DOCSLIB.ORG

A Unique Cysteine-Rich Zinc Finger Domain Present In

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Unique Cysteine-Rich Zinc Finger Domain Present In http://www.diva-portal.org This is the published version of a paper published in Journal of Biological Chemistry. Citation for the original published paper (version of record): Loderer, C., Jonna, V R., Crona, M., Grinberg, I R., Sahlin, M. et al. (2017) A unique cysteine-rich zinc finger domain present in a majority of class II ribonucleotide reductases mediates catalytic turnover Journal of Biological Chemistry, 292(46): 19044-19054 https://doi.org/10.1074/jbc.M117.806331 Access to the published version may require subscription. N.B. When citing this work, cite the original published paper. Permanent link to this version: http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-73795 ARTICLE cro Author’s Choice A unique cysteine-rich zinc finger domain present in a majority of class II ribonucleotide reductases mediates catalytic turnover Received for publication, July 12, 2017, and in revised form, September 28, 2017 Published, Papers in Press, October 2, 2017, DOI 10.1074/jbc.M117.806331 Christoph Loderer‡, Venkateswara Rao Jonna§, Mikael Crona‡1, Inna Rozman Grinberg‡, Margareta Sahlin‡, Anders Hofer§, Daniel Lundin‡2, and Britt-Marie Sjöberg‡3 From the ‡Department of Biochemistry and Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden and the §Department of Medical Biochemistry, Umeå University, SE-901 87 Umeå, Sweden Edited by Ruma Banerjee Ribonucleotide reductases (RNRs) catalyze the reduction of which are required for DNA synthesis and repair. Because this Downloaded from ribonucleotides to the corresponding deoxyribonucleotides, reaction is the only known biological pathway for de novo used in DNA synthesis and repair. Two different mechanisms deoxyribonucleotide synthesis, RNRs are considered to be help deliver the required electrons to the RNR active site. For- essential for every living organism. Today, three different mate can be used as reductant directly in the active site, or glu- classes of RNRs are known, which all share a common fold and taredoxins or thioredoxins reduce a C-terminal cysteine pair, a general reaction mechanism based on a thiyl radical (1). All http://www.jbc.org/ which then delivers the electrons to the active site. Here, we known RNRs, except a few viral RNRs, also share an allosteric characterized a novel cysteine-rich C-terminal domain (CRD), substrate-specificity regulation, where binding of a dNTP or which is present in most class II RNRs found in microbes. The ATP molecule modulates the specificity of the active site of the NrdJd-type RNR from the bacterium Stackebrandtia nassauen- enzyme (1). The three classes share a common ancestor (2); the sis was used as a model enzyme. We show that the CRD is main difference between them is their mechanism of radical involved in both higher oligomeric state formation and electron generation (1, 3). With the different radical, generating mech- at Stockholms Universitetsbibliotek on January 23, 2018 transfer to the active site. The CRD-dependent formation of anisms follow differences in dependence of oxygen and oligo- high oligomers, such as tetramers and hexamers, was induced by meric composition. addition of dATP or dGTP, but not of dTTP or dCTP. The elec- Class I RNRs (NrdAB/NrdEF) generate the radical in a sepa- tron transfer was mediated by an array of six cysteine residues at rate subunit (␤, NrdB/F) via a dimetal center that is oxidized by the very C-terminal end, which also coordinated a zinc atom. molecular oxygen. The radical is then transferred to the cata- The electron transfer can also occur between subunits, depend- lytic subunit (␣, NrdA/E) and back after the catalytic cycle. ␣ ␤ ing on the enzyme’s oligomeric state. An investigation of the Thus, this