Cyclin K Interacts with Β-Catenin to Induce Cyclin D1 Expression And
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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. -
Are Expressed by a Majority of Primary Human Acute Myeloid Leukemia Cells and Inducibility of the TLR Signaling Pathway Is Associated with a More Favorable Phenotype
Cancers 2019, 11 S1 of S19 Supplementary Material Functional Toll-Like Receptors (TLRs) are Expressed by a Majority of Primary Human Acute Myeloid Leukemia Cells and Inducibility of the TLR Signaling Pathway is Associated with a More Favorable Phenotype Annette K. Brenner and Øystein Bruserud Table S1. Median concentration increase in the secretion of 19 (16 patients with G-CSF, 67 patients with GM-CSF) soluble mediators as a result of targeting with four different TLR agonists. More than 5-fold increase is highlighted. LPS (TLR4) Flagellin (TLR5) R848 (TLR7/8) Pam3CSK4 (TLR1/2) IL-6 301.0 45.9 10.2 5.3 TNFα 188.7 10.6 5.0 1.5 IL-1β 89.7 9.2 1.1 1.5 CCL3 56.4 6.0 2.4 1.5 CCL2 52.6 9.4 4.3 2.8 G-CSF 51.9 2.7 1.0 1.0 CXCL1 38.0 5.8 1.4 1.5 CCL4 17.2 3.3 2.0 1.3 CCL5 14.5 2.1 1.3 1.1 MMP-1 11.1 3.4 1.4 1.1 CXCL5 8.3 4.3 1.3 1.4 CXCL8 6.0 4.3 1.7 1.3 GM-CSF 5.2 1.5 1.4 1.0 MMP-2 4.0 1.5 1.2 1.1 CXCL10 3.9 1.6 2.2 1.1 HGF 2.0 1.1 1.0 1.0 MMP-9 1.9 2.5 1.3 1.7 IL-1RA 1.8 1.3 1.3 1.0 Serpin E1 1.3 1.3 1.1 1.1 Cystatin C 1.1 1.1 1.0 1.0 Cancers 2019, 11 S2 of S19 Table S2. -
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). -
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Supplementary Figure S1. Results of flow cytometry analysis, performed to estimate CD34 positivity, after immunomagnetic separation in two different experiments. As monoclonal antibody for labeling the sample, the fluorescein isothiocyanate (FITC)- conjugated mouse anti-human CD34 MoAb (Mylteni) was used. Briefly, cell samples were incubated in the presence of the indicated MoAbs, at the proper dilution, in PBS containing 5% FCS and 1% Fc receptor (FcR) blocking reagent (Miltenyi) for 30 min at 4 C. Cells were then washed twice, resuspended with PBS and analyzed by a Coulter Epics XL (Coulter Electronics Inc., Hialeah, FL, USA) flow cytometer. only use Non-commercial 1 Supplementary Table S1. Complete list of the datasets used in this study and their sources. GEO Total samples Geo selected GEO accession of used Platform Reference series in series samples samples GSM142565 GSM142566 GSM142567 GSM142568 GSE6146 HG-U133A 14 8 - GSM142569 GSM142571 GSM142572 GSM142574 GSM51391 GSM51392 GSE2666 HG-U133A 36 4 1 GSM51393 GSM51394 only GSM321583 GSE12803 HG-U133A 20 3 GSM321584 2 GSM321585 use Promyelocytes_1 Promyelocytes_2 Promyelocytes_3 Promyelocytes_4 HG-U133A 8 8 3 GSE64282 Promyelocytes_5 Promyelocytes_6 Promyelocytes_7 Promyelocytes_8 Non-commercial 2 Supplementary Table S2. Chromosomal regions up-regulated in CD34+ samples as identified by the LAP procedure with the two-class statistics coded in the PREDA R package and an FDR threshold of 0.5. Functional enrichment analysis has been performed using DAVID (http://david.abcc.ncifcrf.gov/) -
Cytotoxic Effects and Changes in Gene Expression Profile
Toxicology in Vitro 34 (2016) 309–320 Contents lists available at ScienceDirect Toxicology in Vitro journal homepage: www.elsevier.com/locate/toxinvit Fusarium mycotoxin enniatin B: Cytotoxic effects and changes in gene expression profile Martina Jonsson a,⁎,MarikaJestoib, Minna Anthoni a, Annikki Welling a, Iida Loivamaa a, Ville Hallikainen c, Matti Kankainen d, Erik Lysøe e, Pertti Koivisto a, Kimmo Peltonen a,f a Chemistry and Toxicology Research Unit, Finnish Food Safety Authority (Evira), Mustialankatu 3, FI-00790 Helsinki, Finland b Product Safety Unit, Finnish Food Safety Authority (Evira), Mustialankatu 3, FI-00790 Helsinki, c The Finnish Forest Research Institute, Rovaniemi Unit, P.O. Box 16, FI-96301 Rovaniemi, Finland d Institute for Molecular Medicine Finland (FIMM), University of Helsinki, P.O. Box 20, FI-00014, Finland e Plant Health and Biotechnology, Norwegian Institute of Bioeconomy, Høyskoleveien 7, NO -1430 Ås, Norway f Finnish Safety and Chemicals Agency (Tukes), Opastinsilta 12 B, FI-00521 Helsinki, Finland article info abstract Article history: The mycotoxin enniatin B, a cyclic hexadepsipeptide produced by the plant pathogen Fusarium,isprevalentin Received 3 December 2015 grains and grain-based products in different geographical areas. Although enniatins have not been associated Received in revised form 5 April 2016 with toxic outbreaks, they have caused toxicity in vitro in several cell lines. In this study, the cytotoxic effects Accepted 28 April 2016 of enniatin B were assessed in relation to cellular energy metabolism, cell proliferation, and the induction of ap- Available online 6 May 2016 optosis in Balb 3T3 and HepG2 cells. The mechanism of toxicity was examined by means of whole genome ex- fi Keywords: pression pro ling of exposed rat primary hepatocytes. -
Supp Table 1.Pdf
Upregulated genes in Hdac8 null cranial neural crest cells fold change Gene Symbol Gene Title 134.39 Stmn4 stathmin-like 4 46.05 Lhx1 LIM homeobox protein 1 31.45 Lect2 leukocyte cell-derived chemotaxin 2 31.09 Zfp108 zinc finger protein 108 27.74 0710007G10Rik RIKEN cDNA 0710007G10 gene 26.31 1700019O17Rik RIKEN cDNA 1700019O17 gene 25.72 Cyb561 Cytochrome b-561 25.35 Tsc22d1 TSC22 domain family, member 1 25.27 4921513I08Rik RIKEN cDNA 4921513I08 gene 24.58 Ofa oncofetal antigen 24.47 B230112I24Rik RIKEN cDNA B230112I24 gene 23.86 Uty ubiquitously transcribed tetratricopeptide repeat gene, Y chromosome 22.84 D8Ertd268e DNA segment, Chr 8, ERATO Doi 268, expressed 19.78 Dag1 Dystroglycan 1 19.74 Pkn1 protein kinase N1 18.64 Cts8 cathepsin 8 18.23 1500012D20Rik RIKEN cDNA 1500012D20 gene 18.09 Slc43a2 solute carrier family 43, member 2 17.17 Pcm1 Pericentriolar material 1 17.17 Prg2 proteoglycan 2, bone marrow 17.11 LOC671579 hypothetical protein LOC671579 17.11 Slco1a5 solute carrier organic anion transporter family, member 1a5 17.02 Fbxl7 F-box and leucine-rich repeat protein 7 17.02 Kcns2 K+ voltage-gated channel, subfamily S, 2 16.93 AW493845 Expressed sequence AW493845 16.12 1600014K23Rik RIKEN cDNA 1600014K23 gene 15.71 Cst8 cystatin 8 (cystatin-related epididymal spermatogenic) 15.68 4922502D21Rik RIKEN cDNA 4922502D21 gene 15.32 2810011L19Rik RIKEN cDNA 2810011L19 gene 15.08 Btbd9 BTB (POZ) domain containing 9 14.77 Hoxa11os homeo box A11, opposite strand transcript 14.74 Obp1a odorant binding protein Ia 14.72 ORF28 open reading -
Human Cyclin-Dependent Kinase 12 (CDK12), Kinase Domain a Target Enabling Package (TEP)
