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- Immunology in the limelight
- Nat Immunol 12(12):1127 (2011)
Nature Immunology | Editorial Immunology in the limelight Journal name:Nature ImmunologyVolume: 12,Page:1127Year published:(2011)DOI:doi:10.1038/ni.2170Published online16 November 2011 With the announcement of the Nobel Prize in physiology or medicine, immunology research is once again in the limelight. Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg In talks in the 1970s, Niels Jerne and Jan Klein predicted the end of immunology research because all fundamental questions would soon be resolved and there would be nothing of interest left to investigate. Decades later, immunology research is still going strong. The fact that on 3 October 2011, the Nobel Assembly at the Karolinska Institute in Sweden awarded the Nobel Prize in physiology or medicine to another three eminent immunologists attests to this. Jules Hoffmann, of the University of Strasbourg in France, and Bruce Beutler, formerly of the Scripps Research Institute in San Diego, were awarded one half of the $1.45 million prize for their discoveries about the activation of innate immunity. In their original 1996 Cell paper (http://www.cell.com/retrieve/pii/S0092867400801725), Hoffmann and Bruno Lemaitre reported that the Drosophila Toll gene, previously associated only with a developmental role, is also important for the innate immune response to fungal and Gram-positive bacteria. Since that landmark paper, the Hoffmann group has continued to work on the molecular and cellular aspects of the innate immune response of Drosophila. More recently, the group has also started working on the mosquito Anopheles, the vector for the malaria parasite. Since the early 1890s it has been known that substances that induce a biological effect at extremely low concentrations often function by interacting with specific, high-affinity receptors. In mammals, therefore, the existence of an 'endotoxin receptor' was predicted after the chemical characterization of lipopolysaccharide, a well-known inducer of the inflammatory response and septic shock. However, it was not until Beutler's landmark 1998 paper in Science (http://www.sciencemag.org/content/282/5396/2085.long) that the lipopolysaccharide-sensing receptor was identified. This receptor, now called Toll-like receptor 4, looked similar to Hoffmann's Toll. Thus, the field of innate immunity experienced what could be called a renaissance. Because many other microbial components induce effects similar to those of lipopolysaccharide in the mammalian system, it was assumed that a family of receptors existed; this paved the way for the discovery of more than nine other Toll-like rece! ptors in the past two decades. More recently, many other pattern-recognition receptors, such as RIG-I and Mda5, have been identified. Notably, Beutler also isolated mouse tumor necrosis factor and discovered its inflammatory properties, along with inventing recombinant inhibitors for tumor necrosis factor. Those inhibitors are now used for the treatment of inflammatory diseases. Now at the University of Texas Southwestern Medical Center, Beutler has in recent years been doing pioneering work using N-ethyl-N-nitrosourea–induced mutagenesis to isolate additional molecules involved in the innate immune response. The other half of the Nobel prize in physiology or medicine was awarded to Ralph Steinman, of the Rockefeller University in New York, for his discovery in 1973 of dendritic cells, published in the Journal of Experimental Medicine (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2139237/?tool=pubmed). Tragically, Steinman never heard the news, as he died after a long battle with pancreatic cancer a few days before the Nobel Prize was announced (an obituary by Carl Nathan is on p 1129 in this issue of Nature Immunology). Fortunately, the Nobel Assembly reaffirmed the prize despite its rules against posthumous awards. Despite much resistance by many in the community to accept the existence of dentritic cells, Steinman continued to collect data over the years that would eventually silence his critics. By the 1990s it had become dogma that dendritic cells trigger the adaptive immune response and are pivotal in determining activation versus tolerance of the immune system. The effect of these three immunologists cannot be underestimated. The identification of dendritic cells and innate immune receptors has paved the way for the development of better vaccines and adjuvants, as well as for new treatments for asthma and autoimmune diseases such as rheumatoid arthritis, type I diabetes and multiple sclerosis. In addition, the work of the three Nobel laureates may lead to better immunotherapy to fight cancer. Indeed, Steinman tried three different dendritic cell therapies to treat his cancer. Although it is difficult to say if the therapies he used extended his life, he did live several years beyond his initial prognosis. With the renaissance of innate immunity, and indeed of other areas of immune research, the field of immunology seems far from over. Big questions that remain include how the immune system controls the balance between responding to exogenous antigens and tolerance to self, and, along the same lines, what triggers the immune system to attack self and cause autoimmunity. Can the immune system be harnessed to be protective against diseases such as human immunodeficiency virus or cancer? How is allergy triggered? Newer questions have also arisen, such as how the microbiome influences the immune response both locally and systemically. These are of course but a few examples of active and interesting research being conducted by immunologists. Many new techniques, such as systems biology, will surely help delineate some of these questions in the near future. Hoffmann, Beutler and Steinman now join 23 other Nobel laureates in immunology (and other closely related fields), including Eli Metchnikoff, MacFarlane Burnet and César Milstein, as elegantly described in the commentary "The Glittering Prizes" by Peter Doherty in Nature Immunology (http://www.nature.com/ni/journal/v11/n10/full/ni1010-875.html). Nature Immunology is confident that the field of immunology research is so fertile, and we look forward to many more Nobel laureates in the future. However, it must be noted that the Nobel prize, like all awards, can be given to three people at a time only across many disciplines. Many scientists past and present have contributed greatly to this field, and Nature Immunology also salutes those unsung heroes. Additional data - Ralph Steinman 1943–2011
- Nat Immunol 12(12):1129 (2011)
Article preview View full access options Nature Immunology | Obituary Ralph Steinman 1943–2011 * Carl Nathan1Journal name:Nature ImmunologyVolume: 12,Page:1129Year published:(2011)DOI:doi:10.1038/ni.2160Published online16 November 2011 On 3 October 2011, immunologists in many parts of the world heard that Ralph Steinman shared the 2011 Nobel Prize in physiology or medicine and fired off congratulatory emails. Hours later, they were shocked to learn of his death three days earlier from pancreatic cancer. Following an unprecedented second meeting on the day of its decision, the Nobel Prize Committee for Physiology or Medicine judiciously tempered the application of its rule against posthumous awards. Below are brief reflections of a scientist who is grateful to the committee for its dual display of wisdom and to Ralph Steinman for 34 years of friendship. It is only with the benefit of hindsight that immunologists now understand that Ralph Steinman put dendritic cells (DCs) on the scientific map in 1973. For years thereafter, DCs were ignored, doubted and disbelieved, as their origins were first obscure, then said to be from macrophages and their precursors and then from lymphocytes as well. Having once discounted antigen presentation, Ralph then hailed the concept and ascribed the process to DCs and then to many other cells, but none as potent as DCs. DCs could ingest but refrain from digesting. They could hug epidermal cells but then let go and swim through lymph to nodes. DCs were assigned to subsets faster than their mechanisms of T cell activation could be identified. All this engendered conflict of the sort that most scientists shun, but not Ralph. He recognized that a battle of ideas is a productive way to advance a field. Decades passed; Ralph soldiered on. Gradually, he went from embattled to embraced. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Immunology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Affiliations * Carl Nathan is in the Department of Microbiology & Immunology, Weill Cornell Medical College, and Program in Immunology and Microbial Pathogenesis, Weill Cornell Graduate School of Medical Sciences, New York, New York, USA. Corresponding author Correspondence to: * Carl Nathan Author Details * Carl Nathan Contact Carl Nathan Search for this author in: * NPG journals * PubMed * Google Scholar - Provocative exhibits at the Seventeen Gallery
- Nat Immunol 12(12):1131-1133 (2011)
Article preview View full access options Nature Immunology | News and Views Provocative exhibits at the Seventeen Gallery * Mahima Swamy1 * Adrian Hayday1 * Affiliations * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:1131–1133Year published:(2011)DOI:doi:10.1038/ni.2164Published online16 November 2011 Two studies identify a tissue-autonomous innate immune mechanism whereby infection provokes epithelial cells to produce IL-17C that engages an epithelial receptor composed of IL-17RA and IL-17RE chains, which promotes host defense and immune activation. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Immunology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Mahima Swamy and Adrian Hayday are in the Peter Gorer Department of Immunobiology, King's College, Guy's Hospital, London, UK, and London Research Institute, Cancer Research UK, London, UK. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Adrian Hayday Author Details * Mahima Swamy Search for this author in: * NPG journals * PubMed * Google Scholar * Adrian Hayday Contact Adrian Hayday Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - It takes two to tango: a new couple in the family of ubiquitin-editing complexes
- Nat Immunol 12(12):1133-1135 (2011)
Article preview View full access options Nature Immunology | News and Views It takes two to tango: a new couple in the family of ubiquitin-editing complexes * Ingrid E Wertz1Journal name:Nature ImmunologyVolume: 12,Pages:1133–1135Year published:(2011)DOI:doi:10.1038/ni.2165Published online16 November 2011 Improper termination of inflammatory signals can contribute to tumorigenesis. Cyld and Itch form an ubiquitin-editing complex that cooperatively downregulates the kinase Tak1 and thereby attenuates downstream activation of the transcription factor NF-κB. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Immunology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Ingrid E. Wertz is in the Department of Early Discovery Biochemistry, Genentech, South San Francisco, California, USA. Competing financial interests I.E.W. is an employee of Genentech Inc., a for-profit institution. Corresponding author Correspondence to: * Ingrid E Wertz Author Details * Ingrid E Wertz Contact Ingrid E Wertz Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Beta-testing NKT cell self-reactivity
- Nat Immunol 12(12):1135-1137 (2011)
Article preview View full access options Nature Immunology | News and Views Beta-testing NKT cell self-reactivity * Dale I Godfrey1 * Daniel G Pellicci1 * Jamie Rossjohn2 * Affiliations * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:1135–1137Year published:(2011)DOI:doi:10.1038/ni.2162Published online16 November 2011 Natural killer T cells (NKT cells) recognize lipid-based antigens presented by CD1d. The mammalian glycolipid β-glucosylceramide, a ubiquitous self antigen for NKT cells, is upregulated by microbial danger signals, which leads to activation of NKT cells in the absence of foreign glycolipid antigen. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Immunology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Dale I. Godfrey and Daniel G. Pellicci are in the Department of Microbiology and Immunology, University of Melbourne, Parkville, Victoria, Australia. * Jamie Rossjohn is in the Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria, Australia. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Dale I Godfrey Author Details * Dale I Godfrey Contact Dale I Godfrey Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel G Pellicci Search for this author in: * NPG journals * PubMed * Google Scholar * Jamie Rossjohn Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - A rescue gone wrong
- Nat Immunol 12(12):1137-1138 (2011)
Article preview View full access options Nature Immunology | News and Views A rescue gone wrong * Steffen Jung1Journal name:Nature ImmunologyVolume: 12,Pages:1137–1138Year published:(2011)DOI:doi:10.1038/ni.2161Published online16 November 2011 Becoming covered in platelets rescues complement-opsonized blood-borne bacteria from rapid clearance by macrophages and redirects them to dendritic cells. Although this allows priming of T cells and the generation of immune memory, bacteria can exploit this route as a beachhead and disseminate throughout host tissues. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Immunology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Steffen Jung is in the Department of Immunology, Weizmann Institute of Science, Rehovot, Israel. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Steffen Jung Author Details * Steffen Jung Contact Steffen Jung Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Turning transcription on or off with STAT5: when more is less
- Nat Immunol 12(12):1139-1140 (2011)
Article preview View full access options Nature Immunology | News and Views Turning transcription on or off with STAT5: when more is less * Michael A Farrar1 * Lynn M Heltemes Harris1 * Affiliations * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:1139–1140Year published:(2011)DOI:doi:10.1038/ni.2163Published online16 November 2011 The transcription factor STAT5 can activate or repress gene expression depending on whether binding of dimer or tetrameric STAT5 occurs. Tetrameric STAT5 recruits the chromatin modifier Ezh2 to silence gene expression. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Immunology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Michael A. Farrar and Lynn M. Heltemes Harris are in the Center for Immunology, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, USA. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Michael A Farrar Author Details * Michael A Farrar Contact Michael A Farrar Search for this author in: * NPG journals * PubMed * Google Scholar * Lynn M Heltemes Harris Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Programmed necrosis: backup to and competitor with apoptosis in the immune system
- Nat Immunol 12(12):1143-1149 (2011)
Nature Immunology | Review Programmed necrosis: backup to and competitor with apoptosis in the immune system * Jiahuai Han1 * Chuan-Qi Zhong1 * Duan-Wu Zhang1 * Affiliations * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:1143–1149Year published:(2011)DOI:doi:10.1038/ni.2159Published online16 November 2011 Abstract * Abstract * Author information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Programmed cell death is essential for the development and maintenance of the immune system and its responses to exogenous and endogenous stimuli. Studies have demonstrated that in addition to caspase-dependent apoptosis, necrosis dependent on the kinases RIP1 and RIP3 (also called necroptosis) is a major programmed cell-death pathway in development and immunity. These two programmed cell-death pathways may suppress each other, and necroptosis also serves as an alternative when caspase-dependent apoptosis is inhibited or absent. Here we summarize recent advancements that have identified the molecular mechanisms that underlie necroptosis and explore the mechanisms that regulate the interplay between apoptosis and necroptosis. View full text Figures at a glance * Figure 1: TNF-induced formation of apoptotic and necroptotic signaling complexes. After ligand binds to the receptor, the intracellular tails of TNFR1 recruit multiple proteins to form the membrane-proximal supramolecular structure complex I. Lys63-linked polyubiquitination (Lys63-Ub) of RIP1 in complex I mediated by cIAP ligases is crucial for the activation of NF-κB and mitogen-activated protein kinases (MAPKs). Deubiquitination of RIP1 by cylindromatosis (CYLD) or inhibition of cIAP proteins promote the conversion of complex I to complex II and inhibits NF-κB activation. Complex II contains RIP1, FADD, caspase-8 and TRADD. Caspase-8 becomes activated in complex II and initiates apoptosis, whereas cFLIPL can prevent activation of caspase-8. In cells with high expression of RIP3, RIP3 enters complex II via interaction with RIP1 after stimulation. The RIP3-containing complex is called complex IIb or the necrosome. In the presence of cFLIPL, caspase-8 is unable to initiate apoptosis but can cleave RIP1 and RIP3 and thus inhibits necroptosis. Depletion of! FADD or caspase-8, inhibition of caspase-8 or induction of RIP3 can free RIP1-RIP3 from inhibition and initiate necroptosis of TNF-treated cells. * Figure 2: Necroptosis is induced by various stimuli. Different necroptotic stimuli are recognized or sensed by specific receptors or sensors on the cell surface or inside cells. The initiation of the necroptotic response to different stimuli is mediated by different receptor-sensor complexes, although the nature of some of these complexes is unknown at present. The formation of the necrotic signaling complex determines cell fate. Different necrotic complexes are found after ligation of different receptors or under genotoxic stress. The necrosome, which contains TRADD, FADD, caspase-8, RIP1 and RIP3, is formed after the ligation of death receptors; the ripotosome, which has a composition slightly different from that of necrosome, is formed in response to double-stranded RNA or genotoxic stress. In each complex, the release of RIP1-RIP3 from suppression by caspase-8 is required for necroptosis. As TRIF can interact with RIP1 and RIP3 through its RHIM domain, it probably forms a necrotic complex with RIP1 and RIP3 downstream of T! LR3-TLR4 signaling. As necroptosis induced by the double-stranded DNA virus MCMV is RIP3 dependent and RIP1 independent, a viral or cellular protein (or proteins) might directly interact with RIP3 to induce necroptosis of host cells. It is clear that the necrotic complexes are heterogenous in their components, but all contain RIP3. The necroptosis induced by the various stimuli participates in a variety of biological processes, including cell death induced by death receptors, pathogens and genotoxic stress, and contributes to T cell population expansion, homeostasis, embryogenesis and the pathogenesis of many inflammation-related diseases. FAF, Fas-associated factor; Anti-, antibody; CD3, invariant signaling protein; CD28, coreceptor; Lck, Zap70 and Fyn, tyrosine kinases; PLC-γ, phospholipase C-γ; LPS, lipopolysaccharide; MD2, TLR4 coreceptor; CD14, lipopolysaccharide receptor; TIRAP, MyD88, TRIF and TRAM, adaptors; dsRNA, double-stranded RNA; IAPs, inhibitors of apoptosi! s. Author information * Abstract * Author information Affiliations * State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China. * Jiahuai Han, * Chuan-Qi Zhong & * Duan-Wu Zhang Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Jiahuai Han Author Details * Jiahuai Han Contact Jiahuai Han Search for this author in: * NPG journals * PubMed * Google Scholar * Chuan-Qi Zhong Search for this author in: * NPG journals * PubMed * Google Scholar * Duan-Wu Zhang Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - IL-17RE is the functional receptor for IL-17C and mediates mucosal immunity to infection with intestinal pathogens
- Nat Immunol 12(12):1151-1158 (2011)
