Phage_Finder: Automated identification and classification of prophage regions in complete bacterial genome sequences

By Derrick E. Fouts. Nucleic Acids Research, 2006

304 citations recorded by the source corpus.

Phage_Finder, a heuristic computer program, was created to identify prophage regions in completed bacterial genomes. Using a test dataset of 42 bacterial genomes whose prophages have been manually identified, Phage_Finder found 91% of the regions, resulting in 7% false positive and 9% false negative prophages. A search of 302 complete bacterial genomes predicted 403 putative prophage regions, accounting for 2.7% of the total bacterial DNA. Analysis of the 285 putative attachment sites revealed tRNAs are targets for integration slightly more frequently (33%) than intergenic (31%) or intragenic (28%) regions, while tmRNAs were targeted in 8% of the regions. The most popular tRNA targets were Arg, Leu, Ser and Thr. Mapping of the insertion point on a consensus tRNA molecule revealed novel insertion points on the 5′ side of the D loop, the 3′ side of the anticodon loop and the anticodon. A novel method of constructing phylogenetic trees of phages and prophages was developed based on the mean of the BLAST score ratio (BSR) of the phage/prophage proteomes. This method verified many known bacteriophage groups, making this a useful tool for predicting the relationships of prophages from bacterial genomes.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/41d6f81c8e711e8649849f5ba804534b9ec5d781

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Citations in the corpus

Genomic analysis of bacteriophage ε34 of Salmonella enterica serovar Anatum (15+) (2008, unknown): “Genomic sequencing has shown that essentially all Salmonellae carry prophages [7-13].”
Identifying viruses from metagenomic data using deep learning (2020, methodology): “…[9], DIA-MOND [13], VirSorter [4], JGI Earth Virome Pipeline [19], MARVEL [6], and most provirus ﬁ nding tools, Prophinder [15], Phage-Finder [14], PhiSpy [16], and PHASTER [17], determine viral sequences mainly by comparing genes in the query sequence against viral gene databases, and see…”
Computational approaches to predict bacteriophage–host relationships (2015, background): “First, when the temperate phage is integrated, it can be detected in silico with prophage finding tools (Fouts 2006; Lima-Mendez et al. 2008; Akhter, Aziz and Edwards 2012; Roux et al. 2015a).”
VirFinder: a novel k-mer based tool for identifying viral sequences from assembled metagenomic data (2017, methodology): “These provirus finding programs include Phage_Finder [9], Prophinder [10], PHAST [11], and PhiSpy [12].”
Bacteriophage targeting of gut bacterium attenuates alcoholic liver disease (2019, unknown): “Preliminary annotation of genes was derived from the automated annotation and from Phage_Finder 42 , which uses curated HMMs and databases of core phage gene to annotate core gene functions.”
Lysogeny in nature: mechanisms, impact and ecology of temperate phages (2017, background): “For example, the detection of λ-like, P1-like or Mu-like phages varies across microbial genomes, with Mu-like and P1-like being least reported (Casjens, 2003; Fouts, 2006; Bobay et al., 2013; Roux et al., 2015b).”