Discovery of Pharmaceutically-Targetable Pathways and Prediction of Survivorship for Pneumonia and Sepsis Patients from the View Point of Ensemble Gene Noise
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Gene Symbol Gene Description ACVR1B Activin a Receptor, Type IB
Table S1. Kinase clones included in human kinase cDNA library for yeast two-hybrid screening Gene Symbol Gene Description ACVR1B activin A receptor, type IB ADCK2 aarF domain containing kinase 2 ADCK4 aarF domain containing kinase 4 AGK multiple substrate lipid kinase;MULK AK1 adenylate kinase 1 AK3 adenylate kinase 3 like 1 AK3L1 adenylate kinase 3 ALDH18A1 aldehyde dehydrogenase 18 family, member A1;ALDH18A1 ALK anaplastic lymphoma kinase (Ki-1) ALPK1 alpha-kinase 1 ALPK2 alpha-kinase 2 AMHR2 anti-Mullerian hormone receptor, type II ARAF v-raf murine sarcoma 3611 viral oncogene homolog 1 ARSG arylsulfatase G;ARSG AURKB aurora kinase B AURKC aurora kinase C BCKDK branched chain alpha-ketoacid dehydrogenase kinase BMPR1A bone morphogenetic protein receptor, type IA BMPR2 bone morphogenetic protein receptor, type II (serine/threonine kinase) BRAF v-raf murine sarcoma viral oncogene homolog B1 BRD3 bromodomain containing 3 BRD4 bromodomain containing 4 BTK Bruton agammaglobulinemia tyrosine kinase BUB1 BUB1 budding uninhibited by benzimidazoles 1 homolog (yeast) BUB1B BUB1 budding uninhibited by benzimidazoles 1 homolog beta (yeast) C9orf98 chromosome 9 open reading frame 98;C9orf98 CABC1 chaperone, ABC1 activity of bc1 complex like (S. pombe) CALM1 calmodulin 1 (phosphorylase kinase, delta) CALM2 calmodulin 2 (phosphorylase kinase, delta) CALM3 calmodulin 3 (phosphorylase kinase, delta) CAMK1 calcium/calmodulin-dependent protein kinase I CAMK2A calcium/calmodulin-dependent protein kinase (CaM kinase) II alpha CAMK2B calcium/calmodulin-dependent -
Targeting the LKB1 Tumor Suppressor
Send Orders for Reprints to [email protected] 32 Current Drug Targets, 2014, 15, 32-52 Targeting the LKB1 Tumor Suppressor Rui-Xun Zhao and Zhi-Xiang Xu* Division of Hematology and Oncology, Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL, USA Abstract: LKB1 (also known as serine-threonine kinase 11, STK11) is a tumor suppressor, which is mutated or deleted in Peutz-Jeghers syndrome (PJS) and in a variety of cancers. Physiologically, LKB1 possesses multiple cellular functions in the regulation of cell bioenergetics metabolism, cell cycle arrest, embryo development, cell polarity, and apoptosis. New studies demonstrated that LKB1 may also play a role in the maintenance of function and dynamics of hematopoietic stem cells. Over the past years, personalized therapy targeting specific genetic aberrations has attracted intense interests. Within this review, several agents with potential activity against aberrant LKB1 signaling have been discussed. Potential strate- gies and challenges in targeting LKB1 inactivation are also considered. Keywords: LKB1 (serine-threonine kinase 11, STK11), AMP-activated protein kinase (AMPK), tumor suppression, mutations, targeting therapeutics. INTRODUCTION THE BIOLOGICAL FUNCTIONS OF LKB1 The LKB1 gene, also known as serine-threonine kinase Cell Metabolism 11 (STK11), was first identified by Jun-ichi Nezu of Chugai About a decade ago, studies from three different groups Pharmaceuticals in 1996 in a screen aimed at identifying new established that LKB1 is the long-sought kinase that phos- kinases [1]. The human LKB1 gene has been mapped to phorylates AMPK [9-11]. AMPK is a heterotrimeric enzyme chromosome 19p13.3. The gene spans 23 kb and is com- complex consisting of a catalytic subunit and regulatory posed of nine coding exons and a noncoding exon [2]. -
Activated Peripheral-Blood-Derived Mononuclear Cells
