Gene Expression Signatures in AML-12 Hepatocyte Cells Upon Dengue Virus Infection and Acetaminophen Treatment

Total Page:16

File Type:pdf, Size:1020Kb

Gene Expression Signatures in AML-12 Hepatocyte Cells Upon Dengue Virus Infection and Acetaminophen Treatment Supplementary Materials: Gene Expression Signatures in AML-12 Hepatocyte Cells Upon Dengue virus Infection and Acetaminophen Treatment Figure S1. Detection of DENV−2 in AML−12 cell cultures. AML−12 cells were grown in DMEM/Ham's F12. The presence of DENV2 into the cells was performed by immunocytochemistry, using a mouse anti−flavivirus envelope protein antibody (4G2), diluted 1:10, and Novolink™ Polymer Detection Systems. Images are shown at 100X magnification. The brown staining indicates the presence of DENV−2 in the cell cultures. Ab control: cells labeled with peroxidase−conjugated antibody. Anti−Env (4G2): cells labeled with mouse anti−Flavivirus envelope protein antibody (4G2) and peroxidase−conjugated antibody. Untreated = cells not incubated with DENV−2 and untreated with APAP (Negative controls). DENV = cells incubated with DENV−2 at a MOI = 1. APAP + DENV = cells incubated with DENV−2 at a MOI = 1 (48 h) and 1 mM APAP (24 h). Figure S2. Evaluation of DENV infection in AML−12 cells by RT−PCR. Total RNA extracted from AML−12 cells was used to run RT−PCR. The cDNA was submitted to PCR assays according to [65] modified by [66]. The PCR products were run at 1% agarose/TAE (Tris−acetate, 0,5 mM EDTA) and stained using SYBR Safe—DNA Gel Stain (Thermo Fisher Scientific). The positive control (C+) pUC− Viruses 2020, 12, 1284 2 of 180 cloning vector, containing a sequence designed for annealing with primers. (C−) PCR reaction control (no cDNA). Untreated = cultured cells (not incubated with DENV−2 and untreated with APAP. APAP = cells treated with APAP 1 mM (24 h). DENV = cells incubated with DENV−2 at a MOI = 1 (24 h). APAP+DENV = cells incubated with DENV−2 at a MOI = 1 (48 h) and treated with 1 mM APAP (24 h). APAP CC50= cells treated with APAP 20 mM (24 h). Figure S3. Multidimensional scaling plot of sequencing libraries of AML−12 cells infected by DENV−2 and/or treated with APAP. The multidimensional scaling plot based on pairwise gene expression profiling distances among AML−12 cells infected by DENV−2 and/or treated with APAP. On the x−axis, it is possible to observe the separation of DENV2−infected cells (DENV−infected and DENV−infected/APAP−treated cells) of the non−infected groups (Untreated and APAP−treated cells). DENV−infected cells: cells incubated for 48 hours with DENV−2 (MOI=1); APAP−treated cells: cells treated with 1mM APAP for 24 hours after additional 24 hours of culture; DENV−infected/APAP−treated cells: cells incubated for 24 hours with DENV−2 (MOI=1) and further treated with 1mM APAP for 24 hours; Untreated cells: untreated cells cultured for 48 hours. Viruses 2020, 12, x 3 of 180 Figure S4. Dot plot of