Human Cyclin-Dependent Kinase 12 (CDK12), Kinase Domain A Target Enabling Package (TEP) Gene ID / UniProt ID / EC CDK12, 51755 / Q9NYV4/ 2.7.11.22, 2.7.11.23 CCNK, 8812 / O75909/ - Target Nominator Gregg Morin (UBC, Canada), Nathanael Gray (Harvard) SGC Authors Sarah E. Dixon-Clarke, Jonathan M. Elkins, Nathanael S. Gray, and Alex N. Bullock Collaborating Authors S.-W. Grace Cheng1, Tinghu Zhang2, Nicholas Kwiatkowski3, Calla M. Olson2, Brian J. Abraham3, Ann K. Greifenberg4, Scott B. Ficarro2, Yanke Liang2, Nancy M. Hannett3, Theresa Manz5, Mingfeng Hao2, Bartlomiej Bartkowiak6, Arno L. Greenleaf6, Jarrod A. Marto2, Matthias Geyer4, Richard A. Young3, and Gregg B. Morin1 Target PI Alex Bullock (SGC Oxford) Therapeutic Area(s) Oncology Disease Relevance CDK12 loss sensitises cancer cells to DNA damage Date approved by TEP 17th June 2016 Evaluation Group Document version Version 3 Document version date April 2018 DOI https://doi.org/10.5281/zenodo.1219680 Affiliations 1. Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency 2. Department of Cancer Biology, Dana-Farber Cancer Institute 3. Whitehead Institute for Biomedical Research 4. Department of Structural Immunology, Institute of Innate Immunity 5. Pharmaceutical and Medicinal Chemistry, Saarland University 6. Department of Biochemistry, Duke University Medical Center USEFUL LINKS (Please note that the inclusion of links to external sites should not be taken as an endorsement of that site by the SGC in any way) SUMMARY OF PROJECT Cyclin-dependent kinase 12 (CDK12) phosphorylates RNA Pol II C-terminal domain (CTD) to promote transcriptional elongation of large DNA damage response genes. CDK12 is frequently mutated or amplified in cancer and its loss sensitises cells to DNA damage. -
G Protein-Coupled Receptors
G PROTEIN-COUPLED RECEPTORS Overview:- The completion of the Human Genome Project allowed the identification of a large family of proteins with a common motif of seven groups of 20-24 hydrophobic amino acids arranged as α-helices. Approximately 800 of these seven transmembrane (7TM) receptors have been identified of which over 300 are non-olfactory receptors (see Frederikson et al., 2003; Lagerstrom and Schioth, 2008). Subdivision on the basis of sequence homology allows the definition of rhodopsin, secretin, adhesion, glutamate and Frizzled receptor families. NC-IUPHAR recognizes Classes A, B, and C, which equate to the rhodopsin, secretin, and glutamate receptor families. The nomenclature of 7TM receptors is commonly used interchangeably with G protein-coupled receptors (GPCR), although the former nomenclature recognises signalling of 7TM receptors through pathways not involving G proteins. For example, adiponectin and membrane progestin receptors have some sequence homology to 7TM receptors but signal independently of G-proteins and appear to reside in membranes in an inverted fashion compared to conventional GPCR. Additionally, the NPR-C natriuretic peptide receptor has a single transmembrane domain structure, but appears to couple to G proteins to generate cellular responses. The 300+ non-olfactory GPCR are the targets for the majority of drugs in clinical usage (Overington et al., 2006), although only a minority of these receptors are exploited therapeutically. Signalling through GPCR is enacted by the activation of heterotrimeric GTP-binding proteins (G proteins), made up of α, β and γ subunits, where the α and βγ subunits are responsible for signalling. The α subunit (tabulated below) allows definition of one series of signalling cascades and allows grouping of GPCRs to suggest common cellular, tissue and behavioural responses. -
Transcriptome Analysis of Human Diabetic Kidney Disease