Nature Immunology | Article IL-17RE is the functional receptor for IL-17C and mediates mucosal immunity to infection with intestinal pathogens * Xinyang Song1 * Shu Zhu1 * Peiqing Shi1 * Yan Liu1 * Yufang Shi1 * Steven D Levin2, 3 * Youcun Qian1 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:1151–1158Year published:(2011)DOI:doi:10.1038/ni.2155Received27 July 2011Accepted04 October 2011Published online12 October 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Interleukin 17 receptor E (IL-17RE) is an orphan receptor of the IL-17 receptor family. Here we show that IL-17RE is a receptor specific to IL-17C and has an essential role in host mucosal defense against infection. IL-17C activated downstream signaling through IL-17RE–IL-17RA complex for the induction of genes encoding antibacterial peptides as well as proinflammatory molecules. IL-17C was upregulated in colon epithelial cells during infection with Citrobacter rodentium and acted in synergy with IL-22 to induce the expression of antibacterial peptides in colon epithelial cells. Loss of IL-17C-mediated signaling in IL-17RE-deficient mice led to lower expression of genes encoding antibacterial molecules, greater bacterial burden and early mortality during infection. Together our data identify IL-17RE as a receptor of IL-17C that regulates early innate immunity to intestinal pathogens. View full text Figures at a glance * Figure 1: IL-17RE is essential for intestinal immunity to infection with C. rodentium. () Real-time quantitative PCR analysis of IL-17RE mRNA in various wild-type mouse tissues; mRNA expression is presented relative to expression of the housekeeping gene Rpl13a (encoding ribosomal protein L13a) throughout. () Survival (left) and body weight change (right) in 7- to 8-week-old Il17re−/− mice (n = 4) or wild-type mice (WT; n = 5) infected orally with 2 × 109 colony-forming units (CFU) of C. rodentium. *P < 0.05, **P < 0.01 and ***P < 0.001 (Student's t-test). () Spleen weight () and weight of cecum and colon () from Il17re−/− mice (n = 6) or wild-type mice (n = 5) at day 0 (uninfected) or day 10 after infection as in . *P < 0.01 (Student's t-test). () Bacterial titers in homogenates of spleen () or colon () from Il17re−/− mice (n = 6) or wild-type mice (n = 5) at day 10 after infection as in . *P < 0.05 and **P < 0.001 (Student's t-test). () Bacterial titers in fecal homogenates at 4–10 d (horizontal axis) after oral infection of wild-type mice (n ! = 6) or Il17re−/− mice (n = 6) with C. rodentium as in . *P < 0.05 and **P < 0.01 (Student's t-test). () Histopathology of colons obtained from Il17re−/− or wild-type mice at day 0 (uninfected (UN)) or day 10 after infection as in and stained with hematoxylin and eosin. Original magnification, ×10 (left and middle) or ×20 (right). Data are representative of two independent experiments (mean and s.e.m. in ). * Figure 2: IL-17RE is critical for the induction of genes encoding antibacterial molecules during C. rodentium infection. () Real-time quantitative PCR analysis of the expression of mRNA encoding antimicrobial peptides, proinflammatory chemokines and cytokines in the colons of Il17re−/− or wild-type mice (n = 6 per group) at day 0 (uninfected) or day 10 after oral infection with 2 × 109 CFU of C. rodentium. *P < 0.05, **P < 0.01 and ***P < 0.001 (Student's t-test). () Real-time quantitative PCR analysis of the expression of mRNA (as in ) in CECs of Il17re−/− or wild-type mice (n = 6 per group) at day 0 or day 10 after infection as in . *P < 0.05 and **P < 0.01 (Student's t-test). Data are representative of two independent experiments (mean and s.e.m.). * Figure 3: IL-17RE is required for IL-17C-induced gene expression in colons cultured ex vivo. () Real-time quantitative PCR analysis of mRNA encoding members of the IL-17 family in C57BL/6 wild-type mouse colons at day 0, 4, 8 or 12 after oral infection with 2 × 109 CFU of C. rodentium.*P < 0.05 and **P < 0.01 (Student's t-test). () Real-time PCR quantitative analysis of mRNA encoding antibacterial peptides, cytokines and chemokines in Il17re−/− or wild-type mouse colons cultured ex vivo and treated for 24 h with IL-17C (100 ng/ml). *P < 0.05, **P < 0.01 and ***P < 0.001 (Student's t-test). () Real-time quantitative PCR analysis of the S100A8 mRNA and CCL20 mRNA in Il17re−/− or wild-type mouse colons cultured ex vivo and treated for 24 h with IL-17A (50 ng/ml). Data are representative of three independent experiments (mean and s.e.m). * Figure 4: IL-17RE is essential for IL-17C-induced gene expression in vivo. () Real-time quantitative PCR analysis of the expression of mRNA encoding antibacterial peptides, cytokines and chemokines in the colons () or CECs isolated from the colons () of Il17re−/− or wild-type mice (n = 4 per group) at day 4 after intravenous injection with adenovirus encoding empty vector (Ad-EV) or mouse IL-17C (Ad–IL-17C). *P < 0.05 and **P < 0.01 (Student's t-test). Data are representative of two independent experiments (mean and s.e.m.). * Figure 5: IL-17C binds to IL-17RE and IL-17RA. () GST-precipitation analysis (GST ppt) of the interaction between GST-tagged empty vector (GST-EV) or IL-17C (GST–IL-17C) and ectopically expressed hemagglutinin-tagged (HA-) receptors of the IL-17R family (above lanes) in HEK293 cells. IB, immunoblot. () GST-precipitation analysis of the interaction between GST-tagged empty vector or IL-17C and ectopically expressed hemagglutinin-tagged IL-17RE (HA–IL-17RE) or its extracellular domain (HA–IL-17RE-dCyt) in HEK293 cells. () GST-precipitation analysis of the interaction between GST-tagged empty vector or IL-17C and ectopically expressed hemagglutinin-tagged IL-17RA (HA–IL-17RA) or its extracellular domain (HA–IL-17RA-dCyt) in HEK293 cells. () GST-precipitation analysis of the interaction between GST-tagged empty vector or IL-17A and ectopically expressed hemagglutinin-tagged IL-17RE or IL-17RA in HEK293 cells. () Coimmunoprecipitation analysis of Flag-tagged IL-17RA (M2–IL-17RA) and hemagglutinin-tagged IL-17RE (H! A–IL-17RE) in HEK293 cells. IP, immunoprecipitation; IgG, immunoglobulin G (control); M2, anti-Flag. Data are representative of three independent experiments. * Figure 6: IL-17RE is indispensable for IL-17C-induced signaling pathways. () Immunoblot analysis of lysates of primary CECs from Il17re−/− and wild-type colons, treated for 0–30 min with IL-17C (100 ng/ml; ) or IL-17A (50 ng/ml; ), probed with antibody to phosphorylated (p-) p65, IkBa, Erk, p38 and Jnk () or to phosphorylated IkBa (). GAPDH, glyceraldehyde phosphate dehydrogenase (loading control). () Real-time PCR analysis of IL-17RE and IL-17RA mRNA in HT-29 cells treated with control siRNA with scrambled sequence (NC) or siRNA designed to knock down IL-17RE (Si-IL-17RE) or IL-17RA (Si-IL-17RA). *P < 0.001 (Student's t-test). () Immunoblot analysis of HT-29 cells treated with control siRNA or siRNA specific for IL-17RE () or IL-17RA () as in and stimulated for 0–30 min with IL-17C (100 ng/ml), probed with antibodies as in . Data are representative of three independent experiments (error bars (), s.e.m.). * Figure 7: IL-17C is upregulated in CECs after they encounter bacteria. () Real-time quantitative PCR analysis of the expression of IL-17C mRNA, TNF mRNA and IL-1b mRNA in CECs isolated from C57BL/6 wild-type mice infected orally for 0, 4 or 8 d (horizontal axes) with 2 × 109 CFU of C. rodentium. *P < 0.05 and **P < 0.001 (Student's t-test). () Real-time quantitative PCR analysis of the expression of mouse IL-17C mRNA in colons cultured ex vivo for 0 or 4 h with C. rodentium. *P < 0.05 (Student's t-test). () Real-time quantitative PCR analysis of the expression of IL-17C mRNA, TNF mRNA and IL-1b mRNA in mouse primary CECs () or CSCs () incubated for 0 or 4 h with C. rodentium (multiplicity of infection, ~100). *P < 0.05, **P < 0.01 and ***P < 0.001 (Student's t-test). () Real-time quantitative PCR analysis of IL-17C mRNA expression in the human epithelial cell lines HT-29 () and SW480 () incubated as in . *P < 0.05 and **P < 0.001 (Student's t-test). () Real-time quantitative PCR analysis of IL-17C mRNA expression in mouse primary CECs treated ! for 4 h with LPS (1 mg/ml), flagellin (200 ng/ml), TNF (10 ng/ml), IL-1b (10 ng/ml), IL-17A (50 ng/ml) or IL-17F (50 ng/ml). *P < 0.05, **P < 0.01 and ***P < 0.001 (Student's t-test). Data are representative of three independent experiments (mean and s.e.m.). * Figure 8: IL-17C and IL-22 synergistically induce genes encoding antibacterial peptides. () Real-time quantitative PCR analysis of IL-22 mRNA in the colon () or cecum () of C57BL/6 wild-type mice at day 0, 4, 8 or 12 after infection with C. rodentium. *P < 0.05 (Student's t-test). () Real-time quantitative PCR analysis of IL-22 mRNA in the colons of Il17re−/− or wild-type mice at day 0, 4 or 10 after infection with C. rodentium. () Real-time quantitative PCR analysis of the expression of mRNA encoding S100A8, S100A9, RegIIIb and RegIIIg in wild-type mouse colon tissues () or mouse primary CECs () cultured ex vivo and treated for 24 h with IL-17C (100 ng/ml) or IL-22 (20 ng/ml) alone or in combination. *P < 0.05, **P < 0.01 and ***P < 0.001 (Student's t-test). () Real-time quantitative PCR analysis of the expression of mRNA (as in ) in Il17re−/− or wild-type mouse colon cultures treated for 24 h as in . NS, not significant. *P < 0.05, **P < 0.01 and ***P < 0.001 (Student's t-test). Data are representative of three independent experiments (mean and s.e.m.). Author information * Abstract * Author information * Supplementary information Affiliations * The Key Laboratory of Stem Cell Biology, Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences & Shanghai Jiao Tong University School of Medicine, Shanghai, China. * Xinyang Song, * Shu Zhu, * Peiqing Shi, * Yan Liu, * Yufang Shi & * Youcun Qian * Department of Immunology, ZymoGenetics, Seattle, Washington, USA. * Steven D Levin * Present address: Novo Nordisk Inflammation Research Center, Department of Cellular Immunology, Seattle, Washington, USA. * Steven D Levin Contributions X.S. and Y.Q. designed the experiments and wrote the manuscript; X.S. did most of the experiments; S.Z. and Y.L. helped with the mouse experiments; P.S. helped with the signaling experiments; and S.D.L. and Y.S. provided reagents and technical support. Competing financial interests S.D.L. was an employee of ZymoGenetics when these studies were done. Corresponding author Correspondence to: * Youcun Qian Author Details * Xinyang Song Search for this author in: * NPG journals * PubMed * Google Scholar * Shu Zhu Search for this author in: * NPG journals * PubMed * Google Scholar * Peiqing Shi Search for this author in: * NPG journals * PubMed * Google Scholar * Yan Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Yufang Shi Search for this author in: * NPG journals * PubMed * Google Scholar * Steven D Levin Search for this author in: * NPG journals * PubMed * Google Scholar * Youcun Qian Contact Youcun Qian Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (6.1M) Supplementary Figures 1–10 and Table 1 Additional data - IL-17C regulates the innate immune function of epithelial cells in an autocrine manner
- Nat Immunol 12(12):1159-1166 (2011)
Nature Immunology | Article IL-17C regulates the innate immune function of epithelial cells in an autocrine manner * Vladimir Ramirez-Carrozzi1 * Arivazhagan Sambandam1 * Elizabeth Luis2 * Zhongua Lin1 * Surinder Jeet1 * Justin Lesch1 * Jason Hackney3 * Janice Kim1 * Meijuan Zhou1 * Joyce Lai4 * Zora Modrusan5 * Tao Sai4 * Wyne Lee1 * Min Xu1 * Patrick Caplazi6 * Lauri Diehl6 * Jason de Voss1 * Mercedesz Balazs1 * Lino Gonzalez Jr2 * Harinder Singh1 * Wenjun Ouyang1 * Rajita Pappu1 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:1159–1166Year published:(2011)DOI:doi:10.1038/ni.2156Received01 August 2011Accepted04 October 2011Published online12 October 2011 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Interleukin 17C (IL-17C) is a member of the IL-17 family that is selectively induced in epithelia by bacterial challenge and inflammatory stimuli. Here we show that IL-17C functioned in a unique autocrine manner, binding to a receptor complex consisting of the receptors IL-17RA and IL-17RE, which was preferentially expressed on tissue epithelial cells. IL-17C stimulated epithelial inflammatory responses, including the expression of proinflammatory cytokines, chemokines and antimicrobial peptides, which were similar to those induced by IL-17A and IL-17F. However, IL-17C was produced by distinct cellular sources, such as epithelial cells, in contrast to IL-17A, which was produced mainly by leukocytes, especially those of the TH17 subset of helper T cells. Whereas IL-17C promoted inflammation in an imiquimod-induced skin-inflammation model, it exerted protective functions in dextran sodium sulfate–induced colitis. Thus, IL-17C is an essential autocrine cytokine that regulates! innate epithelial immune responses. View full text Figures at a glance * Figure 1: The biological effects of IL-17C are mediated through IL-17RA–IL-17RE heterodimeric receptor complexes. () Flow cytometry analysis of the binding of human IL-17C to 293 cells or 293 cells expressing green fluorescent protein GFP (293 GFP), human IL-17RA (293 hIL-17RA) or human IL-17RE (293 hIL-17RE), incubated for 30 min with Flag-tagged human IL-17C, followed by staining with anti-Flag (bold lines). Shaded areas, staining with anti-Flag in the absence of human IL-17C. () Displacement of 125I-labeled human IL-17C (hIL-17C) bound to 293 cells expressing human IL-17RA or IL-17RE by increasing doses of unlabeled human IL-17C. () Quantitative PCR analysis of IL-17RE mRNA in mouse tissues () and human cells (); mRNA results are presented relative to expression of the housekeeping gene RPL19 (encoding the ribosomal protein L19) throughout. BM, bone marrow; mLN, mesenteric lymph node; SI, small intestine. () ELISA of the secretion of human β-defensin-2 (hBD2) and human G-CSF (hG-CSF) from human epidermal keratinocytes stimulated for 48 h with human IL-17C. () ELISA of the secretion ! of human β-defensin-2 and G-CSF in cells stimulated as in in the presence of increasing doses of blocking antibody to human IL-17RA (horizontal axes). () ELISA of the production of G-CSF by human dermal fibroblasts (HDFn) transduced with control retrovirus (Control) or transduced with retrovirus to express human IL-17RE and then stimulated for 48 h with human IL-17C. () Secretion of G-CSF by keratinocytes derived from neonatal Il17re+/+ or Il17re−/− mice and stimulated with mouse IL-17C (mIL-17C) or mouse IL-17A (mIL-17A). Data are representative of three independent experiments (error bars, s.d. (–) or mean ± s.e.m. ()). * Figure 2: IL-17C induces host-defense pathways in epithelial cells. () Microarray analysis of RNA from human epidermal keratinocytes stimulated for 3 or 24 h with human IL-17C or given mock stimulation without cytokine (Control), presented as the ratio of log2-transformed normalized expression to Universal Human Reference RNA (key, left margin). () Quantitative RT-PCR analysis of mRNA encoding various chemokines, IL-1 family cytokines and antimicrobial peptides (horizontal axes) in human epidermal keratinocytes treated for 3 or 24 h with human IL-17C () or human IL-17A (), presented relative to mock-treated control samples. *P < 0.05 (Dunnett's test). () ELISA of the secretion of human β-defensin-2 from human epidermal keratinocytes stimulated for 48 h with medium alone (Med) or with human IL-17C or IL-1β (left) or IL-17C or TNF (right) alone or in combination. Data are representative of two () or three (–) experiments (error bars, s.e.m. of quintuplicates () or s.d. ()). * Figure 3: IL-17C is expressed by mucosal epithelial cells in response to inflammation. () ELISA of the secretion of human IL-17C from human epithelial cells (HCT-15 colon epithelial cells, primary tracheal epithelial cells or epidermal keratinocytes) stimulated for 24 h with heat-killed E. coli. () Quantitative RT-PCR analysis of the kinetics of the production of IL-17C mRNA by HCT-15 cells stimulated with heat-killed E. coli. () ELISA of the secretion of human IL-17C from HCT-15 cells stimulated for 24 h with TLR agonists () or cytokines (). HK, heat-killed; PGN, peptidoglycan; PIC, poly(I:C); FLA, flagellin; CPG, CpG dinucleotide. Data are representative of three independent experiments (error bars (), s.d.). * Figure 4: Many factors independently regulate IL-17C expression. () Quantitative RT-PCR analysis of IL-17C mRNA in epidermal keratinocytes derived from neonatal Myd88+/+ (wild-type (WT)) or Myd88−/− mice and stimulated for 2 h with agonists of TLR2 (peptidoglycan) or TLR5 (flagellin) or the cytokines IL-1β or TNF. () ELISA of the secretion of human IL-17C from HCT-15 cells stimulated for 24 h with heat-killed E. coli, TNF, IL-1β, peptidoglycan or flagellin (horizontal axes) in the presence of isotype-matched control antibody (Isotype), a soluble form of the TNF receptor (as described in Results (TNFRII-Fc); ), anti-IL-1β (), anti-TLR2 () or anti-TLR5 (). *P < 0.05, versus isotype-matched control antibody (Dunnett's test). Data are representative of two experiments (error bars, s.d.). * Figure 5: Leukocytes are not a predominant source of IL-17C in vivo. () Quantitative RT-PCR analysis of IL-17C mRNA in colon tissue from C57BL/6 mice injected intraperitoneally for 2 h with PBS or flagellin. () Quantitative RT-PCR analysis of IL-17C mRNA or IL-22 mRNA in colon tissues from wild-type mice (WT) or mice deficient in both recombination-activating gene 2 and the common γ-chain (Rag2−/−Il2rg−/−; ) or from chimeras generated by the transfer of Il17c−/− bone marrow cells into wild-type mice (Il17c−/− BMIl17c+/+) or wild-type bone marrow cells into Il17c−/− mice (Il17c+/+ BMIl17c−/−; ), treated as in . ND, not detectable. *P < 0.05, versus wild-type (Dunnett's test). Data are representative of two independent experiments (mean and s.e.m. of five mice per genotype). * Figure 6: IL-17C is expressed during DSS-induced colitis. () Quantitative RT-PCR analysis of IL-17C mRNA in colons or mesenteric lymph nodes collected from C57BL/6 mice given 2% DSS on days 0–5 (followed by no DSS), assessed on days 0–14 (horizontal axis). () ELISA of the production of mouse IL-17C by colons from C57BL/6 mice collected on day 8 after initial treatment with 2% DSS and cultured overnight. Each symbol represents an individual mouse; small horizontal lines indicate the mean. *P < 0.05, versus no DSS (Dunnett's test). () Quantitative RT-PCR analysis of IL-17A, IL-17F and IL-22 mRNA as in . Data are representative of three experiments (mean ± s.e.m. of five mice). * Figure 7: Role of the IL-17RE pathway in the recovery of epithelial cells in the DSS-induced colitis model. () Body weight of 8- to 10-week-old Il17re+/+ or Il17re−/− mice on days 4–15 after initial treatment with 2% DSS, relative to initial body weight. () Area under the curve (AUC) for the body weight measurements in , calculated for days 7–12. () Histology scores of colons collected on day 15 from mice treated as in . () Staining of colon sections in with hematoxylin and eosin (H&E), anti-F4/80, Alcian blue (AB) or anti-Ly6G/C. Arrowheads indicate F4/80+ macrophages (brown staining), Alcian blue–positive goblet cells and mucin, or Ly6G/C+ neutrophil infiltrates (brown staining). Scale bars, 100 mm. Each symbol represents an individual mouse; small horizontal lines indicate the mean (). *P < 0.05, versus Il17re+/+ mice (Dunnett's test). Data are representative of two independent experiments with four (no DSS) or eight (DSS) mice per group (mean ± s.e.m. in ). * Figure 8: Proinflammatory role of the IL-17C pathway in a mouse model of psoriasis. () Quantitative RT-PCR analysis of IL-17C mRNA in back skin from BALB/c mice treated for 5 d with 5% topical imiquimod. () Ear thickness of Il17c+/+ or Il17c−/− mice treated as in . () Area under the curve for the ear thickness measurements in , calculated for days 0–5. () Histology of pinnae from Il17c+/+ or Il17c−/− mice left untreated (left) or treated for 5 d with imiquimod (middle and right), stained with hematoxylin and eosin or for Ki67 or Ly6G/C. Double-headed arrows indicate dermal and epidermal hyperplasia; P, epidermal pustules. Scale bars, 50 mm. () Histology scores of pinnae from mice treated as in . () Proliferative activity of keratinocytes from mice treated as in , assessed by Ki67 staining. Each symbol represents an individual mouse; small horizontal lines indicate the mean (). *P < 0.05, versus Il17c+/+ mice (Dunnett's test). Data are representative of two independent experiments (mean ± s.e.m. of five mice in triplicate () or mean ± s.e.m. ()). Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE32620 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Department of Immunology, Genentech, South San Francisco, California, USA. * Vladimir Ramirez-Carrozzi, * Arivazhagan Sambandam, * Zhongua Lin, * Surinder Jeet, * Justin Lesch, * Janice Kim, * Meijuan Zhou, * Wyne Lee, * Min Xu, * Jason de Voss, * Mercedesz Balazs, * Harinder Singh, * Wenjun Ouyang & * Rajita Pappu * Department of Protein Chemistry, Genentech, South San Francisco, California, USA. * Elizabeth Luis & * Lino Gonzalez Jr * Department of Bioinformatics and Computational Biology, Genentech, South San Francisco, California, USA. * Jason Hackney * Department of Antibody Engineering, Genentech, South San Francisco, California, USA. * Joyce Lai & * Tao Sai * Department of Molecular Biology, Genentech, South San Francisco, California, USA. * Zora Modrusan * Department of Pathology, Genentech, South San Francisco, California, USA. * Patrick Caplazi & * Lauri Diehl Contributions V.R.-C. did most of the experiments and analyzed the data; A.S. contributed to identifying the receptors and sources of IL-17C; E.L. and L.G. did the radioligand-binding experiments; Z.L. and M.B. contributed to the imiquimod-induced skin inflammation studies; S.J., J.Lesch, L.D. and J.d.V. did the DSS studies; J.H. analyzed the microarray data; J.K. and M.X. contributed to the adenoviral studies; M.Z. and W.L. did the intradermal IL-17C injections; J.Lai and T.S. generated the mouse antibody to mouse IL-17C; Z.M. contributed to the microarray studies; P.C. contributed to the histological evaluation of the adenoviral, intradermal injection and imiquimod studies; H.S. and W.O. provided scientific input for the project; and R.P. devised and planned the project and wrote the manuscript Competing financial interests All authors are employees of Genentech. Corresponding author Correspondence to: * Rajita Pappu Author Details * Vladimir Ramirez-Carrozzi Search for this author in: * NPG journals * PubMed * Google Scholar * Arivazhagan Sambandam Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth Luis Search for this author in: * NPG journals * PubMed * Google Scholar * Zhongua Lin Search for this author in: * NPG journals * PubMed * Google Scholar * Surinder Jeet Search for this author in: * NPG journals * PubMed * Google Scholar * Justin Lesch Search for this author in: * NPG journals * PubMed * Google Scholar * Jason Hackney Search for this author in: * NPG journals * PubMed * Google Scholar * Janice Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Meijuan Zhou Search for this author in: * NPG journals * PubMed * Google Scholar * Joyce Lai Search for this author in: * NPG journals * PubMed * Google Scholar * Zora Modrusan Search for this author in: * NPG journals * PubMed * Google Scholar * Tao Sai Search for this author in: * NPG journals * PubMed * Google Scholar * Wyne Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Min Xu Search for this author in: * NPG journals * PubMed * Google Scholar * Patrick Caplazi Search for this author in: * NPG journals * PubMed * Google Scholar * Lauri Diehl Search for this author in: * NPG journals * PubMed * Google Scholar * Jason de Voss Search for this author in: * NPG journals * PubMed * Google Scholar * Mercedesz Balazs Search for this author in: * NPG journals * PubMed * Google Scholar * Lino Gonzalez Jr Search for this author in: * NPG journals * PubMed * Google Scholar * Harinder Singh Search for this author in: * NPG journals * PubMed * Google Scholar * Wenjun Ouyang Search for this author in: * NPG journals * PubMed * Google Scholar * Rajita Pappu Contact Rajita Pappu Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (8.3M) Supplementary Figures 1–14, Table 1 and Methods Additional data - The IκB kinase complex regulates the stability of cytokine-encoding mRNA induced by TLR–IL-1R by controlling degradation of regnase-1
- Nat Immunol 12(12):1167-1175 (2011)
Nature Immunology | Article The IκB kinase complex regulates the stability of cytokine-encoding mRNA induced by TLR–IL-1R by controlling degradation of regnase-1 * Hidenori Iwasaki1, 2 * Osamu Takeuchi1, 3 * Shunsuke Teraguchi1, 4 * Kazufumi Matsushita1, 6 * Takuya Uehata1, 5 * Kanako Kuniyoshi1, 3 * Takashi Satoh1 * Tatsuya Saitoh1, 3 * Mutsuyoshi Matsushita2 * Daron M Standley4 * Shizuo Akira1, 3 * Affiliations * Contributions * Corresponding authorsJournal name:Nature ImmunologyVolume: 12,Pages:1167–1175Year published:(2011)DOI:doi:10.1038/ni.2137Received20 May 2011Accepted15 September 2011Published online30 October 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Toll-like receptor (TLR) signaling activates the inhibitor of transcription factor NF-κB (IκB) kinase (IKK) complex, which governs NF-κB-mediated transcription during inflammation. The RNase regnase-1 serves a critical role in preventing autoimmunity by controlling the stability of mRNAs that encode cytokines. Here we show that the IKK complex controlled the stability of mRNA for interleukin 6 (IL-6) by phosphorylating regnase-1 in response to stimulation via the IL-1 receptor (IL-1R) or TLR. Phosphorylated regnase-1 underwent ubiquitination and degradation. Regnase-1 was reexpressed in IL-1R- or TLR-activated cells after a period of lower expression. Regnase-1 mRNA was negatively regulated by regnase-1 itself via a stem-loop region present in the regnase-1 3′ untranslated region. Our data demonstrate that the IKK complex phosphorylates not only IκBα, thereby activating transcription, but also regnase-1, thereby releasing a 'brake' on IL-6 mRNA expression. View full text Figures at a glance * Figure 1: Phosphorylation and degradation of regnase-1 in response to stimulation of TLRs or IL-1R. (,) Immunoblot analysis of regnase-1 (Reg1) in lysates of wild-type (WT) and regnase-1-deficient (Reg1-KO) peritoneal macrophages (MΦ; ) and MEFs () stimulated for 0–4 h (above lanes) with LPS. NS, nonspecific band. () Quantitative PCR analysis of the expression of IL-6 mRNA among total RNA from unstimulated wild-type and regnase-1-deficient macrophages .*P < 0.05 (Student's t-test). () Immunoblot analysis of regnase-1, IκBα and β-actin (loading control) in wild-type, MyD88-deficient (MyD88-KO) and TRIF-deficient (TRIF-KO) macrophages stimulated for 0–240 min (above lanes) with LPS. () Immunoblot analysis of regnase-1, IκBα and β-actin in lysates of wild-type peritoneal macrophages stimulated for 0–240 min (above lanes) with MALP-2 (10 ng/ml), poly(I:C) (100 μg/ml), LPS (100 ng/ml), R-848 (10 nM) or CpG DNA (1 μM). (,) Immunoblot analysis of regnase-1, IκBα, phosphorylated (p-) IKK and β-actin in HeLa cells stimulated for 0–240 min (above lanes) with IL-1! β (10 ng/ml; ) or TNF (10 ng/ml; ). () Immunoblot analysis of regnase-1 in HeLa cell lysates left unstimulated (−) or stimulated (+) with IL-1β and left untreated (−) or treated (+) with λ-phosphatase. () Immunoblot analysis of regnase-1 in HeLa cells pretreated with 0.1% dimethyl sulfoxide (DMSO) or the proteasome inhibitor MG-132 (1 μM), then stimulated for 0–240 min (above lanes) with IL-1β. () Immunoassay of lysates of HeLa cells stimulated for 0–30 min (above lanes) with IL-1β or TNF, followed by immunoprecipitation (IP) with anti-regnase-1 and immunoblot analysis (IB) with antibody to ubiquitin (Ub) or Reg1. Data are representative of three to five independent experiments (error bars (), s.d.). * Figure 2: The IKK complex is essential for regnase-1 phosphorylation. (,) Immunoblot analysis of regnase-1, IκBα and β-actin in MEFs from wild-type mice or mice deficient in IKKα (IKKα-KO), IKKβ (IKKβ-KO) or both IKKα and IKKβ (IKKα-KO,IKKβ-KO; ) and of Rat-1 (NEMO-sufficient) cells and 5R (NEMO-deficient) cells (), stimulated for 0–240 min (above lanes) with LPS. () Alignment of DSGXXS motifs (red) in mouse and human regnase-1 and mouse IκBα, IκBβ and β-catenin. () Regnase-1 domains, including the RNase domain (green), the zinc-finger domain (CCCH ZF; orange) and the DSGXXS domain (red; 596 (far right) indicates total amino acids present). (,) In vitro kinase assay (top) of recombinant IKKβ and wild-type or mutant regnase-1 () or GST fusion proteins of wild-type or mutant regnase-1 (), and SDS-PAGE and Coomassie blue staining (bottom) of wild-type and mutant regnase-1 (all corresponding to regnase-1 amino acids 430–441). kDa, kilodaltons. () Immunoassay of the association of regnase-1 and β-TrCP in HEK293 cells transfect! ed with various combinations (above lanes) of expression plasmids for Flag-tagged β-TrCP (Flag–β-TrCP), wild-type IKKβ (Flag-IKKβ) or kinase-inactive IKKβ (Flag-IKKβ(DN)), and Myc-tagged wild-type regnase-1 (Myc-Reg1) or S435A,S439A mutant regnase-1 (Myc-Reg1(AA)), followed by immunoprecipitation of proteins from lysates with anti-Myc and immunoblot analysis with anti-Flag or anti-Myc. *, immunoglobulin heavy chain. Below, immunoblot analysis of whole-cell lysates (WCL) with anti-Myc or anti-Flag. () Immunoblot analysis of regnase-1, dominant negative β-TrCP(ΔF) and β-actin in HeLa cells expressing Flag-tagged β-TrCP(ΔF) or control plasmid and stimulated for 0–120 min (above lanes) with IL-1β. Data are representative of three to four independent experiments. * Figure 3: Effect of the phosphorylation of regnase-1 by IKKs on IL-6 mRNA expression. () Immunoblot analysis of lysates of HeLa cells expressing empty vector (EV) or expression vector for Flag-tagged wild-type regnase-1 or S435A,S439A mutant regnase-1, stimulated for 0–240 min (above lanes) with IL-1β, probed with anti-Flag or anti-β-actin. Below lanes, densitometry (presented as the ratio of regnase-1 to β-actin). ND, not defined. () Quantitative PCR analysis of the expression of IL-6 mRNA among total RNA from the cells in , presented relative to 18S RNA. () Immunoblot analysis of lysates of regnase-1-deficient MEFs infected with control retrovirus (EV) or retrovirus expressing Flag-tagged wild-type regnase-1 or the S435A,S439A regnase-1 mutant, then stimulated for 0–120 min (above lanes) with IL-1β, probed with anti-Flag or β-actin. Below lanes, densitometry (as in ). () Quantitative PCR analysis as in of total RNA from the cells in . () Semiquantitative RT-PCR analysis of wild-type regnase-1 and S435A,S439A mutant regnase-1 in macrophages prepared! from regnase-1-deficient bone marrow cells infected with retrovirus as in . () Quantitative PCR analysis (as in ) of the cells in , stimulated for 0–240 min (horizontal axis) with LPS. *P < 0.05, empty vector versus regnase-1 (wild type or S435A,S439A), and P < 0.05, wild-type regnase-1 versus S435A,S439A regnase-1 (Student's t-test). Data are representative of three to four independent experiments with similar results (mean ± s.d. of triplicates in ,,). * Figure 4: Differences in the control of IL-6 mRNA stability by IL-1β and TNF. () Quantitative PCR analysis of IL-6 mRNA among total RNA from control Rat-1 cells and NEMO-deficient 5R cells stimulated for 20 min with LPS, followed by treatment for 0–60 min (horizontal axes) with actinomycin D (ActD). () Quantitative PCR analysis of mRNA for IκBα, ICAM1 or IL-6 in HeLa cells stimulated for 0–6 h (horizontal axes) with IL-1β or TNF, presented relative to 18S RNA. () Quantitative PCR analysis of IL-6 mRNA among total RNA from HeLa cells stimulated for 20 or 240 min (above plots) with medium alone (Med), IL-1β or TNF, then treated for 0–120 min (horizontal axes) with actinomycin D. *P < 0.05 (Student's t-test). Data are from three independent experiments (mean ± s.d.). * Figure 5: Interaction of regnase-1 with IRAK1. () Immunoassay of HEK293 cells transfected to express Myc-tagged regnase-1 and/or Flag-tagged IRAK1 (above lanes), followed by immunoprecipitation with anti-Myc and immunoblot analysis with anti-Flag or anti-Myc. Below, immunoblot analysis of whole-cell lysates with anti-Flag or anti-Myc. () Immunoblot analysis of lysates of the cells in overexpressing Reg1 and IRAK1 (Reg1 (+) IRAK1 (+)), assessed after treatment with λ-phosphatase, probed with anti-Myc. () In vitro kinase assay of recombinant regnase-1 and IRAK1 (top), and SDS-PAGE and Coomassie blue staining of regnase-1 (bottom). () Immunoassay of HEK293 cells transfected to express Myc-tagged regnase-1 and/or Flag-tagged IRAK1 or IKKβ (above lanes), followed by immunoprecipitation from lysates with anti-Myc and immunoblot analysis with anti-IKKβ, anti-IRAK1 or anti-Myc. Below, immunoblot analysis of whole-cell lysates with anti-Flag or anti-Myc. () Immunoassay of HEK293 cells transfected to express hemagglutinin-tagge! d ubiquitin (HA-Ub), Myc-tagged regnase-1 and/or IKKβ or IRAK1 (above lanes), followed by immunoprecipitation from lysates with anti-Myc and immunoblot analysis of ubiquitin (with anti-HA). Below, immunoblot analysis of whole-cell lysates with anti-IKKβ, anti-IRAK1 or anti-Myc. Data are representative of three to four independent experiments. * Figure 6: The expression of regnase-1 mRNA is controlled by regnase-1 itself. () Quantitative PCR analysis of the expression of regnase-1 mRNA in HeLa cells stimulated for 0–6 h (horizontal axis) with IL-1β or TNF, presented relative to 18S RNA. *P < 0.05 (Student's t-test). () RNA-hybridization analysis of the abundance of mRNA encoding β-globin or β-actin in HEK293 Tet-off cells transfected with plasmid containing sequence encoding a tetracycline-response element and β-globin-coding sequence plus the 3′ UTR of β-globin (β-globin CDS + 3′ UTR) or regnase-1 (β-globin CDS + Reg1 3′ UTR), together with control empty plasmid (Mock) or expression plasmid for regnase-1 (Mouse Reg1), then divided 3 h after transfection and incubated for an additional 20 h, followed by treatment (time, above lanes) with doxycycline (1 μg/ml). () Quantification of the autoradiographs in , presented as the ratio of β-globin to β-actin. () The 3′ UTR of mouse regnase-1 mRNA (positions 1–865) and deletion constructs. () Luciferase activity of HEK293 cells t! ransfected for 48 h with luciferase reporter plasmids as in (top), together with control plasmid (Mock) or expression plasmid for wild-type regnase-1 or a nuclease-inactive mutant of regnase-1 (D141N); results are presented relative to renilla luciferase activity. () Predicted stem-loop structure of the regnase-1-responsive element in the 3′ UTR of IL-6 mRNA (left) or regnase-1 mRNA (right), pus mutations leading to disruption of the regnase-1 stem-loop structure (Stem mutant 1 and 2). () Luciferase activity of HEK293 cells transfected for 48 h with luciferase reporter plasmids containing sequence as in (stem mutants alone (1 or 2) or together (1+2)), together with expression plasmids as in (presented as in ). Data are representative of three independent experiments (–) or three independent experiments with similar results (,; error bars, s.d. of duplicates). * Figure 7: Computational modeling of the control of IL-6 mRNA expression by regnase-1. Expression of regnase-1 protein, IL-6 mRNA and regnase-1 mRNA in HeLa cells stimulated for 0–120 min (horizontal axes) with IL-1β (Exp (IL-1β)) or TNF (Exp (TNF)), followed by normalization to initial values (obtained from Figs. 4b and 6a). Model fit (IL-1β), model values fit to the data after stimulation with IL-1β (fitted by COPASI 4.6 software for the simulation and analysis of biochemical networks and their dynamics35); Model prediction (TNF), corresponding model predictions for stimulation with TNF. Author information * Abstract * Author information * Supplementary information Affiliations * Laboratory of Host Defense, World Premier International Immunology Frontier Research Center, Osaka University, Osaka, Japan. * Hidenori Iwasaki, * Osamu Takeuchi, * Shunsuke Teraguchi, * Kazufumi Matsushita, * Takuya Uehata, * Kanako Kuniyoshi, * Takashi Satoh, * Tatsuya Saitoh & * Shizuo Akira * Central Pharmaceutical Research Institute, Japan Tobacco, Osaka, Japan. * Hidenori Iwasaki & * Mutsuyoshi Matsushita * Research Institute for Microbial Diseases, Osaka University, Osaka, Japan. * Osamu Takeuchi, * Kanako Kuniyoshi, * Tatsuya Saitoh & * Shizuo Akira * Laboratory of Systems Immunology, World Premier International Immunology Frontier Research Center, Osaka University, Osaka, Japan. * Shunsuke Teraguchi & * Daron M Standley * Department of Geriatric Medicine and Nephrology, Osaka University Graduate School of Medicine, Osaka, Japan. * Takuya Uehata * Present address: Laboratory of Allergic Diseases, Institute for Advanced Medical Sciences, Hyogo College of Medicine, Hyogo, Japan. * Kazufumi Matsushita Contributions H.I. and O.T. designed and did most of the experiments and analyzed the data; K.M., T.U., K.K., T. Satoh and T. Saitoh helped with experiments; S.T. and D.M.S. did mathematical modeling; M.M. provided advice for experiments; H.I., S.T. and O.T. wrote the manuscript; and S.A. supervised the project. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Osamu Takeuchi or * Shizuo Akira Author Details * Hidenori Iwasaki Search for this author in: * NPG journals * PubMed * Google Scholar * Osamu Takeuchi Contact Osamu Takeuchi Search for this author in: * NPG journals * PubMed * Google Scholar * Shunsuke Teraguchi Search for this author in: * NPG journals * PubMed * Google Scholar * Kazufumi Matsushita Search for this author in: * NPG journals * PubMed * Google Scholar * Takuya Uehata Search for this author in: * NPG journals * PubMed * Google Scholar * Kanako Kuniyoshi Search for this author in: * NPG journals * PubMed * Google Scholar * Takashi Satoh Search for this author in: * NPG journals * PubMed * Google Scholar * Tatsuya Saitoh Search for this author in: * NPG journals * PubMed * Google Scholar * Mutsuyoshi Matsushita Search for this author in: * NPG journals * PubMed * Google Scholar * Daron M Standley Search for this author in: * NPG journals * PubMed * Google Scholar * Shizuo Akira Contact Shizuo Akira Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–15 and Tables 1–2 Additional data - The E3 ligase Itch and deubiquitinase Cyld act together to regulate Tak1 and inflammation
- Nat Immunol 12(12):1176-1183 (2011)
