Published April 2, 2025 | Version v1

Data and code from: Engineering bacteriophages through deep mining of metagenomic motifs

  • 1. University of Wisconsin–Madison

Description

Bacteriophages can adapt to new hosts by altering sequence motifs through recombination or convergent evolution. Where such motifs exist and what fitness advantage they confer remains largely unknown. We report a new method, Metagenomic Sequence Informed Functional Scoring (Meta-SIFT), to discover 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 E. coli O121. Meta-SIFT is a powerful tool to unlock the potential encoded in phage metagenomes to engineer bacteriophages.

Notes

Funding provided by: National Institute of Health
ROR ID: https://ror.org/05h1kgg64
Award Number: R35GM143024

Funding provided by: National Institute of Allergy and Infectious Diseases
ROR ID: https://ror.org/043z4tv69
Award Number: R21AI156785

Funding provided by: University of Wisconsin–Madison
ROR ID: https://ror.org/01y2jtd41
Award Number:

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