class is oxygen-dependent and forms active 2 2 native reductant of the system revealed no interaction with glu- heterotetramers. Terminal reduction of the oxidized active site taredoxins or thioredoxins, indicating that this class II RNR uses in ␣ is performed by thioredoxin or glutaredoxin systems at the a different electron source. Our results indicate that the CRD end of each turnover (4, 5). has a crucial role in catalytic turnover and a potentially new Class III RNRs (NrdD) also require a separate subunit (NrdG) terminal reduction mechanism and suggest that the CRD is to generate the radical. An iron–sulfur cluster in NrdG confers important for the activities of many class II RNRs. homolytic cleavage of the cofactor S-adenosyl-L-methionine (AdoMet) that generates a stable glycyl radical in the catalytic subunit. This glycyl radical is extremely sensitive toward oxy- Ribonucleotide reductases (RNRs)4 catalyze the reduction of gen, leading to protein backbone cleavage at oxygen exposition. ribonucleotides to the corresponding deoxyribonucleotides, ␣ NrdDs are described to be active as 2 homodimers and NrdG This work was supported by Swedish Research Council Grant 2016–01920 is only needed to generate the glycyl radical in NrdD (6, 7). and Swedish Cancer Society Grant CAN 2016/670 and by the Wenner-Gren Formate was shown to be a terminal reducing agent for some Foundations, Carl Trygger’s Foundation, and Kempe Foundations. The NrdD enzymes (8). Recently, class III RNRs that use a thiore- authors declare that they have no conflicts of interest with the contents of this article. doxin system for terminal reduction have been described (9). Author’s Choice—Final version free via Creative Commons CC-BY license. The RNR that is the focus of the current study, class II (NrdJ), This article contains supplemental Table S1 and supplemental data. generates the radical via homolytic cleavage of the vitamin B 1 Present address: Swedish Orphan Biovitrum AB, SE-112 76 Solna, Sweden. 12 2 To whom correspondence may be addressed. Tel.: 46-708-123-922; Fax: coenzyme (AdoCbl) within the enzyme, close to the active site. 46-8-155597; E-mail: [email protected]. After the catalytic cycle, AdoCbl is reconstituted (10). This 3 To whom correspondence may be addressed. Tel.: 46-8-164150; Fax: 46-8- mechanism makes NrdJ enzymes independent of oxygen, but 155597; E-mail: [email protected]. 4 The abbreviations used are: RNR, ribonucleotide reductase; AdoCbl, adeno- sylcobalamin; AdoMet, S-adenosyl-L-methionine; CRD, cysteine-rich C-ter- minal domain; GEMMA, gas phase electrophoretic macromolecule analy- class II RNR; NrdJd⌬CRD, the C-terminally deleted version of the S. sis; HED, 2-hydroxyethyl disulfide; ICP, inductively coupled plasma nassauensis class II RNR; SEC, size exclusion chromatography; TCEP, analysis; ICP-OES, inductively coupled plasma optical emission spectrom- tris(2-carboxyethyl)phosphine hydrochloride; IPTG, isopropyl 1-thio-␤-D- etry; NrdJd-wt, the full-length version of the Stackebrandtia nassauensis galactopyranoside. 19044 J. Biol. Chem. (2017) 292(46) 19044–19054 © 2017 by The American Society for Biochemistry and Molecular Biology, Inc. Published in the U.S.A. Catalytic turnover in class II ribonucleotide reductase Downloaded from http://www.jbc.org/ at Stockholms Universitetsbibliotek on January 23, 2018 Figure 1. Abundance and sequence of CRD were studied by phylogenetic and sequence analysis of NrdJ and NrdJd. A, maximum likelihood phyloge- netic tree of a representative selection of NrdJ sequences. Subclasses with characterized members (NrdJm (green), NrdJd (red), and NrdJaϩb(yellow)) and candidate subclasses (cyan, purple, orange, and light blue) are indicated with color. Lactobacillus leichmannii RNR (Ll) is located in subclass NrdJm, whereas the RNR from Thermotoga maritima (Tm) is not part of a defined subclass. B, appearance