ReseaRch highlights
in brief i N N AT E i M M U N i T Y
Statins enhance formation of phagocyte extracellular traps Chow, O. A. et al. Cell Host Microbe 8, 445–454 (2010)
Statins inhibit cholesterol synthesis and are prescribed to those at high risk of developing cardiovascular disease. The widespread use of these drugs has promoted interest in their other effects: this study shows that statins affect phagocyte functions. Pre-treatment with statins increased the capacity of human neutrophils and macrophages to kill various bacteria in vitro, but paradoxically, statins decreased the ability of neutrophils to phagocytose Staphylococcus aureus or induce the oxidative burst. Instead, statins promoted microbial killing by inducing phagocyte production of extracellular traps (mesh-like structures composed of nuclear DNA, histones and antimicrobial peptides). In a model of S. aureus-induced pneumonia, pre-treating mice with statins decreased bacterial loads and pathology in the lungs, and this was associated with increased formation of extracellular traps. Patients with pneumonia or sepsis have better survival rates if they are receiving statin therapy; this study may explain these findings. i N F L A M M AT i O N
A role for mitochondria in NLRP3 inflammasome activation Zhou, R. et al. Nature 1 Dec 2010 (doi:10.1038/nature09663)
The NLRP3 (NOD-, LRR- and pyrin domain-containing 3) inflammasome is activated in response to pathogens or damaged cells and promotes the maturation of inflammatory cytokines, such as interleukin-1β (IL-1β). It is currently unclear how diverse danger signals activate the NLRP3 inflammasome, but one model proposes that the generation of reactive oxygen species (ROS) is involved. This study shows that stressed mitochondria are a rich source of ROS that trigger inflammasome activation. Inhibition of mitochondrial function led to ROS release and subsequent IL-1β induction in wild-type, but not NLRP3-deficient, macrophages. Healthy cells remove ROS-generating mitochondria through mitophagy, a specialized form of autophagy, and inhibiting mitophagy in macrophages led to inflammasome activation. These findings could explain the link between mitochondrial malfunction and chronic inflammatory diseases. MHC MOLECULES
Structure of a classical MHC class I molecule that binds “non-classical” ligands Hee, C. S. et al. PLoS Biol. 8, e1000557 (2010)
This paper reports the crystal structure of one variant of the polymorphic YF1 MHC class I molecule in chickens, showing that this unusual molecule represents a structural link between the peptide-presenting classical MHC class I molecules and the lipid-presenting non-classical MHC class I molecules (CD1 molecules) that are present in mammals. The YF1*7.1 heavy chain associates with β2-microglobulin to form the typical structure of a classical MHC class I molecule, with anti-parallel β-helices forming the binding groove. However, the binding groove of YF1*7.1 is narrower than that of classical MHC class I molecules and is lined by hydrophobic residues. Binding assays showed that YF1*7.1 can bind lipid antigens, and modelling studies suggested that the type of lipid that is bound might be affected by allelic differences in the binding groove. So, the presentation of a large repertoire of lipids, which is accomplished using multiple non-polymorphic CD1 genes in mammals, might be achieved by multiple alleles of a single YF1 gene in chickens (which have only two CD1 genes).
nature reviews | Immunology
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ReseaRch highlights
vIRAL ImmuNIty
Bad memories Seasonal strains of influenza virus cause more severe disease in infants and the elderly, but historically, pan demic strains of influenza virus have induced the most debilitating disease in healthy young adults. A study in Nature Medicine now offers an explanation for this paradox. To explore the mechanisms by which pandemic strains of influenza virus promote disease, the authors characterized samples from patients who had been infected with either pandemic or seasonal strains of influenza virus. Pandemic strains of influenza virus have been pro posed to cause disease by inducing a ‘cytokine storm’; however, naso pharyngeal secretions from patients with pandemic or seasonal influenza contained similar levels of inflamma tory cytokines. Furthermore, mono cytes from healthy donors showed similar cytokine induction following
culture with haemagglutinin 1 (HA1) from pandemic or seasonal influenza virus. The authors next measured the levels of HA1specific antibodies in healthy individuals of different ages. IgG antibodies specific for viral HA1 were not detected in infants, but could be found in sera from young and elderly adults. However, although the HA1specific antibodies from elderly adults could neutralize and protect against a pandemic influenza virus strain from 2009, antibodies from young adults showed lower avidity and could not neutralize the virus. This was despite the fact that antibodies from the young adults showed higher avidity for a seasonal influenza virus. Young adults who became severely ill during the 2009 pandemic had higher serum levels of HA1specific IgG than those who developed mild disease, but the
nATure revIewS | Immunology
HA1specific antibodies from the severely ill individuals showed lower overall avidity for the 2009 influenza virus strain. Together, these data suggest that high levels of low avidity antibody, which was probably generated during previous seasonal influenza virus infections, promoted severe disease during the 2009 influ enza virus pandemic. Lowavidity antibody responses are associated with immune complex mediated disease, and in keeping with this, extensive deposition of the com plement component C4d was seen in lung sections from young adults who were fatally infected during the 2009 pandemic. In addition, although immune complexes were detected in secretions from patients with pandemic influenza, they were rarely found in secretions from patients with seasonal influenza. Finally, extensive deposition of C4d was observed in archived lung sections from adults who died during a 1957 influenza pandemic, indicating that immune complexmediated disease may also have contributed to fatal cases during this pandemic. These findings offer a plausible explanation for the unusual age dis tribution of severe cases that occurs during influenza virus pandemics. Healthy young adults are more likely to have preexisting antibodies to seasonal strains of influenza virus, and these antibodies crossreact with the pandemic strain but are non protective. Instead, the lowavidity antibodies promote the deposition of immune complexes in the lung, leading to severe, and often fatal, respiratory disease.
Yvonne Bordon
ORIGINAL RESEARCH PAPER Monsalvo, A. C. et al. Severe pandemic 2009 H1N1 influenza disease due to pathogenic immune complexes. Nature Med. 5 Dec 2010 (doi:10.1038/nm.2262)
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in brief i N N AT E i M M U N i T Y
Plexin‑A4–semaphorin 3A signaling is required for Toll‑like receptor‑ and sepsis‑induced cytokine storm Wen, H. et al. J. Exp. Med. 22 Nov 2010 (doi:10.1084/jem.20101138)
This study shows that plexin A4 signalling synergizes with Toll-like receptor (TLR) signalling to promote pro-inflammatory cytokine responses. In the absence of plexin A4, macrophages showed defective production of interleukin-6 and tumour necrosis factor in response to various TLR agonists and bacteria. Activation of TLR signalling components was also defective in plexin A4-deficient macrophages. Physiological relevance for plexin A4-enhanced TLR responses was confirmed by the findings that plexin A4-deficient mice showed a reduced cytokine storm after lipopolysaccharide (LPS) treatment compared with wild-type mice and were protected from lethal challenge with LPS. Plexin A4-deficient mice were also resistant to septic inflammation induced by caecal ligation and puncture. Finally, administration of the plexin A4 ligand semaphorin 3A enhanced LPS-induced cytokine production, suggesting that this pathway could be a target in the treatment of sepsis. i N F L A M M AT i O N
Gene from a psoriasis susceptibility locus primes the skin for inflammation Wolf, R. et al. Sci. Transl. Med. 2, 61ra90 (2010)
The chronic skin inflammation of psoriasis could result from an abnormality of epidermal keratinocytes or from a dysregulated immune response. A combination of these factors is probably responsible for the disease, and a new study supports this idea by showing that S100 proteins expressed by keratinocytes activate an inflammatory cascade through the receptor for advanced glycation end products (RAGE). Transgenic mice overexpressing keratinocyte-restricted S100AA — the single mouse orthologue of the human proteins S100A7 and S100A15, which are encoded in psoriasis susceptibility locus 4 (PSORS4) and are highly expressed by keratinocytes from psoriatic lesions — had an exaggerated inflammatory response to wounding of the skin associated with increased levels of T helper 1 (TH1) and TH17 cell-associated cytokines. In turn, these cytokines further upregulated S100AA expression, showing the therapeutic potential of targeting the S100A7/A15–RAGE axis in psoriasis. MUCOSAL iMMUNOLOGY
T helper type 1 memory cells disseminate postoperative ileus over the entire intestinal tract Engel, D. R. et al. Nature Med. 16, 1407–1413 (2010)
Localized intestinal surgery can disrupt the motility of the entire gastrointestinal tract (a condition termed postoperative ileus); this is thought to result from neuronal dysfunction. Using a mouse model, this study shows that it is not the nervous system but the immune system that drives postoperative ileus. Intestinal manipulation activated local dendritic cells to produce interleukin-12 and induce interferon-γ (IFNγ)-producing T helper 1 (TH1) cells, which had dual roles in postoperative ileus: they drove the inflammation that disrupted the local environment and promoted the spread of intestinal dysfunction by migrating to other areas of the intestine. TH1 cells that were induced in manipulated areas expressed the gut-homing receptor CC-chemokine receptor 9 (CCR9), which may have promoted their spread to other regions of the intestine. Interestingly, in patients undergoing abdominal surgery, the number of IFNγ-producing CCR9+ memory T cells in the blood was markedly increased shortly after the operation, but this population remained stable in patients undergoing non-abdominal surgery. nature reviews | Immunology
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I N f L A m m At I O N
Directions from the matrix Emerging evidence reveals that components of the extracellular matrix can directly regulate inflammatory processes. Now, researchers have identified a role for the matrix component biglycan in the pathogenesis of lupus nephritis through its ability to induce expression of the B cell chemoattractant CXC-chemokine ligand 13 (CXCL13). Biglycan, which exists in the extracellular matrix and as a soluble molecule, has previously been shown to act as an endogenous danger signal by activating Toll-like receptor 2 (TLR2), TLR4 and the NLRP3 (NOD-, LRRand pyrin domain-containing 3) inflammasome. This activity led the authors to investigate whether biglycan is involved in renal inflammation associated with systemic lupus erythematosus (SLE). They first observed that biglycan levels are increased in the plasma and kidneys from patients with lupus nephritis, as well as from MRL–lpr mice and NZB/W F1 mice
(mouse models of SLE). Moreover, plasma biglycan levels in MRL–lpr mice increased progressively over time, coinciding with the initiation and progression of disease. In keeping with a role for biglycan in the pathogenesis of lupus nephritis, biglycan-deficient MRL–lpr mice did not develop the enlarged kidneys, high albuminuria and high serum immunoglobulin levels that occurred in wild-type MRL–lpr mice with disease. Furthermore, transient overexpression of soluble human biglycan increased albuminuria and worsened renal pathology in MRL–lpr mice owing to a large influx of mononuclear cells, including macrophages and T cells. This increase in immune cell infiltration was associated with higher renal and plasma levels of the macrophage and T cell chemoattractants CC-chemokine ligand 2 (CCL2), CCL5 and CCL3. Greater numbers of B cells, mainly B-1 cell populations, also infiltrated the
NaTuRE REvIEWS | Immunology
kidneys of mice that overexpressed biglycan compared with the numbers in control mice. Finally, biglycan was also found to promote the production of active caspase 1 and mature interleukin-1β (products of NLRP3 inflammasome activation) in diseased MRL–lpr mice. Of particular interest to the authors was the finding that CXCL13 levels were increased in diseased mice and reduced in biglycan-deficient MRL–lpr mice. CXCL13 recruits B cells that express CXC-chemokine receptor 5 and has previously been described as a marker of disease activity in SLE. Importantly, in vitro incubation of peritoneal macrophages and splenic dendritic cells from wildtype mice with biglycan triggered CXCL13 production, and this was shown to depend on their expression of TLR2 and TLR4 and not on activation of the inflammasome. Finally, in vivo experiments using mice deficient in TLR2, TLR4 or both TLRs confirmed that biglycan acts through these TLRs to induce the production of pro-inflammatory mediators and CXCL13, which drive the infiltration of immune cells into the kidneys. These data identify a new biglycanmediated mechanism of immune regulation, one that could be involved in other B cell-mediated renal diseases, as suggested by the observation that biglycan and CXCL13 levels are increased in plasma and renal biopsies from patients with acute renal allograft rejection.
Lucy Bird
ORIGINAL RESEARCH PAPER Moreth, K. et al. The proteoglycan biglycan regulates expression of the B cell chemoattractant CXCL13 and aggravates murine lupus nephritis. J. Clin. Invest. 120, 4251–4272 (2010)
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ReseaRch highlights
In the news tb’s protective shield Most individuals infected with Mycobacterium tuberculosis remain asymptomatic and do not develop tuberculosis, despite the persistent presence of the bacteria. Researchers based in India have discovered a new mechanism that could explain how M. tuberculosis can persist in the face of potent immune responses. They say the bug’s trick is to recruit mesenchymal stem cells (MSCs) to the site of infection, where these cells suppress anti-mycobacterial T cell responses (Proc. Natl Acad. Sci. USA, 6 Dec 2010). Joanne Flynn, an immunologist at the University of Pittsburgh School of Medicine, Pennsylvania, USA, acknowledged that this was “a novel finding” and suggested that MSCs “may be an important cell subset for balancing inflammation” (The Scientist, 7 Dec 2010). Indeed, MSCs, which are bone marrow-derived pluripotent stem cells, are known to have immunosuppressive properties. Here, the scientists suggest that these stem cells form “a protective coating around granulomas and produce a range of immunosuppressant molecules, such as nitric oxide” (ABC Online, 7 Dec 2010). MSCs that accumulated at the periphery of granulomas containing live M. tuberculosis organisms secreted nitric oxide, which was shown to inhibit T cell proliferation. The MSCs also promoted the induction of regulatory T cells. Sam Behr of Harvard University, Cambridge, Massachusetts, USA, explained: “What they’re suggesting is that these stem cells are interposed between T cells and the infected macrophages … preventing access of the T cells to the macrophages” (The Scientist). The authors claim that the findings “identify these cells as unique targets for therapeutic intervention in tuberculosis” (Bloomberg, 7 Dec 2010), a disease that causes 2 million deaths each year. Gobardhan Das, senior author of the study, says that “If you can target these MSCs then you can destroy the protective layer and expose the bacteria to the macrophages” (ABC Online). Lucy Bird
nature reviews | Immunology
volume 11 | january 2011 © 2011 Macmillan Publishers Limited. All rights reserved
REVIEWS Innate immune mechanisms of colitis and colitis-associated colorectal cancer Maya Saleh* and Giorgio Trinchieri‡
Abstract | The innate immune system provides first-line defences in response to invading microorganisms and endogenous danger signals by triggering robust inflammatory and antimicrobial responses. However, innate immune sensing of commensal microorganisms in the intestinal tract does not lead to chronic intestinal inflammation in healthy individuals, reflecting the intricacy of the regulatory mechanisms that tame the inflammatory response in the gut. Recent findings suggest that innate immune responses to commensal microorganisms, although once considered to be harmful, are necessary for intestinal homeostasis and immune tolerance. This Review discusses recent findings that identify a crucial role for innate immune effector molecules in protection against colitis and colitis-associated colorectal cancer and the therapeutic implications that ensue. Helminth therapy Helminth therapy is a form of immunotherapy aimed at modulating the T helper 1 (TH1)/TH2 immune balance. It involves the deliberate inoculation of patients suffering from immune-mediated inflammatory diseases with helminth (parasitic intestinal nematodes) or helminth larvae. The currently studied regimens in humans use Trichuris suis, which does not cross the intestinal barrier or cause an invasive infection.
*Department of Medicine, McGill University, Montreal, Quebec, H3G 0B1 Canada. ‡ Cancer and Inflammation Program, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702, USA. e-mails: maya.saleh@mcgill. ca;
[email protected] doi:10.1038/nri2891 Published online 10 December 2010
Innate immunity is the body’s alarm system. It senses the presence of ‘foreign’ entities derived from either infections (non-self recognition) or tissue damage (alteredself recognition) and confers protection by actively inducing inflammatory, anti-microbial and anti-stress responses. It also serves to alert and prime the adaptive immune system in case the insult persists. However, dysregulation of these pathways can lead to severe inflammatory and immunological diseases. Inflammatory bowel diseases (IBDs) are inflammatory disorders of the intestinal tract that are most common in developed countries, affecting the quality of life of roughly 1.4 million individuals in the United States and 2.2 million in Europe, mainly of Caucasian descent1,2. The two main types of IBD are Crohn’s disease and ulcerative colitis, which share as a feature an overactive immune response to the intestinal microbiota but differ in the site and nature of the inflammatory pathology. Management of IBD has so far relied on nonspecific immunosuppressive therapies (such as steroids), antibiotics, and biologicals targeting mainly the proinflammatory tumour necrosis factor (TNF) pathway 3,4; however, these treatments are not effective in all patients. In addition, probiotics5 and ‘helminth therapy’6 have been used to modulate the abnormal inflammatory response and have shown promise in various clinical trials. One of the consequences of chronic inflammation is the promotion of tumorigenesis, and patients with IBD have a higher risk of developing colitis-associated colorectal cancer with an odds ratio of approximately three7–10. However, most colorectal cancers develop without any
obvious pre-existing inflammatory pathology. Colorectal cancer is the third most common malignancy in humans, with the highest frequencies observed in North America, Europe and Australia and the lowest in Africa, Asia and South America11. Interestingly, Asian populations that migrate to North America acquire the same risk of colorectal cancer as local populations within one generation12. This suggests that environmental differences and particularly alimentary customs, which probably affect the commensal microbiota, are responsible for the geographical variation in colorectal cancer incidence. As discussed in this Review, recent findings indicate that the sensing of commensal microorganisms by the innate immune system maintains intestinal homeostasis and induces healing responses following injury that confer protection against colitis and colorectal cancer. In addition to inducing antimicrobial responses, this crosstalk also triggers cell survival, autophagy and mucosal regeneration, which are all salutary for the host. Consistently, genetic mutations in the innate immune system that alter the host–microbiota equilibrium and affect epithelial cell regeneration result in enhanced susceptibility to experimental colitis and carcinogenesis. Paradoxically, mutations in negative regulators of innate immunity pathways also favour carcinogenesis by breaking mucosal tolerance to commensal microorganisms and thus amplifying the inflammatory response in the gut. Here, we discuss the mechanisms used by the innate immune system in the intestine in light of recent advances in the study of the microbiology, immunology and genetics of IBD and colon cancer.
NATURE REvIEwS | Immunology
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REVIEWS Autophagy A tightly regulated catabolic process that involves degradation of the cell’s own intracellular components through the lysosomal machinery. It is a normal part of cell growth, development and homeostasis, and recently it has emerged as an efficient innate immunity mechanism.
Villi Villi are projections into the intestinal lumen. Their outer epithelial layer consists mainly of mature, absorptive enterocytes but also contains mucus-secreting goblet cells.
Crypts Crypts are tubular invaginations of the intestinal epithelium. At the base of the crypts are Paneth cells, which produce bactericidal defensins, and stem cells, which continuously divide and are the source of all intestinal epithelial cells.
The pros and cons of the microbiota Commensal microorganisms contribute to host defence by limiting the growth of potentially harmful enteric pathogens, and can control intestinal inflammation and pathology by producing symbiosis factors. For example, Bacteroides fragilis protects animals from experimental colitis induced by Helicobacter hepaticus through the synthesis of polysaccharide A, which suppresses interleukin-17 (Il-17) production in the intestine and promotes the function of Il-10-producing CD4+ T cells13. Through crosstalk with the innate immune system, the microbiota also regulates intestinal homeostasis by providing instructive signals that drive intestinal epithelial cell (IEC) turnover and maturation (see below), lymphocyte development and the conditioning of the immune system both at mucosal sites14,15 and systemically 16. In addition to regulating the inflammatory environment in the intestine, the microbiota has a direct impact on intestinal homeostasis and pathology through the generation of growth factors and hormones or by affecting how natural mutagens and carcinogens are catabolized by the body 17. However, these latter effects will not be discussed further in this article. Despite this mutualism between the microbiota and the host (BOX 1), changes in the composition of the intestinal microbiota or colonization with specific pathogens may alter intestinal homeostasis and the nature of the immune response and may result in spontaneous colitis and/or tumorigenesis. The constant threat posed by commensal organisms is exemplified by the intestinal microbiota of T-bet−/−Rag2−/− ulcerative colitis (TRUC) mice, in which spontaneous colitis and subsequent colorectal cancer develop because of alterations in both innate and
Box 1 | The human–microbiota mutualism The human body, which consists of 1013 cells, is colonized at birth by approximately ten times as many microorganisms. The maternal flora is a major determinant of the eventual composition of that of the progeny120, and the colonization continues for several days after birth with the exposure to the external environment. The intestinal tract is the largest reservoir of human flora and is densely colonized by diverse species of microorganisms: predominantly bacteria, but also protozoa and fungi. Although it is estimated that the microbiota contains 500–1,000 different species of bacteria, 99% of these are predicted to originate from around 30–40 species. The composition of the flora varies widely among individuals, depending on kinship, age, diet, lifestyle changes and stress. There is also variation between different anatomical locations, with the number of bacteria increasing dramatically in the more distal portions of the gastrointestinal tract (the cecum and the colon). Collectively, the gut microbiome contains around 100 times as many genes as there are in the human genome. Recent efforts, through human microbiome projects (for example, the National Institutes of Health (NIH) Roadmap Human Microbiome Project and the European Commission MetaHIT project), are aiming at identifying microbiome common cores (common sets of microbial species) at different anatomical sites and characterizing microorganisms that are associated with health and disease. An intestinal microbiome core has been recently reported, and variations from this core have been associated with obesity121. The mammalian host and its commensal microorganisms share a mutually beneficial, symbiotic and dynamic relationship. The host provides a rich habitat that is suitable for microbial survival and replication and, in return, commensal microorganisms, through their metabolic activities, aid in host physiological functions such as fermentation, digestion and absorption of dietary polysaccharides, synthesis of vitamins, and regulation of host genes needed for deposition of lipids in adipocytes and fat storage122,123. However, this symbiosis extends beyond mere substrate exchange (see main text).
adaptive immune responses18. Recombination-activating gene 2 (RAG2) deficiency eliminates adaptive immune responses, whereas T-bet deficiency in the innate immune system results in excessive TNF production by dendritic cells (DCs). This imbalance in mucosal immunity affects the composition of the gut microbiota, leading to a population of commensal organisms that can transmit the disease to wild-type mice18,19. In particular, two bacterial species, Proteus mirabilis and Klebsiella pneumoniae, are associated with colitis in TRUC mice and, in conjunction with an endogenous microbial community, transmit colitis to wild-type mice20. A second example of a modulatory effect of the microbiota on the mucosal immune response is the association between segmented filamentous bacteria (SFB) colonization (found in mice from certain commercial animal production facilities) and a predominance of T helper 17 (TH17) cells21. Interestingly, colonization of the gut by SFB also exerts systemic effects, as it is sufficient to enhance TH17 cell responses and induce arthritis in a T cell receptor (TCR)-transgenic mouse model of this disease22. Indeed, disruption of host–microbiota homeostasis in the intestine can have consequences on distant organs, resulting in DNA damage, autoimmunity and cancer 23,24. Commensal microorganisms therefore present a constant threat after a mechanical, physical or immunological breach of the intestinal barrier, and this forms the basis of local, as well as some systemic, inflammatory-mediated immune diseases.
Intestinal homeostasis pathways The unique microbial environment of the intestine places the innate immune system at the centre of intestinal homeostasis. This system is not simply a host defence mechanism against invading pathogens, functioning solely in direct killing of microorganisms; it also modulates bacterial handling through autophagy (see below) and affects IEC proliferation, differentiation and survival. As such, the innate immune system is an important determinant in the onset and development of IBD and intestinal cancers. Several host innate immune mechanisms have evolved to deal with the challenge posed by the microbiota. Anatomically, a physical barrier formed by a single layer of columnar IECs, arranged into villi and crypts and covering a surface area of approximately 100 m2, shields the rest of the body from the commensal microorganisms that reside in the intestinal lumen. Multipotent stem cells located at the base of the crypts replenish IECs and regenerate the mucosa in response to tissue injury. Accumulating evidence indicates that IEC barrier integrity and underlying immune tolerance depend on the crosstalk between commensal microorganisms and the innate immune system. For instance, prostaglandin-endoperoxide synthase 2 (PTGS2; also known as COX2)-expressing mesenchymal cells in the crypts sense the microbiota through Toll-like receptors (TlRs), and this is required to maintain the stem cell niche25. Alterations in this crosstalk, as occur in mice deficient in the TlR and Il-1 receptor signalling adaptor molecule MyD88 (myeloid differentiation primary response protein 88), lead to susceptibility to experimental colitis26.
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REVIEWS
Tight junction A ring of proteins that seals apical epithelium; these proteins include the integral membrane proteins occludin and claudin, in association with cytoplasmic zonula occludins proteins.
Lamina propria The connective tissue that underlies the mucosal epithelium and contains various myeloid and lymphoid cells, including macrophages, dendritic cells, B cells and T cells.
In addition to the presence of stem cells, there are four differentiated cell types within the intestinal epithelium that have fundamental roles in instating barrier function through specialized physical, biochemical and immunological mechanisms. The predominant IECs are the absorptive enterocytes. These cells exit the crypts and form the surface epithelium that restricts commensal microorganisms and other antigenic particles to the lumen through an apical brush border and intercellular tight junctions. Alterations in the composition and structure of tight junctions have been noted in inflamed intestinal segments of patients with Crohn’s disease27, and targeted disruption of IEC tight junctions contributes to the development of experimental colitis28. Goblet cells reinforce the enterocyte barrier by secreting mucins, which form a polysaccharide- and glycoproteincontaining glycocalyx bilayer, in which the firm inner layer is devoid of bacteria29. Deficiency in mucin 2, the most abundant gastrointestinal mucin, or missense mutations in its gene, lead to the development of spontaneous chronic colitis and colorectal cancer 30–32. Enteroendocrine cells and Paneth cells, found in the proximity of the stem cell zone, exert innate immune functions by secreting lysozymes and a broad range of antimicrobial peptides, including α-defensins, β-defensins, cathelicidins, calprotectins, lipocalins and the C-type lectin REG3γ (regenerating islet-derived protein 3γ)33. Paneth cells are not found in the colon but antimicrobial products are also produced by colonocytes and have a homeostatic role in the gut by regulating microbial ecology and the makeup of commensal bacteria34. A balance between cell death and survival is key for the maintenance of intestinal homeostasis. IECs are eliminated daily by apoptosis, yet resistance to apoptosis is essential to maintain barrier function and dysregulation of apoptosis has been linked to intestinal pathologies. Interestingly, inflammation and innate immunity are tightly intertwined with apoptosis, and the net outcome is likely to be a consequence of the thresholds set by endogenous inhibitors and counteracting mechanisms. For example, nuclear factor-κB (NF-κB), a master transcriptional regulator that is activated by various cytokine receptors and pattern-recognition receptors (PRRs), controls the expression of pro-inflammatory mediators such as TNF and enhances the survival of cells through the induction of anti-apoptotic genes35. However, TNF triggers both cell survival and cell death depending on the cellular context. Enterocyte-specific ablation of NF-κB signalling — through conditional deletion of NF-κB essential modulator (NEMO; also known as IKKγ) or both IκB kinase-α (IKKα) and IKKβ — leads to spontaneous enterocyte apoptosis and massive intestinal inflammation36. Similarly, mice with IECspecific deletion of the NF-κB component RElA exhibit increased susceptibility to chemically induced colitis37. In these mice, IEC apoptosis is completely driven by TNF, as inhibition of TNF receptor 1 (TNFR1) prevents the development of intestinal inflammation. Furthermore, the E3 ligase editing enzyme A20 (also known as TNFAIP3) terminates NF-κB signalling and inhibits TNF-induced apoptosis, and A20 mutations
have been associated with Crohn’s disease38. Enterocytespecific deficiency of A20 results in susceptibility to experimental colitis owing to a hyper susceptibility to TNF-induced apoptosis, further supporting a role for TNF-induced apoptosis in barrier disruption 39. Thus, we argue that induction of IEC apoptosis is one mechanism by which TNF sustains chronic inflammation in the intestine and that IEC resistance to TNFinduced apoptosis is crucial for protection against colitis. Consistently, TNF-targeting biologicals confer protection in IBD by differentially modulating apoptosis in the gut. Indeed, TNF-blocking antibodies have been proven to inhibit IEC apoptosis and restore barrier function in patients with Crohn’s disease40, whereas they induce apoptosis of lamina propria mononuclear cells41, which contributes to the resolution of the inflammatory response. However, although preventing IEC apoptosis is beneficial in colitis, impaired IEC death is linked to colitis-associated colorectal cancer. Indeed, enterocytespecific deletion of IKKβ leads to decreased tumour incidence owing to enhanced IEC apoptosis in the absence of NF-κB anti-apoptotic target gene expression42. Both environmental triggers and genetic predisposition affect IEC maintenance and survival in IBD and intestinal cancers, and innate immune mechanisms appear to orchestrate the fate of IECs and mucosal homeostasis. In the case of tissue injury, the innate immune system senses the damage and shifts the homeostatic balance towards IEC proliferation, restoration and production of cytoprotective and repair factors, which together trigger tissue repair. we propose that impairment of these responses results in the translocation of commensal microorganisms to the lamina propria, and this leads to excessive stimulation of resident immune cells, chronic inflammation, colitis and colitis-associated colorectal cancer. The innate immune system is thus generally protective in the context of tissue injury. However, colorectal cancer can also arise in the absence of tissue injury because of intrinsic mutations in oncogenes or tumour suppressor genes. In this instance, the innate immune system is deleterious, as it promotes tumorigenesis through the induction of inflammation in the intestine (see below).
Innate immunity, colitis and tissue repair TLRs and MYD88. Triggering of TlRs culminates in cellular responses aimed at killing microorganisms while preserving host cell integrity, and these responses include antimicrobial peptide production, inflammation, maturation of antigen-presenting cells and induction of tissue repair and cell survival pathways43. In the gut, multiple tolerance mechanisms ensure minimal TlR activation by commensal microorganisms. TlRs are expressed at low levels on IECs and are mostly distributed in endosomal vesicles or on the basolateral surface away from luminal content44. In addition, TlR signalling is blunted through distinct molecular mechanisms including: expression of inhibitory molecules such as Toll-interacting protein (TOllIP), single immunoglobulin Il-1-related receptor (SIGIRR; also known as TIR8), Il-1R-associated kinase 3 (IRAK3; also known as IRAK-M) and A20
NATURE REvIEwS | Immunology
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REVIEWS (Ref. 44);
a paucity to respond to commensal products upon constant exposure33,45; and conditioning of resident leukocytes towards an anti-inflammatory phenotype46. Uncontrolled TlR activation, such as in mice deficient in SIGIRR (an inhibitory member of the TlR and Il-1R families), leads to defects in intestinal homoeostasis in
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Wnt pathway A signalling pathway that regulates cell fate determination, proliferation, adhesion, migration and polarity during development. In addition to the crucial role of this pathway in embryogenesis, Wnt ligands and their downstream signalling molecules have been implicated in tumorigenesis and have causative roles in human colon cancers.
Figure 1 | Innate immune effector molecules function in IECs to maintain intestinal homeostasis. Apical 0CVWTG4GXKGYU^+OOWPQNQI[ Toll-like receptor 9 (TLR9) stimulation leads to tolerance via the activation of the Wnt pathway and induction of type I interferon (IFN) production, whereas basolateral TLRs trigger inflammation and tissue repair partially through nuclear factor-κB (NF-κB). Apical TLR9 also leads to accumulation of NF-κB inhibitor α (IκBα), which blocks NF-κB activation. SIGIRR (single immunoglobulin IL-1-related receptor) inhibits TLR signalling. Activation of nucleotide-binding oligomerization domain (NOD) proteins expressed by colonocytes and ileal intestinal epithelial cells (IECs) triggers the release of antimicrobial peptides including defensins that maintain homeostasis by regulating the composition of the microbiota. NOD signalling also leads to the production of tissue repair factors including tumour necrosis factor (TNF), interleukin-6 (IL-6) and CXC-chemokine ligand 1 (CXCL1). NF-κB is one of the downstream effector transcription factors that induce the expression of pro-inflammatory and pro-survival factors. Stimulation of NOD-, LRR- and pyrin domain-containing 3 (NLRP3) by tissue damage and/or commensal-derived products leads to the recruitment of caspase 1 through apoptosis-associated speck-like protein containing a CARD (ASC), forming the inflammasome. This activates caspase 1, enabling it to process pro-IL-18 into its active cytokine form (IL-18), which is required for compensatory proliferation of IECs and for tissue repair. This process is inhibited by caspase 12, which antagonizes the NLRP3 inflammasome. MYD88, myeloid differentiation primary response protein 88.
the steady state. These defects depend on the presence of commensal microorganisms and include persistent IEC survival and enhanced expression of pro-inflammatory cytokines (fIG. 1). Notably, these defects render Sigirr–/– mice susceptible to experimental colitis induced with the IEC cytotoxic agent dextran sulphate sodium (DSS) and to colitis-associated colorectal cancer induced with the procarcinogen azoxymethane (AOM) in conjunction with chronic DSS treatment (BOX 2). Interestingly, tissue-specific transgenic expression of SIGIRR by IECs in Sigirr–/– mice restores immune tolerance and abrogates the susceptibility of Sigirr–/– mice to colitis and tumorigenesis47. Thus, exaggerated TlR signalling in IECs contributes to the development of intestinal pathologies. Nevertheless, although excessive TlR activation in the gut is pathogenic, sensing of the commensal flora by TlRs, particularly by TlR2 and TlR4, is required for intestinal homeostasis and control of tissue repair. MyD88-deficient mice, which cannot signal through Il-1 family receptors and most TlRs have significant defects in the mucosa with increased numbers of proliferating cells in the crypts48. This results in deficient repair of the intestinal barrier following radiation or chemical injury and enhanced susceptibility to colitis and colitisassociated colorectal cancer 48,49. Mice in which the commensal flora is decreased by antibiotic treatment have a similar phenotype to that of MyD88-deficient mice and have very low constitutive expression of factors (such as Il-6, TNF, CXC-chemokine ligand 1 (CXCl1) and heat shock proteins) that are important in preserving intestinal homeostasis50 (fIG. 1). The polarity of IECs also has a major role in regulating the response of TlR9 to bacterial DNA51. TlR9 is expressed both on the apical and basolateral membrane in polarized epithelial cells but only intracellularly in haematopoietic cells. Stimulation of basolateral TlR9 induces NF-κB activation and a pro-inflammatory response, whereas that of apical TlR9 leads to accumulation of NF-κB inhibitor α (IκBα), which blocks NF-κB activation. Apical TlR9 engagement triggers tolerance to various microbial stimuli and results in the production of ligands of the Wnt pathway that regulate the production of antibacterial factors and activate an alternative wnt pathway-dependent antimicrobial mechanism51 (fIG. 1). Thus, activation of apical TlR9 by commensal bacteria contributes to intestinal homeostasis by suppressing inflammation through a mechanism that is partly due to the induction of type I interferons (IFNs), which have been proposed to protect against colonic inflammation by preventing epithelial barrier dysfunction 52. In the presence of mucosal damage, however, microbial translocation takes place and leads to basolateral activation of TlR9, which results in a classical pro-inflammatory response51. NOD2. Mounting evidence points to a paramount role of NlRs (nucleotide-binding oligomerization domain (NOD)- and leucine-rich repeat (lRR)-containing proteins) in the intestine, and their dysregulation has been linked to IBD and colitis-associated colorectal cancer in experimental animal models. Notably, gene-linkage
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REVIEWS Adenomatous polyposis coli (APC). A scaffold protein that sequesters β-catenin in the cytoplasm of resting cells. APC mutations, which are found in 90% of intestinal cancers, lead to constitutively active β-catenin.
