Study shows AI can design bacteriophages with potential to overcome bacterial resistance
Stanford University and Arc Institute researchers have successfully used AI models to design functional bacteriophage genomes. This breakthrough could lead to new treatments for drug-resistant bacterial infections by creating viruses that overcome antibiotic resistance.
Why it matters
AI-designed synthetic biology offers a promising new frontier in medicine to combat the growing global health crisis of antibiotic-resistant superbugs.
Scientists from Stanford University and the Arc Institute have used artificial intelligence to design complete genomes of bacteriophages viruses that infect bacteria, in a study that could advance research into alternatives to antibiotics for treating drug-resistant infections.
Published in Science , the study is among the first demonstrations that AI can design entire viral genomes rather than individual genes or proteins. The researchers generated thousands of potential bacteriophage genomes, chemically synthesised nearly 300 and tested them in the laboratory. Sixteen produced functional viruses capable of infecting Escherichia coli .
The researchers used genome language models called Evo 1 and Evo 2, which learn patterns in DNA sequences in a manner similar to how language models learn patterns in human language. Trained on millions of genomes, the models can capture patterns of genome organisation and constraints shaped by evolution.
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