Unraveling the complexity of betacoronaviruses in bats

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Timothée Poisot

Credit: Amélie Philibert, University of Montreal

While pandemics are of increasing concern on a global scale, an international study led by scientists at the University of Montreal opens new perspectives on the complex evolutionary dynamics of betacoronaviruses in bats, making it possible to better understand the risks posed by these pathogens.

Working with American and New Zealand researchers, they developed a detailed framework that designates geographic areas where these viruses and their hosts evolve differently and highlights densely populated areas where conditions for viral disease emergence are reunited.

Their findings highlight the great diversity in the distribution of viruses around the world. Certain regions, particularly Southeast Asia, sub-Saharan Africa and the Middle East, are emerging as hotspots for viral diversification.

Understanding regional differences

Different regions harbor groups of viruses that evolve differently with their hosts, scientists say, challenging the one-size-fits-all approach of previous models. For example, the authors characterize the neotropical region of the Americas as a potentially unique reservoir of merbecoviruses, indicating that the evolutionary pathways and risks of virus emergence may vary significantly between regions.

The research looks at the coevolutionary dynamics between some of the world’s 1,400 bat species and betacoronaviruses, providing insight into how these viruses and their hosts co-evolve over time and highlighting the mechanisms that could lead to the emergence of new potentially zoonotic viruses.

The complex relationship between host species and viruses shows the complexity of predicting which viruses may pose a future threat to humans, such as the SARS, MERS and COVID-19 outbreaks, scientists say. because the next threat could be a virus that has not yet emerged.

“The great novelty of our work is to clarify the role of evolutionary and ecological processes in the risk of emergence of new betacoronaviruses from bat populations,” said Norma Forero-Muñoz, who is doing her doctorate in machine learning. and data synthesis to predict viral spread events.

“In the past, it was thought that these processes made risk prediction very difficult,” she added. But by working on the basis of coevolutionary principles, we were able to highlight areas in which all the conditions are met for rapid diversification of potential new viruses.”

Working with certain limits

The researcher and her co-authors are aware of the limitations of their study, particularly regarding potential biases caused by uneven sampling and monitoring across different regions. This data inequality could lead to some regions being underrepresented in the study, such as India and West Africa.

The scientists nevertheless hope that their work can influence public health policies.

“By allowing us to better understand where and how bat betacoronaviruses evolve, the research helps us target potential hot spots for the emergence of new zoonoses,” mentioned Timothée Poisot. This is essential to guide surveillance and prevention efforts, particularly in high-risk regions where these new viruses will immediately come into contact with human populations.”