Investigation of LDHA and COPB1 As Candidate Genes for Muscle Development in the MYOD1 Region of Pig Chromosome 2
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Diagnosing Platelet Secretion Disorders: Examples Cases
Diagnosing platelet secretion disorders: examples cases Martina Daly Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield Disclosures for Martina Daly In compliance with COI policy, ISTH requires the following disclosures to the session audience: Research Support/P.I. No relevant conflicts of interest to declare Employee No relevant conflicts of interest to declare Consultant No relevant conflicts of interest to declare Major Stockholder No relevant conflicts of interest to declare Speakers Bureau No relevant conflicts of interest to declare Honoraria No relevant conflicts of interest to declare Scientific Advisory No relevant conflicts of interest to declare Board Platelet granule release Agonists (FIIa, Collagen, ADP) Signals Activation Shape change Membrane fusion Release of granule contents Platelet storage organelles lysosomes a granules Enzymes including cathepsins Adhesive proteins acid hydrolases Clotting factors and their inhibitors Fibrinolytic factors and their inhibitors Proteases and antiproteases Growth and mitogenic factors Chemokines, cytokines Anti-microbial proteins Membrane glycoproteins dense (d) granules ADP/ATP Serotonin histamine inorganic polyphosphate Platelet a-granule contents Type Prominent components Membrane glycoproteins GPIb, aIIbb3, GPVI Clotting factors VWF, FV, FXI, FII, Fibrinogen, HMWK, FXIII? Clotting inhibitors TFPI, protein S, protease nexin-2 Fibrinolysis components PAI-1, TAFI, a2-antiplasmin, plasminogen, uPA Other protease inhibitors a1-antitrypsin, a2-macroglobulin -
View of HER2: Human Epidermal Growth Factor Receptor 2; TNBC: Triple-Negative Breast Resistance to Systemic Therapy in Patients with Breast Cancer
Wen et al. Cancer Cell Int (2018) 18:128 https://doi.org/10.1186/s12935-018-0625-9 Cancer Cell International PRIMARY RESEARCH Open Access Sulbactam‑enhanced cytotoxicity of doxorubicin in breast cancer cells Shao‑hsuan Wen1†, Shey‑chiang Su2†, Bo‑huang Liou3, Cheng‑hao Lin1 and Kuan‑rong Lee1* Abstract Background: Multidrug resistance (MDR) is a major obstacle in breast cancer treatment. The predominant mecha‑ nism underlying MDR is an increase in the activity of adenosine triphosphate (ATP)-dependent drug efux trans‑ porters. Sulbactam, a β-lactamase inhibitor, is generally combined with β-lactam antibiotics for treating bacterial infections. However, sulbactam alone can be used to treat Acinetobacter baumannii infections because it inhibits the expression of ATP-binding cassette (ABC) transporter proteins. This is the frst study to report the efects of sulbactam on mammalian cells. Methods: We used the breast cancer cell lines as a model system to determine whether sulbactam afects cancer cells. The cell viabilities in the present of doxorubicin with or without sulbactam were measured by MTT assay. Protein identities and the changes in protein expression levels in the cells after sulbactam and doxorubicin treatment were determined using LC–MS/MS. Real-time reverse transcription polymerase chain reaction (real-time RT-PCR) was used to analyze the change in mRNA expression levels of ABC transporters after treatment of doxorubicin with or without sulbactam. The efux of doxorubicin was measures by the doxorubicin efux assay. Results: MTT assay revealed that sulbactam enhanced the cytotoxicity of doxorubicin in breast cancer cells. The results of proteomics showed that ABC transporter proteins and proteins associated with the process of transcription and initiation of translation were reduced. -
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. -
Transcriptomic Analysis of the Aquaporin (AQP) Gene Family
