Science：首个AI设计的噬菌体病毒诞生，能够存活、感染宿主，还能对抗抗生素耐药难题

TL;DR - Arc Institute/Stanford's Brian Hie team published in Science (Aug 6, 2026; bioRxiv Sept 2025) the first generative design of complete bacteriophage genomes using genome language models (Evo 1/Evo 2), producing viable phages that infect E. coli. It marks a shift from single-gene/protein design to whole-genome-scale generative biology.

• Used ΦX174 (~5.4 kb, 11 genes, ≥7 regulatory elements, 2 recognition sequences) as the design template; thousands of AI-generated genomes were computationally evaluated, ~300 chemically synthesized, and 16 viable phages recovered.
• Generated phages differ from all known natural phages: de novo mutations, differentiated genes/regulatory elements, and varied genome lengths; cryo-EM showed one used a DNA-packaging protein from an evolutionarily distant phage in its capsid.
• A cocktail of generated phages rapidly overcame E. coli strains resistant to natural ΦX174, whereas a natural ΦX174-like phage cocktail did not — suggesting a route to adaptive phage therapy against antibiotic-resistant/fast-evolving pathogens.
• Demonstrates genome language models capture evolutionary constraints in DNA with enough fidelity for genome-scale design, laying groundwork for larger, more complex synthetic genomes.