DOCSLIB.ORG

Gαi2 Signaling Regulates Inflammasome Priming and Cytokine Production by Biasing Macrophage Phenotype Determination

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Gαi2 Signaling Regulates Inflammasome Priming and Cytokine Production by Biasing Macrophage Phenotype Determination Gαi2 Signaling Regulates Inflammasome Priming and Cytokine Production by Biasing Macrophage Phenotype Determination This information is current as Ali Vural, Neel R. Nabar, Il-Young Hwang, Silke Sohn, of September 26, 2021. Chung Park, Mikael C. I. Karlsson, Joe B. Blumer and John H. Kehrl J Immunol published online 25 January 2019 http://www.jimmunol.org/content/early/2019/01/24/jimmun ol.1801145 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 26, 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 Copyright © 2019 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published January 25, 2019, doi:10.4049/jimmunol.1801145 The Journal of Immunology Gai2 Signaling Regulates Inflammasome Priming and Cytokine Production by Biasing Macrophage Phenotype Determination Ali Vural,*,1,2 Neel R. Nabar,*,†,1 Il-Young Hwang,* Silke Sohn,† Chung Park,* Mikael C. I. Karlsson,† Joe B. Blumer,‡ and John H. Kehrl* Macrophages exist as innate immune subsets that exhibit phenotypic heterogeneity and functional plasticity. Their phenotypes are dictated by inputs from the tissue microenvironment. G-protein–coupled receptors are essential in transducing signals from the microenvironment, and heterotrimeric Ga signaling links these receptors to downstream effectors. Several Gai-coupled G-protein–coupled receptors have been implicated in macrophage polarization. In this study, we use genetically modified mice to investigate the role of Gai2 on inflammasome activity and macrophage polarization. We report that Gai2 in murine bone marrow– Downloaded from derived macrophages (BMDMs) regulates IL-1b release after activation of the NLRP3, AIM2, and NLRC4 inflammasomes. We 2/2 G184S/G184S show this regulation stems from the biased polarity of Gai2 deficient (Gnai2 ) and RGS-insensitive Gai2 (Gnai2 ) G184S/G184S BMDMs. We determined that although Gnai2 BMDMs (excess Gai2 signaling) have a tendency toward classically 2/2 activated proinflammatory (M1) phenotype, Gnai2 BMDMs (Gai2 deficient) are biased toward alternatively activated anti- inflammatory (M2) phenotype. Finally, we find that Gai2-deficient macrophages have increased Akt activation and IFN-b pro- duction but defects in ERK1/2 and STAT3 activation after LPS stimulation. Gai2-deficient macrophages also exhibit increased http://www.jimmunol.org/ STAT6 activation after IL-4 stimulation. In summary, our data indicates that excess Gai2 signaling promotes an M1 macrophage phenotype, whereas Gai2 signaling deficiency promotes an M2 phenotype. Understanding Gai2-mediated effects on macrophage polarization may bring to light insights regarding disease pathogenesis and the reprogramming of macrophages for the devel- opment of novel therapeutics. The Journal of Immunology, 2019, 202: 000–000. acrophages are critical mediators of innate immunity macrophages have heterogeneous and flexible phenotypes that are and participate in both the initial propagation of the dictated by signaling inputs from their microenvironment. Mac- M inflammatory response and later in the suppression of rophages are broadly classified as proinflammatory M1 macro- by guest on September 26, 2021 inflammation promoting a return to homeostasis (1). To do so, phages implicated in initiating and sustaining inflammation or anti-inflammatory M2 macrophages that produce high levels of *B-Cell Molecular Immunology Section, Laboratory of Immunoregulation, National IL-10 and promote tissue repair (2). Although progress has been Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, made, the signaling networks responsible for macrophage polari- † MD 20892; Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, zation remain unclear. 