Nature Reviews Immunology 11, 71 (February 2011)

ReseaRch highlights Nature Reviews Immunology | AOP, published online 14 January 2011; doi:10.1038/nri2920

R E G U L AT O RY T C E L L S

Weight watchers There is a growing understanding of how host metabolism can affect the immune system. Now, a study by Procaccini et al. has described another important link between host energy status and immune function by showing that leptin, a hormone that is mainly produced by adipocytes and that controls food intake and energy expenditure, can activate mammalian target of rapamycin (mTOR) and regulate the proliferative capacity of regulatory T (TReg) cells. mTOR is a serine/threonine kinase that integrates signals from environmental nutrients and growth factors to control cell proliferation and differentiation. In initial experiments conducted in vitro, freshly isolated human TReg cells showed higher mTOR activity and an increased metabolic rate compared with purified effector T cells. Although TReg cells do not normally proliferate in response to in vitro T cell receptor (TCR) stimulation, transient inhibition of mTOR, through pretreatment with rapamycin, led to robust proliferation of TReg cells following culture with CD3- and CD28-specific antibodies. Extending these findings in vivo, the authors found that a single injection of rapamycin promoted TReg cell proliferation in mice, both in the steady state and after immunization with antigen. Additionally, in a model of experimental autoimmune encephalomyelitis (EAE), mice treated with rapamycin before EAE induction showed increased frequencies of TReg cells and decreased disease severity. Interestingly, although decreased mTOR activity seemed to be necessary for the initial phases of TReg cell proliferation, TReg cells that were actively proliferating in vivo

expressed high levels of phosphorylated mTOR. Furthermore, continuous treatment with rapamycin or silencing of mTOR expression with short hairpin RNA failed to reverse TReg cell anergy in vitro. Thus, although early, transient inhibition of mTOR activity could overcome TReg cell anergy, subsequent upregulation of mTOR activity seemed to be required to sustain TReg cell proliferation, indicating that the mTOR pathway has a dynamic role in TReg cell responsiveness. As previous work showed that leptin can be produced by, and inhibits the proliferation of, TReg cells, the authors predicted that this molecule might interact with the mTOR pathway. In support of this, addition of leptin to cultures of TCR-activated, rapamycintreated TReg cells led to increased activation of the mTOR pathway and prevented TReg cell proliferation. In addition, neutralization of leptin markedly reduced mTOR activity in cultured TReg cells, suggesting that autocrine production of leptin by TReg cells may promote their high mTOR activity in vitro. Finally, the authors examined the effects of acute starvation (which markedly reduces circulating levels of leptin and immune function) on the mTOR pathway and TReg cell function. Strikingly, starvation led to increased proportions of TReg cells in peripheral lymph nodes. Furthermore, TReg cells from starved mice showed markedly reduced mTOR activity and increased rates of proliferation in vitro compared with TReg cells from control animals. Taken together, this study describes the leptin–mTOR signalling pathway as an important link

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CORBIS

between host energy status and TReg cell activity. The authors conclude that oscillating mTOR activity is necessary for TReg cell activation and suggest that this may explain why TReg cells are unresponsive to TCR stimulation in vitro, where high levels of leptin and nutrients may sustain mTOR activation.

Yvonne Bordon

ORIGINAL RESEARCH PAPER Procaccini, C. et al. An oscillatory switch in mTOR kinase activity sets regulatory T cell responsiveness. Immunity 33, 929–941 (2010) FURTHER READING Finlay, D. & Cantrell, D. A. Metabolism, migration and memory in cytotoxic T cells. Nature Rev. Immunol. 14 Jan 2011 (doi:10.1038/nri2888)

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ReseaRch highlights Nature Reviews Immunology | AoP, published online 14 January 2011; doi:10.1038/nri2919

m AC R O P H AG E S

Preventing lipid overload Eaten too much over the holiday season? New research shows that macrophages in the mesenteric lymph nodes (MLNs) can offset the proinflammatory effects of overeating saturated fats by expressing angiopoietin-like protein 4 (ANGPTL4), which inhibits the generation of free fatty acids and subsequent lipid uptake by macrophages. After eating saturated fats, longchain fatty acids are incorporated as triglycerides into lipoprotein particles known as chylomicrons, which travel through the lymphatics before entering the blood. The triglycerides in chylomicrons are then hydrolysed by the enzyme lipoprotein lipase (LPL), which is highly expressed by endothelial cells and macrophages, to generate free fatty acids that fuel tissues such

as the heart and muscles. Based on the knowledge that saturated fatty acids have potent pro-inflammatory effects and that ANGPTL4 is an inhibitor of LPL activity, the authors examined the effects of ANGPTL4 on diet-induced obesity and its metabolic consequences. They observed that feeding mice that are deficient for ANGPTL4 (Angptl4–/– mice) a diet rich in saturated fats had lethal consequences, associated with fibrinopurulent peritonitis, intestinal inflammation, a wasting disease and fat-laden ascites fluid. Further analysis showed that these mice had an abundance of chylomicrons in ascites fluid and a marked leukocyte infiltration of the intestine and mesenteric adipose tissues. These abnormalities were preceded by a massive acutephase response, suggesting that fat-induced systemic inflammation was the cause. The authors also noted that the MLNs of Angptl4–/– mice on a highfat diet were dramatically enlarged compared with Angptl4–/– mice on a diet of medium-chain fatty acids, which are not incorporated into chylomicrons and do not flow through the lymphatics. Consistent with chylomicrons having a direct pro-inflammatory effect, the

MLNs of Angptl4–/– mice fed a high-fat diet contained a large number of lipidladen macrophages, known as foam cells, and incubation of peritoneal macrophages from Angptl4–/– mice with an emulsion of chylomicrons led to foam cell formation and the induction of inflammatory gene expression. These effects were shown to be the result of loss of ANGPTL4-mediated inhibition of LPL, as they could be reproduced by incubation with a synthetic inhibitor of LPL and prevented by treatment with recombinant ANGPTL4. Finally, the mechanism of inflammation induced by excess chylomicrons was found to involve activation of endoplasmic reticulum stress pathways, which have previously been linked to inflammation. Together, the findings suggest that ANGPTL4, the expression of which is upregulated in macrophages by chylomicron-derived fatty acids, is part of a feedback mechanism that protects MLN-resident macrophages from lipid overload and associated inflammation.

Lucy Bird

ORIGINAL RESEARCH PAPER Lichtenstein, L. et al. Angptl4 protects against severe proinflammatory effects of saturated fat by inhibiting fatty acid uptake into mesenteric lymph node macrophages. Cell Metab. 12, 580–592 (2010) fuRtHER REAdING Osborn, O., Sears, D. D. & Olefsky, J. M. Fat-induced inflammation unchecked. Cell Metab. 12, 553–554 (2010)

BRAND X

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in brief I M M U N O M E TA B O L I S M

The inflammasome-mediated caspase-1 activation controls adipocyte differentiation and insulin sensitivity Stienstra, R. et al. Cell Metab. 12, 593–605 (2010)

The NLRP3 inflammasome instigates obesity-induced inflammation and insulin resistance Vandanmagsar, B. et al. Nature Med. 9 Jan 2011 (doi:10.1038/nm.2279)

Obesity is associated with chronic low-grade inflammation and is a known risk factor for a number of metabolic diseases, including type 2 diabetes. The link between obesity and inflammation has been unclear, but these studies show that obesity-induced activation of the NOD-, LRR- and pyrin domain-containing 3 (NLRP3) inflammasome is crucial for caspase 1-mediated activation of inflammatory cytokines, such as interleukin-1β (IL-1β) and IL-18, which promote insulin resistance. Stienstra et al. found that caspase 1 expression was upregulated during differentiation of adipocytes, and mice fed a high-fat diet showed markedly increased levels of caspase 1, IL-1β and IL-18 expression in adipose tissue. Elevated IL-1β production was shown to contribute to insulin resistance in adipose tissue, and adipocytes from NLRP3-deficient or caspase 1-deficient mice showed increased insulin sensitivity and were more metabolically active. Furthermore, treatment of obese mice with a caspase 1 inhibitor improved insulin sensitivity in these animals. In the second study, Vandanmagsar et al. showed a direct correlation between adiposity and the expression of NLRP3 and IL-1β in both humans and mice. Weight loss, resulting from calorie restriction or exercise, led to decreased NLRP3 expression and improved insulin sensitivity in adipose tissue. The authors found that ceramides (lipid molecules that are released into the circulation by adipocytes during progressive obesity) directly activate the NLRP3 inflammasome and induce caspase 1 activation in adipocytes and macrophages. NLRP3-deficient mice fed a high-fat diet showed increased insulin sensitivity and, interestingly, showed decreased expression of interferon-γ and reduced effector T cell numbers in adipose tissue. These results suggest that the NLRP3 inflammasome is also important for regulating adipose tissue T cell responses during obesity. I M M U N O M E TA B O L I S M

IL-17 regulates adipogenesis, glucose homeostasis, and obesity Zúñiga, L. A. et al. J. Immunol. 185, 6947–6959 (2010)

The pro-inflammatory cytokine interleukin-17 (IL-17) is upregulated in the blood of obese humans, but its role in metabolic disease remains unclear. This study shows that IL-17 is produced by γδ T cells in adipose tissue and acts as a negative regulator of adipogenesis and glucose metabolism. Comparison of mice fed a normal, low-fat or high-fat diet showed that increasing obesity promoted the accumulation of IL-17-producing γδ T cells in inguinal adipose tissue. Whereas most αβ T cells in adipose tissue produced interferon-γ (IFNγ) but little IL-17, adipose tissue γδ T cells produced high levels of IL-17 but low levels of IFNγ. Interestingly, IL-17 was shown to inhibit lipid uptake and insulin-induced glucose uptake by adipocytes, and to suppress adipogenesis. Young IL-17-deficient mice were more susceptible to diet-induced obesity than wild-type controls, but older IL-17-deficient mice were no longer protected from diet-induced obesity. The authors suggest that the positive metabolic effects of IL-17 may be overwhelmed by other mechanisms once obesity is established.

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vA C C I N E S

Foes of fungi are just 17 The incidence of systemic fungal infections has increased throughout the world, and this has prompted much interest in developing effective vaccines against these pathogens. T helper 1 (TH1) cells are believed to be crucial for protection from pathogenic fungi, but the exact role of TH17 cells has remained unclear and both protective and pathological functions for these cells have been reported. Now, a recent study suggests that TH17 cells, but not TH1 cells, are necessary for vaccine-induced protection of mice against Coccidioides posadasii, Histoplasma capsulatum and Blastomyces dermatitidis, which are the main causes of systemic mycoses in humans in North America. In initial experiments, the authors showed that a protective vaccine against B. dermatitidis induced both antigen-specific interferon-γ (IFNγ)-producing TH1 cells and interleukin-17 (IL-17)producing TH17 cells in mice. Following pulmonary infection with B. dermatitidis, TH1 and TH17 cells were rapidly recruited to the lungs of vaccinated, but not unvaccinated, mice. Most of the vaccinated animals cleared the infection within 6 days; however, unvaccinated mice could not clear B. dermatitidis and were moribund by day 15.

Interestingly, antibody-mediated blockade of IL-17 inhibited the ability of vaccinated mice to clear B. dermatitidis more profoundly than blockade of IFNγ. Furthermore, despite developing normal TH1-type immune responses, vaccinated mice that were deficient in IL-17 or the IL-17 receptor (IL-17R) were not protected from pulmonary B. dermatitidis infection. By contrast, mice that were deficient in molecules necessary for TH1-type immunity, including T-bet and IL-12R, were protected from subsequent B. dermatitidis infection following vaccination. Importantly, in each of the experiments, vaccine-induced TH17 cells promoted protective antifungal immunity without inducing immunopathology in the lungs. The authors extended these findings using T cell receptor-transgenic OT-I mice (which have few endogenous T cells and do not develop protective immunity following vaccination against B. dermatitidis). They showed that adoptive transfer of B. dermatitidis-specific transgenic T cells to OT-I mice prior to vaccination led to the development of IL-17-producing T cells, which protected against subsequent infection with B. dermatitidis. Transfer of B. dermatitidis-specific T cells that were deficient in T-bet or IL-12R also

NATuRE REVIEws | Immunology

promoted successful vaccination in OT-I mice, indicating that antigenspecific TH17 cells are necessary and sufficient for protective vaccination. Vaccine-induced TH17 cells were shown to protect mice from subsequent B. dermatitidis infection by recruiting and activating granulocytes and macrophages. Interestingly, although the pattern recognition receptor dectin 1 (also known as CLEC7A) was previously suggested to be necessary for TH17 cell responses to fungi, the authors found that vaccination-induced differentiation of TH17 cells did not require dectin 1, but instead depended on expression of the Toll-like receptor adaptor molecule myeloid differentiation primary response protein 88 (MYD88). Finally, they showed that TH17 cells are also required for vaccine-induced protection of mice from C. posadasii and H. capsulatum. Together, these results suggest that future vaccination strategies for human fungal infections should concentrate on priming effective TH17 rather than TH1 cell responses.

Yvonne Bordon

ORIGINAL RESEARCH PAPER Wüthrich, M. et al. Vaccine-induced protection against 3 systemic mycoses endemic to North America requires Th17 cells in mice. J. Clin. Invest. 4 Jan 2011 (doi:10.1172/JCI43984)

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In the news One FLu Over? eschew the rest! Last year we had a vaccine surplus (Nature Rev. Immunol., Feb 2010), this year there isn’t enough (The Telegraph, 13 Jan 2011): is there ever any good news when it comes to our struggle with influenza virus? Amid all the media reports of death and despair, a group of scientists provided a glimmer of hope by showing that humans who recover from infection with swine flu (the 2009 H1N1 pandemic strain of influenza virus) may have increased resistance to all other strains of influenza virus (J. Exp. Med., 10 Jan 2010). The researchers, led by Patrick Wilson (University of Chicago) and Rafi Ahmed (Emory University, Atlanta), identified five antibodies from patients infected with swine flu in 2009 that could recognize all H1N1 strains from the last decade, as well as the 1918 ‘Spanish flu’ and deadly H5N1 ‘bird flu’ strains (BBC News, 11 Jan 2011). Strikingly, these antibodies protected mice from otherwise lethal doses of influenza virus. The study has important implications for vaccine development. “It says a universal influenza vaccine is really possible,” said Wilson (Reuters, 10 Jan 2011). The antibodies seem to protect against multiple strains of influenza virus because of their unusual tendency to bind the stalk region of viral haemagglutinin. Unlike other regions of haemagglutinin, the stalk region shows little variation between different influenza virus strains and is, according to Ahmed, “the Achilles’ heel” of the virus (Fox News, 10 Jan 2011). One word of warning: being overweight may reduce your chances of developing these ‘super’ antibodies. Researchers from the California Department of Public Health found that obese individuals have an up to 300% increased risk of death following infection with swine flu (Tehran Times, 13 Jan 2010). The mechanisms may be unclear, but these findings offer yet another fascinating link between host metabolism and immunity. Yvonne Bordon

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m AC R O P H AG E S

A transcription factor to call their own Not to be outdone by the everexpanding list of T cell subsets and their defining transcription factors, macrophages are let in on the act by new research showing that interferon regulatory factor 5 (IRF5) is a subsetdefining factor for M1 macrophages with both activating and repressive transcriptional functions. Monocyte-derived macrophages that are differentiated with granulocyte–macrophage colony stimulating factor (GM-CSF) adopt an M1 (classical) phenotype, which is associated with the production of pro-inflammatory cytokines such as interleukin-12 (IL-12). Conversely, differentiation with M-CSF leads to the polarization of M2 (alternative) macrophages that produce antiinflammatory cytokines such as IL-10. This study showed that treatment of human monocytes with GM-CSF but not M-CSF resulted in increased expression of IRF5.

In line with a role for IRF5 in macrophage plasticity, as well as in initial polarization, the conversion of M2 macrophages to M1 macrophages by culture with GM-CSF also resulted in increased IRF5 expression. Human M2 macrophages that were forced to express IRF5 had increased expression of IL-12p70 and IL-23 and decreased expression of IL-10, whereas inhibition of IRF5 expression in M1 macrophages resulted in the converse levels of cytokine production. These data show that IRF5 promotes the IL-12hiIL-23hiIL-10low cytokine profile that is associated with M1 macrophages, and further studies showed that this is the result of direct effects on transcriptional activity. The mRNA levels for these cytokines were modulated by IRF5 in a manner consistent with the protein data, and genome-wide expression analysis showed that IRF5 induces

the expression of M1-specific genes and represses the expression of M2-specific genes. Furthermore, IRF5 was shown to bind to the promoter regions of the genes encoding IL-12p40, IL-12p35, IL-23p19 and IL-10. Recruitment of RNA polymerase II to the IL10 promoter only occurred after the dissociation of IRF5 from this region. This is in keeping with a role for IRF5 in transcriptional inhibition of the IL10 gene, and is supported by the demonstration that IRF5 inhibits the expression of a reporter construct containing the IL10 promoter sequence. Mutations in IRF5 or the IL10 promoter region that disrupted IRF5–DNA binding prevented this inhibitory effect on reporter expression. These data indicate that the expression of GM-CSF at sites of inflammation can drive M1 macrophage polarization through increased IRF5 expression, which has both positive and negative effects on the transcription of macrophage subset-specific genes. In turn, M1 macrophages are known to drive pro-inflammatory T helper 1 (TH1) cell responses. Indeed, the forced expression of IRF5 by human M2 macrophages resulted in increased proliferation of MHC-mismatched T cells and the differentiation of both TH1 and TH17 cell populations.

Kirsty Minton

ORIGINAL RESEARCH PAPER Krausgruber, T. et al. IRF5 promotes inflammatory macrophage polarization and TH1–TH17 responses. Nature Immunol. 16 Jan 2011 (doi:10.1038/ni.1990)

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A u tO I m m u N I t y

Joint damage without antigen The development of various auto­ immune diseases, including rheuma­ toid arthritis, is thought to be due to a breakdown in CD4+ T cell tolerance for a tissue­specific antigen. However, several lines of evidence have suggested that cognate antigen recognition by CD4+ T cells may not always be necessary. Murakami et al. now show that initiation of CD4+ T cell­dependent arthritis in gp130F759/F759 mice involves the local accumulation of activated T helper 17 (TH17) cells in the absence of cognate antigen recognition. This triggers an interleukin­17A (IL­17A)­dependent IL­6 amplification loop, which the authors termed the ‘IL­6 amplifier’. gp130F759/F759 mice have enhanced IL­6 receptor­mediated signal­ ling and spontaneously develop a

rheumatoid arthritis­like disease as they age. In this study, the authors found that gp130F759/F759 mice engineered to express a single T cell receptor that recognizes a non­joint antigen also develop arthritis, indi­ cating that cognate antigen recogni­ tion was not involved. These mice had a higher number of TH17 cells in lymphoid tissues, and the concentra­ tions of IL­6 and IL­17A in the blood were increased. The authors hypothesized that local events in the joint (such as microbleeding) may contribute to joint inflammation by triggering the accu­ mulation of activated TH17 cells, so they transferred in vitro differentiated TH17 cells to gp130F759/F759 or control C57BL/6 mice that had undergone experimental microbleeding in one

nATuRe RevIewS | Immunology

leg. Arthritis developed in the leg in which microbleeding was induced (but not the other leg) in gp130F759/F759 mice following TH17 cell transfer, but did not occur in control mice, suggesting that the enhanced sensi­ tivity to IL­6 in gp130F759/F759 mice is required for disease. Microbleeding in the joint induced the localized expres­ sion of CC­chemokine ligand 20 (CCL20), which is a chemoattractant for CC­chemokine receptor 6 (CCR6)+ TH17 cells. In addition, IL­6­mediated signalling in type I collagen­expressing cells and local IL­17A production by TH17 cells were shown to be important for disease pathogenesis in this mouse model. So, putting these observations together, the following model emerges. A local event in the joint, such as microbleeding, induces the accumulation of TH17 cells through increased CCL20 expression, resulting in the activation of the IL­6 amplifier and disease develop­ ment. The authors propose that in humans, the availability of TH17 cells for such a model could be due to the known age­dependent increase in memory or activated phenotype T cells. Also, several factors, such as infection, may increase sensitivity to IL­6 in the tissue. Olive Leavy

ORIGINAL RESEARCH PAPER Murakami, M. et al. Local microbleeding facilitates IL‑6‑ and IL‑17‑dependent arthritis in the absence of tissue antigen recognition by activated T cells. J. Exp. Med. 10 Jan 2011 (doi:10.1084/jem.20100900)

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ReseaRch highlights Nature Reviews Immunology | AoP, published online 21 January 2011; doi:10.1038/nri2924

I m m u N E R E G u L At I O N

MicroRNAs keep microglia quiet MicroRNAs regulate gene expression in many biological processes, and now a new study shows that a brainspecific microRNA is a key regulator of microglial cell quiescence in the central nervous system (CNS), thereby helping to prevent CNS inflammation. Microglial cells are CNS-resident macrophages that, under normal conditions, have a resting phenotype that is characterized by low-level expression of CD45 and MHC class II molecules. During CNS inflammation (such as that which occurs in experimental autoimmune encephalomyelitis (EAE)), microglial cells become activated and are thought to contribute, together with peripheral macrophages that infiltrate the inflamed CNS, to the pathological processes. The mechanisms that maintain the unique resting phenotype of microglial cells are unknown, so Weiner and colleagues set out to investigate whether microRNAs might be involved. A comparison of the expression of 31 known microRNAs in macrophages isolated from different organs of healthy adult mice revealed that only CNS-resident microglial cells expressed the microRNA miR-124. During EAE,

however, miR-124 expression by microglial cells decreased, and CNS-infiltrating peripheral macrophages started to express low levels of miR-124 during the onset and recovery phases of the disease. This suggested that miR-124 expression correlates inversely with the activation state of microglial cells and macrophages in the CNS. Consistent with the idea that miR-124 regulates the activation state of macrophages, the authors showed that transfection of bone marrow-derived macrophages with miR-124 results in downregulation of activation markers, including CD45, MHC class II and CD86. miR-124 transfection also inhibited macrophage proliferation, promoted macrophage polarization to an M2 phenotype and altered cell morphology. Investigation of the mechanisms underlying these effects showed that miR-124 directly binds to the mRNA encoding the myeloid cell master transcription factor CCAAT/enhancer-binding protein-α (C/EBPα), causing downregulation of C/EBPα protein expression. Accordingly, mutation of the three predicted miR-124 binding sites in C/EBPα mRNA abolished the inhibitory effect. In turn, the reduced levels

NATURE REvIEWS | Immunology

of C/EBPα in miR-124-transfected cells caused decreased expression of the downstream transcription factor PU.1 and its target genes encoding CD45 and MHC class II. Returning to the in vivo setting, the authors showed that administration of miR-124 shortly after induction of EAE substantially ameliorated or prevented disease symptoms. Mice treated with miR-124 had less microglial cell activation and leukocyte infiltration in the CNS than control mice. These effects on disease were dependent on miR-124-mediated downregulation of C/EBPα, as they could be replicated by a small interfering RNA specific for C/EBPα but not by miR-124 lacking the C/EBPα binding sequence. Finally, evidence from co-culture experiments supports the hypothesis that signals from CNS stromal cells, such as astrocytes, and neurons cause macrophages to adopt a resting microglial cell phenotype through upregulation of miR-124. Lucy Bird ORIGINAL RESEARCH PAPER Ponomarev, E. D. et al. MicroRNA‑124 promotes microglia quiescence and suppresses EAE by deactivating macrophages via the C/EBP‑α‑PU.1 pathway. Nature Med. 17, 64–70 (2011)

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Cy tO k I N E S

Regulating energy stores Stimulation of hepatocytes with IL‑4 shifted the metabolic reliance of these cells from fatty acid to glucose oxida‑ tion. STAT6, downstream of IL‑4, was shown to directly interact with peroxisome proliferator‑activated receptor‑α (PPARα) — an important regulator of the breakdown and oxidation of fatty acids — thereby inhibiting its transcriptional activity. This suggests that IL‑4–STAT6 signal‑ ling inhibits fatty acid breakdown in hepatocytes by inhibiting PPARα. The authors next determined whether IL‑4–STAT6 signalling affected metabolism during obesity. Although Stat6–/– mice were resistant to high‑fat diet‑induced obesity owing to increased energy

MACMILLAN NEW ZEALAND

Whether interleukin‑4 (IL‑4)‑ driven T helper 2 (TH2)‑type immune responses regulate nutrient metabolism and insulin sensitivity is unclear. In this study, Chawla and colleagues show that IL‑4, through activation of signal transducer and activator of transcription 6 (STAT6), enhances the anabolic actions of insulin to promote storage of glucose. This is mediated by inhibition of catabolic metabolism in the liver and attenuation of inflammation in white adipose tissue. IL‑4 was shown to induce STAT6 activation in the liver, but not in skeletal muscle or white adipose tissue, suggesting that this pathway might regulate hepatic metabolism.

expenditure, they exhibited decreased insulin sensitivity. This decrease in insulin action, which was primarily observed in the liver, resulted from a loss of STAT6‑mediated inhibition of PPARα, a transcription factor that has previously been shown to antagonize the anabolic actions of insulin and decrease glucose disposal. Conversely, administration of IL‑4 to wild‑type mice on a high‑fat diet improved glucose tolerance and insulin sensitivity. In this case, IL‑4 treatment inhibited PPARα trans‑ criptional activity in the liver, and attenuated the expression of nuclear factor‑κB (NF‑κB)‑regulated inflam‑ matory genes in white adipose tissue. Finally, using a model of allergic inflammation, the authors showed that polarization towards a TH2‑type immune response in high‑fat diet‑fed mice improves glucose tolerance and insulin sensitivity. Thus, this report highlights that IL‑4–STAT6 signalling, which is associated with TH2‑type immune responses, improves insulin sensi‑ tivity and may protect against the disease‑promoting effects of high‑fat feeding.

Olive Leavy

ORIGINAL RESEARCH PAPER Ricardo-Gonzalez, R. R. et al. IL-4/STAT6 immune axis regulates peripheral nutrient metabolism and insulin sensitivity. Proc. Natl Acad. Sci. USA 107, 22617–22622 (2010)

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Ly m P H O C y t E m I G R At I O N

Travel agents for two T helper 2 (TH2) cells are associated with protection from parasites but also drive immunopathological allergic responses. Dissecting the mechanisms that are involved in the migration of TH2 cells from lymph nodes to peripheral tissues has attracted much interest, as selectively inhibiting these pathways could be an effective new therapy for patients with allergies. Two recent papers in Nature Immunology further our understanding of TH2 cell trafficking, by showing that extracellular matrix protein 1 (ECM1) is necessary for TH2 cell egress from lymphoid tissues and CC-chemokine receptor 8 (CCR8) is needed for TH2 cell migration to allergic skin. Using microarrays, Li et al. had previously shown that ECM1, a glycoprotein with no known immune function, is highly expressed by TH2 but not TH1 cells. Confirming these findings, their new study demonstrated that cultured TH2 cells secrete higher

levels of ECM1 than other T cell subsets. Furthermore, the expression of ECM1 was found to be controlled by the TH2 cell-associated transcription factors signal transducer and activator of transcription 6 (STAT6) and GATA-binding protein 3 (GATA3). Exploring the significance of ECM1 expression, they found that TH2 cell differentiation was normal in ECM1-deficient mice; however, ECM1-deficient TH2 cells were unable to traffic to the lungs and could not promote disease in a mouse model of allergic airway inflammation. The inability of ECM1-deficient TH2 cells to promote allergic inflammation seemed to be due to the failure of these cells to exit lymphoid tissues. In keeping with this, the expression of sphingosine-1-phosphate receptor 1 (S1P1; also known as S1PR1), which has important roles in promoting lymphocyte egress, was decreased in ECM1-deficient TH2 cells. Retroviral transfection of ECM1-deficient TH2 cells with Ecm1 restored both the expression of S1P1 and S1P1dependent chemotaxis in these cells. Interestingly, ECM1-deficient TH2 cells also showed defective expression of CCR4, which has previously been linked to TH2 cell trafficking, but the authors did not further explore this finding. In the second study, Islam et al. found that mouse CC-chemokine ligand 8 (CCL8) is the only member of the monocyte chemoattractant protein (MCP) family to be constitutively expressed at high levels in the skin. Although other MCP family members promote chemotaxis through CCR2, mouse CCL8 was found to induce cell migration solely through CCR8 (which is also

nATURE REvIEwS | Immunology

a functional receptor for CCL1). Using a model of atopic dermatitis, the authors found that mice lacking CCL8 or CCR8 did not develop chronic TH2-type inflammation in the skin. By contrast, antibodymediated blockade of CCL1 could not protect mice from cutaneous disease. Expression of the TH2-type cytokine interleukin-5 (IL-5), but not that of IL-4 or IL-13, was significantly decreased in CCR8-deficient mice during induction of dermatitis, and this led to decreased eosinophilia and IgG1 class switching in these animals. The defective IL-5 response was a result of impaired recruitment of a subset of IL-5-producing TH2 cells; although these cells seemed to differentiate normally in CCR8-deficient mice, they accumulated in skindraining lymph nodes and could not enter the allergen-inflamed skin. Interestingly, in experiments with in vitro-derived TH2 cells, only cells that had undergone multiple rounds of differentiation under TH2-polarizing conditions upregulated CCR8 and IL-5, suggesting that CCR8 is important for recruiting highly differentiated TH2 cells to the skin. Finally, the authors extended their findings to humans, by showing ex vivo that CCR8+CD4+ T cells from healthy donors were enriched for IL-5 production, whereas CCR4+CD4+ T cells produced IL-4 but not IL-5.

Yvonne Bordon

ORIGINAL RESEARCH PAPERS Li, Z. et al. ECM1 controls TH2 cell egress from lymph nodes through re-expression of S1P1. Nature Immunol. 9 Jan 2011 (doi:10.1038/ni.1983) | Islam, S. A. et al. Mouse CCL8, a CCR8 agonist, promotes atopic dermatitis by recruiting IL-5+ TH2 cells. Nature Immunol. 9 Jan 2011 (doi:10.1038/ni.1984)

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ReseaRch highlights Nature Reviews Immunology | AOP, published online 21 January 2011; doi:10.1038/nri2923

H A E m At O P O I E S I S

Baby tolerance The human adaptive immune system starts to form at an early stage of fetal development (as early as gestation week 10), which contrasts with mice, in which the adaptive immune system only starts to develop around birth. Therefore, mechanisms must exist in humans to prevent a fetal immune response to maternal alloantigens. Reporting in Science, Mold et al. show that human T cells arise from different haematopoietic stem and progenitor cell (HSPC) populations during different stages of development and that fetal CD4+ T cells are biased towards immune tolerance. The authors isolated CD4+ T cells from fetal mesenteric lymph nodes after 18–22 weeks of gestation, and compared them with adult naive CD4+ T cells that were isolated from the blood. Fetal naive CD4+ T cells were more responsive than adult CD4+ T cells to allogeneic stimulation, and a higher proportion of the fetal CD4+ T cells developed into CD25+FOXP3+ regulatory T (TReg) cells after stimulation. Furthermore, fetal and adult CD4+ T cells (including fetal and adult TReg cells) had

distinct gene expression profiles, as determined by microarray analysis. These data suggest that fetal and adult CD4+ T cells are distinct populations and that fetal CD4+ T cells are biased towards immune tolerance. The authors next determined whether fetal and adult CD4+ T cells arise from different HSPC populations. During development, the HSPC pool first resides in the aorta–gonad–mesonephros region, then in the fetal liver and finally in the bone marrow, where most HSPCs are thought to reside throughout adulthood. The authors isolated human HSPCs from fetal liver, fetal bone marrow and adult bone marrow and transferred them to SCID-hu Thy/Liv mice (immunodeficient mice that are engrafted with human fetal thymus and liver tissue and are used to model human haematopoiesis), where they could develop into single positive (SP) thymocytes. A significantly higher number of forkhead box P3 (FOXP3)+ TReg cells arose from fetal

liver- and bone marrow-derived HSPCs than from adult bone marrow-derived HSPCs. Fetal HSPC-derived CD4+ SP thymocytes were highly responsive to allogeneic stimulation in vitro, and significantly more developed into TReg cells compared with adult HSPC-derived CD4+ SP thymocytes. In addition, the gene expression profiles of fetal liver- and fetal bone marrowderived CD4+ SP thymocytes were indistinguishable, but were distinct from the gene expression profile of adult bone marrow-derived CD4+ SP thymocytes. These observations suggest that haematopoiesis occurs in waves that generate distinct T cell populations at different times of development. Although it is still not clear whether fetal and adult HSPCs are distinct lineages or whether adult HSPCs arise from fetal HSPCs in the bone marrow, these data show that fetal and adult HSPCs give rise to distinct T cell populations, and that during development the initial waves of CD4+ T cells are biased towards tolerance.

Olive Leavy

ORIGINAL RESEARCH PAPER Mold, J. E. et al. Fetal and adult hematopoietic stem cells give rise to distinct T cell lineages in humans. Science 330, 1695–1699 (2010)

IS RB CO

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ReseaRch highlights

in brief MUCOSAL IMMUNOLOGY

Induction of colonic regulatory T cells by indigenous Clostridium species Atarashi, K. et al. Science 23 Dec 2010 (doi:10.1126/science.1198469)

There is currently much interest in the crosstalk between the gut microbiota and the immune system. This study shows that forkhead box P3 (FOXP3)+ regulatory T (TReg) cells are most abundant in the colon and, through the use of germ-free or antibiotic-treated specific pathogen-free (SPF) mice, that accumulation of these cells after weaning depends on the gut microbiota. Further analysis identified Clostridium spp. belonging to clusters IV and XIV as the specific component of the microbiota that induces colonic TReg cell accumulation. A defined mix of Clostridium spp. induced the production of transforming growth factor-β by intestinal epithelial cells (in a TLR-, NODand dectin 1-independent manner) and the accumulation of IL-10+CTLA4hi TReg cells in the colon. Finally, oral inoculation of neonatal SPF mice with Clostridium spp. suppressed the development of DSS-induced colitis and systemic IgE responses. dENdRITIC CELLS

Mucosal and systemic anti-HIV immunity controlled by A20 in mouse dendritic cells Hong, B. et al. J. Clin. Invest. 4 Jan 2011 (doi:10.1172/JCI42656)

The ubiquitin-modifying enzyme A20 (also known as TNFAIP3) is a negative feedback regulator of several important pro-inflammatory signalling pathways and controls the immunostimulatory function of antigen-presenting cells. Silencing of A20 mRNA may therefore affect the potency of dendritic cells (DCs) in the induction of HIV-specific immune responses. Injection of mice with A20-silenced, bone-marrow-derived DCs loaded with recombinant HIV envelope protein gp120 resulted in cellular and humoral gp120-specific immune responses, both in mucosal tissues and systemically. These DCs migrated more efficiently to the mesenteric lymph nodes than control DCs and induced the expression of gut-homing receptors on activated lymphocytes, partly through the production of retinoic acid. Furthermore, A20-silenced gp120-pulsed DCs enhanced cytotoxic T cell responses in the absence of CD4+ T cells. So, silencing of A20 may enhance the efficacy of DC-based vaccines against HIV. TUMOUR IMMUNOLOGY

CD169-positive macrophages dominate antitumor immunity by crosspresenting dead cell-associated antigens Asano, K. et al. Immunity 30 Dec 2010 (doi:10.1016/j.immuni.2010.12.011)

It is not known how antigen-presenting cells in the lymph node internalize and cross-present tumour-associated antigens to CD8+ T cells for the initiation of effective antitumour cytotoxic T lymphocyte (CTL) responses. In agreement with previous observations, subcutaneous injection of dead tumour cells activated tumour-specific CTLs. However, this did not induce the migration of CD11c+ DCs from the skin to the draining lymph node; instead, the dead cells travelled via lymphatic flow to the draining lymph node, where they were phagocytosed by CD169+ macrophages in a phosphatidylserine-dependent manner. Antitumour responses did not develop when dead tumour cells were administered to tumour-bearing mice that lacked CD169+ macrophages. Finally, CD11c+CD169+ macrophages (which mainly localized in the cortical and paracortical sinus) were shown to directly cross-present dead-cell-associated antigen to CD8+ T cells. So, CD169+ macrophages promote tumour immunity following tumour cell death. nature reviews | Immunology

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F O C U S O N m E TA b O l i S m A N d i m m U N O lO g y

Foreword FOCUS CONTENTS 85

98

Adipokines in inflammation and metabolic disease Noriyuki Ouchi, Jennifer L. Parker, Jesse J. Lugus and Kenneth Walsh Type 2 diabetes as an inflammatory disease Marc Y. Donath and Steven E. Shoelson

109 OPINION Metabolism, migration and memory in cytotoxic T cells David Finlay and Doreen A. Cantrell

Immunometabolism: an emerging frontier Abstract | Immunometabolism is an emerging field of investigation at the interface between the historically distinct disciplines of immunology and metabolism. Accelerating interest in this area is being fuelled by the obesity epidemic and the relatively recent realization that obesity affects the immune system and promotes inflammation, and that obesity-induced inflammation potentially promotes a variety of chronic conditions and diseases. The multilevel interactions between the metabolic and immune systems suggest pathogenic mechanisms that may underlie many of the downstream complications of obesity and offer substantial therapeutic promise. “To lengthen thy life, lessen thy meals.”

Benjamin Franklin, Poor Richards Almanac (1737).

Diane Mathis Department of Pathology, Harvard Medical School, Boston, Massachusetts 02115, USA. e‑mail: [email protected] Steven E. Shoelson Joslin Diabetes Center and Department of Medicine, Harvard Medical School, Boston, Massachusetts 02215, USA. e‑mail: steven.shoelson@ joslin.harvard.edu doi:10.1038/nri2922

It has long been recognized that effector cells of the immune system are required to ward off tumours and infectious agents. Likewise, it is well known that regulatory cells of the immune system rein in such responses, as well as guarding against immune dysregulation, such as that which occurs in allergy and autoimmunity. Even greater respect for this powerful homeostatic system has emerged over the past few years with the increasing appreciation that immune cells also affect important non-immune functions, including neurodegeneration, cardiovascular function and metabolism. This Focus issue of Nature Reviews Immunology, produced with support from sanofi-aventis, draws attention to an emerging frontier, immunometabolism — that is, the interplay between immunological and metabolic processes. On the one hand, it has emerged that certain supposedly non-immune pathologies result in mobilization of the innate and adaptive immune systems and, in the case of obesity, this promotes metabolic abnormalities, culminating in increased susceptibility to type 2 diabetes, cardiovascular diseases, cancer and neurodegeneration. On the other hand, it is now clear that the behaviours of lymphocytes and other leukocytes are controlled on many levels by internal metabolic properties. Dissection of the molecular underpinnings of the immunological–metabolic crosstalk has become a priority.

Obesity and chronic disease The obesity epidemic continues unabated in Western countries, and is rising even more dramatically throughout the rest of the world, paradoxically even

in the countries where poverty and malnutrition are most widespread. Coinciding with recent increases in obesity have been proportional increases in medical conditions with obvious metabolic connections, such as cardiovascular disease, type 2 diabetes, fatty liver disease and cirrhosis. Additional associations are being drawn between obesity and diseases that are less obviously linked to metabolic derangements, including asthma, Alzheimer’s disease and several forms of cancer. Inflammation has been aetiologically linked to the pathogenesis of each of these conditions, and as obesity is causally linked to a systemic low-grade subacute inflammatory state, as well as inflammation in adipose tissue, obesity-induced inflammation may be a common pathogenic denominator. Two articles in this Focus issue discuss the relationship between adipose tissue expansion and inflammation. The article by Ouchi et al.1 focuses on adipokines, which are bioactive proteins that are produced by adipose tissues and have hormonal or cytokine actions locally and in other tissues. The article by Donath and Shoelson2 discusses the immunological effects of expanding fat mass and inflammation in insulin resistance, and the effects of inflammation in pancreatic islets as these relate to the development and severity of type 2 diabetes.

Adipokines Some adipokines, such as leptin and adiponectin, are produced exclusively (or at least predominantly) by adipose tissues, whereas other so-called adipokines are more typical pro-inflammatory or anti-inflammatory cytokines that are best known for their roles in innate and adaptive immune responses. The list of proinflammatory adipokines that are produced by fat

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FOrEwOrd tissues includes tumour necrosis factor (TnF), interleukin-6 (IL-6), resistin, retinol-binding protein 4 (RBP4) and the closely related protein lipocalin 2, CC-chemokine ligand 2 (CCL2), IL-18, nicotinamide phosphoribosyltransferase (nAmPT; also known as visfatin) and CXC-chemokine ligand 5 (CXCL5). The production of each of these adipokines is increased with adipose tissue expansion, suggesting that this contributes to the pro-inflammatory state that is associated with obesity, and potentially to the deleterious consequences of obesity that are mediated by chronic inflammation. By contrast, anti-inflammatory adipokines and other cytokines produced in fat, including adiponectin, IL-10 (Ref. 3) and the WnT inhibitor secreted frizzled-related protein 5 (SFRP5)4, seem to decrease with fat mass expansion, and this could also contribute to the pro-inflammatory state associated with obesity and its deleterious consequences. Although all of the adipokines are found in adipose tissue, the relative amounts produced by adipocytes versus macrophages, endothelial cells, T cells and mast cells, for example, are in many cases unknown. Also unknown are the relative extents to which the adipokines act as primary inhibitors of insulin sensitivity and secretion as opposed to secondary mediators through their effects on leukocyte recruitment and activation.

obesity is causally linked to a systemic lowgrade subacute inflammatory state, as well as inflammation in adipose tissue

Inflammation in type 2 diabetes Attempts to target inflammation in type 2 diabetes have moved quickly for two main reasons. Foremost is the robustness of the clinical end point — that is, changes in measures of glycaemic control. Fasting blood glucose and glycated haemoglobin (HbA1c) levels are easily measured and highly accurate and reproducible. Fasting blood glucose changes within days to weeks of initiating a therapy, whereas HbA1c levels provide an 8–12 week integrated average blood glucose measure. It is therefore possible to test the efficacy of anti-inflammatory strategies within weeks for initial assessment and in months for highly predictive results. This is in contrast to assessments of drug efficacy and safety in other conditions such as cardiovascular disease, which require much larger trial sizes and duration — and hence much greater cost — to assess true clinical outcomes. Trials of drugs to prevent Alzheimer’s disease are even more challenging, as the common forms of the disease cannot be predicted before disease onset, and this makes trial size and duration, and costs, prohibitive. Clinical trials that assess effects on biomarkers that associate with cardiovascular disease or Alzheimer’s disease can be smaller and of shorter duration, but their ability to predict clinical outcomes is often weak or unknown. As trials in type 2 diabetes can be conducted using reasonable numbers of subjects and at a reasonable cost, they may be used as a screen for potential anti-inflammatory treatments for other obesity-induced chronic diseases that are more difficult to study. Completed and ongoing trials are testing this possibility. Three strategies discussed by Donath and Shoelson2 are the use of salicylates, such as salsalate,

and neutralization of either IL-1 or TnF. Small clinical trials report positive outcomes following selective blockade of IL-1 receptor type 1, either with specific antibodies or recombinant IL-1 receptor antagonist 5,6. Salsalate is a prodrug form of salicylate (an orally active, small-molecule anti-inflammatory drug) and has also been shown to lower blood glucose levels in patients with type 2 diabetes7–9. IL-1 antagonism and salsalate are both being tested further in larger clinical trials. Although small clinical trials using TnF blockade have not provided improvements in blood glucose levels in patients with type 2 diabetes, encouraging results in non-diabetic patients being treated with TnF blockers for other conditions suggest that this might be worth re-exploring.

Unique metabolic uses in immune cells A completely different perspective on the immunological–metabolic interface is the extent to which, and the precise mechanisms by which, typical cell-intrinsic metabolic processes influence the performance of immune cells. In most cases, immune cells use and respond to nutrients similarly to other cells, so it is the exceptions to the rules that may be most interesting. The serine/threonine kinases AKT1–3, AmPK (AmPactivated protein kinase), mTOR (mammalian target of rapamycin) and LKB1 (also known as STK11) are generally thought of as cellular nutrient sensors that help to maintain energy homeostasis by relaying signals that determine how cells respond to high or low levels of intracellular carbohydrates or amino acids. Finlay and Cantrell10 suggest that in addition to their more established roles in nutrient responses, AKT1–3, AmPK and LKB1 control a fate switch, from cytotoxic effector to memory CD8+ T cells. They argue that in CD8+ T cells the main role for the AKT proteins is to regulate repertoires of adhesion molecules and chemokine receptors and hence to control trafficking and migration, and that this is what determines the memory versus terminally differentiated effector decision in CD8+ T cells. A separate series of investigations looked at the effects of LKB1 in haematopoietic stem cells (HSCs)11–13. As noted above, in most cells LKB1 is a serine/threonine kinase that is upstream of AmPK (a master regulator of energy homeostasis) and mTOR complex 1 (mTORC1; a protein complex that controls protein synthesis and cell proliferation). These three reports showed that LKB1 regulates the function and dynamics of HSCs through pathways that are independent of AmPK and mTORC1. Deletion of Lkb1 in mice led to an initial expansion of HSCs and multipotent progenitors, but over time the cells were depleted and the mice became pancytopenic. moreover, an Lkb1–/– bone marrow transplant was unable to reconstitute the haematopoietic system in irradiated mice, again suggesting that the survival of HSCs depends on LKB1. Together, these recent studies showed that under certain conditions, immune cells may use metabolic pathways to control fate and function in ways that are different from other cells.

