Latest Articles Include:
- Celebrating 25 years of NF-κB
- Nat Immunol 12(8):681 (2011)
Article preview View full access options Nature Immunology | Editorial 25 YEARS OF NF-κB Focus issue: August 2011 Volume 12, No 8 * * Contents * Editoral * Overview * Reviews * Historical Commentary Celebrating 25 years of NF-κB Journal name:Nature ImmunologyVolume: 12,Page:681Year published:(2011)DOI:doi:10.1038/ni0811-681Published online19 July 2011 Few proteins have had as profound an influence on immunity and biology as the transcription factor NF-κB. 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 - NF-κB is 25
- Nat Immunol 12(8):683-685 (2011)
Article preview View full access options Nature Immunology | Overview 25 YEARS OF NF-κB Focus issue: August 2011 Volume 12, No 8 * * Contents * Editoral * Overview * Reviews * Historical Commentary NF-κB is 25 * David Baltimore1Journal name:Nature ImmunologyVolume: 12,Pages:683–685Year published:(2011)DOI:doi:10.1038/ni.2072Published online19 July 2011 NF-κB-mediated inflammatory biology can be formulated as the following five states: latency, induction, response, resolution and pathology. The first four involve carefully tuned molecular processes; pathology is the loss of control. 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. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Division of Biology, California Institute of Technology, Pasadena, California, USA. * David Baltimore Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * David Baltimore Author Details * David Baltimore Contact David Baltimore Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - The origins of NF-κB
- Nat Immunol 12(8):686-688 (2011)
Article preview View full access options Nature Immunology | Historical Commentary 25 YEARS OF NF-κB Focus issue: August 2011 Volume 12, No 8 * * Contents * Editoral * Overview * Reviews * Historical Commentary The origins of NF-κB * Ranjan Sen1Journal name:Nature ImmunologyVolume: 12,Pages:686–688Year published:(2011)DOI:doi:10.1038/ni.2071Published online19 July 2011 Twenty-five years after its identification, the transcription factor NF-κB continues to attract intense effort from a large and diverse research community. Ranjan Sen offers a personal account of the discovery of NF-κB. 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. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Ranjan Sen is in the Laboratory of Molecular Biology and Immunology, National Institute on Aging, Baltimore, Maryland, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Ranjan Sen Author Details * Ranjan Sen Contact Ranjan Sen Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Hierarchies of NF-κB target-gene regulation
- Nat Immunol 12(8):689-694 (2011)
Nature Immunology | Review 25 YEARS OF NF-κB Focus issue: August 2011 Volume 12, No 8 * * Contents * Editoral * Overview * Reviews * Historical Commentary Hierarchies of NF-κB target-gene regulation * Stephen T Smale1Journal name:Nature ImmunologyVolume: 12,Pages:689–694Year published:(2011)DOI:doi:10.1038/ni.2070Published online19 July 2011 Abstract * Abstract * Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Members of the NF-κB family of transcription factors function as dominant regulators of inducible gene expression in almost all cell types in response to a broad range of stimuli, with particularly important roles in coordinating both innate and adaptive immunity. This review summarizes the present knowledge and recent progress toward elucidating the numerous regulatory layers that confer target-gene selectivity in response to an NF-κB-inducing stimulus. View full text Figures at a glance * Figure 1: Contributors to the selectivity of the NF-κB response. The selectivity of the NF-κB response is regulated by many events that take place during the development of a responsive cell type and by a broad range of events that act after stimulation. * Figure 2: Enhancers for NF-κB target genes may acquire competence for activation at early stages of development. Events that seem to occur at enhancers for NF-κB target genes during development are presented here. Enhancers for some inducible genes seem to be associated with transcription factors in pluripotent cells, which may keep CpG dinucleotides in an unmethylated state and serve as placeholders during the earliest stages of development. During early stages of development, key transcription factors involved in lineage commitment, specification or development, such as PU.1 in cells of the myeloid and B lineages, seem to bind the enhancers and induce local chromatin changes (histone H3K4me1 and nucleosome repositioning) that may confer competence for transcriptional activation in differentiated cells. As the differentiated cell responds to a stimulus, NF-κB and other inducible transcription factors bind the enhancer and recruit essential coactivators, such as p300. The enhancer complex is then thought to interact with the gene's promoter, which also binds constitutive, lineage-spe! cific and inducible transcription factors, including NF-κB, thereby promoting the cascade of events that culminates in transcription initiation and elongation. ESC, embryonic stem cell; MeCpG, methylated CpG. Author information * Abstract * Author information Affiliations * Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, USA. * Stephen T Smale Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Stephen T Smale Author Details * Stephen T Smale Contact Stephen T Smale Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Crosstalk in NF-κB signaling pathways
- Nat Immunol 12(8):695-708 (2011)
Nature Immunology | Review 25 YEARS OF NF-κB Focus issue: August 2011 Volume 12, No 8 * * Contents * Editoral * Overview * Reviews * Historical Commentary Crosstalk in NF-κB signaling pathways * Andrea Oeckinghaus1 * Matthew S Hayden1 * Sankar Ghosh1 * Affiliations * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:695–708Year published:(2011)DOI:doi:10.1038/ni.2065Published online19 July 2011 Abstract * Abstract * Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg NF-κB transcription factors are critical regulators of immunity, stress responses, apoptosis and differentiation. A variety of stimuli coalesce on NF-κB activation, which can in turn mediate varied transcriptional programs. Consequently, NF-κB-dependent transcription is not only tightly controlled by positive and negative regulatory mechanisms but also closely coordinated with other signaling pathways. This intricate crosstalk is crucial to shaping the diverse biological functions of NF-κB into cell type– and context-specific responses. View full text Figures at a glance * Figure 1: Canonical and noncanonical pathways of NF-κB activation. Under resting conditions, NF-κB dimers are bound to inhibitory IκB proteins, which sequester inactive NF-κB complexes in the cytoplasm. Stimulus-induced degradation of IκB proteins is initiated through phosphorylation by the IκB kinase (IKK) complex, which consists of two catalytically active kinases, IKKα and IKKβ, and the regulatory subunit IKKγ (NEMO). Phosphorylated IκB proteins are targeted for ubiquitination and proteasomal degradation, which thus releases the bound NF-κB dimers so they can translocate to the nucleus. NF-κB signaling is often divided into two types of pathways. The canonical pathway (left) is induced by most physiological NF-κB stimuli and is represented here by TNFR1 signaling. Stimulation of TNFR1 leads to the binding of TRADD, which provides an assembly platform for the recruitment of FADD and TRAF2. TRAF2 associates with RIP1 for IKK activation. In the canonical pathway (right), IκBα is phosphorylated in an IKKβ- and NEMO-dependent m! anner, which results in the nuclear translocation of mostly p65-containing heterodimers. Transcriptional activity of nuclear NF-κB is further regulated by PTM. In contrast, the noncanonical pathway, induced by certain TNF family cytokines, such as CD40L, BAFF and lymphotoxin-β (LT-β), involves IKKα-mediated phosphorylation of p100 associated with RelB, which leads to partial processing of p100 and the generation of transcriptionally active p52-RelB complexes. IKKα activation and phosphorylation of p100 depends on NIK, which is subject to complex regulation by TRAF3, TRAF2 and additional ubiquitin ligases. LT-βR, receptor for lymphotoxin-β. * Figure 2: TRAF- and RIP1-dependent signaling pathways. () TRAF-dependent signaling pathways. TRAFs function downstream of many various receptors and promote the activation of AP-1 and NF-κB transcription factors. Also, several receptors can use more than one TRAF protein for signal transduction, which allows combinatorial specification of signaling outcomes. The function of TRAF2 and TRAF5 is best characterized in TNFR1 signaling, whereas TRAF6 and TRAF3 have been extensively studied in IL-1R or TLR signaling and in noncanonical NF-κB signaling, respectively. Each receptor and the signaling pathway(s) it induces are in a similar color. In addition to its role in noncanonical NF-κB signaling (green), TRAF3 has been demonstrated to be critical for virus-induced activation of IRF3-IRF7 and interferon production (yellow). TRAF2 is involved in signaling downstream of CD40 or the BAFF receptor BAFF-R through the regulation of TRAF3 stability and activation of AP-1 and NF-κB. TRAF2 and TRAF5 mediate canonical activation of NF-κB a! nd AP-1 in response to TNF and other proinflammatory cytokines (blue). Downstream of IL-1R and TLR, this role is exerted by TRAF6 (orange). After engagement of TLR1, TLR2 or TLR4, TRAF6 also translocates to mitochondria, where it binds to ECSIT to induce mitochondrial ROS (mROS) and enhance bacterial killing. In osteoclasts, TRAF6 has also been shown to function in signaling via the TRANCE receptor TRANCE-R by mediating activation of c-Src (purple). In addition, TRAF2 has been shown to inhibit IL-4 and T helper type 2 differentiation of T cells by negatively regulating the NFAT-interacting protein NIP45 (gray). () RIP1-dependent signaling pathways. Through its involvement in the regulation of survival (Complex I), apoptosis (Complex II) and necroptosis (Necrosome), RIP1 is positioned at the center of cell-fate 'decisions'. After stimulation with TNF, rapid assembly of complex I (containing TRADD, RIP1 and TRAF2) occurs at the receptor, which triggers NF-κB activation throu! gh recruitment of the IKK complex. In the course of signal tra! nsduction, TRADD-RIP1-TRAF2 dissociates from the receptor, binding FADD and caspases to induce apoptosis. The deubiquitinase CYLD has been demonstrated to promote apoptosis and/or necroptosis by enhancing the RIP1-FADD interaction, which suggests that the ubiquitination status of RIP1 may 'tune' its activity in different pathways. When caspase activation is inhibited, such as during certain viral infections, RIP1 acts with RIP3 to induce necroptosis. RIP1-RIP3 transphosphorylation leads to RIP3-dependent production of ROS, which contributes to necroptotic cell death. Furthermore, RIP1 has been suggested to be involved in activation of the PI(3)K-Akt pathway through NF-κB-independent downregulation of PTEN and to influence EGFR expression through its action as a negative regulator of the transcription factor Sp-1. Bad, Bcl-xL–Bcl-2–associated death promotor. * Figure 3: NF-κB-independent functions of IKK complex subunits. () NF-κB-independent IKKβ signaling. After T-loop phosphorylation, IKKβ activation occurs by trans-autophosphorylation or an IKK kinase (IKK-K). Inhibitory phosphorylation of IKKβ may also occur in certain settings. Additionally, phosphorylation of IKKβ by the IKK-related kinases TBK1 and IKKε has been shown to modulate IKK activation. Phosphorylation of NBD has also been proposed to impede activation of IKKβ. O-GlcNAc modification of IKKβ, which is repressed by p53, may augment IKK activity. IKKβ phosphorylates many substrates in addition to IκB proteins, in general promoting antiapoptotic and proinflammatory processes. Through inhibitory phosphorylation of TSC1 and consequent mTOR activation, IKKβ regulates tumor progression and inflammation-mediated angiogenesis. Other pro-proliferative or antiapoptotic targets include the tumor suppressor Foxo3a, as well as p105 and Dok1, through which IKKβ affects MAPK activation. Phosphorylation of IRS-1 inhibits insulin si! gnal transduction, which affects the development of insulin resistance. Finally, IKKβ phosphorylates the t-SNARE SNAP23 to regulate degranulation in mast cells. () NF-κB-independent IKKα signaling. Because of its nuclear-localization signal, IKKα can target both cytosolic and nuclear proteins. In the nucleus, IKKα modulates gene expression through histone H3 modification and regulation of the recruitment of histone deacetylase (HDAC). IKKα has also been suggested to directly phosphorylate p65 and c-Rel, triggering their turnover and removal from the promoter to terminate the canonical NF-κB response and limit inflammation. In addition, IKKα is also closely intertwined with the regulation of cyclin D1 through transcriptional as well as post-translational processes and can affect interferon production through context-dependent phosphorylation of IRF5 and IRF7. IKKα also exerts kinase activity-independent functions in development. () NF-κB-independent NEMO-dependent ! signaling. Evidence for NF-κB-independent roles of NEMO is mo! re limited than that for IKKα or IKKβ, and for many of the described NF-κB-independent functions of IKKα and IKKβ, it remains unclear whether NEMO is also required. However, the role of NEMO in NF-κB activation in response to DNA damage, in which NEMO translocates to the nucleus and becomes phosphorylated by the kinase ATM, demonstrates that NEMO may function independently of IKKα and IKKβ. NF-κB-independent regulation of the activity IRF3 and IRF7 and of HIF-2α and the activation of MAPKs by NEMO has also been described. Finally, activation of apoptotic pathways counteracts NF-κB signaling via caspase-dependent cleavage of NEMO, which results in a signaling-deficient truncated protein. * Figure 4: Crosstalk mechanisms involving NF-κB subunits. The transcriptional activity of NF-κB subunits is subject to regulation via a variety of PTMs, including phosphorylation, acetylation and methylation. As PTMs have the potential to modulate the interaction of NF-κB with coactivators, corepressors and IκB proteins, as well as the binding of NF-κB to cooperatively functioning, heterologous transcription factors, they represent a major determinant of selectivity in the induced gene expression signature and are thought to be critical for integration of non-NF-κB pathways and contextual tailoring of the transcriptional response. The formation of NF-κB-containing enhanceosomes at the promoters of target genes requires cooperative action between transcription factors, which facilitates both the integration and regulation of non-NF-κB pathways. NF-κB activity also affects heterologous pathways, such as the Jnk and p53 pathways, through transcriptional regulation of signaling pathway components. Gadd45β, growth-arrest and DN! A damage–inducible protein; MnSod, manganese superoxide dismutase; Fhc, ferritin heavy chain; XIAP, X-linked inhibitor of apoptosis protein. Author information * Abstract * Author information Affiliations * Department of Microbiology & Immunology, Columbia University, College of Physicians & Surgeons, New York, New York, USA. * Andrea Oeckinghaus, * Matthew S Hayden & * Sankar Ghosh Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Sankar Ghosh Author Details * Andrea Oeckinghaus Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew S Hayden Search for this author in: * NPG journals * PubMed * Google Scholar * Sankar Ghosh Contact Sankar Ghosh Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Return to homeostasis: downregulation of NF-κB responses
- Nat Immunol 12(8):709-714 (2011)
Nature Immunology | Review 25 YEARS OF NF-κB Focus issue: August 2011 Volume 12, No 8 * * Contents * Editoral * Overview * Reviews * Historical Commentary Return to homeostasis: downregulation of NF-κB responses * Jürgen Ruland1, 2Journal name:Nature ImmunologyVolume: 12,Pages:709–714Year published:(2011)DOI:doi:10.1038/ni.2055Published online19 June 2011 Abstract * Abstract * Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Activation of NF-κB transcription factors by receptors of the innate or adaptive immune system is essential for host defense. However, after danger is eliminated, NF-κB signaling needs to be tightly downregulated for the maintenance of tissue homeostasis. This review highlights key negative regulatory principles that affect the amount, localization or conformational properties of NF-κB-activating proteins to attenuate the NF-κB response. These mechanisms are needed to prevent inflammation, autoimmune disease and oncogenesis. View full text Figures at a glance * Figure 1: IκBα- and A20-dependent negative feedback loops in the canonical NF-κB pathway. Canonical activation of NF-κB by TNF is mediated via the recruitment of TRADD, TRAF2 and cIAP1 and cIAP2, together with RIP1, to the receptor. K63-linked polyubiquitination of RIP1 results in further recruitment of the IKK complex to the activated receptor and IKK activation. IKK phosphorylates IκBα, which triggers its K48-linked polyubiquitination and subsequent degradation by the proteasome. These events allow translocation of NF-κB into the nucleus and activation of gene transcription. Strongly induced NF-κB target genes include those that encode the negative regulators IκBα and A20. After protein synthesis, IκBα binds to nuclear NF-κB complexes and inhibits their function by shuttling NF-κB back into the cytosol. In addition, the ubiquitin-editing enzyme A20 deubiquitinates RIP1 and IKKγ, which leads to the disassembly of proximal NF-κB-activating complexes and shutting down of the inflammatory response. * Figure 2: Dominant-negative adaptors. TLR4 signaling activates the canonical IKK complex via MyD88-dependent and TRIF-dependent mechanisms. MyD88 assembles complexes that contain IRAK kinases together with TRAF6, TAB2, TAB3 and TAK1. TRIF can directly recruit TRAF6 and recruit TAB2, TAB3 and TAK1. The active NF-κB pathway subsequently induces expression of the alternative MyD88 splice product MyD88s, the kinase-inactive IRAK family member IRAK-M and the negative regulatory adaptor molecule SARM. These dominant-negative factors presumably affect the stability of the IKK-activating complexes. * Figure 3: Interference with NF-κB function in the nucleus. () After being phosphorylated by IKKα, PIAS1 can interfere with the binding of RelA–NF-κB complexes to DNA. (,) The COMMD1–SOCS1–Cullin-2 E3 ubiquitin ligase complex () and the E3 ligase PDLIM2 () terminate RelA–NF-κB responses in the nucleus by inducing K48-linked polyubiquitination of RelA, which results in proteasomal degradation of RelA. In addition, PDLIM2 () promotes the relocalization of RelA to transcriptionally silent promyelocytic leukemia nuclear bodies (PML body). * Figure 4: Negative regulation of alternative NF-κB signaling. Engagement of alternative NF-κB signaling by TNF superfamily receptors, such as CD40, induces NIK stabilization and subsequent IKKα-dependent phosphorylation of p100, which results in p100 processing and translocation of RelB-p52 dimers to the nucleus. Key negative regulatory mechanisms depend on NIK proteolysis. Under unstimulated conditions, the stability of NIK protein is negatively regulated by TRAF3, TRAF2 and cIAP1 and cIAP2, which control K48-linked polyubiquitination of NIK, resulting in proteasomal degradation. After receptor ligation and signal initiation, IKKα phosphorylates not only p100 but also NIK in a feedback loop to promote subsequent NIK destabilization through still-uncharacterized pathways that also involve the proteasome. Author information * Abstract * Author information Affiliations * Institut für Molekulare Immunologie, Klinikum rechts der Isar, Technische Universität München, Munich, Germany. * Jürgen Ruland * Laboratory of Signaling in the Immune System, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany. * Jürgen Ruland Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Jürgen Ruland Author Details * Jürgen Ruland Contact Jürgen Ruland Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Inflammation meets cancer, with NF-κB as the matchmaker
