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Published on: 11/09/2020 20:19
The response to Sars-CoV-2 infection varies from person to person, with some patients who develop more severe symptoms than others. The reasons for the differences, observed in the severity of the disease Covid-19, are mostly still unknown. In an article published by ‘Cell Systems’, two researchers from the Complexity and Biosystems Center of the University of Milan, Caterina La Porta and Stefano Zapperi, demonstrated that the immune recognition of Sars-CoV2 differs a lot from person to person and could therefore explain why one can respond differently to the virus.
When a cell is infected with a virus, it exposes fragments of the viral proteins, or peptides, on its surface, in association with Hla (human leukocyte antigen) molecules. There are two classes of Hla molecules: class I and class II. Class I Hla molecules are exposed on the surface of all nucleated cells and trigger the activation of T cells which then destroy the infected cell. Hla molecules differ from individual to individual, as does their ability to bind viral fragments and expose them to the surface of the cell.
In their work, the authors used artificial neural networks to analyze the binding of Sars-CoV-2 peptides to class I Hla molecules. In this way, they identified two series of Hla molecules present in specific human populations: the first series shows a weak binding to the peptides of the virus, while the latter shows a strong binding and a strong propensity for T cells.
Stefano Zapperi, professor of the Physics department, explains that “artificial neural networks are able to analyze huge amounts of experimental data accumulated over the years on Hla binding affinities to produce new predictions for Sars-CoV-2”.
“Our work offers useful support for identifying individual susceptibility to Covid-19 and illustrates a mechanism underlying the variations in the immune response to Sars-CoV-2”, continues Caterina La Porta, Professor of General Pathology at the Department of Sciences and environmental policies, which concludes: “This work opens interesting perspectives for a pre-screening of the population to develop preventive strategies”.
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