title: HostPhinder: A Phage Host Prediction Tool.
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 [1] and as a stand alone download from the Docker registry [2].
authors.affiliation: Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. juliavi@cbs.dtu.dk.
authors.forename: Julia
authors.initials: J
authors.lastname: Villarroel
authors.affiliation: Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. kortinekleinheinz@gmx.de.
authors.forename: Kortine Annina
authors.initials: KA
authors.lastname: Kleinheinz
authors.affiliation: Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. vanessa@cbs.dtu.dk.
authors.forename: Vanessa Isabell
authors.initials: VI
authors.lastname: Jurtz
authors.affiliation: Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. henrike@cbs.dtu.dk.
authors.forename: Henrike
authors.initials: H
authors.lastname: Zschach
authors.affiliation: Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. lund@cbs.dtu.dk.
authors.forename: Ole
authors.initials: O
authors.lastname: Lund
authors.affiliation: Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. mniel@cbs.dtu.dk.|Instituto de Investigaciones Biotecnológicas, Universidad de San Martín, CP(1650) San Martín, Prov. de Buenos Aires, Argentina. mniel@cbs.dtu.dk.
authors.forename: Morten
authors.initials: M
authors.lastname: Nielsen
authors.affiliation: Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. metteb@cbs.dtu.dk.
authors.forename: Mette Voldby
authors.initials: MV
authors.lastname: Larsen
mesh_terms: D001419:Bacteria / Q000821:virology*; D001435:Bacteriophages / Q000235:genetics* / Q000502:physiology*; D019295:Computational Biology / Q000379:methods*; D016679:Genome, Viral; D058507:Host Specificity
keywords: genome; k-mers; prediction; “host specificity”