171 77 Stockholm, Sweden; and ‡Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, SC 29425 G-protein–coupled receptors (GPCRs) play a central role in reg- 1A.V. and N.R.N. contributed equally to this work. ulating macrophage function, as lipid-based inflammatory mediators, 2Current address: Department of Pharmacology, Wayne State University School of vasoactive amines, complement fragments, and other inflammatory/ Medicine, Detroit, MI. anti-inflammatory stimuli activate signaling by GPCRs linked to ORCIDs: 0000-0002-1269-6338 (A.V.); 0000-0002-9704-3570 (N.R.N.); 0000-0002- heterotrimeric G-proteins (3). Typically, GPCR activation leads 7051-0933 (S.S.); 0000-0002-7819-5333 (C.P.); 0000-0002-0020-3815 (J.B.B.); to GTP nucleotide exchange on Ga, causing its dissociation from 0000-0002-6526-159X (J.H.K.). the Gbg heterodimer; this allows both GTP-bound Ga and Gbg Received for publication August 17, 2018. Accepted for publication December 19, heterodimers to activate their corresponding downstream effec- 2018. tor molecules. Signaling is terminated by the inherent GTPase This work was supported by the intramural program of the National Institutes of Allergy and Infectious Diseases. N.R.N. is supported in part by the Thomas Jefferson activity of Ga subunits, which hydrolyze GTP to GDP and cause University M.D., Ph.D. training program. the reassociation of GDP-bound Ga and Gbg. This cycle highlights A.V., N.R.N., and S.S. did the experimental work; A.V., N.R.N., M.C.I.K, and J.H.K. the importance of heterotrimeric G-proteins in cell signaling net- designed and analyzed the experiments; I.-Y.H., C.P., and J.B.B. provided knockout works, as they transduce environmental stimuli from cell surface mouse strains. A.V., N.R.N., and J.H.K. wrote and edited the manuscript. receptors to generate a coordinated biological response (4). Address correspondence and reprint requests to Dr. Neel R. Nabar and Dr. John H. Kehrl, B Cell Molecular Immunology Section, Laboratory of Immunoregulation, National Insti- Apart from the classical GPCR/G-protein signaling paradigm, tute of Allergy and Infectious Diseases, National Institutes of Health, 10 Center Drive, there exist several regulatory proteins that modulate G-protein Room 11A01, Bethesda, MD 20892. E-mail addresses: [email protected] (N.R.N.) and signaling. The regulators of G-protein signaling (RGS) family [email protected] (J.H.K.) consists of more than 30 members and is defined by the presence of Abbreviations used in this article: AGS, activator of G-protein signaling; Arg1, Arginase 1; BMDM, bone marrow–derived macrophage; ChemR23, chemerin receptor 23; FPR2, an RGS domain (5, 6). RGS proteins act as GTPase accelerating formyl peptide receptor 2; GPCR, G-protein–coupled receptor; iNOS, inducible proteins (GAPs) for specific Ga subunits. They enhance the in- NO synthase; KI, knock-in; KO, knockout; PTX, pertussis toxin; RGS, regulator of trinsic GTPase activity of Ga by stabilizing the GTPase transition G-protein signaling; WT, wild-type. state, accelerating the intrinsic Ga GTPase activity by as much as Copyright Ó 2019 by The American Association of Immunologists, Inc. 0022-1767/19/$37.50 100-fold (6, 7). In this way, RGS proteins limit the duration of www.jimmunol.org/cgi/doi/10.4049/jimmunol.1801145 2 A CRITICAL ROLE FOR Gai2 IN MACROPHAGE POLARIZATION GPCR-mediated G-protein signaling, and G-proteins genetically previously described (32–35). All strains were backcrossed a minimum of modified to be RGS-insensitive proteins show higher basal levels of 12 times to C57BL/6J and experiments were performed using 6- to 14-wk- signaling (6). Conversely, the activators of G-protein signaling old mice with littermate controls. (AGS) family broadly functions as receptor independent activators Cell isolation and culture of G-proteins (8, 9). They do so by serving as alternative binding Bone marrow–derived macrophages (BMDMs) were prepared as previ- partners to influence subunit interactions independent of nucleotide ously described (36). Gai2-deficient macrophages were derived from exchange. Group II AGS proteins, including AGS3 and AGS4, are Gnai22/2 or Gnai2fl/flvav1-cre mice; no differences were observed be- of interest because of their high expression levels in macrophages tween strains. In certain experiments, pertussis toxin (PTX) (Sigma- (10). They exert their effects on heterotrimeric G-proteins through Aldrich) was added either on day 0 (50 ng/ml for days 0–2; 100 ng/ml their G-protein regulatory (GPR) motif, which allows them to bind for days 3–7) or on day 7 (200 ng/ml) overnight. Macrophages were M1 polarized using 1 mg/ml LPS from Escherichia coli (Enzo Life Sciences) to GDP-bound Ga, thereby regulating Gbg signaling (8). for4handpolarizedtowardM2bytreatmentwith20ng/mlmouse Several studies have shown that GPCRs can drive both M1 and M2 rIL-4 (R&D Systems) for 48 h. CD4+CD252 splenic Th cells were macrophage polarization (11). Specifically, formyl peptide receptor isolated by negative depletion using biotinylated Abs to B220