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F O C U S O N m E TA b O l i S m A N d i m m UrNEOwlO y FO Og rd in addition to their more established roles in nutrient responses, AKT1–3, AMPK and LKB1 control a fate switch, from cytotoxic effector to memory CD8+ T cells.

Thus, the emerging field of immunometabolism has already yielded some novel insights, which have theoretical and practical implications for future work. On the theoretical side, several important questions have been raised, notably: to what extent are obesity and inflammation triggered in parallel or in sequence? If they are mainly triggered in parallel, what is the common initiating signal? If in sequence, what signals link the two processes? Why does obesity-associated inflammation persist, as opposed to being held in check? By what pathway(s) does inflammation provoke type 2 diabetes, cardiovascular disease and other downstream pathologies? Can genetic and environmental factors reinforce or dissociate the link between metabolic and immunological abnormalities? On the practical side, the finding that inflammation mediates many of the pathological consequences of obesity raises the hope of exploiting the existing armamentarium of antiinflammatory drugs, or future ones, to treat patients with obesity-associated metabolic and cardiovascular disorders (and even perhaps some cancers and neurodegenerative diseases). underscoring this potential, the type 2 diabetes drug metformin has shown promise in cancer prevention14, and is being tested in trials for its ability to prevent various cancers. And even more to the point, a daily dose of aspirin (an anti-inflammatory salicylate) correlates with reduced death from several different cancers15.

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.

Ouchi, N., Parker, J. L., Lugus, J. J. & Walsh, K. Adipokines in inflammation and metabolic disease. Nature Rev. Immunol. 11, 85–97 (2011). Donath, M. Y. & Shoelson, S. E. Type 2 diabetes as an inflammatory disease. Nature Rev. Immunol. 11, 98–107 (2011). Lumeng, C. N., Bodzin, J. L. & Saltiel, A. R. Obesity induces a phenotypic switch in adipose tissue macrophage polarization. J. Clin. Invest. 117, 175–184 (2007). Ouchi, N. et al. Sfrp5 is an anti-inflammatory adipokine that modulates metabolic dysfunction in obesity. Science 329, 454–457 (2010). Larsen, C. M. et al. Interleukin-1-receptor antagonist in type 2 diabetes mellitus. N. Engl. J. Med. 356, 1517–1526 (2007). Larsen, C. M. et al. Sustained effects of interleukin-1 receptor antagonist treatment in type 2 diabetes. Diabetes Care 32, 1663–1668 (2009). Goldfine, A. B. et al. Use of salsalate to target inflammation in the treatment of insulin resistance and type 2 diabetes. Clin. Transl. Sci. 1, 36–43 (2008). Fleischman, A., Shoelson, S. E., Bernier, R. & Goldfine, A. B. Salsalate improves glycemia and inflammatory parameters in obese young adults. Diabetes Care 31, 289–294 (2008). Goldfine, A. B. et al. The effects of salsalate on glycemic control in patients with type 2 diabetes: a randomized trial. Ann. Intern. Med. 152, 346–357 (2010). Finlay, D. & Cantrell, D. A. Metabolism, migration and memory in cytotoxic T cells. Nature Rev. Immunol. 11, 109–117 (2011). Nakada, D., Saunders, T. L. & Morrison, S. J. Lkb1 regulates cell cycle and energy metabolism in haematopoietic stem cells. Nature 468, 653–658 (2010). Gurumurthy, S. et al. The Lkb1 metabolic sensor maintains haematopoietic stem cell survival. Nature 468, 659–663 (2010). Gan, B. et al. Lkb1 regulates quiescence and metabolic homeostasis of haematopoietic stem cells. Nature 468, 701–704 (2010). Gallagher, E. J. & LeRoith, D. Insulin, insulin resistance, obesity, and cancer. Curr. Diab. Rep. 10, 93–100 (2010). Rothwell, P. M. et al. Effect of daily aspirin on long-term risk of death due to cancer: analysis of individual patient data from randomised trials. Lancet 377, 31–41 (2010).

Competing interests statement

The authors declare competing financial interests: see Web version for details.

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REVIEWS Adipokines in inflammation and metabolic disease Noriyuki Ouchi*, Jennifer L. Parker‡, Jesse J. Lugus‡ and Kenneth Walsh‡

Abstract | The worldwide epidemic of obesity has brought considerable attention to research aimed at understanding the biology of adipocytes (fat cells) and the events occurring in adipose tissue (fat) and in the bodies of obese individuals. Accumulating evidence indicates that obesity causes chronic low-grade inflammation and that this contributes to systemic metabolic dysfunction that is associated with obesity-linked disorders. Adipose tissue functions as a key endocrine organ by releasing multiple bioactive substances, known as adipose-derived secreted factors or adipokines, that have pro-inflammatory or anti-inflammatory activities. Dysregulated production or secretion of these adipokines owing to adipose tissue dysfunction can contribute to the pathogenesis of obesity-linked complications. In this Review, we focus on the role of adipokines in inflammatory responses and discuss their potential as regulators of metabolic function. Insulin resistance A condition characterized by the inability of cells (in the muscle, liver and fat) to respond appropriately to endogenous insulin, resulting in increased blood glucose levels.

*Department of Molecular Cardiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho Showa-ku, Nagoya, 466-8550 Japan. ‡ Molecular Cardiology/ Whitaker Cardiovascular Institute, Boston University School of Medicine, 715 Albany Street, W611, Boston, Massachusetts 02118, USA. Correspondence to K.W. e-mail: [email protected] doi:10.1038/nri2921 Published online 21 January 2011

Obesity has become a major worldwide health problem, not least because it is strongly associated with a number of diseases, including insulin resistance , type 2 diabetes, atherosclerosis and ischaemic heart disease, that reduce life expectancy and together have huge economic and societal consequences. Increasing evidence indicates that obesity is causally linked to a chronic low-grade inflammatory state 1,2, which contributes to the development of obesity-linked disorders, in particular to metabolic dysfunction. It is now well established that adipose tissue is not only involved in energy storage but also functions as an endocrine organ that secretes various bioactive substances 3,4. The dysregulated expression of these factors, caused by excess adiposity and adipocyte dysfunction, has been linked to the pathogenesis of various disease processes through altered immune responses. As such, much attention has been paid to developing a better understanding of the immunoregulatory functions of adipose tissue. New factors secreted by adipose tissue have been identified that either promote inflammatory responses and metabolic dysfunction or contribute to the resolution of inflammation and have beneficial effects on obesity-linked metabolic disorders. These findings lend additional support to the notion that an imbalance of pro- and anti-inflammatory adipokines secreted by adipose tissue contributes to metabolic dysfunction.

Obesity and inflammation Clinical observations. Obesity — in particular, excess visceral adiposity — is strongly associated with insulin resistance, hypertension and dyslipidaemia, which contribute to high rates of mortality and morbidity. Accumulating evidence indicates that a state of chronic inflammation has a crucial role in the pathogenesis of obesity-related metabolic dysfunction1,2. Indeed, clinical and epidemiological studies have described a clear connection between the development of low-grade inflammatory responses and metabolic diseases, particularly in the context of obesity and type 2 diabetes. Excess adipose mass (as occurs in obese individuals) is associated with increased levels of the pro-inflammatory marker C-reactive protein (CRP) in the blood5. Increased levels of CRP, and its inducer interleukin-6 (IL-6), are predictive of the development of type 2 diabetes in various populations5,6. In addition, interventions aimed at causing weight loss lead to reductions in the levels of pro-inflammatory proteins, including CRP and IL-6 (Ref. 7). The adipokine concept. Adipose tissue was traditionally considered to be a long-term energy storage organ, but it is now appreciated that it has a key role in the integration of systemic metabolism. This metabolic function is mediated, in part, by its ability to secrete numerous proteins. Factors that are secreted by adipose tissue are collectively

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ReVieWs

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Figure 1 | Adipose tissue depots. Adipose tissue is mainly found in subcutaneous and visceral depots. Under conditions of obesity, adipose tissue expands in these and other depots throughout the body. Common sites of adipose tissue accumulation 0CVWTG4GXKGYU^+OOWPQNQI[ include the heart, the kidneys and the adventitia of blood vessels. Differential adipokine secretion by various adipose tissue depots may selectively affect organ function and systemic metabolism.

referred to as adipokines3,4. Importantly, following the onset of obesity, the secretory status of an adipose tissue depot can be modified by changes in the cellular composition of the tissue, including alterations in the number, phenotype and localization of immune, vascular and structural cells. The expression of adipokines can also vary depending on the site of an adipose tissue depot (fIG. 1). The two most abundant depots are visceral and subcutaneous adipose tissues, which produce unique profiles of adipokines8,9. In addition, adipocyte depots occur throughout the body in association with multiple organs, including the heart and kidneys. Adipocytes are also found in the bone marrow, lungs and the adventitia of major blood vessels. In some instances, it has been shown that high-calorie diets can promote the development of a pro-inflammatory state in these depots in a similar manner to that observed in subcutaneous and visceral adipose tissue (for example, see Ref. 10). Although the functional importance of many of these individual adipose depots is generally not known, recent evidence suggests that diet-induced changes in their adipokine secretion can influence the function of the associated tissue11. brown adipose tissue, which is mainly found in infants and hibernating animals, is functionally distinct from white adipose tissue, and is not covered in this Review. Adipsin (also known as complement factor D) was identified as an adipokine in 1987 (Ref. 12). In 1993, tumour necrosis factor (TNF) was identified as a proinflammatory product of adipose tissue that is induced in models of diabetes and obesity, providing evidence for a functional link between obesity and inflammation13. subsequently, leptin was identified as an adipose tissuespecific secreted protein that regulates food intake and energy expenditure in an endocrine manner 14. similarly,

the identification of plasminogen activator inhibitor 1 (PAI1), an inhibitor of fibrinolysis, as an adipokine that is strongly upregulated in visceral adipose depots in obesity 15 suggested a mechanistic link between obesity and thrombotic disorders. At about the same time, adiponectin (also known as ACRP30 and ADIPOQ) was identified as an adipocyte-specific adipokine16–18. Adiponectin expression was found to be decreased in obesity, and studies in experimental organisms showed that adiponectin protects against several metabolic and cardiovascular disorders that are associated with obesity. These results were surprising as most adipokines stimulate inflammatory responses, are upregulated in obesity and promote obesity-induced metabolic and cardiovascular diseases. Collectively, these findings have led to the notion that metabolic dysfunction that is due to excess adipose tissue mass may partly result from an imbalance in the expression of pro- and anti-inflammatory adipokines, thereby contributing to the development of obesity-linked complications. Accordingly, the concept that adipokines function as regulators of body homeostasis has received widespread attention from the research community (TABLe 1). Infiltration of immune cells into adipose tissue. Adipose tissue is mainly comprised of adipocytes, although other cell types contribute to its growth and function, including pre-adipocytes, lymphocytes, macrophages, fibroblasts and vascular cells (fIG. 2a). Obesity can lead to changes in the cellular composition of the fat pad as well as to the modulation of individual cell phenotypes (BOX 1). Adipose tissues in obese individuals and in animal models of obesity are infiltrated by a large number of macrophages, and this recruitment is linked to systemic inflammation and insulin resistance19,20. moreover, the accumulation of adipose tissue macrophages is proportional to adiposity in both humans and mice19,20, and sustained weight loss results in a reduction in the number of adipose tissue macrophages that is accompanied by a decrease in the pro-inflammatory profiles of obese individuals21. macrophages are also more abundant in visceral than subcutaneous adipose tissue22, and this is in line with the belief that visceral adipose tissue has a more important role in the development of insulin resistance. However, it has been recently reported that macrophages accumulate in adipose tissues during the early phase of weight loss, presumably as a result of adipose tissue lipolysis23. Adipose tissue also contains fibroblasts, which produce extracellular matrix components. Recently, it has been shown that metabolically dysfunctional adipose tissue produces excess matrix components that may interfere with adipose mass expansion and contribute to metabolic dysregulation24. Thus, it is becoming increasingly evident that intercellular communication within adipose tissue is required for normal metabolic function. Examples of such intercellular communication include the counter-regulation between the adipocyte-derived anti-inflammatory factors adiponectin and secreted frizzled-related protein 5 (sFRP5) and the macrophage-derived pro-inflammatory factors TNF and wNT5a. under conditions of obesity, TNF and wNT5a are upregulated, whereas adiponectin and sFRP5 are downregulated3,4,25 (fIG. 2b).

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f o c u s o n m e ta b o l i s m a n d i m m uRneoVlo gy ieW s Table 1 | Sources and functions of key adipokines Adipokine

Primary source(s)

Binding partner or receptor

Function

Leptin

Adipocytes

Leptin receptor

Appetite control through the central nervous system

Resistin

Peripheral blood mononuclear cells (human), adipocytes (rodent)

Unknown

Promotes insulin resistance and inflammation through IL-6 and TNF secretion from macrophages

RBP4

Liver, adipocytes, macrophages

Retinol (vitamin A), transthyretin

Implicated in systemic insulin resistance

Lipocalin 2

Adipocytes, macrophages

Unknown

Promotes insulin resistance and inflammation through TNF secretion from adipocytes

ANGPTL2

Adipocytes, other cells

Unknown

Local and vascular inflammation

TNF

Stromal vascular fraction cells, adipocytes

TNF receptor

Inflammation, antagonism of insulin signalling

IL-6

Adipocytes, stromal vascular fraction cells, liver, muscle

IL-6 receptor

Changes with source and target tissue

IL-18

Stromal vascular fraction cells

IL-18 receptor, IL-18 binding protein

Broad-spectrum inflammation

CCL2

Adipocytes, stromal vascular fraction cells

CCR2

Monocyte recruitment

CXCL5

Stromal vascular fraction cells (macrophages)

CXCR2

Antagonism of insulin signalling through the JAK–STAT pathway

NAMPT

Adipocytes, macrophages, other cells

Unknown

Monocyte chemotactic activity

Adiponectin

Adipocytes

Adiponectin receptors 1 and 2, T-cadherin, calreticulin–CD91

Insulin sensitizer, anti-inflammatory

SFRP5

Adipocytes

WNT5a

Suppression of pro-inflammatory WNT signalling

ANGPTL2, angiopoietin-like protein 2; CCL2, CC-chemokine ligand 2; CXCL5, CXC-chemokine ligand 5; IL, interleukin; JAK, Janus kinase; NAMPT, nicotinamide phosphoribosyltransferase; RBP4, retinol-binding protein 4; SFRP5, secreted frizzled-related protein 5; STAT, signal transducer and activator of transcription; TNF, tumour necrosis factor.

Crown-like structure An aggregation of single or fused macrophages (also referred to as multinucleated giant cells) around a single adipocyte in adipose tissue. These structures are typically associated with obesity, adipose tissue dysfunction and chronic inflammation.

M1 or ‘classically activated’ macrophage A macrophage that is activated by Toll-like receptor ligands (such as lipopolysaccharide) and interferon-γ, and that expresses inducible nitric oxide synthase and nitric oxide, as well as other pro-inflammatory factors.

M2 or ‘alternatively activated’ macrophage A macrophage that is stimulated by interleukin-4 (IL-4) or IL-13, and that expresses arginase 1, the mannose receptor CD206 and the IL-4 receptor α-chain.

It has become evident that in addition to absolute fat quantity, qualitative aspects of adipose tissue function and cellular composition have an important effect on the systemic metabolic phenotype26. Indeed, body massmatched obese individuals can be divided into two categories: those that have fully dysfunctional metabolic control and those that have mildly dysfunctional metabolic control (fIG. 3). Obese individuals with the latter intermediate metabolic phenotype have lower levels of inflammatory marker expression and reduced cardiovascular risk compared with metabolically dysfunctional obese individuals27. In the same study, the classification of metabolically dysfunctional obese individuals correlated with the presence of crown-like structures, which are histological features that represent an accumulation of macrophages around dead adipocytes in inflamed adipose tissue28,29. because a key function of macrophages is to remove apoptotic cells in an immunologically silent manner to prevent the release of noxious substances, it is reasonable to speculate that the presence of crown-like structures in adipose tissue reflects a pro-inflammatory state that is due, in part, to an impairment of the macrophage-mediated phagocytic process. Consistent with this notion is the finding that the induction of adipocyte apoptosis in an inducible mouse model of lipoatrophy leads to macrophage accumulation in adipose tissues30.

However, the process may be more complex as a recent paper has reported that adipocyte death is not increased by obesity in humans31. Different subsets of macrophages are involved in obesity-induced adipose tissue inflammation. macrophages that accumulate in the adipose tissues of obese mice mainly express genes associated with an M1 or ‘classically activated’ macrophage phenotype, whereas adipose tissue macrophages from lean mice express genes associated with an M2 or ‘alternatively activated’ macrophage phenotype32. stimulation with T helper 1 (TH1)-type cytokines, including interferon-γ (IFNγ), or with bacterial products leads to the generation of m1 macrophages, which produce pro-inflammatory cytokines (including TNF and IL-6), express inducible nitric oxide synthase (iNOs) and produce reactive oxygen species (ROs) and nitrogen intermediates33. by contrast, macrophages are polarized to the m2 phenotype by TH2-type cytokines such as IL-4 and IL-13. m2 macrophages upregulate production of the antiinflammatory cytokine IL-10 and downregulate synthesis of pro-inflammatory cytokines. The transcription of several genes, including those encoding arginase 1, macrophage mannose receptor 1 and IL-1 receptor antagonist, is upregulated in m2 macrophages, through a programme that is reported to be regulated by the transcription factors peroxisome proliferator-activated receptor-γ (PPARγ)

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Figure 2 | Components of adipose tissue. a | Adipocytes are the main cellular component of adipose tissue, and they are crucial for both energy storage and 0CVWTG4GXKGYU^+OOWPQNQI[ endocrine activity. The other cell types that are present are precursor cells (including pre-adipocytes), fibroblasts, vascular cells and immune cells, and these cells constitute the stromal vascular fraction of adipose tissue. Vascular cells include both endothelial cells and vascular smooth muscle cells, which are associated with the major blood vessels. The blood vessels in adipose tissue are required for the proper flow of nutrients and oxygen to adipocytes, and they are the conduits that allow for the distribution of adipokines. Vascular cells also secrete, and are responsive to, adipose tissue-secreted proteins. Other active adipose tissue components include macrophages and T cells, which have major roles in determining the immune status of adipose tissue. The fibroblast-derived extracellular matrix functions to provide mechanical support, and excess matrix can lead to adipose tissue dysfunction. Factors that are secreted by these different cellular components are critical for maintaining homeostasis in adipose tissue and throughout the body. b | Examples of intercellular communication between different adipose tissue cell types include the counter-regulation between adiponectin and tumour necrosis factor (TNF), and between secreted frizzled-related protein 5 (SFRP5) and WNT5a. Under conditions of obesity the pro-inflammatory factors (TNF and WNT5a) predominate.

and PPARδ34. Functionally, m2 macrophages are associated with the repair of injured tissues and the resolution of inflammation33. so, it has been suggested that m1 macrophages promote insulin resistance and m2 macrophages protect against obesity-induced insulin resistance35. Recent studies have described subsets of T cells that are present in adipose tissues and seem to be involved in the regulation of macrophage phenotype. CD4+ regulatory T cells are more abundant in the adipose tissues of lean mice and have a protective effect by inhibiting proinflammatory macrophages, leading to the suppression of insulin resistance36. CD8+ effector T cells and TH1 cell-associated factors can initiate the recruitment and activation of macrophages in adipose tissues and promote a pro-inflammatory cascade that is associated with

insulin resistance37,38. Thus, obesity-induced perturbations in the balance between TH1- and TH2-type signals may influence the recruitment and activation of macrophages in adipose tissues, thereby generating either a pathogenic and inflammatory environment or a noninflammatory and protective environment. However, the changes in the adipose tissue microenvironment that initiate T cell recruitment and macrophage activation are not fully understood. Nevertheless, it is important to bear in mind that obesity-associated changes in the cellular composition of adipose tissue complicates our understanding of whether a putative adipokine is expressed entirely by adipocytes or by recruited inflammatory cells (TABLe 1).

Pro-inflammatory adipokines The production of most adipokines is upregulated in the obese state, and these pro-inflammatory proteins typically function to promote obesity-linked metabolic diseases. In addition to leptin, TNF and IL-6, more recently identified adipokines that promote inflammation include resistin, retinol-binding protein 4 (RbP4), lipocalin 2, IL-18, angiopoietin-like protein 2 (ANGPTL2), CC-chemokine ligand 2 (CCL2), CXC-chemokine ligand 5 (CXCL5) and nicotinamide phosphoribosyltransferase (NAmPT) (TABLe 1), and this subset of factors is discussed in more detail below. It is the upregulation of these factors (as well as others) that leads to the development of a chronic inflammatory state and contributes to metabolic dysfunction. below, we briefly describe adipose tissue-derived proteins that generally have pro-inflammatory effects and discuss their metabolic regulatory properties. Leptin. The adipokine leptin is the product of the obese gene (ob; also known as Lep), which was identified in ob/ob mice by positional cloning 14. Leptin regulates feeding behaviour through the central nervous system. mice that lack leptin (ob/ob mice) show hyperphagia (abnormally increased feeding), obesity and insulin resistance, and the administration of leptin to ob/ob mice reverses these changes39. The administration of leptin to lipoatrophic mice (which lack subcutaneous adipose tissue and thus have low levels of leptin) also improves metabolic abnormalities, including insulin resistance and hyperlipidaemia40. Leptin has also been shown to be effective at improving metabolic dysfunction in patients with lipodystrophy or congenital leptin deficiency 41,42. However, leptin levels in the blood positively correlate with adipose mass, indicating the occurrence of leptin resistance, and obese individuals have high levels of leptin without the expected anorexic responses39. Leptin is structurally similar to the family of helical cytokines that includes IL-2 and growth hormone 1, and is thought to have pro-inflammatory activities. Indeed, leptin increases the production of TNF and IL-6 by monocytes and stimulates the production of CC-chemokine ligands (namely, CCL3, CCL4 and CCL5) by macrophages by activating the JAK2 (Janus kinase 2)–sTAT3 (signal transducer and activator of

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f o c u s o n m e ta b o l i s m a n d i m m uRneoVlo gy ieW s Box 1 | Vascular function in adipose tissue Recent interest has been paid to the status of the vasculature in adipose tissue. It has been shown that obesity can lead to capillary rarefaction in adipose tissue leading to localized hypoxia146,147. Theoretically, reductions in blood flow in obese adipose tissue could limit the delivery of nutrients, thereby contributing to insulin resistance. Perhaps more importantly, a restriction of blood flow in adipose tissue could contribute to an inflammatory state, possibly as a result of ischaemia-induced adipocyte necrosis and the subsequent recruitment of macrophages. Furthermore, obesity leads to the downregulation of anti-inflammatory factors, such as adiponectin, that pacify the vascular endothelium, and the upregulation of pro-inflammatory factors that activate endothelial cells and promote a dysfunctional phenotype11. In turn, the activated vascular endothelium expresses adhesion molecules and chemotactic factors that accelerate and localize inflammatory processes. Thus, the status of endothelial cell function may have an integral role both in mediating the effects of metabolic disease on the cardiovascular system and in controlling the metabolic state of the organism by influencing, either positively or negatively, the microenvironment in adipose tissue. Therefore, it can be posited that obesity favours a vicious cycle whereby endothelial cell dysfunction in the adipose tissue leads to metabolic dysfunction, reflected by adipokine dysregulation, adipocyte necrosis and inflammation120. In turn, metabolic dysfunction promotes endothelial cell dysfunction, both in the adipose tissue and systemic circulation, putting further stress on adipocytes. However, in contrast to these considerations, it has been reported that obese mice receiving anti-angiogenic reagents have a reduced body weight and adipose mass, and show increased metabolic rates148. Because there is a close interplay between adipogenesis and angiogenesis in obesity149, further analysis of the role of adipokines in controlling vascular growth and metabolic function during adipose tissue expansion should be of interest.

transcription 3) pathway 43,44. In monocytes, leptin also stimulates the production of ROs and promotes cell proliferation and migratory responses43,45. Leptin levels in the serum and adipose tissues are increased in response to pro-inflammatory stimuli, including TNF and lipopolysaccharide (LPs)46. Furthermore, leptin increases the production of the TH1-type cytokines IL-2 and IFNγ and suppresses the production of the TH2-type cytokine IL-4 by T cells or mononuclear cells47, thus polarizing T cells towards a TH1 cell phenotype. Consistent with these findings, leptin deficiency protects against liver damage in models of T cell-mediated hepatitis48. In addition, ob/ob mice are resistant to the induction of experimental autoimmune encephalomyelitis, owing to the polarization of T cells towards the TH2-type phenotype rather than the pathogenic TH1-type phenotype47,49. Thus, it is generally accepted that leptin acts as a pro-inflammatory adipokine. The metabolic syndrome A disorder characterized by the presence of at least three of the following features: large waist circumference (men: ≥40 inches; women: ≥35 inches), high levels of circulating triglycerides (≥150 mg dl–1), low levels of high-density lipoprotein (men: <40 mg dl–1; women: <50 mg dl–1), high fasting blood glucose (≥100 mg dl–1) and high blood pressure (≥130/85 mm Hg). Together, these conditions increase the risk of heart disease, stroke and type 2 diabetes.

Resistin. Resistin is a member of the cysteine-rich family of resistin-like molecules (RELms) that are associated with the activation of inflammatory processes. Resistin has been shown to induce insulin resistance in mice50, and mice lacking resistin have low blood glucose levels post-fasting owing to low hepatic glucose production51. Resistin deficiency in ob/ob mice leads to increased obesity, but these severely obese mice have improved glucose tolerance and insulin sensitivity 52. The ability of resistin to modulate glucose metabolism is associated with the activation of suppressor of cytokine signalling 3 (sOCs3), an inhibitor of insulin signalling, in adipocytes53. Although studies in animal models consistently show that resistin promotes insulin resistance, evidence for this effect in humans is less clear 54,55.

Resistin is present in two quaternary forms: an abundant high-molecular weight hexamer and a less abundant, but more bioactive, trimer, which strongly induces hepatic insulin resistance56. Although originally identified in adipose tissue, further analyses have shown a broader pattern of expression and led to controversy about the regulation of this adipokine. In mice, resistin protein synthesis is restricted to adipocytes50, whereas in humans, resistin is mainly produced by macrophages and monocytes, and it is not detectable in adipocytes57. In human mononuclear cells, transcription of the resistin gene (RETN) is induced by pro-inflammatory cytokines, including IL-1, IL-6 and TNF58, and in white adipose tissue it is inhibited by the PPARγ agonist rosiglitazone, suggesting that the anti-inflammatory effect of rosiglitazone is mediated in part by the attenuation of RETN transcription59. more recently, studies of mice that lack endogenous resistin expression in adipocytes but express a human RETN transgene in macrophages indicate that the pro-inflammatory properties of macrophage-derived resistin contribute to insulin resistance in vivo60. The pro-inflammatory properties of resistin in human mononuclear cells are evident, as resistin promotes the expression of TNF and IL-6 by these cells61. In addition, resistin directly counters the anti-inflammatory effects of adiponectin on vascular endothelial cells by promoting the expression of the pro-inflammatory adhesion molecules vascular cell adhesion molecule 1 (vCAm1), intercellular adhesion molecule 1 (ICAm1) and pentraxin 3 in these cells, thereby enhancing leukocyte adhesion62,63. RBP4. serum RbP4 is a hepatocyte-secreted factor that is responsible for the transport of retinol (vitamin A) throughout the body 64. Recently, RbP4 was also found to be secreted by both adipocytes65 and macrophages66. The expression of RbP4 is inversely related to that of glucose transporter type 4 (GLuT4; also known as sLC2A4), and administration of recombinant RbP4 to normal mice decreases insulin sensitivity 65. RbP4 is released by adipocytes and inhibits insulin-induced phosphorylation of insulin receptor substrate 1 (IRs1) in an autocrine or paracrine manner 67. These data implicate RbP4 as an adipose tissue-secreted factor that is important for the regulation of glucose homeostasis in models of type 2 diabetes. studies in human populations have supported this concept: increased serum RbP4 levels were found to associate with features of the metabolic syndrome, including high blood pressure, low levels of high-density lipoprotein, high levels of cholesterol and triglycerides, and increased body mass index 68. RbP4 is preferentially produced by visceral adipose tissues in states of obesity and insulin resistance, and it is a marker of intra-abdominal adipose tissue expansion69 and subclinical inflammation70. Recent studies suggest that high levels of RbP4 may be specifically associated with nephropathy 71,72. Accordingly, approaches that lower the levels of RbP4 or reduce its stability by inhibiting its interaction with transthyretin may be beneficial for the treatment of insulin resistance73.

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Figure 3 | Phenotypic modulation of adipose tissue. Adipose tissue can be described by at least three structural and functional classifications: lean with normal metabolic function, obese with mild metabolic dysfunction and obese with full 0CVWTG4GXKGYU^+OOWPQNQI[ metabolic dysfunction. As obesity develops, adipocytes undergo hypertrophy owing to increased triglyceride storage. With limited obesity, it is likely that the tissue retains relatively normal metabolic function and has low levels of immune cell activation and sufficient vascular function. However, qualitative changes in the expanding adipose tissue can promote the transition to a metabolically dysfunctional phenotype. Macrophages in lean adipose tissue express markers of an M2 or alternatively activated state, whereas obesity leads to the recruitment and accumulation of M1 or classically activated macrophages, as well as T cells, in adipose tissue. Anti-inflammatory adipokines, including adiponectin and secreted frizzled-related protein 5 (SFRP5), are preferentially produced by lean adipose tissue. In states of obesity, adipose tissue generates large amounts of pro-inflammatory factors, including leptin, resistin, retinol-binding protein 4 (RBP4), lipocalin 2, angiopoietin-like protein 2 (ANGPTL2), tumour necrosis factor (TNF), interleukin-6 (IL-6), IL-18, CC-chemokine ligand 2 (CCL2), CXC-chemokine ligand 5 (CXCL5) and nicotinamide phosphoribosyltransferase (NAMPT). Obese individuals with adipose tissue in a metabolically intermediate state have improved metabolic parameters, diminished inflammatory marker expression and better vascular function compared with individuals that have metabolically dysfunctional adipose tissue. Metabolically dysfunctional adipose tissue can be associated with higher levels of adipocyte necrosis, and M1 macrophages are arranged around these dead cells in crown-like structures.

Lipocalin 2. Lipocalin 2 (also known as neutrophil gelatinase-associated lipocalin and 24p3) belongs to the lipocalin protein superfamily, which also includes RbP4 (Refs 74,75). Lipocalins bind and transport various small lipophilic substances such as retinoids, arachidonic acid and steroids. Lipocalin 2 can bind weakly to some of the common ligands of lipocalins, including leukotriene b4 and platelet activating factor, although its high-affinity endogenous ligands have not been identified. Lipocalin 2 is abundantly expressed in adipose tissue74,75 and is induced by inflammatory stimuli through activation of nuclear factor-κb (NF-κb) 76. Indeed, lipocalin 2 is found at high levels in the adipose tissues of diet-induced or genetically obese mice74, as well as those of obese individuals77,78. serum concentrations of lipocalin 2 are positively associated with adiposity, hyperglycaemia, insulin resistance and CRP levels77. Lipocalin 2-deficient mice have improved insulin sensitivity compared with control littermates under conditions of ageing or obesity 79. The improved metabolic properties are attributed to the inhibition of arachidonate 12-lipoxygenase, an enzyme that is linked to inflammation and insulin resistance. However, another study reported that lipocalin 2 deficiency potentiates diet-induced obesity and insulin resistance, which is accompanied by the increased

expression of pro-inflammatory mediators80. The reason for these discrepant findings in lipocalin 2-deficient mice is currently unknown. ANGPTL2. It was recently reported that ANGPTL2 functions as an adipokine that promotes inflammation and insulin resistance81. ANGPTL2 levels in adipose tissues and plasma are higher in diet-induced obese mice than in control mice, and circulating ANGPTL2 levels are positively associated with adiposity, markers of insulin resistance and CRP levels in humans. ANGPTL2 deficiency leads to a reduction in inflammation, including downregulation of pro-inflammatory cytokines in adipose tissues and the amelioration of systemic insulin resistance in diet-induced obese mice. Conversely, ANGPTL2 overexpression in adipose tissue leads to exacerbation of adipose tissue inflammation and insulin resistance. Overexpression of ANGPTL2 in the epidermis also stimulates the attachment of leukocytes to the blood vessel walls in the skin and increases vascular permeability, leading to enhanced vascular inflammation81. moreover, ANGPTL2 activates inflammatory responses by endothelial cells, monocytes and macrophages through the activation of integrin signalling 81.

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f o c u s o n m e ta b o l i s m a n d i m m uRneoVlo gy ieW s TNF. TNF is a pro-inflammatory cytokine that is mainly produced by monocytes and macrophages and has a central role in inflammatory and autoimmune diseases. TNF expression is increased in the adipose tissues of experimental animal models of obesity and type 2 diabetes13. Accordingly, neutralization of TNF-induced signalling in obese animals leads to an improvement in insulin sensitivity, which is associated with an enhancement of insulin signalling in muscle and adipose tissues13,82,83. At a mechanistic level, TNF attenuates insulin-stimulated tyrosine phosphorylation of the insulin receptor and IRs1 in muscle and adipose tissues, thus promoting insulin resistance82. These data support the notion that TNF functions as a pro-inflammatory cytokine that has a crucial role in obesity-related insulin resistance. TNF levels are increased in the adipose tissue and plasma of obese individuals, and a reduction of body weight in these individuals is associated with a decrease in TNF expression84,85. TNF levels in the blood were also found to positively correlate with markers of insulin resistance in a community-based cohort study 86. However, clinical trials that have tested the ability of TNF antagonism to improve insulin sensitivity have not provided consistent results. For example, short-term administration of TNF blocking reagents to obese patients with type 2 diabetes led to a reduction in systemic inflammatory markers, but did not ameliorate insulin resistance87,88. similarly, blockade of TNF in patients with the metabolic syndrome resulted in an increase in muscle adiposity, indicating a lack of effect on insulin sensitivity 89. On the other hand, blockade of TNF in patients with severe inflammatory diseases, including rheumatoid arthritis and psoriasis, is reported to promote insulin sensitivity 90,91, suggesting that inhibition of TNF might be effective at improving insulin resistance under certain conditions (such as severe inflammatory states). A recent report also shows that a prolonged period of TNF neutralization in patients with the metabolic syndrome improves fasting glucose levels92, and this supports the notion that increased TNF levels in obesity contribute to impaired glucose homeostasis in humans.

Stromal vascular fraction Non-adipocyte components of adipose tissue, including monocytes, macrophages, vascular cells, pre-adipocytes, T cells and mesenchymal stem cells.

IL‑6. IL-6 is a pro-inflammatory cytokine that may also be involved in obesity-related insulin resistance. Clinically, plasma IL-6 levels positively correlate with adiposity in human populations9, such that increased levels of IL-6 are observed in obese subjects and weight loss leads to a reduction in IL-6 levels7,85. Furthermore, plasma levels of IL-6 are increased in patients with type 2 diabetes, and increased IL-6 levels are predictive of the development of type 2 diabetes6. It is estimated that approximately one-third of total circulating IL-6 is produced by adipose tissues9, and it is possible that increased secretion of IL-6 under conditions of obesity contributes to metabolic dysfunction. However, the role of IL-6 in insulin resistance has been controversial. IL-6 has been shown to suppress insulin-stimulated metabolic actions in hepatocytes through a mechanism that is mediated by the induction of sOCs3 expression93. similarly, infusion of IL-6 into mice abolishes the ability of insulin to suppress glucose production in the liver 94. by contrast, IL-6

deficiency exacerbates hepatic insulin resistance and inflammation in mice on a high-calorie diet95, whereas reduction of IL-6 in adipose tissue (by ablation of JNK) protects against the development of insulin resistance through modulation of sOCs3 expression in the liver 96. Thus, the different actions of IL-6 on insulin signalling may be due to its disparate actions in different organs (liver versus muscle) or the different sources of IL-6 (muscle versus fat)97,98. IL‑18. IL-18 is a pro-inflammatory cytokine, and it is now recognized that it is produced by adipose tissues99. serum levels of IL-18 are increased in obese individuals, and they decline following weight loss100. High levels of IL-18 have also been detected in atherosclerotic lesions in humans and may indicate plaque instability101. Overexpression of IL-18 in rats results in increased expression of endothelial cell adhesion molecules, macrophage infiltration of the blood vessel wall and vascular abnormalities102, whereas IL-18 deficiency led to smaller lesions in a mouse model of atherosclerosis103. Despite the pro-inflammatory nature of IL-18, mice that are deficient in IL-18 or its receptor show hyperphagia and have features of the metabolic syndrome, including insulin resistance, hyperglycaemia and obesity 104. similar results were found in mice that overexpress IL-18 binding protein, which reversibly binds and inactivates IL-18. Thus, IL-18 seems to have complex roles in coordinating inflammation and metabolism. CCL2. The expression of CCL2 (also known as mCP1) has been shown to be increased in adipose tissues under conditions of glucose deprivation105. In addition, genetically obese (ob/ob) mice and diet-induced obese mice have high levels of CCL2 expression in their white adipose tissue, and this observation has been extended to humans106. In mice, high levels of circulating CCL2 (originating from adipose tissues) are sufficient to induce macrophage recruitment to, and inflammation in, adipose tissues, as well as to promote glucose intolerance and insulin insensitivity 105. Accordingly, somatic deletion of Ccl2 protects mice against adipose tissue inflammation and macrophage recruitment, as well as metabolic perturbations, following the initiation of a high-fat diet. Conversely, another study found no differences in adipose tissue inflammation or macrophage accumulation in CCL2-deficient mice107. studies of mice with a somatic deletion of CC-chemokine receptor 2 (Ccr2), the receptor for CCL2, gain as much weight as their wild-type littermates but fail to show adipose tissue inflammation, and maintain insulin sensitivity on a high-fat diet 108,109. As CCR2 functions as a receptor for several chemokines, there may be additional inflammatory chemokines that compensate for the absence of CCL2 (Ref. 110). CXCL5. CXCL5 is secreted by macrophages within the stromal vascular fraction, and has been shown to be linked to adipose tissue inflammation and insulin resistance111. Circulating levels of CXCL5 are higher in obese, insulinresistant individuals than in obese insulin-sensitive individuals, and CXCL5 levels decrease after a 4-week period on a low-calorie diet. mechanistically, CXCL5 interferes

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ReVieWs with insulin signalling in muscles by activating the JAK– sTAT pathway through its receptor CXC-chemokine receptor 2 (CXCR2). Administration of neutralizing antibodies specific for CXCL5 increases insulin sensitivity in both genetic and diet-induced models of obesity. In addition, genetic loss of Cxcr2 improves insulin sensitivity in mice that are fed a high-fat diet. The expression of CXCL5 is controlled through TNF signalling by direct promoter activation, associated with increased occupancy of the CXCL5 promoter by NF-κb111. NAMPT. NAmPT (also known as pre-b cell colony enhancing factor and visfatin) was originally identified as a modulator of b cell differentiation that is expressed in lymphocytes, bone marrow, muscle and liver 112. subsequently, it was reported to be mainly expressed and secreted by adipose tissues (in particular, visceral adipose tissue) through a non-classical secretory pathway 113. It has been reported that NAmPT expression correlates with visceral adiposity in humans and in an experimental model of obesity, and that NAmPT regulates glucose levels in mice, possibly by activating insulin receptors; however, this latter claim was retracted114. High circulating levels of NAmPT are also found in patients with obesity and type 2 diabetes115,116, and in inflammatory bowel disease117, and its expression positively correlates with serum levels of IL-6 and CRP118. NAmPT is thought to function in the NAD biosynthetic pathway and to have an important role in insulin secretion by pancreatic β-cells113. Heterozygous NAmPT-deficient mice have reduced NAD biosynthesis and glucose-stimulated insulin secretion in the pancreas, and this contributes to glucose intolerance113. NAmPT stimulates the p38 mitogen-activated protein kinase (p38 mAPK) and extracellular signal-regulated kinase (ERK) pathways, leading to the production of IL-1β, TNF and IL-6. These factors increase human monocyte chemotactic activity; thus these observations support the idea that NAmPT has a pro-inflammatory role117. Overall, NAmPT seems to be involved in inflammation and pancreatic function. However, further studies are required to understand its physiological functions with regard to obesity-linked metabolic disorders.

Anti-inflammatory adipokines In addition to the numerous pro-inflammatory adipokines described above, adipose tissues also secrete a smaller number of anti-inflammatory factors, such as adiponectin, which has been the subject of intense investigation3,4, and sFRP5, which has been recently identified as an adipokine25. Adiponectin. Adiponectin is almost exclusively synthesized by adipocytes and is present at high levels (3 to 30 μg ml–1) in the blood3. Adiponectin has a collagen-like domain followed by a globular domain that is similar to complement factor C1q. similarly to C1q, adiponectin forms trimers, through collagen-like domain interactions, that can further associate to form stable multimeric oligomers (hexamers and a high molecular weight form)3, and all three forms are detectable in the blood.

Adiponectin levels in the plasma and adipose tissue are decreased in obese individuals compared with lean individuals119. Consistent with this, the production of adiponectin by adipocytes is inhibited by pro-inflammatory factors, such as TNF and IL-6 (Refs 3,4), as well as by hypoxia and oxidative stress120. PPARγ agonists promote adipocyte differentiation, and adiponectin secretion is stimulated in adipocytes by the activation of PPARγ3,4. several clinical observations support an association between adiponectin levels and obesity-linked metabolic dysfunction: first, plasma adiponectin levels negatively correlate with visceral fat accumulation119; second, plasma adiponectin levels are decreased in patients with type 2 diabetes; and third, high adiponectin levels are associated with a lower risk for developing type 2 diabetes3,121. Thus, in view of the pro-inflammatory adipokines discussed previously, adiponectin is unique in that it is expressed at the highest levels by the functional adipocytes that are found in lean organisms but its expression is downregulated in the dysfunctional adipocytes that are associated with obesity. Metabolic actions of adiponectin. much evidence from experimental models indicates that adiponectin protects against obesity-linked metabolic dysfunction. Administration of adiponectin to diabetic mice has been shown to reduce hyperglycaemia by enhancing insulin activity 4 and, when given to obese mice, it increases fatty acid oxidation in muscle tissue and reduces plasma levels of glucose, free fatty acids and triglycerides122. In line with these observations, adiponectin-deficient mice develop exacerbated diet-induced insulin resistance123,124, whereas transgene-mediated overexpression of adiponectin in ob/ob mice improves glucose metabolism independently of weight loss26. The beneficial effects of adiponectin on insulin sensitivity seem to be mediated in part by its ability to activate AmP-activated protein kinase (AmPK) in skeletal muscle and liver 125,126, because AmPK activation leads to an increase in fatty acid oxidation and glucose uptake in muscle tissue, and inhibition of gluconeogenesis in the liver. Adiponectin is thought to mediate AmPK activation through interactions with its cell surface receptors: adiponectin receptor 1 and adiponectin receptor 2 (Ref. 127). Accordingly, adiponectin receptor 1 deficiency results in reduced adiponectin-induced AmPK activation, increased glucose production and impaired insulin resistance, whereas adiponectin receptor 2 deficiency causes decreased activity of PPARα signalling pathways and enhanced insulin resistance128. The disruption of both receptors abolishes adiponectin binding and actions, leading to exacerbation of glucose intolerance. In skeletal muscle cells, adiponectin was found to increase intracellular Ca2+ concentration and the activities of calcium/calmodulin-dependent protein kinase kinase (CamKK), AmPK and sirtuin 1 (sIRT1), resulting in enhanced expression and activity of PPARγ co-activator 1α (PPARγC1α; also known as PGC1α). This pathway is associated with insulin sensitivity, and thus disruption of adiponectin receptor 1 expression specifically in muscle cells was shown to prevent these adiponectinmediated changes and cause insulin resistance129.

