Patients with Systemic Lupus Erythematosus Nucleotide-Releasing Protein 1 in a Subset of Defective Expression of Ras Guanyl
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Rasgrp3 (C33A3) Rabbit Mab A
Revision 1 C 0 2 - t RasGRP3 (C33A3) Rabbit mAb a e r o t S Orders: 877-616-CELL (2355) [email protected] Support: 877-678-TECH (8324) 4 3 Web: [email protected] 3 www.cellsignal.com 3 # 3 Trask Lane Danvers Massachusetts 01923 USA For Research Use Only. Not For Use In Diagnostic Procedures. Applications: Reactivity: Sensitivity: MW (kDa): Source/Isotype: UniProt ID: Entrez-Gene Id: WB H M Endogenous 78 Rabbit IgG Q8IV61 25780 Product Usage Information Application Dilution Western Blotting 1:1000 Storage Supplied in 10 mM sodium HEPES (pH 7.5), 150 mM NaCl, 100 µg/ml BSA, 50% glycerol and less than 0.02% sodium azide. Store at –20°C. Do not aliquot the antibody. Specificity / Sensitivity RasGRP3 (C33A3) Rabbit mAb detects endogenous levels of total RasGRP3 protein. Species Reactivity: Human, Mouse Species predicted to react based on 100% sequence homology: Monkey Source / Purification Monoclonal antibody is produced by immunizing animals with a synthetic peptide corresponding to residues near the carboxy teminus of human RasGRP3. Background Lymphocyte activation occurs in part through activation of the Ras signaling pathway following lymphocyte receptor stimulation. The RasGRP family of guanine nucleotide exchange factors (GEFs) catalyzes the exchange of GDP for GTP on Ras family small GTPases, promoting their active GTP-bound form. Diacylglycerol (DAG) or phorbol ester binding to RasGRP family members causes their translocation to the cell membrane and stimulates their activity (1,2). While T-Cells express RasGRP1, B-cells express both RasGRP1 and RasGRP3. RasGRP3 is important in linking B-cell receptor (BCR) activation to Ras signaling (3). -
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. -
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. -
Mechanistic Characterization of RASGRP1 Variants Identifies an Hnrnp K-Regulated Transcriptional Enhancer Contributing to SLE Susceptibility
bioRxiv preprint doi: https://doi.org/10.1101/568790; this version posted March 6, 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. Mechanistic characterization of RASGRP1 variants identifies an hnRNP K-regulated transcriptional enhancer contributing to SLE susceptibility Julio E. Molineros1*, Bhupinder Singh1*, Chikashi Terao2,3, Yukinori Okada4, Jakub Kaplan1, Barbara McDaniel1, Shuji Akizuki3, Celi Sun1, Carol Webb5, Loren L. Looger6, Swapan K. Nath1 1Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA 2Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan. 3Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan. 4Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan 5Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA 6Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA, USA *Contributed equally Corresponding author Swapan K. Nath, Ph.D. Member Arthritis & Clinical Immunology Program Oklahoma Medical Research Foundation 825 NE 13th St. Oklahoma City, OK 73104 Ph: (405)-271-7765 Fax: (405)-271-4110 [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/568790; this version posted March 6, 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. -
Bioinformatics Analysis of Differentially Expressed Genes in Rotator Cuff Tear
Ren et al. Journal of Orthopaedic Surgery and Research (2018) 13:284 https://doi.org/10.1186/s13018-018-0989-5 RESEARCHARTICLE Open Access Bioinformatics analysis of differentially expressed genes in rotator cuff tear patients using microarray data Yi-Ming Ren†, Yuan-Hui Duan†, Yun-Bo Sun†, Tao Yang and Meng-Qiang Tian* Abstract Background: Rotator cuff tear (RCT) is a common shoulder disorder in the elderly. Muscle atrophy, denervation and fatty infiltration exert secondary injuries on torn rotator cuff muscles. It has been reported that satellite cells (SCs) play roles in pathogenic process and regenerative capacity of human RCT via regulating of target genes. This study aims to complement the differentially expressed genes (DEGs) of SCs that regulated between the torn supraspinatus (SSP) samples and intact subscapularis (SSC) samples, identify their functions and molecular pathways. Methods: The gene expression profile GSE93661 was downloaded and bioinformatics analysis was made. Results: Five hundred fifty one DEGs totally were identified. Among them, 272 DEGs were overexpressed, and