A Web-Platform for Analysis of Host Factors Involved in Viral Infections Discovered by Genome Wide Rnai Screen
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A Missense Polymorphism in the Putative Pheromone Receptor Gene VN1R1 Is Associated with Sociosexual Behavior
OPEN Citation: Transl Psychiatry (2017) 7, e1102; doi:10.1038/tp.2017.70 www.nature.com/tp ORIGINAL ARTICLE A missense polymorphism in the putative pheromone receptor gene VN1R1 is associated with sociosexual behavior S Henningsson1, D Hovey1, K Vass1, H Walum2,3,4,5, K Sandnabba6, P Santtila6, P Jern6 and L Westberg1 Pheromones regulate social and reproductive behavior in most mammalian species. These effects are mediated by the vomeronasal and main olfactory systems. Effects of putative pheromones on human neuroendocrine activity, brain activity and attractiveness ratings suggest that humans may communicate via similar chemosignaling. Here we studied two samples of younger and older individuals, respectively, with respect to one nonsynonymous polymorphism in the gene encoding the human vomeronasal type-1 receptor 1, VN1R1, and one nonsynonymous polymorphism in the gene encoding the olfactory receptor OR7D4. Participants in both samples had self-reported their sociosexual behavior using the sociosexual orientation inventory, including questions regarding lifetime number of one-night stands, number of partners last year and expected number of partners the coming 5 years. In women, there was a significant association between the VN1R1 polymorphism and sociosexual behavior in both samples, driven specifically by the question regarding one-night stands. Our results support the hypothesis that human social interaction is modulated by communication via chemosignaling. Translational Psychiatry (2017) 7, e1102; doi:10.1038/tp.2017.70; published -
Multifactorial Erβ and NOTCH1 Control of Squamous Differentiation and Cancer
Multifactorial ERβ and NOTCH1 control of squamous differentiation and cancer Yang Sui Brooks, … , Karine Lefort, G. Paolo Dotto J Clin Invest. 2014;124(5):2260-2276. https://doi.org/10.1172/JCI72718. Research Article Oncology Downmodulation or loss-of-function mutations of the gene encoding NOTCH1 are associated with dysfunctional squamous cell differentiation and development of squamous cell carcinoma (SCC) in skin and internal organs. While NOTCH1 receptor activation has been well characterized, little is known about how NOTCH1 gene transcription is regulated. Using bioinformatics and functional screening approaches, we identified several regulators of the NOTCH1 gene in keratinocytes, with the transcription factors DLX5 and EGR3 and estrogen receptor β (ERβ) directly controlling its expression in differentiation. DLX5 and ERG3 are required for RNA polymerase II (PolII) recruitment to the NOTCH1 locus, while ERβ controls NOTCH1 transcription through RNA PolII pause release. Expression of several identified NOTCH1 regulators, including ERβ, is frequently compromised in skin, head and neck, and lung SCCs and SCC-derived cell lines. Furthermore, a keratinocyte ERβ–dependent program of gene expression is subverted in SCCs from various body sites, and there are consistent differences in mutation and gene-expression signatures of head and neck and lung SCCs in female versus male patients. Experimentally increased ERβ expression or treatment with ERβ agonists inhibited proliferation of SCC cells and promoted NOTCH1 expression and squamous differentiation both in vitro and in mouse xenotransplants. Our data identify a link between transcriptional control of NOTCH1 expression and the estrogen response in keratinocytes, with implications for differentiation therapy of squamous cancer. Find the latest version: https://jci.me/72718/pdf Research article Multifactorial ERβ and NOTCH1 control of squamous differentiation and cancer Yang Sui Brooks,1,2 Paola Ostano,3 Seung-Hee Jo,1,2 Jun Dai,1,2 Spiro Getsios,4 Piotr Dziunycz,5 Günther F.L. -
Identification of Secretory Granule Phosphatidylinositol 4,5-Bisphosphate- Interacting Proteins Using an Affinity Pulldown Strategy*□S