hierarchical summaries of GO terms enriched in differentially expressed genes AML−12 hepatocytes after infection by DENV−2 and treatment with APAP in gene clusters 2 (A), 4 (B), and 5 (C). Data were obtained from the analysis of the GO terms that were significantly enriched within the Biological Process categories (p.adjust < 0.05) among DEGs from each cluster presented in Figure 2. Dots represent the enriched GO terms after summarization with the REVIGO tool. The color of the dots represents the p−adjust values following Benjamini−Hochberg (BH) significance testing. The position of the dots in the x−axis (Count) is related to the amount of DEGs associated with the GO term. The size of the dots (GeneRatio) represents the number of DEGs related to the number of genes associated with a GO term in the Mus musculus genome. Table S1. Differentially expressed genes identified in AML−12 hepatocytes cells after infection by DENV−2 and/or treatment with APAP. Differentially Expressed Genes in APAP−Treated Cells Compared to Untreated Cells Gene logFC logCPM F p Value FDR Serpinb9b −0.81 5.00 102.13 2.89 x 10−15 1.95 × 10−11 Akr1b7 −0.74 7.09 96.32 9.65 × 10−15 4.35 × 10−11 Viruses 2020Gm13857, 12, x −0.72 6.17 91.88 2.49 × 10−14 8.44 × 104−11 of 180 Azgp1 −0.66 4.62 72.99 1.97 × 10−12 5.33 × 10−09 Eno3 −0.87 5.09 102.17 8.23 × 10−12 1.86 × 10−08 Arhgap36 −0.66 4.39 65.53 1.31 × 10−11 2.52 × 10−08 Crip1 −0.80 6.01 90.22 5.10 × 10−11 7.67 × 10−08 Serpina7 −1.35 1.41 57.90 1.01 × 10−10 1.37 × 10−07 Cyp2c68 −0.70 3.67 55.16 2.18 × 10−10 2.46 × 10−07 Cyp2c55 −0.76 3.80 59.18 1.68 × 10−09 1.62 × 10−06 Gm48702 −0.63 4.78 56.36 2.40 × 10−09 2.17 × 10−06 Lamc2 −0.61 3.87 44.17 5.71 × 10−09 4.16 × 10−06 Ttc36 −0.62 4.81 53.72 7.92 × 10−09 5.36 × 10−06 Spink4 −0.96 2.04 42.81 8.74 × 10−09 5.63 × 10−06 Gm36099 −0.88 2.50 40.98 1.57 × 10−08 8.49 × 10−06 Wnk2 −1.12 1.40 40.17 2.03 × 10−08 1.02 × 10−05 Pax8 −0.60 3.54 39.18 2.81 × 10−08 1.36 × 10−05 Fabp5 −0.59 3.65 38.58 3.42 × 10−08 1.60 × 10−05 Apol7a −0.79 3.63 44.62 9.38 × 10−08 3.73 × 10−05 Asgr2 −0.67 2.97 35.08 1.10 × 10−07 3.83 × 10−05 Apobec1 −0.64 3.72 33.59 1.84 × 10−07 5.40 × 10−05 Hsf2bp −0.59 2.95 29.47 7.90 × 10−07 1.77 × 10−04 X2010204K13Rik −0.93 1.34 29.44 7.97 × 10−07 1.77 × 10−04 Ifi27l2b −1.01 1.81 27.21 1.80 × 10−06 3.21 × 10−04 Tekt4 −0.64 2.77 27.16 1.84 × 10−06 3.23 × 10−04 Gm42603 −0.64 2.79 26.95 1.99 × 10−06 3.31 × 10−04 Orm1 −0.64 2.89 26.91 2.15 × 10−06 3.51 × 10−04 Gm6093 −0.98 0.97 26.61 2.26 × 10−06 3.60 × 10−04 B230322F03Rik −0.85 1.87 26.99 2.42 × 10−06 3.76 × 10−04 Sorbs3 −0.60 2.72 25.98 2.86 × 10−06 4.30 × 10−04 Apof −1.20 1.94 28.08 3.79 × 10−06 5.13 × 10−04 Dbn1 −0.80 1.48 24.21 5.62 × 10−06 6.93 × 10−04 Ltbp1 −0.63 2.51 23.44 7.56 × 10−06 8.05 × 10−04 Ltbp4 −0.69 3.09 28.57 1.05 × 10−05 9.60 × 10−04 Gm27184 −0.81 1.38 22.11 1.27 × 10−05 1.12 × 10−03 Gm13257 −0.64 2.44 20.64 2.46 × 10−05 1.76 × 10−03 Gm9905 −0.71 2.01 20.50 2.58 × 10−05 1.82 × 10−03 Plxnb3 −0.64 2.27 20.20 2.72 × 10−05 1.88 × 10−03 BC064078 −0.68 2.11 20.15 2.78 × 10−05 1.90 × 10−03 Muc5b −0.65 2.99 24.69 2.80 × 10−05 1.91 × 10−03 Fbp2 −0.59 2.34 19.76 3.26 × 10−05 2.11 × 10−03 Hrct1 −0.62 2.22 19.57 3.51 × 10−05 2.22 × 10−03 Pparg −0.68 1.76 19.52 3.59 × 10−05 2.26 × 10−03 Cym −0.84 1.13 19.44 3.72 × 10−05 2.31 × 10−03 Apoc2 −0.59 5.09 30.85 4.47 × 10−05 2.64 × 10−03 X2310040G24Rik −0.62 2.59 20.17 4.85 × 10−05 2.81 × 10−03 Gm8130 −0.69 2.30 20.20 5.59 × 10−05 3.06 × 10−03 A730090N16Rik −0.65 1.83 18.43 5.61 × 10−05 3.06 × 10−03 Gm47577 −0.75 1.38 18.38 5.73 × 10−05 3.10 × 10−03 Atp6v0a4 −0.65 1.71 18.13 6.36 × 10−05 3.33 × 10−03 Orm3 −0.73 1.71 18.03 6.64 × 10−05 3.42 × 10−03 Cbln3 −0.60 4.83 29.63 6.92 × 10−05 3.45 × 10−03 Tmprss6 −0.66 4.52 31.54 7.04 × 10−05 3.47 × 10−03 Cyp2c65 −0.75 1.27 17.59 7.99 × 10−05 3.77 × 10−03 X9130230N09Rik −0.71 1.56 17.34 8.84 × 10−05 3.97 × 10−03 Lmcd1 −0.65 1.88 16.64 1.19 × 10−04 4.74 × 10−03 Crb2 −0.73 1.28 16.47 1.28 × 10−04 4.95 × 10−03 Ifi204 −0.61 8.23 25.04 1.33 × 10−04 5.09 × 10−03 B430218F22Rik −0.84 1.78 19.46 1.42 × 10−04 5.33 × 10−03 Gm47528 −0.61 1.92 15.78 1.72 × 10−04 6.09 × 10−03 Viruses 2020, 12, x 5 of 180 X4930471E19Rik −0.67 1.49 15.53 1.92 × 10−04 6.53 × 10−03 Tmem236 −0.77 1.39 15.89 2.00 × 10−04 6.75 × 10−03 Gm28536 −0.64 2.05 15.98 2.06 × 10−04 6.88 × 10−03 Gm36033 −0.74 1.10 15.32 2.09 × 10−04 6.95 × 10−03 Gjb4 −0.73 1.81 16.86 2.10 × 10−04 6.95 × 10−03 Acnat2 −0.68 1.49 15.06 2.35 × 10−04 7.49 × 10−03 Pnmt −0.62 1.61 15.00 2.41 × 10−04 7.61 × 10−03 Dctd −0.68 1.32 14.80 2.63 × 10−04 8.14 × 10−03 Gm35853 −0.64 1.43 14.45 3.07 × 10−04 9.12 × 10−03 X1200007C13Rik −0.90 1.17 16.14 3.14 × 10−04 9.28 × 10−03 Hpx −0.90 7.37 33.48 3.21 × 10−04 9.39 × 10−03 Gm19935 −0.64 1.37 14.31 3.26 × 10−04 9.44 × 10−03 Hist1h1d 1.54 2.64 131.63 1.13 × 10−17 1.53 × 10−13 Mphosph9 0.59 4.27 48.07 2.94 × 10−09 2.48 × 10−06 Ckap2 1.10 1.93 45.74 5.84 × 10−09 4.16 × 10−06 Casc4 0.66 3.09 36.11 7.78 × 10−08 3.19 × 10−05 Cenpe 0.85 2.47 35.07 2.42 × 10−07 6.85 × 10−05 Pfn2 0.72 2.39 30.20 6.07 × 10−07 1.42 × 10−04 Gm15834 0.62 2.91 27.86 1.42 × 10−06 2.78 × 10−04 Gen1 0.93 1.17 26.68 2.20 × 10−06 3.54 × 10−04 Nanos1 0.75 2.04 26.35 2.49 × 10−06 3.83 × 10−04 Kif15 0.64 2.08 20.03 2.92 × 10−05 1.95 × 10−03 Gm47572 0.64 1.71 17.26 9.17 × 10−05 4.03 × 10−03 Mybl1 0.63 2.13 17.10 9.80 × 10−05 4.14 × 10−03 Gm16042 0.78 1.02 15.76 1.74 × 10−04 6.10 × 10−03 Egr1 1.69 6.12 36.88 2.74 × 10−04 8.35 × 10−03 Differentially expressed genes in DENV−infected cells compared to Untreated cells Gene logFC logCPM F PValue FDR Hsd17b4 −0.99 7.29 182.34 4.42 × 10−21 1.75 × 10−19 Gnmt −1.12 4.24 174.07 1.41 × 10−20 5.49 × 10−19 Pccb −0.96 5.56 171.55 2.04 × 10−20 7.80 × 10−19 Acot12 −1.42 3.35 180.86 2.30 × 10−20 8.75 × 10−19 Kifc2 −1.15 4.20 172.42 2.44 × 10−20 9.22 × 10−19 Acad11 −0.92 6.67 158.18 1.49 × 10−19 5.43 × 10−18 Uroc1 −1.45 