In silico Identification and Taxonomic Distribution of Plant Class C GH9 Endoglucanases
Identifieur interne : 002158 ( Ncbi/Merge ); précédent : 002157; suivant : 002159In silico Identification and Taxonomic Distribution of Plant Class C GH9 Endoglucanases
Auteurs : Siddhartha Kundu [Inde] ; Rita Sharma [Inde]Source :
- Frontiers in Plant Science [ 1664-462X ] ; 2016.
Abstract
The glycoside hydrolase 9 superfamily, mainly comprising the endoglucanases, is represented in all three domains of life. The current division of GH9 enzymes, into three subclasses, namely A, B, and C, is centered on parameters derived from sequence information alone. However, this classification is ambiguous, and is limited by the paralogous ancestry of classes B and C endoglucanases, and paucity of biochemical and structural data. Here, we extend this classification schema to putative GH9 endoglucanases present in green plants, with an emphasis on identifying novel members of the class C subset. These enzymes cleave the β(1 → 4) linkage between non-terminal adjacent D-glucopyranose residues, in both, amorphous and crystalline regions of cellulose. We utilized non redundant plant GH9 enzymes with characterized molecular data, as the training set to construct Hidden Markov Models (HMMs) and train an Artificial Neural Network (ANN). The parameters that were used for predicting dominant enzyme function, were derived from this training set, and subsequently refined on 147 sequences with available expression data. Our knowledge-based approach, can ascribe differential endoglucanase activity (A, B, or C) to a query sequence with high confidence, and was used to construct a local repository of class C GH9 endoglucanases (
Url:
DOI: 10.3389/fpls.2016.01185
PubMed: 27570528
PubMed Central: 4981690
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PMC:4981690Le document en format XML
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Identification and Taxonomic Distribution of Plant Class C GH9 Endoglucanases</title>
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Identification and Taxonomic Distribution of Plant Class C GH9 Endoglucanases</title>
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<front><div type="abstract" xml:lang="en"><p>The glycoside hydrolase 9 superfamily, mainly comprising the endoglucanases, is represented in all three domains of life. The current division of GH9 enzymes, into three subclasses, namely A, B, and C, is centered on parameters derived from sequence information alone. However, this classification is ambiguous, and is limited by the paralogous ancestry of classes B and C endoglucanases, and paucity of biochemical and structural data. Here, we extend this classification schema to putative GH9 endoglucanases present in green plants, with an emphasis on identifying novel members of the class C subset. These enzymes cleave the β(1 → 4) linkage between non-terminal adjacent D-glucopyranose residues, in both, amorphous and crystalline regions of cellulose. We utilized non redundant plant GH9 enzymes with characterized molecular data, as the training set to construct Hidden Markov Models (HMMs) and train an Artificial Neural Network (ANN). The parameters that were used for predicting dominant enzyme function, were derived from this training set, and subsequently refined on 147 sequences with available expression data. Our knowledge-based approach, can ascribe differential endoglucanase activity (A, B, or C) to a query sequence with high confidence, and was used to construct a local repository of class C GH9 endoglucanases (<italic>GH</italic>
9<italic>C</italic>
= 241) from 32 sequenced green plants.</p>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Front Plant Sci</journal-id>
<journal-id journal-id-type="iso-abbrev">Front Plant Sci</journal-id>
<journal-id journal-id-type="publisher-id">Front. Plant Sci.</journal-id>
<journal-title-group><journal-title>Frontiers in Plant Science</journal-title>
</journal-title-group>
<issn pub-type="epub">1664-462X</issn>
<publisher><publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">27570528</article-id>
<article-id pub-id-type="pmc">4981690</article-id>
<article-id pub-id-type="doi">10.3389/fpls.2016.01185</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Plant Science</subject>
<subj-group><subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group><article-title><italic>In silico</italic>
Identification and Taxonomic Distribution of Plant Class C GH9 Endoglucanases</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Kundu</surname>
<given-names>Siddhartha</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup>
</xref>
<xref ref-type="author-notes" rid="fn001"><sup>*</sup>
</xref>
<uri xlink:type="simple" xlink:href="http://loop.frontiersin.org/people/174292/overview"></uri>
