Nuclear Localization of Newcastle Disease Virus Matrix Protein
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Chapter 7: Monogenic Forms of Diabetes
CHAPTER 7 MONOGENIC FORMS OF DIABETES Mark A. Sperling, MD, and Abhimanyu Garg, MD Dr. Mark A. Sperling is Emeritus Professor and Chair, University of Pittsburgh, Department of Pediatrics, Children’s Hospital of Pittsburgh of UPMC, Pittsburgh, PA. Dr. Abhimanyu Garg is Professor of Internal Medicine and Chief of the Division of Nutrition and Metabolic Diseases at University of Texas Southwestern Medical Center, Dallas, TX. SUMMARY Types 1 and 2 diabetes have multiple and complex genetic influences that interact with environmental triggers, such as viral infections or nutritional excesses, to result in their respective phenotypes: young, lean, and insulin-dependence for type 1 diabetes patients or older, overweight, and often manageable by lifestyle interventions and oral medications for type 2 diabetes patients. A small subset of patients, comprising ~2%–3% of all those diagnosed with diabetes, may have characteristics of either type 1 or type 2 diabetes but have single gene defects that interfere with insulin production, secretion, or action, resulting in clinical diabetes. These types of diabetes are known as MODY, originally defined as maturity-onset diabetes of youth, and severe early-onset forms, such as neonatal diabetes mellitus (NDM). Defects in genes involved in adipocyte development, differentiation, and death pathways cause lipodystrophy syndromes, which are also associated with insulin resistance and diabetes. Although these syndromes are considered rare, more awareness of these disorders and increased availability of genetic testing in clinical and research laboratories, as well as growing use of next generation, whole genome, or exome sequencing for clinically challenging phenotypes, are resulting in increased recognition. A correct diagnosis of MODY, NDM, or lipodystrophy syndromes has profound implications for treatment, genetic counseling, and prognosis. -
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. -
Evidence Revealing Deregulation of the KLF11-Mao a Pathway in Association with Chronic Stress and Depressive Disorders
Neuropsychopharmacology (2015) 40, 1373–1382 & 2015 American College of Neuropsychopharmacology. All rights reserved 0893-133X/15 www.neuropsychopharmacology.org Evidence Revealing Deregulation of The KLF11-Mao A Pathway in Association with Chronic Stress and Depressive Disorders 1 1 1,2 1 3 Sharonda Harris , Shakevia Johnson , Jeremy W Duncan , Chinelo Udemgba , Jeffrey H Meyer , Paul R Albert4, Gwen Lomberk5, Raul Urrutia5, Xiao-Ming Ou1, Craig A Stockmeier1,6 and Jun Ming Wang*,1,2,7 1 2 3 Department of Psychiatry and Human Behavior, Jackson, MS, USA; Program in Neuroscience, Jackson, MS, USA; Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; 4Ottawa Hospital Research Institute (Neuroscience), Ottawa, Ontario, Canada; 5Epigenetics and Chromatin Dynamics Laboratory, GI Research Unit, Mayo Clinic, Rochester, MN, 6 7 USA; Department of Psychiatry, Case Western Reserve University, Cleveland, OH, USA; Department of Pathology, University of Mississippi Medical Center, Jackson, MS, USA The biochemical pathways underlying major depressive disorder (MDD) and chronic stress are not well understood. However, it has been reported that monoamine oxidase A (MAO A, a major neurotransmitter-degrading enzyme) is significantly increased in the brains of human subjects affected with MDD and rats exposed to chronic social defeat (CSD) stress, which is used to model depression. In the current study, we compared the protein levels of a MAO A-transcriptional activator, Kruppel-like factor 11 (KLF11 , also recognized as transforming growth factor-beta-inducible early gene 2) between the brains of 18 human subjects with MDD and 18 control subjects. We found that, indeed, the expression of KLF11 is increased by 36% (po0.02) in the postmortem prefrontal cortex of human subjects with MDD compared with controls. -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1. -
The Unfolded Protein Response: an Overview
