交联质谱法用于捕捉细胞膜蛋白质组的蛋白质网络动态变化

Cross-Linking Mass Spectrometry to Capture Protein Network Dynamics of Cell Membranome.

作者信息

Santorelli Lucia, Costanzo Michele, Petrosino Sara, Santoro Michele, Caterino Marianna, Ruoppolo Margherita, Grumati Paolo

机构信息

Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Italy.

Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, Naples, Italy.

出版信息

Methods Mol Biol. 2025;2884:241-258. doi: 10.1007/978-1-0716-4298-6_16.

Abstract

Interactions among proteins are fundamental in driving functions and activities that regulate cell biology, mechanotransduction, and cell-to-cell communication/recognition. Recently, cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for interaction discovery and characterization, driving the enlightenment of novel binding partners otherwise undetected. Covalent linkages of two amino acid residues of proteins (or within complexes) in close proximity can be identified by MS, thus providing structural insights such as distance restraints or unraveling interaction dynamics.The XL-MS workflow described here is applied to map the plasma membrane protein (PMP) networks since they play important roles in the modulation of diverse molecular processes, including transport, signal transduction, endocytosis, and secretion. The strategy includes cross-linking of PMP-enriched fractions, label-free nanoLC-MS/MS, and bioinformatics data analysis. "Membranome" interconnections constitute around 30% of the mammalian proteome and 60% of all drug targets. Exploring such networks under different biological conditions is a promising and unbiased approach to depicting regulatory pathways that govern cell behavior.

摘要

蛋白质之间的相互作用对于驱动调节细胞生物学、机械转导以及细胞间通讯/识别的功能和活动至关重要。最近,交联质谱法(XL-MS)已成为一种用于发现和表征相互作用的强大工具,推动了对否则无法检测到的新型结合伙伴的认识。质谱可识别紧密相邻的蛋白质的两个氨基酸残基(或复合物内)的共价连接,从而提供诸如距离限制等结构见解或揭示相互作用动力学。此处描述的XL-MS工作流程用于绘制质膜蛋白(PMP)网络,因为它们在调节包括运输、信号转导、内吞作用和分泌在内的多种分子过程中发挥重要作用。该策略包括对富含PMP的组分进行交联、无标记的纳升液相色谱-串联质谱分析以及生物信息学数据分析。“膜蛋白质组”的相互连接约占哺乳动物蛋白质组的30%以及所有药物靶点的60%。在不同生物学条件下探索此类网络是描绘控制细胞行为的调节途径的一种有前景且无偏差的方法。

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