Glycopeptides are typically prepared by cleaving the proteins with specific proteolytic enzymes, such as trypsin. The resulting glycopeptides tend to have weak mass spectrometry ion signals (ESI or MALDI) due to their relatively large molecular weight. The identification of glycosylation sites with tandem mass spectrometry is further complicated by fragmentation of both the peptide backbone and the glycan moiety. We explored a method using a nonspecific enzyme, pronase, to generate small glycopeptides (between two and six amino acids). These glycopeptides were enriched and desalted using a microscale hydrophilic interaction chromatography extraction device prior to MALDI QTof MS analysis. MALDI matrix, 2, 5-dihydroxybenzoic acid, doped with ammonium triscitrate, was utilized for analysis. Sodiated ions were observed as minor ions, while protonated ions were enhanced dramatically with this matrix. Collision-induced dissociation was performed on both the protonated and sodiated ions. MS/MS fragmentation spectra reveal that proton has greater affinity for the peptide moiety, while the sodium cation tends to associate with the sugar moiety. Characteristic fragment patterns allowed for identifications of glycosylation sites for both the protonated and the sodiated precursor ions. Model proteins, horseradish peroxidase and alpha1-acid glycoproteins, were analyzed to illustrate the identification of N-linked glycosylation sites and data interpretation algorithm.

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Identification of phosphopeptides by MS is challenging due to their relatively low abundance in proteomic samples and their limited ionization efficiency. Various affinity enrichment methods have been used in the literature. Titanium dioxide SPE devices have been recently proposed as an alternative to immobilized metal affinity chromatography for phosphopeptide enrichment. This study evaluates the TiO(2 )method using sorbent packed in a 96 well microscale extraction plate operated using a vacuum manifold. The phosphopeptide recovery and enrichment selectivity were investigated at various loading conditions. The effectiveness of organic additives such as dihydroxybenzoic acid derivatives and other nonaliphatic carboxylic acids on enrichment selectivity was examined. The performance of TiO(2) was compared to IMAC sorbent. The results suggest that various additives improve the enrichment selectivity by effectively interfering with the acidic peptides binding to TiO(2) sorbent. Interaction of phosphopeptides with sorbent is also affected, which leads to overall reduction in phosphopeptide recovery. The new SPE device was successfully utilized for the extraction of phosphopeptides from yeast lysate digest using 2,5-dihydroxybenzoic acid to minimize the interference from nonphosphorylated peptides.

N-Glycan analysis is routinely performed for biotherapeutic protein characterization. A recently introduced N-glycan analysis kit using RapiFluor-MS (RFMS) labeling provides time savings over reductive amination labeling methods while also providing enhanced fluorescence (FLR) and mass spectrometry (MS) responses. This article demonstrates the semiautomation of this kit using an Andrew Alliance pipetting robot that promises further gains in productivity. This robotic platform uses standard manual pipettors and an optically guided arm to facilitate the automation of manual procedures. The manual RFMS protocol includes two heating and cooling steps during protein denaturation and de-N-glycosylation. However, the current Andrew Alliance automated platform cannot move reaction tubes to and from different heating blocks. As a result, samples prepared using the automated procedure remain in a computer-controlled Peltier effect heating block, requiring reoptimization of denaturation and de-N-glycosylation temperatures. Using hydrophilic interaction liquid chromatography to monitor the RFMS-labeled glycan profiles, the authors demonstrated the reproducibility of the automated protocol with percent relative standard deviations (RSDs) of 9%–19% for the total area and 0.8%–20% for the relative areas of major and minor glycoforms. Overall, the automated platform presented here proves to be a convenient and reliable solution for N-glycan preparation and analysis.