Эрдэмтэд байгалийн жам ёсны хувьслын хэв шинжийг суралцсан хиймэл оюун ухааны загварыг ашиглан бактерийн эсрэг үйлчилгээтэй цоо шинэ бактериофагуудыг гарган авлаа.
Стэнфордын их сургууль болон Arc Institute-ийн судлаачид Evo 1 болон Evo 2 хэмээх хиймэл оюун ухааны загваруудыг ашиглан өмнө нь огт бүртгэгдээгүй, бактерийг устгах чадвартай 16 шинэ вирус бүтээжээ. Судлаачид байгаль дээрх амьтан, ургамал, микробуудын генетикийн олон сая дараалалд үндэслэн эдгээр вирусийн бүтцийг загварчилсан байна. Энэхүү туршилтад Phi X-174 хэмээх бактериофагийг жишиг болгон ашигласан ч хиймэл оюун ухааны үүсгэсэн вирусийн ДНХ-ийн дараалал нь байгалийн гаралтай вирусээс эрс ялгаатай байв.
Туршилтын хүрээнд хиймэл оюун ухаанаар загварчилсан 300 геномыг лабораторийн нөхцөлд синтезлэн гаргаж авч, улмаар E. coli бактерид нэвтрүүлэн туршсан байна. Үүнээс 16 геном нь бүрэн ажиллагаатай, харилцан адилгүй хэмжээтэй, шинэ зохицуулагч элементүүд бүхий бактериофаг болон хөгжжээ. Science сэтгүүлд нийтлэгдсэн энэхүү судалгаагаар хиймэл оюун ухаанаар бүтээсэн эдгээр вирус нь бактерийн эсэргүүцлийг хурдан хугацаанд даван туулж, халдварлах чадвартай болохыг нотолсон юм.
Энэхүү ололт нь антибиотикт тэсвэртэй бактерийн халдвартай тэмцэхэд хувь хүний онцлогт тохирсон эмчилгээний шинэ замыг нээж байна. Гэсэн хэдий ч судлаачид уг технологийг хорлонтой зорилгоор ашиглаж, улмаар шинэ өвчин үүсгэгч эсвэл биологийн зэвсэг бүтээх эрсдэл байгааг анхааруулж байна. Иймд энэхүү дэвшилтэт технологи нь молекул биоанагаах ухаанд томоохон боломж олгохын зэрэгцээ аюулгүй байдлын шинэ сорилтуудыг дагуулж байна.
Дэлгэрэнгүйг эх сурвалжаас харах
↓Эх сурвалжийг нээх ↓
For the first time, an artificial intelligence system has created a series of previously unknown viruses capable of infecting and eliminating certain types of bacteria. This breakthrough opens up new possibilities for combating bacterial resistance. However, it also raises concerns about the potential misuse of this technology to design biological weapons.
For several years now, scientists have been able to synthesize viruses from scratch; these are typically used to develop and evaluate antiviral drugs and vaccines, as well as to expand our understanding of how these microorganisms behave. However, the production of these viral genomes has primarily relied on replicating previously known pathogens or variants.
In contrast, a new study conducted by scientists at Stanford University and the Arc Institute succeeded in having an AI design simple, functional, and previously unseen viruses based on information contained in the genetic sequences of millions of animals, plants, microbes, bacteria, and viruses found in nature
The researchers worked with bacteriophages—microorganisms characterized by relatively small genomes, which are relatively easy to synthesize and manipulate under controlled conditions. These viruses infect only bacteria, making them a tool with enormous biotechnological potential and a promising alternative to antibiotics for combating resistant bacterial infections.
The creation of these entirely new viruses was based on Evo 1 and Evo 2, foundational AI models developed for computational biology applications. Both algorithms were trained on millions of genomes from all domains of life, with the goal of identifying and learning complex evolutionary patterns, including how genes are typically organized, which sequences are conserved, and the biological constraints that allow an organism to remain functional.
The experimental design used the bacteriophage Phi X-174—which is capable of infecting the bacterium Escherichia coli (E. coli)—as a reference. The goal was not to reproduce this virus, but rather to use it solely as a guide for the algorithms to generate thousands of completely new genomes with a genetic architecture compatible with infecting E. coli.
In other words, the viruses derived from the genomes created by the AI retained the functional organization essential for recognizing the bacterium, inserting their DNA, replicating it, producing new viral particles, and assembling them correctly. However, the specific DNA sequences differed considerably from those observed in naturally occurring bacteriophages.
16 New Viruses Created Using AI
The scientists then evaluated the AI-generated genomes to select those most likely to be functional, taking into account factors such as gene organization, the presence of regulatory elements, and other criteria inspired by the biology of the Phi X-174 bacteriophage.
This selection resulted in a sample of 300 genomes, which were artificially synthesized, molecule by molecule, in the laboratory. They were then introduced into E. coli bacteria to test whether they were capable of producing functional viruses.
Of the 300 synthesized genomes, only 16 gave rise to fully functional bacteriophages, featuring previously unpublished sequences, different genes, new regulatory elements, and even varying genome sizes. The behavior of these viruses also varied: While some infected the bacteria more quickly, others exhibited different abilities to replicate.
The research, published this week in the journal Science, also evaluated the ability of AI-generated bacteriophages to combat resistant bacteria. The experiment involved exposing a mixture of AI-designed phages and a mixture of natural phages similar to Phi X-174 to strains of E. coli that had already developed resistance to that virus.
The results showed that the AI-generated viruses were able to rapidly overcome bacterial resistance and establish infection. According to the authors, this finding demonstrates “a path toward artificial intelligence–generated phage therapies against rapidly evolving bacterial pathogens.”
The Two Sides of the Milestone
The discovery opens up new possibilities for tackling the growing problem of bacterial resistance. According to the researchers, this approach could facilitate the development of personalized treatments capable of evolving at nearly the same rate as the pathogens themselves.
Although this milestone represents a significant advance for molecular biomedicine, it also raises concerns about the potential malicious use of this technology to develop, for example, new diseases, highly toxic substances, or pathogens capable of triggering a new pandemic.
