ProphET, prophage estimation tool: A stand-alone prophage sequence prediction tool with self-updating reference database


Autoři: João L. Reis-Cunha aff001;  Daniella C. Bartholomeu aff002;  Abigail L. Manson aff001;  Ashlee M. Earl aff001;  Gustavo C. Cerqueira aff001
Působiště autorů: Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America aff001;  Departamento de Parasitologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil aff002;  Personal Genome Diagnostics, Baltimore, Maryland, United States of America aff003
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0223364

Souhrn

Background

Prophages play a significant role in prokaryotic evolution, often altering the function of the cell that they infect via transfer of new genes e.g., virulence or antibiotic resistance factors, inactivation of existing genes or by modifying gene expression. Recently, phage therapy has gathered renewed interest as a promising alternative to control bacterial infections. Cataloging the repertoire of prophages in large collections of species’ genomes is an important initial step in understanding their evolution and potential therapeutic utility. However, current widely-used tools for identifying prophages within bacterial genome sequences are mainly web-based, can have long response times, and do not scale to keep pace with the many thousands of genomes currently being sequenced routinely.

Methodology

In this work, we present ProphET, an easy to install prophage predictor to be used in Linux operation system, without the constraints associated with a web-based tool. ProphET predictions rely on similarity searches against a database of prophage genes, taking as input a bacterial genome sequence in FASTA format and its corresponding gene annotation in GFF. ProphET identifies prophages in three steps: similarity search, calculation of the density of prophage genes, and edge refinement. ProphET performance was evaluated and compared with other phage predictors based on a set of 54 bacterial genomes containing 267 manually annotated prophages.

Findings and conclusions

ProphET identifies prophages in bacterial genomes with high precision and offers a fast, highly scalable alternative to widely-used web-based applications for prophage detection.

Klíčová slova:

Bacterial genomics – Bacteriophages – Database searching – Genome analysis – Genomic databases – Sequence databases – Sequence similarity searching – Viral genomics


Zdroje

1. Brüssow H, Canchaya C, Hardt W, Bru H. Phages and the Evolution of Bacterial Pathogens: from Genomic Rearrangements to Lysogenic Conversion Phages and the Evolution of Bacterial Pathogens: from Genomic Rearrangements to Lysogenic Conversion. Microbiol Mol Biol Rev. 2004;68(3):560–602. doi: 10.1128/MMBR.68.3.560-602.2004 15353570

2. Davies E V., Winstanley C, Fothergill JL, James CE. The role of temperate bacteriophages in bacterial infection. FEMS Microbiol Lett. 2016;363(5):1–10.

3. Faruque SM, Mekalanos JJ. Phage-bacterial interactions in the evolution of toxigenic Vibrio cholerae. Virulence. 2012;3(7):556–65. Available from: http://www.tandfonline.com/doi/abs/10.4161/viru.22351 23076327

4. Aziz RK, Edwards RA, Taylor WW, Low DE, McGeer A, Kotb M. Mosaic prophages with horizontally acquired genes account for the emergence and diversification of the globally disseminated M1t1 clone of Streptococcus pyogenes. J Bacteriol. 2005;187(10):3311–8. doi: 10.1128/JB.187.10.3311-3318.2005 15866915

5. Casjens S. Prophages and bacterial genomics: What have we learned so far? Vol. 49, Molecular Microbiology. 2003. p. 277–300. doi: 10.1046/j.1365-2958.2003.03580.x 12886937

6. Laing CR, Zhang Y, Gilmour MW, Allen V, Johnson R, Thomas JE, et al. A comparison of Shiga-Toxin 2 bacteriophage from classical enterohemorrhagic Escherichia coli serotypes and the German E. coli O104:H4 outbreak strain. PLoS One. 2012;7(5).

7. Yan X, Fratamico PM, Bono JL, Baranzoni GM, Chen CY. Genome sequencing and comparative genomics provides insights on the evolutionary dynamics and pathogenic potential of different H-serotypes of Shiga toxin-producing Escherichia coli O104. BMC Microbiol. 2015;15(1).

