FluShuffle and FluResort: new algorithms to identify reassorted strains of the influenza virus by mass spectrometry
Identifieur interne : 000519 ( Pmc/Curation ); précédent : 000518; suivant : 000520FluShuffle and FluResort: new algorithms to identify reassorted strains of the influenza virus by mass spectrometry
Auteurs : Aaron Tl Lun [Australie] ; Jason Wh Wong [Australie] ; Kevin M. Downard [Australie]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2012.
Abstract
Influenza is one of the oldest and deadliest infectious diseases known to man. Reassorted strains of the virus pose the greatest risk to both human and animal health and have been associated with all pandemics of the past century, with the possible exception of the 1918 pandemic, resulting in tens of millions of deaths. We have developed and tested new computer algorithms, FluShuffle and FluResort, which enable reassorted viruses to be identified by the most rapid and direct means possible. These algorithms enable reassorted influenza, and other, viruses to be rapidly identified to allow prevention strategies and treatments to be more efficiently implemented.
The FluShuffle and FluResort algorithms were tested with both experimental and simulated mass spectra of whole virus digests. FluShuffle considers different combinations of viral protein identities that match the mass spectral data using a Gibbs sampling algorithm employing a mixed protein Markov chain Monte Carlo (MCMC) method. FluResort utilizes those identities to calculate the weighted distance of each across two or more different phylogenetic trees constructed through viral protein sequence alignments. Each weighted mean distance value is normalized by conversion to a Z-score to establish a reassorted strain.
The new FluShuffle and FluResort algorithms can correctly identify the origins of influenza viral proteins and the number of reassortment events required to produce the strains from the high resolution mass spectral data of whole virus proteolytic digestions. This has been demonstrated in the case of constructed vaccine strains as well as common human seasonal strains of the virus. The algorithms significantly improve the capability of the proteotyping approach to identify reassorted viruses that pose the greatest pandemic risk.
Url:
DOI: 10.1186/1471-2105-13-208
PubMed: 22906155
PubMed Central: 3505172
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>Influenza is one of the oldest and deadliest infectious diseases known to man. Reassorted strains of the virus pose the greatest risk to both human and animal health and have been associated with all pandemics of the past century, with the possible exception of the 1918 pandemic, resulting in tens of millions of deaths. We have developed and tested new computer algorithms, FluShuffle and FluResort, which enable reassorted viruses to be identified by the most rapid and direct means possible. These algorithms enable reassorted influenza, and other, viruses to be rapidly identified to allow prevention strategies and treatments to be more efficiently implemented.</p>
</sec>
<sec><title>Results</title>
<p>The FluShuffle and FluResort algorithms were tested with both experimental and simulated mass spectra of whole virus digests. FluShuffle considers different combinations of viral protein identities that match the mass spectral data using a Gibbs sampling algorithm employing a mixed protein Markov chain Monte Carlo (MCMC) method. FluResort utilizes those identities to calculate the weighted distance of each across two or more different phylogenetic trees constructed through viral protein sequence alignments. Each weighted mean distance value is normalized by conversion to a Z-score to establish a reassorted strain.</p>
</sec>
<sec><title>Conclusions</title>
<p>The new FluShuffle and FluResort algorithms can correctly identify the origins of influenza viral proteins and the number of reassortment events required to produce the strains from the high resolution mass spectral data of whole virus proteolytic digestions. This has been demonstrated in the case of constructed vaccine strains as well as common human seasonal strains of the virus. The algorithms significantly improve the capability of the proteotyping approach to identify reassorted viruses that pose the greatest pandemic risk.</p>
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<author><name sortKey="Johnson, Jr" uniqKey="Johnson J">JR Johnson</name>
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<author><name sortKey="Cociorva, D" uniqKey="Cociorva D">D Cociorva</name>
</author>
<author><name sortKey="Yates, Jr" uniqKey="Yates J">JR Yates</name>
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</analytic>
</biblStruct>
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</author>
<author><name sortKey="Finney, Gl" uniqKey="Finney G">GL Finney</name>
</author>
<author><name sortKey="Maccoss, Mj" uniqKey="Maccoss M">MJ MacCoss</name>