Transcription factor expression in lipopolysaccharide- activated peripheral-blood-derived mononuclear cells Jared C. Roach*†, Kelly D. Smith*‡, Katie L. Strobe*, Stephanie M. Nissen*, Christian D. Haudenschild§, Daixing Zhou§, Thomas J. Vasicek¶, G. A. Heldʈ, Gustavo A. Stolovitzkyʈ, Leroy E. Hood*†, and Alan Aderem* *Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103; ‡Department of Pathology, University of Washington, Seattle, WA 98195; §Illumina, 25861 Industrial Boulevard, Hayward, CA 94545; ¶Medtronic, 710 Medtronic Parkway, Minneapolis, MN 55432; and ʈIBM Computational Biology Center, P.O. Box 218, Yorktown Heights, NY 10598 Contributed by Leroy E. Hood, August 21, 2007 (sent for review January 7, 2007) Transcription factors play a key role in integrating and modulating system. In this model system, we activated peripheral-blood-derived biological information. In this study, we comprehensively measured mononuclear cells, which can be loosely termed ‘‘macrophages,’’ the changing abundances of mRNAs over a time course of activation with lipopolysaccharide (LPS). We focused on the precise mea- of human peripheral-blood-derived mononuclear cells (‘‘macro- surement of mRNA concentrations. There is currently no high- phages’’) with lipopolysaccharide. Global and dynamic analysis of throughput technology that can precisely and sensitively measure all transcription factors in response to a physiological stimulus has yet to mRNAs in a system, although such technologies are likely to be be achieved in a human system, and our efforts significantly available in the near future. To demonstrate the potential utility of advanced this goal. We used multiple global high-throughput tech- such technologies, and to motivate their development and encour- nologies for measuring mRNA levels, including massively parallel age their use, we produced data from a combination of two distinct signature sequencing and GeneChip microarrays. -
Computational Genome-Wide Identification of Heat Shock Protein Genes in the Bovine Genome [Version 1; Peer Review: 2 Approved, 1 Approved with Reservations]
F1000Research 2018, 7:1504 Last updated: 08 AUG 2021 RESEARCH ARTICLE Computational genome-wide identification of heat shock protein genes in the bovine genome [version 1; peer review: 2 approved, 1 approved with reservations] Oyeyemi O. Ajayi1,2, Sunday O. Peters3, Marcos De Donato2,4, Sunday O. Sowande5, Fidalis D.N. Mujibi6, Olanrewaju B. Morenikeji2,7, Bolaji N. Thomas 8, Matthew A. Adeleke 9, Ikhide G. Imumorin2,10,11 1Department of Animal Breeding and Genetics, Federal University of Agriculture, Abeokuta, Nigeria 2International Programs, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY, 14853, USA 3Department of Animal Science, Berry College, Mount Berry, GA, 30149, USA 4Departamento Regional de Bioingenierias, Tecnologico de Monterrey, Escuela de Ingenieria y Ciencias, Queretaro, Mexico 5Department of Animal Production and Health, Federal University of Agriculture, Abeokuta, Nigeria 6Usomi Limited, Nairobi, Kenya 7Department of Animal Production and Health, Federal University of Technology, Akure, Nigeria 8Department of Biomedical Sciences, Rochester Institute of Technology, Rochester, NY, 14623, USA 9School of Life Sciences, University of KwaZulu-Natal, Durban, 4000, South Africa 10School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30032, USA 11African Institute of Bioscience Research and Training, Ibadan, Nigeria v1 First published: 20 Sep 2018, 7:1504 Open Peer Review https://doi.org/10.12688/f1000research.16058.1 Latest published: 20 Sep 2018, 7:1504 https://doi.org/10.12688/f1000research.16058.1 Reviewer Status Invited Reviewers Abstract Background: Heat shock proteins (HSPs) are molecular chaperones 1 2 3 known to bind and sequester client proteins under stress. Methods: To identify and better understand some of these proteins, version 1 we carried out a computational genome-wide survey of the bovine 20 Sep 2018 report report report genome. -
Supplement 1 Overview of Dystonia Genes
