Detection of Large Numbers of Novel Sequences in the Metatranscriptomes of Complex Marine Microbial Communities
Identifieur interne : 000313 ( Pmc/Curation ); précédent : 000312; suivant : 000314Detection of Large Numbers of Novel Sequences in the Metatranscriptomes of Complex Marine Microbial Communities
Auteurs : Jack A. Gilbert [Royaume-Uni] ; Dawn Field [Royaume-Uni] ; Ying Huang [États-Unis] ; Rob Edwards [États-Unis] ; Weizhong Li [États-Unis] ; Paul Gilna [États-Unis] ; Ian Joint [Royaume-Uni]Source :
- PLoS ONE [ 1932-6203 ] ; 2008.
Abstract
Sequencing the expressed genetic information of an ecosystem (metatranscriptome) can provide information about the response of organisms to varying environmental conditions. Until recently, metatranscriptomics has been limited to microarray technology and random cloning methodologies. The application of high-throughput sequencing technology is now enabling access to both known and previously unknown transcripts in natural communities.
We present a study of a complex marine metatranscriptome obtained from random whole-community mRNA using the GS-FLX Pyrosequencing technology. Eight samples, four DNA and four mRNA, were processed from two time points in a controlled coastal ocean mesocosm study (Bergen, Norway) involving an induced phytoplankton bloom producing a total of 323,161,989 base pairs. Our study confirms the finding of the first published metatranscriptomic studies of marine and soil environments that metatranscriptomics targets highly expressed sequences which are frequently novel. Our alternative methodology increases the range of experimental options available for conducting such studies and is characterized by an exceptional enrichment of mRNA (99.92%) versus ribosomal RNA. Analysis of corresponding metagenomes confirms much higher levels of assembly in the metatranscriptomic samples and a far higher yield of large gene families with >100 members, ∼91% of which were novel.
This study provides further evidence that metatranscriptomic studies of natural microbial communities are not only feasible, but when paired with metagenomic data sets, offer an unprecedented opportunity to explore both structure and function of microbial communities – if we can overcome the challenges of elucidating the functions of so many never-seen-before gene families.
Url:
DOI: 10.1371/journal.pone.0003042
PubMed: 18725995
PubMed Central: 2518522
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>Sequencing the expressed genetic information of an ecosystem (metatranscriptome) can provide information about the response of organisms to varying environmental conditions. Until recently, metatranscriptomics has been limited to microarray technology and random cloning methodologies. The application of high-throughput sequencing technology is now enabling access to both known and previously unknown transcripts in natural communities.</p>
</sec>
<sec><title>Methodology/Principal Findings</title>
<p>We present a study of a complex marine metatranscriptome obtained from random whole-community mRNA using the GS-FLX Pyrosequencing technology. Eight samples, four DNA and four mRNA, were processed from two time points in a controlled coastal ocean mesocosm study (Bergen, Norway) involving an induced phytoplankton bloom producing a total of 323,161,989 base pairs. Our study confirms the finding of the first published metatranscriptomic studies of marine and soil environments that metatranscriptomics targets highly expressed sequences which are frequently novel. Our alternative methodology increases the range of experimental options available for conducting such studies and is characterized by an exceptional enrichment of mRNA (99.92%) versus ribosomal RNA. Analysis of corresponding metagenomes confirms much higher levels of assembly in the metatranscriptomic samples and a far higher yield of large gene families with >100 members, ∼91% of which were novel.</p>
</sec>
<sec><title>Conclusions/Significance</title>
<p>This study provides further evidence that metatranscriptomic studies of natural microbial communities are not only feasible, but when paired with metagenomic data sets, offer an unprecedented opportunity to explore both structure and function of microbial communities – if we can overcome the challenges of elucidating the functions of so many never-seen-before gene families.</p>
</sec>
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<publisher><publisher-name>Public Library of Science</publisher-name>
<publisher-loc>San Francisco, USA</publisher-loc>
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<article-id pub-id-type="pmc">2518522</article-id>
<article-id pub-id-type="publisher-id">08-PONE-RA-04404R1</article-id>
<article-id pub-id-type="doi">10.1371/journal.pone.0003042</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline"><subject>Computational Biology/Metagenomics</subject>
<subject>Computational Biology/Protein Homology Detection</subject>
<subject>Ecology/Environmental Microbiology</subject>
<subject>Ecology/Global Change Ecology</subject>
<subject>Ecology/Marine and Freshwater Ecology</subject>
<subject>Genetics and Genomics/Bioinformatics</subject>
<subject>Molecular Biology/Bioinformatics</subject>
</subj-group>
</article-categories>