the remaining 279 DEGs were underexpressed. Gene ontology (GO) and pathway enrichment analysis of target genes were performed. We furthermore identified some relevant core genes using gene–gene interaction network analysis such as GNG13, GCG, NOTCH1, BCL2, NMUR2, PMCH, FFAR1, AVPR2, GNA14, and KALRN, that may contribute to the understanding of the molecular mechanisms of secondary injuries in RCT. We also discovered that GNG13/calcium signaling pathway is highly correlated with the denervation atrophy pathological process of RCT. Conclusion: These genes and pathways provide a new perspective for revealing the underlying pathological mechanisms and therapy strategy of RCT. -
Immune Adaptor SKAP1 Acts a Scaffold for Polo-Like Kinase 1 (PLK1)
www.nature.com/scientificreports OPEN Immune adaptor SKAP1 acts a scafold for Polo-like kinase 1 (PLK1) for the optimal cell cycling Received: 14 September 2018 Accepted: 6 June 2019 of T-cells Published: xx xx xxxx Monika Raab1,2, Klaus Strebhardt1 & Christopher E. Rudd2,3,4 While the immune cell adaptor protein SKAP1 mediates LFA-1 activation induced by antigen-receptor (TCR/CD3) ligation on T-cells, it is unclear whether the adaptor interacts with other mediators of T-cell function. In this context, the serine/threonine kinase, polo-like kinase (PLK1) regulates multiple steps in the mitotic and cell cycle progression of mammalian cells. Here, we show that SKAP1 is phosphorylated by and binds to PLK1 for the optimal cycling of T-cells. PLK1 binds to the N-terminal residue serine 31 (S31) of SKAP1 and the interaction is needed for optimal PLK1 kinase activity. Further, siRNA knock- down of SKAP1 reduced the rate of T-cell division concurrent with a delay in the expression of PLK1, Cyclin A and pH3. Reconstitution of these KD cells with WT SKAP1, but not the SKAP1 S31 mutant, restored normal cell division. SKAP1-PLK1 binding is dynamically regulated during the cell cycle of T-cells. Our fndings identify a novel role for SKAP1 in the regulation of PLK1 and optimal cell cycling needed for T-cell clonal expansion in response to antigenic activation. Polo-like kinase 1 (PLK1) is a serine/threonine kinase that regulates the mitosis of mammalian cells. It is a mem- ber of the Polo-like serine/threonine kinase (PLKs) family that are structurally conserved from yeast to mam- mals. -
Structural Analysis of Autoinhibition in the Ras-Specific Exchange Factor
RESEARCH ARTICLE elife.elifesciences.org Structural analysis of autoinhibition in the Ras-specific exchange factor RasGRP1 Jeffrey S Iwig1,2, Yvonne Vercoulen3†, Rahul Das1,2†, Tiago Barros1,2,4, Andre Limnander3, Yan Che1,2, Jeffrey G Pelton2, David E Wemmer2,5,6, Jeroen P Roose3*, John Kuriyan1,2,4,5,6* 1Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States; 2California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, United States; 3Department of Anatomy, University of California, San Francisco, San Francisco, United States; 4Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, United States; 5Department of Chemistry, University of California, Berkeley, Berkeley, United States; 6Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, United States Abstract RasGRP1 and SOS are Ras-specific nucleotide exchange factors that have distinct roles in lymphocyte development. RasGRP1 is important in some cancers and autoimmune diseases but, in contrast to SOS, its regulatory mechanisms are poorly understood. Activating signals lead to the membrane recruitment of RasGRP1 and Ras engagement, but it is unclear how interactions between RasGRP1 and Ras are suppressed in the absence of such signals. We present a crystal structure of a fragment of RasGRP1 in which the Ras-binding site is blocked by an interdomain linker and the membrane-interaction surface of RasGRP1 is hidden within a dimerization interface that may be stabilized by the C-terminal oligomerization domain. NMR data demonstrate that calcium binding to the regulatory module generates substantial conformational changes that are incompatible with the inactive assembly. These features allow RasGRP1 to be maintained in an inactive state that is poised for activation by calcium and membrane-localization signals. -
Identification of Biomarkers Associated with Metabolic Cardiovascular Disease Using Mrna-SNP-Mirna Regulatory Network Analysis