2.97 155.33 2.31 × 10−19 8.28 × 10−18 Acaa1b −1.73 4.83 360.28 5.75 × 10−19 2.00 × 10−17 Mturn −1.30 6.76 251.67 1.07 × 10−18 3.69 × 10−17 Ackr4 −0.89 5.60 142.94 1.67 × 10−18 5.66 × 10−17 Aldh1a7 −1.08 8.45 179.39 2.56 × 10−18 8.59 × 10−17 Tpmt −1.17 4.45 184.21 1.17 × 10−17 3.82 × 10−16 mt.Tl1 −1.03 4.71 155.91 1.21 × 10−17 3.95 × 10−16 S100a13 −0.92 4.21 130.99 1.26 × 10−17 4.08 × 10−16 Epas1 −1.05 3.87 129.66 1.59 × 10−17 5.01 × 10−16 Hist2h2be −1.10 3.41 128.47 1.96 × 10−17 6.11 × 10−16 X4930486I03Rik −0.90 4.57 126.20 2.94 × 10−17 9.09 × 10−16 Cyp2c55 −1.40 3.80 194.10 3.33 × 10−17 1.03 × 10−15 Ces2a −0.96 4.22 126.24 3.70 × 10−17 1.13 × 10−15 Dbi −0.83 8.95 123.37 4.88 × 10−17 1.48 × 10−15 Mt1 −0.86 10.05 119.23 1.04 × 10−16 3.09 × 10−15 Uqcr11 −0.77 6.09 116.65 1.69 × 10−16 4.89 × 10−15 Eif4b −0.81 9.67 115.51 2.09 × 10−16 6.00 × 10−15 Ndufs2 −0.76 7.35 115.30 2.18 × 10−16 6.24 × 10−15 Mrpl34 −1.03 3.43 113.95 2.81 × 10−16 7.96 × 10−15 Tkfc −0.76 5.77 112.81 3.49 × 10−16 9.78 × 10−15 Klhl13 −0.86 4.35 112.39
Recommended publications
  • Responses of Bats to White-Nose Syndrome and Implications for Conservation
    University of New Hampshire University of New Hampshire Scholars' Repository Doctoral Dissertations Student Scholarship Spring 2020 Responses of Bats to White-Nose Syndrome and Implications for Conservation Meghan Stark University of New Hampshire, Durham Follow this and additional works at: https://scholars.unh.edu/dissertation Recommended Citation Stark, Meghan, "Responses of Bats to White-Nose Syndrome and Implications for Conservation" (2020). Doctoral Dissertations. 2518. https://scholars.unh.edu/dissertation/2518 This Dissertation is brought to you for free and open access by the Student Scholarship at University of New Hampshire Scholars' Repository. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of University of New Hampshire Scholars' Repository. For more information, please contact [email protected]. RESPONSES OF BATS TO WHITE-NOSE SYNDROME AND IMPLICATIONS FOR CONSERVATION BY MEGHAN A. STARK B.S., University of Alabama at Birmingham, 2013 DISSERTATION Submitted to the University of New Hampshire in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy In Genetics May 2020 i This dissertation was examined and approved in partial fulfillment of the requirements for the degree of Ph.D. in Genetics by: Dissertation Director, Matthew MacManes, Assoc. Prof. UNH MCBS Jeffrey T. Foster, Associate Professor, NAU PMI W. Kelley Thomas, Professor, UNH MCBS Rebecca Rowe, Associate Professor, UNH NREN Thomas Lee, Associate Professor Emeritus, UNH NREN On April 6, 2020 Approval signatures are on file with the University of New Hampshire Graduate School. ii DEDICATION I dedicate this work to all of the strong women in my life: Myra Michele Ange Heather Michelle Coons Kaitlyn Danielle Cagle Brindlee Michelle Coons Patricia Gail Miller Sarah Jean Lane “Here’s to strong women.