of the cysteine-rich domain mapped on a phylogenetic tree of a selection of nonmonomeric NrdJ sequences. The selected subset is marked by the dotted line in A. Subclasses with characterized members (NrdJd (red) and NrdJaϩb (yellow)) and candidate subclasses (cyan, purple, orange, and light blue) are indicated with color. The presence of a CRD is indicated with a blue circle, absence with a white circle. The NrdJaϩb subclass has the encoded CRD as a separate gene. C, logo of the CRD derived from 217 nonredundant sequences from subclasses NrdJd and unclassified NrdJ. instead dependent on B12. The oligomeric organization of the class II RNRs contain a so far undescribed cysteine-rich C-ter- NrdJ enzymes is more diverse than in the other classes. Some minal domain (CRD). We show that the CRD is involved in representatives, such as the enzyme from Thermoplasma aci- oligomerization and the terminal reduction of the class II RNR ␣ dophilum, have been shown to be active as 2 homodimers (11); from Stackebrandtia nassauensis and that the CRD hence plays the NrdJ from Lactobacillus leichmannii is active as monomer, a crucial role in the catalytic cycle of class II RNRs. where an additional domain mimics the dimer interface, required for allosteric regulation (12). Higher oligomers have Results been observed for the full-length NrdJ from Thermotoga mari- Phylogenetic analysis tima, whereas a truncated variant utilized for X-ray crystallog- We estimated a maximum likelihood phylogenetic tree from raphy crystallized as a dimer (13). The terminal reductant is an alignment of sequences representing the full diversity of poorly studied for NrdJ enzymes. The monomeric NrdJ from NrdJ sequences at the 75% identity level (Fig. 1A; supplemental L. leichmannii was shown to receive electrons from thioredoxin data). The resolution increased after exclusion of sequences (14), but for other NrdJ enzymes reduction by thioredoxin or from the monomeric class II
Load more

Recommended publications
  • Treebase: an R Package for Discovery, Access and Manipulation of Online Phylogenies
    Methods in Ecology and Evolution 2012, 3, 1060–1066 doi: 10.1111/j.2041-210X.2012.00247.x APPLICATION Treebase: an R package for discovery, access and manipulation of online phylogenies Carl Boettiger1* and Duncan Temple Lang2 1Center for Population Biology, University of California, Davis, CA,95616,USA; and 2Department of Statistics, University of California, Davis, CA,95616,USA Summary 1. The TreeBASE portal is an important and rapidly growing repository of phylogenetic data. The R statistical environment has also become a primary tool for applied phylogenetic analyses across a range of questions, from comparative evolution to community ecology to conservation planning. 2. We have developed treebase, an open-source software package (freely available from http://cran.r-project. org/web/packages/treebase) for the R programming environment, providing simplified, programmatic and inter- active access to phylogenetic data in the TreeBASE repository. 3. We illustrate how this package creates a bridge between the TreeBASE repository and the rapidly growing collection of R packages for phylogenetics that can reduce barriers to discovery and integration across phyloge- netic research. 4. We show how the treebase package can be used to facilitate replication of previous studies and testing of methods and hypotheses across a large sample of phylogenies, which may help make such important reproduc- ibility practices more common. Key-words: application programming interface, database, programmatic, R, software, TreeBASE, workflow include, but are not limited to, ancestral state reconstruction Introduction (Paradis 2004; Butler & King 2004), diversification analysis Applications that use phylogenetic information as part of their (Paradis 2004; Rabosky 2006; Harmon et al.
