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Evolution along the parasitism-mutualism continuum determines the genetic repertoire of prophages.

Authors :
Khan, Amjad
Burmeister, Alita R.
Wahl, Lindi M.
Source :
PLoS Computational Biology. 12/4/2020, Vol. 16 Issue 12, p1-19. 19p. 1 Diagram, 4 Charts, 7 Graphs.
Publication Year :
2020

Abstract

Integrated into their bacterial hosts' genomes, prophage sequences exhibit a wide diversity of length and gene content, from highly degraded cryptic sequences to intact, functional prophages that retain a full complement of lytic-function genes. We apply three approaches—bioinformatics, analytical modelling and computational simulation—to understand the diverse gene content of prophages. In the bioinformatics work, we examine the distributions of over 50,000 annotated prophage genes identified in 1384 prophage sequences, comparing the gene repertoires of intact and incomplete prophages. These data indicate that genes involved in the replication, packaging, and release of phage particles have been preferentially lost in incomplete prophages, while tail fiber, transposase and integrase genes are significantly enriched. Consistent with these results, our mathematical and computational approaches predict that genes involved in phage lytic function are preferentially lost, resulting in shorter prophages that often retain genes that benefit the host. Informed by these models, we offer novel hypotheses for the enrichment of integrase and transposase genes in cryptic prophages. Overall, we demonstrate that functional and cryptic prophages represent a diversity of genetic sequences that evolve along a parasitism-mutualism continuum. Author summary: Prophages exhibit tremendous variation in both length and gene content, but little is understood about the gene repertoires of intact (functional) or degraded (cryptic) prophage sequences. By comparing large datasets of annotated prophage genes, we offer evidence for both the enrichment and loss of genes of specific function, resulting in various "signatures" of prophage gene content. We then use analytical and computational models to understand the evolutionary forces underlying those genomic signatures. In particular, our data analysis demonstrates that tail fiber, integrase and transposase genes are enriched in cryptic prophages. Informed by our simulation studies, we offer novel hypotheses to explain these unexpected results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1553734X
Volume :
16
Issue :
12
Database :
Academic Search Index
Journal :
PLoS Computational Biology
Publication Type :
Academic Journal
Accession number :
147380147
Full Text :
https://doi.org/10.1371/journal.pcbi.1008482