De novo glycan sequencing by electronic excitation dissociation MS2-guided MS3 analysis on an Omnitrap-Orbitrap hybrid instrument

在 Omnitrap-Orbitrap 混合仪器上通过电子激发解离 MS2 引导 MS3 分析进行从头糖基测序

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作者:Juan Wei, Dimitris Papanastasiou, Mariangela Kosmopoulou, Athanasios Smyrnakis, Pengyu Hong, Nafisa Tursumamat, Joshua A Klein, Chaoshuang Xia, Yang Tang, Joseph Zaia, Catherine E Costello, Cheng Lin

Abstract

Comprehensive de novo glycan sequencing remains an elusive goal due to the structural diversity and complexity of glycans. Present strategies employing collision-induced dissociation (CID) and higher energy collisional dissociation (HCD)-based multi-stage tandem mass spectrometry (MSn) or MS/MS combined with sequential exoglycosidase digestions are inherently low-throughput and difficult to automate. Compared to CID and HCD, electron transfer dissociation (ETD) and electron capture dissociation (ECD) each generate more cross-ring cleavages informative about linkage positions, but electronic excitation dissociation (EED) exceeds the information content of all other methods and is also applicable to analysis of singly charged precursors. Although EED can provide extensive glycan structural information in a single stage of MS/MS, its performance has largely been limited to FTICR MS, and thus it has not been widely adopted by the glycoscience research community. Here, the effective performance of EED MS/MS was demonstrated on a hybrid Orbitrap-Omnitrap QE-HF instrument, with high sensitivity, fragmentation efficiency, and analysis speed. In addition, a novel EED MS2-guided MS3 approach was developed for detailed glycan structural analysis. Automated topology reconstruction from MS2 and MS3 spectra could be achieved with a modified GlycoDeNovo software. We showed that the topology and linkage configurations of the Man9GlcNAc2 glycan can be accurately determined from first principles based on one EED MS2 and two CID-EED MS3 analyses, without reliance on biological knowledge, a structure database or a spectral library. The presented approach holds great promise for autonomous, comprehensive and de novo glycan sequencing.

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