Blood Glucose Lowering Nuclear Receptor Agonists Only Partially Normalize Hepatic Gene Expression in Db/Db Mice
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Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
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. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Identification of Transcriptomic Differences Between Lower
International Journal of Molecular Sciences Article Identification of Transcriptomic Differences between Lower Extremities Arterial Disease, Abdominal Aortic Aneurysm and Chronic Venous Disease in Peripheral Blood Mononuclear Cells Specimens Daniel P. Zalewski 1,*,† , Karol P. Ruszel 2,†, Andrzej St˛epniewski 3, Dariusz Gałkowski 4, Jacek Bogucki 5 , Przemysław Kołodziej 6 , Jolanta Szyma ´nska 7 , Bartosz J. Płachno 8 , Tomasz Zubilewicz 9 , Marcin Feldo 9,‡ , Janusz Kocki 2,‡ and Anna Bogucka-Kocka 1,‡ 1 Chair and Department of Biology and Genetics, Medical University of Lublin, 4a Chod´zkiSt., 20-093 Lublin, Poland; [email protected] 2 Chair of Medical Genetics, Department of Clinical Genetics, Medical University of Lublin, 11 Radziwiłłowska St., 20-080 Lublin, Poland; [email protected] (K.P.R.); [email protected] (J.K.) 3 Ecotech Complex Analytical and Programme Centre for Advanced Environmentally Friendly Technologies, University of Marie Curie-Skłodowska, 39 Gł˛ebokaSt., 20-612 Lublin, Poland; [email protected] 4 Department of Pathology and Laboratory Medicine, Rutgers-Robert Wood Johnson Medical School, One Robert Wood Johnson Place, New Brunswick, NJ 08903-0019, USA; [email protected] 5 Chair and Department of Organic Chemistry, Medical University of Lublin, 4a Chod´zkiSt., Citation: Zalewski, D.P.; Ruszel, K.P.; 20-093 Lublin, Poland; [email protected] St˛epniewski,A.; Gałkowski, D.; 6 Laboratory of Diagnostic Parasitology, Chair and Department of Biology and Genetics, Medical University of Bogucki, J.; Kołodziej, P.; Szyma´nska, Lublin, 4a Chod´zkiSt., 20-093 Lublin, Poland; [email protected] J.; Płachno, B.J.; Zubilewicz, T.; Feldo, 7 Department of Integrated Paediatric Dentistry, Chair of Integrated Dentistry, Medical University of Lublin, M.; et al. -
Full Genome Sequencing of Archived Wild Type and Vaccine Rinderpest Virus Isolates Prior to Their Destruction Simon King1, Paulina Rajko-Nenow1, Honorata M
www.nature.com/scientificreports OPEN Full genome sequencing of archived wild type and vaccine rinderpest virus isolates prior to their destruction Simon King1, Paulina Rajko-Nenow1, Honorata M. Ropiak1, Paolo Ribeca1,2, Carrie Batten1 & Michael D. Baron1* When rinderpest virus (RPV) was declared eradicated in 2011, the only remaining samples of this once much-feared livestock virus were those held in various laboratories. In order to allow the destruction of our institute’s stocks of RPV while maintaining the ability to recover the various viruses if ever required, we have determined the full genome sequence of all our distinct samples of RPV, including 51 wild type viruses and examples of three diferent types of vaccine strain. Examination of the sequences of these virus isolates has shown that the African isolates form a single disparate clade, rather than two separate clades, which is more in accord with the known history of the virus in Africa. We have also identifed two groups of goat-passaged viruses which have acquired an extra 6 bases in the long untranslated region between the M and F protein coding sequences, and shown that, for more than half the genomes sequenced, translation of the F protein requires translational frameshift or non-standard translation initiation. Curiously, the clade containing the lapinised vaccine viruses that were developed originally in Korea appears to be more similar to the known African viruses than to any other Asian viruses. Rinderpest (RP) was one of the most severe diseases of cattle ever recorded, with high morbidity rates, and mor- tality rates of 80% to 90% in naïve populations. -
