Related Experiment Video
Updated: May 11, 2025

Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins
Published on: June 11, 2015
Engineering bacteriophages through deep mining of metagenomic motifs
Phil Huss1,2,3, Kristopher Kieft2,3, Anthony Meger1
1Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA.
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.
More Related Videos
09:34A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
Published on: September 25, 2021
11:23Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
Published on: December 22, 2014