biology Review The Unfolded Protein Response: An Overview Adam Read 1,2 and Martin Schröder 1,2,* 1 Department of Biosciences, Durham University, South Road, Durham DH1 3LE, UK; [email protected] 2 Biophysical Sciences Institute, Durham University, South Road, Durham DH1 3LE, UK * Correspondence: [email protected]; Tel.: +44-191-334-1316 Simple Summary: The unfolded protein response (UPR) is the cells’ way of maintaining the balance of protein folding in the endoplasmic reticulum, which is the section of the cell designated for folding proteins with specific destinations such as other organelles or to be secreted by the cell. The UPR is activated when unfolded proteins accumulate in the endoplasmic reticulum. This accumulation puts a greater load on the molecules in charge of folding the proteins, and therefore the UPR works to balance this by lowering the number of unfolded proteins present in the cell. This is done in multiple ways, such as lowering the number of proteins that need to be folded; increasing the folding ability of the endoplasmic reticulum and by removing some of the unfolded proteins which take longer to fold. If the UPR is successful at reducing the number of unfolded proteins, the UPR is inactivated and the cells protein folding balance is returned to normal. However, if the UPR is unsuccessful, then this can lead to cell death. Abstract: The unfolded protein response is the mechanism by which cells control endoplasmic reticulum (ER) protein homeostasis. Under normal conditions, the UPR is not activated; however, under certain stresses, such as hypoxia or altered glycosylation, the UPR can be activated due to an accumulation of unfolded proteins. -
Combinatorial Bzip Dimers Display Complex DNA-Binding Specificity Landscapes
Combinatorial bZIP dimers display complex DNA-binding specificity landscapes The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Rodriguez-Martinez, Jose A et al. “Combinatorial bZIP Dimers Display Complex DNA-Binding Specificity Landscapes.” eLife 6 (2017): n. pag. As Published http://dx.doi.org/10.7554/eLife.19272 Publisher eLife Sciences Publications, Ltd. Version Final published version Citable link http://hdl.handle.net/1721.1/110147 Terms of Use Creative Commons Attribution 4.0 International License Detailed Terms http://creativecommons.org/licenses/by-nc/4.0/ RESEARCH ARTICLE Combinatorial bZIP dimers display complex DNA-binding specificity landscapes Jose´ A Rodrı´guez-Martı´nez1†, Aaron W Reinke2†, Devesh Bhimsaria1,3†, Amy E Keating2,4, Aseem Z Ansari1,5* 1Department of Biochemistry, University of Wisconsin-Madison, Madison, United States; 2Department of Biology, Massachusetts Institute of Technology, Cambridge, United States; 3Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Unites States; 4Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, United States; 5The Genome Center of Wisconsin, University of Wisconsin-Madison, Madison, United States Abstract How transcription factor dimerization impacts DNA-binding specificity is poorly understood. Guided by protein dimerization properties, we examined DNA binding specificities of 270 human bZIP pairs. DNA interactomes of 80 heterodimers and 22 homodimers revealed that 72% of heterodimer motifs correspond to conjoined half-sites preferred by partnering monomers. Remarkably, the remaining motifs are composed of variably-spaced half-sites (12%) or ‘emergent’ sites (16%) that cannot be readily inferred from half-site preferences of partnering monomers. -
Key Genes Regulating Skeletal Muscle Development and Growth in Farm Animals
animals Review Key Genes Regulating Skeletal Muscle Development and Growth in Farm Animals Mohammadreza Mohammadabadi 1 , Farhad Bordbar 1,* , Just Jensen 2 , Min Du 3 and Wei Guo 4 1 Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman 77951, Iran; [email protected] 2 Center for Quantitative Genetics and Genomics, Aarhus University, 8210 Aarhus, Denmark; [email protected] 3 Washington Center for Muscle Biology, Department of Animal Sciences, Washington State University, Pullman, WA 99163, USA; [email protected] 4 Muscle Biology and Animal Biologics, Animal and Dairy Science, University of Wisconsin-Madison, Madison, WI 53558, USA; [email protected] * Correspondence: [email protected] Simple