Reference: Zhao Y, et al. (2014) Online two-dimensional porous graphitic carbon/reversed phase liquid chromatography platform applied to shotgun proteomics and glycoproteomics. Anal Chem 86(24):12172-9

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Abstract


A novel fully automatable two-dimensional liquid chromatography (2DLC) platform has been integrated into a modified commercial off-the-shelf LC instrument, incorporating porous graphitic carbon (PGC) separation and conventional low-pH reversed-phase (RP) separation for both proteomics and N-glycomics analyses; the dual-trap column configuration of this platform offers desirable high-throughput analyses with almost no idle time, in addition to a miniaturized setup and simplified operation. The total run time per analysis was only 19 h when using eight PGC fractions for unattended large-scale qualitative and quantitative proteomic analyses; the identification of 2678 nonredundant proteins and 11,984 unique peptides provided one of the most comprehensive proteome data sets for primary cerebellar granule neurons (CGNs). The effect of pH on the PGC column was investigated for the first time to improve the hydrophobic peptide coverage; the performance of the optimized system was first benchmarked using tryptic digests of Saccharomyces cerevisiae cell lysates and then evaluated through duplicate analyses of Macaca fascicularis cerebral cortex lysates using isobaric tags for relative and absolute quantitation (iTRAQ) technology. An additional plug-and-play PGC module functioned in a complementary manner to recover unretained hydrophilic solutes from the low-pH RP column; synchronization of the fractionations between the PGC-RP system and the PGC module facilitated simultaneous analyses of hydrophobic and hydrophilic compounds from a single sample injection event. This methodology was applied to perform, for the first time, detailed glycomics analyses of Macaca fascicularis plasma, resulting in the identification of a total 130 N-glycosylated plasma proteins, 705 N-glycopeptides, and 254 N-glycosylation sites.

Reference Type
Journal Article | Research Support, Non-U.S. Gov't
Authors
Zhao Y, Szeto SS, Kong RP, Law CH, Li G, Quan Q, Zhang Z, Wang Y, Chu IK
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