Coupled Structural Transitions Enable Highly Cooperative Regulation of 2 Human CTPS2 Filaments 3 4 Eric M
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Datasheet CST 98287
C 0 2 - t CTPS1 Antibody a e r o t S Orders: 877-616-CELL (2355) [email protected] 7 Support: 877-678-TECH (8324) 8 2 Web: [email protected] 8 www.cellsignal.com 9 # 3 Trask Lane Danvers Massachusetts 01923 USA For Research Use Only. Not For Use In Diagnostic Procedures. Applications: Reactivity: Sensitivity: MW (kDa): Source: UniProt ID: Entrez-Gene Id: WB H Endogenous 78 Rabbit P17812 1503 Product Usage Information Application Dilution Western Blotting 1:1000 Storage Supplied in 10 mM sodium HEPES (pH 7.5), 150 mM NaCl, 100 µg/ml BSA and 50% glycerol. Store at –20°C. Do not aliquot the antibody. Specificity / Sensitivity CTPS1 Antibody recognizes endogenous levels of total CTPS1 protein. This antibody does not cross-react with CTPS2 protein. Species Reactivity: Human Source / Purification Polyclonal antibodies are produced by immunizing animals with a synthetic peptide corresponding to residues surrounding Ala340 of human CTPS1 protein. Antibodies are purified by peptide affinity chromatography. Background CTPS1 (cytidine triphosphate synthase 1 or CTP synthase 1) catalyzes the conversion of UTP to CTP through ATP-dependent amination (1). Research studies show that pyrimidine biosynthesis is upregulated in pancreatic cancer cell models of resistance to gemcitabine, a deoxycytidine analog. Increased pyrimidine biosynthesis leads to elevated levels of endogenous dCTP, which outcompetes gemcitabine from incorporating into DNA during replication and, therefore, reduces the anti-cancer effectiveness of gemcitabine. Induction of CTPS1 expression was observed in gemcitabine-resistant pancreatic cancer cell models. Gemcitabine resistance directly correlates with CTPS1 expression levels in various pancreatic cancer cell lines (2). -
Ankrd9 Is a Metabolically-Controlled Regulator of Impdh2 Abundance and Macro-Assembly
ANKRD9 IS A METABOLICALLY-CONTROLLED REGULATOR OF IMPDH2 ABUNDANCE AND MACRO-ASSEMBLY by Dawn Hayward A dissertation submitted to The Johns Hopkins University in conformity with the requirements of the degree of Doctor of Philosophy Baltimore, Maryland April 2019 ABSTRACT Members of a large family of Ankyrin Repeat Domains proteins (ANKRD) regulate numerous cellular processes by binding and changing properties of specific protein targets. We show that interactions with a target protein and the functional outcomes can be markedly altered by cells’ metabolic state. ANKRD9 facilitates degradation of inosine monophosphate dehydrogenase 2 (IMPDH2), the rate-limiting enzyme in GTP biosynthesis. Under basal conditions ANKRD9 is largely segregated from the cytosolic IMPDH2 by binding to vesicles. Upon nutrient limitation, ANKRD9 loses association with vesicles and assembles with IMPDH2 into rod-like structures, in which IMPDH2 is stable. Inhibition of IMPDH2 with Ribavirin favors ANKRD9 binding to rods. The IMPDH2/ANKRD9 assembly is reversed by guanosine, which restores association of ANKRD9 with vesicles. The conserved Cys109Cys110 motif in ANKRD9 is required for the vesicles-to-rods transition as well as binding and regulation of IMPDH2. ANKRD9 knockdown increases IMPDH2 levels and prevents formation of IMPDH2 rods upon nutrient limitation. Thus, the status of guanosine pools affects the mode of ANKRD9 action towards IMPDH2. Advisor: Dr. Svetlana Lutsenko, Department of Physiology, Johns Hopkins University School of Medicine Second reader: -
Linked Mental Retardation Detected by Array CGH
