TSA-Seq Reveals a Largely Conserved Genome Organization Relative to Nuclear Speckles with Small Position Changes Tightly Correlated with Gene Expression Changes
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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. -
Datasheet BA0931 Anti-HSPH1 Antibody
Product datasheet Anti-HSPH1 Antibody Catalog Number: BA0931 BOSTER BIOLOGICAL TECHNOLOGY Special NO.1, International Enterprise Center, 2nd Guanshan Road, Wuhan, China Web: www.boster.com.cn Phone: +86 27 67845390 Fax: +86 27 67845390 Email: [email protected] Basic Information Product Name Anti-HSPH1 Antibody Gene Name HSPH1 Source Rabbit IgG Species Reactivity human,rat,mouse Tested Application WB,IHC-P,ICC/IF,FCM Contents 500ug/ml antibody with PBS ,0.02% NaN3 , 1mg BSA and 50% glycerol. Immunogen A synthetic peptide corresponding to a sequence at the C-terminus of human Hsp105(713-733aa EVMEWMNNVMNAQAKKSLDQD), different from the related mouse sequence by one amino acid, and different from the related rat sequence by two amino acids. Purification Immunogen affinity purified. Observed MW 110KD Dilution Ratios Western blot: 1:500-2000 Immunohistochemistry in paraffin section IHC-(P): 1:50-400 Immunocytochemistry/Immunofluorescence (ICC/IF): 1:50-400 Flow cytometry (FCM): 1-3μg/1x106 cells (Boiling the paraffin sections in 10mM citrate buffer,pH6.0,or PH8.0 EDTA repair liquid for 20 mins is required for the staining of formalin/paraffin sections.) Optimal working dilutions must be determined by end user. Storage 12 months from date of receipt,-20℃ as supplied.6 months 2 to 8℃ after reconstitution. Avoid repeated freezing and thawing Background Information HSP105(HEAT-SHOCK 105/110-KD PROTEIN 1), also called HSPH1 or HSP110, is a protein that in humans is encoded by the HSPH1 gene. Immunohistochemical analysis localizes HSP105 mainly in the cytoplasm. Database analysis indicates that both HSP105 isoforms are highly conserved during evolution. -
At Elevated Temperatures, Heat Shock Protein Genes Show Altered Ratios Of
EXPERIMENTAL AND THERAPEUTIC MEDICINE 22: 900, 2021 At elevated temperatures, heat shock protein genes show altered ratios of different RNAs and expression of new RNAs, including several novel HSPB1 mRNAs encoding HSP27 protein isoforms XIA GAO1,2, KEYIN ZHANG1,2, HAIYAN ZHOU3, LUCAS ZELLMER4, CHENGFU YUAN5, HAI HUANG6 and DEZHONG JOSHUA LIAO2,6 1Department of Pathology, Guizhou Medical University Hospital; 2Key Lab of Endemic and Ethnic Diseases of The Ministry of Education of China in Guizhou Medical University; 3Clinical Research Center, Guizhou Medical University Hospital, Guiyang, Guizhou 550004, P.R. China; 4Masonic Cancer Center, University of Minnesota, Minneapolis, MN 55455, USA; 5Department of Biochemistry, China Three Gorges University, Yichang, Hubei 443002; 6Center for Clinical Laboratories, Guizhou Medical University Hospital, Guiyang, Guizhou 550004, P.R. China Received December 16, 2020; Accepted May 10, 2021 DOI: 10.3892/etm.2021.10332 Abstract. Heat shock proteins (HSP) serve as chaperones genes may engender multiple protein isoforms. These results to maintain the physiological conformation and function of collectively suggested that, besides increasing their expres‑ numerous cellular proteins when the ambient temperature is sion, certain HSP and associated genes also use alternative increased. To determine how accurate the general assumption transcription start sites to produce multiple RNA transcripts that HSP gene expression is increased in febrile situations is, and use alternative splicing of a transcript to produce multiple the RNA levels of the HSF1 (heat shock transcription factor 1) mature RNAs, as important mechanisms for responding to an gene and certain HSP genes were determined in three cell increased ambient temperature in vitro. lines cultured at 37˚C or 39˚C for three days. -
