Discovery and description of novel phage genomes from urban microbiomes sampled by the MetaSUB consortium.

Bacteriophages are recognized as the most abundant members of microbiomes and have therefore a profound impact on microbial communities through the interactions with their bacterial hosts. The International Metagenomics and Metadesign of Subways and Urban Biomes Consortium (MetaSUB) has sampled mass-transit systems in 60 cities over 3 years using metagenomics, throwing light into these hitherto largely unexplored urban environments. MetaSUB focused primarily on the bacterial community. In this work, we explored MetaSUB metagenomic data in order to recover and analyze bacteriophage genomes. We recovered and analyzed 1714 phage genomes with size at least 40 kbp, from the class Caudoviricetes, the vast majority of which (80%) are novel. The recovered genomes were predicted to belong to temperate (69%) and lytic (31%) phages. Thirty-three of these genomes have more than 200 kbp, and one of them reaches 572 kbp, placing it among the largest phage genomes ever found. In general, the phages tended to be site-specific or nearly so, but 194 genomes could be identified in every city from which phage genomes were retrieved. We predicted hosts for 48% of the phages and observed general agreement between phage abundance and the respective bacterial host abundance, which include the most common nosocomial multidrug-resistant pathogens. A small fraction of the phage genomes are carriers of antibiotic resistance genes, and such genomes tended to be particularly abundant in the sites where they were found. We also detected CRISPR-Cas systems in five phage genomes. This study expands the previously reported MetaSUB results and is a contribution to the knowledge about phage diversity, global distribution, and phage genome content.

vHULK, a New Tool for Bacteriophage Host Prediction Based on Annotated Genomic Features and Neural Networks.

Background: The experimental determination of a bacteriophage host is a laborious procedure. Thus, there is a pressing need for reliable computational predictions of bacteriophage hosts. Materials and Methods: We developed the program vHULK for phage host prediction based on 9504 phage genome features, which consider alignment significance scores between predicted proteins and a curated database of viral protein families. The features were fed to a neural network, and two models were trained to predict 77 host genera and 118 host species. Results: In controlled random test sets with 90% redundancy reduction in terms of protein similarity, vHULK obtained on average 83% precision and 79% recall at the genus level, and 71% precision and 67% recall at the species level. The performance of vHULK was compared against three other tools on a test data set with 2153 phage genomes. On this data set, vHULK achieved better performance at both the genus and the species levels than the other tools. Conclusions: Our results suggest that vHULK represents an advance on the state of art in phage host prediction.