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The Phage Proteomic Tree: a genome-based taxonomy for phage.

ABSTRACT: There are approximately 10(31) phage in the biosphere, making them the most abundant biological entities on the planet. Despite their great numbers and ubiquitous presence, very little is known about phage biodiversity, biogeography, or phylogeny. Information is limited, in part, because the current ICTV taxonomical system is based on culturing phage and measuring physical parameters of the free virion. No sequence-based taxonomic systems have previously been established for phage. We present here the "Phage Proteomic Tree," which is based on the overall similarity of 105 completely sequenced phage genomes. The Phage Proteomic Tree places phage relative to both their near neighbors and all other phage included in the analysis. This method groups phage into taxa that predicts several aspects of phage biology and highlights genetic markers that can be used for monitoring phage biodiversity. We propose that the Phage Proteomic Tree be used as the basis of a genome-based taxonomical system for phage.

SUBMITTER: Rohwer F

PROVIDER: S-EPMC135240 | biostudies-literature | 2002 Aug

REPOSITORIES: biostudies-literature

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The Phage Proteomic Tree: a genome-based taxonomy for phage.

Rohwer Forest F Edwards Rob R

Journal of bacteriology 20020801 16

There are approximately 10(31) phage in the biosphere, making them the most abundant biological entities on the planet. Despite their great numbers and ubiquitous presence, very little is known about phage biodiversity, biogeography, or phylogeny. Information is limited, in part, because the current ICTV taxonomical system is based on culturing phage and measuring physical parameters of the free virion. No sequence-based taxonomic systems have previously been established for phage. We present he ...[more]

PMID: 12142423

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Project description:Bacteriophage comparative genomics is complex due to the mosaic nature of the genomes, and an underlying continuum of diversity confounds the identification of clear taxonomic boundaries. Nucleotide sequence comparison methods have been described for phage taxonomy, but they are computationally intensive and scale poorly as the number of sequenced phage genomes increases. Here, we describe PhamClust as a new bioinformatic approach for grouping phages according to their inter-genome relatedness. PhamClust calculates a proteomic equivalence quotient (PEQ) for each pair of phages based on amino acid sequence identity for those genes that are shared among phages. PEQ values span from 0% (no shared genes) to 100% (all genes shared at 100% identity), and using a large mycobacteriophage genome data set, we show that two-step clustering down to a PEQ of 25% constructs genome groupings (clusters) closely mirroring those constructed manually over time, with the differences attributable to historically arising incongruities rather than illogicalities in PhamClust. PEQ values can also faithfully divide clusters into subclusters, although the relationships are highly heterogeneous, with different PEQ values needed for the subdivision of different clusters. PhamClust can be used to assort any group of phages, including the RefSeq phage collection. IMPORTANCE Bacteriophage genomes are pervasively mosaic, presenting challenges to describing phage relatedness. Here, we describe PhamClust, a bioinformatic approach for phage genome comparisons that uses a new metric of proteomic equivalence quotient for comparative genomics. PhamClust reliably assorts genomes into groups or clusters of related phages and can subdivide clusters into subclusters. PhamClust is computationally efficient and can readily process thousands of phage genomes. It is also a useful analytic tool for exploring the different types of inter-genome relatedness characteristic of phages in different clusters.

Project description:BackgroundCharacterizing phage-host interactions is critical to understanding the ecological role of both partners and effective isolation of phage therapeuticals. Unfortunately, experimental methods for studying these interactions are markedly slow, low-throughput, and unsuitable for phages or hosts difficult to maintain in laboratory conditions. Therefore, a number of in silico methods emerged to predict prokaryotic hosts based on viral sequences. One of the leading approaches is the application of the BLAST tool that searches for local similarities between viral and microbial genomes. However, this prediction method has three major limitations: (i) top-scoring sequences do not always point to the actual host; (ii) mosaic virus genomes may match to many, typically related, bacteria; and (iii) viral and host sequences may diverge beyond the point where their relationship can be detected by a BLAST alignment.ResultsWe 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 three benchmark sets of known virus-host pairs, and it improved precision and recall by 11-40 percentage points over currently available, state-of-the-art, alignment-based, alignment-free, and machine-learning host prediction tools. Moreover, the discriminatory power of Phirbo for the recognition of virus-host relationships surpassed the results of other tools by at least 10 percentage points (area under the curve = 0.95), yielding a mean host prediction accuracy of 57% and 68% at the genus and family levels, respectively, and drops by 12 percentage points when using only a fraction of viral genome sequences (3 kb). Finally, we provide insights into a repertoire of protein and ncRNA genes that are shared between phages and hosts and may be prone to horizontal transfer during infection.ConclusionsOur results suggest that Phirbo is a simple and effective tool for predicting phage-host relationships.

Dataset Information

The Phage Proteomic Tree: a genome-based taxonomy for phage.

Publications

The Phage Proteomic Tree: a genome-based taxonomy for phage.

Similar Datasets

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