SARS-CoV2 and immune recognition
The response to SARS-CoV-2 infection differs from person to person, with some patients developing more severe symptoms than others. The reasons for the observed differences in the severity of the Covid-19 disease are mostly still unknown. In a paper published by Cell Systems, two researchers from the Center for Complexity and Biosystems of the University of Milan, Caterina La Porta and Stefano Zapperi, showed that the immune recognition of SARS-CoV-2 differs widely among individuals and could thus explain why we may respond differently to the virus.
When a cell is infected by a virus, it exposes on its surface fragments of the viral proteins, or peptides, in association with HLA molecules. There are two classes of HLA molecules: class I and class II. HLA class I molecules are exposed on the surface of all the nucleated cells and trigger the activation of T cells which then destroy the infected cell. HLA molecules differ from individual to individual and so does their ability to bind viral fragments and expose them on the cell surface. In their work, the authors used artificial neural networks to analyze the binding of SARS-CoV-2 peptides with HLA class I molecules. In this way, they identified two sets of HLA molecules present in specific human populations: the first set displays weak binding with SARS-Cov-2 peptides, while the second shows strong binding and T cell propensity. Stefano Zapperi, professor at the Department of Physics, explains “ artificial neural networks are able to analyze massive amounts of experimental data accumulated over the years on HLA binding affinities to produce new predictions for SARSCoV-2.” “Our work offers a useful support to identify the individual susceptibility to COVID-19 and illustrates a mechanism underlying variations in the immune response to SARS-CoV-2” continues Caterina La Porta, professor of General Pathology at the Department of Environmental Science, that then concludes, ”this paper opens interesting perspectives for a pre-screening of the population to develop preventive strategies”.
The paper is published in Cell Systems.
Link to the paper: