Simple endoglycosidase-assisted peptide mapping workflow for characterizing non-consensus n-glycosylation in therapeutic monoclonal antibodies

•The developed endoglycosidase-assisted peptide mapping workflow facilitates the detection of low-abundance non-consensus N-glycopeptides, which could be overlooked with conventional peptide mapping methods.•No enrichment strategy is required for the characterization of non-consensus N-glycosylation using the developed workflow.•With the current approach, conventional data-dependent acquisition mode with regular higher-energy collisional dissociation is sufficient to identify low-abundance non-consensus N-glycopeptides.•The application of bioinformatic tools substantially simplifies data processing and decreases the analysis time. N-linked glycosylation, an extensively studied protein post-translational modification, was conventionally understood to occur at asparagine (Asn or N) sites with the consensus motif NXS/T, where X can be any amino acid residue except for proline, followed by serine or threonine. However, with advancements in characterization techniques and bioinformatic tools, increasing evidence indicates that Asn residues that are not located in the NXS/T consensus motif can also undergo N-glycosylation, which is also known as non-consensus or noncanonical N-glycosylation. Characterizing non-consensus N-glycosylation remains challenging because of the unpredictable sequon and its relatively low abundance. Here, we report an endoglycosidase-assisted peptide mapping workflow for mass spectrometry (MS) characterization of non-consensus N-glycosylation in monoclonal antibodies (mAbs). The feasibility of the workflow was demonstrated by a challenging case study, in which an atypical glycosite located within an NPNNXN sequence in a 25-residue tryptic peptide was identified in the fragment antigen-binding (Fab) region of a mAb. With the aids of endoglycosidase treatment, the resulting truncated glycan structures improved peptide ionization efficiency in MS and hence facilitated reliable quantitation of glycosite occupancy. Meanwhile, the remaining mono-/di-saccharides served as a large mass tag enabling differentiation between the glycopeptide and deamidated peptide, thus allowing for database searching for glycosite localization and semi-automation of the data processing workflow. This workflow offers a simple solution for characterizing non-consensus N-glycosylation for the development of therapeutic mAbs.