    [Show full text]
  • Biocreative 2012 Proceedings
    Proceedings of 2012 BioCreative Workshop April 4 -5, 2012 Washington, DC USA Editors: Cecilia Arighi Kevin Cohen Lynette Hirschman Martin Krallinger Zhiyong Lu Carolyn Mattingly Alfonso Valencia Thomas Wiegers John Wilbur Cathy Wu 2012 BioCreative Workshop Proceedings Table of Contents Preface…………………………………………………………………………………….......... iv Committees……………………………………………………………………………………... v Workshop Agenda…………………………………………………………………………….. vi Track 1 Collaborative Biocuration-Text Mining Development Task for Document Prioritization for Curation……………………………………..……………………………………………….. 2 T Wiegers, AP Davis, and CJ Mattingly System Description for the BioCreative 2012 Triage Task ………………………………... 20 S Kim, W Kim, CH Wei, Z Lu and WJ Wilbur Ranking of CTD articles and interactions using the OntoGene pipeline ……………..….. 25 F Rinaldi, S Clematide and S Hafner Selection of relevant articles for curation for the Comparative Toxicogenomic Database…………………………………………………………………………………………. 31 D Vishnyakova, E Pasche and P Ruch CoIN: a network exploration for document triage………………………………................... 39 YY Hsu and HY Kao DrTW: A Biomedical Term Weighting Method for Document Recommendation ………... 45 JH Ju, YD Chen and JH Chiang C2HI: a Complete CHemical Information decision system……………………………..….. 52 CH Ke, TLM Lee and JH Chiang Track 2 Overview of BioCreative Curation Workshop Track II: Curation Workflows….…………... 59 Z Lu and L Hirschman WormBase Literature Curation Workflow ……………………………………………………. 66 KV Auken, T Bieri, A Cabunoc, J Chan, Wj Chen, P Davis, A Duong, R Fang, C Grove, Tw Harris, K Howe, R Kishore, R Lee, Y Li, Hm Muller, C Nakamura, B Nash, P Ozersky, M Paulini, D Raciti, A Rangarajan, G Schindelman, Ma Tuli, D Wang, X Wang, G Williams, K Yook, J Hodgkin, M Berriman, R Durbin, P Kersey, J Spieth, L Stein and Pw Sternberg Literature curation workflow at The Arabidopsis Information Resource (TAIR)…..……… 72 D Li, R Muller, TZ Berardini and E Huala Summary of Curation Process for one component of the Mouse Genome Informatics Database Resource …………………………………………………………………………....
    [Show full text]
  • TESE Kelma Sirleide De Souza.Pdf
    UNIVERSIDADE FEDERAL DE PERNAMBUCO CENTRO DE CIÊNCIAS BIOLÓGICAS PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIAS BIOLÓGICAS KELMA SIRLEIDE DE SOUZA Efeitos bioquímicos e genotóxicos de poluentes na ostra Crassostrea sp., na região norte do complexo estuarino Canal de Santa Cruz, litoral norte de Pernambuco Recife 2016 KELMA SIRLEIDE DE SOUZA Efeitos bioquímicos e genotóxicos de poluentes na ostra Crassostrea sp., na região norte do complexo estuarino Canal de Santa Cruz, litoral norte de Pernambuco Tese apresentada ao Programa de Pós- Graduação em Ciências Biológicas da Universidade Federal de Pernambuco como pré- requisito para a obtenção do grau de doutor em Ciências Biológicas. Orientador: Prof. Dr. Ranilson de Souza Bezerra Co- Orientador: Dr. Caio Rodrigo Dias de Assis Recife 2016 Catalogação na fonte Elaine Barroso CRB 1728 Souza, Kelma Sirleide de Efeitos bioquímicos e genotóxicos de poluentes na ostra Crassostrea sp. na região norte do complexo estuarino Canal de Santa Cruz, litoral norte de Pernambuco / Kelma Sirleide de Souza - Recife: O Autor, 2016. 91 folhas: il., fig., tab. Orientador: Ranilson de Souza Bezerra Coorientador: Caio Rodrigo Silva de Assis Tese (doutorado) – Universidade Federal de Pernambuco. Centro de Biociências. Ciências Biológicas, 2016. Inclui referências 1. Ostras 2. Estuários 3. Santa Cruz, Canal de (PE) I. Bezerra, Ranilson de Souza (orient.) II. Assis, Caio Rodrigo Silva de (coorient.) III. Título 594.4 CDD (22.ed.) UFPE/CB-2017- 406 KELMA SIRLEIDE DE SOUZA Efeitos bioquímicos e genotóxicos de poluentes na ostra Crassostrea sp., na região norte do complexo estuarino Canal de Santa Cruz, litoral norte de Pernambuco Tese apresentada ao Programa de Pós- Graduação em Ciências Biológicas da Universidade Federal de Pernambuco como pré- requisito para a obtenção do grau de doutor em Ciências Biológicas.