    [Show full text]
  • Universidade Estadual De Campinas Instituto De Biologia
    UNIVERSIDADE ESTADUAL DE CAMPINAS INSTITUTO DE BIOLOGIA VERÔNICA APARECIDA MONTEIRO SAIA CEREDA O PROTEOMA DO CORPO CALOSO DA ESQUIZOFRENIA THE PROTEOME OF THE CORPUS CALLOSUM IN SCHIZOPHRENIA CAMPINAS 2016 1 VERÔNICA APARECIDA MONTEIRO SAIA CEREDA O PROTEOMA DO CORPO CALOSO DA ESQUIZOFRENIA THE PROTEOME OF THE CORPUS CALLOSUM IN SCHIZOPHRENIA Dissertação apresentada ao Instituto de Biologia da Universidade Estadual de Campinas como parte dos requisitos exigidos para a obtenção do Título de Mestra em Biologia Funcional e Molecular na área de concentração de Bioquímica. Dissertation presented to the Institute of Biology of the University of Campinas in partial fulfillment of the requirements for the degree of Master in Functional and Molecular Biology, in the area of Biochemistry. ESTE ARQUIVO DIGITAL CORRESPONDE À VERSÃO FINAL DA DISSERTAÇÃO DEFENDIDA PELA ALUNA VERÔNICA APARECIDA MONTEIRO SAIA CEREDA E ORIENTADA PELO DANIEL MARTINS-DE-SOUZA. Orientador: Daniel Martins-de-Souza CAMPINAS 2016 2 Agência(s) de fomento e nº(s) de processo(s): CNPq, 151787/2F2014-0 Ficha catalográfica Universidade Estadual de Campinas Biblioteca do Instituto de Biologia Mara Janaina de Oliveira - CRB 8/6972 Saia-Cereda, Verônica Aparecida Monteiro, 1988- Sa21p O proteoma do corpo caloso da esquizofrenia / Verônica Aparecida Monteiro Saia Cereda. – Campinas, SP : [s.n.], 2016. Orientador: Daniel Martins de Souza. Dissertação (mestrado) – Universidade Estadual de Campinas, Instituto de Biologia. 1. Esquizofrenia. 2. Espectrometria de massas. 3. Corpo caloso.
    [Show full text]
  • 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.
    [Show full text]
  • The Role of the Mtor Pathway in Developmental Reprogramming Of
    THE ROLE OF THE MTOR PATHWAY IN DEVELOPMENTAL REPROGRAMMING OF HEPATIC LIPID METABOLISM AND THE HEPATIC TRANSCRIPTOME AFTER EXPOSURE TO 2,2',4,4'- TETRABROMODIPHENYL ETHER (BDE-47) An Honors Thesis Presented By JOSEPH PAUL MCGAUNN Approved as to style and content by: ________________________________________________________** Alexander Suvorov 05/18/20 10:40 ** Chair ________________________________________________________** Laura V Danai 05/18/20 10:51 ** Committee Member ________________________________________________________** Scott C Garman 05/18/20 10:57 ** Honors Program Director ABSTRACT An emerging hypothesis links the epidemic of metabolic diseases, such as non-alcoholic fatty liver disease (NAFLD) and diabetes with chemical exposures during development. Evidence from our lab and others suggests that developmental exposure to environmentally prevalent flame-retardant BDE47 may permanently reprogram hepatic lipid metabolism, resulting in an NAFLD-like phenotype. Additionally, we have demonstrated that BDE-47 alters the activity of both mTOR complexes (mTORC1 and 2) in hepatocytes. The mTOR pathway integrates environmental information from different signaling pathways, and regulates key cellular functions such as lipid metabolism, innate immunity, and ribosome biogenesis. Thus, we hypothesized that the developmental effects of BDE-47 on liver lipid metabolism are mTOR-dependent. To assess this, we generated mice with liver-specific deletions of mTORC1 or mTORC2 and exposed these mice and their respective controls perinatally to
    [Show full text]
  • 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.
    [Show full text]
  • 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.