ORIGINAL ARTICLE Transcriptome Analysis of Human Diabetic Kidney Disease Karolina I. Woroniecka,1 Ae Seo Deok Park,1 Davoud Mohtat,2 David B. Thomas,3 James M. Pullman,4 and Katalin Susztak1,5 OBJECTIVE—Diabetic kidney disease (DKD) is the single cases, mild and then moderate mesangial expansion can be leading cause of kidney failure in the U.S., for which a cure has observed. In general, diabetic kidney disease (DKD) is not yet been found. The aim of our study was to provide an considered a nonimmune-mediated degenerative disease unbiased catalog of gene-expression changes in human diabetic of the glomerulus; however, it has long been noted that kidney biopsy samples. complement and immunoglobulins sometimes can be de- — tected in diseased glomeruli, although their role and sig- RESEARCH DESIGN AND METHODS Affymetrix expression fi arrays were used to identify differentially regulated transcripts in ni cance is not clear (4). 44 microdissected human kidney samples. The DKD samples were The understanding of DKD has been challenged by multi- significant for their racial diversity and decreased glomerular ple issues. First, the diagnosis of DKD usually is made using filtration rate (~20–30 mL/min). Stringent statistical analysis, using clinical criteria, and kidney biopsy often is not performed. the Benjamini-Hochberg corrected two-tailed t test, was used to According to current clinical practice, the development of identify differentially expressed transcripts in control and diseased albuminuria in patients with diabetes is sufficient to make the glomeruli and tubuli. Two different Web-based algorithms were fi diagnosis of DKD (5). We do not understand the correlation used to de ne differentially regulated pathways. -
Multi-Functionality of Proteins Involved in GPCR and G Protein Signaling: Making Sense of Structure–Function Continuum with In
Cellular and Molecular Life Sciences (2019) 76:4461–4492 https://doi.org/10.1007/s00018-019-03276-1 Cellular andMolecular Life Sciences REVIEW Multi‑functionality of proteins involved in GPCR and G protein signaling: making sense of structure–function continuum with intrinsic disorder‑based proteoforms Alexander V. Fonin1 · April L. Darling2 · Irina M. Kuznetsova1 · Konstantin K. Turoverov1,3 · Vladimir N. Uversky2,4 Received: 5 August 2019 / Revised: 5 August 2019 / Accepted: 12 August 2019 / Published online: 19 August 2019 © Springer Nature Switzerland AG 2019 Abstract GPCR–G protein signaling system recognizes a multitude of extracellular ligands and triggers a variety of intracellular signal- ing cascades in response. In humans, this system includes more than 800 various GPCRs and a large set of heterotrimeric G proteins. Complexity of this system goes far beyond a multitude of pair-wise ligand–GPCR and GPCR–G protein interactions. In fact, one GPCR can recognize more than one extracellular signal and interact with more than one G protein. Furthermore, one ligand can activate more than one GPCR, and multiple GPCRs can couple to the same G protein. This defnes an intricate multifunctionality of this important signaling system. Here, we show that the multifunctionality of GPCR–G protein system represents an illustrative example of the protein structure–function continuum, where structures of the involved proteins represent a complex mosaic of diferently folded regions (foldons, non-foldons, unfoldons, semi-foldons, and inducible foldons). The functionality of resulting highly dynamic conformational ensembles is fne-tuned by various post-translational modifcations and alternative splicing, and such ensembles can undergo dramatic changes at interaction with their specifc partners. -
Convergent Molecular, Cellular, and Cortical Neuroimaging Signatures of Major Depressive Disorder
Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder Kevin M. Andersona,1, Meghan A. Collinsa, Ru Kongb,c,d,e,f, Kacey Fanga, Jingwei Lib,c,d,e,f, Tong Heb,c,d,e,f, Adam M. Chekroudg,h, B. T. Thomas Yeob,c,d,e,f,i, and Avram J. Holmesa,g,j aDepartment of Psychology, Yale University, New Haven, CT 06520; bDepartment of Electrical and Computer Engineering, National University of Singapore, Singapore; cCentre for Sleep and Cognition, National University of Singapore, Singapore; dClinical Imaging Research Centre, National University of Singapore, Singapore; eN.1 Institute for Health, National University of Singapore, Singapore; fInstitute for Digital Medicine, National University of Singapore, Singapore; gDepartment of Psychiatry, Yale University, New Haven, CT 06520; hSpring Health, New York, NY 10001; iGraduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore; and jDepartment of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 Edited by Huda Akil, University of Michigan, Ann Arbor, MI, and approved August 12, 2020 (received for review May 5, 2020) Major depressive disorder emerges from the complex interactions detail. To date, there have been few opportunities to directly of biological systems that span genes and molecules through cells, explore the depressive phenotype across levels of analysis—from networks, and behavior. Establishing how neurobiological pro- genes and molecules through cells, circuits, networks, and cesses coalesce to contribute to depression requires a multiscale behavior—simultaneously (14). approach, encompassing measures of brain structure and function In vivo neuroimaging has identified depression-related corre- as well as genetic and cell-specific transcriptional data. -
Human Cyclin-Dependent Kinase 12 (CDK12), Kinase Domain a Target Enabling Package (TEP)
Human Cyclin-Dependent Kinase 12 (CDK12), Kinase Domain A Target Enabling Package (TEP) Gene ID / UniProt ID / EC CDK12, 51755 / Q9NYV4/ 2.7.11.22, 2.7.11.23 CCNK, 8812 / O75909/ - Target Nominator Gregg Morin (UBC, Canada), Nathanael Gray (Harvard) SGC Authors Sarah E. Dixon-Clarke, Jonathan M. Elkins, and Alex N. Bullock Collaborating Authors S.-W. Grace Cheng1, Tinghu Zhang2, Nicholas Kwiatkowski3, Calla M. Olson2, Brian J. Abraham3, Ann K. Greifenberg4, Scott B. Ficarro2, Yanke Liang2, Nancy M. Hannett3, Theresa Manz5, Mingfeng Hao2, Bartlomiej Bartkowiak6, Arno L. Greenleaf6, Jarrod A. Marto2, Matthias Geyer4, Richard A. Young3, Gregg B. Morin1 and Nathanael S. Gray2 Target PI Alex Bullock (SGC Oxford) Therapeutic Area(s) Oncology Disease Relevance CDK12 loss sensitises cancer cells to DNA damage Date approved by TEP 17th June 2016 Evaluation Group Document version Version 9 Document version date March 3rd 2021 Citation Sarah E. Dixon-Clarke, Jonathan M. Elkins, S.-W. Grace Cheng, Tinghu Zhang, Nicholas Kwiatkowski, Calla M. Olson, Brian J. Abraham, Ann K. Greifenberg, Scott B. Ficarro, Yanke Liang, Nancy M. Hannett, Theresa Manz, Mingfeng Hao, Bartlomiej Bartkowiak, Arno L. Greenleaf, Jarrod A. Marto, Matthias Geyer, Richard A. Young, Gregg B. Morin, Nathanael S. Gray and Alex N. Bullock. (2016) Human Cyclin-dependent kinase 12 (CDK12), kinase domain; A Target Enabling Package. 10.5281/zenodo.1219680. Affiliations 1. Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency; 2. Department of Cancer Biology, Dana-Farber Cancer Institute; 3. Whitehead Institute for Biomedical Research; 4. Department of Structural Immunology, Institute of Innate Immunity; 5. Pharmaceutical and Medicinal Chemistry, Saarland University; 6.