xCGE-LIF of released N-glycans and free oligosaccharides

xCGE-LIF of released N-glycans and free oligosaccharides  

xCGE-LIF based separation of glycans.

Multiplexed capillary gel electrophoresis with laser-induced fluorescence detection (xCGE-LIF) is a powerful analytical technique that allows the sensitive, selective, robust, and high-throughput identification and quantification of released N-glycans and free oligosaccharides (glycoprofiling). Due to the use of fluorescent labels and the capillary-based gel electrophoretic separation minute amounts of analytes – including structural isomers – can be separated by size, charge and shape with high peak capacity and detected with high sensitivity, without encountering typical caveats of chromatography-based separation techniques, such as selectivity, carry-over, or overloading effects. The multiplexed separation, with up to 96 capillaries in parallel, provides high-throughput capability to xCGE-LIF. In our group we have established and optimized a modular set of protocols for the xCGE-LIF-based analysis of N-glycans derived from samples of various origins and complexities: this includes, for instance, standard glycoproteins from human or bovine origin such as IgG or fetuin and also pharmaceutically relevant glycoproteins such as erythropoietin, or glycoproteins derived from cell cultures such as MDCK-cell-derived influenza A hemagglutinin. The analysis of entire N-glycomes, for instance, derived from human blood plasma, is also possible [1-6].

MALDI-TOF-MS of released N-Glycans

Figure 2: Ethyl esterification stabilizes sialic acids and allows linkage differentiation, enabling robust and informative MALDI-TOF-MS analysis. Adapted and modified from [7].

In addition to electrophoresis- and chromatography-based methods, we also employ mass spectrometric methods for the analysis of released N-glycans. Matrix-assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI-TOF-MS) combined with sialic-acid stabilization by ethyl esterification not only enables the rapid, robust and linkage-specific analysis of released N-glycans, but also allows their high-throughput relative quantification.

NanoPGC-LC-ESI-FT-MS/MS of released N- and O-glycans

Figure 3: nanoPGC-LC-ESI-FT-FT-MSn with post-column make-up flow. Taken from Nguyen-Khuong et. al (2018), manuscript under revision at Glycoconjugate Journal

For in-depth mass spectrometric analyses of N- and also O-glycans, we have also established an LC-MS/MS workflow that combines the isomeric separation of non-labelled glycans via porous graphitized carbon liquid chromatography with the structural information that can be gained from subsequent high-resolution multistage mass spectrometry with higher-energy collisional dissociation (negative-ion mode nanoPGC-LC-ESI-FT-FT-MSn with HCD fragmentation). Separation of the glycans across a PGC column can yield information on structural isomers. Furthermore, MS-based detection and fragmentation in negative ion mode of such glycans can produce unique fragment ions which – when complemented with its behavior on PGC chromatographic – can impart further details to the glycan structure such as the branching, epitope features, topology and linkage information. In an effort to adapt PGC-LC-ESI-MS(/MS) to the nano-scale operation, spray instability on a standard nano-electrospray ionization source along the nano-PGC-LC gradient occur. Recently, a stable electrospray implementing a post-column make-up flow (PCMF) was achieved [8]. Here, pure acetonitrile is used to supplement the eluate from the nano-PGC-LC column. The improved spray stability enhances detection and resolution of glycans during the analysis runs.


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High-Throughput Profiling of Protein N-Glycosylation by MALDI-TOF-MS Employing Linkage-Specific Sialic Acid Esterification
Anal. Chem., 86(12), 5784–5793 (2014)
Nguyen-Khuong, T., Pralow A., Reichl, U., Rapp, E.
Improvement of Electrospray Stability in Negative Ion Mode for nano-PGC-LC-MS Glycoanalysis via Post-Column Make-Up Flow
Accepted in Glycoconjugate Journal (2018)
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