Research Identification of Secretory Granule Phosphatidylinositol 4,5-Bisphosphate- interacting Proteins Using an Affinity Pulldown Strategy*□S Shona L. Osborne‡§, Tristan P. Wallis¶ʈ, Jose L. Jimenez**, Jeffrey J. Gorman¶ʈ, and Frederic A. Meunier‡§‡‡ Phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P2) syn- required for secretion is synthesized on the plasma mem- thesis is required for calcium-dependent exocytosis in neu- brane (4), and the binding of vesicle-associated proteins to rosecretory cells. We developed a PtdIns(4,5)P2 bead pull- PtdIns(4,5)P2 in trans is thought to be important for bringing down strategy combined with subcellular fractionation to the vesicle and plasma membranes together prior to exocy- Downloaded from identify endogenous chromaffin granule proteins that inter- tosis to ensure rapid and efficient fusion upon calcium influx act with PtdIns(4,5)P . We identified two synaptotagmin iso- 2 (5). Putative PtdIns(4,5)P effectors include synaptotagmin 1 forms, synaptotagmins 1 and 7; spectrin; ␣-adaptin; and 2 (Syt1) (6, 7), calcium-activated protein for secretion (CAPS) (8, synaptotagmin-like protein 4 (granuphilin) by mass spec- 9), and rabphilin (10). trometry and Western blotting. The interaction between https://www.mcponline.org CAPS binds to PtdIns(4,5)P2 and is a potential PtdIns(4,5)P2 synaptotagmin 7 and PtdIns(4,5)P2 and its functional rele- vance was investigated. The 45-kDa isoform of synaptotag- effector for priming of secretory granule exocytosis (9). How- min 7 was found to be highly expressed in adrenal chromaf- ever, recent work on the CAPS1 knock-out mouse highlighted fin cells compared with PC12 cells and to mainly localize to an involvement of CAPS1 in the refilling or storage of cate- secretory granules by subcellular fractionation, immunoiso- cholamine in mature secretory granules therefore suggesting lation, and immunocytochemistry. -
Supplementary Materials
Supplementary Materials: Supplemental Table 1 Abbreviations FMDV Foot and Mouth Disease Virus FMD Foot and Mouth Disease NC Non-treated Control DEGs Differentially Expressed Genes RNA-seq High-throughput Sequencing of Mrna RT-qPCR Quantitative Real-time Reverse Transcriptase PCR TCID50 50% Tissue Culture Infective Doses CPE Cytopathic Effect MOI Multiplicity of Infection DMEM Dulbecco's Modified Eagle Medium FBS Fetal Bovine Serum PBS Phosphate Buffer Saline QC Quality Control FPKM Fragments per Kilo bases per Million fragments method GO Gene Ontology KEGG Kyoto Encyclopedia of Genes and Genomes R Pearson Correlation Coefficient NFKBIA NF-kappa-B Inhibitor alpha IL6 Interleukin 6 CCL4 C-C motif Chemokine 4 CXCL2 C-X-C motif Chemokine 2 TNF Tumor Necrosis Factor VEGFA Vascular Endothelial Growth Gactor A CCL20 C-C motif Chemokine 20 CSF2 Macrophage Colony-Stimulating Factor 2 GADD45B Growth Arrest and DNA Damage Inducible 45 beta MYC Myc proto-oncogene protein FOS Proto-oncogene c-Fos MCL1 Induced myeloid leukemia cell differentiation protein Mcl-1 MAP3K14 Mitogen-activated protein kinase kinase kinase 14 IRF1 Interferon regulatory factor 1 CCL5 C-C motif chemokine 5 ZBTB3 Zinc finger and BTB domain containing 3 OTX1 Orthodenticle homeobox 1 TXNIP Thioredoxin-interacting protein ZNF180 Znc Finger Protein 180 ZNF36 Znc Finger Protein 36 ZNF182 Zinc finger protein 182 GINS3 GINS complex subunit 3 KLF15 Kruppel-like factor 15 Supplemental Table 2 Primers for Verification of RNA-seq-detected DEGs with RT-qPCR TNF F: CGACTCAGTGCCGAGATCAA R: -
Synaptotagmin 7 Switches Short-Term Synaptic Plasticity from Depression
www.nature.com/scientificreports OPEN Synaptotagmin 7 switches short‑term synaptic plasticity from depression to facilitation by suppressing synaptic transmission Takaaki Fujii1, Akira Sakurai1, J. Troy Littleton2 & Motojiro Yoshihara1* Short‑term synaptic plasticity is a fast and robust modifcation in neuronal presynaptic output that can enhance release strength to drive facilitation or diminish it to promote depression. The mechanisms that determine whether neurons display short‑term facilitation or depression are still unclear. Here we show that the Ca2+‑binding protein Synaptotagmin 7 (Syt7) determines the sign of short‑term synaptic plasticity by controlling the initial probability of synaptic vesicle (SV) fusion. Electrophysiological analysis of Syt7 null mutants at Drosophila embryonic neuromuscular junctions demonstrate loss of the protein