The proteomic toolbox for identification, quantification, and characterization of polyclonal antibodies

Abstract

Recent advances in proteomics and mass spectrometry facilitated the in-depth characterization of monoclonal antibodies and enabled innovative approaches for the quantification of polyclonal antibodies generated against numerous antigens. Human respiratory syncytial virus (RSV) is a contagious respiratory pathogen often manifested as a common cold infection in adults and more serious symptoms in infants and the elderly population. Here, we used a reference IgG1{kappa} monoclonal antibody NISTmAb 8671 and its affinity interaction with an RSV fusion glycoprotein F as a model to develop the proteomic toolbox for identification, quantification, and characterization of polyclonal antibodies. Our toolbox integrated a variety of proteomic and mass spectrometry approaches for accurate mass measurements of antibody fragments, antibody digestion with the complimentary proteases (trypsin, asparaginase, and proalanase), immunoaffinity enrichments, and bottom-up or middle-down proteomics. We measured absolute concentrations of anti-RSV antibody isotypes and subclasses in 69 serum samples of healthy individuals and revealed IgG1 (2,580 ng/mL), IgA1 (280 ng/mL), and IgM (180 ng/mL) as the most abundant isotypes. Interestingly, we also identified the presence of IgG2 (74 ng/ml), IgG4 (4.9 ng/mL) and IgA2 (5.5 ng/mL) antibodies. Interactome measurements detected the consistent co-precipitation of C1q complement complexes. Repertoire profiling of the variable regions of polyclonal antibodies revealed the frequent use of IGHV3 subgroup genes, while IGHV5-51 was the most abundant single gene of the anti-RSV polyclonal antibody response. The presented toolbox will facilitate the in-depth characterization of polyclonal antibodies and pave the way to quantitative approaches in serological studies and precision immunology.