Generative design of bacteriophages with genome language models

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Generative design of bacteriophages with genome language modelsSamuel H. King https://orcid.org/0000-0002-1260-5045, Claudia L. Driscoll https://orcid.org/0000-0003-2285-6910, David B. Li https://orcid.org/0000-0002-8921-5168, Daniel Guo https://orcid.org/0009-0002-5347-7569, [...] , and Brian L. Hie https://orcid.org/0000-0003-3224-8142+3 authors Authors Info & Affiliations
Science
6 Aug 2026
Vol 393, Issue 6811
DOI: 10.1126/science.aec2657

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Editor’s summaryThe ability to design complex biological systems with artificial intelligence (AI) has the potential to transform biotechnology, but progress has largely been limited to the scale of individual genes and proteins, with whole-genome design remaining out of reach. King et al. used generative AI models trained on millions of natural genomes to design entire bacteriophages (see the Perspective by Inglesby and Hanke). Experimental tests yielded 16 functional genomes with diverse sequences, structures, and fitness profiles. A cocktail of the generated bacteriophages rapidly overcame bacteria that had evolved resistance to a natural bacteriophage. This work lays a foundation for AI-guided design of biological function at the whole-genome scale. —Di Jiang

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