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Abstract

Glycomics is a rapidly emerging field, that can be viewed as a complement to other „omics“ approaches including proteomics and genomics. Hence, there is a dramatic increase in the demand for sophisticated databases and analytical tools in glycobiology, respectively glycobiotechnology. In order to enhance and improve the comparatively small set of existing glyco-analytical methods and toolboxes, a system and method for automated straightforward, sensitive high-throughput (HTP) and high-resolution glycoanalysis was developed [1,2]. This glycoanalysis approach is based on multiplexed capillary gelelectrophoresis with laser induced fluorescence detection (CGE-LIF), using a capillary DNA-Sequencer (Applied Biosystems). Data is evaluated in conjunction with a novel modular software-tool for data-processing and automated structural elucidation by interfacing a corresponding oligosaccharide-database. The aim of the project presented was to develop tailor-made workflows for multiplexed CGE-LIF based glycoanalysis, optimized for different types of samples, each with its specific characteristics. Exemplarily, three different sample types were chosen: first, a broad variety of N-glycans released from citrate plasma proteins (a complex sample of medium to large, charged and uncharged glyco-structures); second, a relative small set of N-glycans released from IgG (a modest sample with medium sized mainly uncharged glycostructures); and third, the complete pool of oligosaccharides from human breast milk (complex sample of small charged and uncharged glycostuctures). The whole workflow starting from sample clean-up until CGE-LIF analysis using a standard capillary DNA Sequencer was optimized individually to each of the three representative samples. For sample preparation, different chromatographic techniques and materials were tested and different polymers and capillary lengths were investigated for final CGE-LIF analysis.
[1] Schwarzer, J.; E. Rapp; U. Reichl; Electrophoresis (2008) 29, 4203-4214.
[2] Ruhaak, L.R.; Hennig, R.; Huhn, C.; Borowiak, M.; Dolhain, R. J. E. M.; Deelder, A. M.; Rapp, E.; Wuhrer, M.; Journal of Proteome Research (2010) 9, 6655–6664.