Prioritization of Metabolic Genes As Novel Therapeutic Targets in Estrogen-Receptor Negative Breast Tumors Using Multi-Omics Data and Text Mining
www.oncotarget.com Oncotarget, 2019, Vol. 10, (No. 39), pp: 3894-3909 Research Paper Prioritization of metabolic genes as novel therapeutic targets in estrogen-receptor negative breast tumors using multi-omics data and text mining Dinesh Kumar Barupal1,*, Bei Gao1,*, Jan Budczies2, Brett S. Phinney4, Bertrand Perroud4, Carsten Denkert2,3 and Oliver Fiehn1 1West Coast Metabolomics Center, University of California, Davis, CA, USA 2Institute of Pathology, Charité University Hospital, Berlin, Germany 3German Institute of Pathology, Philipps-University Marburg, Marburg, Germany 4UC Davis Genome Center, University of California, Davis, CA, USA *Co-first authors and contributed equally to this work Correspondence to: Oliver Fiehn, email: [email protected] Keywords: set-enrichment; ChemRICH; multi-omics; metabolic networks; candidate gene prioritization Received: March 12, 2019 Accepted: May 13, 2019 Published: June 11, 2019 Copyright: Barupal et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Estrogen-receptor negative (ERneg) breast cancer is an aggressive breast cancer subtype in the need for new therapeutic options. We have analyzed metabolomics, proteomics and transcriptomics data for a cohort of 276 breast tumors (MetaCancer study) and nine public transcriptomics datasets using univariate statistics, meta- analysis, Reactome pathway analysis, biochemical network mapping and text mining of metabolic genes. In the MetaCancer cohort, a total of 29% metabolites, 21% proteins and 33% transcripts were significantly different (raw p <0.05) between ERneg and ERpos breast tumors. -
The Microbiota-Produced N-Formyl Peptide Fmlf Promotes Obesity-Induced Glucose
Page 1 of 230 Diabetes Title: The microbiota-produced N-formyl peptide fMLF promotes obesity-induced glucose intolerance Joshua Wollam1, Matthew Riopel1, Yong-Jiang Xu1,2, Andrew M. F. Johnson1, Jachelle M. Ofrecio1, Wei Ying1, Dalila El Ouarrat1, Luisa S. Chan3, Andrew W. Han3, Nadir A. Mahmood3, Caitlin N. Ryan3, Yun Sok Lee1, Jeramie D. Watrous1,2, Mahendra D. Chordia4, Dongfeng Pan4, Mohit Jain1,2, Jerrold M. Olefsky1 * Affiliations: 1 Division of Endocrinology & Metabolism, Department of Medicine, University of California, San Diego, La Jolla, California, USA. 2 Department of Pharmacology, University of California, San Diego, La Jolla, California, USA. 3 Second Genome, Inc., South San Francisco, California, USA. 4 Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA. * Correspondence to: 858-534-2230, [email protected] Word Count: 4749 Figures: 6 Supplemental Figures: 11 Supplemental Tables: 5 1 Diabetes Publish Ahead of Print, published online April 22, 2019 Diabetes Page 2 of 230 ABSTRACT The composition of the gastrointestinal (GI) microbiota and associated metabolites changes dramatically with diet and the development of obesity. Although many correlations have been described, specific mechanistic links between these changes and glucose homeostasis remain to be defined. Here we show that blood and intestinal levels of the microbiota-produced N-formyl peptide, formyl-methionyl-leucyl-phenylalanine (fMLF), are elevated in high fat diet (HFD)- induced obese mice. Genetic or pharmacological inhibition of the N-formyl peptide receptor Fpr1 leads to increased insulin levels and improved glucose tolerance, dependent upon glucagon- like peptide-1 (GLP-1). Obese Fpr1-knockout (Fpr1-KO) mice also display an altered microbiome, exemplifying the dynamic relationship between host metabolism and microbiota. -
Prioritization of Metabolic Genes As Novel Therapeutic Targets
