Diverse and Potent Chemokine Production by Lung Cd11bhigh Dendritic Cells in Homeostasis and in Allergic Lung Inflammation
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Differentiation and Bone Resorption Role of CX3CL1/Fractalkine In
Role of CX3CL1/Fractalkine in Osteoclast Differentiation and Bone Resorption Keiichi Koizumi, Yurika Saitoh, Takayuki Minami, Nobuhiro Takeno, Koichi Tsuneyama, Tatsuro Miyahara, This information is current as Takashi Nakayama, Hiroaki Sakurai, Yasuo Takano, Miyuki of September 29, 2021. Nishimura, Toshio Imai, Osamu Yoshie and Ikuo Saiki J Immunol published online 18 November 2009 http://www.jimmunol.org/content/early/2009/11/18/jimmuno l.0803627.citation Downloaded from Why The JI? Submit online. http://www.jimmunol.org/ • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average by guest on September 29, 2021 Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published November 18, 2009, doi:10.4049/jimmunol.0803627 The Journal of Immunology Role of CX3CL1/Fractalkine in Osteoclast Differentiation and Bone Resorption1 Keiichi Koizumi,2* Yurika Saitoh,* Takayuki Minami,* Nobuhiro Takeno,* Koichi Tsuneyama,†‡ Tatsuro Miyahara,§ Takashi Nakayama,¶ Hiroaki Sakurai,*† Yasuo Takano,‡ Miyuki Nishimura,ʈ Toshio Imai,ʈ Osamu Yoshie,¶ and Ikuo Saiki*† The recruitment of osteoclast precursors toward osteoblasts and subsequent cell-cell interactions are critical for osteoclast dif- ferentiation. -
SPATA33 Localizes Calcineurin to the Mitochondria and Regulates Sperm Motility in Mice
SPATA33 localizes calcineurin to the mitochondria and regulates sperm motility in mice Haruhiko Miyataa, Seiya Ouraa,b, Akane Morohoshia,c, Keisuke Shimadaa, Daisuke Mashikoa,1, Yuki Oyamaa,b, Yuki Kanedaa,b, Takafumi Matsumuraa,2, Ferheen Abbasia,3, and Masahito Ikawaa,b,c,d,4 aResearch Institute for Microbial Diseases, Osaka University, Osaka 5650871, Japan; bGraduate School of Pharmaceutical Sciences, Osaka University, Osaka 5650871, Japan; cGraduate School of Medicine, Osaka University, Osaka 5650871, Japan; and dThe Institute of Medical Science, The University of Tokyo, Tokyo 1088639, Japan Edited by Mariana F. Wolfner, Cornell University, Ithaca, NY, and approved July 27, 2021 (received for review April 8, 2021) Calcineurin is a calcium-dependent phosphatase that plays roles in calcineurin can be a target for reversible and rapidly acting male a variety of biological processes including immune responses. In sper- contraceptives (5). However, it is challenging to develop molecules matozoa, there is a testis-enriched calcineurin composed of PPP3CC and that specifically inhibit sperm calcineurin and not somatic calci- PPP3R2 (sperm calcineurin) that is essential for sperm motility and male neurin because of sequence similarities (82% amino acid identity fertility. Because sperm calcineurin has been proposed as a target for between human PPP3CA and PPP3CC and 85% amino acid reversible male contraceptives, identifying proteins that interact with identity between human PPP3R1 and PPP3R2). Therefore, identi- sperm calcineurin widens the choice for developing specific inhibitors. fying proteins that interact with sperm calcineurin widens the choice Here, by screening the calcineurin-interacting PxIxIT consensus motif of inhibitors that target the sperm calcineurin pathway. in silico and analyzing the function of candidate proteins through the The PxIxIT motif is a conserved sequence found in generation of gene-modified mice, we discovered that SPATA33 inter- calcineurin-binding proteins (8, 9). -
Ccl9 Induced by Tgf-Β Signaling in Myeloid Cells Enhances Tumor Cell Survival in the Premetastatic Lung
CCL9 INDUCED BY TGF-β SIGNALING IN MYELOID CELLS ENHANCES TUMOR CELL SURVIVAL IN THE PREMETASTATIC LUNG by Hangyi Yan A dissertation submitted to Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland March, 2015 ABSTRACT The majority of cancer patients die from metastasis. To achieve metastasis, tumor cells must first survive and then proliferate to form colonies. Compelling data have shown the indispensable participation of host microenvironment for metastasis. Bone marrow derived myeloid cells sculpt a tumor-promoting microenvironment in the premetastatic organs prior to tumor cell arrival. However, the molecular mechanisms for this “seed and soil” hypothesis are unclear. Here we report that CCL9 was significantly produced and secreted by Gr-1+CD11b+ cells when co-cultured with tumor cells, and in the premetastatic lung. CCL9 knockdown (KD) in myeloid cells decreased metastasis, and this process signaled through its sole receptor CCR1. Overexpression of CCR1 lost the metastasis-promoting function in the context of CCL9 KD. CCL9 enhanced tumor cell survival in the premetastatic organs. The underlying molecular mechanisms included activation of cell survival factors phosphorylated AKT and BCL-2, as well as inhibition of Poly (ADP-ribose) polymerase (PARP)-dependent apoptosis pathway. Additionally, CCL9/CCR1 had autocrine effects, which enhanced CCL9 secretion and the survival of Gr-1+CD11b+ cells. We found that CCL9 was a key effector of myeloid transforming growth factor β (TGF-β) pathway that promotes metastasis. Decreased metastasis in mice with myeloid specific TGF-β receptor II deletion (Tgfbr2MyeKO) correlated with lower CCL9 expression in TGF-β deficient myeloid cells. -
