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Article

Discriminatory Weight of SNPs in Spike SARS-CoV-2 Variants: A Technically Rapid, Unambiguous, and Bioinformatically Validated Laboratory Approach

by
Nicolò Musso
1,†,
Paolo Giuseppe Bonacci
1,†,
Dafne Bongiorno
1,
Stefano Stracquadanio
1,
Dalida Angela Bivona
1,
Concetta Ilenia Palermo
2,
Guido Scalia
2,
Marco Fichera
3,4 and
Stefania Stefani
1,*
1
Department of Biomedical and Biotechnological Sciences (BIOMETEC), Medical Molecular Microbiology and Antibiotic Resistance Laboratory (MMAR Lab), University of Catania, 95125 Catania, Italy
2
4U.O.C. Laboratory Analysis Unit, A.O.U. ‘Policlinico-Vittorio Emanuele’, University of Catania, 95125 Catania, Italy
3
Department of Biomedical and Biotechnological Sciences, Medical Genetics, University of Catania, 95125 Catania, Italy
4
Oasi Research Institute-IRCCS, 94018 Troina, EN, Italy
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Viruses 2022, 14(1), 123; https://doi.org/10.3390/v14010123
Submission received: 13 December 2021 / Revised: 7 January 2022 / Accepted: 8 January 2022 / Published: 11 January 2022
(This article belongs to the Special Issue State-of-the-Art SARS-CoV-2 Research in Italy)
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Abstract

Background: The SARS-CoV-2 virus has assumed considerable importance during the COVID-19 pandemic. Its mutation rate is high, involving the spike (S) gene and thus there has been a rapid spread of new variants. Herein, we describe a rapid, easy, adaptable, and affordable workflow to uniquely identify all currently known variants through as few analyses. Our method only requires two conventional PCRs of the S gene and two Sanger sequencing reactions, and possibly another PCR/sequencing assay on a N gene portion to identify the B.1.160 lineage. Methods: We selected an S gene 1312 bp portion containing a set of SNPs useful for discriminating all variants. Mathematical, statistical, and bioinformatic analyses demonstrated that our choice allowed us to identify all variants even without looking for all related mutations, as some of them are shared by different variants (e.g., N501Y is found in the Alpha, Beta, and Gamma variants) whereas others, that are more informative, are unique (e.g., A57 distinctive to the Alpha variant). Results: A “weight” could be assigned to each mutation that may be present in the selected portion of the S gene. The method’s robustness was confirmed by analyzing 80 SARS-CoV-2-positive samples. Conclusions: Our workflow identified the variants without the need for whole-genome sequencing and with greater reliability than with commercial kits.
Keywords: COVID-19; SARS-CoV-2; COVID-19 variants; Sanger sequencing; bioinformatic validation COVID-19; SARS-CoV-2; COVID-19 variants; Sanger sequencing; bioinformatic validation

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MDPI and ACS Style

Musso, N.; Bonacci, P.G.; Bongiorno, D.; Stracquadanio, S.; Bivona, D.A.; Palermo, C.I.; Scalia, G.; Fichera, M.; Stefani, S. Discriminatory Weight of SNPs in Spike SARS-CoV-2 Variants: A Technically Rapid, Unambiguous, and Bioinformatically Validated Laboratory Approach. Viruses 2022, 14, 123. https://doi.org/10.3390/v14010123

AMA Style

Musso N, Bonacci PG, Bongiorno D, Stracquadanio S, Bivona DA, Palermo CI, Scalia G, Fichera M, Stefani S. Discriminatory Weight of SNPs in Spike SARS-CoV-2 Variants: A Technically Rapid, Unambiguous, and Bioinformatically Validated Laboratory Approach. Viruses. 2022; 14(1):123. https://doi.org/10.3390/v14010123

Chicago/Turabian Style

Musso, Nicolò, Paolo Giuseppe Bonacci, Dafne Bongiorno, Stefano Stracquadanio, Dalida Angela Bivona, Concetta Ilenia Palermo, Guido Scalia, Marco Fichera, and Stefania Stefani. 2022. "Discriminatory Weight of SNPs in Spike SARS-CoV-2 Variants: A Technically Rapid, Unambiguous, and Bioinformatically Validated Laboratory Approach" Viruses 14, no. 1: 123. https://doi.org/10.3390/v14010123

APA Style

Musso, N., Bonacci, P. G., Bongiorno, D., Stracquadanio, S., Bivona, D. A., Palermo, C. I., Scalia, G., Fichera, M., & Stefani, S. (2022). Discriminatory Weight of SNPs in Spike SARS-CoV-2 Variants: A Technically Rapid, Unambiguous, and Bioinformatically Validated Laboratory Approach. Viruses, 14(1), 123. https://doi.org/10.3390/v14010123

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