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f o c u s o n m e ta b o l i s m a n d i m m uRneoVlo gy ieW s However, another study reported the opposite phenotype in adiponectin receptor 2-deficient mice, showing that they are resistant to metabolic alterations that are caused by a high-fat diet 130, and a third study showed that deletion of adiponectin receptor 2 attenuates highfat diet-induced insulin resistance, but exacerbates glucose intolerance after long-term exposure to a high-fat diet, presumably owing to the dysfunction of pancreatic β-cells131. Thus, the roles of adiponectin receptors in mediating the metabolic actions of adiponectin in vivo are controversial and incompletely understood. Adiponectin and inflammation. several studies have investigated the association between adiponectin levels and pro-inflammatory markers in various disease settings. Plasma adiponectin levels are negatively correlated with CRP levels in obese or diabetic patients, and low adiponectin levels are associated with higher CRP levels in non-diabetic or healthy subjects3,132. Adiponectindeficient mice have higher levels of Tnf mRNA in adipose tissue and TNF protein in the blood123, and these parameters were restored to normal levels on administration of adiponectin. Transgenic overexpression of adiponectin in ob/ob mice leads to morbid obesity, but there is marked improvement in glucose metabolism, accompanied by a reduction in macrophage numbers in adipose tissue and decreased expression of TNF in fat pads26. similarly, the acute administration of adiponectin to ob/ob mice improves fatty liver disease through suppression of TNF production133. Therefore, it seems that the ability of adiponectin to suppress pro-inflammatory

cytokine production may be an important feature in its ability to reverse metabolic dysfunction. similarly, these anti-inflammatory activities contribute to the protective actions of adiponectin in cardiovascular tissues (BOX 2). Accumulating evidence suggests that adiponectinmediated modulation of macrophage function and phenotype contributes to its role in controlling inflammation. Adiponectin inhibits the transformation of macrophages into foam cells, and reduces intracellular cholesteryl ester content in human macrophages by suppressing the expression of class A scavenger receptors (sR-A)134. It also abrogates LPs-stimulated TNF production by macrophages135 and inhibits Toll-like receptor-mediated NF-κb activation in mouse macrophages136. Furthermore, adiponectin stimulates the production of the anti-inflammatory cytokine IL-10 by human macrophages137. Peritoneal macrophages and adipose tissue stromal vascular fraction cells of adiponectin-deficient mice show increased expression of proinflammatory m1-type markers and decreased expression of anti-inflammatory m2-type markers138. Conversely, the systemic delivery of adiponectin to mice stimulates arginase 1 expression by peritoneal macrophages and stromal vascular fraction cells, and stimulation of cultured macrophages with recombinant adiponectin results in an increase in the levels of m2-type markers and a reduction in ROs generation138. similar to other members of the collectin family, including C1q and surfactant proteins A and D135, adiponectin can bind to apoptotic cells and facilitate their uptake by macrophages139. Accordingly, macrophages in adiponectin-deficient mice display a reduced ability to

Box 2 | Cardiovascular effects of adiponectin

Foam cell A macrophage in the arterial wall that ingests oxidized low-density lipoprotein and assumes a foamy appearance. These cells secrete various substances involved in atherosclerotic plaque growth.

Clinical studies have identified an association between low serum levels of adiponectin and coronary artery disease150, hypertension151, left ventricular hypertrophy152 and a greater risk of myocardial infarction153. Early experimental studies showed that adiponectin reduces tumour necrosis factor (TNF)-stimulated expression of interleukin-8 (IL-8) and vascular endothelial cell adhesion molecules (such as vascular cell adhesion molecule 1 (VCAM1)) through the suppression of nuclear factor-κB (NF-κB) activation, and thus diminishes monocyte attachment154–156. Consistent with these in vitro findings, overexpression of adiponectin inhibits the formation of atherosclerotic lesions and decreases the expression of class A scavenger receptors (SR-A), TNF and VCAM1 in the aorta in a model of atherosclerosis157,158, whereas the ablation of adiponectin leads to augmented atherosclerosis that is associated with increased T cell accumulation in atheratoma159. However, a recent study did not find an association between atherosclerosis and levels of circulating adiponectin, such that in a low-density lipoprotein receptor (LDLR)-deficient mouse model, atherosclerosis was not altered in states of adiponectin deficiency or chronic overexpression160. Related studies have shown that adiponectin also promotes vascular homeostasis through its ability to activate endothelial nitric oxide synthase (eNOS), a key determinant of endothelial cell function. Adiponectin promotes eNOS activation in endothelial cells through AMP-activated protein kinase (AMPK)-dependent phosphorylation of this enzyme161,162. In addition, adiponectin stimulates endothelial cell migration and differentiation to form capillary-like structures, and prevents endothelial cell apoptosis through activation of AMPK signalling161–163. In keeping with these in vitro observations, adiponectin-deficient mice develop hypertension and impaired endothelial cell-dependent vasodilation when fed an atherogenic diet164. Disruption of adiponectin also leads to the enhancement of salt-induced hypertension and the reduction of eNOS expression in the aorta165. Adiponectin suppresses cerebral ischaemia–reperfusion injury166 and promotes the revascularization response to chronic hindlimb ischaemia through activation of the AMPK–eNOS signalling pathway167,168. Finally, recent evidence has shown that adiponectin also promotes the expression of the autacoid prostaglandin I2 (PGI2) by endothelial cells, contributing to the improved vascular function that is attributed to this adipokine169. Adiponectin also inhibits pathological cardiac remodelling following pressure overload or angiotensin II infusion in vivo, at least in part through its ability to activate AMPK signalling in myocytes170,171. Adiponectin protects the heart from detrimental remodelling (such as fibrosis) and heart failure after myocardial infarction172, and a recent study has shown that aldosterone-infused adiponectin-deficient mice show exacerbated diastolic dysfunction173. Of particular interest, the glycosylphosphatidylinositol (GPI)-anchored cell surface glycoprotein T-cadherin has been shown to be required for localizing adiponectin to the lumenal surface of the vascular endothelium174 and for conferring the cardioprotective action of adiponectin175. Overall, adiponectin is a protective adipokine against the development of obesity-linked heart diseases, and it is a molecular link between adipose and cardiovascular tissues.

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ReVieWs clear early apoptotic cells in the peritoneal cavity. because phagocytosis of early apoptotic cells promotes an m2-like phenotype in macrophages140, these data suggest that adiponectin can protect the organism from systemic inflammation at least in part through its ability to function as a collectin protein. Collectin proteins have important roles in suppressing inflammation in the lungs, and a number of studies have recently documented inflammatory lung disorders in adiponectin-deficient mice (BOX 3). similar to C1q and other collectin proteins, adiponectin binds to calreticulin on the cell surface of macrophages 139. Calreticulin and its adaptor protein CD91 act as a coreceptor system for the uptake and removal of apoptotic cells by macrophages. Adiponectin facilitates the uptake of dead cells through a pathway involving calreticulin and CD91, but not adiponectin receptor 1 or 2 (Ref. 139). Overall, adiponectin can modulate macrophage phenotype through multiple mechanisms, but the receptormediated signalling pathways in macrophages that contribute to the anti-inflammatory actions of adiponectin are poorly understood. Furthermore, adiponectin levels are increased, rather than decreased, in a number of chronic inflammatory and autoimmune diseases141. The upregulation of adiponectin in severe inflammatory diseases may represent a compensatory response as it has been shown that increasing adiponectin levels by treatment with a PPARγ agonist ameliorates disease in a mouse model of lupus142. Thus, the clinical significance of adiponectin in the context of inflammatory diseases requires future investigation. SFRP5. we reported in a recent study the identification of sFRP5 as a new adipokine with anti-inflammatory properties that has beneficial effects on metabolic dysfunction25. sFRPs act as soluble modulators that sequester wNT proteins, preventing them from binding to their receptors. sFRP5 is expressed at high levels in mouse white adipose tissue25 but is downregulated in the adipose tissues of various obese rodents, as well as in the visceral adipose tissue of obese individuals with adipose tissue inflammation and insulin resistance. wNT5a, which is antagonized by sFRP5, is upregulated in the fat depots of obese rodents, and the wNT5a/sFRP5 protein expression ratio in adipose tissue is also increased by obesity. wNT5a has previously been implicated in a variety of inflammatory disorders. Box 3 | Adiponectin and inflammatory lung disease A baseline phenotype of adiponectin-deficient mice is emphysema-like dilated airspaces and alveolar macrophage activation176. In addition, adiponectin-deficient mice develop a pulmonary hypertension phenotype that is associated with perivascular inflammation177,178. Obesity is a risk factor for the development of asthma, and micro-pump administration of recombinant adiponectin is reported to reduce allergic lung inflammation in an asthma model of ovalbumin sensitization and challenge179. Little is known about the mechanisms by which adiponectin suppresses inflammation in the lungs. Adiponectin receptor 1 is expressed by lung epithelial cells180, and T-cadherin seems to be required to facilitate the entry of adiponectin into the lungs181. Whereas expression of adiponectin is reduced in subjects who smoke cigarettes, increased levels are found in those with chronic obstructive pulmonary disease180 and high levels of adiponectin are associated with mortality in patients with respiratory failure182.

sFRP5-deficient mice have normal glucose tolerance when kept on a regular diet, but show impaired insulin sensitivity and increased fatty liver disease compared with control mice25. Exacerbation of metabolic dysfunction induced by sFRP5 deficiency is associated with increased accumulation of macrophages and enhanced production of pro-inflammatory cytokines (including TNF and IL-6) in adipose tissues. Of importance, JuN N-terminal kinase 1 (JNK1; also known as mAPK8), a downstream target of non-canonical wNT signalling, is activated in adipose tissues of sFRP5-deficient mice on a highcalorie diet. A series of in vitro experiments indicated that overexpression of sFRP5 inhibits wNT5a-stimulated phosphorylation of JNK1 in adipocytes, and similarly blocks wNT5a-induced JNK1 activation and the subsequent induction of pro-inflammatory cytokine production in macrophages. Furthermore, deletion of JNK1 in sFRP5-deficient mice reverses the impaired insulin sensitivity and enhanced adipose tissue inflammation observed in sFRP5-deficient mice. Thus, sFRP5 deficiency exacerbates obesity-induced adipose tissue inflammation and metabolic dysfunction through activation of JNK1 in adipose tissue, and this is consistent with the previously described role for JNK1 in the regulation of insulin resistance and inflammation96,143–145. Notably, systemic administration of sFRP5 to obese mice improved metabolic parameters, such as insulin resistance and fatty liver disease. Taken together, these observations indicate that the balance between sFRP5 and wNT5a in adipose tissue has an important role in the regulation of JNK1 activity in adipocytes and adipose tissue macrophages, thereby modulating inflammation and metabolic function. Thus, sFRP5 in adipose tissue is a potential target for the control of obesity-linked abnormalities in glucose homeostasis. Future studies are required to address the role of sFRP5 in the regulation of obesity-linked inflammatory disorders, including atherosclerosis and ischaemic heart disease.

Concluding remarks Adipose tissues can influence and communicate with many other organs, including the brain, heart, vasculature, liver and muscle, through the production of various secretory factors or adipokines. Adipokines have both pro-inflammatory and anti-inflammatory activities, and the balance between the different factors is crucial for determining homeostasis throughout the body based on nutritional status. when adipocyte dysfunction occurs as a result of adipose tissue expansion (which may be due to over-nutrition or physical inactivity, for example), dysregulation of adipokine production can have local or systemic effects on inflammatory responses, thereby contributing to the initiation and progression of obesity-induced metabolic and cardiovascular complications. Thus, further elucidation of the functions and mechanisms of key adipokines will lead to a better understanding of the pathogenesis of obesity-linked disorders. moreover, therapeutic strategies that counteract the imbalance of pro-inflammatory and anti-inflammatory adipokines could be an attractive and useful means for preventing and/or treating obesity-related metabolic and cardiovascular diseases.

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112. Samal, B. et al. Cloning and characterization of the cDNA encoding a novel human pre-B-cell colonyenhancing factor. Mol. Cell Biol. 14, 1431–1437 (1994). 113. Revollo, J. R. et al. Nampt/PBEF/Visfatin regulates insulin secretion in β cells as a systemic NAD biosynthetic enzyme. Cell. Metab. 6, 363–375 (2007). 114. Fukuhara, A. et al. Visfatin: a protein secreted by visceral fat that mimics the effects of insulin. Science 307, 426–430 (2005). 115. Haider, D. G. et al. Increased plasma visfatin concentrations in morbidly obese subjects are reduced after gastric banding. J. Clin. Endocrinol. Metab. 91, 1578–1581 (2006). 116. El-Mesallamy, H. O., Kassem, D. H., El-Demerdash, E. & Amin, A. I. Vaspin and visfatin/Nampt are interesting interrelated adipokines playing a role in the pathogenesis of type 2 diabetes mellitus. Metabolism 60, 63–70 (2011). 117. Moschen, A. R. et al. Visfatin, an adipocytokine with proinflammatory and immunomodulating properties. J. Immunol. 178, 1748–1758 (2007). 118. Oki, K., Yamane, K., Kamei, N., Nojima, H. & Kohno, N. Circulating visfatin level is correlated with inflammation, but not with insulin resistance. Clin. Endocrinol. 67, 796–800 (2007). 119. Ryo, M. et al. Adiponectin as a biomarker of the metabolic syndrome. Circ. J. 68, 975–981 (2004). 120. Hosogai, N. et al. Adipose tissue hypoxia in obesity and its impact on adipocytokine dysregulation. Diabetes 56, 901–911 (2007). 121. Li, S., Shin, H. J., Ding, E. L. & van Dam, R. M. Adiponectin levels and risk of type 2 diabetes: a systematic review and meta-analysis. JAMA 302, 179–188 (2009). 122. Fruebis, J. et al. Proteolytic cleavage product of 30-kDa adipocyte complement-related protein increases fatty acid oxidation in muscle and causes weight loss in mice. Proc. Natl Acad. Sci. USA 98, 2005–2010 (2001). 123. Maeda, N. et al. Diet-induced insulin resistance in mice lacking adiponectin/ACRP30. Nature Med. 8, 731–737 (2002). This study shows that adiponectin deficiency contributes to the development of diet-induced insulin resistance. 124. Nawrocki, A. R. et al. Mice lacking adiponectin show decreased hepatic insulin sensitivity and reduced responsiveness to peroxisome proliferator-activated receptor γ agonists. J. Biol. Chem. 281, 2654–2660 (2006). 125. Tomas, E. et al. Enhanced muscle fat oxidation and glucose transport by ACRP30 globular domain: acetyl-CoA carboxylase inhibition and AMP-activated protein kinase activation. Proc. Natl Acad. Sci. USA 99, 16309–16313 (2002). 126. Yamauchi, T. et al. Adiponectin stimulates glucose utilization and fatty-acid oxidation by activating AMPactivated protein kinase. Nature Med. 8, 1288–1295 (2002). 127. Yamauchi, T. et al. Cloning of adiponectin receptors that mediate antidiabetic metabolic effects. Nature 423, 762–769 (2003). 128. Yamauchi, T. et al. Targeted disruption of AdipoR1 and AdipoR2 causes abrogation of adiponectin binding and metabolic actions. Nature Med. 13, 332–339 (2007). This study reports the molecular cloning and characterization of adiponectin receptors 1 and 2. 129. Iwabu, M. et al. Adiponectin and AdipoR1 regulate PGC-1α and mitochondria by Ca2+ and AMPK/SIRT1. Nature 464, 1313–1319 (2010). 130. Bjursell, M. et al. Opposing effects of adiponectin receptors 1 and 2 on energy metabolism. Diabetes 56, 583–593 (2007). 131. Liu, Y. et al. Deficiency of adiponectin receptor 2 reduces diet-induced insulin resistance but promotes type 2 diabetes. Endocrinology 148, 683–692 (2007). 132. Ouchi, N. et al. Reciprocal association of C-reactive protein with adiponectin in blood stream and adipose tissue. Circulation 107, 671–674 (2003). 133. Xu, A. et al. The fat-derived hormone adiponectin alleviates alcoholic and nonalcoholic fatty liver diseases in mice. J. Clin. Invest. 112, 91–100 (2003). 134. Ouchi, N. et al. Adipocyte-derived plasma protein, adiponectin, suppresses lipid accumulation and class A scavenger receptor expression in human monocytederived macrophages. Circulation 103, 1057–1063 (2001).

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f o c u s o n m e ta b o l i s m a n d i m m uRneoVlo gy ieW s 135. Yokota, T. et al. Adiponectin, a new member of the family of soluble defense collagens, negatively regulates the growth of myelomonocytic progenitors and the functions of macrophages. Blood 96, 1723–1732 (2000). 136. Yamaguchi, N. et al. Adiponectin inhibits Toll-like receptor family-induced signaling. FEBS Lett. 579, 6821–6826 (2005). 137. Kumada, M. et al. Adiponectin specifically increased tissue inhibitor of metalloproteinase-1 through interleukin-10 expression in human macrophages. Circulation 109, 2046–2049 (2004). 138. Ohashi, K. et al. Adiponectin promotes macrophage polarization toward an anti-inflammatory phenotype. J. Biol. Chem. 285, 6153–6160 (2010). 139. Takemura, Y. et al. Adiponectin modulates inflammatory reactions via calreticulin receptordependent clearance of early apoptotic bodies. J. Clin. Invest. 117, 375–386 (2007). This study shows that adiponectin promotes the clearance of apoptotic cells by macrophages, thereby modulating inflammatory responses. 140. Savill, J., Dransfield, I., Gregory, C. & Haslett, C. A blast from the past: clearance of apoptotic cells regulates immune responses. Nature Rev. Immunol. 2, 965–975 (2002). 141. Fantuzzi, G. Adiponectin and inflammation: consensus and controversy. J. Allergy Clin. Immunol. 121, 326–330 (2008). 142. Aprahamian, T. et al. The peroxisome proliferatoractivated receptor γ agonist rosiglitazone ameliorates murine lupus by induction of adiponectin. J. Immunol. 182, 340–346 (2009). 143. Solinas, G. et al. JNK1 in hematopoietically derived cells contributes to diet-induced inflammation and insulin resistance without affecting obesity. Cell. Metab. 6, 386–397 (2007). 144. Vallerie, S. N., Furuhashi, M., Fucho, R. & Hotamisligil, G. S. A predominant role for parenchymal c-Jun amino terminal kinase (JNK) in the regulation of systemic insulin sensitivity. PLoS ONE 3, e3151 (2008). 145. Hirosumi, J. et al. A central role for JNK in obesity and insulin resistance. Nature 420, 333–336 (2002). 146. Pasarica, M. et al. Reduced adipose tissue oxygenation in human obesity: evidence for rarefaction, macrophage chemotaxis, and inflammation without an angiogenic response. Diabetes 58, 718–725 (2009). 147. Ye, J., Gao, Z., Yin, J. & He, Q. Hypoxia is a potential risk factor for chronic inflammation and adiponectin reduction in adipose tissue of ob/ob and dietary obese mice. Am. J. Physiol. Endocrinol. Metab. 293, E1118–E1128 (2007). 148. Rupnick, M. A. et al. Adipose tissue mass can be regulated through the vasculature. Proc. Natl Acad. Sci. USA 99, 10730–10735 (2002). 149. Nishimura, S. et al. Adipogenesis in obesity requires close interplay between differentiating adipocytes, stromal cells, and blood vessels. Diabetes 56, 1517–1526 (2007). 150. Sattar, N. et al. Adiponectin and coronary heart disease: a prospective study and meta-analysis. Circulation 114, 623–629 (2006).

151. Iwashima, Y. et al. Hypoadiponectinemia is an independent risk factor for hypertension. Hypertension 43, 1318–1323 (2004). 152. Hong, S. J., Park, C. G., Seo, H. S., Oh, D. J. & Ro, Y. M. Associations among plasma adiponectin, hypertension, left ventricular diastolic function and left ventricular mass index. Blood Press 13, 236–242 (2004). 153. Pischon, T. et al. Plasma adiponectin levels and risk of myocardial infarction in men. JAMA 291, 1730–1737 (2004). 154. Ouchi, N. et al. Novel modulator for endothelial adhesion molecules: adipocyte-derived plasma protein adiponectin. Circulation 100, 2473–2476 (1999). 155. Kobashi, C. et al. Adiponectin inhibits endothelial synthesis of interleukin-8. Circ. Res. 97, 1245–1252 (2005). 156. Ouchi, N. et al. Adiponectin, an adipocyte-derived plasma protein, inhibits endothelial NF-κB signaling through a cAMP-dependent pathway. Circulation 102, 1296–1301 (2000). 157. Okamoto, Y. et al. Adiponectin reduces atherosclerosis in apolipoprotein E-deficient mice. Circulation 106, 2767–2770 (2002). 158. Yamauchi, T. et al. Globular adiponectin protected ob/ob mice from diabetes and ApoE-deficient mice from atherosclerosis. J. Biol. Chem. 278, 2461–2468 (2003). 159. Okamoto, Y. et al. Adiponectin inhibits the production of CXC receptor 3 chemokine ligands in macrophages and reduces T-lymphocyte recruitment in atherogenesis. Circ. Res. 102, 218–225 (2008). 160. Nawrocki, A. R. et al. Lack of association between adiponectin levels and atherosclerosis in mice. Arterioscler. Thromb. Vasc. Biol. 30, 1159–1165 (2010). 161. Ouchi, N. et al. Adiponectin stimulates angiogenesis by promoting cross-talk between AMP-activated protein kinase and Akt signaling in endothelial cells. J. Biol. Chem. 279, 1304–1309 (2004). 162. Chen, H., Montagnani, M., Funahashi, T., Shimomura, I. & Quon, M. J. Adiponectin stimulates production of nitric oxide in vascular endothelial cells. J. Biol. Chem. 278, 45021–45026 (2003). 163. Kobayashi, H. et al. Selective suppression of endothelial cell apoptosis by the high molecular weight form of adiponectin. Circ. Res. 94, e27–e31 (2004). 164. Li, R. et al. Adiponectin improves endothelial function in hyperlipidemic rats by reducing oxidative/nitrative stress and differential regulation of eNOS/iNOS activity. Am. J. Physiol. Endocrinol. Metab. 293, E1703–E1708 (2007). 165. Ohashi, K. et al. Adiponectin replenishment ameliorates obesity-related hypertension. Hypertension 47, 1108–1116 (2006). 166. Nishimura, M. et al. Adiponectin prevents cerebral ischemic injury through endothelial nitric oxide synthase dependent mechanisms. Circulation 117, 216–223 (2008). 167. Shibata, R. et al. Adiponectin stimulates angiogenesis in response to tissue ischemia through stimulation of AMP-activated protein kinase signaling. J. Biol. Chem. 279, 28670–28674 (2004).

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168. Kondo, M. et al. Caloric restriction stimulates revascularization in response to ischemia via adiponectin-mediated activation of endothelial nitricoxide synthase. J. Biol. Chem. 284, 1718–1724 (2009). 169. Ohashi, K. et al. Adiponectin promotes revascularization of ischemic muscle through a cyclooxygenase 2-dependent mechanism. Mol. Cell Biol. 29, 3487–3499 (2009). 170. Shibata, R. et al. Adiponectin-mediated modulation of hypertrophic signals in the heart. Nature Med. 10, 1384–1389 (2004). 171. Liao, Y. et al. Exacerbation of heart failure in adiponectin-deficient mice due to impaired regulation of AMPK and glucose metabolism. Cardiovasc. Res. 67, 705–713 (2005). 172. Shibata, R. et al. Adiponectin protects against the development of systolic dysfunction following myocardial infarction. J. Mol. Cell Cardiol. 42, 1065–1074 (2007). 173. Sam, F. et al. Adiponectin deficiency, diastolic dysfunction, and diastolic heart failure. Endocrinology 151, 322–331 (2010). 174. Denzel, M. S. et al. Adiponectin deficiency limits tumor vascularization in the MMTV-PyV-mT mouse model of mammary cancer. Clin. Cancer Res. 15, 3256–3264 (2009). 175. Denzel, M. S. et al. T-cadherin is critical for adiponectin-mediated cardioprotection in mice. J. Clin. Invest. 120, 4342–4352 (2010). 176. Summer, R. et al. Alveolar macrophage activation and an emphysema-like phenotype in adiponectin-deficient mice. Am. J. Physiol. Lung Cell. Mol. Physiol. 294, L1035–L1042 (2008). 177. Summer, R. et al. Adiponectin deficiency: a model of pulmonary hypertension associated with pulmonary vascular disease. Am. J. Physiol. Lung Cell. Mol. Physiol. 297, L432–L438 (2009). 178. Nakagawa, Y., Kishida, K., Kihara, S., Funahashi, T. & Shimomura, I. Adiponectin ameliorates hypoxiainduced pulmonary arterial remodeling. Biochem. Biophys. Res. Commun. 382, 183–188 (2009). 179. Shore, S. A., Terry, R. D., Flynt, L., Xu, A. & Hug, C. Adiponectin attenuates allergen-induced airway inflammation and hyperresponsiveness in mice. J. Allergy Clin. Immunol. 118, 389–395 (2006). 180. Miller, M., Cho, J. Y., Pham, A., Ramsdell, J. & Broide, D. H. Adiponectin and functional adiponectin receptor 1 are expressed by airway epithelial cells in chronic obstructive pulmonary disease. J. Immunol. 182, 684–691 (2009). 181. Zhu, M. et al. Impact of adiponectin deficiency on pulmonary responses to acute ozone exposure in mice. Am. J. Respir. Cell. Mol. Biol. 43, 487–497 (2010). 182. Walkey, A. J. et al. Plasma adiponectin and mortality in critically ill subjects with acute respiratory failure. Crit. Care Med. 38, 2329–2334 (2010).

Acknowledgements

The authors are funded by US National Institutes of Health grants (AG34972, HL86785, AG15052 and HL81587).

Competing interests statement

The authors declare no competing financial interests.

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REVIEWS

Type 2 diabetes as an inflammatory disease Marc Y. Donath* and Steven E. Shoelson‡

Abstract | Components of the immune system are altered in obesity and type 2 diabetes (T2D), with the most apparent changes occurring in adipose tissue, the liver, pancreatic islets, the vasculature and circulating leukocytes. These immunological changes include altered levels of specific cytokines and chemokines, changes in the number and activation state of various leukocyte populations and increased apoptosis and tissue fibrosis. Together, these changes suggest that inflammation participates in the pathogenesis of T2D. Preliminary results from clinical trials with salicylates and interleukin‑1 antagonists support this notion and have opened the door for immunomodulatory strategies for the treatment of T2D that simultaneously lower blood glucose levels and potentially reduce the severity and prevalence of the associated complications of this disease. Insulin resistance A pathological condition in which insulin becomes less effective at lowering blood glucose levels.

Endoplasmic reticulum stress (ER stress). A response by the ER that results in the disruption of protein folding and the accumulation of unfolded proteins in the ER.

Lipotoxicity The toxic effects of elevated levels of free fatty acids. These detrimental effects may be functional and reversible, or may lead to cell death.

*Clinic of Endocrinology, Diabetes and Metabolism, University Hospital Basel, CH‑4031 Basel, Switzerland. ‡ Joslin Diabetes Center, Harvard Medical School, One Joslin Place, Boston, Massachusetts 02215, USA. e‑mails: [email protected]; steven.shoelson@joslin. harvard.edu doi:10.1038/nri2925 Published online 14 January 2011

Major advances have been made in understanding the mechanisms that are involved in the pathogenesis of type 2 diabetes (T2D)1–5. A decrease in insulin-stimulated glucose uptake (insulin resistance) is associated with obesity, ageing and inactivity. The pancreatic islets respond to insulin resistance by enhancing their cell mass and insulin secretory activity. However, when the functional expansion of islet β-cells fails to compensate for the degree of insulin resistance, insulin deficiency and ultimately T2D develop. The onset of T2D leads in turn to the development of its long-term consequences: macrovascular complications (including atherosclerosis and amputations) and microvascular complications (including retinopathy, nephropathy and neuropathy). Insulin resistance is typically present throughout the progression from prediabetes to the later stages of overt T2D. By contrast, the onset of T2D and its progression are largely determined by the progressive failure of β-cells to produce sufficient levels of insulin. Interestingly, many insulin-resistant individuals do not become diabetic, because their β-cells are able to compensate for the increased demand for insulin. Only about one-third of obese, insulin-resistant individuals actually develop chronic hyperglycaemia and T2D. The reasons for this heterogeneity are incompletely understood, although genetics and epigenetics probably have roles. The leading hypothesized mechanisms to explain insulin resistance and islet β-cell dysfunction in T2D have been oxidative stress, endoplasmic reticulum stress (ER stress), amyloid deposition in the pancreas, ectopic

lipid deposition in the muscle, liver and pancreas, and lipotoxicity and glucotoxicity (BOX 1). All of these stresses can be caused by overnutrition6–10, although it has been difficult to determine which mechanism is the most important in each tissue and in each model or individual with T2D. It is noteworthy, however, that each of these cellular stresses is also thought to either induce an inflammatory response or to be exacerbated by or associated with inflammation11–15. This Review examines recent evidence that implicates the pathological involvement of the immune system in T2D, dissects potential underlying mechanisms and concludes that obesity is associated with inflammation and that the pathogenesis of T2D can be viewed as an autoinflammatory disease. We also review the recent results from clinical trials using anti-inflammatory drugs to lower blood glucose levels in patients with T2D.

Evidence for T2D as an inflammatory disease Circulating inflammatory factors in obesity and T2D. Cross-sectional and prospective studies have described elevated circulating levels of acute-phase proteins (such as C-reactive protein (CRP), haptoglobin, fibrinogen, plasminogen activator inhibitor and serum amyloid A) and sialic acid, as well as cytokines and chemokines, in patients with T2D16–19. Furthermore, elevated levels of interleukin-1β (IL-1β), IL-6 and CRP are predictive of T2D17,20. Similarly, the serum concentration of IL-1 receptor antagonist (IL-1RA) is elevated in obesity and prediabetes21, with an accelerated increase in IL-1RA levels before the onset of T2D19,22,23. The expression

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f o c u S o n M E ta b o l I S M a n d I M M uRnEoVlo gy IEW S Glucotoxicity The toxic effects of hyperglycaemia. These detrimental effects may be functional and reversible, or may lead to cell death.

Autoinflammatory disease A disease resulting from an attack by the innate immune system on the body’s own tissues. By contrast, autoimmune diseases are caused by the pathological activation of adaptive immune responses. Autoimmune and autoinflammatory diseases have some characteristics in common, including shared effector mechanisms.

M1‑type macrophage A macrophage that is activated by Toll-like receptor ligands (such as lipopolysaccharide) and interferon-γ, and that expresses inducible nitric oxide synthase, which generates nitric oxide.

of IL-1RA is induced by IL-1β and reflects the body’s response to counterbalance increased IL-1β activity. Of particular interest is the increased CRP level, which is currently the best epidemiological biomarker for T2D-associated cardiovascular disease16–19. Most proinflammatory factors that are present at high levels in the blood of patients with T2D are IL-1 dependent, and blocking IL-1 activity has been shown to reduce their concentrations24–27 (see below). Elevated levels of circulating IL-1β, IL-6 and acutephase proteins in T2D may reflect the activation of innate immune cells by increased nutrient concentrations, but the levels of these inflammatory markers may not necessarily reflect the degree of inflammation in individual tissues. For example, the total volume of the pancreatic islets is small compared with the blood volume. Thus, even a high level of islet inflammation is unlikely to demonstrably contribute to the circulating levels of these inflammatory factors. By contrast, the mass of adipose tissue in obese individuals is large, and can make up over half of the body weight in morbid obesity. The liver is also a relatively large organ and is the site for IL-6-induced production of CRP. Thus, the adipose tissue and the liver may disproportionately contribute to the circulating levels of inflammatory markers. Consistent with this, the circulating levels of inflammatory factors in obese individuals with prediabetes are similar to the levels in those with overt diabetes. Furthermore, the levels of circulating CRP or

Box 1 | Potential pathogenic mechanisms in type 2 diabetes Several mechanisms have been described to explain impaired insulin secretion and function in type 2 diabetes (T2D). Interestingly, each of these mechanisms, except for amyloid deposition, is thought to have a role in both insulin resistance and islet β‑cell failure. Although listed separately, these mechanisms are strongly linked and contribute to tissue inflammation. Glucotoxicity. Hyperglycaemia per se impairs insulin secretion116,117 and induces β‑cell death81. Of note, small changes in glucose concentrations, which are apparent years before overt T2D, are toxic for β‑cells7. In vivo studies performed in patients with type 1 diabetes118 and in rat models of the disease119 have demonstrated that chronic hyperglycaemia also promotes insulin resistance. Lipotoxicity. Similar to glucose, long‑chain free fatty acid levels in the plasma are often increased in states of insulin resistance, impairing β‑cell secretory function120,121 and inducing β‑cell apoptosis122,123 and insulin resistance124. Interestingly, saturated fatty acids seem to be particularly toxic, whereas mono‑unsaturated fatty acids are protective, and the combination of elevated glucose and free fatty acids has a potentiating effect on T2D (glucolipotoxicity)125. Lipotoxicity may act through the circulation or locally by ectopic tissue lipid deposition126. Oxidative stress. Several cell stressors (including glucose in particular) lead to the generation of reactive oxygen species127. β‑cells have very low levels of antioxidative enzymes and are therefore particularly vulnerable to oxidative stress. Oxidative stress is also central to the development of insulin resistance128,129. Endoplasmic reticulum stress. In response to insulin resistance, β‑cells dramatically increase insulin production. The flux of proteins through the endoplasmic reticulum (ER) of β‑cells is quite high under physiological conditions and any further increase is expected to tilt the balance towards ER stress10,130,131. ER stress is also thought to have a role in insulin resistance132. Amyloid deposition. Islet amyloid deposits are found in the islets of most patients with T2D. However, it remains unclear whether aggregation of human islet amyloid polypeptide is a cause or consequence of β‑cell failure133.

IL-6 do not predict the efficacy of anti-inflammatory treatments directed towards insulin secretion or insulin resistance25,28. In summary, degrees of inflammation vary within individuals and between tissues, and circulating levels of inflammatory factors may not reflect the severity of inflammation within a specific tissue. Evidence for inflammation in insulin-sensitive tissues and islets. The production of tumour necrosis factor (TNF) by cells in the adipose tissue of obese rodents provided early evidence of tissue inflammation in the pathogenesis of insulin resistance and T2D29 (FIG. 1). Some animal studies30 and several clinical trials using TNF blockade have failed to demonstrate beneficial effects on glucose metabolism31–36 (see below). However, a few small studies conducted with obese individuals or patients being treated for alternative conditions suggest that TNF blockers may alter insulin sensitivity or glycaemic parameters, indicating that further prospective studies may be warranted37–40. Despite the ongoing controversy over whether TNF blockade improves glycaemic parameters in patients with T2D, the identification of adipose tissue-derived TNF has been highly instructive. The source of TNF in adipose tissue was originally thought to be the adipocytes themselves in response to obesity. However, this notion has been revised by the discovery of macrophages in adipose tissue, and the finding that obesity results in increased numbers of macrophages and changes in the activation status of these cells. We now appreciate that adipose tissue macrophages produce a significant proportion of the inflammatory factors that are upregulated by obesity 41,42. The increase in the number of macrophages in adipose tissue largely correlates with the degree of obesity. Initial studies are beginning to characterize the macrophage subtypes in the adipose tissue under different conditions, including in lean or obese animals and individuals43,44, following rapid weight loss45, and in lipodystrophy (a condition of adipose tissue loss that is paradoxically associated with insulin resistance and T2D)46. Similar to resident macrophages in other tissues, adipose tissue macrophages adapt to their environment; for example, their genomic and proteomic expression profiles are highly distinct from those of resident macrophages in other tissues (H. Shapiro, J. Lee and S.E.S., unpublished observations). Furthermore, the genomic profile of adipose tissue macrophages from lean mice differed from the profile of macrophages that had been recently recruited to adipose tissue during the induction of diet-induced obesity. The recently recruited macrophages have a classically activated, pro-inflammatory phenotype (M1-type macrophages; expressing TNF and inducible nitric oxide synthase) compared with the alternatively activated phenotype (M2-type macrophages; expressing yM1 (also known as CHI3L3), arginase 1 and IL-10) of the resident adipose tissue macrophages from lean mice43. The authors proposed that during the progression to obesity, adipose tissue is associated with a phenotypic switch in macrophages from a M2 to a M1 phenotype and that these M1-type macrophages contribute to the

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REVIEWS 2CPETGCVKEKUNGVU

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2TQKPȯCOOCVQT[ E[VQMKPGUCPFEJGOQMKPGU +.β60(%%.%%.%:%. Mast cell Macrophage 1DGUGCFKRQUGVKUUWG

Figure 1 | Development of inflammation in type 2 diabetes. Excessive levels of nutrients, including glucose and free fatty acids, will stress0CVWTG4GXKGYU^+OOWPQNQI[ the pancreatic islets and insulin‑sensitive tissues such as adipose tissue (and the liver and muscle, not shown), leading to the local production and release of cytokines and chemokines. These factors include interleukin‑1β (IL‑1β), tumour necrosis factor (TNF), CC‑chemokine ligand 2 (CCL2), CCL3 and CXC‑chemokine ligand 8 (CXCL8). Furthermore, production of IL‑1 receptor antagonist (IL‑1RA) by β‑cells is decreased. As a result, immune cells will be recruited and contribute to tissue inflammation. The release of cytokines and chemokines from the adipose tissues into the circulation promotes inflammation in other tissues, including the islets.

M2‑type macrophage A macrophage that is stimulated by interleukin-4 (IL-4) or IL-13 and that expresses arginase 1, the mannose receptor CD206 and the IL-4 receptor α-chain.

KitW–sh/W–sh mice The KitW–sh (or sash) mutation abolishes KIT expression in mast cells, and the mutant mice are deficient in mast cells.

Insulitis Inflammation of the pancreatic islets during the progression of diabetes. Insulitis in type 1 diabetes is caused by autoimmunity and in type 2 diabetes by metabolic stressors such as hyperglycaemia and elevated levels of free fatty acids.

development of insulin resistance47. But by comparing resident adipose tissue macrophages from lean mice with recently recruited immature macrophages from obese mice, these studies compared kinetically distinct populations, and this alone might account for their conclusions. A recent study by Shaul et al.44 concluded that resident CD11c+ adipose tissue macrophages in the fat pads of obese mice have a mixed M1/M2 phenotype that did not seem to be pro-inflammatory. Therefore, the precise phenotype of adipose tissue macrophages remains to be clarified, and most importantly, we need to know which macrophage phenotype (if any) is related to the development of insulin resistance. Although macrophages are the most abundant leukocyte population in expanding adipose tissue, other immune cell types are present and their numbers and activities may change during the transition from lean to obese. For example, mast cells were shown to accumulate in subcutaneous adipose tissue during the induction of obesity in mice48. Moreover, obese mast-cell-deficient KitW–sh/W–sh mice and obese mice treated with ketotifen, which blocks mast cell function, had improved insulin resistance compared with wild-type mice or untreated control mice, respectively 48. However, the pathological role of mast cells in obesity and T2D remains to be clarified, as both of these approaches led to substantial weight loss relative to the control mice, which makes it difficult to distinguish the potential mechanisms, as weight loss itself promotes insulin sensitivity.

Cells of the adaptive immune system are also present in adipose tissue and may contribute to metabolic disruption. T cells generally accumulate in obese adipose tissue in parallel with macrophages49, although changes in the relative numbers and activities of CD4+ and CD8+ T cells and of T helper 1 (TH1), TH2 and forkhead box P3 (FOXP3)+ regulatory T (TReg) cells occur asynchronously and with distinct kinetics. In general, CD8+ T cells and TH1 cells are thought to contribute to the insulin resistance phenotype, whereas TReg cells and TH2 cells tend to counter it 50,51. In this scenario, the macrophages would be the effector cells under the control of the T cells. One of the more interesting of the unanswered questions is whether the T cells recognize antigens that are present in the adipose tissue and, if so, what these antigens are. TReg cells are of special interest owing to their important role in the maintenance of self-tolerance and the suppression of potentially autoreactive T cells; through these functions they prevent the development of autoimmunity in experimental models in both mice and humans52,53. The number of TReg cells in the adipose tissue of lean mice is unusually high at ~50% of the CD4+ T cell compartment, but this number decreases dramatically in proportion with increasing obesity 50. This contrasts with the increase in macrophage number that accompanies obesity, and suggests a potential relationship between these two cell populations in adipose tissue. Furthermore, adipose tissue TReg cells express (and are thought to secrete) an unusually high amount of the anti-inflammatory cytokine IL-10, which in lean mice could help to suppress adipose tissue inflammation50. Targeted induction of TReg cells improves circulating glucose levels and insulin sensitivity in obese mice, reduces macrophage numbers and TNF levels in adipose tissue, and decreases pancreatic islet hyperplasia50,51. Tissue inflammation has also been detected in the islets of patients with T2D, along with increased levels of cytokines and chemokines54–56. Of note, patients with T2D and every animal model of T2D investigated to date display immune cell infiltration of the islets56. Islet tissue sections from patients with T2D also show fibrosis, which is found in conjunction with amyloid deposits, and this also argues for an inflammatory response in islets, as fibrosis is a hallmark of chronic inflammation. An interesting recent report shows that human islet amyloid polypeptide (IAPP) induces the secretion of IL-1β by bone marrow-derived macrophages, suggesting that IAPP may contribute to islet inflammation15. Although the concept of insulitis in T2D is recent 14, it is well established in type 1 diabetes and is considered to be a characteristic of the disease. The precise aetiology of the insulitis in both types of diabetes remains to be fully understood, but differences are known to exist; for example, the insulitis in type 1 diabetes is driven by an autoimmune-mediated process, whereas in T2D it is now thought to be due to autoinflammation. However, a common final effector pathway involving IL-1β seems to be activated in both types of diabetes12 (see below). Furthermore, additional overlap exists between both diseases (TABLE 1) and in many cases a clear classification is not feasible, arguing for an involvement of the immune system not only in type 1 diabetes but also in T2D.

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f o c u S o n M E ta b o l I S M a n d I M M uRnEoVlo gy IEW S Table 1 | Comparison of characteristics associated with type 1 and type 2 diabetes* Age of onset

Type 1 diabetes

Type 2 diabetes

Refs

Mainly young but can occur at all ages

Usually associated with ageing but prevalence is increasing in younger individuals

Insulin deficiency Absolute

Relative to the prevailing resistance to insulin

Risk factors

Genetics , obesity, insulin resistance

Genetics , obesity, insulin resistance

Insulitis

Autoimmune

Autoinflammatory

Autoantibodies

Present in 85–90%

May be present

Treatment

Insulin

Diet and exercise, oral agents such as metformin; insulin recommended early in the treatment

‡

‡

134–136 137 135, 138–140 2,12 134–136 141

*No single clinical feature or diagnostic parameter completely discriminates the two diseases142. ‡Genetics are relevant to both type 1 and 2 diabetes, but different susceptibility genes have been identified in different families.

Inflammatory mechanisms in T2D The studies discussed above support the hypothesis that inflammation has a role in the pathogenesis of T2D. Here, we discuss some of potential mechanisms involved in the inflammatory response in this disease. Hypoxia. It has been proposed that hypoxia in expanding adipose tissue may induce an inflammatory response. It is well established in oncology that rapidly growing tissue can expand faster than the vasculature that supports its oxygen and nutrient requirements. Hypoxia ensues as oxygen supplies become limited, and compensatory angiogenesis is induced through the production of various angiogenic factors in an attempt to restore the required levels of oxygen and nutrient delivery 57. Hypoxia and neovascularization are also seen in rodent models of obesity in which the fat mass is rapidly expanding; for example during high-fat feeding 58,59. Furthermore, hypoxia has been observed in human adipose tissue and contributes to adipose tissue dysfunction60,61. Macrophages accumulate at sites of hypoxia or ischaemia, providing a pathological link between adipose tissue expansion and the induction of inflammation. The recruitment of macrophages to hypoxic or ischaemic tissues has been studied in greater detail in tumour growth, wounds and infections, atherogenesis and arthritis62, but the principles seem to be similar for expanding adipose tissue. Hypoxia induces the expression of numerous pro-angiogenic and pro-inflammatory genes in macrophages63, suggesting that the recruited macrophages have an important role in resolving hypoxia, possibly in an attempt to repair damaged tissue.

Ischaemia A condition in which the flow of blood to a tissue or organs is less than normal, and which results in injury to that tissue or organ.

Cell death. Adipocyte expansion beyond oxygen and nutrient requirements also seems to lead to adipocyte cell death. This is readily apparent in mice fed a high-fat diet, as dead adipocytes are located throughout their fat pads64,65, whereas this is not observed in the fat pads of mice fed a normal diet. The most distinguishing feature of the dead adipocytes is that they are located individually and sporadically throughout the fat pads and are surrounded by macrophages to form what are referred to as ‘crown-like structures’ 64,65. There are higher numbers of crown-like structures in the gonadal white adipose tissue of male mice than in the subcutaneous white

adipose tissue. The high proportions of macrophages that are found in crown-like structures suggest that many of the monocytes that are recruited to expanding adipose tissue in obesity are there to remove cellular debris. However, it does not establish that recruited macrophages are causally linked to the development of insulin resistance. In contrast to adipose tissue macrophages, islet macrophages were not detected in the vicinity of necrotic or apoptotic cells56. Furthermore, islet inflammation is an early event in the development of T2D and is apparent in mice after 8 weeks of high-fat feeding56, during which time β-cell function declines but β-cell mass increases without an increase in islet cell death. Therefore, it is unlikely that cell death has an important role in the recruitment of macrophages to the islets. This recruitment may instead be a consequence of islet-derived chemokines that are produced in response to metabolic stress (see below). The NF-κB and JNK pathways. Many of the metabolic stresses that promote insulin resistance and T2D also activate the inflammation- and stress-induced kinases IκB kinase-β (IKKβ) and JuN N-terminal kinase (JNK)1,66,67, suggesting that these kinases may have key roles in the pathogenesis of these conditions. Indeed, IKKβ activates the transcription factor nuclear factor-κB (NF-κB), and obesity induces the expression of NF-κB target genes, such as pro-inflammatory cytokines, in the liver and adipose tissue1,66,67. These cytokines, including TNF, IL-6, and IL-1β, may promote insulin resistance in the tissues where they are produced, such as the liver and adipose tissue, and may also be transported through the circulation to affect more distant sites, including the vessel walls, skeletal and cardiac muscle, the kidneys and circulating leukocytes. The other potentially important kinase, JNK, activates transcription factors such as ELK1, ATF2 (activating transcription factor 2) and JuN, although the potential roles of these JNKresponsive transcription factors in obesity are not well established68. Nevertheless, bone marrow transplant and selective genetic ablation experiments have provided ample evidence to support a role for JNK in the inflammatory response to obesity and the development of insulin resistance (see below).

