Proteomic Analysis and Functional Characterization of P4-Atpase
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Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Expression Gene Network Analyses Reveal Molecular Mechanisms And
www.nature.com/scientificreports OPEN Diferential expression and co- expression gene network analyses reveal molecular mechanisms and candidate biomarkers involved in breast muscle myopathies in chicken Eva Pampouille1,2, Christelle Hennequet-Antier1, Christophe Praud1, Amélie Juanchich1, Aurélien Brionne1, Estelle Godet1, Thierry Bordeau1, Fréderic Fagnoul2, Elisabeth Le Bihan-Duval1 & Cécile Berri1* The broiler industry is facing an increasing prevalence of breast myopathies, such as white striping (WS) and wooden breast (WB), and the precise aetiology of these occurrences remains poorly understood. To progress our understanding of the structural changes and molecular pathways involved in these myopathies, a transcriptomic analysis was performed using an 8 × 60 K Agilent chicken microarray and histological study. The study used pectoralis major muscles from three groups: slow-growing animals (n = 8), fast-growing animals visually free from defects (n = 8), or severely afected by both WS and WB (n = 8). In addition, a weighted correlation network analysis was performed to investigate the relationship between modules of co-expressed genes and histological traits. Functional analysis suggested that selection for fast growing and breast meat yield has progressively led to conditions favouring metabolic shifts towards alternative catabolic pathways to produce energy, leading to an adaptive response to oxidative stress and the frst signs of infammatory, regeneration and fbrosis processes. All these processes are intensifed in muscles afected by severe myopathies, in which new mechanisms related to cellular defences and remodelling seem also activated. Furthermore, our study opens new perspectives for myopathy diagnosis by highlighting fne histological phenotypes and genes whose expression was strongly correlated with defects. Te poultry industry relies on the production of fast-growing chickens, which are slaughtered at high weights and intended for cutting and processing. -
Supplemental Table S1
Entrez Gene Symbol Gene Name Affymetrix EST Glomchip SAGE Stanford Literature HPA confirmed Gene ID Profiling profiling Profiling Profiling array profiling confirmed 1 2 A2M alpha-2-macroglobulin 0 0 0 1 0 2 10347 ABCA7 ATP-binding cassette, sub-family A (ABC1), member 7 1 0 0 0 0 3 10350 ABCA9 ATP-binding cassette, sub-family A (ABC1), member 9 1 0 0 0 0 4 10057 ABCC5 ATP-binding cassette, sub-family C (CFTR/MRP), member 5 1 0 0 0 0 5 10060 ABCC9 ATP-binding cassette, sub-family C (CFTR/MRP), member 9 1 0 0 0 0 6 79575 ABHD8 abhydrolase domain containing 8 1 0 0 0 0 7 51225 ABI3 ABI gene family, member 3 1 0 1 0 0 8 29 ABR active BCR-related gene 1 0 0 0 0 9 25841 ABTB2 ankyrin repeat and BTB (POZ) domain containing 2 1 0 1 0 0 10 30 ACAA1 acetyl-Coenzyme A acyltransferase 1 (peroxisomal 3-oxoacyl-Coenzyme A thiol 0 1 0 0 0 11 43 ACHE acetylcholinesterase (Yt blood group) 1 0 0 0 0 12 58 ACTA1 actin, alpha 1, skeletal muscle 0 1 0 0 0 13 60 ACTB actin, beta 01000 1 14 71 ACTG1 actin, gamma 1 0 1 0 0 0 15 81 ACTN4 actinin, alpha 4 0 0 1 1 1 10700177 16 10096 ACTR3 ARP3 actin-related protein 3 homolog (yeast) 0 1 0 0 0 17 94 ACVRL1 activin A receptor type II-like 1 1 0 1 0 0 18 8038 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 1 0 0 0 0 19 8751 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 1 0 0 0 0 20 8728 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 1 0 0 0 0 21 81792 ADAMTS12 ADAM metallopeptidase with thrombospondin type 1 motif, 12 1 0 0 0 0 22 9507 ADAMTS4 ADAM metallopeptidase with thrombospondin type 1 -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
TMEM50A Shrna (M) Lentiviral Particles: Sc-154474-V
SANTA CRUZ BIOTECHNOLOGY, INC. TMEM50A shRNA (m) Lentiviral Particles: sc-154474-V BACKGROUND PRODUCT TMEM50A (transmembrane protein 50A), also known as small membrane pro- TMEM50A shRNA (m) Lentiviral Particles is a pool of concentrated, trans- tein 1, is a 157 amino acid protein encoded by a gene mapping to human duction-ready viral particles containing 3 target-specific constructs that chromosome 1. Chromosome 1 is the largest human chromosome spanning encode 19-25 nt (plus hairpin) shRNA designed to knock down gene expres- about 260 million base pairs and making up 8% of the human genome. There sion. Each vial contains 200 µl frozen stock containing 1.0 x 106 infectious are about 3,000 genes on chromosome 1, and considering the great number units of virus (IFU) in Dulbecco’s Modified Eagle’s Medium with 25 mM of genes there are also a large number of diseases associated with chromo- HEPES pH 7.3. Suitable for 10-20 transductions. Also see TMEM50A some 1. Notably, the rare aging disease Hutchinson-Gilford progeria is asso- siRNA (m): sc-154474 and TMEM50A shRNA Plasmid (m): sc-154474-SH as ciated with the LMNA gene which encodes Lamin A. When defective, the alternate gene silencing products. LMNA gene product can build up in the nucleus and cause characteristic nuclear blebs. The mechanism of rapidly enhanced aging is unclear and is APPLICATIONS a topic of continuing exploration. The MUTYH gene is located on chromo- TMEM50A shRNA (m) Lentiviral Particles is recommended for the inhibition some 1 and is partially responsible for familial adenomatous polyposis. -