8. Grose JH, Casjens SR. Understanding the enormous diversity of bacteriophages: The tailed phages that infect the bacterial family Enterobacteriaceae. Virology. 2014;468:421–43. doi: 10.1016/j.virol.2014.08.024 25240328

9. Levin BR, Bull JJ. Population and evolutionary dynamics of phage therapy. Nat Rev Microbiol. 2004;2(2):166–73. doi: 10.1038/nrmicro822 15040264

10. Hendrix RW. Bacteriophages: Evolution of the Majority. Vol. 61, Theoretical Population Biology. 2002. p. 471–80. 12167366

11. Suttle C a. Marine viruses—major players in the global ecosystem. Nat Rev Microbiol. 2007;5(10):801–12. doi: 10.1038/nrmicro1750 17853907

12. Pope WH, Bowman CA, Russell DA, Jacobs-Sera D, Asai DJ, Cresawn SG, et al. Whole genome comparison of a large collection of mycobacteriophages reveals a continuum of phage genetic diversity. Elife. 2015 Jan;4:e06416. doi: 10.7554/eLife.06416 25919952

13. Lima-Mendez G, Van Helden J, Toussaint A, Leplae R. Prophinder: A computational tool for prophage prediction in prokaryotic genomes. Bioinformatics. 2008;24(6):863–5. doi: 10.1093/bioinformatics/btn043 18238785

14. Zhou Y, Liang Y, Lynch KH, Dennis JJ, Wishart DS. PHAST: A Fast Phage Search Tool. Nucleic Acids Res. 2011;39(SUPPL. 2).

15. Arndt D, Grant JR, Marcu A, Sajed T, Pon A, Liang Y, et al. PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res. 2016;44(W1):W16–21. doi: 10.1093/nar/gkw387 27141966

16. Akhter S, Aziz RK, Edwards RA. PhiSpy: A novel algorithm for finding prophages in bacterial genomes that combines similarity-and composition-based strategies. Nucleic Acids Res. 2012;40(16).

17. Krupovic M, Prangishvili D, Hendrix RW, Bamford DH. Genomics of bacterial and archaeal viruses: dynamics within the prokaryotic virosphere. Microbiol Mol Biol Rev. 2011 Dec;75(4):610–35. doi: 10.1128/MMBR.00011-11 22126996

18. Davidson AL, Dassa E, Orelle C, Chen J. Structure, function, and evolution of bacterial ATP-binding cassette systems. Microbiol Mol Biol Rev. 2008;72(2):317–64, table of contents. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2415747 doi: 10.1128/MMBR.00031-07 18535149

19. Campbell A. Prophage insertion sites. Vol. 154, Research in Microbiology. 2003. p. 277–82. doi: 10.1016/S0923-2508(03)00071-8 12798232


Článek vyšel v časopise

PLOS One


2019 Číslo 10

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…


Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

Léčba bolesti v ordinaci praktického lékaře
nový kurz
Autoři: MUDr. PhDr. Zdeňka Nováková, Ph.D.

Revmatoidní artritida: včas a k cíli
Autoři: MUDr. Heřman Mann

Jistoty a nástrahy antikoagulační léčby aneb kardiolog - neurolog - farmakolog - nefrolog - právník diskutují
Autoři: doc. MUDr. Štěpán Havránek, Ph.D., prof. MUDr. Roman Herzig, Ph.D., doc. MUDr. Karel Urbánek, Ph.D., prim. MUDr. Jan Vachek, MUDr. et Mgr. Jolana Těšínová, Ph.D.

Léčba akutní pooperační bolesti
Autoři: doc. MUDr. Jiří Málek, CSc.

Nové antipsychotikum kariprazin v léčbě schizofrenie
Autoři: prof. MUDr. Cyril Höschl, DrSc., FRCPsych.

Všechny kurzy
Kurzy Doporučená témata Časopisy
Přihlášení
Zapomenuté heslo

Nemáte účet?  Registrujte se

Zapomenuté heslo

Zadejte e-mailovou adresu se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se