    [Show full text]
  • Lysophosphatidic Acid Signaling in the Nervous System
    Neuron Review Lysophosphatidic Acid Signaling in the Nervous System Yun C. Yung,1,3 Nicole C. Stoddard,1,2,3 Hope Mirendil,1 and Jerold Chun1,* 1Molecular and Cellular Neuroscience Department, Dorris Neuroscience Center, The Scripps Research Institute, La Jolla, CA 92037, USA 2Biomedical Sciences Graduate Program, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA 3Co-first author *Correspondence: [email protected] http://dx.doi.org/10.1016/j.neuron.2015.01.009 The brain is composed of many lipids with varied forms that serve not only as structural components but also as essential signaling molecules. Lysophosphatidic acid (LPA) is an important bioactive lipid species that is part of the lysophospholipid (LP) family. LPA is primarily derived from membrane phospholipids and signals through six cognate G protein-coupled receptors (GPCRs), LPA1-6. These receptors are expressed on most cell types within central and peripheral nervous tissues and have been functionally linked to many neural pro- cesses and pathways. This Review covers a current understanding of LPA signaling in the nervous system, with particular focus on the relevance of LPA to both physiological and diseased states. Introduction LPA synthesis/degradative enzymes (reviewed in Sigal et al., The human brain is composed of approximately 60%–70% lipids 2005; Brindley and Pilquil, 2009; Perrakis and Moolenaar, by dry weight (Svennerholm et al., 1994). These lipids can be 2014). In view of the broad neurobiological influences of LPA divided into two major pools, structural and signaling, which signaling, its dysregulation may lead to diverse neuropathologies include well-known families such as cholesterol, fatty acids, ei- (Bandoh et al., 2000; Houben and Moolenaar, 2011; Yung et al., cosanoids, endocannabinoids, and prostaglandins (Figure 1).
    [Show full text]
  • Transcriptomic Analysis of Native Versus Cultured Human and Mouse Dorsal Root Ganglia Focused on Pharmacological Targets Short
    bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 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. Transcriptomic analysis of native versus cultured human and mouse dorsal root ganglia focused on pharmacological targets Short title: Comparative transcriptomics of acutely dissected versus cultured DRGs Andi Wangzhou1, Lisa A. McIlvried2, Candler Paige1, Paulino Barragan-Iglesias1, Carolyn A. Guzman1, Gregory Dussor1, Pradipta R. Ray1,#, Robert W. Gereau IV2, # and Theodore J. Price1, # 1The University of Texas at Dallas, School of Behavioral and Brain Sciences and Center for Advanced Pain Studies, 800 W Campbell Rd. Richardson, TX, 75080, USA 2Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine # corresponding authors [email protected], [email protected] and [email protected] Funding: NIH grants T32DA007261 (LM); NS065926 and NS102161 (TJP); NS106953 and NS042595 (RWG). The authors declare no conflicts of interest Author Contributions Conceived of the Project: PRR, RWG IV and TJP Performed Experiments: AW, LAM, CP, PB-I Supervised Experiments: GD, RWG IV, TJP Analyzed Data: AW, LAM, CP, CAG, PRR Supervised Bioinformatics Analysis: PRR Drew Figures: AW, PRR Wrote and Edited Manuscript: AW, LAM, CP, GD, PRR, RWG IV, TJP All authors approved the final version of the manuscript. 1 bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 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.
    [Show full text]
  • Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
    Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database.
    [Show full text]
  • Transcriptome Analyses of Tumor-Adjacent Somatic Tissues Reveal Genes Co-Expressed with Transposable Elements Nicky Chung1†, G
    Chung et al. Mobile DNA (2019) 10:39 https://doi.org/10.1186/s13100-019-0180-5 RESEARCH Open Access Transcriptome analyses of tumor-adjacent somatic tissues reveal genes co-expressed with transposable elements Nicky Chung1†, G. M. Jonaid1†, Sophia Quinton1†, Austin Ross1†, Corinne E. Sexton1, Adrian Alberto2, Cody Clymer2, Daphnie Churchill2, Omar Navarro Leija 2 and Mira V. Han1,3* Abstract Background: Despite the long-held assumption that transposons are normally only expressed in the germ-line, recent evidence shows that transcripts of transposable element (TE) sequences are frequently found in the somatic cells. However, the extent of variation in TE transcript levels across different tissues and different individuals are unknown, and the co-expression between TEs and host gene mRNAs have not been examined. Results: Here we report the variation in TE derived transcript levels across tissues and between individuals observed in the non-tumorous tissues collected for The Cancer Genome Atlas. We found core TE co-expression modules consisting mainly of transposons, showing correlated expression across broad classes of TEs. Despite this co-expression within tissues, there are individual TE loci that exhibit tissue-specific expression patterns, when compared across tissues. The core TE modules were negatively correlated with other gene modules that consisted of immune response genes in interferon signaling. KRAB Zinc Finger Proteins (KZFPs) were over-represented gene members of the TE modules, showing positive correlation across multiple tissues. But we did not find overlap between TE-KZFP pairs that are co-expressed and TE-KZFP pairs that are bound in published ChIP-seq studies.
