Rapid isolation and immune profiling of SARS-CoV-2 specific memory B cell in convalescent COVID-19 patients via LIBRA-seq

通过 LIBRA-seq 快速分离并分析 COVID-19 恢复期患者中的 SARS-CoV-2 特异性记忆 B 细胞

阅读:6
作者:Bing He #, Shuning Liu #, Yuanyuan Wang #, Mengxin Xu, Wei Cai, Jia Liu, Wendi Bai, Shupei Ye, Yong Ma, Hengrui Hu, Huicui Meng, Tao Sun, Yanling Li, Huanle Luo, Mang Shi, Xiangjun Du, Wenjing Zhao, Shoudeng Chen, Jingyi Yang, Haipeng Zhu, Yusheng Jie, Yuedong Yang, Deyin Guo, Qiao Wang, Yuwen Liu, 

Abstract

B cell response plays a critical role against SARS-CoV-2 infection. However, little is known about the diversity and frequency of the paired SARS-CoV-2 antigen-specific BCR repertoire after SARS-CoV-2 infection. Here, we performed single-cell RNA sequencing and VDJ sequencing using the memory and plasma B cells isolated from five convalescent COVID-19 patients, and analyzed the spectrum and transcriptional heterogeneity of antibody immune responses. Via linking BCR to antigen specificity through sequencing (LIBRA-seq), we identified a distinct activated memory B cell subgroup (CD11chigh CD95high) had a higher proportion of SARS-CoV-2 antigen-labeled cells compared with memory B cells. Our results revealed the diversity of paired BCR repertoire and the non-stochastic pairing of SARS-CoV-2 antigen-specific immunoglobulin heavy and light chains after SARS-CoV-2 infection. The public antibody clonotypes were shared by distinct convalescent individuals. Moreover, several antibodies isolated by LIBRA-seq showed high binding affinity against SARS-CoV-2 receptor-binding domain (RBD) or nucleoprotein (NP) via ELISA assay. Two RBD-reactive antibodies C14646P3S and C2767P3S isolated by LIBRA-seq exhibited high neutralizing activities against both pseudotyped and authentic SARS-CoV-2 viruses in vitro. Our study provides fundamental insights into B cell response following SARS-CoV-2 infection at the single-cell level.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。