Translocation Between PI(4,5)P2-Poor and PI(4,5)P2-Rich Microdomains During Store Depletion Determines STIM1 Conformation and Orai1 Gating
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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. -
Supplementary Table 4
Li et al. mir-30d in human cancer Table S4. The probe list down-regulated in MDA-MB-231 cells by mir-30d mimic transfection Gene Probe Gene symbol Description Row set 27758 8119801 ABCC10 ATP-binding cassette, sub-family C (CFTR/MRP), member 10 15497 8101675 ABCG2 ATP-binding cassette, sub-family G (WHITE), member 2 18536 8158725 ABL1 c-abl oncogene 1, receptor tyrosine kinase 21232 8058591 ACADL acyl-Coenzyme A dehydrogenase, long chain 12466 7936028 ACTR1A ARP1 actin-related protein 1 homolog A, centractin alpha (yeast) 18102 8056005 ACVR1 activin A receptor, type I 20790 8115490 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 15688 7979904 ADAM21 ADAM metallopeptidase domain 21 14937 8054254 AFF3 AF4/FMR2 family, member 3 23560 8121277 AIM1 absent in melanoma 1 20209 7921434 AIM2 absent in melanoma 2 19272 8136336 AKR1B10 aldo-keto reductase family 1, member B10 (aldose reductase) 18013 7954777 ALG10 asparagine-linked glycosylation 10, alpha-1,2-glucosyltransferase homolog (S. pombe) 30049 7954789 ALG10B asparagine-linked glycosylation 10, alpha-1,2-glucosyltransferase homolog B (yeast) 28807 7962579 AMIGO2 adhesion molecule with Ig-like domain 2 5576 8112596 ANKRA2 ankyrin repeat, family A (RFXANK-like), 2 23414 7922121 ANKRD36BL1 ankyrin repeat domain 36B-like 1 (pseudogene) 29782 8098246 ANXA10 annexin A10 22609 8030470 AP2A1 adaptor-related protein complex 2, alpha 1 subunit 14426 8107421 AP3S1 adaptor-related protein complex 3, sigma 1 subunit 12042 8099760 ARAP2 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 2 30227 8059854 ARL4C ADP-ribosylation factor-like 4C 32785 8143766 ARP11 actin-related Arp11 6497 8052125 ASB3 ankyrin repeat and SOCS box-containing 3 24269 8128592 ATG5 ATG5 autophagy related 5 homolog (S. -
Mechanisms of Synaptic Plasticity Mediated by Clathrin Adaptor-Protein Complexes 1 and 2 in Mice
Mechanisms of synaptic plasticity mediated by Clathrin Adaptor-protein complexes 1 and 2 in mice Dissertation for the award of the degree “Doctor rerum naturalium” at the Georg-August-University Göttingen within the doctoral program “Molecular Biology of Cells” of the Georg-August University School of Science (GAUSS) Submitted by Ratnakar Mishra Born in Birpur, Bihar, India Göttingen, Germany 2019 1 Members of the Thesis Committee Prof. Dr. Peter Schu Institute for Cellular Biochemistry, (Supervisor and first referee) University Medical Center Göttingen, Germany Dr. Hans Dieter Schmitt Neurobiology, Max Planck Institute (Second referee) for Biophysical Chemistry, Göttingen, Germany Prof. Dr. med. Thomas A. Bayer Division of Molecular Psychiatry, University Medical Center, Göttingen, Germany Additional Members of the Examination Board Prof. Dr. Silvio O. Rizzoli Department of Neuro-and Sensory Physiology, University Medical Center Göttingen, Germany Dr. Roland Dosch Institute of Developmental Biochemistry, University Medical Center Göttingen, Germany Prof. Dr. med. Martin Oppermann Institute of Cellular and Molecular Immunology, University Medical Center, Göttingen, Germany Date of oral examination: 14th may 2019 2 Table of Contents List of abbreviations ................................................................................. 5 Abstract ................................................................................................... 7 Chapter 1: Introduction ............................................................................ -
Figure S1. SYT1 and SYT3 Are Induced Under Abiotic Stress (Related to Figure 1)