Nature Immunology | Article The E3 ligase Itch and deubiquitinase Cyld act together to regulate Tak1 and inflammation * Neesar Ahmed1 * Minghui Zeng1 * Indrajit Sinha1 * Lisa Polin1 * Wei-Zen Wei1 * Chozhavendan Rathinam2 * Richard Flavell3 * Ramin Massoumi4 * K Venuprasad1 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:1176–1183Year published:(2011)DOI:doi:10.1038/ni.2157Received13 April 2011Accepted05 October 2011Published online06 November 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Chronic inflammation has been strongly associated with tumor progression, but the underlying mechanisms remain elusive. Here we demonstrate that E3 ligase Itch and deubiquitinase Cyld formed a complex via interaction through 'WW-PPXY' motifs. The Itch-Cyld complex sequentially cleaved Lys63-linked ubiquitin chains and catalyzed Lys48-linked ubiquitination on the kinase Tak1 to terminate inflammatory signaling via tumor necrosis factor. Reconstitution of wild-type Cyld but not the mutant Cyld(Y485A), which cannot associate with Itch, blocked sustained Tak1 activation and proinflammatory cytokine production by Cyld−/− bone marrow–derived macrophages. Deficiency in Itch or Cyld led to chronic production of tumor-promoting cytokines by tumor-associated macrophages and aggressive growth of lung carcinoma. Thus, we have identified an Itch-Cyld–mediated regulatory mechanism in innate inflammatory cells. View full text Figures at a glance * Figure 1: Itch−/− and Cyld−/− mice develop more growth and metastasis of LLC. () Survival of wild-type (WT; n = 12), Cyld−/− (n = 13) and Itch−/− mice (n = 11) inoculated with 1 × 106 LLC cells via the tail vein. () Hematoxylin-and-eosin-stained histological sections of lungs from wild-type, Cyld−/− and Itch−/− mice on day 15 after inoculation of LLC cells (1 × 106 cells). Original magnification, ×100. (,) Lung tumor multiplicity () and tumor size () of the mice in . () Cytokine-encoding mRNA in CD11b+ macrophages from lung tumors of wild-type, Cyld−/− and Itch−/− mice inoculated with LLC cells (1 × 106) via tail vein. () Cytokine abundance in naive Itch−/− and Cyld−/− lung tissues. *P < 0.01 (paired t-test). Data represent three independent experiments (error bars, s.d.). * Figure 2: Itch and Cyld form a complex via interaction through PPXY motif. () Sequence alignment of PPXY motif of Cyld in various species. *, Tyr485 reside critical for the interaction with Itch. () Immunoassay of 293T cells transiently cotransfected with expression vectors for Flag-Itch and Myc-Cyld, followed by immunoprecipitation (IP) with anti-Flag (α-Flag), mouse IgG or anti-Myc (α-Myc) and immunoblot analysis (IB) with anti-Flag or anti-Myc. Lysate (below), immunoblot analysis of total lysates without immunoprecipitation (throughout). () Immunoblot analysis of His-Cyld precipitated with GST or GST-Itch purified from E. coli. Below, input controls for His-Cyld, GST and GST-Itch. () Immunoassay of BMDMs stimulated with TNF for 30 min, followed by immunoprecipitation of lysates with anti-Itch, mouse IgG, anti-Cyld or rabbit IgG and immunoblot analysis with anti-Itch or anti-Cyld. () Immunoassay of 293T cells cotransfected with expression vectors for HX-Cyld(Y485A) and Flag-Itch, followed by immunoprecipitation of lysates with anti-Flag and imm! unoblot analysis with anti-HX. Data represent three (,,) or two () experiments. * Figure 3: Itch and Cyld sequentially cleave K63-linked ubiquitination and catalyzes K48-linked ubiquitination to deactivate Tak1. () Immunoassay of 293T cells transfected with expression vectors for various combinations (above lanes) of Flag-Tak1, Myc-Itch, HX-Itch(C830A) and hemagglutinin-tagged wild-type ubiquitin (HA-Ub(WT)), Ub(K48) and Ub(K63), followed by immunoprecipitation of lysates with anti-Flag and immunoblot analysis with anti-HA. () Immunoassay of 293T cells transfected to express various combinations of Flag-Tak1, Myc-Itch and hemagglutinin-tagged wild-type ubiquitin, Ub(K48) and Ub(K48R), assessed as in . () Immunoassay of 293T cells transfected to express various combinations of Flag-Tak1, Myc-TRAF2, HX-TRAF2Δ (RING-deletion TRAF2 mutant that lacks ligase activity), HA-Ub(K63), HX-Cyld, HX-Cyld(C601A), HX-Cyld(Y485A), Myc-Itch and HA-Ub(K48), assessed as in . () Immunoassay of 293T cells as in but with HA-Ub(K48R) instead of HA-Ub(K63) and HA-Ub(K63R) instead of HA-Ub(K48). () Immunoassay of 293T cells transfected to express various combinations of HX-Tak1, HX-TRAF2, Flag-Ub(K63), Myc! -Itch, HA-Ub(K48) and HX-Cyld, followed by immunoprecipitation of lysates with anti-Tak1 and immunoblot analysis with anti-Flag (to detect K63-linked ubiquitination) and reprobing with anti-HA (to detect K48-linked ubiquitination). Data represent three or more independent experiments. * Figure 4: Itch-mediated polyubiquitination leads to Tak1 degradation. () Immunoblot analysis of 293T cells transfected with expression vector for HA-Tak1 (1 μg) and increasing concentrations (wedges) of expression vector for Flag-Itch or HX-Itch(C830A), probed with anti-HA (to measure cellular Tak1) and reprobed with anti-Flag and anti-HX (to assess Itch and Itch(C830A)). Actin serves as a loading control throughout. () Immunoblot analysis of 293T cells transfected with expression vector for HA-Tak1 (1 μg) and increasing concentrations of the expression vector for Flag-Itch and cultured with or without MG132, probed with anti-HA (to measure cellular Tak1). Data represent two experiments. * Figure 5: Sustained Tak1 activation leads to chronic production of inflammatory cytokines by Itch−/− and Cyld−/− BMDMs. () Immunoassay of Itch−/− and Cyld−/− BMDMs stimulated for 0–60 min (above lanes) with TNF, followed by immunoprecipitation of lysates with anti-TRAF2 and immunoblot analysis with antibody to phosphorylated (p-) Tak1, then reprobing with anti-Tak1 and anti-TRAF2. Below, immunoblot analysis of total cell lysates with anti-Tak1, anti-TRAF2, anti-Cyld, anti-Itch and anti-actin. () Real-time PCR analysis of IL-6, TNF and IL-1β among total RNA from BMDMs stimulated for 0–12 h with TNF. () ELISA of IL-6 and IL-1β in culture supernatants of BMDMs stimulated with TNF. Data represent two experiments () or three experiments (,; mean ± s.d. of triplicate wells). * Figure 6: Inhibiting Tak1 activation diminishes the enhanced inflammatory cytokine production of Itch−/− and Cyld−/− BMDMs. () Real-time PCR analysis of IL-6, TNF and IL-1β in BMDMs preincubated with various concentrations (horizontal axis) of (5Z)-7-oxozeaenol (Ox) and stimulated for 6 h with TNF. () Immunoassay of BMDMs pretreated for 30 min with 100 nM Ox and then stimulated for 0–30 min (above lanes) with TNF, followed by immunoprecipitation of lysates with anti-TRAF2 and immunoblot analysis with antibody to phosphorylated Tak1. Below, immunoblot analysis of total lysates with anti-TRAF2 and anti-actin. () Immunoblot analysis of the efficiency of ectopic expression by wild-type, Cyld−/− and Itch−/− BMDMs left untransduced (−) or transduced (+) with lentivirus vector encoding V5-tagged dominant negative (V5-dnTak1), probed with anti-V5. () Real-time PCR analysis of IL-6, TNF and IL-1β in wild-type, Cyld−/− and Itch−/− BMDMs left untransduced or transduced with lentiviral vector encoding dominant negative Tak1 and stimulated with TNF. Data represent three experiments (mean! ± s.d. of triplicate wells in ,). * Figure 7: Ligase activity of Itch, deubiquitinating activity of Cyld and Cyld-Itch interaction are necessary for termination of TNF-induced Tak1 activation. () Immunoassay of wild-type MEFs expressing endogenous Itch (control) and Itch−/− MEFs reconstituted with V5-tagged wild-type Itch (Itch(WT)) or Itch(C830A) via a lentiviral transduction system and stimulated for 0, 5 or 30 min (above lanes) with TNF, followed by immunoprecipitation of lysates with anti-TRAF2, then immunoblot analysis with antibody to phosphorylated Tak1 and reprobing with anti-Tak1. () ELISA of IL-6 in supernatants of wild-type and Itch−/− MEFs transducedas in and stimulated with TNF. () Immunoassay of wild-type MEFs expressing endogenous Cyld (control) and Cyld−/− MEFs reconstituted with V5-tagged wild-type Cyld (Cyld(WT)), Cyld(Y485A) or Cyld(C601A) and stimulated for 0, 5 or 30 min (above lanes) with TNF, followed by immunoprecipitation and immunoblot analysis as in . () ELISA of IL-6 in supernatants of wild-type and Cyld−/− MEFs transduced as in and stimulated with TNF. Data represent two (,) or three (,) experiments (mean ± s.d. of tri! plicate wells in ,). * Figure 8: Reconstitution of Cyld−/− BMDMs with wild-type 'rescues' defects in termination of Tak1 activation and chronic production of inflammatory cytokines but reconstitution with Cyld(Y485A) does not. () Immunoassay of wild-type MEFs expressing endogenous Cyld (control) and Cyld−/− BMDMs ectopically expressing V5-tagged wild-type Cyld or Cyld(Y485A) via a lentiviral transduction system, stimulated for 0, 5 or 30 min (above lanes) with TNF, followed by immunoprecipitation of lysates with anti-TRAF2, then immunoblot analysis with antibody to phosphorylated Tak1 and reprobing with anti-Tak1. () Real-time PCR analysis of IL-6, TNF and IL-1β in wild-type and Cyld−/− BMDMs transduced as in and stimulated with TNF. () ELISA of IL-6 and IL-1β in supernatants of cells in . Data represent at least three independent experiments (mean ± s.d. of triplicate wells in ,). Author information * Abstract * Author information * Supplementary information Affiliations * Karmanos Cancer Institute, Departments of Oncology, Immunology & Microbiology, Wayne State University School of Medicine, Detroit, Michigan, USA. * Neesar Ahmed, * Minghui Zeng, * Indrajit Sinha, * Lisa Polin, * Wei-Zen Wei & * K Venuprasad * Department of Genetics and Development, Columbia University Medical Center, New York, New York, USA. * Chozhavendan Rathinam * Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut, USA. * Richard Flavell * Department of Laboratory Medicine, Lund University, Malmö, Sweden. * Ramin Massoumi Contributions N.A., M.Z. and I.S. did the experiments and analyzed data; L.P. assisted with in vivo tumor studies; W.-Z.W. assisted in manuscript preparation; C.R. and R.F. provided critical reagents and mouse model; R.M. provided critical mouse model and assisted in manuscript preparation; and K.V. designed the experiments, analyzed data and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * K Venuprasad Author Details * Neesar Ahmed Search for this author in: * NPG journals * PubMed * Google Scholar * Minghui Zeng Search for this author in: * NPG journals * PubMed * Google Scholar * Indrajit Sinha Search for this author in: * NPG journals * PubMed * Google Scholar * Lisa Polin Search for this author in: * NPG journals * PubMed * Google Scholar * Wei-Zen Wei Search for this author in: * NPG journals * PubMed * Google Scholar * Chozhavendan Rathinam Search for this author in: * NPG journals * PubMed * Google Scholar * Richard Flavell Search for this author in: * NPG journals * PubMed * Google Scholar * Ramin Massoumi Search for this author in: * NPG journals * PubMed * Google Scholar * K Venuprasad Contact K Venuprasad Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (385K) Supplementary Figures 1–8 Additional data - Expression of A20 by dendritic cells preserves immune homeostasis and prevents colitis and spondyloarthritis
- Nat Immunol 12(12):1184-1193 (2011)
Nature Immunology | Article Expression of A20 by dendritic cells preserves immune homeostasis and prevents colitis and spondyloarthritis * Gianna Elena Hammer1 * Emre E Turer1 * Kimberly E Taylor1 * Celia J Fang1, 2 * Rommel Advincula1 * Shigeru Oshima1 * Julio Barrera1 * Eric J Huang1, 3, 4 * Baidong Hou5 * Barbara A Malynn1 * Boris Reizis6 * Anthony DeFranco5 * Lindsey A Criswell1 * Mary C Nakamura1, 3, 4 * Averil Ma1 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:1184–1193Year published:(2011)DOI:doi:10.1038/ni.2135Received07 February 2011Accepted07 September 2011Published online23 October 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Dendritic cells (DCs), which are known to support immune activation during infection, may also regulate immune homeostasis in resting animals. Here we show that mice lacking the ubiquitin-editing molecule A20 specifically in DCs spontaneously showed DC activation and population expansion of activated T cells. Analysis of DC-specific epistasis in compound mice lacking both A20 and the signaling adaptor MyD88 specifically in DCs showed that A20 restricted both MyD88-independent signals, which drive activation of DCs and T cells, and MyD88-dependent signals, which drive population expansion of T cells. In addition, mice lacking A20 specifically in DCs spontaneously developed lymphocyte-dependent colitis, seronegative ankylosing arthritis and enthesitis, conditions stereotypical of human inflammatory bowel disease (IBD). Our findings indicate that DCs need A20 to preserve immune quiescence and suggest that A20-dependent DC functions may underlie IBD and IBD-associated arthritide! s. View full text Figures at a glance * Figure 1: A20 prevents spontaneous activation of DCs in A20fl/flCd11c-Cre mice. () Expression of IL-1β RNA and A20 RNA in sorted populations of splenic cDCs and pDCs from wild-type mice; results are presented relative to the expression of HPRT (hypoxanthine guanine phosphoribosyl transferase). P = 0.004 for IL-1β or 0.03 for A20 (Student's t-test). () Flow cytometry of DCs from A20+/+Cd11c-Cre mice (+/+) and A20fl/flCd11c-Cre mice (fl/fl) to distinguish cDCs (CD11chi; top outlined areas) from CD11clo DCs (dashed outlined areas), which include pDCs. Expansion of myeloid cell populations obscures the relative abundance of DCs in A20fl/flCd11c-Cre mice (Fig. 2). MHCII, MHC class II. (,) Flow cytometry analysis of the frequency () and expression () of CD80, CD86 and CD40 by cDCs (gated on top outlined area in ) from A20+/+Cd11c-Cre and A20fl/flCd11c-Cre mice; results in (averaged from all mice) are presented as mean fluorescence intensity (MFI) relative to that of control A20+/+Cd11c-Cre cDCs. () Flow cytometry of CD11cloDCs (gated on dashed outlined area! s in ) second-gated on B220+Ly6C+ DCs to identify pDCs. Numbers above outlined areas indicate percent activated pDCs with low (left) or high (right) expression of MHC class II among total pDCs. (,) Flow cytometry analysis of the frequency () and expression () of CD80, CD86 and CD40 on pDCs in A20fl/flCd11c-Cre mice. *P ≤ 0.001 and **P = 0.01(Student's t-test). Data are pooled from three independent experiments with at least three mice each (; error bars, s.d.) or are from nine separate experiments with at least two mice per genotype (–; average and s.d.) * Figure 2: A20-deficient DCs induce the population expansion of myeloid and lymphoid cells. () Flow cytometry of splenic nonerythroid cells from A20+/+Cd11c-Cre mice (+/+), A20+/flCd11c-Cre mice (+/fl) and A20fl/flCd11c-Cre mice (fl/fl). () Absolute number of various cell types (horizontal axis) in spleens of A20+/+Cd11c-Cre and A20fl/flCd11c-Cre mice; splenic populations of A20+/flCd11c-Cre mice were similar to those of control A20+/+Cd11c-Cre mice (data not shown). (,) Abundance of myeloid cells () and absolute number of CD11b+F4/80+ myeloid cells and lymphocytes () in mouse lymph nodes. (,) Spleen weight () and splenic myeloid cell populations () in sublethally irradiated wild-type (CD45.1+) mice 4 weeks after reconstitution with congenic (CD45.2+) A20+/+Cd11c-Cre bone marrow cells (WT + A20+/+) or A20fl/flCd11c-Cre bone marrow cells (WT + A20fl/fl). () Enzyme-linked immunosorbent assay (ELISA) of cytokines in supernatants of A20+/+, A20+/− and A20−/− BMDCs stimulated for 7 h with LPS. () Recruitment of CD11b+F4/80+ monocytes to lymph nodes by LPS-stimulat! ed A20+/+ (+/+), A20+/− (+/−) or A20−/− (−/−) BMDCs, presented as a frequency among total lymph node cells. () Recruitment of monocytes to lymph nodes by LPS-stimulated A20+/+ or A20−/− BMDCs in wild-type mice pretreated with blocking anti-IL-6 (α-IL-6) or anti-TNF (α-TNF) or isotype-matched control antibody (left two bars). () ELISA of IL-6 in serum from 6- to 10-week-old mice (genotype in key); each symbol represents an individual mouse and small horizontal lines indicate the mean. Numbers above outlined areas (,,) indicate percent CD11b+ cells. *P ≤ 0.01 and **P = 0.03 (Student's t-test). Data are representative of ten experiments (–), three independent experiments with three recipient mice of each genotype in each (,), five experiments (), five independent experiments with at least three recipient mice per group () or are pooled from three independent experiments with at least three mice per genotype () or three recipients per treatment in each (; ! error bars (,,,,–), s.d.). * Figure 3: A20 expression in DCs is needed to prevent aberrant T cell activation. () Flow cytometry of thymocyte populations from A20+/+Cd11c-Cre and A20fl/flCd11c-Cre mice. Numbers in quadrants indicate percent cells in each throughout. () CD25+Foxp3+ CD4+ regulatory T cells among total CD4+ thymocytes and lymph node (LN) CD4+ T cells. (–) Expression of CD69 (,) or CD44 and CD62L (,) by splenic T cells (TCRβ gated) from A20+/+Cd11c-Cre, A20+/flCd11c-Cre and A20fl/flCd11c-Cre mice. Numbers above outlined areas (,) indicate percent CD69+ () or CD44hiCD62Llo () activated CD4+ T cells (top) or CD8+ T cells (bottom). *P ≤ 0.02 (Student's t-test). () Frequency of polyclonal, CFSE-labeled, wild-type CD8+ T cells adoptively transferred into congenic A20fl/flCd11c-Cre mice or control mice that converted into activated CD44hiCD62Llo T cells by day 3, 6 or 10 after transfer. () CFSE dilution by the CD8+ T cells in at 10 d after transfer, to assess T cell proliferation. () Frequency of OT-II T cells among total CD4+ T cells (left) and absolute number of OT-II c! ells (right) in peripheral lymph nodes from A20fl/flCd11c-Cre mice or A20+/+Cd11c-Cre control mice given adoptive transfer of ovalbumin-specific OT-II T cells, followed by injection of PBS (OVAp –; n = 1 recipient per genotype) or ovalbumin-derived peptide (OVAp +; n = 2 recipients per genotype) and analysis 10 d later. Data are from four experiments (), two experiments with four mice per genotype (; average and s.d.), ten independent experiments with at least one mouse per genotype (–; average and s.d. in ,) or one of two experiments (; error bars, s.d.) or are representative of three experiments with two mice per genotype per time point (,). * Figure 4: MyD88-independent signals trigger DC activation and drive aberrant T cell activation in A20fl/flCd11c-Cre mice. () Expression of CD80 and CD40 by splenic cDCs and pDCs from A20+/+Myd88fl/flCd11c-Cre mice (solid black lines) and A20fl/flMyd88fl/flCd11c-Cre mice (shaded areas) and age-matched A20fl/flCd11c-Cre mice (dotted black lines). () Expression of CD80 and CD40 by cDCs and pDCs from A20+/+Cd11c-CreMyd88−/− mice (solid black lines), A20fl/flCd11c-CreMyd88−/− mice (shaded areas) and A20fl/flCd11c-CreMyd88+/− mice (dotted black lines). () Flow cytometry of activated CD4+ or CD8+ T cells in lymph nodes from A20+/+Myd88fl/flCd11c-Cre mice (A20+/+Myd88fl/fl), A20fl/flCd11c-CreMyd88+/+ mice (A20fl/flMyd88+/+) and A20fl/flMyd88fl/flCd11c-Cre mice (A20fl/flMyd88fl/fl). Numbers above outlined areas indicate percent CD44hiCD62Llo cells. (–) Frequency of adoptively transferred T cells converted into activated CD44hiCD62Llo T cells (–) or induced to proliferate (–) in A20fl/flCd11c-Cre mice or control A20+/+Cd11c-Cre mice given adoptive transfer of polyclonal, CFSE-labeled, wil! d-type CD8+ T cells, followed by treatment with isotype-matched control antibody (,) or a combination of anti-CD80 and anti-CD86 (,), assessed 9 d after transfer. Numbers above outlined areas (,) indicate percent CD44hiCD62Llo cells; numbers above bracketed lines (,) indicate percent dividing cells. Data are representative of five independent experiments with at least one mouse per genotype (–) or are from two independent experiments each including two mice per group (–; average and s.d. in ,). * Figure 5: MyD88-dependent signals in DCs drive the expansion of T cell populations in A20fl/flCd11c-Cre mice. () Total cell number, CD4+ T cells and CD8+ T cells in lymph nodes from A20+/+Myd88fl/flCd11c-Cre, A20fl/flMyd88+/+Cd11c-Cre and A20fl/flMyd88fl/flCd11c-Cre. () ELISA of IL-6 and TNF in LPS-stimulated A20+/+ (+/+), A20+/+Myd88−/− (+/+Myd88−/−), A20−/− (−/−) and A20−/−Myd88−/− (−/−Myd88−/−) BMDCs. () Proliferation (left) and activation (right) of polyclonal, wild-type CD8+ T cells adoptively transferred into A20fl/flCd11c-Cre mice or A20+/+Cd11c-Cre control mice, followed by treatment of recipients with anti-IL-6, anti-TNF or isotype-matched control antibody over 9 d. Data are from five independent experiments with one mouse per genotype in each (; average and s.d.) or two independent experiments with two mice per group in each (; average and s.d.) or are representative of two experiments (; error bars, s.d.). * Figure 6: A20 function in DCs preserves intestinal homeostasis. () Colons of 5-month-old littermate A20+/+Cd11c-Cre control mice and A20fl/flCd11c-Cre mice. () Histology of colons from mice as in , stained with hematoxylin and eosin. Original magnification, ×100. () Production of IL-17 and IFN-γ by splenic CD4+ T cells from 6-month-old littermate A20+/+Cd11c-Cre control mice and A20fl/flCd11c-Cre mice. Numbers adjacent to outlined areas indicate percent IL-17+IFN-γ− cells (top left) or IL-17−IFN-γ+ cells (bottom right). () ELISA of IgA in serum from 2- to 3-month-old A20+/+Cd11c-Cre, A20+/flCd11c-Cre and A20fl/flCd11c-Cre mice. () Body weight of 12-week-old A20+/+Cd11c-Cre, A20+/flCd11c-Cre and A20fl/flCd11c-Cre mice (n = 3 per genotype) provided drinking water with DSS for 5 d, presented relative to initial body weight. Each asterisk indicates the death or obligatory killing of a mouse; no A20fl/flCd11c-Cre mice survived beyond 7 d. (,) Inflammatory myeloid cells in the spleen () and colon histology () of 6-month-old A20+/+Cd11c! -CreRag1−/− mice (+/+ Rag1−/−) and A20fl/flCd11c-CreRag1−/− mice (fl/fl Rag1−/−). Numbers above outlined areas in indicate percent CD11b+ cells. Original magnification (), ×100. Data are representative of ten (,), five () or two () experiments (average and s.d. in ) or one experiment with five mice per genotype (,) or are from two experiments with ten mice (; average and s.d.). * Figure 7: A20-deficient DCs activate naive T cells and drive T cell–mediated colitis. () Body weight of A20+/+Cd11c-CreRag1−/− mice (+/+), A20+/flCd11c-CreRag1−/− mice (+/fl) and A20fl/flCd11c-CreRag1−/− mice (fl/fl) after transfer of naive, wild-type CD4+CD62L+CD25− T cells, presented relative to initial weight. () Weight of spleens from A20+/+Cd11c-CreRag1−/−, A20+/flCd11c-CreRag1−/− and A20fl/flCd11c-CreRag1−/− mice 24 d after T cell transfer as in . Data are representative of two independent experiments with at least two mice per genotype (error bars, s.d.). * Figure 8: A20fl/flCd11c-Cre mice spontaneously develop arthritic disease with pathologies similar to human IBD-associated arthritis. (–) Hematocylin and eosin staining of hindpaws from 5-month-old healthy control A20+/+Cd11c-Cre mice (,,) and littermate A20fl/flCd11c-Cre mice suffering acute arthritis (,,). (,) Outlined areas (*) indicate entheses enlarged in ,. (,) Synovitis and inflammatory infiltrates surrounding the tendon and entheses. Ti, tibia; Ta, talus; N, navicular. (–) Joint pathology in 1-year-old A20fl/flCd11c-Cre mice (n = 2). (,) ○, bone cysts; *, pannus; , joint ankylosis and new bone formation. (,) Arrowheads indicate sites of cartilage erosion () or new bone formation and chondrogenesis (). Scale bars, 1 mm (,,–), 100 μm (,) or 500 μM (,). () Rheumatoid factor, antinuclear antigens and anti–cyclic citrullinated peptide (Anti-CCP) in serum from A20+/+Cd11c-Cre, A20+/flCd11c-Cre and A20fl/flCd11c-Cre mice between 5 and 12 months of age. Each symbol represents an individual mouse; small horizontal lines indicate the mean. AEU, arbitrary ELISA units. Data are representative of tw! o experiments with at least seven mice per genotype. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Medicine, University of California at San Francisco, San Francisco, California, USA. * Gianna Elena Hammer, * Emre E Turer, * Kimberly E Taylor, * Celia J Fang, * Rommel Advincula, * Shigeru Oshima, * Julio Barrera, * Eric J Huang, * Barbara A Malynn, * Lindsey A Criswell, * Mary C Nakamura & * Averil Ma * San Francisco Veterans Affairs Medical Center, San Francisco, California, USA. * Celia J Fang * Department of Pathology, University of California at San Francisco, San Francisco, California, USA. * Eric J Huang & * Mary C Nakamura * Pathology Service, VA Medical Center, San Francisco, California, USA. * Eric J Huang & * Mary C Nakamura * Department of Microbiology and Immunology, University of California at San Francisco, San Francisco, California, USA. * Baidong Hou & * Anthony DeFranco * Department of Microbiology and Immunology, Columbia University, New York, New York, USA. * Boris Reizis Contributions G.E.H. designed and did experiments with A20fl/flCd11c-Cre and related mice; E.E.T. and B.A.M. generated A20fl/flCd11c-Cre mice; E.E.T. initiated analyses of A20fl/flCd11c-Cre mice; B.R. generated Cd11c-Cre mice; B.H. and A.D. generated Myd88fl/fl mice; S.O. assisted with colitis experiments; K.E.T. and L.A.C. did genetic analyses of A20 SNPs with data from the Wellcome Trust; C.J.F., E.J.H. and M.C.N. did micro–computed tomography scans and histological analyses of arthritic joints; R.A. and J.B. assisted with breeding, genotyping and radiation chimera experiments; A.M. directed the study; and A.M. and G.E.H., with input from B.A.M., wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Averil Ma Author Details * Gianna Elena Hammer Search for this author in: * NPG journals * PubMed * Google Scholar * Emre E Turer Search for this author in: * NPG journals * PubMed * Google Scholar * Kimberly E Taylor Search for this author in: * NPG journals * PubMed * Google Scholar * Celia J Fang Search for this author in: * NPG journals * PubMed * Google Scholar * Rommel Advincula Search for this author in: * NPG journals * PubMed * Google Scholar * Shigeru Oshima Search for this author in: * NPG journals * PubMed * Google Scholar * Julio Barrera Search for this author in: * NPG journals * PubMed * Google Scholar * Eric J Huang Search for this author in: * NPG journals * PubMed * Google Scholar * Baidong Hou Search for this author in: * NPG journals * PubMed * Google Scholar * Barbara A Malynn Search for this author in: * NPG journals * PubMed * Google Scholar * Boris Reizis Search for this author in: * NPG journals * PubMed * Google Scholar * Anthony DeFranco Search for this author in: * NPG journals * PubMed * Google Scholar * Lindsey A Criswell Search for this author in: * NPG journals * PubMed * Google Scholar * Mary C Nakamura Search for this author in: * NPG journals * PubMed * Google Scholar * Averil Ma Contact Averil Ma Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–10 Additional data - A platelet-mediated system for shuttling blood-borne bacteria to CD8α+ dendritic cells depends on glycoprotein GPIb and complement C3
- Nat Immunol 12(12):1194-1201 (2011)
Nature Immunology | Article A platelet-mediated system for shuttling blood-borne bacteria to CD8α+ dendritic cells depends on glycoprotein GPIb and complement C3 * Admar Verschoor1, 2, 3 * Michael Neuenhahn1, 4 * Alexander A Navarini2, 7 * Patricia Graef1 * Ann Plaumann1 * Amelie Seidlmeier1 * Bernhard Nieswandt5 * Steffen Massberg6 * Rolf M Zinkernagel2, 8 * Hans Hengartner2, 8 * Dirk H Busch1, 3, 4, 8 * Affiliations * Contributions * Corresponding authorsJournal name:Nature ImmunologyVolume: 12,Pages:1194–1201Year published:(2011)DOI:doi:10.1038/ni.2140Received22 August 2011Accepted21 September 2011Published online30 October 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The acquisition of pathogen-derived antigen by dendritic cells (DCs) is a key event in the generation of cytotoxic CD8+ T cell responses. In mice, the intracellular bacterium Listeria monocytogenes is directed from the blood to splenic CD8α+ DCs. We report that L. monocytogenes rapidly associated with platelets in the bloodstream in a manner dependent on GPIb and complement C3. Platelet association targeted a small but immunologically important portion of L. monocytogenes to splenic CD8α+ DCs, diverting bacteria from swift clearance by other, less immunogenic phagocytes. Thus, an effective balance is established between maintaining sterility of the circulation and induction of antibacterial immunity by DCs. Other Gram-positive bacteria also were rapidly tagged by platelets, revealing a broadly active shuttling mechanism for systemic bacteria. View full text Figures at a glance * Figure 1: Complement C3 mediates efficient L. monocytogenes (LM) infection of the spleen. (–) Splenic L. monocytogenes burden in C3−/− or C3+/+ wild-type (WT) mice at 1 d (), 3 d () or 7 d () after intravenous infection. () Enzyme-linked immunosorbent assay (ELISA) of the systemic depletion of C3 from serum by CVF at t = 0. () Splenic L. monocytogenes burdens at 3 d after infection in mice depleted of C3 by CVF injection starting before (t = −20 h, −1 h and +20 h; middle) or shortly after (t = +30 min and +20 h; right) L. monocytogenes infection (t = 0), compared with control wild-type mice (left). () Splenic L. monocytogenes burdens in C3ar1−/− or wild-type mice 3 d after intravenous infection. Dashed lines indicate detection limit () or 50% of maximum absorbance (). NS, not significant. P values, unpaired, two-tailed Student's t-test. Data represent two or more independent experiments (mean ± s.d. of three or more mice). * Figure 2: Complement C3 enables efficient L. monocytogenes entry into splenic CD8α+ DCs. () ELISA of C3 concentrations in wild-type and C3−/− sera (left) used to preincubate L. monocytogenes in vitro; inoculums were washed by repeated centrifugation and resuspension until the ELISA signal from the final wash approached background (middle), which ensured that the C3 signal from the inoculum represented deposited, not soluble, C3 (right). () Viability of L. monocytogenes inoculum after preincubation in wild-type or C3−/− serum, assessed by plating on brain-heart infusion (BHI) agar and overnight incubation at 37 °C. () Early splenic L. monocytogenes burdens of C3−/− mice 1 h after infection with L. monocytogenes incubated with C3−/− or wild-type serum. () Spleens of C3−/− mice obtained 1 h after infection with C3−/− or wild-type serum-incubated L. monocytogenes. Splenic CD11cloCD8αloCD11b+ granulocyte (PMN) and macrophage (Mφ, including monocytes) populations were segregated from CD8α+ and CD8α− CD11c+ DC populations by flow sorting,! and sorted populations were lysed and plated onto BHI agar to determine degree of infection. Total spl, total splenocytes. Dashed line in , detection limit. P values, unpaired, two-tailed Student's t-test. Data represent three independent experiments (mean ± s.d. of three or more mice). * Figure 3: Complement C3 and platelet GPIb enable bacteria-platelet interactions that mediate L. monocytogenes shuttling to splenic CD8α+ DCs. () Flow cytometry (left and middle) and fluorescence microscopy (right) of blood samples of wild-type mice (top) or C3−/− mice (bottom) obtained within 1 min of infection with CFSE-marked L. monocytogenes (middle, right) or left uninfected (left). Platelets, red; L. monocytogenes, green. Scale bars, 5 μm. () Flow cytometry of L. monocytogenes–platelet interactions in wild-type mice treated with CVF before infection (top right) and untreated controls (top left) or in C3−/− mice infected with L. monocytogenes incubated with wild-type serum (bottom left) or C3−/− serum (bottom right). () Flow cytometry analysis of L. monocytogenes–platelet interactions with (left) or without (right) classical and MBL-pathway-enabling complement C4. () Flow cytometry analysis of normal L. monocytogenes–platelet interactions in mice lacking immunoglobulin (Rag1−/−) or complement components C1q or C5. () In vitro blocking assay of hirudinated C4b−/− whole blood and monoc! lonal antibodies to specified platelet surface molecules. () Flow cytometry analysis of blood obtained from GpIba−/− and C4b−/− mice within 1 min of intravenous infection with CFSE-marked L. monocytogenes. () Flow cytometry sorting of cells from spleens of Gp1ba−/− and wild-type mice collected 1 h after infection with L. monocytogenes; sorted CD11cloCD8αloCD11b+ granulocyte (PMN) and macrophage (Mφ, including monocytes) and CD8α+ and CD8α− CD11c+ DC populations were lysed and plated onto BHI agar to determine degree of infection. In ,, numbers below plots at right relate to bacterial gate (right) and show percentage of total L. monocytogenes that are either associated (top) or not associated (bottom) with CD41+ platelets (together 100%). Numbers at left relate to nonbacterial gate (left) and show percent CD41+ platelet events (top) versus nonplatelet events (bottom) (together also 100%). Data represent two to three independent experiments. * Figure 4: Platelets are specifically taken up by splenic CD8α+ DCs and mediate L. monocytogenes delivery to this cell population. () Spleens of platelet-depleted wild-type mice (WT – plt) and control wild-type mice obtained 1 h after L. monocytogenes infection. Splenic CD11cloCD8αloCD11b+ granulocyte (PMN) and macrophage (Mφ, including monocytes) populations were segregated from CD8α+ and CD8α− CD11c+ DCs by flow sorting, and the sorted populations, as well as unsorted splenocytes (Total spl), were lysed and plated onto BHI agar to determine degree of infection. () L. monocytogenes spleen burdens at 3 d after infection in platelet-depleted wild-type and control wild-type mice. Dashed line, detection limit. () Intracellular flow cytometry analysis for platelet marker CD41 within splenocyte populations, including CD8α+ and CD8α− CD11c+ DCs (left and right, respectively) for indicated L. monocytogenes doses. () Summary of intracellular and surface CD41 staining (left and right, respectively) for all sorted splenocyte populations and L. monocytogenes doses. P values, unpaired, two-tailed Studen! t's t-test. Data represent two to three independent experiments (mean ± s.d. of three or more mice). * Figure 5: Impaired anti-L. monocytogenes CD8+ T cell population expansion after inefficient platelet-mediated bacterial targeting to CD8α+ DCs. () Flow cytometry of splenic CD8+ T cells from wild-type (left) and C3−/− mice (right; ) or platelet-depleted wild-type mice (right; ) 7 d after infection with spreading deficient (ΔActA) ovalbumin-expressing L. monocytogenes. Numbers above outlined areas indicate percent H2-Kb–SIINFEKL multimer–positive (ovalbumin-specific) cells. () Flow cytometry analysis of the frequency of adoptively transferred (day −1) CD90.1+ ovalbumin-specific TCR-transgenic OT-I T cells into wild-type (left) versus C3−/− mice (right) subjected to same infection protocol as ,. Middle and right (–), average H2-Kb–SIINFEKL multimer–positive CD8+ T cells (,) or OT-I T cells () among of all CD8+ T cells (middle) or absolute number (right) per spleen. P values, unpaired, two-tailed Student's t-test (). Data are represent two to three independent experiments (mean ± s.d. of three or more mice). * Figure 6: Lack of complement-mediated platelet association leads to accelerated bacterial clearance. () Vascular clearance of L. monocytogenes in minutes after intravenous injection into wild-type and DC-depleted CD11c-DTR mice (), wild-type and C3−/− mice (), macrophage-depleted and control C3−/− mice () or platelet-depleted and control wild-type mice (). () Vascular clearance of L. monocytogenes after intravenous injection into wild-type, C3−/− and platelet-depleted wild-type mice, presented as linear regression best-fit slope (actual values in parentheses) over the first 5 min after infection. () Kinetics of the clearance of L. monocytogenes after intravenous injection. *P < 0.05, **P < 0.01 and ***P < 0.001 (unpaired, two-tailed Student's t-test). Data represent two to five independent experiments (mean ± s.d. of three or more mice). * Figure 7: C3-mediated platelet association among various Gram-positive bacteria. Flow cytometry analysis of blood samples of wild-type (top) or C3−/− mice (bottom) obtained within 1 min of infection with CFSE-marked S. aureus, E. fecalis, B. subtilis or encapsulated or noncapsular forms of S. pneumoniae. Below plots: right (bacterial gate), frequency of total bacteria associated (top) or not associated (bottom) with CD41+ platelets (together 100%); left (nonbacterial gate), frequency of CD41+ platelet events (top) or nonplatelet events (bottom; together, 100%). Author information * Abstract * Author information * Supplementary information Affiliations * Institute for Medical Microbiology, Immunology and Hygiene, and Focus Group, Clinical Cell Processing and Purification, Institute for Advanced Study, Technische Universität München, Munich, Germany. * Admar Verschoor, * Michael Neuenhahn, * Patricia Graef, * Ann Plaumann, * Amelie Seidlmeier & * Dirk H Busch * Institute for Experimental Immunology, University Hospital Zurich, Zurich, Switzerland. * Admar Verschoor, * Alexander A Navarini, * Rolf M Zinkernagel & * Hans Hengartner * German Mouse Clinic, Helmholtz Zentrum München, Neuherberg, Germany. * Admar Verschoor & * Dirk H Busch * Clinical Cooperation Groups Antigen-Specific Immunotherapy Helmholtz Zentrum München and Immune Monitoring, Technische Universität München, Munich, Germany. * Michael Neuenhahn & * Dirk H Busch * Vascular Medicine, University Hospital Würzburg and Rudolf Virchow Center, DFG Research Center for Experimental Biomedicine, University of Würzburg, Würzburg, Germany. * Bernhard Nieswandt * Deutsches Herzzentrum, Klinik für Herz und Kreislauferkrankungen, Technische Universität München, Munich, Germany. * Steffen Massberg * Present address: Department of Dermatology, University Hospital Zurich, Zurich, Switzerland. * Alexander A Navarini * These authors share senior authorship. * Rolf M Zinkernagel, * Hans Hengartner & * Dirk H Busch Contributions A.V., M.N., A.A.N., A.P., A.S. and P.G. did experiments; B.N. and S.M. supplied reagents and assisted with data interpretation; A.V. and D.H.B. conceived the study; A.V., M.N., A.A.N. and P.G. analyzed the data; A.V., H.H., R.M.Z. and D.H.B. planned the experiments and supervised the study. A.V. and D.H.B. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Dirk H Busch or * Admar Verschoor Author Details * Admar Verschoor Contact Admar Verschoor Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Neuenhahn Search for this author in: * NPG journals * PubMed * Google Scholar * Alexander A Navarini Search for this author in: * NPG journals * PubMed * Google Scholar * Patricia Graef Search for this author in: * NPG journals * PubMed * Google Scholar * Ann Plaumann Search for this author in: * NPG journals * PubMed * Google Scholar * Amelie Seidlmeier Search for this author in: * NPG journals * PubMed * Google Scholar * Bernhard Nieswandt Search for this author in: * NPG journals * PubMed * Google Scholar * Steffen Massberg Search for this author in: * NPG journals * PubMed * Google Scholar * Rolf M Zinkernagel Search for this author in: * NPG journals * PubMed * Google Scholar * Hans Hengartner Search for this author in: * NPG journals * PubMed * Google Scholar * Dirk H Busch Contact Dirk H Busch Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (258K) Supplementary Figures 1–2 Additional data - Invariant natural killer T cells recognize lipid self antigen induced by microbial danger signals
- Nat Immunol 12(12):1202-1211 (2011)
Nature Immunology | Article Invariant natural killer T cells recognize lipid self antigen induced by microbial danger signals * Patrick J Brennan1, 5 * Raju V V Tatituri1, 5 * Manfred Brigl1 * Edy Y Kim1 * Amit Tuli1 * Joseph P Sanderson2 * Stephan D Gadola2 * Fong-Fu Hsu3 * Gurdyal S Besra4 * Michael B Brenner1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature ImmunologyVolume: 12,Pages:1202–1211Year published:(2011)DOI:doi:10.1038/ni.2143Received31 August 2011Accepted21 September 2011Published online30 October 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Invariant natural killer T cells (iNKT cells) have a prominent role during infection and other inflammatory processes, and these cells can be activated through their T cell antigen receptors by microbial lipid antigens. However, increasing evidence shows that they are also activated in situations in which foreign lipid antigens would not be present, which suggests a role for lipid self antigen. We found that an abundant endogenous lipid, β-D-glucopyranosylceramide (β-GlcCer), was a potent iNKT cell self antigen in mouse and human and that its activity depended on the composition of the N-acyl chain. Furthermore, β-GlcCer accumulated during infection and in response to Toll-like receptor agonists, contributing to iNKT cell activation. Thus, we propose that recognition of β-GlcCer by the invariant T cell antigen receptor translates innate danger signals into iNKT cell activation. View full text Figures at a glance * Figure 1: Reactivity of iNKT cells to a panel of GSLs. () Enzyme-linked immunosorbent assay (ELISA) of the production of IL-2 by the iNKT cell hybridoma DN32 cultured with RAW cells or CD1d-transfected RAW cells (RAW-CD1d) in the presence of various lipids (horizontal axis; 10 μg/ml). GM1, GM2, GM3 and GD1a, Supplementary Table 1. () ELISA of the production of IFN-γ by a primary iNKT cell line cultured together with wild-type (WT) or Cd1d−/− mouse CD11c+ BMDCs in the presence of various lipids (horizontal axis; 10 μg/ml). (–) ELISA of the production of IFN-γ (,) and IL-4 () by a primary mouse iNKT cell line cultured together with CD11c+ BMDCs in the presence of α-GalCer (10 ng/ml) or bovine milk β-GlcCer (fivefold dose titration with a top concentration of 20 μg/ml), in the absence (,) or presence () of IL-12 (20 pg/ml). Data are representative of at least three independent experiments (mean and range of duplicate wells). * Figure 2: β-GlcCer is present in primary lymphoid tissues and activates iNKT cells. () TLC analysis of polar lipids extracted from mouse thymus, spleen, whole liver and BMDCs along with GSL standards and bovine milk β-GlcCer dose titration. Arrow indicates mobility of β-GlcCer. () ELISA of IL-2 production by the iNKT hybridoma DN32 cultured together with RAW cells or CD1d-transfected RAW cells as APCs, with lipid fractions from mouse thymus and spleen, or bovine milk β-GlcCer (fivefold dose titration to a top concentration of 20 μg/ml). Data are representative of two separate experiments (mean and range of duplicate wells). (,) ESI-MS analysis of β-GalCer purified from thymus () and spleen (), assessed in the electrospray-positive mode and presented relative to the most abundant species, set as 100 (m/z, mass/charge). Major β-GlcCer ions are presented with a lithium adduct; fatty acid composition (determined by collision-induced dissociation tandem mass spectrometry) is in parentheses. Data are representative of two experiments. () Structures of two a! bundant β-GlcCer forms detected by ESI-MS. * Figure 3: Reactivity of iNKT cells to a β-GlcCer panel with differing N-acyl chains. () ELISA of IL-2 production by the iNKT cell hybridoma DN32 cultured together with RAW cells or CD1d-transfected RAW cells, plus β-GlcCer with various N-acyl chains (horizontal axis; fivefold-dose titration of with a top concentration of 10 μg/ml) or α-GalCer (10 ng/ml). () ELISA of IFN-γ production by a primary mouse iNKT cell line cultured together with wild-type CD11c+ BMDCs, plus β-GlcCer C24:1, reported iNKT cell lipid self antigens or a microbial GSL antigen. (,) Cytokine capture assay of IFN-γ () and IL-4 () in liver mononuclear cells from mice given intravenous injection of 25 μg lipid (above plots) or 1 μg α-GalCer, presented as the TCRβ+ PBS-57–loaded tetramer–positive gate, except bottom right plot (total TCRβ+ gate is shown for a CD1d-deficient mouse injected with β-GlcCer C24:1). Numbers in outlined areas indicate percent iNKT cells