Fan et al. BMC Cardiovasc Disord (2021) 21:351 https://doi.org/10.1186/s12872-021-02166-4 RESEARCH Open Access Identifcation of biomarkers associated with metabolic cardiovascular disease using mRNA-SNP-miRNA regulatory network analysis Zhiyuan Fan1, Wenjuan Peng1, Zhiwen Wang2, Ling Zhang1 and Kuo Liu1* Abstract Background: CVD is the leading cause of death in T2DM patients. However, few biomarkers have been identifed to detect and diagnose CVD in the early stage of T2DM. The aim of our study was to identify the important mRNAs, micro (mi)RNAs and SNPs (single nucleotide polymorphisms) that are associated with metabolic cardiovascular disease. Materials and methods: Expression profles and GWAS data were obtained from Gene Expression Omnibus (GEO) database. MiRNA-sequencing was conducted by Illumina HiSeq 2000 platform in T2DM patients and T2DM with CVD patients. EQTL analysis and gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrich- ment analyses were conducted. MRNA-miRNA co-expression network and mRNA-SNP-miRNA interaction network were established and visualized by Cytoscape 3.7.2. Results: In our study, we identifed 56 genes and 16 miRNAs that were signifcantly diferentially expressed. KEGG analyses results indicated that B cell receptor signaling pathway and hematopoietic cell lineage were included in the biological functions of diferentially expressed genes. MRNA-miRNA co-expression network and mRNA-SNP-miRNA interaction network illustrated that let-7i-5p, RASGRP3, KRT1 and CEP41 may be potential biomarkers for the early detection and diagnosis of CVD in T2DM patients. Conclusion: Our results suggested that downregulated let-7i-5p, and upregulated RASGRP3, KRT1 and CEP41 may play crucial roles in molecular mechanisms underlying the initiation and development of CVD in T2DM patients. -
Global Transcriptome Analysis Identifies Weight Regain-Induced
OPEN International Journal of Obesity (2018) 42, 755–764 www.nature.com/ijo ORIGINAL ARTICLE Global transcriptome analysis identifies weight regain-induced activation of adaptive immune responses in white adipose tissue of mice DS Kyung1,2,3,7, HR Sung1,2,7, YJ Kim1,2, KD Kim4, SY Cho2,5, JH Choi4, Y-H Lee6, IY Kim1,2 and JK Seong1,2,3 OBJECTIVE: Studies have indicated that weight regain following weight loss predisposes obese individuals to metabolic disorders; however, the molecular mechanism of this potential adverse effect of weight regain is not fully understood. Here we investigated global transcriptome changes and the immune response in mouse white adipose tissue caused by weight regain. DESIGN: We established a diet switch protocol to compare the effects of weight regain with those of weight gain without precedent weight loss, weight loss maintenance and chow diet. We conducted a time course analysis of global transcriptome changes in gonadal white adipose tissue (gWAT) during the weight fluctuation. Co-expression network analysis was used to identify functional modules associated with the weigh regain phenotype. Immune cell populations in gWAT were characterized by flow- cytometric immunophenotyping. Metabolic phenotypes were monitored by histological analysis of adipose tissue and liver, and blood-chemistry and body weight/composition analyses. RESULTS: In total, 952 genes were differentially expressed in the gWAT in the weight regain vs the weight gain group. Upregulated genes were associated with immune response and leukocyte activation. Co-expression network analysis showed that genes involved in major histocompatibility complex I and II-mediated antigen presentation and T-cell activation function were upregulated. -
Inflammatory, Regulatory, and Autophagy Co-Expression Modules
Durocher et al. Journal of Neuroinflammation (2019) 16:56 https://doi.org/10.1186/s12974-019-1433-4 RESEARCH Open Access Inflammatory, regulatory, and autophagy co-expression modules and hub genes underlie the peripheral immune response to human intracerebral hemorrhage Marc Durocher1, Bradley P. Ander1, Glen Jickling1, Farah Hamade1, Heather Hull1, Bodie Knepp1, Da Zhi Liu1, Xinhua Zhan1, Anh Tran1, Xiyuan Cheng1, Kwan Ng1, Alan Yee1, Frank R. Sharp1 and Boryana Stamova1,2* Abstract Background: Intracerebral hemorrhage (ICH) has a high morbidity and mortality. The peripheral immune system and cross-talk between peripheral blood and brain have been implicated in the ICH immune response. Thus, we delineated the gene networks associated with human ICH in the peripheral blood transcriptome. We also compared the differentially expressed genes in blood following ICH to a prior human study of perihematomal brain tissue. Methods: We