1 Supplemental Appendix Table of Contents Author
Supplemental Appendix Table of Contents Author Lists………………………………………………….…..2-3 Supplemental Figures …………………………………..……..4-20 Supplemental Tables …………………………………….…….21-41 Supplemental References……………………………………..42 ! 1! Brittany A. Goods, PhD1,2*, Michael H. Askenase, PhD3*, Erica Markarian4, Hannah E. Beatty3, Riley Drake1, Ira Fleming1, Jonathan H. DeLong3, Naomi H. Philip5, Charles C. Matouk, MD6, Issam A. Awad, MD7, Mario Zuccarello, MD8, Daniel F. Hanley, MD9, J. Christopher Love, PhD2,4,10,#, Alex K. Shalek, PhD1,2,4,11,12,13,14,#, and Lauren H. Sansing, MD, MS3,15,#, on behalf of the ICHseq Investigators 1Department of Chemistry and Institute for Medical Engineering & Science, Massachusetts Institute of Technology 2Broad Institute, Harvard University & Massachusetts Institute of Technology 3Department of Neurology, Yale University School of Medicine 4Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology 5Department of Immunobiology, Yale University School of Medicine 6Department of Neurosurgery, Yale University School of Medicine 7Department of Neurosurgery, University of Chicago 8Department of Neurosurgery, University of Cincinnati 9Brain Injury Outcomes Division, Johns Hopkins School of Medicine 10Department of Chemical Engineering, Massachusetts Institute of Technology 11Ragon Institute, Harvard University, Massachusetts Institute of Technology, & Massachusetts General Hospital 12Division of Health Science & Technology, Harvard Medical School 13Program in Computational & Systems Biology, Massachusetts -
The C-Terminal GGAP Motif of Hsp70 Mediates Substrate Recognition And
ARTICLE cro The C-terminal GGAP motif of Hsp70 mediates substrate recognition and stress response in yeast Received for publication, March 2, 2018, and in revised form, August 30, 2018 Published, Papers in Press, September 18, 2018, DOI 10.1074/jbc.RA118.002691 Weibin Gong (宫维斌)‡1, Wanhui Hu (胡万辉)‡§1,2, Linan Xu (徐利楠)¶1, Huiwen Wu (吴惠文)‡§3,SiWu(吴思)‡§, Hong Zhang (张红)‡§, Jinfeng Wang (王金凤)‡, Gary W. Jones¶4, and X Sarah Perrett‡§5 From the ‡National Laboratory of Biomacromolecules, Chinese Academy of Sciences Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China, the §University of the Chinese Academy of Sciences, Beijing 100049, China, and the ¶Department of Biology, Maynooth University, Maynooth, W23 W6R7, Kildare, Ireland Edited by Ursula Jakob The allosteric coupling of the highly conserved nucleotide- containing GGAP and GGAP-like tetrapeptide repeats, can and substrate-binding domains of Hsp70 has been studied directly bind to Ure2, the Hsp40 co-chaperone Ydj1, and ␣-sy- intensively. In contrast, the role of the disordered, highly vari- nuclein, but not to the SUMO-like protein SMT3 or BSA. Dele- Downloaded from able C-terminal region of Hsp70 remains unclear. In many tion or substitution of the Ssa1 GGAP motif impaired yeast cell eukaryotic Hsp70s, the extreme C-terminal EEVD motif binds tolerance to temperature and cell-wall damage stress. This study to the tetratricopeptide-repeat domains of Hsp70 co-chaper- highlights that the C-terminal GGAP motif of Hsp70 is impor- ones. Here, we discovered that the TVEEVD sequence of Sac- tant for substrate recognition and mediation of the heat shock charomyces cerevisiae cytoplasmic Hsp70 (Ssa1) functions as a response. -
Genomic Identification, Evolution and Sequence Analysis of the Heat
