NIH Distinguishes CCP Virus From Other Coronaviruses: Key to Preventing Future Outbreaks

A computer image created by Nexu Science Communication together with Trinity College in Dublin, shows a model structurally representative of a betacoronavirus which is the type of virus linked to COVID-19, better known as the coronavirus linked to the Wuhan outbreak, shared with Reuters on Feb. 18, 2020. (NEXU Science Communication/Reuters)

Researchers at the National Institute of Health (NIH) have identified the key genomic feature of the CCP virus that differentiates it from other coronavirus causing less severe diseases.

This will help scientists to detect animal coronaviruses that can cause diseases in humans and prevent future outbreaks.

“In this work, we set out to identify genomic features unique to those coronaviruses that cause severe disease in humans,” said Dr. Eugene Koonin, the lead author of the study in a statement.

The human coronaviruses were first identified in the mid-1960s and there are seven types of them that can infect humans, according to the CDC. These include the coronaviruses that cause Middle East Respiratory Syndrome (MERS), severe acute respiratory syndrome (SARS), and COVID-19.

“Sometimes coronaviruses that infect animals can evolve and make people sick and become a new human coronavirus,” noted CDC.

The research findings published in Proceedings of the National Academy of Sciences noted that CCP virus and MERS-CoV have bat reservoirs and were transmitted to humans through civets and camels.

“Similarly, the closest known relative of SARS-CoV-2 is a bat coronavirus, but the specific route of transmission from bats to humans remains unclear,” said the research paper adding that the findings will help in future interventions.

Koonin said his team of researchers has identified several features that differentiate the CCP virus from less virulent coronaviruses and this could help study pathogenicity in humans.

“The actual demonstration of the relevance of these findings will come from direct experiments that are currently getting underway,” he said.

The research was done using integrated comparative genomics and machine learning techniques and the features identified correlated to the high fatality rate of these coronaviruses and their transmission from animal to human hosts.

“This innovative research is critical to improve researchers’ understanding of SARS-CoV-2 and aid in the response to COVID-19,” said NLM Director Patricia Flatley Brennan.