Box 2 | Animal models of colorectal cancer Various rodent experimental models have been established that reproduce aspects of human colorectal cancer. These models are based on genetic alteration of colorectal cancer pathways (such as Wnt–β-catenin, mismatch repair and transforming growth factor-β (TGFβ) pathways), modulation of factors involved in the mucosal immune response (such as interleukin-2 (IL-2), IL-10, β2-microglobulin, T cell receptor α-chain and G protein-coupled receptors) or treatment with carcinogens, particularly azoxymethane (AOM) or its precursor 1,2-dimethylhydrazine (DMH)124,125. Both DMH and AOM are procarcinogens with organotropism for the colon, and they need to be further metabolized into methylazoxymethanol to induce methylation of the O6 position of guanine, the primary pro-mutagenic lesion produced by AOM treatment125. Different mouse strains are variably susceptible to AOM-mediated induction of colorectal cancer: A/J mice are the most susceptible strain whereas the widely used C57Bl/6 mouse strain has low but variable susceptibility depending on the sub-line (for example C57Bl/6N, C57Bl/6J and C57Bl/6Ha mice)125. AOM induction of colorectal cancer is linked to the ability of AOM to induce mutations in genes that regulate several signalling pathways, including the KRAS, SRC–PI3K–AKT, Wnt–β-catenin, TGFβ and p53 pathways126. Unlike human colorectal cancer, in which adenomatous polyposis coli (APC) mutations are frequent and β-catenin mutations are present in only a minor subset of patients, in the mouse AOM model mutations in β-catenin predominate127. AOM-induced tumorigenesis is significantly enhanced by chronic colitis. Indeed, the number of adenomas and adenocarcinomas is dramatically increased when AOM administration is coupled with repeated treatments with dextran sulphate sodium (DSS), mimicking the pathological process of colitis-associated cancer128. The ApcMin/+ mouse model is among the most widely used mouse genetic models of colorectal cancer. ApcMin/+ mice are heterozygous for a nonsense mutation at codon 850 of Apc, the murine homologue of the human APC gene129. This mutation is analogous to one seen in patients with familial adenomatous polyposis. ApcMin/+ mice develop numerous tumours in the small intestine, and under some conditions develop colorectal cancers. These mice are also more susceptible to mammary and alveolar neoplasia compared with wild-type mice129. AOM treatment of ApcMin/+ mice induces tumorigenesis in the colon, which is otherwise rare in untreated mice. The mutant mice also form larger polyps after AOM treatment than wild-type mice. Interestingly, unlike AOM-induced colorectal cancer in wild-type mice, tumours that form in the colon of ApcMin/+ mice following AOM treatment do not harbour β-catenin mutations130.
studies and genome-wide association (GwA) studies of patients with Crohn’s disease have consistently identified mutations and single-nucleotide polymorphisms (SNPs) in the NOD2-encoding gene CARD15 (Ref. 53). NOD2 contains ten carboxy-terminal lRRs that mediate its ability to sense bacterial peptidoglycans, particularly mycobacterial N-glycolyl muramyl dipeptide (MDP)54. Most of the Crohn’s disease-associated mutations in CARD15 fall within this lRR region, resulting in reduced affinity for MDP. It is generally accepted that alterations in NOD2 function affect susceptibility to IBD because of the key role of this receptor in linking innate signals to the induction of adaptive immune tolerance to the intestinal microbiota. However, the exact mechanism or mechanisms by which defects in NOD2 signalling lead to pathology in Crohn’s disease have been heavily debated. At least five non-mutually exclusive models have been proposed (fIG. 2). The first model conjectures that NOD2 is a negative regulator of TlR signalling and that deficiency in NOD2 function leads to dysregulated TlR signalling, inflammation and colitis55. Consistently, MDP-mediated activation of NOD2 protects animals from experimental acute colitis56. It is possible, however, that the effect of MDP in this study was due to the triggering of IEC compensatory proliferation and tissue repair rather than inhibition of TlR-induced inflammation. The second model suggests that NOD2 signalling leads to polarization of the adaptive immune response towards a TH2-type response and that defects in NOD2 activation lead to excessive TH1 and TH17 cell-mediated inflammation57. The third model proposes that NOD2 is essential for the production of α-defensins by Paneth cells and that alterations in this process change the composition
of the microbiota or result in an overgrowth of pathogenic bacteria, leading to the characteristic granulomatous inflammation of the ileum in Crohn’s disease. Consistent with this third model, it has recently been reported that Nod2–/– mice that are inoculated with the opportunistic commensal pathogen H. hepaticus develop ileal inflammation, which was suppressed by the transgenic expression of α-defensin 5 by Paneth cells of Nod2–/– mice58. However, the reduced α-defensin production in the ileum of patients with Crohn’s disease has been shown to be independent of the CARD15 genotype59. Similarly, it has been reported that patients with Crohn’s disease have a suppressed inflammatory response irrespective of whether or not they carry a mutation in CARD15 (Ref. 60). The fourth model proposes a mechanism that applies to the regulation of human but not rodent NOD2 signalling, emphasizing the importance of interrogating immunological mechanisms in humans. It has been shown that mutant human NOD2 actively inhibits the expression of the anti-inflammatory cytokine Il-10 by suppressing the activity of heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1)61. In the fifth model, NOD2 is proposed to trigger autophagy in response to bacterial sensing 62. Autophagy is a catabolic process that is essential for maintaining cell homeostasis and is also required for bacterial clearance and antigen presentation by DCs62. Defective autophagy has been linked to increased susceptibility to infectious diseases, both in vitro and in vivo63. Recent findings from GwA studies of patients with Crohn’s disease have identified two autophagy loci, ATG16L1 (autophagyrelated 16-like 1) and IRGM (immunity-related GTPase family M), that are linked to Crohn’s disease susceptibility 64–66, suggesting that inefficient autophagy or handling
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Figure 2 | Proposed mechanisms of noD2 function in intestinal homeostasis. In addition to being expressed by ileal intestinal epithelial cells0CVWTG4GXKGYU^+OOWPQNQI[ (IECs) and colonocytes, nucleotide-binding oligomerization domain 2 (NOD2) is predominantly expressed by myeloid cells such as macrophages and dendritic cells. Five different models have been described to account for the role of NOD2 in suppressing the inflammatory response in the gut. The first proposes that NOD2 inhibits Toll-like receptor (TLR) signalling (a). The second describes a role of NOD2 in skewing the T helper (TH) cell response towards TH2 cells (b). The third implicates NOD2 in α-defensin production and subsequent limitation of commensal bacterial numbers and microbiome composition (c). The fourth argues that human NOD2 stimulates the production of the anti-inflammatory cytokine interleukin-10 (IL-10) by regulating heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) (d) and that mutant NOD2 inhibits this process. Finally, the fifth model conjectures that NOD2 stimulates autophagy by interacting with autophagy-related 16-like 1 (ATG16L1), which inhibits the inflammasome thereby suppressing the production of the pro-inflammatory cytokines IL-1β and IL-18 (e). NF-κB, nuclear factor-κB.
Inflammasome A large multiprotein complex formed by a NOD- and LRR-containing (NLR) protein, the adaptor protein apoptosisassociated speck-like protein containing a CARD (ASC; also known as PYCARD) and pro-caspase 1. The assembly of the inflammasome leads to the activation of caspase 1, which cleaves pro-interleukin-1β (pro-IL-1β) and pro-IL-18 to generate the active pro-inflammatory cytokines.
of enteric bacteria in genetically compromised individuals may contribute to disease pathogenesis. Interestingly, NOD2 was reported to interact with ATG16l1 to stimulate autophagy 67,68. DCs expressing Crohn’s disease risk variants of NOD2 or ATG16l1 (NOD2 l1007fsinsC (NOD2fs; a truncated protein resulting from a single nucleotide insertion and associated frameshift) or ATG16l1 T300A) display reduced induction of autophagy following stimulation of NOD2, and this results in reduced bacterial killing and defective antigen presentation67. It has been proposed that NOD2fs prevents ATG16l1 from localizing to sites of bacterial entry by retaining it in the cytoplasm68. Furthermore, ATG16l1-deficient mouse Paneth cells exhibit ultrastructural alterations and impaired secretion of antimicrobial peptides into the intestinal lumen in response to infection69. This phenotype seems to be triggered by infection with certain strains of norovirus (that are endemic in most animal colonies) and is dependent on the presence of commensal microorganisms70, suggesting that in the absence of autophagy, mucosal damage
induced by the virus alters the physiological interaction with the microbiota, leading to inflammation and colitis. whether this is fully dependent on NOD2 is not clear, but it is consistent with the dampened production of antimicrobial peptides observed in Crohn’s disease59. Moreover, ATG16l1-deficient macrophages exhibit enhanced responsiveness to TlR stimulation and exaggerated activation of the inflammasome71, which is similarly linked to increased susceptibility to experimental colitis71 (fIG. 2). Together these results indicate that aberrant bacterial handling could act as a trigger for inflammation in Crohn’s disease. The inflammasomes. Unlike NOD2, which triggers inflammation by activating NF-κB and mitogen-activated protein kinase (MAPK) pathways72, most NlRs recruit and activate inflammatory caspases in macromolecular complexes termed inflammasomes 73. These NlRs include NlRP (NlR family, pyrin domain-containing) proteins, NlRC4 (NlR family, CARD-containing protein 4; also known as IPAF) and NAIP (NlR family, apoptosis inhibitory protein; also known as NlRB1). Caspase 1 (encoded by CASP1) is the main effector inflammatory caspase; it directly processes pro-Il-1β and pro-Il-18 into their mature biologically active forms and induces an inflammatory form of cell death termed pyroptosis74,75. This process is distinct from apoptosis, which is immunologically silent. By contrast, caspase 12 is a repressor of the inflammasome and a molecular ‘brake’ on caspase 1 activity 76–78 (fIG. 1). A recent report has identified SNPs in a regulatory region downstream of the human NLRP3 gene, and these SNPs were found to be associated with Crohn’s disease susceptibility in individuals of European descent 79. SNPs in this region result in decreased NlRP3 expression and dampened Il-1 family cytokine production79. Of these Il-1 family cytokines, Il-18 is probably the most relevant for Crohn’s disease80. Il-18 is generally considered as a pro-inflammatory cytokine. It was originally described as an inducer of IFNγ, functioning mainly by amplifying the effect of other IFNγ inducers such as Il-12, and it was later shown to also enhance the production of other cytokines including TH2 cell-associated cytokines. The functions of Il-18 are complex and their possible contribution to the maintenance of chronic inflammation in the intestine is unclear. Il-18 receptor accessory protein (IL18RAP) polymorphisms have been associated with IBD81, whereas genetic data on polymorphisms of the IL18 gene promoter have been controversial82. Several studies have suggested that Il-18 could be an effector cytokine in IBD as circulating or local Il-18 levels have been associated with disease severity 83. For instance, it has been shown that Il-18 is required for DSS-induced colitis83,84, and this is consistent with its pro-inflammatory role. However, more recent investigations have shown that Il-18- or Il-18R-deficient mice are more susceptible rather than resistant to DSSinduced colitis and colitis-associated colorectal cancer 49,85,86. The mechanism by which Il-18 confers its protective effect on the colonic mucosa is reminiscent of its role in wound healing and repair in the skin87, but
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REVIEWS C6KUUWGTGRCKT
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Figure 3 | The inflammasome–caspase 1–Il‑18–Il‑18R–myD88 axis mediates tissue repair in the intestine. a | Following tissue damage with the intestinal epithelial cell (IEC) cytotoxic agent dextran sulphate sodium (DSS), the NLRP3 (NOD-, LRR- and pyrin domain-containing 3) inflammasome, which contains NLRP3, apoptosis-associated speck-like protein containing a CARD (ASC) and caspase 1, assembles in IECs. This leads to the0CVWTG4GXKGYU^+OOWPQNQI[ production of interleukin-18 (IL-18), which is then released at the mucosal sites. IL-18 binds the IL-18 receptor (IL-18R), which is expressed by myeloid cells in the lamina propria (and possibly by other cell types) and signals through the adaptor molecule myeloid differentiation primary response protein 88 (MYD88). IL-18 signalling induces compensatory proliferation of IECs and tissue repair. b | If this innate immune signalling pathway is impaired (as observed in mice that are deficient in caspase 1, ASC, NLRP3, IL-18, IL-18R or MYD88), persistent tissue damage leads to the translocation of commensal microorganisms to the submucosa, where they stimulate resident immune cells through Toll-like receptors (TLRs) and other pattern recognition receptors (not shown). Secretion of cytokines by activated immune cells results in tumour necrosis factor (TNF)-induced IEC apoptosis and chronic intestinal inflammation. TNFR1, TNF receptor 1.
Pyroptosis A form of cell death that is distinct from immunologically silent apoptosis. It is triggered concomitantly with the activation of the inflammasome and requires caspase 1 activity. During pyroptotic cell death, an inflammasome complex forms to activate caspase 1.
whether it acts directly or indirectly on IECs remains to be investigated. However, excessive production of Il-18 is pathogenic: hyperactivation of the inflammasome and subsequent elevated production of Il-1β and Il-18 by macrophages results in enhanced susceptibility to DSSinduced colitis71. Thus, it appears that Il-18 exerts a dual role in intestinal homeostasis and colitis. Early in the mucosal immune response, its expression by IECs mediates a protective effect88, but under chronic inflammation its excessive production by IECs and lamina propria mononuclear cells results in deleterious effects85,88. we and others have recently demonstrated a role for caspase 1 activation by the inflammasome in epithelial cell regeneration and tissue repair following injury in mice89–91 (fIG. 3). Casp1–/– mice are susceptible to DSS-induced injury with early mortality compared with wild-type animals. This phenotype is primarily ascribed to a lack of Il-18 production by Casp1–/– mice, as it is completely reversed by exogenous administration of this cytokine89,90. Regulation of the function of caspase 1 by caspase 12 is necessary for immune tolerance in the gut. Casp12–/– mice, in which the inflammasome is derepressed, are resistant to acute and chronic colitis89. However, as detailed below, the excessive repair response in these mice, together with an enhanced inflammatory response, renders them significantly more susceptible to colitis-associated tumorigenesis. Therefore, a physiological level of inflammasome activation, triggered by the commensal microbiota in the presence of mucosal injury, is necessary for epithelial cell regeneration and is protective from colitis and colitis-associated colorectal cancer (fIG. 3).
Innate immunity and colorectal cancer Animal models of colorectal cancer (BOX 2) have provided much information on the role of inflammatory mediators in the development of colitis-associated colorectal cancer. In particular, these studies have focused on the roles of innate immune cells, cytokines (such as TNF, Il-1, Il-6, Il-10, Il-11, Il-17, Il-18, Il-22 and Il-23), and the signal transducer and activator of transcription 3 (STAT3) and NF-κB axes92. Notably, the activation of STAT3 downstream of Il-6 and Il-11 signalling has a central role in intestinal mucosal regeneration after injury and in the development of colitis-associated colorectal cancer 93–95 (fIG. 4). The link between inflammation and gastrointestinal cancers is widely established; the canonical example is that of Helicobacter pylori and promotion of gastric cancer. Similarly, enterotoxigenic B. fragilis, which can activate the survival and inflammatory pathways mediated by wnt and NF-κB96, and attaching and effacing Escherichia coli strains, which induce severe colitis and downregulate genes encoding DNA mismatch repair proteins97, have been linked to increased risk of colorectal cancer. The important role of the commensal flora in the development of colon cancer is further underlined by the above-mentioned studies showing that alterations in the gut microbiota that induce colitis in TRUC mice also induce spontaneous progression to colonic dysplasia and rectal adenocarcinoma18. lack of tumour formation in germ-free mice was also observed in several genetic models of colorectal cancer (Il10–/– mice, Gpx1–/–Gpx2–/– mice and Tcrb–/–Trp53–/– mice)
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REVIEWS that are characterized by the inability to control excessive inflammation or by immunodeficiency. AOM increases the frequency of colitis-associated colorectal cancer in conventional Il10–/– mice, but neither colitis C+PLWT[KPFWEGFEQNKVKUCUUQEKCVGFEQNQTGEVCNECPEGT %QOOGPUCNDCEVGTKC
nor tumours are observed in AOM-treated Il10–/– mice that are germ-free or only associated with the mildly colitogenic bacterium Bacteriodes vulgatus 98. Similarly, colorectal carcinogenesis that was induced by AOM
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Figure 4 | A dual role for innate immunity in colitis‑associated colorectal cancer and intestinal malignancy. a | Signalling by the inflammasome, caspase 1, interleukin-18 (IL-18)–IL-18 receptor (IL-18R) and myeloid differentiation primary response protein 88 (MYD88) regulates the homeostasis of the intestinal epithelium and stimulates tissue repair after injury. Loss of these innate immune effector molecules impairs tissue repair, leading to microbial translocation to the lamina propria and chronic stimulation of mononuclear cells. This triggers excessive inflammation and tumour necrosis factor (TNF)-dependent intestinal epithelial cell (IEC) death, which exacerbates the vicious cycle of colitis. Ultimately, the inflammatory environment induced by damage and bacterial translocation promotes the development of colitis-associated colorectal cancer. However, the oncogenic mechanisms involved in the IEC transformation are not clear. b | Although innate immune responses are protective in the case of tissue injury, these responses need to be tightly controlled, as exaggerated caspase 1 activation in the absence of the inflammasome antagonist caspase 12 or exaggerated IL-18R or Toll-like receptor (TLR) activation in the absence of the antagonist single immunoglobulin IL-1-related receptor (SIGIRR) leads to increased incidence of colitis-associated colorectal cancer. This is also observed in the absence of the signal transducer and activator of transcription (STAT) inhibitor suppressor of cytokine signalling 1 (SOCS1; not shown), owing to increased STAT3 function in IECs. STAT3 is a critical effector of IEC proliferation during tissue repair and tumorigenesis and is activated downstream of the IL-6R or IL-11R signalling pathways. In these instances, excessive tissue repair and inflammatory responses drive the tumorigenic phenotype. c | By contrast, tumorigenesis initiated by intrinsic defects in pathways regulating cell proliferation, primarily in the Wnt–APC–β-catenin pathway as observed in ApcMin/+ mice or in mice treated with genotoxic compounds, is driven by inflammation and innate immune signalling pathways. Agonists from the commensal flora and alarmins produced in the tumour microenvironment trigger innate immune pathways to promote tumorigenesis. For instance, signalling through the adaptor MYD88 has been shown to mediate tumorigenesis in ApcMin/+ mice through extracellular signal-regulated kinase (ERK)-dependent MYC phosphorylation and stabilization. In the absence of MYC or MYD88, tumorigenesis in ApcMin/+ mice is markedly reduced. Thus defective innate immune signalling, as in MYD88-deficient mice, leads to decreased tumour burden owing to dampened activation of oncogenic and survival mechanisms. APC, adenomatous polyposis coli; DAMP, damage-associated molecular pattern; NF-κB, nuclear factor-κB; NLRP3, NOD-, LRR- and pyrin domain-containing 3; PRR, pattern recognition receptor; TNFR1, TNF receptor 1.
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REVIEWS
ApcMin/+ mice A mouse strain that carries a point mutation in one adenomatous polyposis coli (Apc) allele and spontaneously develops intestinal adenomas. It is used as a model for human familial adenomatous polyposis and for human sporadic colorectal cancer.
and promoted by bile injection in a subcutaneous cecal hernia was observed in conventionally reared rats but not in those raised under germ-free conditions99. These results indicate that tumour formation occurred only when the inflammatory response was initiated by stimuli derived from the commensal flora100. Importantly, intestinal infection of ApcMin/+ mice (a mouse model of sporadic colorectal cancer) with B. fragilis induces colorectal cancer 96 but, surprisingly, infection with H. hepaticus also induces mammary adenocarcinoma, providing evidence that the inflammatory status of the gut may have systemic effects101. Similarly, it has been shown that oral DSS treatment of wild-type mice induces DNA damage not only in intestinal cells but also in circulating T cells102. This damage seems to result in an altered response to the commensal flora and subsequently in an inflammatory environment that is responsible not only for colitis and colitis-associated colorectal cancer, but also for systemic damage in distant organs. Pro-inflammatory effector molecules released into the circulation and/or microbial translocation leading to systemic inflammation could mediate this systemic response. It has been suggested that a major mechanism by which MyD88 stimulates colorectal cancer in ApcMin/+ mice is through activation of a MAPK, extracellular signal-regulated kinase (ERK), which stabilizes the oncoprotein MyC by preventing its ubiquitylation and proteosomal degradation103. Indeed, in the ApcMin/+ mouse model, MyD88 signalling contributes to adenoma growth and progression104 (fIG. 4c). Myd88–/–ApcMin/+ mice display lower levels of phosphorylated ERK in the intestinal mucosa compared with wild-type mice and have fewer and smaller intestinal tumours. Interestingly, activation of ERK by epidermal growth factor (EGF), which is MyD88 independent, restores tumorigenicity in this model103. MyD88 signalling has also been shown to be required for colon carcinogenesis in two other mouse models: AOM-initiated colon carcinogenesis in Il10–/– mice98 and colon carcinogenesis induced by repeated treatment with AOM104. MyD88 is also necessary for skin chemical carcinogenesis105 and diethylnitrosamine (DEN)-induced liver cancer 106, two models in which host–microbiota interaction may have a role in initiating inflammation and promoting tumour initiation and progression. Thus, in different tissues, signalling through MyD88 is required for cell transformation and carcinogenesis. By contrast, MyD88 signalling is protective in the AOM plus DSS (injury)-induced colitis-associated colorectal cancer model49 (fIG. 4a). This observation suggests that the inability of Myd88–/– mice to heal ulcers generated by injury with DSS creates an altered inflammatory environment that exacerbates the mutation rate in mucosal epithelial cells and results in augmented adenoma formation and cancer progression. Recently, it was found that mice that are deficient in TlR2 reproduce, in part, the phenotype of Myd88–/– mice in the AOM plus DSS model, and display greater tumour incidence and an increased number and size of tumours compared with wild-type control mice107. However, Tlr4–/– mice, which largely reproduce the phenotype of
Myd88–/– mice in terms of their inability to efficiently repair the colonic mucosa following acute DSS-induced injury, are resistant to colitis-associated colorectal cancer 108. Although the contribution of other TlRs remains to be fully analysed, the susceptibility to colitisassociated colorectal cancer of Myd88–/– mice is not due to their inability to signal through TlR4. Instead, mice that lack expression of inflammasome components (caspase 1, apoptosis-associated speck-like protein containing a CARD (ASC; also known as PyCARD) or NlRP3), as well as mice that lack Il-18 or Il-18R expression, phenocopy Myd88–/– mice and display increased susceptibility to AOM plus DSS-induced colitis-associated colorectal cancer 49,91. This suggests that the susceptibility of Myd88–/– mice to colitis and colitis-associated colorectal cancer is in part due to their inability to signal through Il-18R49,91. Both tumour initiation and promotion are enhanced in mice that lack a component of the inflammasome–Il-18–Il-18R–MyD88 axis compared with wild-type animals, as illustrated by the enhanced number and size of polyps49. Interestingly, although the intestinal tissue repair response and IEC proliferation in response to damage are impaired in these mutant mice, their enterocytes express phosphorylated nuclear STAT3 and present evidence of induced activation of wnt–β-catenin, EGF receptor and MET proto-oncogene (HGF receptor) signalling pathways, as well as alterations in Smads expression. These features are suggestive of decreased signalling by the anti-proliferative factor transforming growth factor-β (TGFβ)49. Therefore, these cells are in a proliferation-prone state with activation of many of the cell cycle-inducing pathways, but an as yet unknown mechanism limits their ability to progress through the cell cycle in the repair response. Genetic alterations, possibly facilitated by a genomic instability that is secondary to the downregulation of mismatch repair genes in the absence of Il-18R–MyD88 signalling 49, may overcome such a block in proliferation, leading to colitis-associated colorectal cancer development. During DSS-induced colitis, Il-18 is probably produced prevalently by IECs89. Thus, studies implicating myeloid cells in DSS-induced colitis48 suggest that Il-18R–MyD88 signalling in these cells may be responsible for activating the still unknown mechanisms leading to efficient mucosal repair and tumour suppression. Unlike the ApcMin/+ mouse model of colorectal cancer, in which MyD88 is crucial for the activation of the Il-6–STAT3 pathway 104, in the AOM plus DSS model the damage-induced expression of Il-6 family cytokines and STAT3-dependent genes is independent of MyD88 (Ref. 49). It is plausible that the damage signal is transduced through TlR adaptor molecules other than MyD88, or through NlRs or other damage-associated molecular pattern (DAMP) receptors such as receptor for advanced glycation end-products (RAGE)109. Consistently, the DAMP high-mobility group box 1 (HMGB1) has been shown to induce Il-6 expression and mediate wound healing through RAGE110,111. An alternative hypothesis is that a pro-inflammatory response is intrinsically triggered by DSS-induced DNA damage
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REVIEWS Tumour immunosurveillance Tumour immunosurveillance or attack refers to the identification and elimination of cancerous or pre-cancerous cells by the immune system. However, as tumours do still develop despite a functioning immune system, the concept of ‘immune editing’ has taken over.
1.
2. 3. 4. 5. 6. 7.
without involving classical PRRs112. The expression of the cytokine IFNγ, which is important for tumour immunosurveillance, and IFNγ-dependent genes is reduced in Myd88–/– mice compared with wild-type animals49, which is consistent with the role of Il-18 in the production of IFNγ. Thus, the AOM plus DSS-enhanced tumorigenic phenotype in MyD88- or inflammasome-deficient mice, which express reduced IFNγ levels, might be partially due to impaired tumour immunosurveillance113. Together, these data suggest that mouse colon carcinogenesis models that depend on a genotoxic agent (AOM) along with a mucosal damaging stimulus (DSS) are fuelled by the extensive and durable mucosal erosion that occurs in inflammasome-, MyD88- or Il-18-deficient mouse strains. Thus, even in the absence of signalling through these major pro-inflammatory pathways, pro-carcinogenic genes (such as IL6, IL11 and COX2) are induced through alternative PRRs, indirectly through TNFR1 (Ref. 114), or alternatively through other molecular mechanisms of cell-intrinsic inflammation. Notably, it was observed that despite the lack of mucosal repair in this context, many cell cycle-activating genes were induced in the damaged epithelium. Therefore, it is conceivable that mutations induced by the initial AOM genotoxic treatment or successively by the DSS-triggered inflamed environment would render the few remaining epithelial cells more fit to hijack the growth and proliferation factors from the microenvironment and expand into clonal neoplastic lesions. Interestingly, the direct interaction of certain bacterial species with IECs can induce the downregulation of DNA repair genes97,115, similarly to what was observed in the colons of DSS-treated MyD88- or Il-18-deficient mice49. Thus, altered host–microbiota interaction could favour genetic instability and successive mutations that would further enhance tumorigenesis. Consistently, chronic treatment with DSS alone induces polyp formation in MyD88-deficient mice even in the absence of a genotoxic compound49. In contrast to tumorigenesis that is induced as a consequence of tissue damage, carcinogenesis that occurs in the presence of an intact, or readily repaired, epithelial barrier depends on MyD88 signalling for tumour development (fIG. 4b). Thus, genetic mutations that strengthen
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the inflammatory response, in particular downstream of PRRs, the inflammasome or MyD88, enhance tumour formation by creating an inflammatory environment that favours excessive tissue repair and tumorigenesis. Indeed, Socs1–/–, Sigirr–/– and Casp12–/– mice that exhibit enhanced inflammatory responses with inflammasome hyperactivation and/or increased signalling through TlRs, Il-1 family receptors and IFNγ receptors are highly susceptible to AOM plus DSS-induced tumorigenesis47,89,116,117. Excessive activation of these inflammatory pathways also enhances spontaneous tumorigenesis; accordingly, ApcMin/+Sigirr–/– mice have increased colonic polyposis compared with ApcMin/+ mice118. Therefore, we propose that the mucosal damage induced by DSS in MyD88- or inflammasome-deficient mice, together with associated microbial mucosal translocation89,90,119, are responsible for a dramatically different state of inflammation compared with that elicited during tumorigenesis in the context of an intact mucosal barrier, such as in mice with increased repair responses or in ApcMin/+ mice.
Future directions we are beginning to appreciate the intricacies of innate immune regulation and function in the intestine and it is becoming clear that the ablation of innate immune signalling in the gut as a therapeutic approach for intestinal pathologies needs to be revisited. The net outcome of the interaction between the commensal microbiota and the innate immune system is complex. During physiological conditions, the innate immune system is important for maintaining the homeostasis of the intestinal mucosa, but when altered it becomes the direct cause of the pathways underlying chronic inflammatory and neoplastic diseases. An emerging picture from recent investigations distinguishes between mucosal injury-mediated colitis and colitis-associated colorectal cancer versus pathologies arising in the presence of an intact mucosal barrier because of dysregulated inflammatory responses. The characterization of the innate immune mechanisms implicated in these two scenarios is underway and will certainly set the stage for the development of new and targeted therapies for IBD and intestinal cancer.
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Acknowledgements
M.S. thanks the students and colleagues in her laboratory for reading and commenting on this manuscript. Work in M.S.’s laboratory is supported by the Canadian Institutes for Health Research (MOP-79410, MOP-82801, MOP-86546, CTP-87520) and the Burroughs Wellcome Fund. Work in G.T.’s laboratory is supported by the Intramural Research Program of the US National Institutes of Health, National Cancer Institute, Center for Cancer Research, USA.
Competing interests statement
The authors declare no competing financial interests.
FURTHER INFORMATION Maya Saleh’s homepage: http://www.mcgill.ca/hostres/investigators/saleh Giorgio Trinchieri’s homepage: http://ccr.nci.nih.gov/staff/staff.asp?profileid=11574 European Commission MetaHIT: http://www.metahit.eu National Institutes of Health Roadmap Human Microbiome Project: http://nihroadmap.nih.gov/hmp All lInks ARE ACTIvE In ThE onlInE PDf
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REVIEWS
Imaging techniques for assaying lymphocyte activation in action Lakshmi Balagopalan*, Eilon Sherman*, Valarie A. Barr and Lawrence E. Samelson
Abstract | Imaging techniques have greatly improved our understanding of lymphocyte activation. Technical advances in spatial and temporal resolution and new labelling tools have enabled researchers to directly observe the activation process. Consequently, research using imaging approaches to study lymphocyte activation has expanded, providing an unprecedented level of cellular and molecular detail in the field. As a result, certain models of lymphocyte activation have been verified, others have been revised and yet others have been replaced with new concepts. In this article, we review the current imaging techniques that are used to assess lymphocyte activation in different contexts, from whole animals to single molecules, and discuss the advantages and potential limitations of these methods. Diffraction limit of light This refers to the physical impossibility of focusing light that is emitted from a point source into a single point owing to diffraction, which limits optical resolution to a distance of about half of the light wavelength (~200 nm for green light).
Laboratory of Cellular and Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA. Correspondence to L.E.S. e‑mail:
[email protected] *These authors contributed equally to this work. doi:10.1038/nri2903
Lymphocytes are a central component of immune defence mechanisms and have a pivotal role in our battle against pathogens. During adaptive immune responses, lymphocytes bearing antigen receptors identify and respond to rare pathogen-derived antigens without responding to self antigens. These cells continuously patrol the body, each in search of its cognate antigen. In many cases, such as T cell activation, physical contact between an antigen-presenting cell (APC) and a lymphocyte is required for the antigenspecific receptor to recognize and bind antigen. This initial binding event must be translated into a productive signal in the lymphocyte to generate a successful immune response. The consequences of inappropriate activation in this system are significant. Autoimmunity could result from inappropriate recognition of self, whereas a compromised immune response could lead to infection and death. Information on the events that are triggered by the binding of an antigen receptor to its ligand was initially obtained by biochemical studies, which successfully identified a large number of signalling molecules (including receptors, enzymes, adaptors and second messengers) that are required for lymphocyte activation1–3. Genetic manipulations have confirmed the role of many of these proteins and have aided in understanding the functional hierarchy of molecules in these signalling cascades4. These techniques provide very limited temporal and spatial information at the level of a single cell or molecule. Imaging approaches are unique in providing the ability to monitor individual events and to follow these events in time, thus allowing the investigator to
determine heterogeneity in the immune response and to understand the dynamics of lymphocyte signalling. Consequently, imaging studies have led to unexpected observations of the diversity and dynamics of lymphocyte–APC contacts, the spatial organization of the contact zone between the two cells and the intracellular molecular events. Although imaging of the immune system began more than 100 years ago with Elie Metchnikoff ’s early work on phagocytosis5, in the past three decades rapid advances in light microscopy have revolutionized our understanding of immune processes. Electron and advanced light microscopy techniques have been used to produce high-resolution images of lymphocytes in vitro. The advent of two-photon microscopy in the past decade has also made available data from in vivo settings. Most recently, high-resolution methods have broken the diffraction limit of light to probe subcellular features as small as single molecules. Thus, advances in imaging techniques have enabled the visualization of signalling events in lymphocytes with progressively greater spatial and temporal precision. In this Review, we provide an overview of the imaging toolbox that is used for visualizing lymphocytes during activation. We start out at the whole animal or tissue level, then zoom in to the cellular and subcellular levels and finally discuss techniques for imaging cells at molecular resolution (FIG. 1). Whole body imaging methods such as positron emission tomography (PET), magnetic resonance imaging (MRI) and bioluminescence are not covered and in vivo imaging is discussed only briefly. Instead, we focus on microscopy techniques
nATuRE REvIEWs | Immunology
voLuME 11 | jAnuARy 2011 | 21 © 2011 Macmillan Publishers Limited. All rights reserved
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Figure 1 | Imaging techniques: hierarchy of scale. The study of lymphocyte activation requires observation of samples that vary in size0CVWTG4GXKGYU^+OOWPQNQI[ over six orders of magnitude. This figure shows the T cell receptor (TCR)-mediated signalling pathway and microscopy techniques used at three levels of sample size. a | In whole organisms or intact tissues, encounters between lymphocytes and antigen-presenting cells (APCs) can be studied in situ using two-photon laser scanning microscopy (TPLSM). The specimen size is tens of millimetres. b | Cell–cell interactions and many subcellular details can be monitored using a large number of conventional microscopy techniques. These samples are typically several micrometres in size, but some details are at the diffraction limit of light scale. c | To observe molecular detail, high- and super-resolution imaging techniques are required. The samples here are individual molecules, only a few nanometres in size. DIC, differential interference contrast; LAT, linker for activation of T cells; PALM, photoactivated localization microscopy; SEM, scanning electron microscopy; SIM, structured illumination microscopy; STED, stimulated emission depletion; TEM, transmission electron microscopy; TIRF, total internal reflection fluorescence; ZAP70, ζ-chain-associated protein kinase of 70kDa.
Confocal microscopy A technique in which light that is emitted by fluorescent targets is passed through a pinhole, thus removing out-of-focus light and allowing accurate volume observation by the sequential acquisition of x–y images along the z axis.
Two-photon laser scanning microscopy A technique in which an image is formed by scanning a sample with a high-power pulsed laser. A spot of excitation is produced where the combined energy from the simultaneous absorption of two low-energy photons is sufficient to excite a fluorophore.
that have been used to visualize the subcellular details of lymphocyte activation, with a focus on T cells. We discuss each of the techniques in light of their advantages and limitations regarding resolution, sensitivity and physiological relevance. Although we highlight how these studies have offered unique insights into the molecular and cellular mechanisms that underlie lymphocyte activation, for an in-depth discussion of the biological implications of the data readers are referred to other reviews. our goal is to provide an up-to-date assessment of the methodologies for researchers who are considering the application of imaging techniques to the study of lymphocyte activation.
In vivo imaging The visualization of lymphocyte activation in vivo has always been a major goal of immune system imaging. After decades of inferring the in situ behaviour of lymphocytes from static tissue sections, three studies were published in the early 2000s that showed the interactions between live T cells and APCs in thymic organ cultures or explanted lymph nodes. one of these studies used conventional confocal microscopy6, whereas the others used two-photon laser scanning microscopy (TPLsM)7,8. Two-photon systems are advantageous because they use
long-wavelength infrared lasers that allow observation deep into tissues, while their small excitation volume decreases photobleaching and phototoxicity. These systems were then used for true in situ imaging of exposed lymphoid organs in living animals9,10. The first TPLsM imaging studies generated contradictory data on the motility of naive T cells as well as on the incidence, duration and stability of interactions between T cells and APCs. Further experiments showed that these parameters varied both with the strength of the T cell receptor (TCR) signal and with the location of the cells within the lymph node, information that could only be gained by observing individual cells in an intact organ11,12. Intravital TPLsM studies have continued, generating insights into the regulation of cytotoxic T lymphocytes (CTLs)13, CTL-mediated killing of tumour cells14 and autoimmune interactions of T cells in the central nervous system15. Recently, TPLsM has been used to monitor the correlation between interferon-γ gene (IFNG) expression and the diversification of T cell responses16. TPLsM has also been applied to the in vivo visualization of B cells. An early report showed an important role for chemokines in B cell responses17. other studies revealed that B cells contact antigens not just in solution, but also on the surface of dendritic cells (DCs) and macrophages18–21. In addition, TPLsM has been used to view a wide range of other processes, including germinal centre formation, antigen delivery by macrophages and calcium signalling in T and B cells12. In many in vivo imaging studies, lymphocytes are labelled with dyes or fluorescent proteins that are expressed throughout the cytoplasm (for TPLsM methods, refer to REF. 22). This generates an image of lymphocytes in a dark tissue volume, but offers little insight into how other components of the lymphoid organs affect lymphocyte activation. However, visualization of the extracellular matrix, either by second-harmonic generation signals23 or by labelling of stromal cells with green fluorescent protein (GFP)24, showed that lymphocytes migrate along reticular networks rather than wandering randomly through empty space. The generation of additional mouse strains that express fluorescently tagged molecules in non-lymphoid cells, as well as mice that express combinations of several proteins labelled with different fluorophores, will undoubtedly aid future studies. There are technical limitations that accompany the benefits that are gained by using TPLsM, including scattering of the emitted light and tissue heating by the infrared excitation light. Furthermore, two-photon systems are generally used at lower magnification and have lower axial resolution than confocal microscopy, limiting the view of subcellular details. In fact, the use of a confocal microscope in the study by stoll et al.6 allowed the authors to observe molecular details such as CD43 exclusion from the T cell–APC interface, providing early evidence for immunological synapse formation in vivo. Exciting recent work has extended in vivo imaging to the molecular level, with experiments in lymph nodes showing the localization of two fluorescent fusion proteins (linker for activation of T cells (LAT)–enhanced GFP25 and TCR–GFP26) during T cell activation.
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REVIEWS
Transmission light microscopy A technique that uses light to enlarge and image objects by passing the light through a set of lenses and subsequently detecting it by eye or with a detector.
Differential interference contrast microscopy A phase-imaging technique that produces contrast from differences in refractive indices at various parts of the sample.
Epifluorescence microscopy A technique that captures the fluorescence coming from the entire emitting volume of the sample.
Transmission electron microscopy A technique that produces an image from a beam of electrons that are transmitted through a thin specimen containing electron-dense material to create an image with a very high resolution of several Angstroms.
Scanning electron microscopy A technique that images the surface of a solid sample with high-energy electrons and detects features on its surface with a resolution of several nanometres.
Deconvolution A computational image restoration technique that removes the out-of-focus blur that is typical of epifluorescence images and improves both lateral and axial resolution.