bioRxiv preprint doi: https://doi.org/10.1101/515403; this version posted January 9, 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. 1 Prioritization of metabolic genes as novel therapeutic targets 2 in estrogen-receptor negative breast tumors using multi-omics data and text mining 3 4 Dinesh Kumar Barupal#,1, Bei Gao#, 1, Jan Budczies2, Brett S. Phinney4, Bertrand Perroud4, 5 Carsten Denkert2,3 and Oliver Fiehn*,1 6 Affiliations 7 1West Coast Metabolomics Center, University of California, Davis, CA, 95616 8 2Institute of Pathology, Charité University Hospital, Berlin, 9 3German Institute of Pathology, Philipps-University Marburg, Germany 10 4UC Davis Genome Center, University of California, Davis, CA, 95616 11 #Co-first authors and contributed equally. 12 Email address for all authors 13 Dinesh Kumar Barupal: [email protected] 14 Bei Gao: [email protected] 15 Carsten Denkert: [email protected] 16 Brett S. Phinney: [email protected] 17 Bertrand Perroud: [email protected] 18 Jan Budczies: [email protected] 19 Oliver Fiehn: [email protected] 20 21 * Corresponding Author: 22 Oliver Fiehn 23 West Coast Metabolomics Center, 24 University of California, Davis, CA, 95616 25 Email: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/515403; this version posted January 9, 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. -
The DNA Sequence and Comparative Analysis of Human Chromosome 20
articles The DNA sequence and comparative analysis of human chromosome 20 P. Deloukas, L. H. Matthews, J. Ashurst, J. Burton, J. G. R. Gilbert, M. Jones, G. Stavrides, J. P. Almeida, A. K. Babbage, C. L. Bagguley, J. Bailey, K. F. Barlow, K. N. Bates, L. M. Beard, D. M. Beare, O. P. Beasley, C. P. Bird, S. E. Blakey, A. M. Bridgeman, A. J. Brown, D. Buck, W. Burrill, A. P. Butler, C. Carder, N. P. Carter, J. C. Chapman, M. Clamp, G. Clark, L. N. Clark, S. Y. Clark, C. M. Clee, S. Clegg, V. E. Cobley, R. E. Collier, R. Connor, N. R. Corby, A. Coulson, G. J. Coville, R. Deadman, P. Dhami, M. Dunn, A. G. Ellington, J. A. Frankland, A. Fraser, L. French, P. Garner, D. V. Grafham, C. Grif®ths, M. N. D. Grif®ths, R. Gwilliam, R. E. Hall, S. Hammond, J. L. Harley, P. D. Heath, S. Ho, J. L. Holden, P. J. Howden, E. Huckle, A. R. Hunt, S. E. Hunt, K. Jekosch, C. M. Johnson, D. Johnson, M. P. Kay, A. M. Kimberley, A. King, A. Knights, G. K. Laird, S. Lawlor, M. H. Lehvaslaiho, M. Leversha, C. Lloyd, D. M. Lloyd, J. D. Lovell, V. L. Marsh, S. L. Martin, L. J. McConnachie, K. McLay, A. A. McMurray, S. Milne, D. Mistry, M. J. F. Moore, J. C. Mullikin, T. Nickerson, K. Oliver, A. Parker, R. Patel, T. A. V. Pearce, A. I. Peck, B. J. C. T. Phillimore, S. R. Prathalingam, R. W. Plumb, H. Ramsay, C. M. -
Identification of Novel RNA Polymerase II CTD Interaction Sites
Identification of novel RNA Polymerase II CTD interaction sites on the mRNA Capping Enzyme Marcus G. Bage1,2*, Rajaei Almohammed2, Victoria H. Cowling2, Andrei V. Pisliakov1,3* 1Computational Biology, School of Life Sciences 2Centre for Gene Regulation and Expression, School of Life Sciences 3Physics, School of Science and Engineering, University of Dundee, Dundee, DD1 5EH, UK *Corresponding authors Tel: +44 1382 388758; Email: [email protected] Correspondence may also be addressed to Marcus G. Bage. Email: [email protected] Supplementary Data: • 1 Supplementary Table • 11 Supplementary Figures • 3 Supplementary Movies • Representative snapshots (in a PDB format) for each simulation system 1 Table S1. Summary of the molecular dynamics simulations performed in this work CE GTase CTD cMD aMD 1 human - 3x 200 ns 3x 200 ns 2 PBCV-1 - 3x 200 ns - 3 human 1 heptad, pSer5 and pSer2 3x 200 ns 3x 200 ns 4 human 4 heptads, unphos, extended from N-ter 3x 200 ns 3x 200 ns 5 human 4 heptads, unphos, extended from C-ter 3x 200 ns 3x 200 ns 6 human 4 heptads, pSer5, extended from N-ter 3x 200 ns 3x 200 ns 7 human 4 heptads, pSer5, extended from C-ter 3x 200 ns 3x 200 ns 8 human 4 heptads, pSer2, extended from N-ter 3x 200 ns 3x 200 ns 2 9 human 4 heptads, pSer2, extended from C-ter 3x 200 ns 3x 200 ns 10 human ~2.5 heptads, pSer5, in C. albicans conform. 3x 200 ns 3x 200 ns 11 human 4 heptads, pSer5, from C. -