Pancreatology 19 (2019) 436e442 Contents lists available at ScienceDirect Pancreatology journal homepage: www.elsevier.com/locate/pan Transcriptomic analysis of the Aquaporin (AQP) gene family interactome identifies a molecular panel of four prognostic markers in patients with pancreatic ductal adenocarcinoma Dimitrios E. Magouliotis a, b, Vasiliki S. Tasiopoulou c, Konstantinos Dimas d, * Nikos Sakellaridis d, Konstantina A. Svokos e, Alexis A. Svokos f, Dimitris Zacharoulis b, a Division of Surgery and Interventional Science, Faculty of Medical Sciences, UCL, London, UK b Department of Surgery, University of Thessaly, Biopolis, Larissa, Greece c Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, Larissa, Greece d Department of Pharmacology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, Larissa, Greece e The Warren Alpert Medical School of Brown University, Providence, RI, USA f Riverside Regional Medical Center, Newport News, VA, USA article info abstract Article history: Background: This study aimed to assess the differential gene expression of aquaporin (AQP) gene family Received 14 October 2018 interactome in pancreatic ductal adenocarcinoma (PDAC) using data mining techniques to identify novel Received in revised form candidate genes intervening in the pathogenicity of PDAC. 29 January 2019 Method: Transcriptome data mining techniques were used in order to construct the interactome of the Accepted 9 February 2019 AQP gene family and to determine which genes members are differentially expressed in PDAC as Available online 11 February 2019 compared to controls. The same techniques were used in order to evaluate the potential prognostic role of the differentially expressed genes. Keywords: PDAC Results: Transcriptome microarray data of four GEO datasets were incorporated, including 142 primary Aquaporin tumor samples and 104 normal pancreatic tissue samples. -
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. -
Supplementary Materials
1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No. -
Formation of COPI-Coated Vesicles at a Glance Eric C
© 2018. Published by The Company of Biologists Ltd | Journal of Cell Science (2018) 131, jcs209890. doi:10.1242/jcs.209890 CELL SCIENCE AT A GLANCE Formation of COPI-coated vesicles at a glance Eric C. Arakel1 and Blanche Schwappach1,2,* ABSTRACT unresolved, this review attempts to refocus the perspectives of The coat protein complex I (COPI) allows the precise sorting of lipids the field. and proteins between Golgi cisternae and retrieval from the Golgi KEY WORDS: Arf1, ArfGAP, COPI, Coatomer, Golgi, Endoplasmic to the ER. This essential role maintains the identity of the early reticulum, Vesicle coat secretory pathway and impinges on key cellular processes, such as protein quality control. In this Cell Science at a Glance and accompanying poster, we illustrate the different stages of COPI- Introduction coated vesicle formation and revisit decades of research in the Vesicle coat proteins, such as the archetypal clathrin and the coat context of recent advances in the elucidation of COPI coat structure. protein complexes II and I (COPII and COPI, respectively) are By calling attention to an array of questions that have remained molecular machines with two central roles: enabling vesicle formation, and selecting protein and lipid cargo to be packaged within them. Thus, coat proteins fulfil a central role in the 1Department of Molecular Biology, Universitätsmedizin Göttingen, Humboldtallee homeostasis of the cell’s endomembrane system and are the basis 23, 37073 Göttingen, Germany. 2Max-Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany. of functionally segregated compartments. COPI operates in retrieval from the Golgi to the endoplasmic reticulum (ER) and in intra-Golgi *Author for correspondence ([email protected]) transport (Beck et al., 2009; Duden, 2003; Lee et al., 2004a; Spang, E.C.A., 0000-0001-7716-7149; B.S., 0000-0003-0225-6432 2009), and maintains ER- and Golgi-resident chaperones and enzymes where they belong. -
Supplementary Figures 1-14 and Supplementary References
