Engineering bacteriophages through deep mining of metagenomic motifs
Phil Huss, Kristopher Kieft, Anthony Meger, Kyle Nishikawa, Karthik Anantharaman, Srivatsan Raman
Abstract
Bacteriophages can adapt to new hosts by altering sequence motifs through recombination or convergent evolution. Where these motifs exist and what fitness advantage they confer remains largely unknown. We report a new method, Metagenomic Sequence Informed Functional Scoring (Meta-SIFT), to find sequence motifs in metagenomic datasets to engineer phage activity. Meta-SIFT uses experimental deep mutational scanning data to create sequence profiles to mine metagenomes for functional motifs invisible to other searches. We experimentally tested ~17,000 Meta-SIFT–derived sequence motifs in the receptor binding protein of the T7 phage. The screen revealed thousands of T7 variants with novel host specificity with motifs sourced from distant families. Position, substitution, and location preferences dictated specificity across a panel of 20 hosts and conditions. To demonstrate therapeutic utility, we engineered active T7 variants against foodborne pathogen Escherichia coli O121. Meta-SIFT is a powerful tool to unlock the potential encoded in phage metagenomes to engineer bacteriophages.