GNAI2 Promotes Proliferation and Decreases Apoptosis in Rabbit Melanocytes
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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. -
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. -
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 -
Novel Driver Strength Index Highlights Important Cancer Genes in TCGA Pancanatlas Patients
medRxiv preprint doi: https://doi.org/10.1101/2021.08.01.21261447; this version posted August 5, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Novel Driver Strength Index highlights important cancer genes in TCGA PanCanAtlas patients Aleksey V. Belikov*, Danila V. Otnyukov, Alexey D. Vyatkin and Sergey V. Leonov Laboratory of Innovative Medicine, School of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Moscow Region, Russia *Corresponding author: [email protected] NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2021.08.01.21261447; this version posted August 5, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Abstract Elucidating crucial driver genes is paramount for understanding the cancer origins and mechanisms of progression, as well as selecting targets for molecular therapy. Cancer genes are usually ranked by the frequency of mutation, which, however, does not necessarily reflect their driver strength. Here we hypothesize that driver strength is higher for genes that are preferentially mutated in patients with few driver mutations overall, because these few mutations should be strong enough to initiate cancer. -
G Protein Alpha Inhibitor 1 (GNAI1) Rabbit Polyclonal Antibody Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for TA335036 G protein alpha inhibitor 1 (GNAI1) Rabbit Polyclonal Antibody Product data: Product Type: Primary Antibodies Applications: WB Recommended Dilution: WB Reactivity: Human, Mouse, Rat Host: Rabbit Isotype: IgG Clonality: Polyclonal Immunogen: The immunogen for anti-GNAI1 antibody: synthetic peptide directed towards the middle region of human GNAI1. Synthetic peptide located within the following region: YQLNDSAAYYLNDLDRIAQPNYIPTQQDVLRTRVKTTGIVETHFTFKDLH Formulation: Liquid. Purified antibody supplied in 1x PBS buffer with 0.09% (w/v) sodium azide and 2% sucrose. Note that this product is shipped as lyophilized powder to China customers. Purification: Affinity Purified Conjugation: Unconjugated Storage: Store at -20°C as received. Stability: Stable for 12 months from date of receipt. Predicted Protein Size: 40 kDa Gene Name: G protein subunit alpha i1 Database Link: NP_002060 Entrez Gene 14677 MouseEntrez Gene 25686 RatEntrez Gene 2770 Human P63096 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 4 G protein alpha inhibitor 1 (GNAI1) Rabbit Polyclonal Antibody – TA335036 Background: Guanine nucleotide-binding proteins (G proteins) form a large family of signal-transducing molecules. They are found as heterotrimers made up of alpha, beta, and gamma subunits. Members of the G protein family have been characterized most extensively on the basis of the alpha subunit, which binds guanine nucleotide, is capable of hydrolyzing GTP, and interacts with specific receptor and effector molecules. -
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. -
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. -
Screening of Potential Genes and Transcription Factors Of
ANIMAL STUDY e-ISSN 1643-3750 © Med Sci Monit, 2018; 24: 503-510 DOI: 10.12659/MSM.907445 Received: 2017.10.08 Accepted: 2018.01.01 Screening of Potential Genes and Transcription Published: 2018.01.25 Factors of Postoperative Cognitive Dysfunction via Bioinformatics Methods Authors’ Contribution: ABE 1 Yafeng Wang 1 Department of Anesthesiology, The First Affiliated Hospital of Guangxi Medical Study Design A AB 1 Ailan Huang University, Nanning, Guangxi, P.R. China Data Collection B 2 Department of Gynecology, People’s Hospital of Guangxi Zhuang Autonomous Statistical Analysis C BEF 1 Lixia Gan Region, The First Affiliated Hospital of Guangxi Medical University, Nanning, Data Interpretation D BCF 1 Yanli Bao Guangxi, P.R. China Manuscript Preparation E BDF 1 Weilin Zhu 3 Department of Anesthesiology, The First Affiliated Hospital of Guangxi Medical Literature Search F University, Nanning, Guangxi, P.R. China Funds Collection G EF 1 Yanyan Hu AE 1 Li Ma CF 2 Shiyang Wei DE 3 Yuyan Lan Corresponding Author: Yafeng Wang, e-mail: [email protected] Source of support: Departmental sources Background: The aim of this study was to explore the potential genes and transcription factors involved in postoperative cognitive dysfunction (POCD) via bioinformatics analysis. Material/Methods: GSE95070 miRNA expression profiles were downloaded from Gene Expression Omnibus database, which in- cluded five hippocampal tissues from POCD mice and controls. Moreover, the differentially expressed miRNAs (DEMs) between the two groups were identified. In addition, the target genes of DEMs were predicted using Targetscan 7.1, followed by protein-protein interaction (PPI) network construction, functional enrichment anal- ysis, pathway analysis, and prediction of transcription factors (TFs) targeting the potential targets. -
GNAI3 Gene G Protein Subunit Alpha I3