producing IFN-γ or IL-4. Structures of the synthetic lipids used here are in Supplementary Figure 4, and as all st! ructures contained a d18:1 shingenine base, they are abbreviated throughout with only the N-acyl chain composition listed (for example, 'β-GlcCer 24:1' indicates β-D-glucopyranosylceramide d18:1-C24:1). FSC, forward scatter. Data are representative of three separate experiments (,; mean and range of duplicate wells) or at least three independent experiments (,). * Figure 4: β-GlcCer presented by CD1d activates iNKT cells through cognate TCR interaction. () ELISA of IFN-γ produced by a primary mouse iNKT cell line stimulated with plate-bound biotin-conjugated CD1d or BSA loaded with equal molar concentrations of various lipids (horizontal axis). () Flow cytometry of freshly isolated splenocytes from C57BL/6 and BALB/c mice, stained with PBS-57–CD1d tetramer (tet) and unloaded tetramer or β-GlcCer C24:1 tetramer. Numbers adjacent to outlined areas indicate percent iNKT cells (PBS-57 tetramer–positive, TCRβ+CD19− cells) that stained positive with β-GlcCer C24:1–loaded tetramer. () Flow cytometry of C57BL/6 splenocytes stained with β-GlcCer C24:1 CD1d tetramer and antibody to various TCR Vβ chains (Anti-Vβ; above plot). Results for iNKT cells are presented; numbers in quadrants indicate percent cells in each. () Frequency of iNKT cells from the β-GlcCer C24:1 tetramer–positive population bearing each TCR Vβ in (horizontal axis). Data are representative of three experiments (,; mean and range of duplicate well! s in ) or two experiments () or are from three separate experiments (; mean and s.e.m.). * Figure 5: β-GlcCer is a cognate antigen for human iNKT cells. (,) IFN-γ production by human iNKT cell clones (J3N.5, BM2A.3 and J24L.17) cultured together with human PBMC-derived monocytes in the presence of various lipids (10 μg/ml; horizontal axis; ) or α-GalCer (10 ng/ml; ) and with monoclonal antibody to CD1d (anti-CD1d) or isotype-matched control antibody (). () ELISA of IFN-γ production by a primary human iNKT cell line cultured together with PBMC-derived monocytes, plus β-GlcCer C24:1, reported iNKT cell lipid self antigens or a microbial GSL antigen. () Identification of iNKT cells with anti-CD3ε and PBS-57 tetramers (top) and staining of CD3ε+ PBS-57 tetramer–positive gated cells with anti-Vα24 and anti-Vβ11 to confirm invariant TCR chain use (bottom). Numbers adjacent to outlined areas indicate percent positive cells in each. () Flow cytometry of PBMCs costained with PBS-57–loaded CD1d tetramer and CD1d tetramers loaded with β-GlcCer N-acyl chain variants (above plots), presented as the CD3ε+ gate. CD1d tetrame! rs loaded with β-GlcCer C24:1, C18:1 and C12:0 stain human iNKT cells. Data are representative of three experiments (–; mean and range of duplicate wells), two experiments () or least three separate experiments (). * Figure 6: β-GlcCer contributes to iNKT cell self-reactivity. () ELISA of IFN-γ production by an iNKT cell line cultured together with CD11c+ BMDCs at a ratio of 5:1, with vehicle alone or with NB-DGJ or D-PDMP (inhibitors of β-GlcCer synthesis). () IFN-γ production by iNKT cells cultured together with CD11c+ BMDCs and Gal–α-GalCer, in the presence of vehicle alone or NB-DGJ or D-PDMP. () Quantitative PCR analysis of Ugcg and B4galt6 in CD11c+ BMDCs cultured for 48 h with control siRNA (Ctrl) or Ugcg- or B4galt6-specific siRNA, presented relative to Gapdh expression (encoding glyceraldehyde phosphate dehydrogenase). () ELISA of the production of IFN-γ and IL-4 by a primary iNKT cell line cultured together with the BMDCs in (ratio, horizontal axes), assessing autoreactivity. () IFN-γ production by an iNKT cell line cultured together with CD11c+ BMDCs treated with siRNA as in , assessing the presentation of Gal–α-GalCer. () Flow cytometry analysis of CD1d surface expression on CD11c+ BMDCs treated with siRNA as in . Data are r! epresentative of three separate experiments (mean and range in duplicate wells in ,,,; mean and s.e.m. of triplicates in ). * Figure 7: A role for β-GlcCer in the iNKT cell response to LPS-exposed BMDCs. () Quantitative PCR analysis of the expression of genes involved in β-GlcCer metabolism in CD11c+ BMDCs exposed for 0–24 h (horizontal axes) to LPS (1 ng/ml), presented relative to Gapdh expression. () TLC of polar lipid extracts from LPS-treated CD11c+ BMDCs; arrow indicates the relative mobility of β-GlcCer. () Densitometry of the upper and lower β-GlcCer TLC bands in . () ELISA of IFN-γ production by an iNKT cell line cultured together with CD11c+ BMDCs in the presence of LPS plus vehicle alone or NB-DGJ or D-PDMP. () ELISA of IFN-γ production by a primary iNKT cell line cultured together with siRNA-treated CD11c+ BMDCs (as in Fig. 6c), in the presence of LPS. Data are representative of three independent experiments (error bars, s.e.m. of triplicates (), s.d. () or mean and range of duplicate wells (,)). * Figure 8: β-GlcCer contributes to microbial activation of iNKT cells. () ELISA of IFN-γ production by a primary iNKT cell line cultured together with siRNA-treated CD11c+ BMDCs (as in Fig. 6c) in the presence of heat-killed bacteria (horizontal axes), assessing activation. () TLC of polar lipid extracts from spleens collected on days 0–2 after intravenous infection of mice with E. coli. () TLC analysis of whole-lung lipid extracts on days 0,1 and 3 after intranasal infection with S. pneumoniae, with a solvent system that allowed separation of bacterial GlcDAG from β-GlcCer. Arrows indicate mobility of β-GlcCer. Below (,), densitometry of β-GlcCer bands; each symbol represents an individual mouse, and small horizontal lines indicate the mean. Data are representative of three separate experiments (; mean and range of duplicate wells) or two experiments (,). Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Patrick J Brennan & * Raju V V Tatituri Affiliations * Department of Medicine, Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA. * Patrick J Brennan, * Raju V V Tatituri, * Manfred Brigl, * Edy Y Kim, * Amit Tuli & * Michael B Brenner * Academic Unit of Clinical and Experimental Sciences, Faculty of Medicine, Sir Henry Wellcome and 'Hope' Laboratories, University of Southampton, Southampton, UK. * Joseph P Sanderson & * Stephan D Gadola * Division of Endocrinology, Metabolism and Lipid Research, Washington University, St. Louis, Missouri, USA. * Fong-Fu Hsu * School of Biosciences, University of Birmingham, Birmingham, UK. * Gurdyal S Besra Contributions P.J.B. and R.V.V.T. conceived of, did and interpreted data from the experiments; P.J.B. was the main author of the manuscript; M.B., A.T., F.-F.H., J.P.S., S.D.G. and E.Y.K. assisted with the experimental design and data interpretation, did experiments and edited the manuscript; G.S.B. assisted with the design of the experiments and synthesized key materials; and M.B.B. assisted with the design of the experiments and data interpretation, supervised the research and substantially contributed to the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Gurdyal S Besra or * Michael B Brenner Author Details * Patrick J Brennan Search for this author in: * NPG journals * PubMed * Google Scholar * Raju V V Tatituri Search for this author in: * NPG journals * PubMed * Google Scholar * Manfred Brigl Search for this author in: * NPG journals * PubMed * Google Scholar * Edy Y Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Amit Tuli Search for this author in: * NPG journals * PubMed * Google Scholar * Joseph P Sanderson Search for this author in: * NPG journals * PubMed * Google Scholar * Stephan D Gadola Search for this author in: * NPG journals * PubMed * Google Scholar * Fong-Fu Hsu Search for this author in: * NPG journals * PubMed * Google Scholar * Gurdyal S Besra Contact Gurdyal S Besra Search for this author in: * NPG journals * PubMed * Google Scholar * Michael B Brenner Contact Michael B Brenner Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–15 and Table 1 and Methods Additional data - Epigenetic repression of the Igk locus by STAT5-mediated recruitment of the histone methyltransferase Ezh2
- Nat Immunol 12(12):1212-1220 (2011)
Nature Immunology | Article Epigenetic repression of the Igk locus by STAT5-mediated recruitment of the histone methyltransferase Ezh2 * Malay Mandal1 * Sarah E Powers1 * Mark Maienschein-Cline2 * Elizabeth T Bartom3 * Keith M Hamel1 * Barbara L Kee4 * Aaron R Dinner2 * Marcus R Clark1 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:1212–1220Year published:(2011)DOI:doi:10.1038/ni.2136Received28 July 2011Accepted09 September 2011Published online30 October 2011 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg During B lymphopoiesis, recombination of the locus encoding the immunoglobulin κ-chain complex (Igk) requires expression of the precursor to the B cell antigen receptor (pre-BCR) and escape from signaling via the interleukin 7 receptor (IL-7R). By activating the transcription factor STAT5, IL-7R signaling maintains proliferation and represses Igk germline transcription by unknown mechanisms. We demonstrate that a STAT5 tetramer bound the Igk intronic enhancer (Eκi), which led to recruitment of the histone methyltransferase Ezh2. Ezh2 marked trimethylation of histone H3 at Lys27 (H3K27me3) throughout the κ-chain joining region (Jκ) to the κ-chain constant region (Cκ). In the absence of Ezh2, IL-7 failed to repress Igk germline transcription. H3K27me3 modifications were lost after termination of IL-7R–STAT5 signaling, and the transcription factor E2A bound Eκi, which resulted in acquisition of H3K4me1 and acetylated histone H4 (H4Ac). Genome-wide analyses showed a STA! T5 tetrameric binding motif associated with transcriptional repression. Our data demonstrate how IL-7R signaling represses Igk germline transcription and provide a general model for STAT5-mediated epigenetic transcriptional repression. View full text Figures at a glance * Figure 1: Binding of STAT5 at κS2 in Eκi is functionally important. () Igk intronic enhancer Eκi and its functional motifs (larger letters), including the NF-κB site and the three E-boxes (κE1–κE3), as well as the two putative STAT5-binding sites, κS1 and κS2. () EMSA of nuclear extracts of Irf4−/−Irf8−/− pre-B cells cultured for 24 h in IL-7 (10 ng/ml), assayed with probes corresponding to wild-type (WT) and mutated (Mut) κS1 and κS2 binding sites (above lanes). () EMSA of nuclear extracts of Irf4−/−Irf8−/− pre-B cells cultured for 24 h in IL-7 at a high concentration (10 ng/ml; left, +IL-7) or low concentration (0.1 ng/ml; right, –IL-7) for 24 h, assayed with probes corresponding to wild-type and mutated κS2 binding sites. () EMSA of nuclear extracts of Irf4−/−Irf8−/− pre-B cells cultured with IL-7 as in , assayed with probes corresponding to Oct- or Pax5-binding sites. () Dual-luciferase assay of lysates of COS-7 cells transfected for 48 h with luciferase reporter plasmid containing Eκi(WT), Eκi(mκS! 1), Eκi(mκS2) or Eκi(mκS1-mκS2) (key) plus pRL-TK and control plasmid or combinations of plasmids encoding E47, E12 and/or CA-STAT5B (horizontal axis). AU, arbitrary units. *P < 0.001, versus the Eκi(WT) control; **P < 0.01, versus the Eκi(mκS1) control; ***P < 0.001 and †P < 0.01, versus the Eκi(mκS2) control; ‡P < 0.001, versus the Eκi(mκS1-mκS2) control (unpaired t-test). Data are representative of three independent experiments (average ± s.d. in ). * Figure 2: STAT5 and E2A compete for binding at their respective Eκi sites. () Oligonucleotide spacers with of three, six or nine adenine residues between κS2 and κE1 in pGL3 luciferase reporter plasmids. () Dual-luciferase assay of lysates of COS-7 cells transfected for 48 h with the luciferase reporter plasmids in (key) plus pRL-TK and control plasmid or combinations of plasmids encoding E47 and STAT5B (horizontal axis). *P < 0.001, versus Eκi(WT) control; **P < 0.001, versus the Eκi(κS2-3A-κE1) control; ***P < 0.001, versus the Eκi(κS2-6A-κE1) control; †P < 0.001, versus the Eκi(κS2-9A-κE1) control (unpaired t-test). (,) ChIP (with immunoglobulin G (IgG; control), anti-STAT5 or anti-E47 (key)) of nuclear preparations of COS-7 cells transfected as in (horizontal axis) with Eκi(WT) () or Eκi(κS2-9A-κE1) (), followed by PCR with primers specific for the Eκi fragment in the reporter plasmid. *P < 0.001, versus E47 binding in cells expressing only E47 (unpaired t-test). Data are representative of three independent experiments (avera! ge ± s.d.). * Figure 3: Epigenetic regulation of Eκi during B lymphopoiesis. () ChIP (with anti-H4Ac, anti-H3K4me1, anti-H3K27me3 or IgG (control)) of flow cytometry–isolated wild-type pro-B cells, large pre-B cells, small pre-B cells and immature (Imm) B cells, followed by quantitative PCR with primers specific for Eκi. *P < 0.001, versus H4Ac in pro-B cells; **P < 0.001, versus H3K4me1 in pro-B cells; ***P < 0.001, versus H3K27me3 in pro-B cells (unpaired t-test). () ChIP and PCR as in of Irf4−/−Irf8−/− pre-B cells cultured for 48 h with IL-7 at a high or low concentration. *P < 0.001, versus +IL-7 H4Ac; **P < 0.001, versus +IL-7 H3K4me1; ***P < 0.001, versus +IL-7 H3K27me3 (unpaired t-test). Data are representative of three independent experiments (average ± s.d.). * Figure 4: STAT5 and E2A mediate repressive and activation marks, respectively, from Jκ through Cκ. () ChIP and PCR (as in Fig. 3b) of Irf4−/−Irf8−/− pre-B cells expressing CA-STAT5B or vector alone and cultured for 48 h with a low concentration of IL-7. *P < 0.001, versus mock H4Ac; **P < 0.001, versus mock H3K4me1; ***P < 0.001, versus mock H3K27me3 (unpaired t-test). () ChIP and PCR (as in ) of Irf4−/−Irf8−/− pre-B cells expressing a retrovirus-encoded fusion of the estrogen receptor and inducible Id3 (ER-Id3) and cultured for 48 h with IL-7 at a high or low concentration and mock-treated (Uninduced; left) or induced for 48 h with 1 μM tamoxifen (Induced; right). *P < 0.001, versus uninduced –IL-7 H4Ac; **P < 0.001, versus uninduced –IL-7 H3K4me1 (unpaired t-test). () ChIP (with IgG or anti-H3K27me3) of Irf4−/−Irf8−/− pre-B cells expressing CA-STAT5B or vector alone (Mock) and cultured for 48 h with a low concentration of IL-7, followed by quantitative PCR with nonoverlapping primer sets designed to detect various regions of the Igk locus (b! elow). *P < 0.001, versus mock + H3K27me3 in respective regions (unpaired t-test). Data are representative of three independent experiments (average ± s.d.). * Figure 5: Binding of tetrameric STAT5 to κS2 recruits Ezh2 and represses Igk germline transcription. () ChIP (with anti-STAT5 or IgG) of Irf4−/−Irf8−/− pre-B cells cultured with IL-7 at a high (+) or low (−) concentration, followed by immunoblot analysis (IB) with anti-STAT5 or anti-Ezh2. Right, immunoblot analysis of aliquots of nuclear extracts with anti-STAT5 or anti-Ezh2. () Immunoprecipitation (IP) of nuclear preparations of Irf4−/−Irf8−/− pre-B cells with anti-STAT5 or IgG, without DNA crosslinking (no formaldehyde), followed by immunoblot analysis with anti-STAT5, anti-Ezh2 or anti-H3 (loading control). () EMSA of nuclear extracts of Irf4−/−Irf8−/− pre-B cells cultured for 24 h with IL-7 at a high concentration (Pre-B) or of 3T3 cells transduced with control vector (3T3) or vector to express CA-STAT5 (3T3–CA-STAT5), probed with biotinylated κS2(WT) or oligonucleotides known to bind dimers, tetramers or both dimers and tetramers of STAT5 (above lanes). () EMSA of nuclear extracts of Irf4−/−Irf8−/− pre-B cells cultured with IL-7 at ! a high concentration, assayed with biotinylated κS2(WT) and κS2-end-Mut probes. () Quantitative analysis of the results in obtained with the κS2(WT) probe, presented as band density relative to total density for all three bands in the presence (+) or absence (−) of anti-Ezh. *P < 0.001, versus the appropriate relative band density with or without anti-Ezh2 (unpaired t-test). () Immunoblot analysis of biotinylated κS2(WT) and κS2-end-Mut probes precipitated from nuclear extracts of Irf4−/−Irf8−/− pre-B cells cultured with IL-7 at a high concentration, plus streptavidin (SA)-agarose, probed with anti-STAT5 or anti-Ezh2. () ChIP (with IgG or anti-STAT5) of Irf4−/−Irf8−/− pre-B cells cultured with IL-7 at a high concentration, followed by immunoblot analysis with anti-STAT5, anti-Ezh2, anti-EED or anti-SUZ12. () Quantitative PCR analysis of Ezh2 mRNA expression in Irf4−/−Irf8−/− pre-B cells expressing shRNA targeting firefly luciferase (sh-FF3; co! ntrol) or Ezh2 (sh-Ezh2-390 and sh-Ezh2-1562), presented relat! ive to the expression of β2-microglobulin mRNA. *P < 0.001, versus sh-FF3 (unpaired t-test). () Quantitative PCR analysis of Igk germline transcription in Irf4−/−Irf8−/− pre-B cells expressing shRNA as in and cultured for 48 h with IL-7 at a high or low concentration, presented as in . *P < 0.001 and **P < 0.05 versus sh-FF3 + IL-7; †P < 0.01, versus sh-Ezh2-390 + IL-7 (unpaired t-test). Data are representative of three (,) or two () independent experiments (average ± s.d. in ,). * Figure 6: Binding of tetrameric STAT5 mediates H3K27 trimethylation in vivo. (,) ChIP-Seq analysis (below) of the binding of STAT5 and presence of H3K27me3 at the Igk locus () or Igh locus () in Rag2−/− pro-B cell populations expanded in vitro for 2 d in the presence of IL-7 (10 ng/ml), presented as smoothed tag density (where 'tag' indicates sequence 'read'). Data are representative of two experiments. () Igk locus (above), including the location of Vκ, Jκ, Eκi and Cκ gene segments (mm9 chromosome 6: 70,653,572–70,676,748) and the regions of H3K27me3 and STAT5 binding. () Igh locus (above), including the location of VH, DH, JH, Eμ and CH gene segments (mm9 chromosome 12: 114,496,979–117,248,165) and the regions of H3K27me3 and STAT5 binding. () Conserved new DNA sequence motifs identified among STAT5-bound regions. TF, transcription factor. () Common peaks obtained from ChIP-Seq analysis of STAT5 and H3K27me3. () Predicted tetrameric STAT5–binding motif determined from the gene-regulatory regions showing common peaks for STAT5 and H3K! 27me3 (Supplementary Tables 3 and 4). Letter size indicates nucleotide frequency in that position; number size indicates nucleotides present between two STAT5-binding motifs. * Figure 7: Trimethylation of H3K27 correlates with STAT5 target genes repressed throughout B cell development. () Heat map of genes targeted by both STAT5 and H3K27me3 (identified in Fig. 6), presented as change in expression (log2) as a function of B cell development and maturation relative to the pro-B cell stage (ImmGen Consortium). () EMBER analysis combining ChIP-Seq results for STAT5 and H3K27me3 with total mouse genome expression microarrays from the ImmGen Consortium, assessing predominant expression patterns of genes within 100 kb of STAT5 binding with or without coincidental H3K27me3 marks for all B cell developmental stages compared with expression at the pro-B cell stage. Coincidence required a minimum overlap of 2 bp. In some instances, more than one gene is within 100 kb of a peak; for example, 69 genes are within 100 kb of the 53 coincident peaks for STAT5 and H3K27me3. Change in mean expression (Activity (key)) is categorized as follows: --, > −3 s.d.; −, −1 s.d. to −3 s.d.; 0, −1 s.d. to +1 s.d.; +, 1 s.d. to 3 s.d.; ++, >3 s.d. (where s.d. is the sum of th! e two s.d. values calculated for experimental replicates). T1–T3, transitional B cell stages; GC, germinal center. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Mouse Genome Informatics * 1354193 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Department of Medicine, Section of Rheumatology and Gwen Knapp Center for Lupus and Immunology Research, University of Chicago, Chicago, Illinois, USA. * Malay Mandal, * Sarah E Powers, * Keith M Hamel & * Marcus R Clark * Department of Chemistry and James Franck Institute, University of Chicago, Chicago, Illinois, USA. * Mark Maienschein-Cline & * Aaron R Dinner * University of Chicago Comprehensive Cancer Center, University of Chicago, Chicago, Illinois, USA. * Elizabeth T Bartom * Department of Pathology, University of Chicago, Chicago, Illinois, USA. * Barbara L Kee Contributions M.M. designed, did and analyzed most of the experiments and prepared the first draft of the paper; S.E.P. assisted in the design and analysis of many experiments; M.M.-C. compared mRNA expression and ChIP-Seq data, assisted by K.M.H.; E.T.B. assisted in the ChIP-Seq analysis. B.L.K. provided E2A-specific reagents and contributed to the design of some experiments; A.R.D. oversaw the analysis of microarray and ChIP-Seq data; and M.R.C. oversaw the entire project and prepared the final manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Marcus R Clark Author Details * Malay Mandal Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah E Powers Search for this author in: * NPG journals * PubMed * Google Scholar * Mark Maienschein-Cline Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth T Bartom Search for this author in: * NPG journals * PubMed * Google Scholar * Keith M Hamel Search for this author in: * NPG journals * PubMed * Google Scholar * Barbara L Kee Search for this author in: * NPG journals * PubMed * Google Scholar * Aaron R Dinner Search for this author in: * NPG journals * PubMed * Google Scholar * Marcus R Clark Contact Marcus R Clark Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (10M) Supplementary Figures 1–4 and Tables 1–5 Additional data - The transcriptional regulators Id2 and Id3 control the formation of distinct memory CD8+ T cell subsets