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REVIEWS

Cachexia Severe weight loss, muscle wasting and debility caused by prolonged disease. It is thought to be mediated through neuroimmunoendocrine interactions.

Leptin A protein hormone that regulates energy intake and expenditure. It is one of the most important adipose-derived hormones and its production correlates with the mass of adipose tissue.

Inflammasome A molecular complex of several proteins that, when activated, results in the production of active caspase 1, which cleaves pro-interleukin-1β (pro-IL-1β) and pro-IL-18 to produce the active cytokines.

In fact, many of the same cytokines that are produced in response to NF-κB activation also activate both JNK and NF-κB in a feed-forward manner. This includes TNF and IL-1β, which activate JNK and NF-κB through the engagement of their specific cellular receptors. Other stimuli that promote insulin resistance and T2D, including free fatty acids (FFAs) and advanced glycation end-products, also act through specific cell surface receptors, such as Toll-like receptors (TLRs) and receptor for advanced glycation endproducts (RAGE)69. All these extracellular stimuli bind cell surface receptors and activate intracellular pathways that converge on both IKKβ–NF-κB and JNK signalling. Bone marrow transplant and selective genetic ablation methods have been used to assess the relative contribution of the JNK and IKKβ–NF-κB signalling pathways in haematopoietic and non-haematopoietic parenchymal cells in obesity-induced insulin resistance, and to identify the main tissue sites involved. The liver and adipose tissue are important sites for the activation of both pathways. In the liver, this activation occurs in both hepatocytes and myeloid cells such as macrophages, and upregulates the production of pro-inflammatory cytokines, including TNF, IL-6 and IL-1β66,67,70–72. Although these pathways are activated in both haematopoietic and non-haematopoietic cells, it is the leukocytes that account for most of the local production of pro- and anti-inflammatory cytokines in the liver and adipose tissue. However, in muscle cells, the activation of IKKβ and NF-κB results in wasting and cachexia through the activation of the E3 ubiquitin ligase TRIM63 (also known as MuRF1)73, whereas in the hypothalamus it seems that the IKKβ–NF-κB pathway affects feeding behaviour and the leptin signalling axis74. Therefore, IKKβ–NF-κB activation in these tissues affects insulin resistance indirectly, through changes in body weight, as opposed to the more direct effects on insulin resistance that result from the activation of this pathway in the liver, adipose tissue and leukocytes. NF-κB is also activated in islet β-cells through the actions of glucose and IL-1β, and inhibition of NF-κB seems to protect β-cells from various insults, including from the effects of glucotoxicity or multiple treatments with low-dose streptozotocin (a natural chemical that is particularly toxic to β-cells)55,75. The NF-κB and JNK pathways are thus activated in multiple tissues in obesity and T2D, and have central roles in promoting tissue inflammation. Accordingly, reducing the activity of these pathways may be of therapeutic benefit (see below). IL-6 and insulin resistance. The roles of IL-6 signalling in insulin resistance have been controversial and at times paradoxical76,77. Concentrations of circulating IL-6 and CRP (the hepatic expression of which is induced by IL-6) are increased in obesity and predict the incidence of T2D in predisposed individuals20. Hepatic and adipose production of IL-6 are thought to promote insulin resistance67,76,78, whereas production of IL-6 by skeletal muscle, especially during intense exercise, is thought to be beneficial77. Analysis of hepatocyte-specific deletion of the IL-6 receptor in mice has added to the controversy, as these mice seem to be protected from both local and systemic insulin resistance79,80.

The IL-1 system as a sensor of metabolic stress. The earliest evidence for an inflammatory process in pancreatic islets arose from the observation that hyperglycaemia induces β-cell apoptosis81. By examining the underlying mechanism, it was shown that high glucose concentrations induce the expression of the pro-apoptotic receptor FAS (also known as CD95) on β-cells82, which is further upregulated by glucose-induced IL-1β production by β-cells55. Therefore, IL-1β and FAS contribute to both the glucose-induced impairment of β-cell secretory function and apoptosis55,83. Additional mechanisms regulate IL-1β expression in islets (FIG. 2). FFAs (such as oleate, palmitate and stearate) stimulate IL-1β secretion and the production of IL-1βdependent pro-inflammatory molecules in cultured human and rodent islets84–86. A combination of moderately increased glucose levels and FFAs was shown to induce an even stronger increase in cytokine production than just FFAs alone85. The underlying mechanisms of ‘nutrient’ (that is, glucose and FFA)-induced activation of IL-1β are complex. FFAs may stimulate the production pro-inflammatory molecules by direct activation of TLR2 and TLR4, which can sense lipids, or indirectly through FFA metabolites such as ceramide86–89. Glucose-induced IL-β production is thought to involve the NOD-, LRR- and pyrin domain-containing 3 (NLRP3; also known as NALP3) inflammasome. High concentrations of glucose induce the dissociation of thioredoxin-interacting protein (TXNIP) from thioredoxin under the influence of reactive oxygen species, allowing binding of TXNIP to the NLRP3 inflammasome. This leads to the activation of caspase 1 and the subsequent processing of pro-IL-1β and release of mature IL-1β90. Whether reactive oxygen species are indispensable in this process remains unclear. β-cells have very low levels of antioxidative enzymes and are therefore particularly vulnerable to oxidative stress; however, activation of the inflammasome in the absence of reactive oxygen species has been shown in patients with chronic granulomatous disease91,92. Interestingly, deposition of amyloid in the islets is a hallmark of T2D, and human IAPP seems to contribute to the induction of IL-1β production in the islets through the NLRP3 inflammasome15. However, the induction of IL-1β secretion by IAPP has only been shown in macrophages, and in vivo amyloid deposition requires prolonged high-fat feeding (for a period of 1 year), whereas the first signs of islet inflammation are apparent after 8 weeks56, indicating that IAPP-mediated IL-1β secretion may be a late event in islet inflammation. It remains possible that the inflammasome may act as a sensor of metabolic danger 93, resulting in IL-1β production and the induction of numerous cytokines and chemokines24,94,95. Therefore, activation of the inflammasome may contribute to the recruitment of immune cells, which can mediate a broad inflammatory response. These initial mechanisms of IL-1β induction may be amplified by a cycle of autoinflammation. Indeed, human islets, particularly purified human β-cells, are very sensitive to IL-1β autostimulation84. This is probably a consequence of the abundant expression of IL-1

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f o c u S o n M E ta b o l I S M a n d I M M uRnEoVlo gy IEW S Glucose

FFAs TLR2 or TLR4

βEGNN TXR

TXR

MYD88

TXNIP Inflammasome

CCL2, CCL3 CXCL8

Recruitment

TXNIP 0(κ$

NLRP3

Inflammasome ASC

Amyloid MYD88

Pro-caspase 1 Pro-IL-1β

IL-1R1

Active caspase 1 IL-1β

IL-1β

/CETQRJCIG

Figure 2 | Interleukin‑1β‑induced inflammation in islets of patients with type 2 diabetes. High concentrations of glucose promote β‑cell production of interleukin‑1β (IL‑1β) through the dissociation of thioredoxin‑interacting 0CVWTG4GXKGYU^+OOWPQNQI[ protein (TXNIP) from its inhibitor thioredoxin (TXR), resulting in activation of the NOD‑, LRR‑ and pyrin domain‑ containing 3 (NLRP3) inflammasome, activation of caspase 1 and processing of pro‑IL‑1β into its mature form. IL‑1β induces the production of a wide range of cytokines and chemokines such as CC‑chemokine ligand 2 (CCL2), CCL3 and CXC‑chemokine ligand 8 (CXCL8) through nuclear factor‑κB (NF‑κB) activation. This is enhanced by free fatty acid (FFA)‑induced activation of Toll‑like receptor 2 (TLR2) or TLR4 and leads to the recruitment of macrophages. FFAs may also directly activate the NLRP3 inflammasome. Islet‑derived amyloid can activate the recruited macrophages through the NLRP3 inflammasome, increasing IL‑1β production and the vicious cycle of IL‑1β autostimulation through IL‑1 receptor type 1 (IL‑1R1). ASC, apoptosis‑associated speck‑like protein containing a CARD; MYD88, myeloid differentiation primary‑response protein 88.

receptor type 1 (IL-1R1) by these cells. Analysis of IL-1R1 expression in numerous tissues showed that the highest levels were expressed in mouse islets and by the insulinproducing cell line MIN6 compared with 20 other mouse tissues, including immune tissues such as the spleen and thymus85. IL-1β autostimulation of islets can be prevented by reducing NF-κB activity or by blocking IL-1R1 signalling (with IL-1RA, by ligand neutralization or by the genetic elimination of the IL-1R1-associated signalling protein myeloid differentiation primary-response protein 88 (MyD88))84,85. Blocking IL-1R1 signalling also inhibits FFA- and glucose-induced upregulation of IL-1β84,85. Another factor that promotes islet inflammation in T2D is a defect in an anti-inflammatory mechanism. IL-1RA is highly expressed in the endocrine pancreas of non-diabetic individuals but is decreased in the islets of patients with T2D, and this enhances the susceptibility of the β-cells to IL-1β54. The precise mechanisms responsible for this decrease remain to be elucidated but the adipose tissue-derived hormone leptin might be involved, as it decreases IL-1RA expression in human islets in vitro54. Therefore, the IL-1 system is an integral part of the response to metabolic disturbance and IL-1 antagonism has therapeutic potential (see below).

Chemokines. Adipocytes may secrete chemokines such as CC-chemokine ligand 2 (CCL2; also known as MCP1), which recruits monocytes. Consistent with this hypothesis, the expression of CCL2 is increased in the adipose tissue of obese rodents and humans96–99. Mice with a targeted deletion of either Ccl2 or its receptor CC-chemokine receptor 2 (Ccr2) have decreased numbers of macrophages in adipose tissue41,98, whereas transgenic upregulation of Ccl2 expression in adipocytes results in increased macrophage numbers 100. However, the metabolic consequences of diminished signalling through the CCL2–CCR2 axis are relatively small, possibly owing to the redundancy between chemokines that recruit monocytes101. In addition to CCL2, the expression of CCL3, CCL6, CCL7, CCL8 and CCL9 is increased in adipocytes from mice fed a high-fat diet compared with mice fed a normal diet, suggesting that these chemokines could also have a role in monocyte recruitment 101. These findings are consistent with a potential increase in chemokine-mediated recruitment of monocytes to expanding adipose tissue, although other chemoattractants such as leukotrienes could also be involved. Islet cells can also produce a wide range of chemokines in the context of T2D. In vitro treatment of islets with high concentrations of glucose and the saturated fatty acid palmitate increases the production of

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REVIEWS several biologically active chemotactic factors (CXCchemokine ligand 8 (CXCL8) and CCL3 in human islets; CXCL1 in mouse islets)56,85. Islets isolated from rodent models of T2D (Goto–Kakizaki rats, high-fatfed mice and Zucker rats) also show increased production of various chemokines, including CXCL1, CCL2 and CCL3 (REFS 26,102). Importantly, the relevance of these findings for humans is supported by evidence for the upregulation of various chemokines in lasercaptured nearly pure β-cells from patients with T2D103. Although most chemokines are produced by β-cells in the islets, some (for example, CXCL8) may also be produced by pancreatic α-cells56. The precise functions of the various chemokines remain to be clarified; however, they have a crucial role in tissue infiltration by immune cells in T2D. Adipokines. Adipokines are hormones that are produced mainly or exclusively by adipocytes. Examples include leptin and adiponectin, both of which have potential immunomodulatory effects. Genetically obese ob/ob mice, which produce a mutated, non-functional form of leptin, show many of the same inflammatory changes as other models of obesity (including diet-induced obese mice), and ob/ob mice become both insulin resistant and diabetic. These results indicate that leptin may not have a particularly important role in obesity-induced inflammation. Adiponectin is considered to be an antiinflammatory and cardioprotective protein. It may exert these effects in several ways; for example, by inducing anti-inflammatory cytokines such as IL-10 and IL-1RA104, through vascular mechanisms including enhancement of nitric oxide bioavailability 105, or by reducing endothelial cell–leukocyte adhesion106. In summary, multiple mechanisms may contribute to inflammation in T2D, some of which are general and others are tissue specific. Thus in the pancreatic islet cells, inflammation may be initiated by direct sensing of excess nutrients, leading to activation of the IL-1 system, whereas in adipose tissue, excess storage of fat causes hypoxia and inflammation. Common downstream mechanisms include the activation of NF-κB and JNK pathways and cytokine and chemokine release, leading to the recruitment of immune cells.

Salsalate A prodrug form of salicylic acid that has fewer side effects than sodium salicylate. Salsalate is approved for use in humans as a source of salicylic acid.

Clinical trials and implications Further evidence for roles of inflammation in T2D comes from clinical studies using either small molecule antiinflammatory approaches or biological agents that target specific pro-inflammatory cytokine pathways to improve parameters of glucose control, such as glycated haemoglobin levels. To date, the most promising approaches include the selective blockade of IL-1R1 activation with either IL-1RA or specific antibodies, and inhibition of the NF-κB pathway with salicylate derivatives such as salsalate. Both approaches seem to lower blood glucose levels and improve β-cell secretory function and insulin sensitivity, as well as reducing evidence of systemic inflammation25,107. Of note, the improvement in insulin secretion lasted 39 weeks following the withdrawal of IL-1RA treatment 108. Similarly, 3 months after a single

injection with an IL-1β-specific antibody, individuals with T2D showed sustained reductions in glycated haemoglobin levels and an improvement in insulin secretion by β-cells27. This probably reflects the interruption of IL-1β autoinduction84. These proof-of-concept studies validate the potential approach of targeting of inflammatory mediators as a treatment for T2D and support a causative role for inflammation in the pathogenesis of this disease. They pave the way for new therapeutic approaches that could be disease modifying as opposed to palliative. This offers the opportunity to simultaneously target several features of the disease (including defective insulin secretion by β-cells, insulin resistance in adipose tissue, and microvascular and macrovascular complications) with antiinflammatory drugs (either alone or in combination) to alter the course of the disease. Based on preclinical studies, three anti-inflammatory approaches have been clinically tested: TNF antagonism, IL-1β antagonism and salsalate treatment (TABLE 2). In contrast to IL-1β antagonism and salsalate treatment, TNF antagonism has thus far failed to improve blood glucose levels in patients with T2D32–36. Improvements in glucose metabolism have been observed in patients being treated with TNF blockers for rheumatoid arthritis37,39,40,109–111, and a marginal effect of TNF blockers on fasting glucose levels was observed in obese individuals in a recent report 38. Based on these latest findings additional clinical trials may aim to block TNF signalling, either alone or in conjunction with other cytokine-blocking approaches. Current anti-inflammatory approaches to treating T2D focus on salsalate and IL-1β antagonism. Mechanistically these approaches may have similarities, including the modulation of IL-1R1 and NF-κB pathways1,55,67,112. IL-1 antagonists are large proteins that must be injected and have effects that may last for several weeks to months. By contrast, salsalate is an orally administered small molecule with a short half-life that requires more than once-a-day dosing. IL-1 antagonists are also designed to be highly specific for their targets, whereas salsalate and other non-acetylated forms of salicylate may have broader molecular actions. Thus in addition to the inhibition of NF-κB, they may inhibit other kinases113, upregulate the expression of heat shock factor protein 1 (REF. 114) and inhibit insulin clearance115. In addition to having apparent efficacy and durability in lowering glucose levels, it is encouraging that both approaches also seem to have high margins of safety. Salicylates such as salsalate have been used to treat joint pain in millions of patients over many decades, and many of these patients may also have diabetes, cardiovascular disease or other metabolic conditions. Although not as broadly used, IL-1 antagonists have been used for several indications, including in more than 100,000 patients with rheumatoid arthritis. It is also encouraging that the rate and severity of infections are unaffected, and rare or unusual infections have not been reported for individuals taking either drug, in contrast to certain other immunomodulatory therapies.

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f o c u S o n M E ta b o l I S M a n d I M M uRnEoVlo gy IEW S Table 2 | Clinical studies using anti-inflammatory approaches to treat type 2 diabetes or prediabetes mechanism

Drug

Trial Phase

number of Treatment main findings subjects duration (weeks)

Refs

IL‑1 receptor blockade

Anakinra (Kineret; Amgen/Biovitrum)

II

69

13

↓ Glycated haemoglobin, ↓ CRP, ↑ insulin production

IKKβ–NF‑κB inhibition

Salsalate

II

20

4

↓ FBG, ↓ CRP, ↑ insulin sensitivity, ↑ adiponectin

107

IKKβ–NF‑κB inhibition

Salsalate

II

16

2–4

↓ FBG, ↓ FFA, ↓ triglycerides, ↓ CRP, ↑ adiponectin

143

IKKβ–NF‑κB inhibition

Salsalate

II

40

1

↓ FBG, ↑ insulin

144

IKKβ–NF‑κB inhibition

Salsalate

IIb

104

12

↓ Glycated haemoglobin, ↓ FBG, ↓ triglycerides, ↑ adiponectin

28

IL‑1β‑specific antibody

XOMA 052 (Xoma)

I

98

Single injection

↓ Glycated haemoglobin, ↓ CRP, ↑ insulin production

27

IL‑1 receptor blockade

Anakinra (Kineret; Amgen/Biovitrum)

II

12

4

Ongoing, closed for recruitment

NCT00928876*

IL‑1β‑specific antibody

ACZ885 (canakinumab; II Novartis)

231

Unknown

Ongoing, closed for recruitment

NCT00605475*

IL‑1β‑specific antibody

ACZ885 (canakinumab; II Novartis)

140

48

Ongoing

NCT00995930*

IL‑1β‑specific antibody

ACZ885 (canakinumab; II Novartis)

232

4

Ongoing, closed for recruitment

NCT01068860*

IL‑1β‑specific antibody

ACZ885 (canakinumab; II‑III Novartis)

600

17

Ongoing, closed for recruitment

NCT00900146*

IKKβ–NF‑κB inhibition

Salsalate

III

284

48

Ongoing, closed for recruitment

NCT00799643*

IKKβ–NF‑κB inhibition

Salsalate

II

80

12

Ongoing, closed for recruitment

NCT00330733*

IL‑1β‑specific antibody

XOMA 052 (Xoma)

II

325

26

Ongoing, closed for recruitment

NCT01066715*

IL‑1β‑specific antibody

XOMA 052 (Xoma)

II

80

48

Ongoing, closed for recruitment

NCT01144975*

IL‑1β‑specific antibody

LY2189102 (Lilly)

II

80

12

Ongoing, closed for recruitment

NCT00942188*

IL‑1β‑specific vaccine

CYT013‑IL1bQb (Cytos Biotech.)

I

32

Unknown

Ongoing

NCT00924105*

25

Trials with tumour necrosis factor (TNF) antagonists31–40 are not listed owing to the lack of effects in patients with type 2 diabetes. CRP, C‑reactive protein; FBG, fasting blood glucose; FFA, free fatty acid; IKKβ, IκB kinase‑β; IL‑1, interleukin‑1; NF‑κB, nuclear factor‑κB. *ClinicalTrials.gov identifier.

Outstanding questions and future directions Increasing data suggest a potential role for inflammation in the pathogenesis of T2D. This is supported by the results of both preclinical studies and new clinical trials using anti-inflammatory approaches to treat the disease. But these are early days and there are many unanswered questions. What is the relative contribution of inflammation to the development of T2D? How efficacious are the anti-inflammatory approaches at improving glycaemia and T2D complications, and how durable will the effects be? What will be the best therapeutic modality: life-long

1. 2.

3. 4. 5.

Shoelson, S. E., Lee, J. & Goldfine, A. B. Inflammation and insulin resistance. J. Clin. Invest. 116, 1793–1801 (2006). Donath, M. Y., Boni‑Schnetzler, M., Ellingsgaard, H. & Ehses, J. A. Islet inflammation impairs the pancreatic β‑cell in type 2 diabetes. Physiology 24, 325–331 (2009). Bonner‑Weir, S. Islet growth and development in the adult. J. Mol. Endocrinol. 24, 297–302 (2000). Kahn, B. B. Type 2 diabetes: when insulin secretion fails to compensate for insulin resistance. Cell 92, 593–596 (1998). Rhodes, C. J. Type 2 diabetes‑a matter of β‑cell life and death? Science 307, 380–384 (2005).

6.

7. 8. 9.

treatment or short-term interventions aiming at breaking inflammatory flares? How do drugs such as salsalate and IL-1 blockers really work in T2D? Do anti-inflammatory strategies target the underlying mechanisms of the disease, and if so, would starting these therapies early prevent progression or even the overt manifestation of the disease? The early studies suggest that these strategies are well tolerated with few serious side effects and with little evidence of immunosuppression. From the numerous ongoing preclinical and clinical studies (TABLE 2), some of these questions should be addressed in the near future.

Robertson, R. P., Harmon, J., Tran, P. O. & Poitout, V. β‑cell glucose toxicity, lipotoxicity, and chronic oxidative stress in type 2 diabetes. Diabetes 53, S119–S124 (2004). Weir, G. C. & Bonner‑Weir, S. Five stages of evolving β‑cell dysfunction during progression to diabetes. Diabetes 53, S16–S21 (2004). Prentki, M. & Nolan, C. J. Islet β cell failure in type 2 diabetes. J. Clin. Invest. 116, 1802–1812 (2006). Hull, R. L., Westermark, G. T., Westermark, P. & Kahn, S. E. Islet amyloid: a critical entity in the pathogenesis of type 2 diabetes. J. Clin. Endocrinol. Metab. 89, 3629–3643 (2004).

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Acknowledgements

The authors wish to thank their scientific collaborators who have contributed so much to these studies, in particular A. Goldfine, J. Lee, D. Mathis, K. Maedler, P. Halban, T. Mandrup‑Poulsen, J. Ehses and M. Boni‑Schnetzler.

Competing interests statement

The authors declare competing financial interests: see web version for details.

FURTHER INFORMATION clinicaltrials.gov: http://clinicaltrials.gov All lInks ARe AcTIve In The onlIne PDf

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f o c u s o n m e ta b o l i s m a n d i m m u n o l o g y

PeRsPeCTives OPINION

Metabolism, migration and memory in cytotoxic T cells David Finlay and Doreen A. Cantrell

Abstract | The transcriptional and metabolic programmes that control CD8+ T cells are regulated by a diverse network of serine/threonine kinases. The view has been that the kinases AKT and mammalian target of rapamycin (mTOR) control T cell metabolism. Here, we challenge this paradigm and discuss an alternative role for these kinases in CD8+ T cells, namely to control cell migration. Another emerging concept is that AMP-activated protein kinase (AMPK) family members control T cell metabolism and determine the effector versus memory fate of CD8+ T cells. We speculate that one link between metabolism and immunological memory is provided by kinases that originally evolved to control T cell metabolism and have subsequently acquired the ability to control the expression of key transcription factors that regulate CD8+ T cell effector function and migratory capacity. Cytotoxic T cells that express the CD8 co-receptor and recognize peptide–MHC class I complexes have a key role in clearing viral infections. During a primary immune response to viruses, naive CD8+ T cells expressing pathogen-specific T cell receptors (TCRs) clonally expand and differentiate into effector CD8+ T cells that control the primary infection. This differentiation process produces effector cytotoxic T lymphocytes (CTLs) that can destroy virally infected cells through the targeted secretion of perforin and granzymes from lytic granules. After the primary infection is cleared there is a contraction phase when most of the effector CTLs die by apoptosis. However, an effective immune response also produces a stable population of antigen-specific longlived memory CD8+ T cells that can respond rapidly to clear secondary infections1–3. The transcriptional programmes that determine whether naive T cells differentiate into effector cells or memory cells are controlled by antigen receptors, co-receptors, cytokines and chemokines. These molecules also coordinate T cell metabolism and ensure that during an immune response T cells increase their uptake of glucose, amino acids and iron, and switch to using aerobic glycolysis

to generate ATP. These changes increase cellular nutrient uptake and energy production to meet the biosynthetic demands of effector T cell functions. Another important consideration is that activation of CD8+ T cells induces essential changes in their migratory patterns to redirect effector CTLs to sites of inflammation and concomitantly reduce their capacity to home to secondary lymphoid tissues. The challenge is thus to understand the molecular pathways that synchronize metabolism and migration with effector and memory T cell differentiation. In this Opinion article, we explore how serine/threonine kinases, including AKT (used to refer to all three isoforms; also known as PKB) and members of the AMPactivated protein kinase (AMPK) family (such as LKB1 (also known as STK11) and AMPK), coordinate these processes. We challenge the dogma that AKT has an obligatory role in controlling T cell metabolism and survival, and discuss how LKB1 is perhaps more important. We then discuss the concept that the physiological role for AKT is to coordinate the repertoire of adhesion molecules and chemokine receptors that are expressed by CD8+ T cells, and hence regulate their trafficking and migration.

nATuRE REvIEWS | Immunology

We also discuss the emerging idea that changes in T cell metabolism dictate whether naive CD8+ T cells become memory T cells or terminally differentiated effector T cells. Finally, we consider whether there really is any evidence for such a link or whether the link between metabolism and immunological memory reflects that kinases that evolved to control cell metabolism have acquired the ability to control T cell migration. The regulation of T cell migration by such kinases could then influence the fate of CD8+ T cells in terms of the decision to produce memory versus terminally differentiated effector CD8+ T cells. Metabolism and CTLs It was recognized over 30 years ago that it is important for CTLs to control their cellular metabolism and to coordinate glycolysis and oxidative phosphorylation4–6. Quiescent naive and memory CD8+ T cells only require energy to prevent cell atrophy and for survival and migration. By contrast, effector CTLs have higher energy demands because they need to proliferate rapidly and produce effector cytokines. It is thus essential that CD8+ T cells can increase cellular energy production and nutrient uptake to satisfy increased biosynthetic demands as and when they occur 7. One mechanism involves the upregulation of amino acid transporters, the transferrin receptor and glucose transporters at the cell surface in response to extrinsic signals from antigens and cytokines8–10. This ensures that nutrient uptake is increased to meet the metabolic and biosynthetic needs of the T cell as it responds to either developmental or pathogenic cues. One particularly important metabolic change that occurs in activated T cells is the switch from oxidative phosphorylation to aerobic glycolysis; that is, the cells use an oxygen-independent mechanism to produce ATP from glucose12. Effector CTLs may have to migrate, survive and produce effector cytokines in the hypoxic environment at sites of inflammation. Moreover, lymphoid tissue is also relatively hypoxic as the oxygen tension ranges from 1 to 5%13. A switch to aerobic glycolysis may thus help CTLs to proliferate and mediate their effector function in relatively hypoxic conditions. However, the problem vOLuME 11 | FEBRuARy 2011 | 109

© 2011 Macmillan Publishers Limited. All rights reserved

PersPectives with glycolysis is that it is a relatively inefficient route to produce ATP as it only yields two molecules of ATP for every molecule of glucose. This is in contrast to oxidative phosphorylation, which can produce at least 30 molecules of ATP from each molecule of glucose. Therefore, cells must be able to sustain high levels of glucose uptake to derive energy solely through glycolysis. In CTLs the key process to ensure sustained high-level glucose uptake is the upregulation of the expression and function of glucose transporter type 1 (GLuT1; also known as SLC2A1)8. It is also essential that T cells increase the activity or the expression of rate-limiting glycolytic enzymes, such as hexokinase 1, hexokinase 2 and phosphofructokinase 1 (Refs 12,14). The dependence of CTLs on aerobic glycolysis makes these cells dependent on exogenous glucose7,15. nevertheless, the advantage of glycolysis, and hence the most probable reason that the glycolytic switch occurs in CTLs, is that glycolysis promotes the use of glucose as a source of carbon for the synthesis of nucleic acids and phospholipids12. An increase in the production of such biosynthetic precursors would be favourable for CTLs, which have to maintain high levels of protein and lipid synthesis for their effector functions. 2NCUOCOGODTCPG PtdIns(4,5)P2 PI3K

PtdIns(3,4,5)P3 PH domain Ser473 P AKT P PDK1 Thr308 Active mTORC2

Figure 1 | mechanism of AKT activation. When there are low levels of phosphatidylNature Reviews | Immunology inositol-3,4,5-trisphosphate (Ptdins(3,4,5)P3) in the plasma membrane, AKT is in an inactive conformation and cannot be phosphorylated by the upstream activating kinase 3-phosphoinositidedependent protein kinase 1 (PDK1) (not shown). When Ptdins(3,4,5)P 3 levels increase in the plasma membrane — for example, following the activation of phosphoinositide 3-kinase (Pi3K), which phosphorylates phosphatidylinositol-4,5-bisphosphate (Ptdins(4,5)P2) — AKT binds Ptdins(3,4,5)P 3 through its pleckstrin homology (PH) domain. Binding of Ptdins(3,4,5)P3 to the PH domain of AKT induces a conformational change within its kinase domain allowing PDK1 to phosphorylate the critical residue required for AKT kinase activity, Thr308. Mammalian target of rapamycin complex 2 (mTORC2) also phosphorylates AKT at the carboxy-terminal ser473 site to fully activate its kinase activity. PDK1 has a PH domain that can bind Ptdins(3,4,5)P3 but this interaction is not essential for PDK1 catalytic activity.

AKT and T cell metabolism: the dogma. How do T cells increase their metabolism in response to immune stimulation? The current dogma is that the serine/ threonine kinase AKT has a key role. This kinase is rapidly activated in response to TCR triggering or cytokines such as interleukin-2 (IL-2) and IL-15 (Refs 16–18). The activation of AKT in T cells is regulated by stimuli that increase the levels of phosphatidylinositol-3,4,5-trisphosphate (PtdIns(3,4,5)P3), which is generated by direct phosphorylation of phosphatidylinositol-4,5-bisphosphate (PtdIns(4,5)P2) by phosphoinositide 3-kinase (PI3K). AKT activation also requires its phosphorylation on Thr308 by 3-phosphoinositidedependent protein kinase 1 (PDK1)18,19 and on Ser473 by mammalian target of rapamycin (mTOR) complex 2 (mTORC2)20,21 (fIG. 1). PDK1 and AKT both have a pleckstrin homology (PH) domain that binds PtdIns(3,4,5)P3 with high affinity. The interaction between PtdIns(3,4,5)P3 and AKT is required for PDK1 to phosphorylate AKT on Thr308. However, the binding of PtdIns(3,4,5)P3 to PDK1 is not essential for the catalytic activity of PDK1, although it does promote localization of the enzyme to the plasma membrane and support efficient induction of high levels of AKT activity 18,22. The model that AKT controls metabolic and survival programmes in T cells stems from experiments showing that PI3K inhibitors, which block AKT activation, prevent increases in both glucose and amino acid uptake by activated T cells16,23. In addition, constitutively active mutants of AKT can promote glucose uptake by controlling the expression of GLuT1 (Ref. 24). The mechanism for AKT control of glucose transporter expression is not fully understood, but AKT substrates include the RAB GTPase-activating proteins AS160 (AKT substrate of 160 kDa; also known as TBC1D4) and TBC1D1, which can control the translocation of glucose transporters to the cell membrane25–27. Further evidence that PtdIns(3,4,5)P3–PDK1-mediated activation of AKT controls T cell metabolism was obtained from studies of T cell progenitors in the thymus. In these cells, AKT stimulation is essential for the increases in glucose uptake and in the expression of amino acid transporters and the transferrin receptor that are required to support the survival and proliferation of these cells during thymopoiesis9,28. T cell progenitors that do not express PDK1 or AKT thus fail to express these important nutrient receptors and do not survive, as they cannot meet the metabolic demands of thymopoiesis.

110 | FEBRuARy 2011 | vOLuME 11

AKT and T cell metabolism: the reality. The consensus view of AKT is that it has a universal role in controlling T cell metabolism. It is thus assumed that the metabolic role for AKT in T cell progenitors is recapitulated in all peripheral T cells. Indeed, many of the extrinsic stimuli that control peripheral T cell metabolism activate PI3K and AKT17,29,30. There are also numerous experiments that have used PI3K inhibitors in different T cell populations and support the idea that PI3K, and hence AKT, are important for glucose uptake and/or protein synthesis23,31,32. However, a criticism of many of these studies is that one of the most commonly used PI3K inhibitors (Ly294002) has off-target effects and can inhibit mTOR and the PIM family of serine/threonine kinases33,34. A second criticism is that there is frequently an assumption that all PI3K-dependent responses are mediated by AKT and very little consideration is given to the role of other downstream effector molecules of PtdIns(3,4,5)P3, such as TEC family tyrosine kinases and guanine nucleotide exchange factors for RHO GTPases35. In this context, evidence for AKTindependent pathways that control T cell metabolism, survival and proliferation have now been documented. Although constitutively active AKT has been shown to stimulate glucose uptake and to promote cell growth and survival36, it differentially controls T cell subsets, promoting the survival of CD4+ but not CD8+ T cells37. Another example of how T cell metabolism and survival can be independent of AKT comes from in vivo studies of the role of PDK1. For example, deletion of PDK1 does not prevent IL-7 from supporting CD4+ T cell survival38. One other in vivo demonstration of the AKT independence of T cell metabolism comes from studies of the role of PDK1 in the pathology caused by deletion of the tumour suppressor PTEn (phosphatase and tensin homologue)19. This protein is a lipid phosphatase that removes the phosphate at the D3 position of the inositol ring of PtdIns(3,4,5)P3. The tissue-specific deletion of PTEn in thymic T cell progenitors increases cellular levels of PtdIns(3,4,5)P3 and is sufficient to strongly activate PDK1–AKT signalling. PTEn deletion also causes T cell lymphomagenesis, which results in the development of lymphoma cells — large blastoid cells indicative of unrestrained activation of metabolic pathways39. In normal T cell progenitors, PDK1–AKT signalling controls nutrient receptor expression and cell metabolism and www.nature.com/reviews/immunol

© 2011 Macmillan Publishers Limited. All rights reserved

f o c u s o n m e ta b o l i s m a n d Pi m o tl iovge y e rmsuPn ec s hence is essential for the proliferation and survival of these cells9. However, deletion of PTEn bypasses the normal PDK1–AKTcontrolled metabolic checkpoint in T cell progenitors, such that the growth and proliferation (but not malignant transformation) of PTEn-deficient T cells can occur independently of PDK1 and AKT signalling 19. This result is surprising because it was assumed that the requirement for PDK1 in the malignant transformation of PTEn-deficient thymocytes was due to its control of cell metabolism through the activation of AKT. The fact that the metabolism, survival and proliferation of PTEn-deficient thymocytes can be independent of PDK1 and AKT exemplifies how AKT does not have an equal and obligate role in controlling metabolism in all T cell populations. AKT-independent mechanisms. What are the candidates that may mediate AKTindependent control of T cell metabolism? One possibility is other members of the AGC family of serine/threonine kinases, such as 90 kDa ribosomal protein S6 kinase (p90-RSK), 70 kDa ribosomal protein S6 kinase 1 (p70-S6K1) or serum/glucocorticoidregulated kinase (SGK), which share substrate specificity with AKT40–42. Other candidates are the PIM family of serine/ threonine kinases because they have been shown to have a role in T cell survival, and they also have a substrate specificity similar to AKT43. Moreover, the PIM kinases are inhibited by the PI3K inhibitor Ly294002 (Ref. 34). Other proteins that are emerging as possible controllers of T cell metabolism include the mitogen-activated protein kinases (MAPKs) extracellular signalregulated kinase 1 (ERK1) and ERK2, which have recently been described as essential for the induction of glutamine uptake that accompanies T cell activation44. It has also been proposed that the serine/threonine kinase LKB1 is important for T cell metabolism. LKB1 is an evolutionarily conserved kinase that can regulate cellular responses to energy stress in many cell types and is required to synchronize cellular energy checkpoints and cell division in Drosophila melanogaster 45. LKB1 phosphorylates and activates multiple AMPK family members including AMPK46,47. In T cells, LKB1 phosphorylates and activates AMPK in response to increases in cellular AMP/ATP ratios, but AMPK can also be activated through a Ca2+–calmodulin-dependent protein kinase pathway in response to TCR triggering 48.

In many cell lineages, AMPK acts to restore cellular energy balance by inhibiting ATPconsuming processes and stimulating ATP-generating pathways49. It has thus been proposed that in T cells, increases in intracellular Ca2+ concentrations that activate calmodulin-dependent kinases stimulate AMPK to promote the conservation and accelerated production of ATP in anticipation of energy supplies becoming depleted by T cell activation. What is the evidence that LKB1 and AMPK contribute to the regulation of the energy status of T cells? One compelling set of data shows that LKB1 is essential for the survival and development of thymic T cell progenitors that have undergone TCR β-selection and is also required for the survival and proliferation of peripheral CD8+ T cells50,51. Importantly, LKB1 seems to be necessary for several key metabolic processes in T cells. For example, LKB1 controls the expression of CD98 (also known

as 4F2hc), a key subunit of L-system amino acid transporter 1, and is also required to sustain the phosphorylation of the ribosomal S6 subunit, a crucial regulator of protein synthesis51. Interestingly, LKB1 is an essential regulator of AMPK in energystressed T cells50, yet the loss of AMPK does not phenocopy the loss of LKB1. AMPKdeficient T cells have increased sensitivity to energy stress in vitro but can still develop normally in the thymus in vivo in contrast with LKB1-deficient T cells51,52. This is most likely due to redundancy in vivo between different AMPK family members for the control of T cell metabolism; the loss of LKB1 expression would circumvent this redundancy by preventing the activation of multiple AMPK family members. Therefore, contrary to the current dogma, AKT does not have an obligatory role in controlling T cell metabolism, and evidence is emerging that LKB1-regulated kinases do have a role.

glossary 14‑3‑3 scaffold proteins

Mammalian target of rapamycin

A family of conserved proteins that are present in all eukaryotic organisms. These proteins are involved in diverse cellular processes, such as apoptosis and stress, as well as in intracellular signalling and cell-cycle regulation. They function as adaptors in protein interactions and can regulate protein localization and enzymatic activity. Approximately 100 binding partners have been reported for the 14-3-3 proteins.

(mTOR). A conserved serine/threonine protein kinase that can regulate cell growth and metabolism in response to environmental cues. mTOR receives stimulatory signals from RAs and phosphoinositide 3-kinase (PI3K) downstream of growth factors and nutrients, such as amino acids, glucose and oxygen.

Aerobic glycolysis Glycolysis is an anaerobic metabolic pathway that converts glucose to pyruvate, which can then be either further metabolized in the presence of oxygen to generate ATP through oxidative phosphorylation, or converted to lactate. The term ‘aerobic glycolysis’ describes the conversion of glucose to lactate even though oxygen is present and thus not a limiting factor. for example, most cancer cells predominantly produce energy by a high rate of glycolysis followed by lactic acid fermentation in the cytoplasm, whereas most normal cells use a comparatively low rate of glycolysis followed by oxidation of pyruvate in mitochondria (termed the Warburg effect).

β‑selection A process involving a cell autonomous signalling cascade that leads to the proliferation and survival of thymocytes that have undergone successful recombination at the locus that encodes the β-chain of the T cell receptor (TCR) to express a functional pre-TCR on their cell surface.

Granzymes secreted serine proteases that enter target cells through perforin pores, where they then cleave and activate intracellular caspases to initiate target-cell apoptosis.

Oxidative phosphorylation A metabolic process that encompasses two sets of reactions that occur in the mitochondria. The first reaction involves the conversion of intermediate molecules (pyruvate and fatty acids) to acetyl coenzyme A (acetyl-CoA) and the degradation of acetyl-CoA to carbon dioxide in the tricarboxylic-acid cycle, yielding ‘free’ electrons that are carried by NADH and fADH2. The second reaction involves the transfer of electrons from NADH and fADH2 to the electron-transport chain, resulting in the movement of protons out of the mitochondrial matrix. The resulting electrochemical potential is used by the f1f0 ATP synthase to synthesize ATP.

Perforin A component of cytolytic granules that participates in the permeabilization of plasma membranes, allowing granzymes and other cytotoxic components to enter target cells.

Rapamycin An immunosuppressive drug that blocks mTOR.

Rate‑limiting glycolytic enzymes The enzymes hexokinase, phosphofructokinase and pyruvate kinase, which catalyse the three enzymatic steps in the glycolytic pathway that are essentially irreversible. Allosteric, transcriptional and post-translational regulation of these enzymes is crucial for the regulation of glycolysis. Phosphofructokinase catalyses the main rate-limiting step of glycolysis and is the most important control point.

L‑system amino acid transporter 1 A heterodimeric membrane transport protein that preferentially transports neutral branched amino acids (such as valine, leucine and isoleucine) and aromatic amino acids (such as tryptophan and tyrosine).

