PhoXplex:将富含磷酸的交联与等位标记相结合,定量绘制蛋白质组范围内的蛋白质界面图谱

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-10-18 DOI:10.1021/acs.jproteome.4c0056710.1021/acs.jproteome.4c00567
Runa D. Hoenger Ramazanova, Theodoros I. Roumeliotis*, James C. Wright and Jyoti S. Choudhary*, 
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引用次数: 0

摘要

将交联质谱(XL-MS)整合到结构生物学工作流程中,可提供有关氨基酸序列空间排列的宝贵信息,从而指导蛋白质组装结构的阐明。此外,XL-MS 与肽定量技术的结合是一种强大的方法,可用于描述不同条件下蛋白质界面的动态变化。虽然 XL-MS 对分离蛋白质或小型复合物越来越有效,但它在全细胞样本中的应用却面临着与分析深度和通量有关的技术挑战。可富集交联剂的使用大大提高了整个蛋白质组范围内蛋白质界面的可检测性,促进了全球蛋白质-蛋白质相互作用图谱的绘制。因此,将富集交联和多肽定量结合起来,是实现蛋白质结构属性和蛋白质相互作用比较表征的一种有吸引力的方法。在这里,我们将富集磷酸交联与 TMT 标记结合起来,开发出一种简化的工作流程(PhoXplex),用于在全球范围内检测不同细胞系的不同结构特征。我们实现了深度覆盖,共量化了 9000 多个交联和长环连接,包括潜在的新型相互作用。通过叠加 AlphaFold 预测和无序蛋白质注释,可以探索定量交联数据集,揭示突变与蛋白质结构之间可能存在的关联。最后,我们讨论了大规模全细胞蛋白质界面深度剖析目前存在的不足和前景。
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PhoXplex: Combining Phospho-enrichable Cross-Linking with Isobaric Labeling for Quantitative Proteome-Wide Mapping of Protein Interfaces

Integrating cross-linking mass spectrometry (XL-MS) into structural biology workflows provides valuable information about the spatial arrangement of amino acid stretches, which can guide elucidation of protein assembly architecture. Additionally, the combination of XL-MS with peptide quantitation techniques is a powerful approach to delineate protein interface dynamics across diverse conditions. While XL-MS is increasingly effective with isolated proteins or small complexes, its application to whole-cell samples poses technical challenges related to analysis depth and throughput. The use of enrichable cross-linkers has greatly improved the detectability of protein interfaces in a proteome-wide scale, facilitating global protein–protein interaction mapping. Therefore, bringing together enrichable cross-linking and multiplexed peptide quantification is an appealing approach to enable comparative characterization of structural attributes of proteins and protein interactions. Here, we combined phospho-enrichable cross-linking with TMT labeling to develop a streamline workflow (PhoXplex) for the detection of differential structural features across a panel of cell lines in a global scale. We achieved deep coverage with quantification of over 9000 cross-links and long loop-links in total including potentially novel interactions. Overlaying AlphaFold predictions and disorder protein annotations enables exploration of the quantitative cross-linking data set, to reveal possible associations between mutations and protein structures. Lastly, we discuss current shortcomings and perspectives for deep whole-cell profiling of protein interfaces at large-scale.

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4.30%
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