AI-generated bacteriophage genomes that replicate and kill bacteria
AI-generated bacteriophage genomes that replicate and kill bacteria is graded author verified on whataifound.org, with the AI's role graded ai-led.
Genome language models wrote complete ΦX174-like bacteriophage genomes from scratch; of 285 designs that could be built, 16 produced viable infectious phages, several with faster lysis than the natural virus.
- Verification
- Author verified
- Autonomy
- AI-led
- Lab
- Arc Institute / Stanford University
- Model
- Evo 1 and Evo 2
- Field
- Biology
- Date
- 2025-09-17
- Human collaborators
- Samuel King, Brian Hie
What was found
The team fine-tuned Evo 1 and Evo 2 on a cleaned set of nearly 15,000 Microviridae genomes, generated 302 candidate genomes with ΦX174-like architecture, chemically synthesised the 285 that could be assembled, and tested them for plaque formation in E. coli. Sixteen were viable, with substantial sequence divergence from the template. Several generated phages outcompeted wild-type ΦX174 in growth and lysis kinetics, and a cocktail of them cleared three ΦX174-resistant E. coli strains. The authors frame it as the first generative design of a complete functional genome.
Novelty check
Synthetic phage genomes assembled from natural sequence date to Venter's 2003 ΦX174 reconstruction, and generative design of individual proteins was well established. Generating an entire genome that yields a working organism had not been demonstrated. The claim is bounded to bacteriophages, which infect bacteria only.
Caveats
A bioRxiv preprint, not peer reviewed at the time of this entry, with no independent replication logged. The designs are variants within one small, exceptionally well-characterised template (ΦX174, 5,386 bp), not free-form genomes, and 269 of the 285 that were built did not work. On biosafety, the authors excluded eukaryotic and human-infecting viruses from training and confine the work to phages; the result has nonetheless become a reference point in biosecurity debate, which is context this entry records rather than adjudicates.
Sources
How this is graded
whataifound.org grades every entry on two axes: verification (how solid the result is, from a machine-checked proof down to refuted) and autonomy (how much the AI did versus its human collaborators). This finding is author verified and ai-led. Full definitions are in the methodology.
Cite this entry
whataifound.org (2025). AI-generated bacteriophage genomes that replicate and kill bacteria. whataifound.org: A Registry of AI Scientific and Mathematical Discoveries. https://whataifound.org/finding/2025-09-17-evo-phage-genomes