreover, evidence suggests that they can differ markedly from luminal populations, and be affected by a number of factors such as age and disease. However, results obtained from some of these investigations may not directly reflect bacterial diversity, since the subjects often had pretreatment with antibiotics, laxatives, or other gut cleansers before surgery or colonoscopy. In addition, due to the laborintensive and time-consuming nature of some of the molecular techniques, only a small number of individual bacterial groups have been examined. PCR coupled with denaturing gradient gel electrophoresis (DGGE) is not a quantitative technique and has several limitations including PCR bias; however, it has been useful in producing an intestinal bacterial fingerprint. Using DGGE, Zoetendal et al. (2002) investigated mucosal communities in different parts of the gut. In this study, mucosal microbiotas of the ascending, transverse, and descending colons were compared to fecal populations in 10 healthy individuals. Bacterial communities in different locations on the mucosa were found to be similar, host-specific, and significantly different from fecal populations. Eckburg et al. (2005) used 16S rRNA gene sequencing, cloning, and phylotype analysis to investigate microbial communities in fecal and mucosal samples from three healthy adults. They examined 13,355 prokaryotic ribosomal RNA gene sequences and detected 395 unique phylotypes, the majority of which belonged to Firmicutes (301 phylotypes) and Bacteroidetes (64 phylotypes). Interindividual differences in mucosal
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microbiotas were reported, that were dissimilar to fecal bacterial communities of the same individual. Sixty-two per cent of the bacterial phylotypes were considered to be novel, and 80% of the sequences were from hitherto uncultured bacteria. In addition, only a few sequences were detected for Actinomycetes, of which bifidobacteria constitute a subgroup. In this study, tissue samples were taken at colonoscopy, which could have removed loosely adherent members of the mucosal communities. Only a small number of subjects were analyzed, and the stool samples were collected 1 month after colonoscopy, which could have impacted on the apparent fecal/mucosal community profiles. Table 4.1 shows a comparison of the main groups identified from healthy mucosal tissue in several molecular studies. Wang et al. (2003) found that Bacteroidetes (38%) and Clostridium cluster XIVa (34%) were the predominant groups in the distal ileum and colon of a healthy 35-year-old female, and that the operational taxonomic units for bacteria increased from the terminal ileum to the distal colon. In another study involving a 54-year-old healthy Swedish female, clone libraries of the distal ileum, ascending colon, and rectum had similar diversity indices, and they differed significantly from the microbial communities in the jejunum, which displayed the lowest microbial diversity (Wang et al., 2005). Sequences for Streptococcus (67%) were predominant in the jejunal samples, while Bacteroidetes (27–49%), and Clostridium clusters XIVa (20–34%) and IV (7–13%) were predominant in the other intestinal regions. Less Bacteroidetes sequences were detected in the ascending colon compared the distal ileum and rectum. Hold et al. (2002) found that the majority of bacteria (85–89%) in colonic mucosal tissue from three healthy elderly subjects occurred in the same three phylogenetic groups as fecal populations. Clostridium cluster XIVa predominated (43–49%), followed by Bacteroidetes (20–35%) and Clostridium cluster IV (11–18%). Interestingly, only 72% of the sequences detected were related to known cultured bacteria, and no bifidobacteria were detected. This emphasizes one of the limitations of cloning and other metagenomic analyses, in that results can be affected by the DNA extraction method, primer bias, and multiple heterogeneous copies of 16S rRNA genes within a genome. Primers used for total bacteria may not be suitable for all members of the gut community, and there may be preferences for specific phylogenetic groups; therefore, important members of the microbiota such as bifidobacteria and atopobia may not be detected (Hattori and Taylor, 2009; Horz et al., 2005; Macfarlane and Macfarlane, 2004; Rajilic-Stojanovic et al., 2007; Turroni et al., 2008). Similar lack of bifidobacterial detection, or low proportions of bifidobacteria have also been shown in several molecular studies of fecal and mucosal samples (Eckburg et al., 2005; Gill et al., 2006; Suau et al., 1999; Wang et al., 2003, 2005; Wilson and Blitchington, 1996).
TABLE 4.1
Comparison of the main groups of intestinal bacterial populations from healthy mucosal tissue using molecular analysis % attributed to each phylogenetic group C. coccoides group (Cluster XIVa)
C. leptum subgroup (Cluster IV)
Other Clostridium clusters
Bacteroides group
85 clones from one 54-year-old female 86 clones from one 54-year-old female person 88 clones from one 54year-old female person 110 clones from three elderly subjects 190 clones from one 35-year-old female
20
7
10
49
34
13
15
27
29
8
7
44
46.3
14.5
5.4
26.4
34.1
0
13.7
38
395 phylotypes from one 43-year-old male and two 50-year-old females
53
NDe
16e
16
Tissue location
Distal Ileuma Ascending colona
Rectuma Colonb Ileum, proximal and distal colon combinedc Pooled mucosal samplesd
a b c d e
Adapted from Wang et al. (2005). Adapted from Hold et al. (2002). Adapted from Wang et al. (2003). Pooled samples from the cecum, right colon, descending colon, rectum, and sigmoid rectum. Adapted from Eckburg et al. (2005). ND, not determined, individual values not provided other than for Cluster XIVa.
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Fluorescent in situ hybridization (FISH) with group and speciesspecific probes differs from other molecular techniques in that in addition to quantifying bacterial numbers, it can be used to visualize mucosal communities in situ. Macfarlane et al. (2004) used confocal laser scanning microscopy (CLSM) and FISH with probes specific for a range of intestinal bacteria and live/dead staining for in situ visualization of mucosal biofilm communities. The majority of bacteria were found to be actively growing throughout the mucus layer, with extensive microcolony formation, but were not present in healthy crypts. This differs from another study in which the authors reported that intestinal bacteria do not occur in the mucin layer (Van der Waaij et al., 2005). In this investigation, the mucosal layers of five colonic regions and the terminal ileum of nine subjects were examined by FISH for total bacteria, and specific probes for a range of intestinal anaerobic (bifidobacteria, bacteroides, clostridia, and atopobium) and aerobic bacteria (enterobacteria, enterococci, streptococci, lactobacilli). Bacteria were observed at the luminal side of the mucus layer with few colonies at the mucus layer, and the composition was found to be similar to the fecal microbiota. A more recent study combined DGGE and FISH, with quantitative realtime PCR analysis to investigate mucosal populations in 26 surgical patients undergoing emergency resection of the large bowel (Ahmed et al., 2007). These individuals had not received antibiotics or gut cleansing prior to surgery. This work showed that mucosal bacteria were in fact adherent to the mucus layer, and were able to penetrate the mucin and form heterogeneous communities and microcolonies (Fig. 4.2). Mucosal tissue was taken from the terminal ileum (n ¼ 6), as well as the ascending (n ¼ 8), transverse (n ¼ 8) and descending colons (n ¼ 4). DGGE banding profiles from the gut regions exhibited at least 45% homology and clustered at ca. 75% concordance with five of the profiles from the descending colon. Contrasting with other studies that showed individual differences in mucosal microbiotas (Lepage et al., 2005; Wang et al., 2005; Zoetendal et al., 2002), DGGE profiles in the three regions of the colon were remarkably similar in the different individuals. Although no significant differences in total bacteria was detected in the colonic regions, site-specific differences were found in bacterial colonization of mucosal tissue (Fig. 4.3). Bifidobacteria were detected in higher numbers in the colon than in the terminal ileum, Faecalibacterium prausnitzii and Eubacterium rectale were significantly higher in the ascending and descending colon and lactobacilli in the distal region of the large intestine. Higher numbers of bacteria were also detected in the ileum compared to the colonic regions, which were not evident with the individual probes, indicating that there was a greater proportion still to be identified. Interestingly, FISH analysis using a wider range of fluorescent probes was able to identify members of the atopobium cluster on the intestinal mucosa, that were not detected by DGGE.
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FIGURE 4.2 Confocal FISH light micrographs of mucosal tissue hybridized with 16S rRNA specific oligonucleotide probes. (A) Descending colon labeled with Eubacterium rectale/ Clostridium coccoides probe (red) and an atopobium probe (green). (B) Transverse section of the ascending colon labeled with a ruminococcus probe showing the presence of individual microcolonies, and (C) a confocal section (10 mm) taken vertically through the mucosa showing ruminococcus microcolonies.
The presence of bacteria bound to the human ileal epithelium was also observed in another study (Fakhry et al., 2009). In this investigation, small bowel biopsies from nine healthy volunteers were washed to remove loosely bound bacterial cells and mucin. Cultural analysis indicated that 11 rodshaped bacterial isolates were tightly attached to the epithelial cells, which were identified as Bif. breve (one isolate), Lactobacillus mucosae (eight isolates), and Lactobacillus gasseri (two isolates). All of the isolates were found to be able to form biofilms in simulated intestinal fluid under gastric conditions, while Bif. breve and seven of the L. mucosae strains were able to degrade mucin. The authors suggested that the ability to use mucin might confer a competitive advantage on commensal bacteria, and allow them to grow the epithelial surface more efficiently. Other studies have shown that mucin is degraded extensively by indigenous gut species, allowing them to colonize the epithelium and contribute to mucosal integrity (Macfarlane et al., 2000; Macfarlane and Macfarlane, 2000; Ruas-Madiedo et al., 2008; Yang et al., 2007). A more recent investigation compared bifidobacterial populations in human fecal samples from 29 healthy infants, and intestinal mucosal biopsies from the rectum and sigmoid colons of 30 adolescents and adult volunteers taken at colonoscopy (Turroni et al., 2009). A polyphasic approach combining cultural analysis followed by molecular analysis of selected rRNA gene sequences was used to identify the bifidobacteria. In total, 704
Intestinal Mucosal Communities
Total eubacteria
10 9
Log1016S rRNA gene copies/mg mucosal tissue
Bacteroides
8
Bifidobacteria
7
7
6
6
5
123
8 7 6
5 Lactobacilli
7
4 Eubacterium rectale
8
6
7
7
6
6
3
5
5
2
4
4
5 4
Faecalibacterium prausnitzii
8
Clostridium clostridioforme
8
7 7
6 5
6
4 3
TI
AC
TC
DC
5
TI
AC
TC
Enterobacteria
8
DC
6 5 4 3 2 1 0
Enterococcus faecalis
TI
AC
TC
DC
FIGURE 4.3 Real-time PCR quantification of mucosal bacterial populations in healthy mucosal tissue from patients undergoing resection of the large bowel. IL, terminal ileum (n ¼ 6); AC, ascending colon (n ¼ 8); TC, transverse colon (n ¼ 8); DC, descending colon (n ¼ 4). Values are mean standard deviation. Adapted from Ahmed et al. (2007).
bifidobacterial isolates were collected which belonged to six main taxa: Bif. longum, Bif. pseudocatenulatum, Bif. adolescentis, Bif. pseudolongum, Bif. breve, and Bif. bifidum, in both fecal and mucosal samples. Bifidobacterium animalis subsp. lactis was more frequently detected in infant feces than on mucosal tissues. Significant intersubject variability was also found. The authors reported differences in species complexity in the different communities and that certain species were only present in adults. However, this study has some limitations in that no direct comparisons of fecal and mucosal materials from the same individuals were done, and the infant mucosal bifidobacterial community was not investigated.