Load more

Recommended publications
  • Critical Role for Non‑GAP Function of Gαs in RGS1‑Mediated Promotion of Melanoma Progression Through AKT and ERK Phosphorylation
    ONCOLOGY REPORTS 39: 2673-2680, 2018 Critical role for non‑GAP function of Gαs in RGS1‑mediated promotion of melanoma progression through AKT and ERK phosphorylation MENG-YAN SUN1*, YUCHONG WANG2*, JI ZHU2, CHUAN LV2, KAI WU2, XIN-WEI WANG2 and CHUN-YU XUE2 1Resident Standardized Training Center, Changzheng Hospital, The Second Military Medical University, Shanghai 200001; 2Department of Plastic Surgery, Changhai Hospital, The Second Military Medical University, Shanghai 200433, P.R. China Received October 17, 2017; Accepted March 13, 2018 DOI: 10.3892/or.2018.6341 Abstract. Regulator of G-protein signaling 1 (RGS1) has been early gene responsive to several B-cell activation signals (2), found to be a critical factor in melanoma and other malignan- and it has been shown to be related to the regulation of cies. However, the mechanism involved in the RGS1-mediated chemokine-induced signaling in B cells (3). The RGS1 gene promotion of melanoma progression is not clear. We based our resides at 1q31, which is involved in several malignancies by study on samples collected from pathological specimens of gains or amplifications in certain subtypes of melanoma (4), melanoma patients. We found by immunohistochemistry that non-Hodgkin lymphoma (5), retinoblastoma (6), pancreatic RGS1 expression was significantly higher in melanoma than cancer (7) and nasopharyngeal carcinoma (8). RGS1 has that noted in nevus tissue (P<0.05). Kaplan-Meier analysis been shown to be upregulated by gene expression profiling in demonstrated a significant correlation between increased RGS1 several different tumor model systems. For example, RGS1 has expression and reduced disease‑specific survival (P<0.05).
    [Show full text]
  • Effect of Distinct Regulator of G-Protein Signaling 10 Isoforms On
    EFFECT OF DISTINCT REGULATOR OF G-PROTEIN SIGNALING 10 ISOFORMS ON CYTOKINE PRODUCTION. by BENJAMIN JACKWOOD (Under the Direction of Shelley Hooks) ABSTRACT G-protein coupled receptors (GPCRs) mediate a wide variety of cellular functions related to cell proliferation and survival. Regulators of G-protein Signaling (RGS) proteins that are important negative regulators of both G-proteins and GPCR products. The focus of this thesis involves two human protein variants of RGS10 and their effects on cytokine levels. RGS proteins are GTPase Accelerating Proteins (GAPs) which can facilitate an increased rate of GTP hydrolysis to drive inactivation of GPCR signaling. Based on their ability to regulate GPCRs, RGS proteins are implicated in multiple disease states including cancer and neuro-inflammation. The aim of this study was to define the similarities or differences among RGS10 protein isoforms, and help understand their non-canonical function. Particularly, differences in primary sequence of RGS10 protein variants and their ability to mediate inflammatory cytokines in human embryonic kidney (HEK) cells was investigated. INDEX WORDS: GPCR, RGS10, ISOFORM, TNF-, INFLAMMATION, VARIANTS EFFECT OF DISTINCT REGULATOR OF G-PROTEIN SIGNALING 10 ISOFORMS ON CYTOKINE PRODUCTION. by BENJAMIN JACKWOOD BS, University of North Georgia, 2015 A Thesis Submitted to the Pharmaceutical and Biomedical Sciences department of The University of Georgia in Partial Fulfillment of the Requirements for the Degree. MASTER OF SCIENCE ATHENS, GEORGIA 2017 © 2017 Benjamin Jackwood All Rights Reserved EFFECT OF DISTINCT REGULATOR OF G-PROTEIN RGS10 ISOFORMS ON CYTOKINE PRODUCTION. by BENJAMIN JACKWOOD Major Professor: Shelley B. Hooks Committee: Phillip Greenspan Jason Zastre Electronic Version Approved: Suzanne Barbour Dean of the Graduate School The University of Georgia May 2017 ACKNOWLEDGEMENTS Thanks to my family, friends, and helpful lab mates for all of their support during my time working and studying at the University of Georgia.
