Sakano Wang 2017 Proteomic Analyses of Nucleus Lam.Pdf
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Phosphorylation of Synaptojanin Differentially Regulates Endocytosis of Functionally Distinct Synaptic Vesicle Pools
8882 • The Journal of Neuroscience, August 24, 2016 • 36(34):8882–8894 Cellular/Molecular Phosphorylation of Synaptojanin Differentially Regulates Endocytosis of Functionally Distinct Synaptic Vesicle Pools X Junhua Geng,1* Liping Wang,1,2* Joo Yeun Lee,1,4 XChun-Kan Chen,1 and Karen T. Chang1,3,4 1Zilkha Neurogenetic Institute, 2Department of Biochemistry and Molecular Biology, and 3Department of Cell and Neurobiology, Keck School of Medicine, University of Southern California, Los Angeles, California 90089, and 4Neuroscience Graduate Program, University of Southern California, Los Angeles, California 90089 The rapid replenishment of synaptic vesicles through endocytosis is crucial for sustaining synaptic transmission during intense neuronal activity. Synaptojanin (Synj), a phosphoinositide phosphatase, is known to play an important role in vesicle recycling by promoting the uncoating of clathrin following synaptic vesicle uptake. Synj has been shown to be a substrate of the minibrain (Mnb) kinase, a fly homolog of the dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A); however, the functional impacts of Synj phosphorylation by Mnb are not well understood. Here we identify that Mnb phosphorylates Synj at S1029 in Drosophila. We find that phosphorylation of Synj at S1029 enhances Synj phosphatase activity, alters interaction between Synj and endophilin, and promotes efficient endocytosis of the active cycling vesicle pool (also referred to as exo-endo cycling pool) at the expense of reserve pool vesicle endocytosis. Dephosphorylated Synj, on the other hand, is deficient in the endocytosis of the active recycling pool vesicles but maintains reserve pool vesicle endocytosis to restore total vesicle pool size and sustain synaptic transmission. Together, our findings reveal a novel role for Synj in modulating reserve pool vesicle endocytosis and further indicate that dynamic phosphorylation and dephosphorylation of Synj differentially maintain endocytosis of distinct functional synaptic vesicle pools. -
Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism
ARTICLE Received 24 Aug 2013 | Accepted 14 Mar 2014 | Published 11 Apr 2014 DOI: 10.1038/ncomms4650 OPEN Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism Roser Corominas1,*, Xinping Yang2,3,*, Guan Ning Lin1,*, Shuli Kang1,*, Yun Shen2,3, Lila Ghamsari2,3,w, Martin Broly2,3, Maria Rodriguez2,3, Stanley Tam2,3, Shelly A. Trigg2,3,w, Changyu Fan2,3, Song Yi2,3, Murat Tasan4, Irma Lemmens5, Xingyan Kuang6, Nan Zhao6, Dheeraj Malhotra7, Jacob J. Michaelson7,w, Vladimir Vacic8, Michael A. Calderwood2,3, Frederick P. Roth2,3,4, Jan Tavernier5, Steve Horvath9, Kourosh Salehi-Ashtiani2,3,w, Dmitry Korkin6, Jonathan Sebat7, David E. Hill2,3, Tong Hao2,3, Marc Vidal2,3 & Lilia M. Iakoucheva1 Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases. -
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. -
Oegtp - Epilepsy Test Requisition Lab Use Only: Patient Information
OEGTP - EPILEPSY TEST REQUISITION LAB USE ONLY: PATIENT INFORMATION: Received date: Name: Notes: Address: Date of Birth: YY/MM/DD Sex: M F Health Card No: TEST REQUEST: See page 2 for gene list for each of the panels below Epilepsy Comprehensive panel: 167 genes Childhood Onset Epilepsy panel: 45 genes Focal Epilepsy panel: 14 genes Brain Malformation Epilepsy panel: 44 genes London Health Sciences Centre – (Molecular Genetics) London Health Sciences Centre Progressive Myoclonic Epilepsy panel: 20 genes Actionable Gene Epilepsy panel: 22 genes Early Infantile Epilepsy panel: 51 genes Single gene test: Carrier Testing/ KnownFamily Mutation SAMPLE COLLECTION: Name of index case in the family (include copy of report) Date drawn: YY/MM/DD EDTA blood (lavender top) (5ml at room temp) Affected Unaffected Date of Birth: Relationship to patient: REFERRING PHYSICIAN: Authorized Signature is Required Gene: RefSeq:NM Physician Name (print): Mutation: Signature: Email: REASON FOR REFERRAL: Clinic/Hospital: Diagnostic Testing Address: Clinical Diagnosis: Telephone: Fax: CC report to: Name: Clinical Presentation: Address: Telephone: Fax: Molecular Genetics Laboratory Victoria Hospital, Room B10-123A 800 Commissioners Rd. E. London, Ontario | N6A 5W9 Pathology and Laboratory Medicine Ph: 519-685-8122 | Fax: 519-685-8279 Page 1 of 6 Page OEGTP (2021/05/28) OEGTP - EPILEPSY TEST PANELS Patient Identifier: COMPREHENSIVE EPILEPSY PANEL: 167 Genes ACTB, ACTG1, ADSL, AKT3, ALDH7A1, AMT, AP3B2, ARFGEF2, ARHGEF9, ARV1, ARX, ASAH1, ASNS, ATP1A3, ATP6V0A2, ATP7A, -
