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Microbial Community Profiling of Human Saliva Using Shotgun Metagenomic Sequencing

Identifieur interne : 000752 ( Pmc/Curation ); précédent : 000751; suivant : 000753

Microbial Community Profiling of Human Saliva Using Shotgun Metagenomic Sequencing

Auteurs : Nur A. Hasan [États-Unis] ; Brian A. Young [États-Unis] ; Angela T. Minard-Smith [États-Unis] ; Kelly Saeed [États-Unis] ; Huai Li [États-Unis] ; Esley M. Heizer [États-Unis] ; Nancy J. Mcmillan [États-Unis] ; Richard Isom [États-Unis] ; Abdul Shakur Abdullah [États-Unis] ; Daniel M. Bornman [États-Unis] ; Seth A. Faith [États-Unis] ; Seon Young Choi [États-Unis] ; Michael L. Dickens [États-Unis] ; Thomas A. Cebula [États-Unis] ; Rita R. Colwell [États-Unis]

Source :

RBID : PMC:4028220

Abstract

Human saliva is clinically informative of both oral and general health. Since next generation shotgun sequencing (NGS) is now widely used to identify and quantify bacteria, we investigated the bacterial flora of saliva microbiomes of two healthy volunteers and five datasets from the Human Microbiome Project, along with a control dataset containing short NGS reads from bacterial species representative of the bacterial flora of human saliva. GENIUS, a system designed to identify and quantify bacterial species using unassembled short NGS reads was used to identify the bacterial species comprising the microbiomes of the saliva samples and datasets. Results, achieved within minutes and at greater than 90% accuracy, showed more than 175 bacterial species comprised the bacterial flora of human saliva, including bacteria known to be commensal human flora but also Haemophilus influenzae, Neisseria meningitidis, Streptococcus pneumoniae, and Gamma proteobacteria. Basic Local Alignment Search Tool (BLASTn) analysis in parallel, reported ca. five times more species than those actually comprising the in silico sample. Both GENIUSand BLAST analyses of saliva samples identified major genera comprising the bacterial flora of saliva, but GENIUS provided a more precise description of species composition, identifying to strain in most cases and delivered results at least 10,000 times faster. Therefore, GENIUS offers a facile and accurate system for identification and quantification of bacterial species and/or strains in metagenomic samples.


