Public Baseline and shared response structures support the theory of antibody repertoire functional commonality

The naïve antibody/B-cell receptor (BCR) repertoires of different individuals ought to exhibit significant functional commonality, given that most pathogens trigger an effective antibody response to immunodominant epitopes. Sequence-based repertoire analysis has so far offered little evidence for this phenomenon. For example, a recent study estimated the number of shared (‘public’) antibody clonotypes in circulating baseline repertoires to be around 0.02% across ten unrelated individuals. However, to engage the same epitope, antibodies only require a similar binding site structure and the presence of key paratope interactions, which can occur even when their sequences are dissimilar. Here, we search for evidence of geometric similarity/convergence across human antibody repertoires. We first structurally profile naïve (‘baseline’) antibody diversity using snapshots from 41 unrelated individuals, predicting all modellable distinct structures within each repertoire. This analysis uncovers a high (much greater than random) degree of structural commonality. For instance, around 3% of distinct structures are common to the ten most diverse individual samples (‘Public Baseline’ structures). Our approach is the first computational method to find levels of BCR commonality commensurate with epitope immunodominance and could therefore be harnessed to find more genetically distant antibodies with same-epitope complementarity. We then apply the same structural profiling approach to repertoire snapshots from three individuals before and after flu vaccination, detecting a convergent structural drift indicative of recognising similar epitopes (‘Public Response’ structures). We show that Antibody Model Libraries derived from Public Baseline and Public Response structures represent a powerful geometric basis set of low-immunogenicity candidates exploitable for general or target-focused therapeutic antibody screening.Author summary: It is commonly thought that most people’s adaptive immune systems can recognise the same endemic pathogens, many of which invade our bodies daily. However, existing methods of antibody repertoire comparison (which focus on genetic relatedness) only predict a tiny number of functionally equivalent antibodies in the resting state repertoires of different individuals. Here, we propose a novel approach that predicts the structural diversity of antibody binding sites within a repertoire sequence dataset. This orthogonal methodology can be applied to pool together antibodies from different genetic lineages with topological potential to bind to the same pathogen surface, and that may be functionally equivalent if they share a sufficiently similar surface interaction profile. Our methodology finds that a much greater than random set of binding site geometries exist across resting-state repertoires and can detect binding site geometric convergence in response to vaccination, both of which are consistent with underlying functional commonality between individuals. We further show that knowledge of these geometries could be useful in therapeutic antibody drug discovery, through rational screening library design. Different repertoire sequencing datasets could be interrogated to achieve a more general set of topologies compatible with many pathogens or a tailored set bespoke to a single pathogen.