Computational detection of antigen-specific B cell receptors following immunization

• 成果类型: Article
• 署名作者: Abbate, Maria Francesca; Dupic, Thomas; Vigne, Emmanuelle; Shahsavarian, Melody A.; Walczak, Aleksandra M.; Mora, Thierry
• 署名单位: Universite PSL; Ecole Normale Superieure (ENS); Sorbonne Universite; Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); Universite Paris Cite; Sanofi-Aventis; Sanofi France; Harvard University
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-11344
• DOI: 10.1073/pnas.2401058121
• 发表日期: 2024-08-27
• 关键词: repertoire; antibodies; single; identification; vaccination; responses; promise; tool

摘要

B cell receptors (BCRs) play a crucial role in recognizing and fighting foreign antigens. High-throughput sequencing enables in-depth sampling of the BCRs repertoire after immunization. However, only a minor fraction of BCRs actively participate in any given infection. To what extent can we accurately identify antigen-specific sequences directly from BCRs repertoires? We present a computational method grounded on sequence similarity, aimed at identifying statistically significant responsive BCRs. This method leverages well-known characteristics of affinity maturation and expected diversity. We validate its effectiveness using longitudinally sampled human immune repertoire data following influenza vaccination and SARS-CoV-2 infections. We show that different lineages converge to the same responding Complementarity Determining Region 3, demonstrating convergent selection within an individual. The outcomes of this method hold promise for application in vaccine development, personalized medicine, and antibody-derived therapeutics.