tetano
Editor, Senior Moderator
Front Immunol
. 2022 Mar 24;13:861050.
doi: 10.3389/fimmu.2022.861050. eCollection 2022.
Computation of Antigenicity Predicts SARS-CoV-2 Vaccine Breakthrough Variants
Ye-Fan Hu[SUP] 1 2 [/SUP], Jing-Chu Hu[SUP] 3 [/SUP], Hua-Rui Gong[SUP] 1 [/SUP], Antoine Danchin[SUP] 1 4 [/SUP], Ren Sun[SUP] 1 [/SUP], Hin Chu[SUP] 5 [/SUP], Ivan Fan-Ngai Hung[SUP] 2 [/SUP], Kwok Yung Yuen[SUP] 5 [/SUP], Kelvin Kai-Wang To[SUP] 5 [/SUP], Bao-Zhong Zhang[SUP] 3 [/SUP], Thomas Yau[SUP] 2 [/SUP], Jian-Dong Huang[SUP] 1 3 6 [/SUP]
Affiliations
Abstract
It has been reported that multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) including Alpha, Beta, Gamma, and Delta can reduce neutralization by antibodies, resulting in vaccine breakthrough infections. Virus-antiserum neutralization assays are typically performed to monitor potential vaccine breakthrough strains. However, experiment-based methods took several weeks whether newly emerging variants can break through current vaccines or therapeutic antibodies. To address this, we sought to establish a computational model to predict the antigenicity of SARS-CoV-2 variants by sequence alone. In this study, we firstly identified the relationship between the antigenic difference transformed from the amino acid sequence and the antigenic distance from the neutralization titers. Based on this correlation, we obtained a computational model for the receptor-binding domain (RBD) of the spike protein to predict the fold decrease in virus-antiserum neutralization titers with high accuracy (~0.79). Our predicted results were comparable to experimental neutralization titers of variants, including Alpha, Beta, Delta, Gamma, Epsilon, Iota, Kappa, and Lambda, as well as SARS-CoV. Here, we predicted the fold of decrease of Omicron as 17.4-fold less susceptible to neutralization. We visualized all 1,521 SARS-CoV-2 lineages to indicate variants including Mu, B.1.630, B.1.633, B.1.649, and C.1.2, which can induce vaccine breakthrough infections in addition to reported VOCs Beta, Gamma, Delta, and Omicron. Our study offers a quick approach to predict the antigenicity of SARS-CoV-2 variants as soon as they emerge. Furthermore, this approach can facilitate future vaccine updates to cover all major variants. An online version can be accessed at http://jdlab.online.
Keywords: SARS-CoV-2; antigenicity prediction; computation of antigenicity; vaccine breakthrough variants; variants of concern.
. 2022 Mar 24;13:861050.
doi: 10.3389/fimmu.2022.861050. eCollection 2022.
Computation of Antigenicity Predicts SARS-CoV-2 Vaccine Breakthrough Variants
Ye-Fan Hu[SUP] 1 2 [/SUP], Jing-Chu Hu[SUP] 3 [/SUP], Hua-Rui Gong[SUP] 1 [/SUP], Antoine Danchin[SUP] 1 4 [/SUP], Ren Sun[SUP] 1 [/SUP], Hin Chu[SUP] 5 [/SUP], Ivan Fan-Ngai Hung[SUP] 2 [/SUP], Kwok Yung Yuen[SUP] 5 [/SUP], Kelvin Kai-Wang To[SUP] 5 [/SUP], Bao-Zhong Zhang[SUP] 3 [/SUP], Thomas Yau[SUP] 2 [/SUP], Jian-Dong Huang[SUP] 1 3 6 [/SUP]
Affiliations
- PMID: 35401572
- PMCID: PMC8987580
- DOI: 10.3389/fimmu.2022.861050
Abstract
It has been reported that multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) including Alpha, Beta, Gamma, and Delta can reduce neutralization by antibodies, resulting in vaccine breakthrough infections. Virus-antiserum neutralization assays are typically performed to monitor potential vaccine breakthrough strains. However, experiment-based methods took several weeks whether newly emerging variants can break through current vaccines or therapeutic antibodies. To address this, we sought to establish a computational model to predict the antigenicity of SARS-CoV-2 variants by sequence alone. In this study, we firstly identified the relationship between the antigenic difference transformed from the amino acid sequence and the antigenic distance from the neutralization titers. Based on this correlation, we obtained a computational model for the receptor-binding domain (RBD) of the spike protein to predict the fold decrease in virus-antiserum neutralization titers with high accuracy (~0.79). Our predicted results were comparable to experimental neutralization titers of variants, including Alpha, Beta, Delta, Gamma, Epsilon, Iota, Kappa, and Lambda, as well as SARS-CoV. Here, we predicted the fold of decrease of Omicron as 17.4-fold less susceptible to neutralization. We visualized all 1,521 SARS-CoV-2 lineages to indicate variants including Mu, B.1.630, B.1.633, B.1.649, and C.1.2, which can induce vaccine breakthrough infections in addition to reported VOCs Beta, Gamma, Delta, and Omicron. Our study offers a quick approach to predict the antigenicity of SARS-CoV-2 variants as soon as they emerge. Furthermore, this approach can facilitate future vaccine updates to cover all major variants. An online version can be accessed at http://jdlab.online.
Keywords: SARS-CoV-2; antigenicity prediction; computation of antigenicity; vaccine breakthrough variants; variants of concern.