The performance and applicability of in vivo imaging improve with each technical advance. Better detectors lead to better images, and high-sensitivity gallium arsenide phosphide photomultipliers are already being used in conjunction with TPLsM26. In situations in which the increased penetration of TPLsM is not needed, the sensitivity of confocal systems can be improved with electron-multiplying charge-coupled-device cameras, and this technology has been used to detect fungal infection of the brain in vivo 27. Furthermore, the recent combination of two-photon excitation with fluorescence lifetime microscopy allows more precise measurement of intracellular fluorescent resonance energy transfer (FRET) signals, thus enabling the use of FRET sensors in situ28,29. Adding an optical parametric oscillator to an infrared laser can extend the range of usable wavelengths to 1,600 nm, allowing imaging of deeper regions of tissues as well as imaging of red fluorescent proteins30. This technology has been used for intravital brain imaging of three fluorescent proteins31. Finally, other techniques are available for in vivo imaging, including optical-resolution photoacoustic microscopy, which has been used for imaging vascular beds, cancer cells and amyloid plaques32,33. so, although TPLsM has markedly improved our understanding of lymphocyte behaviour, the future will bring even higher resolution and more physiological imaging of the immune system.
Imaging of cell–cell interactions T cells and APCs have to find each other and engage in direct cell–cell contact to initiate an immune response. Although the in vivo studies described above examine the behaviour of cells in their natural or near-natural environment, current technologies do not have sufficient resolution to detect dynamic molecular details of activation in vivo. The in vitro studies described below have provided information about the activities of single cells at the subcellular and molecular levels and proved to be particularly fruitful in the study of lymphocyte activation. Morphological changes on initial contact. Migrating lymphocytes have a polarized morphology with a leading edge that is rich in actin and a trailing edge or uropod in which the microtubule-organizing centre and the Golgi apparatus are localized34. In the early 1980s, when the fluorescence microscope came into routine use, transmission light microscopy combined with fluorescent antibody detection techniques revealed that on contact with APCs, T cells rapidly polarize their cytoskeleton and Golgi apparatus towards the APC35,36. In one of the earliest imaging studies of immune cell activation, Geiger et al.37 combined electron and fluorescence microscopy to demonstrate the polarization of CTLs during the directional killing of target cells by monitoring the reorientation of their microtubuleorganizing centres towards the contact area between the cells. since then, immunologists have used increasingly advanced imaging techniques to visualize the APC–lymphocyte junction.
Imaging of the increase in intracellular calcium levels on TCR engagement was one of the first real-time observations of lymphocyte activation in live cells38. simultaneous differential interference contrast microscopy (DIC microscopy; also known as nomarski microscopy) and epifluorescence microscopy imaging of chemical calcium indicators revealed morphological changes and sustained global calcium increases in T cells following ligand engagement 39,40. As the resolution of light microscopy is limited, immunologists turned to other classic imaging techniques such as transmission electron microscopy and scanning electron microscopy to image the morphological changes induced by antigen recognition. The spatial resolution achieved by transmission electron microscopy (~0.1 nm) is far greater than that of light microscopy (~200 nm) and has thus allowed for imaging of the fine structure at the T cell–APC interface41,42. The resolution of scanning electron microscopy is lower than that of transmission electron microscopy but provides a good three-dimensional representation of cell surface morphology, producing striking images of the spreading response of T and B cells on activation43,44. Supramolecular changes on cell–cell contact. In concert with cell shape changes during antigen recognition, spatial reorganization of membrane proteins occurs at the junction of the T cell and the APC. The result is a clearly organized interface, several micrometres in diameter, termed the immunological synapse. The first detailed view of the immunological synapse was provided by the Kupfer laboratory more than a decade ago45 using optical deconvolution and digital reconstruction. This study revealed a ‘bull’s eye’ synapse with discrete concentric domains. TCRs and CD3 molecules occupy the central region termed the central supramolecular activation cluster (csMAC), which is surrounded by an outer ring of adhesion molecules in the peripheral sMAC (psMAC)45. subsequently, a third sMAC termed the distal sMAC (dsMAC), which is enriched with the phosphatase CD45, was detected in a ring outside the psMAC46. The immunological synapse has been identified at the stimulated interface of CD8+ T cells47, B cells44, natural killer (nK) cells48 and mast cells49. over the past decade it has become clear that there is not just one type of immunological synapse50,51. For example: some T cell lines, thymocytes and weakly stimulated T cells do not show sMAC formation52–54; in vitro T cell–DC conjugates tend to have multifocal synapses41; and mobile T cell– APC junctions known as kinapses55 have been observed. At the same time, our understanding of immunological synapse function has evolved considerably, and this subject has been recently reviewed56. The Dustin laboratory provided the first dynamic pictures of the stimulated T cell interface in a study in which the APC was replaced by planar lipid bilayers57 (discussed further below). other investigators probed the dynamics of activation in the context of two interacting cells. These studies used three-dimensional video microscopy to capture the T cell–APC interface and revealed that small TCR clusters and increased
nATuRE REvIEWs | Immunology
voLuME 11 | jAnuARy 2011 | 23 © 2011 Macmillan Publishers Limited. All rights reserved
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Figure 2 | Antigen-presenting cell substitutes used for lymphocyte activation. Several model systems have been developed to enable lymphocyte imaging at improved resolution. These models use a surrogate substrate for activation 0CVWTG4GXKGYU^+OOWPQNQI[ instead of an antigen-presenting cell (APC). a | Beads, typically coated with stimulatory antibodies, can be easily prepared and customized but do not allow rapid imaging of cell activation. b | Supported lipid bilayers that incorporate peptide–MHC molecules and other molecules such as integrins provide a better surface for imaging. Although the molecules are mobile, the bilayer lacks diffusion barriers that may be present in real cells. c | Coverslips that are coated with stimulatory molecules, including peptide–MHC molecules and antibodies, also allow controlled concentrations of a wide range of ligands and optimal surface imaging. However, the bound molecules are immobile.
Optical trapping A technique that uses a focused laser beam to exert small mechanical forces to trap cells or other microscopic objects in suspension, thus restricting or directing their motion and orientation and allowing their subsequent study by light microscopy.
calcium concentrations preceded the consolidation of the csMAC58,59. The recruitment of downstream signalling molecules into small, peripheral TCR clusters was also observed before csMAC consolidation in subsequent studies46,60. other supramolecular structures have also been observed using imaging techniques. Away from the immunological synapse, on the opposite side of the cell, an accumulation of proteins forms the distal pole complex 61,62. Interestingly, in addition to being localized to the immunological synapse as discrete puncta, the calcium-release-activated calcium (CRAC) channel components stromal interaction molecule 1 (sTIM1) and CRAC channel protein 1 (oRAI1) accumulate in cap-like structures opposite the immunological synapse at the distal pole of the cell63. visualization of the various sMACs, the distal pole complex and protein clusters highlights an important contribution that imaging studies have made to the understanding of T cell activation: specifically, how the partitioning of different molecules in different cellular compartments contributes to T cell responses. Moreover, the changing molecular composition of distinct domains over time indicates the importance of intracellular kinetics. However, imaging of the immune cell interface is fraught with challenges. As it is impossible to predict where the conjugates and synapses will form, it is extremely difficult to catch the earliest events of T cell activation. The complex topology of the T cell and the APC at the contact site requires the acquisition of large
z stacks to capture the interaction between the cells. This results in low temporal resolution, while spatial resolution is reduced to minimize acquisition time. several current approaches address these concerns. Optical trapping can be used to orient cells during synapse formation, allowing the direct visualization of the contact interface between the cells at markedly increased temporal and spatial resolution64. Another approach that has proved to be productive in the study of the stimulated lymphocyte surface is the use of surrogate stimuli on planar substrates.
Modelling the stimulated cell interface To experimentally manipulate lymphocyte activation, researchers have reduced the complexity of the system by substituting non-cellular surrogates for the APC. Ligandcoated beads are good substitutes for APCs and allow precise control of the activating ligands (FIG. 2a). Beadinduced activation has been used to address many issues, including T cell migration, calcium fluxes and the role of mitochondrial polarization during lymphocyte activation. However, it is still difficult to capture the dynamics of activation because the locations of the first contacts are unpredictable and it is still necessary to image a large three-dimensional volume. Instead, model systems in which the APC is replaced with a planar activation surface (such as an antigen-containing mobile lipid bilayer (FIG. 2b) or antibody-coated coverslip (FIG. 2c)) have produced the best high-resolution images of T cell activation. Planar substrates improve resolution because in lens-based microscopy the resolution in the horizontal
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Figure 3 | light-microscopy techniques that are widely used for cell imaging. a | Epifluorescence microscopy. 0CVWTG4GXKGYU^+OOWPQNQI[ b | Confocal microscopy. c | Total internal reflection fluorescence (TIRF) microscopy. d | Two-photon laser scanning microscopy (TPLSM). Illumination is depicted in yellow and the detection volume is labelled. The images show fluorescent clusters of linker for activation of T cells (LAT) in Jurkat T cells activated on antibody-coated coverslips.
Total internal reflection fluorescence microscopy A technique that uses an evanescent wave, which is generated when the excitation beam is completely reflected from the coverslip, to excite fluorescent molecules in a thin layer within about one hundred nanometres of the coverslip.
Interference reflection microscopy A technique that uses the interference of reflected rays of light to produce an image that contains only the regions of close contact between the cell and the contact surface (0–200 nm).
x–y plane is substantially better than that in the axial or z plane. As only a thin z-stack is required to capture the entire contact surface and the plane of activation is known beforehand, confocal microscopy (FIG. 3) can be used to view the rapid changes that are induced by activation. Moreover, since the activating surface is mounted on a coverslip, two additional high-resolution imaging techniques are available. The first, total internal reflection fluorescence microscopy (TIRF microscopy)65 (FIG. 3), improves z-plane resolution, and the second, interference reflection microscopy (IRM)66, produces an image that contains only the regions of close contact between the cell and the activating surface (0–200 nm from the surface). Morphological changes on planar substrates. IRM imaging of T cells on both bilayers and immobilized ligands demonstrated that dramatic morphological changes occur rapidly following T cell activation. Tight contacts containing polymerized actin were seen as the T cell touched the activating surface. on lipid bilayers, these tight contacts were made on the leading edge of migrating T cells57, whereas on immobilized ligands, the areas of first contact resembled filopodia67. Initial contact was immediately followed by a rapid burst of cell expansion that involves lamellipodia and the formation of an actin-rich ring 67,68. on immobile ligands, the cells maintain maximal spreading, whereas on mobile substrates, the spreading phase was followed
by contraction involving retrograde actin flow and myosin II-generated forces68,69. Experiments on planar substrates have shown that the polarization of the microtubule-organizing centre towards the immunological synapse depends on signalling through ζ-chainassociated protein kinase of 70 kDa (ZAP70), LAT and sH2 domain-containing leukocyte protein of 76 kDa (sLP76) to activate phospholipase Cγ1 (PLCγ1), creating local changes in diacylglycerol levels70. Microclusters as sites of activation. In 1999, Grakoui et al.57 visualized the changes in the localization of TCRs and lymphocyte function-associated antigen 1 (LFA1) following activation of T cells on a lipid bilayer. Following engagement with activating ligand, small peripheral clusters of TCRs were seen within 30 seconds of contact. These TCR-enriched discrete structures have been termed microclusters. In 2002, studies from the samelson laboratory using immobilized TCRspecific antibodies on coverslips and confocal microscopy showed that several signalling molecules were rapidly recruited to microclusters that were generated at the edge of the spreading T cells71. studies using immobilized ligands have determined that the initial complexes contain many kinases, scaffold proteins and effector molecules. These proteins include the TCR; the protein tyrosine kinases LCK and ZAP70; the adaptors LAT, growth factor receptor-bound protein 2 (GRB2),
nATuRE REvIEWs | Immunology
voLuME 11 | jAnuARy 2011 | 25 © 2011 Macmillan Publishers Limited. All rights reserved
REVIEWS GRB2-related adaptor protein 2 (GRAP2; also known as GADs), sLP76, non-catalytic region of tyrosine kinase (nCK) and Wiskott–Aldrich syndrome protein (WAsP); and the enzymes PLCγ1, Casitas B-lineage lymphoma (CBL) and vAv171–73. Larger glycoproteins, such as CD43 and the tyrosine phosphatase CD45, are excluded71. Huse et al.74 further refined the timing of these events using immobilized and photoactivatable peptide–MHC complexes, and showed that adaptor proteins are recruited to signalling microclusters within 4 seconds of activation. Investigators using TIRF microscopy of antigen– MHC ligands on lipid bilayers observed analogous TCR microclusters into which ZAP70, LCK, LAT and sLP76 were rapidly recruited75. Importantly, in both coverslip and bilayer systems, peripheral microclusters are predominant sites of tyrosine phosphorylation, and cytosolic calcium fluxes coincide with the onset of microcluster formation, indicating that they are sites of signal initiation. Moreover, defects in cluster assembly and persistence are associated with defects in T cell activation76,77. Planar activation has now also been used to study B cells, nK cells and mast cells. When activated by mobile ligands in a bilayer, the B cell receptor (BCR) forms microclusters that are necessary for early signalling events and for the subsequent translocation of the BCR microclusters to the centre of the contact interface. The recruitment of Lyn, PLCγ2, BLnK (B cell linker protein) and vAv1 to BCR microclusters has been demonstrated to date78.
Mechanical trapping The use of nanometre-scale structures built into lipid bilayers that act as barriers and inhibit the movement of T cell receptor microclusters.
Microcluster dynamics and signal termination. Realtime imaging studies have demonstrated the dynamic nature and changing composition of microclusters. on antibody-coated coverslips, the composition of the microclusters changes quickly as LAT and associated molecules separate from the immobilized TCR and ZAP7071. on lipid bilayers, the TCR is mobile and all of these proteins move towards the forming csMAC. However, signalling proteins, including kinases and adaptors, dissociate from the TCR as they translocate radially 75. Therefore, in both systems, although signalling molecules are initially recruited to TCR microclusters, a subset of molecules rapidly dissociates and can form separate signalling clusters. studies on lipid bilayers have also investigated the dynamics of the co-stimulatory receptors CD2 and CD28. Although both of these co-receptors initially form microclusters that contain TCRs, in the csMAC they localize to discrete regions away from the TCRs and support sustained signalling 79,80. Microcluster movement towards the centre of the contact interface involves the cytoskeleton, as radial movement requires actin retrograde flow, myosin II and an intact microtubule network68,69,81.This movement of microclusters has been linked with signal termination. Tyrosine phosphorylation occurs predominantly in peripheral clusters, whereas central clusters are thought to be sites where signalling is terminated by endocytosis and degradation82. Multiple studies have reported that clusters of signalling molecules undergo endocytosis as they move
towards the centre of the synapse and that this endocytosis depends on the cellular ubiquitin system81,83–86. Inhibition of the movement or internalization of clusters by mechanical trapping, inhibition of endocytosis or co-stimulation leads to enhanced signalling 83,85,87,88. An evaluation of planar models. Antibody-coated coverslips immobilize the TCR, and as a result individual microclusters can be visualized as they form, mature and evolve in composition over time. In addition, the lifetime of each constituent in a fixed cluster can be accurately determined. Furthermore, visualization of signalling complexes after they dissociate from the initiating receptor is possible. By comparison, in lipid bilayer studies the molecules can move laterally and physiological ligands can be incorporated into the bilayer. Importantly, the mobility of the ligands allows the tracking of receptor microclusters as they migrate radially inwards to form the csMAC. However, neither of these model systems accurately reproduces the forces exerted on microclusters following activation by an APC. Immobilized ligands fail to support TCR movement and immunological synapse formation, whereas the ligands in lipid bilayers are much more mobile than those presented by an APC. Moreover, the APC itself is important for activation, as perturbation of the DC cytoskeleton decreases T cell activation and WAsP-deficient DCs fail to form a stable immunological synapse89. nonetheless, experiments on planar substrates are responsible for the discovery and characterization of the dynamic microclusters that are the first sites of TCR activation. The existence and importance of microclusters have since been confirmed in cell–cell conjugates90. Thus, the investigation of model systems that can be imaged at high resolution can generate important observations, and these findings can then be verified with APC–lymphocyte conjugates.
Molecular interactions and dynamics The composition and dynamics of activation-induced microclusters have been largely studied by live-cell fluorescence imaging, as described above. We now discuss fluorescence microscopy techniques that have helped to refine the spatial and temporal resolution in the study of the motility and interactions of molecular signalling assemblies with submicrometre dimensions (FIG. 4). Early receptor activation events revealed by FRET. FRET has been used to look at ligand-induced conformational changes in antigen receptors, protein–protein interactions and early signalling events in lymphocytes. FRET is the non-radiative transfer of excited-state energy from an excited molecule, the donor, to a non-excited molecule, the acceptor. For energy transfer to occur, the emission spectrum of the donor molecule must overlap with the excitation spectrum of the acceptor, and the donor and acceptor must be in a favourable orientation, no more than 10 nm away from each other. on conducting careful control measurements, energy transfer can be reported in several different ways (see supplementary information s1 (box)).
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Figure 4 | Techniques for imaging molecular dynamics and interactions. a | Fluorescent resonance energy transfer (FRET) occurs when a suitable donor is in close proximity to an acceptor fluorophore; the process is illustrated here by 0CVWTG4GXKGYU^+OOWPQNQI[ arrows showing donor excitation, donor emission, energy transfer and acceptor emission. For bimolecular FRET, synthetic fluorescent probes (green and red stars) or fluorescent proteins can be used, whereas FRET sensors primarily incorporate fluorescent proteins. See Supplementary Information S1 (box) for further details on FRET measurements. b | Fluorescence recovery after photobleaching (FRAP), showing fluorescent proteins in a region of membrane undergoing selective photobleaching, followed by the recovery of fluorescence in this area as a result of repopulation with unbleached mobile molecules. c | Single-particle tracking (SPT), showing a single fluorescently tagged molecule as it is tracked over time.
The immune recognition receptors can undergo significant clustering on binding to antigen, and receptor clustering is considered to be important for the activation of signalling cascades that are associated with lymphocyte activation. However, the molecular events that initiate clustering remain undefined. To assess the earliest events that follow receptor binding, the Pierce laboratory used live-cell FRET imaging to probe the interactions between the different BCR subunits. They provided FRET-based evidence for monomeric BCRs on the surface of resting cells, and found that these BCRs then clustered on antigen binding. In addition, they showed that whereas antigen binding induced a conformational change in the membrane-proximal Fc portion of the BCR that promoted BCR clustering, the cytoplasmic domains of the
BCR moved apart 91,92. Thus, initiation of BCR signalling involves conformational changes in both the ectodomain and cytoplasmic domains of antigen-engaged BCRs. Conformational changes have also been invoked to explain TCR activation. However, this process has been poorly understood despite the efforts of several groups. Recently, Xu et al.93 used live-cell FRET imaging to show a close interaction between the CD3ε cytoplasmic domain and the plasma membrane. The FRET data, in combination with striking nuclear magnetic resonance measurements, led to the conclusion that CD3ε binds to the inner leaflet of the plasma membrane, burying tyrosine residues that are crucial for activation in the lipid bilayer. FRET has also been used to look at interactions between the TCR and co-receptors94.
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REVIEWS Measuring TCR–peptide–MHC binding with singlemolecule FRET. The relationship between the strength of TCR–peptide–MHC interactions and the final functional activation of a T cell remains an important unknown issue. Recently, Huppa et al.95 used FRET between single TCRs (on live cells) bound to peptide–MHC complexes on planar lipid bilayers to measure on-rates and to calculate off-rates from estimates of inter-probe distances. strikingly, they found dissociation rates in situ that were significantly (4–12-fold) faster than the rates obtained from measurements made in solution. However, an even larger (100-fold) increase in association rates resulted in an apparent increase in net affinity compared with solution measurements. In these experiments the ligands could freely diffuse away from the TCR following dissociation, but it is unclear whether the same mobility is allowed in a cellular context. FRET between proximal signalling molecules. FRET has been used to study interactions between various molecules in the signalling cascade that colocalize in microclusters. In addition to FRET between the TCR and the kinase ZAP70 (REF. 96), FRET was detected between PLCγ1 and LAT, CBL, vAv1 or sLP76, and between sLP76 and nCK within microclusters, indicating that there are direct interactions between these proteins when clustered72,73. By comparison, lower FRET was observed between LAT and either sLP76 or nCK, and this is consistent with previous data showing that these molecules interact indirectly. FRET was also used to follow the interactions between nCK and WAsP that lead to actin polymerization72. In addition, when the levels of proteins in multimolecular complexes were manipulated through gene silencing, FRET measurements were used to probe the cooperative nature of multimolecular interactions97. Further downstream in the signalling cascade, positive FRET between the calcium channel proteins sTIM1 (which is resident in the endoplasmic reticulum) and oRAI1 (which is localized in the plasma membrane) indicated a direct interaction between the calcium sensor and channel63,128,129.
Lipid raft An ordered sphingolipid- and cholesterol-rich membrane domain. These domains are thought to reside within the more diffusive and unordered pool of lipids of the plasma membrane.
Fluorescence recovery after photobleaching A technique that involves photobleaching fluorescent molecules in a region of a cell and then measuring the recovery of fluorescence that is due to the repopulation of the bleached area by diffusion of unbleached molecules.
Mapping protein activation across the cell. A wide range of FRET sensors have been developed and extensively used to study protein–protein interactions, enzymatic activity and local concentrations of second messengers in live cells. of specific interest to the study of lymphocyte activation are the sensors for monitoring membrane-restricted lipid molecules and intracellular levels of Ca2+, and activity reporters for proteins such as PLCγ, WAsP and protein kinase C98. Importantly, two recently developed sensors for monitoring the activity of LCK99 and ZAP70 (REF. 100) showed unexpected results when used in activated T cells. The LCK sensor indicated that neither significant conformational change nor phosphorylation on a key regulatory tyrosine is required for LCK to phosphorylate the TCRζ and CD3 chains. In experiments using the second sensor, ZAP70 activity was detected not just at the contact area but also at the distal pole of the cell following TCR activation.
Highly sensitive FLIM-FRET (see supplementary information s1 (box)) has also been used to look directly at early signalling events in lymphocytes. using FRET between a fluorescently tagged inhibitory nK cell receptor and a fluorescently tagged phosphotyrosine-specific antibody, the authors showed that phosphorylation was localized to discrete regions within receptor clusters101. Characterizing protein–lipid interactions. The first steps in antigen recognition and activation of lymphocytes take place at the plasma membrane, where protein–lipid interactions can have an important role. It has been suggested that lipid rafts, which are ordered sphingolipid- and cholesterol-rich domains in the plasma membrane, can coalesce on receptor activation into larger signalling domains that have an important role in lymphocyte activation102. However, the role of lipid rafts has come under considerable scrutiny 103–105 and imaging methods have provided evidence on both sides of the debate. Dynamic studies using dyes that are sensitive to plasma membrane ordering have indicated that raftlike domains arise during T cell activation at the contact site between T cells and APCs106–108. studies using transmission electron microscopy showed that ordered lipid phases were associated with signalling complexes 109–111. Furthermore, FRET-based studies in B cells showed that clustered BCR–lipid interactions exist, although they are weak and transient 112. By contrast, studies in T cells failed to show significant association of raft markers and microclusters, either by colocalization or by FRET analysis71,96,113. Furthermore, studies using LAT mutants showed that protein interactions, not lipid raft recruitment, were required for LAT localization to microclusters and confinement to signalling domains114. Further study will be needed to understand the role of lipid domains and to determine the forces that are involved in the formation of signalling complexes. Tracking of molecular dynamics using FRAP and SPT. The mobility of signalling molecules affects how signalling is translated into activation. Fluorescence recovery after photobleaching (FRAP) methods allow the evaluation of the mobility and diffusion of populations of molecules. studies of the dynamics of microclusters using this technique revealed the fast exchange of molecules at the clusters, although the clusters themselves were static71,114,115. In contrast to the unexpectedly fast dynamics of interactions between TCRs and peptide–MHC complexes that were revealed by singlemolecule FRET95, as discussed above, FRAP measurements showed unexpectedly slow off-rates for the interactions between the cell surface molecules CD2 and CD58 (REF. 116), suggesting that this interaction is longer-lived in the contact area than in solution. These FRAP measurements emphasize once again the need for detailed imaging measurements of molecular interaction rates in the contact areas between T cells and model APC interfaces or intact APCs, as the results are difficult to predict.
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REVIEWS Anisotropy A method that measures the loss of correlation in polarization between the polarized excitation light and the light emitted from a rotating probe; this can be used to indicate changes in rotation speed caused by binding of the labelled molecule.
By contrast, single-particle tracking (sPT) using TIRF microscopy tracks single fluorescent molecules in space and time, and is a powerful tool for following the dynamics of individual plasma membrane constituents. For example, previous FRAP and anisotropy studies suggested that the high-affinity Fc receptor for
IgE (FcεRI) must be immobilized to induce signalling. However, in a recent study, single quantum dot tracking showed that small, antigen-induced oligomers of IgE and FcεRI remained competent for signalling while being mobile, and became immobile only at elevated levels of multivalent antigen117.
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Figure 5 | High-resolution imaging techniques. These techniques are needed to image cellular structures beyond the 0CVWTG4GXKGYU^+OOWPQNQI[ diffraction limit of light. a | Super-resolution light microscopy techniques — photoactivated localization microscopy (PALM), fluorescence PALM (FPALM) and stochastic optical reconstruction microscopy (STORM) — are based on stochastic detection of single particles (red stars) and their subsequent bleaching and localization (white circles). Localized molecules are summed over time to reveal sub-diffraction-sized features. b | Structured illumination microscopy (SIM) uses a sequence of illumination patterns to decode cellular features (blue line) with different components of spatial orientation. Summing all of the resolved spatial components results in a super-resolved image of the cellular feature (solid grey line). c | Stimulated emission depletion (STED) microscopy uses two concentric focused illumination beams (yellow and orange cones) to reduce the effective volume of detection. The illumination beams are scanned across the cell to resolve small cellular features. d | Transmission electron microscopy (TEM) uses a beam of high-voltage electrons to image features within thin layers or membrane sheets of cells. nATuRE REvIEWs | Immunology
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REVIEWS Plasma membrane sheets The part of the plasma membrane of an adherent cell that remains on the adhering surface after the rest of the cell is removed during preparation for subsequent electron microscopy imaging.
Photoactivatable fluorophores Fluorophores (fluorescent proteins or synthetic fluorophores) that change their spectral properties on the absorption of light, providing a unique method for the optical labelling and tracking of molecules.
Fluorescence cross-correlation spectroscopy A spectroscopy method that correlates the fluctuations in intensity of two types of probes that diffuse through a small illumination volume, thus reporting on their binding.
sPT studies have provided detailed insights into the mobility of proteins in TCR microclusters. sPT of the adaptor LAT revealed that the mobility of LAT molecules at the T cell plasma membrane can change abruptly between immobility and rapid diffusion. Transient immobilization of LAT correlated strongly with encounter with clusters, indicating that LAT molecules diffuse between clusters and are occasionally trapped within clusters114. In a more recent study, the vale laboratory used sPT to gain insight into the mechanism of formation of the ‘bull’s eye’ immunological synapse68. Tracking of single intercellular adhesion molecule 1 (ICAM1) molecules showed that they rarely penetrated into the TCR-rich csMAC and were deflected when they encountered the edge of this region. These observations led to the suggestion that a diffusion barrier around the mature csMAC may help to exclude adhesion molecules from this region68.
A closer look at signalling domains The ability to study intact live cells in physiologically relevant conditions is a great advantage of light microscopy. However, the resolution of light microscopy is generally subject to the diffraction limit of light. Recent developments in light microscopy have been able to break the diffraction limit of light in multiple ways118 and currently pose new opportunities for studying the subcellular and molecular events that lead to the activation of lymphocytes. Super-resolution imaging of signalling microclusters. several techniques have been used to generate highresolution images of the microclusters that are formed following lymphocyte activation. Transmission electron microscopy images of the plasma membrane sheets of activated mast cells showed the formation of ‘primary signalling domains’ that include the receptor FcεRI, spleen tyrosine kinase (syK) and PLCγ2, and ‘secondary
signalling domains’ that include LAT and PLCγ1 but not the Fc receptor 109. These submicrometre-sized domains have been shown to exist before receptor activation. However, on receptor activation, these domains come into close contact to form larger patches that are probably equivalent to the microclusters observed by diffraction-limited light microscopy. More recent work from the Davis group has harnessed photoactivated localization microscopy (PALM) to give us the first direct look at the nanoscale organization of TCRs and LAT molecules at the plasma membrane of live T cells that are spread on lipid bilayers119. PALM is a super-resolution technique that is capable of resolving single fluorescent molecules. stochastic photoactivation of a few well-spaced molecules allows these individual emitters to be imaged until they are photobleached, and this sequence of events is repeated to build up an image120. Related techniques include fluorescence PALM (FPALM), stochastic optical reconstruction microscopy (sToRM; which uses sets of photoactivatable fluorophores) and a considerable list of other variants (FIG. 5). using rapid PALM imaging of live cells, Lillemeier et al.119 could identify the existence of discrete TCR and LAT domains (with dimensions in the order of 60–130 nm) in naive unactivated cells. In stimulated T cells, these ‘islands’ seemed to coalesce to form larger structures that were comparable in size to the microclusters observed by TIRF and confocal microscopy. Moreover, using dual-colour fluorescence cross-correlation spectroscopy (FCCs), they could further show that these domains migrated together only on TCR activation119.
Perspectives Current imaging technologies have generated considerable advances in our understanding of lymphocyte activation. Intravital imaging has provided new insights into lymphocyte behaviour in a physiological environment. Imaging of cell–cell contacts has led to an appreciation
Table 1 | Applications of imaging techniques Research question
live-cell imaging
Fixed-cell imaging
Molecular structure
No
Crystallography, electron microscopy
Conformational changes
FRET, single-molecule FRET
Crystallography, electron microscopy
Mobility of bound species
FRAP, FCCS, SPT
No
Intracellular activity of proteins FRET sensors, FRET
No
Intracellular localization
Confocal microscopy, STED microscopy
Confocal microscopy, STED microscopy, SIM, PALM
Aggregation state of receptors
Anisotropy, FRET, PALM, STORM, FCCS and TEM, PALM, STORM, FRET related analyses of molecular brightness
Mobility at the plasma membrane
TIRF microscopy, FRAP, SPT and sptPALM, confocal microscopy, STED microscopy
No
Cell morphology
Confocal microscopy, epifluorescence microscopy, TIRF microscopy, DIC microscopy
Confocal microscopy, epifluorescence microscopy, TIRF microscopy, DIC microscopy
Cell adherence to a surface
TIRF microscopy, DIC microscopy, IRM
TIRF microscopy, DIC microscopy, IRM, TEM
DIC, differential interference contrast; FCCS, fluorescence cross-correlation spectroscopy; FRAP, fluorescence recovery after photobleaching; FRET, fluorescent resonance energy transfer; IRM, interference reflection microscopy; PALM, photoactivated localization microscopy; SIM, structured illumination microscopy; SPT, single-particle tracking; STED, stimulated emission depletion; STORM, stochastic optical reconstruction microscopy; TEM, transmission electron microscopy; TIRF, total internal reflection fluorescence.
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REVIEWS Box 1 | Desired and novel imaging-related capabilities Combination of super-resolution and automated live-cell imaging Automated high-throughput imaging systems are currently used for multiparametric screening of cells. In principle, such systems are technically compatible with super-resolution imaging techniques, with the understanding that super-resolution will slow down the throughput of the system. High-resolution molecular imaging in situ Two-photon laser scanning microscopy (TPLSM) is able to activate several genetically encoded fluorescent proteins, thus enabling molecular imaging in situ. However, high-resolution imaging is limited by the low numerical aperture of long-workingdistance objective lenses and the significant loss of signal owing to tissue scattering and absorption. Using optimized, long-wavelength-emitting fluorescent proteins and getting closer to the imaged cells, for example using minimally invasive endoscopes, could substantially enhance in situ imaging capabilities. Real-time multiple-colour three-dimensional imaging The incorporation of highly sensitive imaging sensors, such as electron-multiplying charge-coupled devices, into the fastest three-dimensional imaging systems (for example, spinning-disk confocal microscopes or structured illumination microscopy systems with no moving parts) is expected to significantly accelerate the imaging of cells, while maintaining multiple-colour imaging capabilities (for example, by spectral multiplexing). Electron microscopy with genetic tagging Genetically encoded probes could be created for electron microscopy imaging that would serve as analogues to fluorescent proteins in light microscopy, but with the enhanced resolution provided by electron microscopy.
of the dramatic supramolecular changes that take place at the site of antigen engagement. Imaging at molecular resolution in cells has given us an understanding of the dynamic and heterogeneous nature of complexes and clusters as they evolve over time. These are just some examples of the observations from imaging studies that have substantially influenced our thinking about immune cell function. When considering the developments in imaging technologies and their effect on the study of lymphocyte activation, it is clear that one must carefully consider the strengths and limitations of the different techniques in light of the specific research question at hand (TABLE 1). no single current technology provides a simple solution for studying the molecular details of lymphocyte
1. 2. 3. 4. 5.
6. 7.
8.
Huse, M. The T-cell-receptor signaling network. J. Cell Sci. 122, 1269–1273 (2009). Lin, J. & Weiss, A. T cell receptor signalling. J. Cell Sci. 114, 243–244 (2001). Samelson, L. E. Signal transduction mediated by the T cell antigen receptor: the role of adapter proteins. Annu. Rev. Immunol. 20, 371–394 (2002). Schwartzberg, P. L. Genetic approaches to tyrosine kinase signaling pathways in the immune system. Immunol. Res. 27, 481–488 (2003). Kaufmann, S. H. Immunology’s foundation: the 100-year anniversary of the Nobel Prize to Paul Ehrlich and Elie Metchnikoff. Nature Immunol. 9, 705–712 (2008). Stoll, S., Delon, J., Brotz, T. M. & Germain, R. N. Dynamic imaging of T cell–dendritic cell interactions in lymph nodes. Science 296, 1873–1876 (2002). Bousso, P., Bhakta, N. R., Lewis, R. S. & Robey, E. Dynamics of thymocyte–stromal cell interactions visualized by two-photon microscopy. Science 296, 1876–1880 (2002). Miller, M. J., Wei, S. H., Parker, I. & Cahalan, M. D. Two-photon imaging of lymphocyte motility and antigen response in intact lymph node. Science 296, 1869–1873 (2002).
9. 10.
11. 12.
13.
14.
15.
activation in vivo in real time. Physiological context may have to be sacrificed to some degree for higher resolution, or vice versa. Given these trade-offs, a combination of low-resolution in vivo imaging and high-resolution in vitro experiments will allow advances in the study of where, when and how lymphocytes become activated. nevertheless, there have been constant improvements in both in vivo and in vitro imaging systems. Advances in TPLsM technology 121 and the generation of various fluorescent reporter mice will take us a long way towards the long-term goal of imaging the molecular details of cells in their natural environment. At the same time, the addition of better planar models of the cellular interface122 and the use of optical tweezers or other techniques to optimally visualize cell–cell interactions64 will improve the high-resolution imaging of activated lymphocytes. Another key issue related to cell imaging is the diversity and heterogeneity of the cells themselves, and the choice of samples may be subject to the bias of the observer. As imaging is generally a low-throughput process, the recent introduction of automated instruments for highspeed sequential imaging of cells (such as imaging flow cytometry systems123,124 and high-throughput screening systems with imaging capabilities) will allow users to collect an immense number of unbiased images with minimal compromise on resolution. Looking ahead, recent developments in advanced imaging techniques and their integration into commercially available systems are likely to greatly improve our capability to image lymphocytes. Many turn-key microscopes can now integrate some kind of superresolution technique, including structured illumination microscopy (sIM), PALM or direct sToRM (dsToRM), sToRM and stimulated emission depletion (sTED) microscopy117 (FIG. 5). Furthermore, the continuous introduction of new labelling reagents and modalities125–127 promises a bright and colourful future for imaging of molecular details. Given the rapid rate of technological advances, we expect significant progress in the near future towards our ultimate wish of realtime, targeted probing of molecular dynamics and interactions in live cells in vivo (BOX 1).
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Acknowledgements
We thank R. Kortum for critically reading the manuscript. This research was supported by the Intramural Research Program of the National Institutes of Health (NIH), National Cancer Institute (NCI), Center for Cancer Research (CCR).
Competing interests statement
The authors declare no competing financial interests.
SUPPLEMENTARY INFORMATION See online article: S1 (box) All lInks ARE ACTIvE In THE onlInE pdF
voLuME 11 | jAnuARy 2011 | 33 © 2011 Macmillan Publishers Limited. All rights reserved
REVIEWS
The double life of a B-1 cell: self-reactivity selects for protective effector functions Nicole Baumgarth
Abstract | During their development, B and T cells with self-reactive antigen receptors are generally deleted from the repertoire to avoid autoimmune diseases. Paradoxically, innate-like B-1 cells in mice are positively selected for self-reactivity and form a pool of long-lived, self-renewing B cells that produce most of the circulating natural IgM antibodies. This Review provides an overview of the developmental processes that shape the B-1 cell pool in mice, outlines the functions of B-1 cells in both the steady state and during host defence, and discusses possible functional B-1 cell homologues that exist in humans. Natural antibodies Antibodies found in individuals who have not had any previous known exposure to the antigens recognized by the antibodies.
T cell-independent antigens Antigens that directly activate B cells.
Follicular B cells Recirculating, mature B cells that continuously develop from precursors in the bone marrow and populate the follicles of the spleen and lymph nodes.
