  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 CDR3, demonstrating
convergent selection within an individual. The outcomes of this method hold
promise for application in vaccine development, personalized medicine, and
antibody-derived therapeutics.
