A new study published in Cell this Wednesday by a research team from Sun Yat-sen University's School of Medicine, in collaboration with Alibaba Cloud, reports the discovery of over 160,000 putative RNA virus species and 180 RNA virus supergroups, significantly expanding the knowledge of the diversity within the RNA virosphere.
The study published in Cell (Screenshot of the Cell Press)
The research aligns with Guangdong's latest action plan to drive advancements in the bioengineering and pharmaceutical industries. As the province plans to provide more funding and policy incentives for those emerging sectors, the integration of artificial intelligence with biology and medicine—central to this research—has become a key area.
The team used an AI algorithm, LucaProt, to analyze 10,487 metatranscriptomes generated from diverse global ecosystems. This approach identified over 510,000 viral genomes, indicating the potential existence of more than 160,000 novel RNA virus species and 180 RNA virus supergroups. Among these, 23 supergroups, usually referred to as "viral dark matter," were previously undetectable with the current tools for metagenomic identification.
Graphical abstract of the study (Photo provided by Sun Yat-sen University)
"AI algorithms can discover viruses that we previously overlooked or were completely unaware of, which is crucial for disease prevention and the rapid identification of new pathogens," said Professor Mang Shi, leader of the research team at Sun Yat-sen University. "Especially during outbreaks, AI can help scientists quickly pinpoint potential pathogens."
The study is expected to reshape current understanding of the global virosphere, as it also reports the discovery of the longest RNA virus genomes ever recorded—spanning up to 47,250 nucleotides—suggesting an exceptionally complex genomic structure.
Meanwhile, RNA viruses are found even in the most extreme environments, including Antarctic sediment, deep-sea hydrothermal vents, and salt flats. These findings suggest RNA viruses are far more widespread than previously believed.
"The current virus classification system is struggling to accommodate these distantly related new viruses. In the future, we may see major adjustments at the phylum and class levels," said Professor Shi.
"The diversity of viruses is far greater than we can imagine, and what we've observed so far is just the tip of the iceberg," he added, expressing the hope to see more cross-disciplinary collaboration, where cloud computing and AI can be harnessed to tackle challenges in life science.
Reporter | Chen Siyuan
Editor | Nan, Will, James
