Genomic mapping of wastewater bacteriophage may predict potential bacterial pathogens infecting the community.

Most existing wastewater surveillance studies that focus on viruses have identified a large fraction of bacteriophages. Identifying bacteria by considering bacteriophage-host interactions is a novel method for detecting bacterial pathogens circulating in a community, using wastewater surveillance. This study aims to identify human-related bacterial pathogens in municipal wastewater collected in metro Detroit, using high-throughput sequencing and bioinformatics. Untreated municipal wastewater samples were collected on August 11, 2020, and bacteriophages were concentrated using the VIRus ADsorption-ELution (VIRADEL) method. Bacteriophage-related contigs in samples ranged from 15.53 % to 18.91 %, with 2477 classified and 8853 unclassified contigs. Most identified bacteriophages were from Caudoviricetes and Malgrandaviricetes classes belonging to 19 families. Hosts of bacteriophages were predicted with the PhaBOX (CHERRY) tool. The results indicated that out of the 2477 classified phages, 2373 were associated with known bacterial hosts. Also, out of 8853 unclassified bacteriophages, 8421 were associated with known bacterial hosts, and the remaining 432 were with unknown bacterial hosts. Among all bacteriophage-associated hosts, 399 were identified as pathogenic bacteria at the species level. Approximately, 85 % of the identified pathogenic bacteria are reported to be associated with human diseases. Genome quality assessments showed that 15 bacteriophages had nearly complete genomes, which were further analyzed to understand bacteriophage-bacteria interactions in wastewater. Identified hosts of these complete-genome phages included human pathogens such as Salmonella enterica, Bacillus cereus, Achromobacter xylosoxidans, and Escherichia coli. The S. enterica bacteriophage (k141_1005294) genomic map was annotated, and responsible open reading frames (ORFs) were characterized to illustrate bacteriophage behavior during infection of pathogenic bacteria in untreated wastewater. To the best of our knowledge, this is the first attempt to characterize human bacterial pathogens in wastewater through bacteriophage-pathogen interactions. Novel bioinformatic approaches enhance pathogen detection and improve the understanding of community wastewater microbiomes.