Comparison of Human and Murine Enteroendocrine Cells by Transcriptomic and Peptidomic Profiling
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Edinburgh Research Explorer
Edinburgh Research Explorer International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list Citation for published version: Davenport, AP, Alexander, SPH, Sharman, JL, Pawson, AJ, Benson, HE, Monaghan, AE, Liew, WC, Mpamhanga, CP, Bonner, TI, Neubig, RR, Pin, JP, Spedding, M & Harmar, AJ 2013, 'International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list: recommendations for new pairings with cognate ligands', Pharmacological reviews, vol. 65, no. 3, pp. 967-86. https://doi.org/10.1124/pr.112.007179 Digital Object Identifier (DOI): 10.1124/pr.112.007179 Link: Link to publication record in Edinburgh Research Explorer Document Version: Publisher's PDF, also known as Version of record Published In: Pharmacological reviews Publisher Rights Statement: U.S. Government work not protected by U.S. copyright General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 02. Oct. 2021 1521-0081/65/3/967–986$25.00 http://dx.doi.org/10.1124/pr.112.007179 PHARMACOLOGICAL REVIEWS Pharmacol Rev 65:967–986, July 2013 U.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. -
Early Pregnancy Vitamin D Status and Risk of Preeclampsia
Early pregnancy vitamin D status and risk of preeclampsia Hooman Mirzakhani, … , Joseph Loscalzo, Scott T. Weiss J Clin Invest. 2016;126(12):4702-4715. https://doi.org/10.1172/JCI89031. Clinical Medicine Clinical trials Reproductive biology BACKGROUND. Low vitamin D status in pregnancy was proposed as a risk factor of preeclampsia. METHODS. We assessed the effect of vitamin D supplementation (4,400 vs. 400 IU/day), initiated early in pregnancy (10–18 weeks), on the development of preeclampsia. The effects of serum vitamin D (25-hydroxyvitamin D [25OHD]) levels on preeclampsia incidence at trial entry and in the third trimester (32–38 weeks) were studied. We also conducted a nested case-control study of 157 women to investigate peripheral blood vitamin D–associated gene expression profiles at 10 to 18 weeks in 47 participants who developed preeclampsia. RESULTS. Of 881 women randomized, outcome data were available for 816, with 67 (8.2%) developing preeclampsia. There was no significant difference between treatment (N = 408) or control (N = 408) groups in the incidence of preeclampsia (8.08% vs. 8.33%, respectively; relative risk: 0.97; 95% CI, 0.61–1.53). However, in a cohort analysis and after adjustment for confounders, a significant effect of sufficient vitamin D status (25OHD ≥30 ng/ml) was observed in both early and late pregnancy compared with insufficient levels (25OHD <30 ng/ml) (adjusted odds ratio, 0.28; 95% CI, 0.10–0.96). Differential expression of 348 vitamin D–associated […] Find the latest version: https://jci.me/89031/pdf CLINICAL MEDICINE The Journal of Clinical Investigation Early pregnancy vitamin D status and risk of preeclampsia Hooman Mirzakhani,1 Augusto A. -
Structural Capacitance in Protein Evolution and Human Diseases
Article Structural Capacitance in Protein Evolution and Human Diseases Chen Li 1,2, Liah V.T. Clark 1, Rory Zhang 1, Benjamin T. Porebski 1,3, Julia M. McCoey 1, Natalie A. Borg 1, Geoffrey I. Webb 4, Itamar Kass 1,5, Malcolm Buckle 6, Jiangning Song 1, Adrian Woolfson 7 and Ashley M. Buckle 1 1 - Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia 2 - Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich 8093, Switzerland 3 - Medical Research Council Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK 4 - Faculty of Information Technology, Monash University, Clayton, Victoria 3800, Australia 5 - Amai Proteins, Prof. A. D. Bergman 2B, Suite 212, Rehovot 7670504, Israel 6 - LBPA, ENS Cachan, CNRS, Université Paris-Saclay, F-94235 Cachan, France 7 - Nouscom, Baumleingasse, CH-4051 Basel, Switzerland Correspondence to Adrian Woolfson and Ashley M. Buckle: [email protected]; [email protected] https://doi.org/10.1016/j.jmb.2018.06.051 Edited by Dan Tawfik Abstract Canonical mechanisms of protein evolution include the duplication