Center for Comparative Medicine, University of California, Davis, California 95616, USA. e-mail:
[email protected] doi:10.1038/nri2901 Published online 10 December 2010
B cells, as producers of specific antibodies, are hallmark effector cells of the adaptive immune system, but not all antibody production is triggered by prior immune activation. Experiments with germ-free mice have shown that the production of natural antibodies occurs even in the absence of microorganisms1–3 and, as such, must be regulated differently from the induction of specific antibodies during infection. Furthermore, it has been known since the 1970s that B cells can proliferate and secrete antibodies in response to the ubiquitous Gramnegative bacterial cell membrane component lipopolysaccharide (LPS) independently of their specific B cell receptor (BCR)4. This led some investigators to conclude that in the case of T cell-independent antigens, B cell activation is independent of the fine specificity of the BCR5. The identification of Toll-like receptor 4 (TLR4) as the recognition receptor for LPS and subsequent studies of other pattern recognition receptors (PRRs) have shown that B cells express numerous innate immune receptors, including TLR3, TLR4, TLR7, TLR8 and TLR9 (Refs 6–8). However, not all B cells respond equally to innate immune signals. The largest population of B cells, known as follicular B cells or B-2 cells, responds less well to LPS stimulation than do splenic marginal zone B cells and B-1 cells; these latter subpopulations seem to be involved mainly in T cell-independent and innate-like immune responses9,10. So, some B cell subsets might be considered to be effectors of the innate immune system. B-1 cells are the main producers of natural antibodies and participate in maintaining tissue homeostasis, as well as in immune defence against mucosal pathogens, by expressing a BCR repertoire that is enriched for
highly polyspecific (that is, crossreactive) receptors that bind to both self antigens and microbial antigens11–13. The selection of B-1 cells for self-reactivity seems contrary to existing models of tolerance induction and discrimination between self and non-self, and it indicates that a distinct developmental programme underlies the development of this unusual innate-like B cell subset; these cells must differ in function and be regulated differently from conventional B-2 cells. This Review focuses on the development, function and regulation of innate-like B-1 cells. I review our current understanding of B-1 cell development and the functions of these cells in the steady state, where they are involved in maintaining tissue homeostasis. I also discuss the contribution and response patterns of B-1 cells following pathogen encounter. I do not focus on their role in autoimmune diseases, as this has been reviewed elsewhere14–16. Finally, I discuss the current candidates in humans for the functional homologues of mouse B-1 cells.
B‑1 cell subsets Mouse B-1 cells were first described in 1983 as a relatively small population of CD5+ splenic B cells (at the time, CD5 was known as Ly5.1 and was thought to be a T cell-specific marker) that spontaneously secrete IgM and are markedly increased in number in autoimmuneprone NZB/NZW f1 mice, thereby linking these cells to autoimmunity 17. Later studies showed that B-1 cells are the main B cell population in the peritoneal and pleural cavities of common laboratory mouse strains, but are rare in lymph nodes18. Other studies described the presence
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REVIEWS Marginal zone B cell A type of mature B cell that is enriched in the marginal zone of the spleen. These cells recognize antigen through semi-invariant receptors, which stimulates their rapid differentiation to antibody-secreting cells. They are thought to be important for host defence against circulating blood-borne pathogens.
NZB/NZW F1 mice
The f1 generation of the cross between New Zealand black (NZB) mice and New Zealand white (NZW) mice. NZB/NZW f1 mice have a disease that closely resembles the human disease systemic lupus erythematosus.
Splanchnopleura region An embryonic tissue in developing mice and birds that functions as an important site of primitive haematopoiesis
Terminal deoxynucleotidyl transferase (TdT) An enzyme expressed during lymphocyte development that inserts nucleotides into the variable regions of T cell receptor and immunoglobulin genes, to create junctional diversity.
of a second, minor subset of B cells that closely resemble these CD5+ B cells in terms of their tissue distribution, phenotype and development, but do not express CD5 (Ref. 19) (BOX 1). The term ‘B-1 cells’ was adopted for these cell subsets20, as they develop earlier than follicular B cells during ontogeny 21. B-1 cells expressing CD5 are known as B-1a cells and those lacking expression of CD5, but having other hallmarks of B-1 cells, are known as B-1b cells. The phenotypically distinct follicular and marginal zone B cell populations were termed ‘B-2 cells’ as they develop later in ontogeny than B-1 cells and develop from a common bone marrow precursor20. Currently, the term B-2 cell is used mostly in a narrower sense to describe follicular B cells. The relationship between the recently identified interleukin-10 (IL-10)-producing regulatory B cell population22–24 and B-1 and B-2 cells is currently unclear. These regulatory B cells share some functional (IL-10 production) and phenotypical (CD19hiCD5+) characteristics with B-1a cells, but they also have similar characteristics to marginal zone B cells (high-level expression of CD1d and CD21). Similarities in terms of functional characteristics between marginal zone B cells and B-1 cells have been described before25. The regulatory B cell subset might therefore be a new member of an emerging group of ‘innate-like’ B cell populations, which in mice include B-1a cells, B-1b cells and marginal zone B cells (see below) (fIG. 1).
B‑1 cell development To understand the functions of B-1a and B-1b cells, it is important to also understand the mechanisms underlying their development, although these are as yet incompletely resolved. Two models have been put forward to
Box 1 | The phenotype of B‑1 cells The identification of B‑1 cells outside of the peritoneal and pleural cavities is challenging, owing to their low frequency and the lack of a clearly discernable, discrete marker for these cells. B‑1a and B‑1b cells are usually identified by a combination of at least six cell surface markers, having the phenotype CD19hiCD23–CD43+IgMhiIgD(variable) CD5± (Refs 136,137). B‑1 cells are also slightly larger in size than conventional, resting B‑2 cells. The levels of CD5 expressed by B‑1a cells are at least tenfold lower than those on T cells; therefore, sensitive reagents are needed for the flow cytometric detection of CD5 expression by B‑1a cells, and CD5 is generally not a suitable marker for identifying B‑1a cells by immunohistochemistry137. In the coelomic cavities, many but not all B‑1a and B‑1b cells express the integrin CD11b138,139, but they lose expression of this integrin after leaving these sites86. A subset of B‑1 cells in the body cavities (20–30%) lack CD43 expression140, but almost all B‑1 cells in other tissues express CD43 (Y. S. Choi, J. Dieter, K. Rothaeusler, Z. Luo and N.B., unpublished observations). So, B‑1 cells outside of the peritoneal and pleural cavities phenotypically resemble activated, unswitched IgM+IgDlowCD23– conventional B‑2 cells, which can upregulate CD43 expression during differentiation to antibody‑secreting cells. Even CD5, which is often used as a distinct B‑1a cell marker, can be induced on B‑2 cells after in vitro activation through the B cell receptor141 and is expressed by anergic B‑2 cells99. Additional markers of B‑1 cells are the interleukin‑5 receptor, which is also expressed by pre‑plasmablasts142, and CD9, which is highly expressed by B‑1 cells but also by splenic marginal zone B cells and plasma cells143. Taken together, these data show that the phenotypical profile of B‑1 cells resembles in many, but not all, aspects that of antigen‑experienced B cells. The unequivocal identification of B‑1 cells therefore requires adoptive transfer, or other approaches that introduce discrete markers, so that their identification does not rely on surface phenotype alone.
explain B-1 cell development: the ‘lineage hypothesis’ proposes that B-1 and B-2 cells develop from distinct B cell precursors; the ‘induced differentiation hypothesis’ proposes that a common precursor can give rise to either a B-1 or B-2 cell depending on the specific signals received during development and selection. For an in-depth discussion of the experimental details underlying each model the reader is referred to previously published reviews26–28. B‑1 cell ontogeny. B-1a cells are efficiently generated both before birth and during the first few weeks after birth. B-1a cell-restricted precursors have been found as early as day 8.5 of mouse embryonic development in the splanchnopleura region21. The fetal liver is also an efficient source of B-1a cells28, but B-1a cells are generally poorly reconstituted from the bone marrow in adult mice28. B-1b cell precursors have not been identified in the splanchnopleura region of the developing embryo21, but B-1b cells can be reconstituted from fetal liver and, to a greater extent than B-1a cells, from B-1 cell-restricted precursors in adult bone marrow 27. In contrast to the continuous de novo development of B-2 cells, once B-1 cells have populated the various tissue locations of the host, the de novo influx of B-1 cells during adulthood seems to be severely restricted under steady state conditions29. Instead, B-1 cells seem to be maintained by a process termed ‘self-renewal’; that is, they undergo limited proliferation to replace dying cells and sustain a stable population size over time. Indeed, B-1 cells in the peritoneal cavity have slow turnover rates 30, and their introduction into the peritoneal cavity of neonatal, short-term B celldepleted hosts can completely reconstitute B-1 cells in all host tissues for many months, with little influx from host-derived cells. In such mice, no more than 10–20% of B-1 cells are derived from host bone marrow at 8 months after donor cell transfer, whereas the B-2 cell compartment is completely host derived within weeks29,31. This feedback inhibition of de novo B cell development might be mediated, at least in part, by secreted IgM, as mice deficient for secreted IgM have an enlarged B-1 cell compartment 30,32. However, following alterations to the steady state, such as the depletion of peripheral B-1 cells by irradiation or chemical ablation, B-1 cells can be reintroduced into the periphery from bone marrow precursors33,34. This process is much slower than the reconstitution of the B-2 cell pool35 and the physiological signals that regulate self-renewal versus de novo generation of B-1 cells are unknown. Early studies showed that immunoglobulin heavy chain variable region (VH) gene usage by B-1 cells is more restricted than that of adult B-2 cells and instead resembles that of embryonic-derived B cells36. also, B-1 cells have fewer non-templated nucleotide insertions in their immunoglobulin genes than do B-2 cells36,37, although these do occur in B-1 cells more frequently than was originally thought 37. as the expression of terminal deoxynucleotidyl transferase (TdT) is induced only after birth38, the data are consistent with the concept
naTuRE REVIEwS | Immunology
VOLuME 11 | januaRy 2011 | 35 © 2011 Macmillan Publishers Limited. All rights reserved
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Figure 1 | mature splenic B cell subsets. Five subsets of mature B cells are present in the mouse spleen. Bone marrow-derived follicular B cells and marginal zone B cells, which form the B-2 cell population, constitute the majority0CVWTG4GXKGYU^+OOWPQNQI[ of splenic B cells and differ from each other in terms of phenotype and location (they are found in the B cell follicles and marginal zone, respectively). B-1a and B-1b cells are clearly distinct but are minor subsets in terms of their frequency in the spleen. B-1a and B-1b cells can be distinguished phenotypically on the basis of CD5 expression: B-1a cells are CD5+ and B-1b cells are CD5–. A regulatory B cell subset that expresses high levels of CD1d was recently identified among CD23+ B cells (BOX 2). Other studies have reported the existence of regulatory B cells among CD1dhiCD5+CD23– B cells. Therefore, regulatory B cells have phenotypical markers of both B-1 and B-2 cells. The relationship between regulatory B cells and the other mature B cell subsets is currently unknown.
of a predominantly fetal or neonatal origin of the B-1 cell pool, followed by self-renewal. However, given the presence of some non-templated nucleotide insertions in the immunoglobulin genes of the B-1 cell population, the data also indicate that some replenishment from adult-derived precursor cells occurs over time in the steady state (that is, without induced leukopaenia)39.
Negative selection The process by which developing lymphocytes expressing potentially autoreactive antigen-specific receptors are induced to undergo apoptosis.
B‑1 cell selection. antigen specificity is a crucial determinant of B-1 cell development and function. B-1 cells secrete antibodies that are specific for self antigens, such as oxidized lipids40 and antigens expressed by apoptotic cells, including annexin IV and phosphatidylcholine41. In addition, B-1 cell-derived antibodies have specificity for pathogen-expressed molecules, including phosphorylcholine of Gram-positive bacteria, LPS of Gram-negative bacteria and various viral and parasite-expressed antigens (reviewed in Ref. 42). These polyreactive germline-encoded antibodies produced by B-1 cells form the natural antibody repertoire, which is generated in the complete absence of foreign antigen exposure1–3. The overall low affinity of B-1 cellderived antibodies for self antigens might allow these cells to evade negative selection, in a similar manner to T cell development in the thymus, whereby thymocytes with a low-affinity T cell receptor are spared from apoptosis43. However, evasion from negative selection does not explain the apparent enrichment of the B-1 cell repertoire for self- and polyreactive specificities. a seminal study 44 provided a compelling explanation
for this enrichment of the B-1 cell repertoire, by showing that autoantibody-producing B-1 cells undergo a positive-selection event, indicating that B-1 cells are actually selected for their self-reactivity. The study showed that gene-targeted mice lacking the Thy1 antigen (also known as CD90) did not develop Thy1-specific B-1 cells or secrete Thy1-specific antibodies, which are commonly found in wild-type mice. Such BCR-mediated positive selection seems to be restricted to the development of B-1 cells. For example, the frequency of B-1 cells in BCR-transgenic mice — generated with immunoglobulin genes that encode a known BCR specificity of B-1 cells — was markedly decreased after the introduction of a second, B-2 cellderived immunoglobulin heavy chain; furthermore, the few remaining B-1 cells had deleted the B-2 cell-derived BCR transgene45. These data strongly argue in favour of positive selection based on BCR specificity being a crucial step during the development of B-1 cells. Further support for a BCR-mediated positive selection event during B-1 cell development comes from studies indicating that BCR signal strength is the determining factor in B-1 cell selection46; numerous studies showed that the deletion of positive regulators of BCR signalling, or the deletion of co-stimulatory molecules, resulted in a decreased number of B-1 cells or eliminated them entirely, whereas the removal of negative regulators of BCR signalling increased the frequency of B-1 cells (reviewed in Ref. 26). So, BCR signalling mediated by self-recognition during development seems to be a crucial positive selection event during B-1 cell development. Positive selection also explains how a natural antibody repertoire, derived mainly from germline-encoded sequences and lacking non-templated nucleotide insertions, can be faithfully recapitulated in all individuals, despite the fact that antibody generation relies on the stochastic assembly of V-D-j immunoglobulin variable genes during B cell development. A two‑pathway model of B‑1 cell development. The recent identification of a precursor cell in bone marrow and fetal liver that specifically gives rise to B-1 cells (mainly B-1b cells) is the most definitive evidence so far in support of the lineage hypothesis of B-1 cell development 35,47. However, these data do not completely resolve the issue of B-1a cell development 16, and do not preclude that under certain physiological conditions, B-2 cell precursors with the appropriate antigen specificity could give rise to B cells that have all the attributes of B-1 cells. I suggest therefore that the existing models of B-1 cell development (the lineage and induced differentiation models) are not mutually exclusive, and instead function as two coexisting developmental pathways that ensure the generation and maintenance of the B-1 cell pool throughout pre- and post-embryonic life. The incorporation of these two pathways into a combined model, which I refer to as the ‘two-pathway model’ of B-1 cell development (fIG. 2), is in my view most consistent with the existing experimental evidence.
36 | januaRy 2011 | VOLuME 11
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REVIEWS In the two-pathway model, B-1 cell pools are established before and within a few weeks after birth. Once they have been generated, B-1 cells inhibit further de novo B-1 cell development through feedback inhibition. The B-1 cell pools are maintained mainly by
self-renewal under steady state conditions, a process that might uniquely rely on cyclin D2 (Ref. 48), and they are supported, particularly early in life, by the constitutive secretion of IL-5 and also IL-9 (Refs 49,50); the latter mainly expands B-1b cell populations. It is
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Figure 2 | B-1 cell development in the steady state and after B-1 cell ablation. Current data support a two-pathway model of B-1 cell development, in which B-1 cell generation differs depending on the stage in ontogeny. During late embryonic life and around the time of birth, peripheral B-1a cells are mainly selected in a process that requires B cell 0CVWTG4GXKGYU^+OOWPQNQI[ receptor (BCR) signalling and positive selection on self antigens. This process generates a biased neonatal repertoire of BCR specificities, characterized by the over-representation of certain immunoglobulin heavy chain variable region (VH) genes and a lack of non-templated nucleotide insertions. By contrast, B-2 cells that bind self antigens are mainly deleted from the peripheral B cell repertoire. Once B-1a cells are fully developed, the peripheral B-1a cell compartment is maintained by self-renewal through the continuous turnover of existing B-1a cells. In the steady state, bone marrow precursor cells contribute little to the peripheral B-1 cell compartment. By contrast, B-2 cells are slowly but continuously replenished (the half-life of splenic B-2 cells is approximately 5 months148) and develop de novo from bone marrow precursors. Alterations in the steady state that decrease the size of peripheral B-1 cell pools lead to increased de novo synthesis or selection of B-1 cells into the mature pool. This results in the accumulation of the ‘adult’ B-1 cells that are observed in older animals and that have abundant non-templated nucleotide insertions and broader VH gene usage. naTuRE REVIEwS | Immunology
VOLuME 11 | januaRy 2011 | 37 © 2011 Macmillan Publishers Limited. All rights reserved
REVIEWS Omentum A large fold of peritoneum between the stomach and abdomen that contains lymphoid aggregates known as ‘milky spots’.
Coelomic cavities Pleural and peritoneal body cavities, which are surrounded by a thin layer of serosa that contains the internal organs.
possible that a recently identified population of innate KIT +SCa1 + lymphoid cells in adipose tissue is the main source of the IL-5 necessary for maintaining B-1 cells51. Over time, precursors in the bone marrow 35 also contribute to the B-1 cell pool, thereby broadening the neonatal repertoire of B-1 cells, particularly of B-1b cells, to include additional VH genes and non-templated nucleotide insertions in their complementarity-determining region 3 (CDR3) sequences. B-1a cells are positively selected for binding to self antigens, possibly those antigens that predominate, or that are predominantly available to B cells, in the neonatal environment. Changes to steady state B-1 cell pools, for example after whole-body irradiation, seem to increase B-1a cell output from the bone marrow, although the mechanisms involved are unknown. It is conceivable that B-2 cell precursors that generate BCR specificities associated with B-1 cells (that is, certain self-reactive BCR specificities) undergo a B-1 cell-like selection process and contribute to the B-1 cell pool. Given the evidence from adoptive transfer experiments, however, it should be noted that such a process would occur infrequently under physiological conditions. It is similarly plausible that such selfreactive B-2 cells are always deleted or are selected into the marginal zone B cell pool and that any contribution to the adult B-1 cell pool would always come from distinct B-1 cell precursors.
Functions of B‑1 cells in the steady state The presence of a distinct B cell subset that produces many self-reactive antibodies contradicts the current paradigm of lymphocyte development and selection, whereby self-reactive clones are deleted to avoid autoimmunity. as outlined below, emerging data indicate that it is precisely this self-reactive BCR repertoire that enables B-1 cells to carry out their unique functions in the regulation of tissue homeostasis. Given that B-1 cell-derived antibodies crossreact Table 1 | Distribution and function of B‑1 cells in the steady state Tissue
B-1 cell frequency (% of CD19+ B cells)
Spontaneous antibody secretion?
References
Pleural and peritoneal cavities
35–70%
No*
57,86,149 and unpublished observations‡
Blood
0.3–0.5%
Unknown
Unpublished observations§
Spleen
1–2%
IgM
86,149
Bone marrow
0.1–0.2%
IgM
Unpublished observations‡
Lymph nodes
0.1–0.3%
Intestinal lamina propria Lung parenchyma
No
60
Up to 50% of IgA cells
IgA
72,150
0.4–0.6%
IgM and IgA
+
60 and unpublished observations‡
*B-1 cells will form pinhead-size spots in ELISPOT assays but do not secrete antibody into supernatants. ‡Y. S. Choi, J. Dieter, K. Rothaeusler, Z. Luo and N.B., unpublished observations. § E. Waffarn and N.B., unpublished observations.
with pathogens, it is possible that the self antigens that shape the BCR repertoire of B-1 cells function as templates for the selection of evolutionarily ‘useful’ antibody specificities11. Such pre-existing templateselected B cells ensure the early and continuous production of protective antibodies, independently of previous encounter with a pathogen, making B-1 cells unique contributors to immune defence. However, the presence of a pool of potentially autoreactive B cells highlights the need for special regulatory mechanisms to control their activation. Tissue distribution of B‑1 cells. B‑1 cells are the majority B cell subpopulation in pleural and peritoneal cavities18. They continuously traffic to and from the pleural and peritoneal cavities through the omentum in a process that requires CXC-chemokine ligand 13 (CXCL13), which is probably produced by resident macrophages52. Splenectomy was reported to result in the depletion of B-1 (but not B-2) cells in the peritoneal cavity, and it was therefore proposed that the renewal of B-1 cells takes place from precursors present in the spleen53. although this is consistent with the fact that splenic B-1a cells have a higher turnover rate than other B-1 cell populations54, independent studies have failed to show a complete depletion of B-1 cells in the peritoneal cavity of splenectomized mice55. The role of the spleen in the regulation of the B-1 cell pool remains to be fully explored52. B-1 cells are present also in secondary lymphoid tissues, mucosal sites, the omentum52, the blood and, as recently shown, the bone marrow (y. S. Choi, j. Dieter, K. Rothaeusler, Z. Luo and n.B., unpublished observations) (TABLe 1). The spleen and bone marrow contain B-1 cells that spontaneously secrete large amounts of IgM and are thought to contribute a large proportion of the systemic circulating levels of natural antibodies. B-1 cells in the coelomic cavities, by contrast, produce only small amounts of antibodies in the steady state56,57 (and y. S. Choi, j. Dieter, K. Rothaeusler, Z. Luo and n.B., unpublished observations), which is consistent with their low levels of mRna encoding secreted IgM56 and their lack of expression of the transcriptional master regulator B lymphocyte-induced maturation protein 1 (BLIMP1), which is expressed by plasma cells57,58. although this lack of BLIMP1 expression by B-1 cells in the peritoneal cavity led some investigators to conclude that BLIMP1 is not required for IgM secretion by B-1 cells57, others have reported that BLIMP1 expression is required for natural IgM-mediated early immune protection against influenza virus infection59. as B-1 cells were recently shown to actively induce IgM secretion in the respiratory tract in response to influenza virus infection60 (see below), and the latter studies 59 did not distinguish between natural and virus-induced B-1 cell-derived IgM, it remains to be determined to what extent BLIMP1 is required for IgM production in the steady state. Hence, it remains to be clarified whether B-1 cells in the body cavities are active producers of small amounts of natural IgM or function as a pool of rapidly inducible natural antibody-secreting cells.
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REVIEWS Natural antibody production. The steady state production of natural IgM by B-1 cells provides a crucial barrier against pathogen replication before the establishment of specific immune responses25,61–66. In immunoglobulin allotype chimeric mice — generated by the shortterm depletion of host B cells and the introduction of allotype-disparate but congenic B-1 cells — at least 80% of the serum IgM is derived from B-1 cells31. Despite their overall low affinity and broad crossreactivity, these preexisting IgM antibodies directly neutralize and, partly through complement binding 64, inhibit early pathogen replication61,62,65,66. Furthermore, natural IgM antibodies enhance ensuing B-2 cell-dependent pathogen-specific IgG responses32,61, possibly by promoting the deposition of IgM antigen–antibody complexes on follicular dendritic cells64,67, although additional mechanisms are likely to be involved67.
Follicular dendritic cells specialized nonhaematopoietic stromal cells that reside in the lymphoid follicles and germinal centres. These cells have long dendrites and carry intact antigen on their surface. They are crucial for the optimal selection of B cells that produce antigen-binding antibody.
Class-switch recombination This process alters the immunoglobulin heavy chain constant region (CH) gene that will be expressed by a B cell from the Cμ gene to one of the other CH genes. This results in a switch of immunoglobulin isotype from IgM/IgD to IgG, IgA or Ige, without altering antigen specificity.
IgA production. Polyspecific Iga-producing B-1 cells function as a first layer of immune defence in the gut mucosa (reviewed in Ref. 68) and in the respiratory tract 60 (and n.B., unpublished observations). Indeed, although B-1 cells can undergo class-switch recombination to all immunoglobulin isotypes in vitro, they preferentially switch to Iga69,70 and this is induced by signals that are distinct from those involved in Iga class switching in B-2 cells69. Iga-secreting B-1 cells in the lamina propria of the intestine develop from precursors in the peritoneal cavity in a process that depends on IL-5 production50 and possibly also on the presence of commensal bacteria71. natural Iga antibodies contribute significantly to secretory Iga production in the intestinal tract and they might provide the major pool of commensalspecific antibodies68,72,73. The continuous production of Iga antibodies specific for common antigenic components of the microflora is likely to profoundly affect the establishment and maintenance of a symbiotic gastrointestinal microbiota74. Such effects on the commensal microbiota might be an important, although relatively unexplored, homeostatic function of mucosal B-1 cells (see below). Reconstitution of germ-free adult mice with individual bacterial species of the common gut microbiota failed to induce Iga production by intestinal B-1 cells and instead induced B-2 cell responses71. This indicates that early exposure to a commensal microbial flora might be crucial for the development of local Iga-producing B-1 cells. The failure to induce local Igaproducing B-1 cell populations during ontogeny might disturb the delicate balance that exists in the intestines, where the immune system must mount vigorous immune responses to pathogens while avoiding detrimental immune responses to the commensal flora and to foodderived antigens. Therefore, an absence of Iga-producing B-1 cells in the intestines might increase the risk of food allergies, as indicated recently 75. B‑1 cells and maintenance of tissue homeostasis. B-1 cells seem to participate in tissue homeostasis through their ability to bind altered self antigens, such as those expressed by apoptotic cells. a lack of secreted IgM in gene-targeted mice increases the incidence of
autoimmunity, as shown by the accelerated production of self-reactive IgG and increased disease progression76. Binding of natural IgM to oxidized low-density lipoproteins can also decrease the development of atherosclerosis40,77. In addition, secreted IgM antibodies specific for apoptotic cells promote phagocytosis by immature dendritic cells in vitro78. Crucially, these innate ‘housekeeping’ functions of B-1 cells and natural antibodies inhibit the induction of inflammatory responses and are analogous to the roles of macrophages in scavenging apoptotic cells79. Redundant mechanisms seem to be in place for these crucial functions, as mice deficient for secreted IgM develop normally and do not show overt signs of a failure of tissue homeostasis or the accumulation of apoptotic cells32. nonetheless, the number of B-1 cells in the peritoneal cavity is increased approximately threefold in secretory IgM-deficient mice compared with wild-type mice32 and this increase probably enhances the direct uptake of apoptotic bodies by B-1 cells, either through the BCR or through other surface receptors, such as T cell immunoglobulin and mucin domain-containing protein 4 (TIM4), which is a receptor for TIM1 but also for phosphatidylserine found on apoptotic cell membranes. Deficiency of TIM4 decreases the ability of B-1 cells (and macrophages) to engulf apoptotic cells, leading to an increase in Dna-specific autoantibody production80. Thus, B-1 cells can affect tissue homeostasis and the maintenance of a symbiotic mucosal microbiota by BCRdependent and -independent means. Irrespective of the type of receptor signalling pathways that B-1 cells use for antigen uptake under steady state conditions, they all seem to result in the suppression of inflammatory responses. The ability of B-1 cells to secrete large amounts of IL-10 (Ref. 81) might further contribute to their antiinflammatory role and, together with the production of Iga (an isotype that does not bind complement), decrease the risk of tissue damage during an immune response. These crucial regulatory functions of B-1 cells and natural IgM might explain why the depletion of B cells in certain patients with autoimmune disease can exacerbate rather than decrease disease severity 82.
B‑1 cell activation: signals and outcomes Innate immune signal‑mediated responses. a consistent observation regarding B-1 cells in body cavities is that following BCR-independent activation of these cells by stimuli such as IL-5, IL-10, TLR agonists or whole bacteria, they alter their normal trafficking patterns52,83. activated B-1 cells in the peritoneal cavity rapidly accumulate in the omentum but also migrate to the spleen, regional lymph nodes or intestinal lamina propria83–86. It is unclear if BCR-mediated signals have similar effects on B-1 cell trafficking. It has been suggested that the exit of B-1 cells from the peritoneal cavity in response to LPS or commensal bacteria is induced by myeloid differentiation primary response protein 88 (MyD88)-dependent signals that downregulate the expression of integrins and CD9, thereby allowing the detachment of B-1 cells from the peritoneal cavity and promoting their emigration83. as the
naTuRE REVIEwS | Immunology
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REVIEWS activation-induced redistribution of body cavity B-1 cells seems to be a common response in various disease models, it is probable that multiple innate immune signals can induce changes in B-1 cell mobility, possibly by regulating their expression of integrins and chemokine receptors, although this remains to be fully explored. Following their rapid dissemination from the body cavities, B-1 cells differentiate and secrete large amounts of IgM and/or Iga83–86. The partial differentiation state of B-1 cells in the body cavities might explain the rapid kinetics of this altered migration and the rapid BLIMP1 upregulation and differentiation to antibody secretion by these cells58,87. Such rapid responses after innate immune stimulation are also observed for marginal zone B cells. So, both B-1 cells and marginal zone B cells seem to be innate-like B cell populations that rapidly produce antibodies to protect the host from pathogens entering through mucosal surfaces and the blood, respectively 10 (BOX 2). BCR‑mediated responses. One of the unusual characteristics of peritoneal cavity B-1 cells is their inability to mobilize intracellular Ca2+ (they have relatively high levels of cytoplasmic free Ca2+ (Ref. 88)) and to proliferate in response to BCR crosslinking 89. although some studies have reported that B-1 cells undergo apoptosis following BCR signalling 90,91, B-1 cell survival does not seem to be affected by antigen stimulation89; in fact B-1 cells survive much longer than B-2 cells in in vitro culture16,92. CD5 was identified as an important inhibitor of BCR-induced proliferation in B-1 cells90; however, deletion of CD5 does not affect steady state antibody levels and CD5– B-1b cells fail to proliferate in response to BCR crosslinking 93. More recently, it was suggested that the inhibition of BCR-mediated B-1a cell proliferation requires the co-expression of CD5 and the Src Box 2 | Other innate‑like B cell subsets in mice There are many similarities between bone marrow‑derived marginal zone B cells and B‑1 cells127,144 as they both respond quickly to blood‑borne pathogens with T cell‑independent antibody secretion25. Although marginal zone B cells are often listed as a source of natural antibodies, studies with immunoglobulin allotype chimeric mice indicate that natural antibodies are produced almost exclusively by B‑1 cells31,60,145. A population of innate‑like, non‑marginal zone B cells with regulatory properties has been identified that expresses high levels of CD1d and regulates inflammatory responses in a mouse model of chronic colitis by secreting interleukin‑10 (IL‑10)22. Recently, similar CD1dhi B cells that express CD5 and have suppressive activity were indentified in mice with experimental autoimmune encephalomyelitis23. Owing to their distinct ability to secrete IL‑10, a function that seems to depend on the presence of the cytokine B cell‑activating factor (BAFF)24, these cells were termed ‘B10 cells’146. The relationship between B‑1a cells and regulatory B10 cells is unclear. Although B‑1a cells and CD1dhi regulatory B cells are phenotypically distinct, they have in common their apparent dependence on CD19 for development. Mice that lack CD19 have neither B‑1a cells nor CD1dhi regulatory B cells, and mice that overexpress CD19 have larger populations of these subsets146. Given that B‑1 cells were described as an important source of IL‑10 following the initial identification of this cytokine81, it is conceivable that CD1dmidCD23– cells upregulate these surface molecules in response to unknown, potentially innate, signals such as lipopolysaccharide147. Continuous CD40 ligation can induce CD5 expression and IL‑10 production by splenic B‑2 cells and therefore it remains possible that engagement through stimulatory receptors, such as CD1d and CD40, might induce a regulatory B‑2 cell population.
family kinase LCK94,95. another study, however, failed to find evidence of LCK expression by B-1 cells96. Sialic acid-binding immunoglobulin-like lectin G (Siglec-G) was recently identified as a strong inhibitor of BCRinduced Ca2+ influx in B-1 cells, but deletion of Siglec-G did not affect the rate of B-1 cell turnover in vivo or B-1 cell proliferation after treatment with an IgM-specific antibody in vitro 97. So, the molecular mechanisms that inhibit BCR-mediated proliferation of B-1 cells remain unclear. a lack of cell proliferation and nuclear factor-κB induction after BCR crosslinking 89, constitutive ERK phosphorylation92,98, low-level self-reactivity and the expression of CD5 are features that B-1a cells share with anergic B-2 cells98,99. This has led some investigators to conclude that B-1 cells are anergic B cells98. However, B-1 cells and anergic B-2 cells are clearly functionally distinct. First, B-1 cells mainly express high levels of surface IgM and low levels of surface IgD, whereas anergized B-2 cells express low levels of surface IgM but high levels of surface IgD100,101 Second, B-1 cells are long-lived both in vitro and in vivo16,98, whereas anergic B-2 cells undergo rapid cell death102. Third, BCR crosslinking of B-1 cells results in phosphorylation of the pro-survival kinase aKT, a process that depends on the phosphoinositide 3-kinase catalytic subunit p110δ103, and increases cell-surface expression levels of MHC class II molecules; neither of these processes occurs in anergic B-2 cells. Finally, B-1 cells constitutively express higher levels than anergic B-2 cells of costimulatory molecules, such as CD86, which is similar to activated B-2 cells. Collectively, these data show that peritoneal cavity B-1 cells have a selective unresponsiveness to BCRinduced clonal expansion, but an enhanced response to innate immune signals such as TLR agonists. So, unlike for B-2 cells, the responses of B-1 cells in vivo are not driven mainly by their BCR specificity. alternatively, B-1 cells might require innate immune signals in addition to BCR signals to clonally expand, such as those provided through PRR signalling, as previously suggested25; this might explain the modest clonal expansion of B-1a cells seen in some infectious disease models25,104 (see below). Increased B-1 cell responses, such as those seen after reperfusion injury (see below), might be driven by continuous B-1 cell proliferation and ongoing differentiation through signals that overcome the block in BCR-mediated proliferation that usually controls B-1 cell responses. Such alterations in B-1 cell homeostasis might also drive autoimmune diseases that are associated with expansions of B-1 cell populations, such as in the nZB/nZw mouse model17.
B‑1 cell effector functions B‑1 cell responses to tissue injury and infection. Studies of B-1 cell responses to pathogen exposure or tissue injury have shown that there are at least three distinct response types and outcomes (fIG. 3). In the first type of response, B-1 cells begin to produce high levels of polyreactive IgM antibodies at the site of infection. This occurs during infection with influenza virus, in which
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REVIEWS the virus is highly localized to the respiratory tract epithelium whereas cytokines and other innate immune signals are distributed systemically (fIG. 3a). B-1a cells, which generate most of the protective natural IgM antibodies specific for influenza virus in the steady state31, respond to infection by accumulating locally in the regional lymph nodes60 in response to unknown, but probably innate, signals. These accumulating B-1a cells do not proliferate or show other signs of clonal expansion in vivo, indicating that they must be recruited from distal sites, possibly the body cavities and/or the spleen. Once in the lymph nodes, B-1a cells differentiate into antibody-secreting cells. approximately 90% of the IgM-secreting B-1 cells produce antibodies that are not specific for influenza virus, further indicating the antigen-nonspecific manner of their activation; it is therefore unlikely that BCR signalling significantly induces or regulates this response60. B-1b cells do not
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accumulate or otherwise contribute to the acute local antiviral response60, and increases in B-1 cell-derived antibody production were found only in the respiratory tract, but not systemically 60. a second type of B-1 cell response occurs in response to various stimuli delivered intraperitoneally or intravenously, such as live Streptococcus pneumo‑ niae25 or Borrelia hermsii 105, certain carbohydrates106 or LPS83,86,104, or cytokines such as IL-5 and IL-10 (Ref. 85) (fIG. 3b). In response to such stimuli, both B-1a cells25 and B-1b cells106 rapidly migrate from the peritoneal cavity to the spleen25,86,106 or mucosal tissues85, where they differentiate into IgM- or Iga-secreting cells, respectively. This response type seems to be associated with a low level of B-1 cell proliferation and possibly clonal expansion, as shown by the approximately sixfold increase in the number of LPS-binding cells after injection with Francisella tularensis LPS104 and increased
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Figure 3 | Immune functions of B-1 cells. a | Infections at mucosal surfaces, such as in the lung after infection with influenza virus, can cause B-1a cells to redistribute to the regional lymph nodes, possibly from the body cavities, through unknown mechanisms60. In the lymph nodes, B-1a cells differentiate to IgM-secreting cells. The response is polyclonal and does not result in the clonal expansion of virus-specific B-1 cells and/or the preferential secretion of virus-specific antibodies. Therefore, the response is independent of the B cell receptor (BCR) specificity of the B-1a cells. In addition to providing immediate protection against pathogens, B-1a cell-derived IgM can enhance adaptive immune responses, such as IgG production by B-2 cells. b | Systemic challenge with Streptococcus pneumoniae25, lipopolysaccharide (LPS) or cytokines such as interleukin-5 (IL-5) and IL-10 induces B-1 cell migration from the body cavities to the spleen or the intestinal lamina propria84,85. Low-level proliferation of B-1 cells seems to occur in the associated lymphoid tissues; the extent to which such proliferation is antigen specific is unknown. B-1 cells differentiate into IgM- or IgA-secreting cells in lymphoid or mucosal tissues. The binding of B-1 cell-secreted antibodies to complement might enhance the effectiveness of these secreted antibodies in neutralizing pathogens or promote the uptake of apoptotic cells. However, following tissue injury, these antibodies might promote further tissue destruction. c | Unlike B-1a cells, B-1b cells seem to undergo clonal expansion in response to antigen exposure. It is not known whether this expansion occurs in the body cavities or after the migration of B-1b cells to lymphoid tissues. After adoptive transfer and repeated stimulation with antigen, B-1b cells produce increased amounts of antigen-specific antibodies. Antibody production by B-1b cells is presumed to occur in the spleen, although this has not been shown experimentally. B. hermsii, Borrelia hermsii.
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VOLuME 11 | januaRy 2011 | 41 © 2011 Macmillan Publishers Limited. All rights reserved
REVIEWS
Delayed-type hypersensitivity (DTH) response A cellular immune response to antigen that develops over 24–72 hours with the infiltration of T cells and monocytes, and depends on the production of T helper 1 cell-specific cytokines.