IV. ALTERATIONS IN INTESTINAL MUCOSAL COMMUNITIES IN IBD Much of our knowledge regarding mucosal bacterial community structure in apparently healthy individuals has come largely as a by-product from investigations made on tissue samples taken from sick people. Probably
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the area that has seen the most rapid development over the past decade concerns microbial involvement in IBD. Ulcerative colitis (UC) and Crohn’s disease (CD) are the two principal forms of idiopathic IBD. UC is an acute and chronic inflammation of the mucosa, which only affects the large intestine, while CD can present across the entire gastrointestinal tract (Whitehead, 1995). The current view is that the pathological response in IBD is multifactorial and associated with aberrant immune responses to the normal intestinal microbiota, together with a defective epithelial barrier in genetically susceptible individuals. In the normal situation, in a healthy person, commensal bacteria are tolerated in an immune sense and do not prime the inflammatory response. Several studies have reported that a dysbiosis occurs in fecal microbiota structure in IBD, with a loss of potentially beneficial species Macfarlane et al., 2009a. However, since many mucosal bacteria exist in biofilms that occur in close juxtaposition to host tissues, it might be expected that these organisms interact to a greater extent with the immune and neuroendocrine systems than their luminal counterparts. This has prompted interest in their involvement in IBD. So far, work suggests that while the role of microorganisms belonging to the normal mucosal microbiota in disease processes associated with CD is uncertain, the case for their involvement in UC is stronger. UC usually starts in the distal bowel, and over time, it progresses proximally along the colon (Maratka, 1986). Animal studies have indicated that commensal organisms play a key role in the initiation and maintenance of UC-like conditions (Cummings et al., 2003; Hill, 1986), and a number of organisms including desulfovibrios, fusobacteria, shigellas, bacteroides, and streptococci have variously been associated with disease etiology (Gibson et al., 1991; Macfarlane et al., 2005a; Onderdonk, 1983). Culturing studies have found no significant differences in total numbers of bacteria growing on mucosal surfaces in healthy controls and UC patients (Macfarlane et al., 2004; Poxton et al., 1997). Macfarlane et al. (2004) found that colonization occurred throughout the mucus layer in both IBD patients, and healthy controls, although no bacteria were present in healthy crypts, which may be attributed to higher localized concentrations of host-produced defensive peptides (Furrie et al., 2005). Many organisms on the gut mucosa were shown to occur in microcolonies, and FISH together with live/dead staining of these structures demonstrated that most of the bacteria were living, especially those organisms adjacent to the mucosal surface. These observations indicated that the bacteria were actively growing and that they were not there simply as a result of passive transfer from luminal material. The presence of immunogenic bacterial species in microcolonies on the rectal epithelium may have implications for UC, and other gut diseases, since higher localized concentrations of bacterial antigens or secretory products would result in greater tissue damage.
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In contrast, other investigators have reported that higher numbers of microorganisms are present in IBD than in controls. In one study, the distribution of bacteria was examined in rectal biopsies from 16 IBD patients and controls, using FISH (Schultsz et al., 1999). Bacteria were found in the mucin layer in the majority of the IBD patients but were not seen in the healthy controls. Swidsinski et al. (2005) examined mucosal biopsies recovered from control individuals and from both inflammatory and noninflammatory gut disorders. Biopsies were fixed in Carnoy solution before paraffin embedding, and the binding of a wide range of groupspecific 16S rRNA-targeted fluorescent probes was then quantified by microscopy. In healthy controls, or in patients suffering from irritable bowel syndrome (IBS), adherent bacteria were detected on a small proportion of the colonic mucosa, and the mean concentration of adherent bacteria was low (< 109 ml 1). In untreated IBD (CD and UC), however, more of the epithelial surface was colonized, and the mean bacterial concentration was some 100-fold higher. The mucosal biofilm in the disease state was dominated by the Bacteroides/Prevotella group, especially by B. fragilis. Gram-positive anaerobes related to E. rectale–C. coccoides represented a higher proportion of the mucosal biofilm bacteria in the noninflamed compared to the inflammatory condition. Bacteroides were also the major anaerobes found on epithelial surfaces in the large bowel by Poxton et al. (1997), in UC patients using culturing methods, as well as in individuals with noninflammatory bowel conditions. Bacteroides thetaiotaomicron was reported to be more prevalent in UC patients. The study also showed that bacteroides accounted for up to 69% of the total anaerobe counts on the gut epithelium, with B. vulgatus predominating. A more recent study using culturing and chemotaxonomic identification of mucosal bacterial isolates in nine UC patients and 10 controls confirmed that bacteroides were the most ubiquitous culturable bacteria on the gut rectal mucosa in health and disease (Macfarlane et al., 2004). Sixteen different species of bacteroides were detected in this study, with B. vulgatus, B. thetaiotaomicron, and B. fragilis being the most numerous. In contrast, using a combination of real-time PCR, and single-strand conformational polymorphism fingerprinting on mucosal biopsies from 31 active UC and 26 Crohn’s patients, and 46 noninflammatory controls, it was observed that a reduction in bacterial diversity and numbers of bacteroides and enterobacteria occurred in IBD patients, compared to the control group (Ott et al., 2004). It is uncertain whether bacteroides are directly involved in IBD, however, although UC patients have increased antibodies against anaerobic bacteria in general (Monteiro et al., 1971), particularly high antibody titers are found against bacteroides (Bamba et al., 1995; Matsuda et al., 2000; Saitoh et al., 2002; Tvede et al., 1983). Fifty-four percent of UC patients were shown to have IgG antibodies active against an outer membrane protein of B. vulgatus,
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compared to only 9% in healthy individuals (Matsuda et al., 2000), while a 100 kDA protein of Bacteroides caccae has been reported to react to a pANCA monoclonal antibody (Cohavy et al., 2000) formed in response to a neutrophil protein in patients with UC (Satsangi et al., 1998). E. coli has been implicated in the etiology of IBD, particularly adherent-invasive E. coli (AIEC) (Darfeuille-Michaud et al., 2004; Macfarlane et al., 2009b). Early reports using cultural analysis suggested that E. coli from UC patients were more adherent to buccal cells than those from healthy people, and that they occurred in higher numbers in the feces of UC patients (Burke and Axon, 1988; Chadwick, 1991; Giaffer et al., 1992). However, later studies found that E. coli occurred in lower numbers in tissue (Walmsley et al., 1998), and that there was no increase in bacterial adherence (Hartley et al., 1993; Schultsz et al., 1997). Darfeuille-Michaud et al. (1998) reported that E. coli constituted 50–100% of bacteria in chronic ileal mucosal lesions and using FISH analysis, E. coli was observed to occur in higher numbers in UC rectal biopsies than in control subjects (Mylonaki et al., 2005). In 36% of CD patients with ileal involvement, mucosal lesions were also found to be colonized by AIEC (Glasser et al., 2001; Rolhion and Darfeuille-Michaud, 2007). These AIEC were shown to be able to replicate in macrophages without causing cell death and produce high amounts of the pro-inflammatory cytokine TNF-a, which is elevated in CD, and may account for granuloma formation in these patients. Comparisons of invasive E. coli in mucosal biopsies from UC and CD patients with those from healthy controls found that 98% of invasive bacteria in CD were E. coli, while they constituted 42% of UC isolates, and only 2% of the controls. Isolated E. coli from the CD patients may be able to play a role in the breakdown of epithelial barrier function, since they were able to significantly reduce transepithelial resistance, and displace the tight junction proteins ZO-1 and E-cadherin, from the apical junction complex (Sasaki et al., 2007). Increased release of IL-8 in HT29 cell lines and higher epithelial invasion by mucosa-associated E. coli from CD compared to UC patients’ isolates has also been shown (Subramanian et al., 2008). de Hertogh et al. (2006) cloned 16S rRNA genes from microdissected mucosal biopsies from CD patients and found that E. coli could initiate and colonize lesions, although they did not examine healthy controls. Martinez-Medina et al. (2009) examined the molecular diversity of E. coli on colonic and ileal mucosae in 20 CD patients, and 28 healthy controls. The clonality of the isolates was identified by repetitive palindrome-polymerase chain reaction (REP-PCR and pulsed field gel electrophoresis). AIEC identification was done using a 407 intestinal cell line, and they also investigated the abilities of bacteria to survive and replicate in macrophages. Higher counts of E. coli were found in Crohn’s patients compared to controls, however, richness and diversity was similar in both cohorts. In contrast, the abundance, prevalence, and richness of AIEC was
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greater in CD than controls, with the B2 phylogroup being the most prevalent. An earlier study had also shown higher numbers of E. coli and the B2þD group, which has been associated with virulence, occurred on mucosal tissue from IBD patients than controls (Kotlowski et al., 2007). Baumgart et al. (2007) found that the number of E. coli detected in situ by FISH correlated with ileal disease severity, and that invasive E. coli were only detected on inflamed mucosae. In the same study, clone library analysis demonstrated an increase in E. coli sequences on the ileal mucosa in CD patients, and a reduction in a subset of the Clostridiales. Culturing of E. coli isolates revealed a novel phylogeny, and that the organisms displayed pathogenic attributes. In another study, E. coli was also implicated in Crohn’s patients with predominantly ileal involvement (Willing et al., 2009). Mucosal biopsy samples were taken at various gut sites from monozygotic twins that were discordant (n ¼ 6) or concordant (n ¼ 4) for CD. The composition of the mucosal microbiota was found to be similar along the length of the GI tract in each individual; however, CD patients with ileal involvement had higher numbers of E. coli, and lower numbers of F. prausnitzii than their healthy, or CD twin with colonic involvement. Sokol et al. (2008) observed that lower numbers of F. prausnitzii on the ileal mucosa was associated with a greater risk of postoperative recurrence of ileal CD after surgical resection, and in a previous study, it was reported that low numbers of F. prausnitzii occurred on the colonic mucosa of CD patients (Vasquez et al., 2007). DGGE profiling of ileocolonic mucosal populations of 19 CD and 15 healthy patients found that sequences for E. coli, Ruminococcus, and Clostridium spp. were more prevalent in CD patients, with the reverse being true for Faecalibacterium spp. in the healthy control group (Martinez-Medina et al., 2006). Fusobacterium varium has also been implicated in the etiology of UC. Immunohistochemical staining for F. varium showed that it was able to invade the mucosa and occurred in a greater number of UC patients (84%) compared to Crohn’s patients (16%), or control groups (3–13%) (Ohkusa et al., 2002). In addition, Western blot analysis of patient’s sera only gave specific reactions for F. varium. The diversity of fungi in mucosa-associated microbiotas was examined in another investigation (Ott et al., 2008). Mucosal tissues from 47 controls and 57 IBD patients were investigated using a combination of 18S rRNAbased DGGE, clone libraries, sequencing, and FISH. All of the mucosal tissue was reported to contain fungi-specific 18S rDNA fungal specific signatures, which accounted for 0.02% of the mucosal microbiota. A higher diversity was found in CD patients compared to the control group, however, no fungal species could be directly linked to either CD or UC. Sulfate-reducing bacteria (SRB), particularly species belonging to the genus Desulfovibrio, have been linked to the etiology of UC (Macfarlane et al., 2009b). This mainly derives from their ability to form sulfide by
