Department of Chemistry, Ralph N. Adams Institute for Bioanalytical Chemistry, University of Kansas, Lawrence, Kanas, USA.
Mass Spectrom Rev. 2022 Nov;41(6):901-921. doi: 10.1002/mas.21688. Epub 2021 Feb 10.
Glycans introduce complexity to the proteins to which they are attached. These modifications vary during the progression of many diseases; thus, they serve as potential biomarkers for disease diagnosis and prognosis. The immense structural diversity of glycans makes glycosylation analysis and quantitation difficult. Fortunately, recent advances in analytical techniques provide the opportunity to quantify even low-abundant glycopeptides and glycans derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Understanding the strengths and weaknesses of different quantitative glycomics analysis methods is important for selecting the best strategy to analyze glycosylation changes in any given set of clinical samples. To provide guidance towards selecting the proper approach, we discuss four widely used quantitative glycomics analysis platforms, including fluorescence-based analysis of released N-linked glycans and three different varieties of MS-based analysis: liquid chromatography (LC)-mass spectrometry (MS) analysis of glycopeptides, matrix-assisted laser desorption ionization-time of flight MS, and LC-ESI-MS analysis of released N-linked glycans. These methods' strengths and weaknesses are compared, particularly associated with the figures of merit that are important for clinical biomarker studies, including: the initial sample requirements, the methods' throughput, sample preparation time, the number of species identified, the methods' utility for isomer separation and structural characterization, method-related challenges associated with quantitation, repeatability, the expertise required, and the cost for each analysis. This review, therefore, provides unique guidance to researchers who endeavor to undertake a clinical glycomics analysis by offering insights on the available analysis technologies.
聚糖为其连接的蛋白质带来复杂性。这些修饰在许多疾病的进展过程中发生变化;因此,它们可作为疾病诊断和预后的潜在生物标志物。聚糖具有巨大的结构多样性,使得糖基化分析和定量变得困难。幸运的是,分析技术的最新进展为定量分析来自复杂生物混合物的低丰度糖肽和聚糖提供了机会,从而能够识别健康样本和来自疾病状态的样本之间的糖基化差异。了解不同定量糖组学分析方法的优缺点对于选择分析任何给定临床样本中糖基化变化的最佳策略非常重要。为了提供选择适当方法的指导,我们讨论了四种广泛使用的定量糖组学分析平台,包括释放的 N-连接聚糖的荧光分析和三种不同类型的基于 MS 的分析:糖肽的 LC-MS 分析、基质辅助激光解吸电离飞行时间 MS 和 LC-ESI-MS 分析释放的 N-连接聚糖。比较了这些方法的优缺点,特别是与对临床生物标志物研究很重要的衡量标准有关,包括:初始样品要求、方法的通量、样品制备时间、鉴定的物种数量、方法对异构体分离和结构表征的实用性、与定量相关的方法挑战、重复性、所需的专业知识以及每次分析的成本。因此,通过提供有关可用分析技术的见解,本综述为努力进行临床糖组学分析的研究人员提供了独特的指导。