Noninvasive Sleep Monitoring in Large-Scale Screening of Knock-Out Mice
bioRxiv preprint doi: https://doi.org/10.1101/517680; this version posted January 11, 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-ND 4.0 International license. Noninvasive sleep monitoring in large-scale screening of knock-out mice reveals novel sleep-related genes Shreyas S. Joshi1*, Mansi Sethi1*, Martin Striz1, Neil Cole2, James M. Denegre2, Jennifer Ryan2, Michael E. Lhamon3, Anuj Agarwal3, Steve Murray2, Robert E. Braun2, David W. Fardo4, Vivek Kumar2, Kevin D. Donohue3,5, Sridhar Sunderam6, Elissa J. Chesler2, Karen L. Svenson2, Bruce F. O'Hara1,3 1Dept. of Biology, University of Kentucky, Lexington, KY 40506, USA, 2The Jackson Laboratory, Bar Harbor, ME 04609, USA, 3Signal solutions, LLC, Lexington, KY 40503, USA, 4Dept. of Biostatistics, University of Kentucky, Lexington, KY 40536, USA, 5Dept. of Electrical and Computer Engineering, University of Kentucky, Lexington, KY 40506, USA. 6Dept. of Biomedical Engineering, University of Kentucky, Lexington, KY 40506, USA. *These authors contributed equally Address for correspondence and proofs: Shreyas S. Joshi, Ph.D. Dept. of Biology University of Kentucky 675 Rose Street 101 Morgan Building Lexington, KY 40506 U.S.A. Phone: (859) 257-2805 FAX: (859) 257-1717 Email: [email protected] Running title: Sleep changes in knockout mice bioRxiv preprint doi: https://doi.org/10.1101/517680; this version posted January 11, 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. -
Atrazine and Cell Death Symbol Synonym(S)
Supplementary Table S1: Atrazine and Cell Death Symbol Synonym(s) Entrez Gene Name Location Family AR AIS, Andr, androgen receptor androgen receptor Nucleus ligand- dependent nuclear receptor atrazine 1,3,5-triazine-2,4-diamine Other chemical toxicant beta-estradiol (8R,9S,13S,14S,17S)-13-methyl- Other chemical - 6,7,8,9,11,12,14,15,16,17- endogenous decahydrocyclopenta[a]phenanthrene- mammalian 3,17-diol CGB (includes beta HCG5, CGB3, CGB5, CGB7, chorionic gonadotropin, beta Extracellular other others) CGB8, chorionic gonadotropin polypeptide Space CLEC11A AW457320, C-type lectin domain C-type lectin domain family 11, Extracellular growth factor family 11, member A, STEM CELL member A Space GROWTH FACTOR CYP11A1 CHOLESTEROL SIDE-CHAIN cytochrome P450, family 11, Cytoplasm enzyme CLEAVAGE ENZYME subfamily A, polypeptide 1 CYP19A1 Ar, ArKO, ARO, ARO1, Aromatase cytochrome P450, family 19, Cytoplasm enzyme subfamily A, polypeptide 1 ESR1 AA420328, Alpha estrogen receptor,(α) estrogen receptor 1 Nucleus ligand- dependent nuclear receptor estrogen C18 steroids, oestrogen Other chemical drug estrogen receptor ER, ESR, ESR1/2, esr1/esr2 Nucleus group estrone (8R,9S,13S,14S)-3-hydroxy-13-methyl- Other chemical - 7,8,9,11,12,14,15,16-octahydro-6H- endogenous cyclopenta[a]phenanthren-17-one mammalian G6PD BOS 25472, G28A, G6PD1, G6PDX, glucose-6-phosphate Cytoplasm enzyme Glucose-6-P Dehydrogenase dehydrogenase GATA4 ASD2, GATA binding protein 4, GATA binding protein 4 Nucleus transcription TACHD, TOF, VSD1 regulator GHRHR growth hormone releasing -
Yeast Genome Gazetteer P35-65