- Nat Immunol 12(8):715-723 (2011)
Nature Immunology | Review 25 YEARS OF NF-κB Focus issue: August 2011 Volume 12, No 8 * * Contents * Editoral * Overview * Reviews * Historical Commentary Inflammation meets cancer, with NF-κB as the matchmaker * Yinon Ben-Neriah1 * Michael Karin2 * Affiliations * Corresponding authorsJournal name:Nature ImmunologyVolume: 12,Pages:715–723Year published:(2011)DOI:doi:10.1038/ni.2060Published online19 July 2011 Abstract * Abstract * Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Inflammation is a fundamental protective response that sometimes goes awry and becomes a major cofactor in the pathogenesis of many chronic human diseases, including cancer. Here we review the evolutionary relationship and opposing functions of the transcription factor NF-κB in inflammation and cancer. Although it seems to fulfill a distinctly tumor-promoting role in many types of cancer, NF-κB has a confounding role in certain tumors. Understanding the activity and function of NF-κB in the context of tumorigenesis is critical for its successful taming, an important challenge for modern cancer biology. View full text Figures at a glance * Figure 1: Hypothetical model for the generation of colorectal tumors as a result of interplay among intestinal crypt microflora NF-κB activation, and mutatagenesis mechanisms in intestinal stem cell. Encounters of bacteria with stem cells and their niche (composed mainly of Paneth-like CD24+ cells35 (granule-filled cells)) at the bottom of the colonic crypts may induce activation of NF-κB in Paneth cells and stem cells. NF-κB activation results in the release of cytokines and the production of ROS and nitric oxide (NO), as well as the upregulation of activation-induced cytidine deaminase (AID) in the stem cells149, which all results in stem cell mutagenesis. Further activation of NF-κB in tumor-initiating cells supports their survival. () A normal colonic crypt with CD24+ cells and stem cells (thin columnar cells) at the bottom. () Bacteria-loaded crypt, which results in NF-κB activation in CD24+ cells and stem cells (red nuclei) and the release of cytokines and enzymes. () NF-κB-mediated production of ROS and nitric oxide, which results in mutagenesis of the gene encoding adenomatosis polyposis coli (APC) in an intestinal stem cell and adenoma growth34. iNOS, induc! ible nitric oxide synthase. () NF-κB-induced upregulation of activation-induced cytidine deaminase (AID), which results in mutagenesis of the gene encoding p53, dysplasia and invasion150, typical of colorectal cancer associated with inflammatory bowel disease151. * Figure 2: Pro- and anti-inflammatory functions of NF-κB and their relationship to tumorigenesis. () Activation of NF-κB downstream of TNF receptors (TNFRs), TLRs and the IL-1 receptor (IL-1R) results in the induction of genes encoding prosurvival and pro-proliferative molecules, cytokines and chemokines. The products of such genes contribute to inflammation and tumor development. However, NF-κB activation also promotes tissue integrity through the induction of genes encoding barrier molecules, protease inhibitors and antioxidants. Such molecules can suppress tumor development. By inducing the expression of antioxidant proteins, NF-κB also prevents the accumulation of pro-tumorigenic ROS and can induce DNA damage and genomic instability and lead to the activation of pro-tumorigenic transcription factors, such as STAT3 and AP-1. () A particularly intriguing NF-κB target gene encodes pro-IL-1β, which is processed by caspase-1 or neutrophil protease to the key proinflammatory and tumor-promoting cytokine IL-1β. Notable, while promoting pro-IL-1β expression, NF-κB ne! gatively controls its processing to mature IL-1β through the induction of various protease inhibitors. * Figure 3: Pro- and anti-tumorigenic effects of NF-κB activation in cancer cells and their microenvironment. Opposing NF-κB inhibition effects are found in distinct cancer types, yet also in cancers of a similar type, depending on the mechanism of carcinogenesis. Hence, whereas NF-κB inhibition suppresses inflammation (hepatitis)-associated liver cancer (HCC), it facilitates carcinogen-induced HCC. Author information * Abstract * Author information Affiliations * Lautenberg Center for Immunology, Institute for Medical Research-Israel-Canada, Hebrew University-Hadassah Medical School, Jerusalem, Israel. * Yinon Ben-Neriah * Laboratory of Gene Regulation and Signal Transduction, Department of Pharmacology and Cancer Center, School of Medicine, University of California, San Diego, La Jolla, California, USA. * Michael Karin Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Yinon Ben-Neriah or * Michael Karin Author Details * Yinon Ben-Neriah Contact Yinon Ben-Neriah Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Karin Contact Michael Karin Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Research Highlights
- Nat Immunol 12(8):724 (2011)
Article preview View full access options Nature Immunology | Research Highlights Research Highlights Journal name:Nature ImmunologyVolume: 12,Page:724Year published:(2011)DOI:doi:10.1038/ni0811-724Published online19 July 2011 The transcription factor HIF-1α is a central integrator of the hypoxic and innate immune stimulation in myeloid cells. In Immunity, Jain and colleagues demonstrate that the transcription factor KLF2 inhibits HIF-1α-dependent activation of myeloid cells. Myeloid-specific deficiency in KLF2 leads to spontaneous activation of myeloid cells, manifested as higher concentrations of several inflammatory cytokines in the serum of KLF2-deficient mice. These mice have higher expression of genes encoding antimicrobial and metabolic molecules and enhanced bactericidal activity after bacterial infection, as well as greater sensitivity to endotoxin challenge. This phenotype is rescued by ablation of HIF-1α. Mechanistically, KLF2 negatively regulates the recruitment of critical coactivators of NF-κB to the promoter of the gene encoding HIF-1α. Lower expression of KLF2 mRNA and higher expression of HIF-1α mRNA is seen in circulating human myeloid cells from patients with sepsis. IV Immunity, 715–728 (2011) 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 - SHP works a double shift to control TLR signaling
- Nat Immunol 12(8):725-727 (2011)
Article preview View full access options Nature Immunology | News and Views SHP works a double shift to control TLR signaling * Rudi Beyaert1Journal name:Nature ImmunologyVolume: 12,Pages:725–727Year published:(2011)DOI:doi:10.1038/ni.2075Published online19 July 2011 Innate immune responses need to be tightly controlled to avoid autoimmune and inflammatory diseases. The atypical orphan nuclear receptor SHP has now been identified as a negative regulator of Toll-like receptor–induced 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 * Rudi Beyaert is at the Department for Molecular Biomedical Research, Unit of Molecular Signal Transduction in Inflammation, VIB, Ghent, Belgium, and Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Rudi Beyaert Author Details * Rudi Beyaert Contact Rudi Beyaert Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - NUR who? An orphan transcription factor holds promise for monomaniacs
- Nat Immunol 12(8):727-729 (2011)
Article preview View full access options Nature Immunology | News and Views NUR who? An orphan transcription factor holds promise for monomaniacs * Derek W Cain1 * Michael D Gunn2 * Affiliations * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:727–729Year published:(2011)DOI:doi:10.1038/ni.2074Published online19 July 2011 The generation of Ly6C− patrolling monocytes requires the transcription factor NR4A1 (Nur77). This finding provides insight into the development and function of these blood-resident cells. 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 * Derek W. Cain is in the Department of Immunology, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA. * Michael D. Gunn is in the Division of Cardiology and Department of Immunology, Duke University Medical Center, Durham, North Carolina, USA. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Michael D Gunn Author Details * Derek W Cain Search for this author in: * NPG journals * PubMed * Google Scholar * Michael D Gunn Contact Michael D Gunn Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Solving vaccine mysteries: a systems biology perspective
- Nat Immunol 12(8):729-731 (2011)
Article preview View full access options Nature Immunology | News and Views Solving vaccine mysteries: a systems biology perspective * Lydie Trautmann1 * Rafick-Pierre Sekaly1 * Affiliations * Corresponding authorJournal name:Nature ImmunologyVolume: 12,Pages:729–731Year published:(2011)DOI:doi:10.1038/ni.2078Published online19 July 2011 Systems biology has emerged as a promising research strategy that can be applied to vaccine development. This approach can lead to the identification of new mechanisms and predictors of inactivated vaccine immunogenicity. 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 * Lydie Trautmann and Rafick-Pierre Sekaly are with the Vaccine and Gene Therapy Institute of Florida, Port Saint Lucie, Florida, USA. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Rafick-Pierre Sekaly Author Details * Lydie Trautmann Search for this author in: * NPG journals * PubMed * Google Scholar * Rafick-Pierre Sekaly Contact Rafick-Pierre Sekaly Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Research Highlights
- Nat Immunol 12(8):732 (2011)
Article preview View full access options Nature Immunology | Research Highlights Research Highlights Journal name:Nature ImmunologyVolume: 12,Page:732Year published:(2011)DOI:doi:10.1038/ni0811-732Published online19 July 2011 There are several subsets of dendritic cells (DCs), each with its own functional specialty. In Blood, Rothman and colleagues investigate the differentiation of one of these subsets: CD8α+ DCs. The leucine zipper transcription factor E4BP4 is known chiefly for its influence on the circadian rhythm and for its role in natural killer cell differentiation. The authors observe that the various DC subsets all have high expression of E4BP4. E4BP4-deficient (Nfil3−/−) mice lack CD8α+ DCs but have normal frequencies of CD8α− DCs and plasmacytoid DCs, which indicates a selective developmental defect. Attempts to differentiate CD8α− DCs from Nfil3−/− mice in vitro or in vivo with the stimulatory cytokine Flt3L all fail. Functionally, CD8α+ DCs are required for antigen cross-presentation; consistent with their absence, Nfil3−/− mice have impaired cross-presentation. The precise action of E4BP4 is unclear, but it seems to act in part via the transcription factor BATF! . ZF Blood, 6193–6197 (2011) 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 - Essential role for the prolyl isomerase Pin1 in Toll-like receptor signaling and type I interferon–mediated immunity
- Nat Immunol 12(8):733-741 (2011)
Nature Immunology | Article Essential role for the prolyl isomerase Pin1 in Toll-like receptor signaling and type I interferon–mediated immunity * Adrian Tun-Kyi1, 6 * Greg Finn1, 6 * Alex Greenwood2 * Michael Nowak1 * Tae Ho Lee1 * John M Asara1 * George C Tsokos1 * Kate Fitzgerald3 * Elliot Israel4 * Xiaoxia Li5 * Mark Exley1 * Linda K Nicholson2 * Kun Ping Lu1 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyYear published:(2011)DOI:doi:10.1038/ni.2069Received18 January 2011Accepted09 June 2011Published online10 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Toll-like receptors (TLRs) shape innate and adaptive immunity to microorganisms. The enzyme IRAK1 transduces signals from TLRs, but mechanisms for its activation and regulation remain unknown. We found here that TLR7 and TLR9 activated the isomerase Pin1, which then bound to IRAK1; this resulted in activation of IRAK1 and facilitated its release from the receptor complex to activate the transcription factor IRF7 and induce type I interferons. Consequently, Pin1-deficient cells and mice failed to mount TLR-mediated, interferon-dependent innate and adaptive immune responses. Given the critical role of aberrant activation of IRAK1 and type I interferons in various immune diseases, controlling IRAK1 activation via inhibition of Pin1 may represent a useful therapeutic approach. View full text Figures at a glance * Figure 1: Pin1 is activated and required for cytokine and especially type I interferon secretion after TLR stimulation. (–) ELISA of IL-6 (), IL-12p40 () and tumor necrosis factor (TNF; ) in supernatants of wild-type (WT) or Pin1-deficient (KO) bone marrow–derived mDCs stimulated for 12 h with PBS, LPS (100 ng/ml), Pam3CSK4 (1 μg/ml), CpG-B (0.1 μM) or R-848 (0.1 μg/ml). ND, not detectable. (,) IFN-α in supernatants of purified splenic (B220+CD11cint) pDCs () and Flt3L-induced bone marrow–derived pDCs () treated for 24 h with PBS, R-848 (0.1 μg/ml) or CpG-A (0.1 μM). (,) ELISA of IFN-α in supernatants of splenic pDCs () and Flt3L-induced bone marrow–derived pDCs () stimulated for 24 h with PBS, influenza A virus (H1N1) or MCMV. () Quantitative real-time RT-PCR analysis of the expression of IFN-α and IFN-β mRNA in splenic pDCs stimulated for 6 h with PBS, R-848 or CpG; results are presented relative to the expression of GAPDH (encoding glyceraldehyde phosphate dehydrogenase). () Protease-coupled assay of Pin1 isomerase activity in lysates of purified human peripheral blood mon! onuclear cells treated for 30 min with PBS, R-848 or CpG, presented as absorbance at 390 nm (A390). Inset, immunoblot analysis of Pin1 in lysate fractions; tubulin serves as a loading control. Data represent three independent experiments (mean and s.d.). * Figure 2: Identification of IRAK1 as a major Pin1 substrate after TLR stimulation, by a proteomics approach. () Precipitation of proteins interacting with GST-Pin1 (arrowhead) from lysates of THP-1 cells stimulated for 45 min with R-848, followed by SDS-PAGE and staining with colloidal Coomassie brilliant blue. Input, total cell lysate. After excision of specific bands containing proteins that interacted with GST-Pin1, seven peptides that corresponded to IRAK1 were identified by liquid chromatography–mass spectrometry (Supplementary Fig. 3a). () Immunoassay of the interaction between Pin1 and IRAK1 in RAW264.7 cells stimulated for 30 min with PBS (Control), R-848 or CpG, detected without precipitation (Input) after precipitation (ppt) with GST or GST-Pin1, followed by immunoblot analysis with antibody to total IRAK1 (anti-IRAK1). () Immunoassay of the interaction between endogenous Pin1 and IRAK1 in THP-1 cells stimulated with PBS, poly(I:C), R-848 or CpG, detected without immunoprecipitation (Input) or after immunoprecipitation (IP) with anti-Pin1 or control immunoglobulin G (Ig! G), followed by immunoblot analysis (IB) with anti-IRAK1. () Analysis of the IRAK1-Pin1 interaction in TLR7-expressing HEK293T cells transfected with plasmid expressing Flag-tagged IRAK1 and stimulated with R-848; lysates left untreated (−) or treated for 60 min at 30 °C (+) with calf intestinal phosphatase (CIP) were subjected to GST-Pin1 precipitation and analyzed by immunoblot for IRAK1. () GST-precipitation analysis of IRAK1-deficient 293T cells expressing Flag-tagged KD-IRAK1 alone (KD) or in combination with wild-type IRAK1 (KD + IRAK1). X (above), K239S substitution. () Protein-protein immunoblot analysis of IRAK1-deficient 293T cells expressing Flag-tagged wild-type IRAK1 or KD-IRAK1, purified with Flag-agarose, followed by incubation with GST–Pin1 WW; right (Strip reprobe), membranes reprobed with anti-Flag (control). () GST-precipitation analysis of MEFs with retroviral expression of Flag-tagged wild-type IRAK1 or KD-IRAK1, treated with R-848 (+) or control b! uffer (−). () GST-precipitation analysis of MEFs with retrov! iral expression of Flag-tagged wild-type IRAK1 (WT), KD-IRAK1 (KD) or IRAK1 mutants with replacement of serine with alanine at various positions (above lanes), treated with R-848 or control buffer. 