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using sulfate as a terminal electron acceptor. Sulfide is toxic to intestinal cells and inhibits butyrate oxidation, thereby suppressing colonocyte energy generation resulting in cellular hyperproliferation and epithelial cell abnormalities. High numbers of SRB have been detected in fecal material in patients with UC (Loubinoux et al., 2002; Pitcher et al., 2000). In contrast, in one study lower numbers of SRB were found in feces from UC patients, however, they were found to be more metabolically active than strains isolated from healthy people (Gibson et al., 1991). Since UC can result in massive damage to the mucosa, it is of interest to determine mucosal carriage of SRB. Cultural analysis found that epithelial-associated SRB were only detected in 52% of control mucosal tissue (n ¼ 61) compared to 92% in UC (n ¼ 13), although subsequent analysis by PCR found SRB in all biopsies, and that there were no differences between both groups (Zinkevich and Beech, 2000). Fite et al. (2004) did real-time qPCR on rectal tissues, and although they detected significant levels of mucosal SRB in both healthy and UC biopsies, no differences were found between the groups. It was postulated that some defect in sulfide detoxification pathways might provide a link between SRB and UC. Sulfide disposal in humans is thought to be brought about by the enzymes mercaptopyruvate sulfur transferase (MST), sulfite oxidase, and rhodanese. Lower levels of rhodanese and MST have been found in the colonic tissue of UC patients compared to healthy people, particularly in the distal large bowel (Kong et al., 2004, 2005). Several studies used nonquantitative fingerprinting techniques such as DGGE and temporal TGGE profiles, as well as other molecular techniques to determine if there were differences in bacterial diversity in inflamed and noninflamed tissues in IBD patients. Zhang et al. (2007) used DGGE to examine the composition of lactobacilli, the Clostridium leptum subgroup and Bacteroides spp. on ulcerated and nonulcerated mucosal biopsies from 24 patients with mild to moderate IBD. While no difference was found in diversity of bacteroides, or at the different tissue locations, they found that host-specific differences occurred in the lactobacillus diversity and the C. leptum subgroup. In another study, the microbiotas of inflamed and noninflamed tissues of newly diagnosed untreated CD and UC patients, together with those of healthy individuals were examined with a combination of PCR-DGGE, pooled clone libraries, and real-time qPCR for selected bacterial species. DGGE profiles and cloning indicated that diversity was similar between the tissue sites that higher numbers of bacteria were associated with the UC mucosa than in CD tissues, and that bacteroides were more prevalent in CD (Bibiloni et al., 2006). Similarly, Vasquez et al. (2007) using a combination of temporal temperature gradient gel electrophoresis (TTGE) with FISH on inflamed and uninflamed ileal mucosae of 15 CD patients, found that bacteria occurred in the mucus layer, that no significant differences were
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evident in similarity indices for TTGE profiles between the tissue sites, and that the Bacteroidetes phylum was predominant in both inflamed (32%) and noninflamed tissues (29%). In contrast, Sepehri et al. (2007) using automated ribosomal intergenic spacer analysis (ARISA), and T-RFLP analysis, detected reductions in diversity and species richness in inflamed tissue from UC and CD patients, compared to controls and noninflamed tissue from the same patients. No variations could be attributed to disease state, and clustering analysis was able to place inflamed and noninflamed mucosae into two distinct groups. In another investigation, similarity indices and species diversities of bacteria from the ileum, right colon, left colon, and rectum of 20 patients with CD, 11 with UC, and four controls were assessed by TGGE (Lepage et al., 2005). Fingerprint profiles from the different gut locations were found to be similar (94.7% 4.0%) within individuals, in both IBD and control groups, and did not cluster with disease status. Differences were also reported in fecal and mucosal profiles of seven individuals at all four bowel sites. While scientific support for a specific transmissible agent in UC is weak, evidence for the involvement of mucosal bacteria in the disease is strong, either through inappropriate host immune responses to members of the normal microbiota (Furrie et al., 2004) or an increase in the numbers of pathogenic bacteria colonizing the epithelial surface. For example, in the study by Macfarlane et al. (2004), mucosal peptostreptococci and veillonellae were shown to be present in UC patients, but not in healthy people. These observations correlated with results obtained in an earlier study, in which the authors could only find peptostreptococci on UC rectal mucosae (Matsuda et al., 2000). While some members of this genus are known pathogens in humans (Ezaki et al., 1991), these organisms are also normal members of the fecal microbiota that do not seem to be able to colonize the healthy rectal epithelium. Higher numbers of mucosal enterococci have also been detected in rectal mucosal biofilms in some patients with active UC (Macfarlane et al., 2004), indicating that there may be a link with these bacteria and the disease. Another way in which nonpathogenic commensal species in the normal mucosal microbiota can be involved in IBD is that some organisms might occupy specific adhesion sites on the gut wall, thereby preventing the attachment of harmful bacteria. There is some indirect evidence to support this hypothesis: Marked differences have been found in protective bifidobacterial populations on the UC mucosa, in both quantitative and qualitative terms (Macfarlane et al., 2004). Compared to the situation in healthy people, bifidobacteria occur in considerably lower numbers in UC, and this was shown to be particularly true with respect to Bif. adolescentis. Although seven different species of bifidobacteria were detected in this investigation, only Bif. angulatum and Bif. bifidum were found in significant numbers in both subject groups. Low numbers of
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bifidobacteria or the absence of particular bifidobacterial species on the mucosa may be of significance in UC. Some species have well-documented immunomodulatory properties (Famularo et al., 1997), and together with lactobacilli, they are believed to make a significant contribution toward host defenses in the gut (Gill et al., 2001), through interactions with the immune system, and colonization resistance (Lu and Walker, 2001). Despite the fact that differences can be seen in some mucosal bacterial populations in IBD patients, it is uncertain as to whether these changes are directly related to disease etiology or were simply a result of inflammatory processes in the gut, where tissue damage and bleeding would affect substrate availability, and other growth conditions for bacteria on the epithelial surface. Both bifidobacteria and peptostreptococci are highly immunogenic in UC patients (Furrie et al., 2004), further supporting the notion that the presence or absence of these organisms may be linked to the disease process.
V. THERAPEUTIC MANIPULATION OF MUCOSAL BIOFILM COMMUNITIES Mucosal bacterial populations are almost certainly important in colonization resistance, and the maintenance of an intact epithelial barrier to the ingress of pathogenic organisms, and as discussed earlier, dysbiosis in these communities has been linked to several disease conditions such as BE and IBD. Many of these organisms are often found growing in biofilms, which have been shown to be more resistant to the effects of antimicrobial substances (Anwar et al., 1990), or therapeutic levels of the antibiotic may not reach the mucosal surface. Although mucosal bacteria are linked to IBD etiology, few trials that have found that there are any clinical benefits in the use of antibiotics or assessed their effects on mucosal bacterial communities. In one study, 20 patients with mild to moderate disease and high serum titers of IgG, IgM, and IgA to F. varium (Nomura et al., 2005) were randomly given triple therapy with amoxicillin, tetracycline, and metranidazole for 2 weeks or no antibiotic. Clinical and histology scores demonstrated a greater improvement in the antibiotic group compared to the controls. A significant reduction in T-RFLP polymorphism peaks, and a reduction in numbers of F. varium as measured by real-time qPCR, was reported in the antibiotic group but not in the controls. More recently, mucosal-adherent microbiotas of UC and indeterminate colitis patients who were given the antibiotics metronidazole and ciprofloxacin for 1 day and 7–14 days were compared to a nonantibiotic control group, using a range of FISH probes and the nucleic acid stain DAPI (Swidsinski et al., 2008). Concentrations of mucosal bacteria in the antibiotic-treated groups were also assessed up to
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36 weeks after cessation of the antibiotics. Total numbers of mucosal bacteria were reported to be significantly decreased in both antibiotic treatment periods compared to the controls; however, a marked increase in mucosal bacteria occurred 1 week following cessation of antibiotic therapy. It was noted in the study that although mucosal bacteria could be visualized with the DNA stain in the antibiotic-treated patients, the composition of mucosal microbiotas could not be accurately determined using the FISH probes, which may be due to a reduction in metabolic activities (ribosome formation) and numbers of bacterial targets brought about by antibiotic therapy. Due to limitations associated with antibiotic use, there is increasing interest in the use of functional food such as probiotics, prebiotics, and synbiotics to improve species composition, and gut barrier function by restoring a more beneficial microbial composition in the gut (Macfarlane et al., 2009b; O’May and Macfarlane, 2005; Steed et al., 2008). Probiotic bacteria are live microorganisms which when introduced in sufficient amounts confer a health benefit on the host (FAO/WHO, 2001). Lactobacilli and bifidobacteria are the main probiotic bacteria probiotics used in humans, but several organisms including E. coli, Bacillus subtilis, and Saccharomyces boulardii have also been tested. Adhesion is one of a range of beneficial traits attributed with optimal probiotic efficiency. However, while studies have shown that probiotics can adhere to mucosal surfaces, to date, the majority of clinical investigations has concentrated on changes in fecal community structure and has not assessed the effect of probiotics on mucosal microcosms. Certain lactobacilli used as probiotics have been shown to colonize the mucosal surface, and to displace other organisms. Analysis of intestinal biopsies showed that 19 test strains of lactobacilli fed to healthy volunteers in fermented oatmeal soup colonized jejunal and rectal mucosae ( Johansson et al., 1993). High numbers of adherent lactobacilli were recovered 11 days after cessation of the lactobacillus feeding, while clostridial numbers were shown to decrease 10- to 100-fold in some volunteers. Total anaerobes and enterobacteria were reduced in rectal tissue, with Lactobacillus plantarum being the predominant adherent species. Prebiotics were originally defined as non-digestable food ingredients that beneficially affect the host by selectively stimulating the growth and/ or activities of one or a limited number of bacteria in the colon, thereby improving host health (Gibson and Roberfroid, 1995). The principal prebiotics that have been studied in vitro and in vivo are inulins, fructooligosaccharides (FOS), and galacto-oligosaccharides (GOS). Prebiotics such as inulin and FOS are found naturally occurring in plants such as onions, leek, garlic, and Jerusalem artichokes or can be synthesized industrially from chicory roots. Human milk was one of the earliest sources of GOS and the high prevalence of bifidobacteria in breast fed infants is thought to be due to their ability to use GOS and other milk