Supplement 1 Overview of genes that may cause dystonia in children and adolescents Gene (OMIM) Disease name/phenotype Mode of inheritance 1: (Formerly called) Primary dystonias (DYTs): TOR1A (605204) DYT1: Early-onset generalized AD primary torsion dystonia (PTD) TUBB4A (602662) DYT4: Whispering dystonia AD GCH1 (600225) DYT5: GTP-cyclohydrolase 1 AD deficiency THAP1 (609520) DYT6: Adolescent onset torsion AD dystonia, mixed type PNKD/MR1 (609023) DYT8: Paroxysmal non- AD kinesigenic dyskinesia SLC2A1 (138140) DYT9/18: Paroxysmal choreoathetosis with episodic AD ataxia and spasticity/GLUT1 deficiency syndrome-1 PRRT2 (614386) DYT10: Paroxysmal kinesigenic AD dyskinesia SGCE (604149) DYT11: Myoclonus-dystonia AD ATP1A3 (182350) DYT12: Rapid-onset dystonia AD parkinsonism PRKRA (603424) DYT16: Young-onset dystonia AR parkinsonism ANO3 (610110) DYT24: Primary focal dystonia AD GNAL (139312) DYT25: Primary torsion dystonia AD 2: Inborn errors of metabolism: GCDH (608801) Glutaric aciduria type 1 AR PCCA (232000) Propionic aciduria AR PCCB (232050) Propionic aciduria AR MUT (609058) Methylmalonic aciduria AR MMAA (607481) Cobalamin A deficiency AR MMAB (607568) Cobalamin B deficiency AR MMACHC (609831) Cobalamin C deficiency AR C2orf25 (611935) Cobalamin D deficiency AR MTRR (602568) Cobalamin E deficiency AR LMBRD1 (612625) Cobalamin F deficiency AR MTR (156570) Cobalamin G deficiency AR CBS (613381) Homocysteinuria AR PCBD (126090) Hyperphelaninemia variant D AR TH (191290) Tyrosine hydroxylase deficiency AR SPR (182125) Sepiaterine reductase -
Supplemental Table S1
Entrez Gene Symbol Gene Name Affymetrix EST Glomchip SAGE Stanford Literature HPA confirmed Gene ID Profiling profiling Profiling Profiling array profiling confirmed 1 2 A2M alpha-2-macroglobulin 0 0 0 1 0 2 10347 ABCA7 ATP-binding cassette, sub-family A (ABC1), member 7 1 0 0 0 0 3 10350 ABCA9 ATP-binding cassette, sub-family A (ABC1), member 9 1 0 0 0 0 4 10057 ABCC5 ATP-binding cassette, sub-family C (CFTR/MRP), member 5 1 0 0 0 0 5 10060 ABCC9 ATP-binding cassette, sub-family C (CFTR/MRP), member 9 1 0 0 0 0 6 79575 ABHD8 abhydrolase domain containing 8 1 0 0 0 0 7 51225 ABI3 ABI gene family, member 3 1 0 1 0 0 8 29 ABR active BCR-related gene 1 0 0 0 0 9 25841 ABTB2 ankyrin repeat and BTB (POZ) domain containing 2 1 0 1 0 0 10 30 ACAA1 acetyl-Coenzyme A acyltransferase 1 (peroxisomal 3-oxoacyl-Coenzyme A thiol 0 1 0 0 0 11 43 ACHE acetylcholinesterase (Yt blood group) 1 0 0 0 0 12 58 ACTA1 actin, alpha 1, skeletal muscle 0 1 0 0 0 13 60 ACTB actin, beta 01000 1 14 71 ACTG1 actin, gamma 1 0 1 0 0 0 15 81 ACTN4 actinin, alpha 4 0 0 1 1 1 10700177 16 10096 ACTR3 ARP3 actin-related protein 3 homolog (yeast) 0 1 0 0 0 17 94 ACVRL1 activin A receptor type II-like 1 1 0 1 0 0 18 8038 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 1 0 0 0 0 19 8751 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 1 0 0 0 0 20 8728 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 1 0 0 0 0 21 81792 ADAMTS12 ADAM metallopeptidase with thrombospondin type 1 motif, 12 1 0 0 0 0 22 9507 ADAMTS4 ADAM metallopeptidase with thrombospondin type 1 -
Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony
Supplementary Data Th2 and non-Th2 molecular phenotypes of asthma using sputum transcriptomics in UBIOPRED Chih-Hsi Scott Kuo1.2, Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony Rowe3, Iaonnis Pandis2, Ana Sousa4, Julie Corfield5, Ratko Djukanovic6, Rene 7 7 8 2 1† Lutter , Peter J. Sterk , Charles Auffray , Yike Guo , Ian M. Adcock & Kian Fan 1†* # Chung on behalf of the U-BIOPRED consortium project team 1Airways Disease, National Heart & Lung Institute, Imperial College London, & Biomedical Research Unit, Biomedical Research Unit, Royal Brompton & Harefield NHS Trust, London, United Kingdom; 2Department of Computing & Data Science Institute, Imperial College London, United Kingdom; 3Janssen Research and Development, High