3A, S131A +S144A + S173A. () Flow cytometry of THP-1 cells stimulated with PBS, CpG or R-848, then stained intracellularly with antibody to phosphorylated Ser173 (p-Ser173), followed by a secondary fluorescence-conjugated antibody. Data are representative of at least two (–) or three (,) experiments. * Figure 3: Phosphorylated Ser131-Pro132, S144-Pro145 and S173-Pro174 sites in the IRAK1 undetermined domain bind to and are isomerized by Pin1. () Chemical-shift perturbations in 15N-labeled WW detected by two-dimensional 15N-1H heteronuclear single-quantum coherence spectra resulting from titration with IRAK1 peptides phosphorylated at Ser131, Ser144 or Ser173. Red indicates WW in the absence of peptide other colors along the spectrum represent increasing concentrations of peptides (purple is the highest); and arrows indicate peak movement after the addition of peptide. () Binding curves for various residues in the WW domain of Pin1, showing weighted chemical shift changes as a function of the total concentration of peptide (lines represent global fits): S16, Ser16; S18, Ser18; Q33, Gln33; W34sc, side chain of Trp34; E35, Glu35. () Two-dimensional 1H-1H rotating-frame Overhauser effect spectroscopy spectra (mixing time, 100 ms) of phosphorylated IRAK1 peptides in the presence (top) or absence (bottom) of a catalytic amount of Pin1. Arrows indicate exchange cross-peaks (trans-to-cis (tc) and cis-to-trans (ct)) conne! cting auto-peaks (trans (tt) and cis (cc)). Data are representative of single () experiment. * Figure 4: Pin1 is essential for IRAK1 activation after TLR ligation. () Immunoblot analysis of IRAK1 activation in TLR7-expressing MEF cells (above) and in wild-type and Pin1-deficient Flt3L-derived pDCs (below) stimulated for 0–60 min with R-848; IRAK4 and Pin1 serve as controls. () Immunoprecipitation kinase assay of IRAK1 and IRAK4 in wild-type and Pin1-deficient peritoneal macrophages stimulated for 0–60 min with R-848; IRAK1, IRAK4 and Pin1 protein serve as controls. () Immunoblot analysis of THP-1 monocytes infected with virus encoding control short hairpin RNA (Ctrl) or short hairpin RNA targeting Pin1 (Pin1-RNAi) and simulated for 0–60 min with poly(I:C), R-848 or CpG. () In vivo assay of IRAK1 kinase activity in wild-type and Pin1-deficient MEFs with retroviral expression of vector control (VCT) or Flag-tagged wild-type IRAK1 or KD-IRAK1, plus a hemagglutinin (HA)-tagged N-terminal 220–amino acid fragment of IRAK1 (left) as a substrate. ProS/T, proline-, serine- and threonine-rich domain. () Immunoblot analysis of wild-type a! nd Pin1-deficient MEFs with retroviral expression of Flag-tagged wild-type IRAK1 or KD-IRAK1 coexpressed with TLR7, stimulated for 0–60 min with R-848. () Immunoblot analysis of Pin1-deficient MEFs stably expressing Flag-tagged IRAK1 and transfected with plasmid encoding wild-type Pin1, Pin1(WT), Pin1(W34A), Pin1(K63A) or Pin1 PPIase (below blots), plus plasmid encoding TLR7, and stimulated for 0–60 min with R-848. Data are representative of at least three independent experiments. * Figure 5: Pin1 facilitates IRAK1 release from the receptor complex to activate IRF7 after TLR ligation. () Immunoblot analysis of wild-type and Pin1-deficient MEFs with retroviral expression of hemagglutinin-tagged MyD88 and Flag-tagged IRAK1, assessed after immunoprecipitation with anti-hemagglutinin and probed with anti-Flag. () Immunoblot analysis of THP-1 cells treated with control or Pin1-specific RNA-mediated interference and stimulated for 0–90 min with CpG, followed by coimmunoprecipitation of IRF7 and TRAF6. (,) Immunoblot analysis of nuclear and cytoplasmic fractions of THP-1 cells after ligation of TLR7 () or TLR9 () for 0–240 min, probed with anti-IRF7; immunoblot analysis with anti-tubulin or anti–lamin A/C indicates the purity of nuclear and cytosolic fractions, respectively. () Confocal microscopy of wild-type and Pin1-deficient pDCs stimulated with PBS, R-848 or CpG, then immunostained with anti-IRF7 and counterstained with the DNA-intercalating dye DAPI. Original magnification, ×640. Data are representative of at least three independent experiments. * Figure 6: Pin1 is required for IRF7 activation and IFN-α production after TLR ligation in vitro. (,) Luciferase activity of wild-type and Pin1-deficient cells transiently coexpressing a Gal4–upstream activating system (Gal4-UAS) reporter plasmid, Gal4-IRF7 and either TLR7 () or TLR9 (), then stimulated for 12 h with R-848 () or CpG (); results were normalized to renilla luciferase activity and are presented relative to those of unstimulated wild-type cells. (,) Luciferase activity () and ELISA of IFN-α () in wild-type and Pin1-deficient MEFs stably expressing IRAK1 and transiently cotransfected with Gal4-UAS and Gal4-IRF7 plus empty vector (EV) or vector for wild-type Pin1, Pin1(W34A) or Pin1(K63A); wild-type MEFs stably expressing IRAK1and transfected with empty vector serve as a control. Below, immunoblot analysis of wild-type, Pin1(W34A) and Pin1(K63A). () Luciferase activity of wild-type and Pin1-deficient MEFs transiently transfected with Gal4-UAS, Gal4-IRF7, vector for MyD88 (20 ng) and various amounts (horizontal axis) of KD-IRAK1 or control vector (0), assess! ed as in . (,) Luciferase activity () and ELISA of IFN-α () in wild-type and Pin1-deficient cells stably expressing empty vector or vector for wild-type IRAK1, IRAK1 mutants with replacement of serine with alanine at various positions (horizontal axes) or KD-IRAK1, cotransfected with Gal4-UAS and Gal4-IRF7 () or with plasmid encoding IRF7 (). Below (), immunoblot analysis of the expression of wild-type IRAK1 and IRAK1 mutants. () VSV production by monolayers of L929 cells treated with supernatants of wild-type and Pin1-deficient cells stably expressing vectors as in ,, assessed 24 h after infection with VSV (0.1 plaque-forming units (PFU) per cell). () VSV plaques in the cells in . Data are representative of three experiments (error bars (–), s.d.). * Figure 7: Pin1 is required for TLR-mediated, type I interferon-dependent innate and adaptive immunity in vivo. (–) IFN-α in the serum of wild-type and Pin1-deficient mice (n = 3 per group) injected with R-848 (50 nmol; intravenously; ), CpG-A in complex with DOTAP (5 μg; intravenously; ) or MCMV (5 × 104 plaque-forming units; intraperitoneally; ). (,) Change in body weight () and morbidity () of wild-type and Pin1-deficient mice (n = 6 per group) injected with MCMV (2.5 × 104 () or 1 × 105 () plaque-forming units). () Flow cytometry of splenocytes isolated from wild-type and Pin1-deficient mice immunized with ovalbumin and anti-CD40, plus PBS (Control) or CpG-A in complex with DOTAP (CpG), assessed 6 d later with anti-CD8α and anti-CD44 and a major histocompatibility complex (MHC) tetramer; results are gated on CD8α+ events. Numbers adjacent to outlined areas indicate percent tetramer-positive cells among total CD8α+ T cells. Data represent three (–,) or six (,) experiments (mean and s.d. in –). Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Adrian Tun-Kyi & * Greg Finn Affiliations * Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA. * Adrian Tun-Kyi, * Greg Finn, * Michael Nowak, * Tae Ho Lee, * John M Asara, * George C Tsokos, * Mark Exley & * Kun Ping Lu * Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, USA. * Alex Greenwood & * Linda K Nicholson * Division of Infectious Diseases and Immunology, University of Massachusetts Medical School, Worcester, Massachusetts, USA. * Kate Fitzgerald * Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA. * Elliot Israel * Department of Immunology, Cleveland Clinic Foundation, Cleveland, Ohio, USA. * Xiaoxia Li Contributions A.T.K. and G.F. designed and did the experiments and wrote the manuscript; A.G. did nuclear magnetic resonance experiments; M.N. and T.H.L. provided technical assistance; J.M.A. did mass spectrometry analysis; K.F., X.L., G.C.T., M.E. and E.I. provided reagents and technical expertise; and L.K.N. and K.P.L. designed the experiments, supervised the project and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Kun Ping Lu Author Details * Adrian Tun-Kyi Search for this author in: * NPG journals * PubMed * Google Scholar * Greg Finn Search for this author in: * NPG journals * PubMed * Google Scholar * Alex Greenwood Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Nowak Search for this author in: * NPG journals * PubMed * Google Scholar * Tae Ho Lee Search for this author in: * NPG journals * PubMed * Google Scholar * John M Asara Search for this author in: * NPG journals * PubMed * Google Scholar * George C Tsokos Search for this author in: * NPG journals * PubMed * Google Scholar * Kate Fitzgerald Search for this author in: * NPG journals * PubMed * Google Scholar * Elliot Israel Search for this author in: * NPG journals * PubMed * Google Scholar * Xiaoxia Li Search for this author in: * NPG journals * PubMed * Google Scholar * Mark Exley Search for this author in: * NPG journals * PubMed * Google Scholar * Linda K Nicholson Search for this author in: * NPG journals * PubMed * Google Scholar * Kun Ping Lu Contact Kun Ping Lu 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 1–11 and Supplementary Note Additional data - The orphan nuclear receptor SHP acts as a negative regulator in inflammatory signaling triggered by Toll-like receptors
- Nat Immunol 12(8):742-751 (2011)
Nature Immunology | Article The orphan nuclear receptor SHP acts as a negative regulator in inflammatory signaling triggered by Toll-like receptors * Jae-Min Yuk1, 2, 11 * Dong-Min Shin1, 2, 11 * Hye-Mi Lee1, 2 * Jwa-Jin Kim1, 2 * Sun-Woong Kim1 * Hyo Sun Jin1, 2 * Chul-Su Yang1, 2, 10 * Kyeong Ah Park2, 3 * Dipanjan Chanda4 * Don-Kyu Kim4 * Song Mei Huang2, 5 * Sang Ki Lee6 * Chul-Ho Lee7 * Jin-Man Kim2, 5 * Chang-Hwa Song1 * Soo Young Lee8 * Gang Min Hur2, 3 * David D Moore9 * Hueng-Sik Choi4 * Eun-Kyeong Jo1, 2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature ImmunologyYear published:(2011)DOI:doi:10.1038/ni.2064Received21 April 2011Accepted01 June 2011Published online03 July 2011 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The orphan nuclear receptor SHP (small heterodimer partner) is a transcriptional corepressor that regulates hepatic metabolic pathways. Here we identified a role for SHP as an intrinsic negative regulator of Toll-like receptor (TLR)-triggered inflammatory responses. SHP-deficient mice were more susceptible to endotoxin-induced sepsis. SHP had dual regulatory functions in a canonical transcription factor NF-κB signaling pathway, acting as both a repressor of transactivation of the NF-κB subunit p65 and an inhibitor of polyubiquitination of the adaptor TRAF6. SHP-mediated inhibition of signaling via the TLR was mimicked by macrophage-stimulating protein (MSP), a strong inducer of SHP expression, via an AMP-activated protein kinase–dependent signaling pathway. Our data identify a previously unrecognized role for SHP in the regulation of TLR signaling. View full text Figures at a glance * Figure 1: SHP protects against LPS-induced lethal shock through the inhibition of inflammatory responses in vivo. () Survival of Shp+/+ and Shp−/− mice (n = 14 per genotype) challenged with LPS (20 mg per kg body weight; intraperitoneally). () Enzyme-linked immunosorbent assay (ELISA) of TNF and IL-6 in serum from Shp+/+ and Shp−/− mice (n = 3 per group), assessed 18 h after intraperitoneal injection of various concentrations of LPS (horizontal axes; in mg per kg body weight (mg/kg)). () Semiquantitative RT-PCR analysis of the expression of Tnf, Il6, Il1b and Shp mRNA in spleen and liver samples from mice treated with various doses of LPS (above lanes); Actb (encoding β-actin) serves as a loading control throughout. () Cyclooxygenase-2 (COX-2) in lung tissue from Shp+/+ and Shp−/− mice treated with PBS or LPS (n = 3 per group). Scale bar, 50 μm. Right (below), COX-2+ cells (in ten random fields); inset, RT-PCR analysis of Shp. () Size of Shp+/+ and Shp−/− spleens 3 h after injection of PBS or LPS. Left margin, size (hash marks, 0.5 cm). (,) ELISA of serum TNF and IL-6 ! (; n = 3 mice per group) and survival (; n = 16 mice per group) of 12-week-old chimeras injected with LPS (30 mg/kg; intraperitoneally): Shp−/− mice reconstituted with Shp+/+ (Shp+/+Shp−/−) or Shp−/− (Shp−/−Shp−/−) bone marrow–derived cells, and Shp+/+ mice reconstituted with Shp−/− (Shp−/−Shp+/+) or Shp+/+ (Shp+/+Shp+/+) bone marrow–derived cells. *P < 0.05, **P < 0.01 and ***P < 0.001, compared with Shp+/+ mice treated with LPS (log-rank test (,) or two-tailed Student's t-test (,,)). Data are from one representative of at least two (,,) or three (–,) independent experiments (mean and s.d. of triplicate (, (bottom right), )). * Figure 2: SHP inhibits LPS-induced inflammatory responses in macrophages and splenocytes. () ELISA of TNF, IL-6, IL-1β and IL-10 in culture supernatants of Shp+/+ and Shp−/− BMDMs incubated for 0–48 h with LPS (100 ng/ml). () Semiquantitative RT-PCR analysis of Tnf, Il6, Il1b and Il10 mRNA in Shp+/+ and Shp−/− BMDMs incubated for 0–18 h with LPS (100 ng/ml). () Immunoblot analysis of inducible nitric oxide synthase (iNOS) and SHP in whole-cell lysates (top) and detection of nitrite in culture supernatants (with Griess reagent; bottom) of cells as in . () ELISA of TNF, IL-6, IL-1β and IL-10 in BMDMs transduced for 36 h with adenovirus encoding GFP only (Ad-GFP), SHP (Ad-SHP) or Shp-specific small interfering RNA (Ad-siSHP), at a multiplicity of infection of 10, followed by treatment for 18 h with LPS. Top, RT-PCR analysis of transduction efficiency. () ELISA of TNF and IL-6 in Shp+/+ and Shp−/− splenocytes and peritoneal macrophages (MΦ) stimulated for 0–48 h with LPS (100 ng/ml). *P < 0.05, **P < 0.01 and ***P < 0.001, compared with LPS-stimu! lated Shp+/+ cells (two-tailed Student's t-test). Data are from one representative of at least three independent experiments (mean and s.d. of triplicates (, (bottom), ,)). * Figure 3: SHP is a regulator of signaling by Nod2 and RLRs but not of dectin-1 signaling. () Survival of Shp+/+ and Shp−/− mice (n = 15 per genotype) challenged for 0–72 h with zymosan (0.5 mg/g; intraperitoneally). () ELISA of TNF and IL-6 in Shp+/+ and Shp−/− BMDMs incubated for 0–48 h with zymosan (Zym; 100 μg/ml). (,) ELISA of TNF and IL-6 () and semiquantitative RT-PCR analysis of Tnf, Il6 and Shp mRNA () in BMDMs transduced for 36 h with adenovirus (as in Fig. 2d) before treatment for 18 h () or 6 h () with zymosan (100 μg/ml); below (), densitometry results, presented relative to expression in unstimulated cells. () ELISA of TNF and IL-6 in Shp+/+ and Shp−/− BMDMs incubated for 0–48 h with curdlan (100 μg/ml). () Semiquantitative RT-PCR analysis of Ccl5 and Shp mRNA in Shp+/+ and Shp−/− BMDMs incubated for 0–18 h with MDP (100 ng/ml); below, densitometry (as in ). (,) Quantitative RT-PCR analysis of mRNA for interferon-β (Ifnb) in Shp+/+ and Shp−/− BMDMs incubated for 0–18 h with triphosphate RNA in complex with Lipofectam! ine 2000 (3pRNA-Lipo; 20 ng/ml; ) or poly(I:C) in complex with LyoVec (poly(I:C)-LyoVec; 100 ng/ml; ); results (by densitometry) are presented relative to expression in Shp+/+ cells at 0 h. *P < 0.05, **P < 0.01 and ***P < 0.001, compared with Shp+/+ cells (log-rank test () or two-tailed Student's t-test (–,–)). Data are from one representative of at least two () or three (–) independent experiments (mean and s.d. of triplicates (, (bottom), ,,,,)). * Figure 4: SHP regulates TLR4-mediated NF-κB signaling through an interaction between SHP and p65. (,) Immunoblot analysis of phosphorylated (p-) IKKα-IKKβ and total IκBα and SHP in Shp+/+ and Shp−/− BMDMs stimulated with LPS (100 ng/ml); below, densitometry. () Immunofluorescence microscopy of p65 (green) in Shp+/+ and Shp−/− BMDMs stimulated with LPS (100 ng/ml); nuclei are stained with the DNA-intercalating dye DAPI (blue). Scale bar, 50 μm. Right, quantification of DAPI+ or p65+ pixels in the cytoplasm and nucleus (numbers correspond to time of LPS incubation), assessing the nuclear translocation of p65. FITC, fluorescein isothiocyanate. () Luciferase assay of Tnf promoter activity in BMDMs transduced with adenovirus (as in Fig. 2d), plus adenovirus carrying a TNF luciferase reporter construct, then stimulated for 6 h with LPS; results are presented relative to activity in unstimulated cells. Above, RT-PCR analysis of transduction efficiency. (,) Immunoprecipitation (IP) of p65, p50 or immunoglobulin G (IgG; ) or of SHP () from RAW264.7 cells transduced w! ith adenovirus (as in Fig. 2d) before stimulation for 1 h with LPS, followed by PCR with primers specific for the Tnf promoter () or immunoblot analysis (IB) with antibody to p65 or SHP (). Input (, bottom), PCR analysis of DNA without immunoprecipitation; TNF-p65 (top), p65-binding region of the Tnf promoter. () Confocal microsopy of NF-κB (green) and SHP (red) in BMDMs expressing endogenous SHP (Endo SHP) or overexpressing SHP via adenovirus encoding SHP (Overexp SHP), assessed after stimulation for 0, 15 or 30 min with LPS. Scale bar, 10 μm. Right, dual-color pixel analysis of the colocalization of NF-κB and SHP. () Quantitative analysis of the colocalization coefficients in . *P < 0.05 and **P < 0.01, compared with Shp+/+ cell cultures (two-tailed Student's t-test). Data are from one representative of at least three independent experiments (mean and s.d. of triplicates ( (bottom), ,)). * Figure 5: SHP interacts with TRAF6 to negatively modulate its ubiquitination. () Immunoblot analysis of IRAK1 and SHP in Shp+/+ and Shp−/− BMDMs stimulated for 0–60 min with LPS (100 ng/ml). (,) Immunoprecipitation of endogenous TRAF6 from lysates of LPS-treated Shp+/+ and Shp−/− BMDMs () or RAW264.7 cells transduced with adenovirus encoding SHP (), followed by immunoblot analysis with antibody to TRAF6, ubiquitin (Ub) or SHP. MOI, multiplicity of infection. Below, immunoblot analysis without immunoprecipitation (loading control throughout). () Immunoprecipitation of endogenous SHP from lysates of LPS-stimulated RAW264.7 cells, followed by immunoblot analysis with antibody to TRAF6, TRAF2 or SHP. () Microscopy of BMDMs left unstimulated (US) or stimulated for 30 min with LPS, then stained with DAPI (blue) and immunolabeled with antibody to SHP (conjugated to the red fluorescent dye TRITC) or antibody to TRAF6 (conjugated to the green fluorescent dye Alexa Fluor 488 (Alexa488)). Scale bar, 20 μm. Below, quantification of fluorescence intensi! ty; distance (horizontal axis) is relative to the white bars in the far right images above. () Immunoprecipitation of SHP from LPS-stimulated RAW264.7 cells (subjected to subcellular fractionation), followed by immunoblot analysis with antibody to TRAF6 or p65. () Immunoprecipitation (with antibody to hemagglutinin) of Flag-tagged TRAF6 (Flag-TRAF6) together with hemagglutinin-tagged SHP (HA-SHP) from lysates of HEK293 human epithelial T cells left untransfected (−) or transfected with plasmid encoding full-length Flag-tagged TRAF6 or TRAF6 deletion mutants consisting of amino acids 132–530 