Summary: Skeletal muscle mass is an important economic trait, and muscle development and growth is a crucial factor to supply enough meat for human consumption. Thus, understanding (candidate) genes regulating skeletal muscle development is crucial for understanding molecular genetic regulation of muscle growth and can be benefit the meat industry toward the goal of in- creasing meat yields. During the past years, significant progress has been made for understanding these mechanisms, and thus, we decided to write a comprehensive review covering regulators and (candidate) genes crucial for muscle development and growth in farm animals. Detection of these genes and factors increases our understanding of muscle growth and development and is a great help for breeders to satisfy demands for meat production on a global scale. Citation: Mohammadabadi, M.; Abstract: Farm-animal species play crucial roles in satisfying demands for meat on a global scale, Bordbar, F.; Jensen, J.; Du, M.; Guo, W. -
Ahn Supp. Fig. 1 AB 1.5 ARRDC4 1.5 ARRDC4 * * * 1.0 1.0
Ahn_Supp. Fig. 1 AB 1.5 ARRDC4 1.5 ARRDC4 * * * 1.0 1.0 * * 0.5 * 0.5 * * * Relative mRNA levels mRNA Relative Relative mRNA levels mRNA Relative 0.0 0.0 1.5 MLXIP (MondoA) 1.5 MLXIP (MondoA) 1.0 1.0 0.5 0.5 Relative mRNA levels mRNA Relative Relative mRNA levels mRNA Relative 0.0 0.0 MondoA MondoA 0124824 Starvation (6h) -++++++ Glucose Starvation (h) Refeeding (h) --0.51248 C 1.5 ARRDC4 1.5 MLXIP (MondoA) † Con # KD 1.0 1.0 0.5 0.5 * * * * Relative mRNA levels mRNA Relative Relative mRNA levels mRNA Relative * * 0.0 0.0 BasalStarvation Refeeding BasalStarvation Refeeding MondoA Con + + - - + + - - + + - - KD - - + + - - + + - - + + BasalStarvation Refeeding Supplemental Figure 1. Glucose-mediated regulation of ARRDC4 is dependent on MondoA in human skeletal myotubes. (A) (top) ARRDC4 and MLXIP (MondoA) mRNA levels were determined by qRT-PCR in human skeletal myotubes following deprivation of glucose at the indicated time (n=4). (bottom) Representative Western blot analysis of MondoA demonstrating the effect of glucose deprivation. *p<0.05 vs. 0h. (B) (top) ARRDC4 and MLXIP (MondoA) expression in human myotubes following a 6h glucose removal and refeeding at the times indicated (n=4). (bottom) Corresponding Western blot analysis. *p<0.05 vs Starvation 6h. (C) (top) Expression of ARRDC4 and MLXIP in human myotubes following deprivation and refeeding of glucose in the absence or presence of siRNA-mediated MondoA KD (n=4). (bottom) Corresponding Western blot analysis. *p<0.05 vs siControl. # p<0.05. § p<0.05. The data represents mean ± SD. All statistical significance determined by one-way ANOVA with Tukey multiple comparison post-hoc test. -
Open Chromatin Profiling in Adipose Tissue Marks Genomic Regions with Functional Roles in Cardiometabolic Traits
INVESTIGATION Open Chromatin Profiling in Adipose Tissue Marks Genomic Regions with Functional Roles in Cardiometabolic Traits Maren E. Cannon,*,1 Kevin W. Currin,*,1 Kristin L. Young,† Hannah J. Perrin,* Swarooparani Vadlamudi,* Alexias Safi,‡ Lingyun Song,‡ Ying Wu,* Martin Wabitsch,§ Markku Laakso,** Gregory E. Crawford,‡ and Karen L. Mohlke*,2 *Department of Genetics, †Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, ‡Department of Pediatrics, Division of Medical Genetics and Center for Genomic and Computational Biology, § Duke University, NC 27710, Department of Pediatrics and Adolescents Medicine, Division of Pediatric Endocrinology and Diabetes, University of Ulm, Germany 89081, and **Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland 70210 ORCID ID: 0000-0001-6721-153X (K.L.M.) ABSTRACT Identifying the regulatory mechanisms of genome-wide association study (GWAS) loci KEYWORDS affecting adipose tissue has been restricted due to limited characterization of adipose transcriptional chromatin regulatory elements. We profiled chromatin accessibility in three frozen human subcutaneous adipose accessibility tissue needle biopsies and preadipocytes and adipocytes from the Simpson Golabi-Behmel Syndrome adipose tissue (SGBS) cell strain using an assay for transposase-accessible chromatin (ATAC-seq). We identified preadipocytes 68,571 representative accessible chromatin regions (peaks) across adipose tissue samples (FDR , 5%). GWAS GWAS loci for eight cardiometabolic traits were enriched in these peaks (P , 0.005), with the strongest cardiometabolic enrichment for waist-hip ratio. Of 110 recently described cardiometabolic GWAS loci colocalized with trait adiposetissueeQTLs,59locihadoneormorevariantsoverlappinganadiposetissuepeak.Annotated variants at the SNX10 waist-hip ratio locus and the ATP2A1-SH2B1 body mass index locus showed allelic differences in regulatory assays. -
