An Innovative AI-based primer design tool for precise and accurate detection of SARS-CoV-2 variants of concern
Publication date
2023-12
Authors
Perez-Romero, Carmina Angelica
Mendoza-Maldonado, Lucero
Tonda, Alberto
Coz, Etienne
Tabeling, Patrick
Vanhomwegen, Jessica
MacSharry, John
Szafran, Joanna
Bobadilla-Morales, Lucina
Corona-Rivera, Alfredo
Editors
Advisors
Supervisors
Document Type
Article
Metadata
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License
cc_by
Abstract
As the COVID-19 pandemic winds down, it leaves behind the serious concern that future, even more disruptive pandemics may eventually surface. One of the crucial steps in handling the SARS-CoV-2 pandemic was being able to detect the presence of the virus in an accurate and timely manner, to then develop policies counteracting the spread. Nevertheless, as the pandemic evolved, new variants with potentially dangerous mutations appeared. Faced by these developments, it becomes clear that there is a need for fast and reliable techniques to create highly specific molecular tests, able to uniquely identify VOCs. Using an automated pipeline built around evolutionary algorithms, we designed primer sets for SARS-CoV-2 (main lineage) and for VOC, B.1.1.7 (Alpha) and B.1.1.529 (Omicron). Starting from sequences openly available in the GISAID repository, our pipeline was able to deliver the primer sets for the main lineage and each variant in a matter of hours. Preliminary in-silico validation showed that the sequences in the primer sets featured high accuracy. A pilot test in a laboratory setting confirmed the results: the developed primers were favorably compared against existing commercial versions for the main lineage, and the specific versions for the VOCs B.1.1.7 and B.1.1.529 were clinically tested successfully.
Keywords
Artificial Intelligence, COVID-19/diagnosis, Humans, Pandemics, SARS-CoV-2/genetics, Journal Article
Citation
Perez-Romero, C A, Mendoza-Maldonado, L, Tonda, A, Coz, E, Tabeling, P, Vanhomwegen, J, MacSharry, J, Szafran, J, Bobadilla-Morales, L, Corona-Rivera, A, Claassen, E, Garssen, J, Kraneveld, A D & Lopez-Rincon, A 2023, 'An Innovative AI-based primer design tool for precise and accurate detection of SARS-CoV-2 variants of concern', Scientific Reports, vol. 13, no. 1, 15782. https://doi.org/10.1038/s41598-023-42348-y