or 212–530, followed by immunoblot analysis with antibody to Flag or hemagglutinin. WCL, immunoblot analysis of whole-cell lysates without immunoprecipitation. () Immunoprecipitation (with antibody to Flag) of proteins from HEK293 cells overexpressing Myc-tagged SHP (Myc-SHP) or mock vector (Myc-Mock), mock transfected (Mock) or transfected with plasmid encoding Flag-tagged wild-ty! pe TRAF6 (WT) or TRAF6 with deletion of the RING domain (ΔR),! with or without plasmid encoding hemagglutinin-tagged ubiquitin (HA-Ub), followed by immunoblot analysis with antibody to Flag or hemagglutinin. () Quantitative RT-PCR analysis of Tnf and Il6 mRNA in RAW264.7 cells transfected with empty vector control (Mock) or TRAF6 with deletion of the RING domain, followed by transduction with adenovirus encoding GFP only or SHP and stimulation for 6 h with LPS; results are presented relative to expression in unstimulated cells. Data are from one representative of at least three independent experiments (mean and s.d. of triplicates in ). * Figure 6: TLR4 activation induces SHP expression in macrophages via Ca2+-dependent activation of AMPK. (,) RT-PCR analysis of Shp mRNA () and immunoblot analysis of SHP () in BMDMs stimulated with LPS (100 ng/ml). () Immunoblot analysis of phosphorylated AMPKα and ACC in BMDMs stimulated with LPS. Below, densitometry. () Microscopy of Ca2+ in THP-1 cells left unstimulated (US) or stimulated with LPS (LPS), assessed with the fluorescent Ca2+ indicator Fluo-2 AM (top), and kinetics of Ca2+ influx in THP-1 cells stimulated with LPS at 100 s and treated with ATP at 1,000 s, in images captured at intervals of 5 s (bottom). Original magnification (top), ×400. () Immunoblot analysis of phosphorylated AMPKα and ACC and total SHP in BMDMs left unstimulated (US), treated with dimethyl sulfoxide (D) or stimulated for 4 h (AMPKα and ACC analysis) or 36 h (SHP analysis) with LPS, plus increasing concentrations (wedges) of the CaMK inhibitor KN93 (5, 10 or 25 μM), the calcium-specific chelator BAPTA-AM (BAPTA; 5, 10 or 25 μM) or the AMPK inhibitor compound C (CompC; 5, 10 or 25 μM).! () RT-PCR analysis of BMDMs left unstimulated or stimulated for 24 h with LPS, then treated as in . () Immunoblot analysis of lysates of BMDMs transduced with lentivirus expressing nonspecific shRNA (shNS) or shRNA specific for CaMKKβ (shCaMKKβ) or AMPK (shAMPK), then cultured for 36 h in the presence or absence of LPS, probed with antibody to SHP, CaMKKβ or AMPK. () Immunoblot analysis of SHP and USF1 in BMDMs transduced with lentivirus expressing nonspecific shRNA or shRNA specific for USF1 (shUSFI), then incubated for 36 h with LPS with or without compound C. Data are from one representative of at least three independent experiments. * Figure 7: MSP-induced SHP regulates TLR4-mediated proinflammatory signaling through the activation of an LKB1-dependent AMPK pathway. () RT-PCR analysis of Shp mRNA in BMDMs treated for 0–24 h with MSP (100 ng/ml). Below, densitometry. () RT-PCR analysis of Shp mRNA in BMDMs transduced for 36 h with adenovirus encoding GFP only (Ad-GFP), dominant negative AMPK (Ad-DN) or constitutively active AMPK (Ad-CA; multiplicity of infection, 10) and treated for 6 h with MSP (100 ng/ml). Below, densitometry (as in Fig 3d). () Immunoblot analysis of phosphorylated AMPKα and total LKB1 and SHP in BMDMs transduced with lentivirus encoding nonspecific shRNA or shRNA specific for LKB1 (shLKB1; multiplicity of infection, 10) and treated for 4 h with MSP (100 ng/ml). () ELISA of TNF, IL-10, IL-6 and IL-1β in Shp+/+ and Shp−/− BMDMs pretreated for 4 h with MSP (100 ng/ml), followed by incubation for 18 h with LPS (100 ng/ml). () Immunoprecipitation of endogenous TRAF6 from BMDMs pretreated with MSP as in and incubated for 30 min with LPS (100 ng/ml), followed by immunoblot analysis with antibody to ubiquitin or TRAF6! . () Immunoblot analysis of NF-κB and phosphorylated mitogen-activated protein kinases (p-p44/42 and p-p38) in BMDMs pretreated with MSP as in and stimulated for 0–120 min with LPS (100 ng/ml). () Confocal microscopy of p65 in cells as in , stained with antibody to p65 and counterstained with DAPI. Scale bars, 50 μm. Right, analysis of the nuclear translocation of p65 (as in Fig. 4b). () Immunoprecipitation of endogenous SHP from RAW264.7 cells pretreated as in and incubated for 30 min with LPS (100 ng/ml), followed by immunoblot analysis with antibody to p65 or SHP. Data are from one representative of at least three independent experiments (mean and s.d. of triplicates (, (bottom) and )). Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Mouse Genome Informatics * 1346344 Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Jae-Min Yuk & * Dong-Min Shin Affiliations * Department of Microbiology, Chungnam National University School of Medicine, Daejeon, South Korea. * Jae-Min Yuk, * Dong-Min Shin, * Hye-Mi Lee, * Jwa-Jin Kim, * Sun-Woong Kim, * Hyo Sun Jin, * Chul-Su Yang, * Chang-Hwa Song & * Eun-Kyeong Jo * Infection Signaling Network Research Center, Chungnam National University School of Medicine, Daejeon, South Korea. * Jae-Min Yuk, * Dong-Min Shin, * Hye-Mi Lee, * Jwa-Jin Kim, * Hyo Sun Jin, * Chul-Su Yang, * Kyeong Ah Park, * Song Mei Huang, * Jin-Man Kim, * Gang Min Hur & * Eun-Kyeong Jo * Department of Pharmacology, Chungnam National University School of Medicine, Daejeon, South Korea. * Kyeong Ah Park & * Gang Min Hur * National Creative Research Initiatives Center for Nuclear Receptor Signals, Hormone Research Center, School of Biological Sciences and Technology, Chonnam National University, Gwangju, South Korea. * Dipanjan Chanda, * Don-Kyu Kim & * Hueng-Sik Choi * Department of Pathology, Chungnam National University School of Medicine, Daejeon, South Korea. * Song Mei Huang & * Jin-Man Kim * Department of Sports Science, College of Natural Science, Chungnam National University, Daejeon, South Korea. * Sang Ki Lee * Animal Model Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, South Korea. * Chul-Ho Lee * Department of Bioinspired Science, College of Life Science, Ewha Womans University, Seoul, South Korea. * Soo Young Lee * Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA. * David D Moore * Present address: Department of Molecular Microbiology and Immunology, University of Southern California, Keck School of Medicine, Los Angeles, California, USA. * Chul-Su Yang Contributions J.-M.Y., D.-M.S., H.-M.L., S.-W.K, H.S.J., C.-S.Y., D.C., D.-K.K., S.M.H. and S.K.L. planned and did experiments and analyzed data; J.-J.K. and C.-H.S. planned and did most of the bone marrow–chimera experiments; K.A.P. and G.M.H. planned and did ubiquitination experiments; C.-H.L., J.-M.K., S.Y.L. and D.D.M. contributed to some of the experiments; H.-S.C. and E.-K.J. supervised the project, designed experiments and wrote the manuscript with comments from the coauthors; and all authors collaborated on the work. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Hueng-Sik Choi or * Eun-Kyeong Jo Author Details * Jae-Min Yuk Search for this author in: * NPG journals * PubMed * Google Scholar * Dong-Min Shin Search for this author in: * NPG journals * PubMed * Google Scholar * Hye-Mi Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Jwa-Jin Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Sun-Woong Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Hyo Sun Jin Search for this author in: * NPG journals * PubMed * Google Scholar * Chul-Su Yang Search for this author in: * NPG journals * PubMed * Google Scholar * Kyeong Ah Park Search for this author in: * NPG journals * PubMed * Google Scholar * Dipanjan Chanda Search for this author in: * NPG journals * PubMed * Google Scholar * Don-Kyu Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Song Mei Huang Search for this author in: * NPG journals * PubMed * Google Scholar * Sang Ki Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Chul-Ho Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Jin-Man Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Chang-Hwa Song Search for this author in: * NPG journals * PubMed * Google Scholar * Soo Young Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Gang Min Hur Search for this author in: * NPG journals * PubMed * Google Scholar * David D Moore Search for this author in: * NPG journals * PubMed * Google Scholar * Hueng-Sik Choi Contact Hueng-Sik Choi Search for this author in: * NPG journals * PubMed * Google Scholar * Eun-Kyeong Jo Contact Eun-Kyeong Jo 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 (17M) Supplementary Figures 1–20, Supplementary Table 1 and Supplementary Methods Additional data - Inositol hexakisphosphate kinase 1 regulates neutrophil function in innate immunity by inhibiting phosphatidylinositol-(3,4,5)-trisphosphate signaling
- Nat Immunol 12(8):752-760 (2011)
Nature Immunology | Article Inositol hexakisphosphate kinase 1 regulates neutrophil function in innate immunity by inhibiting phosphatidylinositol-(3,4,5)-trisphosphate signaling * Amit Prasad1, 4 * Yonghui Jia1, 4 * Anutosh Chakraborty2 * Yitang Li1 * Supriya K Jain1 * Jia Zhong1 * Saurabh Ghosh Roy1 * Fabien Loison1 * Subhanjan Mondal1 * Jiro Sakai1 * Catlyn Blanchard1 * Solomon H Snyder2 * Hongbo R Luo1, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyYear published:(2011)DOI:doi:10.1038/ni.2052Received06 January 2011Accepted12 May 2011Published online19 June 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Inositol phosphates are widely produced throughout animal and plant tissues. Diphosphoinositol pentakisphosphate (InsP7) contains an energetic pyrophosphate bond. Here we demonstrate that disruption of inositol hexakisphosphate kinase 1 (InsP6K1), one of the three mammalian inositol hexakisphosphate kinases (InsP6Ks) that convert inositol hexakisphosphate (InsP6) to InsP7, conferred enhanced phosphatidylinositol-(3,4,5)-trisphosphate (PtdIns(3,4,5)P3)-mediated membrane translocation of the pleckstrin homology domain of the kinase Akt and thus augmented downstream PtdIns(3,4,5)P3 signaling in mouse neutrophils. Consequently, these neutrophils had greater phagocytic and bactericidal ability and amplified NADPH oxidase–mediated production of superoxide. These phenotypes were replicated in human primary neutrophils with pharmacologically inhibited InsP6Ks. In contrast, an increase in intracellular InsP7 blocked chemoattractant-elicited translocation of the pleckstrin homology ! domain to the membrane and substantially suppressed PtdIns(3,4,5)P3-mediated cellular events in neutrophils. Our findings establish a role for InsP7 in signal transduction and provide a mechanism for modulating PtdIns(3,4,5)P3 signaling in neutrophils. View full text Figures at a glance * Figure 1: Disruption of InsP6K1 in mouse neutrophils augments PtdIns(3,4,5)P3 signaling. () RT-PCR analysis of the expression of InsP6K isoforms in neutrophils and brain (positive control); GAPDH (glyceraldehyde phosphate dehydrogenase) serves as a loading control. () Immunoblot analysis of InsP6K1 in wild-type (WT) and Ip6k1−/− (KO) neutrophils; actin serves as a loading control throughout. () Immunoblot analysis of total Akt and Akt phosphorylated at Ser473 (p-Akt(S473)) in neutrophils stimulated for 0–300 min (above lanes) with 1 μM fMLP. () Phosphorylated Akt in neutrophils stimulated with 1 μM fMLP, presented relative to total Akt. *P < 0.01 (Student's t-test). () Time-lapse images of wild-type and Ip6k1−/− bone marrow–derived neutrophils transfected with a PHAkt-GFP construct, then stimulated for 0–60 min (horizontal axis) with 1 μM fMLP. Original magnification, ×60. () Membrane translocation of PHAkt-GFP in mouse bone marrow–derived neutrophils stimulated with 1 μM fMLP, presented as mean membrane fluorescence intensity in arbitrary u! nits (AU). *P < 0.01 (Student's t-test). Data are representative of three experiments (–,) or are from three independent experiments (,; mean ± s.d.). * Figure 2: Disruption of InsP6K1 leads to enhanced chemoattractant-elicited intracellular and extracellular superoxide production in mouse neutrophils. () Isoluminol chemiluminescence assay of extracellular ROS production in wild-type and Ip6k1−/− bone marrow–derived neutrophils stimulated with Hank's balanced-salt solution (HBSS) or with various concentrations (above plots) of fMLP, C5a or PMA; results are presented as arbitrary light units (ALU). () Extracellular ROS production elicited by 10 μM or 100 nM fMLP. () Cytochrome c–reduction assay of total ROS production in wild-type and Ip6k1−/− bone marrow neutrophils incubated with cytochrome c with or without superoxide dismutase and stimulated for 5 min with fMLP; results are presented as the difference in absorbance at 550 nm of samples with or without superoxide dismutase (ΔA550). () Luminol chemiluminescence assay of intracellular ROS production in wild-type and Ip6k1−/− bone marrow–derived neutrophils stimulated with 1 μM fMLP, 200 nM C5a or 200 nM PMA. *P < 0.01 (Student's t-test). Data are from three independent experiments (mean ± s.d.). * Figure 3: Pharmacological inhibition of InsP6K activity augments PtdIns(3,4,5)P3 signaling and NADPH oxidase–mediated production of superoxide in human primary neutrophils. () Immunoblot analysis of total Akt and phosphorylated Akt (p-Akt) in human neutrophils treated with dimethyl sulfoxide (DMSO) or 10 μM TNP and stimulated with 1 μM fMLP. Bottom, quantification of phosphorylated Akt. (,) Extracellular () and intracellular () ROS production in human neutrophils treated with dimethyl sulfoxide or TNP and left unstimulated (HBSS) or stimulated with fMLP (assessed as in Fig. 2a). (,) Extracellular () and intracellular () ROS production in human neutrophils treated with dimethyl sulfoxide or TNP and stimulated with 100 nM or 500 nM C5a (assessed as in Fig. 2a). *P < 0.01 (Student's t-test). Data are representative of three experiments (mean ± s.d.). * Figure 4: InsP6K1 disruption does not alter the amount of PtdIns(3,4,5)P3 in neutrophils. (,) PtdIns(3,4,5)P3 in human neutrophils () or dHL60 cells () treated with dimethyl sulfoxide or 10 μM TNP and left unstimulated (US) or stimulated for 2 min with 1 μM fMLP. () PtdIns(3,4,5)P3 in wild-type and Ip6k1−/− neutrophils left unstimulated or stimulated for 2 min with 1 μM fMLP. Data are from three experiments (mean ± s.d.). * Figure 5: Overexpression of InsP6Ks suppresses PtdIns(3,4,5)P3 signaling in dHL60 cells. () Expression of Myc-tagged InsP6Ks in dHL60 cells transfected with constructs of Myc-tagged InsP6K1, InsP6K2 or InsP6K3 or the 'kinase-dead' InsP6K1 mutant (InsP6K1(KD)). () High-performance liquid chromatography analysis of InsP7 in cells transfected as in ; inositol phosphates were identified by coelution with H3-labeled inositol phosphate standards and results were normalized to total protein extracted from the same sample. () Immunoblot analysis of total and phosphorylated Akt in dHL60 cells transfected as in and left unstimulated or stimulated for 3 min with 1 μM fMLP; right, quantification of phosphorylated Akt. () Membrane translocation of PHAkt-GFP indHL60 cells co-transfected with the PHAkt-GFP construct and a construct for InsP6K1 or the 'kinase-dead' InsP6K1 mutant. Original magnification, ×60. () Membrane fluorescence intensity in . () ROS production in dHL60 cells transfected as in and left unstimulated (HBSS) or uniformly stimulated with 1 μM fMLP (assessed! as in Fig. 2a). Data are representative of three experiments (,,) or are from three independent experiments (,,; mean ± s.d.). * Figure 6: Inhibition of superoxide production by InsP7 in a cell-free reconstitution assay. () Reconstitution reactions with permeabilized polymorphonuclear neutrophil cores alone (Core only; control) or with purified cytosol (Core + cytosol), supplemented with ATP, creatine kinase, PMA and NADPH in presence of GTPγS without wortmannin (top); in the presence (▴) or absence (▪) of GTPγS without wortmannin (middle); or in the presence of GTPγS with (▴) or without (▪) wortmannin (bottom). () Luminol-dependent chemiluminescence assay of GTPγS-induced superoxide production in reaction mixtures incubated for 10 min at 37 °C, then assessed in the presence of inositol hexakissulfate (InsS6), InsP6 or InsP7. *P < 0.01 (Student's t-test). Data are from three independent experiments (mean ± s.d.). * Figure 7: Chemoattractant stimulation rapidly diminishes InsP7 in neutrophils. () InsP7 and InsP6 in dHL60 cells left unstimulated or stimulated for 1 min with 1 μM fMLP, normalized to total protein extracted from the same sample (assessed as in Fig. 5b). () InsP7 in dHL60 cells stimulated for 0–60 s (horizontal axis) with 1 μM fMLP. () InsP7 in dHL60 cells treated for 30 min at 37 °C with dimethyl sulfoxide (− TNP) or 10 μM TNP (+ TNP) and left unstimulated or stimulated for 1 min with 1 μM fMLP (assessed as in Fig. 5b). Data are from three experiments (mean ± s.d.). * Figure 8: Enhanced in vivo bacteria-killing ability of Ip6k1−/− mice. () ROS accumulation in the inflamed peritoneal cavity of wild-type and Ip6k1−/− mice (assessed as in Fig. 2c). () In vivo killing of E. coli by wild-type and Ip6k1−/− mice, assessed as bacteria colony-forming units; numbers in images indicate dilution ratios of peritoneal fluid. () Total surviving E. coli (left) or E. coli killed, relative to recruited polymorphonuclear neutrophils (PMN; right). () In vivo killing of S. aureus by wild-type and Ip6k1−/− mice, assessed as in ; numbers above images indicate dilution ratios of peritoneal fluid. () Total surviving S. aureus (left) or S. aureus killed (right), assessed as in . *P < 0.01 (Student's t-test). Data are from three experiments (mean and s.d. in ,,). * Figure 9: Augmented in vitro bacteria-killing ability of Ip6k1−/− neutrophils, with enhanced phagocytosis and ROS production. () In vitro killing by wild-type and Ip6k1−/− neutrophils of diluted aliquots of E. coli spread on agar plates and incubated overnight at 37 °C, quantified (right) as bacteria colony-forming units (CFU). () In vitro killing of S. aureus by wild-type and Ip6k1−/− neutrophils (assessed as in ). () Superoxide production by wild-type and Ip6k1−/− neutrophils in response to zymosan or E. coli. () Phagocytosis-associated ROS production by dHL60 cells incubated with HBSS, zymosan or E. coli and left untreated or treated for 2 h with 10 μM TNP. () In vitro killing of internalized E. coli by wild-type and Ip6k1−/− neutrophils, assessed by gentamicin-protection assay (assessed as in ). () Phagocytosis of fluorescein isothiocyanate (FITC)-conjugated zymosan particles by wild-type and Ip6k1−/− neutrophils. Original magnification, ×60. () Index for the phagocytosis of bioparticles by neutrophils in , presented as bioparticles engulfed by 100 neutrophils (n > 200 ne! utrophils per group). () Index for the binding of bioparticles with neutrophils in , presented as bioparticles bound by 100 neutrophils. *P < 0.01 (Student's t-test). Data are from three independent experiments (–,,; mean ± s.d.) or are representative of three experiments (). Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Amit Prasad & * Yonghui Jia Affiliations * Department of Pathology, Harvard Medical School, Department of Lab Medicine, Children's Hospital Boston, Boston, Massachusetts, USA. * Amit Prasad, * Yonghui Jia, * Yitang Li, * Supriya K Jain, * Jia Zhong, * Saurabh Ghosh Roy, * Fabien Loison, * Subhanjan Mondal, * Jiro Sakai, * Catlyn Blanchard & * Hongbo R Luo * Department of Neuroscience, Department of Pharmacology and Molecular Sciences and Department of Psychiatry, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * Anutosh Chakraborty & * Solomon H Snyder * Dana-Farber/Harvard Cancer Center, Harvard Medical School, Boston, Massachusetts, USA. * Hongbo R Luo Contributions A.P., Y.J., A.C., S.H.S. and H.R.L. designed the experiments; A.P., Y.J., A.C., Y.L., S.K.J., J.Z., S.G.R., F.L., S.M., J.S. and C.B. did the experiments; A.P., Y.J., A.C., S.H.S. and H.R.L. analyzed data; and A.P., Y.J., S.H.S. and H.R.L. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Hongbo R Luo Author Details * Amit Prasad Search for this author in: * NPG journals * PubMed * Google Scholar * Yonghui Jia Search for this author in: * NPG journals * PubMed * Google Scholar * Anutosh Chakraborty Search for this author in: * NPG journals * PubMed * Google Scholar * Yitang Li Search for this author in: * NPG journals * PubMed * Google Scholar * Supriya K Jain Search for this author in: * NPG journals * PubMed * Google Scholar * Jia Zhong Search for this author in: * NPG journals * PubMed * Google Scholar * Saurabh Ghosh Roy Search for this author in: * NPG journals * PubMed * Google Scholar * Fabien Loison Search for this author in: * NPG journals * PubMed * Google Scholar * Subhanjan Mondal Search for this author in: * NPG journals * PubMed * Google Scholar * Jiro Sakai Search for this author in: * NPG journals * PubMed * Google Scholar * Catlyn Blanchard Search for this author in: * NPG journals * PubMed * Google Scholar * Solomon H Snyder Search for this author in: * NPG journals * PubMed * Google Scholar * Hongbo R Luo Contact Hongbo R Luo Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Movie 1 (2M) Chemoattractant-elicited polarization of WT neutrophils * Supplementary Movie 2 (2M) Chemoattractant-elicited polarization of InsP6K−/− neutrophils * Supplementary Movie 3 (819K) Adhesion of WT (left) and InsP6K−/− (right) neutrophils under shear flow * Supplementary Movie 4 (1M) Detachment of adhered WT (left) and InsP6K−/− (right) neutrophils under shear flow * Supplementary Movie 5 (905K) Chemotaxis of WT neutrophils (bottom) towards 1 AM of fMLP (top) in EZ-TAXIScan chamber * Supplementary Movie 6 (885K) Chemotaxis of InsP6K1−/− neutrophils (bottom) towards 1 AM of fMLP (top) in EZ-TAXIScan chamber PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–10 and Supplementary Methods Additional data - The junctional adhesion molecule JAM-C regulates polarized transendothelial migration of neutrophils in vivo
- Nat Immunol 12(8):761-769 (2011)
Nature Immunology | Article The junctional adhesion molecule JAM-C regulates polarized transendothelial migration of neutrophils in vivo * Abigail Woodfin1 * Mathieu-Benoit Voisin1 * Martina Beyrau1 * Bartomeu Colom1 * Dorothée Caille2 * Frantzeska-Maria Diapouli3 * Gerard B Nash3 * Triantafyllos Chavakis4, 6 * Steven M Albelda5, 6 * G Ed Rainger3, 6 * Paolo Meda2, 6 * Beat A Imhof2 * Sussan Nourshargh1 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyYear published:(2011)DOI:doi:10.1038/ni.2062Received10 March 2011Accepted26 May 2011Published online26 June 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The migration of neutrophils into inflamed tissues is a fundamental component of innate immunity. A decisive step in this process is the polarized migration of blood neutrophils through endothelial cells (ECs) lining the venular lumen (transendothelial migration (TEM)) in a luminal-to-abluminal direction. By real-time confocal imaging, we found that neutrophils had disrupted polarized TEM ('hesitant' and 'reverse') in vivo. We noted these events in inflammation after ischemia-reperfusion injury, characterized by lower expression of junctional adhesion molecule C (JAM-C) at EC junctions, and they were enhanced by blockade or genetic deletion of JAM-C in ECs. Our results identify JAM-C as a key regulator of polarized neutrophil TEM in vivo and suggest that reverse TEM of neutrophils can contribute to the dissemination of systemic inflammation. View full text Figures at a glance * Figure 1: Development of a four-dimensional imaging platform for the analysis of leukocyte TEM in vivo. () Confocal intravital microscopy of cremasteric venules of lys-EGFP-ki mice (green leukocytes) immunostained in vivo for EC junctions by intrascrotal injection of Alexa Fluor 555–labeled mAb 390 to PECAM-1 (red) and stimulated for 120 min by intrascrotal injection of IL-1β, followed by surgical exteriorization and capture of images in vivo at intervals of 1 min for a period of 90 min (from 120 to 210 min after IL-1β injection), showing the development of an inflammatory response in a post-capillary venular segment (Supplementary Video 1). Original magnification, ×40. Scale bar, 10 μm. (,) Brightfield intravital microscopy of leukocyte adhesion and transmigration in wild-type mice given no pretreatment (No mAb) or pretreated intravenously () or intrascrotally () with mAb 390, mAb MEC 13.3 or IgG2b isotype-matched control mAb, then left untreated (saline) or given intrascrotal administration of IL-1β, followed by exteriorization of tissues 4 h later. *P < 0.05 and **P ! < 0.01, IL-1β versus saline and ***P < 0.001 (analysis of variance (ANOVA)). Data are representative of six experiments () or are from three to eight () or three to five () experiments per group (one mouse per experiment; error bars (,), s.e.m.). * Figure 2: Neutrophil paracellular and transcellular TEM in vivo. () Paracellular TEM of a leukocyte (*; top row) and its associated transient junctional pore formation (bottom row) in IL-1β-stimulated, PECAM-1-labeled tissues (red) of lys-EGFP-ki mice (leukocytes, green; time (below images) relative to Supplementary Video 3). () Transcellular TEM through ECs with no disruption of PECAM-1-enriched junctions, in tissues as in (top row); below, false-color images of the PECAM-1 channel (white, high intensity; blue, low intensity) for visualization of the transcellular pore (arrows); time (below images) relative to Supplementary Video 4. (,) Paracellular TEM () and transcellular TEM () in tissues as in . Right, transcellular pores in close proximity to EC junctions without disruption of PECAM-1-labeled junctions. Dotted yellow lines indicate areas analyzed further in ,. Scale bars (–), 10 μm. (,) Linear intensity profiles of the PECAM-1 channel (EC; red) and GFP (leukocyte; green) of TEM events along the dotted lines in ,; intensity profi! les after TEM illustrate pore closure. JN, junction. (,) Frequency () and duration () of TEM events induced by IL-1β, fMLP or I-R. *P < 0.01 and **P < 0.001, nonjunctional versus bicellular and ***P < 0.05 and †P < 0.001, nonjunctional versus multicellular (ANOVA). Data are representative of four to seven experiments () or are from four to seven experiments with >103 TEM events per group (–; one mouse per experiment; error bars (,), s.e.m.). * Figure 3: Disrupted forms of polarized paracellular TEM. () Time-lapse images of a GFP-expressing leukocyte (*) undergoing hesitant paracellular TEM: top, transverse section of venule; middle, luminal view; bottom, sub-EC segments of the migrating leukocyte in light green with dashed outline (time (below images) relative to Supplementary Video 5; additional examples, Supplementary Fig. 2 and Supplementary Videos 6 and 7). () Time-lapse images of a leukocyte undergoing rTEM as it migrates through a bicellular junction in an abluminal-to-luminal direction, disengages from the junction and crawls away on the luminal surface: top, transverse section of venule; bottom, luminal view (time (below images) relative to Supplementary Video 8). () Frequency of normal, hesitant and reverse paracellular TEM events induced by IL-1β, fMLP or I-R, presented as frequency among total paracellular TEM events. () Duration of normal, hesitant and rTEM events in tissues injured by I-R. Scale bars (,), 10 μm. *P < 0.001, normal versus disrupted (hesita! nt TEM and rTEM) and **P < 0.001, hesitant TEM versus rTEM (ANOVA). Data are representative of seven experiments (,) or are from four to seven experiments with >103 TEM events per group (,; one mouse per experiment; error bars (,), s.e.m.). * Figure 4: Disrupted forms of polarized paracellular neutrophil TEM. () Frequency of normal and disrupted TEM events (rTEM and hesitant TEM) induced by I-R in control and neutrophil-depleted lys-EGFP-ki mice, assessed over 30 min (standard image sequence capture time). () GFP intensity of monocytes (CD115+; n = 81) and neutrophils (CD115−; n = 158) in CCL2-stimulated cremaster muscles from lys-EGFP-ki mice (n = 4), quantified from two-dimensional projections at standard settings (routinely used and optimized for analysis of GFP+ neutrophils) and high-GFP-gain image-capture settings, compared with the threshold intensity for visibility in three-dimensional reconstructions (dashed line; ~200 Gy/μm2). () Three-dimensional reconstruction image of a CCL2-stimulated lys-EGFP-ki mouse cremasteric venule, with EC junctions labeled with antibody to PECAM-1 (red), acquired by standard GFP gain settings: green, GFP+ neutrophils; blue, monocytes immunostained with intravenous mAb to CD115. Scale bar, 10 μm. *P < 0.05 and **P < 0.01, control versus ne! utrophil depletion (ANOVA) or **P < 0.01 and ***P < 0.001, background versus leukocyte associated (ANOVA). Data are from seven to nine () or four experiments () or are representative of four experiments (; one mouse per experiment; error bars (,), s.e.m.). * Figure 5: Disruption of JAM-C at EC junctions in response to I-R injury but not in response to IL-1β. () Microscopy of cremasteric venules in wild-type mouse tissues left unstimulated (control), stimulated with IL-1β or subjected to I-R injury and then immunostained ex vivo for VE-cadherin (green), PECAM-1 (red) or JAM-C (blue); N, JAM-C+ nerve. Scale bars, 10 μm. () Fluorescence intensity at EC junctions in mice treated as in or pretreated with superoxide dismutase and catalase (SOD + cat) before the induction of I-R injury (Supplementary Methods). AU, arbitrary units. *P < 0.05 and **P < 0.01, stimulus versus treatment (ANOVA). () Immunoelectron microscopy analysis of the distribution of JAM-C in ECs in control (saline-injected or sham-operated) tissues and cremaster muscles stimulated with IL-1β or subjected to I-R injury (image examples and raw data, Supplementary Fig. 5a,b). *P < 0.001, I-R versus IL-1β (chi-squared test). Data are representative of () or are from () seven to fifteen experiments with four to ten vessels per mouse or two to five experiments with 17�! �33 total ECs per group (; one experiment per mouse; error bars (,), s.e.m.). * Figure 6: Critical role for EC JAM-C in mediating polarized neutrophil paracellular TEM. () Normal, hesitant and rTEM responses in lys-EGFP-ki mice pretreated with intravenous saline (no mAb), control nonblocking mAb H36 to JAM-C or blocking H33 mAb to JAM-C (each at a dose of 3 mg per kg body weight (3 mg/kg)), then subjected to I-R injury; results are presented as frequency among total observed paracellular responses. *P < 0.05 and **P < 0.01 (multinomial logistic regression analysis). () All disrupted TEM events (hesitant TEM and rTEM) in lys-EGFP-ki mice given no pretreatment (no mAb) or pretreated with mAb to JAM-A, mAb to JAM-C or soluble JAM-C (all administered intravenously at a dose of 3 mg or 10 mg per kg body weight) and in lys-EGFP-ki mice with EC-specific JAM-C deficiency not pretreated with antibody (eJAM-C-KO), then subjected to I-R injury or treated with IL-1β; results are presented as frequency among total quantified paracellular responses. *P < 0.05, treated versus untreated (ANOVA). Data are from four to ten experiments with 52–109 total TE! M events per group (one mouse per experiment; error bars, s.e.m.). * Figure 7: Association of neutrophil rTEM with pulmonary inflammation after I-R injury. () ICAM-1 expression on fresh bone marrow neutrophils (Fresh BM) and bone marrow neutrophils that had undergone rTEM in vitro (rTEM BM; Supplementary Methods), analyzed by flow cytometry (left), and quantification of ICAM-1 expression on peritoneal and blood neutrophils, fresh bone marrow neutrophils, bone marrow neutrophils cultured for 24 h (cultured BM) and bone marrow neutrophils that had undergone rTEM in vitro, presented as relative fluorescence intensity relative to (the binding of isotype-matched control mAb RFI; right). () Infiltration of lung tissue by neutrophils after sham operation or I-R injury of the cremaster muscle (cremaster I-R) or lower limb (limb I-R), with (light gray) or without (black and dark gray) treatment with mAb to JAM-C (3 mg/kg), quantified by flow cytometry of cells from digested and homogenized tissues. () Edema formation after sham operation or lower-limb I-R injury, assessed as local accumulation of intravenously injected Evans blue. () Fl! ow cytometry analysis of ICAM-1 expression by neutrophils in pulmonary vascular washouts from mice subjected to sham operation or lower-limb I-R. FSC, forward scatter. Numbers in outlined areas indicate percent FSChiICAM-1hi cells. () Generation of ROS (quantified as the fluorescence intensity of dihydrorhodamine 123 (DHR)) by ICAM-1lo and ICAM-1hi neutrophils in pulmonary vascular washouts of mice subjected to lower-limb I-R; lymphocytes serve as a negative control (right). () Total ICAM-1hi neutrophils in pulmonary vascular washouts of mice subjected to sham operation or I-R injury with or without treatment with mAb to JAM-C (as in ). () Correlation of the frequency of ICAM-1hi neutrophils in pulmonary vascular washouts and number of neutrophils infiltrating lung tissue in all mice subjected to I-R injury. *P < 0.05, **P < 0.01 and ***P < 0.001, control versus experimental and †P < 0.001 (ANOVA (–) or Spearman's rank correlation ()). Data are representative of three e! xperiments (, left) or six experiments (, left) or are from fi! ve to nine ( (right), ,,) or six (,,) experiments per group (one mouse per experiment; error bars, s.e.m.). Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Triantafyllos Chavakis, * Steven M Albelda, * G Ed Rainger & * Paolo Meda Affiliations * William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, UK. * Abigail Woodfin, * Mathieu-Benoit Voisin, * Martina Beyrau, * Bartomeu Colom & * Sussan Nourshargh * Centre Médical Universitaire, Geneva, Switzerland. * Dorothée Caille, * Paolo Meda & * Beat A Imhof * Centre for Cardiovascular Research, School of Clinical and Experimental Medicine, College of Medicine and Dentistry, University of Birmingham, Birmingham, UK. * Frantzeska-Maria Diapouli, * Gerard B Nash & * G Ed Rainger * Dresden University of Technology, Dresden, Germany. * Triantafyllos Chavakis * University of Pennsylvania, Philadelphia, Pennsylvania, USA. * Steven M Albelda Contributions A.W. designed and did most experiments, analyzed data and contributed to the writing of the manuscript; M.-B.V. designed and did the immunofluorescence staining experiments and contributed to method development and data analysis and interpretation; M.B. designed and did flow cytometry assays and contributed to data analysis and interpretation; B.C., D.C. and F.-M.D. designed and did some assays; G.B. T.C., S.M.A., G.E.R. and P.M. provided reagents and/or contributed to the design of experiments; B.A.I. provided reagents and made intellectual contributions to the study; and S.N. provided overall project supervision and contributed to the design of the experiments and the writing of the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Sussan Nourshargh Author Details * Abigail Woodfin Search for this author in: * NPG journals * PubMed * Google Scholar * Mathieu-Benoit Voisin Search for this author in: * NPG journals * PubMed * Google Scholar * Martina Beyrau Search for this author in: * NPG journals * PubMed * Google Scholar * Bartomeu Colom Search for this author in: * NPG journals * PubMed * Google Scholar * Dorothée Caille Search for this author in: * NPG journals * PubMed * Google Scholar * Frantzeska-Maria Diapouli Search for this author in: * NPG journals * PubMed * Google Scholar * Gerard B Nash Search for this author in: * NPG journals * PubMed * Google Scholar * Triantafyllos Chavakis Search for this author in: * NPG journals * PubMed * Google Scholar * Steven M Albelda Search for this author in: * NPG journals * PubMed * Google Scholar * G Ed Rainger Search for this author in: * NPG journals * PubMed * Google Scholar * Paolo Meda Search for this author in: * NPG journals * PubMed * Google Scholar * Beat A Imhof Search for this author in: * NPG journals * PubMed * Google Scholar * Sussan Nourshargh Contact Sussan Nourshargh Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Video 1 (2M) Development of an inflammatory response in an IL-1β-stimulated tissue. * Supplementary Video 2 (1M) Migration of leukocytes in a paracellular mode. * Supplementary Video 3 (1M) Paracellular transmigration and pore formation * Supplementary Video 4 (1M) Transcellular TEM and pore formation * Supplementary Video 5 (1M) Hesitant TEM as induced by I-R injury (example 1). * Supplementary Video 6 (1M) Hesitant TEM as induced by I-R injury (example 2). * Supplementary Video 7 (942K) Hesitant TEM as induced by I-R injury (example 3). * Supplementary Video 8 (2M) Reverse TEM as induced by I-R injury. PDF files * Supplementary Text and Figures (774K) Supplementary Figures 1–6, Supplementary Methods and Supplementary Results Additional data - Perforin pores in the endosomal membrane trigger the release of endocytosed granzyme B into the cytosol of target cells