    [Show full text]
  • Tutorial: Environment for Tree Exploration Release 3.0.0B7
    Tutorial: Environment for Tree Exploration Release 3.0.0b7 Jaime Huerta-Cepas November 25, 2015 Contents 1 Changelog history3 1.1 What’s new in ETE 2.3...................................3 1.2 What’s new in ETE 2.2...................................5 1.3 What’s new in ETE 2.1...................................9 2 The ETE tutorial 13 2.1 Working With Tree Data Structures............................ 13 2.2 The Programmable Tree Drawing Engine......................... 43 2.3 Phylogenetic Trees..................................... 64 2.4 Clustering Trees...................................... 80 2.5 Phylogenetic XML standards............................... 85 2.6 Interactive web tree visualization............................. 93 2.7 Testing Evolutionary Hypothesis.............................. 95 2.8 Dealing with the NCBI Taxonomy database........................ 105 2.9 SCRIPTS: orthoXML................................... 108 3 ETE’s Reference Guide 115 3.1 Master Tree class...................................... 115 3.2 Treeview module...................................... 127 3.3 PhyloTree class....................................... 138 3.4 Clustering module..................................... 141 3.5 Nexml module....................................... 142 3.6 Phyloxml Module..................................... 158 3.7 Seqgroup class....................................... 161 3.8 WebTreeApplication object................................ 161 3.9 EvolTree class....................................... 162 3.10 NCBITaxa class.....................................
    [Show full text]
  • Dendropy Tutorial Release 3.12.1
    DendroPy Tutorial Release 3.12.1 Jeet Sukumaran and Mark T. Holder March 22, 2014 Contents i ii CHAPTER 1 Phylogenetic Data in DendroPy 1.1 Introduction to Phylogenetic Data Objects 1.1.1 Types of Phylogenetic Data Objects Phylogenetic data in DendroPy is represented by one or more objects of the following classes: Taxon A representation of an operational taxonomic unit, with an attribute, label, corresponding to the taxon label. TaxonSet A collection of Taxon objects representing a distinct definition of taxa (for example, as specified explicitly in a NEXUS “TAXA” block, or implicitly in the set of all taxon labels used across a Newick tree file). Tree A collection of Node and Edge objects representing a phylogenetic tree. Each Tree object maintains a reference to a TaxonSet object in its attribute, taxon_set, which specifies the set of taxa that are referenced by the tree and its nodes. Each Node object has a taxon attribute (which points to a particular Taxon object if there is an operational taxonomic unit associated with this node, or is None if not), a parent_node attribute (which will be None if the Node has no parent, e.g., a root node), a Edge attribute, as well as a list of references to child nodes, a copy of which can be obtained by calling child_nodes. TreeList A list of Tree objects. A TreeList object has an attribute, taxon_set, which speci- fies the set of taxa that are referenced by all member Tree elements. This is enforced when a Tree object is added to a TreeList, with the TaxonSet of the Tree object and all Taxon references of the Node objects in the Tree mapped to the TaxonSet of the TreeList.
    [Show full text]
  • Tutorial: Environment for Tree Exploration Release 2.3.6
    Tutorial: Environment for Tree Exploration Release 2.3.6 Jaime Huerta-Cepas August 11, 2015 Contents 1 Changelog history3 1.1 What’s new in ETE 2.3...................................3 1.2 What’s new in ETE 2.2...................................5 1.3 What’s new in ETE 2.1...................................9 2 The ETE tutorial 13 2.1 Working With Tree Data Structures............................ 13 2.2 The Programmable Tree Drawing Engine......................... 43 2.3 Phylogenetic Trees..................................... 63 2.4 Clustering Trees...................................... 80 2.5 Phylogenetic XML standards............................... 85 2.6 Interactive web tree visualization............................. 92 2.7 Testing Evolutionary Hypothesis.............................. 94 2.8 Dealing with the NCBI Taxonomy database........................ 104 2.9 SCRIPTS: orthoXML................................... 108 3 ETE’s Reference Guide 115 3.1 Master Tree class...................................... 115 3.2 Treeview module...................................... 127 3.3 PhyloTree class....................................... 137 3.4 Clustering module..................................... 140 3.5 Nexml module....................................... 142 3.6 Phyloxml Module..................................... 157 3.7 Seqgroup class....................................... 160 3.8 WebTreeApplication object................................ 161 3.9 EvolTree class....................................... 161 3.10 NCBITaxa class.....................................