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Transferrin receptor (Also known as CD71). A receptor that regulates the cellular import of iron by binding the iron-carrier protein transferrin.

vOLuME 11 | FEBRuARy 2011 | 111 © 2011 Macmillan Publishers Limited. All rights reserved

PersPectives Control of CD8+ T cell migration AKT and migration. Recent work has established that the activation of AKT downregulates the expression of the adhesion molecule CD62L (also known as L-selectin) and the chemokine receptors CC-chemokine receptor 7 (CCR7) and sphingosine-1-phosphate receptor 1 (S1P1; also known as S1PR1) in CD8+ T cells; through this mechanism AKT determines the different trafficking patterns of naive and effector T cells18,19,53. naive and memory CD8+ T cells constantly circulate between the blood, lymphoid tissues and lymphatic vessels. By contrast, activated CD8+ T cells must suspend migration and reside in lymphoid tissue while they clonally expand and differentiate into effector CTLs. It is then vital that effector CTLs regain their motility, exit the lymphoid tissue and migrate to the site of infection to mount an immune response. The balanced and differential trafficking of naive versus effector CD8+ T cells is thus crucial for the function of CD8+ T cells during adaptive immune responses. In this context, naive and memory CD8+ T cells enter secondary lymphoid organs because they express CCR7 and can react to a gradient of CCR7 ligands that allows them to cross the endothelial cell barrier in specialized high endothelial venules

(HEvs)17,54. naive and memory CD8+ T cells also express high levels of CD62L, which mediates the first step of transendothelial migration — the capture and rolling of T cells on the endothelium of HEvs. Once T cells are in the lymph nodes their migration is coordinated by the fibroblastic reticular cell (FRC) network, chemokines such as CCR7 ligands (CCL19 and CCL21), and sphingosine-1-phosphate (S1P)54,55. naive T cells then spend several hours in the lymph node before exiting into the efferent lymphatic vessels and returning to the circulation. The egress of T cells from lymph nodes is determined by S1P1 (Refs 55,56). Activated T cells are retained in the lymph node because they downregulate or inactivate the expression of S1P1 (Refs 55–57). They then undergo a period of clonal expansion and differentiation to effector CTLs, at which point the cells regain S1P1 function and exit to the periphery. Effector CTLs migrate to sites of inflammation or infection, and have a reduced ability to home to peripheral lymph nodes compared with naive and memory CD8+ T cells. The changes in the trafficking behaviour of effector CTLs occur because the cells downregulate CCR7, CD62L and S1P1 expression and upregulate the expression of pro-inflammatory adhesion molecules

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Figure 2 | AKT-mediated control of adhesion and chemokine receptor expression. When AKT is strongly activated (for example in cytotoxic T lymphocytes (CTLs) that areNature cultured with |interleukin-2 Reviews Immunology (iL-2)), forkhead box O (FOXO) transcription factors are sequestered in the cytoplasm, where they bind 14-3-3 proteins. This prevents FOXO proteins from activating the transcription of target genes, including the transcription factor Krüppel-like factor 2 (KLF2). When AKT is inactive or activated suboptimally (for example in quiescent naive T cells or CTLs cultured with iL-15), FOXO transcription factors can gain access to the nucleus and drive the expression of KLF2. KLF2 in turn induces the expression of multiple adhesion and chemokine receptors, such as CD62L (also known as L-selectin), CC-chemokine receptor 7 (CCR7) and sphingosine-1-phosphate receptor 1 (s1P1), which control migration of T cells. 112 | FEBRuARy 2011 | vOLuME 11

(such as vLA4 (very late antigen 4) and ligands for P-selectin and E-selectin) and proinflammatory chemokine receptors (such as CXC-chemokine receptor 3 (CXCR3) and CCR5)54,57,58. The loss of CD62L, CCR7 and S1P1 expression by CTLs is an important mechanism that prevents these effector CTLs from re-entering secondary lymphoid organs and allows their redirection to peripheral tissues. Moreover, the importance of tightly regulating the expression of these receptors is evidenced by observations that changes in the turnover of S1P1, CCR7 or CD62L can markedly modify CTL-mediated immune responses58,59. Recently, some of the molecular mechanisms that control the expression of these key receptors have been described. One of the first clues came from observations that the cytokines IL-2 and IL-15 differed in their ability to downregulate CD62L expression on antigen-primed CD8+ T cells and diffferentially regulated AKT activation16,17. Antigen-primed CD8+ T cells that are cultured in the presence of IL-2 sustain AKT activation at high levels and downregulate CD62L. By contrast, T cells that are cultured with IL-15 sustain only low-level AKT activation and fail to downregulate CD62L expression16,17. These observations were initially speculative but subsequent work verified that CD62L, CCR7 and S1P1 expression by CD8+ T cells reflected the level of AKT activation in the cell17–19 (fIG. 2). Hence, effector CTLs have high levels of AKT activity, express low levels of CD62L, CCR7 and S1P1 and cannot traffic from the blood to lymphoid tissue. By contrast, CTLs that cannot fully activate AKT retain expression of CD62L, CCR7 and S1P1 and retain the ability to traffic to lymph nodes18. Conversely, in naive T cells, which normally express high levels of CD62L, CCR7 and S1P1, PDK1-mediated activation of AKT is sufficient to terminate the expression of these homing receptors and prevent the cells from homing to peripheral lymph nodes or spleen19. Therefore, lymph node homing by T cells is controlled by the level of AKT signalling, which controls the expression of key adhesion and chemokine receptors that direct T cells into the secondary lymphoid tissues. FOXO, mTOR and T cell migration. How does active AKT suppress the expression of CD62L? The answer to this question lies in the ability of AKT to control the activity of the forkhead box O (FOXO) family transcription factors FOXO1 and FOXO3A, and hence to control the expression of www.nature.com/reviews/immunol

© 2011 Macmillan Publishers Limited. All rights reserved

f o c u s o n m e ta b o l i s m a n d Pi m o tl iovge y e rmsuPn ec s the transcription factor Krüppel-like factor 2 (KLF2)53 (fIG. 2). Studies in mice have shown that KLF2 directly regulates Cd62l gene transcription60–62; thus KLF2-deficient naive CD8+ T cells do not express CD62L homing receptors and fail to home to secondary lymphoid organs and instead migrate to peripheral tissues. FOXO1 and FOXO3A are active in the nucleus of quiescent naive T cells and drive the expression of KLF2. Following immune activation, AKT-mediated phosphorylation of FOXO transcription factors results in their translocation from the nucleus to the cytoplasm63, where they form a complex with 14-3-3 scaffold proteins64. AKT-mediated inhibition of FOXO proteins thus terminates the expression of KLF2 and hence the expression of KLF2 gene targets, including Cd62l and S1p1 (Ref. 18). Another way in which AKT could control the expression of KLF2 is by regulating mTOR in the mTORC1 complex 65. AKT phosphorylates and inactivates the RHEB GTPase-activating protein tuberin (TSC2), resulting in the accumulation of RHEB–GTP, which activates mTORC1 (fIG. 3). AKT also regulates mTORC1 by phosphorylating PRAS40 (40kDa proline-rich AKT1 substrate, also known as AKT1S1), thereby blocking PRAS40-mediated inhibition of mTORC1 (Ref. 66) (fIG. 3). The mTORC1 complex can regulate protein synthesis by controlling ribosomal biogenesis and the translation of a subset of mRnAs65,67, although it is not known whether these metabolic functions of mTOR are important in T cells. However, mTOR activation does downregulate the expression of KLF2 and, therefore, CD62L, CCR7 and S1P1 (Ref. 17). The molecular details of the control of KLF2 expression by mTOR in T cells remains to be fully determined but it seems to be independent of regulated FOXO phosphorylation or localization (D.F. and D.A.C., unpublished observations). The salient fact about the link between mTORC1 and KLF2 is that the mTORC1 inhibitor rapamycin, which is widely used clinically as an immunosuppressant, causes CTLs to re-express KLF2, CD62L and CCR7 and regain the ability to home to lymph nodes17. It is generally believed that rapamycin suppresses immune responses through its suppression of T cell proliferation. However, it is now clear that rapamycin treatment can also redirect the trafficking of effector CTLs from peripheral tissues to the lymph nodes and spleen17. The ability to redirect CTLs to secondary lymphoid tissue would result in their retention in secondary

lymphoid organs and hence prevent immune destruction of target cells in peripheral tissues. It could also promote the destruction of antigen-primed antigen-presenting cells (APCs) by CTLs in lymph nodes, which could contribute to the clinical efficacy of rapamycin as an immunosuppressant. Determining metabolism versus migration Different AKT activation thresholds. The discussions above indicate how AKT can control the activity of pathways that converge to control T cell migration (fIG. 4). However, one significant observation is that AKT does not function as a simple on/off switch in T cells; rather, the magnitude of AKT activity is relevant. This insight comes from studies of T cells homozygous for a knock-in mutant of PDK1 (Lys465Glu) that cannot bind PtdIns(3,4,5)P3 (Refs 18,22). The integrity of the PDK1 PH domain is not required for PDK1 catalytic activity but the loss of PtdIns(3,4,5)P3-binding by PDK1 strongly reduces AKT phosphorylation and activation. The PDK1 Lys465Glu mutant can thus only support submaximal activation of AKT in activated T cells (approximately 10–20% of that in wild-type T cells)18. Intriguingly, the low levels of AKT activity in T cells expressing the PDK1 Lys465Glu mutant are sufficient for T cell growth and proliferation, and thus are clearly sufficient to support T cell metabolism during thymopoiesis and during the T cell response to cognate antigen. However, these low levels of AKT activity are not sufficient to terminate the expression of KLF2 or to switch the chemokine and adhesion receptor profile of naive T cells to that of CTLs. These data suggest that the initial strength of TCR triggering might dictate the outcome of an immune response by controlling the ability of the T cells to migrate rather than by controlling their ability to proliferate. For example, the downregulation of S1P1 following CD8+ T cell activation is one of the mechanisms that retain activated CD8+ T cells in lymph nodes, but only occurs if there is strong activation of AKT. Activation with weak TCR agonists that cause weak activation of AKT might thus support T cell proliferation but would be unable to downregulate S1P1 expression and, therefore, the T cells would not be retained in the lymph nodes. The premature exit of activated CD8+ T cells from lymph nodes into the blood in response to weak stimulation has been observed68, and would curtail CD8+ T cell exposure to APCs and pro-inflammatory cytokines, resulting in an attenuated immune response.

nATuRE REvIEWS | Immunology

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PRAS40 RAPTOR mTOR mTORC1

RAPTOR P Ser792

Figure 3 | Regulation of mToRC1 activity. Reviews | Immunology Mammalian target ofNature rapamycin (mTOR) activity is regulated by the balance of multiple signalling pathways. Phosphoinositide 3-kinase (Pi3K)–AKT signalling activates mTOR complex 1 (mTORC1) through the phosphorylation of the GTPaseactivating protein (GAP) tuberin (TsC2) at position ser1462. This phosphorylation event results in the dissociation of the hamartin (TsC1)–TsC2 complex and thus prevents TsC2 from stimulating the intrinsic GTPase activity of the small G protein RHeB, resulting in the accumulation of GTP-bound RHeB, which is a positive regulator of mTORC1. AKT also phosphorylates 40 kDa proline-rich AKT1 substrate (PRAs40; also known as AKT1s1) at position Thr246, resulting in its dissociation from mTOR and thus blocking PRAs40-mediated mTORC1 inhibition. AMPactivated protein kinase (AMPK) activity inhibits mTORC1 by phosphorylating both TsC2 and the mTORC1 component regulatory associated protein of mTOR (RAPTOR). Phosphorylation of TsC2 (at Thr1227 and ser1345) by AMPK positively regulates its GAP activity, leading to RHeBmediated GTP hydrolysis, thereby preventing activation of mTORC1. Phosphorylation of RAPTOR (at ser722 and ser792) facilitates its binding to 14-3-3 proteins (not shown) and the subsequent inhibition of mTORC1 function.

AMPK, mTOR and T cell memory. It has recently been proposed that changes in T cell metabolism might be at the core of the decision of CD8+ T cells to produce memory T cells rather than terminally differentiated effector T cells69–71. This idea originates from experiments showing that treatment of mice with the mTOR inhibitor rapamycin increases the production of memory CD8+ T cells by accelerating the conversion of effector CD8+ T cells into the memory pool69,71. It has also been shown that the activation of AMPK in mice by treatment with the drug metformin enhances the production of memory vOLuME 11 | FEBRuARy 2011 | 113

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Figure 4 | mToRC1 regulation of effector versus memory CD8+ T cell fate. Mammalian target of rapamycin complex 1 (mTORC1) controls CD8+ T cell migration by regulating the expresReviewsreceptors | Immunology sion of Krüppel-like factor 2 (KLF2), which controls the expression ofNature chemokine and adhesion molecules that are crucial for lymph node homing. mTORC1 also regulates the expression of T-bet, which induces the expression of P-selectin ligands and CXC-chemokine receptor 3 (CXCR3), both of which are crucial for the trafficking of effector CD8+ T cells to sites of inflammation. in addition, mTORC1 regulates the balance of T-bet and eomesodermin; these transcription factors are known regulators of effector versus memory CD8+ T cell function. T-bet is required for the cytotoxic functions of effector T cells and the production of effector cytokines, whereas eomesodermin expression is required for the acquisition of the memory phenotype. AMPK, AMP-activated protein kinase; CCR7, CC-chemokine receptor 7; FOXO, forkhead box O; iL-7R, interleukin-7 receptor; s1P1, sphingosine-1-phosphate receptor 1.

CD8+ T cells71. These two sets of observations might be linked because metformin interferes with oxidative phosphorylationmediated ATP synthesis through inhibition of respiratory chain complex I, and hence causes an increase in cellular AMP/ ATP ratio. This energy stress can drive an LKB1-dependent activation of AMPK, which then phosphorylates TSC2 and RAPTOR (regulatory associated protein of mTOR) to coordinately suppress mTORC1 activity 72 (fIG. 3). The T cell memory experiments with metformin were initiated by the observation that TnFR-associated factor 6 (TRAF6)-deficient CD8+ T cells cannot develop into memory CD8+ T cells and have reduced activity of AMPK71. However, whether AMPK-deficient T cells can develop into memory T cells has not been directly assessed. Moreover, evidence is emerging that metformin can control cellular metabolism independently of AMPK73,74. nevertheless, as the primary effect of metformin is to inhibit respiratory chain complex I74, the metformin data are a good indication that changes in cell metabolism can change T cell behaviour. However, there are many issues to resolve concerning the effect of metformin on T cell memory. First, there has been no clear demonstration that the in vivo

effects of metformin reflect the action of this drug specifically on T cells rather than on other cells of the immune system. Second, it needs to be proved that metformin acts through AMPK. One other factor to be considered is that mTOR and AMPK should not be considered solely as enzymes that control T cell metabolism. For example, the ability of mTOR to control T cell migration by regulating the expression of KLF2, CD62L, CCR7 and S1P1 is independent of any metabolic function of this enzyme17. Rapamycin treatment restores expression of KLF2 and its targets in IL-2-maintained CTLs and redirects CTL trafficking to secondary lymphoid tissue, even though IL-2-mediated control of CD8+ T cell survival and proliferation is not rapamycin sensitive17. How could inhibition of mTORC1 with rapamycin or through activation of AMPK promote the transition of effector CTLs to memory CD8+ T cells? One explanation could be the ability of rapamycin to reprogramme the trafficking of effector CTLs such that these cells regain the ability to enter secondary lymphoid tissue17,75. This would bring them into the proximity of stromal cells, which produce cytokines (such as IL-7 and IL-15) that are required for the survival and homeostasis of memory T cells. It is also relevant here that in CD8+

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T cells, mTOR activation is required to sustain the expression of the transcription factor T-bet while suppressing the expression of eomesodermin75 (fIG. 4). The molecular basis for mTOR-mediated control of T-bet and eomesodermin expression is not known nor is it clear if this is in any way linked to the role of mTOR as a metabolic regulator. However, the balance of T-bet and eomesodermin expression can determine the effector or memory fate of CD8+ T cells76, and the ability of mTOR to control the expression of these transcription factors gives some insights into how levels of mTOR activity might determine CTL fate. T-bet is a key transcription factor in CTLs and is important for driving expression of the cytolytic differentiation programme58. This raises the fundamental question of whether changes in CD8+ T cell metabolism determine the effector or memory fate of CD8+ T cells by directly controlling their differentiation. It is however intriguing that T-bet also controls the expression of P-selectin ligands and CXCR3, which are crucial for the trafficking of effector CD8+ T cells to sites of inflammation58,77. Thus an alternative view is that enzymes that evolved to control T cell metabolism have gained the ability to control T cell migration, and that it is their effects on migration and T cell homing that influence the fate of CD8+ T cells. This view is probably too simplistic, but if T cells migrate to different sites, they will have the potential to adopt different fates because they will exist in a different cytokine and chemokine milieu. The most probable scenario is that mTOR controls CD8+ T cell fate by a combination of mechanisms, including regulating T cell trafficking and directing the expression of the key transcription factors that control CTL effector function. What about the proposal that metabolism regulates T cell memory? This concept stems from the recognition that mTOR can control immunological memory and the underlying dogma that mTOR controls T cell metabolism. However, there is no direct evidence that mTOR regulates T cell metabolism in the cellular models that demonstrate a role for mTOR in CTL function. nevertheless, it should be remembered that mTOR activity will be determined by nutrient availability 78. Hence any change in the strength or quality of T cell activation during an immune response could cause suboptimal expression of nutrient receptors on T cells, thereby limiting their glucose and amino acid uptake and limiting the strength of mTOR activation. www.nature.com/reviews/immunol

© 2011 Macmillan Publishers Limited. All rights reserved

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Figure 5 | model for how differential AKT and mToR signalling controls effector versus memory CD8+ T cell formation. a | Naive CD8+ T cells (TN) circulate between the blood, lymph nodes and efferent lymphatics. These T cells express several molecules that are crucial to this trafficking cycle. CD62L (also known as L-selectin) mediates adhesion to high endothelial venules (Hevs), CC-chemokine receptor 7 (CCR7) directs transendothelial migration into lymph nodes, and sphingosine1-phosphate receptor 1 (s1P1) directs T cell migration into the efferent lymphatic vessels. b | During an infection, CD8+ T cells are activated by their cognate antigen when it is presented to them by antigen-presenting cells in the lymph node. They then cease trafficking, and proliferate and differentiate to produce effector cytotoxic T lymphocytes (CTLs; Te). After a period, the CTLs exit the lymph node, and strongly activated cells that no longer express CD62L or CCR7 are unable to re-enter secondary lymphoid tissue. Moreover, such strongly activated CTLs will upregulate the expression of P-selectin and e-selectin ligands and pro-inflammatory

Differential AKT and mTOR signalling There is a lot of evidence that effector and memory T cells can develop from a common naive T cell progenitor 79–81, and that memory CD8+ T cells can also develop from antigen-primed CD8+ T cells that have differentiated into effector CTLs82. However, if differential activation of mTOR signalling is a driver of effector versus memory CD8+ T cell fate, then how can the progeny of a single cell generate heterogeneous mTOR signalling? How can an effector CD8+ T cell divert to a memory CD8+ T cell fate? Moreover, in the context of this discussion, is there a link with metabolism? One plausible idea is that competition for essential cytokines, such as IL-2, IL-12 and IL-15, could be the mechanism that creates heterogeneity in mTOR signalling in T cells. It is quite reasonable to assume that levels of these cytokines are finite in any tissue. It is also well established that sustained signalling by these cytokines is essential for CD8+ T cell differentiation. Moreover, in the context of IL-2 signal

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chemokine receptors such as CXC-chemokine receptor 3 (CXCR3), allowing them to traffic across inflamed endothelium to sites of infection and Nature Reviews | Immunology inflammation. As the infection resolves, cytokines become limiting at the site of inflammation, and in the absence of these survival signals effector CTLs undergo apoptosis (not shown). The loss of cytokine signalling also causes loss of AKT–mammalian target of rapamycin (mTOR) signalling and could allow re-expression of CD62L and CCR7 on some CTLs and hence allow these cells to return to secondary lymphoid tissues. This would bring them into proximity with the stromal cells that produce the homeostatic cytokines iL-7 and iL-15. in this environment, these T cells have the potential to generate memory CD8+ T cells (TM). An alternative possibility is that cells that only weakly activate AKT–mTOR signalling during the initial immune activation within the lymph nodes could retain the expression of CD62L and CCR7, and hence immediately resume a pattern of homing to secondary lymphoid organs, which would favour their development into memory T cells.

transduction, the ‘strength’ and duration of exposure to IL-2 is important 83,84. In vivo studies show that CD8+ T cells that express high levels of the high-affinity IL-2 receptor are more likely to develop into terminally differentiated effector CD8+ T cells, whereas cells with lower levels of IL-2 receptors give rise to longlived memory CD8+ T cells84. Similarly, in vitro experiments show that antigenprimed CD8+ T cells that are cultured with high-dose IL-2 differentiate into effector CTLs, whereas cells that are cultured in low-dose IL-2 differentiate into memory CD8+ T cells83. Importantly, IL-15 could only support the production of memory CD8+ T cells, reflecting the fact that IL-15 can only weakly activate AKT in antigen-primed CD8+ T cells16,17,83. So a simple idea of how a single antigenprimed naive CD8+ T cell could produce progeny that are heterogeneous for AKT activation is to consider that populations of T cells have to compete for cytokines such as IL-2 (fIG. 5). This could be a stochastic process initially or it could be directed by

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heterogeneity in the expression of the IL-2 receptor by CTLs84. Cells with a low level of IL-2 signalling would have lower levels of AKT and mTOR activity. As discussed, this would change the trafficking properties of these cells and any heterogeneity would be reinforced when the cells moved to different microenvironments. It is also relevant that IL-2 is a potent regulator of the expression of the receptors for key cytokines that determine CD8+ T cell fate: IL-2 can thus positively regulate IL-12 receptor expression85 and negatively control IL-7 receptor levels86. Therefore, in addition to altering T cell migratory properties as a result of lower AKT and mTOR activity, low-dose IL-2 would cause CD8+ T cells to downregulate IL-12 receptor expression and increase their expression of IL-7 receptors. This would favour their differentiation towards a memory CD8+ T cell fate. Returning to the theme of metabolism, high levels of IL-2 signalling could support the high metabolic rate required for effector CTL responses, whereas low levels of IL-2 would not. vOLuME 11 | FEBRuARy 2011 | 115

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PersPectives This is obviously an over-simplistic view and it is unlikely that the complexities of effector versus memory CD8+ T cell decisions can be explained on the basis of how T cells deal with a single cytokine. However, these cell fate decisions could be explained by a model that places AKT and mTOR at the core of a pathway that integrates signals from a wide range of cytokines, co-stimulatory molecules and antigen receptors to direct CD8+ T cell fate. The key to this model is that the strength and duration of AKT, and hence mTOR, activation is determined by the balance of signals from these surface receptors, so there are multiple routes to modulate AKT activation at any time as T cells respond to immune-mediated activation signals. In addition to the example of cytokine competition discussed above, another route could involve changes in the levels of TCR triggering. Effector CD8+ T cells at the sites of infection might sustain high levels of AKT activity as a result of continual antigen receptor occupancy. Then, as pathogens are cleared from the body, the levels of TCR triggering would decrease, allowing the levels of active AKT to drop and thereby directing the CD8+ T cells to home back to secondary lymphoid tissues where competition for homeostatic cytokines would determine the number of memory CD8+ T cells that could be supported within a particular niche.

1.

Concluding remarks We still have much to learn about how CD8+ T cells control their metabolism to meet the energy demands of their effector function. However, we have begun to understand an extraordinary amount about how the enzymes that evolved to control T cell metabolism are also able to control T cell migration and differentiation and determine the balance of effector versus memory CD8+ T cell development. We have also been able to see how changes in the strength of activation of serine/threonine kinases can create heterogeneity in signal transduction pathways, allowing a single T cell to generate progeny that have different fates. This work provides important insights about pharmacological strategies that might be able to manipulate immune responses to ensure effective vaccination and/or stem the T cell pathology caused by effector CTLs.

13.

David Finlay and Doreen A. Cantrell are at the Division of Cell Biology and Immunology, University of Dundee, Dundee, UK. Correspondence to D.A.C. e‑mail: [email protected] doi:10.1038/nri2888 Published online 14 January 2011

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Competing interests statement

The authors declare no competing financial interests.

vOLuME 11 | FEBRuARy 2011 | 117 © 2011 Macmillan Publishers Limited. All rights reserved

REVIEWS Phenotypical and functional specialization of FOXP3+ regulatory T cells Daniel J. Campbell*‡ and Meghan A. Koch*‡

Abstract | Forkhead box P3 (FOXP3)+ regulatory T (TReg) cells prevent autoimmune disease, maintain immune homeostasis and modulate immune responses during infection. To accomplish these tasks, TReg cell activity is precisely controlled, and this requires TReg cells to alter their migratory, functional and homeostatic properties in response to specific cues in the immune environment. We review progress in understanding the diversity of TReg cells, TReg cell function in different anatomical and inflammatory settings, and the influence of the immune environment on TReg cell activity. We also consider how these factors affect immune-mediated disease in the contexts of infection, autoimmunity, cancer and transplantation.

*Immunology Program, Benaroya Research Institute, Seattle, Washington 98103, USA. ‡ Department of Immunology, University of Washington School of Medicine, Seattle, Washington 98195-7650, USA. Correspondence to D.J.C. e-mail: campbell@ benaroyaresearch.org doi:10.1038/nri2916

Forkhead box P3 (FOXP3)+ regulatory T (TReg) cells function to maintain immune tolerance and prevent inflammatory diseases1. This is best exemplified by the severe systemic autoimmunity and lymphoproliferative disease observed in TReg cell-deficient mice and in humans carrying non-functional or hypomorphic alleles of the FOXP3 gene. The impaired function and/or homeostasis of TReg cells has also been implicated in the development of several common autoimmune and inflammatory diseases, including type 1 diabetes, rheumatoid arthritis, multiple sclerosis and systemic lupus erythematosus2–5. In addition to preventing autoimmunity, TReg cells regulate immunity to infections of viral, bacterial or parasitic origin, and can also restrain immune responses directed towards tumours or transplanted tissue6,7. Thus, TReg cells must ‘walk the line’, allowing protective antitumour and antipathogen immunity, but preventing inflammatory disease by restraining aberrant responses to self or to innocuous antigens. To function properly, TReg cells must modulate the activities of a wide variety of cellular components of both the innate and the adaptive immune systems, and this depends on their ability to come into physical proximity with their targets by migrating to specific tissues and microenvironments. Additionally, it is crucial that TReg cells use appropriate immunomodulatory mechanisms that can effectively inhibit the targeted cell population. Recently, it has become clear that TReg cells can be divided into several distinct subsets, with unique functional and homeostatic properties, that work in concert to maintain normal immune homeostasis 8. In this Review,

we summarize recent advances in our understanding of the relationship between TReg cell trafficking and function in lymphoid and non-lymphoid tissues, TReg cell specialization during different types of immune responses, and the impact of the cytokine milieu on the phenotype, function and stability of TReg cells.

Widespread distribution of TReg cells TReg cells localize to lymphoid and non-lymphoid sites. The cells and tissues of the immune system are anatomically organized to facilitate the cellular interactions that are required for the development, activation, function and regulation of diverse leukocyte populations9. The organization of the immune system is the result of tissueand microenvironment-specific lymphocyte homing, which in turn is mediated by lymphocyte expression of surface adhesion and chemoattractant receptors. Although TReg cells were initially identified in the secondary lymphoid tissues of mice and the peripheral blood of humans, they express a dizzying array of adhesion molecules and chemoattractant receptors that are expected to target them to both lymphoid and non-lymphoid sites (TABLE 1). Indeed, in addition to their constitutive presence in secondary lymphoid tissues, TReg cells can be found in most non-lymphoid tissues, even in the absence of any overt inflammation10. Additionally, TReg cells can be found in abundance within tumours, where they are thought to blunt effective tumour clearance7. In recent years, genetic studies have revealed the importance of several homing receptors for the appropriate tissue distribution and function of TReg cells. For instance,

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REVIEWS Table 1 | A summary of the important homing receptors expressed by TReg cells and their functions Site of TReg cell migration

Receptor

Function

Key references

Lymphoid tissues

CD62L

Migration to lymph nodes

• Function in TReg cell migration to lymph nodes112 • Importance in the NOD–SCID model of diabetes113

CCR7

Migration to lymph nodes and the spleen

• CCR7–/– TReg cells fail to prevent colitis14 • Importance in TReg cell migration during allograft rejection18

E-selectin and P-selectin ligands

Migration to skin and inflamed tissues • Expression by human TReg cells114 • Function in the cutaneous hypersensitivity response115 • Importance in cutaneous tolerance11

αEβ7 integrin

Epithelial localization

• Expression by mouse TReg cells20 • TReg cell retention during infection with Leishmania major12

α4β7 integrin

Migration to gut-associated lymphoid tissues

• Function in TReg cell migration to the intestine116

CCR2

Migration to inflamed tissues

• Expression by human and mouse TReg cells19,117 • Importance in TReg cell migration during allograft rejection18

CCR4

Migration to skin and other inflamed tissues

• Expression by human TReg cells114 • Importance in cutaneous and pulmonary tolerance10 • CCR4–/– TReg cells fail to prevent colitis118

CCR5

Migration to inflamed tissues

• Importance in TReg cell migration during allograft rejection18 • Function in migration to the inflamed intestine119 • Directing TReg cell localization during infection with L. major120

CCR6

Migration to sites of TH17 cell-mediated inflammation

• Expression by IL-10-producing TReg cells121 • Function in TReg cell migration during TH17 cell-mediated autoimmunity15,122

CCR8

Migration to skin and sites of TH2 cell-mediated inflammation

• Expression by TReg cells123

CCR9

Migration to the small intestine

• Expression by TReg cells in the intestinal lamina propria124

CCR10

Migration to mucosal tissues and skin

• Expression by TReg cells in inflamed human liver125

CXCR3

Migration to sites of TH1-mediated inflammation

• Expression by TReg cells is T-bet dependent47 • Importance in TReg cell localization to inflamed liver16,126

CXCR5

Migration to B cell follicles and germinal centres

• Expression by human TReg cells127 • Inhibition of B cell responses by TReg cells128

CXCR6

Migration to the liver

• Expression by human TReg cells127

CXCR4

Migration to bone marrow, Peyer’s patches and tumour sites

• Expression by naive phenotype TReg cells127 • Association with tumour-infiltrating TReg cells129,130

Non-lymphoid tissues

Both lymphoid and non-lymphoid tissues

CCR, CC-chemokine receptor; CXCR, CXC-chemokine receptor; IL-10, interleukin-10; NOD, non-obese diabetic; SCID, severe combined immunodeficiency; TH, T helper; TReg, regulatory T.

expression of the αe integrin chain (also known as CD103) and the chemokine receptor CC-chemokine receptor 4 (CCR4), as well as the ability to generate carbohydrate ligands for P-selectin and e-selectin by the action of the α-(1,3)-fucosyltransferase vII enzyme are all important for the migration and/or retention of TReg cells within the skin. Accordingly, deletion of any of these molecules on TReg cells results in the development of skin-specific autoimmunity and altered pathogen clearance during cutaneous infection10–13. similarly, loss of CCR7 blocks TReg cell migration to the lymph nodes and inhibits TReg cell function in an experimental model of colitis14. In addition to their constitutive recirculation, TReg cell recruitment to non-lymphoid tissues is substantially enhanced during inflammation. However, the contributions of individual homing receptors to this ‘inflammation-induced’ Treg cell migration vary considerably depending on the tissue involved and the type

of inflammatory response. For example, interleukin-17 (Il-17) produced during T helper 17 (T H17) cellmediated inflammation promotes epithelial cell expression of the CCR6 ligand, CC-chemokine ligand 20 (CCl20), and CCR6 is essential for the optimal recruitment of TReg cells to sites of TH17-mediated inflammation in experimental autoimmune encephalomyelitis (eAe) 15. similarly, interferon-γ (IFnγ) induces expression of the CXC-chemokine receptor 3 (CXCR3) ligands CXC-chemokine ligand 9 (CXCl9), CXCl10 and CXCl11 and the subsequent recruitment of CXCR3+ TReg cells to the liver in a model of concanavalin A-induced hepatitis16. Additionally, CXCR3 may influence the microenvironmental positioning of TReg cells in the central nervous system in eAe17. In this manner, recruitment of CCR6+ and CXCR3+ TReg cells occurs downstream of the key effector cytokines Il-17 and IFnγ in a feedback loop to limit T H17 cell-induced and TH1 cell-induced inflammatory responses.

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REVIEWS Box 1 | Influence of the T cell receptor on TReg cell phenotype and function Thymically derived regulatory T (TReg) cells are thought to be largely autoreactive106. However, the identities of the natural self-antigens that are thought to drive TReg cell development are still completely unknown. Despite the fact that TReg cell specificity is still poorly characterized, there is evidence that T cell receptor (TCR) recognition has a key role in influencing the phenotype, function and localization of TReg cells in vivo. For example, antigen-specific activation of TReg cells isolated from TCR-transgenic mice alters their expression of several lymphocyte homing receptors, resulting in their subsequent redistribution to non-lymphoid tissues10,19. Moreover, TReg cells isolated from different tissues have distinct TCR repertoires, indicating that TCR-driven activation helps to impart cells with a tropism for specific sets of lymphoid and non-lymphoid tissues107. This probably occurs because TReg cells specific for tissue-restricted self-antigens encounter signals during their activation that drive expression of tissue-specific homing receptors62. Although together these data suggest a key role for TCR recognition of specific self-antigens in driving the phenotypical diversity that is present among TReg cells, a better understanding of the self-antigens recognized by TReg cells is necessary to clarify precisely how their specificity affects their localization, phenotype, homeostasis and function.

In addition to CCR6 and CXCR3, many other homing receptors have been implicated in the inflammatory recruitment of TReg cells in different immunological settings, including CCR1, CCR2, CCR4, CCR5, CCR8, CCR9, CXCR4, CXCR5, CXCR6, α4β1 integrin (also known as vlA4), αeβ7 integrin, α4β7 integrin and the P- and e-selectin ligands. Indeed, TReg cells probably use a combination of homing molecules that can function redundantly to control their migration during inflammatory responses. For example, in an islet allograft model, TReg cells used CCR2, CCR5, CCR4 and P- and e-selectin ligands to migrate to the transplant site, whereas CCR2, CCR5 and CCR7 were required for trafficking from the inflamed allograft to the draining lymph node18. Interestingly, this sequential migration of TReg cells from the graft site to the draining lymph node was required for prevention of graft rejection, highlighting the complex and dynamic nature of TReg cell migration during inflammation. Thus, therapeutically targeting TReg cell migration in the contexts of autoimmunity, transplantation, chronic infection and cancer remains a daunting task that will require significantly more study in both animal models and patient populations. Differences in T Reg cells in lymphoid versus nonlymphoid tissues. Although TReg cells can be found throughout the body, there is substantial phenotypical and functional variation between TReg cells in lymphoid and non-lymphoid tissues. Developing TReg cells in the thymus are a fairly homogenous population of CD25hiCD62l+CCR7+ cells that resemble conventional naive T cells and preferentially migrate to secondary lymphoid tissues. However, on entering the periphery, a subset of TReg cells rapidly acquires phenotypical features of effector or memory T cells, becoming CD44hi and upregulating expression of homing receptors that allow them to access non-lymphoid sites19,20. moreover, similar to conventional naive T cells and effector and memory T cells, CD44low and CD44hi TReg cell subsets have distinct homeostatic characteristics, with CD44hi TReg cells proliferating at a substantially higher rate in

the steady state21. This suggests that there is a ‘division of labour’ between distinct TReg cell subsets that are specialized for functioning either in lymphoid or in nonlymphoid tissues. In addition, the phenotype of the CD44hi effector- or memory-like TReg cell pool indicates that this population arises as a result of TReg cell activation, presumably owing to recognition of self-antigens in secondary lymphoid tissues (BOX 1). Although the functional mechanisms used by TReg cells are complex and still incompletely understood, there is increasing evidence that TReg cells use different mechanisms to regulate immune responses in lymphoid and non-lymphoid tissues. This concept is best exemplified by the distinct phenotypes in mice that selectively lack TReg cell expression of either Il-10 or cytotoxic T lymphocyte antigen 4 (CTlA4) (FIG. 1). Il-10 is a cytokine that is produced by CD44hi TReg cells and can both directly and indirectly inhibit effector T cell responses during infection, autoimmunity and cancer22–24. Although it is also expressed by other leukocyte populations, deletion of Il10 selectively in TReg cells resulted in the development of spontaneous colitis and exaggerated immune responses at other environmental interfaces such as the skin and lungs25. However, these animals did not develop the systemic autoimmunity and dysregulated T cell activation profiles that are characteristic of mice with a complete loss of TReg cell function. by contrast, loss of CTlA4 expression in TReg cells resulted in severe lymphoproliferative disease characterized by massive lymphadenopathy and splenomegaly, and was associated with the accumulation of CD4+CD44hiFOXP3– effector T cells, spontaneous multi-organ autoimmunity and early death26. Immunoregulation by TReg cell-expressed CTlA4 is due, at least in part, to the ability of CTlA4 to reduce the immunostimulatory activity of dendritic cells (DCs) in lymphoid tissues by downregulating their surface expression of the co-stimulatory ligands CD80 and CD86 (REF. 26). Additionally, CTlA4 ligation of CD80 and CD86 on DCs can induce expression of the immunosuppressive enzyme indoleamine 2,3-dioxygenase (IDO)27,28. Together, these activities can raise the threshold required for T cell activation, thereby preventing the priming of autoreactive T cells. Indeed, time-lapse imaging studies have revealed that TReg cells form long-lasting, stable contacts with DCs, and this has led to the hypothesis that a primary mode of TReg cell-mediated suppression within lymphoid tissues may be through inhibition of DC activation and/or function29,30. TReg cells can also induce perforin-dependent cytolysis of DCs in tumour-draining lymph nodes31. Thus, TReg cells use multiple mechanisms to limit DC activity in secondary lymphoid tissues, thereby quelling effector T cell activation and promoting functional tolerance. Accordingly, acute depletion of TReg cells in mice leads to the rapid development of systemic autoimmunity, associated with increases in both the number and activation state of DCs in lymphoid tissues32. The importance of TReg cell function in secondary lymphoid tissues extends beyond their integral role in preventing autoimmunity. For instance, depletion of TReg cells following intravaginal infection with herpes

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Figure 1 | Differing immunosuppressive mechanisms used by TReg cells in lymphoid and non-lymphoid tissues. Regulatory T (TReg) cells in secondary lymphoid tissues use multiple mechanisms to inhibit dendritic cell (DC) function and block initiation of autoimmunity or prevent tumour clearance. TReg cell production of interleukin-10 (IL-10) is essential for 0CVWTG4GXKGYU^+OOWPQNQI[ immunoregulation at mucosal tissues, such as the intestines and the lungs, and in the skin. In tissue-draining lymph nodes, TReg cells can inhibit the priming of effector T cells by preventing DC maturation (through cytotoxic T lymphocyte antigen 4 (CTLA4)-dependent mechanisms) or by killing mature DCs in a perforin- and granzyme-dependent manner. The relative importance of other immunosuppressive mechanisms used by TReg cells (central box) in lymphoid and non-lymphoid tissues remains to be established. LAG3, lymphocyte activation gene 3; TCR, T cell receptor; TGFβ, transforming growth factor-β.

simplex virus 2 (Hsv-2) accentuated T cell priming and proliferation in the draining lymph node, but prevented effector T cell mobilization from the lymph node to the vaginal epithelium, resulting in uncontrolled viral replication and death. These results highlight a previously unappreciated function of TReg cells in down-modulating immune responses in the lymphoid tissues to allow efficient effector T cell migration to sites of infection33. The spontaneous phenotypes of mice lacking either Il-10 or CTlA-4 in TReg cells demonstrate that these molecules are essential for proper TReg cell function in vivo. However, numerous other mechanisms have been implicated in TReg cell function in both lymphoid and non-lymphoid tissues in various experimental settings 34. These include production of additional immunosuppressive cytokines such as transforming growth factor-β (TGFβ) and Il-35, along with metabolic inhibition of effector T cells through adenosine

or cyclic AmP. Thus, TReg cells use a variety of immunosuppressive mechanisms to modulate both the initiation of the immune response in secondary lymphoid tissues and the progression and termination of inflammatory responses at non-lymphoid sites, and the choice of mechanism seems to be influenced by both the tissue site and the character of the inflammatory response. Indeed, it has been difficult to determine the importance of specific TReg cell immunoregulatory mechanisms, indicating that although TReg cells are clearly essential for establishing and maintaining tolerance, substantial functional redundancy may exist in the means that they use to do so. Further unravelling of the complex relationship between TReg cell localization and function is likely to yield important new insights into the functional diversity of TReg cells and increase our understanding of how specific immunomodulatory functions are delivered to different tissues during the course of the immune response.

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REVIEWS TReg cell control of distinct immune responses Functional specialization of TReg cells. CD4+ effector T cells can adopt one of several functional fates and elaborate distinct effector mechanisms depending on the cytokines that are present during their initial activation35. Production of these polarizing cytokines is dictated by the type of pathogen encountered, such that: TGFβ and Il-6 direct the development of Il-17-producing TH17 cells during extracellular bacterial or fungal infection; IFnγ and Il-12 drive the differentiation of IFnγproducing TH1 cells that help to combat intracellular pathogens; and Il-4 induces Il-4-producing TH2 cells during infection with large mucosal parasites36–38. The functional specialization of these various CD4+ T cell subsets is due to the differential expression of ‘master’ transcription factors, namely retinoic acid receptorrelated orphan receptor-γt (RORγt), T-bet and GATAbinding protein 3 (GATA3), which turn on distinct programmes of gene expression that control T cell function and migration39–41. However, each of these responses is pro-inflammatory and potentially harmful to host tissues. Accordingly, aberrant TH1, TH2 and TH17 cell responses can all contribute to immunopathology in the contexts of infection, autoimmunity, allergy and other inflammatory conditions42,43. Therefore, these distinct immune responses must be carefully regulated to ensure that they are initiated only when appropriate, and are efficiently resolved upon pathogen eradication or when the burden of tissue destruction outweighs the benefit of pathogen control. Indeed, defects in TReg cell function can result in TH1, TH2 or TH17 cell-mediated inflammatory disease, indicating that these cells are required for the proper regulation of multiple types of immune responses. Recently, several groups demonstrated that TReg cells use canonical TH cell-associated transcription factors to maintain or restore immune homeostasis during polarized TH1, TH2 and TH17 cell-driven immune responses. T-bet is the master transcription factor controlling the differentiation, migration and function of IFnγproducing TH1 cells. In addition, T-bet influences the generation of effector and memory CD8+ T cells, and regulates the homeostasis and function of natural killer (nK) cells, thereby coordinating the cellular immune response to intracellular infection40,44–46. Interestingly, T-bet is also expressed by a subset of TReg cells, and is required for TReg cell homeostasis and function during polarized TH1-type inflammatory responses47. T-bet+ TReg cells accumulate at sites of TH1-type inflammation, and T-bet-deficient TReg cells display impaired proliferation during TH1 cell-mediated immune responses, ultimately failing to control expansion of IFnγ-producing TH1 cells when transferred into FOXP3-deficient scurfy mice. similarly, TReg cell expression of interferon regulatory factor 4 (IRF4), a transcription factor involved in the control of Il-4 production by CD4+ T cells and in TH2 cell differentiation, is required for TReg cell-mediated control of TH2-type inflammatory responses48. mice in which Irf4 is specifically deleted within FOXP3+ TReg cells develop a lymphoproliferative disease that is associated with a selective increase in the number and frequency

of Il-4- and Il-5-producing CD4+ T cells, and have elevated serum levels of IgG1 and Ige. Consistent with this increase in serum antibodies, these animals also contain dramatically increased numbers of plasma cells and spontaneously develop splenic germinal centres. Interestingly, IRF4 is also crucial for the differentiation of T follicular helper (TFH) cells, which provide assistance to b cells and help to regulate antibody production in vivo49. The profound increase in germinal centre formation in mice with a TReg cell-specific Irf4 deletion, in the absence of an increase in Il-13-producing CD4+ T cell or eosinophil numbers, indicates that TReg cell expression of IRF4 may be required to control a specific component of TH2 cell-associated inflammation, namely aberrant TFH cell activation and high-affinity antibody production. Finally, deletion of signal transducer and activator of transcription 3 (Stat3) in TReg cells results in the development of spontaneous fatal intestinal inflammation that is characterized by excessive Il-17 production but normal levels of TH1 or TH2 cell-associated inflammatory cytokines, indicating that there is selective dysregulation of TH17-type responses in the absence of sTAT3-expressing TReg cells50. The mechanisms by which T-bet, IRF4 and sTAT3 control TReg cell activity during TH1, TH2 and TH17 cell-mediated responses are still unclear, but are likely to involve a combination of influences on TReg cell migration, function and homeostasis. For example, TReg cells that are deficient in T-bet, IRF4 or sTAT3 display impaired expression of chemokine receptors that are implicated in TReg cell localization during TH1-, TH2- or TH17-type inflammation (CXCR3, CCR8 and CCR6, respectively), suggesting that altered TReg cell migration may underlie some of the functional defects in these cells47,48,50. Additionally, loss of these transcription factors may affect the functional properties of TReg cells. Of note, TReg cells lacking T-bet, IRF4 or sTAT3 all show reduced expression of Il10 (REFs 47,48,50). moreover, IRF4-deficient or sTAT3-deficient TReg cells have reduced expression of other genes that are associated with TReg cell function, such as Icos (inducible T cell co-stimulator), Fgl2 (fibrinogen-like protein 2), Ebi3 (epstein–barr virus-induced gene 3; which encodes a component of the immunosuppressive cytokine Il-35), Prf1 (perforin 1) and Gzmb (granzyme b)48,50. by contrast, expression of Ctla4 is substantially increased in sTAT3-deficient TReg cells, whereas Tgfb1 expression was unaltered in TReg cells lacking any of the aforementioned transcription factors. Finally, loss of T-bet expression resulted in the impaired proliferation and accumulation of TReg cells during TH1-type inflammatory responses. Therefore, the failure of T-bet-deficient TReg cells to control TH1-driven inflammatory responses may result from their inability to survive and proliferate in a highly polarized TH1-type environment47. From these data, a model emerges in which selective expression or activation of transcriptional regulators associated with TH1, TH2 and TH17 cells drives the phenotypical and functional specialization of TReg cells, endowing them with the molecular machinery needed to restrain these different types of CD4+ T cell responses (FIG. 2). This model has important implications for the

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Figure 2 | Functional differentiation of TReg cells and TH cells. The differentiation of 0CVWTG4GXKGYU^+OOWPQNQI[ naive T cells into functionally distinct effector subsets, such as T helper 17 (TH17), TH1, TH2 and induced regulatory T (iTReg) cells, is dependent on the induction of the key transcriptional regulators retinoic acid receptor-related orphan receptor-γt (RORγt), T-bet, GATA-binding protein 3 (GATA3) and forkhead box P3 (FOXP3) following T cell receptor stimulation and cytokine-induced signal transducer and activator of transcription (STAT) activation. Comparably, thymus-derived TReg cells use specific molecular programmes driven by STAT3, T-bet or interferon regulatory factor 4 (IRF4) to restrain particular types of immune responses orchestrated by distinct effector T cell subsets. IFNγ, interferon-γ; IL, interleukin; TGFβ, transforming growth factor-β.

therapeutic use of TReg cells, as it implies that only specific subsets of TReg cells will be efficacious in treating TH1, TH2 or TH17 cell-mediated inflammatory diseases. Thus, it will be crucial in future studies to identify and characterize the cellular and molecular mechanisms that underlie the functional specialization of TReg cells, and to develop methods for selectively isolating and expanding different TReg cell subsets.

