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AI designs functional bacteriophage genomes to overcome bacterial resistance
Researchers at Stanford University and the Arc Institute in California have used artificial intelligence to design complete bacteriophage genomes from scratch, producing functional viruses capable of infecting bacteria that had evolved resistance to a naturally occurring bacteriophage. The work demonstrates how generative AI systems can engineer entire biological systems rather than just individual genes or smaller genetic components. However, the research also highlights significant biosafety and biosecurity concerns surrounding the ability to design and synthesise complete genomes. Despite advances in DNA sequencing and synthesis making it more feasible to read and write entire genomes, designing a functional genome from scratch remains exceptionally challenging because genes, regulatory sequences and other genetic elements interact in complex ways. AI-guided genome design Samuel King, a PhD student in Bioengineering at Stanford University and a member of Brian Hie’s lab at the Arc Institute in Palo Alto developed, with several colleagues, an approach that combines the Evo family of genomic language models, including Evo 1, with computational biology and experimental screening. The researchers applied the approach to bacteriophages, viruses that infect bacteria and have potential applications as biotechnology tools and treatments for bacterial infections. Using the well-studied ΦX174 bacteriophage as a model, the team computationally...