SUPPORTING INFORMATION Spatial Cross-Talk Between Oxidative Stress and DNA Replication in Human Fibroblasts Marko Radulovic,1,2 Noor O Baqader,1 Kai Stoeber,3† and Jasminka Godovac-Zimmermann1* 1Division of Medicine, University College London, Center for Nephrology, Royal Free Campus, Rowland Hill Street, London, NW3 2PF, UK. 2Insitute of Oncology and Radiology, Pasterova 14, 11000 Belgrade, Serbia 3Research Department of Pathology and UCL Cancer Institute, Rockefeller Building, University College London, University Street, London WC1E 6JJ, UK †Present Address: Shionogi Europe, 33 Kingsway, Holborn, London WC2B 6UF, UK TABLE OF CONTENTS 1. Supplementary Figures 1-14 and Supplementary References. Figure S-1. Network and joint spatial razor plot for 18 enzymes of glycolysis and the pentose phosphate shunt. Figure S-2. Correlation of SILAC ratios between OXS and OAC for proteins assigned to the SAME class. Figure S-3. Overlap matrix (r = 1) for groups of CORUM complexes containing 19 proteins of the 49-set. Figure S-4. Joint spatial razor plots for the Nop56p complex and FIB-associated complex involved in ribosome biogenesis. Figure S-5. Analysis of the response of emerin nuclear envelope complexes to OXS and OAC. Figure S-6. Joint spatial razor plots for the CCT protein folding complex, ATP synthase and V-Type ATPase. Figure S-7. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated by GO to nucleocytoplasmic transport (GO:0006913). Figure S-8. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated to endocytosis (GO:0006897). Figure S-9. Joint spatial razor plots for 401-set proteins annotated by GO to small GTPase mediated signal transduction (GO:0007264) and/or GTPase activity (GO:0003924). -
Discovery of Genes Required for Body Axis and Limb Formation by Global Identification of Conserved Retinoic Acid Regulated Enhancers and Silencers
bioRxiv preprint doi: https://doi.org/10.1101/778191; this version posted December 17, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Discovery of genes required for body axis and limb formation by global identification of conserved retinoic acid regulated enhancers and silencers Marie Berenguer1, Karolin F. Meyer1, Jun Yin2, and Gregg Duester1,* 1Development, Aging, and Regeneration Program 2Bioinformatics Core Facility Sanford Burnham Prebys Medical Discovery Institute, 10901 N. Torrey Pines Road, La Jolla, CA 92037, USA *Corresponding Author ([email protected]) Keywords: Body axis formation; retinoic acid signaling; enhancer; silencer; Aldh1a2 knockout; Nr2f1; Nr2f2 Short title: RNA-seq/ChIP-seq to find RA target genes 1 bioRxiv preprint doi: https://doi.org/10.1101/778191; this version posted December 17, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Identification of target genes for transcription factors is hampered by the large number of genes whose expression changes when the factor is removed from a specific tissue and the numerous binding sites for the factor in the genome. Retinoic acid (RA) regulates transcription via RA receptors bound to RA response elements (RAREs) of which there are thousands in vertebrate genomes. Here, we combined ChIP-seq and RNA-seq on trunk tissue from wild-type and Aldh1a2-/- embryos lacking RA synthesis that exhibit body axis and forelimb defects. We identified a relatively small number of genes with altered expression when RA is missing that also have nearby RA- regulated deposition of H3K27ac (gene activation mark) or H3K27me3 (gene repression mark) associated with conserved RAREs. -
The Role of ARF Family Proteins and Their Regulators and Effectors in Cancer Progression: a Therapeutic Perspective
fcell-08-00217 April 17, 2020 Time: 19:19 # 1 REVIEW published: 21 April 2020 doi: 10.3389/fcell.2020.00217 The Role of ARF Family Proteins and Their Regulators and Effectors in Cancer Progression: A Therapeutic Perspective Cristina Casalou†, Andreia Ferreira† and Duarte C. Barral* CEDOC, NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Lisbon, Portugal The Adenosine diphosphate-Ribosylation Factor (ARF) family belongs to the RAS superfamily of small GTPases and is involved in a wide variety of physiological processes, such as cell proliferation, motility and differentiation by regulating membrane Edited by: traffic and associating with the cytoskeleton. Like other members of the RAS Sunil Kumar Verma, superfamily, ARF family proteins are activated by Guanine nucleotide Exchange Factors Centre for Cellular & Molecular (GEFs) and inactivated by GTPase-Activating Proteins (GAPs). When active, they bind Biology (CCMB), India effectors, which mediate downstream functions. Several studies have reported that Reviewed by: Wei-Hsiung Yang, cancer cells are able to subvert membrane traffic regulators to enhance migration and Mercer University, United