Hapten A molecule that can bind the B cell receptor but cannot by itself elicit an immune response. Antibodies that are specific for a hapten can be generated when the hapten is chemically linked to a protein carrier that can elicit a T cell response.
Recombination-activating gene 1 (Rag1)–/– mice Recombination-activating genes (Rag1 and Rag2) are expressed in developing lymphocytes. Mice that are deficient for either of these genes fail to produce B or T cells owing to a developmental block in the gene rearrangement that is necessary for antigen receptor expression.
serum levels of B-1 cell-derived phosphorylcholinespecific antibodies after infection with S. pneumoniae25. It remains to be determined whether these responses are mainly restricted to antigen-specific cells or are part of a much broader B-1a cell response. However, as cytokines alone can induce the redistribution and differentiation of B-1 cells, BCR signalling is clearly not essential for this type of response85. an early delayed-type hypersensitivity (DTH) response induced by skin painting with a hapten is also associated with rapid IgM secretion by B-1 cells (reviewed in Ref. 107), although a recent study suggested that, on the basis of phenotypical differences, the responding cells in this situation might be distinct from the major B-1a cell population108. IgM is thought to form antigen–antibody complexes at the site of antigen deposition after hapten challenge, thereby activating local complement component C5, which stimulates the release of vasoactive substances from mast cells and platelets and promotes the recruitment of CD4+ T cells to induce a classical DTH response. Interestingly, IgM secretion by B-1 cells in this situation seemed to depend on the presence of another type of innate lymphocyte, Vα14 + invariant natural killer T (inKT) cells, and IL-4 (Ref. 107). The interaction of B-1 cells with inKT cells was also shown to be required for the enhanced autoantibody production in nZB/nZw mice109. Earlier studies had provided evidence that non-cognate help by γδ T cells affects antibody production by B-1 cells110. Therefore, B-1 cells might receive help for antibody secretion from other innate-type lymphocytes. a similar, but ultimately destructive, type of polyreactive IgM-mediated and highly localized tissue inflammation response is observed during ischaemia– reperfusion injury 41,111. Hypoxic stress (ischaemia) of tissues followed by sudden reperfusion often results in extensive tissue damage. natural IgM antibodies seem to induce or enhance this injury by binding to apoptotic cells and altered tissue antigens, perhaps in an attempt to re-establish tissue homeostasis. The extensive local deposition of antigen–antibody complexes and activation of the complement cascade that results mediates further tissue injury and the perpetuation of natural IgM-mediated tissue destruction41,111. a third outcome, attributed exclusively to the B-1b cell subset, is the accumulation of a ‘memory’ B cell population in the peritoneal cavity (fIG. 3c). after infection with the relapsing fever-inducing spirochete B. hermsii 105, intraperitoneal injection of the porin protein of nontyphoidal Salmonella spp.112 or immunization with purified pneumococcal polysaccharide type 3 (Ref. 63), there is an expansion of antigen-specific cell populations in the peritoneal cavity that resemble B-1b cells. when they are adoptively transferred into recombination-activating gene 1 (Rag1)–/– mice, these cells provide a protective antibody response against pathogen challenge. The high level of BCR specificity and extensive clonal expansion of B-1 cells that accompany this type of response distinguish it from other B-1 cell responses, indicating that this type of response might have unique regulatory pathways that remain to be identified.
Immune regulatory functions of B‑1 cells. B‑1 cells accumulate in regional lymphoid tissues during most B-1 cell responses, including in the pancreatic lymph nodes of non-obese diabetic (nOD) mice113, and seem to regulate the adaptive immune response. For example, B-1 cell-derived IgM promotes increased production of IgG by B-2 cells32,61. In many cases, the accumulation of B-1 cells in the regional lymphoid tissues is independent of their BCR specificity. During influenza virus infection, 90% of the accumulating B-1 cells are not specific for the virus, demonstrating the innate immune-like quality of the B-1 cell response60. However, rather than viewing this as a ‘primitive’ B cell response of poor quality, I would argue that it is precisely this polyreactivity that allows B-1 cells to carry out their important and complex functions60,61. There are several functions of B-1 cells that could not be achieved by a more specific response. First, the local secretion of a broad repertoire of polyreactive IgM (or Iga) antibodies can provide protection against secondary infections with other pathogens that threaten an already injured mucosal tissue. Second, these antibodies might be involved in the re-establishment of tissue homeostasis by removing dead and dying cells. Third, self-reactive B-1 cells might suppress potential self-reactive T cell responses by presenting self antigens that are released during tissue injury and promoting the suppression of effector T cell responses. Indeed, subsets of peritoneal cavity B cells were shown to inhibit T cell activation in response to a superantigen114, prevent autoreactive responses in nOD mice113 and control pancreatic T cell infiltration by modulating the expression of vascular cell adhesion molecule 1 on the pancreatic vasculature115. In addition, peritoneal B cells from neonatal mice were shown to produce IL-10 and to limit the ability of dendritic cells to prime T cells for interferon-γ production116. So, the B-1 cell response during an infection might often be directed against self antigens rather than pathogen-expressed antigens. The level of specificity achieved with a B-1 cell response would then not be regulated at the level of clonal expansion, but rather by the selection events that shape a self-reactive B-1 cell repertoire. Independent of the specificity of the B-1 cell response, there is now increasing evidence that B-1 cells function as both effectors and regulators of the adaptive immune response. Determining how B-1 cells are related to other recently identified regulatory B cell subsets (BOX 2) will be crucial to fully define all B-1 cell functions during an active immune response.
Innate‑like B cells in humans Following the original discovery of B-1a cells in mice, various studies have provided evidence that polyreactive IgM-producing B cells can be found in the CD5+ B cell subset in adult humans117–120, although innate-like B-1 cells resident in the peritoneal cavity do not seem to exist in the steady state in humans121. Human CD5+CD19+ polyreactive Iga-producing B cells have been reported in patients with primary Iga nephropathy 122; these cells might resemble the Iga-producing B-1 cells that are
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REVIEWS Table 2 | Comparison of mouse B‑1 cells and human innate‑like B cell subsets Property
mouse B-1 cells
Human B cell subset
References
CD27 Igm cells
CD21 FCRl4 cells
Activation status
Blast-like
Blast-like
Blast-like, in G1 phase of mitosis
Inhibitory receptors expressed
CD5 with LCK, Siglec-G and CD22
Not known
FCRL4 and CD22
BCR-induced Ca+ influx and proliferation
Low
Not known
Low
+
+
low
+
17,134 94,97,134
97,133,134
Mitogen-induced IgM secretion
Strong
Weak
Strong
Self-reactivity and polyreactivity
Yes
Low
Yes
16,130,132,133
134,151
Somatic mutations of immunoglobulin genes
No
Yes
No
37,130,134,133
Tissue distribution
Lymphoid tissues and mucosa
Blood and spleen
Lymphoid tissues of the mucosa
97,124,133
BCR, B cell receptor; FCRL4, Fc receptor-like protein 4; Siglec-G, sialic acid-binding immunoglobulin-like lectin G.
found in mice69,70. However, it is clear that CD5 alone is an insufficient marker for identifying human (or mouse) B-1 cells123–126. Furthermore, the predominance of CD5+ B cells in human umbilical cord blood — which was previously interpreted as indicating the similarities in ontogeny between mouse B-1a cells and human CD5+ B cells — was recently shown to result from the presence of a large number of ‘pre-naive’ B cells in humans126.
Common variable immunodeficiency The most common symptomatic primary antibody deficiency, characterized by decreased levels of serum immunoglobulin, and a low or normal number of B cells. Most patients suffer from recurrent infections, mainly of the respiratory and gastrointestinal tracts. The incidence of malignancies, such as gastric carcinoma or lymphoma, is also increased in these patients.
Human ‘unswitched’ memory B cells. Phenotypical and gene expression analyses have linked both B-1 cells and marginal zone B cells to human IgM+IgD+CD27+ ‘unswitched’ memory B cells127,128. These cells are usually found in the spleen and peripheral blood, and are absent in asplenic humans129. In contrast to mouse B-1 cells, human unswitched memory B cells express a highly diverse and diversified polyclonal immunoglobulin repertoire130. Indeed, in contrast to the predominance of self-reactive BCR specificities among mouse B-1 cells, self-reactive and broadly pathogen-reactive cells are selectively removed from the unswitched IgM+ memory B cell pool in humans131. In addition, human IgM+ memory B cells are characterized by the expression of relatively short CDR3 sequences130,131, whereas autoreactive and polyreactive BCRs are enriched for long CDR3 sequences132. Taken together, these data show that mouse B-1 cells and human IgM+CD27+ unswitched memory B cells have marked differences and are unlikely to be homologous populations. CD21 lowIgM hi B cells. an expanded population of CD19 hiCD21 lowCD23 –CD86 hiIgM hi cells that have many phenotypical and functional characteristics similar to mouse B-1 cells was recently identified in the peripheral blood of patients with common variable immunodeficiency133. These CD21low cells also seem to be closely related to Fc receptor-like protein 4 (FCRL4)+ memory B cell subsets that are found in the mucosaassociated lymphoid tissue of humans134. FCRL4 functions as a potent BCR inhibitory receptor and human
CD21low B cells, similarly to mouse B-1 cells, are unable to respond fully to BCR signalling. Human CD21low B cells have limited Ca2+ influx after BCR stimulation and only low levels of BCR-mediated proliferation, but they readily differentiate into IgM-producing cells. also, similarly to mouse B-1 cells, human CD21 low B cells have few somatic mutations in their immunoglobulin genes134. Clonal expansion of these cells has been noted in viraemic HIV-infected patients, in whom these cells were characterized as ‘exhausted’ memory B cells that proliferate poorly in response to various stimuli135. Further work is required to determine the extent to which the CD21low B cell population or other B cell subsets in humans constitute true homologues of mouse B-1 cells (TABLe 2).
Concluding remarks and future perspectives Various B cell subsets exist that can be distinguished in terms of their development, phenotype and function. Recent studies in mice are beginning to reveal important immune-modulating actions of innate-like B-1 cells. B-1 cell-derived IgM and Iga antibodies provide innate immune protection during infection and also have crucial housekeeping functions, such as the clearance of apoptotic cells and oxidized lipids, and maintain homeostatic interactions with the intestinal microbiota. unravelling the differences and similarities between B-1 cells and the newly identified regulatory B cell subsets will increase our understanding of the roles of innate-like B cells during inflammatory responses. Clinical studies showing that B cell depletion can, in some cases, increase rather then decrease symptoms of autoimmune diseases indicate that ineffective, rather than overactive, innate-like B cell functions could be involved in some of these chronic conditions. Further studies on the basic mechanisms of innate B cell activation and function and a better characterization of human innate-like B cells are therefore likely to be important for predicting the usefulness of therapeutics targeting B cells.
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REVIEWS 135. Moir, S. et al. Evidence for HIV-associated B cell exhaustion in a dysfunctional memory B cell compartment in HIV-infected viremic individuals. J. Exp. Med. 205, 1797–1805 (2008). 136. Baumgarth, N. B-cell immunophenotyping. Methods Cell Biol. 75, 643–662 (2004). 137. Baumgarth, N. & Roederer, M. A practical approach to multicolor flow cytometry for immunophenotyping. J. Immunol. Methods 243, 77–97 (2000). 138. Ghosn, E. E., Yang, Y., Tung, J. & Herzenberg, L. A. CD11b expression distinguishes sequential stages of peritoneal B-1 development. Proc. Natl Acad. Sci. USA 105, 5195–5200 (2008). 139. Hastings, W. D., Gurdak, S. M., Tumang, J. R. & Rothstein, T. L. CD5+/Mac-1– peritoneal B cells: a novel B cell subset that exhibits characteristics of B-1 cells. Immunol. Lett. 105, 90–96 (2006). 140. Wells, S. M., Kantor, A. B. & Stall, A. M. CD43 (S7) expression identifies peripheral B cell subsets. J. Immunol. 153, 5503–5515 (1994). 141. Cong, Y. Z., Rabin, E. & Wortis, H. H. Treatment of murine CD5– B cells with anti-Ig, but not LPS, induces surface CD5: two B-cell activation pathways. Int. Immunol. 3, 467–476 (1991). This study showed that CD5 expression can be upregulated on B‑2 cells in response to BCR‑mediated signalling and forms the basis
of the ‘induced differentiation hypothesis’ of B‑1 cell development. 142. Emslie, D. et al. Oct2 enhances antibody-secreting cell differentiation through regulation of IL-5 receptor α chain expression on activated B cells. J. Exp. Med. 205, 409–421 (2008). 143. Won, W. J. & Kearney, J. F. CD9 is a unique marker for marginal zone B cells, B1 cells, and plasma cells in mice. J. Immunol. 168, 5605–5611 (2002). 144. Martin, F. & Kearney, J. F. Marginal-zone B cells. Nature Rev. Immunol. 2, 323–335 (2002). 145. Kantor, A. B. & Herzenberg, L. A. Origin of murine B cell lineages. Annu. Rev. Immunol. 11, 501–538 (1993). 146. Bouaziz, J. D., Yanaba, K. & Tedder, T. F. Regulatory B cells as inhibitors of immune responses and inflammation. Immunol. Rev. 224, 201–214 (2008). 147. Yanaba, K., Bouaziz, J. D., Matsushita, T., Tsubata, T. & Tedder, T. F. The development and function of regulatory B cells expressing IL-10 (B10 cells) requires antigen receptor diversity and TLR signals. J. Immunol. 182, 7459–7472 (2009). 148. Hao, Z. & Rajewsky, K. Homeostasis of peripheral B cells in the absence of B cell influx from the bone marrow. J. Exp. Med. 194, 1151–1164 (2001). 149. Kawahara, T., Ohdan, H., Zhao, G., Yang, Y. G. & Sykes, M. Peritoneal cavity B cells are precursors of splenic IgM natural antibody-producing cells. J. Immunol. 171, 5406–5414 (2003).
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150. Rosado, M. M. et al. From the fetal liver to spleen and gut: the highway to natural antibody. Mucosal Immunol. 2, 351–361 (2009). 151. Kurosaki, T., Aiba, Y., Kometani, K., Moriyama, S. & Takahashi, Y. Unique properties of memory B cells of different isotypes. Immunol. Rev. 237, 104–116 (2010).
Acknowledgements
I would like to thank the current and previous members of my laboratory for their dedicated work allowing me to ponder and write about B-1 cells, and Lee and Len Herzenberg for their generosity and the tremendous opportunities they afforded me while I worked in their laboratory. I apologize to my colleagues whose work I could not adequately cite owing to space constraints. Current work relevant to this Review was supported by grants from the US National Institutes of Health/National Institute of Allergy and Infectious Diseases (AI051354 and AI073911).
Competing interests statement
The author declares no competing financial interests.
FURTHER INFORMATION Nicole Baumgarth’s laboratory: http://ccm.ucdavis.edu/baumgarthlab/index.html All lInkS ARe ACTIve In THe onlIne PDF
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Mechanisms for T cell receptor triggering P. Anton van der Merwe and Omer Dushek
Abstract | There is considerable controversy about the mechanism of T cell receptor (TCR) triggering, the process by which the TCR tranduces signals across the plasma membrane after binding to its ligand (an agonist peptide complexed with an MHC molecule). Three main types of mechanism have been proposed, which involve aggregation, conformational change and segregation. Here, we review recently published evidence for each type of mechanism and conclude that all three may be involved. This complexity may reflect the uniquely demanding nature of TCR-mediated antigen recognition, which requires the detection of a very weak ‘signal’ (very rare foreign peptide–MHC ligands) in the presence of considerable ‘noise’ (abundant self peptide–MHC molecules). Immunoreceptor tyrosine-based activation motif (ITAM). A sequence that is present in the cytoplasmic domains of the invariant chains of various cell-surface immune receptors, such as the T cell receptor–CD3 complex. Following phosphorylation of their tyrosine residue, ITAMs function as docking sites for Src homology 2 (SH2) domaincontaining tyrosine kinases and adaptor molecules, thereby facilitating intracellular signalling cascades.
Sir William Dunn School of Pathology, University of Oxford, Oxford, OX1 3RE, UK. Correspondence to P.A.v.d.M. e‑mail: anton.vandermerwe@ path.ox.ac.uk doi:10.1038/nri2887 Published online 3 December 2010
The T cell receptor (TCR) consists of a variable TCRαβ heterodimer that binds to ligands. The TCR forms a multisubunit receptor complex with the non-variable signal transduction CD3 complex, which contains CD3γ, CD3δ, CD3ε and TCRζ subunits. All CD3 complex subunits contain immunoreceptor tyrosine-based activation motifs (ITAMs) in their cytoplasmic domains. TCRαβ binds complexes of peptide and MHC molecules on the surface of antigen-presenting cells (APCs) or target cells, which results in biochemical changes in the cytoplasmic portions of the CD3 complex. One biochemical change that is known to be essential for TCR signalling is phosphorylation of the ITAMs in the CD3 complex by the Src family tyrosine kinases LCK and FYN (reviewed in REFS 1,2). In addition, various conformational changes have been reported, some of which are independent of tyrosine phosphorylation3–5, and some of which are postulated to precede, and be required for, ITAM phosphorylation6,7. The process by which TCR binding to peptide–MHC molecules leads to biochemical changes in the cytoplasmic regions of the CD3 complex is referred to as TCR triggering and is the main focus of this Review. Although this area has been reviewed previously, there have been considerable advances made in the past 2 years, and this Review focuses on this new research.
The challenges While evaluating possible models of TCR triggering, it is important to bear in mind some of the unusual features of TCR antigen recognition, which distinguish it from other cell-surface receptor recognition events. These
features clarify the challenges faced by any triggering mechanism and place constraints on the types of model that are mechanistically plausible. Sensitivity. The first notable feature is the very low abundance of agonist peptide–MHC ligands on APCs or target cells. The TCR on a given T cell is ‘restricted’ to a subset of the MHC molecules on an APC, and the highaffinity agonist (typically ‘foreign’) peptide will only be present on a tiny fraction of these molecules. Hence TCR triggering needs to be very sensitive, and indeed TCRs can be triggered when only a single antigenic peptide–MHC ligand is within the contact area8–10. Discrimination. A second feature is the presence on APCs and target cells of abundant self peptide–MHC molecules to which the TCR can also bind. To develop into mature peripheral T cells, developing T cells need to undergo positive selection whereby only T cells expressing TCRs that bind self peptide–MHC molecules can survive. Therefore, all peripheral T cells express TCRs that bind self peptide– MHC molecules. Indeed, there is evidence that continued recognition of self peptide–MHC molecules is required for survival of peripheral T cells11–13. Although negative selection of developing T cells ensures that the TCRs do not have a high affinity for self peptide–MHC molecules, the affinity threshold for negative selection is sharp and close to the affinity threshold for foreign peptide–MHC ligand recognition14. As a result, any given TCR is likely to bind a fraction of self peptide–MHC molecules with affinities that are not much lower than the affinities for foreign peptide–MHC ligands. Furthermore, the self
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REVIEWS Serial-triggering model A model that was proposed to account for the observation that small numbers of agonist peptide–MHC complexes seemed to trigger large numbers of T cell receptors (TCRs), and that postulates that a given peptide–MHC complex can serially bind to and trigger multiple TCRs. As it is the number of productive TCR engagements that determines peptide–MHC efficacy, high-affinity peptide–MHC complexes with long half-lives may be less effective. According to this model there is an optimal affinity or half-life for a TCR–peptide–MHC complex.
peptide–MHC molecules that a given TCR can bind are collectively likely to be far more abundant than foreign agonist peptide–MHC ligands, only a few of which will be recognized by a specific TCR. Because T cells are sensitive to only a small number of recognition events, the stochastic nature of the molecular events involved creates a serious problem of discrimination (BOX 1): how do T cells detect very low numbers of foreign peptide– MHC ligands (signal) in the presence of high levels of self peptide–MHC molecules (noise)? Molecular mechanisms that have been proposed to explain this remarkable ability to discriminate signal from noise either extend the time available for recognition or invoke cooperative effects, whereby individual TCRs somehow communicate with each other following ligand recognition. Given the remarkable speed of antigen recognition by T cells15, only cooperative effects can satisfactorily account for discrimination 16. This cooperation could either involve a direct physical interaction, which would require the TCR–CD3 complexes to form aggregates17,18, or communication via signalling pathways, a process termed signal spreading 16,19,20. Versatility. A third requirement of TCR recognition is that it is necessary for the same TCR to recognize multiple ligands with a range of affinities and produce different responses depending on the affinity. For example, in the thymus, developing T cells need to recognize both low-affinity and high-affinity self peptide–MHC
Box 1 | Distinguishing signal from noise T cells can detect tiny amounts of high-affinity foreign peptide–MHC ligand (signal) presented in the context of large amounts of low-affinity self peptide–MHC complex (noise). To appreciate this feat, it is helpful to consider a specific example. Consider a T cell receptor (TCR) that dissociates from a self peptide–MHC complex with an average half-life of 1 second (koff = 0.69 s–1) and from a foreign peptide–MHC complex with a half-life of 5 seconds (koff = 0.14 s–1), but has the same on rate for both (kon= 0.001 μm2 s–1). Further assume that the concentration of the self peptide–MHC ligand is tenfold higher than that of the foreign peptide–MHC ligand (10 μm–2 and 1 μm–2, respectively). How can the T cell only respond when foreign peptide–MHC complexes are present? The simplest discrimination mechanism is the number of occupied TCRs. With some assumptions (such as the conservation of TCR and peptide–MHC complexes) we can compute the number of engaged TCR complexes (C) using the following equation: %
# 2 6 - s 26 66 -F s 26 66 6 6 F
where A (π52 μm2) is the area of the contact interface, PT and TT are the total concentration of the peptide–MHC and TCR complexes, respectively, and Kd is the dissociation Nature Reviews constant. Substituting in the values| Immunology above, we find that TCR occupancy produces a poor signal-to-noise ratio of 0.33 (0.42 μm–2 / 1.2 μm–2). Therefore, on average, more receptors will be occupied by self peptide–MHC ligand than foreign peptide–MHC ligand. An alternative output that the T cell can potentially respond to is the rate of TCR binding events, as in the serial-triggering model28. The rate of binding events is simply koffC, which is 68 s–1 and 4.5 s–1 for self and foreign peptide–MHC ligands, respectively. This produces an even lower signal to noise ratio of 0.07. This ratio can be improved if we stipulate that each TCR will only signal if bound for a threshold time (τ), as in the kinetic proof-reading model29,30. In this case, the rate of productive binding events is koffC exp(–koffτ). Taking τ = 5 seconds, we find that the revised binding rate is 2.1 s–1 and 2.2 s–1 for self and foreign peptide–MHC ligands, respectively, which corresponds to a signal-to-noise ratio of 1.1. Although this is a substantial improvement, it is still inadequate because both self and foreign peptide–MHC ligands will produce a similar number of productive binding events, making them indistinguishable.
molecules and respond differently to each21. Similarly, mature T cells require recognition of low-affinity self peptide–MHC molecules to promote survival, whereas recognition of high-affinity foreign peptide–MHC ligands leads to activation and proliferation. Any triggering mechanism or mechanisms must allow recognition of a range of different ligands and produce distinct signals depending on the strength of binding. Structural diversity. A fourth unusual feature of TCR recognition is the diverse nature of the binding interface between the TCR and a peptide–MHC molecule, and the fact that TCRs need to recognize ligands (foreign peptide) that they have never previously encountered. Although there are clearly common general features in TCR–peptide–MHC complex interactions, the variability of peptide sequences and TCR complementarity-determining region 3 (CDR3) loops results in great diversity in the fine structure of the interface. There are conserved contacts between subsets of TCRs (with similar variable (v) segments) and subsets of MHC molecules22,23, but no contacts or conformational changes at the binding interface have been identified that are conserved in all TCR–peptide–MHC complex structures22–24. Rossjohn et al.25 observed that a triad of MHC class I residues was involved in all published structures of TCR–peptide– MHC class I complexes, but their TCR contacts were variable, as was their contribution to binding energy 26. Thus, despite having conserved features, such as a broadly diagonal orientation, the TCR–peptide–MHC binding interface is diverse at the atomic level, with no contacts or conformational changes that are common to all TCR– peptide–MHC complexes. Any triggering mechanism needs to accommodate this structural diversity. The key issue in TCR triggering is explaining how TCR binding to a peptide–MHC complex results in biochemical changes in the cytoplasmic domains of the TCR–CD3 complex. Models of TCR triggering invoke one or more of three basic mechanisms: aggregation, conformational change and segregation or redistribution of the TCR–CD3 complex 27. Although it is likely that triggering will involve a combination of these mechanisms, it is useful to consider each mechanism separately. Several TCR signalling models (such as the serial-triggering model28 and the kinetic proof-reading model29,30) have been proposed to account for certain quantitative features of T cell activation such as antigen discrimination. As they do not imply any particular molecular mechanisms of TCR triggering, they are not discussed further here. Aggregation It is not difficult to envisage how aggregation of TCR–CD3 complexes following TCR engagement could lead to enhanced phosphorylation. This aggregation could, for example, increase the proximity of associated LCK molecules, resulting in the activation of the second receptor in the aggregate by trans-autophosphorylation31. Forced aggregation of TCRs using either soluble antibodies or soluble multimeric forms of peptide–MHC complexes is sufficient to initiate TCR triggering. Although this clearly shows that artificial aggregation is sufficient for
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REVIEWS #IITGICVKQP C%QTGEGRVQTJGVGTQFKOGTK\CVKQP #IQPKUVRGRVKFGs/*%
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Figure 1 | mechanisms of TCR triggering. Models are grouped according to whether the primary mechanism is aggregation, conformational change or segregation. a | In the Reviews | Immunology co-receptor heterodimerization model, co-receptor binding toNature the same peptide–MHC complex as the T cell receptor (TCR) brings co-receptor-associated LCK into proximity with TCR–CD3 immunoreceptor tyrosine-based activation motifs (ITAMs). b | The pseudodimer model postulates that two TCRs are brought together by binding low-affinity self (green) or high-affinity agonist (blue) peptide–MHC ligand and that the co-receptor associated with one TCR engages the agonist peptide–MHC complex, thereby forming a dimer. c | A piston-like displacement of the TCR–CD3 complex is induced by the mechanical effects (primarily pulling; black arrow) of peptide–MHC binding to the TCR. This leads to a change in the conformation of the CD3 cytoplasmic domains, allowing ITAM phosphorylation. d | Clustering is induced by a conformational change in TCR–CD3 complex, possibly enhancing kinase activity. The conformational change in the cytoplasmic domains is depicted as dissociation from the membrane, as proposed in the ‘safety-catch’ model7. e | The kinetic-segregation model proposes that TCR binding to peptide–MHC ligand traps the TCR–CD3 complex in close-contact zones, thereby segregating it from the inhibitory tyrosine phosphatase CD45, leading to stable phosphorylation of TCR–CD3 ITAMs by LCK. f | Lipid raft models postulate that peptide–MHC engagement somehow results in partitioning of the TCR–CD3 complex into regions of membrane enriched in LCK and deficient in CD45. APC, antigen-presenting cell.
triggering, the challenge has been to explain how binding of agonist peptide–MHC ligand alone can induce aggregation when the ligand is present at such low surface densities. Indeed, TCR triggering can be observed with a single agonist peptide–MHC ligand8–10. Several models have been proposed to account for this.
The co-receptor heterodimerization model (reviewed in REF. 32) postulates that CD4 or CD8 co-receptors bind to the same agonist peptide–MHC complex as the TCR, thereby recruiting co-receptor-associated LCK into close proximity with CD3 complex ITAMs to mediate their phosphorylation (FIG. 1a). However, TCR triggering can occur in the complete absence of coreceptors33,34, indicating that co-receptor heterodimerization is not essential for TCR triggering. Furthermore, in most studies, soluble agonist peptide–MHC monomers cannot induce TCR triggering, indicating that coreceptor heterodimerization is usually not sufficient for TCR triggering. The pseudodimer model postulates a role for self peptide–MHC molecules in TCR triggering 9,35. According to this model, one TCR binds an agonist peptide–MHC molecule and a second TCR binds a self peptide–MHC molecule. Dimerization is enhanced because the co-receptor associated with the TCR that is complexed with the self peptide–MHC molecule binds to the agonist peptide–MHC complex. A pseudodimer is hence formed by the dual interaction of a second TCR with self peptide–MHC and its associated CD4 or CD8 co-receptor with the agonist peptide– MHC complex (FIG. 1b). As self peptide–MHC molecules are present at a much higher surface density, this helps to address the problem of low surface density of agonist peptide–MHC molecules. A key prediction of this model is that self peptide–MHC molecules would enhance TCR triggering, especially at low densities of agonist peptide–MHC ligands. evidence for this is clearest in the case of CD4+ T cells, whereas there are conflicting data for CD8+ T cells (reviewed in REF. 36 ). Interestingly, a high proportion of self peptide–MHC molecules (50–100% of those tested) seem to enhance agonist peptide–MHC ligand recognition36,37. It is therefore plausible that aggregates of agonist and self peptide–MHC molecules could induce clustering of TCRs and co-receptors simply by binding to the TCR. Finally, some models propose that engagement of peptide–MHC molecules induces conformational changes in the TCR–CD3 complex that predispose it to dimerization and aggregation38,39. These models are considered in the next section. There is some controversy as to the natural state of the TCR at the cell surface. Some studies report that at least a proportion of TCRs are in aggregates (or clusters) 40–43 that can form what some have termed ‘protein islands’41, whereas other studies suggest that the TCRs are primarily monomeric44,45. The observed TCR clusters were 30–300 nm in diameter and contained 5–20 TCRs 41–43. It is noteworthy that in the cases in which clustering was reported, the T cells were in contact with artificial surfaces and the clusters were observed in these contact areas. These results can be reconciled if it is postulated that TCRs are primarily monomeric but are predisposed to clustering following initial triggering, and that contact with surfaces can induce clustering by inducing weak TCR triggering 46.
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REVIEWS Whatever the natural state of the TCR before engagement of peptide–MHC molecules, it is clear that this engagement results in increased aggregation of TCRs into what have been termed ‘microclusters’, containing 10–100 TCRs43,47. The formation of these microclusters was first visualized by total internal reflection fluorescence (TIRF) microscopy of T cells in contact with planar bilayers47,48. Interestingly, their size seems to vary little with the surface density of peptide–MHC molecules43. This raises the question as to the mechanism of microcluster formation. Is it simply a physical consequence of the binding of agonist and self peptide–MHC molecules by TCRs and their co-receptors? Or are other processes involved? In support of the latter is the observation that microcluster formation is blocked by the inhibition of actin polymerization, suggesting a role for the actin cytoskeleton in microcluster formation47,48. It is possible that TCR triggering itself leads to clustering, through, for example, signalling molecules that associate with and crosslink the TCR–CD3 cytoplasmic domains. Imaging studies to date have been unable to resolve whether TCR triggering precedes microcluster formation or vice versa. However, some formation of microclusters is still observed in the presence of Src tyrosine kinase inhibitors48,49. This shows that ITAM phosphorylation is not required for microcluster formation, but does not rule out a role for other signalling pathways. In conclusion, recent studies on the ability of self peptide–MHC molecules to engage TCRs suggest that aggregation is a plausible mechanism of TCR triggering despite the low density of agonist peptide–MHC ligands. Conformational change Several models have been proposed that invoke bindinginduced conformational change as a mechanism of TCR triggering. An attraction of these models has been that they can account for triggering at very low densities of agonist peptide–MHC molecules. A conformational change model needs to explain in molecular detail how TCR binding to peptide–MHC molecules can lead to changes in the CD3 cytoplasmic domains. At present there are no models that can do this satisfactorily. This is partially because we still do not know the structure of the intact TCR–CD3 complex. However, structural and other studies of different portions of the TCR–CD3 complex have provided intriguing clues.
Kinetic proof-reading model A model that was proposed to account for the ability of T cells to discriminate between peptide–MHC ligands that have small differences in their affinity or half-life. It postulates that T cell receptor (TCR) triggering requires multiple sequential steps that can only proceed while the TCR is engaged with a peptide–MHC complex and that are completely reversed as soon as the TCR dissociates from the complex.
TCR ectodomains. Although the binding of peptide– MHC molecules often induces conformational changes in the TCR24, these are primarily in the contact area and are not widely conserved. However, crystallographic studies of a TCR in the bound and unbound state suggested a possible subtle conformational change in the membrane-proximal AB loop of the TCRα constant (Cα) domain50. A recent follow-up study 51 confirmed this using a different technique and reported a similar change in a different TCR. In addition, this study showed that mutation of residues in the AB loop abrogates TCR antigen recognition51. However, the AB loop of the TCR Cα domain is often poorly resolved in the crystal structures of TCR–peptide–MHC complexes,
so it is not clear how widespread the conformational change is following TCR binding 51. Further structural studies in which the relevant TCR regions are well resolved are needed to address this. How could such a conserved conformational change in the TCR Cα domain be produced given the diversity at the binding interface of the TCR–peptide–MHC complex? One possible mechanism, discussed below, is through a mechanical force generated by the peptide– MHC complex pulling on the TCR. Another question is how changes in this region of the TCR could be transduced to the cell interior. Based on their observation that mutations of the AB loop affect TCR dimerization, Kuhns et al.40 have proposed that the conformational change in the AB loop of the TCR Cα domain regulates TCR dimerization. Thus, binding-induced conformational changes may signal by inducing clustering. Similar models have been previously proposed based on reports that TCR binding to peptide–MHC complexes leads to clustering 38,39. CD3 ectodomains. The ectodomains of CD3δ and CD3γ form stable heterodimers with the CD3ε ectodomain, and the structures of the CD3δε52,53 and CD3γε54,55 heterodimers have been determined. Although it is not yet understood how the TCRαβ ectodomain associates with the CD3 ectodomains, compelling evidence of direct association between the transmembrane regions56 suggests that these ectodomains will be in close physical contact, at least in the portions that are close to the membrane. In the absence of structural data, indirect methods have been used to infer the arrangement of the TCR and CD3 ectodomains, with contradictory results57. However, recent studies support a model in which the CD3 ectodomains are arranged on one side of the TCRαβ ectodomain, with CD3δ and CD3γ contacting the TCR Cα and Cβ domains, respectively, and with the two CD3ε subunits in close proximity to each other40,58,59. In this model, the AB loop of the TCR Cα domain is not in contact with the CD3 heterodimers and is potentially available to mediate TCR dimerization40. Reinherz and colleagues54 have observed that the CD3γε heterodimer seems to be relatively rigid and, on this basis, argued in favour of a role for mechanical pistonlike forces (see below). Structural studies of the CD3γε and CD3δε heterodimers have not provided any direct evidence for conformational change, but molecular dynamic simulations have identified possible conformational changes in the CD3ε stalk60. Mutation of residues in this region, including in a conserved CXXC motif, abrogated TCR signalling in vitro and T cell development in vivo60,61. Surprisingly, these mutant forms of CD3ε inhibited TCR function even in the presence of excess wild-type CD3ε60, supporting a model in which TCR–CD3 complexes form cooperative microclusters18. CD3 cytoplasmic domains. Several studies have suggested that the cytoplasmic portions of the CD3 complex undergo conformational change and that this could be implicated in TCR triggering. Alarcon and colleagues3–5 provided evidence for conformational changes when
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REVIEWS the TCR is engaged by antibody or by peptide–MHC molecules, and implicated a proline-rich motif in CD3ε that binds the adaptor protein non-catalytic region of tyrosine kinase (NCK). However, this motif seems to be involved in regulating the expression of TCR and CD3 subunits, and not in TCR triggering 62,63. Stern and colleagues6 used circular dichroism to investigate the protein structures and showed that the cytoplasmic portion of TCRζ undergoes a conformational change upon binding to acidic lipid vesicles. This change in conformation is accompanied by changes in tyrosine fluorescence and a decreased susceptibility to phosphorylation. More recently it was shown that a basic residue rich sequence (BRS) in CD3ε mediates binding to negatively charged phospholipids in the cell membrane7,64. Wucherpfennig and colleagues7 also provided nuclear magnetic resonance evidence that the tyrosine residues in the CD3ε ITAMs may be buried in the lipid bilayers. Based on these findings, and the observation that the TCRζ cytoplasmic domain also contains BRSs, a ‘safety-catch’ model was proposed, postulating that some TCR–CD3 ITAMs are protected from phosphorylation in the resting state (safety on) and that TCR engagement by ligand results in the
dissociation of these ITAMs from the phospholipids in the cell membrane (safety off), exposing them to phosphorylation6,65. However, the finding that exposure of T cells to the tyrosine phosphatase inhibitor pervanadate induces dramatic TCR–CD3 ITAM phosphorylation66–69 shows that these ITAMs are accessible to kinases in the absence of TCR engagement. Also arguing against this model is the finding that mutation of the CD3ε BRS abrogates phosphorylation 64,69. Wucherpfennig and colleagues70 have countered that the effects of pervanadate are secondary to lipid modification and that BRS mutants could disrupt the CD3ε conformation. Further experiments are needed to resolve these issues. Mechanical effects. Recently, there has been increased interest in conformational change models that invoke a role for mechanical forces such as pulling or shearing 27,54,71–73. These models have been inspired by several lines of evidence. First, the recognition that imposition of a mechanical pulling force on the TCR–CD3 complex is an inevitable consequence of binding to the peptide–MHC ligand74, which has recently been supported by measurement of the TCR–peptide–MHC complex
Box 2 | Two-dimensional binding properties Given that the T cell receptor (TCR) and peptide–MHC complex are normally associated with cell surfaces, it has long been a goal to measure the binding properties of this interaction in situ. As membrane-associated molecules are constricted to diffuse in two dimensions, their binding properties are stated in two-dimensional (2D) units, in contrast with solution binding properties, which are three-dimensional (3D). Two recent landmark studies have measured the 2D binding properties using very different approaches, producing intriguing results and valuable insights105,106. Huppa et al.106 used fluorescent protein tags, total internal reflection fluorescence (TIRF) microscopy and fluorescent resonance energy transfer (FRET) to measure the surface densities of TCR, peptide–MHC and TCR–peptide–MHC complexes at the interface between T cells and planar bilayers onto which peptide–MHC complexes and other ligands had been attached. By assuming that these interactions were at equilibrium, they used these data to calculate the 2D dissociation constant (Kd) in the T cell–bilayer interface at the resolution of TIRF microscopy. By measuring the duration of FRET for a large number of TCR–peptide–MHC complexes they were also able to estimate the 2D off rate (koff). Huang et al.105 used mechanical assays to measure the 2D binding parameters. In these assays, peptide–MHC molecules that were attached directly or indirectly to erythrocytes were brought into contact with T cells for varying periods, and binding was detected by deformation of the erythrocytes when the cells were pulled apart. Both studies found that the 2D koff was significantly faster than the solution koff, and that this difference was reduced by inhibitors of the actin cytoskeleton105,106. This is evidence that the TCR–peptide–MHC interaction is subjected to mechanical forces, as previously predicted74. A second key finding was that the 2D Kd was highly variable, and that this variability was largely the result of changes in the 2D on rate (kon). Huppa et al. found considerable variation (~200-fold) for a given TCR–peptide–MHC combination even within a single contact interface106, whereas Huang et al. found even greater variation (~2,000-fold) between a set of peptide–MHC analogues, despite the fact that their solution or 3D kon did not vary much105. Interestingly, the dramatic differences in 2D kon correlated well with activation potency105. Paradoxically, Huang et al. also found that the 2D koff correlated with activation potency and inversely with 3D koff. Furthermore, the 2D kon was reduced by treatments that would be expected to inhibit TCR triggering and TCR clustering, and the same treatments decreased the 2D koff. A plausible explanation for these intriguing results is that TCR triggering, which is induced by binding to agonist peptide–MHC ligand, rapidly leads to changes in the local surface density and/or orientation of the TCR–CD3 complex, and these changes are accompanied by an increase in the mechanical force that the TCR–peptide–MHC interaction is subjected to. Triggering-induced TCR clustering could increase the surface density of TCR–CD3 complexes over 100-fold in the immediate vicinity of the engaged TCR, accounting for most of the apparent increase in 2D kon. Triggering-induced clustering could also enhance the apparent 2D kon by optimizing the TCR–CD3 orientation (for example, by making it more upright). A previous study from the same group showing an increased probability of TCR–peptide–MHC binding upon subsequent encounters also supports triggering-induced enhancement of TCR–CD3 binding by clustering and/or reorientation107. These studies reveal that measuring 2D binding properties in the context of functional T cells is complicated by triggering-induced changes in TCR surface density and/or orientation and in the mechanical forces that act on the TCR–peptide–MHC interaction. Measurements in systems in which these effects are controlled will be necessary to fully elucidate the relationship between 2D binding properties and TCR triggering.