performed peripheral blood whole-transcriptome analysis of ICH and matched vascular risk factor control subjects (n = 66). Gene co-expression network analysis identified groups of co-expressed genes (modules) associated with ICH and their most interconnected genes (hubs). Mixed-effects regression identified differentially expressed genes in ICH compared to controls. Results: Of seven ICH-associated modules, six were enriched with cell-specific genes: one neutrophil module, one neutrophil plus monocyte module, one T cell module, one Natural Killer cell module, and two erythroblast modules. The neutrophil/monocyte modules were enriched in inflammatory/immune pathways; the T cell module in T cell receptor signaling genes; and the Natural Killer cell module in genes regulating alternative splicing, epigenetic, and post-translational modifications. -
Rasgrp1 Overexpression in the Epidermis of Transgenic Mice Contributes to Tumor Progression During Multistage Skin Carcinogenesis Courtney T
Research Article RasGRP1 Overexpression in the Epidermis of Transgenic Mice Contributes to Tumor Progression during Multistage Skin Carcinogenesis Courtney T. Luke,1 Carolyn E. Oki-Idouchi,1 J. Mark Cline,2 and Patricia S. Lorenzo1 1Natural Products and Cancer Biology Program, Cancer Research Center of Hawaii, University of Hawaii at Manoa, Honolulu, Hawaii and 2Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, North Carolina Abstract diacylglycerol and its ultrapotent analogues, the phorbol esters (3). RasGRP1 is a guanine nucleotide exchange factor for Ras, Previous studies on RasGRP1 and RasGRP3 showed their high- activated in response to the second messenger diacylglycerol affinity binding to diacylglycerol analogues (4–6), resulting in the and its ultrapotent analogues, the phorbol esters. We have activation of Ras and Ras signaling cascades, and suggesting that previously shown that RasGRP1 is expressed in mouse pathways besides PKC could transmit signals from diacylglycerol to epidermal keratinocytes and that transgenic mice over- Ras. In fact, the discovery of RasGRP1 has led to a better under- expressing RasGRP1 in the epidermis under the keratin 5 standing of the link between T-cell receptor stimulation and phos- promoter (K5.RasGRP1) are prone to developing spontaneous pholipase C activation with Ras signaling (7). In contrast to PKC, RasGRP members have limited tissue distribution. RasGRP1, for papillomas and squamous cell carcinomas, suggesting a role for RasGRP1 in skin tumorigenesis. Here, we examined the example, is expressed in Tcells and at lower levels in B cells, neurons, response of the K5.RasGRP1 mice to multistage skin carcino- mastocytes, and some kidney cells (8–12). -
Integrating Autoimmune Risk Loci with Gene-Expression Data Identifies Specific Pathogenic Immune Cell Subsets
Integrating Autoimmune Risk Loci with Gene-Expression Data Identifies Specific Pathogenic Immune Cell Subsets The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Hu, Xinli et al. “Integrating Autoimmune Risk Loci with Gene- Expression Data Identifies Specific Pathogenic Immune Cell Subsets.” The American Journal of Human Genetics 89 (2011): 496-506. As Published http://dx.doi.org/10.1016/j.ajhg.2011.09.002 Publisher Elsevier B.V. Version Final Published Version Citable link http://hdl.handle.net/1721.1/66693 Terms of Use Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. ARTICLE Integrating Autoimmune Risk Loci with Gene-Expression Data Identifies Specific Pathogenic Immune Cell Subsets Xinli Hu,1,2,3,4 Hyun Kim,1,2 Eli Stahl,1,2,3 Robert Plenge,1,2,3 Mark Daly,3,5 and Soumya Raychaudhuri1,2,3,6,* Although genome-wide association studies have implicated many individual loci in complex diseases, identifying the exact causal alleles and the cell types within which they act remains greatly challenging. To ultimately understand disease mechanism, researchers must carefully conceive functional studies in relevant pathogenic cell types to demonstrate the cellular impact of disease-associated genetic variants. This challenge is highlighted in autoimmune diseases, such as rheumatoid arthritis, where any of a broad range of immunological cell types might potentially be impacted by genetic variation to cause disease. To this end, we developed a statistical approach to identify potentially pathogenic cell types in autoimmune diseases by using a gene-expression data set of 223 murine-sorted immune cells from the Immunological Genome Consortium.