PhageWeb – Web Interface for Rapid Identification and Characterization of Prophages in Bacterial Genomes

This study developed a computational tool with a graphical interface and a web-service that allows the identification of phage regions through homology search and gene clustering. It uses G+C content variation evaluation and tRNA prediction sites as evidence to reinforce the presence of prophages in indeterminate regions. Also, it performs the functional characterization of the prophages regions through data integration of biological databases. The performance of PhageWeb was compared to other available tools (PHASTER, Prophinder, and PhiSpy) using Sensitivity (Sn) and Positive Predictive Value (PPV) tests. As a reference for the tests, more than 80 manually annotated genomes were used. In the PhageWeb analysis, the Sn index was 86.1% and the PPV was approximately 87%, while the second best tool presented Sn and PPV values of 83.3 and 86.5%, respectively. These numbers allowed us to observe a greater precision in the regions identified by PhageWeb while compared to other prediction tools submitted to the same tests. Additionally, PhageWeb was much faster than the other computational alternatives, decreasing the processing time to approximately one-ninth of the time required by the second best software. PhageWeb is freely available at http://computationalbiology.ufpa.br/phageweb.

[1]  Allan Campbell,et al.  Prophage insertion sites. , 2003, Research in microbiology.

[2]  Nicola K. Petty,et al.  BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons , 2011, BMC Genomics.

[3]  Arthur Zimek,et al.  Density-Based Clustering Validation , 2014, SDM.

[4]  J. Bull,et al.  Population and evolutionary dynamics of phage therapy , 2004, Nature Reviews Microbiology.

[5]  Fiona S. L. Brinkman,et al.  Detecting genomic islands using bioinformatics approaches , 2010, Nature Reviews Microbiology.

[6]  G. Winter,et al.  Making antibodies by phage display technology. , 1994, Annual review of immunology.

[7]  A. V. S. K. Mohan Katta,et al.  Identification of Prophages in Bacterial Genomes by Dinucleotide Relative Abundance Difference , 2007, PloS one.

[8]  Jacques van Helden,et al.  Prophinder: a computational tool for prophage prediction in prokaryotic genomes , 2008, Bioinform..

[9]  A. Caprioli,et al.  Shiga toxin-converting phages and the emergence of new pathogenic Escherichia coli: a world in motion , 2014, Front. Cell. Infect. Microbiol..

[10]  T. B. Rasmussen,et al.  In silico prediction of horizontal gene transfer in Streptococcus thermophilus , 2011, Archives of Microbiology.

[11]  Robert A. Edwards,et al.  PhiSpy: a novel algorithm for finding prophages in bacterial genomes that combines similarity- and composition-based strategies , 2012, Nucleic acids research.

[12]  Donald W. Bouldin,et al.  A Cluster Separation Measure , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  David S. Wishart,et al.  PHAST: A Fast Phage Search Tool , 2011, Nucleic Acids Res..

[14]  Testing hypotheses for the presence of tRNA genes in mycobacteriophage genomes , 2016, Bacteriophage.

[15]  João C. Setubal,et al.  MARVEL, a Tool for Prediction of Bacteriophage Sequences in Metagenomic Bins , 2018, Front. Genet..

[16]  H. Ochman,et al.  Lateral gene transfer and the nature of bacterial innovation , 2000, Nature.

[17]  Ghislain Fournous,et al.  Prophage Genomics , 2003, Microbiology and Molecular Biology Reviews.

[18]  David S. Wishart,et al.  PHASTER: a better, faster version of the PHAST phage search tool , 2016, Nucleic Acids Res..

[19]  Ishtiaq Qadri,et al.  Bacteriophages and their implications on future biotechnology: a review , 2012, Virology Journal.

[20]  N. Sharp,et al.  Phage-based platforms for the clinical detection of human bacterial pathogens , 2012, Bacteriophage.

[21]  D. W. Kim,et al.  Whole-genome sequence comparisons reveal the evolution of Vibrio cholerae O1. , 2015, Trends in microbiology.

[22]  J. Dunn.  Well-Separated Clusters and Optimal Fuzzy Partitions , 1974 .

[23]  M. Metzker.  Sequencing technologies — the next generation , 2010, Nature Reviews Genetics.

[24]  Hon Wai Leong,et al.  Computational methods for predicting genomic islands in microbial genomes , 2016, Computational and structural biotechnology journal.

[25]  S. Abediankenari,et al.  Phage Particles as Vaccine Delivery Vehicles: Concepts, Applications and Prospects. , 2016, Asian Pacific journal of cancer prevention : APJCP.

[26]  P. Rousseeuw.  Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[27]  Chao Xie,et al.  Fast and sensitive protein alignment using DIAMOND , 2014, Nature Methods.

[28]  Sallie W. Chisholm,et al.  Cyanophages infecting the oceanic cyanobacterium Prochlorococcus , 2003, Nature.

[29]  Forest Rohwer,et al.  Global Phage Diversity , 2003, Cell.

[30]  S. Casjens,et al.  Prophages and bacterial genomics: what have we learned so far? , 2003, Molecular microbiology.

[31]  Viruses cooperate to defeat bacteria , 2018, Nature.

[32]  Wolf-Dietrich Hardt,et al.  Phages and the Evolution of Bacterial Pathogens: from Genomic Rearrangements to Lysogenic Conversion , 2004, Microbiology and Molecular Biology Reviews.