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Lipid raft An area of the plasma membrane that is rich in cholesterol, glycosphingolipids, glycosylphosphatidylinositolanchored proteins and several signalling proteins — such as Src family kinases, LAT (linker for activation of T cells) and PAG (protein associated with glycolipid-enriched microdomains).These domains are also known as glycolipidenriched microdomains (GEMs) and detergentinsoluble glycolipid-enriched membranes (DIGs).
off rate in intact cells (BOX 2). Second, the structural evidence that the CD3γε heterodimer may be rigid54 and that the protruding FG loop of the TCR Cβ domain is in contact with the membrane-distal top end of the CD3γε heterodimer 58,75. Thus any force applied to the TCRαβ heterodimer could be transmitted through the CD3γε heterodimer to the membrane. Third, the longstanding observation that T cell activation by artificial ligands is optimal when the ligands are anchored to a surface76,77. Fourth, an appreciation that elongation of the peptide–MHC ligand could abrogate TCR triggering by reducing any mechanical force on the TCR71,78,79. And, finally, reports that the application of mechanical force on the TCR enhances TCR triggering 73,80. The mechanical forces could be generated by several processes74. The small size of the TCR–peptide–MHC complex would generate a force as larger molecules that are excluded from or compressed within closecontact areas try to diffuse in or straighten out. This is consistent with the observation that elongation of the peptide–MHC ligands abrogates triggering 78,79. Active sources of force include the movement of cell processes and membranes, driven by cytoskeletal and endocytic mechanisms. This is supported by the longstanding observation that reagents that disrupt the actin cytoskeleton abrogate TCR triggering 81. A major attraction of these mechanical force models is that they can readily explain how binding at a structurally variable peptide–MHC binding site in the TCR could induce the same conformational change in all TCR–CD3 complexes, because the mechanical force is a direct consequence of binding. Discrimination between different ligands comes about because the duration of the applied mechanical force and the resulting conformational change will be determined by the duration of binding. It has also been proposed that peptide–MHC binding could push and/or twist the TCR57,82. However, an advantage of pulling or shearing mechanisms is that they are inherently specific because only specific interactions between the TCR and the peptide–MHC ligand can resist the pulling or shearing forces. By contrast, pushing does not necessarily require binding and could be nonspecific. How might the effect of mechanical pulling on the TCR–CD3 complex be transduced into the cell interior? One possibility is that binding leads to a pistonlike movement of the CD3 cytoplasmic tails, relative to the plasma membrane, that could alter their conformation (FIG. 1c). evidence cited in support of this includes the apparent rigidity of the CD3 ectodomains54 and the observations that mutations in the conserved stalk region of CD3ε abrogate T cell activation60,61. In addition, the transmembrane regions of the TCR–CD3 complex specifically interact with each other, suggesting that they could form a relatively rigid structure83,84. However, convincing direct evidence of rigidity of the entire CD3 complex is lacking, particularly for the segments between the membrane and the ITAM region, making it unclear how piston-like movement could be transduced to the ITAMs.
A second possibility is that pulling induces a conformational change in the structure of the TCR–CD3 ectodomains and/or transmembrane domains that leads to clustering of the engaged TCR–CD3 complex with other TCR–CD3 complexes (FIG. 1d). Such a mechanism has been proposed for B cell receptor (BCR) triggering 85. Pierce and colleagues86 have shown that binding of monomeric, surface-immobilized antigen to the IgM BCR induces clustering through its membrane-proximal Cμ4 domain. In conclusion, evidence that a conformational change is involved in TCR triggering is mounting, but the nature of the conformational change and the mechanism by which peptide–MHC binding induces the conformational change remain unclear. Segregation and redistribution A third type of mechanism that has been proposed for TCR triggering is binding-induced segregation or redistribution of the TCR–CD3 complex with respect to other cell membrane-associated proteins. The TCR–CD3 complex is embedded in the plasma membrane along with molecules that favour signalling (such as the tyrosine kinase LCK) and molecules that inhibit signalling (such as the receptor tyrosine phosphatases CD45 and CD148). Treatment of resting T cells with inhibitors of tyrosine phosphatases leads to increased phosphorylation of TCR–CD3 ITAMs, resulting in TCR signalling and T cell activation even in the complete absence of TCR ligands66–68. Recently, Acuto and colleagues87 reported that a substantial amount of LCK is constitutively active in resting T cells and that this did not increase detectably upon TCR engagement. These results suggest that phosphorylation by constitutively active LCK is held in check by constitutively active phosphatases. It follows that anything that disturbs this balance could induce an increase in TCR–CD3 ITAM phosphorylation and TCR signalling. One way of disturbing this balance is through the redistribution of the TCR–CD3 complex, LCK and CD45 with respect to each other. Two types of redistribution or segregation models have been proposed. The kinetic-segregation model proposes that segregation of an engaged TCR–CD3 complex from CD45 is driven by differences in ectodomain size88,89, whereas the lipid raft model proposes that redistribution is driven by changes in the lipid environment of the TCR90. As the kinetic-segregation model has recently been reviewed91, it is discussed only briefly here. The model postulates that multiple zones of close contact (~15 nm apart) form at the cell–cell interface, from which molecules with large ectodomains, such as the inhibitory tyrosine phosphatases CD45 and CD148, are excluded (FIG. 1e). As a result, ITAM phosphorylation is strongly favoured. Binding to an agonist peptide–MHC ligand serves to trap the TCR–CD3 complex within a closecontact zone where it is protected from dephosphorylation by CD45 and CD148. This results in long-lived phosphorylation of TCR–CD3 ITAMs, leading to recruitment and activation of ζ-chain-associated protein kinase of 70 kDa (ZAP70) and subsequent phosphorylation by ZAP70 of the adaptor molecules SH2 domain-containing leukocyte protein of 76 kDa (SLP76; also known as LCP2) and linker for activation of T cells (LAT).
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REVIEWS Several lines of evidence support this model: first, CD45 and CD148 are excluded from areas of TCR triggering 43,92; second, truncation of the large CD45 and CD148 ectodomains inhibits TCR triggering 92,93; third, elongation of the peptide–MHC complex inhibits TCR triggering 78,79; fourth, surface-associated TCR ligands induce TCR triggering more effectively than their soluble counterparts76,77; and, finally, recognition by engineered TCRs is optimal when the epitope is positioned close to the plasma membrane of the target cell94,95. Although these results provide compelling evidence in support of the kinetic-segregation model, they do not exclude other mechanisms. Indeed, the last three lines of evidence cited above are also consistent with a mechanical pulling mechanism for TCR triggering. Lipid raft models propose that TCR binding to peptide–MHC complexes leads to an association of the TCR–CD3 complex with lipid rafts. This enhances phosphorylation of TCR–CD3 ITAMs because lipid rafts are enriched in some proteins (such as LCK) and deficient in others (such as CD45) (FIG. 1f). The binding of peptide–MHC to TCR–CD3 may alter its lipid environment by immobilizing and/or clustering TCR–CD3 complexes. The role of lipid rafts has been controversial because the early techniques that were used to implicate them were later found to be unreliable96. Recent studies using new techniques have confirmed the existence of these structures and showed that they are smaller and more dynamic than previously appreciated97. Although there is substantial evidence supporting a role for lipid rafts in TCR signal transduction90,98–100, some of this evidence has been challenged101–104. One study was unable to show co-localization of lipid raft markers with TCR microclusters102. Although this argues against a role for lipid rafts in microcluster formation it does not rule out a role for lipid rafts at earlier time points and/or on a smaller scale. Further studies using higher resolution imaging techniques are needed to elucidate the role of lipid rafts in the initial steps of TCR triggering. Although these findings suggest that segregation or redistribution of the TCR are likely to have an important role in TCR triggering, it is unclear whether they alone are sufficient to induce triggering.
Conclusion Is it possible to reconcile all of the diverse experimental findings that support the different triggering mechanisms discussed above? We suggest the following scenario (FIG. 2). In resting T cells there is a delicate balance between tyrosine phosphorylation of the TCR–CD3 complex by constitutively active LCK and dephosphorylation by constitutively active phosphatases, with the phosphatases dominating (FIG. 2a). In principle, TCR triggering can be induced by any mechanism that tilts this balance in favour of phosphorylation. engagement of the peptide–MHC complex leads simultaneously to aggregation of TCR–CD3 complexes and their segregation from other membrane proteins, which decreases the local phosphatase activity and increases the local kinase activity of LCK (FIG. 2b). engagement also leads to conformational change in the cytoplasmic domain of the
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Figure 2 | Integrated TCR triggering model. a | In the Nature Reviews complex | Immunology resting state, the T cell receptor (TCR)–CD3 is primarily monomeric or forms very transient small aggregates. Phosphatase activity dominates and the level of TCR–CD3 immunoreceptor tyrosine-based activation motif (ITAM) phosphorylation is low. b | TCR engagement with peptide–MHC complex leads to segregation of the TCR–CD3 complex from phosphatases such as CD45, as well as aggregation and conformational change in the TCR–CD3 cytoplasmic domains. It is possible that aggregation alters the lipid environment of the TCR–CD3 complex (not shown). The overall result is a substantial increase in kinase activity and decrease in phosphatase activity, leading to increased ITAM phosphorylation. c | The TCR–CD3 complex aggregates enlarge to form microclusters as signalling proceeds. We suggest that these microclusters are the site of cooperative interactions that are required for ligand discrimination; for example, TCRs engaging agonist peptide–MHC ligand enhance signalling by other TCRs in the microcluster through positive feedback. APC, antigen-presenting cell.
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REVIEWS TCR–CD3 complex, which may alter susceptibility to phosphorylation. With continued triggering, TCR–CD3 complex aggregates enlarge to form microclusters containing 10–100 TCRs, some of which are bound to foreign peptide–MHC complexes (FIG. 2c). The crucial requirement for TCRs to discriminate between abundant self and rare foreign peptide–MHC complexes is achieved at two levels. Individual TCRs use mechanisms such as kinetic proof-reading to discriminate binding events of different duration. However, as this is insufficient to cope with the stochastic nature of individual TCR–peptide–MHC interactions, we suggest that TCR microclusters are sites where multiple TCR–CD3 complexes cooperate to enable discrimination of rare foreign peptide–MHC ligands from more abundant self peptide–MHC molecules.
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Further progress in our understanding of TCR triggering will require better information about the structure of the full TCR–CD3 complex and how this structure changes on peptide–MHC binding. Determining the structure of transmembrane proteins, particularly multisubunit proteins, is a major research bottleneck and progress in this area is likely to be slow and require considerable ingenuity. Also important is high-resolution information about the arrangement of the TCR–CD3 complex and other cell-surface and signalling molecules and how this arrangement changes following peptide–MHC engagement. Recent developments in super-resolution fluorescence microscopy suggest that advances in this area are probable over the next decade as these new techniques become more widely available.
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70. Gagnon, E. et al. Response multilayered control of T cell receptor phosphorylation. Cell 142, 669–671 (2010). 71. Ma, Z., Janmey, P. A. & Finkel, T. H. The receptor deformation model of TCR triggering. FASEB J. 22, 1002–1008 (2008). 72. Choudhuri, A., Kearney, A., Bakker, T. R. & van der Merwe, P. A. Immunology: how do T cells recognize antigen? Curr. Biol. 15, R382–R385 (2005). 73. Li, Y. C. et al. Cutting edge: mechanical forces acting on T cells immobilized via the TCR complex can trigger TCR signaling. J. Immunol. 184, 5959–5963 (2010). This study provides evidence that the application of mechanical force on the TCR may induce TCR triggering. 74. van der Merwe, P. The TCR triggering puzzle. Immunity 14, 665–668 (2001). 75. Ghendler, Y., Smolyar, A., Chang, H. C. & Reinherz, E. L. One of the CD3ε subunits within a T cell receptor complex lies in close proximity to the Cβ FG loop. J. Exp. Med. 187, 1529–1536 (1998). 76. Geppert, T. D. & Lipsky, P. E. Accessory cell independent proliferation of human T4 cells stimulated by immobilized monoclonal antibodies to CD3. J. Immunol. 138, 1660–1666 (1987). 77. Ma, Z., Sharp, K. A., Janmey, P. A. & Finkel, T. H. Surface-anchored monomeric agonist pMHCs alone trigger TCR with high sensitivity. PLoS Biol. 6, e43 (2008). 78. Choudhuri, K. et al. Peptide–MHC dimensions control proximal kinase–phosphatase balance during T cell activation. J. Biol. Chem. 284, 26096–26105 (2009). 79. Choudhuri, K., Wiseman, D., Brown, M. H., Gould, K. & van der Merwe, P. A. T cell receptor triggering is critically dependent on the dimensions of its peptide– MHC ligand. Nature 436, 578–582 (2005). 80. Kim, S. T. et al. The αβ T cell receptor is an anisotropic mechanosensor. J. Biol. Chem. 284, 31028–31037 (2009). 81. Valitutti, S., Dessing, M., Aktories, K., Gallati, H. & Lanzavecchia, A. Sustained signalling leading to T cell activation results from prolonged T cell receptor occupancy. Role of the T cell actin cytoskeleton. J. Exp. Med. 181, 577–584 (1995). 82. Davis, M. M. A new trigger for T cells. Cell 110, 285–287 (2002). 83. Call, M. E., Pyrdol, J., Wiedmann, M. & Wucherpfennig, K. W. The organizing principle in the formation of the T cell receptor–CD3 complex. Cell 111, 967–979 (2002). 84. Call, M. E. et al. The structure of the ζζ transmembrane dimer reveals features essential for its assembly with the T cell receptor. Cell 127, 355–368 (2006). 85. Tolar, P. & Pierce, S. K. A conformation-induced oligomerization model for B cell receptor microclustering and signaling. Curr. Top. Microbiol. Immunol. 340, 155–169 (2010). 86. Tolar, P., Hanna, J., Krueger, P. D. & Pierce, S. K. The constant region of the membrane immunoglobulin mediates B cell-receptor clustering and signaling in response to membrane antigens. Immunity 30, 44–55 (2009). 87. Nika, K. et al. Constitutively active Lck kinase in T cells drives antigen receptor signal transduction. Immunity 32, 766–777 (2010). This study showed that a large proportion of LCK in resting T cells is already in the active form and that this does not seem to change significantly upon TCR triggering. 88. Davis, S. J. & van der Merwe, P. A. The structure and ligand interactions of CD2: implications for T-cell function. Immunol. Today 17, 177–187 (1996). 89. van der Merwe, P. A., Davis, S. J., Shaw, A. S. & Dustin, M. L. Cytoskeletal polarization and redistribution of cell surface molecules during T cell antigen recognition. Semin. Immunol. 12, 5–21 (2000).
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90. Horejsi, V. Lipid rafts and their roles in T-cell activation. Microbes Infect. 7, 310–316 (2005). 91. Davis, S. J. & van der Merwe, P. A. The kineticsegregation model: TCR triggering and beyond. Nature Immunol. 7, 803–809 (2006). 92. Lin, J. & Weiss, A. The tyrosine phosphatase CD148 is excluded from the immunologic synapse and downregulates prolonged T cell signaling. J. Cell Biol. 162, 673–682 (2003). 93. Irles, C. et al. CD45 ectodomain controls interaction with GEMs and Lck activity for optimal TCR signaling. Nature Immunol. 4, 189–197 (2003). 94. Bluemel, C. et al. Epitope distance to the target cell membrane and antigen size determine the potency of T cell-mediated lysis by BiTE antibodies specific for a large melanoma surface antigen. Cancer Immunol. Immunother. 59, 1197–1209 (2010). 95. James, S. E. et al. Antigen sensitivity of CD22-specific chimeric TCR is modulated by target epitope distance from the cell membrane. J. Immunol. 180, 7028–7038 (2008). 96. Munro, S. Lipid rafts: elusive or illusive? Cell 115, 377–388 (2003). 97. Lingwood, D. & Simons, K. Lipid rafts as a membrane-organizing principle. Science 327, 46–50 (2010). 98. Gaus, K., Chklovskaia, E., Fazekas de St. Groth, B., Jessup, W. & Harder, T. Condensation of the plasma membrane at the site of T lymphocyte activation. J. Cell Biol. 171, 121–131 (2005). 99. Zech, T. et al. Accumulation of raft lipids in T-cell plasma membrane domains engaged in TCR signalling. EMBO J. 28, 466–476 (2009). 100. Harder, T. & Sangani, D. Plasma membrane rafts engaged in T cell signalling: new developments in an old concept. Cell Commun. Signal. 7, 21 (2009). 101. Glebov, O. O. & Nichols, B. J. Lipid raft proteins have a random distribution during localized activation of the T-cell receptor. Nature Cell Biol. 6, 238–243 (2004). 102. Hashimoto-Tane, A. et al. T-cell receptor microclusters critical for T-cell activation are formed independently of lipid raft clustering. Mol. Cell. Biol. 30, 3421–3429 (2010). 103. Pizzo, P. et al. Lipid rafts and T cell receptor signaling: a critical re-evaluation. Eur. J. Immunol. 32, 3082–3091 (2002). 104. Zhu, M., Shen, S., Liu, Y., Granillo, O. & Zhang, W. Cutting edge: localization of linker for activation of T cells to lipid rafts is not essential in T cell activation and development. J. Immunol. 174, 31–35 (2005). 105. Huang, J. et al. The kinetics of two-dimensional TCR and pMHC interactions determine T-cell responsiveness. Nature 464, 932–936 (2010). 106. Huppa, J. B. et al. TCR–peptide–MHC interactions in situ show accelerated kinetics and increased affinity. Nature 463, 963–967 (2010). References 105 and 106 measured the two-dimensional affinity and kinetics of TCR–peptide–MHC interactions for the first time. 107. Zarnitsyna, V. I. et al. Memory in receptor– ligand-mediated cell adhesion. Proc. Natl Acad. Sci. USA 104, 18037–18042 (2007).
Acknowledgements
We thank our many scientific colleagues and collaborators, including S. Cordoba, H. Zhang, S. Davis, T. Harder, M. Brown, N. Barclay and O. Acuto, for many valuable discussions and insights, and for communicating results before publication. We also thank the referees for their comments and suggestions.
Competing interests statement
The authors declare no competing financial interests.
FURTHER INFORMATION P. Anton van der Merwe’s homepage: http://www.path.ox.ac.uk/groups/vandermerwe All lInks ARe ACTIve In The onlIne pdf
vOLuMe 11 | jANuARY 2011 | 55 © 2011 Macmillan Publishers Limited. All rights reserved
PerSPecTIveS Science and Society
Experimental human challenge infections can accelerate clinical malaria vaccine development Robert W. Sauerwein, Meta Roestenberg and Vasee S. Moorthy
Abstract | Malaria is one of the most frequently occurring infectious diseases worldwide, with almost 1 million deaths and an estimated 243 million clinical cases annually. Several candidate malaria vaccines have reached Phase IIb clinical trials, but results have often been disappointing. As an alternative to these Phase IIb field trials, the efficacy of candidate malaria vaccines can first be assessed through the deliberate exposure of participants to the bites of infectious mosquitoes (sporozoite challenge) or to an inoculum of blood-stage parasites (blood-stage challenge). With an increasing number of malaria vaccine candidates being developed, should human malaria challenge models be more widely used to reduce cost and time investments? This article reviews previous experience with both the sporozoite and blood-stage human malaria challenge models and provides future perspectives for these models in malaria vaccine development. Half of the world’s population (more than 3 billion people) live in malaria-endemic areas, and an estimated 243 million cases of malaria led to nearly 863,000 deaths in 2008 according to the World Health Organization (WHO) World Malaria Report 2009. There are five species of human malaria parasite: Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, Plasmodium malariae and Plasmodium knowlesi. Recent evidence indicates that P. ovale is composed of two subspecies1. Most infections are caused by P. falciparum, which is particularly dominant in sub-Saharan Africa. P. vivax is the most widely spread cause of malaria, being responsible for an estimated 80 million to 300 million cases every year, and thus it accounts for a major burden of disease2. Plasmodium parasites are highly prevalent in Asia and South America, where individuals can be infected with more than one malaria parasite species simultaneously. Infective foci of P. knowlesi have been identified in the past decade in Malaysia, where P. knowlesi is transmitted from simian hosts to humans.
Plasmodia are transmitted by the bites of infected Anopheles mosquitoes. Control strategies are based on the early diagnosis and treatment of uncomplicated infections with artemisinin-based combination therapies, thereby also decreasing transmission3, combined with preventive measures aimed at vector (mosquito) control. Artemisinin-based combination therapies — such as artemether plus lumefantrine, artesunate plus amodiaquine, artesunate plus mefloquine or artesunate plus sulphadoxine–pyrimethamine — have been the WHO-recommended treatment for uncomplicated P. falciparum malaria since the development of widespread resistance to chloroquine and sulphadoxine–pyrimethamine. Unfortunately, in P. falciparum, resistance has been observed to all current antimalarial drugs (amodiaquine, chloroquine, mefloquine, quinine and sulphadoxine-pyrimethamine) and, more recently, also to artemisinin derivatives. For uncomplicated P. vivax infection, treatment with chloroquine is recommended in
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those areas without chloroquine resistance. Artemisinin-based combination therapies can be used as an alternative treatment for chloroquine-resistant P. vivax. In these cases, artemether plus sulphadoxine–pyrimethamine is not recommended because P. vivax can acquire resistance to sulphadoxine– pyrimethamine. To fully eradicate P. vivax infection, primaquine must be administered to prevent relapses. P. ovale and P. malariae infections are treated similarly to P. vivax infections, although there is no need for primaquine treatment in patients who are infected with P. malariae, as this species does not form dormant or latent hypnozoites in hepatocytes (see the WHO Guidelines for the Treatment of Malaria). Vector control is the primary intervention for decreasing malaria transmission at the community level. When universal vector control coverage is achieved by impregnating bed nets and spraying indoor surfaces of houses with insecticides, malaria transmission can be decreased to close to zero. Unfortunately, the increasing resistance of mosquitoes to insecticides such as dichlorodiphenyltrichloroethane (DDT) and pyrethroids, particularly in Africa, poses challenges to current prevention policies (see the WHO World Malaria Report 2009). In this context, the development of an effective vaccine could make a significant contribution to the fight against malaria. Ambitious goals in this regard have been set by the Malaria Vaccine Technology Roadmap Process, which aims to achieve a licensed first-generation P. falciparum malaria vaccine with more than 50% protective efficacy against severe disease and death, lasting for at least 1 year, by the year 2015. Malaria vaccine development has been fuelled by new technology enabling the sequencing of the P. falciparum, P. vivax and Anopheles gambiae genomes and the development of experimentally relevant animal models, combined with significant increases in financial resources from funders such as the Bill & Melinda Gates Foundation, the European Union, the US National Institutes of Allergy and Infectious Diseases and the US Agency for International Development. Currently, there are 38 P. falciparum and two P. vivax candidate malaria vaccines or VOlUME 11 | jANUARy 2011 | 57
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PersPectives
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Figure 1 | Plasmodium falciparum life cycle showing the three developmental stages of the parasite that are targeted by malaria vaccine candidates. Parasites (sporozoite stage) are injected into the skin by a female Anopheles spp. mosquito. From the skin, a proportion of sporozoites will travel 0CVWTG4GXKGYU^+OOWPQNQI[ through the bloodstream to the liver. Some sporozoites will be trapped in regional lymph nodes. In hepatocytes, parasites develop and multiply for 6–7 days before merosomes are budded from the cell and enter the hepatic sinusoids. Merosomes eventually rupture, releasing merozoite-stage parasites that invade erythrocytes for further reproduction. clinical malaria is caused by the 48-hour cyclical proliferation of asexual-stage parasites in erythrocytes. Malaria mortality is primarily due to organ dysfunction, in particular of the brain, following sequestration of infected erythrocytes in the microvasculature. The development of sexual forms of the parasite (gametocytes) in the blood allows the transmission of parasites to mosquitoes with subsequent bites. Once ingested, the parasite gametocytes taken up in the blood further differentiate into male or female gametes and then fuse in the mosquito gut. This produces an ookinete that penetrates the gut lining and produces an oocyst in the gut wall. When the oocyst ruptures, it releases sporozoites that migrate through the mosquito’s body to the salivary glands, where they are then ready to infect a new human host. Image is modified, with permission, from REF. 59 © (2004) Macmillan Publishers Ltd. All rights reserved.
vaccine components in advanced preclinical or clinical development as listed by the WHO Malaria Vaccine Rainbow Tables. Malaria vaccine candidates are categorized according to the Plasmodium life cycle stage at which the targeted antigen is expressed (FIG. 1). Pre-erythrocytic stage vaccines aim to prevent the passage of parasites through the human liver and subsequent blood-stage infection, leading to
the induction of sterile immunity. Asexual erythrocytic stage vaccines focus on delaying or decreasing parasite multiplication in red blood cells, thereby decreasing morbidity and preventing mortality. Transmissionblocking vaccines consist of sexual- or mosquito-stage antigens that prevent infection passing from humans to mosquitoes, thereby decreasing the spread of malaria in the population.
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Generally, less than 10% of preclinical vaccine projects progress to Phase III clinical evaluation4. Clinical development is time consuming and costly. Candidate malaria vaccines are selected downstream of clinical testing on the basis of safety, immunogenicity and, eventually, efficacy profiles. Whereas the first two criteria can generally be assessed in a small initial Phase I trial, field vaccine efficacy can only be assessed in Phase II trials, which require larger study groups in malaria-endemic areas. The sample size of Phase II trials depends on the prevalence of malaria infections in that area and the expected efficacy of the candidate vaccine. Ideally, immunological assays carried out in initial clinical trials should predict potential efficacy in subsequent trials, by analogy with, for example, hepatitis B virus surface antigen (HBsAg)specific antibody titres for the hepatitis B vaccine. However, with the current lack of unequivocal correlates of immune protection against malaria in either animal models or in vitro assays on human samples, there is a continuous need to test field efficacy in time-consuming and costly Phase II trials in malaria-endemic areas. There are only a limited number of competent field trial sites for malaria that can adhere to the good clinical practice guidelines established by the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH), which describe the monitoring, reporting and archiving responsibilities of all participants in the conduct of clinical trials (see The Malaria Product Pipeline: Planning for the Future). Finally, there seems to be a downward trend in malaria incidence in several endemic areas, most probably as a result of improved policy and adherence to malaria control measures, and this will further increase the size and costs of Phase II field trials5. Human experimental sporozoite infections carried out under strictly controlled laboratory and clinical conditions, in which volunteers are exposed to the bites of laboratory-reared Plasmodium-infected mosquitoes, are an intermediate step between Phase I and Phase II trials, providing information on preliminary vaccine efficacy. It is common practice to test the efficacy of pre-erythrocytic stage malaria vaccine candidates by experimental sporozoite infection before going into the field. In such cases, a distinction is thus made between Phase IIa trials using experimental infection of volunteers in non-endemic areas and Phase IIb field trials in endemic areas. www.nature.com/reviews/immunol
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PersPectives Poor preliminary efficacy in Phase IIa trials may subsequently halt progression of the vaccine candidate to Phase IIb trials. By contrast, the efficacy of asexual erythrocytic stage vaccine candidates is generally assessed in field trials only, although blood-stage challenge models have been used. Here, we present the history of artificial malaria challenge infections, the clinical aspects of P. falciparum challenges using sporozoites or blood-stage parasites and experience with P. vivax challenges. We discuss the strengths and limitations of both models and provide future perspectives. Historical perspective Deliberate infection of humans with malaria was first carried out in 1917 by Wagner von jauregg6 as a therapy primarily for patients with neurosyphilis, and he was awarded the Nobel Prize in Medicine for his work in 1927. Thousands of patients have undergone this treatment, which was administered by the bites of infectious mosquitoes or by intravenous or subcutaneous inoculation of dissected Plasmodium sporozoites suspended in media. Historically, P. vivax was used most frequently, but infections were also carried out with P. falciparum, P. malariae and P. ovale. The objective was to induce a febrile illness that was thought to be beneficial for the prognosis of the disease. This practice stopped with the advent of antibiotics for the treatment of the Treponema pallidum infection that causes syphilis. In the 1960s, experimental human malaria infections were used to assess the effects of anti-malaria treatments on healthy non-immune male inmates in the United States7. Following the discovery of protocols for the continuous culture of P. falciparum in 1976 (REF. 8) and protocols for the generation of mature P. falciparum gametocytes in vitro in 1981 (REF. 9), laboratory-reared infectious mosquitoes could be produced10 and human malaria sporozoite infections could be carried out more routinely. The first well-documented study of human experimental malaria infection with these laboratory-reared infectious mosquitoes was carried out in 1986 at the US Walter Reed Army Institute of Research (WRAIR), the US Naval Medical Research Institute (NMRI) and the US National Institutes of Health (NIH). Six volunteers were infected with P. falciparum sporozoites by the bites of infectious Anopheles freeborni and Anopheles stephensi mosquitoes11. The following year, the efficacies of the first recombinant protein and synthetic peptide
P. falciparum vaccines were tested in experimentally infected volunteers12,13. Since the late 1980s, the number of institutions carrying out experimental infections with P. falciparum sporozoites has been growing. In 2007, data were published from a total of 532 volunteers14. So far, unpublished analysis shows that a total of 1,343 volunteers have been experimentally infected with P. falciparum between 1985 and 2009 (REF. 15); 526 of these volunteers took part in vaccine trials (TABLE 1), and of these, 118 volunteers were protected against infection by the vaccine candidate. The most successful immunogens were RTS,S (a pre-erythrocytic stage vaccine consisting of the P. falciparum circumsporozoite protein combined with HBsAg; developed by GlaxoSmithKline in partnership with PATH Malaria Vaccine Initiative) and irradiated whole parasites delivered by mosquito bite. comparison with field trials Differences between natural and experimental infections mean that it is important to validate the results of Phase IIa challenge trials with data from Phase IIb field trials in malaria-endemic areas. Only three candidate vaccines have been assessed by both types of trial, allowing a comparison of the protective outcomes. The best studied candidate vaccine, RTS,S, which is currently in Phase III trials, has repeatedly demonstrated a protective efficacy of ~30–50% in Phase IIa trials with sterile protection as the study end point 16–18. Interestingly, a similar ~30–50% efficacy of RTS,S was found in Phase IIb trials in the field using time to first clinical malaria episode as the primary study end point19. A similar association between the results of Phase IIa and Phase IIb trials was found when testing long-term protection in adults19,20. A second pre-erythrocytic stage candidate vaccine, ME-TRAP (a multi-epitope string fused to thrombospondin-related adhesion protein), delivered by a DNA prime and attenuated poxvirus boost, induced complete protection in only a few volunteers (three out of 74) in Phase IIa trials, and no protection was found in adult Phase IIb field studies in the Gambia21,22. Artificial blood-stage challenge has been used in a Phase II trial after immunization with Combination B (a combination of merozoite surface protein 1 (MSP1), MSP2 and ring-infected erythrocyte surface antigen (RESA)) in 17 volunteers, which resulted in no decrease in parasite growth rates23,24; this is in line with results from a Phase IIb trial of Combination B conducted in Papua New
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Guinea25. These limited data indicate that results obtained in experimental challenges are generally in line with results in the field, but more comparisons are required before definite conclusions can be drawn. experimental sporozoite infection The delivery of sporozoite-stage malaria parasites by mosquito bites has traditionally been used as a model to test pre-erythrocytic stage vaccines. Since the late 1980s, standardization of experimental sporozoite infections has improved and efforts to further increase harmonization are ongoing. Such infections are currently routinely carried out at: the US Military Malaria Vaccine Program; the University of Maryland, USA; Radboud University Nijmegen Medical Centre (RUNMC), the Netherlands; the University of Oxford, UK; and, more recently, Seattle Biomed, USA15. All centres use A. stephensi mosquitoes that feed on either the chloroquine-sensitive NF54 strain of P. falciparum or the 3D7 clone of NF54. In addition, limited numbers of volunteers have been challenged with the 7G8 strain of P. falciparum14. Approximately 14–21 days after feeding, mosquitoes are checked for infection by microscopic examination of salivary glands. Healthy human volunteers are subsequently exposed to the bites of five infectious mosquitoes for either 5 or 10 minutes (FIG. 2). Almost 100% of volunteers bitten by five infected mosquitoes develop patent parasitaemia, with very rare exceptions26,27. Infection rates drop significantly when volunteers are exposed to fewer than five infected mosquitoes27,28. After infection, subjects are monitored closely on an outpatient basis. Signs and symptoms such as headache, myalgia and fever are noted, and a physical examination and thick blood smears (a drop of blood on a glass slide) are carried out once, twice or thrice daily. The period before blood-stage parasites can be detected in thick smears by microscopy (the prepatent period) ranges from 7 to 20 days, with a mean of approximately 11 days7,14,26. As soon as parasites are microscopically detected, volunteers are treated with a curative regimen of chloroquine, artemether plus lumefantrine, or atovaquone plus proguanil. Nearly all volunteers will develop symptoms of clinical malaria infection; approximately one-fifth of volunteers temporarily develop symptoms graded as severe (symptoms that prevent daily activities), but severe or life-threatening malaria has never occurred26. The most common symptoms are fatigue and headache, VOlUME 11 | jANUARy 2011 | 59
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PersPectives Table 1 | Summary of published Phase iia sporozoite challenge trials with Plasmodium falciparum candidate vaccines Vaccine
Plasmodium protein
Category
number of number of volunteers volunteers challenged protected
year of publication
Institution or company
Irradiated sporozoites
Whole parasite
Pre-erythrocytic 37
Several products
cSP
Several products AMA1 with AS02A or AS01B
20 (54.05%)
1970s–1993
NMrI* and WrAIr*; University of Maryland, USA; University of Sydney, Australia
Pre-erythrocytic 317
94 (29.65%)
1987–2009
University of Maryland; WrAIr*; University of Oxford, UK; Johns Hopkins University School of Hygiene and Public Health, Maryland, USA; NMrI*; University of Lausanne, Switzerland
12,13,16, 18,20,22, 40,45,62, 66–73
TrAP
Pre-erythrocytic 74
3 (4.05%)
2003–2006
University of Oxford
22,74,75
AMA1
Asexual erythrocytic
16
0 (0%)
2009
US Military Malaria vaccine Program
35
LSA1-Nrc with AS01 or AS02
LSA1
Pre-erythrocytic 22
0 (0%)
2010
WrAIr*
76
NYvAc-Pf7
cSP, SSP2, LSA1, MSP1, SerA, AMA1, Pfs25
All stages
1 (2.86%)
1998
WrAIr*
77
FFM Me-TrAP plus Pev3A
cSP, TrAP and AMA1
Pre-erythrocytic 24 and asexual erythrocytic
0 (0%)
2008
University of Oxford
78
SPf(66)30 or SPf(105)20 with Alum
MSP
Asexual erythrocytic
0 (0%)‡
1988
Universidad Nacional de colombia
79
MuStDO 5
cSP, eXP1, SSP2, LSA1, LSA3
Pre-erythrocytic 31
0 (0%)
2005
Naval Medical research center*
80
FMP1 with AS02A
MSP1
Asexual erythrocytic
0 (0%)
2005
WrAIr*
81
35
9
Unknown
Refs
60–65
Alum, aluminium hydroxide adjuvant (Alhydrogel; Brenntag biosector); AMA1, apical membrane antigen 1; AS01, GlaxoSmithKline adjuvant system 01; cSP, circumsporozoite protein; eXP1, exported protein 1; FFM Me-TrAP, multi-epitope string fused to TrAP that is delivered in fowlpox virus strain FP9 and modified vaccinia virus Ankara vectors in prime–boost combinations; FMP1, carboxy-terminal region of MSP1; LSA, liver-stage antigen; LSA1-Nrc, full-length carboxy- and amino-terminal flanking domains and two of the 17 amino acid repeats from the central repeat region of LSA1; MSP, merozoite surface protein; MuStDO 5, multi-stage DNA vaccine operation 5 antigens; NMrI, Naval Medical research Institute, USA; NYvAc-Pf7, a highly attenuated vaccinia virus with seven P. falciparum genes inserted into its genome; Pev3A, virosomal formulation of cSP and AMA1; Pfs25, 25kDa ookinete surface antigen; SerA, serine-repeat antigen protein; SSP2, sporozoite surface protein 2; SPf, synthetic P. falciparum peptides of MSP; TrAP, thrombospondin-related adhesion protein; WrAIr, Walter reed Army Institute of research, USA. *currently the US Military Malaria vaccine Program. ‡Three of five volunteers immunized with SPf(66)30 eventually cleared parasitaemia after they experienced asexual parasitaemia that was detectable by microscopy.
and severe symptoms can include headache, fatigue, malaise, chills, myalgia, rigors, nausea and vomiting. Clinical symptoms generally coincide with the detection of blood-stage parasites at densities of 10–20 parasites per μl of blood by microscopy of thick blood smears26. This corresponds to a parasitaemia of approximately 0.0004%. Severe malaria is generally diagnosed when parasitaemia is 3 to 4 logs greater than the peak parasitaemia in challenge trials. After the start of malaria treatment, symptoms can temporarily increase in severity but subside quickly with an average duration of approximately 2–3 days. Routine laboratory checks generally show a moderate decrease in leukocyte and platelet numbers during infection, with no change in haemoglobin concentration27. Bleeding or thrombogenic complications have never been described26,27.
