GAG-ID: Heparan Sulfate (HS) and Heparin Glycosaminoglycan High-Throughput Identification Software
GAG-ID: Heparan Sulfate (HS) and Heparin Glycosaminoglycan High-Throughput Identification Software
复制标题
DOI：
10.1074/mcp.m114.045856
复制
发表时间：
2015-06-01
影响因子：
7
通讯作者：
Sharp, Joshua S.
中科院分区：
文献类型：
--
作者：
Chiu, Yulun;Huang, Rongrong;Sharp, Joshua S.
肝素和硫酸乙酰肝素是非常大的线性多糖，其经历复杂的各种修饰，并且已知在人类发育、细胞-细胞通信和疾病中起重要作用。液相色谱-串联质谱法测定肝素和硫酸乙酰肝素等高硫酸化糖胺聚糖寡糖的序列由于在寡糖的复杂混合物中存在多种异构体序列，分离这些异构体的困难，以及MS/MS中硫酸盐的容易损失。我们以前介绍了一种肝素/硫酸乙酰肝素寡糖，涉及用稳定的乙酰基取代不稳定的硫酸酯的化学衍生。该化学衍生化方案允许使用反相LC进行高分辨率分离，并使用MS/MS对异构硫酸乙酰肝素寡糖进行测序。然而，由于肝素/HS寡糖的复杂混合物中存在大量分析物，因此所得LC-MS/MS数据集很大，并且由于专门设计的化学衍生化策略，无法使用现有糖组学软件进行注释。我们开发了一种称为GAG-ID的工具，用于基于修改后的多变量超几何分布来自动解释衍生化肝素/硫酸乙酰肝素LC-MS/MS数据，以加权更强峰的注释。在从21种合成硫酸乙酰肝素四糖的混合物收集的LC-MS/MS数据集上测试该软件。通过测试该系统的评分区分度，我们表明将峰分层为不同强度类别有利于评分区分度，并且GAG-ID能够从单个LC-MS/MS运行中正确分配定义混合物中的所有21种合成四糖。
Heparin and heparan sulfate are very large linear polysaccharides that undergo a complex variety of modifications and are known to play important roles in human development, cell-cell communication and disease. Sequencing of highly sulfated glycosaminoglycan oligosaccharides like heparin and heparan sulfate by liquid chromatography-tandem mass spectrometry (LC-MS/MS) remains challenging because of the presence of multiple isomeric sequences in a complex mixture of oligosaccharides, the difficulties in separation of these isomers, and the facile loss of sulfates in MS/MS. We have previously introduced a method for structural sequencing of heparin/heparan sulfate oligosaccharides involving chemical derivatizations that replace labile sulfates with stable acetyl groups. This chemical derivatization scheme allows the use of reversed phase LC for high-resolution separation and MS/MS for sequencing of isomeric heparan sulfate oligosaccharides. However, because of the large number of analytes present in complex mixtures of heparin/HS oligosaccharides, the resulting LC-MS/MS data sets are large and cannot be annotated with existing glycomics software because of the specifically designed chemical derivatization strategy. We have developed a tool, called GAG-ID, to automate the interpretation of derivatized heparin/heparan sulfate LC-MS/MS data based on a modified multivariate hypergeometric distribution to weight the annotation of more intense peaks. The software is tested on a LC-MS/MS data set collected from a mixture of 21 synthesized heparan sulfate tetrasaccharides. By testing the discrimination of scoring with this system, we show that stratifying peaks into different intensity classes benefits the discrimination of scoring, and GAG-ID is able to properly assign all 21 synthetic tetrasaccharides in a defined mixture from a single LC-MS/MS run.