converts the normally observed synaptic facilitation response during repetitive stimulation into synaptic depression. In contrast, overexpression of Syt7 dramatically enhanced the magnitude of short‑term facilitation. These changes in short‑term plasticity were mirrored by corresponding alterations in the initial evoked response, with SV release probability enhanced in Syt7 mutants and suppressed following Syt7 overexpression. Indeed, Syt7 mutants were able to display facilitation in lower [Ca2+] where release was reduced. These data suggest Syt7 does not act by directly sensing residual Ca2+ and argues for the existence of a distinct Ca2+ sensor beyond Syt7 that mediates facilitation. Instead, Syt7 normally suppresses synaptic transmission to maintain an output range where facilitation is available to the neuron. Synaptotagmins (Syts) are a large family of Ca2+ binding proteins, with the Syt1 isoform functioning as the major Ca2+ sensor for synchronous synaptic vesicle (SV) fusion1. Ca2+ also controls presynaptic forms of short-term plasticity, with other Syt isoforms representing promising candidates to mediate these processes. -
Communication Between the Endoplasmic Reticulum and Peroxisomes in Mammalian Cells
Communication between the Endoplasmic Reticulum and Peroxisomes in Mammalian Cells by Rong Hua A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of Biochemistry University of Toronto © Copyright by Rong Hua (2017) ii Communication between the Endoplasmic Reticulum and Peroxisomes in Mammalian Cells Rong Hua Doctor of Philosophy Department of Biochemistry University of Toronto 2017 Abstract Peroxisomes are important metabolic organelles found in virtually all eukaryotic cells. Since their discovery, peroxisomes have long been seen in close proximity to the endoplasmic reticulum (ER). The interplay between the two organelles is suggested to be important for peroxisome biogenesis as the ER may serve as a source for both lipids and peroxisomal membrane proteins (PMPs) for peroxisome growth and maintenance. On the other hand, various lipid molecules are exchanged between them for the biosynthesis of specialized lipids such as bile acids, plasmalogens and cholesterol. However, how proteins and lipids are transported between the two organelles is not yet fully understood. Previously, the peroxisomal biogenesis factor PEX16 was shown to serve as a receptor for PMPs in the ER and also as a mediator of the subsequent transport of these ER-targeted PMPs to peroxisomes. Here, I extended these results by carrying out a comprehensive mutational analysis of PEX16 aimed at gaining insights into the molecular targeting signals responsible for its ER-to-peroxisome trafficking and the domain(s) involved in its PMP recruitment function at the ER. I also showed that the recruitment function of PEX16 is conserved in plants. To gain further mechanistic insight into PEX16 function, the proteins proximal to iii PEX16 were identified using the proximity-dependent BioID analysis. -
A Minimum-Labeling Approach for Reconstructing Protein Networks Across Multiple Conditions
A Minimum-Labeling Approach for Reconstructing Protein Networks across Multiple Conditions Arnon Mazza1, Irit Gat-Viks2, Hesso Farhan3, and Roded Sharan1 1 Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. Email: [email protected]. 2 Dept. of Cell Research and Immunology, Tel Aviv University, Tel Aviv 69978, Israel. 3 Biotechnology Institute Thurgau, University of Konstanz, Unterseestrasse 47, CH-8280 Kreuzlingen, Switzerland. Abstract. The sheer amounts of biological data that are generated in recent years have driven the development of network analysis tools to fa- cilitate the interpretation and representation of these data. A fundamen- tal challenge in this domain is the reconstruction of a protein-protein sub- network that underlies a process of interest from a genome-wide screen of associated genes. Despite intense work in this area, current algorith- mic approaches are largely limited to analyzing a single screen and are, thus, unable to account for information on condition-specific genes, or reveal the dynamics (over time or condition) of the process in question. Here we propose a novel formulation for network reconstruction from multiple-condition data and devise an efficient integer program solution for it. We apply our algorithm to analyze the response to influenza in- fection in humans over time as well as to analyze a pair of ER export related screens in humans. By comparing to an extant, single-condition tool we demonstrate the power of our new approach in integrating data from multiple conditions in a compact and coherent manner, capturing the dynamics of the underlying processes. 