States invasion. Indeed, members of the ARF family, including ARF-Like (ARL) proteins have Ira Daar, National Cancer Institute (NCI), been implicated in tumorigenesis and progression of several types of cancer. Here, we United States review the role of ARF family members, their GEFs/GAPs and effectors in tumorigenesis *Correspondence: and cancer progression, highlighting the ones that can have a pro-oncogenic behavior Duarte C. Barral or function as tumor suppressors. Moreover, we propose possible mechanisms and [email protected] approaches to target these proteins, toward the development of novel therapeutic †These authors have contributed equally to this work strategies to impair tumor progression. -
Supplementary Material
BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Page 1 / 45 SUPPLEMENTARY MATERIAL Appendix A1: Neuropsychological protocol. Appendix A2: Description of the four cases at the transitional stage. Table A1: Clinical status and center proportion in each batch. Table A2: Complete output from EdgeR. Table A3: List of the putative target genes. Table A4: Complete output from DIANA-miRPath v.3. Table A5: Comparison of studies investigating miRNAs from brain samples. Figure A1: Stratified nested cross-validation. Figure A2: Expression heatmap of miRNA signature. Figure A3: Bootstrapped ROC AUC scores. Figure A4: ROC AUC scores with 100 different fold splits. Figure A5: Presymptomatic subjects probability scores. Figure A6: Heatmap of the level of enrichment in KEGG pathways. Kmetzsch V, et al. J Neurol Neurosurg Psychiatry 2021; 92:485–493. doi: 10.1136/jnnp-2020-324647 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Appendix A1. Neuropsychological protocol The PREV-DEMALS cognitive evaluation included standardized neuropsychological tests to investigate all cognitive domains, and in particular frontal lobe functions. The scores were provided previously (Bertrand et al., 2018). Briefly, global cognitive efficiency was evaluated by means of Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS). Frontal executive functions were assessed with Frontal Assessment Battery (FAB), forward and backward digit spans, Trail Making Test part A and B (TMT-A and TMT-B), Wisconsin Card Sorting Test (WCST), and Symbol-Digit Modalities test. -
The University of Chicago Genetic Services Laboratories Labolaboratories
The University of Chicago Genetic Services Laboratories LaboLaboratories5841 S. Maryland Ave., Rm. G701, MC 0077, Chicago, Illinois 60637 3637 [email protected] dnatesting.uchicago.edu CLIA #: 14D0917593 CAP #: 18827-49 Next Generation Sequencing Panel for Albinism Clinical Features: Albinism is a group of inherited disorders in which melanin biosynthesis is reduced or absent [1]. The lack or reduction in pigment can affect the eyes, skin and hair, or only the eyes. In addition, there are several syndromic forms of albinism in which the hypopigmented and visual phenotypes are seen in addition to other systems involvement [2]. Our Albinism Sequencing Panel includes sequence analysis of all 20 genes listed below. Our Albinism Deletion/Duplication Panel includes sequence analysis of all 20 genes listed below. Albinism Sequencing Panel Chediak- Griscelli Oculocutaneous Ocular Hermansky Pudlak syndrome Higashi syndrome Albinism Albinism syndrome TYR SLC45A2 GPR143 HPS1 HPS4 DTNBP1 LYST MYO5A OCA2 SLC24A5 AP3B1 HPS5 BLOC1S3 RAB27A TYRP1 C10ORF11 HPS3 HPS6 BLOC1S6 MLPH Oculocutaneous Albinism Oculocutaneous albinism (OCA) is a genetically heterogeneous congenital disorder characterized by decreased or absent pigmentation in the hair, skin, and eyes. Clinical features can include varying degrees of congenital nystagmus, hypopigmentation and translucency, reduced pigmentation of the retinal pigment epithelium and foveal hypoplasia. Vision acuity is typically reduced and refractive errors, color vision impairment and photophobia also occur [3]. Gene Clinical Features Details TYR Albinism, OCA1 is caused by mutations in the tyrosinase gene, TYR. Mutations completely oculocutaneous, abolishing tyrosinase activity result in OCA1A, while mutations rendering some type I enzyme activity result in OCA1B allowing some accumulation of melanin pigment production throughout life.