Figure S1. SYT1 and SYT3 are induced under abiotic stress (related to Figure 1). (A) Phylogenetic clustering of the Arabidopsis protein coding sequence of SYT1, SYT2, SYT3, SYT4, SYT5 and the Homo sapiens E-Syt1. Phylogenetic tree was inferred using the Neighbor-Joining method. The optimal tree with the sum of branch length = 3.26 is shown. The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the p-distance method and are in the units of the number of amino acid differences per site. This analysis involved 11 amino acid sequences. All ambiguous positions were removed for each sequence pair (pairwise deletion option). There were a total of 1752 positions in the final dataset. Evolutionary analyses were conducted using MEGA X (Kumar et al., 2018). (B) Gene expression profiles based on RNA-seq analysis of SYT1, SYT2, SYT3, SYT4, and SYT5 in vegetative tissues at different developmental stages from TRAVA database http://travadb.org/). Each dot represent a RNAseq value and the bar represent the median. (C) Gene expression profiles based on RNA-seq analysis of SYT1, SYT3, and SYT5 in eFP-seq Browser after various abiotic stresses (https://bar.utoronto.ca/eFP-Seq_Browser/).https://bar.utoronto.ca/eFP- Seq_Browser/). (D) Heatmap representing the expression responses to abiotic stress of SYT1, SYT3 and SYT5. Expression levels genes are represented as the fold-change relative to the control. Red represents a gene that is induced, and blue represents a gene that is repressed in response to the indicated abiotic stress. -
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 -
Identification of Potential Key Genes and Pathway Linked with Sporadic Creutzfeldt-Jakob Disease Based on Integrated Bioinformatics Analyses
medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. 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. All rights reserved. No reuse allowed without permission. Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. 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. All rights reserved. No reuse allowed without permission. Abstract Sporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened. -
Integrating Protein Copy Numbers with Interaction Networks to Quantify Stoichiometry in Mammalian Endocytosis
bioRxiv preprint doi: https://doi.org/10.1101/2020.10.29.361196; this version posted October 29, 2020. 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-ND 4.0 International license. Integrating protein copy numbers with interaction networks to quantify stoichiometry in mammalian endocytosis Daisy Duan1, Meretta Hanson1, David O. Holland2, Margaret E Johnson1* 1TC Jenkins Department of Biophysics, Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21218. 2NIH, Bethesda, MD, 20892. *Corresponding Author: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.10.29.361196; this version posted October 29, 2020. 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-ND 4.0 International license. Abstract Proteins that drive processes like clathrin-mediated endocytosis (CME) are expressed at various copy numbers within a cell, from hundreds (e.g. auxilin) to millions (e.g. clathrin). Between cell types with identical genomes, copy numbers further vary significantly both in absolute and relative abundance. These variations contain essential information about each protein’s function, but how significant are these variations and how can they be quantified to infer useful functional behavior? Here, we address this by quantifying the stoichiometry of proteins involved in the CME network. We find robust trends across three cell types in proteins that are sub- vs super-stoichiometric in terms of protein function, network topology (e.g. -
Genes and Symptoms of Schizophrenia: Modifiers, Networks, and Interactions in Complex Disease
Virginia Commonwealth University VCU Scholars Compass Theses and Dissertations Graduate School 2009 Genes and Symptoms of Schizophrenia: Modifiers, Networks, and Interactions in Complex Disease Sarah Bergen Virginia Commonwealth University Follow this and additional works at: https://scholarscompass.vcu.edu/etd Part of the Medical Genetics Commons © The Author Downloaded from https://scholarscompass.vcu.edu/etd/1940 This Dissertation is brought to you for free and open access by the Graduate School at VCU Scholars Compass. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of VCU Scholars Compass. For more information, please contact [email protected]. Genes and Symptoms of Schizophrenia: Modifiers, Networks, and Interactions in Complex Disease A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University by: Sarah E. Bergen B.A., Macalester College, 2000 M.S., University of Pittsburgh, 2004 Director: Kenneth S. Kendler, M.D. Distinguished Professor, Departments of Psychiatry and Human and Molecular Genetics Virginia Commonwealth University Richmond, VA September, 2009 Acknowledgements First, I want to thank my parents whose unconditional love and only slightly conditional support has carried me through every bump and rough patch on my journey through grad school (and life). None of my work would have been accomplished without all you have done for me, and I am profoundly grateful. I have been extremely fortunate in my experiences here to not only have been quite productive scientifically, but also to have enjoyed the graduate school experience. This is almost entirely due to the brilliant and kind people I have had the opportunity to work with. -
Article (Published Version)
Article Endogenous beta-cell CART regulates insulin secretion and transcription of beta-cell genes SHCHERBINA, L., et al. Reference SHCHERBINA, L., et al. Endogenous beta-cell CART regulates insulin secretion and transcription of beta-cell genes. Molecular and Cellular Endocrinology, 2017, vol. 447, p. 52-60 DOI : 10.1016/j.mce.2017.02.027 Available at: http://archive-ouverte.unige.ch/unige:94430 Disclaimer: layout of this document may differ from the published version. 1 / 1 Molecular and Cellular Endocrinology 447 (2017) 52e60 Contents lists available at ScienceDirect Molecular and Cellular Endocrinology journal homepage: www.elsevier.com/locate/mce Endogenous beta-cell CART regulates insulin secretion and transcription of beta-cell genes L. Shcherbina a, A. Edlund a, J.L.S. Esguerra a, M. Abels a, Y. Zhou a, E. Ottosson-Laakso a, * C.B. Wollheim a, b, O. Hansson a, L. Eliasson a, N. Wierup a, a Lund University Diabetes Centre, Skåne University Hospital, Jan Waldenstroms€ Gata 35, 214 28 Malmo,€ Sweden b Department of Cell Physiology and Metabolism, University Medical Center, 1 Rue Michel-Servet, CH-1211 Geneve 4, Switzerland article info abstract Article history: Impaired beta-cell function is key to the development of type 2 diabetes. Cocaine- and amphetamine- Received 14 October 2016 regulated transcript (CART) is an islet peptide with insulinotropic and glucagonostatic properties. Here Received in revised form we studied the role of endogenous CART in beta-cell function. CART silencing in INS-1 (832/13) beta-cells 16 February 2017 reduced insulin secretion and production, ATP levels and beta-cell exocytosis. This was substantiated by Accepted 16 February 2017 reduced expression of several exocytosis genes, as well as reduced expression of genes important for Available online 24 February 2017 insulin secretion and processing. -
Drosophila and Human Transcriptomic Data Mining Provides Evidence for Therapeutic
Drosophila and human transcriptomic data mining provides evidence for therapeutic mechanism of pentylenetetrazole in Down syndrome Author Abhay Sharma Institute of Genomics and Integrative Biology Council of Scientific and Industrial Research Delhi University Campus, Mall Road Delhi 110007, India Tel: +91-11-27666156, Fax: +91-11-27662407 Email: [email protected] Nature Precedings : hdl:10101/npre.2010.4330.1 Posted 5 Apr 2010 Running head: Pentylenetetrazole mechanism in Down syndrome 1 Abstract Pentylenetetrazole (PTZ) has recently been found to ameliorate cognitive impairment in rodent models of Down syndrome (DS). The mechanism underlying PTZ’s therapeutic effect is however not clear. Microarray profiling has previously reported differential expression of genes in DS. No mammalian transcriptomic data on PTZ treatment however exists. Nevertheless, a Drosophila model inspired by rodent models of PTZ induced kindling plasticity has recently been described. Microarray profiling has shown PTZ’s downregulatory effect on gene expression in fly heads. In a comparative transcriptomics approach, I have analyzed the available microarray data in order to identify potential mechanism of PTZ action in DS. I find that transcriptomic correlates of chronic PTZ in Drosophila and DS counteract each other. A significant enrichment is observed between PTZ downregulated and DS upregulated genes, and a significant depletion between PTZ downregulated and DS dowwnregulated genes. Further, the common genes in PTZ Nature Precedings : hdl:10101/npre.2010.4330.1 Posted 5 Apr 2010 downregulated and DS upregulated sets show enrichment for MAP kinase pathway. My analysis suggests that downregulation of MAP kinase pathway may mediate therapeutic effect of PTZ in DS. Existing evidence implicating MAP kinase pathway in DS supports this observation. -
