OpenAI and Retro Biosciences reveal that their joint efforts in longevity research have led to an important breakthrough in cellular reprogramming. Early evidence suggests that they have achieved more efficient reprogramming of human cells into stem cells.
GPT-4b micro, a scaled-down version of OpenAI’s multimodal GPT-4o model that has been retrained for protein engineering. Retro Bio used this model to redesign two key transcription factors, which showed over a fifty-fold increase in expression of stem cell markers compared with wild-type controls in lab experiments. Furthermore, the research revealed that the optimised factors demonstrated improved DNA damage repair, a key indicator of cellular rejuvenation.
One of the company’s programs is focused on using cell transcriptomics to target multiple mechanisms of aging, prevent age-related diseases, and extend lifespan. This program builds on Professor Shinya Yamanaka’s Nobel Prize-winning discovery that an adult cell could be reverted back into an embryonic stem cell by exposing it to a key group of protein transcription factors, now called the Yamanaka factors.
The Yamanaka factors – OCT4, SOX2, KLF4, and MYC are critical to the reprogramming process but are inadequate in their natural form, converting fewer than one in a thousand cells. So Retro Bio used GPT-4b micro to generate RetroSOX and RetroKLF variants of SOX2 and KLF4.
OpenAI reported that over 30% of the AI-designed SOX2 variants outperformed the natural protein in initial screens, while approximately half of the KLF4 variants showed superior activity. When the RetroSOX and RetroKLF factors were combined, they accelerated the appearance of key pluripotency markers in human fibroblasts. Furthermore, colonies derived from these cells also showed strong alkaline phosphatase staining, another hallmark of successful reprogramming.
This AI-driven advance indicates significant progress in cellular rejuvenation technology. The newly designed proteins could improve research and treatment options for tissue engineering, age-related diseases, and longevity studies.