JMG Online First, published on September 16, 2005 as 10.1136/jmg.2005.036178 J Med Genet: first published as 10.1136/jmg.2005.036178 on 16 September 2005. Downloaded from Chromosomal copy number changes in patients with non-syndromic X- linked mental retardation detected by array CGH D Lugtenberg1, A P M de Brouwer1, T Kleefstra1, A R Oudakker1, S G M Frints2, C T R M Schrander- Stumpel2, J P Fryns3, L R Jensen4, J Chelly5, C Moraine6, G Turner7, J A Veltman1, B C J Hamel1, B B A de Vries1, H van Bokhoven1, H G Yntema1 1Department of Human Genetics, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands; 2Department of Clinical Genetics, University Hospital Maastricht, Maastricht, The Netherlands; 3Center for Human Genetics, University of Leuven, Leuven, Belgium; 4Max Planck Institute for Molecular Genetics, Berlin, Germany; 5INSERM 129-ICGM, Faculté de Médecine Cochin, Paris, France; 6Service de Génétique et INSERM U316, Hôpital Bretonneau, Tours, France; 7 GOLD Program, Hunter Genetics, University of Newcastle, Callaghan, New South Wales 2308, Australia http://jmg.bmj.com/ Corresponding author: on October 2, 2021 by guest. Protected copyright. Helger G. Yntema, PhD Department of Human Genetics Radboud University Nijmegen Medical Centre P.O. Box 9101 6500 HB Nijmegen The Netherlands E-mail: [email protected] tel: +31-24-3613799 fax: +31-24-3616658 1 Copyright Article author (or their employer) 2005. Produced by BMJ Publishing Group Ltd under licence. J Med Genet: first published as 10.1136/jmg.2005.036178 on 16 September 2005. Downloaded from ABSTRACT Introduction: Several studies have shown that array based comparative genomic hybridization (array CGH) is a powerful tool for the detection of copy number changes in the genome of individuals with a congenital disorder. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
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. -
Structures, Functions, and Mechanisms of Filament Forming Enzymes: a Renaissance of Enzyme Filamentation
Structures, Functions, and Mechanisms of Filament Forming Enzymes: A Renaissance of Enzyme Filamentation A Review By Chad K. Park & Nancy C. Horton Department of Molecular and Cellular Biology University of Arizona Tucson, AZ 85721 N. C. Horton ([email protected], ORCID: 0000-0003-2710-8284) C. K. Park ([email protected], ORCID: 0000-0003-1089-9091) Keywords: Enzyme, Regulation, DNA binding, Nuclease, Run-On Oligomerization, self-association 1 Abstract Filament formation by non-cytoskeletal enzymes has been known for decades, yet only relatively recently has its wide-spread role in enzyme regulation and biology come to be appreciated. This comprehensive review summarizes what is known for each enzyme confirmed to form filamentous structures in vitro, and for the many that are known only to form large self-assemblies within cells. For some enzymes, studies describing both the in vitro filamentous structures and cellular self-assembly formation are also known and described. Special attention is paid to the detailed structures of each type of enzyme filament, as well as the roles the structures play in enzyme regulation and in biology. Where it is known or hypothesized, the advantages conferred by enzyme filamentation are reviewed. Finally, the similarities, differences, and comparison to the SgrAI system are also highlighted. 2 Contents INTRODUCTION…………………………………………………………..4 STRUCTURALLY CHARACTERIZED ENZYME FILAMENTS…….5 Acetyl CoA Carboxylase (ACC)……………………………………………………………………5 Phosphofructokinase (PFK)……………………………………………………………………….6 -
A Path Towards SARS-Cov-2 Attenuation: Metabolic Pressure on CTP Synthesis Rules the Virus Evolution
bioRxiv preprint doi: https://doi.org/10.1101/2020.06.20.162933; this version posted June 21, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 1 A path towards SARS-CoV-2 attenuation: metabolic pressure on CTP synthesis rules the virus evolution Zhihua Ou1,2, Christos Ouzounis3, Daxi Wang1,2, Wanying Sun1,2,4, Junhua Li1,2, Weijun Chen2,5*, Philippe Marlière6, Antoine Danchin7,8* 1. BGI-Shenzhen, Shenzhen 518083, China. 2. Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen 518083, China. 3. Biological Computation and Process Laboratory, Centre for Research and Technology Hellas, Chemical Process and Energy Resources Institute, Thessalonica 57001, Greece 4. BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, 518083, China. 5. BGI PathoGenesis Pharmaceutical Technology, BGI-Shenzhen, Shenzhen, China. 6. TESSSI, The European Syndicate of Synthetic Scientists and Industrialists, 81 rue Réaumur, 75002, Paris, France 7. Kodikos Labs, Institut Cochin, 24, rue du Faubourg Saint-Jacques Paris 75014, France. 8. School of Biomedical Sciences, Li KaShing Faculty of Medicine, Hong Kong University, 21 Sassoon Road, Pokfulam, Hong Kong. * To whom correspondence should be addressed Tel: +331 4441 2551; Fax: +331 4441 2559 E-mail: [email protected] Correspondence may also be addressed to [email protected] Keywords ABCE1; cytoophidia; innate immunity; Maxwell’s demon; Nsp1; phosphoribosyltransferase; queuine bioRxiv preprint doi: https://doi.org/10.1101/2020.06.20.162933; this version posted June 21, 2020. -
