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. 2019 Feb 24;11(2):195.
doi: 10.3390/v11020195.

Classifying the Unclassified: A Phage Classification Method

Cynthia Maria Chibani  1 , Anton Farr  2 , Sandra Klama  3 , Sascha Dietrich  4 , Heiko Liesegang  5
Affiliations

Classifying the Unclassified: A Phage Classification Method

Cynthia Maria Chibani et al. Viruses. .

Abstract

This work reports the method ClassiPhage to classify phage genomes using sequence derived taxonomic features. ClassiPhage uses a set of phage specific Hidden Markov Models (HMMs) generated from clusters of related proteins. The method was validated on all publicly available genomes of phages that are known to infect Vibrionaceae. The phages belong to the well-described phage families of Myoviridae, Podoviridae, Siphoviridae, and Inoviridae. The achieved classification is consistent with the assignments of the International Committee on Taxonomy of Viruses (ICTV), all tested phages were assigned to the corresponding group of the ICTV-database. In addition, 44 out of 58 genomes of Vibrio phages not yet classified could be assigned to a phage family. The remaining 14 genomes may represent phages of new families or subfamilies. Comparative genomics indicates that the ability of the approach to identify and classify phages is correlated to the conserved genomic organization. ClassiPhage classifies phages exclusively based on genome sequence data and can be applied on distinct phage genomes as well as on prophage regions within host genomes. Possible applications include (a) classifying phages from assembled metagenomes; and (b) the identification and classification of integrated prophages and the splitting of phage families into subfamilies.

Keywords: Hidden Markov Models; Inoviridae; Keywords; Myoviridae; Podoviridae; Siphoviridae; Vibrionaceae; classification; phages; protein coding sequences; vibriophages.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Markov Models (HMM) scan of phage family derived models own input “CDS” and coding sequences of other families. The scan of the protein sequences derived from Ino-, Myo-, Podo-, and Siphoviridae, was conducted by the profile HMMs. The names of all phages grouped into phage-families are marked at the bottom of heatmap. The bit-score of the HMM matches was normalized by the size (in bp) of the HMM’s consensus sequence (data see Table S9). The results are color-coded from blue (low-score) to red (high-score).
Figure 2
Figure 2
Alignment of Caudovirales genomes. (A) Myoviridae, (B) Podoviridae, and (C) Siphoviridae. Genomes of phages that have not yet been assigned by ICTV are marked in pink. Four phages JSF9, JSF10, JSF12, and JSF15 are boxed in red. JSF12 has been assigned to Podoviridae based on transmission electron micrographs (TEM) the complete genome alignment indicates a close relation to the Siphoviridae phage JSF10. The data has been visualized with Easyfig.
Figure 3
Figure 3
Taxonomic classification of vibriophages. This heatmap shows a profile HMM scan on the proteins of 58 unclassified bacteriophages genomes. Forty-one unclassified genomes generated sufficient with enough hits to be assigned to a taxonomic group. The HMMs have been integrated in the heatmap (x-axis). The HMMs are grouped (on the y-axis) into the respective phage families. The indicator for the quality of a hit is color coded to the normalized bit-score assigned for the respective match by hmmscan.
Figure 4
Figure 4
HMM scan results of all Inoviridae phages.This heatmap shows an Inoviridae derived profile HMM (y-axis) scan on the proteins of 119 Inoviridae genomes grouped by host genome (x-axis). HMMs ranged from hits specific to Inoviridae infecting Vibrionaecea to general hits for Inoviridae infecting other hosts. The indicator for the quality of a hit is color coded to the normalized bit-score assigned for the respective match by hmmscan.
Figure 5
Figure 5
Profile HMM scan of Podoviridae HMMs from Vibrionaceae versus genomes from Podoviridae phages infecting non-vibrio hosts. This heatmap shows a profile HMM scan on the proteome of 1066 Podoviridae genomes. Sufficient hits were generated to discriminate four groupings of Podoviridae. The HMMs have been integrated in the heatmap (y-axis). The HMMs are grouped (on the x-axis) into general Podoviridae subclassifications. The indicator for the quality of a hit is color coded to thenormalized bit-score assigned for the respective match by hmmscan. The generated hmmscan output was visualized using matplotlib library in Python 3.5.
Figure 6
Figure 6
HMM search for prophages in Vibrio genomes with proven phage activities.Family specific HMMs constructed for Ino-, Myo-, Podo-, andSiphoviridae (grouped on x-axis) were used to scan all proteins derived from the genome of nine V. alginolyticus and one V. typhli genomes (x-axis per phage family grouping). In all of the V. alginolyticus genomes, regions encoding proteins matching to the profile HMMs were found (plotted per position and grouped per replicon on the y-axis). In cases where a region with consecutive HMM hits predicted as well by PHASTER was separately faceted.
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References

    1. Chow C.-E.T., Suttle C.A. Biogeography of Viruses in the Sea. Annu. Rev. Virol. 2015;2:41–66. doi: 10.1146/annurev-virology-031413-085540. - DOI - PubMed
    1. Suttle C.A. Marine viruses-Major players in the global ecosystem. Nat. Rev. Microbiol. 2007;5:801–812. doi: 10.1038/nrmicro1750. - DOI - PubMed
    1. Adams M.J., Lefkowitz E.J., King A.M.Q., Harrach B., Harrison R.L., Knowles N.J., Kropinski A.M., Krupovic M., Kuhn J.H., Mushegian A.R., et al. 50 years of the International Committee on Taxonomy of Viruses: Progress and prospects. Arch. Virol. 2017;162:1441–1446. doi: 10.1007/s00705-016-3215-y. - DOI - PubMed
    1. Ackermann H.W. Classification of Bacteriophages. In: Calendar R., editor. The Bacteriophages. Oxford University Press; New York, NY, USA: 2006. p. 746.
    1. Simmonds P., Adams M.J., Benk M., Breitbart M., Brister J.R., Carstens E.B., Davison A.J., Delwart E., Gorbalenya A.E., Harrach B., et al. Consensus statement: Virus taxonomy in the age of metagenomics. Nat. Rev. Microbiol. 2017;15:161–168. doi: 10.1038/nrmicro.2016.177. - DOI - PubMed

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