Environmental control of TReg cells The need to carefully modulate both the number and the activity of TReg cells to maintain the balance between autoimmunity and immunosuppression suggests that TReg cells pay close attention to the immune environment and alter their phenotype, migration and function in response to specific cues that they encounter in the periphery. Cytokines are a diverse group of mainly secreted proteins that control nearly all aspects of leukocyte biology. They do so by binding to specific receptors on the surface of cells, and these receptors transmit signals promoting cellular proliferation, activation, differentiation and/or death. broadly speaking, cytokines can be divided into those that are constitutively expressed and promote normal lymphocyte development and homeostasis, and those that are induced by specific inflammatory stimuli. Decades of research have demonstrated that both homeostatic and inflammatory

cytokines have a profound influence on the phenotypical and functional differentiation of the various T cell populations. In addition to cytokines, small nonprotein molecules such as steroids, sphingolipids and metabolites of vitamins A and D can also influence T cell differentiation, migration and function51–54. In the following sections, we discuss recent progress in understanding how TReg cells respond to the cytokines, vitamin metabolites and other factors that are present in the immune environment, and how this controls their activity in health and disease (FIG. 3).

Control of TReg cell homeostasis Common-γ-chain-signalling cytokines. by far the best studied cytokine in terms of its impact on the development, homeostasis and function of TReg cells is Il-2 (REF. 55). Indeed, TReg cells were initially identified based on their constitutive expression of the high-affinity Il-2 receptor component CD25. moreover, it is clear that Il-2 has an essential and non-redundant role in controlling TReg cell function in the periphery, as shown by the development of lymphoproliferative disease and colitis in mice that are deficient in either Il-2 or CD25. However, the precise manner by which Il-2 influences TReg cell function is still largely unknown. several studies have demonstrated that TReg cells occupy a distinct homeostatic ‘niche’, and this is thought to be controlled in part by access to Il-2 (REFs 56,57). Accordingly, blocking Il-2 activity in mice through the administration of Il-2-specific antibodies decreases the proliferation of CD4+CD25+ T cells and impairs TReg cell function58. These data have led to a model in which Il-2 produced by activated CD4+FOXP3– T cells acts in a paracrine manner to promote TReg cell proliferation and survival. However, both the frequency and the absolute number of peripheral TReg cells are largely normal in mice lacking either Il-2 or CD25, indicating that the homeostasis of TReg cells is more complicated than previously appreciated59,60 (BOX 2). In addition, the expression of CD25 varies substantially among different TReg cell populations, with activated CD44hi TReg cells generally being CD25low or CD25– (REF. 21). Interestingly, nearly all TReg cells in Il-2- or CD25-deficient mice belong to the CD44hi subset, and have increased expression of other activation markers such as CD69, CD103 and ICOs57. Although the activated phenotype of TReg cells in these mice is thought to be secondary to their inflammatory disease, an alternative interpretation of these results is that the crucial function of Il-2 is to help sustain the CD44lowCD25hi TReg cell subset, and that this population has a nonredundant function in preventing lymphoproliferative and autoimmune disease. The abundance of functional CD44hi TReg cells in Il-2- or CD25-deficient mice indicates that either the maintenance of these cells does not normally depend on Il-2, or other cytokines can compensate for loss of Il-2 in driving the homeostasis of this population. both Il-2 and Il-15 use the common γ-chain (also known as CD132) and CD122 as the signalling components of their receptors. As such, these two cytokines are thought to deliver very similar signals into cells, and

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REVIEWS thus could have redundant functions. For example, thymic development of TReg cells proceeds normally in mice with a single deficiency in Il-2, Il-15, CD25 or Il-15 receptor subunit-α (Il-15Rα), but is severely disrupted in CD122-deficient mice and mice that lack both Il-2 and Il-15 (REFs 59,60). In the periphery, Il-15 is ‘trans-presented’ in association with Il-15Rα on the surface of DCs, where it supports the homeostasis of CD8+ memory T cells and nK cells61. As previously discussed, TReg cells functionally interact with DCs in lymphoid tissues29,30, and this may grant them access to trans-presented Il-15 that could help to support their peripheral survival and function. However, the precise role of Il-15 in the Il-2-independent peripheral homeostasis of different TReg cell populations has not been explored.

by influencing the development and homeostasis of cutaneous and intestinal TReg cells. For example, retinoic acid produced from dietary vitamin A induces TReg cell expression of the intestinal homing receptors α4β7 integrin and CCR9 (REF. 62). Additionally, retinoic acid promotes the peripheral differentiation of induced TReg cells and helps to sustain TReg cell numbers and function during inflammatory responses63–66. Among DCs, the enzymes that convert vitamin A into retinoic acid are most prominently expressed in a population of CD103+ DCs that is found in the intestine and the gut-associated lymphoid tissues64,65. Thus, under steadystate conditions, retinoic acid produced by these DCs is thought to influence the balance of effector and regulatory T cells in the intestine, and help promote tolerance to commensal bacteria and food antigens. Although retinoic acid is primarily thought to promote TReg cell activity in the intestine, the active form of vitamin D (1,25-dihydroxyvitamin D3) can have similar effects in the skin, where vitamin D is produced in response to sunlight. 1,25-dihydroxyvitamin D3 can both augment the function of existing TReg cells and promote de novo differentiation of TReg cells from naive CD4+ T cell precursors, in a similar way to retinoic acid54,67.

Vitamin A and D metabolites. At barrier tissues such as the intestine and skin, the immune system faces the daunting task of ignoring the large number of commensal organisms and harmless environmental antigens but responding vigorously to enteric and cutaneous pathogens. Recent studies have demonstrated that metabolites of vitamins A and D can help to control this balance

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Figure 3 | modulation of TReg cell activity by different environmental factors. The vitamin A metabolite retinoic acid can boost regulatory T (TReg) cell activity within the intestine by inducing forkhead box P3 (FOXP3) expression in naive T cells and upregulating the expression of the gut-homing receptors CC-chemokine receptor 9 (CCR9) and α4β7 integrin on both TReg and induced TReg (iTReg) cells (left). During T helper 17 (TH17) cell-driven inflammation, interleukin-6 (IL-6) impairs TReg cell activity by directly blocking TReg function and by promoting TH17 cell differentiation at the expense of iTReg cell generation (right). During TH1-type inflammatory responses, such as those that occur following infection with Mycobacterium tuberculosis, interferon-γ (IFNγ) and IL-12 direct TH1 cell differentiation. Coordinately, IFNγ produced in response to infection directs the differentiation of T-bet+ TReg cells that are specialized to restrain pro-inflammatory TH1 cells (bottom). APC, antigen-presenting cell; CXCR3, CXC-chemokine receptor 3; DC, dendritic cell; EAE, experimental autoimmune encephalomyelitis; TCR, T cell receptor; TGFβ, transforming growth factor-β. 0CVWTG4GXKGYU^+OOWPQNQI[

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REVIEWS Box 2 | TReg cell homeostasis — beyond IL‑2 Lymphocyte homeostasis is the process by which various T and B cell populations are maintained at near constant frequencies in the periphery owing to their balanced generation, proliferation and death. The major cytokine thought to control regulatory T (TReg) cell homeostasis is interleukin-2 (IL-2). However, many other factors have been identified that influence TReg cell homeostasis. For example, TReg cell expression of the co-stimulatory molecule CD28 is required for their peripheral maintenance, and TReg cell numbers are substantially reduced in CD28-deficient mice108. Accordingly, these animals show enhanced susceptibility to autoimmune diabetes109. Given that TReg cells form long-lasting contacts with dendritic cells (DCs) in the secondary lymphoid tissues, it is also not surprising that TReg cell proliferation and abundance are highly sensitive to changes in DC frequency110. This is probably due to the ability of DCs to present self-antigens to TReg cells and to provide CD28-dependent co-stimulatory signals through CD80 and CD86 that can drive TReg cell activation and proliferation. Another molecule that influences TReg cell homeostasis is sphingosine-1-phosphate (S1P). S1P is best known for promoting lymphocyte egress from the thymus, spleen and lymph nodes. However, TReg cells overexpressing the S1P receptor S1P1 (also known as S1PR1) have a competitive disadvantage in the periphery, suggesting that S1P can also modulate the proliferation and/or survival of TReg cells through activation of the AKT–mTOR (mammalian target of rapamycin) pathway51. Other molecules implicated in TReg cell homeostasis include CD44, which can promote TReg cell proliferation upon binding to high-molecular-mass hyaluronan in the extracellular matrix111, and CC-chemokine receptor 4 (CCR4), which is required for the proper homeostasis of CD103hi cutaneous TReg cells10. Thus, TReg cell homeostasis is far more complex than currently appreciated, and much more work needs to be done to understand how TReg cell abundance is controlled in various tissues, both in the steady state and during the course of different types of immune responses.

moreover, 1,25-dihydroxyvitamin D3 produced by cutaneous DCs can induce T cell expression of CCR10, a chemokine receptor that is implicated in T cell localization to the epidermis68, although this has not been formally demonstrated in TReg cells. nonetheless, these data raise the intriguing possibility that anatomical cues delivered by metabolites that are enriched in the skin or the intestine can drive TReg cell specialization, endowing them with the migratory and functional properties needed for immunoregulation in these tissues.

Inflammatory cytokines and TReg cells During infection, cytokines that are produced in response to pathogen recognition by cells of the innate immune system initiate the inflammatory response, which is subsequently amplified by products of the adaptive immune response. These inflammatory cytokines have broad effects on the phenotypes, functions and migration of T cells and other leukocyte populations, and ultimately dictate the course of pathogen control. Additionally, dysregulated production of inflammatory cytokines underlies the pathogenesis of most autoimmune and inflammatory diseases. because of their central function in driving inflammatory responses, it is not surprising that many of these cytokines can also act directly on TReg cells, influencing their phenotype and activity in complex ways such that vigorous immune responses are allowed to occur when necessary, but generally with the restraint needed to prevent collateral damage and immunopathology. Indeed, this complexity is only beginning to be appreciated and addressed experimentally, and although not exhaustive, the following discussion highlights the fact that many cytokines

can have both positive and negative effects on TReg cell activity. Thus, careful analyses are still required to determine how TReg cell activity is augmented and inhibited by various inflammatory cytokines during different types of inflammatory responses. This promises to be a fruitful area of future study that will have considerable implications for the development of therapies aimed at manipulating TReg cell activity. IFNγ and IL-12. IFnγ and Il-12 function together to promote T H1 cell differentiation and function69. Additionally, IFnγ is the principal effector cytokine produced by TH1 cells, nK cells and CD8+ T cells, and is required for clearance of intracellular pathogens such as Mycobacterium tuberculosis, Leishmania major and Listeria monocytogenes70–72. similar to many other inflammatory cytokines, IFnγ actively inhibits the peripheral generation of FOXP3+ TReg cells from naive CD4+ cells73. However, IFnγ signalling through sTAT1 activation also drives T-bet expression by thymus-derived TReg cells, and as discussed in the preceding section, this endows them with the molecular machinery that is required for the efficient control of TH1-type responses47. Thus, in addition to being a pro-inflammatory cytokine essential for combating intracellular pathogens, IFnγ has an immunoregulatory function that may help to limit the magnitude and duration of TH1-type inflammatory responses. However, although IFnγ-induced signalling within TReg cells may be beneficial for the differentiation of functionally specialized T-bet+ TReg cells, excessive sTAT1 activation can have a deleterious effect on TReg cell function, resulting in excessive TH1 cell activity and inflammatory disease74. similarly, a recent study demonstrated that when Il-2 availability is limited during oral infection with Toxoplasma gondii, TReg cells become Il-12 responsive, express high amounts of T-bet and acquire the ability to produce IFnγ, subsequently contributing to the fatal intestinal immunopathology that develops during infection75. Thus, IFnγ and Il-12 can either promote or inhibit TReg cell activity depending on the magnitude of the cytokine response and the context in which it is perceived. These studies emphasize the need to precisely regulate TReg cell responses to these cytokines during TH1 cell-mediated inflammation, and underscore the complex and confounding impact that cytokines can have on TReg cell activity in vivo. IL-6. Il-6 is a widely expressed cytokine with multiple functions that can have a profound influence on TReg cell development and activity76,77. For example, Il-6 potently prevents the TGFβ-mediated development of induced TReg cells, and instead acts with TGFβ to induce TH17 cell differentiation78. Thus, the presence or absence of Il-6 can regulate the induction of pro-inflammatory and tolerogenic T cell responses, respectively. moreover, in addition to controlling the development of induced TReg cells, Il-6 can also influence the stability and function of thymus-derived TReg cells. For example, stimulation of TReg cells in the presence of Il-6 results in loss of FOXP3 expression and acquisition of a TH17 cell phenotype and function79,80. moreover, Il-6 produced downstream of

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REVIEWS Toll-like receptor ligation blocks TReg cell-mediated inhibition of T cell activation, and this is probably due both to direct effects of Il-6 on TReg cells, and to the ability of Il-6 to render effector T cells resistant to TReg cell-mediated suppression81. Although these studies emphasize the ability of Il-6 to inhibit TReg cell activity, the importance of sTAT3 for TReg cell-mediated control of T H17 responses raises the intriguing question: what are the important sTAT3-activating cytokines that act on TReg cells? Il-6 is a potent activator of sTAT3, and thus it is tempting to speculate that, as with IFnγ and sTAT1 during TH1 cell responses, Il-6 simultaneously promotes TH17 cell differentiation while acting on TReg cells through sTAT3 to maximize their ability to modulate TH17-type responses. However, several other cytokines also activate sTAT3, including Il-10, Il-27 and Il-21, and the impact of these cytokines on TReg cell activity during TH17-type responses remains to be determined. nonetheless, it is clear that the presence or absence of Il-6 can modulate TReg cell activity during inflammatory responses. As drugs that target Il-6 reach the clinic82, it will be interesting to determine how Il-6 blockade affects the abundance, phenotype and functional activity of TReg cells in the context of immunemediated diseases such as rheumatoid arthritis and inflammatory bowel disease. IL-4. Il-4 is a key effector cytokine produced by TH2 cells, and is also required for TH2 cell differentiation. However, although the effects of Il-4 on TH2 cell differentiation and function are well characterized, its impact on TReg cell stability and function are not well understood. Indeed, like many other inflammatory cytokines, Il-4 can both augment and inhibit TReg cell development and function in different experimental settings. For instance, similar to Il-6, Il-4 can inhibit TGFβ-induced peripheral TReg cell development and act with TGFβ to drive development of a recently described population of Il-9-producing effector T cells83,84. Additionally, Il-4 is thought to render TH2 cells resistant to TReg cell-mediated suppression85. by contrast, Il-4 stimulation of TReg cells can boost their expression of CD25 and FOXP3, prevent their apoptosis and increase their suppressive function in vitro85,86. Thus, the effects of Il-4 on TReg cells clearly require further investigation and probably depend on other factors, such as the presence or absence of TGFβ in the inflammatory environment. Type 1 IFNs. The type 1 IFns are a group of more than a dozen closely related cytokines that are highly upregulated during viral infection. They function to block viral replication and to qualitatively and quantitatively influence the antiviral adaptive immune response. However, overproduction of type 1 IFns has been associated with a variety of autoimmune disorders87. surprisingly, despite the dramatic effects type 1 IFns can have on conventional CD4+ and CD8+ effector T cells, and the clear association between type 1 IFn production and the development of autoimmunity, the effects of type 1 IFns on the development, homeostasis and function of

TReg cells are largely unexplored. several studies have indicated that IFnβ treatment can help to restore the number and function of TReg cells in patients with multiple sclerosis88,89. by contrast, stimulation with IFnα inhibited TReg cell generation in an in vitro culture system, although this was largely due to inhibition of effector T cell production of Il-2 (REF. 90). Clearly, further defining how type 1 IFns affect TReg cells will help delineate how TReg cell activity is controlled during acute and chronic viral infections and in type 1 IFn-associated autoimmune diseases. TNF and IL-1. Tumour necrosis factor (TnF) and Il-1 are both pleiotropic cytokines that act on a wide range of cells and generally promote inflammation. Indeed, both TnF and Il-1 have been successfully targeted therapeutically for the treatment of a number of inflammatory and autoimmune diseases, including rheumatoid arthritis, psoriasis and inflammatory bowel disease91. It is not surprising, therefore, that these cytokines can significantly affect TReg cell function. Although TnF is primarily known for its pro-inflammatory functions, most current evidence indicates that upon binding and signalling through TnF receptor 2 (TnFR2; also known as TnFRsF1b) this cytokine actually potentiates TReg cell activity92. Indeed, TnFR2 is expressed by a subset of effector or memory phenotype TReg cells that are highly suppressive, and in vitro treatment of mouse TReg cells with TnF can augment their proliferation and suppressive activity93. Furthermore, blockade of TnF actually exacerbates cutaneous inflammation in a mouse model of psoriasis, and this is associated with decreased frequency of TReg cells 94. similarly, TnF–TnFR2 interactions may control TReg cell population expansion during cecal ligation and puncture (ClP) in mice93, although the requirement for direct recognition of TnF by TReg cells was not addressed in either the psoriasis or ClP studies. The impact of Il-1 on TReg cell function is still poorly understood. Although Il-1 has been shown to potentiate expansion of FOXP3+ cells from cultures of CD4+CD25+ cells, this was caused by effects of Il-1 on FOXP3– cells, and Il-1 did not directly augment proliferation of FOXP3 + cells95. In fact, in conjunction with Il-2, Il-1 acts to convert TReg cells into FOXP3– TH17 cells96.

Stability of TReg cells The ability of cytokines such as Il-1, Il-6 and Il-12 to downregulate FOXP3 expression and convert TReg cells into pro-inflammatory effector cells suggests that TReg cells retain some functional plasticity. Indeed, a subject of recent controversy is the extent to which TReg cells can extinguish FOXP3 expression and convert to conventional FOXP3– effector T cells. TReg cells induced by TGFβ in the periphery show incomplete demethylation of the Foxp3 locus, and this is associated with unstable FOXP3 expression97. However, several studies have demonstrated that even thymic-derived TReg cells can convert to an effector phenotype following transfer into lymphopenic recipients98–100 and during ex vivo stimulation with inflammatory cytokines79,80,96.

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REVIEWS To determine whether a portion of TReg cells convert to an effector phenotype following transfer to lymphopenic mice, two groups recently generated mice that were engineered to track the fate of FOXP3+ cells in vivo. In these systems, mice expressing the Cre recombinase in TReg cells under the control of regulatory elements from the Foxp3 gene were crossed with mice in which Cre-mediated recombination removes a stop codon from within a fluorescent-protein-encoding reporter gene that was knocked in to the ubiquitously expressed Rosa26 locus. Thus, in these animals, cells even transiently expressing FOXP3 are permanently marked, and their phenotypical and functional properties can be spatially and temporally examined. using this system, bluestone and colleagues observed that a portion of CD4+FOXP3+ T cells downregulate FOXP3 expression and acquire the ability to produce effector cytokines such as IFnγ, even in the absence of any experimental manipulation. Furthermore, the frequency of these ‘ex-TReg cells’ was increased in the pancreatic islets of non-obese diabetic (nOD) mice, indicating that they may contribute to autoimmune pathology101. These data are complemented by another recent study demonstrating that during infection with Toxoplasma gondii, TReg cells can lose FOXP3 expression and acquire TH1 cell effector characteristics75. Together, these studies suggest that highly polarized inflammatory environments can subvert TReg cell function by converting them to FOXP3– effector T cells in vivo, and are consistent with a recent epigenetic analysis demonstrating that the loci encoding the key transcription factors and cytokines that are associated with TH1, TH2 and TH17 cells are not fully repressed in TReg cells102. However, using a similar reporter mouse system to monitor TReg cell stability, Rudensky’s group recently demonstrated that FOXP3 expression by TReg cells is remarkably stable, even in highly inflammatory settings103. The discrepancies in these studies may be due to differences in the inflammatory systems used to examine TReg cell stability in vivo, or to subtle differences in the way the reporter mice were constructed. bluestone’s group drove Cre expression using a bacterial artificial chromosome (bAC) transgene, whereas Rudensky’s group knocked a Cre expression cassette into the 3ʹ untranslated region of the endogenous Foxp3 locus. This may have led to differences in the timing and extent of Cre expression that resulted in the divergent conclusions of these studies.

1. 2. 3.

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Sakaguchi, S., Yamaguchi, T., Nomura, T. & Ono, M. Regulatory T cells and immune tolerance. Cell 133, 775–787 (2008). Horwitz, D. A. Regulatory T cells in systemic lupus erythematosus: past, present and future. Arthritis Res. Ther. 10, 227 (2008). Viglietta, V., Baecher-Allan, C., Weiner, H. L. & Hafler, D. A. Loss of functional suppression by CD4+CD25+ regulatory T cells in patients with multiple sclerosis. J. Exp. Med. 199, 971–979 (2004). Ehrenstein, M. R. et al. Compromised function of regulatory T cells in rheumatoid arthritis and reversal by anti-TNFα therapy. J. Exp. Med. 200, 277–285 (2004). Lindley, S. et al. Defective suppressor function in CD4+CD25+ T-cells from patients with type 1 diabetes. Diabetes 54, 92–99 (2005). Belkaid, Y. Regulatory T cells and infection: a dangerous necessity. Nature Rev. Immunol. 7, 875–888 (2007).

In discussing the stability of TReg cells, it is also important to keep in mind the differences in FOXP3 expression that have been observed in mouse and human T cells. In mice, FOXP3 seems to be a robust marker for thymicderived and induced TReg cells. However, nearly all human CD4+ T cells transiently express FOXP3 during activation, and this is not associated with acquisition of regulatory function. Thus, FOXP3 alone is not a reliable marker for human TReg cells, further complicating analyses of their function and stability. moreover, because thymic output is severely curtailed following puberty and fewer TReg cells emerge from the thymus, the less-stable induced TReg cells may assume a greater role in maintaining immune homeostasis in adults104. Clearly, the degree to which TReg cells can acquire effector functions and contribute to the development of autoimmune and inflammatory diseases merits further study, and careful attention must be paid to the potential differences between mouse and human systems.

Concluding remarks TReg cells have emerged as potent anti-inflammatory cells, and this has generated considerable excitement because of the potential to therapeutically manipulate TReg cell activity to treat autoimmune disease, prevent graft rejection, and boost immune responses during cancer and chronic infection105. However, it is now evident that TReg cells are a dynamic and diverse T cell population composed of several phenotypically and functionally distinct subsets, the differentiation and function of which are controlled by specific signals in the immune environment. Thus, in order to optimally utilize TReg cells in the clinic, it is essential that we better understand how these subsets function together to ensure that robust immune responses can occur when needed without the development of significant immunopathology and inflammatory disease. Key unresolved issues include: defining the importance of each TReg cell subset in the control of different types of inflammatory responses; identifying the factors that govern the peripheral differentiation of these subsets; and determining how cytokines and other factors in the immune environment influence TReg cell activity and stability during the initiation, progression and termination of normal and pathological immune responses.

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60. Soper, D. M., Kasprowicz, D. J. & Ziegler, S. F. IL-2Rβ links IL-2R signaling with Foxp3 expression. Eur. J. Immunol. 37, 1817–1826 (2007). 61. Burkett, P. R. et al. Coordinate expression and trans presentation of interleukin (IL)-15Rα and IL-15 supports natural killer cell and memory CD8+ T cell homeostasis. J. Exp. Med. 200, 825–834 (2004). 62. Siewert, C. et al. Induction of organ-selective CD4+ regulatory T cell homing. Eur. J. Immunol. 37, 978–989 (2007). 63. Mucida, D. et al. Reciprocal TH17 and regulatory T cell differentiation mediated by retinoic acid. Science 317, 256–260 (2007). 64. Coombes, J. L. et al. A functionally specialized population of mucosal CD103+ DCs induces Foxp3+ regulatory T cells via a TGF-β and retinoic aciddependent mechanism. J. Exp. Med. 204, 1757–1764 (2007). 65. Sun, C. M. et al. Small intestine lamina propria dendritic cells promote de novo generation of Foxp3 T reg cells via retinoic acid. J. Exp. Med. 204, 1775–1785 (2007). 66. Zhou, X. et al. Cutting edge: all-trans retinoic acid sustains the stability and function of natural regulatory T cells in an inflammatory milieu. J. Immunol. 185, 2675–2679 (2010). 67. Gorman, S. et al. Topically applied 1,25-dihydroxyvitamin D3 enhances the suppressive activity of CD4+CD25+ cells in the draining lymph nodes. J. Immunol. 179, 6273–6283 (2007). 68. Sigmundsdottir, H. et al. DCs metabolize sunlightinduced vitamin D3 to ‘program’ T cell attraction to the epidermal chemokine CCL27. Nature Immunol. 8, 285–293 (2007). 69. Murphy, K. M. et al. T helper differentiation proceeds through Stat1-dependent, Stat4-dependent and Stat4-independent phases. Curr. Top. Microbiol. Immunol. 238, 13–26 (1999). 70. Cooper, A. M. et al. Disseminated tuberculosis in interferon γ gene-disrupted mice. J. Exp. Med. 178, 2243–2247 (1993). 71. Harty, J. T. & Bevan, M. J. Specific immunity to Listeria monocytogenes in the absence of IFNγ. Immunity. 3, 109–117 (1995). 72. Wang, Z. E., Reiner, S. L., Zheng, S., Dalton, D. K. & Locksley, R. M. CD4+ effector cells default to the Th2 pathway in interferon γ-deficient mice infected with Leishmania major. J. Exp. Med. 179, 1367–1371 (1994). 73. Caretto, D., Katzman, S. D., Villarino, A. V., Gallo, E. & Abbas, A. K. Cutting edge: the Th1 response inhibits the generation of peripheral regulatory T cells. J. Immunol. 184, 30–34 (2010). 74. Lu, L. F. et al. Function of miR-146a in controlling Treg cell-mediated regulation of Th1 responses. Cell 142, 914–929 (2010). This study demonstrated that the microRNA miR-146a dampens STAT1 activity in TReg cells and prevents them from acquiring pro-inflammatory effector functions. 75. Oldenhove, G. et al. Decrease of Foxp3+ Treg cell number and acquisition of effector cell phenotype during lethal infection. Immunity. 31, 772–786 (2009). This paper showed that during intestinal infection with Toxoplasma gondii, TReg cells downregulate FOXP3, acquire TH1 effector functions and contribute to infection-associated immunopathology. 76. Kishimoto, T. IL-6: from its discovery to clinical applications. Int. Immunol. 22, 347–352 (2010). 77. Bettelli, E., Oukka, M. & Kuchroo, V. K. TH-17 cells in the circle of immunity and autoimmunity. Nature Immunol. 8, 345–350 (2007). 78. Bettelli, E. et al. Reciprocal developmental pathways for the generation of pathogenic effector TH17 and regulatory T cells. Nature 441, 235–238 (2006). This study defined the role of IL-6 in controlling TH17 and iTReg cell differentiation. 79. Zheng, S. G., Wang, J. & Horwitz, D. A. Cutting edge: Foxp3+CD4+CD25+ regulatory T cells induced by IL-2 and TGF-β are resistant to Th17 conversion by IL-6. J. Immunol. 180, 7112–7116 (2008). 80. Xu, L., Kitani, A., Fuss, I. & Strober, W. Cutting edge: regulatory T cells induce CD4+CD25–Foxp3– T cells or are self-induced to become Th17 cells in the absence of exogenous TGF-β. J. Immunol. 178, 6725–6729 (2007). 81. Pasare, C. & Medzhitov, R. Toll pathway-dependent blockade of CD4+CD25+ T cell-mediated suppression by dendritic cells. Science 299, 1033–1036 (2003).

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REVIEWS 82. Mima, T. & Nishimoto, N. Clinical value of blocking IL-6 receptor. Curr. Opin. Rheumatol. 21, 224–230 (2009). 83. Dardalhon, V. et al. IL-4 inhibits TGF-β-induced Foxp3+ T cells and, together with TGF-β, generates IL-9+ IL-10+ Foxp3– effector T cells. Nature Immunol. 9, 1347–1355 (2008). 84. Veldhoen, M. et al. Transforming growth factor-β ‘reprograms’ the differentiation of T helper 2 cells and promotes an interleukin 9-producing subset. Nature Immunol. 9, 1341–1346 (2008). 85. Pillemer, B. B. et al. STAT6 activation confers upon T helper cells resistance to suppression by regulatory T cells. J. Immunol. 183, 155–163 (2009). 86. Maerten, P. et al. Effects of interleukin 4 on CD25+CD4+ regulatory T cell function. J. Autoimmun. 25, 112–120 (2005). 87. Trinchieri, G. Type I interferon: friend or foe? J. Exp. Med. 207, 2053–2063 (2010). 88. Namdar, A., Nikbin, B., Ghabaee, M., Bayati, A. & Izad, M. Effect of IFN-β therapy on the frequency and function of CD4+CD25+ regulatory T cells and Foxp3 gene expression in relapsing-remitting multiple sclerosis (RRMS): a preliminary study. J. Neuroimmunol. 218, 120–124 (2010). 89. Vandenbark, A. A. et al. Interferon-β-1a treatment increases CD56bright natural killer cells and CD4+CD25+ Foxp3 expression in subjects with multiple sclerosis. J. Neuroimmunol. 215, 125–128 (2009). 90. Golding, A., Rosen, A., Petri, M., Akhter, E. & Andrade, F. Interferon-α regulates the dynamic balance between human activated regulatory and effector T cells: implications for antiviral and autoimmune responses. Immunology 131, 107–117 (2010). 91. Hoffman, H. M. Therapy of autoinflammatory syndromes. J. Allergy Clin. Immunol. 124, 1129–1138 (2009). 92. Chen, X. & Oppenheim, J. J. TNF-α: an activator of CD4+FoxP3+TNFR2+ regulatory T cells. Curr. Dir. Autoimmun. 11, 119–134 (2010). 93. Chen, X., Baumel, M., Mannel, D. N., Howard, O. M. & Oppenheim, J. J. Interaction of TNF with TNF receptor type 2 promotes expansion and function of mouse CD4+CD25+ T regulatory cells. J. Immunol. 179, 154–161 (2007). 94. Ma, H. L. et al. Tumor necrosis factor α blockade exacerbates murine psoriasis-like disease by enhancing Th17 function and decreasing expansion of Treg cells. Arthritis Rheum. 62, 430–440 (2010). 95. Brinster, C. & Shevach, E. M. Costimulatory effects of IL-1 on the expansion/differentiation of CD4+CD25+Foxp3+ and CD4+CD25+Foxp3– T cells. J. Leukoc. Biol. 84, 480–487 (2008). 96. Deknuydt, F., Bioley, G., Valmori, D. & Ayyoub, M. IL-1β and IL-2 convert human Treg into TH17 cells. Clin. Immunol. 131, 298–307 (2009). 97. Floess, S. et al. Epigenetic control of the foxp3 locus in regulatory T cells. PLoS. Biol. 5, e38 (2007). 98. Tsuji, M. et al. Preferential generation of follicular B helper T cells from Foxp3+ T cells in gut Peyer’s patches. Science 323, 1488–1492 (2009). 99. Komatsu, N. et al. Heterogeneity of natural Foxp3+ T cells: a committed regulatory T-cell lineage and an uncommitted minor population retaining plasticity. Proc. Natl Acad. Sci. USA 106, 1903–1908 (2009).

100. Gavin, M. A. et al. Foxp3-dependent programme of regulatory T-cell differentiation. Nature 445, 771–775 (2007). 101. Zhou, X. et al. Instability of the transcription factor Foxp3 leads to the generation of pathogenic memory T cells in vivo. Nature Immunol. 10, 1000–1007 (2009). 102. Wei, G. et al. Global mapping of H3K4me3 and H3K27me3 reveals specificity and plasticity in lineage fate determination of differentiating CD4+ T cells. Immunity. 30, 155–167 (2009). By performing genome-wide analysis of histone modification, this study demonstrated the potential for substantial functional plasticity in CD4+ T cell subsets. 103. Rubtsov, Y. P. et al. Stability of the regulatory T cell lineage in vivo. Science 329, 1667–1671 (2010). Along with reference 101, this study used lineage tracing to examine the phenotypical and functional stability of TReg cells in different immune settings. 104. Akbar, A. N., Vukmanovic-Stejic, M., Taams, L. S. & Macallan, D. C. The dynamic co-evolution of memory and regulatory CD4+ T cells in the periphery. Nature Rev. Immunol. 7, 231–237 (2007). 105. Allan, S. E. et al. CD4+ T-regulatory cells: toward therapy for human diseases. Immunol. Rev. 223, 391–421 (2008). 106. Picca, C. C. et al. Role of TCR specificity in CD4+ CD25+ regulatory T-cell selection. Immunol. Rev. 212, 74–85 (2006). 107. Lathrop, S. K., Santacruz, N. A., Pham, D., Luo, J. & Hsieh, C. S. Antigen-specific peripheral shaping of the natural regulatory T cell population. J. Exp. Med. 205, 3105–3117 (2008). 108. Tang, Q. et al. Cutting edge: CD28 controls peripheral homeostasis of CD4+CD25+ regulatory T cells. J. Immunol. 171, 3348–3352 (2003). 109. Salomon, B. et al. B7/CD28 costimulation is essential for the homeostasis of the CD4+CD25+ immunoregulatory T cells that control autoimmune diabetes. Immunity. 12, 431–440 (2000). 110. Darrasse-Jeze, G. et al. Feedback control of regulatory T cell homeostasis by dendritic cells in vivo. J. Exp. Med. 206, 1853–1862 (2009). This paper demonstrated that, in vivo, TReg cell and DC homeostasis are intricately linked. 111. Bollyky, P. L. et al. Intact extracellular matrix and the maintenance of immune tolerance: high molecular weight hyaluronan promotes persistence of induced CD4+CD25+ regulatory T cells. J. Leukoc. Biol. 86, 567–572 (2009). 112. Venturi, G. M., Conway, R. M., Steeber, D. A. & Tedder, T. F. CD25+CD4+ regulatory T cell migration requires L-selectin expression: L-selectin transcriptional regulation balances constitutive receptor turnover. J. Immunol. 178, 291–300 (2007). 113. Szanya, V., Ermann, J., Taylor, C., Holness, C. & Fathman, C. G. The subpopulation of CD4+CD25+ splenocytes that delays adoptive transfer of diabetes expresses L-selectin and high levels of CCR7. J. Immunol. 169, 2461–2465 (2002). 114. Hirahara, K. et al. The majority of human peripheral blood CD4+CD25highFoxp3+ regulatory T cells bear functional skin-homing receptors. J. Immunol. 177, 4488–4494 (2006). 115. Siegmund, K. et al. Migration matters: regulatory T-cell compartmentalization determines suppressive activity in vivo. Blood 106, 3097–3104 (2005).

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116. Denning, T. L., Kim, G. & Kronenberg, M. Cutting edge: CD4+CD25+ regulatory T cells impaired for intestinal homing can prevent colitis. J. Immunol. 174, 7487–7491 (2005). 117. Lim, H. W., Lee, J., Hillsamer, P. & Kim, C. H. Human Th17 cells share major trafficking receptors with both polarized effector T cells and FOXP3+ regulatory T cells. J. Immunol. 180, 122–129 (2008). 118. Yuan, Q. et al. CCR4-dependent regulatory T cell function in inflammatory bowel disease. J. Exp. Med. 204, 1327–1334 (2007). 119. Kang, S. G. et al. Identification of a chemokine network that recruits FoxP3+ regulatory T cells into chronically inflamed intestine. Gastroenterology 132, 966–981 (2007). 120. Yurchenko, E. et al. CCR5-dependent homing of naturally occurring CD4+ regulatory T cells to sites of Leishmania major infection favors pathogen persistence. J. Exp. Med. 203, 2451–2460 (2006). 121. Kleinewietfeld, M. et al. CCR6 expression defines regulatory effector/memory-like cells within the CD25+CD4+ T cell subset. Blood 105, 2877–2886 (2004). 122. Hirota, K. et al. Preferential recruitment of CCR6-expressing Th17 cells to inflamed joints via CCL20 in rheumatoid arthritis and its animal model. J. Exp. Med. 204, 2803–2812 (2007). 123. Soler, D. et al. CCR8 expression identifies CD4 memory T cells enriched for FOXP3+ regulatory and Th2 effector lymphocytes. J. Immunol. 177, 6940–6951 (2006). 124. Guo, Z. et al. CD4+CD25+ regulatory T cells in the small intestinal lamina propria show an effector/ memory phenotype. Int. Immunol. 20, 307–315 (2008). 125. Eksteen, B. et al. Epithelial inflammation is associated with CCL28 production and the recruitment of regulatory T cells expressing CCR10. J. Immunol. 177, 593–603 (2006). 126. Oo, Y. H. et al. Distinct roles for CCR4 and CXCR3 in the recruitment and positioning of regulatory T cells in the inflamed human liver. J. Immunol. 184, 2886–2898 (2010). 127. Lim, H. W., Broxmeyer, H. E. & Kim, C. H. Regulation of trafficking receptor expression in human forkhead box P3+ regulatory T cells. J. Immunol. 177, 840–851 (2006). 128. Lim, H. W., Hillsamer, P. & Kim, C. H. Regulatory T cells can migrate to follicles upon T cell activation and suppress GC-Th cells and GC-Th cell-driven B cell responses. J. Clin. Invest. 114, 1640–1649 (2004). 129. Grauer, O. M. et al. CD4+FoxP3+ regulatory T cells gradually accumulate in gliomas during tumor growth and efficiently suppress antiglioma immune responses in vivo. Int. J. Cancer 121, 95–105 (2007). 130. Wald, O. et al. CD4+CXCR4highCD69+ T cells accumulate in lung adenocarcinoma. J. Immunol. 177, 6983–6990 (2006).

Acknowledgements

The authors would like to thank all past and present members of the Campbell lab for interesting discussions and intellectual input essential to this Review.

Competing interests statement

The authors declare no competing financial interests.

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REVIEWS

Presumed guilty: natural killer T cell defects and human disease Stuart P. Berzins*, Mark J. Smyth‡ and Alan G. Baxter§

Abstract | Natural killer T (NKT) cells are important regulatory lymphocytes that have been shown in mouse studies, to have a crucial role in promoting immunity to tumours, bacteria and viruses, and in suppressing cell-mediated autoimmunity. Many clinical studies have indicated that NKT cell deficiencies and functional defects might also contribute to similar human diseases, although there is no real consensus about the nature of the NKT cell defects or whether NKT cells could be important for the diagnosis and/or treatment of these conditions. In this Review, we describe the approaches that have been used to analyse the NKT cell populations of various patient groups, suggest new strategies to determine how (or indeed, if) NKT cell defects contribute to human disease, and discuss the prospects for using NKT cells for therapeutic benefit.

*Department of Microbiology & Immunology, University of Melbourne, Parkville, Victoria 3010, Australia. ‡ Cancer Immunology Program, Peter MacCallum Cancer Centre, East Melbourne, Victoria 3002, Australia. § Comparative Genomics Centre, Molecular Sciences Building 2, James Cook University, Townsville, Queensland 4811, Australia. Correspondence to S.P.B. e‑mail: [email protected] doi:10.1038/nri2904

Natural killer T (NKT) cells are a small population of thymus-derived T cells that are found in mice and humans and are restricted by the non-classical MHC class I molecule CD1d. The term NKT cell was initially used to refer to any T cell that expresses cell surface antigens associated with the NK cell lineage, but this classification of NKT cells is problematic because it does not define a T cell lineage with unique phenotypical or functional attributes. Even among CD1d-restricted T cells, distinct lineages that can express NK cell antigens1 include type 1 NKT cells (also known as invariant NKT (iNKT) cells), which express the invariant Vα24–Jα18 T cell receptor (TCR) α-chain, and type 2 NKT cells, which have a more diverse TCR repertoire. There are also CD1d-restricted T cells with an invariant TCR that is distinct from the TCR of type 1 NKT cells that can also express NK cell antigens. As such, many of the pioneering studies that reported NKT cell defects in humans with disease examined heterogeneous cell populations that included some or all of these cell types, as well as MHC-restricted T cells that express the NK cell markers CD56 and/or CD161. As a result, early studies of NKT cells can inadvertently provide ambiguous information about type 1 NKT cells, because these cells have emerged as the most well studied type of NKT cell and are now often referred to as NKT cells without further qualification. For clarity, here we also use the term NKT cells to describe type 1 NKT cells. In this Review, we examine the evidence that defects that affect these cells contribute to human disease, including evidence from studies where some data and conclusions may need revisiting because of the way in which NKT cells were identified and analysed.

NKT cell heterogeneity NKT cells are known for their potent cytokine production and immunoregulatory potential. They express a semi-invariant TCR that confers a specificity for glycolipid antigens that is mainly conserved between mice and humans1. This implies that NKT cells recognize a restricted set of important antigens, although such antigens have been frustratingly difficult to identify. The best-known NKT cell antigen is α-galactosylceramide (αGalCer), which is used as the prototypical antigen for stimulating NKT cells and for identifying them using αGalCer-loaded CD1d multimers2. Activated NKT cells release large amounts of cytokines that can alter the strength and character of immune responses through crosstalk with dendritic cells, neutrophils, lymphocytes and myeloid-derived suppressor cells, and by shifting cytokine responses to (or from) a T helper 1 (TH1), TH2 or TH17 cell-type profile3–6. Mature NKT cells from mice and humans can be divided into functionally distinct CD4 +CD8 – and CD4 –CD8 – subsets 7,8, and humans also have a CD4–CD8+ NKT cell subset that is not found in mice9,10. Human CD4+CD8– NKT cells are broadly associated with T H0-type immune responses, whereas CD4 – NKT cells have a TH1 cell-type phenotype8,10. However, there is marked heterogeneity in the expression of functionally important cell surface receptors and cytokines by CD4+ and CD4– NKT cells8–11, which indicates that additional subsets might also exist. Indeed, the functional versatility of NKT cells is increasingly being attributed to NKT cell subsets with distinct cytokine

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REVIEWS Table 1 | Comparison of the characteristics of mouse and human NKT cells Characteristic

mouse

Human

Semi-invariant T cell receptor

Yes (Vα14–Jα18/Vβ8, Vβ7 or Vβ2)

Yes (Vα24/Vβ11)

CD1d restricted

Yes

Functionally distinct mature NKT cell subsets

CD4 CD8 , CD4 CD8 , NK1.1 and NK1.1

CD4+CD8–, CD4–CD8– and CD4–CD8+

Expression of NK cell markers*

Yes (for example, NK1.1, CD49b, NKG2A, NKG2C, NKG2D, NKG2E and Ly49a)

Yes (for example, CD161, CD56 and CD16)

Development in the thymus

Yes, all mature subsets develop in the thymus

Yes, although functional maturity is reached in the periphery. CD4– NKT cell subsets develop in the periphery

Potent cytokine production‡

Yes (TNF, IFNγ, IL-2, IL-4, IL-10, IL-13, IL-17, IL-21, IL-22 and GMCSF)

Yes (TNF, IFNγ, IL-4, IL-10, IL-13 and GMCSF)

Present at birth

No, first detected at ~day 5 after birth

Yes, mostly CD4+ NKT cell subsets at birth. The CD4– NKT cell subset emerges with age

Cytotoxic activity§

Yes, NKT cells can participate in perforin-, CD95–CD95L- and TNF-induced cytotoxicity

Yes, NKT cells can participate in perforin-, CD95–CD95L- and TNF-induced cytotoxicity and express granulysin

Glycolipid antigens

Yes, including αGalCer and analogues

Yes, including αGalCer and analogues

Frequency in the blood

0.2–0.5%

0.01–0.5% (highly variable; reported frequencies range from undetectable to >3%)

Relative NKT cell frequency in tissues (as a % of total lymphocytes)||

• Highest in liver (~30%) • Similar in thymus, spleen, bone marrow and blood (0.2–0.5%) • Lowest in lymph nodes (0.1–0.2%), although can vary between lymph nodes

• Highest in liver (~1%) and omentum (~10%) • Similar in spleen, blood, bone marrow and lymph nodes (0.01–0.5%; typically 0.01–0.1%) • Lower in thymus (<0.001–0.01%)

Relative cytokine production by NKT cells in tissues||

Potent cytokine production by NKT cells from all tissues

Potent cytokine production by NKT cells from blood. NKT cells from the thymus are poor cytokine producers

Relative protection provided by NKT cells from specific tissues

• NKT cells from the thymus protect against type 1 diabetes. NKT cells from other tissues not tested • Liver NKT cells offer best protection against tumours. Thymus and spleen NKT cells are less effective

Not tested

Yes +

–

–

–

+

–

*NK cell marker expression by NKT cells is heterogeneous and varies between individuals. ‡The cytokine profile varies between NKT cell subsets. §Cytotoxicity is not considered to be a main function of NKT cells. ||Relative NKT cell frequencies and cytokine production have only been extensively characterized in the thymus and blood for humans. αGalCer, α-galactosylceramide; GMCSF, granulocyte/macrophage colony stimulating factor; IFNγ, interferon-γ; IL, interleukin; NKT cell, natural killer T cell; TNF, tumour necrosis factor.

profiles12, and there is evidence that alterations to the structure of glycolipid ligands can affect the cytokine responses of NKT cells through selective stimulation of particular NKT cell subsets. An important difference between human and mouse NKT cells relates to their frequency (TABLE 1). In mice, NKT cells constitute 0.2–0.5% of lymphocytes (and 0.5–2% of total T cells) in the thymus, spleen, blood and bone marrow, and 15–35% of liver lymphocytes (30–50% of liver T cells). In humans, the frequency of NKT cells is lower and more variable, although it remains stable within individuals13,14. NKT cells usually account for between 0.001% and 3% (typically 0.01–0.1%) of human peripheral blood mononuclear cells (PbMCs)8,15 and there are similar frequencies of NKT cells in human bone marrow and spleen14. The frequency of human NKT cells is lower in the thymus (~0.001–0.01% of lymphocytes)16,17 and higher in the liver (~1%)18 and omentum (10%)19. Humans have higher frequencies than mice of other innate and innate-like T cells — such as type 2 NKT cells20, mucosal-associated invariant T (MAIT) cells 21 and

CD1a-, CD1b- and CD1c-restricted T cells22 — which could suggest that these cell types might compensate functionally for the comparatively smaller number of NKT cells in humans. Most of the direct evidence supporting a role for NKT cell defects in disease comes from mice that are completely deficient for NKT cells. These mice are generally healthy, but they are predisposed to the development of autoimmunity and cancer, and they have impaired immune responses to pathogens in some settings23,24. Research interest in human NKT cells increased markedly following reports of NKT cell defects in patients with autoimmune diseases, cancer and infections23,25. However, for most of these conditions, the NKT cell defect has been only partially characterized and in some cases has been disputed by contradictory studies. one problem is that many of the human studies used nonstringent methods for the identification of NKT cells and carried out only limited analysis of the distribution and/or function of NKT cell subsets. Consequently, there is little consensus in the field about the significance

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REVIEWS Table 2 | Comparative stringency of flow cytometry approaches used to identify human type 1 NKT cells nKT cell assay

Rationale

Stringency

limitations

Does the approach identify most type 1 nKT cells?