- Nat Immunol 12(12):1221-1229 (2011)
Nature Immunology | Article The transcriptional regulators Id2 and Id3 control the formation of distinct memory CD8+ T cell subsets * Cliff Y Yang1 * J Adam Best1 * Jamie Knell1 * Edward Yang1 * Alison D Sheridan1 * Adam K Jesionek1 * Haiyan S Li2 * Richard R Rivera1 * Kristin Camfield Lind1 * Louise M D'Cruz1 * Stephanie S Watowich2, 3 * Cornelis Murre1 * Ananda W Goldrath1 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:1221–1229Year published:(2011)DOI:doi:10.1038/ni.2158Received10 August 2011Accepted06 October 2011Published online06 November 2011 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg During infection, naive CD8+ T cells differentiate into effector cells, which are armed to eliminate pathogens, and memory cells, which are poised to protect against reinfection. The transcriptional program that regulates terminal differentiation into short-lived effector-memory versus long-lived memory cells is not clearly defined. Through the use of mice expressing reporters for the DNA-binding inhibitors Id2 and Id3, we identified Id3hi precursors of long-lived memory cells before the peak of T cell population expansion or upregulation of cell-surface receptors that indicate memory potential. Deficiency in Id2 or Id3 resulted in loss of distinct CD8+ effector and memory populations, which demonstrated unique roles for these inhibitors of E-protein transcription factors. Furthermore, cytokines altered the expression of Id2 and Id3 differently, which provides insight into how external cues influence gene expression. View full text Figures at a glance * Figure 1: Expression of Id2-YFP and Id3-GFP reporters in CD8+ T cells during infection identifies distinct effector populations. () Flow cytometry analysis of the expression of Id2-YFP and Id3-GFP top row and of KLRG-1 and CD127 (bottom row) by CD45.1+ OT-I CD8+ T cells among splenocytes from CD45.2+ C57BL/6 mice that received Id2Y/+Id3G/+ CD45.1+ OT-I cells (2.5 × 104) 1 d before infection with VSV-OVA. Numbers in quadrants indicate percent cells in each throughout. () Quantification of Id3-GFP and Id2-YFP in Id2Y/+Id3G/+ OT-I cells responding to VSV-OVA infection, presented relative to expression in naive cells. () Flow cytometry analysis of the expression of Id2-YFP and Id3-GFP (top row) and KLRG-1 and CD127 (bottom row) by CD45.1+ OT-I CD8+ T cells among splenocytes from CD45.2+ C57BL/6 mice that received Id2Y/+Id3G/+ CD45.1+ OT-I cells (2.5 × 104) 1 d before infection with LM-OVA. () Time course of the induction of Id2 and Id3 mRNA during in vivo activation of CD45.1+ OT-I T cells sorted (to >98% purity) from the spleens of CD45.2+ C57BL/6 mice that received Id2Y/+Id3G/+ CD45.1+ OT-I cells (1 �! � 104) 1 d before infection with VSV-OVA, presented relative to expression in naive cells. () Flow cytometry (left) and quantification (right) of the expression of Id3-GFP and Id2-YFP by CD45.1+ OT-I T cells from CD45.2+ C57BL/6 mice that received 5 × 103, 5 × 104 or 5 × 105Id2Y/+Id3G/+ CD45.1+ OT-I cells 1 d before infection with VSV-OVA, assessed on day 7 of infection. *P < 0.05 and **P < 0.005 (two-tailed unpaired Student's t-test). Data are representative of six (,) or three (,) independent experiments with two to three (–) or two to four () mice per group or two experiments (; error bars, s.e.m.). * Figure 2: Expression of Id2-YFP and Id3-GFP during infection correlates with effector and memory precursor subsets. () Flow cytometry analysis (left) of the expression of KLRG-1 and CD127 (middle row) and of CD44 and CD62L (bottom row) by Id3-GFPhi (Id3hi) and Id3-GFPlo (Id3lo) donor cells (top) from CD45.2+ C57BL/6 mice that received Id2Y/+Id3G/+ CD45.1+ OT-I cells (5 × 104) 1 d before infection with VSV-OVA, assessed on day 7 of infection. Right, quantification of the expression of Id3-GFP and Id2-YFP (top row) and frequency of the KLRG-1hiCD127lo, KLRG-1loCD127hi and CD44hi CD62Lhi subsets (below). () Flow cytometry (top) and quantification (bottom) of the production of IL-2, IFN-γ and TNF by splenocytes restimulated for 6 h in vitro with OVA peptide, assessed on day 7 after VSV infection. Dashed lines, unstained cells. *P < 0.001 (two-tailed unpaired Student's t-test). Data are representative of four independent experiments with two to three mice per group (error bars, s.e.m.). * Figure 3: The Id3-GFPhi effector CD8+ T cell population includes long-lived memory precursor cells before expression of KLRG-1 or CD127. () Experimental design: CD45.2+ C57BL/6 mice received Id2Y/+Id3G/+ CD45.1+ OT-I cells (2.5 × 104) 1 d before infection with LM-OVA or VSV-OVA; on day 5 after infection, CD25−CD62L−CD127−KLRG-1− OT-I cells were sorted on the basis of Id3-GFP expression and equal numbers of Id3-GFPhi or Id3-GFPlo cells were adoptively transferred into infection-matched CD45.2+ C57BL/6 hosts. (,) Flow cytometry analysis of the expression of KLRG-1 and CD127 (left) by Id3-GFPlo and Id3-GFPhi CD45.1+ OT-I cells from spleen and liver on day 3 () and day 6 () after transfer of sorted cells after LM-OVA infection. Middle and right, frequency of KLRG-1hiCD127lo and KLRG-1loCD127hi subsets (middle) and total donor cells recovered from spleen and liver (right). () Incorporation of BrdU by sorted OT-I cells responding to VSV-OVA, transferred into infection-matched host given BrdU water for 2 d before collection of cells and analysis 4 d after transfer. () Kinetics of the population expansion of! Id3-GFPlo and Id3-GFPhi CD45.1+ OT-I CD8+ T cells among PBLs after transfer of OT-I cells responding to VSV-OVA into mice subsequently rechallenged with LM-OVA. *P < 0.05, **P < 0.005 and ***P < 0.001 (two-tailed unpaired Student's t-test). Data are representative of three independent experiments with two to three mice per group (,) or three to five mice () or two independent experiments with three mice per group (; error bars, s.e.m.). * Figure 4: Early Id3 expression correlates with memory potential. Gene-expression analysis of CD8+ effector cells in CD45.2+ mice that received Id2Y/+Id3G/+ CD45.1+ OT-I cells (2.5 × 104) 1 d before infection with VSV-OVA, followed by sorting of CD25−CD62L−CD127−KLRG-1−OT-I cells based on Id3-GFP expression on day 5 after infection. () Gene expression in Id3-GFPhi versus Id3-GFPlo CD8+ effector cells. Numbers in corners indicate genes with expression ≥1.5-fold higher in Id3-GFPhi cells (red) or 1.5-fold higher in Id3-GFPlo cells (blue). () 'Volcano' plot of the data in ; colors indicate genes upregulated more than twofold in CD127hi cells (red) or CD127lo cells (blue), and numbers indicate genes that correlate with Id3-GFPhi expression (right) or Id3-GFPlo expression (left). P values, χ2 test. () Gene expression in Id3-GFPhi versus Id3-GFPlo cells; green indicates E2A occupancy, identified by chromatin immunoprecipitation followed by deep sequencing. () Gene expression by effector (day 6) and memory (day 100) OT-I cells respond! ing to VSV-OVA infection; colors indicate genes upregulated (red) or downregulated (blue) ≥1.5-fold in Id3-GFPhi cells relative to their expression in Id3-GFPlo cells, and numbers indicate genes up- or downregulated in memory cells. P values, χ2 test. () Change in gene expression in Id3-GFPhi versus Id3-GFPlo cells; green indicates E2A occupancy. () Quantitative PCR analysis of mRNA in Id3-GFPhi cells, presented relative to expression in Id3-GFPlo cells. ND, not detected. Data are from two independent data sets (–; average) or are representative of two experiments (; average and s.e.m. of triplicates). * Figure 5: Id3 deficiency results in the defective formation of long-lived memory CD8+ T cells. () Flow cytometry analysis (top) and time course (bottom) of the population expansion of Id3+/+ (CD45.1+) and Id3G/G (CD45.1+CD45.2+) OT-I CD8+ T cells among PBLs from CD45.2+ mice that received equal numbers of CD44loId3+/+ CD45.1.2+ and Id3G/G CD45.1+ OT-I cells 1 d before infection with VSV-OVA. () Phenotype (top) and total number (bottom) of Id3+/+ CD45.1+ and Id3G/G CD45.1.2+ OT-I cells recovered from the spleen on day 60 after infection as in . () BrdU incorporation (top) and Bcl-2 expression (bottom) of Id3+/+ CD45.1+ and Id3G/G CD45.1.2+ OT-I cells from mice infected as in , followed by treatment of recipient mice for 7 d with BrdU in drinking water and recovery of cells from the spleen on day 80 after infection. () Flow cytometry (top) and quantification (bottom) of the production of IL-2, IFN-γ and TNF by splenocytes restimulated for 8 h in vitro with OVA peptide on day 80 after infection as in . Dashed lines, unstained cells. *P < 0.005 (two-tailed unpaired Stude! nt's t-test). Data are representative of two independent experiments with five to six mice per group (,; average s.e.m. in ) or one experiment with three mice per group (,; error bars, s.e.m. in ). * Figure 6: Id2-deficient CD8+ T cells upregulate Id3 and do not generate short-lived effector-memory cells. () Reporter expression in splenic antigen-specific CD8+ T cells on day 15 after infection of Id2Y/+Id3G/+, Id2Y/YId3G/+ and Id2Y/+Id3G/G fetal liver chimeras with LM-OVA. () Flow cytometry analysis of the expression of KLRG-1 and CD127 by Id2+/+ or Id2Y/Y splenic antigen-specific CD8+ T cells on day 15 after infection as in . *P < 0.005 and **P < 0.001 (two-tailed unpaired Student's t-test). Data are representative of four independent experiments with two to four mice per group () or three independent experiments with two to five mice per group (; error bars, s.e.m.). * Figure 7: Id3-GFP expression and Id2-YFP expression are inversely coregulated by cytokines. () Flow cytometry analysis (left) and quantification (right) of the expression of Id3-GFP and Id2-YFP by Id2Y/+Id3G/+ CD45.1+ OT-I cells cultured for 3–4 d with OVA peptide–pulsed APCs with cytokines (gray) or without cytokines (white; Control). () Expression of Id3-GFP and Id2-YFP by Id2Y/+Id3G/+ CD45.1+ OT-I cells adoptively transferred into CD45.2 C57BL/6 or IL-12-deficient mice, analyzed on day 15 after infection with VSV-OVA. () Flow cytometry analysis (left) and quantification (right) of Id2-YFP expression in Il2ra+/+ and Il2ra−/− cells from mixed chimeras infected with VSV-OVA, followed by analysis of antigen-specific splenic CD8+ T cells from the donor on day 12 of infection. () Sequence alignment of human and mouse genes encoding Id2 from the VISTA genome browser (left), and immunoprecipitation of chromatin (with anti-STAT4, anti-STAT5 or immunoglobulin G (IgG)) from wild type OT-I cells on day 7 of infection, followed by quantitative PCR analysis of input o! r precipitated DNA containing various binding sites (arrows; right). *P < 0.05, **P < 0.005 and ***P < 0.001 (two-tailed unpaired Student's t-test). Data are representative of four independent experiments with three replicates () or two independent experiments with four to five mice per group () or three to five chimeras () or are pooled from three independent experiments with five mice (; error bars, s.e.m.). Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE 32675 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Division of Biological Sciences, University of California San Diego, La Jolla, California, USA. * Cliff Y Yang, * J Adam Best, * Jamie Knell, * Edward Yang, * Alison D Sheridan, * Adam K Jesionek, * Richard R Rivera, * Kristin Camfield Lind, * Louise M D'Cruz, * Cornelis Murre & * Ananda W Goldrath * Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. * Haiyan S Li & * Stephanie S Watowich * The University of Texas Graduate School of Biomedical Sciences, Houston, Texas, USA. * Stephanie S Watowich Contributions C.Y.Y. designed and completed the majority of experiments, analyzed and interpreted data, and wrote the manuscript; A.D.S. and R.R.R. generated the reporter mouse lines; J.A.B., J.K., E.Y. and K.C.L. did experiments and discussed and interpreted results; A.K.J. provided technical assistance; H.S.L. and S.S.W. discussed results and provided advice; L.M.D. and C.M. discussed and interpreted results and wrote the manuscript; and A.W.G. directed the study, analyzed and interpreted results, and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Ananda W Goldrath Author Details * Cliff Y Yang Search for this author in: * NPG journals * PubMed * Google Scholar * J Adam Best Search for this author in: * NPG journals * PubMed * Google Scholar * Jamie Knell Search for this author in: * NPG journals * PubMed * Google Scholar * Edward Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Alison D Sheridan Search for this author in: * NPG journals * PubMed * Google Scholar * Adam K Jesionek Search for this author in: * NPG journals * PubMed * Google Scholar * Haiyan S Li Search for this author in: * NPG journals * PubMed * Google Scholar * Richard R Rivera Search for this author in: * NPG journals * PubMed * Google Scholar * Kristin Camfield Lind Search for this author in: * NPG journals * PubMed * Google Scholar * Louise M D'Cruz Search for this author in: * NPG journals * PubMed * Google Scholar * Stephanie S Watowich Search for this author in: * NPG journals * PubMed * Google Scholar * Cornelis Murre Search for this author in: * NPG journals * PubMed * Google Scholar * Ananda W Goldrath Contact Ananda W Goldrath Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–6 and Table 1 Additional data - Repression of the DNA-binding inhibitor Id3 by Blimp-1 limits the formation of memory CD8+ T cells
- Nat Immunol 12(12):1230-1237 (2011)
Nature Immunology | Article Repression of the DNA-binding inhibitor Id3 by Blimp-1 limits the formation of memory CD8+ T cells * Yun Ji1 * Zoltan Pos2, 3 * Mahadev Rao1 * Christopher A Klebanoff1 * Zhiya Yu1 * Madhusudhanan Sukumar1 * Robert N Reger1 * Douglas C Palmer1 * Zachary A Borman1 * Pawel Muranski1 * Ena Wang2, 3 * David S Schrump1 * Francesco M Marincola2, 3 * Nicholas P Restifo1 * Luca Gattinoni1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature ImmunologyVolume: 12,Pages:1230–1237Year published:(2011)DOI:doi:10.1038/ni.2153Received01 August 2011Accepted29 September 2011Published online06 November 2011 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The transcriptional repressor Blimp-1 promotes the differentiation of CD8+ T cells into short-lived effector cells (SLECs) that express the lectin-like receptor KLRG-1, but how it operates remains poorly defined. Here we show that Blimp-1 bound to and repressed the promoter of the gene encoding the DNA-binding inhibitor Id3 in SLECs. Repression of Id3 by Blimp-1 was dispensable for SLEC development but limited the ability of SLECs to persist as memory cells. Enforced expression of Id3 was sufficient to restore SLEC survival and enhanced recall responses. Id3 function was mediated in part through inhibition of the transcriptional activity of E2A and induction of genes regulating genome stability. Our findings identify the Blimp-1–Id3–E2A axis as a key molecular switch that determines whether effector CD8+ T cells are programmed to die or enter the memory pool. View full text Figures at a glance * Figure 1: Blimp-1 binds to the Id3 promoter and represses Id3 expression in effector CD8+ T cells. () Quantitative RT-PCR analysis of the expression of Prdm1 and Id3 mRNA in naive pmel-1 CD8+ T cells before (0) or 1–6 d after (horizontal axis) adoptive transfer into recipient wild-type mice infected with gp100-VV; results are presented relative to Actb mRNA (encoding β-actin). () Immunoblot analysis of Blimp-1 and Id3 in CD8+ T cells 0–8 d (above lanes) after stimulation with antibody to CD3 (anti-CD3), anti-CD28 and IL-2; β-actin serves as a loading control throughout. () Quantitative RT-PCR analysis of the expression of Prdm1 and Id3 in KLRG-1+ and KLRG-1− pmel-1 CD8+ T cells sorted 5 d after adoptive transfer into wild-type mice infected with gp100-VV; results are presented relative to Actb mRNA. () Immunoblot analysis of Blimp-1 and Id3 in KLRG-1+ and KLRG-1− pmel-1 CD8+ T cells obtained as in . () Amplification of the promoter regions of Id3 and Csf1 (nonspecific control) in chromatin immunoprecipitated from effector CD8+ T cells with anti-Blimp-1 (α-Blimp! -1) or in input DNA (Input (far left), control for equal starting material). α-IgG, antibody to immunoglobulin G (nonspecific control); H2O, water only; gDNA, genomic DNA. () Quantitative PCR analysis of the promoter regions of Id3 and Csf1 in chromatin immunoprecipitated with anti-IgG or anti-Blimp-1. NS, not significant; *P < 0.05 and **P < 0.001 (two-tailed t-test). Data are representative of two (,–) or four () independent experiments (error bars (,), s.e.m. of three samples). * Figure 2: Id3 is essential for the generation of CD8+ memory T cells. () Flow cytometry of pmel-1 Rag1−/−Id3+/+ and pmel-1 Rag1−/−Id3−/− T cells before (left) and after (Post-sort; right) sorting of naive CD8+ T cells, after gating on CD8+ cells. Numbers in bottom right quadrants indicate percent CD44−CD62L+ cells. () Flow cytometry analysis of the incorporation of BrdU into splenocytes 4 d after adoptive transfer of pmel-1 Rag1−/−Id3+/+ or pmel-1 Rag1−/−Id3−/− CD8+ T cells into wild-type mice infected with gp100-VV, followed by treatment of recipient mice with 1.5 mg BrdU 16 h before analysis. Numbers above bracketed lines indicate percent BrdU+ cells. () Flow cytometry of the expression of Ly5.2 by pmel-1 CD8+ T cells after adoptive transfer of 6 × 103 pmel-1 Rag1−/−Id3+/+ or pmel-1 Rag1−/−Id3−/− CD8+ T cells into wild-type mice infected with gp100-VV, assessed 0–32 d after infection (above plots). Numbers adjacent to outlined areas indicate percent Ly5.2+ T cells after gating on CD8+ cells. SSC, side! scatter. () Quantification of Ly5.2+ pmel-1 CD8+ T cells in , assessed 0–35 d after infection (horizontal axis). () Frequency of CD62L+ or KLRG-1+ pmel-1 Rag1−/−Id3+/+ or pmel-1 Rag1−/−Id3−/− CD8+ T cells after transfer into wild-type mice infected with gp100-VV, assessed 6 d after infection. () Ly5.2+ pmel-1 CD8+ T cells in the spleen, lymph nodes (LN) and lungs after adoptive transfer of 4 × 104 pmel-1 Rag1−/−Id3+/+ or pmel-1 Rag1−/−Id3−/− CD8+ T cell into wild-type mice infected with gp100-VV, assessed 30 d after infection. Each symbol represents an individual mouse; small horizontal lines indicate the mean (and s.e.m.). *P < 0.05, **P < 0.01 and ***P < 0.001 (two-tailed t-test). Data are representative of two independent experiments (error bars (,), s.e.m. of three to four samples). * Figure 3: Enforced expression of Id3 promotes the long-term survival of KLRG-1+ effector T cells. () Frequency of Thy-1.1+ cells (numbers above bracketed lines) among pmel-1 CD8+ T cells transduced with retrovirus expressing Id3–Thy-1.1 or Thy-1.1 alone. () Immunoblot analysis of pmel-1 CD8+ T cells transduced as in , probed with anti-Id3. () Flow cytometry of splenic T cells after adoptive transfer of 6 × 102 pmel-1 CD8+ T cells (transduced as in ) into wild-type mice infected with gp100-VV, assessed 4–34 d after infection (above plots). Numbers adjacent to outlined areas indicate percent Thy-1.1+ T cells after gating on CD8+ cells. () Abundance of Thy-1.1+ pmel-1 CD8+ T cells in the spleen after adoptive transfer of pmel-1 CD8+ T cells (transduced as in ) into wild-type mice infected with gp100-VV, assessed 0–35 d after infection (horizontal axis). (,). Frequency of KLRG-1+ () or CD62L+ () T cells among Thy-1.1+ pmel-1 CD8+ T cells as in . (,) Frequency of Thy-1.1+ pmel-1 CD8+ T cells producing IFN-γ or IL-2 after stimulation with a leukocyte-activation 'cockta! il', assessed 5 d () or 30 d () after adoptive transfer into wild-type mice infected with gp100-VV. *P < 0.05; **P < 0.01 and ***P < 0.001 (two-tailed t-test). Data are representative of five (,,), three (,,) or two (,) independent experiments (error bars (–), s.e.m. of