Tracing mother-infant transmission of bacteriophages by means of a novel analytical tool for shotgun metagenomic datasets: METAnnotatorX

Background: Despite the relevance of viral populations, our knowledge of (bacterio) phage populations, i.e., the phageome, suffers from the absence of a "gold standard" protocol for viral DNA extraction with associated in silico sequence processing analyses. To overcome this apparent hiatus, we present here a comprehensive performance evaluation of various protocols and propose an optimized pipeline that covers DNA extraction, sequencing, and bioinformatic analysis of phageome data. Results: Five widely used protocols for viral DNA extraction from fecal samples were tested for their performance in removal of non-viral DNA. Moreover, we developed a novel bioinformatic platform, METAnnotatorX, for metagenomic dataset analysis. This in silico tool facilitates a range of read- and assembly-based analyses, including taxonomic profiling using an iterative multi-database pipeline, classification of contigs at genus and species level, as well as functional characterizations of reads and assembled data. Performances of METAnnotatorX were assessed through investigation of seven mother-newborn pairs, leading to the identification of shared phage genotypes, of which two were genomically decoded and characterized. METAnnotatorX was furthermore employed to evaluate a protocol for the identification of contaminant non-viral DNA in sequenced datasets and was exploited to determine the amount of metagenomic data needed for robust evaluation of human adult-derived (fecal) phageomes. Conclusions: Results obtained in this study demonstrate that a comprehensive pipeline for analysis of phageomes will be pivotal for future explorations of the ecology of phages in the gut environment as well as for understanding their impact on the physiology and bacterial community kinetics as players of dysbiosis and homeostasis in the gut microbiota.