The Role of Data-Independent Acquisition for Glycoproteomics.
The Role of Data-Independent Acquisition for Glycoproteomics.
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DOI：
10.1074/mcp.r120.002204
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Vakhrushev SY
中科院分区：
文献类型：
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作者：
Ye Z;Vakhrushev SY
数据独立采集（DIA）是自下而上蛋白质组学中的一种新兴方法，能够实现蛋白质组的深度覆盖和精确的无标记定量。然而，对于翻译后修饰，如糖基化，DIA方法仍处于早期发展阶段。糖蛋白的完整表征需要位点特异性聚糖鉴定以及每个位点的聚糖结构的后续定量。糖基化的巨大复杂性代表了糖蛋白质组学中的重大分析挑战。本文综述了DIA方法在N-和O-连接糖蛋白组学中的发展和前景，并认为基于DIA的糖蛋白组学可能是解决糖蛋白组学中一些具有挑战性的方面的首选方法。首先，简要介绍了糖蛋白质组学的研究现状和DIA的基本原理。结合实际样品，从四个方面对基于DIA的糖蛋白质组学进行了总结和描述。最后，我们讨论了该领域的重要挑战和未来前景。我们相信，DIA可以显着促进糖蛋白质组学研究，并有助于在糖蛋白质组学领域的未来先进的工具和方法的发展。糖蛋白质组学中的蛋白质糖基化和挑战。去糖基化和完整N-连接糖肽的数据独立采集。从所有糖肽前体中无偏筛选氧鎓离子。对粘蛋白型O-糖肽的糖数据独立采集。蛋白质糖基化作为一种高度丰富和多样的翻译后修饰，在包括质谱在内的各种方法中具有很大的挑战性。在基于质谱的蛋白质组学中，数据独立获取（data-independent acquisition，DIA）技术得到了迅速发展，并显示出优异的分析性能。DIA现在开始应用于糖蛋白质组学的不同方面，包括去糖基化和完整的N-连接和O-连接糖肽，以及氧离子的筛选。本文综述了DIA在糖蛋白质组学研究中的应用现状，并对其局限性和发展前景进行了讨论。
Data-independent acquisition (DIA) is now an emerging method in bottom–up proteomics and capable of achieving deep proteome coverage and accurate label-free quantification. However, for post-translational modifications, such as glycosylation, DIA methodology is still in the early stage of development. The full characterization of glycoproteins requires site-specific glycan identification as well as subsequent quantification of glycan structures at each site. The tremendous complexity of glycosylation represents a significant analytical challenge in glycoproteomics. This review focuses on the development and perspectives of DIA methodology for N- and O-linked glycoproteomics and posits that DIA-based glycoproteomics could be a method of choice to address some of the challenging aspects of glycoproteomics. First, the current challenges in glycoproteomics and the basic principles of DIA are briefly introduced. DIA-based glycoproteomics is then summarized and described into four aspects based on the actual samples. Finally, we discussed the important challenges and future perspectives in the field. We believe that DIA can significantly facilitate glycoproteomic studies and contribute to the development of future advanced tools and approaches in the field of glycoproteomics. Protein glycosylation and challenges in glycoproteomics. Data-independent acquisition for deglycosylated and intact N-linked glycopeptides. Unbiased screening of oxonium ions from all glycopeptide precursors. Glyco–data-independent acquisition on mucin-type O-glycopeptides. As a highly abundant and diverse post-translational modification, protein glycosylation is challenging to characterize in various approaches including MS. In MS-based proteomics, data-independent acquisition (DIA) has been advanced rapidly and showed outstanding analytical performances. DIA now started to be applied in different facets of glycoproteomics, including deglycosylated and intact N-linked and O-linked glycopeptides, and screening of oxonium ions. We summarized current applications of DIA in glycoproteomics and discussed its limitations and perspectives.