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oligosaccharides. GOS is produced from lactose in transgalactosylation reactions by microbial b-galactosidases and then used as a functional food ingredient. Several studies have shown that prebiotics can be used to improve host health, and to increase numbers of fecal bifidobacteria and lactobacilli (reviewed in Macfarlane et al., 2008). Studies in gnotobiotic rats have found that feeding inulin and oligofructose can alter the mucosal architecture, increase mucin production by goblet cells, and increase levels of mucosal bifidobacteria, which may aid in improving the intestinal barrier (Kleessen et al., 2003). In the human feeding study carried out by Langlands et al. (2004), a prebiotic mixture composed of 7.5 g inulin and 7.5 g FOS was fed to 14 patients for 2 weeks prior to colonoscopy. Mucosal microbiotas of the proximal and distal colons, together with those from a control group not fed prebiotics (15 patients) were analyzed by culture and chemotaxonomic analysis. Results showed that the prebiotic increased numbers of bifidobacteria and eubacteria more than 10-fold on the gut mucosa, demonstrating that prebiotic dietary manipulation could affect mucosal microbial communities in the large gut. No major differences were observed in levels of total bacteria, clostridia, bacteroides, enterobacteria, and lactobacilli in the study. There was, however, a significance increase in eubacteria, in addition to the bifidobacteria, which is probably explained by metabolic cross-feeding, where lactate produced by bifidobacteria was utilized by the eubacteria, leading to proliferation of these organisms. As well as being an important fuel for the colonic epithelium, butyrate has anti-inflammatory properties and has been shown to increase the expression of tight junction proteins and reduce intestinal epithelial permeability (Hamer et al., 2008). Cross-feeding of bifidobacteria, which do not form butyrate, with butyrate-producing Roseburia sp., Anaerostipes caccae, and Eubacterium hallii has been shown to occur in in vitro coculture experiments in which the roseburia and eubacterium were able to assimilate hydrolysis products formed by bifidobacteria growing on FOS (Belenguer et al., 2006; Bourriaud et al., 2005). High levels of butyrate have been shown to be produced in vitro by the utilization of lactic acid by butyrate-producing bacteria belonging to clostridial cluster XIVa (Louis and Flint, 2009). In a recent in vitro experiment, the addition of FOS to batch culture fomenters was shown to increase levels of F. prausnitzii, a butyrate-producing organism, which has been reported to occur in lower numbers in fecal and mucosal samples from CD patients (Frank et al., 2007; Martinez-Medina et al., 2006; Sokol et al., 2009). F. prausnitzii has also recently been shown to be stimulated by the prebiotic inulin in coculture with Bif. adolescentis in batch culture experiments (RamirezFarias et al., 2009). Since IBD patients often have low numbers of some beneficial bacteria, the addition of probiotics to increase numbers of
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health-promoting microorganisms or prebiotics to increase indigenous bifidobacteria or butyrate-producing bacteria may provide added benefit in the treatment of IBD (Gionchetti et al., 2000; Van Immerseel et al., 2010). So far, the majority of clinical trials involving functional foods have concentrated on analyzing luminal bacterial communities, and only a few has investigated the effect on mucosal intestinal populations. The use of a synbiotic which is a synergistic combination of a prebiotic and probiotic may be beneficial (Macfarlane, 2006). The rationale for employing a synbiotic is that the prebiotic, if chosen carefully, can enhance growth of the probiotic component in the gut, giving it a competitive advantage, while also stimulating the growth of autochthonous microorganisms (Macfarlane et al., 2008). In one study, a double-blind randomized control trial was done using 18 patients with active UC, who were fed either a placebo or a synbiotic composed of 2 1011 of the probiotic Bif. longum and 12 g of the prebiotic Synergy 1 (a mixture of oligofructose and inulin) for 4 weeks (Furrie et al., 2005). The Bif. longum had been isolated from a healthy volunteer in a previous UC study (Macfarlane et al., 2004) and had been found to be reduce synthesis of the pro-inflammatory cytokines TNF-a and IL-1a when incubated with the HT-29 human cell line. Unprepared samples taken from the rectal mucosa were used to avoid loss of mucosal bacteria. Using real-time qPCR, the synbiotic was shown to significantly increase bifidobacterial numbers by 42-fold on the rectal mucosa compared to the healthy controls and to reduce TNF-a, IL-1a to normal levels. In addition, a significant reduction in the inducible antimicrobial peptides human beta human defensins (hBDs) 2, 3, and 4 were detected. These hBD are markers of mucosal inflammation in UC. Histology showed that regeneration of the epithelium and a decrease in inflammation also occurred in patients receiving the synbiotic.
VI. MODELING STUDIES The inaccessibility of many sites in the gastrointestinal tract has led to the development of several in vitro methods to determine interactions of intestinal luminal communities. To date, only a few studies have used these techniques to obtain information on mucosal-associated microbiotas in the gastrointestinal tract. These include simple methods utilizing mucin coated surfaces (Rinkinen et al., 2003; Van den Abbeele et al., 2009), to more elaborate in vitro batch and continuous culture fermentation systems, that model various regions of the gut (Macfarlane and Macfarlane, 2007). Macfarlane et al. (2005b) employed a two-stage continuous culture model to study mucosal-associated bacteria and mucin degradation, under nutrient-rich and nutrient-depleted conditions, representing the proximal and distal colons. The model was
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inoculated with fecal bacteria to simulate colonic populations. The establishment of mucosal communities on mucin gels placed in the culture vessels was determined by selective culture, and CLSM. The mucin gels were also analyzed for the presence of residual mucin sugars. Bacterial communities were shown to colonize the gels, which were similar in composition to those in the planktonic (luminal) phase. Gel surfaces were rapidly colonized by a range of intestinal bacteria, with the main groups being bacteroides, clostridia, and bifidobacteria. Differences were seen between the two fermentation vessels, with bifidobacteria, for example, colonizing only in the nutrient-poor chemostat (representing the distal colon). Similarly, B. caccae only colonized gels in this fermenter, while B. distasonis only colonized the nutrient-rich culture vessel, demonstrating again that luminal factors influence the composition of biofilm microbiotas. The use of CLSM, with FISH and 16S rRNA probes demonstrated that bifidobacteria were widely dispersed through the mucin, while bacteroides mainly occurred as microcolonies, and there was evidence of co-localization of enterobacteria and bacteroides on the mucin gels. Measurement of residual carbohydrates in the vessels and mucin gels showed that the majority of the constituent oligosaccharides were utilized by both the luminal and mucin biofilm communities (Table 4.2). Another experimental approach has been to suspend insoluble substrates including porcine-gastric mucin within a porous nylon mesh in continuous culture vessels inoculated with fecal bacteria. The vessels were TABLE 4.2 Utilization of mucin oligosaccharides by luminal bacterial populations and biofilm communities on mucin gels in a two-stage colonic model systema % utilization Vessel 1b
a b c d e
Vessel 2c
Oligosaccharide
Luminald
Mucin gele
Luminald
Mucin gele
N-Acetyl neuraminic acid N-Acetyl galactosamine N-Acetyl glucosamine Fucose Galactose Mannose
44 100 84 77 74 100
71 7 46 46 31 100
75 100 86 80 75 100
82 55 60 58 38 70
Adapted from Macfarlane et al. (2005b). Vessel 1 represents the proximal colon. Vessel 2 represents the distal colon. Values indicate percent utilization of mucin sugars compared to the initial feed medium. Values indicate carbohydrate utilization after colonization of the mucin gels in the vessels for 48 h.
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inoculated with four different fecal samples, and communities adherent to the mucin surface identified by cloning, PCR-amplified 16S rRNA gene sequences analysis, and FISH. Interindividual differences were observed in colonization of the mucin substrate, with sequences for Bif. bifidum and uncultured clostridial cluster XIVa bacteria related to Ruminococcus lactaris being the most common (McWilliam Leitch et al., 2006).
VII. CONCLUSIONS Many of the methods used to study the mucosal populations are destructive and nonquantitative and do not produce useful information on the structural composition of the communities or bacterial interactions. To date, no consistent approach has been used for sampling or the analysis of mucosal communities, which makes comparison between studies difficult. Nevertheless, we are beginning to understand the composition and some of the metabolic functions of mucosal biofilm populations in the intestinal tract, and there is increasing evidence that a dysbiosis in mucosal populations is involved in gastrointestinal diseases such as BE and IBD. However, we still know very little about their role in the disease process, the physiological importance of these mucosal communities to the host, or their ecological significance. Although a number of genes and cellular structures concerned with biofilm formation have been identified, their role in the colonization of intestinal surfaces is not yet clear. More effort needs to be directed at understanding biofilm formation by commensal gut bacteria, as well as the microbiological and environmental factors that determine mucosal colonization. The use of functional foods to modulate the composition of mucosal communities shows promise, and more information should be obtained from future studies on the effects of dietary interventions on intestinal mucosal communities.
