The Use of Metagenomic Approaches to Analyze Changes in Microbial Communities
Identifieur interne : 000519 ( Ncbi/Merge ); précédent : 000518; suivant : 000520The Use of Metagenomic Approaches to Analyze Changes in Microbial Communities
Auteurs : Girish Neelakanta ; Hameeda SultanaSource :
- Microbiology Insights [ 1178-6361 ] ; 2013.
Abstract
Microbes are the most abundant biological entities found in the biosphere. Identification and measurement of microorganisms (including viruses, bacteria, archaea, fungi, and protists) in the biosphere cannot be readily achieved due to limitations in culturing methods. A non-culture based approach, called “metagenomics”, was developed that enabled researchers to comprehensively analyse microbial communities in different ecosystems. In this study, we highlight recent advances in the field of metagenomics for analyzing microbial communities in different ecosystems ranging from oceans to the human microbiome. Developments in several bioinformatics approaches are also discussed in context of microbial metagenomics that include taxonomic systems, sequence databases, and sequence-alignment tools. In summary, we provide a snapshot for the recent advances in metagenomics approach for analyzing changes in the microbial communities in different ecosystems.
Url:
DOI: 10.4137/MBI.S10819
PubMed: 24826073
PubMed Central: 3987754
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">The Use of Metagenomic Approaches to Analyze Changes in Microbial Communities</title><author><name sortKey="Neelakanta, Girish" sort="Neelakanta, Girish" uniqKey="Neelakanta G" first="Girish" last="Neelakanta">Girish Neelakanta</name></author><author><name sortKey="Sultana, Hameeda" sort="Sultana, Hameeda" uniqKey="Sultana H" first="Hameeda" last="Sultana">Hameeda Sultana</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">24826073</idno><idno type="pmc">3987754</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3987754</idno><idno type="RBID">PMC:3987754</idno><idno type="doi">10.4137/MBI.S10819</idno><date when="2013">2013</date><idno type="wicri:Area/Pmc/Corpus">000713</idno><idno type="wicri:Area/Pmc/Curation">000713</idno><idno type="wicri:Area/Pmc/Checkpoint">000256</idno><idno type="wicri:Area/Ncbi/Merge">000519</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">The Use of Metagenomic Approaches to Analyze Changes in Microbial Communities</title><author><name sortKey="Neelakanta, Girish" sort="Neelakanta, Girish" uniqKey="Neelakanta G" first="Girish" last="Neelakanta">Girish Neelakanta</name></author><author><name sortKey="Sultana, Hameeda" sort="Sultana, Hameeda" uniqKey="Sultana H" first="Hameeda" last="Sultana">Hameeda Sultana</name></author></analytic><series><title level="j">Microbiology Insights</title><idno type="eISSN">1178-6361</idno><imprint><date when="2013">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Microbes are the most abundant biological entities found in the biosphere. Identification and measurement of microorganisms (including viruses, bacteria, archaea, fungi, and protists) in the biosphere cannot be readily achieved due to limitations in culturing methods. A non-culture based approach, called “metagenomics”, was developed that enabled researchers to comprehensively analyse microbial communities in different ecosystems. In this study, we highlight recent advances in the field of metagenomics for analyzing microbial communities in different ecosystems ranging from oceans to the human microbiome. Developments in several bioinformatics approaches are also discussed in context of microbial metagenomics that include taxonomic systems, sequence databases, and sequence-alignment tools. In summary, we provide a snapshot for the recent advances in metagenomics approach for analyzing changes in the microbial communities in different ecosystems.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Handelsman, J" uniqKey="Handelsman J">J Handelsman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Staley, Jt" uniqKey="Staley J">JT Staley</name></author><author><name sortKey="Konopka, A" uniqKey="Konopka A">A Konopka</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Whang, K" uniqKey="Whang K">K Whang</name></author><author><name sortKey="Hattori, T" uniqKey="Hattori T">T Hattori</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Riesenfeld, Cs" uniqKey="Riesenfeld C">CS Riesenfeld</name></author><author><name sortKey="Schloss, Pd" uniqKey="Schloss P">PD Schloss</name></author><author><name sortKey="Handelsman, J" 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Microbiol