- Nat Immunol 12(8):770-777 (2011)
Nature Immunology | Article Perforin pores in the endosomal membrane trigger the release of endocytosed granzyme B into the cytosol of target cells * Jerome Thiery1, 2 * Dennis Keefe1, 2 * Steeve Boulant1, 3 * Emmanuel Boucrot1, 3 * Michael Walch1, 2 * Denis Martinvalet1, 2, 4 * Ing Swie Goping5 * R Chris Bleackley5 * Tomas Kirchhausen1, 3 * Judy Lieberman1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyYear published:(2011)DOI:doi:10.1038/ni.2050Received18 March 2011Accepted10 May 2011Published online19 June 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg How the pore-forming protein perforin delivers apoptosis-inducing granzymes to the cytosol of target cells is uncertain. Perforin induces a transient Ca2+ flux in the target cell, which triggers a process to repair the damaged cell membrane. As a consequence, both perforin and granzymes are endocytosed into enlarged endosomes called 'gigantosomes'. Here we show that perforin formed pores in the gigantosome membrane, allowing endosomal cargo, including granzymes, to be gradually released. After about 15 min, gigantosomes ruptured, releasing their remaining content. Thus, perforin delivers granzymes by a two-step process that involves first transient pores in the cell membrane that trigger the endocytosis of granzyme and perforin and then pore formation in endosomes to trigger cytosolic release. View full text Figures at a glance * Figure 1: Inhibition of gigantosome formation does not impair granzyme B–induced apoptosis. () Flow cytometry of eGFP in untransfected control HeLa cells or in cells transfected with plasmid encoding eGFP-tagged wild-type Rab5 (Rab5(WT)) or Rab5(S34N) (top row), then treated for 2 h with buffer or a sublytic concentration of rat perforin (PFN) or 100 nM native human granzyme B (GzmB) alone or together (PFN + GzmB) and labeled with monoclonal antibody M30 (which recognizes a cytokeratin-18 epitope after caspase cleavage) for analysis of apoptosis of eGFP+ cells (below). Numbers above bracketed lines indicate percent eGFP+ cells (top row) or cells that underwent apoptosis (below); numbers in parentheses below bracketed lines indicate mean fluorescence intensity. () Frequency of M30+ apoptotic cells in . NS, not significant (unpaired two-tailed Student's t-test). () Immunoblot analysis of the activation of pro-caspase-3 in HeLa cells transfected with plasmid encoding eGFP-tagged wild-type Rab5 or Rab5(S34N), then treated for 30 min with buffer or a sublytic concentrat! ion of rat perforin or 50 nM native human granzyme B alone or together. Actin serves as a loading control. Data are from three independent experiments (,; mean ± s.d.) or are representative of two independent experiments (). * Figure 2: Perforin inhibits endosome acidification. (,) Frequency of M30+ apoptotic cells among HeLa cells preincubated for 1 h with bafilomycin A1 () or NH4Cl () with subsequent treatment (killing assay) for 2 h with granzyme B or a sublytic concentration of rat perforin, alone or together, with (1 h + 2 h) or without (1 h) the addition of bafilomycin A1 or NH4Cl during the killing assay. () 51Cr-release analysis of NK cell–mediated killing of 721.221 target cells with (+) or without (−) pretreatment with bafilomycin A1. () Live-cell imaging of HeLa cells expressing eGFP-tagged EEA1 (eGFP-EEA1) incubated with pHrodo dextran with or without a sublytic concentration of perforin, followed by analysis of fluorescence in normal endosomes (−PFN) or in gigantosomes (+PFN) 5 min later (T + 5 min; downward arrow); for numbers below images, time 0 is 5 min after the addition of pHrodo dextran. Color keys (right margin) indicate fluorescence intensity levels in arbitrary units throughout. Scale bars, 2 μm. () Pseudocoloring of t! he fluorescence intensity of pHrodo dextran in (image size as in ). () Fluorescence intensity of pHrodo dextran in normal endosomes or gigantosomes (n = 6) in the cells in ; + Dextran ± PFN indicates dextran with or without perforin. AU, arbitrary units. () Confocal microscopy of eGFP-EEA1–transfected HeLa cells 10 min after the addition of a sublytic concentration of perforin and pHrodo dextran; dashed lines indicate plasma membrane. Scale bars, 10 μm. Data are from four (,) or six (–) independent experiments (mean ± s.d. in ,,) or are representative of two () or three () independent experiments (mean ± s.d. of triplicates in ). * Figure 3: Perforin multimerizes in gigantosome membranes. (–) Confocal microscopy of HeLa cells stained with Pf-80 (,) or Pf-344 (,) after incubation for various times (above images) with buffer or a sublytic concentration of human perforin; dashed lines indicate plasma membrane. Color bars indicate staining intensity; numbers in images (,) indicate percent cells with PFN staining (mean ± s.d.). Scale bars, 10 μm (,) or 5 μm (,). (,) Flow cytometry of HeLa cells stained with Pf-80 or Pf-344 at various times (left margin () or horizontal axis ()) after incubation with a sublytic concentration of human perforin. Numbers above bracketed lines () indicate percent perforin-positive cells. *P < 0.025 and **P < 0.002 (; unpaired two-tailed Student's t-test). () Immunoblot analysis of perforin aggregates in K562 human myelogenous leukemia cells incubated for various times (above lanes) with native human perforin, followed by the addition of the crosslinking agent disuccinimidyl suberate (DSS) for 30 min; arrowheads indicate perforin m! onomer (60 kDa) and perforin multimers above (~420 kDa and near top). Data are representative of at least three independent experiments (–,), are from one experiment () or are representative of three independent experiments (; mean ± s.d.). * Figure 4: Endocytosed granzyme B is released into the cytosol beginning within ~10 min of the loading of perforin. () Spinning-disk confocal imagery of HeLa cells treated for various times (left margin) with granzyme B with or without a sublytic concentration of perforin, then fixed and stained for EEA1 and granzyme B. Numbers in images (top right corner; Merge) indicate percent cells with granzyme B in gigantosomes or in the cytosol (mean ± s.d.). () Microscopy of HeLa cells treated for various times (above images) with native human granzyme B with or without a sublytic concentration of rat perforin, then fixed and stained for granzyme B and with the DNA-intercalating dye DAPI; images were acquired by three-dimensional capture widefield microscopy followed by iterative deconvolution and projection. () Microscopy of HeLa cells treated for various times (above images) with Alexa Fluor–labeled granzyme B (A488-GzmB) with or without a sublytic concentration of perforin (left margin), then fixed. Dashed lines (,) indicate plasma membrane; color bars indicate fluorescence intensity. Scale ! bars, 5 μm () or 10 μm (,). Data are from three independent experiments () or are representative of three () or two () independent experiments. * Figure 5: Release of endocytosed cargo from gigantosomes into the cytosol. () Microscopy of the uptake of TR-dextran in HeLa cells transfected with plasmid encoding eGFP-EEA1 and left untreated (−PFN) or treated for 10 min with a sublytic concentration of perforin (+PFN). () Microscopy of the release of dextran from gigantosomes in HeLa cells transfected with plasmid encoding eGFP-EEA1 and incubated for 10–17 min with TR-dextran and a sublytic concentration of perforin. () Time-lapse confocal microscopy of eGFP-EEA1+ HeLa cells, acquired every 10 s beginning 10 min after treatment with TR-dextran and a sublytic concentration of perforin (source, Supplementary Movie 1). White arrowheads indicate discrete release of TR-dextran; open arrowheads indicate dextran dispersal after gigantosome rupture. () Intensity of dextran in a perforin-induced gigantosome (+PFN) or in a normal endosome (−PFN; right vertical axis) and in the local surrounding area (left vertical axis) of HeLa cells beginning 7 min after treatment with TR-dextran with or without a ! sublytic concentration of perforin (+Dextran ± PFN); background intensity was measured in a region devoid of gigantosomes and endosomes. Below, images corresponding to the data above. Color bars indicate fluorescence intensity. Scale bars, 5 μm () or 2 μm (–). Data are representative of six (), five () or three () independent experiments. * Figure 6: Granzyme B and perforin localize in gigantosomes in target cells during lysis by NK cells. (,) Spinning-disk confocal microscopy (z-stack series projections) of YT-Indy NK cells incubated for various times (left margin) with 721.221 target cells, then stained for granzyme B () or perforin (). Arrows indicate granzyme B or perforin signal (pseudocolor) in target cells; dashed lines indicate plasma membrane. () Widefield live imaging (time-lapse series) of YT-Indy NK cells expressing eGFP–granzyme B (eGFP-GzmB) incubated with 721.221 target cells and imaged every minute (numbers in top right corners indicate time (in min) after conjugate formation). Phase contrast is red. For visualization of the low granzyme B signal in the target cell, the eGFP channel was overexposed. Bottom row right (No overexposure), control YT-Indy cell imaged with normal exposure time to confirm the granular expression of eGFP–granzyme B. Color bars indicate fluorescence intensity. Scale bars, 10 μm. Data are representative of two independent experiments. Author information * Abstract * Author information * Supplementary information Affiliations * Immune Disease Institute and Program in Cellular and Molecular Medicine, Children's Hospital, Boston, Massachusetts, USA. * Jerome Thiery, * Dennis Keefe, * Steeve Boulant, * Emmanuel Boucrot, * Michael Walch, * Denis Martinvalet, * Tomas Kirchhausen & * Judy Lieberman * Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA. * Jerome Thiery, * Dennis Keefe, * Michael Walch, * Denis Martinvalet & * Judy Lieberman * Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, USA. * Steeve Boulant, * Emmanuel Boucrot & * Tomas Kirchhausen * Department of Cell Physiology and Metabolism, University of Geneva, Geneva, Switzerland. * Denis Martinvalet * Department of Biochemistry, University of Alberta, Edmonton, Alberta, Canada. * Ing Swie Goping & * R Chris Bleackley Contributions J.T. designed and did experiments, analyzed data and wrote the manuscript; S.B., D.K. and E.B. did and helped analyze some experiments; M.W. and D.M. purified granzyme B and helped with perforin purification; I.S.G. and R.C.B. developed the NK cell line expressing eGFP–granzyme B; and T.K. and J.L. conceived of and supervised the project, helped design experiments and coordinated the writing of the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Judy Lieberman Author Details * Jerome Thiery Search for this author in: * NPG journals * PubMed * Google Scholar * Dennis Keefe Search for this author in: * NPG journals * PubMed * Google Scholar * Steeve Boulant Search for this author in: * NPG journals * PubMed * Google Scholar * Emmanuel Boucrot Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Walch Search for this author in: * NPG journals * PubMed * Google Scholar * Denis Martinvalet Search for this author in: * NPG journals * PubMed * Google Scholar * Ing Swie Goping Search for this author in: * NPG journals * PubMed * Google Scholar * R Chris Bleackley Search for this author in: * NPG journals * PubMed * Google Scholar * Tomas Kirchhausen Search for this author in: * NPG journals * PubMed * Google Scholar * Judy Lieberman Contact Judy Lieberman Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Video 1 (2M) PFN-mediated release of endocytosed dextran from a gigantosome. Representative EGFP-EEA-1+ (green) gigantosomes from transfected HeLa cells treated with TR-Dextran (red) and sublytic rat PFN. Live images were acquired by spinning disk confocal microscopy starting 10 min after addition of TR-Dextran and PFN (duration 5 min, 2.5 sec/frame). Selected static individual frames from these movies are shown in Figure 5c. * Supplementary Video 2 (119K) PFN-mediated release of endocytosed dextran from a gigantosome. Representative EGFP-EEA-1+ (green) gigantosomes from transfected HeLa cells treated with TR-Dextran (red) and sublytic rat PFN. Live images were acquired by spinning disk confocal microscopy starting 10 min after addition of TR-Dextran and PFN (duration 6 min, 10 sec/frame). Selected static individual frames from these movies are shown in Supplementary Figure 6a. * Supplementary Video 3 (475K) PFN-mediated release of endocytosed dextran from a gigantosome. Representative EGFP-EEA-1+ (green) gigantosomes from transfected HeLa cells treated with TR-Dextran (red) and sublytic rat PFN. Live images were acquired by spinning disk confocal microscopy starting 10 min after addition of TR-Dextran and PFN (duration 13.5 min, 10 sec/frame). Selected static individual frames from these movies are shown in Supplementary Figure 6b. PDF files * Supplementary Text and Figures (967K) Supplementary Figures 1–7 and Supplementary Methods Additional data - The transcription factor NR4A1 (Nur77) controls bone marrow differentiation and the survival of Ly6C− monocytes
- Nat Immunol 12(8):778-785 (2011)
Nature Immunology | Article The transcription factor NR4A1 (Nur77) controls bone marrow differentiation and the survival of Ly6C− monocytes * Richard N Hanna1 * Leo M Carlin2 * Harper G Hubbeling3 * Dominika Nackiewicz4 * Angela M Green1 * Jennifer A Punt3 * Frederic Geissmann2 * Catherine C Hedrick1 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyYear published:(2011)DOI:doi:10.1038/ni.2063Received18 April 2011Accepted27 May 2011Published online03 July 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The transcription factors that regulate differentiation into the monocyte subset in bone marrow have not yet been identified. Here we found that the orphan nuclear receptor NR4A1 controlled the differentiation of Ly6C− monocytes. Ly6C− monocytes, which function in a surveillance role in circulation, were absent from Nr4a1−/− mice. Normal numbers of myeloid progenitor cells were present in Nr4a1−/− mice, which indicated that the defect occurred during later stages of monocyte development. The defect was cell intrinsic, as wild-type mice that received bone marrow from Nr4a1−/− mice developed fewer patrolling monocytes than did recipients of wild-type bone marrow. The Ly6C− monocytes remaining in the bone marrow of Nr4a1−/− mice were arrested in S phase of the cell cycle and underwent apoptosis. Thus, NR4A1 functions as a master regulator of the differentiation and survival of 'patrolling' Ly6C− monocytes. View full text Figures at a glance * Figure 1: Expression of NR4A1 by Ly6C− monocytes. () Quantitative real-time PCR analysis of the expression of Nr4a1, Nr4a2 and Nr4a3 mRNA in Ly6C+ and Ly6C− cells and MDPs and common myeloid precursor (CMP) populations sorted by flow cytometry from wild-type bone marrow (n = 6 mice), presented relative to expression by Ly6C+ monocytes. () Intracellular staining of NR4A1 in Ly6C+ and Ly6C− monocyte populations from wild-type bone marrow and in CD11b− nonmyeloid cells, assessed by flow cytometry with antibody to NR4A1. MFI, mean fluorescence intensity; Isotype, isotype-matched control antibody. In ,, isolated monocyte populations were over 95% pure, as measured in cytospin preparations of sorted cells stained with Hema 3 dye (used to assess cellular morphology). () Expression of GFP (NR4A1-GFP) in live F4/80+CD11b+ Ly6C+ and Ly6C− monocytes from the peripheral blood of a NR4A1-GFP mouse and cells from a NR4A1-GFP–negative (GFP−) littermate (right), assessed by flow cytometry; left and middle, gating strategy to id! entify Ly6C+ and Ly6C− monocytes: the live cell population (outlined area, left) was further gated on Ly6C+F4/80+ cells (top outlined area, middle) or Ly6C−F4/80+ cells (bottom outlined area, middle). Numbers adjacent to outlined areas indicate percent of gated cell population (left and center); numbers above bracketed lines indicate percent GFP+ cells (right). SSC, side scatter; FSC, forward scatter. () Flow cytometry of NR4A1-GFP peripheral blood cells; numbers adjacent to outlined areas indicate percent CD62L−GFP+ cells (left), CD11a+GFP+ cells (middle) or CD11c+GFP+ cells (right); numbers in quadrants indicate percent cells in each. Data are representative of four independent experiments (mean and s.e.m. in ,). * Figure 2: Absence of Ly6C− monocytes in Nr4a1−/− mice. () Expression of CD115 and CD11b by live Nr4a1−− or wild-type (WT) cells with low side scatter (left), followed by further gating of CD115+CD11b+ monocyte populations for expression of Ly6C (right). Numbers adjacent to outlined areas indicate percent CD115+CD11b+ cells (left), Ly6C+CD11b+ cells (top right) or Ly6C−CD11b+ cells (bottom right). () Total monocytes per spleen (far left), total Ly6C+ or Ly6C− monocytes per spleen (middle left) and frequency of Ly6C+ or Ly6C− monocytes among all live spleen cells (middle); frequency of Ly6C+ and Ly6C− monocyte populations in blood (middle right) and bone marrow (far right) of Nr4a1−− mice and wild-type mice (n = 10 per group), analyzed by flow cytometry. *P < 0.001 (unpaired Student's t-test). () Quantification of hematopoietic cell populations in the blood of Nr4a1−− and wild-type mice (n = 10 per group), analyzed by flow cytometry: Mono, monocytes; Gran, granulocytes; NKT, natural killer T cells; B, B cells; ! T, T cells. *P < 0.01 (unpaired Student's t-test). Data are representative of three independent experiments in each panel (mean and s.e.m. in ,). * Figure 3: Cell-intrinsic defect in monocyte development and lack of patrolling ability of monocytes from Nr4a1−/− bone marrow. () Ly6C+ and Ly6C− monocyte populations in the blood of irradiated (two doses of 600 rads each) Nr4a1−/− recipients reconstituted by transplantation of Nr4a1−/− (Nr4a1−/−Nr4a1−/−) or wild-type (WTNr4a1−/−) whole bone marrow (5 × 106 cells), followed by reconstitution for 6 weeks (assessed as in Fig. 2a). () Quantification of Ly6C+ and Ly6C− monocyte populations in blood from irradiated wild-type or Nr4a1−/− recipients (n = 7 per group) of wild-type or Nr4a1−/− bone marrow (as in ). *P < 0.001 (unpaired Student's t-test). () Tracking of CD11b+ cells in irradiated (9.5 Gy) wild-type CD45.1+ recipients reconstituted with bone marrow from wild-type or Nr4a1−/− CD45.2+ donors; anesthetized recipients