G C A T T A C G G C A T genes Article Genomic Identification, Evolution and Sequence Analysis of the Heat-Shock Protein Gene Family in Buffalo 1, 2, 3 4 1 Saif ur Rehman y, Asif Nadeem y , Maryam Javed , Faiz-ul Hassan , Xier Luo , Ruqayya Bint Khalid 3 and Qingyou Liu 1,* 1 State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China; [email protected] (S.u.R.); [email protected] (X.L.) 2 Department of Biotechnology, Virtual University of Pakistan, Lahore-54000, Pakistan; [email protected] 3 Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore-54000, Pakistan; [email protected] (M.J.); [email protected] (R.B.K.) 4 Institute of Animal and Dairy Sciences, Faculty of Animal Husbandry, University of Agriculture, Faisalabad-38040, Pakistan; [email protected] * Correspondence: [email protected]; Tel.: +86-138-7880-5296 These authors contributed equally to this manuscript. y Received: 26 October 2020; Accepted: 18 November 2020; Published: 23 November 2020 Abstract: Heat-shock proteins (HSP) are conserved chaperones crucial for protein degradation, maturation, and refolding. These adenosine triphosphate dependent chaperones were classified based on their molecular mass that ranges between 10–100 kDA, including; HSP10, HSP40, HSP70, HSP90, HSPB1, HSPD, and HSPH1 family. HSPs are essential for cellular responses and imperative for protein homeostasis and survival under stress conditions. This study performed a computational analysis of the HSP protein family to better understand these proteins at the molecular level. -
1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor
xO GENE PANEL 1714 gene comprehensive cancer panel enriched for clinically actionable genes with additional biologically relevant genes 400-500x average coverage on tumor Genes A-C Genes D-F Genes G-I Genes J-L AATK ATAD2B BTG1 CDH7 CREM DACH1 EPHA1 FES G6PC3 HGF IL18RAP JADE1 LMO1 ABCA1 ATF1 BTG2 CDK1 CRHR1 DACH2 EPHA2 FEV G6PD HIF1A IL1R1 JAK1 LMO2 ABCB1 ATM BTG3 CDK10 CRK DAXX EPHA3 FGF1 GAB1 HIF1AN IL1R2 JAK2 LMO7 ABCB11 ATR BTK CDK11A CRKL DBH EPHA4 FGF10 GAB2 HIST1H1E IL1RAP JAK3 LMTK2 ABCB4 ATRX BTRC CDK11B CRLF2 DCC EPHA5 FGF11 GABPA HIST1H3B IL20RA JARID2 LMTK3 ABCC1 AURKA BUB1 CDK12 CRTC1 DCUN1D1 EPHA6 FGF12 GALNT12 HIST1H4E IL20RB JAZF1 LPHN2 ABCC2 AURKB BUB1B CDK13 CRTC2 DCUN1D2 EPHA7 FGF13 GATA1 HLA-A IL21R JMJD1C LPHN3 ABCG1 AURKC BUB3 CDK14 CRTC3 DDB2 EPHA8 FGF14 GATA2 HLA-B IL22RA1 JMJD4 LPP ABCG2 AXIN1 C11orf30 CDK15 CSF1 DDIT3 EPHB1 FGF16 GATA3 HLF IL22RA2 JMJD6 LRP1B ABI1 AXIN2 CACNA1C CDK16 CSF1R DDR1 EPHB2 FGF17 GATA5 HLTF IL23R JMJD7 LRP5 ABL1 AXL CACNA1S CDK17 CSF2RA DDR2 EPHB3 FGF18 GATA6 HMGA1 IL2RA JMJD8 LRP6 ABL2 B2M CACNB2 CDK18 CSF2RB DDX3X EPHB4 FGF19 GDNF HMGA2 IL2RB JUN LRRK2 ACE BABAM1 CADM2 CDK19 CSF3R DDX5 EPHB6 FGF2 GFI1 HMGCR IL2RG JUNB LSM1 ACSL6 BACH1 CALR CDK2 CSK DDX6 EPOR FGF20 GFI1B HNF1A IL3 JUND LTK ACTA2 BACH2 CAMTA1 CDK20 CSNK1D DEK ERBB2 FGF21 GFRA4 HNF1B IL3RA JUP LYL1 ACTC1 BAG4 CAPRIN2 CDK3 CSNK1E DHFR ERBB3 FGF22 GGCX HNRNPA3 IL4R KAT2A LYN ACVR1 BAI3 CARD10 CDK4 CTCF DHH ERBB4 FGF23 GHR HOXA10 IL5RA KAT2B LZTR1 ACVR1B BAP1 CARD11 CDK5 CTCFL DIAPH1 ERCC1 FGF3 GID4 HOXA11 IL6R KAT5 ACVR2A -
Transcriptomic and Proteomic Profiling Provides Insight Into
BASIC RESEARCH www.jasn.org Transcriptomic and Proteomic Profiling Provides Insight into Mesangial Cell Function in IgA Nephropathy † † ‡ Peidi Liu,* Emelie Lassén,* Viji Nair, Celine C. Berthier, Miyuki Suguro, Carina Sihlbom,§ † | † Matthias Kretzler, Christer Betsholtz, ¶ Börje Haraldsson,* Wenjun Ju, Kerstin Ebefors,* and Jenny Nyström* *Department of Physiology, Institute of Neuroscience and Physiology, §Proteomics Core Facility at University of Gothenburg, University of Gothenburg, Gothenburg, Sweden; †Division of Nephrology, Department of Internal Medicine and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan; ‡Division of Molecular Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan; |Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden; and ¶Integrated Cardio Metabolic Centre, Karolinska Institutet Novum, Huddinge, Sweden ABSTRACT IgA nephropathy (IgAN), the most common GN worldwide, is characterized by circulating galactose-deficient IgA (gd-IgA) that forms immune complexes. The immune complexes are deposited in the glomerular mesangium, leading to inflammation and loss of renal function, but the complete pathophysiology of the