In-depth site-specific investigations of protein glycosylation are the basis for understanding the biological function of glycoproteins. Mass spectrometry-based N- and O-glycopeptide analyses enable determination of the glycosylation site, site occupancy, as well as glycan varieties present on a particular site. However, the depth of information is highly dependent on the applied analytical tools, including glycopeptide fragmentation regimes and automated data analysis. Here, we used a small set of synthetic disialylated, biantennary N-glycopeptides to systematically tune Q-TOF instrument parameters towards optimal energy stepping collision induced dissociation (CID) of glycopeptides. A linear dependency of m/z-ratio and optimal fragmentation energy was found, showing that with increasing m/z-ratio, more energy is required for glycopeptide fragmentation. Based on these optimized fragmentation parameters, a method combining lower- and higher-energy CID was developed, allowing the online acquisition of glycan and peptide-specific fragments within a single tandem MS experiment. We validated this method analyzing a set of human immunoglobulins (IgA1+2, sIgA, IgG1+2, IgE, IgD, IgM) as well as bovine fetuin. These optimized fragmentation parameters also enabled software-assisted glycopeptide assignment of both N- and O-glycopeptides including information about the most abundant glycan compositions, peptide sequence and putative structures. Twenty-six out of 30 N-glycopeptides and four out of five O-glycopeptides carrying >110 different glycoforms could be identified by this optimized LC-ESI tandem MS method with minimal user input. The Q-TOF based glycopeptide analysis platform presented here opens the way to a range of different applications in glycoproteomics research as well as biopharmaceutical development and quality control.Graphical AbstractᅟElectronic supplementary materialThe online version of this article (doi:10.1007/s13361-015-1308-6) contains supplementary material, which is available to authorized users.

Mass spectrometry (MS) is used to quantify the relative distribution of glycans attached to particular protein glycosylation sites (micro-heterogeneity) and evaluate the molar site occupancy (macro-heterogeneity) in glycoproteomics. However, the accuracy of MS for such quantitative measurements remains to be clarified. As a key step towards this goal, a panel of related tryptic peptides with and without complex, biantennary, disialylated N-glycans was chemically synthesised by solid-phase peptide synthesis. Peptides mimicking those resulting from enzymatic deglycosylation using PNGase F/A and endo D/F/H were synthetically produced, carrying aspartic acid and N-acetylglucosamine-linked asparagine residues, respectively, at the glycosylation site. The MS ionisation/detection strengths of these pure, well-defined and quantified compounds were investigated using various MS ionisation techniques and mass analysers (ESI-IT, ESI-Q-TOF, MALDI-TOF, ESI/MALDI-FT-ICR-MS). Depending on the ion source/mass analyser, glycopeptides carrying complex-type N-glycans exhibited clearly lower signal strengths (10-50% of an unglycosylated peptide) when equimolar amounts were analysed. Less ionisation/detection bias was observed when the glycopeptides were analysed by nano-ESI and medium-pressure MALDI. The position of the glycosylation site within the tryptic peptides also influenced the signal response, in particular if detected as singly or doubly charged signals. This is the first study to systematically and quantitatively address and determine MS glycopeptide ionisation/detection strengths to evaluate glycoprotein micro-heterogeneity and macro-heterogeneity by label-free approaches. These data form a much needed knowledge base for accurate quantitative glycoproteomics.

The spike (S) glycoprotein in the envelope of SARS-CoV-2 is densely glycosylated but the functions of its glycosylation are unknown. Here we demonstrate that S is recognized in a glycan-dependent manner by multiple innate immune receptors including the mannose receptor MR/CD206, DC-SIGN/CD209, L-SIGN/CD209L, and MGL/CLEC10A/CD301. Single-cell RNA sequencing analyses indicate that such receptors are highly expressed in innate immune cells in tissues susceptible to SARS-CoV-2 infection. Binding of the above receptors to S is characterized by affinities in the picomolar range and consistent with S glycosylation analysis demonstrating a variety of N- and O-glycans as receptor ligands. These results indicate multiple routes for SARS-CoV-2 to interact with human cells and suggest alternative strategies for therapeutic intervention.

Colorectal cancer is the third most common cancer worldwide with an annual incidence of ∼1 million cases and an annual mortality rate of ∼655,000 individuals. There is an urgent need for identifying novel targets to develop more sensitive, reliable, and specific tests for early stage detection of colon cancer. Post-translational modifications are known to play an important role in cancer progression and immune surveillance of tumors. In the present study, we compared the N-glycan profiles from 13 colorectal cancer tumor tissues and corresponding control colon tissues. The N-glycans were enzymatically released, purified, and labeled with 2-aminobenzoic acid. Aliquots were profiled by hydrophilic interaction liquid chromatography (HILIC-HPLC) with fluorescence detection and by negative mode MALDI-TOF-MS. Using partial least squares discriminant analysis to investigate the N-glycosylation changes in colorectal cancer, an excellent separation and prediction ability were observed for both HILIC-HPLC and MALDI-TOF-MS data. For structure elucidation, information from positive mode ESI-ion trap-MS/MS and negative mode MALDI-TOF/TOF-MS was combined. Among the features with a high separation power, structures containing a bisecting GlcNAc were found to be decreased in the tumor, whereas sulfated glycans, paucimannosidic glycans, and glycans containing a sialylated Lewis type epitope were shown to be increased in tumor tissues. In addition, core-fucosylated high mannose N-glycans were detected in tumor samples. In conclusion, the combination of HILIC and MALDI-TOF-MS profiling of N-glycans with multivariate statistical analysis demonstrated its potential for identifying N-glycosylation changes in colorectal cancer tissues and provided new leads that might be used as candidate biomarkers.