    [Show full text]
  • Gene Expression-Based Recurrence Prediction of Hepatitis B Virus-Related Human Hepatocellular Carcinoma
    GSK 후원 해외연수지원 기금 연구보고 Gene expression-based recurrence prediction of hepatitis B virus-related human hepatocellular carcinoma Yoon Jun Kim, M.D. Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea ABSTRACT Hepatocellular carcinoma (HCC) is one of poor prognostic malignancies because of the high rate of recurrence even after curative resection of tumors. To predict and classify the molecular signatures associated with early recurrence, we profiled the gene expression of 65 HCC samples with hepatitis B infection using genome-scale oligonucleotide microarray. We identified 348 unique gene set well reflecting early recurrence (ER) of HCC, which revealed to be enriched by GTPase signaling related genes, transcription, immune response, cell adhesion and motility related genes. We also generated a signature responding to recurrence time by using Cox proportional hazard model (HR genes). Hierarchical clustering showed that HR genes are more accurate classifier than ER genes. In addition, we applied a meta-analysis to integrate earlier expression data (Iizuka et al, 2003), and obtained 232 genes consistently expressed in both the independent data. This signature was validated in an independent study indicating its robustness for the prediction of HCC recurrence. In conclusion, the gene signatures retrieved from different but complementary methods may provide clues to predict patients with increased risk of developing early recurrence, and to identify novel therapeutic targets for HCC. Key Words: Hepatitis B Virus; Hepatocellular carcinoma; Recurrence; Microarray; Gene Expression Profile Corresponding Author: Yoon Jun Kim, Department of Internal Medicine, Seoul National University Hospital, 28 Yongon-dong, Chongno-gu, Seoul 110-744, Korea.
    [Show full text]
  • Emerging Roles for 3 Utrs in Neurons
    International Journal of Molecular Sciences Review 0 Emerging Roles for 3 UTRs in Neurons Bongmin Bae and Pedro Miura * Department of Biology, University of Nevada, Reno, NV 89557, USA; [email protected] * Correspondence: [email protected] Received: 8 April 2020; Accepted: 9 May 2020; Published: 12 May 2020 Abstract: The 30 untranslated regions (30 UTRs) of mRNAs serve as hubs for post-transcriptional control as the targets of microRNAs (miRNAs) and RNA-binding proteins (RBPs). Sequences in 30 UTRs confer alterations in mRNA stability, direct mRNA localization to subcellular regions, and impart translational control. Thousands of mRNAs are localized to subcellular compartments in neurons—including axons, dendrites, and synapses—where they are thought to undergo local translation. Despite an established role for 30 UTR sequences in imparting mRNA localization in neurons, the specific RNA sequences and structural features at play remain poorly understood. The nervous system selectively expresses longer 30 UTR isoforms via alternative polyadenylation (APA). The regulation of APA in neurons and the neuronal functions of longer 30 UTR mRNA isoforms are starting to be uncovered. Surprising roles for 30 UTRs are emerging beyond the regulation of protein synthesis and include roles as RBP delivery scaffolds and regulators of alternative splicing. Evidence is also emerging that 30 UTRs can be cleaved, leading to stable, isolated 30 UTR fragments which are of unknown function. Mutations in 30 UTRs are implicated in several neurological disorders—more studies are needed to uncover how these mutations impact gene regulation and what is their relationship to disease severity. Keywords: 30 UTR; alternative polyadenylation; local translation; RNA-binding protein; RNA-sequencing; post-transcriptional regulation 1.
