Xu Guang, Stupak Jacek, Yang Li, Hu Luokai, Guo Bo, Li Jianjun
Hubei Education Cloud Service Engineering Technology Research Center, Hubei University of Education, Wuhan, 430205, China.
Human Health Therapeutics, National Research Council Canada, Ottawa, Ontario, Canada, K1A 0R6.
Rapid Commun Mass Spectrom. 2018 May 30;32(10):763-774. doi: 10.1002/rcm.8103.
Mass spectrometry (MS) has played a vital role across a broad range of fields and applications in proteomics. The development of high-resolution MS has significantly advanced biology in areas such as protein structure, function, post-translational modification and global protein dynamics. The two most widely used MS ionization techniques in proteomics are electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI). ESI typically yields multiple charge values for each molecular mass and an isotopic cluster for each nominal mass-to-charge (m/z) value. Although MALDI mass spectra typically contain only singly charged ions, overlapping isotope patterns can be problematic for accurate mass measurement. To overcome these challenges of overlapping isotope patterns associated with complex samples in MS-based proteomics research, deconvolution strategies are being used. This manuscript describes a wide variety of deconvolution strategies, including de-isotoping and de-charging processes, deconvolution of co-eluting isomers or peptides with different sequences in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes, and data analysis in intact protein mass determination, ion mobility MS, native MS, and hydrogen/deuterium exchange MS. It concludes with a discussion of future prospects in the development of bioinformatics and potential new applications in proteomics.
质谱(MS)在蛋白质组学的广泛领域和应用中发挥了至关重要的作用。高分辨率质谱的发展在蛋白质结构、功能、翻译后修饰和整体蛋白质动力学等领域极大地推动了生物学的进步。蛋白质组学中两种应用最广泛的质谱电离技术是电喷雾电离(ESI)和基质辅助激光解吸/电离(MALDI)。ESI通常会为每个分子量产生多个电荷值,并为每个标称质荷比(m/z)值产生一个同位素簇。虽然MALDI质谱通常只包含单电荷离子,但重叠的同位素模式可能会给精确质量测量带来问题。为了克服基于质谱的蛋白质组学研究中与复杂样品相关的重叠同位素模式的这些挑战,正在使用去卷积策略。本文描述了各种各样的去卷积策略,包括去同位素和去电荷过程、在数据依赖采集(DDA)和数据独立采集(DIA)模式下对共洗脱异构体或不同序列肽段的去卷积,以及完整蛋白质质量测定、离子淌度质谱、天然质谱和氢/氘交换质谱中的数据分析。文章最后讨论了生物信息学发展的未来前景以及蛋白质组学中潜在的新应用。