Genetic and Genomic Analysis of Hyperlipidemia, Obesity and Diabetes Using (C57BL/6J × TALLYHO/Jngj) F2 Mice
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Nutrition Publications and Other Works Nutrition 12-19-2010 Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P. Stewart Marshall University Hyoung Y. Kim University of Tennessee - Knoxville, [email protected] Arnold M. Saxton University of Tennessee - Knoxville, [email protected] Jung H. Kim Marshall University Follow this and additional works at: https://trace.tennessee.edu/utk_nutrpubs Part of the Animal Sciences Commons, and the Nutrition Commons Recommended Citation BMC Genomics 2010, 11:713 doi:10.1186/1471-2164-11-713 This Article is brought to you for free and open access by the Nutrition at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Nutrition Publications and Other Works by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Stewart et al. BMC Genomics 2010, 11:713 http://www.biomedcentral.com/1471-2164/11/713 RESEARCH ARTICLE Open Access Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P Stewart1, Hyoung Yon Kim2, Arnold M Saxton3, Jung Han Kim1* Abstract Background: Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/ JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
CCL9 Is Secreted by the Follicle-Associated Epithelium and Recruits Dome Region Peyer's Patch Cd11b+ Dendritic Cells
CCL9 Is Secreted by the Follicle-Associated Epithelium and Recruits Dome Region Peyer's Patch CD11b+ Dendritic Cells This information is current as Xinyan Zhao, Ayuko Sato, Charles S. Dela Cruz, Melissa of October 1, 2021. Linehan, Andreas Luegering, Torsten Kucharzik, Aiko-Konno Shirakawa, Gabriel Marquez, Joshua M. Farber, Ifor Williams and Akiko Iwasaki J Immunol 2003; 171:2797-2803; ; doi: 10.4049/jimmunol.171.6.2797 http://www.jimmunol.org/content/171/6/2797 Downloaded from References This article cites 32 articles, 19 of which you can access for free at: http://www.jimmunol.org/content/171/6/2797.full#ref-list-1 http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on October 1, 2021 *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts Errata An erratum has been published regarding this article. Please see next page or: /content/172/11/7220.2.full.pdf The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2003 by The American Association of Immunologists All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology CCL9 Is Secreted by the Follicle-Associated Epithelium and Recruits Dome Region Peyer’s Patch CD11b؉ Dendritic Cells1 Xinyan Zhao,2* Ayuko Sato,* Charles S. -
Chemokine Signatures of Pathogen-Specific T Cells II: Memory T Cells in Acute and Chronic Infection
Chemokine Signatures of Pathogen-Specific T Cells II: Memory T Cells in Acute and Chronic Infection This information is current as Bennett Davenport, Jens Eberlein, Tom T. Nguyen, of September 24, 2021. Francisco Victorino, Verena van der Heide, Maxim Kuleshov, Avi Ma'ayan, Ross Kedl and Dirk Homann J Immunol published online 18 September 2020 http://www.jimmunol.org/content/early/2020/09/17/jimmun ol.2000254 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2020/09/17/jimmunol.200025 Material 4.DCSupplemental http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on September 24, 2021 *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2020 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published September 18, 2020, doi:10.4049/jimmunol.2000254 The Journal of Immunology Chemokine Signatures of Pathogen-Specific T Cells II: Memory T Cells in Acute and Chronic Infection Bennett Davenport,*,†,‡,x,{ Jens Eberlein,*,† Tom T. Nguyen,*,‡ Francisco Victorino,*,†,‡ Verena van der Heide,x,{ Maxim Kuleshov,‖,# Avi Ma’ayan,‖,# Ross Kedl,† and Dirk Homann*,†,‡,x,{ Pathogen-specific memory T cells (TM) contribute to enhanced immune protection under conditions of reinfection, and their effective recruitment into a recall response relies, in part, on cues imparted by chemokines that coordinate their spatiotemporal positioning. -
Identification of Eight Genes Encoding Chemokine-Like
