Supplementary Table S2: Global List of Proteins Identified and Quantified in the Whole Cellular Extract and Conditioned Medium of Cafs
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Aspartate Aminotransferase (AST, GOT), Human Liver
BioVision 05/18 For research use only Aspartate Aminotransferase (AST, GOT), Human Liver CATALOG NO: P1299-100 1 units RELATED PRODUCTS: ALTERNATE NAMES: Aspartate Transaminase, Glutamate Oxaloacetate, AST, GOT, Aspartate Aminotransferase (AST) (Mouse) ELISA Kit (Cat. No. E4320) sGOT, AspAT, ASAT, serum glutamic oxaloacetic transaminase, AAT Aspartate Aminotransferase (AST) (Human) ELISA Kit (Cat. No. E4319) Aspartate Aminotransferase (AST) (Rat) ELISA Kit (Cat. No. E4321) SOURCE: Human Liver Aspartate Aminotransferase (AST or SGOT) Activity Colorimetric Assay Kit (Cat. PURITY: Purified No. K753) Anti-GOT2 Antibody (cat. No. A1273) MOL. WEIGHT: ~92 kDa Anti-GOT1 Antibody (Cat. No. A1272) FORM: Lyophilized GOT2, human recombinant (Cat. No. 7809) GOT1, human recombinant (Cat. No. 7808) STORAGE CONDITIONS: Store at -20°C. Avoid repeated freezing and thawing cycles. BIOLOGICAL ACTIVITY: ≥ 1 U/mg (Dimension® Clinical Chemistry System) UNIT DEFINITATION: One unit will catalyze the transamination of one micromole of L- aspartate to alpha-ketoglutarate forming L-glutamate and oxaloacetate per minute at 37°C and pH 7.8.Measured at 340 nm as one equimolar amount of NAD produced by a coupled reaction. RECONSTITUTION: > 1 mg/mL in tris buffered saline, 1% BSA, pH 8.0. AST/SGOT is found in many tissues throughout the body, including DESCRIPTION: the liver, heart, muscles, kidney, and brain. If any of these organs or tissues is affected by disease or injury, AST is released into the bloodstream. This means that AST isn't as specific an indicator of liver damage as ALT (also known as alanine aminotransferase, another type of enzyme found almost entirely in the liver). The ratio of AST and ALT levels are commonly used as biomarkers for liver health. -
C8cc08685k1.Pdf
Electronic Supplementary Material (ESI) for ChemComm. This journal is © The Royal Society of Chemistry 2018 Supporting Information Minimalist Linkers Suitable for Irreversible Inhibitors in Simultaneous Proteome Profiling, Live-Cell Imaging and Drug Screening Cuiping Guo,Yu Chang, Xin Wang, Chengqian Zhang, Piliang Hao*, Ke Ding and Zhengqiu Li* School of Pharmacy, Jinan University, Guangzhou, China 510632 *Corresponding author ([email protected]) 1. General Information All chemicals were purchased from commercial vendors and used without further purification, unless indicated otherwise. All reactions requiring anhydrous conditions were carried out under argon or nitrogen atmosphere using oven-dried glassware. AR-grade solvents were used for all reactions. Reaction progress was monitored by TLC on pre-coated silica plates (Merck 60 F254 nm, 0.25 µm) and spots were visualized by UV, iodine or other suitable stains. Flash column chromatography was carried out using silica gel (Qingdao Ocean). All NMR spectra (1H-NMR, 13C-NMR) were recorded on Bruker 300 MHz/400 MHz NMR spectrometers. Chemical shifts were reported in parts per million (ppm) referenced with respect to appropriate internal standards or residual solvent peaks (CDCl3 = 7.26 ppm, DMSO-d6 = 2.50 ppm). The following abbreviations were used in reporting spectra, br s (broad singlet), s (singlet), d (doublet), t (triplet), q (quartet), m (multiplet), dd (doublet of doublets). Mass spectra were obtained on Agilent LC-ESI-MS system. All analytical HPLC were carried out on Agilent system. Water with 0.1% TFA and acetonitrile with 0.1% TFA were used as eluents and the flow rate was 0.5 mL/min. -
Topological Scoring of Protein Interaction Networks
