Deep immunoglobulin repertoire sequencing depicts a comprehensive atlas of spike-specific antibody lineages shared among COVID-19 convalescents

Qihong Yan; Yudi Zhang; Ruitian Hou; Wenjing Pan; Huan Liang; Xijie Gao; Weiqi Deng; Xiaohan Huang; Linbing Qu; Congli Tang; Ping He; Banghui Liu; Qian Wang; Xinwei Zhao; Zihan Lin; Zhaoming Chen; Pingchao Li; Jian Han; Xiaoli Xiong; Jincun Zhao; Song Li; Xuefeng Niu; Ling Chen

doi:10.1080/22221751.2023.2290841

Emerging Microbes and Infections (Dec 2024)

Deep immunoglobulin repertoire sequencing depicts a comprehensive atlas of spike-specific antibody lineages shared among COVID-19 convalescents

Qihong Yan,
Yudi Zhang,
Ruitian Hou,
Wenjing Pan,
Huan Liang,
Xijie Gao,
Weiqi Deng,
Xiaohan Huang,
Linbing Qu,
Congli Tang,
Ping He,
Banghui Liu,
Qian Wang,
Xinwei Zhao,
Zihan Lin,
Zhaoming Chen,
Pingchao Li,
Jian Han,
Xiaoli Xiong,
Jincun Zhao,
Song Li,
Xuefeng Niu,
Ling Chen

Affiliations

Qihong Yan: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Yudi Zhang: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Ruitian Hou: Guangzhou Institute of Infectious Disease, Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, People’s Republic of China
Wenjing Pan: Hengyang Medical School, University of South China, Hengyang, People’s Republic of China
Huan Liang: State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China
Xijie Gao: Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China
Weiqi Deng: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Xiaohan Huang: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Linbing Qu: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Congli Tang: Nanjing ARP Biotechnology Co., Ltd, Nanjing, People’s Republic of China
Ping He: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Banghui Liu: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Qian Wang: Guangzhou National Laboratory, Guangzhou, People’s Republic of China
Xinwei Zhao: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Zihan Lin: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Zhaoming Chen: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Pingchao Li: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Jian Han: iRepertoire Inc., Huntsville, AL, USA
Xiaoli Xiong: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China
Jincun Zhao: State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China
Song Li: Hengyang Medical School, University of South China, Hengyang, People’s Republic of China
Xuefeng Niu: State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China
Ling Chen: State Key Laboratory of Respiratory Disease, Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People’s Republic of China

DOI: https://doi.org/10.1080/22221751.2023.2290841
Journal volume & issue: Vol. 13, no. 1

Abstract

Read online

ABSTRACTNeutralizing antibodies are a key component in protective humoral immunity against SARS-CoV-2. Currently, available technologies cannot track epitope-specific antibodies in global antibody repertoires. Thus, the comprehensive repertoire of spike-specific neutralizing antibodies elicited by SARS-CoV-2 infection is not fully understood. We therefore combined high-throughput immunoglobulin heavy chain (IgH) repertoire sequencing, and structural and bioinformatics analysis to establish an antibodyomics pipeline, which enables tracking spike-specific antibody lineages that target certain neutralizing epitopes. We mapped the neutralizing epitopes on the spike and determined the epitope-preferential antibody lineages. This analysis also revealed numerous overlaps between immunodominant neutralizing antibody-binding sites and mutation hotspots on spikes as observed so far in SARS-CoV-2 variants. By clustering 2677 spike-specific antibodies with 360 million IgH sequences that we sequenced, a total of 329 shared spike-specific antibody clonotypes were identified from 33 COVID-19 convalescents and 24 SARS-CoV-2-naïve individuals. Epitope mapping showed that the shared antibody responses target not only neutralizing epitopes on RBD and NTD but also non-neutralizing epitopes on S2. The immunodominance of neutralizing antibody response is determined by the occurrence of specific precursors in human naïve B-cell repertoires. We identified that only 28 out of the 329 shared spike-specific antibody clonotypes persisted for at least 12 months. Among them, long-lived IGHV3-53 antibodies are likely to evolve cross-reactivity to Omicron variants through accumulating somatic hypermutations. Altogether, we created a comprehensive atlas of spike-targeting antibody lineages in COVID-19 convalescents and antibody precursors in human naïve B cell repertoires, providing a valuable reference for future vaccine design and evaluation.

Published in Emerging Microbes and Infections

ISSN: 2222-1751 (Online)
Publisher: Taylor & Francis Group
Country of publisher: United Kingdom
LCC subjects: Medicine: Internal medicine: Infectious and parasitic diseases; Science: Microbiology
Website: https://www.tandfonline.com/journals/temi

About the journal

Abstract

Keywords