1 Introduction With the increasing availability of high-throughput data, network biol- arXiv:1307.7803v1 [q-bio.QM] 30 Jul 2013 ogy has become the method of choice for filtering, interpreting and rep- resenting these data. -
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 Materials
1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No. -
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Supplementary Figure S1. Results of flow cytometry analysis, performed to estimate CD34 positivity, after immunomagnetic separation in two different experiments. As monoclonal antibody for labeling the sample, the fluorescein isothiocyanate (FITC)- conjugated mouse anti-human CD34 MoAb (Mylteni) was used. Briefly, cell samples were incubated in the presence of the indicated MoAbs, at the proper dilution, in PBS containing 5% FCS and 1% Fc receptor (FcR) blocking reagent (Miltenyi) for 30 min at 4 C. Cells were then washed twice, resuspended with PBS and analyzed by a Coulter Epics XL (Coulter Electronics Inc., Hialeah, FL, USA) flow cytometer. only use Non-commercial 1 Supplementary Table S1. Complete list of the datasets used in this study and their sources. GEO Total samples Geo selected GEO accession of used Platform Reference series in series samples samples GSM142565 GSM142566 GSM142567 GSM142568 GSE6146 HG-U133A 14 8 - GSM142569 GSM142571 GSM142572 GSM142574 GSM51391 GSM51392 GSE2666 HG-U133A 36 4 1 GSM51393 GSM51394 only GSM321583 GSE12803 HG-U133A 20 3 GSM321584 2 GSM321585 use Promyelocytes_1 Promyelocytes_2 Promyelocytes_3 Promyelocytes_4 HG-U133A 8 8 3 GSE64282 Promyelocytes_5 Promyelocytes_6 Promyelocytes_7 Promyelocytes_8 Non-commercial 2 Supplementary Table S2. Chromosomal regions up-regulated in CD34+ samples as identified by the LAP procedure with the two-class statistics coded in the PREDA R package and an FDR threshold of 0.5. Functional enrichment analysis has been performed using DAVID (http://david.abcc.ncifcrf.gov/) -
Genetics of Aggressive Behavior: an Overview Kim Veroude,1 Yanli Zhang-James,2,3 No Elia Fern Andez-Castillo,4,5,6 Mireille J
RESEARCH ARTICLE Neuropsychiatric Genetics Genetics of Aggressive Behavior: An Overview Kim Veroude,1 Yanli Zhang-James,2,3 Noelia Fernandez-Castillo,4,5,6 Mireille J. Bakker,1 Bru Cormand,4,5,6 and Stephen V. Faraone2,3,7* 1Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, The Netherlands 2Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, New York 3Departments of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, New York 4Departament de Genetica, Facultat de Biologia, Universitat de Barcelona, Catalonia, Spain 5Institut de Biomedicina de la Universitat de Barcelona (IBUB), Catalonia, Spain 6Centro de Investigacion Biomedica en Red de Enfermedades Raras (CIBERER), Spain 7K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway Manuscript Received: 22 April 2015; Manuscript Accepted: 5 August 2015 The Research Domain Criteria (RDoC) address three types of aggression: frustrative non-reward, defensive aggression and How to Cite this Article: offensive/proactive aggression. This review sought to present Veroude K, Zhang-James Y, Fernandez- the evidence for genetic underpinnings of aggression and to Castillo N, Bakker MJ, Cormand B, determine to what degree prior studies have examined pheno- Faraone SV. 2016. Genetics of Aggressive types that fit into the RDoC framework. Although the constructs Behavior: An Overview. of defensive and offensive aggression have been widely used in the animal genetics literature, the human literature is mostly Am J Med Genet Part B 171B:3–43. agnostic with regard to all the RDoC constructs. We know from twin studies that about half the variance in behavior may be explained by genetic risk factors. -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1.