# Prediction of antigen-responding VHH antibodies by tracking the evolution of antibody along the time course of immunization

## TL;DR

The study shows how tracking antibody evolution during immunization can predict which antibodies respond to antigens, without needing extra lab tests.

## Contribution

A new method to predict antigen-responding antibodies by analyzing antibody repertoire evolution during immunization.

## Key findings

- Tracking antibody evolution via high-throughput sequencing predicted antigen-responding VHH antibodies with over 80% success.
- The method successfully predicted antigen-binding clusters in alpacas immunized with IgG fragments and epidermal growth factor receptor.
- Rare immune-responsive clusters were identified without empirical screening data.

## Abstract

Antibody maturation is the central function of the adaptive immune response. This process is driven by the repetitive selection of mutations that increase the affinity toward antigens. We hypothesized that a precise observation of this process by high-throughput sequencing along the time course of immunization will enable us to predict the antibodies reacting to the immunized antigen without any additional in vitro screening. An alpaca was immunized with IgG fragments using multiple antigen injections, and the antibody repertoire development was traced via high-throughput sequencing periodically for months. The sequences were processed into clusters, and the antibodies in the 16 most abundant clusters were generated to determine whether the clusters included antigen-binding antibodies. The sequences of most antigen-responsive clusters resembled those of germline cells in the early stages. These sequences were observed to accumulate significant mutations and also showed a continuous sequence turnover throughout the experimental period. The foregoing characteristics gave us >80% successful prediction of clusters composed of antigen-responding VHHs against IgG fragment. Furthermore, when the prediction method was applied to the data from other alpaca immunized with epidermal growth factor receptor, the success rate exceeded 80% as well, confirming the general applicability of the prediction method. Superior to previous studies, we identified the immune-responsive but very rare clusters or sequences from the immunized alpaca without any empirical screening data.