Design of a companion bioinformatic tool to detect the emergence and geographical distribution of SARS-CoV-2 Spike protein genetic variants.


Journal

Journal of translational medicine
ISSN: 1479-5876
Titre abrégé: J Transl Med
Pays: England
ID NLM: 101190741

Informations de publication

Date de publication:
30 12 2020
Historique:
received: 13 07 2020
accepted: 11 12 2020
entrez: 31 12 2020
pubmed: 1 1 2021
medline: 15 1 2021
Statut: epublish

Résumé

Tracking the genetic variability of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) is a crucial challenge. Mainly to identify target sequences in order to generate robust vaccines and neutralizing monoclonal antibodies, but also to track viral genetic temporal and geographic evolution and to mine for variants associated with reduced or increased disease severity. Several online tools and bioinformatic phylogenetic analyses have been released, but the main interest lies in the Spike protein, which is the pivotal element of current vaccine design, and in the Receptor Binding Domain, that accounts for most of the neutralizing the antibody activity. Here, we present an open-source bioinformatic protocol, and a web portal focused on SARS-CoV-2 single mutations and minimal consensus sequence building as a companion vaccine design tool. Furthermore, we provide immunogenomic analyses to understand the impact of the most frequent RBD variations. Results on the whole GISAID sequence dataset at the time of the writing (October 2020) reveals an emerging mutation, S477N, located on the central part of the Spike protein Receptor Binding Domain, the Receptor Binding Motif. Immunogenomic analyses revealed some variation in mutated epitope MHC compatibility, T-cell recognition, and B-cell epitope probability for most frequent human HLAs. This work provides a framework able to track down SARS-CoV-2 genomic variability.

Sections du résumé

BACKGROUND
Tracking the genetic variability of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) is a crucial challenge. Mainly to identify target sequences in order to generate robust vaccines and neutralizing monoclonal antibodies, but also to track viral genetic temporal and geographic evolution and to mine for variants associated with reduced or increased disease severity. Several online tools and bioinformatic phylogenetic analyses have been released, but the main interest lies in the Spike protein, which is the pivotal element of current vaccine design, and in the Receptor Binding Domain, that accounts for most of the neutralizing the antibody activity.
METHODS
Here, we present an open-source bioinformatic protocol, and a web portal focused on SARS-CoV-2 single mutations and minimal consensus sequence building as a companion vaccine design tool. Furthermore, we provide immunogenomic analyses to understand the impact of the most frequent RBD variations.
RESULTS
Results on the whole GISAID sequence dataset at the time of the writing (October 2020) reveals an emerging mutation, S477N, located on the central part of the Spike protein Receptor Binding Domain, the Receptor Binding Motif. Immunogenomic analyses revealed some variation in mutated epitope MHC compatibility, T-cell recognition, and B-cell epitope probability for most frequent human HLAs.
CONCLUSIONS
This work provides a framework able to track down SARS-CoV-2 genomic variability.

Identifiants

pubmed: 33380328
doi: 10.1186/s12967-020-02675-4
pii: 10.1186/s12967-020-02675-4
pmc: PMC7772798
doi:

Substances chimiques

COVID-19 Vaccines 0
Receptors, Virus 0
Spike Glycoprotein, Coronavirus 0
spike protein, SARS-CoV-2 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

494

Subventions

Organisme : Ministero della Salute
ID : Ricerca Corrente 2019
Pays : International

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Auteurs

Alice Massacci (A)

Takis srl, Rome, Italy.

Eleonora Sperandio (E)

Biostatistics, Bioinformatics and Clinical Trial Center, IRCCS Regina Elena National Cancer Institute, Rome, Italy.

Lorenzo D'Ambrosio (L)

Tumor Immunology and Immunotherapy Unit, IRCCS Regina Elena National Cancer Institute, Rome, Italy.

Mariano Maffei (M)

EvviVax srl, Rome, Italy.

Fabio Palombo (F)

Takis srl, Rome, Italy.

Luigi Aurisicchio (L)

Takis srl, Rome, Italy.

Gennaro Ciliberto (G)

Scientific Direction, IRCCS Regina Elena National Cancer Institute, Rome, Italy.

Matteo Pallocca (M)

Biostatistics, Bioinformatics and Clinical Trial Center, IRCCS Regina Elena National Cancer Institute, Rome, Italy. matteo.pallocca@ifo.gov.it.

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Classifications MeSH