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通过聚糖还原和同位素标记提供仿生糖组作为内标,实现基于 MALDI-MS 的可靠、简单的 N-糖组定量分析。

Providing Bionic Glycome as internal standards by glycan reducing and isotope labeling for reliable and simple quantitation of N-glycome based on MALDI- MS.

机构信息

NHC Key Laboratory of Glycoconjugates Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China.

Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200090, China.

出版信息

Anal Chim Acta. 2019 Nov 12;1081:112-119. doi: 10.1016/j.aca.2019.07.003. Epub 2019 Jul 3.

DOI:10.1016/j.aca.2019.07.003
PMID:31446948
Abstract

Accurate, simple and economical methods for quantifying N-glycans are continuously required for discovering disease biomarkers and quality control of biopharmaceuticals. Quantitative N-glycomics based on MS using exogenous isotopic labeling internal standards is promising as it is simple and accurate. However, it is largely hampered by the lack of available glycan internal standard libraries with good coverage of the natural glycan structural heterogeneity as well as broad dynamic mass and ion abundance range. To overcome this limitation, we developed a novel method, providing 'Bionic Glycome' as internal standards for glycan quantitation by MALDI-MS. Bionic Glycome was produced using N-glycome from pooled samples to be analyzed as substrate by one step of glycan reducing and isotope labeling (Glycan-RAIL). Each bionic glycan has 3 Da mass increment over its corresponding glycan analyte based on hemiacetals/alditols and H/D mass difference. In addition, Bionic Glycome has the same glycome composition and similar glycome profile in abundance with N-glycome to be analyzed from biological sample. Through the investigation of single glycan standard and complex glycans released from model glycoprotein and serum, the results demonstrate that the method has good quantitative accuracy and high reproducibility. Lastly, this method was successfully used for discovery of lung cancer specific glycan markers by comparing the serum glycans from each sample in lung cancer group (n = 16) and healthy controls (n = 16), indicating its potential in clinical applications.

摘要

为了发现疾病生物标志物和生物制药的质量控制,我们不断需要准确、简单和经济的方法来定量 N-聚糖。基于 MS 的定量 N-糖组学使用外源性同位素标记内标是有前途的,因为它简单且准确。然而,由于缺乏具有良好覆盖天然聚糖结构异质性以及广泛动态质量和离子丰度范围的可用聚糖内标库,它在很大程度上受到了阻碍。为了克服这一限制,我们开发了一种新方法,通过 MALDI-MS 提供“仿生糖组”作为聚糖定量的内标。仿生糖组是使用要分析的混合样品中的 N-糖组作为底物,通过一步聚糖还原和同位素标记(Glycan-RAIL)来制备的。每个仿生聚糖在基于半缩醛/醛醇和 H/D 质量差的情况下,相对于其相应的聚糖分析物具有 3 Da 的质量增量。此外,仿生糖组与要从生物样品中分析的 N-糖组具有相同的糖组组成和相似的糖组丰度分布。通过对单糖标准和模型糖蛋白和血清中释放的复杂聚糖的研究,结果表明该方法具有良好的定量准确性和高重现性。最后,通过比较肺癌组(n=16)和健康对照组(n=16)中每个样本的血清聚糖,该方法成功用于发现肺癌特异性聚糖标志物,表明其在临床应用中的潜力。

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