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INDEX A Acyl homoserine lactones (AHLs), 5 Adherent-invasive E. coli (AIEC), 126–127 Ammonia monooxygenase (AMO), 43 Ammonia oxidizer community AMO, 43 amoABC, 43 amoA gene, 42–43, 47–48 AOA, 42–43 AOB, 42–43 HAO, 44 hao gene, 42–43, 44 nirK gene, 44 norB gene, 44 Ammonia-oxidizing bacteria (AOB), 42–43, 49 amoABC operon, 43 amoA gene, 42–43, 47–48 Archaeal ammonia oxidizer (AOA), 42–43, 48–49 Automated ribosomal intergenic spacer analysis (ARISA), 128–129 Autotrophic nitrification ammonia oxidation, 38 nitrifier denitrification, 38–39 B Bacteriolytic myxobacteria, 8 Barrett’s esophagus (BE), 114 Biofilm, 16–17. See also Mucosal biofilm communities, human intestinal tract; Outer membrane vesicle (OMV) Biophotolytic H2 production, 73 Bioprospecting, hydrogen production, 80 C Cellulolytic myxobacteria, 8 Chemodenitrification, 42 Chlamydomonas reinhardtii, hydrogen production
anoxic conditions culturing conditions optimizimation, 91 inducible promoters, PSII activity regulation, 91 O2 levels reduction, 92 photosynthesis, mutants altered rates, 91–92 Rubisco mutants, 92 sulfur starvation improvement, 90 auxiliary electron transport pathways cyclic electron flow, 83–87 Mehler reaction and chlororespiration, 82–83 biophotolytic production, 73 fermentative pathways acetyl-CoA, 88–89 hydrogenase reductant, 87 PFL1 knockout, 89 pyruvate metabolism, 88 genetic tools, 79 hydrogenase-ferredoxin interactions, 81 hydrogen conversion efficiency, 78 mutations affects, 84 O2-tolerant hydrogenase bioprospecting, 80 [FeFe]-hydrogenase, 79–81 intelligent design, 80 random mutagenesis, 80 photosynthetic apparatus modification light-harvesting antennae, 89–90 photosynthetic rates, 90 reductant sources PSII-dependent pathways, 74 PSII-independent pathways, 74–75 schematic representation, 75 thylakoid proton gradient distruption, 81–82 wild-type strains choice, 78 Codenitrification, 41 Crohn’s disease (CD) AEIC colonization, 126–127 DGGE, 128–129
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Crohn’s disease (CD) (cont.) E. coli, 126–127 Faecalibacterium spp, 127 fungi diversity, 127 TGGE, 128–129 Cyclic electron flow (CEF) antimycin A-insensitive pathway, 83 antimycin A-sensitive pathway, 83 efficacy, 83 mutant screeening, 83, 84 state transitions, 83 targeted gene knockout, 83–87 D Denaturing gradient gel electrophoresis (DGGE), 118, 128–129 Denitrification, 40–41 bacteria, 44 denitrifying microbiota diversity, 51–52 exogenous signal, 52–53 functional group, 52–53 genotype, 54–55 nirK gene, 53–54, 55 nirS gene, 53–54 nosZ gene, 53 size, 49–50 fungi, 44–45 marker gene napA, 45 narGH, 45 nirK, 44, 45–46, 47–48 nirS, 45–46 norB, 44, 45–46 nosZ, 45–46 E Elasticotaxis, 15 F Fluorescent in situ hybridization (FISH), 121, 126–127 Fructooligosaccharides (FOS), 131–132 Fruiting body, 10–11 Functional foods, 131, 133 G Galacto-oligosaccharides (GOS), 131–132 Green algae hydrogen production. See Solar-driven hydrogen production, green algae
H hao, 42–43, 44 Heterotrophic nitrification, 39–40 Hole-in-the-pipe model, 46–47 Human beta human defensins (hBDs), 133 Human intestinal tract, mucosal biofilm communities. See Mucosal biofilm communities, human intestinal tract Hydrogen production, algal. See Solardriven hydrogen production, green algae Hydroxylamine oxidoreductase (HAO), 44 Hypothesized model, N2O emission, 49, 50 I Intestinal mucosal biofilm communities. See Mucosal biofilm communities, human intestinal tract L Laughing gas. See Nitrous oxide (N2O) production M Mercaptopyruvate sulfur transferase (MST), 127–128 Mucosal biofilm communities, human intestinal tract bacterial hydrolytic enzymes, 112–113 colonization, upper gastrointestinal (see Upper gastrointestinal tract bacterial colonization) gastrointestinal illness and gut health, 112 inflammatory bowel disease adherent bacteria, 125 adherent-invasive E. coli, 126–127 antibodies, 125–126 automated ribosomal intergenic spacer analysis, 128–129 bacteroides, 125–126 bifidobacteria, 129–130 clone library analysis, 126–127 dysbiosis, 123–124 E. coli, 126–127 fungi diversity, 127 Fusobacterium prausnitzii, 127 Fusobacterium varium, 127 microcolonies, 124 mucosal bacterial isolates, 125–126
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nonquantitative fingerprinting techniques, 128–129 pathological response, 123–124 peptostreptococci and veillonellae, 129 rectal biopsies, 125, 126–127 sulfate-reducing bacteria, 127–128 in vitro methods, 133–134 large bowel bacterial isolates, 122 bifidobacterial identification, 122–123 Clostridium cluster and Bacteroidetes, 119 cultural and molecular analyses, 118 DGGE, 118 fluorescent in situ hybridization, 121, 122 intestinal bacterial populations, 120 microbial diversity, 119 quantitative real-time PCR analysis, 121, 123 16S rRNA, 118–119 mucin oligosaccharides, luminal bacterial populations, 134 mucin substrate, 134–135 therapeutic manipulation antibiotic therapy, 130–131 butyrate, 132–133 culture and chemotaxonomic analysis, 132 functional foods, 131 inulin and oligofructose, 132 prebiotics, 131–132 probiotics, 131 synbiotics, 133 two-stage continuous culture model, 133–134, 134 Myxobacteria characteristics, 8 genome sequence, 8 intercellular signals, 16 motility, 15 multicellular development C-signaling, 13–14 myxospore, cheating phenotypes, 14–15 regulation, signaling pathway, 14 starvation, amino acid deprivation, 13–14 predation degradative enzyme, 12–13 predatory efficiency, 13 protein secretion, 16
secondary metabolites anticancer activity, 10 antineoplastic drug, 8–10 rare bacterial and large hybrid metabolite production, 10 structure and roles, 9 sociobiology fruiting body, 10–11 M. xanthus, life-cycle, 11–12 vegetative state, 10–11 types, 8 vesicle Myxococcus xanthus. See Myxococcus xanthus outer membrane vesicle (see Outer membrane vesicle) Myxococcus xanthus genome sequence, 8 life-cycle, 11 motility, 15, 22 multicellular development, 13–15 outer membrane vesicle biofilm, 18–19 protein secretion, 18 size, 17 starvation, 17–18 predation, 12–13 replication, 8 secretion of protein, 16 N napA gene, 45 narGH gene, 45 nirK gene, 44, 45–46, 47–48, 53–54 nirS gene, 45–46, 53–54 Nitrification autotrophic nitrification ammonia oxidation, 38 nitrifier denitrification, 38–39 heterotrophic nitrification, 39–40 natural and managed soils, 37–38 nitrifier community ammonia oxidation, 48–49 AOA, 48–49 AOB, 49 diversity, 51–52 environmental condition, 49 hypothesized model, 49, 50 phylogenetic information, 48–49 size, 55–56 primary sources, 37
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Index
Nitrous oxide (N2O) production ammonia oxidizer community (see Ammonia oxidizer community) chemodenitrification, 42 codenitrification, 41 denitrification, 40–41. see also Denitrification) dissimilatory nitrate reduction, 41 hole-in-the-pipe model, 46–47 nitrate assimilation, 41 nitrification (see Nitrification) nitrogen cycle, 38 significance atmospheric concentration, 36–37 global warming, 35–36 natural sources, 36–37 norB gene, 44, 45–46 nosZ gene, 45–46, 53 O Outer membrane vesicle (OMV) applications, 7–8 biomolecule secretion, 3–4 cargo of, 22–23 in gram-negative bacteria, 2–3 motility, 22 M. xanthus biofilm, 18–19 protein secretion, 18 size, 17 starvation, 17–18 natural roles biofilm formation, 4 DNA transformation, 5 lytic enzymes and antibacterial metabolites, 4–5 signaling, 5 vesicle-mediated transport, 4, 5–7 predation lytic activity, 19–20 lytic factor, 20 spatial aspects of, 21 vesicle formation, 3 P Photobioreactors (PBR) artificial systems, 96–97 biohydrogen production, 93–94 flat-plate reactors, 96 geometries, 95 open and enclosed system, 93
stirred-tank reactors, 94 tubular reactors, 94–96 vertical-column reactors, 94 Photosynthetic electron transport (PET) chain, 74 Photosystem II (PSII) pathways, hydrogen production dependent, 74 independent, 74–75 sulfur starvation, 77 Photovoltaic technologies, 73 Prebiotics, 131–132 Probiotics, 131 Pseudomonas quinolone signal (PQS), 5 Pyruvate:ferredoxin oxidoreductase (PFOR), 74–75 Q Quorum signals, 5 R Random mutagenesis, 80 Rubisco mutants, 92 S Secondary metabolites, myxobacteria anticancer activity, 10 antineoplastic drug, 8–10 rare bacterial and large hybrid metabolite production, 10 structure and roles, 9 Solar-driven hydrogen production, green algae biophotolytic production, 73 Chlamydomonas reinhardtii, 74 anoxic conditions, 90–92 auxiliary electron transport pathway, 82–87 fermentative pathway, 87–89 genetic tools, 79 hydrogenase-ferredoxin interactions, 81 mutations affects, 84 O2-tolerant hydrogenase, 79–81 photosynthetic apparatus modification, 89–90 pyruvate metabolism, 88 reductant sources, 74–75 thylakoid proton gradient distruption, 81–82 wild-type strain choice, 78
149
Index
CO2 emissions, 72 Cyanothecae, 98 vs. fossil fuels, 97–98 global energy consumption, 72 H2 metabolism, 74 hydrogen economy, 72–73 photobioreactors (see Photobioreactors (PBR)) sulfur depletion (see Sulfur depletion, hydrogen production) Sulfate-reducing bacteria (SRB), 127–128 Sulfur depletion, hydrogen production aerobic phases, 75–76 ATP and NADH formation, 76 O2 consumption phases, 75–76 PSII contribution, sulfur starvation, 77 starch and acetate role, 77–78 Synbiotics, 133 T Temperature gradient gel electrophoresis (TGGE), 128–129 Terminal restriction fragment length polymorphism (T-RFLP), 117–118
U Ulcerative colitis (UC) AEIC colonization, 126–127 bacteroides, 125–126 bifidobacteria, 129–130 DGGE, 128–129 E. coli, 126–127 enterococci, 129 peptostreptococci, 129–130 sulfate-reducing bacteria, 127–128 TGGE, 128–129 Upper gastrointestinal tract bacterial colonization esophageal mucosae Barrett’s esophagus, 114 culture-independent molecular analyses, 116 esophageal aspirates, 113–114 live/dead staining, 115 nitrate reducing veillonellas, 114–115 gastric microbiota gastric biopsies, 117 H. pylori-associated gastritis, 116–117 T-RFLP analysis, 117–118
