Antigenic cartography of SARS-CoV-2 reveals that Omicron BA.1 and BA.2 are antigenically distinct.
Antigenic cartography of SARS-CoV-2 reveals that Omicron BA.1 and BA.2 are antigenically distinct.
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DOI:
10.1126/sciimmunol.abq4450
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发表时间:
2022-09-23
影响因子:
24.8
通讯作者:
中科院分区:
文献类型:
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作者:
The emergence and rapid spread of SARS-CoV-2 variants may impact vaccine efficacy significantly. The Omicron variant termed BA.2, which differs substantially from BA.1 based on genetic sequence, is currently replacing BA.1 in several countries, but its antigenic characteristics have not yet been assessed. Here, we used antigenic cartography to quantify and visualize antigenic differences between early SARS-CoV-2 variants (614G, Alpha, Beta, Gamma, Zeta, Delta and Mu) using hamster antisera obtained after primary infection. We first verified that the choice of the cell line for the neutralization assay did not affect the topology of the map substantially. Antigenic maps generated using pseudotyped SARS-CoV-2 on the widely used VeroE6 cell line and the human airway cell line Calu-3 generated similar maps. Maps made using authentic SARS-CoV-2 on Calu-3 cells also closely resembled those generated with pseudotyped viruses. The antigenic maps revealed a central cluster of SARS-CoV-2 variants, which grouped based on mutual spike mutations. Whereas these early variants are antigenically similar, clustering relatively close to each other in antigenic space, Omicron BA.1 and BA.2 have evolved as two distinct antigenic outliers. Our data show that BA.1 and BA.2 both escape vaccine-induced antibody responses as a result of different antigenic characteristics. Thus, antigenic cartography could be used to assess antigenic properties of future SARS-CoV-2 variants of concern that emerge and to decide on the composition of novel spike-based (booster) vaccines. Antigenic evolution by SARS-CoV-2 can be monitored by antigenic cartography, informing future coronavirus vaccine strain selections.
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影响因子:
64.8
作者:
Muñoz-Fontela C;Dowling WE;Funnell SGP;Gsell PS;Riveros-Balta AX;Albrecht RA;Andersen H;Baric RS;Carroll MW;Cavaleri M;Qin C;Crozier I;Dallmeier K;de Waal L;de Wit E;Delang L;Dohm E;Duprex WP;Falzarano D;Finch CL;Frieman MB;Graham BS;Gralinski LE;Guilfoyle K;Haagmans BL;Hamilton GA;Hartman AL;Herfst S;Kaptein SJF;Klimstra WB;Knezevic I;Krause PR;Kuhn JH;Le Grand R;Lewis MG;Liu WC;Maisonnasse P;McElroy AK;Munster V;Oreshkova N;Rasmussen AL;Rocha-Pereira J;Rockx B;Rodríguez E;Rogers TF;Salguero FJ;Schotsaert M;Stittelaar KJ;Thibaut HJ;Tseng CT;Vergara-Alert J;Beer M;Brasel T;Chan JFW;García-Sastre A;Neyts J;Perlman S;Reed DS;Richt JA;Roy CJ;Segalés J;Vasan SS;Henao-Restrepo AM;Barouch DH
通讯作者:
Barouch DH
影响因子:
64.5
作者:
Hoffmann M;Arora P;Groß R;Seidel A;Hörnich BF;Hahn AS;Krüger N;Graichen L;Hofmann-Winkler H;Kempf A;Winkler MS;Schulz S;Jäck HM;Jahrsdörfer B;Schrezenmeier H;Müller M;Kleger A;Münch J;Pöhlmann S
通讯作者:
Pöhlmann S
影响因子:
4
作者:
Potter, CW
通讯作者:
Potter, CW
影响因子:
56.9
作者:
Lamers, Mart M.;Beumer, Joep;Clevers, Hans
通讯作者:
Clevers, Hans
影响因子:
64.8
作者:
Mlcochova P;Kemp SA;Dhar MS;Papa G;Meng B;Ferreira IATM;Datir R;Collier DA;Albecka A;Singh S;Pandey R;Brown J;Zhou J;Goonawardane N;Mishra S;Whittaker C;Mellan T;Marwal R;Datta M;Sengupta S;Ponnusamy K;Radhakrishnan VS;Abdullahi A;Charles O;Chattopadhyay P;Devi P;Caputo D;Peacock T;Wattal C;Goel N;Satwik A;Vaishya R;Agarwal M;Indian SARS-CoV-2 Genomics Consortium (INSACOG);Genotype to Phenotype Japan (G2P-Japan) Consortium;CITIID-NIHR BioResource COVID-19 Collaboration;Mavousian A;Lee JH;Bassi J;Silacci-Fegni C;Saliba C;Pinto D;Irie T;Yoshida I;Hamilton WL;Sato K;Bhatt S;Flaxman S;James LC;Corti D;Piccoli L;Barclay WS;Rakshit P;Agrawal A;Gupta RK
通讯作者:
Gupta RK