(From left to right). Mireia Coscollá Devís, Miguel Álvarez Herrera and Jordi Sevilla, at the I2SysBio headquarters, with a mural of a virus by the artist Mariano Collantes.

A research team from the Institute of Integrative Systems Biology (I2SysBio, a joint center of the University of Valencia and the Higher Council for Scientific Research) and other Spanish centers has created software that allows analyzing the evolution of SARS-CoV-2 within patients who suffer chronic infections from this virus, which can last many months. The tool, VIPERA (Viral Intra-Patient Evolution Reporting and Analysis), has been described in the journal Virus Evolution, and evaluates the evolution of serial samples during infection through the report it generates automatically. viruses within the same patient and study their adaptive changes associated with their transmissibility, pathogenicity or the administration of treatments. The Department of Clinical Microbiology of the Hospital Clínic of Barcelona, ​​the CIBER of Infectious Diseases (CIBERINFEC), the Institute of Biomedicine of València (IBV-CSIC) and the CIBER of Epidemiology and Public Health (CIBERESP) have also participated in the project.

“After validating the software with known data sets, we have successfully applied it to a new case, and we have managed to reveal interesting population dynamics and evidence of adaptive evolution," explains Mireia Coscollá, researcher at the same patient. I²SysBio.

The importance of this work lies in the fact that it analyzes chronic, more pathogenic or transmissible infections, as a potential source of new variants of SARS-CoV-2 of concern. “With the report generated, you can analyze how the virus evolves throughout the infection,” explains Miguel Álvarez Herrera, researcher at I²SysBio and first signatory of the article.

Until now there was no tool that integrated and standardized the analysis of evolution SARS-CoV-2 intrapatient. Using VIPERA is simple and generates an easily interpretable report. Additionally, it is open source and scalable. “By applying this tool, we have analyzed a chronic infection in depth, revealing the appearance of mutations associated with immune escape and variants of concern,” highlights Jordi Sevilla, co-first signatory of the article. NextGenerationEU/PRTR, the Ministry of Science and Innovation, the Generalitat Valenciana, the European Research Council, the Ministry of Industry and Competitiveness, and by the FEDER Funds. The computational work was carried out in Garnatxa, the high-performance computing (HPC) cluster of the Institute of Integrative Systems Biology (I²SysBio).

Article reference: https://doi.org/10.1093/ve/veae018