Abnormalities of liver enzymes have been observed, but these abnormalities did not result in clinical manifestations and they resolved after a few days26,27. Immediate treatment of volunteers at the earliest phase of microscopically detectable blood-stage infection ensures that the potential risks of complications associated with severe malaria are minimized to the greatest extent possible. Indeed, human malaria challenge infections have been shown to be safe in the 1,343 volunteers challenged so far 14,26,27. Recently, safety concerns were raised because of a cardiac event in a young volunteer shortly after treatment for diagnosed malaria, although a definite relationship between the cardiac event and the experimental malaria infection was not established29. Nevertheless, it has been generally agreed that volunteers with an increased risk of cardiac disease should be excluded from such trials.
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In addition to the clinical manifestations, participation in an experimental sporozoite infection trial has a major impact on the daily life of volunteers, particularly because of the intense follow-up with blood sampling several times daily. Volunteers’ perception of their participation in such a trial depends mainly on whether they have realistic expectations of trial procedures and the severity of symptoms, indicating the importance of providing accurate and sufficient information to volunteers before the onset of the trial. Measurement of parasitaemia A real-time quantitative PCR assay based on 18S ribosomal RNA gene transcripts has been developed for tracking the kinetics of developing parasitaemia before a positive diagnosis of infection can be made from a thick blood smear using microscopy30. This www.nature.com/reviews/immunol
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PersPectives assay is becoming increasingly important for assessing very low parasite densities and incremental changes in density in smallscale Phase IIa trials31. The detection of parasites below microscopy thresholds by PCR allows for a detailed analysis of cyclical parasite growth in the blood, albeit for a short time window of 2–3 days between liver-stage infection and microscopic detection30. Several statistical models have been developed to further analyse profiles of parasitaemia and partial protection in vaccine trials32–34. For example, these models allow a separate estimation of liver-stage and blood-stage parasite development. From the first wave of parasite DNA that is detected in the blood, an estimation can be made of the number of merozoites released from the liver, making it possible to approximate the extent of pre-erythrocytic stage inhibition resulting from a vaccine (simulated in FIG. 3a). Similarly, the ratio of parasite DNA between the second and first replication cycles in the blood reflects the growth rate of blood-stage parasites. Comparing these ratios between test subjects and controls can indicate inhibitory effects of a vaccine candidate on the growth of blood-stage parasites (simulated in FIG. 3b). Such analyses could be of particular interest in trials of multi-stage vaccines (combining both liver- and blood-stage antigens) to assess stage-specific protective immunity. For example, statistical modelling of parasitaemia from a recent Phase IIa trial with the vaccine candidate apical membrane antigen 1 (AMA1), a protein that is mainly expressed by blood-stage parasites, indicates inhibition of pre-erythrocytic parasite stages35, which highlights the possible role of sporozoite-expressed AMA1 in disease progression36. experimental blood-stage infection The evaluation of asexual erythrocytic stage vaccine candidates requires follow-up of blood-stage parasitaemia over a sufficiently lengthy period of time to determine parasite growth rates. This requirement could compromise the safety of volunteers, as blood-stage parasitaemia is responsible for malaria morbidity and even mortality. In currently accepted protocols, the appearance of Plasmodium-infected erythrocytes in thick blood smears examined microscopically leads to immediate initiation of treatment with curative anti-malarial drugs. Harbouring higher numbers of parasites in the bloodstream increases the risks to volunteer safety, so the length of the observation period for parasite multiplication in erythrocytes is limited.
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Figure 2 | Timeline of Plasmodium falciparum sporozoite challenge infection in humans. Gametocytes are derived from in vitro parasite culture in donor blood and are fed to laboratory-reared 0CVWTG4GXKGYU^+OOWPQNQI[ Anopheles stephensi mosquitoes. After 14–21 days, five infectious mosquitoes are allowed to feed on malaria-naive human volunteers for 5–10 minutes. Subsequent development of liver-stage parasites is subclinical and takes approximately 6 days. Parasites can be detected in the blood of unprotected volunteers by microscopy (using a thick blood smear) on average 11 days (range 7–15 days) after challenge.
A possible solution is the intravenous inoculation of very small numbers of infected erythrocytes, based on the idea that such a low level of sub-microscopic parasitaemia will not result in clinical risks and will allow extended follow-up of parasite replication in erythrocytes. The number of parasites that are inoculated is approximately 1,000 times lower than the estimated number of merozoites released from the liver following a standard experimental sporozoite challenge with bites from five infected mosquitoes. This allows for an extended blood-stage follow-up of approximately three more replication cycles (6 days) before thick blood smear detection thresholds are reached, with obligatory treatment. A master cell bank of infected erythrocytes for human clinical use has been generated by storing infected erythrocytes from two parasitaemic volunteers who were infected by mosquito bites, in compliance with blood bank safety criteria37. Since the 1990s, approximately 50 humans have been infected by direct inoculation of infected erythrocytes from this master cell bank. The length of the prepatent period — the interval from inoculation until infected erythrocytes are microscopically detectable — correlates with the number of inoculated parasites7. The sensitivity of the model has been further increased by the administration of very small inoculae of infected erythrocytes, combined with the introduction of the quantitative real-time PCR assay for measuring parasite growth rates during this sub-microscopic period37,38. With inoculae as small as 300 infected erythrocytes, parasite growth curves were generated over a 7–9-day period before initiation of treatment was required 37.
NATURE REVIEWS | Immunology
The blood-stage challenge model has several potential shortcomings. The viability of the injected parasites can only be determined retrospectively by culture, so it is difficult to standardize the exact number of viable injected parasites. Differences of a factor of ten in terms of the number of viable parasites have been described between inoculae38,39. Furthermore, although the small number of inoculated parasites allows for a long window of observation, it may also boost the immune response, and low-level blood-stage infections are very efficient at inducing complete protection40. Finally, the liver stage of parasite development is circumvented by this model, bypassing potential immune effects induced by the vaccine on liverstage parasites. This may be important, as some asexual erythrocytic stage vaccine candidate antigens can also be expressed during the liver stage36. However, irrespective of these disadvantages, low-dose blood-stage challenges allow sufficient time to monitor several parasite multiplication cycles. With further validation, they might function as a crucial decision point for progress to Phase IIb trials, thereby saving time and money, and decreasing the requirement for Phase IIb trial subjects. So far, only one asexual erythrocytic stage vaccine has been tested by blood-stage challenge24. The results of a second trial with the vaccine AMA1 carried out at the University of Oxford, UK, will soon be reported (ClinicalTrials.gov identifier: NCT00984763). A direct comparison between blood-stage and sporozoite-stage challenge infections will be helpful to determine the most suitable model to test such asexual erythrocytic stage vaccines. VOlUME 11 | jANUARy 2011 | 61
© 2011 Macmillan Publishers Limited. All rights reserved
PersPectives
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Figure 3 | Simulated effects of immunization on parasite growth in the peripheral blood of volunteers after Plasmodium falciparum sporozoite challenge, based on statistical modelling. 0CVWTG4GXKGYU^+OOWPQNQI[ The kinetics of parasite growth after immunization depend on which parasite stage the vaccine targets. We simulated the effect of a pre-erythrocytic (a) or asexual erythrocytic (b) stage vaccine on cyclical parasite growth in peripheral blood. The effects of 0%, 70% or 90% inhibition on parasite numbers are shown. After sporozoite challenge, the kinetics of blood-stage parasitaemia can be evaluated by quantitative real-time Pcr up to the threshold of detection of parasites in the blood by microscopy (thick blood smear); this threshold is approximately 4 × 103 parasites per ml of blood. A careful comparison of blood-stage parasitaemia between immunized and control volunteers in a sporozoite challenge trial will allow investigators to distinguish between pre-erythrocytic or asexual erythrocytic stage inhibition. Furthermore, the percentage inhibition can be estimated. Image is modified, with permission, from REF. 32 © (2004) The American Society of Tropical Medicine and Hygiene.
Plasmodium vivax infection Although the first experimental human malaria infections were carried out with P. vivax41, the standardization of P. vivax challenge for routine use has proven to be much more difficult than for P. falciparum challenge. A major hurdle is the absolute requirement for reticulocytes or young erythrocytes to obtain long-term in vitro growth of P. vivax. Nevertheless, promising results have been obtained through an alternative approach in which experimental infections are initiated using wild-type P. vivax parasites obtained from infected humans in Colombia. Blood from P. vivax-infected patients was assessed using routine blood bank procedures to exclude the presence of other transmissible agents (such as T. pallidum, hepatitis B virus and hepatitis C virus) and was subsequently fed to laboratory-reared Anopheles albimanus mosquitoes. After 14–15 days, mosquitoes were allowed to feed for 10–15 minutes on the forearms of healthy human volunteers. A total of 40 non-immune volunteers took part in two different trials, and data from 17 volunteers have been published so far15,42. After microscopic detection of parasites by thick blood smear, all participants were treated with a combination of chloroquine and primaquine. Because a proportion of P. vivax parasites can lay dormant as hypnozoites in the liver or develop slowly in humans, resulting in long prepatent periods23, primaquine is prescribed to
ensure clearance of all liver-stage parasites. This complicated protocol may be further compromised by drug resistance of some P. vivax strains, as is commonly observed in Southeast Asia. The most frequently reported symptoms were myalgia, headache and malaise, without the occurrence of severe or serious adverse events. The prepatent period was 9–13 days42. The P. vivax challenge model has been further developed in the US Military Malaria Vaccine Program by the transportation of freshly infected Anopheles dirus mosquitoes from the Thai– Burmese border to infect malaria-naive volunteers in the United States (ClinicalTrials. gov identifier: NCT00935623). Currently, the first P. vivax vaccine candidate, based on the P. vivax circumsporozoite protein VMP001, is being tested by such challenge studies in the United States (ClinicalTrials. gov identifier: NCT01157897). Quantitative real-time PCR detection of P. vivax parasite load and genotyping of wild-type parasites will further improve the P. vivax challenge model15. Hopefully, the future development of new laboratory tools, including the use of stem cells as a source for young erythrocytes, will facilitate the long-term in vitro culture of P. vivax. Strengths and limitations Experimental human challenges aim to predict the potential efficacy of vaccine candidates against natural infections in the field. A major strength of the sporozoite
62 | jANUARy 2011 | VOlUME 11
infection model is the use of infectious mosquitoes, mimicking the natural route of infection. Moreover, human experimental challenges are carried out in a controlled environment, allowing detailed evaluation of parasite growth and immunological determinants. In addition to the evaluation of vaccine efficacy, experimental challenges provide the opportunity to study correlates and mechanisms of protection. An example is the induction of immunity using whole parasites, by exposure of malaria-naive volunteers to infectious mosquito bites while using chloroquine prophylaxis43. Chloroquine kills blood-stage parasites but leaves liver-stage parasites unaffected, thereby exposing the liver-stage and early blood-stage antigens to the immune system. Subsequent challenge showed that volunteers were completely protected from infection, and this was associated with multi-functional memory T cell responses. However, such immunization protocols are not practical for use in the field because parasite inoculation cannot be controlled and chloroquine resistance is widespread. Several differences between experimental and naturally acquired infections might limit the interpretation of results from experimental challenge models. First, experimental infections are carried out using one parasite strain only, whereas it is well accepted that P. falciparum field strains are genetically diverse within and between regions44. Genetic diversity of the parasite strains is a major challenge for protein-based vaccines that target strain-specific antigens, and puts limitations on the direct translation of results from Phase IIa trials into the field situation. The availability of a small portfolio of genetically well-characterized P. falciparum strains for experimental infections would be a major asset. Trials to test such strains in humans are currently being carried out. Another potential difference is that in an experimental infection the parasite load is delivered almost instantly by five infected mosquitoes. Such a high parasite burden has been considered unnatural and might be an overly stringent test for the protective capacity of the vaccine-induced immune response45. However, although the frequency of infectious mosquito bites is generally less than this in malaria-endemic areas, intense transmission can occur. A person may be subjected to 35–96 mosquito bites per night, and in certain areas approximately 10% of mosquitoes are infected with P. falciparum46. www.nature.com/reviews/immunol
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PersPectives A final potential limitation of current malaria challenge models involving sporozoite infection relates to the uncontrolled number of sporozoites inoculated by biting mosquitoes. This number is generally thought to vary up to a maximum of several thousand sporozoites47–51. Use of a well-defined number of inoculated sporozoites will strengthen the power of the model, as the dose probably influences the prepatent period7,27,52. In principle, the most accurate way of dosing sporozoites is to inject them directly by needle and syringe, as the number of sporozoites counted in mosquito salivary glands or the number of mosquito bites is a poor predictor of the number of sporozoites injected49. Early in the practice of malaria therapy, sporozoites were extracted from mosquito salivary glands (in 1927)53 and the number of injected sporozoites was determined (in 1937)54. However, standardized sporozoite viability assays are not yet available. Recent progress has been made by Sanaria Inc.55, which has developed technology for the purification and cryopreservation of aseptic sporozoites for use in humans according to the current safety standards. The first results of a human challenge study with aseptic P. falciparum sporozoite-infected mosquitoes indicate that these mosquitoes might be very efficient at conveying infection56. Experimental human infections are underway to test the infectiousness of these cryopreserved sporozoites by needle injection. However, one must bear in mind that needle and syringe administration of a bolus of sporozoites is clearly different from mosquito bite delivery, which may be an important factor to consider particularly for sporozoite vaccines that aim to induce antibodies to immobilize sporozoites. conclusions and perspectives Experimental human infections provide a crude model to predict malaria vaccine efficacy in future field trials in a well-controlled setting. The experimental malaria challenge model in humans using P. falciparuminfected mosquito bites is now well established in several international sites and increasingly used as a crucial check point for the clinical development of pre-erythrocytic stage malaria vaccines. Taking into account the potential limitations, such efficacy data from Phase IIa trials will support the decisionmaking process by ethical boards and communities in malaria-endemic countries regarding whether to further test a candidate vaccine in Phase IIb trials in susceptible populations. In addition to vaccine safety data, the availability of information on potential efficacy is an important asset for ethical
justification to conduct experimental malaria infections in human volunteers. In vaccine research, most risk is borne by study subjects and the benefits accrue mainly to the community in finding safe and protective vaccines57. The only candidate malaria vaccine showing protective efficacy in Phase IIb field trials so far is RTS,S. This candidate vaccine would almost certainly never have been developed without optimization in a series of Phase IIa trials. As is true for any type of clinical research, risks must be minimized and scientific benefits maximized. We believe that the benefits of Phase IIa trials outweigh the potential risks in well-designed studies and will be essential to the development of an effective malaria vaccine, provided that all safeguards are in place for the safety of volunteers58. The more recent introduction of a sensitive PCR assay for parasite detection has enhanced the reproducibility and statistical power of human challenge infections. Statistical models will be applied to further improve the discriminative power between control and test groups as well as to provide biological information about the parasite life cycle (including the duration of liver-stage maturation, number of infected hepatocytes, duration of blood-stage trophozoite maturation and multiplication rates). Initiatives are underway to further strengthen and harmonize the human challenge model, with possible applications for testing asexual erythrocytic stage vaccines and for P. vivax vaccine research15. As there is substantial variation in the numbers of sporozoites that are injected by mosquitoes and this cannot be controlled in the sporozoite challenge model, administration of a known number of sporozoites by needle injection may be a further improvement to the model. In addition, the human challenge model will benefit from the availability of a small portfolio of genetically well-characterized strains to explore immune responses to different strains and heterologous protection. Such advances will accelerate malaria vaccine development, with the aim of meeting the ambitious goals of the Malaria Vaccine Technology Roadmap by 2015–2025. Robert W. Sauerwein and Meta Roestenberg are at the Department of Medical Microbiology, Radboud University Nijmegen Medical Centre, P.O. BOX 9101, 6500 HB Nijmegen, The Netherlands. Vasee S. Moorthy is at the Initiative for Vaccine Research, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland. Correspondence to R.W.S. e‑mail:
[email protected] doi:10.1038/nri2902
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Acknowledgements
The views expressed in this manuscript are those of the authors and should not be taken to represent the views or stated policy of the World Health Organization.
Competing interests statement
The authors declare no competing financial interests.
FURtHeR inFoRMation clinicaltrials.gov: http://clinicaltrials.gov icH: http://www.ich.org Malaria vaccine technology roadmap Process: http://www.malariavaccine.org/files/Malaria_vaccine_TrM_ exec_Summary_Final_000.pdf the Malaria Product Pipeline: Planning for the Future: www.policycures.org/downloads/The_malaria_product_ pipeline_planning_for_the_future.pdf WHO Guidelines for the treatment of Malaria: http://www. who.int/malaria/publications/atoz/9789,241,547,925/en/ index.html WHO Malaria vaccine rainbow tables: www.who.int/vaccine_research/links/rainbow/en/index. html WHO World Malaria report 2009: http://www.who.int/malaria All lInkS ARe ACTIVe In The onlIne pdf
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PersPectives OpiniOn
The quest for a T cell-based immune correlate of protection against HIV: a story of trials and errors Richard A. Koup, Barney S. Graham and Daniel C. Douek
Abstract | Even before the partial success of a preventive HIV vaccine in a recent Phase III clinical trial, there had been an active research effort to determine one or more immune correlates of protection for HIV infection. This effort has been hampered by the lack of natural protective immunity against HIV. As a result, most of the studies have focused on long-term non-progressive infection or other clinical situations, none of which fully recapitulates protective immunity against HIV. Although this effort has been successful in defining characteristics of T cells in acute and non-progressive HIV infection, and has therefore greatly expanded our knowledge of the immunopathogenesis of AIDS, its success in defining immune correlates of protection is less clear. In this Opinion article we offer a perspective on how successful this effort has been in defining immune correlates of protection that have been, or will be, of use in the development of an HIV vaccine. Our view is that investing in an iterative approach to human vaccine efficacy trials of sufficient size and sampling frequency will improve the likelihood that an immune correlate of vaccine protection will be defined. Only a few potential HIV vaccines have undergone testing for efficacy in humans1–3, and only the one tested in the recent RV144 vaccine trial has shown partial protection against infection4 (TABLE 1). Despite the absence of a vaccine that can clearly protect against HIV, we and numerous others have spent the past several years trying to define correlates of protection against HIV. The obvious hope was that by knowing what correlated with protection, we could predict which vaccines would and would not work in efficacy trials, even before the trials were performed. Although trying to define such a correlate of protection has been a worthwhile endeavour, achieving evidence of efficacy in the RV144 vaccine trial changes the outlook of the field and compels an appraisal of the rationale for this effort and an assessment of whether the findings proved useful in the quest for an HIV vaccine. Why do we need an immune correlate? Most vaccines for viral infections have been developed empirically by testing the efficacy of inactivated or attenuated virus preparations in protecting against infection or disease in the absence of a known mechanism of immune protection (although this is almost always an antibody response)5,6.
Once protective efficacy of the vaccine is shown, an immune correlate can be established statistically and can then be used as a surrogate for efficacy as vaccine production methods and processes are updated, thereby avoiding the need to re-test efficacy with every change or improvement in a vaccine (BOX 1). This approach is supported by the fact that for most viral illnesses there are individuals who have survived natural infection, are protected against reinfection and in whom the ongoing reliance on a given immune correlate can be validated. Unfortunately, such individuals do not exist in the case of HIV infection, rendering unrealistic the prospect of validating an immune correlate based on protection afforded by clearance of natural infection. Therefore, the precedent for defining an immune correlate (especially a T cell-based correlate) before proving vaccine efficacy is a weak one at best, and certainly does not exist for an infection in which there are no individuals who have cleared infection and are subsequently immune to reinfection. Nevertheless, this problem did not deter researchers from searching for an immune correlate of protection against HIV as no reasonable alternative strategy was readily apparent.
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Alternative definitions of protection In the absence of natural protection against infection, many investigators sought other clinical situations in which to evaluate protection against HIV. In human populations, these included studies of highly exposed but uninfected individuals7, long-term nonprogressors or elite controllers of HIV-1 infection8, subjects with HIV-2 infection who do not progress to AIDS9, and acute HIV-1 seroconverters (that is, those who convert from an HIV-specific antibody negative state to an HIV-specific antibody positive state)10,11. Unfortunately, none of these clinical situations accurately models pre-existing immune protection against HIV. Specifically, despite years of study, the mechanisms underlying lack of infection in the majority of exposed but uninfected individuals are unknown. The data are equally consistent with an innate or genetic predisposition to non-infection12 and with protection through the generation of a systemic or local immune response13, and the data do not predict the effector functions mediated by pre-existing adaptive immunity. In an effort to understand how a vaccineinduced T cell response could control viral replication in the absence of sterilizing immunity, the greatest emphasis has been on the study of long-term non-progressors, elite controllers and HIV-2-infected nonprogressors. It is important to remember that the T cells that are evaluated in these studies are derived from chronically infected individuals who have some degree of ongoing viral replication and continued mutation of the virus, allowing escape from the T cell response. The scope of this effort has been too great to be fully covered in this Opinion article, and so we provide a selective list of optimal characteristics for a T cell vaccine based on these efforts (BOX 2). A protective vaccine should stimulate CD4+ T cells14 and/or CD8+ T cells15,16 that: have a central17 or effector 18,19 memory phenotype; can proliferate20; kill HIV-infected targets21–23 or at least inhibit HIV replication in vitro24–26; can secrete several cytokines27; express a diverse T cell receptor repertoire28,29; do not express markers of exhaustion30–32; and target several epitopes in HIV group-specific antigen (Gag) but do not target the envelope protein (Env)33–35. The Gag epitopes that should be targeted are those that are restricted by certain HLA alleles36–39, are conserved across strains40,41 and in which mutation is detrimental to viral fitness42,43. Although such investigations have been an incredibly rich and valuable source of information for the study of HIV disease VOLUME 11 | jANUARy 2011 | 65
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PersPectives Table 1 | past and current efficacy trials for HiV vaccines* Vaccine trial
Schedule (months) 0
1
Vax003
Env protein
Env protein
STEP
Adenoviral Adenoviral vector vector
RV144
ALVAC vector
ALVAC vector
HVTN 505
Plasmid DNA
Plasmid DNA
Population Immunity 2
3
6
ALVAC vector and Env protein Plasmid DNA
Rate of infection
Efficacy
Vaccine
Placebo
Env protein
MSM and IVDU
Antibody and CD4+ T cells
191/3,330 (5.7%)
98/1,679 (5.8%)
0%
Adenoviral vector
MSM
CD8+ and CD4+ T cells
65/893 (7.3%)
45/894 (5.0%)
–31.5% (NS)
ALVAC vector General and Env population protein
Antibody, CD8+ 51/8,197 and CD4+ T cells (0.6%)
74/8,198 (0.9%)
+31.2% (p = 0.4)
Adenoviral vector
Antibody, CD8+ Ongoing and CD4+ T cells
Ongoing
Unknown
MSM
IVDU, intravenous drug user; MSM, men who have sex with men; NS, not significant. *Not included in the table are the Vax004 vaccine trial, which was similar to the Vax003 vaccine trial and failed to show efficacy, and the Phambili trial, which was similar to the STEP trial but was terminated before full enrolment after the STEP trial was halted.
pathogenesis, the fact that these data were drawn from the study of chronically infected individuals means it is difficult to know which attributes would be crucial for an HIV-specific T cell that was present in the individual before infection with the virus. In fact, studies have shown that many of these characteristics of vaccine-induced T cell responses rapidly convert to those seen during chronic progressive HIV infection once the subject becomes infected44, and they have not prevented secondary infection or the generation of viral variants through recombination. In the absence of a T cell vaccine with proven efficacy against HIV, these characteristics need to be considered solely as correlates of lower viral loads in chronic HIV infection. How any of these characteristics could or should be effectively applied to the development of a vaccine against HIV is unclear. Another clinical situation that is being applied to the search for a T cell correlate is the study of acute HIV infection11,45. Based on elegant studies of the viruses and immune responses that are generated during acute HIV infection, we now know that: the viral epitopes targeted by the early T cell response often differ from those that are targeted later in infection46; the early response helps to control virus replication47, but the virus rapidly escapes from this control48; and reversion of mutated ‘escaped’ epitopes to their original sequence may or may not occur when viruses are transmitted to individuals whose T cell response does not target the escaped epitopes49–51. However, it remains unclear whether a vaccine should stimulate responses against epitopes that are targeted early in the infection or those that are targeted late. The answer to that question has to await the testing of an efficacious T cell vaccine, in which targeting of early or late epitopes can be evaluated as a potential correlate.
nonhuman primate studies An obvious setting to evaluate immune correlates is in animal models of human infections in which vaccines can be shown to be protective and immune analyses can be performed. Unfortunately, HIV does not adequately infect and cause disease in any readily available small animal model, so researchers have had to resort to the use of a similar virus (simian immunodeficiency virus (SIV) or simian–HIV (SHIV)) in nonhuman primates. Although disease pathogenesis in SIV-infected nonhuman primates is remarkably similar to HIV disease in humans, and there are only subtle differences in the specific immune responses generated in both infections, the main source of difficulty in using this model to evaluate immune correlates is in defining how well the model recapitulates human sexual transmission of HIV. we know that mucosal transmission of HIV in humans is inefficient 52,53 and usually leads to the establishment of a single clone of replicating virus from the numerous viruses present in the inoculum54. Recent studies have shown that models involving the use of repeated low-dose mucosal virus challenge show transmission of single SIV variants across a mucosal surface55. However, appropriate
application of this model has greatly increased the number (and cost) of nonhuman primates needed in each study to show protection by a given vaccine56 and still does not equate to the human setting in which dozens of encounters with virus are typically required for mucosal transmission to occur even during the time of peak viraemia in the infected partner 52,53. In addition, there are limited numbers of SIV isolates that can be used to test protection across genetically diverse virus strains, a major obstacle for any field test of an HIV vaccine. Finally, because antibodies may be an important component of the protective response, and SIV Env differs substantially from HIV Env, SHIV recombinant viruses, which have HIV Env proteins and an SIV backbone have been derived; however, SHIVs are an imperfect solution. Differences in how they are transmitted, which CD4+ T cells they infect and how they induce disease in nonhuman primates make many investigators wary of relying on them as a predictor of vaccine efficacy in humans57–59. Because of such limitations, some have argued that showing protection in nonhuman primates should not be a gatekeeper for advancement of a particular vaccine product or approach into human efficacy trials.
Box 1 | Definition and use of immune correlates in vaccine development An immune correlate of protection is an immune response that is statistically correlated with protection against infection or disease. Ideally, an immune correlate of protection can be quantified and associated with a threshold value that can be measured in the blood or other easily accessible samples. An immune correlate is strongest when it is also an immunological determinant of protection, which means that the assay measures a biological function that is necessary and sufficient for achieving protection against the pathogen. If a determinant or correlate of protection can be defined, that measurement can potentially become a surrogate endpoint for future clinical efficacy trials. In other words, defining immune responses associated with protection from infection or clinical disease allows subsequent studies to substitute the immune response measurement for the clinical endpoint, which would substantially reduce the study sizes, cost and time that are required for completing vaccine development.
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PersPectives Another concern is that most T cell vaccines that are tested in nonhuman primate models have shown effects not on viral transmission but on viral load, but they did not predict the lack of impact on viral load that was seen in the STEP vaccine trial (Merck & Co.)1,60,61 (TABLE 1). The type of unique protection against acquisition of infection afforded by vaccines using a rhesus macaque cytomegalovirus vector has yet to be evaluated in human clinical trials, and is probably years from such efficacy testing 62. However, the successful efficacy testing of a vaccine in humans may help to direct future studies in nonhuman primates. Specifically, vaccines based on approaches that have been shown to protect humans from HIV can now be used to evaluate, improve, select and validate existing nonhuman primate models so that they more accurately reflect the protective outcomes observed in humans. At that point, they may become useful as gatekeepers of future vaccine concepts. Determining immune correlates From failed trials? Among the handful of HIV vaccines that have been tested for efficacy, one was based on a hypothesis that T cells provide protection. The vaccine tested by Merck & Co. in the STEP and Phambili trials contained genes encoding HIV Gag, Pol and Nef, but not Env, and therefore stimulated neither virion-binding antibodies nor neutralizing antibodies1,60. Protection was intended to be produced by stimulation of CD8+ T cell responses that would control viral replication following infection, and preclinical testing of the vaccine in nonhuman primates supported this assertion61. Although the vaccine was shown to stimulate T cells with several of the characteristics associated with long-term non-progression (each of which was touted as a mechanism of immune protection), the vaccine failed to protect volunteers from acquisition of infection and to reduce viral loads after infection1,60. The main measure of T cell immunogenicity that led to the clinical testing of this vaccine was the enumeration of interferon-γ (IFNγ)-producing T cells using enzyme-linked immunosorbent spot (ELISPOT) assays. The lack of vaccine efficacy in the trial called into question the use of this assay as a correlate of protection, and indicated that newer and better measures of T cell function were needed63,64. Although such questioning of the importance of IFNγ as an antiviral effector is justifiable, its measurement nevertheless reveals the ability of T cells
to recognize and respond to HIV-derived peptides65. More importantly, this raises the question of whether it is valid to reject a specific T cell function as an immune correlate based on a vaccine trial that did not show protection. Indeed, a correlate is a statistical term, and a potential correlate can only be eliminated from consideration when it is shown to be unable to discriminate protected from unprotected recipients of a partially protective vaccine (BOX 1). Thus, the vaccine that was tested in the STEP and Phambili trials is an example of a failed vaccine, and although these studies suggest that something quantitatively or qualitatively different is needed, they do not provide the basis for defining or eliminating a particular immune measurement as a potential correlate of protection. Rather than advocating for more T cell-based vaccines or the use of ELISPOT assays as a sole measurement of vaccine immunogenicity, this specific example illustrates the general principle that the analyses of correlates should be evaluated in the context of an at least partially effective vaccine. In the absence of protection, any measure of an immune response will fail to be a correlate, irrespective of its potential role in protection. From current and future trials? For pathogens such as HIV, which are likely to require an iterative approach to vaccine design with many generations of product modifications and improvements, focusing on the identification of immune correlates of protection deserves substantial investment. Current HIV vaccine efficacy trials should be designed to identify a correlate of protection and should not focus on direct and immediate development of a product. Performing a test-of-concept efficacy trial to define a correlate of protection requires three major factors. The first is the clinical trial infrastructure and use of well-characterized risk cohorts with a high enough incidence of HIV infection to make accumulation of >100 infection endpoints feasible. Second, the candidate vaccine needs to induce the immune response of interest at a sufficient frequency to support a correlates analysis (30–70%). Third, there has to be clinical efficacy. Identifying and maintaining highrisk cohorts and the clinical infrastructure to conduct HIV vaccine efficacy trials is expensive and dynamic. Many factors other than the vaccine intervention tend to reduce HIV incidence in relevant study populations66–68. Education, counselling, self-esteem and access to medical care for trial participants all contribute to reduce
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Box 2 | T cell immune correlates Several characteristics of T cells have been investigated as potential correlates of immune protection in HIV.
T cell phenotype • CD4+ or CD8+ T cells • Central memory, effector memory or effector T cells • Expression of homing markers • Expression of exhaustion markers T cell function • Expression of individual cytokines and chemokines • Production of single versus several cytokines and chemokines • Killing capacity or perforin expression • Inhibition of virus in vitro • Proliferation T cell antigen specificity • Responses to Gag, Env, Pol, Nef and accessory proteins • Number of epitopes targeted • Sequence conservation of epitopes • Ease of sequence escape within epitopes • Effect of sequence escape on viral fitness HlA restriction • Frequency in human population • Association with lack of disease progression T cell receptor • Diverse or restricted • Ability to cover several clades • Ability to cover potential escape variants • Public T cell receptors (dominant in multiple individuals) or private T cell receptors (rarely present in multiple individuals)
incidence of infection, and over time new options for prevention, such as circumcision, pre-exposure prophylaxis or microbicides, will change the constituency of study populations that are appropriate for HIV vaccine clinical trials. This will add to the expense and complexity of performing the trials that are needed to establish a correlate of protection. There are several candidate vaccine regimens in development, but few immunological hypotheses for how vaccine-induced immunity might protect. Candidate vaccine regimens with immunological endpoints that have distinct specificity or functional properties should be considered for analysis in test-of-concept efficacy trials to define a correlate of protection. Currently, it is typical in Phase I and Phase II clinical trials of candidate HIV vaccines to exclude individuals who are at high risk of HIV infection, VOLUME 11 | jANUARy 2011 | 67
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Figure 1 | Conventional and adaptive trial design. Conventional clinical trials explicitly follow a protocol that is designed to provide an unbiased answer to a discrete question stated as the primary 0CVWTG4GXKGYU^+OOWPQNQI[ objective. Achieving the predetermined number of study endpoints should then provide a statistically robust conclusion. Adaptive trial designs may be useful when there are multiple objectives or multiple treatment arms to test, or both. Adaptive designs provide an unbiased approach to shift from one study objective to another or shift the emphasis from many treatment groups to a few. For example, if a vaccine study using a 1/1 allocation of vaccine to placebo was discovered to have efficacy during a proscribed interim analysis, the allocation could be changed to a 2/1 ratio to shift the primary focus towards defining an immune correlate. Alternatively, if an immune correlate was known, it could be used as a surrogate endpoint in a study that tests multiple vaccine concepts. When a particular vaccine achieved the predetermined immunological endpoint, it would trigger an altered randomization scheme to assure more subjects would be enrolled in study arms that achieve the immunogenicity objective. This would allow the emphasis to shift from immunogenicity to efficacy evaluation.
so there are relatively few exposures and breakthrough infection cases to evaluate. The inclusion of subjects who are at risk of HIV infection in early Phase clinical trials would be one way of improving our knowledge of vaccine-induced immunity and would provide another parameter of safety to assess before commencing larger test-ofconcept efficacy trials. Importantly, robust and frequent sample collection is crucial. Extensive sample collection may not be necessary for a candidate vaccine being developed for licensure, but is essential for defining a correlate of protection. Frequent sampling allows the assessment of immunity closer to the time of infection and helps to define the timing of infection more precisely. The measurement of peak immunogenicity time points is useful for product validation but is much less likely to provide a correlate with efficacy than estimates of immunity near the time of HIV exposure that may be distant from the time of immunization. The use of similar collection time points and uniform assays across a series of clinical efficacy trials will improve the likelihood of identifying a correlate of
protection and would ultimately help to generalize findings by providing data for subsequent meta-analysis69. From trials that show partial protection? It is crucial for funding bodies and decisionmakers to appreciate that an immune correlate of protection can be defined from trials of vaccines that show partial efficacy. If properly designed with enough clinical endpoints and sufficient sample collection, efficacy as low as 10–15% may allow identification of an immune correlate of protection. This would then allow the subsequent evaluation of several vaccine delivery platforms and antigen concepts, and product development can proceed in a more logical and systematic way. The concept of using ‘adaptive’ trial designs for HIV vaccine evaluation has recently been a topic of considerable discussion. Adaptive trial design implies that flexibility to accommodate changes in study design in response to accumulating data is incorporated into the protocol (FIG. 1). Adaptive trial designs have gained some momentum in treatment-intervention
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studies in which a clinical endpoint can be detected soon after treatment initiation. The theoretical advantage of an adaptive approach is that it provides a mechanism to evaluate many approaches in a shorter amount of time. However, the practical advantage is lost if events that trigger adaptation are infrequent and distant from the time of subject randomization. There may be ways in which adaptive trial designs facilitate the identification of correlates of vaccine-induced immunity. Although vaccine efficacy is determined by comparing the frequency of study endpoints in recipients of the vaccine and the placebo, to detect immune correlates a case-controlled comparison is performed between vaccine recipients who become infected and those who do not. Therefore, enrolling additional vaccine recipients in trials that show early evidence of efficacy would improve the chances of defining immune correlates. However, this would not provide a notable time advantage. To attain the time efficiency promised by adaptive trial designs for defining efficacy, adjustments to group allocation would need to be done in real-time based on an immunological ‘surrogate’ endpoint (BOX 1). For example, if an antibody response with a particular specificity and function or a T cell response with certain phenotypic characteristics was found to be a correlate of protection, then parallel trials with several product concepts could be initiated, and every time an immunized subject achieved the ‘surrogate’ endpoint or the immune correlate of protection, that group would gain an advantage in future subject allocations. In that way, enrolment could proceed for many concepts, but only the ones achieving the correlate at a high frequency would accrue enough subjects to determine clinical efficacy. Defining a correlate of protection to use as a surrogate endpoint is the crucial step that would allow the best use of adaptive trial designs and improve the likelihood of eventually achieving a significant level of clinical efficacy. Adaptive vaccine clinical trials that use a clinical endpoint of infection or disease progression require too much time and clinical trial capacity to remain relevant. Performing efficacy trials that are designed to detect high levels of clinical efficacy (>50%) but are of insufficient size or intensity to define a correlate of protection may result in a fortuitous breakthrough that could support the further development of a selected product. However, they are much less likely to support incremental scientific advances that would lead to a highly effective HIV vaccine. As we have witnessed in the two www.nature.com/reviews/immunol
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PersPectives Box 3 | Antibody immune correlates Characteristics of antibodies that will be investigated as potential correlates of immune protection in the RV144 vaccine trial.
