Issue 57, 2017, Issue in Progress

A facile method for cellular N-glycomic profiling by matrix-assisted laser desorption/ionization mass spectrometry

Abstract

Conventional protocols for cellular N-glycan profiling often need several time-consuming and labor-intensive steps, and a large amount of material (5–20 × 106 cells) is required. In this study, an optimized co-derivatization method was applied for convenient, rapid and highly-sensitive analysis of cellular N-glycan. Taking human cervical carcinoma cells (HeLa) as a model, the required amount for comprehensive cellular N-glycans analysis was reduced down to an original cell number of 105 and the total analysis time was decreased from several days to several hours. Good reproducibility of the method was also obtained with the CV averaging to less than 13.1%. In addition, compared to permethylation derivatization, more than 5-fold sensitivity improvement was achieved and more concise and clear mass spectra were obtained with the new developed method. As a preliminary study, this method was also successfully applied to reveal the difference in cellular N-glycan profiling of two heterogeneous live cell lines, human normal liver cells (L-02) and human hepatocyte carcinoma cells (HepG2), showing great potential for high-throughput analysis of N-glycans from limited cell samples, such as primary cell lines, cells obtained from cell sorting and small size cancer specimens.

Graphical abstract: A facile method for cellular N-glycomic profiling by matrix-assisted laser desorption/ionization mass spectrometry

Supplementary files

Article information

Article type
Paper
Submitted
31 May 2017
Accepted
12 Jul 2017
First published
20 Jul 2017
This article is Open Access
Creative Commons BY license

RSC Adv., 2017,7, 35687-35693

A facile method for cellular N-glycomic profiling by matrix-assisted laser desorption/ionization mass spectrometry

W. Gao, Y. Jiang, Z. Zhang, Y. Zhang, Y. Liu, Y. Zhou and X. Liu, RSC Adv., 2017, 7, 35687 DOI: 10.1039/C7RA06071H

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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