AI Tool Unify Maps Cell Evolution Across 700 Million Years
Researchers at KAUST created a tool that identifies shared biological functions in cells across distant species, improving human health research.
Key points
- Unify compares cell functions across 125 types from seven species separated by 700 million years.
- The tool groups genes by biological role rather than direct match, revealing hidden similarities.
- It predicts human cell responses based on animal data with higher accuracy than existing methods.
Scientists at the King Abdullah University of Science and Technology have introduced a new artificial intelligence tool designed to bridge the gap between different species. The system, named Unify, allows researchers to compare cell types across organisms that are separated by hundreds of millions of years of evolutionary history. This approach addresses a significant limitation in current biology, where direct genetic comparisons often fail to recognize deep functional similarities.
The primary goal of this innovation is to determine which findings from animal studies are most relevant to human health. By looking beyond simple gene matches, the tool helps identify shared biological roles, such as immune defense mechanisms, even when the underlying genetic code has diverged significantly. As reported by news-medical.net, this method offers a more accurate way to translate discoveries from model organisms like mice and fish into practical insights for human medicine.
Overcoming limitations of direct gene matching
Traditional methods for comparing cells rely heavily on finding one-to-one matches between genes. This technique works well for closely related species but becomes increasingly difficult as evolutionary distance grows. When species diverge over millions of years, their genes change, making it hard to spot that two different cells are performing the same essential job.
Unify solves this problem by focusing on biological function rather than genetic identity. Instead of acting like a dictionary that looks for exact word-for-word translations, the AI analyzes protein sequences and scientific descriptions of gene roles. It groups genes with similar functions into units called macrogenes, allowing the system to recognize shared biological meaning even when the specific genetic components no longer match directly.
Identifying shared immune defense tactics
The tool successfully reconstructed relationships among 125 cell types from seven different species. It distinguished between genes that are identical, those that have evolved new functions, and different genes that independently evolved to perform the same task. In one specific test, Unify identified shared defense strategies in immune cells across multiple species that would have been missed by conventional comparison methods.
The accuracy of the tool was further demonstrated in a prediction experiment involving human blood cells. By analyzing the response of mouse lymph-node immune cells to a specific signaling protein, the AI predicted how human cells would react. The results showed that Unify’s predictions were more accurate than existing methods, highlighting its potential to streamline the process of identifying which animal-based discoveries are most applicable to humans.
Expanding the scope of biological analysis
The research team is currently working to expand the capabilities of Unify. Future versions will incorporate information about gene regulation and the physical positions of cells within tissues. These additions aim to provide a more comprehensive view of the biological principles shared across life. By combining extensive biological knowledge with advanced AI, the tool can identify complex patterns at a scale that would take researchers far longer to discover through manual, gene-by-gene analysis.