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<pmc article-type="product-review" xml:lang="en"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Bioinformatics</journal-id>
<journal-id journal-id-type="iso-abbrev">BMC Bioinformatics</journal-id>
<journal-title-group><journal-title>BMC Bioinformatics</journal-title>
</journal-title-group>
<issn pub-type="epub">1471-2105</issn>
<publisher><publisher-name>BioMed Central</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">22906155</article-id>
<article-id pub-id-type="pmc">3505172</article-id>
<article-id pub-id-type="publisher-id">1471-2105-13-208</article-id>
<article-id pub-id-type="doi">10.1186/1471-2105-13-208</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Software</subject>
</subj-group>
</article-categories>
<title-group><article-title>FluShuffle and FluResort: new algorithms to identify reassorted strains of the influenza virus by mass spectrometry</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" id="A1"><name><surname>Lun</surname>
<given-names>Aaron TL</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>alun1181@uni.sydney.edu.au</email>
</contrib>
<contrib contrib-type="author" id="A2"><name><surname>Wong</surname>
<given-names>Jason WH</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<xref ref-type="aff" rid="I2">2</xref>
<email>jason.wong@unsw.edu.au</email>
</contrib>
<contrib contrib-type="author" corresp="yes" id="A3"><name><surname>Downard</surname>
<given-names>Kevin M</given-names>
</name>
<xref ref-type="aff" rid="I1">1</xref>
<email>k.downard@sydney.edu.au</email>
</contrib>
</contrib-group>
<aff id="I1"><label>1</label>
School of Molecular Bioscience G-08, The University of Sydney, Sydney, NSW, 2006, Australia</aff>
<aff id="I2"><label>2</label>
Prince of Wales Clinical School and Lowy Cancer Research Centre, University of New South Wales, Sydney, NSW, Australia</aff>
<pub-date pub-type="collection"><year>2012</year>
</pub-date>
<pub-date pub-type="epub"><day>20</day>
<month>8</month>
<year>2012</year>
</pub-date>
<volume>13</volume>
<fpage>208</fpage>
<lpage>208</lpage>
<history><date date-type="received"><day>30</day>
<month>3</month>
<year>2012</year>
</date>
<date date-type="accepted"><day>10</day>
<month>8</month>
<year>2012</year>
</date>
</history>
<permissions><copyright-statement>Copyright ©2012 Lun et al.; licensee BioMed Central Ltd.</copyright-statement>
<copyright-year>2012</copyright-year>
<copyright-holder>Lun et al.; licensee BioMed Central Ltd.</copyright-holder>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0">http://creativecommons.org/licenses/by/2.0</ext-link>
), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
</license>
</permissions>
<self-uri xlink:href="http://www.biomedcentral.com/1471-2105/13/208"></self-uri>
<abstract><sec><title>Background</title>
<p>Influenza is one of the oldest and deadliest infectious diseases known to man. Reassorted strains of the virus pose the greatest risk to both human and animal health and have been associated with all pandemics of the past century, with the possible exception of the 1918 pandemic, resulting in tens of millions of deaths. We have developed and tested new computer algorithms, FluShuffle and FluResort, which enable reassorted viruses to be identified by the most rapid and direct means possible. These algorithms enable reassorted influenza, and other, viruses to be rapidly identified to allow prevention strategies and treatments to be more efficiently implemented.</p>
</sec>
<sec><title>Results</title>
<p>The FluShuffle and FluResort algorithms were tested with both experimental and simulated mass spectra of whole virus digests. FluShuffle considers different combinations of viral protein identities that match the mass spectral data using a Gibbs sampling algorithm employing a mixed protein Markov chain Monte Carlo (MCMC) method. FluResort utilizes those identities to calculate the weighted distance of each across two or more different phylogenetic trees constructed through viral protein sequence alignments. Each weighted mean distance value is normalized by conversion to a Z-score to establish a reassorted strain.</p>
</sec>
<sec><title>Conclusions</title>
<p>The new FluShuffle and FluResort algorithms can correctly identify the origins of influenza viral proteins and the number of reassortment events required to produce the strains from the high resolution mass spectral data of whole virus proteolytic digestions. This has been demonstrated in the case of constructed vaccine strains as well as common human seasonal strains of the virus. The algorithms significantly improve the capability of the proteotyping approach to identify reassorted viruses that pose the greatest pandemic risk.</p>
</sec>
</abstract>
<kwd-group><kwd>Influenza virus</kwd>
<kwd>Reassortment</kwd>
<kwd>Proteotyping</kwd>
<kwd>Computer algorithm</kwd>
<kwd>Phylogenetics</kwd>
<kwd>Mass spectrometry</kwd>
</kwd-group>
</article-meta>
</front>
</pmc>
</record>
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