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • Transcriptional Control of Tissue-Resident Memory T Cell Generation
    Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Filip Cvetkovski All rights reserved ABSTRACT Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Tissue-resident memory T cells (TRM) are a non-circulating subset of memory that are maintained at sites of pathogen entry and mediate optimal protection against reinfection. Lung TRM can be generated in response to respiratory infection or vaccination, however, the molecular pathways involved in CD4+TRM establishment have not been defined. Here, we performed transcriptional profiling of influenza-specific lung CD4+TRM following influenza infection to identify pathways implicated in CD4+TRM generation and homeostasis. Lung CD4+TRM displayed a unique transcriptional profile distinct from spleen memory, including up-regulation of a gene network induced by the transcription factor IRF4, a known regulator of effector T cell differentiation. In addition, the gene expression profile of lung CD4+TRM was enriched in gene sets previously described in tissue-resident regulatory T cells. Up-regulation of immunomodulatory molecules such as CTLA-4, PD-1, and ICOS, suggested a potential regulatory role for CD4+TRM in tissues. Using loss-of-function genetic experiments in mice, we demonstrate that IRF4 is required for the generation of lung-localized pathogen-specific effector CD4+T cells during acute influenza infection. Influenza-specific IRF4−/− T cells failed to fully express CD44, and maintained high levels of CD62L compared to wild type, suggesting a defect in complete differentiation into lung-tropic effector T cells.
    [Show full text]
  • Predicting Coupling Probabilities of G-Protein Coupled Receptors Gurdeep Singh1,2,†, Asuka Inoue3,*,†, J
    Published online 30 May 2019 Nucleic Acids Research, 2019, Vol. 47, Web Server issue W395–W401 doi: 10.1093/nar/gkz392 PRECOG: PREdicting COupling probabilities of G-protein coupled receptors Gurdeep Singh1,2,†, Asuka Inoue3,*,†, J. Silvio Gutkind4, Robert B. Russell1,2,* and Francesco Raimondi1,2,* 1CellNetworks, Bioquant, Heidelberg University, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany, 2Biochemie Zentrum Heidelberg (BZH), Heidelberg University, Im Neuenheimer Feld 328, 69120 Heidelberg, Germany, 3Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi 980-8578, Japan and 4Department of Pharmacology and Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA Received February 10, 2019; Revised April 13, 2019; Editorial Decision April 24, 2019; Accepted May 01, 2019 ABSTRACT great use in tinkering with signalling pathways in living sys- tems (5). G-protein coupled receptors (GPCRs) control multi- Ligand binding to GPCRs induces conformational ple physiological states by transducing a multitude changes that lead to binding and activation of G-proteins of extracellular stimuli into the cell via coupling to situated on the inner cell membrane. Most of mammalian intra-cellular heterotrimeric G-proteins. Deciphering GPCRs couple with more than one G-protein giving each which G-proteins couple to each of the hundreds receptor a distinct coupling profile (6) and thus specific of GPCRs present in a typical eukaryotic organism downstream cellular responses. Determining these coupling is therefore critical to understand signalling. Here, profiles is critical to understand GPCR biology and phar- we present PRECOG (precog.russelllab.org): a web- macology. Despite decades of research and hundreds of ob- server for predicting GPCR coupling, which allows served interactions, coupling information is still missing for users to: (i) predict coupling probabilities for GPCRs many receptors and sequence determinants of coupling- specificity are still largely unknown.
    [Show full text]
  • Pathognomonic and Epistatic Genetic Alterations in B-Cell Non-Hodgkin
    bioRxiv preprint doi: https://doi.org/10.1101/674259; this version posted June 19, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Pathognomonic and epistatic genetic alterations in 2 B-cell non-Hodgkin lymphoma 3 4 Man Chun John Ma1¥, Saber Tadros1¥, Alyssa Bouska2, Tayla B. Heavican2, Haopeng Yang1, 5 Qing Deng1, Dalia Moore3, Ariz Akhter4, Keenan Hartert3, Neeraj Jain1, Jordan Showell1, 6 Sreejoyee Ghosh1, Lesley Street5, Marta Davidson5, Christopher Carey6, Joshua Tobin7, 7 Deepak Perumal8, Julie M. Vose9, Matthew A. Lunning9, Aliyah R. Sohani10, Benjamin J. 8 Chen11, Shannon Buckley12, Loretta J. Nastoupil1, R. Eric Davis1, Jason R. Westin1, Nathan H. 9 Fowler1, Samir Parekh8, Maher K. Gandhi7, Sattva S. Neelapu1, Douglas Stewart5, Javeed 10 Iqbal2, Timothy Greiner2, Scott J. Rodig13, Adnan Mansoor5, Michael R. Green1,14,15* 11 1Department of Lymphoma and Myeloma, Division of Cancer Medicine, The University of Texas MD 12 Anderson Cancer Center, Houston, TX, USA; 2Department of Pathology and Microbiology, University of 13 Nebraska Medical Center, Omaha, NE, USA; 3Eppley Institute for Research in Cancer and Allied 14 Diseases, University of Nebraska Medical Center, Omaha, NE, USA; 4Department of Pathology and 15 Laboratory Medicine, University of Calgary, Calgary, AB, Canada; 5Section of Hematology, Department of 16 Medicine, University
    [Show full text]
  • Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses
    bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract The high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a proteinprotein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes.
