Current opportunities and challenges in microbial metagenome analysis—a bioinformatic perspective
Identifieur interne : 000428 ( Pmc/Checkpoint ); précédent : 000427; suivant : 000429Current opportunities and challenges in microbial metagenome analysis—a bioinformatic perspective
Auteurs : Hanno Teeling ; Frank Oliver GlöcknerSource :
- Briefings in Bioinformatics [ 1467-5463 ] ; 2012.
Abstract
Metagenomics has become an indispensable tool for studying the diversity and metabolic potential of environmental microbes, whose bulk is as yet non-cultivable. Continual progress in next-generation sequencing allows for generating increasingly large metagenomes and studying multiple metagenomes over time or space. Recently, a new type of holistic ecosystem study has emerged that seeks to combine metagenomics with biodiversity, meta-expression and contextual data. Such ‘ecosystems biology’ approaches bear the potential to not only advance our understanding of environmental microbes to a new level but also impose challenges due to increasing data complexities, in particular with respect to bioinformatic post-processing. This mini review aims to address selected opportunities and challenges of modern metagenomics from a bioinformatics perspective and hopefully will serve as a useful resource for microbial ecologists and bioinformaticians alike.
Url:
DOI: 10.1093/bib/bbs039
PubMed: 22966151
PubMed Central: 3504927
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Current opportunities and challenges in microbial metagenome analysis—a bioinformatic perspective</title><author><name sortKey="Teeling, Hanno" sort="Teeling, Hanno" uniqKey="Teeling H" first="Hanno" last="Teeling">Hanno Teeling</name></author><author><name sortKey="Glockner, Frank Oliver" sort="Glockner, Frank Oliver" uniqKey="Glockner F" first="Frank Oliver" last="Glöckner">Frank Oliver Glöckner</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">22966151</idno><idno type="pmc">3504927</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3504927</idno><idno type="RBID">PMC:3504927</idno><idno type="doi">10.1093/bib/bbs039</idno><date when="2012">2012</date><idno type="wicri:Area/Pmc/Corpus">000509</idno><idno type="wicri:Area/Pmc/Curation">000509</idno><idno type="wicri:Area/Pmc/Checkpoint">000428</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Current opportunities and challenges in microbial metagenome analysis—a bioinformatic perspective</title><author><name sortKey="Teeling, Hanno" sort="Teeling, Hanno" uniqKey="Teeling H" first="Hanno" last="Teeling">Hanno Teeling</name></author><author><name sortKey="Glockner, Frank Oliver" sort="Glockner, Frank Oliver" uniqKey="Glockner F" first="Frank Oliver" last="Glöckner">Frank Oliver Glöckner</name></author></analytic><series><title level="j">Briefings in Bioinformatics</title><idno type="ISSN">1467-5463</idno><idno type="eISSN">1477-4054</idno><imprint><date when="2012">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Metagenomics has become an indispensable tool for studying the diversity and metabolic potential of environmental microbes, whose bulk is as yet non-cultivable. Continual progress in next-generation sequencing allows for generating increasingly large metagenomes and studying multiple metagenomes over time or space. Recently, a new type of holistic ecosystem study has emerged that seeks to combine metagenomics with biodiversity, meta-expression and contextual data. Such ‘ecosystems biology’ approaches bear the potential to not only advance our understanding of environmental microbes to a new level but also impose challenges due to increasing data complexities, in particular with respect to bioinformatic post-processing. This mini review aims to address selected opportunities and challenges of modern metagenomics from a bioinformatics perspective and hopefully will serve as a useful resource for microbial ecologists and bioinformaticians alike.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Lane, Dj" uniqKey="Lane D">DJ Lane</name></author><author><name sortKey="Pace, B" uniqKey="Pace B">B Pace</name></author><author><name sortKey="Olsen, Gj" uniqKey="Olsen G">GJ Olsen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Pruesse, E" uniqKey="Pruesse E">E Pruesse</name></author><author><name sortKey="Quast, C" uniqKey="Quast C">C Quast</name></author><author><name sortKey="Knittel, K" uniqKey="Knittel K">K Knittel</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Curtis, Tp" uniqKey="Curtis T">TP Curtis</name></author><author><name sortKey="Sloan, Wt" uniqKey="Sloan W">WT 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Brief Bioinform</journal-id><journal-id journal-id-type="iso-abbrev">Brief. Bioinformatics</journal-id><journal-id journal-id-type="publisher-id">bib</journal-id><journal-id journal-id-type="hwp">bib</journal-id><journal-title-group><journal-title>Briefings in Bioinformatics</journal-title></journal-title-group><issn pub-type="ppub">1467-5463</issn><issn pub-type="epub">1477-4054</issn><publisher><publisher-name>Oxford University Press</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">22966151</article-id><article-id pub-id-type="pmc">3504927</article-id><article-id pub-id-type="doi">10.1093/bib/bbs039</article-id><article-id pub-id-type="publisher-id">bbs039</article-id><article-categories><subj-group subj-group-type="heading"><subject>Papers</subject></subj-group></article-categories><title-group><article-title>Current opportunities and challenges in microbial metagenome analysis—a bioinformatic perspective</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Teeling</surname><given-names>Hanno</given-names></name><xref ref-type="bio" rid="d34e36">*</xref></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Glöckner</surname><given-names>Frank Oliver</given-names></name><xref ref-type="bio" rid="d34e47">*</xref></contrib></contrib-group><author-notes><corresp>Corresponding author. Frank Oliver Glöckner. Department of Molecular Ecology, Max Planck Institute for Marine Microbiology, Microbial Genomics and Bioinformatics Group, Celsiusstrasse 1, Bremen 28359, Germany. Tel.: <phone>+49 421 2028-970</phone>; Fax: <fax>+49 421 2028-580</fax>; E-mail: <email>fgloeckn@mpi-bremen.de</email></corresp></author-notes><pub-date pub-type="ppub"><month>11</month><year>2012</year></pub-date><pub-date pub-type="epub"><day>8</day><month>9</month><year>2012</year></pub-date><pub-date pub-type="pmc-release"><day>8</day><month>9</month><year>2012</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on the
