Computational detection of antigen-specific B-cell receptors

B-cell receptors (BCR) play a crucial role in recognizing and fighting foreign antigens. High-throughput sequencing enables in-depth examination of the BCR repertoire after immunization. However, a fundamental question remains: to what extent can we accurately identify antigen-specific sequences within the extensive BCR repertoire, since only a minor fraction of these receptors actively participate in any given infection?

To address this challenge, 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. The outcomes of this method hold promise for application in vaccine development, personalized medicine, and antibody-derived therapeutics.