CONTENTS OF PREVIOUS VOLUMES Volume 40 Microbial Cellulases: Protein Architecture, Molecular Properties, and Biosynthesis Ajay Singh and Kiyoshi Hayashi Factors Inhibiting and Stimulating Bacterial Growth in Milk: An Historical Perspective D. K. O’Toole Challenges in Commercial Biotechnology. Part I. Product, Process, and Market Discovery Alesˇ Prokop Challenges in Commercial Biotechnology. Part II. Product, Process, and Market Development Alesˇ Prokop Effects of Genetically Engineered Microorganisms on Microbial Populations and Processes in Natural Habitats Jack D. Doyle, Guenther Stotzky, Gwendolyn McClung, and Charles W. Hendricks Detection, Isolation, and Stability of Megaplasmid-Encoded Chloroaromatic Herbicide-Degrading Genes within Pseudomonas Species Douglas J. Cork and Amjad Khalil
Improving Productivity of Heterologous Proteins in Recombinant Saccharomyces cerevisiae Fermentations Amit Vasavada Manipulations of Catabolic Genes for the Degradation and Detoxification of Xenobiotics Rup Lal, Sukanya Lal, P. S. Dhanaraj, and D. M. Saxena Aqueous Two-Phase Extraction for Downstream Processing of Enzymes/Proteins K. S. M. S. Raghava Rao, N. K. Rastogi, M. K. Gowthaman, and N. G. Karanth Biotechnological Potentials of Anoxygenic Phototrophic Bacteria. Part I. Production of Single Cell Protein, Vitamins, Ubiquinones, Hormones, and Enzymes and Use in Waste Treatment Ch. Sasikala and Ch. V. Ramana Biotechnological Potentials of Anoxygenic Phototrophic Bacteria. Part II. Biopolyesters, Biopesticide, Biofuel, and Biofertilizer Ch. Sasikala and Ch. V. Ramana Index
Volume 42
Volume 41
The Insecticidal Proteins of Bacillus thuringiensis P. Ananda Kumar, R. P. Sharma, and V. S. Malik
Microbial Oxidation of Unsaturated Fatty Acids Ching T. Hou
Microbiological Production of Lactic Acid John H. Litchfield
Index
151
152
Contents of Previous Volumes
Biodegradable Polyesters Ch. Sasikala The Utility of Strains of Morphological Group II Bacillus Samuel Singer
Investigation of the Carbon- and Sulfur-Oxidizing Capabilities of Microorganisms by Active-Site Modeling Herbert L. Holland
Phytase Rudy J. Wodzinski and A. H. J. Ullah
Microbial Synthesis of D-Ribose: Metabolic Deregulation and Fermentation Process P. de Wulf and E. J. Vandamme
Index
Production and Application of Tannin Acyl Hydrolase: State of the Art P. K. Lekha and B. K. Lonsane
Volume 43 Production of Acetic Acid by Clostridium thermoaceticum Munir Cheryan, Sarad Parekh, Minish Shah, and Kusuma Witjitra Contact Lenses, Disinfectants, and Acanthamoeba Keratitis Donald G. Ahearn and Manal M. Gabriel Marine Microorganisms as a Source of New Natural Products V. S. Bernan, M. Greenstein, and W. M. Maiese Stereoselective Biotransformations in Synthesis of Some Pharmaceutical Intermediates Ramesh N. Patel Microbial Xylanolytic Enzyme System: Properties and Applications Pratima Bajpai Oleaginous Microorganisms: An Assessment of the Potential Jacek Leman Index
Volume 44 Biologically Active Fungal Metabolites Cedric Pearce Old and New Synthetic Capacities of Baker’s Yeast P. D’Arrigo, G. Pedrocchi-Fantoni, and S. Servi
Ethanol Production from Agricultural Biomass Substrates Rodney J. Bothast and Badal C. Saha Thermal Processing of Foods, A Retrospective, Part I: Uncertainties in Thermal Processing and Statistical Analysis M. N. Ramesh, S. G. Prapulla, M. A. Kumar, and M. Mahadevaiah Thermal Processing of Foods, A Retrospective, Part II: On-Line Methods for Ensuring Commercial Sterility M. N. Ramesh, M. A. Kumar, S. G. Prapulla, and M. Mahadevaiah Index
Volume 45 One Gene to Whole Pathway: The Role of Norsolorinic Acid in Aflatoxin Research J. W. Bennett, P.-K. Chang, and D. Bhatnagar Formation of Flavor Compounds in Cheese P. F. Fox and J. M. Wallace The Role of Microorganisms in Soy Sauce Production Desmond K. O’Toole Gene Transfer Among Bacteria in Natural Environments Xiaoming Yin and G. Stotzky
Contents of Previous Volumes
Breathing Manganese and Iron: Solid-State Respiration Kenneth H. Nealson and Brenda Little
Microbial Production of Oligosaccharides: A Review S. G. Prapulla, V. Subhaprada, and N. G. Karanth
Enzymatic Deinking Pratima Bajpai
Index
Microbial Production of Docosahexaenoic Acid (DHA, C22:6) Ajay Singh and Owen P. Word Index
Volume 46 Cumulative Subject Index
Volume 47 Seeing Red: The Story of Prodigiosin J. W. Bennett and Ronald Bentley Microbial/Enzymatic Synthesis of Chiral Drug Intermediates Ramesh N. Patel Recent Developments in the Molecular Genetics of the Erythromycin-Producing Organism Saccharopolyspora erythraea Thomas J. Vanden Boom Bioactive Products from Streptomyces Vladisalv Behal Advances in Phytase Research Edward J. Mullaney, Catherine B. Daly, and Abdul H. J. Ullah Biotransformation of Unsaturated Fatty Acids of industrial Products Ching T. Hou Ethanol and Thermotolerance in the Bioconversion of Xylose by Yeasts Thomas W. Jeffries and Yong-Su Jin Microbial Degradation of the Pesticide Lindane (g-Hexachlorocyclohexane) Brajesh Kumar Singh, Ramesh Chander Kuhad, Ajay Singh, K. K. Tripathi, and P. K. Ghosh
153
Volume 48 Biodegredation of Nitro-Substituted Explosives by White-Rot Fungi: A Mechanistic Approach Benoit Van Aken and Spiros N. Agathos Microbial Degredation of Pollutants in Pulp Mill Effluents Pratima Bajpai Bioremediation Technologies for Metal-Containing Wastewaters Using Metabolically Active Microorganisms Thomas Pumpel and Kishorel M. Paknikar The Role of Microorganisms in Ecological Risk Assessment of Hydrophobic Organic Contaminants in Soils C. J. A. MacLeod, A. W. J. Morriss, and K. T. Semple The Development of Fungi: A New Concept Introduced By Anton de Bary Gerhart Drews Bartolomeo Gosio, 1863–1944: An Appreciation Ronald Bentley Index
Volume 49 Biodegredation of Explosives Susan J. Rosser, Amrik Basran, Emmal R. Travis, Christopher E. French, and Neil C. Bruce Biodiversity of Acidophilic Prokaryotes Kevin B. Hallberg and D. Barrie Johnson
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Contents of Previous Volumes
Laboratory Birproduction of Paralytic Shellfish Toxins in Dinoflagellates Dennis P. H. Hsieh, Dazhi Wang, and Garry H. Chang Metal Toxicity in Yeasts and the Role of Oxidative Stress S. V. Avery Foodbourne Microbial Pathogens and the Food Research Institute M. Ellin Doyle and Michael W. Pariza Alexander Flemin and the Discovery of Penicillin J. W. Bennett and King-Thom Chung Index
Volume 50 Paleobiology of the Archean Sherry L. Cady A Comparative Genomics Approach for Studying Ancestral Proteins and Evolution Ping Liang and Monica Riley Chromosome Packaging by Archaeal Histones Kathleen Sandman and John N. Reeve DNA Recombination and Repair in the Archaea Erica M. Seitz, Cynthia A. Haseltine, and Stephen C. Kowalczykowski Basal and Regulated Transcription in Archaea Jo¨rg Soppa Protein Folding and Molecular Chaperones in Archaea Michel R. Leroux Archaeal Proteasomes: Proteolytic Nanocompartments of the Cell Julie A. Maupin-Furlow, Steven J. Kaczowka, Mark S. Ou, and Heather L. Wilson Archaeal Catabolite Repression: A Gene Regulatory Paradigm Elisabetta Bini and Paul Blum Index
Volume 51 The Biochemistry and Molecular Biology of Lipid Accumulation in Oleaginous Microorganisms Colin Ratledge and James P. Wynn Bioethanol Technology: Developments and Perspectives Owen P. Ward and Ajay Singh Progress of Aspergillus oryzae Genomics Masayuki Machida Transmission Genetics of Microbotryum violaceum (Ustilago violacea): A Case History E. D. Garber and M. Ruddat Molecular Biology of the Koji Molds Katsuhiko Kitamoto Noninvasive Methods for the Investigation of Organisms at Low Oxygen Levels David Lloyd The Development of the Penicillin Production Process in Delft, The Netherlands, During World War II Under Nazi Occupation Marlene Burns and Piet W. M. van Dijck Genomics for Applied Microbiology William C. Nierman and Karen E. Nelson Index
Volume 52 Soil-Based Gene Discovery: A New Technology to Accelerate and Broaden Biocatalytic Applications Kevin A. Gray, Toby H. Richardson, Dan E. Robertson, Paul E. Swanson, and Mani V. Subramanian The Potential of Site-Specific Recombinases as Novel Reporters in Whole-Cell Biosensors of Pollution Paul Hinde, Jane Meadows, Jon Saunders, and Clive Edwards
Contents of Previous Volumes
Microbial Phosphate Removal and Polyphosphate Production from Wastewaters John W. McGrath and John P. Quinn Biosurfactants: Evolution and Diversity in Bacteria Raina M. Maier Comparative Biology of Mesophilic and Thermophilic Nitrile Hydratases Don A. Cowan, Rory A. Cameron, and Tsepo L. Tsekoa From Enzyme Adaptation to Gene Regulation William C. Summers Acid Resistance in Escherichia coli Hope T. Richard and John W. Foster Iron Chelation in Chemotherapy Eugene D. Weinberg Angular Leaf Spot: A Disease Caused by the Fungus Phaeoisariopsis griseola (Sacc.) Ferraris on Phaseolus vulgaris L. Sebastian Stenglein, L. Daniel Ploper, Oscar Vizgarra, and Pedro Balatti The Fungal Genetics Stock Center: From Molds to Molecules Kevin McCluskey Adaptation by Phase Variation in Pathogenic Bacteria Laurence Salau¨n, Lori A. S. Snyder, and Nigel J. Saunders What Is an Antibiotic? Revisited Ronald Bentley and J. W. Bennett An Alternative View of the Early History of Microbiology Milton Wainwright The Delft School of Microbiology, from the Nineteenth to the Twenty-first Century Lesley A. Robertson
155