    [Show full text]
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
    [Show full text]
  • G Protein-Coupled Receptors
    G PROTEIN-COUPLED RECEPTORS Overview:- The completion of the Human Genome Project allowed the identification of a large family of proteins with a common motif of seven groups of 20-24 hydrophobic amino acids arranged as α-helices. Approximately 800 of these seven transmembrane (7TM) receptors have been identified of which over 300 are non-olfactory receptors (see Frederikson et al., 2003; Lagerstrom and Schioth, 2008). Subdivision on the basis of sequence homology allows the definition of rhodopsin, secretin, adhesion, glutamate and Frizzled receptor families. NC-IUPHAR recognizes Classes A, B, and C, which equate to the rhodopsin, secretin, and glutamate receptor families. The nomenclature of 7TM receptors is commonly used interchangeably with G protein-coupled receptors (GPCR), although the former nomenclature recognises signalling of 7TM receptors through pathways not involving G proteins. For example, adiponectin and membrane progestin receptors have some sequence homology to 7TM receptors but signal independently of G-proteins and appear to reside in membranes in an inverted fashion compared to conventional GPCR. Additionally, the NPR-C natriuretic peptide receptor has a single transmembrane domain structure, but appears to couple to G proteins to generate cellular responses. The 300+ non-olfactory GPCR are the targets for the majority of drugs in clinical usage (Overington et al., 2006), although only a minority of these receptors are exploited therapeutically. Signalling through GPCR is enacted by the activation of heterotrimeric GTP-binding proteins (G proteins), made up of α, β and γ subunits, where the α and βγ subunits are responsible for signalling. The α subunit (tabulated below) allows definition of one series of signalling cascades and allows grouping of GPCRs to suggest common cellular, tissue and behavioural responses.
    [Show full text]
  • ANALYSIS Doi:10.1038/Nature14663
    ANALYSIS doi:10.1038/nature14663 Universal allosteric mechanism for Ga activation by GPCRs Tilman Flock1, Charles N. J. Ravarani1*, Dawei Sun2,3*, A. J. Venkatakrishnan1{, Melis Kayikci1, Christopher G. Tate1, Dmitry B. Veprintsev2,3 & M. Madan Babu1 G protein-coupled receptors (GPCRs) allosterically activate heterotrimeric G proteins and trigger GDP release. Given that there are 800 human GPCRs and 16 different Ga genes, this raises the question of whether a universal allosteric mechanism governs Ga activation. Here we show that different GPCRs interact with and activate Ga proteins through a highly conserved mechanism. Comparison of Ga with the small G protein Ras reveals how the evolution of short segments that undergo disorder-to-order transitions can decouple regions important for allosteric activation from receptor binding specificity. This might explain how the GPCR–Ga system diversified rapidly, while conserving the allosteric activation mechanism. proteins bind guanine nucleotides and act as molecular switches almost 30 A˚ away from the GDP binding region5 and allosterically trig- in a number of signalling pathways by interconverting between ger GDP release to activate them. 1,2 G a GDP-bound inactive and a GTP-bound active state . They The high-resolution structure of the Gas-bound b2-adrenergic recep- 3 5 consist of two major classes: monomeric small G proteins and hetero- tor (b2AR) provided crucial insights into the receptor–G protein inter- trimeric G proteins4. While small G proteins and the a-subunit (Ga)of face and conformational changes in Ga upon receptor binding6,7. Recent 6 8 heterotrimeric G proteins both contain a GTPase domain (G-domain), studies described dynamic regions in Gas and Gai , the importance of ˚ Ga contains an additional helical domain (H-domain) and also forms a displacement of helix 5 (H5) of Gas and Gat by up to 6 A into the complex with the Gb and Gc subunits.
    [Show full text]