HostPhinder: A Phage Host Prediction Tool
Identifieur interne : 001218 ( Main/Exploration ); précédent : 001217; suivant : 001219HostPhinder: A Phage Host Prediction Tool
Auteurs : Julia Villarroel ; Kortine Annina Kleinheinz ; Vanessa Isabell Jurtz ; Henrike Zschach ; Ole Lund ; Morten Nielsen [Argentine] ; Mette Voldby LarsenSource :
- Viruses [ 1999-4915 ] ; 2016.
Descripteurs français
- KwdFr :
- MESH :
- génétique : Bactériophages.
- physiologie : Bactériophages.
- virologie : Bactéries.
- Biologie informatique, Génome viral, Spécificité d'hôte.
English descriptors
- KwdEn :
- MESH :
- genetics : Bacteriophages.
- methods : Computational Biology.
- physiology : Bacteriophages.
- virology : Bacteria.
- Genome, Viral, Host Specificity.
Abstract
The current dramatic increase of antibiotic resistant bacteria has revitalised the interest in bacteriophages as alternative antibacterial treatment. Meanwhile, the development of bioinformatics methods for analysing genomic data places high-throughput approaches for phage characterization within reach. Here, we present HostPhinder, a tool aimed at predicting the bacterial host of phages by examining the phage genome sequence. Using a reference database of 2196 phages with known hosts, HostPhinder predicts the host species of a query phage as the host of the most genomically similar reference phages. As a measure of genomic similarity the number of co-occurring k-mers (DNA sequences of length k) is used. Using an independent evaluation set, HostPhinder was able to correctly predict host genus and species for 81% and 74% of the phages respectively, giving predictions for more phages than BLAST and significantly outperforming BLAST on phages for which both had predictions. HostPhinder predictions on phage draft genomes from the INTESTI phage cocktail corresponded well with the advertised targets of the cocktail. Our study indicates that for most phages genomic similarity correlates well with related bacterial hosts. HostPhinder is available as an interactive web service [
Url:
DOI: 10.3390/v8050116
PubMed: 27153081
PubMed Central: 4885074
Affiliations:
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Le document en format XML
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">HostPhinder: A Phage Host Prediction Tool</title>
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<series><title level="j">Viruses</title>
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<term>Computational Biology (methods)</term>
<term>Genome, Viral</term>
<term>Host Specificity</term>
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<keywords scheme="KwdFr" xml:lang="fr"><term>Bactéries (virologie)</term>
<term>Bactériophages (génétique)</term>
<term>Bactériophages (physiologie)</term>
<term>Biologie informatique ()</term>
<term>Génome viral</term>
<term>Spécificité d'hôte</term>
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<keywords scheme="MESH" qualifier="physiologie" xml:lang="fr"><term>Bactériophages</term>
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<front><div type="abstract" xml:lang="en"><p>The current dramatic increase of antibiotic resistant bacteria has revitalised the interest in bacteriophages as alternative antibacterial treatment. Meanwhile, the development of bioinformatics methods for analysing genomic data places high-throughput approaches for phage characterization within reach. Here, we present HostPhinder, a tool aimed at predicting the bacterial host of phages by examining the phage genome sequence. Using a reference database of 2196 phages with known hosts, HostPhinder predicts the host species of a query phage as the host of the most genomically similar reference phages. As a measure of genomic similarity the number of co-occurring k-mers (DNA sequences of length k) is used. Using an independent evaluation set, HostPhinder was able to correctly predict host genus and species for 81% and 74% of the phages respectively, giving predictions for more phages than BLAST and significantly outperforming BLAST on phages for which both had predictions. HostPhinder predictions on phage draft genomes from the INTESTI phage cocktail corresponded well with the advertised targets of the cocktail. Our study indicates that for most phages genomic similarity correlates well with related bacterial hosts. HostPhinder is available as an interactive web service [<xref rid="B1-viruses-08-00116" ref-type="bibr">1</xref>
] and as a stand alone download from the Docker registry [<xref rid="B2-viruses-08-00116" ref-type="bibr">2</xref>
].</p>
</div>
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</back>
</TEI>
<affiliations><list><country><li>Argentine</li>
</country>
</list>
<tree><noCountry><name sortKey="Jurtz, Vanessa Isabell" sort="Jurtz, Vanessa Isabell" uniqKey="Jurtz V" first="Vanessa Isabell" last="Jurtz">Vanessa Isabell Jurtz</name>
<name sortKey="Kleinheinz, Kortine Annina" sort="Kleinheinz, Kortine Annina" uniqKey="Kleinheinz K" first="Kortine Annina" last="Kleinheinz">Kortine Annina Kleinheinz</name>
<name sortKey="Larsen, Mette Voldby" sort="Larsen, Mette Voldby" uniqKey="Larsen M" first="Mette Voldby" last="Larsen">Mette Voldby Larsen</name>
<name sortKey="Lund, Ole" sort="Lund, Ole" uniqKey="Lund O" first="Ole" last="Lund">Ole Lund</name>
<name sortKey="Villarroel, Julia" sort="Villarroel, Julia" uniqKey="Villarroel J" first="Julia" last="Villarroel">Julia Villarroel</name>
<name sortKey="Zschach, Henrike" sort="Zschach, Henrike" uniqKey="Zschach H" first="Henrike" last="Zschach">Henrike Zschach</name>
</noCountry>
<country name="Argentine"><noRegion><name sortKey="Nielsen, Morten" sort="Nielsen, Morten" uniqKey="Nielsen M" first="Morten" last="Nielsen">Morten Nielsen</name>
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</country>
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</affiliations>
</record>
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