disease is not understood. Using an integrated global transcriptomic and proteomic profiling approach, we investigated the role of the mesangium in the onset and progression of IgAN. Global gene expression was investigated by microarray analysis of the glomerular compartment of renal biopsy specimens from patients with IgAN (n=19) and controls (n=22). Using curated glomerular cell type–specific genes from the published literature, we found differential expression of a much higher percentage of mesangial cell–positive standard genes than podocyte-positive standard genes in IgAN. Principal coordinate analysis of expression data revealed clear separation of patient and control samples on the basis of mesangial but not podocyte cell–positive standard genes. -
(HECT) E3 Ubiquitin Ligase Family. NEDD3 Is Overexpressed in CRC Patients, and NEDD4 Promotes Colon Cancer Cell Growth [1, 2]
Supplementary Materials NEDD3 belongs to the homologous to E6AP C-terminus (HECT) E3 ubiquitin ligase family. NEDD3 is overexpressed in CRC patients, and NEDD4 promotes colon cancer cell growth [1, 2]. The expression levels of the signal transducer and activator of transcription 1 and 3 (STAT1 and STAT3) were investigated in CRC biopsy samples of 400 patients [3]. The results suggested that STAT1 and STAT3 are effective prognostic biomarkers in CRC. In addition, activation of STAT3 promotes rectal cancer growth by inducing loss of PTPN4 [4]. TRAF6 is a member of the tumor-necrosis factor family and is involved in the NF-kappa B signaling pathway. Wu et al. showed that TRAF6 can effectively suppress CRC metastasis by promoting CTNNB1 degradation, suggesting its potential as a target for the treatment of advanced CRC [5]. HSP90AA1 and HSP90AB1 belong to the heat shock protein 90 family. Drug resistance caused by HSP90AA1-mediated autophagy was observed in chemotherapy-treated osteosarcoma [6]. Wang et al. suggested that HSP90AB1 could serve as a novel biomarker of poor prognosis in lung adenocarcinoma. The association of these genes with CRC remains to be established [7]. Table S1. Differentially expressed genes between responders and non-responders in the training cohort. Sr. No. Gene p-value Fold-Change * 1 ID1 2.17 × 10−2 −2.78 2 WNT11 1.99 × 10−2 −2.32 3 NKD1 1.90 × 10−3 −2.27 4 SFN 2.45 × 10−3 −2.24 5 LAMA5 8.51 × 10−3 −1.96 6 CACNA1D 5.06 × 10−4 −1.96 7 IKBKB 9.91 × 10−3 −1.88 8 PLA2G4F 5.89 × 10−3 −1.83 9 CDK6 3.63 × 10−3 −1.79 10 CIC 1.21 × 10−2 −1.76 11 SMARCB1 5.80 × 10−4 −1.75 12 SRSF2 3.07 × 10−3 −1.73 13 IKBKG 1.51 × 10−2 −1.68 14 BAP1 9.01 × 10−3 −1.68 15 SPRY2 1.52 × 10−3 −1.65 16 AXIN2 5.01 × 10−3 −1.65 17 GNA11 6.73 × 10−3 −1.64 18 FGFR4 1.69 × 10−3 −1.64 19 FGFR3 1.05 × 10−3 −1.62 20 HDAC10 1.08 × 10−3 −1.62 21 SGK2 5.64 × 10−3 −1.6 22 H3F3A 2.42 × 10−3 −1.58 23 EPHA2 1.74 × 10−2 −1.57 24 U2AF1 4.56 × 10−3 −1.56 25 ITGB4 3.14 × 10−3 −1.56 26 TRAF7 6.07 × 10−3 −1.54 27 CBL 5.56 × 10−3 −1.53 28 MAP2K2 1.99 × 10−3 −1.51 Sr. -
Neuronal Vulnerability and Multilineage Diversity in Multiple Sclerosis
Europe PMC Funders Group Author Manuscript Nature. Author manuscript; available in PMC 2020 January 17. Published in final edited form as: Nature. 2019 June 13; 573(7772): 75–82. doi:10.1038/s41586-019-1404-z. Europe PMC Funders Author Manuscripts Neuronal vulnerability and multilineage diversity in multiple sclerosis Lucas Schirmer#1,2,3,4, Dmitry Velmeshev#1,5, Staffan Holmqvist2, Max Kaufmann6, Sebastian Werneburg7, Diane Jung1,5, Stephanie Vistnes1,4, John H. Stockley2, Adam Young8, Maike Steindel2,8, Brian Tung1,5,9, Nitasha Goyal1,5,9, Aparna Bhaduri1,5, Simone Mayer1,5, Jan Broder Engler6, Omer A. Bayraktar2, Robin J. M. Franklin8, Maximilian Haeussler10, Richard Reynolds11, Dorothy P. Schafer7, Manuel A. Friese6, Lawrence R. Shiow1,4, Arnold R. Kriegstein1,5,†, David H. Rowitch1,2,4,† 1Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA 2Department of Paediatrics and Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, CB2 0QQ, UK 3Department of Neurology, Medical Faculty Mannheim, University of Heidelberg, 68167 Mannheim, Germany 4Department of Pediatrics/Neonatology, University of California, San Francisco, San Francisco, CA 94158, USA 5Department of Neurology, University of California, San Francisco, San Francisco, CA 94158, Europe PMC Funders Author Manuscripts USA 6Institute of Neuroimmunology and Multiple Sclerosis, Center for Molecular Neurobiology Hamburg, University Medical Center Hamburg-Eppendorf, -