and diversification of pre-existing folds through genetic alterations that include point mutations, insertions, deletions, and copy number amplifications, as well as post-translational modifications that modify processes such as folding efficiency and cellular localization. Following a survey of the human mutation database, we have identified an additional mechanism that we term “structural capacitance,” which results in the de novo generation of microstructure in previously disordered regions. We suggest that the potential for structural capacitance confers select proteins with the capacity to evolve over rapid timescales, facilitating saltatory evolution as opposed to gradualistic canonical Darwinian mechanisms. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Structural Capacitance in Protein Evolution and Human Diseases
Structural Capacitance in Protein Evolution and Human Diseases Adrian Woolfson, Ashley Buckle, Natalie Borg, Geoffrey Webb, Itamar Kass, Malcolm Buckle, Jiangning Song, Chen Li, Liah Clark, Rory Zhang, et al. To cite this version: Adrian Woolfson, Ashley Buckle, Natalie Borg, Geoffrey Webb, Itamar Kass, et al.. Structural Ca- pacitance in Protein Evolution and Human Diseases. Journal of Molecular Biology, Elsevier, 2018, 10.1016/j.jmb.2018.06.051. hal-02368321 HAL Id: hal-02368321 https://hal.archives-ouvertes.fr/hal-02368321 Submitted on 20 Nov 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Structural Capacitance in Protein Evolution and Human Diseases Chen Li, Liah Clark, Rory Zhang, Benjamin Porebski, Julia Mccoey, Natalie Borg, Geoffrey Webb, Itamar Kass, Malcolm Buckle, Jiangning Song, etal. To cite this version: Chen Li, Liah Clark, Rory Zhang, Benjamin Porebski, Julia Mccoey, et al.. Structural Capaci- tance in Protein Evolution and Human Diseases. Journal of Molecular Biology, Elsevier, 2018, 10.1016/j.jmb.2018.06.051. hal-02368321 HAL Id: hal-02368321 https://hal.archives-ouvertes.fr/hal-02368321 Submitted on 20 Nov 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. -
G Protein-Coupled Receptors
S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2015/16: G protein-coupled receptors. British Journal of Pharmacology (2015) 172, 5744–5869 THE CONCISE GUIDE TO PHARMACOLOGY 2015/16: G protein-coupled receptors Stephen PH Alexander1, Anthony P Davenport2, Eamonn Kelly3, Neil Marrion3, John A Peters4, Helen E Benson5, Elena Faccenda5, Adam J Pawson5, Joanna L Sharman5, Christopher Southan5, Jamie A Davies5 and CGTP Collaborators 1School of Biomedical Sciences, University of Nottingham Medical School, Nottingham, NG7 2UH, UK, 2Clinical Pharmacology Unit, University of Cambridge, Cambridge, CB2 0QQ, UK, 3School of Physiology and Pharmacology, University of Bristol, Bristol, BS8 1TD, UK, 4Neuroscience Division, Medical Education Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK, 5Centre for Integrative Physiology, University of Edinburgh, Edinburgh, EH8 9XD, UK Abstract The Concise Guide to PHARMACOLOGY 2015/16 provides concise overviews of the key properties of over 1750 human drug targets with their pharmacology, plus links to an open access knowledgebase of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. The full contents can be found at http://onlinelibrary.wiley.com/doi/ 10.1111/bph.13348/full. G protein-coupled receptors are one of the eight major pharmacological targets into which the Guide is divided, with the others being: ligand-gated ion channels, voltage-gated ion channels, other ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. -
G Protein‐Coupled Receptors