Distinct Roles of Jun : Fos and Jun : ATF Dimers in Oncogenesis
Oncogene (2001) 20, 2453 ± 2464 ã 2001 Nature Publishing Group All rights reserved 0950 ± 9232/01 $15.00 www.nature.com/onc Distinct roles of Jun : Fos and Jun : ATF dimers in oncogenesis Hans van Dam*,1 and Marc Castellazzi2 1Department of Molecular Cell Biology, Leiden University Medical Center, Sylvius Laboratories, PO Box 9503, 2300 RA Leiden, The Netherlands; 2Unite de Virologie Humaine, Institut National de la Sante et de la Recherche MeÂdicale (INSERM-U412), Ecole Normale SupeÂrieure, 46 alleÂe d'Italie, 69364 Lyon Cedex 07, France Jun : Fos and Jun : ATF complexes represent two classes dimers with emphasis on their roles in oncogenic of AP-1 dimers that (1) preferentially bind to either transformation in avian model systems. Previous heptameric or octameric AP-1 binding sites, and (2) are reviews on AP-1 and cell transformation include dierently regulated by cellular signaling pathways and references: (Angel and Karin, 1991; Wisdom, 1999; oncogene products. To discriminate between the func- Vogt, 1994; Karin et al., 1997; van Dam and van der tions of Jun : Fos, Jun: ATF and Jun : Jun, mutants were Eb, 1994; Hagmeyer et al., 1995). developed that restrict the ability of Jun to dimerize either to itself, or to Fos(-like) or ATF(-like) partners. Introduction of these mutants in chicken embryo Jun : Fos and Jun : ATF transcription factors: dimeric ®broblasts shows that Jun : Fra2 and Jun : ATF2 dimers complexes with variable composition and activities play distinct, complementary roles in in vitro oncogenesis by inducing either anchorage independence or growth AP-1 sub-units: members of the bZip protein family factor independence, respectively. -
Tgfβ-Regulated Gene Expression by Smads and Sp1/KLF-Like Transcription Factors in Cancer VOLKER ELLENRIEDER
ANTICANCER RESEARCH 28 : 1531-1540 (2008) Review TGFβ-regulated Gene Expression by Smads and Sp1/KLF-like Transcription Factors in Cancer VOLKER ELLENRIEDER Signal Transduction Laboratory, Internal Medicine, Department of Gastroenterology and Endocrinology, University of Marburg, Marburg, Germany Abstract. Transforming growth factor beta (TGF β) controls complex induces the canonical Smad signaling molecules which vital cellular functions through its ability to regulate gene then translocate into the nucleus to regulate transcription (2). The expression. TGFβ binding to its transmembrane receptor cellular response to TGF β can be extremely variable depending kinases initiates distinct intracellular signalling cascades on the cell type and the activation status of a cell at a given time. including the Smad signalling and transcription factors and also For instance, TGF β induces growth arrest and apoptosis in Smad-independent pathways. In normal epithelial cells, TGF β healthy epithelial cells, whereas it can also promote tumor stimulation induces a cytostatic program which includes the progression through stimulation of cell proliferation and the transcriptional repression of the c-Myc oncogene and the later induction of an epithelial-to-mesenchymal transition of tumor induction of the cell cycle inhibitors p15 INK4b and p21 Cip1 . cells (1, 3). In the last decade it has become clear that both the During carcinogenesis, however, many tumor cells lose their tumor suppressing and the tumor promoting functions of TGF β ability to respond to TGF β with growth inhibition, and instead, are primarily regulated on the level of gene expression through activate genes involved in cell proliferation, invasion and Smad-dependent and -independent mechanisms (1, 2, 4). -
Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7,