Wycombe, Buckinghamshire, United Kingdom; 4Respiratory Therapeutic Unit, GSK, Stockley Park, United Kingdom; 5AstraZeneca R&D Molndal, Sweden and Areteva R&D, Nottingham, United Kingdom; 6Faculty of Medicine, Southampton University, Southampton, United Kingdom; 7Faculty of Medicine, University of Amsterdam, Amsterdam, Netherlands; 8European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL, Université de Lyon, France. †Contributed equally #Consortium project team members are listed under Supplementary 1 Materials *To whom correspondence should be addressed: [email protected] 2 List of the U-BIOPRED Consortium project team members Uruj Hoda & Christos Rossios, Airways Disease, National Heart & Lung Institute, Imperial College London, UK & Biomedical Research Unit, Biomedical Research Unit, Royal -
Assessment of a Targeted Gene Panel for Identification of Genes Associated with Movement Disorders
Supplementary Online Content Montaut S, Tranchant C, Drouot N, et al; French Parkinson’s and Movement Disorders Consortium. Assessment of a targeted gene panel for identification of genes associated with movement disorders. JAMA Neurol. Published online June 18, 2018. doi:10.1001/jamaneurol.2018.1478 eMethods. Supplemental methods. eTable 1. Name, phenotype and inheritance of the genes included in the panel. eTable 2. Probable pathogenic variants identified in a cohort of 23 patients with cerebellar ataxia using WES analysis. eTable 3. Negative cases in a cohort of 23 patients with cerebellar ataxia studied using WES analysis. eTable 4. Variants of unknown significance (VUSs) identified in the cohort. eFigure 1. Examples of pedigrees of cases with identified causative variants. eFigure 2. Pedigrees suggesting mendelian inheritance in negative cases. eFigure 3. Examples of pedigrees of cases with identified VUSs. eResults. Supplemental results. This supplementary material has been provided by the authors to give readers additional information about their work. © 2018 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/26/2021 eMethods. Supplemental methods Patients selection In the multicentric, prospective study, patients were selected from 25 French, 1 Luxembourg and 1 Algerian tertiary MDs centers between September 2014 and July 2016. Inclusion criteria were patients (1) who had developed one or several chronic MDs (2) with an age of onset below 40 years and/or presence of a family history of MDs. Patients suffering from essential tremor, tic or Gilles de la Tourette syndrome, pure cerebellar ataxia or with clinical/paraclinical findings suggestive of an acquired cause were excluded. -
Anti-SEK1 / MKK4 Phospho (Ser80) Antibody (ARG51673)
Product datasheet [email protected] ARG51673 Package: 100 μl, 50 μl anti-SEK1 / MKK4 phospho (Ser80) antibody Store at: -20°C Summary Product Description Rabbit Polyclonal antibody recognizes SEK1 / MKK4 phospho (Ser80) Tested Reactivity Hu, Ms, Rat Tested Application ICC/IF, IHC-P, WB Host Rabbit Clonality Polyclonal Isotype IgG Target Name SEK1 / MKK4 Antigen Species Human Immunogen Peptide sequence around phosphorylation site of serine 80 (T-H-S(p)-I-E) derived from Human SEK1/MKK4. Conjugation Un-conjugated Alternate Names MEK 4; MAPK/ERK kinase 4; PRKMK4; SAPKK-1; SAPK/ERK kinase 1; SKK1; JNK-activating kinase 1; EC 2.7.12.2; MEK4; MAP kinase kinase 4; c-Jun N-terminal kinase kinase 1; SEK1; SAPKK1; MAPKK4; Stress- activated protein kinase kinase 1; JNKK1; MKK4; SERK1; SAPK kinase 1; Dual specificity mitogen- activated protein kinase kinase 4; JNKK; MAPKK 4 Application Instructions Application table Application Dilution ICC/IF 1:100 - 1:200 IHC-P 1:50 - 1:100 WB 1:500 - 1:1000 Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 44 kDa Properties Form Liquid Purification Antibodies were produced by immunizing rabbits with KLH-conjugated synthetic phosphopeptide. Antibodies were purified by affinity-chromatography using epitope-specific phosphopeptide. In addition, non-phospho specific antibodies were removed by chromatogramphy using non- phosphopeptide. Buffer PBS (without Mg2+ and Ca2+, pH 7.4), 150mM NaCl, 0.02% Sodium azide and 50% Glycerol. Preservative 0.02% Sodium azide Stabilizer 50% Glycerol www.arigobio.com 1/3 Concentration 1 mg/ml Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. -