S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2019/20: G protein-coupled receptors. British Journal of Pharmacology (2019) 176, S21–S141 THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: G protein-coupled receptors Stephen PH Alexander1 , Arthur Christopoulos2 , Anthony P Davenport3 , Eamonn Kelly4, Alistair Mathie5 , John A Peters6 , Emma L Veale5 ,JaneFArmstrong7 , Elena Faccenda7 ,SimonDHarding7 ,AdamJPawson7 , Joanna L Sharman7 , Christopher Southan7 , Jamie A Davies7 and CGTP Collaborators 1School of Life Sciences, University of Nottingham Medical School, Nottingham, NG7 2UH, UK 2Monash Institute of Pharmaceutical Sciences and Department of Pharmacology, Monash University, Parkville, Victoria 3052, Australia 3Clinical Pharmacology Unit, University of Cambridge, Cambridge, CB2 0QQ, UK 4School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, BS8 1TD, UK 5Medway School of Pharmacy, The Universities of Greenwich and Kent at Medway, Anson Building, Central Avenue, Chatham Maritime, Chatham, Kent, ME4 4TB, UK 6Neuroscience Division, Medical Education Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK 7Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD, UK Abstract The Concise Guide to PHARMACOLOGY 2019/20 is the fourth in this series of biennial publications. The Concise Guide provides concise overviews of the key properties of nearly 1800 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide represents approximately 400 pages, the material presented is substantially reduced compared to information and links presented on the website. -
Hippo and Sonic Hedgehog Signalling Pathway Modulation of Human Urothelial Tissue Homeostasis
Hippo and Sonic Hedgehog signalling pathway modulation of human urothelial tissue homeostasis Thomas Crighton PhD University of York Department of Biology November 2020 Abstract The urinary tract is lined by a barrier-forming, mitotically-quiescent urothelium, which retains the ability to regenerate following injury. Regulation of tissue homeostasis by Hippo and Sonic Hedgehog signalling has previously been implicated in various mammalian epithelia, but limited evidence exists as to their role in adult human urothelial physiology. Focussing on the Hippo pathway, the aims of this thesis were to characterise expression of said pathways in urothelium, determine what role the pathways have in regulating urothelial phenotype, and investigate whether the pathways are implicated in muscle-invasive bladder cancer (MIBC). These aims were assessed using a cell culture paradigm of Normal Human Urothelial (NHU) cells that can be manipulated in vitro to represent different differentiated phenotypes, alongside MIBC cell lines and The Cancer Genome Atlas resource. Transcriptomic analysis of NHU cells identified a significant induction of VGLL1, a poorly understood regulator of Hippo signalling, in differentiated cells. Activation of upstream transcription factors PPARγ and GATA3 and/or blockade of active EGFR/RAS/RAF/MEK/ERK signalling were identified as mechanisms which induce VGLL1 expression in NHU cells. Ectopic overexpression of VGLL1 in undifferentiated NHU cells and MIBC cell line T24 resulted in significantly reduced proliferation. Conversely, knockdown of VGLL1 in differentiated NHU cells significantly reduced barrier tightness in an unwounded state, while inhibiting regeneration and increasing cell cycle activation in scratch-wounded cultures. A signalling pathway previously observed to be inhibited by VGLL1 function, YAP/TAZ, was unaffected by VGLL1 manipulation. -
Genetic Network Analysis of Human CD34+ Hematopoietic Stem
■ ORIGINAL ARTICLE ■ + GENETIC NETWORK ANALYSIS OF HUMAN CD34 HEMATOPOIETIC STEM/PRECURSOR CELLS Shing-Jyh Chang1,2, Tse-Sung Huang3, Kung-Liahng Wang4,5,6, Tao-Yeuan Wang7, Yuh-Cheng Yang4, Margaret Dah-Tsyr Chang2, Yu-Hsuan Wu3, Hsei-Wei Wang3,8,9,10* 1Department of Obstetrics and Gynecology, Mackay Memorial Hospital, 2National Tsing Hua University, HsinChu, 3Institute of Microbiology and Immunology, National Yang-Ming University, 4Department of Obstetrics and Gynecology, Mackay Memorial Hospital, 5National Taipei College of Nursing, 6Mackay Medicine, Nursing and Management College, 7Department of Pathology, Mackay Memorial Hospital, 8Institute of Clinical Medicine and 9VGH-YM Genome Center, National Yang-Ming University, and 10Department of Education and Research, Taipei City Hospital, Taipei, Taiwan. SUMMARY Objective: Somatic CD34+ hematopoietic stem/precursor cells (HSPCs) give rise to hematopoietic cells and endothelial cells and have been used in clinical applications. Understanding the genes responsible for stemness and how they interact with