Background

The spread of multidrug-resistant bacteria (MDR), which do not respond to existing antibiotics, is a major health crisis facing modern medicine. Health authorities warn that annual deaths due to antibiotic resistance could reach 10 million by 2050. Conversely, the development of new antibiotics is stagnant due to massive costs and the rapid acquisition of resistance. In this deadlock, bacteriophages—viruses that selectively infect and kill specific bacteria—have emerged as an alternative. However, the academic consensus is that using natural bacteriophages as therapeutics has clear limitations. Natural phages have an excessively narrow host range and are easily neutralized by bacterial CRISPR-Cas defense systems. Some phages also cause side effects by remaining latent in the host genome and spreading toxins or resistance genes. Existing synthetic biology was limited to modifying parts of proteins. It was impossible for humans to individually reconstruct the entire regulatory network of a genome spanning tens of millions of base pairs (bp). This created a demand for technology capable of designing the entire viral life cycle from scratch.

Key Findings

The research team constructed a large-scale genomic language model to design bacteriophage genomes that target and destroy specific bacteria from scratch on a computer. This was achieved by the AI model deeply learning viral sequence data from hundreds of thousands of species, thereby autonomously mastering gene arrangement rules. Establishment of a genome generation system that comprehensively covers gene overlap structures and transcriptional regulatory factors at once. The resulting artificial phage genome has a size of approximately 42,000 base pairs, with sequence homology to natural phages being less than 60%. Despite being a completely new sequence, the endolysin gene, which decomposes capsid proteins and bacterial cell walls, is arranged according to precise rules. The researchers assembled the synthesized long-chain DNA in an in vitro expression system, injected it into bacterial hosts, and successfully resurrected actual virus particles with infectivity. The result of computer code manifesting as a physical virus. In vitro experiments showed that it completely lysed 28 out of 30 clinical strains of multidrug-resistant Pseudomonas aeruginosa. The target range was 2.6 times wider than that of natural phages. By optimizing the binding site, the frequency of bacterial resistance mutations was suppressed to one-tenth of the original level.

Significance and Prospects

This study is recognized as the first case in which a virus's entire genome was designed from scratch using artificial intelligence and expressed as a functional entity. It lays the technical groundwork for rapidly fabricating custom-designed viruses via computer commands. There is hope that the supply period for patient-specific phage therapy can be reduced from several months to within a few weeks. However, there are still significant challenges to overcome for its clinical adoption. The process cost of synthesizing and assembling long-chain DNA with tens of thousands of base pairs without error remains burdensome. It is difficult to rule out the risk that when artificial antigens are administered into the body, the patient's immune system recognizes them as foreign invaders and generates neutralizing antibodies. Proof of in vivo safety that does not harm beneficial microbiota must be established first. It is also urgent to establish a biosecurity verification system. The need for a software safety mechanism to block the creation of harmful viruses has been pointed out. Subsequent research is expected to focus on enhancing immune evasion capabilities and increasing DNA synthesis rates.