Mouse Ctps2 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Ctps2 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Ctps2 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Ctps2 gene (NCBI Reference Sequence: NM_001168568 ; Ensembl: ENSMUSG00000031360 ) is located on Mouse chromosome X. 19 exons are identified, with the ATG start codon in exon 2 and the TGA stop codon in exon 18 (Transcript: ENSMUST00000033727). Exon 4 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Ctps2 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-31A20 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Male chimeras hemizygous for a gene trapped allele appear normal at E9.5. Exon 4 starts from about 19.23% of the coding region. The knockout of Exon 4 will result in frameshift of the gene. The size of intron 3 for 5'-loxP site insertion: 3028 bp, and the size of intron 4 for 3'-loxP site insertion: 7890 bp. The size of effective cKO region: ~601 bp. The cKO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 4 19 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Ctps2 Homology arm cKO region loxP site Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024
Document downloaded from http://www.elsevier.es, day 26/09/2021. This copy is for personal use. Any transmission of this document by any media or format is strictly prohibited. Nº Ref Uniprot Proteína Péptidos identificados 1 P01024 CO3_HUMAN Complement C3 OS=Homo sapiens GN=C3 PE=1 SV=2 por 162MS/MS 2 P02751 FINC_HUMAN Fibronectin OS=Homo sapiens GN=FN1 PE=1 SV=4 131 3 P01023 A2MG_HUMAN Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 128 4 P0C0L4 CO4A_HUMAN Complement C4-A OS=Homo sapiens GN=C4A PE=1 SV=1 95 5 P04275 VWF_HUMAN von Willebrand factor OS=Homo sapiens GN=VWF PE=1 SV=4 81 6 P02675 FIBB_HUMAN Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 78 7 P01031 CO5_HUMAN Complement C5 OS=Homo sapiens GN=C5 PE=1 SV=4 66 8 P02768 ALBU_HUMAN Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 66 9 P00450 CERU_HUMAN Ceruloplasmin OS=Homo sapiens GN=CP PE=1 SV=1 64 10 P02671 FIBA_HUMAN Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 58 11 P08603 CFAH_HUMAN Complement factor H OS=Homo sapiens GN=CFH PE=1 SV=4 56 12 P02787 TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3 54 13 P00747 PLMN_HUMAN Plasminogen OS=Homo sapiens GN=PLG PE=1 SV=2 48 14 P02679 FIBG_HUMAN Fibrinogen gamma chain OS=Homo sapiens GN=FGG PE=1 SV=3 47 15 P01871 IGHM_HUMAN Ig mu chain C region OS=Homo sapiens GN=IGHM PE=1 SV=3 41 16 P04003 C4BPA_HUMAN C4b-binding protein alpha chain OS=Homo sapiens GN=C4BPA PE=1 SV=2 37 17 Q9Y6R7 FCGBP_HUMAN IgGFc-binding protein OS=Homo sapiens GN=FCGBP PE=1 SV=3 30 18 O43866 CD5L_HUMAN CD5 antigen-like OS=Homo -
Ehrlichia Chaffeensis
RESEARCH ARTICLE Ehrlichia chaffeensis TRP47 enters the nucleus via a MYND-binding domain-dependent mechanism and predominantly binds enhancers of host genes associated with signal transduction, cytoskeletal organization, and immune response a1111111111 1 1 2 1 1 a1111111111 Clayton E. KiblerID , Sarah L. Milligan , Tierra R. Farris , Bing Zhu , Shubhajit Mitra , Jere a1111111111 W. McBride1,2,3,4,5* a1111111111 a1111111111 1 Department of Pathology, University of Texas Medical Branch, Galveston, Texas, United States of America, 2 Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, Texas, United States of America, 3 Center for Biodefense and Emerging Infectious Diseases, University of Texas Medical Branch, Galveston, Texas, United States of America, 4 Sealy Center for Vaccine Development, University of Texas Medical Branch, Galveston, Texas, United States of America, 5 Institute for Human Infections and Immunity, University of Texas Medical Branch, Galveston, Texas, United States of OPEN ACCESS America Citation: Kibler CE, Milligan SL, Farris TR, Zhu B, * [email protected] Mitra S, McBride JW (2018) Ehrlichia chaffeensis TRP47 enters the nucleus via a MYND-binding