    [Show full text]
  • The DBCLS Biohackathon: Standardization and Interoperability for Bioinformatics Web Services and Workflows
    UC San Diego UC San Diego Previously Published Works Title The DBCLS BioHackathon: standardization and interoperability for bioinformatics web services and workflows Permalink https://escholarship.org/uc/item/6v60h2hh Journal Journal of Biomedical Semantics, 1(1) ISSN 2041-1480 Authors Katayama, Toshiaki Arakawa, Kazuharu Nakao, Mitsuteru et al. Publication Date 2010-08-21 DOI http://dx.doi.org/10.1186/2041-1480-1-8 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Katayama et al. Journal of Biomedical Semantics 2010, 1:8 http://www.jbiomedsem.com/content/1/1/8 JOURNAL OF BIOMEDICAL SEMANTICS REVIEW Open Access The DBCLS BioHackathon: standardization and interoperability for bioinformatics web services and workflows. The DBCLS BioHackathon Consortium* Toshiaki Katayama*, Kazuharu Arakawa, Mitsuteru Nakao, Keiichiro Ono, Kiyoko F Aoki-Kinoshita, Yasunori Yamamoto, Atsuko Yamaguchi, Shuichi Kawashima, Hong-Woo Chun, Jan Aerts, Bruno Aranda, Lord Hendrix Barboza, Raoul JP Bonnal, Richard Bruskiewich, Jan C Bryne, José M Fernández, Akira Funahashi, Paul MK Gordon, Naohisa Goto, Andreas Groscurth, Alex Gutteridge, Richard Holland, Yoshinobu Kano, Edward A Kawas, Arnaud Kerhornou, Eri Kibukawa, Akira R Kinjo, Michael Kuhn, Hilmar Lapp, Heikki Lehvaslaiho, Hiroyuki Nakamura, Yasukazu Nakamura, Tatsuya Nishizawa, Chikashi Nobata, Tamotsu Noguchi, Thomas M Oinn, Shinobu Okamoto, Stuart Owen, Evangelos Pafilis, Matthew Pocock, Pjotr Prins, René Ranzinger, Florian Reisinger, Lukasz Salwinski, Mark Schreiber,
    [Show full text]
  • The Biological Object Notation (BON): a Structured Fle Format for Biological Data Received: 19 January 2018 Jan P
    www.nature.com/scientificreports OPEN The Biological Object Notation (BON): a structured fle format for biological data Received: 19 January 2018 Jan P. Buchmann 1, Mathieu Fourment2 & Edward C. Holmes 1 Accepted: 13 June 2018 The large size and high complexity of biological data can represent a major methodological challenge Published: xx xx xxxx for the analysis and exchange of data sets between computers and applications. There has also been a substantial increase in the amount of metadata associated with biological data sets, which is being increasingly incorporated into existing data formats. Despite the existence of structured formats based on XML, biological data sets are mainly formatted using unstructured fle formats, and the incorporation of metadata results in increasingly complex parsing routines such that they become more error prone. To overcome these problems, we present the “biological object notation” (BON) format, a new way to exchange and parse nearly all biological data sets more efciently and with less error than other currently available formats. Based on JavaScript Object Notation (JSON), BON simplifes parsing by clearly separating the biological data from its metadata and reduces complexity compared to XML based formats. The ability to selectively compress data up to 87% compared to other fle formats and the reduced complexity results in improved transfer times and less error prone applications. Biological data, which includes, but is not limited to molecular sequences, annotations and phylogenetic trees, are still predominantly exchanged as fat fles or in line-based formats despite the existence of more structured fle notations that are better suited to complex data.
