Benchmarking of mass spectrometry-based antibody repertoire profiling reveals extensive systematic biases

The serum antibody repertoire is crucial for long-term immune protection, holding significant immunological and biotechnological value. Bottom-up proteomics is the most widely used mass spectrometry (MS) technique for profiling the sequence diversity of serum antibodies. However, serum antibody bottom-up proteomics (Ab-seq) has not been thoroughly benchmarked. In this study, we quantified the replicability and robustness of Ab-seq using six monoclonal antibodies with known protein sequences in 70 concentration and polyclonality combinations with and without polyclonal blood IgG background. Each combination underwent four protease treatments and was analyzed across four experimental and three technical replicates (3,360 LC-MS/MS runs). We quantified the dependence of MS-based antibody sequence identification on antibody sequence as well as concentration, protease, background signal diversity, and bioinformatics setup. Integrating experimental replicates, multiple proteases, and bioinformatics tools enhanced antibody identification. De novo peptide sequencing further improved sequence identification, complementing database-dependent methods. Our work provides a foundational resource for the field of MS-based serum antibody profiling.