Does the approach exclude most nonnKT cells?

αGalCer-loaded CD1d multimers

Bind to semi-invariant TCR of NKT cells; high (>95%) cross reactivity between human and mouse CD1d; variants of αGalCer such as PBS-57 are available and effective

Excellent

Binding can be hindered by TCR downregulation following NKT cell stimulation

Yes

Yes

6B11 monoclonal antibodies

Specific for semi-invariant TCR of NKT cells

Excellent

Binding can be hindered by TCR downregulation following NKT cell stimulation

Yes

Yes

Antibody staining for Vα24 and Vβ11

Specific for semi-invariant TCR of NKT cells

Very good

Might include some non-NKT cells; can exclude a small proportion of Vα24– NKT cells that are reactive to αGalCer; hindered by TCR downregulation

Yes

Yes

Antibody staining for Vα24

Specific for α-chain of semi-invariant TCR of NKT cells

Good

Includes most NKT cells, but will include some other T cells; hindered by TCR downregulation

Yes

Yes, although Vα24+ non-NKT cells exist

Antibody staining for NK cell antigens (such as CD56 and/or CD161)

Many NKT cells express NK cell antigens

Poor

Many non-NKT cells No, many NKT cells included; many NKT cells do do not express these not express these markers antigens

No, these antigens can be expressed by conventional T cells, particularly after activation

Antibody staining for CD4–CD8– phenotype

Many CD4–CD8– T cells are NKT cells

Poor

Excludes the major populations of CD4+ and CD8+ NKT cells

No, there are significant numbers of CD4–CD8– conventional T cells

No, many NKT cells express CD4 or CD8

αGalCer, α-galactosylceramide; NKT cell, natural killer T cell; TCR, T cell receptor.

of NKT cell defects in humans, or the potential for using NKT cells as a biomarker or therapeutic agent for diagnosing or treating these conditions, respectively. In this Review, we discuss the approaches (and their limitations) that have been used to study NKT cells in human disease and suggest ways to reach a consensus view about the importance of NKT cell defects in human diseases through a more detailed understanding of NKT cell biology, function and diversity.

Clinical analysis of NKT cells Identification of NKT cells. The evolution of methods used to define and characterize NKT cells has been described previously1, and stringent approaches to identification are now used in most areas of NKT cell research. However, clinical studies of NKT cells in human disease have often used less stringent surrogate methods for identifying NKT cells (TABLE 2). For example, the identification of NKT cells based on the expression of NK cellassociated markers (such as CD56 and CD161) by T cells is insufficient because not all of the cells that express these markers have the distinctive functional characteristics of the NKT cell lineage, and not all NKT cells express NK cell antigens1. Human type 1 NKT cells are best identified using reagents that bind to their semi-invariant TCR. such reagents include αGalCer-loaded CD1d multimers, the monoclonal antibody 6b11 (which is

specific for the Vα24–Jα18 TCR) and/or a Vα24-specific antibody in combination with a Vβ11-specific antibody 11,13,26. use of the Vα24-specific antibody alone identifies most type 1 NKT cells, but it will also detect unpredictable numbers of contaminating Vα24+ nonNKT cells and will exclude the small proportion of Vα24– NKT cells27. Analysis of NKT cell phenotype. Analysing NKT cells by flow cytometry potentially enables researchers to assess their frequency, activation phenotype, cytokine production, migratory characteristics and subset distribution. The identification of NKT cell subsets is important because simple enumeration of NKT cells can fail to identify subset-specific defects that could affect the function of NKT cells and contribute to disease. Analysing the expression by NKT cells of cell surface antigens, such as CD25, CD56, CD62l (also known as l-selectin), CD69 and CD161, and of chemokine receptors, such as CC-chemokine receptor 5 (CCR5), has been important for the developmental and functional analysis of NKT cell subsets in healthy human donors8,10,28, but such analysis has rarely been carried out in the context of human disease. with notable exceptions (such as REFS 13,14,29), the assessment of NKT cell defects in patients has been limited to the analysis of NKT cell frequency and CD4 expression.

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REVIEWS 8αs,α6%4

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Figure 1 | nKT cell defects and disease. A causative association between natural killer T (NKT) cells and disease is poorly defined, but probably involves one of two mechanisms. a | In the first mechanism, quantitative or qualitative defects in the NKT cell pool negatively affect the immunoregulatory roles that are normally carried out by NKT cells. As a result, diseases 0CVWTG4GXKGYU^+OOWPQNQI[ associated with failures of immune regulation become more common, including autoimmune diseases (failures of immune tolerance), cancer (failures of tumour immune surveillance) and some infectious diseases (such as failed immune maintenance of latency in tuberculosis). b | The second mechanism involves a direct or indirect pathogenic role for NKT cells, in which NKT cells might be normal in number and functionally competent, but they respond inappropriately to self (or non-self) glycolipid antigens or cytokines. This inappropriate activation of NKT cells has been proposed to contribute to diseases such as asthma and atherosclerosis and to conditions such as graft-versus-host disease. IL-12, interleukin-12; TCR, T cell receptor.

Analysis of NKT cell function. Most clinical studies of NKT cells have not assessed the cytokine production profile of the cells, and of those that have, most have been limited to an assessment of interferon-γ (IFNγ), interleukin-4 (Il-4) and sometimes tumour necrosis factor (TNF) production by activated NKT cells (see REFS 11, 30–33 for examples, and REF. 13 as a notable exception). The assays have mostly involved testing the total NKT cell population (often within a heterogeneous cell mix) or NKT cell lines, rather than using the more informative (although technically more difficult) approach of isolating NKT cell subsets and testing their cytokine responses immediately ex vivo. similar to the analysis of cell surface antigen expression, cytokine production by NKT cells has usually been measured in terms of individual cytokines or pairs of cytokines (almost always IFNγ and Il-4), rather than in larger combinations that would enable patterns of cytokine co-expression to be determined for each NKT cell subset, as is now routinely used for the analysis of NK cell, T cell and dendritic cell subsets.

cytokine production) are thought to compromise immune regulation and increase an individual’s predisposition to autoimmune diseases, cancer and some infections3,23,34 (FIG. 1a). In the second category, NKT cells can be normal in number and functionally competent, but they mount pathogenic immune responses that could contribute to diseases such as atherosclerosis, graft-versus-host disease, asthma, allergy and some skin disorders3,25 (FIG. 1b). In the third category, NKT cells do not necessarily contribute to disease pathology; rather, the stimulation of NKT cell function (for example, by administering glycolipids) might be beneficial for treating the disease35. Here, we focus on the first of these categories, in which intrinsic NKT cell defects are associated with disease. we do not intend to review every study that has contributed to this topic (see REFS 23,25,34 for detailed reviews); instead, we provide key examples of the approaches used and describe the caveats that apply to some aspects of these studies, which have prevented a consensus view regarding the importance of NKT cell defects in human diseases from being reached.

Diseases linked to NKT cell defects The reported associations between NKT cells and human disease can be grouped into three categories. In the first category, NKT cell defects (such as deficiency or impaired

Type 1 diabetes. It is thought that NKT cell defects can cause failures of immune regulation that predispose an individual to autoimmune diseases such as type 1 diabetes, multiple sclerosis, systemic lupus erythematosus,

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REVIEWS rheumatoid arthritis, sjogren’s syndrome or others23,36. The most controversial association between NKT cell defects and autoimmune disease relates to type 1 diabetes23,37,38. Diabetes-prone non-obese diabetic (NoD) mice have defects in NKT cell frequency and cytokine production37,38, and the development of diabetes in these mice can be prevented by adoptive transfer of NKT cells or by overexpression of the NKT cell TCR39. overexpression of CD1d40 or stimulation of NKT cells with αGalCer also prevents the development of diabetes in NoD mice41, and the rate of diabetes is higher in NKT cell-deficient (Cd1d–/– or Ja18–/–) NoD mice compared with wild-type NoD mice37,40. There have been similar reports of decreased NKT cell frequency in the peripheral blood, decreased IFNγ and Il-4 production and/or an altered ratio of CD4+ to CD4– NKT cell subsets in humans with, or at high risk of, type 1 diabetes30,42–44, although other studies have disagreed with these findings 13,45–47. There are several potential explanations for the conflicting results, including genetic and environmental factors, patient age, stage of disease and the methods used to characterize NKT cells, although contrasting results have also come from studies of similar design. Recent evidence indicates that the number of peripheral blood NKT cells is probably normal in patients with type 1 diabetes; however, most studies have measured only the overall frequency of blood NKT cells (sometimes also examining CD4+ and CD4– subsets) and their production of IFNγ and Il-4, whereas we now know that there are many other potential defects in the NKT cell pool11,13,43. one additional concern is that the NKT cell frequency in the blood of NoD mice is normal, despite there being significant deficiencies of NKT cells in other tissues48. It is not known whether NKT cells from the peripheral blood provide a better reflection of the systemic NKT cell pool in humans than in mice, but this uncertainty, together with the unresolved contradictions between studies of NKT cells in patients with type 1 diabetes, means that a more extensive characterization of human NKT cells (particularly from the tissues) is needed before NKT cell defects can be excluded as a contributing factor in human type 1 diabetes11,13. Multiple sclerosis. Although the evidence supporting a role for NKT cell defects in human type 1 diabetes is conflicting, for some other types of autoimmune disease there is a more general agreement that NKT cell defects exist in one form or another. we use multiple sclerosis as an example, although similar findings apply to rheumatoid arthritis and systemic lupus erythematosus. NKT cells from patients with multiple sclerosis are reportedly decreased in number 31,36,49 and defective in cytokine production31,32. It has been speculated that the observed deficiency of NKT cells in the blood could be the result of NKT cells trafficking to plaques and lesions in the central nervous system, but this model is not supported by the finding of a comparatively low proportion of NKT cells at these sites49. As for many diseases associated with NKT cell defects, it is not known whether the defects precede the development

of multiple sclerosis or are a consequence of it. This uncertainty could help to explain the varied nature of NKT cell defects reported between studies, particularly as NKT cells were analysed during different phases of multiple sclerosis in some cases32,49,50. An important caveat is that some studies defined NKT cells as a subset of CD4–CD8– T cells (thereby excluding CD4+ NKT cells)51 or as Vα24+ cells (without confirming Vβ11 or Jα18 usage) 50. Also, some studies used PCR-based analysis of NKT cells49–51 that restricted the quantification and characterization of these cells and reduced the potential for comparing data from different studies. The studies reporting abnormal cytokine production by NKT cells from patients with multiple sclerosis31,32,52 analysed a restricted array of cytokines (two studies measured Il-4 and IFNγ production, and a third study also measured Il-2, Il-5 and Il-10 production) produced by NKT cell lines derived from patients. overall, the data supporting an association between multiple sclerosis and NKT cell defects are intriguing, particularly in view of the evidence that treatment of multiple sclerosis can increase NKT cell frequency and cytokine production52. However, the field would benefit from a more comprehensive characterization of NKT cell subsets derived from the blood and from disease lesions in humans, particularly if carried out during both the relapse and remission phases of disease in one patient group. Solid cancers. There is compelling evidence that NKT cells have an important role in tumour surveillance in mice, in which NKT cell defects predispose to cancer and the adoptive transfer or stimulation of NKT cells can provide protection against cancer 24,34,53,54. The CD4– NKT cell subset seems to have the main role in surveillance of some tumours in mice, and the cytokine profile of CD4– NKT cells in humans indicates that they might have a similar role7,8,10. NKT cell deficits have been reported in the peripheral blood of patients with cancer 55–57, as well as in the tissues surrounding tumours19,58 and in the tumours themselves25. NKT cell frequency is reported to correlate inversely with tumour load and positively with prognosis59. There are examples in which the number of NKT cells was not decreased in patients with cancer 60 (although NKT cell proliferation was defective) and increased NKT cell frequency has been found in some tumours, which could, in isolation, be seen to support an antitumour role for NKT cells61,62. Reassuringly, many of these studies used relatively stringent methods for the identification of NKT cells. As is the case for multiple sclerosis, a key unanswered question regarding the role of NKT cells in cancer is whether NKT cell deficiencies predispose to disease or whether the loss of NKT cells is secondary to tumour development. some studies have shown that tumours (or associated myeloid dendritic cells) have a direct effect on the number of NKT cells58,63, but other studies55 report no such effect and instead show that the number of peripheral blood NKT cells is unaffected by the removal of tumours.

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REVIEWS NKT cells from patients with cancer have been shown in some studies to produce less IFNγ (and perhaps Il-2) than NKT cells from healthy individuals55,63,64, which could potentially decrease the IFNγ-dependent antitumour activities of NK cells and conventional CD8+ T cells65. However, the NKT cells analysed in these studies were not always tested directly or isolated from PbMCs, and it is uncertain whether this observation is the result of a decreased number of NKT cells55 or intrinsically defective cytokine production by NKT cells63,64. In summary, although NKT cell defects have been widely reported in some patient groups with cancer, there is a need for more detailed analysis of NKT cell number, subset distribution and cytokine production in patients with distinct forms of cancer. Patient characteristics and the type of cancer have varied widely between studies, and this has made it difficult to directly compare data from different studies and to define the contributory role of NKT cell defects in specific disease contexts. Haematological cancers. In addition to their association with solid tumours, NKT cell defects are associated with haematological cancers, including leukaemia, multiple myeloma and myelodysplastic syndromes66. These conditions are difficult to analyse in terms of their association with immune cell defects because the immune system is often severely affected by the disease and its treatment. However, as for solid tumours, smaller than normal numbers of NKT cells and defects in NKT cell cytokine production have been reported from the analysis of blood from these patients33,66–68. There is also evidence that NKT cell frequency and function increase with some treatments for haematological malignancies67,69. It is speculated that defective immune regulation predisposes individuals to these conditions, but there is no consensus about the nature of the defects, and the role of NKT cells is controversial66. Three separate groups have reported decreased numbers of NKT cells in the peripheral blood of patients with myelodysplastic syndromes70–72. These findings were of particular interest because the immunomodulatory drug lenalidomide, which has been tested in clinical trials as a potential new treatment for myelodysplastic syndromes and multiple myeloma69,73, had been shown to increase NKT cell frequency and cytokine production66,69. These results supported the idea that NKT cell defects are important in these diseases and that part of the therapeutic benefit of lenalidomide is related to its effects on NKT cells68,69. However, there are significant caveats relating to each of these studies, including the fact that they defined NKT cells as Vα24+Vβ11+CD4–CD8–, Vα24+CD161+ or Vα24+Vβ11+ cells. Two of the studies did not test for NKT cell function70,72 and the third study used cytokine analysis of cultured PbMCs to show functional defects of NKT cells70. These caveats were addressed in a recent study using αGalCer-loaded tetramers and longitudinal analysis, which showed that patients with myelodysplastic syndromes had normal numbers of NKT cells and normal cytokine production, and that these factors were unaffected by lenalidomide treatment 14. This study does not

necessarily indicate that NKT cells have no role in the disease, as there is evidence of changes in CD1d expression and lipid-specific responses that are consistent with altered NKT cell activity in such diseases74,75, and unpublished studies from our group support earlier findings that NKT cells are defective in patients with multiple myeloma. Moreover, our in vitro data support the idea that lenalidomide can modulate NKT cell function14,69,76. However, the literature relating to NKT cells in patients with myelodysplastic syndromes provides a cautionary illustration of the inconsistencies that can emerge between studies using different approaches to analyse NKT cells. Infectious diseases. Numerous studies in mice show that stimulation of NKT cells can assist or modulate immunity to infection77–79, but far fewer studies show that NKT cell defects can predispose to infectious disease. The identification of antigens that can stimulate NKT cells in Borrelia burgdorferi 80 and Sphingomonas spp.81,82 implies that NKT cell deficiency could predispose to lyme disease (as a result of B. burgdorferi infection) and to certain nosocomial infections, although this has not been formally tested and the natural role of NKT cells in immunity to these microorganisms remains uncertain. However, there is emerging evidence that NKT cell deficiency might predispose patients who are infected with Mycobacterium tuberculosis to acute tuberculosis. A comparison of immune biomarkers from patients with latent or acute tuberculosis found that NKT cell deficiency accurately predicted the presence of active disease in infected individuals83. The distribution and function of NKT cell subsets in patients with tuberculosis were not examined and it remains to be determined whether NKT cell deficiency contributes to infection with M. tuberculosis, but it is intriguing that normal NKT cell frequencies were restored in these patients by treatment for active tuberculosis. This is in line with the findings of three earlier studies: one study showed that NKT cells were decreased in frequency in patients with tuberculosis but had an activated phenotype29; a second study reported a nonsignificant trend of decreased NKT cell frequency and abnormal CD4+ to CD4– NKT cell subset ratio in patients with tuberculosis84; and a third study reported that large NKT cell numbers were associated with rapid responses to treatment for tuberculosis85. Although NKT cells were defined as CD3lowCD56+ cells in the earliest report 85, the other three studies29,83,84 used more stringent methods for the identification of NKT cells, and collectively they provide a compelling rationale for a more detailed characterization of NKT cells in patients with tuberculosis, including the analysis of surface antigen expression by NKT cells and cytokine production profiles throughout the disease course.

Improvements and opportunities The aforementioned clinical studies, together with convincing data from mouse studies, have established that NKT cell defects might have important roles in many human diseases, but there is no consensus view about the significance of NKT cell defects for any of

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Figure 2 | Potential clinical uses for nKT cells. The growing evidence that natural killer T (NKT) cell defects, and the cells themselves, have an important role in many different human diseases raises the prospect that these cells will 0CVWTG4GXKGYU^+OOWPQNQI[ become useful biomarkers or therapeutic targets. As biomarkers, NKT cells could conceivably be used to identify patients at high risk of developing diseases for which NKT cell defects are a contributory factor. There is also evidence that the characteristics of NKT cell subsets can sometimes correlate with distinct phases of a disease or can vary according to the prognosis or course of treatment. If such characteristics are predictable and unique to the patient’s circumstance, then detailed screening of the NKT cell pool could become an important part of clinical care for some patient groups. A more advanced area of research is the prospect of manipulating NKT cells for therapeutic advantage, usually by stimulating NKT cells with glycolipid antigens. This approach does not presume that an NKT cell defect exists, although stimulation of NKT cells with glycolipid agonists with a good safety profile (for example, α-galactosylceramide (αGalCer)) can be used to increase NKT cell numbers or increase cytokine production in those circumstances. More widely, the approach of administering agents to directly improve NKT cell function is already seen as a potential means of optimizing anticancer therapies and there is ongoing interest in manipulating NKT cells to improve vaccine efficacy and to treat autoimmune diseases. Less well defined is the possibility that pathogenic NKT cell responses could be directly targeted (for example, by using reagents such as the monoclonal antibody 6B11 to block NKT cell activation or migration), although this is also a promising area of research. The development of NKT cell-based treatments had initially been restricted to the relatively straightforward approach of using αGalCer to activate all NKT cells without taking into account the varied (sometimes opposing) functions of NKT cell subsets. However, this field is rapidly changing following improvements in our understanding of the functional heterogeneity of the NKT cell pool and advances in the synthesis of glycolipid antigens that can stimulate distinct cytokine responses or target specific NKT cell subsets. This raises the prospect of tailoring NKT cell-based therapies to treat a specific disease and/or patient, although this will probably require a pre-assay of NKT cells from each patient before treatment to take into account variations between individuals in terms of NKT cell subset frequency and function.

these conditions and NKT cells are still rarely considered in terms of the prevention, diagnosis or treatment of patients. Although some Phase I clinical trials have targeted NKT cells, a more comprehensive characterization of NKT cells in the context of these diseases is needed before the impact of NKT cell defects can be defined and NKT cell-based therapies can be widely applied (FIG 2). Here, we describe some of the opportunities that now exist to clarify and extend the findings of earlier studies. More detailed analysis of human NKT cells. To reliably identify systemic NKT cell defects in humans, it will first be important to understand the correlation between NKT cells isolated from the blood and those present elsewhere in the body. studies in mice indicate that the characteristics of NKT cells from the blood cannot be directly extrapolated to the entire NKT cell pool,

so comparative flow cytometry, genetic and functional analyses of NKT cells from the blood, thymus, spleen and liver of individual human donors are required. blood will remain the main source of NKT cells for most clinical studies, but the significance of blood NKT cells in a prognostic or diagnostic setting will remain in question until their relationship to NKT cells in other organs is established, or until blood NKT cells themselves are shown to have an effect on disease. The low frequency of NKT cells in the blood and the small volumes of blood available for clinical studies might preclude microarray or proteomic analysis of patient samples, but multiparameter flow cytometry should enable the analysis of NKT cell frequency, subset distribution and cell surface antigen expression. The expression of surface antigens other than CD4 is rarely monitored in clinical studies of NKT cells. by contrast, multiparameter cell classification is routinely used to

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REVIEWS define the developmental and functional status of subsets of conventional T cells, NK cells and dendritic cells, and a similar approach should be possible for NKT cells. For example, the analysis of cytokine production by human NKT cells is a crucial aspect of screening for NKT cell defects, but if sample volumes are prohibitively low, it is still possible to infer that a decreased frequency of CD4+ NKT cells will correspond to decreased production of Il-4. If a more complete understanding of the correlation between patterns of antigen expression and cytokine production profiles can be established (using NKT cells from healthy individuals), it might become possible to provisionally identify functional defects on the basis of the cell surface antigens (and combinations thereof) expressed by NKT cells from patient samples. Longitudinal studies. Many clinical studies of NKT cells have examined only one sample from each patient, which can result in variables between samples that cannot easily be controlled. NKT cell defects could conceivably be evident at some stages of disease (or treatment), but not others, so a definitive assessment of whether NKT cell defects are present should involve analysis throughout the course of the disease. one approach can be to divide samples according to patientspecific characteristics (such as age, sex and treatment group). However, it is more informative to carry out a longitudinal analysis for each patient, as this allows NKT cell defects to be detected when they emerge, which can help to determine whether a defect predisposes to disease. sequential sampling from each patient increases the probability of identifying any NKT cell defects (or changes) associated with factors that might vary between individuals, including the phase of disease, treatment regime and characteristics of other cell types (for example, conventional T cells). longitudinal studies will also benefit our understanding of conditions in which NKT cells might have a pathogenic role, such as asthma86,87 and atherosclerosis88,89, and they will be particularly helpful for determining the role of NKT cells in chronic diseases, or conditions where it is possible to identify individuals with an increased risk of developing acute disease. These high risk individuals will variously develop acute disease and respond differently to treatment, so periodically mapping their NKT cell characteristics from before the onset of disease will maximize the opportunity to identify a causal relationship between NKT cell defects and the disease. NKT cells as biomarkers. when coupled with more detailed NKT cell analysis, longitudinal studies of healthy individuals and patients with disease might allow certain characteristics of NKT cells to be identified as useful biomarkers for disease diagnosis, prognosis and selection of treatments. owing to the variable and low frequency of NKT cells in human peripheral blood, NKT cell frequency in isolation is unlikely to become a clinically important biomarker, but more detailed characterization of NKT cells might be more useful. The objective should be to identify patterns of NKT cell characteristics

(for example, frequency, subset proportions, cell surface antigen expression and cytokine production) that allow healthy individuals to be distinguished from those with an NKT cell disorder that predisposes them to disease. For some diseases associated with NKT cell defects, the frequency of NKT cells has been reported to correlate with aspects of prognosis, so it is reasonable to argue that a more detailed characterization of the NKT cell compartment in these diseases could lead to advances in patient care, including improved diagnosis and treatment selection. NKT cells as therapeutic targets. some clinicians are already attempting to enhance or restore NKT cell function in patients by administering NKT cell mitogens such as αGalCer. Phase I clinical trials have shown that αGalCer administration is well tolerated by humans and can result in the expansion of residual NKT cell populations and increased levels of cytokines in the blood90–94. In broad terms, the rationale of such therapies is to increase the number of NKT cells and/or stimulate them to produce cytokines that achieve a desired immunoregulatory effect. some NKT cell mitogens show promise as vaccine adjuvants for b cell and T cell responses, and the clinical impact of NKT cell stimulation on disease is under investigation. However, these approaches might need to be refined because the high variability of NKT cell frequency and subset distribution in the general human population makes it difficult to predict the size and cytokine profile of the NKT cell response in any one individual95. It might become useful to pre-assay an individual’s NKT cell frequency and subset distribution to facilitate the design of customized therapies12. Recent studies have shown that structural analogues of αGalCer can elicit distinct NKT cellmediated cytokine responses and a better understanding of this phenomenon should allow for the generation of more tailored NKT cell responses through selective activation of NKT cell subsets12. Although this Review focuses on diseases that are associated with defects in the type 1 NKT cell pool, the suggestions we have made for improving NKT cell analysis in clinical studies apply equally to other patient groups in which NKT cells might have a pathological role in the development of disease and/or be important targets for the treatment of disease. An obvious candidate disease is asthma, in which the role of NKT cells is highly controversial because studies of similar design have provided conflicting data regarding the frequency and activation status of NKT cells in the lungs and airways of patients with asthma86,87,96–98. one suggestion is that such differences could be the result of methodological uncertainties and artefacts99, which strongly implies that more refined approaches, including the longitudinal analysis of NKT cell subsets from the blood and bronchoalveolar lavage fluid of patients with asthma, will establish a firmer basis from which to assess the importance of NKT cells in this and other diseases. of course, the overall success of this objective relies on stringent approaches being consistently applied by different research groups.

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REVIEWS Central questions and challenges What causes NKT cell defects? A useful approach to determine how NKT cell defects arise is genomewide association studies of individuals with distinct NKT cell characteristics (such as high or low NKT cell frequency)100. one possibility is that polymorphisms in molecules that are important for NKT cell development (such as slAM receptors101 or the transcription factor PZlF102) might predict person-to-person variations in NKT cell frequency 103. However, it will also be important to establish where NKT cell defects arise. In mice, systemic NKT cell deficiencies often develop in the thymus, although defects could emerge during NKT cell proliferation and differentiation phases in the periphery. The same is also true for humans because NKT cell subsets emerge and reach functional maturity in the periphery. we have only a limited understanding of this process and it remains a major challenge in the field to fully understand the developmental pathway of human NKT cells so that defects can be better defined and eventually treated. How do NKT cells mediate their function? The large number of diseases that are associated with NKT cell defects indicates that these cells have an important role in maintaining effective immunity, yet the mechanisms by which they do so are poorly defined. Cytokine production seems to be central to their protective role in many mouse models of disease, but this has mostly been demonstrated by activating NKT cells with glycolipids such as αGalCer or with inflammatory cytokines such as Il-12 (REFS 3,104). Few studies report the spontaneous in vivo activation of mouse or human NKT cells, although in vitro analysis has shown that human NKT cells recognize glycolipids from Borrelia spp. and Sphingomonas spp., and they can be activated during infection in response to Il-12 and CD1d-restricted self antigens105, including lyso-phosphospholipids, that can function as inflammatory messengers106. The ability of activated NKT cells to influence other types of immune cell is well established, but it is more difficult to reconcile the normally quiescent state of NKT cells in naive mice and humans with their purported regulatory roles in systemic tumour surveillance and immune tolerance, which would presumably also require some form of activation. Although it is possible that NKT cells only become activated when a threat emerges107, defining the mechanisms by which NKT cells normally provide protection against diseases in which NKT cell defects are a contributing factor would be an important breakthrough. Where do NKT cells mediate their function? Presumably, disease-associated stimuli for NKT cells are most abundant near the acute site of disease (for example, in tumours or autoimmune lesions), but the evidence for trafficking of NKT cells to these areas is relatively sparse, even in mice. NKT cells are found throughout the immune system and can be activated in most of these locations108, but it is somewhat confounding that they are most abundant at sites that are distant from the tissues

most commonly affected by autoimmune diseases and cancers. NKT cells have been found in tumours and in the lesions of patients with multiple sclerosis, but at a frequency that could result from the nonspecific trafficking of blood-borne lymphocytes to areas of inflammation, and it is not clear whether the infiltrating NKT cells subsequently become activated in situ. An alternative possibility is that NKT cells function systemically. These are challenging issues to address, but it will be important to carry out mechanistic studies that define the trafficking and activation status of human NKT cell subsets during immune regulation. The use of humanized mice and more detailed characterization of NKT cells in patients should be highly informative and will increase our understanding of the specific consequences of NKT cell defects and improve the prospects for addressing the impact of such defects. What is the prognostic value of identifying defects common to many diseases? we now know that many different diseases are associated with NKT cell defects38. one consequence of this is that the significance of NKT cell deficiency in an otherwise healthy individual becomes questionable: are such individuals at increased risk of each of these diseases? In view of recent studies highlighting the heterogeneity of NKT cells, it seems probable that a better understanding of human NKT cell subsets, including their cytokine production profiles, will allow for more sophisticated analysis of NKT cell deficiencies. such analysis might be required to identify diseasespecific defects that affect particular NKT cell subsets and/or functions, and therefore provide better prognostic value and important information for the design and application of preventative immunotherapies23,66,109. Is it feasible to characterize human NKT cells from clinical samples? The limited volumes of blood available for analysis are a practical consideration for all types of clinical research, but this is a greater issue for NKT cell analysis than for most other cell types. The frequency of NKT cells in the blood is often close to the limit of detection, so when the volume of whole blood is small, it might not be possible to isolate sufficient NKT cells to carry out multiple assays. This has been particularly limiting in clinical studies that use 3- or 4-colour flow cytometry to analyse NKT cells. Hence, it is crucial to develop a more detailed understanding of the correlation between patterns of cell surface antigen expression by NKT cells and their function, so that functionally significant defects in the NKT cell pool can be inferred or provisionally identified by multiparameter flow cytometry-based screening of clinical samples. Does analysis of human blood NKT cells reflect the systemic pool? studies in mice that have identified roles for NKT cells in disease have typically involved NKT cells isolated from the thymus, spleen or liver, rather than from the blood. This is potentially problematic because the blood is the main source of NKT cells for clinical studies, and NKT cells from different organs are functionally distinct. For example,

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REVIEWS in mice, NKT cells from the liver provide superior protection against cancer compared with NKT cells from the spleen or thymus, and NKT cells from each of these locations have distinct cytokine production profiles12,110. There is also evidence that NKT cells from mouse blood poorly represent NKT cells from elsewhere in the body, as the severe systemic deficiency of NKT cells in NoD mice is evident in the thymus, spleen, liver, bone marrow and lymph nodes, but not the blood48. less is known about the comparative biology of NKT cells from different organs in humans, but the frequency and function of NKT cells in human peripheral blood differ significantly from those of NKT cells from the thymus and cord blood 16,17. It is therefore difficult to know the implications of NKT cell defects identified in human blood until it is established how the characteristics of these cells correlate with the characteristics of NKT cells elsewhere in the body. Given that clinical studies of NKT cells rely almost exclusively on analysis of the blood and it is impractical to routinely look elsewhere, a detailed comparative characterization of NKT cells from different tissues of healthy donors is needed. The hope is that this will define the similarities and differences between NKT cells in the blood and other tissues, and identify surrogate markers that could be used for the analysis of blood NKT cells to reveal NKT cell defects affecting other tissues.

Godfrey, D. I., MacDonald, H. R., Kronenberg, M., Smyth, M. J. & Van Kaer, L. NKT cells: what’s in a name? Nature Rev. Immunol. 4, 231–237 (2004). 2. Matsuda, J. L. et al. Tracking the response of natural killer T cells to a glycolipid antigen using CD1d tetramers. J. Exp. Med. 192, 741–754 (2000). 3. Bendelac, A., Savage, P. B. & Teyton, L. The biology of NKT cells. Annu. Rev. Immunol. 25, 297–336 (2007). 4. Matsuda, J. L., Mallevaey, T., Scott-Browne, J. & Gapin, L. CD1d-restricted iNKT cells, the ‘Swiss-Army knife’ of the immune system. Curr. Opin. Immunol. 20, 358–368 (2008). 5. De Santo, C. et al. Invariant NKT cells reduce the immunosuppressive activity of influenza A virusinduced myeloid-derived suppressor cells in mice and humans. J. Clin. Invest. 118, 4036–4048 (2008). 6. De Santo, C. et al. Invariant NKT cells modulate the suppressive activity of IL-10-secreting neutrophils differentiated with serum amyloid A. Nature Immunol. 11, 1039–1046 (2010). 7. Crowe, N. Y. et al. Differential antitumor immunity mediated by NKT cell subsets in vivo. J. Exp. Med. 202, 1279–1288 (2005). This was the first in vivo study to show differential antitumour activity by different NKT cell subsets in mice. 8. Lee, P. T., Benlagha, K., Teyton, L. & Bendelac, A. Distinct functional lineages of human Vα24 natural killer T cells. J. Exp. Med. 195, 637–641 (2002). 9. Kim, C. H., Johnston, B. & Butcher, E. C. Trafficking machinery of NKT cells: shared and differential chemokine receptor expression among Vα24+Vβ11+ NKT cell subsets with distinct cytokine-producing capacity. Blood 100, 11–16 (2002). 10. Gumperz, J. E., Miyake, S., Yamamura, T. & Brenner, M. B. Functionally distinct subsets of CD1d-restricted natural killer T cells revealed by CD1d tetramer staining. J. Exp. Med. 195, 625–636 (2002). References 8–10 were pivotal in identifying heterogeneity within the human NKT cell compartment, including the functional characterization of CD4+ and CD4– subsets. 1.

11.

12. 13.

14.

15.

16.

17.

Summary and conclusions NKT cells are a potentially significant factor in the diagnosis and treatment of many human diseases. It has been proposed that NKT cell defects contribute to immune dysregulation and predispose affected individuals to conditions such as autoimmunity and cancer, but there is little direct evidence to support this hypothesis in humans. The evidence is far stronger in mice, and although many associative studies carried out in humans are consistent with this idea, uncertainties remain about the nature of NKT cell defects in humans and whether there is a causal relationship between NKT cell defects and human disease. It is now necessary for the NKT cell field to progress from carrying out primarily association studies to more detailed characterization of NKT cell subsets in healthy individuals and in the context of disease. For conditions in which NKT cell defects are definitively identified, the hope is that NKT cells can be therapeutically targeted to restore normal NKT cell frequency and function. so far, this has not been possible for several reasons, including the technical difficulties associated with analysing and manipulating this lineage and a relatively superficial understanding of the NKT cell population. Many of these issues can now be addressed, and this has created the opportunity to determine if NKT cell defects contribute to human disease and the real possibility that NKT cells could become valuable clinical tools for new treatments.

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revealed by an ontogeny study of paired tissue samples. Eur. J. Immunol. 35, 1399–1407 (2005). References 16 and 17 were the first to characterize NKT cell development in the human thymus. They illustrate important differences between thymus and blood NKT cells and indirectly show that some important stages of NKT cell differentiation occur in the periphery. Kenna, T. et al. NKT cells from normal and tumorbearing human livers are phenotypically and functionally distinct from murine NKT cells. J. Immunol. 171, 1775–1779 (2003). Lynch, L. et al. Invariant NKT cells and CD1d+ cells amass in human omentum and are depleted in patients with cancer and obesity. Eur. J. Immunol. 39, 1893–1901 (2009). Exley, M. A. et al. Cutting edge: A major fraction of human bone marrow lymphocytes are Th2-like CD1d-reactive T cells that can suppress mixed lymphocyte responses. J. Immunol. 167, 5531–5534 (2001). Gapin, L. Where do MAIT cells fit in the family of unconventional T cells? PLoS Biol. 7, e70 (2009). Cohen, N. R., Garg, S. & Brenner, M. B. Antigen presentation by CD1 lipids, T cells, and NKT cells in microbial immunity. Adv. Immunol. 102, 1–94 (2009). Wu, L. & Van Kaer, L. Natural killer T cells and autoimmune disease. Curr. Mol. Med. 9, 4–14 (2009). Swann, J. B., Coquet, J. M., Smyth, M. J. & Godfrey, D. I. CD1-restricted T cells and tumor immunity. Curr. Top. Microbiol. Immunol. 314, 293–323 (2007). Balato, A., Unutmaz, D. & Gaspari, A. A. Natural killer T cells: an unconventional T-cell subset with diverse effector and regulatory functions. J. Invest. Dermatol. 129, 1628–1642 (2009). Berzins, S. P., Smyth, M. J. & Godfrey, D. I. Working with NKT cells — pitfalls and practicalities. Curr. Opin. Immunol. 17, 448–454 (2005). Gadola, S. D., Dulphy, N., Salio, M. & Cerundolo, V. Vα24–JαQ-independent, CD1d-restricted recognition of α-galactosylceramide by human CD4+ and CD8αβ+ T lymphocytes. J. Immunol. 168, 5514–5520 (2002).

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108. Barral, P. et al. CD169+ macrophages present lipid antigens to mediate early activation of iNKT cells in lymph nodes. Nature Immunol. 11, 303–312 (2010). This paper provides an insight into how and where NKT cells become activated during an in vivo immune response. 109. Cerundolo, V. & Salio, M. Harnessing NKT cells for therapeutic applications. Curr. Top. Microbiol. Immunol. 314, 325–340 (2007). 110. Coquet, J. M. et al. Diverse cytokine production by NKT cell subsets and identification of an IL-17-producing CD4–NK1.1– NKT cell population. Proc. Natl Acad. Sci. USA 105, 11287–11292 (2008).

Acknowledgements

S.P.B. is supported by an Australian National Health and Medical Research Council (NHMRC) R. D. Wright Fellowship. M.J.S. is supported by an Australian NHMRC Australia Fellowship and Program Grant. A.G.B. is supported by an Australian NHMRC Senior Research Fellowship. We thank D. Godfrey and A. Chan for helpful advice during the planning and preparation of this manuscript.

Competing interests statement

The authors declare no competing financial interests.

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REVIEWS

Recognition of herpesviruses by the innate immune system Søren R. Paludan*, Andrew G. Bowie‡, Kristy A. Horan* and Katherine A. Fitzgerald§

Abstract | Advances in innate immunity over the past decade have revealed distinct classes of pattern recognition receptors (PRRs) that detect pathogens at the cell surface and in intracellular compartments. This has shed light on how herpesviruses, which are large disease-causing DNA viruses that replicate in the nucleus, are initially recognized during cellular infection. Surprisingly, this involves multiple PRRs both on the cell surface and within endosomes and the cytosol. In this article we describe recent advances in our understanding of innate detection of herpesviruses, how this innate detection translates into anti-herpesvirus host defence, and how the viruses seek to evade this innate detection to establish persistent infections. Lytic infection Viral replication in host cells either causes cellular death and lysis (lytic infection) or is compatible with cell survival (persistent infection).

Permissive cells Cells that support the replication of a given virus. Permissiveness is often determined by the expression of specific components in the cells and/or the ability of viruses to circumvent host defence mechanisms.

*Department of Medical Microbiology and Immunology, The Bartholin Building, Aarhus University, DK‑8000 Aarhus C, Denmark. ‡ School of Biochemistry and Immunology, Trinity College Dublin, Dublin 2, Ireland. § Division of Infectious Diseases and Immunology, University of Massachusetts Medical School, Worcester, Massachusetts, USA. Correspondence to S.R.P. e‑mail: [email protected] doi:10.1038/nri2937

Herpesviruses are a large family of DNA viruses. Among the known herpesviruses, eight can cause diseases in humans (TABLE 1), particularly in children and immuno‑ compromised individuals1. Herpesviruses can be sub‑ divided into the α‑, β‑ or γ‑subfamilies based on their biological functions and sequence similarities (TABLE 1), but common to all herpesviruses is the ability to cause lytic infection in permissive cells, and to establish latency in specific specialized cell types (BOX 1), such as neurons in the case of alphaherpesviruses, myeloid progenitors and/or lymphocytes in the case of betaherpesviruses, and lymphocytes in the case of gammaherpesviruses. Immunological control of herpesviruses is achieved by both the innate and the adaptive immune systems, with CD8+ T cells having a crucial role in the adaptive immune response2–5. In the innate antiviral immune response, type I interferons (IFNs) and natural killer (NK) cells have key roles in the containment of herpes‑ virus infections 6–9. The innate immune system is activated following sensing of infections by pattern recognition receptors (PRRs) that detect pathogenassociated molecular patterns (PAMPs)10. Toll‑like recep‑ tors (TLRs) are the first discovered and best character‑ ized PRRs (FIG. 1). They are membrane‑bound receptors that are localized in the plasma membrane and endosomal compartments. The TLRs in the plasma membrane gen‑ erally recognize hydrophobic molecules such as lipids and proteins, whereas the endosomal TLRs sense nucleic acids10. More recently, intracellular PRRs have been identified that can detect pathogen nucleic acids in the cytoplasm. RNA is recognized by the RIG‑I‑like recep‑ tors (RLRs) retinoic acid‑inducible gene I (RIG‑I) and

melanoma differentiation‑associated gene 5 (MDA5), which detect 5ʹ triphosphate‑panhandle RNA and higher order RNA structures, respectively 11–13. Currently, five intracellular DNA sensing proteins are known: DNA‑ dependent activator of IFN‑regulatory factors (DAI; also known as ZBP1), absent in melanoma 2 (AIM2), RNA polymerase III, leucine‑rich repeat flightless‑ interacting protein 1 (LRRFIP1) and, most recently, IFNγ‑inducible protein 16 (IFI16)14–22. With the excep‑ tion of AIM2 (and under some circumstances RIG‑I23), all TLRs and intracellular nucleic acid sensors induce intracellular signalling pathways that lead to the expres‑ sion of proteins with pro‑inflammatory and microbicidal activities, including cytokines and type I IFNs (IFNα and IFNβ)10,24. The stimulation of pro‑inflammatory responses generally relies on activation of the transcrip‑ tion factors nuclear factor‑κB (NF‑κB) and activator protein 1 (AP1)10,24, whereas the induction of IFNα expression depends on activation of IFN regulatory factor (IRF) family members, and IFNβ expression requires IRFs and NF‑κB25. By contrast, AIM2 activates the inflammasome, a large multiprotein complex that stimulates a proteolytic caspase 1‑dependent path‑ way that cleaves pro‑interleukin‑1β (pro‑IL‑1β) and pro‑IL‑18 into the mature bioactive pro‑inflammatory cytokines15–18. Importantly, there is substantial overlap between the downstream activities stimulated by PRRs so that some of the pathways that lead to IFN activa‑ tion also drive activation of other cytokines and cell death. For example, IFI16 stimulates activation of both the IRF3 and NF‑κB pathways, as well as activation of caspase 2 and caspase 3 (REFs 22,26).

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REVIEWS Table 1 | Human herpesviruses name

Subfamily

Sequence characteristics

Cell types infected

HSV-1 (HHV1)

α

HSV-2 (HHV2)

Pathophysiology

gC content

% coding

lytic infection

latent infection

68%

79

Epithelial cells

Neurons

Orofacial infections, encephalitis

α

70%

79

Epithelial cells

Neurons

Genital and neonatal infections

VZV (HHV3)

α

46%

89

Epithelial cells

Neurons

Chickenpox, shingles

EBV (HHV4)

γ

59%

68

B cells, epithelial cells

B cells

Infectious mononucleosis, lymphoma, carcinoma

CMV (HHV5)

β

57%

79

Macrophages, lymphocytes, epithelial cells

Macrophages, lymphocytes, epithelial cells

Congenital infection, retinitis, hepatitis

HHV6

β

42%

79 (subtype A); CD4+ T cells 82 (subtype B)

Monocytes, macrophages

Exanthem subitum

HHV7

β

36%

79

T cells

T cells

Exanthem subitum

HHV8

γ

53%

83

Lymphocytes

Lymphocytes

Kaposi’s sarcoma

CMV, cytomegalovirus; EBV, Epstein–Barr virus; HHV, human herpesvirus; HSV, herpes simplex virus; VZV, varicella-zoster virus.