three to four samples). * Figure 4: Peripheral tissues are enriched for CD8+ T cells overexpressing Id3. () Flow cytometry of T cells from spleen, lymph nodes and lungs after adoptive transfer of 3 × 105 pmel-1 CD8+ T cells (transduced as in Fig. 3a to express Thy-1.1 or Id3–Thy-1.1) into wild-type mice infected with gp100-VV, assessed 40 d after infection. Numbers adjacent to outlined areas indicate percent Thy-1.1+ T cells after gating on CD8+ cells. () Frequency of Thy-1.1+ pmel-1 CD8+ T cells in the spleen, lymph nodes and lungs of mice treated as in . () Flow cytometry of Thy-1.1+ pmel-1 CD8+ T cells from the spleen, lymph nodes and lungs of mice treated as in . Numbers in quadrants indicate percent KLRG-1+CD62L− cells (top left) or KLRG-1−CD62L+ cells (bottom right) after gating on Thy-1.1+ CD8+ cells. *P < 0.05 and **P < 0.01 (two-tailed t-test). Data are representative of two independent experiments (error bars (), s.e.m. of three samples). * Figure 5: CD8+ T cells overexpressing Id3 mediate enhanced secondary responses. () Flow cytometry of splenic T cells after adoptive transfer of 6 × 102 pmel-1 CD8+ T cells (transduced as in Fig. 3a to express Thy-1.1 or Id3–Thy-1.1) into wild-type mice infected with gp100-VV, followed by secondary challenge with gp100 fowlpox virus 30 d after primary infection, assessed 3–30 d after secondary infection (above plots). Numbers adjacent to outlined areas indicate percent Thy-1.1+ T cells after gating on CD8+ cells. () Abundance of Thy-1.1+ pmel-1 CD8+ T cells in the spleen, assessed 0–35 d after secondary infection as described in (horizontal axis). () Survival of wild-type mice challenged with 1 × 105 B16 melanoma cells 30 d after vaccination with gp100-VV with no adoptive transfer (No CD8+ T cells) or after adoptive transfer of pmel-1 CD8+ T cells transduced (as in Fig. 3a) to express Id3–Thy-1.1 or Thy-1.1. *P < 0.05 and **P < 0.001 (log-rank (Mantel-Cox) test). Data are representative of (,) or pooled from () two independent experiments (erro! r bars (), s.e.m. of three to seven samples). * Figure 6: Id3 does not affect Id2 expression in effector CD8+ T cells. () Quantitative RT-PCR analysis of Id2 mRNA in naive pmel-1 CD8+ T cells, before (0) or 1–6 d after (horizontal axis) adoptive transfer into wild-type recipient mice infected with gp100-VV; results are presented relative to Actb mRNA. () Immunoblot analysis of Id2 in KLRG-1+ or KLRG-1− pmel-1 CD8+ T cells sorted 5 d after adoptive transfer into wild-type mice infected with gp100-VV. () Quantitative RT-PCR analysis of Id2 mRNA in pmel-1 Rag1−/−Id3+/+ and pmel-1 Rag1−/−Id3−/− CD8+ T cells (left) or pmel-1 CD8+ T cells transduced (as in Fig. 3a) to express Id3–Thy-1.1 or Thy-1.1 (right), assessed 5 d after adoptive transfer into wild-type mice infected with gp100-VV; results are presented relative to Actb mRNA. Data are representative of two independent experiments (error bars (), s.e.m. of triplicates). * Figure 7: Id3 modulates the expression of genes encoding molecules involved in DNA replication and repair. (,) Heat map of genes with different expression in pmel-1 Rag1−/−Id3+/+ or pmel-1 Rag1−/−Id3−/− CD8+ T cells () or pmel-1 CD8+ T cells transduced (as in Fig. 3a) to express Id3–Thy-1.1 or Thy-1.1 (), sorted 5 d after adoptive transfer into wild-type mice infected with gp100-VV (>1.3-fold change in expression; false discovery rate, P < 0.05). Brackets (top) indicate hierarchical clustering. () Change in the expression of genes encoding molecules involved in the DNA-replication and DNA-repair network, showing expression in pmel-1 Rag1−/−Id3−/− CD8+ T cells or Id3–Thy-1.1+ pmel-1 CD8+ T cells relative to expression in pmel-1 Rag1−/−Id3+/+ or Thy-1.1+ control T cells, respectively. Data represent one experiment each with quadruplicates (,) or the combined analysis of two independent experiments (; error bars, s.e.m.). * Figure 8: Deletion of E2A results in more CD8+ memory T cell formation. () Gene-set enrichment analysis of genes overexpressed in Tcf3-deficient pre-B-cell lines relative to transcriptomes of pmel-1 Rag1−/−Id3−/− or pmel-1 Rag1−/−Id3+/+ CD8+ T cells (left) or pmel-1 CD8+ T cells transduced (as in Fig. 3a) to express Id3–Thy-1.1 or Thy-1.1 (right), sorted 5 d after adoptive transfer into wild-type mice infected with gp100-VV. Enrich, enrichment profile; Hits, genes in functional set; RMS, ranking metric score. () Electrophoretic mobility-shift assay of nuclear extracts of pmel-1 CD8+ T cells transduced (as in Fig. 3a) to express Thy-1.1 or Id3–Thy-1.1, incubated with biotin-labeled oligonucleotide probes containing E-box-binding sites (uE5) and/or unlabeled oligonucleotide probes (competitors) and probed with anti-E2A (α-E2A) or nonspecific antibody (Ab) to determine the specificity of shifted bands. () Abundance of Ly5.2+ pmel-1 CD8+ T cells in the spleen after adoptive transfer of 6 × 103 pmel-1 Tcf3flox/flox Cre-ERT2 CD8+ T c! ells (previously activated in vitro for 5 d with (TAM) or without (No TAM) tamoxifen, for the deletion of Tcf3) into wild-type mice infected with gp100-VV. *P < 0.05 and **P < 0.01 (one-tailed t-test). Data represent two separate experiments (left and right) with quadruplicate samples () or are representative of six () or two () independent experiments (error bars (), s.e.m. of three or four samples). Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE23568 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Center for Cancer Research, National Cancer Institute, US National Institutes of Health, Bethesda, Maryland, USA. * Yun Ji, * Mahadev Rao, * Christopher A Klebanoff, * Zhiya Yu, * Madhusudhanan Sukumar, * Robert N Reger, * Douglas C Palmer, * Zachary A Borman, * Pawel Muranski, * David S Schrump, * Nicholas P Restifo & * Luca Gattinoni * Infectious Disease and Immunogenetics Section, Department of Transfusion Medicine, Clinical Center, US National Institutes of Health, Bethesda, Maryland, USA. * Zoltan Pos, * Ena Wang & * Francesco M Marincola * Center for Human Immunology, US National Institutes of Health, Bethesda, Maryland, USA. * Zoltan Pos, * Ena Wang & * Francesco M Marincola Contributions Y.J., Z.P., M.R., C.A.K., Z.Y., M.S., R.N.R., D.C.P., Z.A.B. and L.G. did experiments; Y.J., Z.P., M.R., C.A.K., E.W. and L.G. analyzed experiments; Y.J., Z.P., P.M., D.S.S., F.M.M., N.P.R. and L.G. designed experiments; and Y.J., N.P.R. and L.G. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Nicholas P Restifo or * Luca Gattinoni Author Details * Yun Ji Search for this author in: * NPG journals * PubMed * Google Scholar * Zoltan Pos Search for this author in: * NPG journals * PubMed * Google Scholar * Mahadev Rao Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher A Klebanoff Search for this author in: * NPG journals * PubMed * Google Scholar * Zhiya Yu Search for this author in: * NPG journals * PubMed * Google Scholar * Madhusudhanan Sukumar Search for this author in: * NPG journals * PubMed * Google Scholar * Robert N Reger Search for this author in: * NPG journals * PubMed * Google Scholar * Douglas C Palmer Search for this author in: * NPG journals * PubMed * Google Scholar * Zachary A Borman Search for this author in: * NPG journals * PubMed * Google Scholar * Pawel Muranski Search for this author in: * NPG journals * PubMed * Google Scholar * Ena Wang Search for this author in: * NPG journals * PubMed * Google Scholar * David S Schrump Search for this author in: * NPG journals * PubMed * Google Scholar * Francesco M Marincola Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas P Restifo Contact Nicholas P Restifo Search for this author in: * NPG journals * PubMed * Google Scholar * Luca Gattinoni Contact Luca Gattinoni Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–10, Table 1 and Methods Additional data - Transcription factor c-Maf mediates the TGF-β-dependent suppression of IL-22 production in TH17 cells
- Nat Immunol 12(12):1238-1245 (2011)
Nature Immunology | Article Transcription factor c-Maf mediates the TGF-β-dependent suppression of IL-22 production in TH17 cells * Sascha Rutz1 * Rajkumar Noubade1 * Céline Eidenschenk1 * Naruhisa Ota1 * Wenwen Zeng1 * Yan Zheng1, 3 * Jason Hackney2 * Jiabing Ding1 * Harinder Singh1 * Wenjun Ouyang1 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:1238–1245Year published:(2011)DOI:doi:10.1038/ni.2134Received09 May 2011Accepted06 September 2011Published online16 October 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Interleukin 22 (IL-22), which is produced by cells of the TH17 subset of helper T cells and other leukocytes, not only enhances proinflammatory innate defense mechanisms in epithelial cells but also provides crucial protection to tissues from damage caused by inflammation and infection. In TH17 cells, transforming growth factor-β (TGF-β) regulates IL-22 and IL-17 differently. IL-6 alone induces T cells to produce only IL-22, whereas the combination of IL-6 and high concentrations of TGF-β results in the production of IL-17 but not IL-22 by T cells. Here we identify the transcription factor c-Maf, which is induced by TGF-β, as a downstream repressor of Il22. We found that c-Maf bound to the Il22 promoter and was both necessary and sufficient for the TGF-β-dependent suppression of IL-22 production in TH17 cells. View full text Figures at a glance * Figure 1: TGF-β suppresses IL-22 production in TH17 cells. (,) Expression of Il22 mRNA and IL-22 protein () or Il17a mRNA and IL-17A protein () in naive T cells stimulated with anti-CD3 and anti-CD28 and cultured for 3 d in the presence of recombinant IL-6 plus increasing amounts of recombinant TGF-β, or neutralizing antibody (nAb) to IL-6 or TGF-β (horizontal axes). Results for mRNA are presented relative to the expression of Rpl19 mRNA (encoding ribosomal protein L19). () Intracellular staining for IL-22 and IL-17A in naive T cells cultured for 2 d with APCs plus recombinant IL-6 and IL-23 in the presence of neutralizing anti-TGF-β (α-TGF-β; left), no anti-TGF-β or TGF-β (middle) or recombinant TGF-β (right) and restimulated with the phorbol ester PMA and ionomycin. Numbers in quadrants indicate percent cells in each, gated on CD4+ cells. Data are representative of four independent experiments (error bars (,), s.e.m.). * Figure 2: Inhibition of IL-22 by TGF-β is independent of IL-9, IL-10 and IL-21 but correlates with the induction of c-Maf. () ELISA of the production of IL-9, IL-10 and IL-21 by naive T cells stimulated with anti-CD3 and anti-CD28 and cultured for 3 d with recombinant IL-6 plus neutralizing anti-TGF-β or recombinant TGF-β. () ELISA of IL-22 production by naive T cells stimulated with anti-CD3 and anti-CD28 and cultured for 3 d with recombinant IL-6 and TGF-β with (+) or without (−) neutralizing anti-IL-9, anti-IL-10 or anti-IL-21. () Heat map of gene-expression profiling of naive T cells cultured under TH0 conditions, with recombinant IL-6 alone or with recombinant IL-6 and TGF-β; probes were ranked by the difference (log2 fold) between results obtained with recombinant IL-6 alone and those obtained with recombinant IL-6 plus TGF-β. Right, top 30 genes with the greatest change in expression after the addition of TGF-β. (,) Expression of Maf mRNA () and c-Maf protein () in naive T cells stimulated with anti-CD3 and anti-CD28 and cultured for 2 d in the presence of recombinant IL-6 and inc! reasing amounts of recombinant TGF-β (or neutralizing antibody). Results for mRNA are presented relative to the expression of Rpl19 mRNA. *P < 0.05 and **P < 0.01 (Student's t-test). Data are representative of two (,), four () or three () independent experiments (error bars (,,,), s.e.m.). * Figure 3: Inhibition of IL-22 production in T cells by c-Maf alone. (–) ELISA of the production of IL-22 (), IL-17A () or IL-10 () by naive T cells stimulated polyclonally with anti-CD3 and anti-CD28 and cultured for 24 h with recombinant IL-6 with (+) or without (−) recombinant TGF-β, followed by retroviral transduction of control vector (RV GFP) or expression vector for c-Maf (RV c-Maf) and another 48 h of culture, then isolation on the basis of GFP expression and restimulation for 24 h with anti-CD3 and anti-CD28. () Intracellular staining for IL-22 and IL-17A in naive T cells cultured for 24 h with anti-CD3 and anti-CD28 in the presence of APCs and recombinant IL-6 and IL-23 plus anti-TGF-β, followed by retroviral transduction of control vector or c-Maf and culture for another 48 h, then restimulation with PMA and ionomycin. Numbers in quadrants indicate percent cells in each, gated on CD4+GFP+ cells. () Intracellular staining for IL-22 in naive T cells cultured with anti-CD3 and anti-CD28 and recombinant IL-6 plus neutralizing ant! i-TGF-β, followed by retroviral transduction of control vector or c-Maf and culture for another 48 h, then restimulation with PMA and ionomycin. Numbers in quadrants indicate percent IL-22+ cells among GFP− cells (left) or GFP+ cells (right), gated on CD4+ cells. *P < 0.001 (Student's t-test). Data representative of three independent experiments (error bars (–), s.e.m.). * Figure 4: TGF-β-mediated suppression of IL-22 requires c-Maf. (,) Expression of Maf mRNA () or c-Maf protein () in naive T cells transfected with no siRNA (−), control siRNA (Ctrl) or siRNA targeting c-Maf (c-Maf) and cultured for 24 h or 48 h () or 24 h () with anti-CD3 and anti-CD28 plus recombinant IL-6 and TGF-β. Results for mRNA are presented relative to the expression of Rpl19 mRNA. (–) ELISA of the production of IL-22 (), IL-17A () or IL-10 () in naive T cells transfected with siRNA as in , and cultured for 72 h with recombinant IL-6 alone (−) or in combination with recombinant TGF-β (+). *P < 0.05 and **P < 0.001 (Student's t-test). Data are representative of four (,–) or two () independent experiments (error bars (,–), s.e.m.). * Figure 5: TGF-β and c-Maf do not repress the expression of RORγt or BATF. () Kinetics of the expression of Maf, Ahr, Rorc and Batf in naive T cells stimulated polyclonally with anti-CD3 and anti-CD28 and cultured with recombinant IL-6 or TGF-β alone or in combination; results are presented relative to the expression of Rpl19 mRNA. () Immunoblot analysis of AhR, RORγt and BATF in naive T cells stimulated with anti-CD3 and anti-CD28 and cultured for 2 d in the presence of recombinant IL-6 and increasing amounts of recombinant TGF-β (or neutralizing antibody). () Expression of Ahr, Rorc and Batf mRNA in naive T cells after retroviral transduction of control vector or vector encoding c-Maf and culture for 3 d with recombinant IL-6 plus anti-TGF-β (transduced cells isolated as in Fig. 3a–c); results are presented relative to the expression of Rpl19 mRNA. (,) ELISA of IL-22 in naive T cells stimulated with anti-CD3 and anti-CD28 and cultured for 3 d with recombinant IL-6 plus anti-TGF-β, with retroviral transduction (at 24 h of culture) of contro! l vector or vector encoding RORγt () or BATF () alone or in combination with c-Maf (horizontal axes), followed by isolation on the basis of the expression of GFP and/or human CD4 and restimulation for 24 h with anti-CD3 and anti-CD28. *P < 0.01 and **P < 0.001 (Student's t-test). Data are representative of one (), two () or three (–) independent experiments (error bars (,–), s.e.m.). * Figure 6: High expression of IL-22 does not require AhR. (,) ELISA of IL-22 in naive T cells stimulated with anti-CD3 and anti-CD28 and cultured for 3 d with recombinant IL-6 plus recombinant TGF-β (,) or in the absence of TGF-β (addition of neutralizing antibody; ,) in the presence of increasing concentrations of the AhR antagonist CH-223191 (,) or the AhR agonist FICZ (,). Data are representative of three independent experiments (mean ± s.e.m.). * Figure 7: Binding of c-Maf to a motif in the proximal Il22 promoter. () Putative c-Maf-binding sites in the proximal Il22 promoter (top; positions relative to ATG start site): −3942, 5′-TAACTTTTACTAAGCACCCCA-3′; −3504, 5′-AAAGTCTGAATCACTAAGCTT-3′; −2642: 5′-CTTCCGTGTGTCATAGTCTCC-3′; −2595: 5′-AAAAAATTACAAAGCAATTTA-3′; −511: 5′-AGCTATTGAGTCAGCGTTTTG-3′. Bottom, regions covered by chromatin-immunoprecipitation analysis; middle, sequence of overlapping binding motif for c-Maf and AP-1 at position −511. () EMSA of nuclear extracts of 293T cells overexpressing c-Maf, assessed with a probe covering the putative c-Maf motif at position −511: lane 1, probe only; lane 2, nuclear extract alone; lane 3, nuclear extract plus unlabeled probe (100× excess); lane 4: nuclear extract plus anti-Maf; lane 5: nuclear extract plus isotype-matched control antibody. () Chromatin-immunoprecipitation analysis of two regions in the Il22 promoter (, bottom) in nuclear extracts of naive T cells cultured for 48 h with recombinant IL-6 i! n the presence (TGF-β) or absence (α-TGF-β) of recombinant TGF-β, precipitated with anti-c-Maf or isotype-matched control antibody. () EMSA of nuclear extracts of 293T cells overexpressing BATF, assessed with a probe as in : lanes 1–3,5 as in ; lane 4: nuclear extract plus anti-BATF. () EMSA of nuclear extracts of naive T cells stimulated polyclonally for 22 h with anti-CD3 and anti-CD28 and cultured with recombinant IL-6 alone (left) or in combination with recombinant TGF-β (right), assessed with a probe as in : lane 1, probe only; lanes 2,6, nuclear extract alone; lanes 3–9, nuclear extract plus anti-Maf (lanes 3,7), anti-BATF (lanes 4,8) or isotype-matched control antibody (lanes 5,9). () EMSA of nuclear extracts of 293T cells overexpressing BATF and c-Maf, assessed with a probe as in : lanes 1–3 as in ; lanes 4–6, nuclear extract plus anti-Maf (lane 4), anti-BATF (lane 5) or isotype-matched control antibody (lane 6). Data are representative of two (,–) or! three () independent experiments. * Figure 8: Repressor activity of c-Maf in the regulation of IL-22. () Domain structures of full-length c-Maf and c-Maf truncation mutants lacking the transactivation domain (TA; c-Maf(dTA)), the DNA-binding domain (DB; c-Maf(dDB)) or the dimerization domain (DD; c-Maf(dDD)). H, hinge region; numbers indicate amino acid positions. (–) ELISA of IL-22 (), IL-10 () and IL-17A () in naive T cells stimulated with anti-CD3 and anti-CD28, cultured with recombinant IL-6 and anti-TGF-β and transduced with retrovirus expressing full-length or truncated c-Maf (as in ) or vector control, isolated at 72 h of culture on the basis of GFP expression and restimulated for 24 h with anti-CD3 and anti-CD28. *P < 0.05, **P < 0.01 and ***P < 0.001 (Student's t-test). Data are representative of three independent experiments (error bars, s.e.m.). Author information * Abstract * Author information * Supplementary information Affiliations * Department of Immunology, Genentech, South San Francisco, California, USA. * Sascha Rutz, * Rajkumar Noubade, * Céline Eidenschenk, * Naruhisa Ota, * Wenwen Zeng, * Yan Zheng, * Jiabing Ding, * Harinder Singh & * Wenjun Ouyang * Bioinformatics & Computational Biology, Genentech, South San Francisco, California, USA. * Jason Hackney * Present address: Target Discovery & Validation, Novo Nordisk Inflammation Research Center, Seattle, Washington, USA. * Yan Zheng Contributions S.R. did most of the experiments and analyzed the data; R.N. contributed to Figures 2, 4 and 5 and Supplementary Figure 4; C.E. contributed to Figures 2 and 5 and Supplementary Figure 1; W.Z. and H.S. contributed to Figure 7; Y.Z. contributed to Figures 1 and 2; N.O. and J.D. cloned c-Maf and RORγt constructs; J.H. analyzed Affymetrix data; W.O. devised and planned the project; and S.R. and W.O. wrote the manuscript. Competing financial interests All authors are employees of Genentech. Corresponding author Correspondence to: * Wenjun Ouyang Author Details * Sascha Rutz Search for this author in: * NPG journals * PubMed * Google Scholar * Rajkumar Noubade Search for this author in: * NPG journals * PubMed * Google Scholar * Céline Eidenschenk Search for this author in: * NPG journals * PubMed * Google Scholar * Naruhisa Ota Search for this author in: * NPG journals * PubMed * Google Scholar * Wenwen Zeng Search for this author in: * NPG journals * PubMed * Google Scholar * Yan Zheng Search for this author in: * NPG journals * PubMed * Google Scholar * Jason Hackney Search for this author in: * NPG journals * PubMed * Google Scholar * Jiabing Ding Search for this author in: * NPG journals * PubMed * Google Scholar * Harinder Singh Search for this author in: * NPG journals * PubMed * Google Scholar * Wenjun Ouyang Contact Wenjun Ouyang Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (561K) Supplementary Figures 1–13 and Tables 1–2 Additional data
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