Anaerobic Dehalogenation of Organohalide Contaminants in the Marine Environment Max M. Ha¨ggblom, Young-Boem Ahn, Donna E. Fennell, Lee J. Kerkhof, and Sung-Keun Rhee Biotechnological Application of Metal-Reducing Microorganisms Jonathan R. Lloyd, Derek R. Lovley, and Lynne E. Macaskie Determinants of Freeze Tolerance in Microorganisms, Physiological Importance, and Biotechnological Applications An Tanghe, Patrick Van Dijck, and Johan M. Thevelein Fungal Osmotolerance P. Hooley, D. A. Fincham, M. P. Whitehead, and N. J. W. Clipson Mycotoxin Research in South Africa M. F. Dutton Electrophoretic Karyotype Analysis in Fungi J. Beadle, M. Wright, L. McNeely, and J. W. Bennett Tissue Infection and Site-Specific Gene Expression in Candida albicans Chantal Fradin and Bernard Hube LuxS and Autoinducer-2: Their Contribution to Quorum Sensing and Metabolism in Bacteria Klaus Winzer, Kim R. Hardie, and Paul Williams Microbiological Contributions to the Search of Extraterrestrial Life Brendlyn D. Faison Index
Volume 54
Volume 53
Metarhizium spp.: Cosmopolitan InsectPathogenic Fungi – Mycological Aspects Donald W. Roberts and Raymond J. St. Leger
Biodegradation of Organic Pollutants in the Rhizosphere Liz J. Shaw and Richard G. Burns
Molecular Biology of the Burkholderia cepacia Complex Jimmy S. H. Tsang
Index
156
Contents of Previous Volumes
Non-Culturable Bacteria in Complex Commensal Populations William G. Wade l Red-Mediated Genetic Manipulation of Antibiotic-Producing Streptomyces Bertolt Gust, Govind Chandra, Dagmara Jakimowicz, Tian Yuqing, Celia J. Bruton, and Keith F. Chater Colicins and Microcins: The Next Generation Antimicrobials Osnat Gillor, Benjamin C. Kirkup, and Margaret A. Riley Mannose-Binding Quinone Glycoside, MBQ: Potential Utility and Action Mechanism Yasuhiro Igarashi and Toshikazu Oki Protozoan Grazing of Freshwater Biofilms Jacqueline Dawn Parry Metals in Yeast Fermentation Processes Graeme M. Walker Interactions between Lactobacilli and Antibiotic-Associated Diarrhea Paul Naaber and Marika Mikelsaar Bacterial Diversity in the Human Gut Sandra MacFarlane and George T. MacFarlane Interpreting the Host-Pathogen Dialogue Through Microarrays Brian K. Coombes, Philip R. Hardwidge, and B. Brett Finlay The Inactivation of Microbes by Sunlight: Solar Disinfection as a Water Treatment Process Robert H. Reed Index
Volume 55 Fungi and the Indoor Environment: Their Impact on Human Health
J. D. Cooley, W. C. Wong, C. A. Jumper, and D. C. Straus Fungal Contamination as a Major Contributor to Sick Building Syndrome De-Wei LI and Chin S. Yang Indoor Moulds and Their Associations with Air Distribution Systems Donald G. Ahearn, Daniel L. Price, Robert Simmons, Judith Noble-Wang, and Sidney A. Crow, Jr. Microbial Cell Wall Agents and Sick Building Syndrome Ragnar Rylander The Role of Stachybotrys in the Phenomenon Known as Sick Building Syndrome Eeva-Liisa Hintikka Moisture-Problem Buildings with Molds Causing Work-Related Diseases Kari Reijula Possible Role of Fungal Hemolysins in Sick Building Syndrome Stephen J. Vesper and Mary Jo Vesper The Roles of Penicillium and Aspergillus in Sick Building Syndrome (SBS) Christopher J. Schwab and David C. Straus Pulmonary Effects of Stachybotrys chartarum in Animal Studies Iwona Yike and Dorr G. Dearborn Toxic Mold Syndrome Michael B. Levy and Jordan N. Fink Fungal Hypersensitivity: Pathophysiology, Diagnosis, Therapy Vincent A. Marinkovich Indoor Molds and Asthma in Adults Maritta S. Jaakkola and Jouni J. K. Jaakkola Role of Molds and Mycotoxins in Being Sick in Buildings: Neurobehavioral and Pulmonary Impairment Kaye H. Kilburn
Contents of Previous Volumes
The Diagnosis of Cognitive Impairment Associated with Exposure to Mold Wayne A. Gordon and Joshua B. Cantor Mold and Mycotoxins: Effects on the Neurological and Immune Systems in Humans Andrew W. Campbell, Jack D. Thrasher, Michael R. Gray, and Aristo Vojdani Identification, Remediation, and Monitoring Processes Used in a Mold-Contaminated High School S. C. Wilson, W. H. Holder, K. V. Easterwood, G. D. Hubbard, R. F. Johnson, J. D. Cooley, and D. C. Straus The Microbial Status and Remediation of Contents in Mold-Contaminated Structures Stephen C. Wilson and Robert C. Layton Specific Detection of Fungi Associated With SBS When Using Quantitative Polymerase Chain Reaction Patricia Cruz and Linda D. Stetzenbach Index
Volume 56 Potential and Opportunities for Use of Recombinant Lactic Acid Bacteria in Human Health Sean Hanniffy, Ursula Wiedermann, Andreas Repa, Annick Mercenier, Catherine Daniel, Jean Fioramonti, Helena Tlaskolova, Hana Kozakova, Hans Israelsen, S ren Madsen, Astrid Vrang, Pascal Hols, Jean Delcour, Peter Bron, Michiel Kleerebezem, and Jerry Wells Novel Aspects of Signaling in Streptomyces Development Gilles P. van Wezel and Erik Vijgenboom Polysaccharide Breakdown by Anaerobic Microorganisms Inhabiting the Mammalian Gut Harry J. Flint Lincosamides: Chemical Structure, Biosynthesis, Mechanism of Action, Resistance, and Applications
157
Jaroslav Spı´zˇek, Jitka Novotna´, and Toma´sˇ Rˇezanka Ribosome Engineering and Secondary Metabolite Production Kozo Ochi, Susumu Okamoto, Yuzuru Tozawa, Takashi Inaoka, Takeshi Hosaka, Jun Xu, and Kazuhiko Kurosawa Developments in Microbial Methods for the Treatment of Dye Effluents R. C. Kuhad, N. Sood, K. K. Tripathi, A. Singh, and O. P. Ward Extracellular Glycosyl Hydrolases from Clostridia Wolfgang H. Schwarz, Vladimir V. Zverlov, and Hubert Bahl Kernel Knowledge: Smut of Corn Marı´a D. Garcı´a-Pedrajas and Scott E. Gold Bacterial ACC Deaminase and the Alleviation of Plant Stress Bernard R. Glick Uses of Trichoderma spp. to Alleviate or Remediate Soil and Water Pollution G. E. Harman, M. Lorito, and J. M. Lynch Bacteriophage Defense Systems and Strategies for Lactic Acid Bacteria Joseph M. Sturino and Todd R. Klaenhammer Current Issues in Genetic Toxicology Testing for Microbiologists Kristien Mortelmans and Doppalapudi S. Rupa Index
Volume 57 Microbial Transformations of Mercury: Potentials, Challenges, and Achievements in Controlling Mercury Toxicity in the Environment Tamar Barkay and Irene Wagner-Do¨bler
158
Contents of Previous Volumes
Interactions Between Nematodes and Microorganisms: Bridging Ecological and Molecular Approaches Keith G. Davies Biofilm Development in Bacteria Katharine Kierek-Pearson and Ece Karatan Microbial Biogeochemistry of Uranium Mill Tailings Edward R. Landa Yeast Modulation of Wine Flavor Jan H. Swiegers and Isak S. Pretorius Moving Toward a Systems Biology Approach to the Study of Fungal Pathogenesis in the Rice Blast Fungus Magnaporthe grisea Claire Veneault-Fourrey and Nicholas J. Talbot
Richard ffrench-Constant and Nicholas Waterfield Engineering Antibodies for Biosensor Technologies Sarah Goodchild, Tracey Love, Neal Hopkins, and Carl Mayers Molecular Characterization of Ochratoxin A Biosynthesis and Producing Fungi J. O’Callaghan and A. D. W. Dobson Index
Volume 59 Biodegradation by Members of the Genus Rhodococcus: Biochemistry, Physiology, and Genetic Adaptation Michael J. Larkin, Leonid A. Kulakov, and Christopher C. R. Allen
The Biotrophic Stages of Oomycete–Plant Interactions Laura J. Grenville-Briggs and Pieter van West
Genomes as Resources for Biocatalysis Jon D. Stewart
Contribution of Nanosized Bacteria to the Total Biomass and Activity of a Soil Microbial Community Nicolai S. Panikov
Process and Catalyst Design Objectives for Specific Redox Biocatalysis Daniel Meyer, Bruno Bu¨hler, and Andreas Schmid
Index
Volume 58 Physiology and Biotechnology of Aspergillus O. P. Ward, W. M. Qin, J. Dhanjoon, J. Ye, and A. Singh Conjugative Gene Transfer in the Gastrointestinal Environment Tine Rask Licht and Andrea Wilcks Force Measurements Between a Bacterium and Another Surface In Situ Ruchirej Yongsunthon and Steven K. Lower
The Biosynthesis of Polyketide Metabolites by Dinoflagellates Kathleen S. Rein and Richard V. Snyder Biological Halogenation has Moved far Beyond Haloperoxidases Karl-Heinz van Pe´e, Changjiang Dong, Silvana Flecks, Jim Naismith, Eugenio P. Patallo, and Tobias Wage Phage for Rapid Detection and Control of Bacterial Pathogens in Food Catherine E. D. Rees and Christine E. R. Dodd Gastrointestinal Microflora: Probiotics S. Kolida, D. M. Saulnier, and G. R. Gibson
Actinomycetes and Lignin Degradation Ralph Kirby
The Role of Helen Purdy Beale in the Early Development of Plant Serology and Virology Karen-Beth G. Scholthof and Paul D. Peterson
An ABC Guide to the Bacterial Toxin Complexes
Index
Contents of Previous Volumes
Volume 60 Microbial Biocatalytic Processes and Their Development John M. Woodley Occurrence and Biocatalytic Potential of Carbohydrate Oxidases Erik W. van Hellemond, Nicole G. H. Leferink, Dominic P. H. M. Heuts, Marco W. Fraaije, and Willem J. H. van Berkel Microbial Interactions with Humic Substances J. Ian Van Trump, Yvonne Sun, and John D. Coates Significance of Microbial Interactions in the Mycorrhizosphere Gary D. Bending, Thomas J. Aspray, and John M. Whipps Escherich and Escherichia Herbert C. Friedmann Index
Volume 61 Unusual Two-Component Signal Transduction Pathways in the Actinobacteria Matthew I. Hutchings Acyl-HSL Signal Decay: Intrinsic to Bacterial Cell–Cell Communications Ya-Juan Wang, Jean Jing Huang, and Jared Renton Leadbetter Microbial Exoenzyme Production in Food Peggy G. Braun Biogenetic Diversity of Cyanobacterial Metabolites Ryan M. Van Wagoner, Allison K. Drummond, and Jeffrey L. C. Wright Pathways to Discovering New Microbial Metabolism for Functional Genomics and Biotechnology Lawrence P. Wackett
159
Biocatalysis by Dehalogenating Enzymes Dick B. Janssen Lipases from Extremophiles and Potential for Industrial Applications Moh’d Salameh and Juergen Wiegel In Situ Bioremediation Kirsten S. J rgensen Bacterial Cycling of Methyl Halides Hendrik Scha¨fer, Laurence G. Miller, Ronald S. Oremland, and J. Colin Murrell Index