Antibody titre • Binding by enzyme-linked immunosorbent assay • Duration Antibody function • Neutralization (compared with several panels of isolates) • Antibody-dependent cell-mediated cytotoxicity • Antibody-dependent cell-mediated virus inhibition • Fc binding • Effect on viral mobility in mucous • Affinity and avidity Antibody specificity • Clade specificity of antibody functions • Cross-competition with known neutralizing antibodies • Linear epitope mapping Antibody phenotype • Immunoglobulin class and subclass • Fc modifications (sialylation and glycosylation) Antibody location • Serum • Mucosal samples
most recent efficacy trials, it is hard to guess based on established scientific paradigms what the outcome of a vaccine trial will be. The STEP trial focused on inducing Gagspecific CD8+ T cell responses and was considered promising by the scientific community but resulted in vaccine-enhanced infection rates, whereas the vaccine tested in the RV144 trial, which induced relatively weak CD8+ T cell responses and nonneutralizing antibodies and was highly criticized by the scientific community, showed partial efficacy. Unfortunately, neither trial was specifically designed to define an immune correlate of protection, and the retrospective analysis of available samples is not likely to reach a definitive answer. The current HVTN 505 efficacy trial has relatively extensive sample collection, but is not large enough to accumulate a sufficient number of subjects in the vaccine group to be sure of defining a correlate of protection if partial efficacy is achieved. It should also be noted that in the absence of a strong T cell response in the RV144 trial, an antibody correlate is most likely to derive from the correlates
analysis. This does not, however, diminish the complexity of the investigation. Similarly to the T cell response, there are many aspects of the antibody response that can and will be evaluated in the search for an antibody correlate of protection in the RV144 vaccine trial (BOX 3). Until there is sufficient investment in the process to define a correlate of protection to allow the establishment of surrogate immunological endpoints for efficacy trials, development of a vaccine for HIV will remain a distant hope, a point made recently by the Global HIV Vaccine Enterprise70. Conclusion The challenge presented in developing an HIV vaccine is both new and unique. Infected individuals do not clear the virus, are not immune to subsequent reinfection and do not typically survive in the absence of antiretroviral therapy. This separates the quest for an HIV vaccine from other vaccine efforts in which correlates of protection may arise from an empirical approach, instead of being prerequisites for the rational design of the vaccine. The search for correlates of protection in cohorts such as long-term non-progressors seemed to be a reasonable approach but may ultimately have led us astray. Although polyfunctional Gagspecific cytotoxic T cells were heralded as the goal to be achieved in a successful vaccine, in fact they may be only a correlate of lower viral load in chronically infected people. Observations in highly exposed uninfected people are equally consistent with innate rather than adaptive host immune factors as underlying mechanisms for protection, and it is unclear how these mechanisms may be relevant to a vaccine. Furthermore, although there has been much progress in the elicitation of Env-specific antibodies by vaccines, studies in infected individuals certainly did not reveal them as correlates of protection and, in fact, suggested that stimulating T cell responses to Env would be harmful. Thus the focus of our studies should shift to the establishment of correlates of protection in uninfected people in large vaccine trials, rather than protection from virus replication or disease progression in chronically infected people. when we embark on such trials we must bear in mind that should a trial fail, certain response thresholds may be found to be inadequate, but assays themselves cannot be formally negated. Only in a trial that has partial efficacy can a correlate be disregarded if it fails to distinguish protected from unprotected individuals. As transmission incidence is generally low, defining
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correlates is inherently difficult, and therefore we should be guided in this endeavour by the necessity for the recruitment of large numbers of volunteers who should be sampled frequently. The path to a successful vaccine for HIV is likely to be an iterative one, driven forward by a process of successive approximation or, as it is more colloquially termed, trial and error. Richard A. Koup, Barney S. Graham and Daniel C. Douek are at the Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland 20892‑3017, USA. Correspondence to D.C.D. e‑mail:
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PersPectives 18. Addo, M. M. et al. Fully differentiated HIV-1 specific CD8+ T effector cells are more frequently detectable in controlled than in progressive HIV-1 infection. PLoS ONE 2, e321 (2007). 19. Hess, C. et al. HIV-1 specific CD8+ T cells with an effector phenotype and control of viral replication. Lancet 363, 863–866 (2004). 20. Day, C. L. et al. Proliferative capacity of epitopespecific CD8 T-cell responses is inversely related to viral load in chronic human immunodeficiency virus type 1 infection. J. Virol. 81, 434–438 (2007). 21. Hersperger, A. R. et al. Perforin expression directly ex vivo by HIV-specific CD8 T-cells is a correlate of HIV elite control. PLoS Pathog. 6, e1000917 (2010). 22. Migueles, S. A. et al. Lytic granule loading of CD8+ T cells is required for HIV-infected cell elimination associated with immune control. Immunity 29, 1009–1021 (2008). 23. Yang, O. O. et al. Efficient lysis of human immunodeficiency virus type 1-infected cells by cytotoxic T lymphocytes. J. Virol. 70, 5799–5806 (1996). 24. Blackbourn, D. J. et al. Suppression of HIV replication by lymphoid tissue CD8+ cells correlates with the clinical state of HIV-infected individuals. Proc. Natl Acad. Sci. USA 93, 13125–13130 (1996). 25. Spentzou, A. et al. Viral inhibition assay: a CD8 T cell neutralization assay for use in clinical trials of HIV-1 vaccine candidates. J. Infect. Dis. 201, 720–729 (2010). 26. Yang, O. O. et al. Suppression of human immunodeficiency virus type 1 replication by CD8+ cells: evidence for HLA class I-restricted triggering of cytolytic and noncytolytic mechanisms. J. Virol. 71, 3120–3128 (1997). 27. Betts, M. R. et al. HIV nonprogressors preferentially maintain highly functional HIV-specific CD8+ T cells. Blood 107, 4781–4789 (2006). 28. Geldmacher, C. et al. Minor viral and host genetic polymorphisms can dramatically impact the biologic outcome of an epitope-specific CD8 T-cell response. Blood 114, 1553–1562 (2009). 29. Simons, B. C. et al. Despite biased TRBV gene usage against a dominant HLA B57-restricted epitope, TCR diversity can provide recognition of circulating epitope variants. J. Immunol. 181, 5137–5146 (2008). 30. Day, C. L. et al. PD-1 expression on HIV-specific T cells is associated with T-cell exhaustion and disease progression. Nature 443, 350–354 (2006). 31. Petrovas, C. et al. PD-1 is a regulator of virus-specific CD8+ T cell survival in HIV infection. J. Exp. Med. 203, 2281–2292 (2006). 32. Trautmann, L. et al. Upregulation of PD-1 expression on HIV-specific CD8+ T cells leads to reversible immune dysfunction. Nature Med. 12, 1198–1202 (2006). 33. Kiepiela, P. et al. CD8+ T-cell responses to different HIV proteins have discordant associations with viral load. Nature Med. 13, 46–53 (2007). 34. Rolland, M. et al. Broad and Gag-biased HIV-1 epitope repertoires are associated with lower viral loads. PLoS ONE 3, e1424 (2008). 35. Zuniga, R. et al. Relative dominance of Gag p24-specific cytotoxic T lymphocytes is associated with human immunodeficiency virus control. J. Virol. 80, 3122–3125 (2006). 36. Gao, X. et al. Effect of a single amino acid change in MHC class I molecules on the rate of progression to AIDS. N. Engl. J. Med. 344, 1668–1675 (2001). 37. Hendel, H. et al. New class I and II HLA alleles strongly associated with opposite patterns of progression to AIDS. J. Immunol. 162, 6942–6946 (1999).
38. Kaslow, R. A. et al. Influence of combinations of human major histocompatibility complex genes on the course of HIV-1 infection. Nature Med. 2, 405–411 (1996). 39. Migueles, S. A. et al. HLA B*5701 is highly associated with restriction of virus replication in a subgroup of HIV-infected long term nonprogressors. Proc. Natl Acad. Sci. USA 97, 2709–2714 (2000). 40. Goulder, P. J. et al. Novel, cross-restricted, conserved, and immunodominant cytotoxic T lymphocyte epitopes in slow progressors in HIV type 1 infection. AIDS Res. Hum. Retroviruses 12, 1691–1698 (1996). 41. Turnbull, E. L. et al. HIV-1 epitope-specific CD8+ T cell responses strongly associated with delayed disease progression cross-recognize epitope variants efficiently. J. Immunol. 176, 6130–6146 (2006). 42. Martinez-Picado, J. et al. Fitness cost of escape mutations in p24 Gag in association with control of human immunodeficiency virus type 1. J. Virol. 80, 3617–3623 (2006). 43. Schneidewind, A. et al. Escape from the dominant HLA-B27-restricted cytotoxic T-lymphocyte response in Gag is associated with a dramatic reduction in human immunodeficiency virus type 1 replication. J. Virol. 81, 12382–12393 (2007). 44. Betts, M. R. et al. Characterization of functional and phenotypic changes in anti-Gag vaccine-induced T cell responses and their role in protection after HIV-1 infection. Proc. Natl Acad. Sci. USA 102, 4512–4517 (2005). 45. Streeck, H. et al. Human immunodeficiency virus type 1-specific CD8+ T-cell responses during primary infection are major determinants of the viral set point and loss of CD4+ T cells. J. Virol. 83, 7641–7648 (2009). 46. Goulder, P. J. et al. Substantial differences in specificity of HIV-specific cytotoxic T cells in acute and chronic HIV infection. J. Exp. Med. 193, 181–194 (2001). 47. Goonetilleke, N. et al. The first T cell response to transmitted/founder virus contributes to the control of acute viremia in HIV-1 infection. J. Exp. Med. 206, 1253–1272 (2009). 48. Leslie, A. J. et al. HIV evolution: CTL escape mutation and reversion after transmission. Nature Med. 10, 282–289 (2004). 49. Feeney, M. E. et al. HIV-1 viral escape in infancy followed by emergence of a variant-specific CTL response. J. Immunol. 174, 7524–7530 (2005). 50. Goepfert, P. A. et al. Transmission of HIV-1 Gag immune escape mutations is associated with reduced viral load in linked recipients. J. Exp. Med. 205, 1009–1017 (2008). 51. Goulder, P. J. et al. Evolution and transmission of stable CTL escape mutations in HIV infection. Nature 412, 334–338 (2001). 52. Gray, R. H. et al. Probability of HIV-1 transmission per coital act in monogamous, heterosexual, HIV-1-discordant couples in Rakai, Uganda. Lancet 357, 1149–1153 (2001). 53. Wawer, M. J. et al. Rates of HIV-1 transmission per coital act, by stage of HIV-1 infection, in Rakai, Uganda. J. Infect. Dis. 191, 1403–1409 (2005). 54. Salazar-Gonzalez, J. F. et al. Genetic identity, biological phenotype, and evolutionary pathways of transmitted/ founder viruses in acute and early HIV-1 infection. J. Exp. Med. 206, 1273–1289 (2009). 55. Keele, B. F. et al. Low-dose rectal inoculation of rhesus macaques by SIVsmE660 or SIVmac251 recapitulates human mucosal infection by HIV-1. J. Exp. Med. 206, 1117–1134 (2009).
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56. Hudgens, M. G. et al. Power to detect the effects of HIV vaccination in repeated low-dose challenge experiments. J. Infect. Dis. 200, 609–613 (2009). 57. Morgan, C. et al. The use of nonhuman primate models in HIV vaccine development. PLoS Med. 5, e173 (2008). 58. Nishimura, Y. et al. Highly pathogenic SHIVs and SIVs target different CD4+ T cell subsets in rhesus monkeys, explaining their divergent clinical courses. Proc. Natl Acad. Sci. USA 101, 12324–12329 (2004). 59. Shedlock, D. J., Silvestri, G. & Weiner, D. B. Monkeying around with HIV vaccines: using rhesus macaques to define ‘gatekeepers’ for clinical trials. Nature Rev. Immunol. 9, 717–728 (2009). 60. McElrath, M. J. et al. HIV-1 vaccine-induced immunity in the test-of-concept Step Study: a case-cohort analysis. Lancet 372, 1894–1905 (2008). 61. Shiver, J. W. et al. Replication-incompetent adenoviral vaccine vector elicits effective anti-immunodeficiency-virus immunity. Nature 415, 331–335 (2002). 62. Hansen, S. G. et al. Effector memory T cell responses are associated with protection of rhesus monkeys from mucosal simian immunodeficiency virus challenge. Nature Med. 15, 293–299 (2009). 63. D’Souza, M. P. & Altfeld, M. Measuring HIV-1-specific T cell immunity: how valid are current assays? J. Infect. Dis. 197, 337–339 (2008). 64. Streeck, H., Frahm, N. & Walker, B. D. The role of IFN-γ Elispot assay in HIV vaccine research. Nature Protoc. 4, 461–469 (2009). 65. Janetzki, S., Cox, J. H., Oden, N. & Ferrari, G. Standardization and validation issues of the ELISPOT assay. Methods Mol. Biol. 302, 51–86 (2005). 66. Baeten, J. M. et al. Trends in HIV-1 incidence in a cohort of prostitutes in Kenya: implications for HIV-1 vaccine efficacy trials. J. Acquir. Immune Defic. Syndr. 24, 458–464 (2000). 67. Kaul, R. et al. Reduced HIV risk-taking and low HIV incidence after enrollment and risk-reduction counseling in a sexually transmitted disease prevention trial in Nairobi, Kenya. J. Acquir. Immune Defic. Syndr. 30, 69–72 (2002). 68. van Loggerenberg, F. et al. Establishing a cohort at high risk of HIV infection in South Africa: challenges and experiences of the CAPRISA 002 acute infection study. PLoS ONE 3, e1954 (2008). 69. Qin, L., Gilbert, P. B., Corey, L., McElrath, M. J. & Self, S. G. A framework for assessing immunological correlates of protection in vaccine trials. J. Infect. Dis. 196, 1304–1312 (2007). 70. The Council of the Global HIV Vaccine Enterprise et al. The 2010 scientific strategic plan of the Global HIV Vaccine Enterprise. Nature Med. 16, 981–989 (2010).
Acknowledgements
We thank the many members of the Vaccine Research Center whose helpful discussions over the years have helped to frame the opinions expressed here.
Competing interests statement
The authors declare no competing financial interests.
FURTHER inFORMATiOn Authors’ homepage: http://www.niaid.nih.gov/about/organization/vrc All lInkS ARE ACTIVE In THE onlInE Pdf
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ReseaRch highlights Nature Reviews Immunology | AOP, published online 3 December 2010; doi:10.1038/nri2905
R E G u L At O Ry t C E L L S
Kings of the delta blues Regulatory T (TReg) cells prevent excessive inflammatory responses and are crucial for maintaining intestinal homeostasis. Several distinct leukocyte populations are known to be targets of TReg cell-mediated suppression; Sankar Ghosh and colleagues now report that TReg cells can also prevent uncontrolled γδ T cell-mediated attacks against the intestinal microbiota. Previous work described an essential role for 3-phosphoinositidedependent protein kinase 1 (PDK1) in transducing activatory signals from the co-receptor CD28 during CD4+ T cell activation. Surprisingly, the authors found that transgenic mice with a CD4+ T cell-specific deletion of PDK1 developed spontaneous colitis, despite showing defective CD4+ T cell activation. By characterizing colonic leukocyte populations, they found that γδ T cells (but not αβ T cell or B cell populations) were markedly increased in the colonic epithelium of mice with PDK1-deficient CD4+ T cells. In particular, an increased proportion of interleukin-17 (IL-17)producing γδ T cells was found in the colons of the transgenic mice compared with wild-type mice, suggesting
that these γδ T cells contributed to disease development. To explore this further, the authors crossed mice with PDK1-deficient CD4+ T cells with animals lacking γδ T cells and found that these double-deficient mice no longer developed colitis. Treatment with antibiotics also prevented disease in mice with PDK1-deficient CD4+ T cells. These findings confirmed that γδ T cells are required for colitis development in this model and suggested that γδ T cells are activated in response to the commensal microbiota. As the transgenic mice also lacked PDK1 expression in CD4+ TReg cells, the authors next explored whether colitis in these animals resulted from a TReg cell defect. In mice with PDK1-deficient CD4+ T cells, forkhead box P3 (FOXP3)+ TReg cells developed normally and were only slightly reduced in number in the periphery. However, in contrast to wild-type TReg cells, PDK1-deficient TReg cells failed to upregulate various antiinflammatory cytokines, including IL-10, following activation with CD3- and CD28-specific antibodies, and were only weakly suppressive
nATuRe RevIewS | Immunology
in vitro. Furthermore, in the classic T cell transfer model of colitis, PDK1-deficient TReg cells could not prevent disease development. In a series of transfer experiments, the authors showed that wild-type, but not PDK1-deficient, TReg cells can inhibit proliferation and IL-17 production by γδ T cells in vivo. TReg cell-mediated suppression of γδ T cells was not contactdependent but instead depended on TReg cell production of IL-10; this was an interesting finding, as the ability of TReg cells to inhibit CD4+ αβ T cell responses is independent of TReg cell-derived IL-10. Finally, the authors found that colitis did not develop in transgenic mice with PDK1-deficient CD4+ T cells following the transfer of wild-type TReg cells, indicating that disease in these mice is caused by defective TReg cellmediated suppression of γδ T cells, rather than due to an intrinsic defect in γδ T cell populations.
Yvonne Bordon
ORIGINAL RESEARCH PAPER Park, S. et al. T regulatory cells maintain intestinal homeostasis by suppressing γδ T cells. Immunity 33, 791–803 (2010)
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ReseaRch highlights Nature Reviews Immunology | AoP, published online 3 December 2010; doi:10.1038/nri2906
B CELLS
Illuminating the dark zone In a recent paper published in Cell, Dustin, Nussenzweig and colleagues illuminate the dynamics of germinal centre B cell migration and show that T cell help is the limiting factor for the selection of high-affinity B cells. Although much research has focused on defining the mechanisms of B cell selection in germinal centres and the importance of migration between germinal centre dark and light zones, a clear picture of the dynamics of B cell selection in these structures is lacking. To address this issue, the authors generated transgenic mice that expressed photoactivatable green fluorescent protein (PA-GFP) in their haematopoietic cells. These cells can be photoactivated with great precision
B cells expressing photoactivatable green fluorescent protein can be photoactivated with high spatial precision in germinal centres. Follicular dendritic cells in the germinal centre light zone are labelled with an antigen-conjugated red fluorescent protein and collagen is in blue. Image courtesy of G. D. Victora and M. Nussenzweig, The Rockefeller University, New York, USA.
(close to one cell diameter) in these mice and can be analysed by multiphoton laser scanning microscopy and flow cytometry. This method allows for the precise labelling, tracking and molecular analysis of cells within living tissues. The authors then generated antigen-specific germinal centres in which transferred antigenspecific PA-GFP-expressing B cells could be specifically photoactivated in either the dark zone or the light zone. The light zone was identified by injecting an antigen-conjugated red fluorescent protein. In antigenimmunized mice this forms immune complexes that bind follicular dendritic cells (FDCs), which are confined to the light zone. The authors found that dark zone B cells were CXCR4hiCD83lowCD86low and expressed genes associated with cell division and somatic hypermutation at high levels, whereas light zone B cells were CXCR4lowCD83hiCD86hi and expressed activation markers (associated with antigen encounter and T cell help) and apoptosis regulators. Analysis of B cell migration in germinal centres in the popliteal lymph nodes of living mice showed that photoactivated dark zone B cells migrated rapidly to the light zone, with up to 50% of cells migrating to the light zone in 4 hours. By contrast, migration from the light zone to the dark zone was slow, with only 15% of cells making the transition in 6 hours. These observations are consistent with the model in which the dark zone acts as a source of proliferating B cells with mutated B cell receptors (BCRs) that migrate to and undergo
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selection in the light zone. B cells in the light zone must compete for a limiting factor that promotes their return to the dark zone for further rounds of proliferation. But what is the limiting factor? It has been proposed that affinity-based selection of B cells may be driven by BCR cross-linking by antigen that is deposited in immune complexes on FDCs and/or by help from follicular helper T (TFH) cells following antigen uptake and presentation by high-affinity B cells. The authors devised a model to address the exact mechanism of B cell selection, and found that targeting TFH cell help to a subpopulation of B cells resulted in migration of these B cells from the light zone to the dark zone. They also showed that TFH cell help was required for clonal expansion and affinity maturation of these B cells. BCR cross-linking was necessary but not sufficient for affinity maturation, indicating that TFH cell help is the limiting factor for B cell selection in germinal centres. So, using a unique method that combines PA-GFP expression in B cells with multiphoton microscopy and flow cytometry, this study defines specific mechanisms that govern B cell selection in germinal centres.
Olive Leavy
ORIGINAL RESEARCH PAPER Victora, G. D. et al. Germinal center dynamics revealed by multiphoton microscopy with a photoactivatable fluorescent reporter. Cell 143, 592–605 (2010) fuRtHER REAdING Cyster, J. G. Shining a light on germinal center B cells. Cell 143, 503–505 (2010)
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ReseaRch highlights Nature Reviews Immunology | AOP, published online 17 December 2010; doi:10.1038/nri2907
I N N At E I m m u N I t y
Calling on the neighbours The enteric bacterium Shigella flexneri is known to produce multiple effector proteins that interfere with host cell inflammatory responses. But despite this, infection with this bacterium induces a dramatic inflammatory response, including the secretion of large amounts of CXC-chemokine ligand 8 (CXCL8; also known as IL-8). A recent study published in Immunity provides an explanation for this, by showing that infected intestinal epithelial cells communicate with uninfected neighbouring epithelial cells to promote inflammatory chemokine secretion that is unrestrained by bacterial effector proteins. A related, independent study in PLoS Pathogens describes another mechanism of intercellular communication that allows amplification of innate immune responses to Listeria monocytogenes. In the first study, Kasper et al. noted, to their surprise, that when epithelial cells were exposed to low doses of S. flexneri, not only infected cells but also uninfected cells showed activation of the pro-inflammatory transcription factor nuclear factor-κB (NF-κB). The uninfected cells with active NF-κB seemed to neighbour infected cells, suggesting the occurrence of bystander activation. Such activation was not a result of bacterial spread to neighbouring cells, as it was not reduced following infection with a non-motile mutant of S. flexneri.
Further analysis revealed that the uninfected bystander cells also showed activation of JUN N-terminal kinase (JNK), extracellular signalregulated kinase (ERK) and the mitogen-activated protein kinase p38, all of which are involved in inflammatory responses to S. flexneri. In particular, p38 activation was much higher in these uninfected cells than in the infected cells, and this was shown to be a result of dephosphorylation of p38 in the infected cells by the bacterial effector protein OspF; accordingly, p38 activation was increased in cells that were infected with an OspF-deficient S. flexneri mutant. In keeping with the observed activation of pro-inflammatory signalling, uninfected epithelial cells produced much more CXCL8 than infected cells, as assessed on a singlecell level using immunofluorescence microscopy or mRNA hybridization. So, how is the infection communicated to bystander cells? Treatment of the epithelial cells with brefeldin A, which blocks protein secretion, had no effect on bystander activation during S. flexneri infection, indicating that activation was not mediated by paracrine signalling involving secreted proteins. By contrast, pharmacological blockade of gap junctions, which allow the passage of small molecules between adjacent epithelial cells, did reduce CXCL8 secretion by bystander cells. Moreover, S. flexneri infection
NATURE REvIEwS | Immunology
of an epithelial cell line that lacks expression of the gap junction protein connexin 43 (also known as GJA1) failed to induce activation of NF-κB, JNK, ERK and p38 in bystander cells. Finally, the finding that connexin 43 had to be expressed by both the infected and the uninfected bystander cells confirmed that epithelial cell inflammatory responses are propagated during bacterial infection through gap junction communication. In the study by Dolowschiak et al., communication between intestinal epithelial cells did not seem to depend on gap junctions but instead was shown to be mediated by reactive oxygen intermediates that were produced by NADPH oxidase in cells that were infected with the cytosolic bacterium L. monocytogenes. However, despite the differing mechanisms of intercellular communication that are described, these papers identify an important new way in which innate immune responses can be amplified at the early stages of bacterial infection.
Lucy Bird
ORIGINAL RESEARCH PAPERS Kasper, C. A. et al. Cell-cell propagation of NF-κB transcription factor and MAP kinase activation amplifies innate immunity against bacterial infection. Immunity 33, 804–816 (2010) | Dolowschiak, T. et al. Potentiation of epithelial innate host responses by intercellular communication. PLoS Pathog. 6, e1001194 (2010)
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ReseaRch highlights Nature Reviews Immunology | AoP, published online 17 December 2010; doi:10.1038/nri2908
T cells
Shaping Il4 gene expression Transcription of the T helper 2 (TH2)-associated cytokine genes — interleukin-4 (IL4), IL5 and IL13 — is controlled by the TH2 cell master regulator GATA-binding protein 3 (GATA3). However, the molecular basis of GATA3-mediated gene regulation during TH2 cell development is unclear and controversial. Tanaka et al. now show that binding of GATA3 to DNase I hypersensitive site 2 (HS2) in the second intron of the Il4 locus is specifically required for chromosomal modifications at this locus that allow transcription of Il4. Numerous regulatory elements in the TH2 cytokine locus have been identified, but whether TH2-associated cytokine expression is controlled by a single element or by the coordinated activity of multiple elements is not known. To address this issue, the authors generated a series of mutant mice that lack each hypersensitive element in the Il4–Il13 locus and assessed the effect of each deletion on cytokine production. TH2 cells from mice that lack HS2 produced the lowest levels of IL-4 following activation, whereas the expression of other TH2-type cytokines by these cells was similar to wild-type TH2 cells. These data suggest a specific role for HS2 in IL-4 expression. Deletion of other regulatory elements also impaired IL-4 expression, but to a lesser extent, suggesting that multiple elements are required for complete lineage-specific expression of IL-4. By contrast, naive T cells that lack the conserved GATA3-response element (GCRE) in the Il13 locus gave rise to wild-type
numbers of IL-4-producing T cells but few IL-13-producing T cells in TH2 cell-inducing conditions, indicating that this element regulates Il13 transcription. Next, the authors assessed whether GATA3 is linked to the function of the HS2 enhancer. Unlike in wild-type TH1 cells, overexpression of GATA3 in HS2-deficient TH1 cells
NATURE REvIEwS | Immunology
did not result in IL-4 expression. Furthermore, GATA3 directly binds to HS2 during TH2 cell differentiation, as determined by chromatin immunoprecipitation analysis. GATA3 functions mainly as an epigenetic modifier, so it is possible that binding of GATA3 to HS2 is required for transcription-permissive epigenetic changes at the Il4 locus. Indeed, acetylation of histone H3 at Lys9 and Lys14, and trimethylation of histone H3 at Lys4 (all of which are permissive modifications) were impaired in HS2-deficient TH2 cells, but only at the Il4 locus. By contrast, deletion of GCRE resulted in impaired methylation of histone H3 at Lys4 at the Il13 locus but not the Il4 locus. Finally, antigen-specific IgG1 and IgE levels, eosinophilia and airway hyperresponsiveness to acetylcholine were reduced in HS2-deficient mice compared with wild-type mice in models of allergic lung inflammation, confirming that the TH2 cell response was impaired in HS2-deficient mice. So, HS2 is a crucial GATA3binding site in the Il4 locus and is required for the GATA3-mediated epigenetic modifications that are necessary for lineage-specific IL-4 expression.
Olive Leavy
ORIGINAl ReseARcH PAPeR Tanaka, S. et al. The enhancer HS2 critically regulates GATA‑3‑mediated Il4 transcription in TH2 cells. Nature Immunol. 5 Dec 2010 (doi:10.1038/ni.1966) FURTHeR ReADING Wilson, C. B., Rowell, E. & Sekimata, M. Epigenetic control of T‑helper‑cell differentiation. Nature Rev. Immunol. 9, 91–105 (2009)
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ReseaRCh highlights Nature Reviews Immunology | AoP, published online 17 December 2010; doi:10.1038/nri2909
dENdRItIC CELLS
pDCs play off scratch Plasmacytoid dendritic cells (pDCs) express Toll-like receptor 7 (TLR7) and TLR9 and produce large amounts of type I interferons (IFNs) in response to viral nucleic acids. However, the contribution of this rare circulating cell population to host immunity remains unclear. Two recent studies in the Journal of Experimental Medicine now show that, although they are absent from normal skin, pDCs are rapidly recruited to sites of cutaneous inflammation. Here, they serve as an early source of type I IFNs and contribute to wound healing in normal mice, but can promote an autoimmune skin reaction in lupus-prone animals. Using a mechanical tape-stripping model to induce acute skin inflammation in mice, Gregorio et al. found that pDCs infiltrated and transiently accumulated in the injured skin around 24 hours after injury. Infiltration of pDCs to injured skin was associated with the production of type I IFNs, and antibody-mediated depletion of pDCs abrogated the IFN response, suggesting that pDCs were the chief source of the IFNs. Mice that were treated with IRS954 (a selective inhibitor of TLR7 and TLR9) prior to tape stripping failed to upregulate type I IFNs, indicating that activation of pDCs through these TLRs is necessary for IFN production. The sterile nature of the model suggested that pDCs were activated by host-derived nucleic acids, possibly those released by damaged keratinocytes. Depletion of pDCs or blockade of IFN-mediated signalling prior to tape stripping decreased the production of cytokines that are involved in wound
repair, such as interleukin-6 (IL-6), IL-17 and IL-22, and led to delayed regrowth of the epidermis. In healthy human volunteers, mechanical or chemical-induced skin injury also led to pDC recruitment and upregulation of type I IFNs early in the immune response, suggesting that the transient recruitment of IFN-producing pDCs may contribute to wound healing in humans as well as in mice. Similarly, Guiducci et al. found that tape stripping led to early recruitment of IFNα-producing pDCs to the skin, and that treating mice with IRS954 reduced the expression of IFNs and other inflammatory cytokines in injured skin. In addition, these authors found that in a lupus-prone mouse strain, tape stripping led to the development of chronic skin lesions resembling those seen in patients with cutaneous lupus. Treating lupus-prone mice with IRS954 or depleting pDCs before tape stripping prevented the development of these skin lesions, suggesting that pDCs and signalling through TLR7 and TLR9 are necessary for this pathological response. Furthermore, IRS954 promoted healing in lupus-prone mice with already established skin lesions, indicating that continued signalling through TLR7 and TLR9 was necessary for the chronic inflammatory response; however, the exact role of pDCs was not identified. The ability to explore the functions of pDCs in chronic skin lesions may have been hampered by a lack of suitable reagents to deplete pDCs. Antibodies against bone marrow stromal antigen 2 (BST2) are commonly used to deplete
NATURe RevIewS | Immunology
pDCs in mice, but BST2 is upregulated by other cell types during inflammation. A new transgenic mouse, in which pDCs can be conditionally depleted, has been described in a recent Immunity article and could clarify this matter. Using this mouse to explore pDC functions during viral infection, Swiecki et al. found that pDCs are only essential for type I IFN production during the early stages of infection with murine cytomegalovirus or vesicular stomatitis virus; however, this early pDC response can, depending on the viral load, be crucial for containing these viruses. Together, these studies suggest that the physiological role of pDCs is to serve as an early, transient source of type I IFNs following activation by foreign or endogenous damage-associated nucleic acids. As such, pDCs seem to be important for containing early viral infections and promoting tissue repair following acute injury. However, in genetically susceptible individuals, pDCs may become chronically activated and contribute to the breakdown of tolerance and the development of autoimmunity in the skin.
Yvonne Bordon
ORIGINAL RESEARCH PAPERS Gregorio, J. et al. Plasmacytoid dendritic cells sense skin injury and promote wound healing through type I interferons. J. Exp. Med. 29 Nov 2010 (doi:10.1084/jem.20101102) | Guiducci, C. et al. Autoimmune skin inflammation is dependent on plasmacytoid dendritic cell activation by nucleic acids via TLR7 and TLR9. J. Exp. Med. 29 Nov 2010 (doi:10.1084/jem.20101048) | Swiecki, M. et al. Plasmacytoid dendritic cell ablation impacts early interferon responses and antiviral NK and CD8+ T cell accrual. Immunity. 2 Dec 2010 (doi:10.1016/j.immuni.2010.11.020)
voLUMe 11 | jANUARy 2011 © 2010 Macmillan Publishers Limited. All rights reserved
ReseaRch highlights Nature Reviews Immunology | AOP, published online 17 December 2010; doi:10.1038/nri2910
tumOuR ImmuNOLOGy
CD4+ T cells sponsor oncogene addicts Naturally occurring tumours have multiple and complex genetic abnormalities, but their growth and survival can often be inhibited by the inactivation of a single oncogene. This phenomenon — known as ‘oncogene addiction’ — can explain the effects of some of our most successful cancer therapeutics, such as the tyrosine kinase inhibitor imatinib mesylate (Gleevec; Novartis). Oncogene inactivation was thought to have cell-autonomous effects on tumour cell apoptosis, proliferation, differentiation and senescence, but new research published in Cancer Cell shows that an intact immune system is necessary for ‘addicted’ tumour cells to respond to oncogene withdrawal. The authors used a transgenic mouse model of Myc-induced haematopoietic tumorigenesis, in which Myc can be inactivated by administering doxycycline,
to investigate the role of the immune system in oncogene addiction. Following transplantation of tumour cells from these mice into various immunocompromised mouse strains and subsequent inactivation of Myc, the kinetics of tumour regression were found to be significantly delayed compared with wild-type hosts. The immunodeficient hosts also showed a significant increase in minimal residual disease and in tumour recurrence. Deficiency of CD4+ T cells, but not CD8+ T cells, in the transplantation hosts was sufficient to impede tumour regression after Myc inactivation. There were no differences between wild-type and immunodeficient hosts in terms of the increased tumour cell apoptosis or decreased proliferation that occur after Myc inactivation, showing that these effects do not depend on the immune system. However, whereas tumour cells that were transplanted into wild-type hosts had increased expression of senescence-associated markers after Myc inactivation, this did not occur in immunodeficient Cd4–/– mice. Similarly, in Cd4–/– mice, Myc inactivation failed to inhibit angiogenesis, and the higher mean vascular density in Cd4–/– mice compared with wild-type mice after Myc inactivation was associated with decreased production of the antiangiogenic protein thrombospondin 1 (TSP1; encoded by Thbs1). So, the absence of CD4+ T cells impairs the induction of cellular senescence and the inhibition of angiogenesis following oncogene inactivation.
NATuRe ReviewS | Immunology
The role of CD4+ T cells in the effects of oncogene inactivation was confirmed by showing that the reconstitution of immunodeficient hosts with CD4+ T cells, but not CD8+ T cells, completely eliminated minimal residual disease and prolonged tumour-free survival after Myc inactivation. Also, CD4+ T cells rapidly localized to the tumour site after Myc inactivation and were associated with the increased production of ‘antitumour’ cytokines such as TSP1 and the decreased production of ‘pro-tumour’ cytokines such as vascular endothelial growth factor. Reconstitution of immunodeficient mice with Thbs1–/–Thbs2–/– splenocytes failed to prevent tumour relapse after Myc inactivation, showing the importance of thrombospondins for tumour regression. These data indicate that oncogene addiction is not entirely cell autonomous and that changes in the cytokine milieu elicited by CD4+ T cells are required for cellular senescence and the shutdown of angiogenesis, which might be involved in constraining minimal residual disease. This highlights the importance of testing targeted oncogene therapies in immunocompetent models and the potential for combining such therapies with immunotherapeutic agents that boost the CD4+ T cell response. Kirsty Minton
ORIGINAL RESEARCH PAPER Rakhra, K. et al. CD4+ T cells contribute to the remodeling of the microenvironment required for sustained tumor regression upon oncogene inactivation. Cancer Cell 18, 485–498 (2010)
vOlume 11 | jANuARy 2011 © 2010 Macmillan Publishers Limited. All rights reserved