bioRxiv preprint doi: https://doi.org/10.1101/438408; this version posted October 8, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Topological Scoring of Protein Interaction Networks Mihaela E. Sardiu1, Joshua M. Gilmore1,2, Brad D. Groppe1,3, Arnob Dutta1,4, Laurence Florens1, and Michael P. Washburn1,5‡ 1Stowers Institute for Medical Research, Kansas City, MO 64110 U.S.A. 2Current Address: Boehringer Ingelheim Vetmedica, St. Joseph, MO 64506 U.S.A. 3Current Address: Thermo Fisher Scientific, Waltham, MA 02451, U.S.A. 4Current Address: Department of Cell and Molecular Biology, University of Rhode Island, 287 CBLS, 120 Flagg Road, Kingston, RI 02881. 5 Department of Pathology and Laboratory Medicine, The University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, Kansas 66160, USA ‡To whom correspondence should be addressed: Michael Washburn, Ph.D. Stowers Institute for Medical Research 1000 E. 50th St. Kansas City, MO 64110 Phone: 816-926-4457 E-mail: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/438408; this version posted October 8, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract It remains a significant challenge to define individual protein associations within networks where an individual protein can directly interact with other proteins and/or be part of large complexes, which contain functional modules. Here we demonstrate the topological scoring (TopS) algorithm for the analysis of quantitative proteomic analyses of affinity purifications. -
Reprogramming of Trna Modifications Controls the Oxidative Stress Response by Codon-Biased Translation of Proteins
Reprogramming of tRNA modifications controls the oxidative stress response by codon-biased translation of proteins The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Chan, Clement T.Y. et al. “Reprogramming of tRNA Modifications Controls the Oxidative Stress Response by Codon-biased Translation of Proteins.” Nature Communications 3 (2012): 937. As Published http://dx.doi.org/10.1038/ncomms1938 Publisher Nature Publishing Group Version Author's final manuscript Citable link http://hdl.handle.net/1721.1/76775 Terms of Use Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. Reprogramming of tRNA modifications controls the oxidative stress response by codon-biased translation of proteins Clement T.Y. Chan,1,2 Yan Ling Joy Pang,1 Wenjun Deng,1 I. Ramesh Babu,1 Madhu Dyavaiah,3 Thomas J. Begley3 and Peter C. Dedon1,4* 1Department of Biological Engineering, 2Department of Chemistry and 4Center for Environmental Health Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139; 3College of Nanoscale Science and Engineering, University at Albany, SUNY, Albany, NY 12203 * Corresponding author: PCD, Department of Biological Engineering, NE47-277, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139; tel 617-253-8017; fax 617-324-7554; email [email protected] 2 ABSTRACT Selective translation of survival proteins is an important facet of cellular stress response. We recently demonstrated that this translational control involves a stress-specific reprogramming of modified ribonucleosides in tRNA. -
Ornithine Aminotransferase, an Important Glutamate-Metabolizing Enzyme at the Crossroads of Multiple Metabolic Pathways
biology Review Ornithine Aminotransferase, an Important Glutamate-Metabolizing Enzyme at the Crossroads of Multiple Metabolic Pathways Antonin Ginguay 1,2, Luc Cynober 1,2,*, Emmanuel Curis 3,4,5,6 and Ioannis Nicolis 3,7 1 Clinical Chemistry, Cochin Hospital, GH HUPC, AP-HP, 75014 Paris, France; [email protected] 2 Laboratory of Biological Nutrition, EA 4466 PRETRAM, Faculté de Pharmacie, Université Paris Descartes, 75006 Paris, France 3 Laboratoire de biomathématiques, plateau iB2, Faculté de Pharmacie, Université Paris Descartes, 75006 Paris, France; [email protected] (E.C.); [email protected] (I.N.) 4 UMR 1144, INSERM, Université Paris Descartes, 75006 Paris, France 5 UMR 1144, Université Paris Descartes, 75006 Paris, France 6 Service de biostatistiques et d’informatique médicales, hôpital Saint-Louis, Assistance publique-hôpitaux de Paris, 75010 Paris, France 7 EA 4064 “Épidémiologie environnementale: Impact sanitaire des pollutions”, Faculté de Pharmacie, Université Paris Descartes, 75006 Paris, France * Correspondence: [email protected]; Tel.: +33-158-411-599 Academic Editors: Arthur J.L. Cooper and Thomas M. Jeitner Received: 26 October 2016; Accepted: 24 February 2017; Published: 6 March 2017 Abstract: Ornithine δ-aminotransferase (OAT, E.C. 2.6.1.13) catalyzes the transfer of the δ-amino group from ornithine (Orn) to α-ketoglutarate (aKG), yielding glutamate-5-semialdehyde and glutamate (Glu), and vice versa. In mammals, OAT is a mitochondrial enzyme, mainly located in the liver, intestine, brain, and kidney. In general, OAT serves to form glutamate from ornithine, with the notable exception of the intestine, where citrulline (Cit) or arginine (Arg) are end products. -