</contrib>
<contrib contrib-type="author"><name><surname>Sharma</surname>
<given-names>Rita</given-names>
</name>
<xref ref-type="aff" rid="aff3"><sup>3</sup>
</xref>
<xref ref-type="author-notes" rid="fn002"><sup>*</sup>
</xref>
<uri xlink:type="simple" xlink:href="http://loop.frontiersin.org/people/86227/overview"></uri>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup>
<institution>Department of Biochemistry, Dr. Baba Saheb Ambedkar Medical College & Hospital</institution>
<country>New Delhi, India</country>
</aff>
<aff id="aff2"><sup>2</sup>
<institution>Mathematical and Computational Biology, Information Technology Research Academy, Media Lab Asia</institution>
<country>New Delhi, India</country>
</aff>
<aff id="aff3"><sup>3</sup>
<institution>School of Computational and Integrative Sciences, Jawaharlal Nehru University</institution>
<country>New Delhi, India</country>
</aff>
<author-notes><fn fn-type="edited-by"><p>Edited by: Manisha Goel, University of Delhi, India</p>
</fn>
<fn fn-type="edited-by"><p>Reviewed by: Michael Poidinger, Singapore Immunology Network, Singapore; Arthur Gruber, University of São Paulo, Brazil</p>
</fn>
<corresp id="fn001">*Correspondence: Siddhartha Kundu <email xlink:type="simple">siddhartha_kundu@yahoo.co.in</email>
</corresp>
<corresp id="fn002">Rita Sharma <email xlink:type="simple">rita.genomics@gmail.com</email>
</corresp>
<fn fn-type="other" id="fn003"><p>This article was submitted to Bioinformatics and Computational Biology, a section of the journal Frontiers in Plant Science</p>
</fn>
</author-notes>
<pub-date pub-type="epub"><day>12</day>
<month>8</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="collection"><year>2016</year>
</pub-date>
<volume>7</volume>
<elocation-id>1185</elocation-id>
<history><date date-type="received"><day>04</day>
<month>4</month>
<year>2016</year>
</date>
<date date-type="accepted"><day>22</day>
<month>7</month>
<year>2016</year>
</date>
</history>
<permissions><copyright-statement>Copyright © 2016 Kundu and Sharma.</copyright-statement>
<copyright-year>2016</copyright-year>
<copyright-holder>Kundu and Sharma</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract><p>The glycoside hydrolase 9 superfamily, mainly comprising the endoglucanases, is represented in all three domains of life. The current division of GH9 enzymes, into three subclasses, namely A, B, and C, is centered on parameters derived from sequence information alone. However, this classification is ambiguous, and is limited by the paralogous ancestry of classes B and C endoglucanases, and paucity of biochemical and structural data. Here, we extend this classification schema to putative GH9 endoglucanases present in green plants, with an emphasis on identifying novel members of the class C subset. These enzymes cleave the β(1 → 4) linkage between non-terminal adjacent D-glucopyranose residues, in both, amorphous and crystalline regions of cellulose. We utilized non redundant plant GH9 enzymes with characterized molecular data, as the training set to construct Hidden Markov Models (HMMs) and train an Artificial Neural Network (ANN). The parameters that were used for predicting dominant enzyme function, were derived from this training set, and subsequently refined on 147 sequences with available expression data. Our knowledge-based approach, can ascribe differential endoglucanase activity (A, B, or C) to a query sequence with high confidence, and was used to construct a local repository of class C GH9 endoglucanases (<italic>GH</italic>
9<italic>C</italic>
= 241) from 32 sequenced green plants.</p>
</abstract>
<kwd-group><kwd>artificial neural network</kwd>
<kwd>carbohydrate binding module</kwd>
<kwd>cellulose</kwd>
<kwd>endoglucanase</kwd>
<kwd>glycoside hydrolase</kwd>
<kwd>hidden markov models</kwd>
</kwd-group>
<counts><fig-count count="7"></fig-count>
<table-count count="5"></table-count>
<equation-count count="22"></equation-count>
<ref-count count="104"></ref-count>
<page-count count="21"></page-count>
<word-count count="12519"></word-count>
</counts>
</article-meta>
</front>
</pmc>
<affiliations><list><country><li>Inde</li>
</country>
</list>
<tree><country name="Inde"><noRegion><name sortKey="Kundu, Siddhartha" sort="Kundu, Siddhartha" uniqKey="Kundu S" first="Siddhartha" last="Kundu">Siddhartha Kundu</name>
</noRegion>
<name sortKey="Kundu, Siddhartha" sort="Kundu, Siddhartha" uniqKey="Kundu S" first="Siddhartha" last="Kundu">Siddhartha Kundu</name>
<name sortKey="Kundu, Siddhartha" sort="Kundu, Siddhartha" uniqKey="Kundu S" first="Siddhartha" last="Kundu">Siddhartha Kundu</name>
<name sortKey="Sharma, Rita" sort="Sharma, Rita" uniqKey="Sharma R" first="Rita" last="Sharma">Rita Sharma</name>
</country>
</tree>
</affiliations>
</record>
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