Machine learning identifies mammal species with the potential to spread SARS-CoV-2

Back and forth transmission of SARS-CoV-2, the virus that causes COVID-19, between humans and other mammals increases the risk of new variants and threatens efforts to control the disease.

A U.S. National Science Foundation-funded study, published in Proceedings of the Royal Society B, used a novel modelling approach to predict the capacity of 5,400 mammal species to spread the virus, extending predictive capacity by an order of magnitude. Of the high-risk species flagged, many live near people and in COVID-19 hotspots. 

A major bottleneck to predicting high-risk mammal species is limited data on ACE2, the cell receptor that SARS-CoV-2 binds to in animals. ACE2 allows SARS-CoV-2 to enter host cells and is found in all major vertebrate groups. It is likely that all vertebrates have ACE2 receptors, but sequences were only available for 326 species. 

Read more…