    [Show full text]
  • Nexml: Rich, Extensible, and Verifiable Representation of Comparative Data and Metadata
    Syst. Biol. 61(4):675–689, 2012 c The Author(s) 2012. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. DOI:10.1093/sysbio/sys025 Advance Access publication on February 22, 2012 NeXML: Rich, Extensible, and Verifiable Representation of Comparative Data and Metadata 1, 2,3 4 5 2 RUTGER A. VOS ∗,JAMES P. BALHOFF ,JASON A. CARAVAS ,MARK T. HOLDER ,HILMAR LAPP , WAYNE P. MADDISON6,PETER E. MIDFORD2,ANURAG PRIYAM7,JEET SUKUMARAN5, XUHUA XIA8, AND ARLIN STOLTZFUS9 1NCB Naturalis, Leiden, the Netherlands; 2National Evolutionary Synthesis Center, Durham, NC, USA; 3Department of Biology, University of North Carolina, Chapel Hill, NC, USA; 4Department of Biological Sciences, Wayne State University, USA; 5Department of Ecology and Evolutionary Biology, University of Kansas, USA; 6Departments of Zoology and Botany, and Beaty Biodiversity Museum, University of British Columbia, Canada; 7Department of Mechanical Engineering, Indian Institute of Technology Kharagpur, India; 8Department of Biology, University of Ottawa, Canada; and 9Biochemical Science Division, National Institute of Standards and Technology, Gaithersburg, MD, USA; ∗Correspondence to be sent to: NCB Naturalis, Postbus 9517, 2300 RA, Leiden, the Netherlands; E-mail: [email protected]. Received 16 May 2011; reviews returned 29 July 2011; accepted 7 February 2012 Associate Editor: Peter Foster Abstract.—In scientific research, integration and synthesis require a common understanding of where data come from,how much they can be trusted, and what they may be used for.
    [Show full text]
  • Proceedings of Biocreative III Workshop
    Proceedings of 2012 BioCreative Workshop April 4 -5, 2012 Washington, DC USA Editors: Cecilia Arighi Kevin Cohen Lynette Hirschman Martin Krallinger Zhiyong Lu Carolyn Mattingly Alfonso Valencia Thomas Wiegers John Wilbur Cathy Wu 2012 BioCreative Workshop Proceedings Table of Contents Preface…………………………………………………………………………………….......... iv Committees……………………………………………………………………………………... v Workshop Agenda…………………………………………………………………………….. vi Track 1 Collaborative Biocuration-Text Mining Development Task for Document Prioritization for Curation……………………………………..……………………………………………….. 2 T Wiegers, AP Davis, and CJ Mattingly System Description for the BioCreative 2012 Triage Task ………………………………... 20 S Kim, W Kim, CH Wei, Z Lu and WJ Wilbur Ranking of CTD articles and interactions using the OntoGene pipeline ……………..….. 25 F Rinaldi, S Clematide and S Hafner Selection of relevant articles for curation for the Comparative Toxicogenomic Database…………………………………………………………………………………………. 31 D Vishnyakova, E Pasche and P Ruch CoIN: a network exploration for document triage………………………………................... 39 YY Hsu and HY Kao DrTW: A Biomedical Term Weighting Method for Document Recommendation ………... 45 JH Ju, YD Chen and JH Chiang C2HI: a Complete CHemical Information decision system……………………………..….. 52 CH Ke, TLM Lee and JH Chiang Track 2 Overview of BioCreative Curation Workshop Track II: Curation Workflows….…………... 59 Z Lu and L Hirschman WormBase Literature Curation Workflow ……………………………………………………. 66 KV Auken, T Bieri, A Cabunoc, J Chan, Wj Chen, P Davis, A Duong, R Fang, C Grove, Tw Harris, K Howe, R Kishore, R Lee, Y Li, Hm Muller, C Nakamura, B Nash, P Ozersky, M Paulini, D Raciti, A Rangarajan, G Schindelman, Ma Tuli, D Wang, X Wang, G Williams, K Yook, J Hodgkin, M Berriman, R Durbin, P Kersey, J Spieth, L Stein and Pw Sternberg Literature curation workflow at The Arabidopsis Information Resource (TAIR)…..……… 72 D Li, R Muller, TZ Berardini and E Huala Summary of Curation Process for one component of the Mouse Genome Informatics Database Resource …………………………………………………………………………....
