AMT Gene Aminomethyltransferase
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Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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 Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
GCSH Rabbit Pab
Leader in Biomolecular Solutions for Life Science GCSH Rabbit pAb Catalog No.: A3880 Basic Information Background Catalog No. Degradation of glycine is brought about by the glycine cleavage system, which is A3880 composed of four mitochondrial protein components: P protein (a pyridoxal phosphate- dependent glycine decarboxylase), H protein (a lipoic acid-containing protein), T protein Observed MW (a tetrahydrofolate-requiring enzyme), and L protein (a lipoamide dehydrogenase). The 28kDa protein encoded by this gene is the H protein, which transfers the methylamine group of glycine from the P protein to the T protein. Defects in this gene are a cause of nonketotic Calculated MW hyperglycinemia (NKH). Two transcript variants, one protein-coding and the other 18kDa probably not protein-coding,have been found for this gene. Also, several transcribed and non-transcribed pseudogenes of this gene exist throughout the genome. Category Primary antibody Applications WB Cross-Reactivity Human Recommended Dilutions Immunogen Information WB 1:500 - 1:1000 Gene ID Swiss Prot 2653 P23434 Immunogen A synthetic peptide of human GCSH Synonyms GCSH;GCE;NKH Contact Product Information www.abclonal.com Source Isotype Purification Rabbit IgG Affinity purification Storage Store at 4℃. Avoid freeze / thaw cycles. Buffer: PBS with 0.02% sodium azide, pH7.3. Validation Data Western blot analysis of extracts of T47D cells, using GCSH antibody (A3880). Secondary antibody: HRP Goat Anti-Rabbit IgG (H+L) (AS014) at 1:10000 dilution. Lysates/proteins: 25ug per lane. Blocking buffer: 3% nonfat dry milk in TBST. Antibody | Protein | ELISA Kits | Enzyme | NGS | Service For research use only. Not for therapeutic or diagnostic purposes. -
Supplementary Table S1. Table 1. List of Bacterial Strains Used in This Study Suppl
Supplementary Material Supplementary Tables: Supplementary Table S1. Table 1. List of bacterial strains used in this study Supplementary Table S2. List of plasmids used in this study Supplementary Table 3. List of primers used for mutagenesis of P. intermedia Supplementary Table 4. List of primers used for qRT-PCR analysis in P. intermedia Supplementary Table 5. List of the most highly upregulated genes in P. intermedia OxyR mutant Supplementary Table 6. List of the most highly downregulated genes in P. intermedia OxyR mutant Supplementary Table 7. List of the most highly upregulated genes in P. intermedia grown in iron-deplete conditions Supplementary Table 8. List of the most highly downregulated genes in P. intermedia grown in iron-deplete conditions Supplementary Figures: Supplementary Figure 1. Comparison of the genomic loci encoding OxyR in Prevotella species. Supplementary Figure 2. Distribution of SOD and glutathione peroxidase genes within the genus Prevotella. Supplementary Table S1. Bacterial strains Strain Description Source or reference P. intermedia V3147 Wild type OMA14 isolated from the (1) periodontal pocket of a Japanese patient with periodontitis V3203 OMA14 PIOMA14_I_0073(oxyR)::ermF This study E. coli XL-1 Blue Host strain for cloning Stratagene S17-1 RP-4-2-Tc::Mu aph::Tn7 recA, Smr (2) 1 Supplementary Table S2. Plasmids Plasmid Relevant property Source or reference pUC118 Takara pBSSK pNDR-Dual Clonetech pTCB Apr Tcr, E. coli-Bacteroides shuttle vector (3) plasmid pKD954 Contains the Porpyromonas gulae catalase (4) -
770.Full-Text.Pdf
Published OnlineFirst January 14, 2019; DOI: 10.1158/1055-9965.EPI-18-0936 Research Article Cancer Epidemiology, Biomarkers Serum Metabolic Profiling Identified a Distinct & Prevention Metabolic Signature in Bladder Cancer Smokers: A Key Metabolic Enzyme Associated with Patient Survival Chandra Sekhar Amara1, Chandrashekar R. Ambati2, Venkatrao Vantaku1, Danthasinghe Waduge Badrajee Piyarathna1, Sri Ramya Donepudi2, Shiva Shankar Ravi1, James M. Arnold3, Vasanta Putluri2, Gurkamal Chatta4, Khurshid A. Guru5, Hoda Badr6, Martha K. Terris7, Roni J. Bollag7, Arun Sreekumar1,3, Andrea B. Apolo8, and Nagireddy Putluri1 Abstract Background: The current system to predict the outcome of nylalanine, proline, serine, valine, isoleucine, glycine, and smokers with bladder cancer is insufficient