Simultaneous polyclonal antibody sequencing and epitope mapping by cryo-electron microscopy and mass spectrometry

Antibodies are a major component of adaptive immunity against invading pathogens. In this presentation, we will describe an analytical approach to characterize the antigen-specific antibody repertoire directly from the secreted proteins in convalescent serum. This approach enables simultaneous antibody sequencing and epitope mapping using a combination of single particle cryo-electron microscopy (cryo-EM) and bottom-up proteomics techniques based on mass spectrometry (LC-MS/MS). We evaluate the performance of the deep-learning tool ModelAngelo in determining de novo antibody sequences directly from reconstructed 3D volumes of antibody-antigen complexes. We demonstrate that while map quality is a critical bottleneck, it is possible to sequence antibody variable domains from cryo-EM reconstructions with accuracies of up to 80-90%. While the rate of errors exceeds the typical levels of somatic hypermutation, we show that the ModelAngelo-derived sequences can be used to assign the used V-genes. This provides a functional guide to assemble de novo peptides from LC-MS/MS data more accurately and improves the tolerance to a background of polyclonal antibody sequences.

 

We show that such EM-derived templates indeed improve MS-based sequencing accuracy in the context of complex antibody mixtures and that publicly available EMPEM reconstructions are of sufficient quality to leverage this approach. This proof-of-principle offers a promising perspective to integrate cryo-EM and MS methods for a comprehensive characterization of the antibody repertoire on both sequence and epitope levels.

 

Learning Objectives