Insights</journal-id><journal-id journal-id-type="iso-abbrev">Microbiol Insights</journal-id><journal-title-group><journal-title>Microbiology Insights</journal-title></journal-title-group><issn pub-type="epub">1178-6361</issn><publisher><publisher-name>Libertas Academica</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">24826073</article-id><article-id pub-id-type="pmc">3987754</article-id><article-id pub-id-type="doi">10.4137/MBI.S10819</article-id><article-id pub-id-type="publisher-id">mbi-6-2013-037</article-id><article-categories><subj-group subj-group-type="heading"><subject>Review</subject></subj-group></article-categories><title-group><article-title>The Use of Metagenomic Approaches to Analyze Changes in Microbial Communities</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Neelakanta</surname><given-names>Girish</given-names></name></contrib><contrib contrib-type="author"><name><surname>Sultana</surname><given-names>Hameeda</given-names></name><xref ref-type="corresp" rid="c1-mbi-6-2013-037"></xref></contrib><aff id="af1-mbi-6-2013-037">Center for Molecular Medicine, Department of Biological Sciences, Old Dominion University, Norfolk, VA, USA.</aff></contrib-group><author-notes><corresp id="c1-mbi-6-2013-037">Corresponding author email: <email>hsultana@odu.edu</email></corresp></author-notes><pub-date pub-type="collection"><year>2013</year></pub-date><pub-date pub-type="epub"><day>16</day><month>4</month><year>2013</year></pub-date><volume>6</volume><fpage>37</fpage><lpage>48</lpage><permissions><copyright-statement>© 2013 the author(s), publisher and licensee Libertas Academica Ltd.</copyright-statement><copyright-year>2013</copyright-year><license license-type="open-access"><license-p>This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited.</license-p></license></permissions><abstract><p>Microbes are the most abundant biological entities found in the biosphere. Identification and measurement of microorganisms (including viruses, bacteria, archaea, fungi, and protists) in the biosphere cannot be readily achieved due to limitations in culturing methods. A non-culture based approach, called “metagenomics”, was developed that enabled researchers to comprehensively analyse microbial communities in different ecosystems. In this study, we highlight recent advances in the field of metagenomics for analyzing microbial communities in different ecosystems ranging from oceans to the human microbiome. Developments in several bioinformatics approaches are also discussed in context of microbial metagenomics that include taxonomic systems, sequence databases, and sequence-alignment tools. In summary, we provide a snapshot for the recent advances in metagenomics approach for analyzing changes in the microbial communities in different ecosystems.</p></abstract><kwd-group><kwd>metagenomics</kwd><kwd>sequencing</kwd><kwd>microbial diversity</kwd><kwd>bioinformatics</kwd><kwd>microbial changes</kwd></kwd-group></article-meta></front><floats-group><fig id="f1-mbi-6-2013-037" position="float"><label>Figure 1</label><caption><p>Overview of metagenomic analysis.</p><p><bold>Notes:</bold> Schematic representation of a typical metagenomic analysis is shown. Samples from various sources such as from Ocean, soil, hot springs, glaciers, acidic environments, ticks and human skin and feces samples are processed for total DNA extraction to amplify microbial sequences. The extracted DNA is then processed for metagenomic analysis that is comprised of the following steps: sequencing; sequence binning; annotation of sequences; taxonomic classification of microbial species; statistical analysis of the metagenomic data; and data storage in central metagenome databases. Some of the potential coding sequences that include but are not limited to enzymes, antibiotics, and proteases are cloned into heterologous expression vectors. The expressed proteins are later used in variety of applications. In addition, the information obtained from typical metagenomic analysis would provide substantial insights in the field of microbial diversity, ecology, and evolution.</p></caption><graphic xlink:href="mbi-6-2013-037f1"></graphic></fig></floats-group></pmc><affiliations><list></list><tree><noCountry><name sortKey="Neelakanta, Girish" sort="Neelakanta, Girish" uniqKey="Neelakanta G" first="Girish" last="Neelakanta">Girish Neelakanta</name><name sortKey="Sultana, Hameeda" sort="Sultana, Hameeda" uniqKey="Sultana H" first="Hameeda" last="Sultana">Hameeda Sultana</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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