Nailing viral evolution accurately

The new method, called ‘ReconbinHunt’, has been found to be accurate with its high specificity and sensitivity, confirming manual expert analyses.
Representative Image
Representative ImagePhoto | Shekhar Yadav, EPS

Science has now found a way to predict new pandemics through data analytics. Researchers from Department of Electronics, Information and Bioengineering of the Politecnico di Milano and the University of Milan have developed a new data-driven method which can identify recombinant SARS-CoV-2 genomes with one or two breakpoints with high accuracy and computational efficiency.

Taking the opportunity of the 2020 Covid-19 pandemic, researchers across the world had scouted several methods to detect recombinant genomes of SARS-CoV-2 virus to predict its future evolution. However, none was able to successfully accomplish it with high accuracy, which is much needed for the medical fraternity to be prepared in advance and minimise its effects.

However, the new method, called ‘ReconbinHunt’, has been found to be high accurate with its high specificity and sensitivity, confirming manual expert analyses. The method tracks the composition of two or more viral genomes to form a new genome — which is called ‘Recombination’ — a process that is known to be an efficient molecular mechanism for virus evolution and adaptation which can evade drugs.

This method has been developed under the PRIN PNRR 2022, SENSIBLE project (Small-data Early warNing System for viral pathogens In puBLic hEalth), which successfully identified recombinant viral genomes from a recent monkeypox epidemic. This was done with high accuracy, and suggested that the approach was robust.

The research team has said this approach can be applied to any epidemic or pandemic virus, representing an important tool to combat future pandemics. According to researchers, the study demonstrated how development of innovative computational methods allows experts to detect and predict the evolution of pathogens.

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