Allele-Specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish
Allele-specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish by Ailu Chen A dissertation submitted to the Graduate Faculty of Auburn University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Auburn, Alabama August 1, 2015 Keywords: catfish, interspecific hybrids, allele-specific expression, ribosomal protein Copyright 2015 by Ailu Chen Approved by Zhanjiang Liu, Chair, Professor, School of Fisheries, Aquaculture and Aquatic Sciences Nannan Liu, Professor, Entomology and Plant Pathology Eric Peatman, Associate Professor, School of Fisheries, Aquaculture and Aquatic Sciences Aaron M. Rashotte, Associate Professor, Biological Sciences Abstract Interspecific hybridization results in a vast reservoir of allelic variations, which may potentially contribute to phenotypical enhancement in the hybrids. Whether the allelic variations are related to the downstream phenotypic differences of interspecific hybrid is still an open question. The recently developed genome-wide allele-specific approaches that harness high- throughput sequencing technology allow direct quantification of allelic variations and gene expression patterns. In this work, I investigated allele-specific expression (ASE) pattern using RNA-Seq datasets generated from interspecific catfish hybrids. The objective of the study is to determine the ASE genes and pathways in which they are involved. Specifically, my study investigated ASE-SNPs, ASE-genes, parent-of-origins of ASE allele and how ASE would possibly contribute to heterosis. My data showed that ASE was operating in the interspecific catfish system. Of the 66,251 and 177,841 SNPs identified from the datasets of the liver and gill, 5,420 (8.2%) and 13,390 (7.5%) SNPs were identified as significant ASE-SNPs, respectively. -
Upregulation of Peroxisome Proliferator-Activated Receptor-Α And
Upregulation of peroxisome proliferator-activated receptor-α and the lipid metabolism pathway promotes carcinogenesis of ampullary cancer Chih-Yang Wang, Ying-Jui Chao, Yi-Ling Chen, Tzu-Wen Wang, Nam Nhut Phan, Hui-Ping Hsu, Yan-Shen Shan, Ming-Derg Lai 1 Supplementary Table 1. Demographics and clinical outcomes of five patients with ampullary cancer Time of Tumor Time to Age Differentia survival/ Sex Staging size Morphology Recurrence recurrence Condition (years) tion expired (cm) (months) (months) T2N0, 51 F 211 Polypoid Unknown No -- Survived 193 stage Ib T2N0, 2.41.5 58 F Mixed Good Yes 14 Expired 17 stage Ib 0.6 T3N0, 4.53.5 68 M Polypoid Good No -- Survived 162 stage IIA 1.2 T3N0, 66 M 110.8 Ulcerative Good Yes 64 Expired 227 stage IIA T3N0, 60 M 21.81 Mixed Moderate Yes 5.6 Expired 16.7 stage IIA 2 Supplementary Table 2. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of an ampullary cancer microarray using the Database for Annotation, Visualization and Integrated Discovery (DAVID). This table contains only pathways with p values that ranged 0.0001~0.05. KEGG Pathway p value Genes Pentose and 1.50E-04 UGT1A6, CRYL1, UGT1A8, AKR1B1, UGT2B11, UGT2A3, glucuronate UGT2B10, UGT2B7, XYLB interconversions Drug metabolism 1.63E-04 CYP3A4, XDH, UGT1A6, CYP3A5, CES2, CYP3A7, UGT1A8, NAT2, UGT2B11, DPYD, UGT2A3, UGT2B10, UGT2B7 Maturity-onset 2.43E-04 HNF1A, HNF4A, SLC2A2, PKLR, NEUROD1, HNF4G, diabetes of the PDX1, NR5A2, NKX2-2 young Starch and sucrose 6.03E-04 GBA3, UGT1A6, G6PC, UGT1A8, ENPP3, MGAM, SI, metabolism -
Fkbp10 (NM 010221) Mouse Untagged Clone – MC201811 | Origene