<title-group><article-title>Detection of Large Numbers of Novel Sequences in the Metatranscriptomes of Complex Marine Microbial Communities</article-title>
<alt-title alt-title-type="running-head">Novel Marine Metatranscripts</alt-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Gilbert</surname>
<given-names>Jack A.</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
<xref ref-type="corresp" rid="cor1"><sup>*</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Field</surname>
<given-names>Dawn</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Huang</surname>
<given-names>Ying</given-names>
</name>
<xref ref-type="aff" rid="aff3"><sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Edwards</surname>
<given-names>Rob</given-names>
</name>
<xref ref-type="aff" rid="aff4"><sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5"><sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Li</surname>
<given-names>Weizhong</given-names>
</name>
<xref ref-type="aff" rid="aff3"><sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Gilna</surname>
<given-names>Paul</given-names>
</name>
<xref ref-type="aff" rid="aff3"><sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Joint</surname>
<given-names>Ian</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1"><label>1</label>
<addr-line>Plymouth Marine Laboratory, Prospect Place, Plymouth, United Kingdom</addr-line>
</aff>
<aff id="aff2"><label>2</label>
<addr-line>NERC Centre for Ecology and Hydrology, CEH Oxford, Oxford, United Kingdom</addr-line>
</aff>
<aff id="aff3"><label>3</label>
<addr-line>California Institute for Telecommunications and Information Technology, University of California San Diego, La Jolla, California, United States of America</addr-line>
</aff>
<aff id="aff4"><label>4</label>
<addr-line>Department of Computer Science, San Diego State University, San Diego, California, United States of America</addr-line>
</aff>
<aff id="aff5"><label>5</label>
<addr-line>Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois, United States of America</addr-line>
</aff>
<contrib-group><contrib contrib-type="editor"><name><surname>Ahmed</surname>
<given-names>Niyaz</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"></xref>
</contrib>
</contrib-group>
<aff id="edit1">Centre for DNA Fingerprinting and Diagnostics, India</aff>
<author-notes><corresp id="cor1">* E-mail: <email>jagi@pml.ac.uk</email>
</corresp>
<fn fn-type="con"><p>Conceived and designed the experiments: JAG DF IJ. Performed the experiments: JAG. Analyzed the data: JAG DF YH RAE WL PG. Contributed reagents/materials/analysis tools: JAG IJ. Wrote the paper: JAG DF WL IJ.</p>
</fn>
</author-notes>
<pub-date pub-type="collection"><year>2008</year>
</pub-date>
<pub-date pub-type="epub"><day>22</day>
<month>8</month>
<year>2008</year>
</pub-date>
<volume>3</volume>
<issue>8</issue>
<elocation-id>e3042</elocation-id>
<history><date date-type="received"><day>21</day>
<month>4</month>
<year>2008</year>
</date>
<date date-type="accepted"><day>5</day>
<month>8</month>
<year>2008</year>
</date>
</history>
<copyright-statement>Gilbert et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</copyright-statement>
<copyright-year>2008</copyright-year>
<abstract><sec><title>Background</title>
<p>Sequencing the expressed genetic information of an ecosystem (metatranscriptome) can provide information about the response of organisms to varying environmental conditions. Until recently, metatranscriptomics has been limited to microarray technology and random cloning methodologies. The application of high-throughput sequencing technology is now enabling access to both known and previously unknown transcripts in natural communities.</p>
</sec>
<sec><title>Methodology/Principal Findings</title>
<p>We present a study of a complex marine metatranscriptome obtained from random whole-community mRNA using the GS-FLX Pyrosequencing technology. Eight samples, four DNA and four mRNA, were processed from two time points in a controlled coastal ocean mesocosm study (Bergen, Norway) involving an induced phytoplankton bloom producing a total of 323,161,989 base pairs. Our study confirms the finding of the first published metatranscriptomic studies of marine and soil environments that metatranscriptomics targets highly expressed sequences which are frequently novel. Our alternative methodology increases the range of experimental options available for conducting such studies and is characterized by an exceptional enrichment of mRNA (99.92%) versus ribosomal RNA. Analysis of corresponding metagenomes confirms much higher levels of assembly in the metatranscriptomic samples and a far higher yield of large gene families with >100 members, ∼91% of which were novel.</p>
</sec>
<sec><title>Conclusions/Significance</title>
<p>This study provides further evidence that metatranscriptomic studies of natural microbial communities are not only feasible, but when paired with metagenomic data sets, offer an unprecedented opportunity to explore both structure and function of microbial communities – if we can overcome the challenges of elucidating the functions of so many never-seen-before gene families.</p>
</sec>
</abstract>
<counts><page-count count="13"></page-count>
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