Resolving spectral congestion of (any?) intact glycoprotein using DIA-PTCR

The molecular complexity of proteins with multiple glycosylation sites challenges traditional analytical methods for intact mass analysis. Glycans play a pivotal role in defining the functional and structural properties of proteins; however, their biosynthesis is not template-driven and are thereby (rather unpredictably) structurally diverse. This inherent molecular diversity impedes thorough characterization using only mass spectrometry (MS) or other conventional techniques, especially for the purposes of assigning function to glycoforms subpopulations or individual proteoforms. Current approaches to analyzing heterogeneous glycoprotein samples, such as those involving biotherapeutics or in targeted structural/glycobiological studies, involve fragment measurements or partial digestion of glycans.

In our recent Nature Communications publication (4/2024), we present a streamlined workflow for the direct, intact analysis of heterogeneous proteins that have previously posed challenges for intact MS characterization. This innovative method, termed "DIA-PTCR," employs a data-independent approach to analyze intact glycoproteins and non-covalent complexes using proton-transfer charge-reduction tandem MS (PTCR).

Owing to the high-mass range quadrupole of the new Ascend Orbitrap platform, which can isolate ions up to 8000 m/z with an exceptionally narrow m/z window, DIA-PTCR provides mass information on spectrally unresolvable proteins without the need for denaturation, upfront digestion, or separation.

We tested the approach on various heavily glycosylated molecules, including cytokines, TNF-fusions, and peptide-bound MHC class II complexes to demonstrate efficacy in measuring their proteoform-level diversity while also retaining information about non-covalent structure, co-occurrence of glycans and other PTMs such as phosphorylation and acetylation. We observed subunit truncations, differential glycosylation between samples, and were able confirm subunit assembly in the midst of extreme proteoform diversity.

Additionally, we establish a bioinformatic data analysis strategy for DIA-PTCR that may offer insights into glycan composition. Due to the staggering combinatorial diversity of glycosylation, probable annotations for detected intact masses –reflecting the limited set of glycan combinations– were modeled using validated glycan candidates from glycopeptide and glycomic data, providing relative abundances of putative glycoforms for each DIA-PTCR molecular weight. Notably, we inferred the glycoform abundances for hundreds of molecular weights for the eight-times glycosylated cytokine IL22-Fc dimer, enabling correlations between sialylated glycoform sub-populations and their interaction with the IL22 receptor.

Further development of the DIA-PTCR workflow may incorporate top-down fragmentation for glycoform characterization as well analysis of immuno-enriched glycoproteins to elucidate the network of readers, writers and erasers of glycosylation.