due to complex asparagine) and taurine were observed in bladder cancer genomic and transcriptomic heterogeneities. This study aims smokers. Integration of differential metabolomic gene signa- to identify serum metabolite-associated genes related to sur- ture and transcriptomics data from TCGA cohort revealed an vival in this population. intersection of 17 genes that showed significant correlation Methods: We performed LC/MS-based targeted metabo- with patient survival in bladder cancer smokers. Importantly, lomic analysis for >300 metabolites in serum obtained catechol-O-methyltransferase, iodotyrosine deiodinase, and from two independent cohorts of bladder cancer never tubulin tyrosine ligase showed a significant association with smokers, smokers, healthy smokers, and healthy never patient survival in publicly available bladder cancer smoker smokers. A subset of differential metabolites was validated datasets and did not have any clinical association in never using Biocrates absoluteIDQ p180 Kit. Genes associated smokers. with differential metabolites were integrated with a publicly Conclusions: Serum metabolic profiling of bladder cancer available cohort of The Cancer Genome Atlas (TCGA) to smokers revealed dysregulated amino acid metabolism. -
Proteome Cold-Shock Response in the Extremely Acidophilic Archaeon, Cuniculiplasma Divulgatum
microorganisms Article Proteome Cold-Shock Response in the Extremely Acidophilic Archaeon, Cuniculiplasma divulgatum Rafael Bargiela 1 , Karin Lanthaler 1,2, Colin M. Potter 1,2 , Manuel Ferrer 3 , Alexander F. Yakunin 1,2, Bela Paizs 1,2, Peter N. Golyshin 1,2 and Olga V. Golyshina 1,2,* 1 School of Natural Sciences, Bangor University, Deiniol Rd, Bangor LL57 2UW, UK; [email protected] (R.B.); [email protected] (K.L.); [email protected] (C.M.P.); [email protected] (A.F.Y.); [email protected] (B.P.); [email protected] (P.N.G.) 2 Centre for Environmental Biotechnology, Bangor University, Deiniol Rd, Bangor LL57 2UW, UK 3 Systems Biotechnology Group, Department of Applied Biocatalysis, CSIC—Institute of Catalysis, Marie Curie 2, 28049 Madrid, Spain; [email protected] * Correspondence: [email protected]; Tel.: +44-1248-388607; Fax: +44-1248-382569 Received: 27 April 2020; Accepted: 15 May 2020; Published: 19 May 2020 Abstract: The archaeon Cuniculiplasma divulgatum is ubiquitous in acidic environments with low-to-moderate temperatures. However, molecular mechanisms underlying its ability to thrive at lower temperatures remain unexplored. Using mass spectrometry (MS)-based proteomics, we analysed the effect of short-term (3 h) exposure to cold. The C. divulgatum genome encodes 2016 protein-coding genes, from which 819 proteins were identified in the cells grown under optimal conditions. In line with the peptidolytic lifestyle of C. divulgatum, its intracellular proteome revealed the abundance of proteases, ABC transporters and cytochrome C oxidase. From 747 quantifiable polypeptides, the levels of 582 proteins showed no change after the cold shock, whereas 104 proteins were upregulated suggesting that they might be contributing to cold adaptation. -
Noelia Díaz Blanco
Effects of environmental factors on the gonadal transcriptome of European sea bass (Dicentrarchus labrax), juvenile growth and sex ratios Noelia Díaz Blanco Ph.D. thesis 2014 Submitted in partial fulfillment of the requirements for the Ph.D. degree from the Universitat Pompeu Fabra (UPF). This work has been carried out at the Group of Biology of Reproduction (GBR), at the Department of Renewable Marine Resources of the Institute of Marine Sciences (ICM-CSIC). Thesis supervisor: Dr. Francesc Piferrer Professor d’Investigació Institut de Ciències del Mar (ICM-CSIC) i ii A mis padres A Xavi iii iv Acknowledgements This thesis has been made possible by the support of many people who in one way or another, many times unknowingly, gave me the strength to overcome this "long and winding road". First of all, I would like to thank my supervisor, Dr. Francesc Piferrer, for his patience, guidance and wise advice throughout all this Ph.D. experience. But above all, for the trust he placed on me almost seven years ago when he offered me the opportunity to be part of his team. Thanks also for teaching me how to question always everything, for sharing with me your enthusiasm for science and for giving me the opportunity of learning from you by participating in many projects, collaborations and scientific meetings. I am also thankful to my colleagues (former and present Group of Biology of Reproduction members) for your support and encouragement throughout this journey. To the “exGBRs”, thanks for helping me with my first steps into this world. Working as an undergrad with you Dr. -
