Researchers have developed a powerful tool that can detect variants of SARS-CoV-2 with high transmission potential before they become widespread. This approach could significantly support public health efforts to control outbreaks and help identify new variants that need closer monitoring.
By analyzing millions of viral genome sequences from around the world, a team of scientists, led by the Peter Doherty Institute for Infection and Immunity (Doherty Institute) and the University of Pittsburgh, uncovered the specific mutations that give SARS-CoV-2 a 'turbo boost' in its ability to spread.
"Among thousands of SARS-CoV-2 mutations, we identified a small number that increase the virus' ability to spread," said Professor Matthew McKay, a Laboratory Head at the Doherty Institute and ARC Future Fellow in the Department of Electrical and Electronic Engineering at the University of Melbourne, and co-lead author of the study published in Nature Communications.
Many of these key mutations are in the spike protein, which helps the virus enter human cells and is the target of antibodies. But the team also found important mutations in other, less-studied parts of the virus that enhance its ability to bind to human cells, evade the immune system or alter protein structure.
Our approach is mathematically simple yet highly effective. Unlike previous techniques, our model leverages genomic surveillance data to pinpoint the exact mutations driving the spread of certain variants, even when they appear in just a small fraction of cases."
Professor Matthew McKay, a Laboratory Head at the Doherty Institute
While this new model focuses exclusively on SARS-CoV-2, the researchers believe it can be adapted to study the transmission of other pathogens, such as influenza.
"This is one of the first practical tools to systematically quantify how individual mutations impact viral transmission on a global scale," said Associate Professor John Barton from the University of Pittsburgh, co-lead author of the study.
"Our method is like a magnifying glass for viral evolution, helping public health systems spot and monitor highly transmissible variants before they become widespread.
"Not only can we track SARS-CoV-2 more effectively, but our method can also be adapted to study the evolution of other pathogens, helping us stay ahead of future outbreaks. It's a powerful tool for global efforts to tackle emerging diseases."
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Journal reference:
Lee, B., et al. (2025). Inferring effects of mutations on SARS-CoV-2 transmission from genomic surveillance data. Nature Communications. doi.org/10.1038/s41467-024-55593-0.