Unlocking the puzzle: non-defining mutations in SARS-CoV-2 proteome may affect vaccine effectiveness.


Journal

Frontiers in public health
ISSN: 2296-2565
Titre abrégé: Front Public Health
Pays: Switzerland
ID NLM: 101616579

Informations de publication

Date de publication:
2024
Historique:
received: 15 02 2024
accepted: 02 08 2024
medline: 4 9 2024
pubmed: 4 9 2024
entrez: 4 9 2024
Statut: epublish

Résumé

SARS-CoV-2 variants are defined by specific genome-wide mutations compared to the Wuhan genome. However, non-clade-defining mutations may also impact protein structure and function, potentially leading to reduced vaccine effectiveness. Our objective is to identify mutations across the entire viral genome rather than focus on individual mutations that may be associated with vaccine failure and to examine the physicochemical properties of the resulting amino acid changes. Whole-genome consensus sequences of SARS-CoV-2 from COVID-19 patients were retrieved from the GISAID database. Analysis focused on Dataset_1 (7,154 genomes from Italy) and Dataset_2 (8,819 sequences from Spain). Bioinformatic tools identified amino acid changes resulting from codon mutations with frequencies of 10% or higher, and sequences were organized into sets based on identical amino acid combinations. Non-defining mutations in SARS-CoV-2 genomes belonging to clades 21 L (Omicron), 22B/22E (Omicron), 22F/23A (Omicron) and 21J (Delta) were associated with vaccine failure. Four sets of sequences from Dataset_1 were significantly linked to low vaccine coverage: one from clade 21L with mutations L3201F (ORF1a), A27- (S) and G30- (N); two sets shared by clades 22B and 22E with changes A27- (S), I68- (S), R346T (S) and G30- (N); and one set shared by clades 22F and 23A containing changes A27- (S), F486P (S) and G30- (N). Booster doses showed a slight improvement in protection against Omicron clades. Regarding 21J (Delta) two sets of sequences from Dataset_2 exhibited the combination of non-clade mutations P2046L (ORF1a), P2287S (ORF1a), L829I (ORF1b), T95I (S), Y145H (S), R158- (S) and Q9L (N), that was associated with vaccine failure. Vaccine coverage associations appear to be influenced by the mutations harbored by marketed vaccines. An analysis of the physicochemical properties of amino acid revealed that primarily hydrophobic and polar amino acid substitutions occurred. Our results suggest that non-defining mutations across the proteome of SARS-CoV-2 variants could affect the extent of protection of the COVID-19 vaccine. In addition, alteration of the physicochemical characteristics of viral amino acids could potentially disrupt protein structure or function or both.

Identifiants

pubmed: 39228849
doi: 10.3389/fpubh.2024.1386596
pmc: PMC11369981
doi:

Substances chimiques

COVID-19 Vaccines 0
Proteome 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1386596

Informations de copyright

Copyright © 2024 Ulzurrun, Grande-Pérez, del Hoyo, Guevara, Gil, Sorzano and Campillo.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Auteurs

Eugenia Ulzurrun (E)

Center for Biological Research Margarita Salas, Spanish National Research Council (CSIC), Madrid, Spain.
National Center for Biotechnology, Spanish National Research Council (CSIC), Madrid, Spain.
Institute of Mathematical Sciences, Spanish National Research Council (CSIC), Madrid, Spain.

Ana Grande-Pérez (A)

Department of Cellular Biology, Genetics, and Physiology, University of Malaga, Málaga, Spain.

Daniel Del Hoyo (D)

National Center for Biotechnology, Spanish National Research Council (CSIC), Madrid, Spain.

Cesar Guevara (C)

Mechatronics and Interactive Systems - MIST Research Center, Universidad Tecnológica Indoamérica, Quito, Ecuador.

Carmen Gil (C)

Center for Biological Research Margarita Salas, Spanish National Research Council (CSIC), Madrid, Spain.

Carlos Oscar Sorzano (CO)

National Center for Biotechnology, Spanish National Research Council (CSIC), Madrid, Spain.

Nuria E Campillo (NE)

Center for Biological Research Margarita Salas, Spanish National Research Council (CSIC), Madrid, Spain.

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Classifications MeSH