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. 2023 Sep 22;13(1):15782.
doi: 10.1038/s41598-023-42348-y.

An Innovative AI-based primer design tool for precise and accurate detection of SARS-CoV-2 variants of concern

Carmina Angelica Perez-Romero #  1 , Lucero Mendoza-Maldonado #  2 , Alberto Tonda  3 , Etienne Coz  4 , Patrick Tabeling  4 , Jessica Vanhomwegen  5 , John MacSharry  6 , Joanna Szafran  6 , Lucina Bobadilla-Morales  2 , Alfredo Corona-Rivera  2 , Eric Claassen  7 , Johan Garssen  8   9 , Aletta D Kraneveld  8 , Alejandro Lopez-Rincon  10   11
Affiliations

An Innovative AI-based primer design tool for precise and accurate detection of SARS-CoV-2 variants of concern

Carmina Angelica Perez-Romero et al. Sci Rep. .

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.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
GeneFinder COVID-19 Plus RealAmp standard viral load curve (Left). UtrechtU-ORF3a standard viral load curve (Right).
Figure 2
Figure 2
Comparison between non-specific primer set IP2 and IP4 and our designed primer set B.1.1.7-1 for B.1.1.7 variant and others.
Figure 3
Figure 3
Summary of the procedure to create, validate and test a primer set designed using evolutionary algorithms.
Figure 4
Figure 4
Summary of the EA where we expect to find a target 21-bps sequence in position p and in sample k to be used as a forward primer.
Figure 5
Figure 5
(Left) Cost function in 20 runs of the EA for 100 generations to find a forward primer in the main lineage. (Right) Percentage of appearance of the primer set in the 2,107,300 SARS-CoV-2 sequences.
Figure 6
Figure 6
(Left) Cost function in 10 runs of the EA for 100 generations to find a forward primer in the the variant B.1.1.7. (Right) Percentage of appearance of the primer set in the 2,107,300 SARS-CoV-2 sequences.
Figure 7
Figure 7
(Left) Cost function in 10 runs of the EA for 100 generations to find a forward primer in the the variant B.1.1.529. (Right) Percentage of appearance of the primer set in the 2,107,300 SARS-CoV-2 sequences.
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