    [Show full text]
  • CRL4-DCAF12 Ubiquitin Ligase Controls MOV10 RNA Helicase During Spermatogenesis and T Cell Activation
    International Journal of Molecular Sciences Article CRL4-DCAF12 Ubiquitin Ligase Controls MOV10 RNA Helicase during Spermatogenesis and T Cell Activation Tomas Lidak 1,2, Nikol Baloghova 1, Vladimir Korinek 1,3 , Radislav Sedlacek 4, Jana Balounova 4 , Petr Kasparek 4 and Lukas Cermak 1,* 1 Laboratory of Cancer Biology, Institute of Molecular Genetics of the Czech Academy of Sciences, 252 42 Vestec, Czech Republic; [email protected] (T.L.); [email protected] (N.B.); [email protected] (V.K.) 2 Faculty of Science, Charles University, 128 00 Prague, Czech Republic 3 Laboratory of Cell and Developmental Biology, Institute of Molecular Genetics of the Czech Academy of Sciences, 252 42 Vestec, Czech Republic 4 Czech Centre for Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, 252 50 Vestec, Czech Republic; [email protected] (R.S.); [email protected] (J.B.); [email protected] (P.K.) * Correspondence: [email protected] Abstract: Multisubunit cullin-RING ubiquitin ligase 4 (CRL4)-DCAF12 recognizes the C-terminal degron containing acidic amino acid residues. However, its physiological roles and substrates are largely unknown. Purification of CRL4-DCAF12 complexes revealed a wide range of potential substrates, including MOV10, an “ancient” RNA-induced silencing complex (RISC) complex RNA helicase. We show that DCAF12 controls the MOV10 protein level via its C-terminal motif in a Citation: Lidak, T.; Baloghova, N.; proteasome- and CRL-dependent manner. Next, we generated Dcaf12 knockout mice and demon- Korinek, V.; Sedlacek, R.; Balounova, strated that the DCAF12-mediated degradation of MOV10 is conserved in mice and humans.
    [Show full text]
  • Myopia in African Americans Is Significantly Linked to Chromosome 7P15.2-14.2
    Genetics Myopia in African Americans Is Significantly Linked to Chromosome 7p15.2-14.2 Claire L. Simpson,1,2,* Anthony M. Musolf,2,* Roberto Y. Cordero,1 Jennifer B. Cordero,1 Laura Portas,2 Federico Murgia,2 Deyana D. Lewis,2 Candace D. Middlebrooks,2 Elise B. Ciner,3 Joan E. Bailey-Wilson,1,† and Dwight Stambolian4,† 1Department of Genetics, Genomics and Informatics and Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, Tennessee, United States 2Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland, United States 3The Pennsylvania College of Optometry at Salus University, Elkins Park, Pennsylvania, United States 4Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, United States Correspondence: Joan E. PURPOSE. The purpose of this study was to perform genetic linkage analysis and associ- Bailey-Wilson, NIH/NHGRI, 333 ation analysis on exome genotyping from highly aggregated African American families Cassell Drive, Suite 1200, Baltimore, with nonpathogenic myopia. African Americans are a particularly understudied popula- MD 21131, USA; tion with respect to myopia. [email protected]. METHODS. One hundred six African American families from the Philadelphia area with a CLS and AMM contributed equally to family history of myopia were genotyped using an Illumina ExomePlus array and merged this work and should be considered co-first authors. with previous microsatellite data. Myopia was initially measured in mean spherical equiv- JEB-W and DS contributed equally alent (MSE) and converted to a binary phenotype where individuals were identified as to this work and should be affected, unaffected, or unknown.
    [Show full text]