中国科技论文在线 http://www.paper.edu.cn Genomics 81 (2003) 609–617 Identification of eight genes encoding chemokine-like factor superfamily members 1–8 (CKLFSF1–8) by in silico cloning and experimental validation૾ Wenling Han,1 Peiguo Ding,1 Mingxu Xu, Lu Wang, Min Rui, Shuang Shi, Yanan Liu, Ying Zheng, Yingyu Chen, Tian Yang, and Dalong Ma* Center for Human Disease Genomics, Peking University, 38 Xueyuan Road, Beijing 100083, China Received 21 November 2002; accepted 14 March 2003 Abstract TM4SF11 is only 102 kb from the chemokine gene cluster composed of SCYA22, SCYD1, and SCYA17 on chromosome 16q13. CKLF maps on chromosome 16q22. CKLFs have some characteristics associated with the CCL22/MDC, CX3CL1/fractalkine, CCL17/TARC, and TM4SF proteins. Bioinformatics based on CKLF2 cDNA and protein sequences in combination with experimental validation identified eight novel genes designated chemokine-like factor superfamily members 1–8 (CKLFSF1–8). CKLFSF1–8 form gene clusters; the sequence identities between CKLF2 and CKLFSF1–8 are from 12.5 to 39.7%. Most of the CKLFSFs have alternative RNA splicing forms. CKLFSF1 has a CC motif and higher sequence similarity with chemokines than with any of the other CKLFSFs. CKLFSF8 shares 39.3% amino acid identity with TM4SF11. CKLFSF1 links the CKLFSF family with chemokines, and CKLFSF8 links it with TM4SF. The characteristics of CKLFSF2–7 are intermediate between CKLFSF1 and CKLFSF8. This indicates that CKLFSF represents a novel gene family between the SCY and the TM4SF gene families. © 2003 Elsevier Science (USA). All rights reserved. Keywords: CKLF; CKLFSF; Bioinformatics; Gene cluster; Chemokine; TM4SF11 Chemokines are small, secreted proteins that can be CXC chemokines (CXCL1–16), 2 C chemokines (XCL1– subdivided according to their NH2-terminal cysteine-motif 2), and one CX3C chemokine (CX3CL1/fractalkine) iden- into the CC, CXC, C, and CX3C classes. -
MOCHI Enables Discovery of Heterogeneous Interactome Modules in 3D Nucleome
Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press MOCHI enables discovery of heterogeneous interactome modules in 3D nucleome Dechao Tian1,# , Ruochi Zhang1,# , Yang Zhang1, Xiaopeng Zhu1, and Jian Ma1,* 1Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA #These two authors contributed equally *Correspondence: [email protected] Contact To whom correspondence should be addressed: Jian Ma School of Computer Science Carnegie Mellon University 7705 Gates-Hillman Complex 5000 Forbes Avenue Pittsburgh, PA 15213 Phone: +1 (412) 268-2776 Email: [email protected] 1 Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract The composition of the cell nucleus is highly heterogeneous, with different constituents forming complex interactomes. However, the global patterns of these interwoven heterogeneous interactomes remain poorly understood. Here we focus on two different interactomes, chromatin interaction network and gene regulatory network, as a proof-of-principle, to identify heterogeneous interactome modules (HIMs), each of which represents a cluster of gene loci that are in spatial contact more frequently than expected and that are regulated by the same group of transcription factors. HIM integrates transcription factor binding and 3D genome structure to reflect “transcriptional niche” in the nucleus. We develop a new algorithm MOCHI to facilitate the discovery of HIMs based on network motif clustering in heterogeneous interactomes. By applying MOCHI to five different cell types, we found that HIMs have strong spatial preference within the nucleus and exhibit distinct functional properties. Through integrative analysis, this work demonstrates the utility of MOCHI to identify HIMs, which may provide new perspectives on the interplay between transcriptional regulation and 3D genome organization. -
Chemokine and Chemokine Receptor Expression During Colony Stimulating Factor-1-Induced Osteoclast Differentiation in the Toothle
University of Massachusetts Medical School eScholarship@UMMS Open Access Articles Open Access Publications by UMMS Authors 2005-11-24 Chemokine and chemokine receptor expression during colony stimulating factor-1-induced osteoclast differentiation in the toothless osteopetrotic rat: a key role for CCL9 (MIP-1gamma) in osteoclastogenesis in vivo and in vitro Meilheng Yang University of Massachusetts Medical School Et al. Let us know how access to this document benefits ou.y Follow this and additional works at: https://escholarship.umassmed.edu/oapubs Part of the Cell Biology Commons Repository Citation Yang M, Mailhot G, MacKay CA, Mason-Savas A, Aubin J, Odgren PR. (2005). Chemokine and chemokine receptor expression during colony stimulating