<pmc-comment> oupReleaseDelayRemoved from OA Article (10.1093/bib/bbs039bbs039PapersCurrent opportunities and challenges in microbial metagenome analysis—a bioinformatic perspectiveTeelingHannoHanno Teeling followed independent educations as a chemist and biologist before specializing on bioinformatics for microbial genomics. He has worked for 12 years in this field and is currently a scientist at the Max Planck Institute for Marine Microbiology in Bremen.GlöcknerFrank OliverFrank Oliver Glöckner entered the field of bioinformatics more than 15 years ago. He specialized on tools and databases for microbial biodiversity analysis and microbial genomics. He is the head of the Microbial Genomics and Bioinformatics Research Group at the Max Planck Institute for Marine Microbiology and Professor of Bioinformatics at the Jacobs University Bremen.Corresponding author. Frank Oliver Glöckner. Department of Molecular Ecology, Max Planck Institute for Marine Microbiology, Microbial Genomics and Bioinformatics Group, Celsiusstrasse 1, Bremen 28359, Germany. Tel.: +49 421 2028-970; Fax: +49 421 2028-580; E-mail: fgloeckn@mpi-bremen.de112012892012136Special Issue: Bioinformatics approaches and tools for metagenomic analysis7287423032012962012© The Author 2012. Published by Oxford University Press.2012This 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.Metagenomics has become an indispensable tool for studying the diversity and metabolic potential of environmental microbes, whose bulk is as yet non-cultivable. Continual progress in next-generation sequencing allows for generating increasingly large metagenomes and studying multiple metagenomes over time or space. Recently, a new type of holistic ecosystem study has emerged that seeks to combine metagenomics with biodiversity, meta-expression and contextual data. Such ‘ecosystems biology’ approaches bear the potential to not only advance our understanding of environmental microbes to a new level but also impose challenges due to increasing data complexities, in particular with respect to bioinformatic post-processing. This mini review aims to address selected opportunities and challenges of modern metagenomics from a bioinformatics perspective and hopefully will serve as a useful resource for microbial ecologists and bioinformaticians alike.16S rRNA biodiversitybinningbioinformaticsGenomic Standards Consortiummetagenomicsnext-generation sequencing) </pmc-comment>
<volume>13</volume><issue>6</issue><issue-title>Special Issue: Bioinformatics approaches and tools for metagenomic analysis</issue-title><fpage>728</fpage><lpage>742</lpage><history><date date-type="received"><day>30</day><month>3</month><year>2012</year></date><date date-type="accepted"><day>9</day><month>6</month><year>2012</year></date></history><permissions><copyright-statement>© The Author 2012. Published by Oxford University Press.</copyright-statement><copyright-year>2012</copyright-year><license license-type="creative-commons" xlink:href="http://creativecommons.org/licenses/by-nc/3.0"><license-p><pmc-comment>CREATIVE COMMONS</pmc-comment>This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by-nc/3.0">http://creativecommons.org/licenses/by-nc/3.0</ext-link>), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><abstract><p>Metagenomics has become an indispensable tool for studying the diversity and metabolic potential of environmental microbes, whose bulk is as yet non-cultivable. Continual progress in next-generation sequencing allows for generating increasingly large metagenomes and studying multiple metagenomes over time or space. Recently, a new type of holistic ecosystem study has emerged that seeks to combine metagenomics with biodiversity, meta-expression and contextual data. Such ‘ecosystems biology’ approaches bear the potential to not only advance our understanding of environmental microbes to a new level but also impose challenges due to increasing data complexities, in particular with respect to bioinformatic post-processing. This mini review aims to address selected opportunities and challenges of modern metagenomics from a bioinformatics perspective and hopefully will serve as a useful resource for microbial ecologists and bioinformaticians alike.</p></abstract><kwd-group><kwd>16S rRNA biodiversity</kwd><kwd>binning</kwd><kwd>bioinformatics</kwd><kwd>Genomic Standards Consortium</kwd><kwd>metagenomics</kwd><kwd>next-generation sequencing</kwd></kwd-group><counts><page-count count="15"></page-count></counts></article-meta></front></pmc><affiliations><list></list><tree><noCountry><name sortKey="Glockner, Frank Oliver" sort="Glockner, Frank Oliver" uniqKey="Glockner F" first="Frank Oliver" last="Glöckner">Frank Oliver Glöckner</name><name sortKey="Teeling, Hanno" sort="Teeling, Hanno" uniqKey="Teeling H" first="Hanno" last="Teeling">Hanno Teeling</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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