each other will help us to manipulate these cells more efficiently in the future. Materials and Methods: We performed microarray analysis on human CD34+ HSPCs and on two different progeny cell types, i.e. microvascular endothelial cells and peripheral blood mononuclear cells. Systems biology and advanced bioinformatics tools were used to help clarify the genetic networks associated with these stem cell genes. Results: We identified CD34+ HSPC genes and found that they were involved in critical biologic processes such as cell cycle regulation, chromosome organization, and DNA repair. We also identified a novel precursor gene cluster on chromosome 19p13.3. Analysis of HSPC-enriched genes using systems biology tools revealed a com- plex genetic network functioning in CD34+ cells, in which several genes acted as hubs to maintain the stability (such as GATA1) or connectivity (such as hepatic growth factor) of the whole network. -
Antibody List
產品編號 產品名稱 PA569955 1110059E24Rik Polyclonal Antibody PA569956 1110059E24Rik Polyclonal Antibody PA570131 1190002N15Rik Polyclonal Antibody 01-1234-42 123count eBeads Counting Beads MA512242 14.3.3 Pan Monoclonal Antibody (CG15) LFMA0074 14-3-3 beta Monoclonal Antibody (60C10) LFPA0077 14-3-3 beta Polyclonal Antibody PA137002 14-3-3 beta Polyclonal Antibody PA14647 14-3-3 beta Polyclonal Antibody PA515477 14-3-3 beta Polyclonal Antibody PA517425 14-3-3 beta Polyclonal Antibody PA522264 14-3-3 beta Polyclonal Antibody PA529689 14-3-3 beta Polyclonal Antibody MA134561 14-3-3 beta/epsilon/zeta Monoclonal Antibody (3C8) MA125492 14-3-3 beta/zeta Monoclonal Antibody (22-IID8B) MA125665 14-3-3 beta/zeta Monoclonal Antibody (4E2) 702477 14-3-3 delta/zeta Antibody (1H9L19), ABfinity Rabbit Monoclonal 711507 14-3-3 delta/zeta Antibody (1HCLC), ABfinity Rabbit Oligoclonal 702241 14-3-3 epsilon Antibody (5H10L5), ABfinity Rabbit Monoclonal 711273 14-3-3 epsilon Antibody (5HCLC), ABfinity Rabbit Oligoclonal PA517104 14-3-3 epsilon Polyclonal Antibody PA528937 14-3-3 epsilon Polyclonal Antibody PA529773 14-3-3 epsilon Polyclonal Antibody PA575298 14-3-3 eta (Lys81) Polyclonal Antibody MA524792 14-3-3 eta Monoclonal Antibody PA528113 14-3-3 eta Polyclonal Antibody PA529774 14-3-3 eta Polyclonal Antibody PA546811 14-3-3 eta Polyclonal Antibody MA116588 14-3-3 gamma Monoclonal Antibody (HS23) MA116587 14-3-3 gamma Monoclonal Antibody (KC21) PA529690 14-3-3 gamma Polyclonal Antibody PA578233 14-3-3 gamma Polyclonal Antibody 510700 14-3-3 Pan Polyclonal -
SUPPLEMENTARY DATA Supplementary Table 1. Top Ten
SUPPLEMENTARY DATA Supplementary Table 1. Top ten most highly expressed protein-coding genes in the EndoC-βH1 cell line. Expression levels provided for non-mitochondrial genes in EndoC-βH1 and the corresponding expression levels in sorted primary human β-cells (1). Ensembl gene ID Gene Name EndoC-βH1 [RPKM] Primary β cells [RPKM] ENSG00000254647.2 INS 8012.452 166347.111 ENSG00000087086.9 FTL 3090.7454 2066.464 ENSG00000100604.8 CHGA 2853.107 1113.162 ENSG00000099194.5 SCD 1411.631 238.714 ENSG00000118271.5 TTR 1312.8928 1488.996 ENSG00000184009.5 ACTG1 1108.0277 839.681 ENSG00000124172.5 ATP5E 863.42334 254.779 ENSG00000156508.13 EEF1A1 831.17316 637.281 ENSG00000112972.10 HMGCS1 719.7504 22.104 ENSG00000167552.9 TUBA1A 689.1415 511.699 ©2016 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db16-0361/-/DC1 SUPPLEMENTARY DATA Supplementary Table 2. List of genes selected for inclusion in the primary screen. Expression levels in EndoC-βH1 and sorted primary human β-cells are shown for all genes targeted for silencing in the primary screen, ordered by locus association (1). For gene selection, the following criteria were applied: we first considered (1) all protein-coding genes within 1 Mb of a type 2 diabetes association signal that (2) had non-zero expression (RPKM > 0) in both EndoC-βH1 and primary human β-cells. Previous studies have shown cis-eQTLs to form a relatively tight, symmetrical distribution around the target-gene transcription start site, and a 1 Mb cut-off is thus likely to capture most effector transcripts subject to cis regulation (2-5).