For herpesviruses to establish infection, it is essential that they modulate host cells27 and evade host immune responses28–43. evading the innate immune system may be particularly important for herpesviruses, given their slow replication cycle and their maintenance of life‑long latent infections. In this Review we present the current knowledge on how the innate immune system detects herpesvirus infections, how this translates into antiviral immune responses, and how herpesviruses specifically evade this response during both primary infection and reactivation from latency.

Recognition by TLRs substantial literature shows that TLRs can recognize herpesvirus PAMPs (TABLE 2, FIG. 1). This recognition controls cytokine and IFN expression in various cell types. The three classes of herpesvirus PAMPs that are recognized by TLRs are viral proteins, DNA and RNA.

Latency A state in which viruses lie dormant in infected cells with no detectable viral replication. From the latent state, viruses can become activated to initiate productive replication.

Pathogen-associated molecular patterns (PAMPs). Evolutionarily conserved molecular structures that are recognized by pattern recognition receptors. PAMPs are either specific for whole classes of pathogens or used by both microorganism and host but present in abnormal locations.

TLR2. Following binding of herpesviruses to specific cellular receptors, the viral envelope glycoprotein triad — gH, gL and gB — mediate the mixing of virion and host cell lipids, followed by full fusion of the virus and host cell membranes 44–46. TLR2 on the plasma membrane, presumably in complex with TLR1 (REF. 47), recognizes herpesviruses through a process that, in the case of human cytomegalovirus (HCMv), can be blocked by antibodies specific for gB and gH 47–52. exactly how herpesviruses stimulate TLR2 has not been elucidated, and in this respect it is also interesting that not all strains of herpes simplex virus type 1 (Hsv‑1) activate TLR2 (REF. 53). As TLR2 recognizes hydrophobic PAMPs, such as lipopeptides10,24, it is possible that TLR2 detects hydrophobic peptides in gH and gB that are normally buried in the interior of these viral proteins and are only exposed during virus–host cell membrane fusion. However, the available data do not exclude the possibility that TLR2 detects a lipid component that

is exposed during viral entry. It should be mentioned that in the case of Hsv‑1, there is also evidence for innate immune recognition of viral glycoproteins inde‑ pendent of TLR2 (REF. 54). TLR2 is mainly expressed by myeloid cells, and has generally been ascribed roles in the stimulation of inflammation10,24. During herpes‑ virus infections, TLR2 activation stimulates signalling that leads to activation of NF‑κB and expression of pro‑ inflammatory cytokines49,51,52, but it has recently been reported that the type I IFN response of inflamma‑ tory monocytes after infection with viruses, including mouse cytomegalovirus (MCMv), partially depends on TLR2 (REF. 55). Mouse studies have shown both beneficial and del‑ eterious roles for TLR2 in host defence against herpes‑ viruses. Neonatal TLR2‑deficient mice were protected against Hsv‑1 encephalitis following intraperitoneal infection, owing to reduced inflammation rather than elevated viral load49. subsequent studies have shown that TLR2 has protective roles in three models for Hsv‑2 and CMv infections. Mice lacking both TLR2 and TLR9 were significantly more susceptible to Hsv‑2 dissemination to the central nervous system than either TLR2‑deficient or TLR9‑deficient mice after intraperi‑ toneal or intravaginal infection50, and TLR2‑deficient mice had elevated levels of MCMv in the spleen and liver after intraperitoneal infection56. Both studies reported that a lack of TLR2 led to impaired expression of cytokines and reduced activation of NK cells50,56, and it was demonstrated that MCMv‑induced production of type I IFNs was compromised in TLR2‑deficient mice56. Two genetic studies in humans have now shown that TLR2 has protective roles during natural herpesvirus infections. Two haplotypes of TLR2 (haplotypes 2 and 4) were shown to be associated with increased frequency of genital Hsv‑2 lesions and viral shedding in infected individuals57, and transplant recipients with the TLR2 polymorphism R753Q have elevated HCMv replication

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REVIEWS Box 1 | The herpes virion and the lytic replication cycle The herpes virion is composed of a double-stranded DNA genome, which encodes approximately 100 transcripts; an icosahedral capsid composed of 162 capsomers, including four protein subunits; the tegument, an amorphous layer of proteins that is released into the host cell following infection; a lipid membrane bilayer envelope, which is derived from the trans-Golgi network of the producer cell; and glycoproteins (at least 11) that are embedded in the lipid bilayer. Herpesviruses enter host cells either at the cell surface or via pH-dependent endocytosis through a process involving a trio of glycoproteins that are conserved among all herpesviruses. The tegument proteins are then released into the cell and the capsid is transported to the nuclear membrane, where DNA is released into the nucleus. The viral replication process is initiated by the expression of immediate-early *GTRGUXKTWU2#/2U /KPKOWOQHIN[EQRTQVGKPU genes, which encode proteins r)N[EQRTQVGKPU XKTKQP I.I*CPFI$CTGEQPUGTXGF that promote the expression of r)GPQOKE&0# XKTKQP 8KTCN r'PVT[ r40#UVTWEVWTGU TGRNKECVKQP GPXGNQRG r'ITGUU viral genes and also have a role r1VJGT! r*QUVGXCUKQP in innate immune evasion. This r%GNNVQEGNNURTGCF is followed by expression of the early proteins, which are responsible for replication of the viral DNA genome, and eventually the late proteins, which include capsid, tegument and envelope proteins. The late protein products and the replicated DNA are assembled into progeny virions, which are released from the cell either by exocytosis through the trans-Golgi network or by cell lysis (see figure). Establishment and maintenance of latency is a complex process that involves many viral and cellular components. It is believed that suppression of immediate-early genes, by virus-encoded microRNAs for example, has a central role in this process. The innate immune system can detect components of the herpesvirus particle (glycoproteins and DNA) or replication intermediates that are produced during productive infection (RNA structures).

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and are more likely to develop CMv disease . Both of these studies addressed the role of TLR2 in established infection, and therefore suggest that TLR2 is involved in controlling herpesviruses in the latent state. 58

TLR9. The most potent immune‑stimulating component of herpesvirus particles is probably the genomic DNA. TLR9 senses DNA in endosomes59, and all three classes of human herpesviruses are recognized by TLR9 (REFs 60–64). In addition, MCMv and murine gammaherpesvirus 68 (MHv68) are recognized by this PRR, allowing pathogen‑ esis studies in animal models65–67. Based on studies using synthetic DNA, the prevailing paradigm has been that TLR9 recognizes CpG motif‑containing DNA, which is abundantly present in herpesvirus genomes. Recent stud‑ ies using natural DNA suggest that both CpG content and the level of methylation of the motif strongly affect the

ability of DNA to activate TLR9 (REF. 68), whereas the DNA backbone sugar 2ʹ deoxyribose rather than the CpG motif determines TLR9 activation by synthetic DNA69. Thus, the molecular mechanism of TLR9‑mediated sens‑ ing of herpesvirus DNA remains to be fully understood. In humans, TLR9 expression is restricted to B cells and plasmacytoid DCs (pDCs), whereas in mice it is widely expressed by many cell types10,24. As TLR9 signalling leads to the activation of IRF7 (REF. 70), recognition of herpes‑ viruses by TLR9 in both human and mouse pDCs results in expression of type I IFNs60,61,63,71. Initial studies of herpesvirus infections in TLR9‑ deficient mice failed to show an effect on antiviral activity61. subsequently, modest effects of TLR9 deficiency on early antiviral and inflammatory events after Hsv infections have been reported, mainly owing to impaired pDC‑ derived type I IFN responses in the TLR9‑deficient mice

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REVIEWS and impaired NK cell activation50,72–74. Importantly, in a model of corneal Hsv‑1 infection, TLR9‑deficient mice displayed a more pronounced phenotype involving mark‑ edly compromised expression of IFN-stimulated genes (IsGs), recruitment of neutrophils and control of viral load75. In the MCMv model, infection of TLR9‑deficient mice through the intraperitoneal route revealed an impaired antiviral response and increased mortality. TLR9 was shown to stimulate early type I IFN produc‑ tion, as well as NK cell production of IFNγ71. other groups have confirmed the role of TLR9 in the early type I IFN response, and demonstrated the source to be pDCs76,77. Finally, TLR9 deficiency has also been reported to impair the host response to MHv68 infection, as reduced cytokine expression by DCs and higher viral load during both lytic and latent infection is observed in mice lacking TLR9 (REF. 67). With respect to gammaherpesviruses, it has been demonstrated that TLR9 has essential roles during the elimination of acute MHv68 infection and the con‑ trol of latent viral load67 following infection through the intraperitoneal route, but not after intranasal infection. Therefore, TLR9 is only important for the host immune response to pathogens that reach locations where pDCs are abundantly present (such as the lymphoid organs and blood). The specialized but often redundant role of TLR9

IFN-stimulated genes (IsGs). Genes that are induced by interferons (IFNs) through their IFN-stimulated response element (IsRE), which is bound by the IFN-activated transcription factor IsGF3. A subgroup of IsGs is induced by pattern recognition receptor signalling, through transcription factors of the IRF family.

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in the protective immune response to herpesvirus infec‑ tions is further supported by the observation that patients with an IL‑1R‑associated kinase 4 (IRAK4) mutation, which abolishes the production of IFNs following stimu‑ lation of TLR7, TLR8 and TLR9, do not have increased susceptibility to infections with herpesviruses78. TLR3. Whereas TLR2 and TLR9 are activated by PAMPs that are present in the herpesvirus particle, replication of herpesviruses leads to the intracellular accumulation of double‑stranded RNA (dsRNA) structures79, which can function as TLR3 agonists80. Although the specific RNA species from alphaherpesviruses and betaherpesviruses that stimulate TLR3 have not been characterized, it has been reported that latency‑associated epstein–Barr virus (eBv)‑encoded small RNAs (eBeRs), which are non‑polyadenylated, non‑coding dsRNAs with stem– loop structures, are released from eBv‑infected cells and stimulate TLR3 (REF. 81). TLR3 is constitutively expressed by several cell types including epithelial cells and CD8α+ DCs. In addition, TLR3 expression is strongly induced by type I IFNs and viral infections in most cell types82. TLR3 signalling through the adaptor protein TIR‑domain‑containing adaptor protein inducing IFNβ (TRIF; also known as

Figure 1 | Innate immune recognition and activation by herpesviruses. a | The herpes virion is sensed by Toll-like receptor 2 (TLR2), which probably detects herpesvirus glycoproteins and then induces the expression of pro-inflammatory cytokines, and in specific cell types also type I interferons (IFNs). Viral genomic DNA is detected by TLR9 in endosomes, and by DNA-dependent activator of IFN-regulatory factors (DAI), DEAH box protein 9 (DHX9) and DHX36, absent in melanoma 2 (AIM2) and IFNγ-inducible protein 16 (IFI16) in the cytoplasm. DNA sensing by the RNA polymerase III (Pol III) and retinoic acid-inducible gene I (RIG-I) system may take place in either the nucleus or the cytoplasm. Productive replication of herpesviruses leads to the accumulation of RNA species, including higher order RNA structures. These RNAs are sensed either in the cytoplasm by melanoma differentiationassociated gene 5 (MDA5) or in endosomes by TLR3 and TLR7. b | The intracellular DNA sensing pathways together lead to the expression of cytokines, including type I IFNs, and the activation of the inflammasome. The cellular response to RNA sensing involves the production of IFNs and other cytokines. 1o, 2o and 3o responses indicate the proposed relative importance of the downstream events activated by the pattern recognition receptors (PRRs). MAVS, mitochondrial antiviral signalling protein.

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REVIEWS Cross-presentation The ability of certain antigen-presenting cells (APCs) to load peptides that are derived from exogenous antigens onto MHC class I molecules. This property is atypical, because most cells exclusively present peptides from their endogenous proteins on MHC class I molecules. Cross-presentation is essential for the initiation of immune responses to viruses that do not infect APCs.

Autophagy A catabolic process in which cells degrade cytosolic content, including organelles, through the lysosomal machinery.

TICAM1) potently activates IRF3 and NF‑κB, leading to the expression of IFNβ and other pro‑inflammatory cytokines83. The specific expression of TLR3 by CD8α+ DCs promotes the cross-presentation of viral antigens84, which contributes to development of an efficient CD8+ T cell response against Hsv‑1 (REF. 85). Currently it is not known how the herpesvirus RNA that accumulates in the cytoplasm is detected by endosomal TLR3. The mechanism may involve phagocytosis of infected cells in the case of CD8α+ DCs84, but it is less obvious what happens in stromal cells, although one possibility is that autophagy is used to traffic this viral danger signal to TLR3‑containing compartments. MCMv‑infected TLR3‑deficient mice have increased viral loads in the spleen and reduced serum cytokine lev‑ els, but show no difference in survival compared with wild‑type mice65. In addition, it was recently shown that TLR3‑deficient mice exhibit impaired generation of virus‑specific CD8+ T cells following skin Hsv‑1 infec‑ tion, and this was associated with impaired control of the virus at late time points post‑infection85, suggesting a role for TLR3 in stimulation of the adaptive immune response, as previously proposed84. The most compel‑ ling evidence for a role for TLR3 in host defence against herpesvirus infections stems from the finding that two children with Hsv‑1 encephalitis were homozygous for

Table 2 | PRRs and PAMPs in innate immune recognition of herpesviruses PRR

Virus

Proposed PAmP

Refs

TLR2

HSV-1, HSV-2

Virion component

49,50

VZV

Virion component

51

HCMV

gB and/or gH

47

EBV

Virion component, dUTPase

HSV-1

dsRNA

86

MCMV

dsRNA

65

TLR3

52,140

EBV

EBERs

81

TLR7

MCMV

ssRNA

76

TLR9

HSV-1, HSV-2

Genomic DNA

60,61

MCMV, HCMV

Genomic DNA

62,65,66 63,64

EBV

Genomic DNA

MDA5

HSV-1

Replication intermediate

94

Pol III and RIG-I

HSV-1

Genomic DNA

20

EBV

EBER DNA

19

HSV-1

Genomic DNA

14

HCMV

Genomic DNA

99

IFI16

HSV-1

Genomic DNA

22

DHX9 and DHX36

HSV

Genomic DNA

102

AIM2

MCMV

Genomic DNA

105

DAI

AIM2, absent in melanoma 2; DAI, DNA-dependent activator of interferon-regulatory factors; DHX, DEAH box protein; dsRNA, double-stranded RNA; EBER, EBV-encoded small RNA; EBV, Epstein–Barr virus; gB, envelope glycoprotein B; gH, envelope glycoprotein H; HCMV, human cytomegalovirus; HHV, human herpesvirus; HSV, herpes simplex virus; IFI16, interferon-γinducible protein 16; MCMV, mouse cytomegalovirus; MDA5, melanoma differentiationassociated gene 5; PAMP, pathogen-associated molecular pattern; Pol III, RNA polymerase III; PRR, pattern recognition receptor; RIG-I, retinoic acid-inducible gene I; ssRNA, single-stranded RNA; TLR, Toll-like receptor; VZV, varicella-zoster virus.

a rare TLR3 mutation (P554s) that was absent in more than 1,500 healthy controls86. Fibroblasts from these two patients responded to Hsv‑1 infection with an impaired IFNβ response86. Finally, a recent case report describes the L412F TLR3 variant, which has reduced activity 87, in a patient with frequently recurrent lymphocytic Hsv‑2 meningitis88. Despite these data, the mechanism by which TLR3 protects against Hsv infection in the central nervous system is unknown. TLR7. In addition to TLR3, TLR7, which is a sensor of single‑stranded RNA that is expressed by pDCs76, has recently been reported to sense MCMv infection, and this recognition is essential for a full IFNα response and optimal antiviral defence76. Mice that are deficient in both TLR7 and TLR9 are considerably more sus‑ ceptible to MCMv infection than either of the single knockout mouse strains76, and have a phenotype that is comparable to mice that lack the TLR adaptor protein myeloid differentiation primary‑response protein 88 (MyD88). since both alphaherpesvirus and betaher‑ pesvirus particles have been reported to contain viral mRNAs89,90, it is not clear whether TLR7 senses virion‑ or replication‑associated RNA. Collectively, herpesviruses are detected by TLR2, TLR3, TLR7 and TLR9. Whereas TLR3, TLR7 and TLR9 detect herpesvirus nucleic acids, TLR2 senses virions, although we still lack a full understanding of the nature of the PAMP that is recognized by TLR2. so, TLR‑ mediated sensing of herpesviruses orchestrates early antiviral and inflammatory responses.

Recognition by intracellular nucleic acid receptors Although TLRs have a clear role in the sensing of herpes‑ virus infections, the fact that viruses replicate and persist intracellularly suggested that PRRs that function in the intracellular environment to detect viral RNA and DNA PAMPs also contribute to innate immune recognition of these viruses91. RNA. Intracellular herpesvirus RNA can be recognized by the RLRs. similar to TLR3, RIG‑I senses eBeRs, but it does so in the cytoplasm, leading to induction of IFNs and IL‑10 (REFs 92,93). We have recently reported that Hsv‑1‑induced IFN responses by primary human monocyte‑derived macrophages depend on MDA5 and its adaptor protein mitochondrial antiviral signal‑ ling protein (MAvs; also known as CARDIF, IPs1 and vIsA)35,94. As the response was also dependent on viral gene expression, which correlated with the induction of IFNs and IsGs, these data suggest that replication‑induced higher‑order RNA structures are detected by MDA5 in Hsv‑1‑infected human macrophages35,94. In contrast to most TLRs, the RLRs are expressed by most cells in the body, and are also strongly induced by IFNs95. Therefore, RLRs could be involved in the recognition of herpesvirus infection in permissive cells, particularly at later stages of infection when the expression of RLRs is highly upregu‑ lated. In such a scenario, RLRs would not be responsible for the initial antiviral IFN response, but would instead contribute to the control of productive infections.

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REVIEWS

Pyrin and HIN domaincontaining protein family A family of proteins with both pyrin and HIN domains. Pyrin domains mediate pyrin–pyrin homotypic interactions and stimulate signal transduction, whereas HIN domains bind DNA.

DNA. Given that herpesviruses have DNA genomes, the main focus of the search for host intracellular sensing systems has been on viral DNA recognition. Akira and colleagues first reported that transfection of Hsv and HCMv DNA into fibroblasts induces TLR‑independent expression of IFNβ 96. We subsequently reported that expression of type I IFNs by splenic conventional DCs was independent of TLR9, but dependent on viral entry and genomic DNA72. The first cytoplasmic DNA sensor to be identified was the IsG DAI, which induces signalling to activate IRF3 and promote type I IFN expression14, and the initial report indicated a role for DAI in Hsv‑1‑induced IFNβ expression14. However, this was only seen in a mouse fibroblast‑like cell line14, and subsequent analysis of DAI‑deficient mice has failed to identify any essential roles for DAI in innate antiviral responses97. Based on this, it seems that DAI is not the main sensor of, at least, Hsv DNA, and that DAI has a more specialized role, which remains to be described. Interestingly, recent studies show that type I IFN produc‑ tion by HCMv‑infected fibroblasts is mediated by DAI98,99, which suggests a role for DAI in the early response to herpesvirus infections in a specific subset of cells. Although the RLRs are sensors of RNA, some data have suggested a role for this system in the detection of DNA100. Two reports have now provided a potential mechanism. AT‑rich DNA can be transcribed by RNA polymerase III into 5ʹ‑triphosphate RNA, which subse‑ quently activates RIG‑I. This pathway was reported to be involved in type I IFN induction during eBv infections in which eBeRs are produced from viral DNA by RNA polymerase III19. This indirect DNA‑sensing system was also reported to be involved in the induction of type I IFNs following Hsv‑1 infection20. However, other studies have not been able to show a role for RNA polymerase III in sensing of Hsv‑1 DNA22,94, and one report has shown direct interaction between Hsv‑1 DNA and RIG‑I and non‑redundant roles for RIG‑I and MDA5 in the sens‑ ing of Hsv DNA by fibroblasts101. These findings raise questions as to the requirement for RNA polymerase III in herpesvirus DNA recognition and urge identification of the potential mechanism involved. RLRs belong to the family of DexD/H box helicases, and two other members of this family, namely DeAH box protein 9 (DHX9) and DHX36, have recently been reported to recognize CpG‑containing DNA in pDCs and induce activation of NF‑κB and IRF7, respectively, through MyD88 (REF. 102). Importantly, DHX9 and DHX36 were associated with the expression of pro‑ inflammatory cytokines and IFNα, respectively, after Hsv‑1 infection of a human pDC line102. The proposal that DHX9 and DHX36 are newly described sensors of cytosolic DNA in pDCs may explain previously unexplained findings of TLR9‑independent cytokine responses to Hsv and CMv infections in pDCs50,72,77. Herpesviruses are also known to activate inflammas‑ omes leading to caspase 1 activation. The identification of AIM2 as a cytosolic dsDNA sensor that stimulates caspase 1 activation has provided a mechanism for this 15–18. AIM2 belongs to the pyrin and HIN domaincontaining protein family (PyHIN family) and binds

DNA through its HIN domain103,104. AIM2 then engages apoptosis‑associated speck‑like protein containing a CARD (AsC; also known as PyCARD) through pyrin domain interactions and recruits pro‑caspase 1, leading to the production of active caspase 1 and mature IL‑1β and IL‑18. There is genetic evidence demonstrating that the AIM2 inflammasome is activated by MCMv105, and MCMv‑infected AIM2‑deficient mice display reduced levels of serum IL‑18 and lower spleen IFNγ production, and have higher viral loads105. By contrast, the inflammasome that is activated by Hsv‑1 seems to be independent of AIM2 and remains to be further characterized105. Recently, in a collaborative effort between our labo‑ ratories, we identified IFI16, another PyHIN family protein, as an intracellular sensor of Hsv‑1 DNA that stimulates the expression of IFNβ and pro‑inflammatory genes during infection with this virus22. Free Hsv‑1 genomic DNA was found in the host cell cytosol dur‑ ing infection and IFI16 bound directly to isolated viral DNA motifs. Reduction in the expression of IFI16, or its mouse orthologue IFI204, by RNA interference inhibited DNA‑ and Hsv‑1‑mediated gene induction and activation of IRF3 and NF‑κB22. Although IFI16 is mainly present in the nucleus, a significant portion localizes to the cytosol, where it colocalizes with viral DNA22. However, it remains possible that IFI16 recog‑ nizes Hsv‑1 DNA in the nucleus and migrates to the cytoplasm to stimulate signal transduction. Together with AIM2 and IFI202 (a PyHIN family protein that negatively regulates AIM2), these proteins constitute a new family of AIM2‑like receptors (ALRs) that rec‑ ognize intracellular DNA. The role of IFI16 in innate antiviral defence against herpesviruses in vivo remains to be described, including its role in directing adaptive immune responses. As MCMv and HCMv exploit IFI16 (IFI204 in mice) for their own benefit to promote replication29,106, it will be interesting to determine if the net effect of herpesvirus–IFI16 interactions are bene‑ ficial or detrimental for the ability of herpesviruses to replicate. In summary, intracellular nucleic acid‑sensing PRRs have an important role in the activation of innate immune responses against viruses. In the case of her‑ pesviruses, RNA replication intermediates can stimulate endosomal and cytosolic PRRs, but it seems that the genomic DNA is the main trigger of the innate immune response. In the case of recognition of RNA viruses by RLRs, it was recently reported that genomic RNA gen‑ erated by viral replication constitutes the major trigger for RLRs107. Based on the available data on herpesvirus recognition, and the observation that herpesvirus DNA replication occurs after innate immune activation is ini‑ tiated, it seems that for DNA viruses it is the incoming genomic material that is sensed by PRRs. Exposure of herpesvirus nucleic acid PAMPs to intra­ cellular PRRs. Despite the identification of several PRRs that can recognize herpesvirus nucleic acid PAMPs, it is not known how the genomic material arrives at these cellular compartments nor how the capsid‑protected

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REVIEWS 8KTWU

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Figure 2 | Intracellular detection of herpesvirus DnA and activation of signal 0CVWTG4GXKGYU^+OOWPQNQI[ transduction. Productive replication of herpesviruses requires transport of the viral capsid to a nuclear pore, where the genomic DNA is released into the nucleus. Alternatively, herpesvirus DNA may be released from the capsid into the cytosol and be subject to immune recognition. Cytosolic sensors of viral capsids may exist, which target the capsid for degradation through either autophagy or the proteasome. Autophagy-mediated degradation of the capsid will expose the viral DNA to Toll-like receptor 9 (TLR9) in endosomes. Alternatively, TLR9 could receive the viral DNA from an endocytic or phagocytic route. Degradation of the capsid in the cytosol exposes the DNA to the cytosolic DNA sensors, including interferon-γ (IFNγ)-inducible protein 16 (IFI16) and DNA-dependent activator of IFN-regulatory factors (DAI), which in turn associates with stimulator of IFN genes (STING) and re-localizes from the endoplasmic reticulum (ER) to perinuclear vesicles from where signalling takes place. DEAH box protein 9 (DHX9) and DHX36 detect cytosolic DNA and signal through myeloid differentiation primary-response protein 88 (MYD88) like TLR9. DDX3, DEAD box protein 3; IKK, IκB kinase; IRF, IFN regulatory factor; NF-κB, nuclear factor-κB; TBK1, TANK-binding kinase 1.

DNA is made accessible to PRRs. Herpesviruses can enter cells through both endocytic and non‑endocytic pathways 44. Following endocytic entry, endosomal processing of viral capsids can potentially lead to the exposure of viral DNA and presentation to TLR9 (FIG. 2). After entry through the non‑endocytic pathway, which

also results in TLR9 stimulation72, an alternative path‑ way of virus delivery to endosomes must be involved. This could involve autophagy, in parallel to the reported role for autophagy in delivering cytosolic viral RNA to TLR7 in endosomes108. We recently demonstrated that Hsv‑1 DNA can be detected in the cytosol of infected cells22. However, whether DNA in the cytosol originates from the nuclear, cytoplasmic or endosomal compartment is still unclear. viruses that enter the cell through an endocytic route may be subject to degradation44, which could be followed by the translocation of DNA PAMPs from the endosomal lumen to the cytosol. Alternatively, herpesvirus DNA may be exposed to the cytosol following proteasomal degradation of the viral capsid. Proteasomal activity is essential for the induction of IsGs during Hsv infection and for the delivery of Hsv DNA from the capsid to the nucleus109,110. Thus, there are many potential mechanisms that may mediate the exposure of herpesvirus DNA to the cytosolic DNA‑sensing machinery, all requiring further examination. Herpesvirus DNA replication occurs in the nucleus of infected cells, potentially providing an abun‑ dance of DNA for recognition at this location. However, at present there is no evidence for innate immune sensing by herpesviruses in the nucleus, although the localization of IFI16 to both the cytosol and nucleus is intriguing and urges investigation of its potential role in the recognition of herpesvirus DNA in the nucleus. Activation of signal transduction in response to intra­ cellular DNA sensing. Cytosolic DNA recognition leads to the activation of TANK‑binding kinase 1 (TBK1) and IRF3, and the production of type I IFNs and pro‑ inflammatory cytokines (FIG. 2). However, the signalling pathway linking upstream DNA sensors to TBK1 are poorly characterized. TBK1 associates with DDX3, a DeAD box RNA helicase, which regulates IRF3‑induced IFNβ transcription99,111,112. In addition, TBK1 interacts with the exocyst protein seC5 (also known as eXoC2) in a complex that includes the recently identified endo‑ plasmic reticulum (eR) adaptor stimulator of IFN genes (sTING; also known as TMeM173)113, although the role of seC5 in this complex is unclear. sTING is essential for activation of the signalling pathway upstream of TBK1 following Hsv‑1 infection113,114 and has been shown to associate with IFI16 and to relay signals downstream of DAI22,99. sTING interacts with the eR translocon com‑ ponents seC61β and TRAPβ in a manner that is essen‑ tial for the regulation of cytosolic DNA‑induced type I IFN production113, although the mechanism involved is not known. Concerning the subcellular location where cytosolic sTING‑dependent DNA signalling occurs, recent studies have provided interesting but somewhat con‑ tradictory conclusions. In unstimulated cells, sTING localizes to the eR and perhaps eR‑associated mito‑ chondria22,99,115. Following stimulation with cytosolic DNA and Hsv‑1, sTING translocates to perinuclear foci, via the Golgi22,99,115. However, the nature of these sTING‑containing structures is contentious. one report indicates that sTING localizes partially to endosomes,

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Figure 3 | Herpesvirus evasion of PRR-mediated recognition, signalling and gene expression. Herpesviruses 0CVWTG4GXKGYU^+OOWPQNQI[ encode proteins that help them to evade detection by pattern recognition receptors (PRRs). For example, the herpes simplex virus type 1 (HSV-1) proteins ICP34.5 and virion host shut-off protein (Vhs) prevent the recognition of viral nucleic acids by inhibiting autophagy and degrading viral RNA, respectively. Herpesviruses also inhibit signalling through PRRs using multiple mechanisms. Some are specific to individual PRRs; for example: HSV-1 ICP0 protein inhibits Toll-like receptor 2 (TLR2) signalling by stimulating the degradation of TLR adaptor molecules; and murine cytomegalovirus (MCMV) M45 protein inhibits the recruitment of receptor-interacting protein 1 (RIP1) to DNA-dependent activator of IFN-regulatory factors (DAI). There are also more general mechanisms that target all PRRs; for example, human herpesvirus 8 (HHV8) ORF45 protein interacts with IFN regulatory factor 7 (IRF7) and inhibits its phosphorylation and nuclear translocation. Finally, several herpesvirus-encoded proteins (such as HHV8 v-IRF3) inhibit transcription by interacting with nuclear factor-κB (NF-κB) and IRF3 and/or IRF7 in the nucleus. This prevents the interaction of these transcription factors with DNA, and the assembly of functional transcriptional complexes. DDX3, DEAD box protein 3; DHX9, DEAH box protein 9; EBV, Epstein–Barr virus; HCMV, human cytomegalovirus; IE, immediate-early protein; IFI16, IFNγ-inducible protein 16; IκB, inhibitor of NF-κB; IKK, IκB kinase; LANA1, latency-associated nuclear antigen 1; MAVS, mitochondrial antiviral signalling protein; MDA5, melanoma differentiation-associated gene 5; RIG-I, retinoic acid-inducible gene I; TBK1, TANK-binding kinase 1; v-PK, viral protein kinase; VZV, varicella-zoster virus.

particularly seC5‑positive structures114, whereas another report has shown that sTING localizes to vesicular structures, which are not peroxisomes, mitochondria, endosomes or autophagosomes115. Clearly, further work is required to elucidate the composition and sites of signalling in response to intracellular DNA recognition.

Viral evasion of innate immune responses Herpesviruses are large viruses, with slow replication cycles and the ability to establish latent infections. Initiation of replication and establishment of infection

are strongly influenced by the early virus–host interac‑ tions occurring within minutes of exposure, including hijacking of pre‑existing host cell signalling pathways (such as the phosphoinositide 3‑kinase–AKT pathway)27. Therefore, to successfully colonize the host, herpesvi‑ ruses need to actively evade and modulate host responses at all stages of infection. There is strong evidence for herpesviruses evading the innate immune system28–43 (FIG. 3). The mechanisms include avoidance of sensing by PRRs, blocking of the action of PRRs, and inhibi‑ tion of signalling pathways and gene expression. With

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REVIEWS

Neurovirulence factor A factor that is essential for the ability of a pathogen to be pathogenic in the nervous system. Herpes simplex virus and rabies virus are neurovirulent viruses.

Tegument An amorphous layer of proteins that lines the space between the lipid membrane and the nucleocapsid of herpesviruses. The tegument proteins generally support viral replication and evasion of immune responses.

respect to evasion of recognition, the Hsv‑1‑encoded RNA endonuclease virion host shut‑off protein (vhs), an mRNA‑specific RNase that cleaves virus and host mRNA116, was recently reported to impair activation of the RNA‑sensing pathways through TLR3 and RLRs in conventional DCs, presumably by destroying the viral agonists that trigger this response30. similarly, Hsv‑1 counteracts the delivery of PAMPs from the cytoplasm to endosomal compartments where TLR3, TLR7 and TLR9 operate117. The neurovirulence factor ICP34.5 pre‑ vents autophagy by directly binding to the autophagy‑ inducing protein beclin 1 (REF. 34). Given the reported role for autophagy in delivery of viral cargo to endo‑ somes108, the ICP34.5‑mediated inhibition of autophagy is likely to counteract the detection of viral nucleic acids by endosomal TLRs. The second principle in innate immune evasion is inhibition of the action of specific PRRs. For exam‑ ple, the Hsv immediate‑early protein ICP0 inhibits TLR2‑induced responses by promoting the degradation of MyD88 and MyD88‑adaptor‑like protein (MAL; also known as TIRAP)33. Following the recent identification of cytosolic DNA sensors proposed to be involved in the stimulation of innate immune responses during herpesvirus infections14,19,20,22,102, it is interesting that there is now evidence that herpesvirus proteins inhibit several of these sensors — DAI, DHX9 and IFI16 (REFs 29,31,37) . The HCMv tegument protein uL83 (also known as pp65), which has long been known to inhibit virus‑induced expression of IsGs118,119, has been found to directly interact with IFI16, suggesting an immune evasion strategy whereby HCMv could inhibit IFI16‑dependent antiviral responses29. In support of this idea, the deletion of uL83 in guinea pig CMv signifi‑ cantly attenuated the virus in vivo120. Likewise, MCMv targets DAI signalling through its M45 protein31, and the HHv8 viral protein kinase (v‑PK) directly interacts with DHX9 and inhibits downstream activities of the receptor 37. Together, these data suggest an important role for the intracellular DNA sensors in the innate immune response to herpesviruses. The third principle in innate immune evasion involves viral inhibition of downstream signalling and gene expression programmes that are activated by PRRs. Given the important role for type I IFNs in innate anti‑ viral defence against herpesviruses6,7,121, it is no surprise that all classes of herpesviruses target the IRF–IFN path‑ way at various levels28,32,35,36,38–40,42,43 (FIG. 3). The e3 ubiq‑ uitin ligase ICP0 of Hsv‑1 and other alphaherpesviruses can inhibit nuclear accumulation of IRF3 and induction of IFNs28,122. At the mechanistic level, this involves both the degradation of IRF3 and the sequestration of IRF3 and CBP/p300, and this is dependent on cytoplasmic localization of ICP0 (REFs 28,123,124). Although most herpesvirus immune evasion proteins have no or limited sequence similarity to the proteins that they antagonize, the HHv8 genome contains a cluster of open reading frames that encode proteins with homology to the IRF family 40, known as v‑IRFs, which inhibit host cell expres‑ sion of IFNs. For example, v‑IRF3 inhibits the action of IRF3, IRF5 and IRF7 by directly interacting with the

cellular IRFs, hence preventing DNA binding and IFN promoter activation125,126. Collectively, herpesviruses tar‑ get the innate immune system by avoiding sensing by PRRs, blocking the action of specific PRRs and inhibit‑ ing signalling pathways and the expression of antiviral genes. The identification of such viral immune evasion strategies provides strong evidence for the importance of the early innate immune system in the control of herpesvirus infections.

Innate immune control of latent infections Latent herpesvirus infections are characterized by the presence of viral DNA in the nucleus of infected cells, but limited or no viral replication activities. It has long been known that CD8+ T cells are important for control‑ ling herpesvirus infections during latency and reactiva‑ tion2,3, but emerging evidence suggests that the innate branch of the immune system also has a central role in controlling latent herpesvirus infections. For example, pDCs infiltrate the dermis of recurrent genital Hsv‑2 lesions and stimulate T cell proliferation127. Interestingly, the cells in the dermis that immediately surround the pDCs express IsGs, suggesting a role for type I IFNs in controlling recurrent Hsv‑2 infection. This is fur‑ ther supported by the ability of Hsv‑1 ICP0, which is a rate‑limiting protein in reactivation of alphaherpes‑ viruses, to inhibit IRF3 activation and IFN production28. Although the involvement of ICP0 in reactivation was originally believed to be due to its role in replication, this involvement may also be attributed to the essential role of ICP0 in limiting the host IFN response, a function that is now also ascribed to the HHv8 latency‑associated nuclear antigen 1 (LANA1)42. Finally, one of the reported patients with the TLR3 P554s mutation developed Hsv encephalitis during both primary and recurrent infec‑ tion, further suggesting a role for the innate immune system in controlling herpesviruses in the latent state86. The innate immune system may affect herpesvirus latency at various steps. The classical innate antiviral activ‑ ity of type I IFNs during primary infection may reduce the latent viral genome load per cell as suggested from mouse studies67,128. second, IFNs could be induced during reactivation, as indicated by the expression of IsGs during Hsv‑2 reactivation127. This would suggest that PRRs, such as ALRs, sense low‑grade reactivation or even the latent viral genome. Third, the ability of the innate immune response to shape the adaptive immune response could affect the potency of the CD8+ T cell response. In this respect it is worth noting that TLR3‑deficient mice exhibit impaired development of virus‑specific CD8+ T cells in a model for Hsv‑1 skin infection85. Further support for a role of the innate immune system in controlling herpesviruses comes from evi‑ dence that TLRs are exploited by these viruses to establish latency and reactivation. establishment of latency by MHv68 has been reported to be impaired in MyD88‑deficient mice, probably owing to reduced acti‑ vation of B cells, which are the main latency reservoir 129, suggesting that MHv68 uses TLR signalling to condition the target cell for establishment of latency. In addition, two studies have shown that TLR stimulation of cells that

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REVIEWS 2’-5’-oligoadenylate synthetase A family of interferon- and virus-inducible enzymes that catalyses the formation 2’-5’ oligomers of adenosine to stimulate antiviral activities that are dependent and independent of RNase L.

are latently infected with MHv68 or HHv8 reactivates these two gammaherpesviruses130,131. For HHv8 infec‑ tion, it was further shown that not only synthetic PAMPs but also infection with vesicular stomatitis virus, which stimulates TLR7 and RIG‑I, led to reactivation of the infection130. These findings demonstrate that second‑ ary pathogen infection can reactivate HHv8 through stimulation of PRRs.

Conclusions and perspectives our understanding of how herpesviruses are detected by the innate immune system and stimulate antiviral activi‑ ties has grown tremendously over the past decade. This has been accompanied by an improved understanding of how these viruses evade the innate immune response and establish persistent infection. This field now faces several interesting questions that need to be addressed for the translation of basic knowledge into understanding of disease pathogenesis. First, with the identification of new intracellular PRRs that sense herpesvirus infections, it is essential to establish their roles and mechanisms of action in immune defence and pathogenesis. Given the important role of ALRs in the recognition of herpes‑ viruses, understanding the intracellular dynamics of rec‑ ognition and signalling molecules, and also how the viral DNA is made accessible for PRRs, is essential. Progress in this area may also start to resolve the important ques‑ tion of whether herpesviruses are detected by the innate immune system in the nucleus and, if this is the case, how viral DNA is then distinguished from host DNA. second, although it is clear that detection of classi‑ cal PAMPs is central to immune surveillance, we also believe that the innate immune system can sense viral infections through other mechanisms. It seems likely that novel principles of pathogen recognition, by which viral activities rather than molecular structures are sensed, remain to be discovered. This would allow the host to

1. 2.

3.

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Pellett, P. E. & Roizman, B. The Family: Herpesviridae A Brief Introduction in Fields Virology 2479–2500 (Lippincort, Williams & Wilkins, Philadelphia, 2007). Liu, T., Khanna, K. M., Chen, X., Fink, D. J. & Hendricks, R. L. CD8+ T cells can block herpes simplex virus type 1 (HSV-1) reactivation from latency in sensory neurons. J. Exp. Med. 191, 1459–1466 (2000). Liu, T., Khanna, K. M., Carriere, B. N. & Hendricks, R. L. Gamma interferon can prevent herpes simplex virus type 1 reactivation from latency in sensory neurons. J. Virol. 75, 11178–11184 (2001). Reusser, P., Riddell, S. R., Meyers, J. D. & Greenberg, P. D. Cytotoxic T-lymphocyte response to cytomegalovirus after human allogeneic bone marrow transplantation: pattern of recovery and correlation with cytomegalovirus infection and disease. Blood 78, 1373–1380 (1991). Braaten, D. C., Sparks-Thissen, R. L., Kreher, S., Speck, S. H. & Virgin, H. W. An optimized CD8+ T-cell response controls productive and latent gammaherpesvirus infection. J. Virol. 79, 2573–2583 (2005). Dupuis, S. et al. Impaired response to interferon-α/β and lethal viral disease in human STAT1 deficiency. Nature Genet. 33, 388–391 (2003). This paper showed that patients with STAT1 deficiency do not respond to type I IFNs and are susceptible to herpes simplex virus encephalitis. Salazar-Mather, T. P., Lewis, C. A. & Biron, C. A. Type I interferons regulate inflammatory cell trafficking and macrophage inflammatory protein 1α

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distinguish pathogenic from non‑pathogenic infec‑ tions. Lytic infection, a property of all herpesviruses, is an activity that is directly associated with pathogenicity, and a recent report has shown that 2’-5’-oligoadenylate synthetase is induced in virus‑infected cells, released following cell lysis and subsequently taken up by non‑ infected cells to exert antiviral activity 132. It will be inter‑ esting to establish if host sensing of pathogen‑induced processes is a new layer of immune surveillance that is yet to be described. Third, herpesviruses, and in particular eBv, have been proposed to be involved in the pathogenesis of autoimmune diseases133,134. Given the overlap between the PRRs that recognize herpesviruses, most notably TLR9 and IFI16, and those proposed to be involved in the pathogenesis of autoimmune diseases (such as sys‑ temic lupus erythematosus, sjogren’s syndrome and systemic sclerosis) 135–137, the role of herpesviruses and PRRs in these conditions should be explored further to potentially identify the long‑sought‑after missing link between herpesviruses and autoimmune diseases. Finally, although the intellectual and experimental forefront of immunology research has always been centred on studies in rodents, it is important that the findings from these model studies are tested in human systems. Moreover, a close interaction between the basic and clinical research communities will ensure that new discoveries are rapidly investigated under conditions that are directly rel‑ evant to the diseases caused by herpesviruses in humans. The identification of several novel primary immuno‑ deficiencies with defects in viral sensing and type I IFN production, all of which are associated with susceptibility to Hsv encephalitis6,86,138,139, underscores the important role of the innate immune system in controlling herpes‑ virus infections and maintaining the balance between the virus and the host that has been achieved through millions of years of co‑evolution.

delivery to the liver. J. Clin. Invest. 110, 321–330 (2002). Biron, C. A., Byron, K. S. & Sullivan, J. L. Severe herpesvirus infections in an adolescent without natural killer cells. N. Engl. J. Med. 320, 1731–1735 (1989). Rager-Zisman, B., Quan, P. C., Rosner, M., Moller, J. R. & Bloom, B. R. Role of NK cells in protection of mice against herpes simplex virus-1 infection. J. Immunol. 138, 884–888 (1987). Takeuchi, O. & Akira, S. Pattern recognition receptors and inflammation. Cell 140, 805–820 (2010). Schlee, M. et al. Recognition of 5ʹ triphosphate by RIG-I helicase requires short blunt double-stranded RNA as contained in panhandle of negative-strand virus. Immunity 31, 25–34 (2009). Schmidt, A. et al. 5ʹ-triphosphate RNA requires basepaired structures to activate antiviral signaling via RIG-I. Proc. Natl Acad. Sci. USA 106, 12067–12072 (2009). Pichlmair, A. et al. Activation of MDA5 requires higher-order RNA structures generated during virus infection. J. Virol. 83, 10761–10769 (2009). Takaoka, A. et al. DAI (DLM-1/ZBP1) is a cytosolic DNA sensor and an activator of innate immune response. Nature 448, 501–505 (2007). DAI was the first cytoplasmic DNA sensor to be identified, and was shown to contribute to the type I IFN response to HSV‑1 infection. Hornung, V. et al. AIM2 recognizes cytosolic dsDNA and forms a caspase-1-activating inflammasome with ASC. Nature 458, 514–518 (2009).

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Acknowledgements

This work was supported by grants awarded to S.R.P. from the Danish Medical Research Council (09-072,636), the Lundbeck Foundation (R34-A3855), Velux Fonden, Kathrine og Vigo Skovgaards Fond and Elvira og Rasmus Riisforts almenvelgørende Fond; by grants awarded to K.A.F. from the US National Institutes of Health (AI067497, AI64349, AI083713 and AI079293); and by grants to A.G.B. from Science Foundation Ireland. K.A.H. was supported by a Marie Curie Incoming International Fellowship.

Competing interests statement

The authors declare no competing financial interests.

FURTHER INFORMATION Søren Paludan’s homepage: www.paludanlab.dk Andrew Bowie’s homepage: www.tcd.ie/Biochemistry/research/a_bowie.php Katherine Fitzgerald’s homepage: www.umassmed.edu/igp/faculty/fitzgerald.cfm All lInkS ARe ACtIVe In tHe onlIne PDf

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