gazetteer Metabolism 35 tRNA modification mitochondrial transport amino-acid metabolism other tRNA-transcription activities vesicular transport (Golgi network, etc.) nitrogen and sulphur metabolism mRNA synthesis peroxisomal transport nucleotide metabolism mRNA processing (splicing) vacuolar transport phosphate metabolism mRNA processing (5’-end, 3’-end processing extracellular transport carbohydrate metabolism and mRNA degradation) cellular import lipid, fatty-acid and sterol metabolism other mRNA-transcription activities other intracellular-transport activities biosynthesis of vitamins, cofactors and RNA transport prosthetic groups other transcription activities Cellular organization and biogenesis 54 ionic homeostasis organization and biogenesis of cell wall and Protein synthesis 48 plasma membrane Energy 40 ribosomal proteins organization and biogenesis of glycolysis translation (initiation,elongation and cytoskeleton gluconeogenesis termination) organization and biogenesis of endoplasmic pentose-phosphate pathway translational control reticulum and Golgi tricarboxylic-acid pathway tRNA synthetases organization and biogenesis of chromosome respiration other protein-synthesis activities structure fermentation mitochondrial organization and biogenesis metabolism of energy reserves (glycogen Protein destination 49 peroxisomal organization and biogenesis and trehalose) protein folding and stabilization endosomal organization and biogenesis other energy-generation activities protein targeting, sorting and translocation vacuolar and lysosomal -
Mutations in Pi(3,5)P2 Signaling and Neurodegeneration in Mouse and Human
MUTATIONS IN PI(3,5)P2 SIGNALING AND NEURODEGENERATION IN MOUSE AND HUMAN by Clement Y. Chow A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Human Genetics) in The University of Michigan 2008 Doctoral Committee: Professor Miriam H. Meisler, Chair Professor Sally A. Camper Professor David Ginsburg Associate Professor David C. Kohrman Assistant Professor Geoffrey G. Murphy Clement Y. Chow 2008 To my wife, Candace For all her love and support ii ACKNOWLEDGEMENTS I would first like to thank my mentor, Miriam Meisler. She is the consummate scientist. Miriam is inquisitive and interested in a wide range of topics. This trait has taught me to always ask the right questions and be skeptical of conclusions that are not supported by data. Miriam’s unending desire to make each oral presentation perfect drove me to improve my own skills. I came to this lab without any public presentation skills, but I am now greatly improved in my presentation abilities, a skill crucial for a successful scientific career. Miriam is a perfectionist when it comes to writing and always encouraged me to do the same. I will continue to strive to perfect my writing abilities. I came to the lab wanting to positionally clone a mouse mutant. I told Miriam that I would stay in the lab if she allowed me to do so. She was supportive and excited from the beginning, allowing me to pursue a project with an unknown future. This allowed me to learn, first hand, many aspects of genetics that such a project provides. -
Thioesterase Superfamily Member 1 Undergoes Stimulus-Coupled Conformational Reorganization to Regulate Metabolism in Mice
ARTICLE https://doi.org/10.1038/s41467-021-23595-x OPEN Thioesterase superfamily member 1 undergoes stimulus-coupled conformational reorganization to regulate metabolism in mice Yue Li 1,2, Norihiro Imai3, Hayley T. Nicholls 3, Blaine R. Roberts 4, Samaksh Goyal 1,2, Tibor I. Krisko 3, Lay-Hong Ang 1,2, Matthew C. Tillman4, Anne M. Roberts4, Mahnoor Baqai 1,2, Eric A. Ortlund 4, ✉ ✉ David E. Cohen 3 & Susan J. Hagen 1,2 1234567890():,; In brown adipose tissue, thermogenesis is suppressed by thioesterase superfamily member 1 (Them1), a long chain fatty acyl-CoA thioesterase. Them1 is highly upregulated by cold ambient temperature, where it reduces fatty acid availability and limits thermogenesis. Here, we show that Them1 regulates metabolism by undergoing conformational changes in response to β-adrenergic stimulation that alter Them1 intracellular distribution. Them1 forms metabolically active puncta near lipid droplets and mitochondria. Upon stimulation, Them1 is phosphorylated at the N-terminus, inhibiting puncta formation and activity and resulting in a diffuse intracellular localization. We show by correlative light and electron microscopy that Them1 puncta are biomolecular condensates that are inhibited by phosphorylation. Thus, Them1 forms intracellular biomolecular condensates that limit fatty acid oxidation and sup- press thermogenesis. During a period of energy demand, the condensates are disrupted by phosphorylation to allow for maximal thermogenesis. The stimulus-coupled reorganization of Them1 provides fine-tuning of thermogenesis and energy expenditure. 1 Division of General Surgery, Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, USA. 2 Department of Surgery, Harvard Medical School, Boston, MA, USA. 3 Division of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medical College, New York, NY, USA. -
