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Taxonomy-aware, sequence similarity ranking reliably predicts phage-host relationships

View ORCID ProfileAndrzej Zielezinski, View ORCID ProfileJakub Barylski, View ORCID ProfileWojciech M. Karlowski
doi: https://doi.org/10.1101/2021.01.05.425417
Andrzej Zielezinski
1Department of Computational Biology, Faculty of Biology, Adam Mickiewicz University Poznan, Uniwersytetu Poznanskiego 6, 61-614, Poznan, Poland
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  • For correspondence: andrzejz@amu.edu.pl
Jakub Barylski
2Molecular Virology Research Unit, Faculty of Biology, Adam Mickiewicz University Poznan, Uniwersytetu Poznanskiego 6, 61-614, Poznan, Poland
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Wojciech M. Karlowski
1Department of Computational Biology, Faculty of Biology, Adam Mickiewicz University Poznan, Uniwersytetu Poznanskiego 6, 61-614, Poznan, Poland
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ABSTRACT

Motivation Similar regions in virus and host genomes provide strong evidence for phage-host interaction, and BLAST is one of the leading tools to predict hosts from phage sequences. However, BLAST-based host prediction has three limitations: (i) top-scoring prokaryotic sequences do not always point to the actual host, (ii) mosaic phage genomes may produce matches to many, typically related, bacteria, and (iii) phage and host sequences may diverge beyond the point where their relationship can be detected by a BLAST alignment.

Results We created an extension to BLAST, named Phirbo, that improves host prediction quality beyond what is obtainable from standard BLAST searches. The tool harnesses information concerning sequence similarity and bacteria relatedness to predict phage-host interactions. Phirbo was evaluated on two benchmark sets of known phage-host pairs, and it improved precision and recall by 25 percentage points, as well as the discriminatory power for the recognition of phage-host relationships by 10 percentage points (Area Under the Curve = 0.95). Phirbo also yielded a mean host prediction accuracy of 60% and 70% at the genus and family levels, respectively, representing a 5% improvement over BLAST. When using only a fraction of phage genome sequences (3 kb), the prediction accuracy of Phirbo was 5-11% higher than BLAST at all taxonomic levels.

Conclusion Our results suggest that Phirbo is an effective, unsupervised tool for predicting phage-host relationships.

Availability Phirbo is available at https://github.com/aziele/phirbo.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted January 06, 2021.
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Taxonomy-aware, sequence similarity ranking reliably predicts phage-host relationships
Andrzej Zielezinski, Jakub Barylski, Wojciech M. Karlowski
bioRxiv 2021.01.05.425417; doi: https://doi.org/10.1101/2021.01.05.425417
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Taxonomy-aware, sequence similarity ranking reliably predicts phage-host relationships
Andrzej Zielezinski, Jakub Barylski, Wojciech M. Karlowski
bioRxiv 2021.01.05.425417; doi: https://doi.org/10.1101/2021.01.05.425417

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