Supplementary Materials
Supplementary Materials COMPARATIVE ANALYSIS OF THE TRANSCRIPTOME, PROTEOME AND miRNA PROFILE OF KUPFFER CELLS AND MONOCYTES Andrey Elchaninov1,3*, Anastasiya Lokhonina1,3, Maria Nikitina2, Polina Vishnyakova1,3, Andrey Makarov1, Irina Arutyunyan1, Anastasiya Poltavets1, Evgeniya Kananykhina2, Sergey Kovalchuk4, Evgeny Karpulevich5,6, Galina Bolshakova2, Gennady Sukhikh1, Timur Fatkhudinov2,3 1 Laboratory of Regenerative Medicine, National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of Ministry of Healthcare of Russian Federation, Moscow, Russia 2 Laboratory of Growth and Development, Scientific Research Institute of Human Morphology, Moscow, Russia 3 Histology Department, Medical Institute, Peoples' Friendship University of Russia, Moscow, Russia 4 Laboratory of Bioinformatic methods for Combinatorial Chemistry and Biology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia 5 Information Systems Department, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow, Russia 6 Genome Engineering Laboratory, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia Figure S1. Flow cytometry analysis of unsorted blood sample. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S2. Flow cytometry analysis of unsorted liver stromal cells. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S3. MiRNAs expression analysis in monocytes and Kupffer cells. Full-length of heatmaps are presented. -
Supplemental Methods
Supplemental Methods: Sample Collection Duplicate surface samples were collected from the Amazon River plume aboard the R/V Knorr in June 2010 (4 52.71’N, 51 21.59’W) during a period of high river discharge. The collection site (Station 10, 4° 52.71’N, 51° 21.59’W; S = 21.0; T = 29.6°C), located ~ 500 Km to the north of the Amazon River mouth, was characterized by the presence of coastal diatoms in the top 8 m of the water column. Sampling was conducted between 0700 and 0900 local time by gently impeller pumping (modified Rule 1800 submersible sump pump) surface water through 10 m of tygon tubing (3 cm) to the ship's deck where it then flowed through a 156 µm mesh into 20 L carboys. In the lab, cells were partitioned into two size fractions by sequential filtration (using a Masterflex peristaltic pump) of the pre-filtered seawater through a 2.0 µm pore-size, 142 mm diameter polycarbonate (PCTE) membrane filter (Sterlitech Corporation, Kent, CWA) and a 0.22 µm pore-size, 142 mm diameter Supor membrane filter (Pall, Port Washington, NY). Metagenomic and non-selective metatranscriptomic analyses were conducted on both pore-size filters; poly(A)-selected (eukaryote-dominated) metatranscriptomic analyses were conducted only on the larger pore-size filter (2.0 µm pore-size). All filters were immediately submerged in RNAlater (Applied Biosystems, Austin, TX) in sterile 50 mL conical tubes, incubated at room temperature overnight and then stored at -80oC until extraction. Filtration and stabilization of each sample was completed within 30 min of water collection. -
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 -
The Microbiota-Produced N-Formyl Peptide Fmlf Promotes Obesity-Induced Glucose
Page 1 of 230 Diabetes Title: The microbiota-produced N-formyl peptide fMLF promotes obesity-induced glucose intolerance Joshua Wollam1, Matthew Riopel1, Yong-Jiang Xu1,2, Andrew M. F. Johnson1, Jachelle M. Ofrecio1, Wei Ying1, Dalila El Ouarrat1, Luisa S. Chan3, Andrew W. Han3, Nadir A. Mahmood3, Caitlin N. Ryan3, Yun Sok Lee1, Jeramie D. Watrous1,2, Mahendra D. Chordia4, Dongfeng Pan4, Mohit Jain1,2, Jerrold M. Olefsky1 * Affiliations: 1 Division of Endocrinology & Metabolism, Department of Medicine, University of California, San Diego, La Jolla, California, USA. 2 Department of Pharmacology, University of California, San Diego, La Jolla, California, USA. 3 Second Genome, Inc., South San Francisco, California, USA. 4 Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA. * Correspondence to: 858-534-2230, [email protected] Word Count: 4749 Figures: 6 Supplemental Figures: 11 Supplemental Tables: 5 1 Diabetes Publish Ahead of Print, published online April 22, 2019 