Gangliosides Interact with Synaptotagmin to Form the High-Affinity Receptor Complex for Botulinum Neurotoxin B
Gangliosides interact with synaptotagmin to form the high-affinity receptor complex for botulinum neurotoxin B Alessandra Floresa,b,1, Jorge Ramirez-Francoa,b,1, Richard Desplantesa,b, Kévin Debreuxa,b, Géraldine Ferraccib,c, Florian Wernerta,b, Marie-Pierre Blanchardb,c, Yves Mauleta,b, Fahamoe Youssoufa,b, Marion Sangiardia,b, Cécile Iborraa,b, Michel Robert Popoffd, Michael Seagara,b, Jacques Fantinia,b, Christian Lévêquea,b, and Oussama El Fara,b,2 aUnité de Neurobiologie des Canaux Ioniques et de la Synapse, INSERM UMR_S 1072, 13015 Marseille, France; bAix-Marseille Université, 13015 Marseille, France; cInstitut de Neurophysiopathologie, CNRS UMR 7051, 13015 Marseille, France; and dBacterial Toxins, Équipe de Recherche Labellisée 6002, Institut Pasteur, 75015 Paris, France Edited by Solomon H. Snyder, Johns Hopkins University School of Medicine, Baltimore, MD, and approved August 1, 2019 (received for review May 15, 2019) Botulinum neurotoxin type B (BoNT/B) recognizes nerve terminals synaptic vesicle proteins that become accessible at the presynaptic by binding to 2 receptor components: a polysialoganglioside, membrane upon exocytosis. BoNT/A and E bind to the synaptic predominantly GT1b, and synaptotagmin 1/2. It is widely thought vesicle protein 2 (SV2), while BoNT/B binds synaptotagmin (SYT that BoNT/B initially binds to GT1b then diffuses in the plane of isoforms 1 and 2). the membrane to interact with synaptotagmin. We have addressed Gangliosides are amphiphilic glycosphingolipid molecules the hypothesis that a GT1b–synaptotagmin cis complex forms the predominantly anchored, via their ceramide group, in the outer BoNT/B receptor. We identified a consensus glycosphingolipid-binding leaflet of plasma membranes. Their extracellular polar part is motif in the extracellular juxtamembrane domain of synaptotagmins composed of several characteristic sugar molecules with the 1/2 and confirmed by Langmuir monolayer, surface plasmon reso- negatively charged sialic acids at precise positions. -
The Mrna-Binding Protein RBM3 Regulates Activity Patterns and Local Synaptic Translation in Cultured Hippocampal Neurons
The Journal of Neuroscience, February 10, 2021 • 41(6):1157–1173 • 1157 Cellular/Molecular The mRNA-Binding Protein RBM3 Regulates Activity Patterns and Local Synaptic Translation in Cultured Hippocampal Neurons Sinem M. Sertel,1,2 Malena S. von Elling-Tammen,1 and Silvio O. Rizzoli1,2 1Institute for Neuro- and Sensory Physiology, University Medical Center Göttingen, Göttingen, 37073, Germany, and 2Cluster of Excellence “Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells” (MBExC), University of Göttingen, Göttingen 37073, Germany The activity and the metabolism of the brain change rhythmically during the day/night cycle. Such rhythmicity is also observed in cultured neurons from the suprachiasmatic nucleus, which is a critical center in rhythm maintenance. However, this issue has not been extensively studied in cultures from areas less involved in timekeeping, as the hippocampus. Using neurons cultured from the hippocampi of newborn rats (both male and female), we observed significant time-dependent changes in global activity, in synaptic vesicle dynamics, in synapse size, and in synaptic mRNA amounts. A transcriptome analysis of the neurons, performed at different times over 24 h, revealed significant changes only for RNA-binding motif 3 (Rbm3). RBM3 amounts changed, especially in synapses. RBM3 knockdown altered synaptic vesicle dynamics and changed the neuronal activity patterns. This procedure also altered local translation in synapses, albeit it left the global cellular trans- lation unaffected. We conclude that hippocampal cultured neurons can exhibit strong changes in their activity levels over 24 h, in an RBM3-dependent fashion. Key words: circadian; local translation; primary hippocampal culture; RBM3; RNA-binding protein; synaptic transmission Significance Statement This work is important in several ways.