Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States.
School of Medicine, University of Michigan, Ann Arbor, Michigan 48109, United States.
J Am Soc Mass Spectrom. 2024 Aug 7;35(8):1865-1874. doi: 10.1021/jasms.4c00176. Epub 2024 Jul 5.
Ion mobility-mass spectrometry (IM-MS) has become a technology deployed across a wide range of structural biology applications despite the challenges in characterizing closely related protein structures. Collision-induced unfolding (CIU) has emerged as a valuable technique for distinguishing closely related, iso-cross-sectional protein and protein complex ions through their distinct unfolding pathways in the gas phase. With the speed and sensitivity of CIU analyses, there has been a rapid growth of CIU-based assays, especially regarding biomolecular targets that remain challenging to assess and characterize with other structural biology tools. With information-rich CIU data, many software tools have been developed to automate laborious data analysis. However, with the recent development of new IM-MS technologies, such as cyclic IM-MS, CIU continues to evolve, necessitating improved data analysis tools to keep pace with new technologies and facilitating the automation of various data processing tasks. Here, we present CIUSuite 3, a software package that contains updated algorithms that support various IM-MS platforms and supports the automation of various data analysis tasks such as peak detection, multidimensional classification, and collision cross section (CCS) calibration. CIUSuite 3 uses local maxima searches along with peak width and prominence filters to detect peaks to automate CIU data extraction. To support both the primary CIU (CIU) and secondary CIU (CIU) experiments enabled by cyclic IM-MS, two-dimensional data preprocessing is deployed, which allows multidimensional classification. Our data suggest that additional dimensions in classification improve the overall accuracy of class assignments. CIUSuite 3 also supports CCS calibration for both traveling wave and drift tube IM-MS, and we demonstrate the accuracy of a new single-field CCS calibration method designed for drift tube IM-MS leveraging calibrant CIU data. Overall, CIUSuite 3 is positioned to support current and next-generation IM-MS and CIU assay development deployed in an automated format.
离子淌度-质谱（IM-MS）已成为一种在广泛的结构生物学应用中部署的技术，尽管在表征密切相关的蛋白质结构方面存在挑战。碰撞诱导解折叠（CIU）已成为一种有价值的技术，可以通过其在气相中的独特解折叠途径来区分密切相关的等横截面积的蛋白质和蛋白质复合物离子。由于 CIU 分析的速度和灵敏度，基于 CIU 的分析方法迅速发展，特别是对于其他结构生物学工具仍然难以评估和表征的生物分子靶标。利用信息丰富的 CIU 数据，已经开发了许多软件工具来自动执行繁琐的数据分析。然而，随着新型 IM-MS 技术（如循环 IM-MS）的最新发展，CIU 不断发展，需要改进数据分析工具以跟上新技术的步伐，并促进各种数据处理任务的自动化。在这里，我们介绍了 CIUSuite 3，这是一个软件包，其中包含了更新的算法，支持各种 IM-MS 平台，并支持各种数据分析任务的自动化，如峰检测、多维分类和碰撞截面（CCS）校准。CIUSuite 3 使用局部最大值搜索以及峰宽和突出度滤波器来检测峰，以实现 CIU 数据的自动提取。为了支持循环 IM-MS 启用的主要 CIU（CIU）和次要 CIU（CIU）实验，部署了二维数据预处理，允许多维分类。我们的数据表明，分类中的附加维度可以提高分类任务的整体准确性。CIUSuite 3 还支持 traveling wave 和 drift tube IM-MS 的 CCS 校准，我们展示了一种新的单场 CCS 校准方法的准确性，该方法是为 drift tube IM-MS 设计的，利用校准 CIU 数据。总体而言，CIUSuite 3 定位于以自动化格式支持当前和下一代 IM-MS 和 CIU 分析方法的开发。