Url:
DOI: 10.1371/journal.pone.0097699
PubMed: 24846174
PubMed Central: 4028220

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PMC:4028220

Le document en format XML

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<name sortKey="Abdullah, Abdul Shakur" sort="Abdullah, Abdul Shakur" uniqKey="Abdullah A" first="Abdul Shakur" last="Abdullah">Abdul Shakur Abdullah</name>
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<div type="abstract" xml:lang="en">
<p>Human saliva is clinically informative of both oral and general health. Since next generation shotgun sequencing (NGS) is now widely used to identify and quantify bacteria, we investigated the bacterial flora of saliva microbiomes of two healthy volunteers and five datasets from the Human Microbiome Project, along with a control dataset containing short NGS reads from bacterial species representative of the bacterial flora of human saliva. GENIUS, a system designed to identify and quantify bacterial species using unassembled short NGS reads was used to identify the bacterial species comprising the microbiomes of the saliva samples and datasets. Results, achieved within minutes and at greater than 90% accuracy, showed more than 175 bacterial species comprised the bacterial flora of human saliva, including bacteria known to be commensal human flora but also
<italic>Haemophilus influenzae</italic>
,
<italic>Neisseria meningitidis</italic>
,
<italic>Streptococcus pneumoniae</italic>
, and Gamma proteobacteria. Basic Local Alignment Search Tool (BLASTn) analysis in parallel, reported
<italic>ca</italic>
. five times more species than those actually comprising the
<italic>in silico</italic>
sample. Both GENIUSand BLAST analyses of saliva samples identified major genera comprising the bacterial flora of saliva, but GENIUS provided a more precise description of species composition, identifying to strain in most cases and delivered results at least 10,000 times faster. Therefore, GENIUS offers a facile and accurate system for identification and quantification of bacterial species and/or strains in metagenomic samples.</p>
</div>
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<name sortKey="Smith, Gl" uniqKey="Smith G">GL Smith</name>
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<author>
<name sortKey="Dzink, Jl" uniqKey="Dzink J">JL Dzink</name>
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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">PLoS One</journal-id>
<journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id>
<journal-id journal-id-type="publisher-id">plos</journal-id>
<journal-id journal-id-type="pmc">plosone</journal-id>
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<journal-title>PLoS ONE</journal-title>
</journal-title-group>
<issn pub-type="epub">1932-6203</issn>
<publisher>
<publisher-name>Public Library of Science</publisher-name>
<publisher-loc>San Francisco, USA</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">24846174</article-id>
<article-id pub-id-type="pmc">4028220</article-id>
<article-id pub-id-type="publisher-id">PONE-D-13-52680</article-id>
<article-id pub-id-type="doi">10.1371/journal.pone.0097699</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline-v2">
<subject>Biology and Life Sciences</subject>
<subj-group>
<subject>Genetics</subject>
<subj-group>
<subject>Genomics</subject>
</subj-group>
</subj-group>
<subj-group>
<subject>Microbiology</subject>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v2">
<subject>Medicine and Health Sciences</subject>
<subj-group>
<subject>Diagnostic Medicine</subject>
<subj-group>
<subject>Clinical Laboratory Sciences</subject>
</subj-group>
</subj-group>
<subj-group>
<subject>Infectious Diseases</subject>
<subj-group>
<subject>Bacterial Diseases</subject>
<subject>Fungal Diseases</subject>
</subj-group>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Microbial Community Profiling of Human Saliva Using Shotgun Metagenomic Sequencing</article-title>
<alt-title alt-title-type="running-head">Shotgun Metagenomics for Human Salivary Microbiome</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Hasan</surname>
<given-names>Nur A.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Young</surname>
<given-names>Brian A.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Minard-Smith</surname>
<given-names>Angela T.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Saeed</surname>
<given-names>Kelly</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Huai</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Heizer</surname>
<given-names>Esley M.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>McMillan</surname>
<given-names>Nancy J.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Isom</surname>
<given-names>Richard</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Abdullah</surname>
<given-names>Abdul Shakur</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Bornman</surname>
<given-names>Daniel M.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Faith</surname>
<given-names>Seth A.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Choi</surname>
<given-names>Seon Young</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Dickens</surname>
<given-names>Michael L.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cebula</surname>
<given-names>Thomas A.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Colwell</surname>
<given-names>Rita R.</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="aff5">
<sup>5</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<xref ref-type="corresp" rid="cor1">
<sup>*</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<label>1</label>
<addr-line>CosmosID, College Park, Maryland, United States of America</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, United States of America</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Battelle, Columbus, Ohio, United States of America</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>Department of Biology, Johns Hopkins University, Baltimore, Maryland, United States of America</addr-line>
</aff>
<aff id="aff5">
<label>5</label>
<addr-line>University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland, United States of America</addr-line>
</aff>
<aff id="aff6">
<label>6</label>
<addr-line>Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, 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">
<addr-line>University of Hyderabad, , India</addr-line>
</aff>
<author-notes>
<corresp id="cor1">* E-mail:
<email>rcolwell@umiacs.umd.edu</email>
</corresp>
<fn fn-type="conflict">
<p>
<bold>Competing Interests: </bold>
Rita R. Colwell is Founder and Chairman of the Board, CosmosID®, and some of the other authors are employees of the company, a bioinformatics company. Rita R. Colwell is also Distinguished University Professor at the University of Maryland, College Park and at Johns Hopkins University Bloomberg School of Public Health. Affiliation with CosmosID and, similarly, with Battelle does not alter the authors’ adherence to all PLoS One policies on sharing data and materials online as detailed in the online guide for authors.</p>
</fn>
<fn fn-type="con">
<p>Conceived and designed the experiments: TAC RRC NAH BAY DMB SAF. Analyzed the data: NAH HL KS RI ASA SYC DMB ATM-S EMH NJM SAF BAY. Contributed reagents/materials/analysis tools: RRC HL BAY MLD. Wrote the paper: NAH RRC TAC HL RI KS SYC ATM-S NJM EMH BAY MLD. Critical review of the paper for intellectual content: RRC NAH TAC BAY MLD.</p>
</fn>
</author-notes>
<pub-date pub-type="collection">
<year>2014</year>
</pub-date>
<pub-date pub-type="epub">
<day>20</day>
<month>5</month>
<year>2014</year>
</pub-date>
<volume>9</volume>
<issue>5</issue>
<elocation-id>e97699</elocation-id>
<history>
<date date-type="received">
<day>18</day>
<month>12</month>
<year>2013</year>
</date>
<date date-type="accepted">
<day>22</day>
<month>4</month>
<year>2014</year>
</date>
</history>
<permissions>
<copyright-year>2014</copyright-year>
<copyright-holder>Hasan et al</copyright-holder>
<license>
<license-p>This is an open-access article distributed under the terms of the
<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>
, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<abstract>
<p>Human saliva is clinically informative of both oral and general health. Since next generation shotgun sequencing (NGS) is now widely used to identify and quantify bacteria, we investigated the bacterial flora of saliva microbiomes of two healthy volunteers and five datasets from the Human Microbiome Project, along with a control dataset containing short NGS reads from bacterial species representative of the bacterial flora of human saliva. GENIUS, a system designed to identify and quantify bacterial species using unassembled short NGS reads was used to identify the bacterial species comprising the microbiomes of the saliva samples and datasets. Results, achieved within minutes and at greater than 90% accuracy, showed more than 175 bacterial species comprised the bacterial flora of human saliva, including bacteria known to be commensal human flora but also
<italic>Haemophilus influenzae</italic>
,
<italic>Neisseria meningitidis</italic>
,
<italic>Streptococcus pneumoniae</italic>
, and Gamma proteobacteria. Basic Local Alignment Search Tool (BLASTn) analysis in parallel, reported
<italic>ca</italic>
. five times more species than those actually comprising the
<italic>in silico</italic>
sample. Both GENIUSand BLAST analyses of saliva samples identified major genera comprising the bacterial flora of saliva, but GENIUS provided a more precise description of species composition, identifying to strain in most cases and delivered results at least 10,000 times faster. Therefore, GENIUS offers a facile and accurate system for identification and quantification of bacterial species and/or strains in metagenomic samples.</p>
</abstract>
<funding-group>
<funding-statement>Funding for this study was provided, in part, by NIH Grants 1RO1A139129-01 and 2RO1A1039129-11A2. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement>
</funding-group>
<counts>
<page-count count="10"></page-count>
</counts>
</article-meta>
</front>
</pmc>
</record>

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