Application of network smoothing to glycan LC-MS profiling
Application of network smoothing to glycan LC-MS profiling
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DOI：
10.1093/bioinformatics/bty397
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发表时间：
2018-10-15
期刊：
影响因子：
5.8
通讯作者：
Zaia, Joseph
中科院分区：
文献类型：
--
作者：
Klein, Joshua;Carvalho, Luis;Zaia, Joseph
目的：糖基化是蛋白质翻译后修饰中最复杂、最不均一的修饰之一。液相色谱-质谱联用（LC-MS）是分析复杂生物样品的常用高通量方法。聚糖的精确研究需要高分辨率质谱。质谱数据包含编码质量和丰度的复杂子结构，在其可用于识别生物分子之前需要几次转换，需要自动化工具以高通量设置分析样品。现有的工具，用于解释所得到的数据不考虑相关的聚糖时，评估个别observations，限制其sensitivity.Results：我们开发了一种算法分配聚糖组合物从LC-MS数据，通过探索生物合成网络之间的关系聚糖。我们的算法优化了一组可能性评分函数的基础上聚糖的化学性质，但使用网络拉普拉斯正则化和可选的先验信息预期聚糖家庭平滑的可能性，从而实现一致的和更具代表性的解决方案。与以前的方法相比，我们的方法能够识别尽可能多或更多的聚糖组合物，并且证明了正则化的更高灵敏度。我们的网络定义是针对N-聚糖定制的，但是该方法可以应用于来自其他聚糖家族的糖组学数据，如O-聚糖或硫酸乙酰肝素，其中组成之间的关系可以表示为图。
Motivation: Glycosylation is one of the most heterogeneous and complex protein post-translational modifications. Liquid chromatography coupled mass spectrometry (LC-MS) is a common high throughput method for analyzing complex biological samples. Accurate study of glycans require high resolution mass spectrometry. Mass spectrometry data contains intricate substructures that encode mass and abundance, requiring several transformations before it can be used to identify biological molecules, requiring automated tools to analyze samples in a high throughput setting. Existing tools for interpreting the resulting data do not take into account related glycans when evaluating individual observations, limiting their sensitivity.Results: We developed an algorithm for assigning glycan compositions from LC-MS data by exploring biosynthetic network relationships among glycans. Our algorithm optimizes a set of likelihood scoring functions based on glycan chemical properties but uses network Laplacian regularization and optionally prior information about expected glycan families to smooth the likelihood and thus achieve a consistent and more representative solution. Our method was able to identify as many, or more glycan compositions compared to previous approaches, and demonstrated greater sensitivity with regularization. Our network definition was tailored to N-glycans but the method may be applied to glycomics data from other glycan families like O-glycans or heparan sulfate where the relationships between compositions can be expressed as a graph.