    [Show full text]
  • DATA Poster Numbers: P Da001 - 130 Application Posters: P Da001 - 041
    POSTER LIST ORDERED ALPHABETICALLY BY POSTER TITLE GROUPED BY THEME/TRACK THEME/TRACK: DATA Poster numbers: P_Da001 - 130 Application posters: P_Da001 - 041 Poster EasyChair Presenting Author list Title Abstract Theme/track Topics number number author APPLICATION POSTERS WITHIN DATA THEME P_Da001 773 Benoît Carrères, Anne Benoît Carrères A systems approach to explore Microalgae are promising platforms for sustainable biofuel production. They produce triacyl-glycerides (TAG) which are easily converted into biofuel. When exposed to nitrogen limitation, Data/ Application Klok, Maria Suarez Diez, triacylglycerol production in Neochloris Neochloris oleoabundans accumulates up to 40% of its dry weight in TAG. However, a feasible production requires a decrease of production costs, which can be partially reached by Application Lenny de Jaeger, Mark oleoabundans increasing TAG yield.We built a constraint-based model describing primary metabolism of N. oleoabundans. It was grown in combinations of light absorption and nitrate supply rates and the poster Sturme, Packo Lamers, parameters needed for modeling of metabolism were measured. Fluxes were then calculated by flux balance analysis. cDNA samples of 16 experimental conditions were sequenced, Rene' Wijffels, Vitor Dos assembled and functionally annotated. Relative expression changes and relative flux changes for all reactions in the model were compared.The model predicts a maximum TAG yield on light Santos, Peter Schaap of 1.07g (mol photons)-1, more than 3 times current yield under optimal conditions. Furthermore, from optimization scenarios we concluded that increasing light efficiency has much higher and Dirk Martens potential to increase TAG yield than blocking entire pathways.Certain reaction expression patterns suggested an interdependence of the response to nitrogen and light supply.
    [Show full text]
  • Download, Allowing Biologists to Design Custom Analyses of the Data on Their Local Computers
    bioRxiv preprint doi: https://doi.org/10.1101/399030; this version posted August 29, 2018. 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. TreeBASEdmp: A Toolkit for Phyloinformatic Research William H. Piel1,2 and Rutger A. Vos3,4 1Yale-NUS College, 10 College Avenue West #01-101, Singapore 138609 2National University of Singapore, Department of Biological Sciences, Singapore. 3Naturalis Biodiversity Center, P.O. Box 9517, 2300RA Leiden, the Netherlands 4Leiden University, Institute of Biology Leiden, the Netherlands Corresponding author: W. H. Piel; [email protected] Keywords. — TreeBASE, phyloinformatics, supertree, SQL, phylogenetic querying Abstract. — Over the last 20 years, TreeBASE has acquired a substantial body of phylogenetic data, including more than 20,000 published phylogenies. Given latency issues and limited options when it comes to querying the database remotely, a simplified and consolidated version of the database, here called TreeBASEdmp, is made available for download, allowing biologists to design custom analyses of the data on their local computers. The database is indexed to support searching for phylogenetic topologies using nested sets and closure tables. Here we propose a new approach to find broadly-defined phylogenetic patterns, a method we call Generic Topological Querying, which allows the user to find hypotheses of relationship without being constrained to use particular sets of specific taxa. Additionally, we normalize as many leaf nodes as possible to an equivalent species rank identifier to assist in supertree synthesis. Our example script rapidly assembles sets of trees and generates a matrix representation of them for subsequent supertree generation.
    [Show full text]