RaFAH: Host prediction for viruses of Bacteria and Archaea based on protein content
Felipe Hernandes Coutinho,
Asier Zaragoza-Solas,
Mario López-Pérez,
Jakub Barylski,
Andrzej Zielezinski,
Bas E. Dutilh,
Robert Edwards,
Francisco Rodriguez-Valera
Affiliations
Felipe Hernandes Coutinho
Evolutionary Genomics Group, Departamento de Producción Vegetal y Microbiología, Universidad Miguel Hernández, Aptdo. 18., Ctra. Alicante-Valencia N-332, s/n, San Juan de Alicante, 03550 Alicante, Spain; Corresponding author
Asier Zaragoza-Solas
Evolutionary Genomics Group, Departamento de Producción Vegetal y Microbiología, Universidad Miguel Hernández, Aptdo. 18., Ctra. Alicante-Valencia N-332, s/n, San Juan de Alicante, 03550 Alicante, Spain
Mario López-Pérez
Evolutionary Genomics Group, Departamento de Producción Vegetal y Microbiología, Universidad Miguel Hernández, Aptdo. 18., Ctra. Alicante-Valencia N-332, s/n, San Juan de Alicante, 03550 Alicante, Spain
Jakub Barylski
Molecular Virology Research Unit, Faculty of Biology, Adam Mickiewicz University Poznan, 61-614 Poznan, Poland
Andrzej Zielezinski
Department of Computational Biology, Faculty of Biology, Adam Mickiewicz University Poznan, 61-614 Poznan, Poland
Bas E. Dutilh
Centre for Molecular and Biomolecular Informatics (CMBI), Radboud University Medical Centre/Radboud Institute for Molecular Life Sciences, 6525 GA Nijmegen, the Netherlands; Theoretical Biology and Bioinformatics, Science for Life, Utrecht University (UU), 3584 CH Utrecht, the Netherlands
Robert Edwards
College of Science and Engineering, Flinders University, Bedford Park, SA 5042, Australia
Francisco Rodriguez-Valera
Evolutionary Genomics Group, Departamento de Producción Vegetal y Microbiología, Universidad Miguel Hernández, Aptdo. 18., Ctra. Alicante-Valencia N-332, s/n, San Juan de Alicante, 03550 Alicante, Spain; Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russia
Summary: Culture-independent approaches have recently shed light on the genomic diversity of viruses of prokaryotes. One fundamental question when trying to understand their ecological roles is: which host do they infect? To tackle this issue we developed a machine-learning approach named Random Forest Assignment of Hosts (RaFAH), that uses scores to 43,644 protein clusters to assign hosts to complete or fragmented genomes of viruses of Archaea and Bacteria. RaFAH displayed performance comparable with that of other methods for virus-host prediction in three different benchmarks encompassing viruses from RefSeq, single amplified genomes, and metagenomes. RaFAH was applied to assembled metagenomic datasets of uncultured viruses from eight different biomes of medical, biotechnological, and environmental relevance. Our analyses led to the identification of 537 sequences of archaeal viruses representing unknown lineages, whose genomes encode novel auxiliary metabolic genes, shedding light on how these viruses interfere with the host molecular machinery. RaFAH is available at https://sourceforge.net/projects/rafah/. The bigger picture: Viruses that infect Bacteria and Archaea are ubiquitous and extremely abundant. Recent advances have led to the discovery of many thousands of complete and partial genomes of these biological entities. Understanding the biology of these viruses and how they influence their ecosystems depends on knowing which hosts they infect. We developed a tool that uses data from complete or fragmented genomes to predict the hosts of viruses using a machine-learning approach. Our tool, RaFAH, displayed performance comparable with or superior to that of other host-prediction tools. In addition, it identified hundreds of sequences as derived from the genomes of viruses of Archaea, which are one of the least characterized fractions of the global virosphere.