Actin Nucleator Spire 1 Is a Regulator of Ectoplasmic Specialization in the Testis Qing Wen1,Nanli1,Xiangxiao 1,2,Wing-Yeelui3, Darren S
Wen et al. Cell Death and Disease (2018) 9:208 DOI 10.1038/s41419-017-0201-6 Cell Death & Disease ARTICLE Open Access Actin nucleator Spire 1 is a regulator of ectoplasmic specialization in the testis Qing Wen1,NanLi1,XiangXiao 1,2,Wing-yeeLui3, Darren S. Chu1, Chris K. C. Wong4, Qingquan Lian5,RenshanGe5, Will M. Lee3, Bruno Silvestrini6 and C. Yan Cheng 1 Abstract Germ cell differentiation during the epithelial cycle of spermatogenesis is accompanied by extensive remodeling at the Sertoli cell–cell and Sertoli cell–spermatid interface to accommodate the transport of preleptotene spermatocytes and developing spermatids across the blood–testis barrier (BTB) and the adluminal compartment of the seminiferous epithelium, respectively. The unique cell junction in the testis is the actin-rich ectoplasmic specialization (ES) designated basal ES at the Sertoli cell–cell interface, and the apical ES at the Sertoli–spermatid interface. Since ES dynamics (i.e., disassembly, reassembly and stabilization) are supported by actin microfilaments, which rapidly converts between their bundled and unbundled/branched configuration to confer plasticity to the ES, it is logical to speculate that actin nucleation proteins play a crucial role to ES dynamics. Herein, we reported findings that Spire 1, an actin nucleator known to polymerize actins into long stretches of linear microfilaments in cells, is an important regulator of ES dynamics. Its knockdown by RNAi in Sertoli cells cultured in vitro was found to impede the Sertoli cell tight junction (TJ)-permeability barrier through changes in the organization of F-actin across Sertoli cell cytosol. Unexpectedly, Spire 1 knockdown also perturbed microtubule (MT) organization in Sertoli cells cultured in vitro. -
Applying Expression Profile Similarity for Discovery of Patient-Specific
bioRxiv preprint doi: https://doi.org/10.1101/172015; this version posted September 17, 2017. 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 4.0 International license. Applying expression profile similarity for discovery of patient-specific functional mutations Guofeng Meng Partner Institute of Computational Biology, Yueyang 333, Shanghai, China email: [email protected] Abstract The progress of cancer genome sequencing projects yields unprecedented information of mutations for numerous patients. However, the complexity of mutation profiles of patients hinders the further understanding of mechanisms of oncogenesis. One basic question is how to uncover mutations with functional impacts. In this work, we introduce a computational method to predict functional somatic mutations for each of patient by integrating mutation recurrence with similarity of expression profiles of patients. With this method, the functional mutations are determined by checking the mutation enrichment among a group of patients with similar expression profiles. We applied this method to three cancer types and identified the functional mutations. Comparison of the predictions for three cancer types suggested that most of the functional mutations were cancer-type-specific with one exception to p53. By checking prediction results, we found that our method effectively filtered non-functional mutations resulting from large protein sizes. In addition, this methods can also perform functional annotation to each patient to describe their association with signalling pathways or biological processes. In breast cancer, we predicted "cell adhesion" and other mutated gene associated terms to be significantly enriched among patients. -
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