Diabetes Page 2 of 230 ABSTRACT The composition of the gastrointestinal (GI) microbiota and associated metabolites changes dramatically with diet and the development of obesity. Although many correlations have been described, specific mechanistic links between these changes and glucose homeostasis remain to be defined. Here we show that blood and intestinal levels of the microbiota-produced N-formyl peptide, formyl-methionyl-leucyl-phenylalanine (fMLF), are elevated in high fat diet (HFD)- induced obese mice. Genetic or pharmacological inhibition of the N-formyl peptide receptor Fpr1 leads to increased insulin levels and improved glucose tolerance, dependent upon glucagon- like peptide-1 (GLP-1). Obese Fpr1-knockout (Fpr1-KO) mice also display an altered microbiome, exemplifying the dynamic relationship between host metabolism and microbiota. -
Role and Regulation of the P53-Homolog P73 in the Transformation of Normal Human Fibroblasts
Role and regulation of the p53-homolog p73 in the transformation of normal human fibroblasts Dissertation zur Erlangung des naturwissenschaftlichen Doktorgrades der Bayerischen Julius-Maximilians-Universität Würzburg vorgelegt von Lars Hofmann aus Aschaffenburg Würzburg 2007 Eingereicht am Mitglieder der Promotionskommission: Vorsitzender: Prof. Dr. Dr. Martin J. Müller Gutachter: Prof. Dr. Michael P. Schön Gutachter : Prof. Dr. Georg Krohne Tag des Promotionskolloquiums: Doktorurkunde ausgehändigt am Erklärung Hiermit erkläre ich, dass ich die vorliegende Arbeit selbständig angefertigt und keine anderen als die angegebenen Hilfsmittel und Quellen verwendet habe. Diese Arbeit wurde weder in gleicher noch in ähnlicher Form in einem anderen Prüfungsverfahren vorgelegt. Ich habe früher, außer den mit dem Zulassungsgesuch urkundlichen Graden, keine weiteren akademischen Grade erworben und zu erwerben gesucht. Würzburg, Lars Hofmann Content SUMMARY ................................................................................................................ IV ZUSAMMENFASSUNG ............................................................................................. V 1. INTRODUCTION ................................................................................................. 1 1.1. Molecular basics of cancer .......................................................................................... 1 1.2. Early research on tumorigenesis ................................................................................. 3 1.3. Developing -
A Single Nucleotide Substitution That Abolishes the Initiator Methionine Codon of the GLDC Gene Is Prevalent Among Patients with Glycine Encephalopathy in Jerusalem
J Hum Genet (2005) 50:230–234 DOI 10.1007/s10038-005-0243-y ORIGINAL ARTICLE Avihu Boneh Æ Stanley H. Korman Æ Kenichi Sato Junko Kanno Æ Yoichi Matsubara Æ Israela Lerer Ziva Ben-Neriah Æ Shigeo Kure A single nucleotide substitution that abolishes the initiator methionine codon of the GLDC gene is prevalent among patients with glycine encephalopathy in Jerusalem Received: 12 January 2005 / Accepted: 23 February 2005 / Published online: 29 April 2005 Ó The Japan Society of Human Genetics and Springer-Verlag 2005 Abstract Glycine encephalopathy (GE) (non-ketotic Introduction hyperglycinemia) is an autosomal recessive neurometa- bolic disease caused by defective activity of the glycine Glycine encephalopathy (GE; or non-ketotic hypergly- cleavage system. Clinically, patients present usually in cinemia, OMIM 238300) is an autosomal recessive the neonatal period with hypotonia, encephalopathy, neurometabolic disease caused by defective activity of hiccups and breath arrests with or without overt seizures. the glycine cleavage system (Hamosh and Johnston GE is considered rare, but its incidence is relatively high 2001). This complex is made of four proteins that work in several geographical areas around the world. We in concert in the metabolic process of glycine: a P pro- report a novel mutation causing GE in six extended tein, a pyridoxal-phosphate-containing glycine decar- Arab families, all from a small suburban village (popu- boxylase (GLDC), a T protein, a tetrahydrofolate lation 5,000). A methionine to threonine change in the requiring aminomethyltransferase, an L protein, a lip- initiation codon of the glycine decarboxylase gene led to oamide dehydrogenase and a lipoic-acid-containing H markedly reduced glycine decarboxylase mRNA levels protein.