Chau The Huong, Chernykh Anastasia, Kawahara Rebeca, Thaysen-Andersen Morten
School of Natural Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, Australia.
School of Natural Sciences, Faculty of Science and Engineering, Macquarie University, Sydney, Australia; Biomolecular Discovery Research Centre, Macquarie University, Sydney, Australia; Institute for Glyco-core Research (iGCORE), Nagoya University, Nagoya, Japan.
Curr Opin Chem Biol. 2023 Apr;73:102272. doi: 10.1016/j.cbpa.2023.102272. Epub 2023 Feb 7.
N-Glycoproteomics, the system-wide study of glycans asparagine-linked to protein carriers, holds a unique and still largely untapped potential to provide deep insights into the complexity and dynamics of the heterogeneous N-glycoproteome. Despite the advent of innovative analytical and informatics tools aiding the analysis, N-glycoproteomics remains challenging and consequently largely restricted to specialised laboratories. Aiming to stimulate discussions of method harmonisation, data standardisation and reporting guidelines to make N-glycoproteomics more reproducible and accessible to the community, we here discuss critical considerations related to the design and execution of N-glycoproteomics experiments and highlight good practices in N-glycopeptide data collection, analysis, interpretation and sharing. Giving the rapid maturation and, expectedly, a wide-spread implementation of N-glycoproteomics capabilities across the community in future years, this piece aims to point out common pitfalls, to encourage good data sharing and documentation practices, and to highlight practical solutions and strategies to enhance the insight into the N-glycoproteome.
N-糖蛋白质组学是对与蛋白质载体相连的天冬酰胺聚糖进行的全系统研究,在深入洞察异质N-糖蛋白质组的复杂性和动态性方面具有独特且尚未充分挖掘的潜力。尽管出现了有助于分析的创新分析和信息学工具,但N-糖蛋白质组学仍然具有挑战性,因此在很大程度上仅限于专业实验室。为了推动关于方法协调、数据标准化和报告指南的讨论,以使N-糖蛋白质组学更具可重复性并为科学界所接受,我们在此讨论与N-糖蛋白质组学实验设计和实施相关的关键考虑因素,并强调N-糖肽数据收集、分析、解释和共享方面的良好实践。鉴于未来几年N-糖蛋白质组学能力在整个科学界的迅速成熟以及预期的广泛应用,本文旨在指出常见的陷阱,鼓励良好的数据共享和记录实践,并突出增强对N-糖蛋白质组理解的实际解决方案和策略。