4.7 Article

Optimized Workflow for Preparation of APTS-Labeled N-Glycans Allowing High-Throughput Analysis of Human Plasma Glycomes using 48-Channel Multiplexed CGE-LIF

期刊

JOURNAL OF PROTEOME RESEARCH
卷 9, 期 12, 页码 6655-6664

出版社

AMER CHEMICAL SOC
DOI: 10.1021/pr100802f

关键词

glycan profiling; high throughput N-glycan analysis; CGE-LIF; APTS; HILIC-SPE; plasma

资金

  1. Max Planck Society [IGE05007]

向作者/读者索取更多资源

High throughput methods for oligosaccharide analysis are required when searching for glycan based biomarkers Next to mass spectrometry based methods which allow fast and reproducible analysis of such compounds further separation based techniques are needed which allow for quantitative analysis Here an optimized sample preparation method for N glycan profiling by multiplexed capillary gel electrophoresis with laser induced fluorescence detection (CGE LIF) was developed, enabling high throughput glycosylation analysis First, glycans are released enzymatically from denatured plasma glycoproteins Second, glycans are labeled with APTS using 2-picoline borane as a nontoxic and efficient reducing agent Reaction conditions are optimized for a high labeling efficiency short handling times and only limited loss of sialic acids Third samples are subjected to hydrophilic interaction chromatography (HILIC) purification at the 96 well plate format Subsequently, purified APTS labeled N glycans are analyzed by CGE LIF using a 48-capillary DNA sequencer The method was found to be robust and suitable for high-throughput glycan analysis Even though the method comprises two overnight incubations, 96 samples can be analyzed with an overall labor allocation time of 2 5 h The method was applied to serum samples from a pregnant woman, which were sampled during first second and third trimesters of pregnancy, as well as 6 weeks 3 months, and 6 months postpartum Alterations in the glycosylation patterns were observed with gestation and time after delivery

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据