Explore antibody repertoire in the era of AI

The diverse antibodies of adaptive immunity comprise an antibody repertoire that combats various pathogens. This repertoire is shaped by both intrinsic antibody gene diversification and extrinsic cellular selection. Conversely, an antibody repertoire contains multiple layers of immunological information, including the history of pathogen exposure. High-throughput sequencing-based antibody repertoire cloning approaches have revealed unexpected features of adaptive immunity. However, our understanding of antibody repertoire data is still in its infancy. In this review, we introduce the emerging concepts and discuss the application of deep learning approaches to understanding antibody repertoires. First, we introduce the definition and functional features of antibody clonotype. Next, we review the evolution of antibody clonotypes and discuss potential antibody repertoire-directed vaccination approaches. Lastly, we summarize the application of deep learning in predicting antibody binding, generating specific antibodies, and making immunologic diagnoses. Recently, artificial intelligence (AI) has made revolutionary progress in biology. Leveraging high-dimensional antibody repertoire information, deep learning models have the potential to transform our understanding of antibody repertoire.