Volume 62 Anaerobic Biodegradation of Methyl tert-Butyl Ether (MTBE) and Related Fuel Oxygenates Max M. Ha¨ggblom, Laura K. G. Youngster, Piyapawn Somsamak, and Hans H. Richnow Controlled Biomineralization by and Applications of Magnetotactic Bacteria Dennis A. Bazylinski and Sabrina Schu¨bbe The Distribution and Diversity of Euryarchaeota in Termite Guts Kevin J. Purdy Understanding Microbially Active Biogeochemical Environments Deirdre Gleeson, Frank McDermott, and Nicholas Clipson The Scale-Up of Microbial Batch and Fed-Batch Fermentation Processes Christopher J. Hewitt and Alvin W. Neinow Production of Recombinant Proteins in Bacillus subtilis Wolfgang Schumann
160
Contents of Previous Volumes
Quorum Sensing: Fact, Fiction, and Everything in Between Yevgeniy Turovskiy, Dimitri Kashtanov, Boris Paskhover, and Michael L. Chikindas Rhizobacteria and Plant Sulfur Supply Michael A. Kertesz, Emma Fellows, and Achim Schmalenberger Antibiotics and Resistance Genes: Influencing the Microbial Ecosystem in the Gut Katarzyna A. Kazimierczak and Karen P. Scott Index
Volume 63 A Ferment of Fermentations: Reflections on the Production of Commodity Chemicals Using Microorganisms Ronald Bentley and Joan W. Bennett Submerged Culture Fermentation of ‘‘Higher Fungi’’: The Macrofungi Mariana L. Fazenda, Robert Seviour, Brian McNeil, and Linda M. Harvey Bioprocessing Using Novel Cell Culture Systems Sarad Parekh, Venkatesh Srinivasan, and Michael Horn Nanotechnology in the Detection and Control of Microorganisms Pengju G. Luo and Fred J. Stutzenberger Metabolic Aspects of Aerobic Obligate Methanotrophy Yuri A. Trotsenko and John Colin Murrell Bacterial Efflux Transport in Biotechnology Tina K. Van Dyk Antibiotic Resistance in the Environment, with Particular Reference to MRSA William Gaze, Colette O’Neill, Elizabeth Wellington, and Peter Hawkey Host Defense Peptides in the Oral Cavity Deirdre A. Devine and Celine Cosseau Index
Volume 64 Diversity of Microbial Toluene Degradation Pathways R. E. Parales, J. V. Parales, D. A. Pelletier, and J. L. Ditty Microbial Endocrinology: Experimental Design Issues in the Study of Interkingdom Signalling in Infectious Disease Primrose P. E. Freestone and Mark Lyte Molecular Genetics of Selenate Reduction by Enterobacter cloacae SLD1a-1 Nathan Yee and Donald Y. Kobayashi Metagenomics of Dental Biofilms Peter Mullany, Stephanie Hunter, and Elaine Allan Biosensors for Ligand Detection Alison K. East, Tim H. Mauchline, and Philip S. Poole Islands Shaping Thought in Microbial Ecology Christopher J. van der Gast Human Pathogens and the Phyllosphere John M. Whipps, Paul Hand, David A. C. Pink, and Gary D. Bending Microbial Retention on Open Food Contact Surfaces and Implications for Food Contamination Joanna Verran, Paul Airey, Adele Packer, and Kathryn A. Whitehead Index
Volume 65 Capsular Polysaccharides in Escherichia coli David Corbett and Ian S. Roberts Microbial PAH Degradation Evelyn Doyle, Lorraine Muckian, Anne Marie Hickey, and Nicholas Clipson Acid Stress Responses in Listeria monocytogenes Sheila Ryan, Colin Hill, and Cormac G. M. Gahan
Contents of Previous Volumes
Global Regulators of Transcription in Escherichia coli: Mechanisms of Action and Methods for Study David C. Grainger and Stephen J. W. Busby The Role of Sigma B (sB) in the Stress Adaptations of Listeria monocytogenes: Overlaps Between Stress Adaptation and Virulence Conor P. O’ Byrne and Kimon A. G. Karatzas Protein Secretion and Membrane Insertion Systems in Bacteria and Eukaryotic Organelles Milton H. Saier, Chin Hong Ma, Loren Rodgers, Dorjee G. Tamang, and Ming Ren Yen Metabolic Behavior of Bacterial Biological Control Agents in Soil and Plant Rhizospheres Cynthia A. Pielach, Daniel P. Roberts, and Donald Y. Kobayashi Copper Homeostasis in Bacteria Deenah Osman and Jennifer S. Cavet Pathogen Surveillance Through Monitoring of Sewer Systems Ryan G. Sinclair, Christopher Y. Choi, Mark R. Riley, and Charles P. Gerba Index
161
Cutinases: Properties and Industrial Applications Tatiana Fontes Pio and Gabriela Alves Macedo Microbial Deterioration of Stone Monuments—An Updated Overview Stefanie Scheerer, Otto Ortega-Morales, and Christine Gaylarde Microbial Processes in Oil Fields: Culprits, Problems, and Opportunities Noha Youssef, Mostafa S. Elshahed, and Michael J. McInerney Index
Volume 67 Phage Evolution and Ecology Stephen T. Abedon Nucleoid-Associated Proteins and Bacterial Physiology Charles J. Dorman Biodegradation of Pharmaceutical and Personal Care Products Jeanne Kagle, Abigail W. Porter, Robert W. Murdoch, Giomar Rivera-Cancel, and Anthony G. Hay Bioremediation of Cyanotoxins Christine Edwards and Linda A. Lawton Virulence in Cryptococcus Species Hansong Ma and Robin C. May
Volume 66 Multiple Effector Mechanisms Induced by Recombinant Listeria monocytogenes Anticancer Immunotherapeutics Anu Wallecha, Kyla Driscoll Carroll, Paulo Cesar Maciag, Sandra Rivera, Vafa Shahabi, and Yvonne Paterson Diagnosis of Clinically Relevant Fungi in Medicine and Veterinary Sciences Olivier Sparagano and Sam Foggett Diversity in Bacterial Chemotactic Responses and Niche Adaptation Lance D. Miller, Matthew H. Russell, and Gladys Alexandre
Molecular Networks in the Fungal Pathogen Candida albicans Rebecca A. Hall, Fabien Cottier, and Fritz A. Mu¨hlschlegel Temperature Sensors of Eubacteria Wolfgang Schumann Deciphering Bacterial Flagellar Gene Regulatory Networks in the Genomic Era Todd G. Smith and Timothy R. Hoover Genetic Tools to Study Gene Expression During Bacterial Pathogen Infection Ansel Hsiao and Jun Zhu Index
162
Contents of Previous Volumes
Volume 68 Bacterial L-Forms E. J. Allan, C. Hoischen, and J. Gumpert Biochemistry, Physiology and Biotechnology of Sulfate-Reducing Bacteria Larry L. Barton and Guy D. Fauque Biotechnological Applications of Recombinant Microbial Prolidases Casey M. Theriot, Sherry R. Tove, and Amy M. Grunden The Capsule of the Fungal Pathogen Cryptococcus neoformans Oscar Zaragoza, Marcio L. Rodrigues, Magdia De Jesus, Susana Frases, Ekaterina Dadachova, and Arturo Casadevall Baculovirus Interactions In Vitro and In Vivo Xiao-Wen Cheng and Dwight E. Lynn Posttranscriptional Gene Regulation in Kaposi’s Sarcoma-Associated Herpesvirus Nicholas K. Conrad Index
Volume 69 Variation in Form and Function: The Helix-Turn-Helix Regulators of the GntR Superfamily Paul A. Hoskisson and Se´bastien Rigali Biogenesis of the Cell Wall and Other Glycoconjugates of Mycobacterium tuberculosis Devinder Kaur, Marcelo E. Guerin, Henrieta Sˇkovierova´, Patrick J. Brennan, and Mary Jackson Antimicrobial Properties of Hydroxyxanthenes Joy G. Waite and Ahmed E. Yousef In Vitro Biofilm Models: An Overview Andrew J. McBain Zones of Inhibition? The Transfer of Information
Relating to Penicillin in Europe during World War II Gilbert Shama The Genomes of Lager Yeasts Ursula Bond Index
Volume 70 Thermostable Enzymes as Biocatalysts in the Biofuel Industry Carl J. Yeoman, Yejun Han, Dylan Dodd, Charles M. Schroeder, Roderick I. Mackie, and Isaac K. O. Cann Production of Biofuels from Synthesis Gas Using Microbial Catalysts Oscar Tirado-Acevedo, Mari S. Chinn, and Amy M. Grunden Microbial Naphthenic Acid Degradation Corinne Whitby Surface and Adhesion Properties of Lactobacilli G. Deepika and D. Charalampopoulos Shining Light on the Microbial World: The Application of Raman Microspectroscopy Wei E. Huang, Mengqiu Li, Roger M. Jarvis, Royston Goodacre, and Steven A. Banwart Detection of Invasive Aspergillosis Christopher R. Thornton Bacteriophage Host Range and Bacterial Resistance Paul Hyman and Stephen T. Abedon Index
Volume 71 Influence of Escherichia coli Shiga Toxin on the Mammalian Central Nervous System Fumiko Obata Natural Products for Type II Diabetes Treatment Amruta Bedekar, Karan Shah, and Mattheos Koffas
Contents of Previous Volumes
Experimental Models Used to Study Human Tuberculosis Ronan O’Toole Biosynthesis of Peptide Signals in Gram-Positive Bacteria Matthew Thoendel and Alexander R. Horswill Cell Immobilization for Production of Lactic Acid: Biofilms Do It Naturally Suzanne F. Dagher, Alicia L. Ragout, Faustino Sin˜eriz, and Jose´ M. Bruno-Ba´rcena Microbial Fingerprinting using Matrix-Assisted Laser Desorption Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS): Applications and Challenges R. Giebel, C. Worden, S. M. Rust, G. T. Kleinheinz, M. Robbins, and T. R. Sandrin
Index
Volume 72
163
N. D. Gray, A. Sherry, C. Hubert, J. Dolfing, and I. M. Head Index
Volume 73 Heterologous Protein Secretion by Bacillus Species: From the Cradle to the Grave Susanne Pohl and Colin R. Harwood Function of Protein Phosphatase-1, Glc7, in Saccharomyces cerevisiae John F. Cannon Milliliter-Scale Stirred Tank Reactors for the Cultivation of Microorganisms Ralf Hortsch and Dirk Weuster-Botz Type I Interferon Modulates the Battle of Host Immune System Against Viruses Young-Jin Seo and Bumsuk Hahm Index
Evolution of the Probiotic Concept: From Conception to Validation and Acceptance in Medical Science Walter J. Dobrogosz, Trent J. Peacock, and Hosni M. Hassan
Volume 74
Prokaryotic and Eukaryotic Diversity of the Human Gut Julian R. Marchesi
Recent Advances in Hantavirus Molecular Biology and Disease Islam T. M. Hussein, Abdul Haseeb, Absarul Haque, and Mohammad A. Mir
Oxalate-Degrading Bacteria of the Human Gut as Probiotics in the Management of Kidney Stone Disease Valerie R. Abratt and Sharon J. Reid Morphology and Rheology in Filamentous Cultivations T. Wucherpfennig, K. A. Kiep, H. Driouch, C. Wittmann, and R. Krull Methanogenic Degradation of Petroleum Hydrocarbons in Subsurface Environments: Remediation, Heavy Oil Formation, and Energy Recovery
Bacterial Strategies for Growth on Aromatic Compounds Kevin W. George and Anthony G. Hay
Antigenic Variation and the Genetics and Epigenetics of the PfEMP1 Erythrocyte Surface Antigens in Plasmodium falciparum Malaria David E. Arnot and Anja T. R. Jensen Biological Warfare of the Spiny Plant: Introducing Pathogenic Microorganisms into Herbivore’s Tissues Malka Halpern, Avivit Waissler, Adi Dror, and Simcha Lev-Yadun Index