factor-1-induced osteoclast differentiation in the toothless osteopetrotic rat: a key role for CCL9 (MIP-1gamma) in osteoclastogenesis in vivo and in vitro. Open Access Articles. https://doi.org/10.1182/blood-2005-08-3365. Retrieved from https://escholarship.umassmed.edu/oapubs/275 This material is brought to you by eScholarship@UMMS. It has been accepted for inclusion in Open Access Articles by an authorized administrator of eScholarship@UMMS. For more information, please contact [email protected]. CHEMOKINES, CYTOKINES, AND INTERLEUKINS Chemokine and chemokine receptor expression during colony stimulating factor-1–induced osteoclast differentiation in the toothless osteopetrotic rat: a key role for CCL9 (MIP-1␥) in osteoclastogenesis in vivo and in vitro Meiheng Yang, Genevie`ve Mailhot, Carole A. MacKay, April Mason-Savas, Justin Aubin, and Paul R. Odgren Osteoclasts differentiate from hematopoi- peared on day 2, peaked on day 4, and oclasts on day 2 and in mature cells at etic precursors under systemic and local decreased slightly on day 6, as marrow later times. -
Macrophage-Derived CXCL9 and CXCL10 Are Required for Antitumor Immune Responses Following Immune Checkpoint Blockade a C Imran G
Published OnlineFirst October 21, 2019; DOI: 10.1158/1078-0432.CCR-19-1868 CLINICAL CANCER RESEARCH | TRANSLATIONAL CANCER MECHANISMS AND THERAPY Macrophage-Derived CXCL9 and CXCL10 Are Required for Antitumor Immune Responses Following Immune Checkpoint Blockade A C Imran G. House1,2, Peter Savas2,3, Junyun Lai1,2, Amanda X.Y. Chen1,2, Amanda J. Oliver1,2, Zhi L. Teo2,3, Kirsten L. Todd1,2, Melissa A. Henderson1,2, Lauren Giuffrida1,2, Emma V. Petley1,2, Kevin Sek1,2, Sherly Mardiana1,2, Tuba N. Gide4, Camelia Quek4, Richard A. Scolyer4,5, Georgina V. Long4,6,7, James S. Wilmott4, Sherene Loi2,3, Phillip K. Darcy1,2,8,9, and Paul A. Beavis1,2 ABSTRACT ◥ Purpose: Response rates to immune checkpoint blockade (ICB; single-cell RNA-sequencing (RNA-seq) and paired survival anti-PD-1/anti-CTLA-4) correlate with the extent of tumor analyses. immune infiltrate, but the mechanisms underlying the recruit- Results: The CXCR3 ligands, CXCL9 and CXCL10, were sig- ment of T cells following therapy are poorly characterized. A nificantly upregulated following dual PD-1/CTLA-4 blockade and þ greater understanding of these processes may see the develop- both CD8 T-cell infiltration and therapeutic efficacy were CXCR3 ment of therapeutic interventions that enhance T-cell recruit- dependent. In both murine models and patients undergoing immu- ment and, consequently, improved patient outcomes. We there- notherapy, macrophages were the predominant source of CXCL9 þ fore investigated the chemokines essential for immune cell and their depletion abrogated CD8 T-cell infiltration and the recruitment and subsequent therapeutic efficacy of these immu- therapeutic efficacy of dual ICB. -
A Tool to Identify Coordinately Expressed Genes
The CO-Regulation Database (CORD): A Tool to Identify Coordinately Expressed Genes John P. Fahrenbach1*, Jorge Andrade2, Elizabeth M. McNally1,3 1 Department of Medicine, The University of Chicago, Chicago, Illinois, United States of America, 2 Center for Research Informatics, The University of Chicago, Chicago, Illinois, United States of America, 3 Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America Abstract Background: Meta-analysis of gene expression array databases has the potential to reveal information about gene function. The identification of gene-gene interactions may be inferred from gene expression information but such meta-analysis is often limited to a single microarray platform. To address this limitation, we developed a gene-centered approach to analyze differential expression across thousands of gene expression experiments and created the CO-Regulation Database (CORD) to determine which genes are correlated with a queried gene. Results: Using the GEO and ArrayExpress database, we analyzed over 120,000 group by group experiments from gene microarrays to determine the correlating genes for over 30,000 different genes or hypothesized genes. CORD output data is presented for sample queries with focus on genes with well-known interaction networks including p16 (CDKN2A), vimentin (VIM), MyoD (MYOD1). CDKN2A, VIM, and MYOD1 all displayed gene correlations consistent with known interacting genes. Conclusions: We developed a facile, web-enabled program to determine gene-gene correlations across different gene expression microarray platforms. Using well-characterized genes, we illustrate how CORD’s identification of co-expressed genes contributes to a better understanding a gene’s potential function. The website is found at http://cord-db.org.