domain-dependent mechanism and predominantly binds enhancers of host genes associated with Abstract signal transduction, cytoskeletal organization, and immune response. PLoS ONE 13(11): e0205983. Ehrlichia chaffeensis is an obligately intracellular bacterium that establishes infection in https://doi.org/10.1371/journal.pone.0205983 mononuclear phagocytes through largely undefined reprogramming strategies including Editor: Gary M. Winslow, State University of New modulation of host gene transcription. In this study, we demonstrate that the E. chaffeensis York Upstate Medical University, UNITED STATES effector TRP47 enters the host cell nucleus and binds regulatory regions of host genes rele- Received: April 25, 2018 vant to infection. -
190323111.Pdf
Characterization of polymers of nucleotide biosynthetic enzymes By Sajitha Anthony April, 2017 A dissertation presented to the faculty of Drexel University College of Medicine in partial fulfillment for the requirements for the degree of Doctor of Philosophy in Molecular and Cellular Biology and Genetics i ii ACKNOWLEDGEMENTS First and foremost, I would like to thank my mentor Dr. Jeffrey Peterson for all of his support and guidance throughout the five years that I have been in his lab. He has truly inspired me with his tremendous enthusiasm for science and his constant encouragement. He has changed, for the better, the way I approach and see science. I could not have asked for a better mentor. Secondly, I would like to thank my committee members for all of their great ideas and their never-ending support. I thank them for answering all of my questions so patiently and always listening to what I had to say. After every meeting I’ve had with them, I always felt encouraged and confident. I would also like to thank my collaborators over at the University of Washington—Justin Kollman, Anika Burrell, and Matthew Johnson. It has been such a pleasure working with them. The journey of discovery that we took together has been very exciting. This was my first collaboration, and they have made it such a memorable and positive experience. iii I would like to thank my lab members, in particular Alex for being an awesome cubemate, colleague, and friend. He has been the sounding board for so many of my project’s ideas over the years and has given such knowledgeable input. -
The Emergence of Pattern Discovery Techniques in Computational Biology
Metabolic Engineering, 2(3):159-177, July 2000 The Emergence Of Pattern Discovery Techniques In Computational Biology Isidore Rigoutsos1 Aris Floratos Laxmi Parida Yuan Gao Daniel Platt Bioinformatics and Pattern Discovery Group IBM TJ Watson Research Center Yorktown Heights, NY 10598. October 17, 1999 / Revised: March 24 2000 Abstract In the last few years, pattern discovery has been emerging as a generic tool of choice for tackling problems from the computational biology domain. In this presentation, and after defining the problem in its generality, we review some of the algorithms that have appeared in the literature, and describe several applications of pattern discovery to problems from computational biology. 1. Introduction Recent years have witnessed an emergence of pattern discovery methodologies for solving numerous tasks which arise in computational biology. Known also as ‘data mining’ approaches, they represent a novel approach for extracting useful information from databases containing various types of biological information. Initially, dynamic programming techniques were applied to the analysis of biological sequences and to the determination of sequence similarity between a query sequence and one or more biological sequences (DNA, proteins, and fragments) from a collection. Subsequent studies of such sequence similarity revealed conserved functional and structural signals, thus making the argument for the usefulness of such approaches. Research effort spanning almost two decades gave rise to a number of useful algorithms and an abundance of interesting scientific results [58,77,63,2]. Almost in parallel, researchers began looking into other approaches in an effort to develop concise consensus sequences that captured and represented regions of similarity across several sequences presumed to be related.