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 MC201811 Fkbp10 (NM_010221) Mouse Untagged Clone Product data: Product Type: Expression Plasmids Product Name: Fkbp10 (NM_010221) Mouse Untagged Clone Tag: Tag Free Symbol: Fkbp10 Synonyms: AI325255; FKBP-10; FKBP-65; Fkbp-rs1; Fkbp1-rs; Fkbp6; FKBP65; Fkbprp Vector: PCMV6-Kan/Neo E. coli Selection: Kanamycin (25 ug/mL) Cell Selection: Neomycin 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 / 3 Fkbp10 (NM_010221) Mouse Untagged Clone – MC201811 Fully Sequenced ORF: >BC029546 sequence for NM_010221 GTCCGCTCTCACTGCCGGCGTCCCTGGTCTGGGCACCATGTTCCTTGTGGGGTCCTCCAGCCACACCCTC CATCGGCTCCGCATACTGCCGTTGCTGTTGCTTCTACAGACCTTGGAGAGGGGACTGGGCCGTGCCAGCC CGGCCGGAGCCCCCTTGGAAGATGTGGTCATCGAGAGATACCACATCCCTCGGGCCTGTCCCCGAGAAGT GCAGATGGGGGATTTTGTGCGTTACCACTACAATGGCACTTTCGAAGACGGGAAAAAGTTTGACTCCAGC TATGACCGTAGCACCCTGGTGGCCATCGTTGTGGGCGTAGGCCGCCTCATCACCGGCATGGACCGGGGTC TCATGGGCATGTGTGTCAACGAGCGCCGCCGCCTCATTGTGCCTCCCCACCTGGGCTACGGCAGCATCGG TGTGGCGGGCCTCATCCCCCCTGATGCCACCCTCTATTTTGACGTGGTCCTGCTGGACGTGTGGAACAAA GCAGACACGGTGCAGTCAACTATCCTCCTGCGCCCTCCCTACTGCCCCCGAATGGTGCAGAACAGTGACT TTGTGCGCTATCACTACAATGGCACTCTGCTGGATGGCACTGCCTTTGACAACAGCTACAGTAGGGGAGG CACTTATGACACCTACATCGGCTCTGGTTGGCTGATCAAAGGCATGGACCAGGGGCTGCTGGGCATGTGC -
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. -
Electronic Supplementary Material (ESI) for Molecular Biosystems
Electronic Supplementary Material (ESI) for Molecular BioSystems. This journal is © The Royal Society of Chemistry 2015 Table S5 Mass data of proteins identified with label free shotgun proteomics a #Alt. Proteins; b Scores; c #Peptides; d SC [%]; e RMS90 [ppm]; f Rank; g Median(Controls:GLP1); h #(Controls:GLP1); i CV [%](Controls:GLP1); l Median(Controls:Palmitate); m #(Controls:Palmitate) ; n CV [%](Controls:Palmitate); o Median(Controls:GLP1 + Palmitate); p #(Controls:GLP1 + Palmitate); q CV [%](Controls:GLP1 + Palmitate) MW OK Accession Protein pI a b c d e f g h i l m n o p q [kDa] 78 kDa glucose-regulated protein OS=Rattus 1672.6 true GRP78_RAT 72.3 4.9 1 22 39 1.48 1 1.16 6 20.53 1.18 9 9.56 1.24 10 13.52 norvegicus GN=Hspa5 PE=1 SV=1 (M:1672.6) Endoplasmin OS=Rattus norvegicus 1253.0 true ENPL_RAT 92.7 4.6 1 23 29 3.34 2 0.85 8 33.34 1.19 6 39.58 1.18 10 28.11 GN=Hsp90b1 PE=1 SV=2 (M:1253.0) Stress-70 protein, mitochondrial OS=Rattus 1138.8 true GRP75_RAT 73.8 5.9 1 17 28.7 1.18 3 1.21 5 7.62 0.78 1 1.1 8 8.04 norvegicus GN=Hspa9 PE=1 SV=3 (M:1138.8) Protein disulfide-isomerase A3 OS=Rattus 1035.4 true PDIA3_RAT 56.6 5.8 1 16 35.2 2.84 4 0.94 3 17.22 1.15 4 26.62 1.25 4 7.86 norvegicus GN=Pdia3 PE=1 SV=2 (M:1035.4) Aconitate hydratase, mitochondrial 983.8 true ACON_RAT OS=Rattus norvegicus GN=Aco2 PE=1 85.4 8.7 1 19 31.4 2.72 5 0.89 2 23.6 1.21 2 9.25 0.89 3 32.87 (M:983.8) SV=2 60 kDa heat shock protein, mitochondrial 906.9 true CH60_RAT OS=Rattus norvegicus GN=Hspd1 PE=1 60.9 5.8 1 13 32.5 3.26 6 1.05 5 13.15 1.01 2 32.54 1.01 -
Genetic and Genomic Analysis of Hyperlipidemia, Obesity and Diabetes Using (C57BL/6J × TALLYHO/Jngj) F2 Mice
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Nutrition Publications and Other Works Nutrition 12-19-2010 Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P. Stewart Marshall University Hyoung Y. Kim University of Tennessee - Knoxville, [email protected] Arnold M. Saxton University of Tennessee - Knoxville, [email protected] Jung H. Kim Marshall University Follow this and additional works at: https://trace.tennessee.edu/utk_nutrpubs Part of the Animal Sciences Commons, and the Nutrition Commons Recommended Citation BMC Genomics 2010, 11:713 doi:10.1186/1471-2164-11-713 This Article is brought to you for free and open access by the Nutrition at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Nutrition Publications and Other Works by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Stewart et al. BMC Genomics 2010, 11:713 http://www.biomedcentral.com/1471-2164/11/713 RESEARCH ARTICLE Open Access Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P Stewart1, Hyoung Yon Kim2, Arnold M Saxton3, Jung Han Kim1* Abstract Background: Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/ JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia.