Tool identifies probable reservoir species for SARS-CoV-2

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APublic health experts continue to fight the spread of SARS-CoV-2 among humans as fears have grown that the virus will find other viable hosts. If humans transmit the virus to other species susceptible to infection, these animals could serve as a reservoir for the virus and possibly transmit mutated versions to humans, prolonging and potentially exacerbating the pandemic. The big question is which species are most likely to pose this risk.

To begin to answer this, researchers at the Cary Institute of Ecosystem Studies in New York City have developed a machine learning model that uses characteristics of an animal to predict the structure of its cell converting enzyme receptors. angiostatin 2 (ACE2) – the main molecular receptor for SARS-CoV-2 used to enter cells. Based on these structures, the team identified the species most likely to be at risk of contracting and spreading SARS-CoV-2, the team reports today (November 16) in Proceedings of the Royal Society B.

Among 5,400 animals, the new study highlights some pets, livestock and wildlife as potentially vulnerable to the virus. Some, such as cats and primates, were expected, especially given the documented infections. Others, like the scimitar-horned oryx, are more surprising, because despite the contact of animals with humans in zoos and breeding programs, no infections have yet been reported.

The authors say their findings can help prioritize which species to test and monitor, which experts say is badly needed. “It’s a great study,” says Suresh Kuchipudi, who is researching zoonotic viruses at Pennsylvania State University and was not involved in the work. “The recent discovery of a widespread SARS-CoV-2 infection in free-living white-tailed deer has highlighted the urgent need for expanded active surveillance of potential animal reservoirs. This tool could help identify animal species at risk to implement more targeted surveillance programs.

Barbara Han, lead author of the new study and a disease ecologist at the Cary Institute of Ecosystem Studies in New York City, and her team began this research over a year ago, long before news broke that no longer 80 percent of white tails from Iowa deer were infected with the virus last winter. By the time the team started, people had only found a handful of infections in the animals.

See “What species transmit COVID-19 to humans?” We are still not sure.

Since so many animals have ACE2 receptors, scientists have started looking at the amino acid sequences of ACE2 receptors from different animals and comparing them to those found in humans in hopes of predicting sensitivity. But protein sequences are not always a reliable indicator of a virus’s ability to bind to the receptor. Han and his team therefore decided to use the sequences to model three-dimensional receptor structures, which more accurately predict how tightly SARS-CoV-2 binds. “We just downloaded so many of these [sequences] as we could find in the public repositories available “to model their 3D shapes, explains Han.

Unfortunately, the ACE2 sequences have not been determined for most animals. Those available only allowed the team to predict the susceptibility of a few hundred animals, including 142 mammals.

To expand the projections to thousands of more species, Han and his team turned to artificial intelligence. They collected biological data on 5,400 species, from their size to what they eat. These features, Han says, can help predict the structure of the ACE2 receptor in animals that lack ACE2 sequence data.

“ACE2 is highly conserved in vertebrates because it is essential for controlling things like blood pressure,” says Han. Characteristics such as size and diet can hint at other aspects of an animal’s biology, such as if it is prone to high blood pressure – and this, in turn, hints at structure. of its animal ACE2. “We argued that the traits should be relatively predictive of whether the species has some sort of ACE2 that would strongly bind the virus,” Han explains.

Using the traits and the 362 known ACE2 sequences they found, she and her team created a machine learning model that estimated and ranked each animal’s likely susceptibility to contracting and spreading the virus. Primates consistently top the list, as have shrews, sloths, anteaters and pangolins.

Some predictions of the model have already come true: it suggested that the white-tailed deer would be particularly sensitive, for example. Others don’t. For example, the study identified pigs as a likely vulnerable species, but actual studies did not show that they were at high risk of becoming infected.

See “Our pets can harbor much more than the coronavirus”

Researchers highlight sensitive species most likely to encounter humans, to narrow down those that might be the most important to watch out for, as animals that rarely interact with humans are less likely to catch the disease or transmit it to humans even though their ACE2 receptors bind the virus. Their list of suggested monitoring priorities includes dogs and cats, Asian black bears, gray wolves, mountain gorillas, and 35 species of bats.

“Although the prediction results are not perfect, they provide a useful tool for reducing potentially sensitive species,” said Scott Kenney, a veterinary virologist at Ohio State University who was not involved in the study. He cautions, however, that “predictions must be recognized for what they are: predictions requiring further testing.”

“It worries me that pets with the top of the sensitivity categories may be unfairly slaughtered out of fear rather than fact,” Kenney adds.

Han says she shares those concerns, stressing the need for coordination between different types of researchers to determine the real risk. “There has to be an interaction between the people who do pure modeling and the people who do pure bench work and the people who do surveillance. There must be a feedback loop between the three of us. And I don’t think these returns are still common.

See “Predicting future zoonotic epidemics”


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