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. -
PROTEOMIC ANALYSIS of HUMAN URINARY EXOSOMES. Patricia
ABSTRACT Title of Document: PROTEOMIC ANALYSIS OF HUMAN URINARY EXOSOMES. Patricia Amalia Gonzales Mancilla, Ph.D., 2009 Directed By: Associate Professor Nam Sun Wang, Department of Chemical and Biomolecular Engineering Exosomes originate as the internal vesicles of multivesicular bodies (MVBs) in cells. These small vesicles (40-100 nm) have been shown to be secreted by most cell types throughout the body. In the kidney, urinary exosomes are released to the urine by fusion of the outer membrane of the MVBs with the apical plasma membrane of renal tubular epithelia. Exosomes contain apical membrane and cytosolic proteins and can be isolated using differential centrifugation. The analysis of urinary exosomes provides a non- invasive means of acquiring information about the physiological or pathophysiological state of renal cells. The overall objective of this research was to develop methods and knowledge infrastructure for urinary proteomics. We proposed to conduct a proteomic analysis of human urinary exosomes. The first objective was to profile the proteome of human urinary exosomes using liquid chromatography-tandem spectrometry (LC- MS/MS) and specialized software for identification of peptide sequences from fragmentation spectra. We unambiguously identified 1132 proteins. In addition, the phosphoproteome of human urinary exosomes was profiled using the neutral loss scanning acquisition mode of LC-MS/MS. The phosphoproteomic profiling identified 19 phosphorylation sites corresponding to 14 phosphoproteins. The second objective was to analyze urinary exosomes samples isolated from patients with genetic mutations. Polyclonal antibodies were generated to recognize epitopes on the gene products of these genetic mutations, NKCC2 and MRP4. The potential usefulness of urinary exosome analysis was demonstrated using the well-defined renal tubulopathy, Bartter syndrome type I and using the single nucleotide polymorphism in the ABCC4 gene. -
To Study Mutant P53 Gain of Function, Various Tumor-Derived P53 Mutants
Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science By Shama K Khokhar M.Sc., Bilaspur University, 2004 B.Sc., Bhopal University, 2002 2007 1 COPYRIGHT SHAMA K KHOKHAR 2007 2 WRIGHT STATE UNIVERSITY SCHOOL OF GRADUATE STUDIES Date of Defense: 12-03-07 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY SHAMA KHAN KHOKHAR ENTITLED Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science Madhavi P. Kadakia, Ph.D. Thesis Director Daniel Organisciak , Ph.D. Department Chair Committee on Final Examination Madhavi P. Kadakia, Ph.D. Steven J. Berberich, Ph.D. Michael Leffak, Ph.D. Joseph F. Thomas, Jr., Ph.D. Dean, School of Graduate Studies 3 Abstract Khokhar, Shama K. M.S., Department of Biochemistry and Molecular Biology, Wright State University, 2007 Differential effect of TAp63γ mutants on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. p63, a member of the p53 gene family, known to play a role in development, has more recently also been implicated in cancer progression. Mice lacking p63 exhibit severe developmental defects such as limb truncations, abnormal skin, and absence of hair follicles, teeth, and mammary glands. Germline missense mutations of p63 have been shown to be responsible for several human developmental syndromes including SHFM, EEC and ADULT syndromes and are associated with anomalies in the development of organs of epithelial origin.