Department of Chemistry and Molecular Biosciences, the Chemistry of Life Processes Institute, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois, USA.
Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, USA.
Electrophoresis. 2021 May;42(9-10):1050-1059. doi: 10.1002/elps.202000317. Epub 2021 Jan 27.
Native mass spectrometry (nMS) is a rapidly growing method for the characterization of large proteins and protein complexes, preserving "native" non-covalent inter- and intramolecular interactions. Direct infusion of purified analytes into a mass spectrometer represents the standard approach for conducting nMS experiments. Alternatively, CZE can be performed under native conditions, providing high separation performance while consuming trace amounts of sample material. Here, we provide standard operating procedures for acquiring high-quality data using CZE in native mode coupled online to various Orbitrap mass spectrometers via a commercial sheathless interface, covering a wide range of analytes from 30-800 kDa. Using a standard protein mix, the influence of various CZE method parameters were evaluated, such as BGE/conductive liquid composition and separation voltage. Additionally, a universal approach for the optimization of fragmentation settings in the context of protein subunit and metalloenzyme characterization is discussed in detail for model analytes. A short section is dedicated to troubleshooting of the nCZE-MS setup. This study is aimed to help normalize nCZE-MS practices to enhance the CE community and provide a resource for the production of reproducible and high-quality data.
天然质谱法(nMS)是一种快速发展的方法,用于表征大型蛋白质和蛋白质复合物,保留“天然”的非共价相互作用和分子内相互作用。将纯化的分析物直接注入质谱仪是进行 nMS 实验的标准方法。或者,可以在天然条件下进行 CZE,在消耗微量样品材料的同时提供高分离性能。在这里,我们提供了使用通过商业无鞘接口在线连接到各种轨道阱质谱仪的天然模式下的 CZE 获取高质量数据的标准操作程序,涵盖了从 30-800 kDa 的各种分析物。使用标准蛋白质混合物,评估了各种 CZE 方法参数的影响,例如 BGE/导电液体组成和分离电压。此外,还详细讨论了针对模型分析物的蛋白质亚基和金属酶表征中碎片设置优化的通用方法。本文的一小部分专门用于解决 nCZE-MS 装置的故障排除问题。本研究旨在帮助标准化 nCZE-MS 实践,以增强 CE 社区,并为生产可重复和高质量的数据提供资源。