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AutoCCS:用于离子淌度谱-质谱联用的自动碰撞截面计算软件。

AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry-mass spectrometry.

机构信息

Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA 99352, USA.

Department of Chemistry & Chemical Biology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA.

出版信息

Bioinformatics. 2021 Nov 18;37(22):4193-4201. doi: 10.1093/bioinformatics/btab429.

Abstract

MOTIVATION

Ion mobility spectrometry (IMS) separations are increasingly used in conjunction with mass spectrometry (MS) for separation and characterization of ionized molecular species. Information obtained from IMS measurements includes the ion's collision cross section (CCS), which reflects its size and structure and constitutes a descriptor for distinguishing similar species in mixtures that cannot be separated using conventional approaches. Incorporating CCS into MS-based workflows can improve the specificity and confidence of molecular identification. At present, there is no automated, open-source pipeline for determining CCS of analyte ions in both targeted and untargeted fashion, and intensive user-assisted processing with vendor software and manual evaluation is often required.

RESULTS

We present AutoCCS, an open-source software to rapidly determine CCS values from IMS-MS measurements. We conducted various IMS experiments in different formats to demonstrate the flexibility of AutoCCS for automated CCS calculation: (i) stepped-field methods for drift tube-based IMS (DTIMS), (ii) single-field methods for DTIMS (supporting two calibration methods: a standard and a new enhanced method) and (iii) linear calibration for Bruker timsTOF and non-linear calibration methods for traveling wave based-IMS in Waters Synapt and Structures for Lossless Ion Manipulations. We demonstrated that AutoCCS offers an accurate and reproducible determination of CCS for both standard and unknown analyte ions in various IMS-MS platforms, IMS-field methods, ionization modes and collision gases, without requiring manual processing.

AVAILABILITY AND IMPLEMENTATION

https://github.com/PNNL-Comp-Mass-Spec/AutoCCS.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online. Demo datasets are publicly available at MassIVE (Dataset ID: MSV000085979).

摘要

动机

离子迁移谱(IMS)分离越来越多地与质谱(MS)结合使用,用于分离和表征离子化分子物种。从 IMS 测量中获得的信息包括离子的碰撞截面(CCS),它反映了离子的大小和结构,并且是区分混合物中不能通过传统方法分离的相似物种的描述符。将 CCS 纳入基于 MS 的工作流程可以提高分子鉴定的特异性和置信度。目前,没有用于以靶向和非靶向方式确定分析物离子 CCS 的自动化、开源管道,并且通常需要用户密集型的供应商软件辅助处理和手动评估。

结果

我们提出了 AutoCCS,这是一种用于从 IMS-MS 测量中快速确定 CCS 值的开源软件。我们进行了各种不同格式的 IMS 实验,以展示 AutoCCS 用于自动化 CCS 计算的灵活性:(i)用于基于漂移管的 IMS(DTIMS)的分步场方法,(ii)用于 DTIMS 的单场方法(支持两种校准方法:标准和新增强方法)和(iii)用于 Bruker timsTOF 的线性校准和 Waters Synapt 和结构的基于行进波的 IMS 的非线性校准方法。我们证明了 AutoCCS 可用于在各种 IMS-MS 平台、IMS 场方法、电离模式和碰撞气体中对标准和未知分析物离子的 CCS 进行准确且可重现的测定,而无需手动处理。

可用性和实现

https://github.com/PNNL-Comp-Mass-Spec/AutoCCS。

补充信息

补充数据可在 Bioinformatics 在线获得。演示数据集可在 MassIVE(数据集 ID:MSV000085979)上公开获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5041/9502155/375661bfd1b9/btab429f1.jpg

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