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. -
Role of Excess Inorganic Pyrophosphate in Primer-Extension Genotyping Assays
Methods Role of Excess Inorganic Pyrophosphate in Primer-Extension Genotyping Assays Ming Xiao,1 Angie Phong,1 Kristen L. Lum,1 Richard A. Greene,2 Philip R. Buzby,2,3 and Pui-Yan Kwok1,4,5 1Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California 94143-0130, USA; 2PerkinElmer Life and Analytical Sciences, Inc., Boston, Massachusetts 02118-2512, USA We have developed and genotyped >15,000 SNP assays by using a primer extension genotyping assay with fluorescence polarization (FP) detection. Although the 80% success rate of this assay is similar to those of other SNP genotyping assays, we wanted to determine the reasons for the failures and find ways to improve the assay. We observed that the failed assays fell into three general patterns: PCR failure, excess of heterozygous genotypes, and loss of FP signal for one of the dye labels. After analyzing several hundred failed assays, we concluded that 5% of the assays had PCR failure and had to be redesigned. We also discovered that the other two categories of failures were due to misincorporation of one of the dye-terminators during the primer extension reaction as a result of primer shortening with a reverse reaction involving inorganic pyrophosphate, and to the quenching of R110-terminator after its incorporation onto the SNP primer. The relatively slow incorporation of R110 acycloterminators by AcycloPol compounds the problem with the R110 label. In this report, we describe the source of the problems and simple ways to correct these problems by adding pyrophosphatase, using quenching as part of the analysis, and replacing R110 by Texas red as one of the dye labels. -
Illuminating Dna Packaging in Sperm Chromatin: How Polycation Lengths, Underprotamination and Disulfide Linkages Alters Dna Condensation and Stability
University of Kentucky UKnowledge Theses and Dissertations--Chemistry Chemistry 2019 ILLUMINATING DNA PACKAGING IN SPERM CHROMATIN: HOW POLYCATION LENGTHS, UNDERPROTAMINATION AND DISULFIDE LINKAGES ALTERS DNA CONDENSATION AND STABILITY Daniel Kirchhoff University of Kentucky, [email protected] Digital Object Identifier: https://doi.org/10.13023/etd.2019.233 Right click to open a feedback form in a new tab to let us know how this document benefits ou.y Recommended Citation Kirchhoff, Daniel, "ILLUMINATING DNA PACKAGING IN SPERM CHROMATIN: HOW POLYCATION LENGTHS, UNDERPROTAMINATION AND DISULFIDE LINKAGES ALTERS DNA CONDENSATION AND STABILITY" (2019). Theses and Dissertations--Chemistry. 112. https://uknowledge.uky.edu/chemistry_etds/112 This Doctoral Dissertation is brought to you for free and open access by the Chemistry at UKnowledge. It has been accepted for inclusion in Theses and Dissertations--Chemistry by an authorized administrator of UKnowledge. For more information, please contact [email protected]. STUDENT AGREEMENT: I represent that my thesis or dissertation and abstract are my original work. Proper attribution has been given to all outside sources. I understand that I am solely responsible for obtaining any needed copyright permissions. I have obtained needed written permission statement(s) from the owner(s) of each third-party copyrighted matter to be included in my work, allowing electronic distribution (if such use is not permitted by the fair use doctrine) which will be submitted to UKnowledge as Additional File. I hereby grant to The University of Kentucky and its agents the irrevocable, non-exclusive, and royalty-free license to archive and make accessible my work in whole or in part in all forms of media, now or hereafter known. -
Membrane Protein Folding Makes the Transition
