Bioinformatics Program, Center for Biomedical Mass Spectrometry, Department, of Biochemistry, Boston University, Boston, Massachusetts, USA.
PLoS One. 2012;7(9):e45474. doi: 10.1371/journal.pone.0045474. Epub 2012 Sep 26.
Glycosylation modifies the physicochemical properties and protein binding functions of glycoconjugates. These modifications are biosynthesized in the endoplasmic reticulum and Golgi apparatus by a series of enzymatic transformations that are under complex control. As a result, mature glycans on a given site are heterogeneous mixtures of glycoforms. This gives rise to a spectrum of adhesive properties that strongly influences interactions with binding partners and resultant biological effects. In order to understand the roles glycosylation plays in normal and disease processes, efficient structural analysis tools are necessary. In the field of glycomics, liquid chromatography/mass spectrometry (LC/MS) is used to profile the glycans present in a given sample. This technology enables comparison of glycan compositions and abundances among different biological samples, i.e. normal versus disease, normal versus mutant, etc. Manual analysis of the glycan profiling LC/MS data is extremely time-consuming and efficient software tools are needed to eliminate this bottleneck. In this work, we have developed a tool to computationally model LC/MS data to enable efficient profiling of glycans. Using LC/MS data deconvoluted by Decon2LS/DeconTools, we built a list of unique neutral masses corresponding to candidate glycan compositions summarized over their various charge states, adducts and range of elution times. Our work aims to provide confident identification of true compounds in complex data sets that are not amenable to manual interpretation. This capability is an essential part of glycomics work flows. We demonstrate this tool, GlycReSoft, using an LC/MS dataset on tissue derived heparan sulfate oligosaccharides. The software, code and a test data set are publically archived under an open source license.
糖基化修饰了糖缀合物的物理化学性质和蛋白结合功能。这些修饰是在内质网和高尔基体中通过一系列酶促转化生物合成的,这些转化受到复杂的控制。因此,给定部位的成熟聚糖是糖型的异质混合物。这导致了一系列的粘附特性,强烈影响与结合伴侣的相互作用和产生的生物学效应。为了了解糖基化在正常和疾病过程中所起的作用,需要有效的结构分析工具。在糖组学领域,液相色谱/质谱(LC/MS)用于分析给定样品中存在的聚糖。这项技术使我们能够比较不同生物样品中聚糖的组成和丰度,例如正常与疾病、正常与突变等。对糖谱 LC/MS 数据的手动分析极其耗时,因此需要有效的软件工具来消除这一瓶颈。在这项工作中,我们开发了一种工具,用于对 LC/MS 数据进行计算建模,以实现聚糖的高效分析。使用 Decon2LS/DeconTools 解卷积的 LC/MS 数据,我们构建了一个与候选糖组成相对应的独特中性质量列表,这些候选糖组成总结了它们各种电荷状态、加合物和洗脱时间范围。我们的工作旨在为复杂数据集(不适合手动解释)中真正化合物的可靠鉴定提供帮助。这种能力是糖组学工作流程的重要组成部分。我们使用组织来源的硫酸乙酰肝素寡糖的 LC/MS 数据集来演示这个工具 GlycReSoft。软件、代码和测试数据集以开源许可证公开发布。