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提高氢氘交换数据分析中谱图验证率。

Improving Spectral Validation Rates in Hydrogen-Deuterium Exchange Data Analysis.

机构信息

Department of Chemistry, University of Calgary, Calgary, Alberta, Canada T2N-4N1.

Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Alberta, Canada T2N-4N1.

出版信息

Anal Chem. 2021 Mar 9;93(9):4246-4254. doi: 10.1021/acs.analchem.0c05045. Epub 2021 Feb 16.

Abstract

The data analysis practices associated with hydrogen-deuterium exchange mass spectrometry (HX-MS) lag far behind that of most other MS-based protein analysis tools. A reliance on external tools from other fields and a persistent need for manual data validation restrict this powerful technology to the expert user. Here, we provide an extensive upgrade to the HX data analysis suite available in the Mass Spec Studio in the form of two new apps (HX-PIPE and HX-DEAL), completing a workflow that provides an HX-tailored peptide identification capability, accelerated validation routines, automated spectral deconvolution strategies, and a rich set of exportable graphics and statistical reports. With these new tools, we demonstrate that the peptide identifications obtained from undeuterated samples generated at the start of a project contain information that helps predict and control the extent of manual validation required. We also uncover a large fraction of HX-usable peptides that remains unidentified in most experiments. We show that automated spectral deconvolution routines can identify exchange regimes in a project-wide manner, although they remain difficult to accurately assign in all scenarios. Taken together, these new tools provide a robust and complete solution suitable for the analysis of high-complexity HX-MS data.

摘要

与氢氘交换质谱(HX-MS)相关的数据分析实践远远落后于大多数其他基于 MS 的蛋白质分析工具。对其他领域外部工具的依赖以及对人工数据验证的持续需求,将这项强大的技术限制在专家用户手中。在这里,我们通过两个新应用程序(HX-PIPE 和 HX-DEAL)为 Mass Spec Studio 中提供的 HX 数据分析套件提供了广泛的升级,完成了一个工作流程,该流程提供了针对 HX 的肽鉴定能力、加速验证例程、自动化光谱分解策略以及一系列丰富的可导出图形和统计报告。有了这些新工具,我们证明了从项目开始时生成的未氘化样品中获得的肽鉴定包含有助于预测和控制所需人工验证程度的信息。我们还发现了大多数实验中仍未鉴定出的大量 HX 可使用肽。我们表明,自动化光谱分解例程可以以项目范围的方式识别交换区,但在所有情况下,它们仍然难以准确分配。总之,这些新工具提供了一个强大而完整的解决方案,适用于高复杂度 HX-MS 数据的分析。

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