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Contributions of P2- and P22-like prophages to understanding the enormous diversity and abundance of tailed bacteriophages.

ABSTRACT: We identified 9371 tailed phage prophages of 20 known types in reported complete genome sequences of 3298 bacteria in the Salmonella genus. These include 4758 P2 type and 744 P22 type prophages. The latter prophage types were found in the genome sequences of 127 and 24 bacterial host genera, increasing the known host ranges of phages in these groups by 114 and 20 genera, respectively. These prophage nucleotide sequences displayed much more diversity than was previously known from the 48 P2 and 24 P22 type authentic phages whose genomes have been sequenced. More detailed analysis of these prophage sequences indicated that major capsid protein (MCP) gene exchange between tailed phage clusters or types is extremely rare and that P22 prophage-encoded tailspikes correspond perfectly with their hosts' surface polysaccharide structure; thus, MCP and tailspike sequences accurately predict tailed phage type (and thus lifestyle) and host cell surface polysaccharide structure, respectively.

SUBMITTER: Casjens SR

PROVIDER: S-EPMC4969182 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Contributions of P2- and P22-like prophages to understanding the enormous diversity and abundance of tailed bacteriophages.

Casjens Sherwood R SR Grose Julianne H JH

Virology 20160630

We identified 9371 tailed phage prophages of 20 known types in reported complete genome sequences of 3298 bacteria in the Salmonella genus. These include 4758 P2 type and 744 P22 type prophages. The latter prophage types were found in the genome sequences of 127 and 24 bacterial host genera, increasing the known host ranges of phages in these groups by 114 and 20 genera, respectively. These prophage nucleotide sequences displayed much more diversity than was previously known from the 48 P2 and 2 ...[more]

PMID: 27372181

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Project description:BACKGROUND: The genetic diversity observed among bacteriophages remains a major obstacle for the identification of homologs and the comparison of their functional modules. In the structural module, although several classes of homologous proteins contributing to the head and tail structure can be detected, proteins of the head-to-tail connection (or neck) are generally more divergent. Yet, molecular analyses of a few tailed phages belonging to different morphological classes suggested that only a limited number of structural solutions are used in order to produce a functional virion. To challenge this hypothesis and analyze proteins diversity at the virion neck, we developed a specific computational strategy to cope with sequence divergence in phage proteins. We searched for homologs of a set of proteins encoded in the structural module using a phage learning database. RESULTS: We show that using a combination of iterative profile-profile comparison and gene context analyses, we can identify a set of head, neck and tail proteins in most tailed bacteriophages of our database. Classification of phages based on neck protein sequences delineates 4 Types corresponding to known morphological subfamilies. Further analysis of the most abundant Type 1 yields 10 Clusters characterized by consistent sets of head, neck and tail proteins. We developed Virfam, a webserver that automatically identifies proteins of the phage head-neck-tail module and assign phages to the most closely related cluster of phages. This server was tested against 624 new phages from the NCBI database. 93% of the tailed and unclassified phages could be assigned to our head-neck-tail based categories, thus highlighting the large representativeness of the identified virion architectures. Types and Clusters delineate consistent subgroups of Caudovirales, which correlate with several virion properties. CONCLUSIONS: Our method and webserver have the capacity to automatically classify most tailed phages, detect their structural module, assign a function to a set of their head, neck and tail genes, provide their morphologic subtype and localize these phages within a "head-neck-tail" based classification. It should enable analysis of large sets of phage genomes. In particular, it should contribute to the classification of the abundant unknown viruses found on assembled contigs of metagenomic samples.

Dataset Information

Contributions of P2- and P22-like prophages to understanding the enormous diversity and abundance of tailed bacteriophages.

Publications

Contributions of P2- and P22-like prophages to understanding the enormous diversity and abundance of tailed bacteriophages.

Similar Datasets

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