COMMENTARY Membrane protein folding makes the transition Paula J. Bootha,1 and Jane Clarkeb,1 aDepartment of Biochemistry, School of Medical Sciences, University of Bristol, Bristol BS8 1TD, United Kingdom; and bDepartment of Chemistry and Medical Research Council Centre for Protein Engineering, University of Cambridge, Cambridge CB2 1EW, United Kingdom he study of the folding of mem- brane proteins has lagged far T behind that of small soluble proteins—yet proteins that reside within biological membranes ac- count for approximately a third of all proteomes. The article by Huysmans et al. in this issue of PNAS (1) represents a breakthrough by reporting a compre- hensive ϕ-value analysis of the folding of a membrane protein (i.e., PagP) into a lipid bilayer. ϕ-value analysis is the most powerful tool for experimental analysis of protein folding pathways (2). It com- bines protein engineering with equilibrium and kinetic measurements to determine which regions of a protein are largely fol- ded (high ϕ-values) or largely unfolded (low ϕ-values) at the rate-limiting transition state. Fig. 1. Schematic diagrams of proposed folding models for β-barrel and α-helical membrane proteins, There are two major structural classes highlighting potential transition state structures from ϕ-value studies. Folding of a β-barrel protein oc- of integral membrane proteins: α-helical curs from a fully denatured, membrane-absorbed state in urea with a tilted, partly inserted transition bundles and β-barrels. The latter are found state as proposed by Huysmans et al. (1). In contrast, folding of an α-helical protein such as bacterio- in the outer membranes of Gram- rhodopsin occurs from a partly denatured state in SDS, which contains some helical content. -
Molecular Regulation and Physiology of the H ,K -Atpases in Kidney
Molecular Regulation and Physiology of the H؉,K؉-ATPases in Kidney Juan Codina and Thomas D. DuBose Jr Two H؉,K؉-adenosine triphosphatase (ATPase) proteins participate in K؉ absorption and ؉ ؉ ؉ H secretion in the renal medulla. Both the gastric (HK␣1) and colonic (HK␣2)H,K - ATPases have been localized and characterized by a number of techniques, and are known to be highly regulated in response to acid-base and electrolyte disturbances. Both ATPases are dimers of composition ␣/ that localize to the apical membrane and both interact with the tetraspanin protein CD63. Although CD63 interacts with the carboxy-terminus of the subunit of the colonic H؉,K؉-ATPase, it interacts with the -subunit of the gastric-␣ H؉,K؉-ATPase. Pharmacologically, both ATPases are distinct; for example, the gastric H؉,K؉-ATPase is inhibited by Sch-28080, but the colonic H؉,K؉-ATPase is inhibited by .ouabain (a classic inhibitor of the Na؉-pump) and is completely insensitive to Sch-28080 The ␣-subunit of the colonic H؉,K؉-ATPase is the only subunit of the X؉,K؉-ATPase superfamily that has 3 different splice variants that emerge by deletion or elongation of the amino-terminus. The messenger RNA and protein of one of these splice variants (HK␣2C)is specifically up-regulated in newborn rats and becomes undetectable in adult rats. There- fore, HK␣2, in addition to its role in potassium and acid-base homeostasis, appears to play a significant role in early growth and development. Finally, because chronic hypokalemia appears to be the most potent stimulus for upregulation of HK␣2, we propose that the HK␣2 participates importantly in the maintenance of chronic metabolic alkalosis. -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
© Ferrata Storti Foundation
Red Cell Biology & its Disorders ARTICLE ATP11C is a major flippase in human erythrocytes and its defect causes congenital Ferrata Storti EUROPEAN HEMATOLOGY Foundation hemolytic anemia ASSOCIATION Nobuto Arashiki,1 Yuichi Takakuwa,1 Narla Mohandas,2 John Hale,2 Kenichi Yoshida,3 Hiromi Ogura,4 Taiju Utsugisawa,4 Shouichi Ohga,5 Satoru Miyano,6 Seishi Ogawa,3 Seiji Kojima,7 and Hitoshi Kanno,4,8 1Department of Biochemistry, School of Medicine, Tokyo Women’s Medical University, Japan; 2Red Cell Physiology Laboratory, New York Blood Center, NY, USA; 3Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Japan; 4Department of Transfusion Medicine and Cell Processing, School of Medicine, Tokyo Women’s Medical University, Japan; 5Department of Pediatrics, Graduate School of Medicine, Yamaguchi University, Japan; 6Laboratory of DNA Information Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo, Japan; 7Department of Pediatrics, Graduate School of Medicine, Nagoya University, Japan; and 8Division of Genomic Medicine, Department of Advanced Biomedical Engineering and Haematologica 2016 Science, Graduate School of Medicine, Tokyo Women's Medical University, Japan Volume 101(5):559-565 ABSTRACT hosphatidylserine is localized exclusively to the inner leaflet of the membrane lipid bilayer of most cells, including erythrocytes. This Pasymmetric distribution is critical for the survival of erythrocytes in circulation since externalized phosphatidylserine is a phagocytic signal for splenic macrophages. Flippases are P-IV ATPase family proteins that active- ly transport phosphatidylserine from the outer to inner leaflet. It has not yet been determined which of the 14 members of this family of proteins is the flippase in human erythrocytes.