DIPPER, a Spatiotemporal Proteomics Atlas of Human Intervertebral Discs
TOOLS AND RESOURCES DIPPER, a spatiotemporal proteomics atlas of human intervertebral discs for exploring ageing and degeneration dynamics Vivian Tam1,2†, Peikai Chen1†‡, Anita Yee1, Nestor Solis3, Theo Klein3§, Mateusz Kudelko1, Rakesh Sharma4, Wilson CW Chan1,2,5, Christopher M Overall3, Lisbet Haglund6, Pak C Sham7, Kathryn Song Eng Cheah1, Danny Chan1,2* 1School of Biomedical Sciences, , The University of Hong Kong, Hong Kong; 2The University of Hong Kong Shenzhen of Research Institute and Innovation (HKU-SIRI), Shenzhen, China; 3Centre for Blood Research, Faculty of Dentistry, University of British Columbia, Vancouver, Canada; 4Proteomics and Metabolomics Core Facility, The University of Hong Kong, Hong Kong; 5Department of Orthopaedics Surgery and Traumatology, HKU-Shenzhen Hospital, Shenzhen, China; 6Department of Surgery, McGill University, Montreal, Canada; 7Centre for PanorOmic Sciences (CPOS), The University of Hong Kong, Hong Kong Abstract The spatiotemporal proteome of the intervertebral disc (IVD) underpins its integrity *For correspondence: and function. We present DIPPER, a deep and comprehensive IVD proteomic resource comprising [email protected] 94 genome-wide profiles from 17 individuals. To begin with, protein modules defining key †These authors contributed directional trends spanning the lateral and anteroposterior axes were derived from high-resolution equally to this work spatial proteomes of intact young cadaveric lumbar IVDs. They revealed novel region-specific Present address: ‡Department profiles of regulatory activities -
Supplementary Material Contents
Supplementary Material Contents Immune modulating proteins identified from exosomal samples.....................................................................2 Figure S1: Overlap between exosomal and soluble proteomes.................................................................................... 4 Bacterial strains:..............................................................................................................................................4 Figure S2: Variability between subjects of effects of exosomes on BL21-lux growth.................................................... 5 Figure S3: Early effects of exosomes on growth of BL21 E. coli .................................................................................... 5 Figure S4: Exosomal Lysis............................................................................................................................................ 6 Figure S5: Effect of pH on exosomal action.................................................................................................................. 7 Figure S6: Effect of exosomes on growth of UPEC (pH = 6.5) suspended in exosome-depleted urine supernatant ....... 8 Effective exosomal concentration....................................................................................................................8 Figure S7: Sample constitution for luminometry experiments..................................................................................... 8 Figure S8: Determining effective concentration .........................................................................................................