AI-driven bacteriophage development targets resistant E. coli strains
Researchers from Stanford and the Broad Institute utilized AI to design novel bacteriophages capable of targeting antibiotic-resistant E. coli strains, showing promise for future therapies.
A group of scientists from Stanford University and the Broad Institute have developed bacteriophages to fight antimicrobial-resistant Escherichia coli strains using artificial intelligence (AI). Favorable findings from their study are reported in a CIDRAP article by Mary Van Beusekom, MS and published in Science.
The researchers utilized the ΦX174 bacteriophage and combined the genomic language models (Evo 1 and Evo 2) that they had built with computational biology and created 16 complete bacteriophages with substantially different genomes.
Certain phages developed by the researchers acted similarly to naturally occurring relatives, while others conquered two strains of E coli that were resistant to ΦX174-like phages. While the findings could lead to more resilient phage therapies for other diseases, two Johns Hopkins University scientists caution that biosafety and biosecurity should be considered.