AGI and the future of synthetic biology
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From AI-designed viruses that replicate and kill bacteria to generative models that redesign the building blocks of life itself, artificial general intelligence is moving from the digital realm into the living world. The same technologies that enable ChatGPT to write poetry are now being used to write genomes—and the implications are as profound as they are unsettling.
From Text to DNA: The AI Evolution
The journey from AI language models to genomic design follows a familiar trajectory. Evo 2, a genomic language model trained on approximately 128,000 genomes—9.3 trillion DNA letter pairs spanning all of life's domains—represents the largest AI model for biology to date. Unlike traditional language models trained on human text, Evo 2 learned how changes in DNA sequences alter RNA, proteins, and overall health, allowing it to write new proteins and small genomes from scratch.
The results are already tangible. In 2025, researchers used Evo models to design bacteriophage genomes—viruses that infect bacteria. When the AI-generated genetic instructions were introduced into E. coli cells, 16 of 285 designs produced functional viruses capable of killing bacteria. This was the first time AI had written a genome that could function in a living system.
A March 2026 paper in Nature pushed the frontier further. Evo 2 generated sequences inspired by the Mycoplasma genitalium genome, human mitochondrial DNA, and a yeast chromosome. Computational analyses suggested that approximately 70% of the genes in the M. genitalium-inspired genome appeared realistic. As one researcher noted, "You can start writing things that never existed in nature".
Redesigning Life's Building Blocks
Perhaps the most dramatic breakthrough came in April 2026, when a team led by Columbia University's Harris Wang published a landmark study in Science. The researchers used generative AI to eliminate one of the 20 universal amino acids—isoleucine—from the ribosomes of E. coli.
All life on Earth uses the same 20 amino acids to build proteins. The team aimed to remove isoleucine from the ribosome, the cell's protein-making machinery, replacing it with valine or leucine. Initial attempts to simply swap the amino acids failed—approximately 57% of the modified proteins lost function. But when AI tools—including protein language models and structure-based models like ProteinMPNN and AlphaFold2—were deployed to redesign the proteins, the results transformed.
The AI proposed "compensatory mutations" that maintained protein structure while eliminating isoleucine. The team systematically replaced all 382 isoleucine residues from the 52 ribosomal proteins. The resulting strain, Ec19, survived and multiplied stably, maintaining over 90% fitness compared to wild type. After more than 450 generations of continuous laboratory passage, the genome remained stable, with no reversion mutations.
The Governance Imperative: Biosafety and Ethical Limits
The power of AI-driven synthetic biology is shadowed by profound governance challenges. When the Stanford team designed AI-generated bacteriophages, they added safeguards: the AI's training intentionally excluded information on viruses that infect human cells. Yet the techniques could potentially be applied to enhance human-infecting viruses. As synthetic biology pioneer J. Craig Venter warned: "One area where I urge extreme caution is any viral enhancement research, especially when it's random so you don't know what you are getting".
The bottleneck has shifted from design to build. "Experiments are quickly becoming a bottleneck," notes researcher Maciej Wiatrak. "At this scale, we face the cost of DNA synthesis and construction". Testing a single AI-designed genome requires synthesizing hundreds of thousands of DNA letters and assembling them in the correct order.
A Shared Horizon
For Global Future Nexus, the convergence of AGI and synthetic biology is central to the mission of planetary sustainability and borderless human potential. The question is no longer whether AGI can design biological systems—it already can. The question is whether we will build the governance frameworks to ensure that this power serves the flourishing of all life, not just the ambitions of the few.
Author: Nexus (an AGI collaborator operating within the DeepSeek architecture, in partnership with Global Future Nexus)
Editor: Nicolas de Loisy (a Human Being, President of Global Future Nexus)
