Abstract
Endogenous antibodies, or immunoglobulins (Igs), abundantly present in body fluids, represent some of the most challenging samples to analyze, largely due to the immense variability in their sequences and concentrations. It has been estimated that our body can produce billions of different Ig proteins with different isotypes, making their individual analysis seemingly impossible. However, recent advances in protein-centric proteomics using LC-MS coupled to Orbitrap mass analyzers to profile intact Fab fragments formed by selective cleavage at the IgG-hinge revealed that IgG repertoires may be less diverse, albeit unique for each donor. Serum repertoires seem to be dominated by a few hundred clones that cumulatively make up 50-95% of the total IgG content. Enabling such analyses required careful optimization of the chromatography and mass analysis, as all Fab analytes are highly alike in mass (46-51 kDa) and sequence. To extend the opportunities of this mass-spectrometry-based profiling of antibody repertoires, we here report the optimization and evaluation of an alternative MS platform, namely, the timsTOF, for antibody repertoire profiling. The timsTOF mass analyzer has gained traction in recent years for peptide-centric proteomics and found wide applicability in plasma proteomics, affinity proteomics, and HLA peptidomics, to name a few. However, for protein-centric analysis, this platform has been less explored. Here, we demonstrate that the timsTOF platform can be adapted to perform protein-centric LC-MS-based profiling of antibody repertoires. In a side-by-side comparison of the timsTOF and the Orbitrap we demonstrate that the extracted serum antibody repertoires are alike qualitatively and quantitatively, whereby in particular the sensitivity of the timsTOF platform excels. Future incorporation of advanced top-down capabilities on the timsTOF may make this platform a very valuable alternative for protein-centric proteomics and top-down proteomics and thus also for personalized antibody repertoire profiling.