Purification and Analysis of Endogenous Human RNA Exosome Complexes
Downloaded from rnajournal.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press METHOD Purification and analysis of endogenous human RNA exosome complexes MICHAL DOMANSKI,1,2,7 PAULA UPLA,1,3 WILLIAM J. RICE,4 KELLY R. MOLLOY,5 NATALIA E. KETAREN,1 DAVID L. STOKES,3 TORBEN HEICK JENSEN,2 MICHAEL P. ROUT,1 and JOHN LACAVA1,6 1Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, New York 10065, USA 2Centre for mRNP Biogenesis and Metabolism, Department of Molecular Biology and Genetics, Aarhus University, 8000 Aarhus C, Denmark 3Skirball Institute and Department of Cell Biology, New York University School of Medicine, New York, New York 10016, USA 4Simons Electron Microscopy Center at New York Structural Biology Center, New York, New York 10027, USA 5Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, New York, New York 10065, USA 6Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, New York 10016, USA ABSTRACT As a result of its importance in key RNA metabolic processes, the ribonucleolytic RNA exosome complex has been the focus of intense study for almost two decades. Research on exosome subunit assembly, cofactor and substrate interaction, enzymatic catalysis and structure have largely been conducted using complexes produced in the yeast Saccharomyces cerevisiae or in bacteria. Here, we examine different populations of endogenous exosomes from human embryonic kidney (HEK) 293 cells and test their enzymatic activity and structural integrity. We describe methods to prepare EXOSC10-containing, enzymatically active endogenous human exosomes at suitable yield and purity for in vitro biochemistry and negative stain transmission electron microscopy. -
Spatial Sorting Enables Comprehensive Characterization of Liver Zonation
ARTICLES https://doi.org/10.1038/s42255-019-0109-9 Spatial sorting enables comprehensive characterization of liver zonation Shani Ben-Moshe1,3, Yonatan Shapira1,3, Andreas E. Moor 1,2, Rita Manco1, Tamar Veg1, Keren Bahar Halpern1 and Shalev Itzkovitz 1* The mammalian liver is composed of repeating hexagonal units termed lobules. Spatially resolved single-cell transcriptomics has revealed that about half of hepatocyte genes are differentially expressed across the lobule, yet technical limitations have impeded reconstructing similar global spatial maps of other hepatocyte features. Here, we show how zonated surface markers can be used to sort hepatocytes from defined lobule zones with high spatial resolution. We apply transcriptomics, microRNA (miRNA) array measurements and mass spectrometry proteomics to reconstruct spatial atlases of multiple zon- ated features. We demonstrate that protein zonation largely overlaps with messenger RNA zonation, with the periportal HNF4α as an exception. We identify zonation of miRNAs, such as miR-122, and inverse zonation of miRNAs and their hepa- tocyte target genes, highlighting potential regulation of gene expression levels through zonated mRNA degradation. Among the targets, we find the pericentral Wingless-related integration site (Wnt) receptors Fzd7 and Fzd8 and the periportal Wnt inhibitors Tcf7l1 and Ctnnbip1. Our approach facilitates reconstructing spatial atlases of multiple cellular features in the liver and other structured tissues. he mammalian liver is a structured organ, consisting of measurements would broaden our understanding of the regulation repeating hexagonally shaped units termed ‘lobules’ (Fig. 1a). of liver zonation and could be used to model liver metabolic func- In mice, each lobule consists of around 9–12 concentric lay- tion more precisely.