were injected intravenously with 10 μg phycoerythrin-conjugated antibody to mouse CD11b (M1/70), then cell tracks (left) and displacement vectors of individual cells (red arrows, right) were assessed after 6 weeks. Scale bars, 60 μm. () Patrolli! ng CD11b+ cells in mice reconstituted with from wild-type bone marrow (n = 2; three fields per hour) or Nr4a1−/− bone marrow (n = 4; seven fields per hour) as described in . *P < 0.01 (unpaired Student's t-test). Data are representative of two independent experiments (mean and s.e.m. in ,). * Figure 4: Normal stem cell populations and abnormal Ly6C− monocytes in Nr4a1−/− mice. () Quantification of hematopoietic stem cells (HSC), common myeloid precursors and MDPs in wild-type and Nr4a1−/− bone marrow (n = 10 mice per group), analyzed by flow cytometry. () Hema 3 staining of CD115+CD11b+ Ly6C+ or Ly6C− monocytes isolated from wild-type or Nr4a1−/− bone marrow by cell sorting. Scale bars, 10 μm. Data are representative of three independent experiments (mean ± s.e.m.). * Figure 5: Specific defect in the differentiation of Nr4a1−/− Ly6C− monocytes from MDPs in the bone marrow. () Frequency of Nr4a1−/− and wild-type donor cells among Ly6C− and Ly6C− monocytes and DCs in the spleen and Ly6C− and Ly6C− cells in the blood of lethally irradiated wild-type CD45.1+ recipients (n = 6 per group) of Nr4a1−/− CD45.2+ and wild-type CD45.1+ whole bone marrow (2.5 × 106 cells from each donor, mixed at a ratio of 1:1). () Frequency of Nr4a1−/− and wild-type donor cells among Ly6C− and Ly6C− cells in the blood of lethally irradiated wild-type CD45.1+ mice (n = 4 per group) that received Nr4a1−/− CD45.2+ and wild-type CD45.1+ MDPs (isolated by cell sorting from bone marrow, with 1 × 104 cells from each donor mixed at a ratio of 1:1), followed by reconstitution for 7 d. Data are representative of two independent experiments. * Figure 6: Abnormal cell cycle and DNA damage in Ly6C− monocytes from Nr4a1−/− mice. () Flow cytometry analysis of the cell-cycle progression of wild-type and Nr4a1−/−Ly6C− bone marrow monocytes, stained with propidium iodide. Numbers above bracketed lines indicate percent cells in phases G0–G1 (left), S (middle) and G2 (right). () Quantification of results in (n = 6 mice per group). P < 0.009, Nr4a1−/− versus wild-type, for G0–G1 and S (unpaired Student's t-test). () Flow cytometry analysis of DNA damage in wild-type and Nr4a1−/− Ly6C− bone marrow monocytes during cell-cycle progression, assessed as phosphorylation of histone H2AX at Ser139 (p-H2AX(S139)) and propidium iodide staining. Numbers adjacent to outlined areas indicate percent cells in phases G0–G1 (left) or S–G2 (right). () Phosphorylation of histone H2AX at Ser139 in wild-type and Nr4a1−/− Ly6C− bone marrow monocytes. () Quantitative real-time PCR analysis of the expression of transcripts encoding cyclin A2 (Ccna2), Cdk1 (Cdc2a) and E2F2 (E2f2) in Ly6C− monocytes ! isolated by flow cytometry from Nr4a1−/− or wild-type bone marrow (n = 6 mice per group), presented relative to expression by wild-type cells. *P < 0.05 (unpaired Student's t-test). Data are representative of three (), two (,) or four () experiments (mean and s.e.m. in ). * Figure 7: Greater apoptosis exclusively of Ly6C− bone marrow monocytes from Nr4a1−/− mice. () Apoptosis of Ly6C+ and Ly6C− monocytes from the bone marrow, spleen and blood of wild-type and Nr4a1−/− mice (n = 6 per group), assessed by flow cytometry analysis of annexin V (AnnV) staining. *P < 0.01 (unpaired Student's t-test). () Apoptosis and cell death of Ly6C− bone marrow monocytes from wild-type and Nr4a1−/− mice (n = 6 per group), assessed as annexin V and propidium iodide staining, respectively (left). Numbers in quadrants indicate percent cells in each. Right, quantification of apoptotic and dead cells. *P < 0.01 (unpaired Student's t-test). () Frequency of wild-type and Nr4a1−/− bone marrow monocytes (n = 8 mice per group) expressing cleaved (active) caspase-3, assessed by flow cytometry. *P < 0.009 (unpaired Student's t-test). () Immunofluorescence microscopy of cleaved (active) caspase-3 (green) in Ly6C− bone marrow monocytes isolated by flow cytometry from wild-type and Nr4a1−/− mice; nuclei are stained with the DNA-intercalating dye! DAPI. Scale bar, 5 μm. () Apoptosis of myeloid stem cell populations in bone marrow from wild-type and Nr4a1−/− mice (n = 6 per group), assessed by flow cytometry analysis of annexin V staining. Data are representative of three (,,) or two (,) experiments (mean and s.e.m. in –,). * Figure 8: Lower expression of chemokine receptors, adhesion molecules and differentiation factors in Nr4a1−/− Ly6C− monocytes. () Expression of CX3CR1, CCR2 and CD11a (LFA-1) in monocyte populations from wild-type and Nr4a1−/− bone marrow (n = 5 mice per group), assessed by flow cytometry (left for each), and quantification of the mean fluorescence intensity, presented relative to that in wild-type Ly6C+ cells, set as 1 (right for each). *P < 0.05 (unpaired Student's t-test). () Quantitative real time-PCR analysis of the expression of transcripts encoding CX3CR1 (Cx3cr1), C/EBP-β (Cebpb), JunB (Junb) and PU.1 (Sfpi1) in Ly6C− monocytes isolated by flow cytometry from bone marrow of wild-type or Nr4a1−/− mice (n = 6 per group); results are presented relative to expression in wild-type cells. *P < 0.05 (unpaired Student's t-test). Data are representative of two () or three () experiments (mean and s.e.m.). Author information * Abstract * Author information * Supplementary information Affiliations * Division of Inflammation Biology, La Jolla Institute for Allergy and Immunology, La Jolla, California, USA. * Richard N Hanna, * Angela M Green & * Catherine C Hedrick * Centre for Molecular and Cellular Biology of Inflammation, King's College London, London, UK. * Leo M Carlin & * Frederic Geissmann * Department of Biology, Haverford College, Haverford, Pennsylvania, USA. * Harper G Hubbeling & * Jennifer A Punt * Department of Genetics of Microorganisms, University of Lodz, Lodz, Poland. * Dominika Nackiewicz Contributions R.N.H. and L.M.C. designed and did experiments, analyzed data and contributed to the writing of the manuscript; H.G.H. did experiments with NR4A1-GFP mice; D.N. and A.M.G. did experiments; J.A.P. conceived of the studies of NR4A1-GFP mice, analyzed data and contributed to the writing of the manuscript; F.G. conceived of and directed the research related to intravital microscopy, analyzed data and contributed to the writing of the manuscript; and C.C.H. conceived of the research, directed the study, assisted with experimental design and contributed to the writing of the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Catherine C Hedrick Author Details * Richard N Hanna Search for this author in: * NPG journals * PubMed * Google Scholar * Leo M Carlin Search for this author in: * NPG journals * PubMed * Google Scholar * Harper G Hubbeling Search for this author in: * NPG journals * PubMed * Google Scholar * Dominika Nackiewicz Search for this author in: * NPG journals * PubMed * Google Scholar * Angela M Green Search for this author in: * NPG journals * PubMed * Google Scholar * Jennifer A Punt Search for this author in: * NPG journals * PubMed * Google Scholar * Frederic Geissmann Search for this author in: * NPG journals * PubMed * Google Scholar * Catherine C Hedrick Contact Catherine C Hedrick 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 1–8 Additional data - Systems biology of vaccination for seasonal influenza in humans
- Nat Immunol 12(8):786-795 (2011)
Nature Immunology | Resource Systems biology of vaccination for seasonal influenza in humans * Helder I Nakaya1, 2 * Jens Wrammert1, 3 * Eva K Lee4 * Luigi Racioppi5, 6 * Stephanie Marie-Kunze1, 2 * W Nicholas Haining7 * Anthony R Means6 * Sudhir P Kasturi1, 2 * Nooruddin Khan1, 2 * Gui-Mei Li1, 3 * Megan McCausland1, 3 * Vibhu Kanchan1, 3 * Kenneth E Kokko8 * Shuzhao Li1, 2 * Rivka Elbein9 * Aneesh K Mehta9 * Alan Aderem10 * Kanta Subbarao11 * Rafi Ahmed1, 3 * Bali Pulendran1, 2, 12 * Affiliations * Contributions * Corresponding authorJournal name:Nature ImmunologyYear published:(2011)DOI:doi:10.1038/ni.2067Received12 April 2011Accepted06 June 2011Published online10 July 2011 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Here we have used a systems biology approach to study innate and adaptive responses to vaccination against influenza in humans during three consecutive influenza seasons. We studied healthy adults vaccinated with trivalent inactivated influenza vaccine (TIV) or live attenuated influenza vaccine (LAIV). TIV induced higher antibody titers and more plasmablasts than LAIV did. In subjects vaccinated with TIV, early molecular signatures correlated with and could be used to accurately predict later antibody titers in two independent trials. Notably, expression of the kinase CaMKIV at day 3 was inversely correlated with later antibody titers. Vaccination of CaMKIV-deficient mice with TIV induced enhanced antigen-specific antibody titers, which demonstrated an unappreciated role for CaMKIV in the regulation of antibody responses. Thus, systems approaches can be used to predict immunogenicity and provide new mechanistic insights about vaccines. View full text Figures at a glance * Figure 1: Analysis of humoral immunity to influenza vaccination. () HAI titers in plasma on day 28 after vaccination with TIV or LAIV, relative to baseline (day 0); results are the highest HAI response among all three influenza strains in the vaccine: low responders, no increase above twofold; high responders, fourfold or more above baseline. P < 0.0001, mean HAI response, TIV versus LAIV (t-test). () ELISPOT assay of influenza-specific IgG–secreting plasmablasts among PBMCs from all vaccinees at 0 and 7 d after vaccination. Each symbol represents an individual donor; small horizontal lines indicate the median (numbers adjacent median values); dotted lines are the limit of detection. () Flow cytometry analysis of plasmablasts in the plasmablast gate (CD3−CD20lo−negCD19+CD27hiCD38hi) in blood from subjects vaccinated with TIV or LAIV. Numbers adjacent to outlined areas indicate percent cells in the plasmablast gate. () Frequency of plasmablasts, assessed by flow cytometry, versus the number of influenza-specific IgG–secreting plasm! ablasts, assessed by ELISPOT, at day 7 after vaccination with TIV (blue) or LAIV (black). r = 0.58 (Pearson); P < 0.0001 (for Pearson correlation; two-tailed test). () Influenza-specific IgG–secreting plasmablasts at day 7 versus the antibody response at day 28 after vaccination with TIV. r = 0.43 (Pearson); P = 0.02 (for Pearson correlation; two-tailed test). Data are from one experiment with 56 subjects assayed in duplicate (), 61 subjects assayed in duplicate () or 59 subjects assayed once () or were generated from data in – (,). * Figure 2: Molecular signature induced by vaccination with LAIV. () Interferon-related genes upregulated (Up) or downregulated (Down) on day 3 or 7 ('X' in key) after vaccination with LAIV relative to their expression at day 0 (colors in key): solid lines indicate direct interactions; dashed lines indicate indirect interactions. () Quantitative RT-PCR confirmation of the induction of key interferon-related genes (OAS1, IRF7, MX2 and STAT1) in PBMCs obtained from healthy subjects and left unstimulated (Medium) or stimulated for 24 h in vitro with LAIV, TIV or YF-17D; results are normalized to the expression of GAPDH (glyceraldehyde phosphate dehydrogenase) and are presented relative to those of unstimulated PBMCs. Data are representative of one experiment () or three independent experiments with one subject each (; error bars, s.d.). * Figure 3: Molecular signatures induced by vaccination with TIV. () Heat map of gene signatures of cells of the immune response, identified by meta-analysis. Expression of each gene (rows) is presented as s.d. above (red) or below (blue) the average value for that gene for all samples (columns). mDC, myeloid DC; pDC, plasmacytoid DC; NK, natural killer. () Enrichment for genes upregulated by TIV among genes with high expression in any PBMC subset (numbers in plot indicate enrichment (fold)). () Enrichment for genes upregulated by TIV among genes with high expression in B cells and also in a specific B cell subset. () Heat map of genes upregulated after vaccination with TIV and also with high expression in B cells (PBMCs) and ASCs (B cell subsets); 'abParts' indicates probe sets mapping to antibody variable regions, and Affymetrix probe identifiers are provided for probe sets not annotated. () Enrichment for genes upregulated by LAIV among genes with high expression in any PBMC subset. *P < 10−10 (two-tailed Fisher's exact test). Data ar! e representative of 28 experiments with 281 samples. * Figure 4: Molecular signatures that correlate with titers of antibody to TIV. () Heat map of probe sets (rows) and subjects (columns) whose baseline-normalized expression at day 3 (top) or day 7 (bottom) correlated with baseline-normalized antibody response at day 28 after vaccination with TIV (colors in map indicate gene expression at day 3 or 7 relative to expression at day 0). Right margin, number of probe sets with negative correlation (blue) or positive correlation (red). Probe sets that correlated with the HAI response on both day 3 and day 7 were considered 'day 7'. P < 0.05 (Pearson). () HAI response–correlated genes associated with the unfolded protein response (purple shading) or ASC differentiation (tan shading) and/or regulated by XBP-1 (solid and dashed lines as in Fig. 2a). P < 0.05 (Pearson). () Enrichment for genes (among those with high expression in any PBMC subset) whose expression on day 3 or 7 after vaccination with TIV was positively or negatively correlated with HAI titers (cutoff, P < 0.05 (Pearson)). *P < 10−10 (two-tailed! Fisher's exact test). () Heat map of probe sets with high expression in B cells and ASCs whose baseline-normalized expression correlated with the baseline-normalized HAI response. P < 0.05 (Pearson). Data are representative of one experiment with 28 subjects. * Figure 5: Signatures that can be used to predict the antibody response induced by TIV. () Experimental design used to identify the early gene signatures that can be used to predict antibody responses to vaccination with TIV: the 2008–2009 trial was used as a training set to identify predictive signatures with the DAMIP model; those signatures were then tested on the data from the 2007–2008 trial (the testing set). The expression of a subset of genes in the DAMIP predictive signatures of the 2007–2008 and 2008–2009 trials was then quantified by RT-PCR in a third independent trial (2009–2010 trial); the DAMIP model was again used to confirm the predictive signatures. () RT-PCR confirmation of the expression of a subset of genes in the predictive signatures generated by the DAMIP model. Each symbol represents a single gene at a given time point. P < 10−11, microarray versus RT-PCR (Pearson); r = 0.68; n = 2,897 XY pairs. Data are representative of one experiment with 44 genes from 28 subjects at two time points. () DAMIP gene signatures identified wit! h the 2008–2009 trial as the training set and the 2007–2008 and 2009–2010 trials as the validation sets (DAMIP model 3); the accuracy represents the number of subjects correctly classified as 'low responders' or 'high responders' (Fig. 1a). Data are representative of three independent experiments. * Figure 6: CaMKIV regulates the antibody response to vaccines against influenza. () HAI response at day 28 versus microarray analysis of CAMK4 mRNA in PBMCs at day 3 after vaccination with TIV in the 2008–2009 trial (left; r = −0.47 (Pearson); P = 0.016 (for Pearson correlation; two-tailed test) or the 2007–2008 trial (right; r = −0.73 (Pearson); P = 0.024 (for Pearson correlation; two-tailed test). () ELISPOT analysis of influenza-specific IgG–secreting plasmablasts at day 7 versus microarray analysis of CAMK4 mRNA on PBMCs at day 3 after vaccination with TIV. () Immunoblot analysis of the phosphorylation (p-) of mouse CaMKIV after in vitro stimulation of splenocytes for 1 or 2 h with various doses of TIV (above lanes). () Immunoblot analysis of the phosphorylation of CaMKIV after in vitro stimulation of human PBMCs for 0–720 min with lipopolysaccharide (LPS) or TIV. () Serum antigen-specific IgG1 (top) and IgG2c (bottom) responses of wild-type and Camk4−/− mice at days 7, 14 and 28 after immunization with TIV (symbols represent individu! al mice), presented as absorption at 450 nm (A450). *P < 0.05 and **P < 0.01 (Student's t-test). Data are representative of one trial each with 26 subjects (2008–2009) or 9 subjects (2007–2008; ), one experiment with 26 subjects (), three experiments (,) or at least four independent experiments (). Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE29619 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Emory Vaccine Center, Emory University, Atlanta, Georgia, USA. * Helder I Nakaya, * Jens Wrammert, * Stephanie Marie-Kunze, * Sudhir P Kasturi, * Nooruddin Khan, * Gui-Mei Li, * Megan McCausland, * Vibhu Kanchan, * Shuzhao Li, * Rafi Ahmed & * Bali Pulendran * Yerkes National Primate Research Center, Emory University, Atlanta, Georgia, USA. * Helder I Nakaya, * Stephanie Marie-Kunze, * Sudhir P Kasturi, * Nooruddin Khan, * Shuzhao Li & * Bali Pulendran * Department of Microbiology and Immunology, Emory University, Atlanta, Georgia, USA. * Jens Wrammert, * Gui-Mei Li, * Megan McCausland, * Vibhu Kanchan & * Rafi Ahmed * Center for Operations Research in Medicine & Healthcare, School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA. * Eva K Lee * Department of Pharmacology and Cancer Biology, Duke University, Durham, North Carolina, USA. * Luigi Racioppi * Department of Cellular and Molecular Biology and Pathology, University of Naples Federico II, Naples, Italy. * Luigi Racioppi & * Anthony R Means * Dana-Farber Cancer Institute, Boston, Massachusetts, USA. * W Nicholas Haining * Department of Medicine, Division of Nephrology, Emory University School of Medicine, Atlanta, Georgia, USA. * Kenneth E Kokko * Division of Infectious Diseases, Department of Medicine, School of Medicine, Emory University, Atlanta, Georgia, USA. * Rivka Elbein & * Aneesh K Mehta * Institute for Systems Biology, Seattle, Washington, USA. * Alan Aderem * Laboratory of Infectious Diseases, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA. * Kanta Subbarao * Department of Pathology, Emory University School of Medicine, Atlanta, Georgia, USA. * Bali Pulendran Contributions H.I.N. did all the experiments and analyses in Figures 2,3,4,5 and 6 and Supplementary Figures 2–8; J.W., G.