GNAI3 gene G protein subunit alpha i3 Normal Function The GNAI3 gene provides instructions for making one component, the inhibitory alpha subunit, of a protein complex called a guanine nucleotide-binding protein (G protein). G proteins are composed of three protein subunits: alpha, beta, and gamma. Each of these subunits is produced from a different gene. Through a process called signal transduction, G proteins trigger a complex network of signaling pathways within cells. These pathways help transmit information from outside the cell to inside the cell. Specifically, G proteins made with the GNAI3 inhibitory alpha subunit reduce (inhibit) the activity of an enzyme called adenylyl cyclase, which is an important chemical messenger within cells. G protein signaling ultimately influences many cell activities, instructing the cell to grow, divide, or take on specialized functions. Studies suggest that G protein signaling involving the GNAI3 inhibitory alpha subunit contributes to the development of the first and second pharyngeal arches. These embryonic structures ultimately develop into the jawbones, facial muscles, middle ear bones, ear canals, outer ears, and related tissues. Health Conditions Related to Genetic Changes Auriculo-condylar syndrome At least two mutations in the GNAI3 gene have been found to cause auriculo-condylar syndrome, a disorder that primarily affects the development of the ears and lower jaw ( mandible). The identified mutations change single protein building blocks (amino acids) in the inhibitory alpha subunit. These mutations likely alter the structure of the inhibitory alpha subunit and impair G protein signaling. Abnormal signaling alters the formation of the lower jaw: instead of developing normally, the lower jaw becomes shaped more like the smaller upper jaw (maxilla). -
Expression of Regulator of G Protei
Toll-Like Receptor Signaling Alters the Expression of Regulator of G Protein Signaling Proteins in Dendritic Cells: Implications for G Protein-Coupled Receptor This information is current as Signaling of September 29, 2021. Geng-Xian Shi, Kathleen Harrison, Sang-Bae Han, Chantal Moratz and John H. Kehrl J Immunol 2004; 172:5175-5184; ; doi: 10.4049/jimmunol.172.9.5175 Downloaded from http://www.jimmunol.org/content/172/9/5175 References This article cites 49 articles, 26 of which you can access for free at: http://www.jimmunol.org/ http://www.jimmunol.org/content/172/9/5175.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists by guest on September 29, 2021 • Fast Publication! 4 weeks from acceptance to publication *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 © 2004 by The American Association of Immunologists All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Toll-Like Receptor Signaling Alters the Expression of Regulator of G Protein Signaling Proteins in Dendritic Cells: Implications for G Protein-Coupled Receptor Signaling Geng-Xian Shi,1 Kathleen Harrison,1 Sang-Bae Han,1 Chantal Moratz, and John H. -
Stearic Acid Blunts Growth-Factor Signaling Via Oleoylation of GNAI Proteins
ARTICLE https://doi.org/10.1038/s41467-021-24844-9 OPEN Stearic acid blunts growth-factor signaling via oleoylation of GNAI proteins Hana Nůsková 1,2, Marina V. Serebryakova 3,5, Anna Ferrer-Caelles 1,2,5, Timo Sachsenheimer4, Christian Lüchtenborg4, Aubry K. Miller 1, Britta Brügger 4, Larisa V. Kordyukova 3 & ✉ Aurelio A. Teleman 1,2 Covalent attachment of C16:0 to proteins (palmitoylation) regulates protein function. Pro- 1234567890():,; teins are also S-acylated by other fatty acids including C18:0. Whether protein acylation with different fatty acids has different functional outcomes is not well studied. We show here that C18:0 (stearate) and C18:1 (oleate) compete with C16:0 to S-acylate Cys3 of GNAI proteins. C18:0 becomes desaturated so that C18:0 and C18:1 both cause S-oleoylation of GNAI. Exposure of cells to C16:0 or C18:0 shifts GNAI acylation towards palmitoylation or oleoy- lation, respectively. Oleoylation causes GNAI proteins to shift out of cell membrane detergent-resistant fractions where they potentiate EGFR signaling. Consequently, exposure of cells to C18:0 reduces recruitment of Gab1 to EGFR and reduces AKT activation. This provides a molecular mechanism for the anti-tumor effects of C18:0, uncovers a mechanistic link how metabolites affect cell signaling, and provides evidence that the identity of the fatty acid acylating a protein can have functional consequences. 1 German Cancer Research Center (DKFZ), Heidelberg, Germany. 2 Heidelberg University, Heidelberg, Germany. 3 A.N. Belozersky Institute of Physico- Chemical Biology, M.V. Lomonosov Moscow State University, Moscow, Russia. 4 Heidelberg University Biochemistry Center (BZH), Heidelberg, Germany. -
Multi-Functionality of Proteins Involved in GPCR and G Protein Signaling: Making Sense of Structure–Function Continuum with In
Cellular and Molecular Life Sciences (2019) 76:4461–4492 https://doi.org/10.1007/s00018-019-03276-1 Cellular andMolecular Life Sciences REVIEW Multi‑functionality of proteins involved in GPCR and G protein signaling: making sense of structure–function continuum with intrinsic disorder‑based proteoforms Alexander V. Fonin1 · April L. Darling2 · Irina M. Kuznetsova1 · Konstantin K. Turoverov1,3 · Vladimir N. Uversky2,4 Received: 5 August 2019 / Revised: 5 August 2019 / Accepted: 12 August 2019 / Published online: 19 August 2019 © Springer Nature Switzerland AG 2019 Abstract GPCR–G protein signaling system recognizes a multitude of extracellular ligands and triggers a variety of intracellular signal- ing cascades in response. In humans, this system includes more than 800 various GPCRs and a large set of heterotrimeric G proteins. Complexity of this system goes far beyond a multitude of pair-wise ligand–GPCR and GPCR–G protein interactions. In fact, one GPCR can recognize more than one extracellular signal and interact with more than one G protein. Furthermore, one ligand can activate more than one GPCR, and multiple GPCRs can couple to the same G protein. This defnes an intricate multifunctionality of this important signaling system. Here, we show that the multifunctionality of GPCR–G protein system represents an illustrative example of the protein structure–function continuum, where structures of the involved proteins represent a complex mosaic of diferently folded regions (foldons, non-foldons, unfoldons, semi-foldons, and inducible foldons). The functionality of resulting highly dynamic conformational ensembles is fne-tuned by various post-translational modifcations and alternative splicing, and such ensembles can undergo dramatic changes at interaction with their specifc partners.