-M.L., M.M. and V.K. did the analyses in Figure 1 and Supplementary Figure 1; E.K.L. did the DAMIP model analyses in Figure 5; L.R., A.R.M., S.P.K. and N.K. did the mouse experiments in Figure 6; W.N.H. helped with the microarray analyses in Supplementary Figure 4; S.L. assisted with the bioinformatics analyses of the data in Figure 3; A.A. did the microarray analysis of samples from the 2007 influenza annual season; S.M.-K., K.E.K., R.E. and A.K.M. assisted with the collection and processing of samples; K.S. measured HAI titers; R.A. helped conceive of and design the study and supervised the studies in Figure 1 and Supplementary Figure 1; B.P. conceived of the study and designed and supervised the experiments and analyses in Figures 1,2,3,4,5 and 6 and Supplementary Figures 1–8; and B.P. and H.I.N. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Bali Pulendran Author Details * Helder I Nakaya Search for this author in: * NPG journals * PubMed * Google Scholar * Jens Wrammert Search for this author in: * NPG journals * PubMed * Google Scholar * Eva K Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Luigi Racioppi Search for this author in: * NPG journals * PubMed * Google Scholar * Stephanie Marie-Kunze Search for this author in: * NPG journals * PubMed * Google Scholar * W Nicholas Haining Search for this author in: * NPG journals * PubMed * Google Scholar * Anthony R Means Search for this author in: * NPG journals * PubMed * Google Scholar * Sudhir P Kasturi Search for this author in: * NPG journals * PubMed * Google Scholar * Nooruddin Khan Search for this author in: * NPG journals * PubMed * Google Scholar * Gui-Mei Li Search for this author in: * NPG journals * PubMed * Google Scholar * Megan McCausland Search for this author in: * NPG journals * PubMed * Google Scholar * Vibhu Kanchan Search for this author in: * NPG journals * PubMed * Google Scholar * Kenneth E Kokko Search for this author in: * NPG journals * PubMed * Google Scholar * Shuzhao Li Search for this author in: * NPG journals * PubMed * Google Scholar * Rivka Elbein Search for this author in: * NPG journals * PubMed * Google Scholar * Aneesh K Mehta Search for this author in: * NPG journals * PubMed * Google Scholar * Alan Aderem Search for this author in: * NPG journals * PubMed * Google Scholar * Kanta Subbarao Search for this author in: * NPG journals * PubMed * Google Scholar * Rafi Ahmed Search for this author in: * NPG journals * PubMed * Google Scholar * Bali Pulendran Contact Bali Pulendran Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information Excel files * Supplementary Table 1 (684K) All the differentially expressed genes identified in PBMCs of TIV or LAIV vaccinees * Supplementary Table 2 (528K) All the differentially expressed genes identified in monocytes, mDCs, pDCs and B cells from TIV or LAIV vaccinees * Supplementary Table 3 (20K) Microarray study ID (from NCBI GEO) and microarray sample ID used in the meta analysis of PBMC subsets and of B cell subsets * Supplementary Table 4 (1M) Genes identified in our meta-analysis as highly expressed in a given PBMC cell subset or in a given B cell subset * Supplementary Table 5 (233K) All the genes whose expression (d3/d0 or d7/d0) correlates to the fold increase in HAI titers (d28/d0) * Supplementary Table 6 (49K) Sets of 2-4 genes identified by DAMIP model (first analysis) as predictors of HAI response and Number of appearances in the DAMIP model (first analysis) * Supplementary Table 7 (94K) Microarray expression and RT-qPCR values of selected genes from TIV vaccinees of 2007-2008 and 2008-2009 Influenza seasons and Genes selected for RT-qPCR validation * Supplementary Table 8 (20K) Sets of 2-4 genes identified by DAMIP model (second analysis) as predictors of HAI response and Number of appearances in the DAMIP model (second analysis) * Supplementary Table 9 (20K) Sets of 2-4 genes identified by DAMIP model (third analysis) as predictors of HAI response and Number of appearances in the DAMIP model (third analysis) * Supplementary Table 10 (12K) This table shows the Influenza vaccine composition and the gender and age of vaccinees in each Influenza season PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–8 and Supplementary Methods Additional data - Distinct microRNA signatures in human lymphocyte subsets and enforcement of the naive state in CD4+ T cells by the microRNA miR-125b
- Nat Immunol 12(8):796-803 (2011)
Nature Immunology | Resource Distinct microRNA signatures in human lymphocyte subsets and enforcement of the naive state in CD4+ T cells by the microRNA miR-125b * Riccardo L Rossi1, 5 * Grazisa Rossetti1, 5 * Lynn Wenandy1, 5 * Serena Curti1 * Anna Ripamonti1 * Raoul J P Bonnal1 * Roberto Sciarretta Birolo1 * Monica Moro1 * Maria C Crosti1 * Paola Gruarin1 * Stefano Maglie1 * Francesco Marabita1 * Debora Mascheroni1 * Valeria Parente1 * Mario Comelli2 * Emilio Trabucchi3 * Raffaele De Francesco1 * Jens Geginat1 * Sergio Abrignani1, 4 * Massimiliano Pagani1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature ImmunologyYear published:(2011)DOI:doi:10.1038/ni.2057Received08 February 2011Accepted19 May 2011Published online26 June 2011 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg MicroRNAs are small noncoding RNAs that regulate gene expression post-transcriptionally. Here we applied microRNA profiling to 17 human lymphocyte subsets to identify microRNA signatures that were distinct among various subsets and different from those of mouse lymphocytes. One of the signature microRNAs of naive CD4+ T cells, miR-125b, regulated the expression of genes encoding molecules involved in T cell differentiation, including IFNG, IL2RB, IL10RA and PRDM1. The expression of synthetic miR-125b and lentiviral vectors encoding the precursor to miR-125b in naive lymphocytes inhibited differentiation to effector cells. Our data provide an 'atlas' of microRNA expression in human lymphocytes, define subset-specific signatures and their target genes and indicate that the naive state of T cells is enforced by microRNA. View full text Figures at a glance * Figure 1: Expression of microRNA describes and discriminates among different lymphocyte subsets. () Unsupervised hierarchical clusters of 242 subset-specific miRNAs in various cell subsets, selected by one-way ANOVA (P < 0.001). Top (yellow to blue gradient), range of expression values (normalized change in cycling threshold, ΔCT), after log transformation and mean centering; color coding below identifies the 17 cell subsets (letters in parentheses in sample names indicate donor). Treg, regulatory T cell; TCM, central memory T cell; TEM, effector memory T cell; TEMRA, effector memory RA T cell (expressing CD45RA). () Enlargement of the hierarchical tree and color coding of cell-lineage segregation in . () Heat map of average expression values (z-scores of ΔCT) for mature miRNA across all 17 lymphocyte subsets profiled. () Heat map of the z-scores of signature miRNAs for the naive CD4+ T cell, TH1, TH17 and TH2 subsets: miRNAs with differences in expression were selected by the comparative cycling threshold method (ΔΔCT) and filtered for statistical significance (P 1.5); significance is plotted as −log of P values. Expressed genes (M/N > 1.5), expressed predicted targets (M/N < 1.5) and unexpressed predicted targets serve as control groups. NC, not computable. () Molecular network of functional relationships (direct interactions) extracted from the ingenuity pathway analysis knowledge base for expressed predicted targets wi! th an M/N ratio of over 1.5: dark blue, genes encoding molecules that are 'network eligible' by ingenuity pathway analysis; light blue, genes encoding molecules in the network predicted to be miR-125b targets; white, genes encoding other network molecules. Data are representative of three to six experiments (n in Table 1; ; mean and s.e.m.) or four experiments (,). * Figure 3: Direct regulation by miR-125b of genes key to T cell differentiation. () Dual-luciferase assay of HEK-293T cells transfected with luciferase constructs containing genes (n = 14) predicted to be regulated by miR-125b, together with synthetic mature miR-125b (synth miR-125b) or a synthetic control miRNA with scrambled sequence (scr ctrl). Empty vector and GAPDH (not a target of miR-125b) serve as negative controls; vector with a tandem stretch of six miR-125b target sites (sponge) serves as a positive control. Dashed red line indicates the threshold (75%) of luciferase activity. *P < 0.001, relative to scrambled control (t-test). () Dual-luciferase assay (as in ) of HEK-293T cells transfected with luciferase constructs containing wild-type (WT) 3′ UTR or mutated (mut) 3′ UTR (with deletion of the miR-125b-responsive element) from IFNG, IL10RA, IL2RB and PRDM1, plus miRNA (as in ). *P < 0.001 (ANOVA). () Quantitative RT-PCR analysis of the expression of IFNG, IL10RA, IL2RB and PRDM1 transcripts in activated naive CD4+ T cells transduced with ! lentiviral vector encoding the precursor to miR-125b (LV-125b) or mock control (LV-ctrl); results are presented in arbitrary units derived from ΔCT. Numbers in parentheses above bars indicate expression relative to control. () Comparison of miR-125b-responsive elements in human and mouse transcripts encoding IFN-γ (IFNG and Ifng), IL-10Rα (IL10RA and Il10ra), IL-2Rβ (IL2RB and Il2rb) and Blimp-1 (PRDM1 and Prdm1) by TargetScanHuman, release 5.1. Colors in key indicate branch length (and match to miR-125b): 8mer, eight-nucleotide sequence; 7mer-m8, seven-nucleotide sequence (exact match to positions 2–8 of mature miR-125b); 7mer-1A, seven-nucleotide sequence (exact match to positions 2–7 of mature miR-125b followed by 'A'). CDS, coding sequence. Data are representative of eighteen experiments (,) or are from three independent experiments (; average and s.e.m.). * Figure 4: Preservation of the naive state of CD4+ T cells by miR-125b. () Flow cytometry of the surface expression of CXCR3 and CCR4 (assessed at day 3) or CD45RA, CD45RO, CD4 and major histocompatibility complex class I (MHCI; assessed at day 5) in purified peripheral blood naive CD4+ T cells stimulated with antibody to CD3 (anti-CD3) and allogenic PBMCs and transfected by nucleofection with mimic-125b or miRNA with scrambled sequence (Control). Numbers in quadrants or above bracketed lines indicate percent cells in each area. () Flow cytometry of the surface expression of IL-10Rα and IL-2Rβ on the cells in . () Proliferation of purified unlabeled or CFSE-labeled naive CD4+ T cells stimulated and transfected as in , assessed by Ki67 staining or CFSE dilution, respectively, at day 5. Number above bracketed line (left) indicate percent Ki67+ cells. Data are representative of three independent experiments with similar results. * Figure 5: Regulation of the differentiation of naive CD4+ T cells by miR-125b. () Intracellular staining of IL-13 and IFN-γ (acquisition of effector function) in purified naive CD4+ T cells stimulated with anti-CD3 and anti-CD28 and left untransduced (unt) or transduced for 7 d with lentiviral vector encoding the precursor to miR-125b (LV-125b) or mock control lentivirus (LV-ctrl), then reactivated for 6 h with PMA and ionomycin. Numbers in quadrants indicate percent cells in each. () Quantification of the results in . () Quantitative RT-PCR analysis of miR-125b expression in naive CD4+ T cells transduced as in and stimulated for 7 d with anti-CD3 and anti-CD28. Untransduced primary naive CD4+ T cells (naive) and CD4+ TH1 memory cells (TH1) serve as controls. Data are representative of six independent experiments with similar results (,) or three independent experiments (; mean and s.e.m. in ,). Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE22880 Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Riccardo L Rossi, * Grazisa Rossetti & * Lynn Wenandy Affiliations * Istituto Nazionale Genetica Molecolare, Milano, Italy. * Riccardo L Rossi, * Grazisa Rossetti, * Lynn Wenandy, * Serena Curti, * Anna Ripamonti, * Raoul J P Bonnal, * Roberto Sciarretta Birolo, * Monica Moro, * Maria C Crosti, * Paola Gruarin, * Stefano Maglie, * Francesco Marabita, * Debora Mascheroni, * Valeria Parente, * Raffaele De Francesco, * Jens Geginat, * Sergio Abrignani & * Massimiliano Pagani * Dipartimento di Scienze Sanitarie Applicate, Università di Pavia, Pavia, Italy. * Mario Comelli * Pio Albergo Trivulzio, Milano, Italy. * Emilio Trabucchi * Istituto di Ricovero e Cura a Carattere Scientifico, Ca'Granda Ospedale Maggiore Policlinico, Milano, Italy. * Sergio Abrignani Contributions R.L.R., G.R. and L.W. designed and did experiments, analyzed data and wrote the manuscript; M.M. and M.C.C. did flow cytometry; R.J.P.B. did bioinformatic analyses; M.C. did statistical analyses; R.S.B., S.C., S.M., P.G., F.M., D.M., V.P. and A.R. did experiments and analyzed data; E.T. provided advice; R.D.F. discussed results, provided advice and commented on the manuscript; J.G. designed and supervised research and wrote the manuscript; and S.A. and M.P. designed the study, supervised research and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Sergio Abrignani or * Massimiliano Pagani Author Details * Riccardo L Rossi Search for this author in: * NPG journals * PubMed * Google Scholar * Grazisa Rossetti Search for this author in: * NPG journals * PubMed * Google Scholar * Lynn Wenandy Search for this author in: * NPG journals * PubMed * Google Scholar * Serena Curti Search for this author in: * NPG journals * PubMed * Google Scholar * Anna Ripamonti Search for this author in: * NPG journals * PubMed * Google Scholar * Raoul J P Bonnal Search for this author in: * NPG journals * PubMed * Google Scholar * Roberto Sciarretta Birolo Search for this author in: * NPG journals * PubMed * Google Scholar * Monica Moro Search for this author in: * NPG journals * PubMed * Google Scholar * Maria C Crosti Search for this author in: * NPG journals * PubMed * Google Scholar * Paola Gruarin Search for this author in: * NPG journals * PubMed * Google Scholar * Stefano Maglie Search for this author in: * NPG journals * PubMed * Google Scholar * Francesco Marabita Search for this author in: * NPG journals * PubMed * Google Scholar * Debora Mascheroni Search for this author in: * NPG journals * PubMed * Google Scholar * Valeria Parente Search for this author in: * NPG journals * PubMed * Google Scholar * Mario Comelli Search for this author in: * NPG journals * PubMed * Google Scholar * Emilio Trabucchi Search for this author in: * NPG journals * PubMed * Google Scholar * Raffaele De Francesco Search for this author in: * NPG journals * PubMed * Google Scholar * Jens Geginat Search for this author in: * NPG journals * PubMed * Google Scholar * Sergio Abrignani Contact Sergio Abrignani Search for this author in: * NPG journals * PubMed * Google Scholar * Massimiliano Pagani Contact Massimiliano Pagani Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information Text files * Supplementary Spreadsheet (225K) RTqPCR raw CT data for all samples profiled. PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–6 and Supplementary Tables 1–4 and Supplementary Methods Additional data - The helminth product ES-62 protects against septic shock via Toll-like receptor 4–dependent autophagosomal degradation of the adaptor MyD88
- Nat Immunol 12(8):804 (2011)
Nature Immunology | Retraction The helminth product ES-62 protects against septic shock via Toll-like receptor 4–dependent autophagosomal degradation of the adaptor MyD88 * Padmam Puneet * Mairi A McGrath * Hwee Kee Tay * Lamyaa Al-Riyami * Justyna Rzepecka * Shabbir M Moochhala * Shazib Pervaiz * Margaret M Harnett * William Harnett * Alirio J MelendezJournal name:Nature ImmunologyVolume: 12,Page:804Year published:(2011)DOI:doi:10.1038/ni0811-804aPublished online19 July 2011 Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Nat. Immunol.12, 344–351 (2011); published online 27 February 2011; retracted 24 June 2011 The authors wish to note the following. Irregularities have been identified in some of the figures in this paper. The conclusions drawn from these data, that ES-62 protects against the development of pathology in the sepsis models and results in the induction of autophagy in macrophages, cannot be made. As these conclusions constitute major components of the paper, we wish to retract this paper. Additional data Author Details * Padmam Puneet Search for this author in: * NPG journals * PubMed * Google Scholar * Mairi A McGrath Search for this author in: * NPG journals * PubMed * Google Scholar * Hwee Kee Tay Search for this author in: * NPG journals * PubMed * Google Scholar * Lamyaa Al-Riyami Search for this author in: * NPG journals * PubMed * Google Scholar * Justyna Rzepecka Search for this author in: * NPG journals * PubMed * Google Scholar * Shabbir M Moochhala Search for this author in: * NPG journals * PubMed * Google Scholar * Shazib Pervaiz Search for this author in: * NPG journals * PubMed * Google Scholar * Margaret M Harnett Search for this author in: * NPG journals * PubMed * Google Scholar * William Harnett Search for this author in: * NPG journals * PubMed * Google Scholar * Alirio J Melendez Search for this author in: * NPG journals * PubMed * Google Scholar - Defeating sepsis by misleading MyD88
- Nat Immunol 12(8):804 (2011)
Nature Immunology | Addendum Defeating sepsis by misleading MyD88 * Katherine A Smith * Rick M MaizelsJournal name:Nature ImmunologyVolume: 12,Page:804Year published:(2011)DOI:doi:10.1038/ni0811-804bPublished online19 July 2011 Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Nat. Immunol.12, 284–286 (2011); published online 21 April 2011; addendum published after print 24 June 2011 The article to which this News and Views refers has been retracted (http://www.nature.com/ni/journal/v12/n4/abs/ni.2004.html). Nature Immunology wishes to inform readers that some of the comments made in this News and Views, although made in good faith based on the article's conclusions, may no longer be valid. Additional data Author Details * Katherine A Smith Search for this author in: * NPG journals * PubMed * Google Scholar * Rick M Maizels Search for this author in: * NPG journals * PubMed * Google Scholar
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