Department of Microchemistry, Proteomics and Lipidomics , Genentech , South San Francisco , California 94080 , United States.
Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States.
J Proteome Res. 2019 Feb 1;18(2):594-605. doi: 10.1021/acs.jproteome.8b00767. Epub 2018 Dec 12.
Triggered by Offset, Multiplexed, Accurate mass, High resolution, and Absolute Quantitation (TOMAHAQ) is a recently introduced targeted proteomics method that combines peptide and sample multiplexing. TOMAHAQ assays enable sensitive and accurate multiplexed quantification by implementing an intricate data collection scheme that comprises multiple MS scans, mass inclusion lists, and data-driven filters. Consequently, manual creation of TOMAHAQ methods can be time-consuming and error prone, while the resulting TOMAHAQ data may not be compatible with common mass spectrometry analysis pipelines. To address these concerns we introduce TomahaqCompanion, an open-source desktop application that enables rapid creation of TOMAHAQ methods and analysis of TOMAHAQ data. Starting from a list of peptide sequences, a user can perform each step of TOMAHAQ assay development including (1) generation of priming run target list, (2) analysis of priming run data, (3) generation of TOMAHAQ method file, and (4) analysis and export of quantitative TOMAHAQ data. We demonstrate the flexibility of TomahaqCompanion by creating a variety of methods testing TOMAHAQ parameters (e.g., number of SPS notches, run length, etc.). Lastly, we analyze an interference sample comprising heavy yeast peptides, a standard human peptide mixture, TMT11-plex, and super heavy TMT (shTMT) isobaric labels to demonstrate ∼10-200 attomol limit of quantification within a complex background using TOMAHAQ.
触发偏移、多重、精确质量、高分辨率和绝对定量(TOMAHAQ)是一种新引入的靶向蛋白质组学方法,它结合了肽和样品的多重化。TOMAHAQ 分析通过实施复杂的数据采集方案来实现灵敏且准确的多重定量,该方案包括多个 MS 扫描、质量包含列表和数据驱动的过滤器。因此,手动创建 TOMAHAQ 方法可能既耗时又容易出错,而生成的 TOMAHAQ 数据可能与常见的质谱分析管道不兼容。为了解决这些问题,我们引入了 TomahaqCompanion,这是一个开源的桌面应用程序,可实现快速创建 TOMAHAQ 方法和分析 TOMAHAQ 数据。从肽序列列表开始,用户可以执行 TOMAHAQ 分析开发的每个步骤,包括 (1) 生成起始运行目标列表,(2) 分析起始运行数据,(3) 生成 TOMAHAQ 方法文件,以及 (4) 分析和导出定量 TOMAHAQ 数据。我们通过创建各种测试 TOMAHAQ 参数的方法(例如,SPS 缺口数量、运行长度等)来展示 TomahaqCompanion 的灵活性。最后,我们分析了一个包含重酵母肽、标准人肽混合物、TMT11-多重和超重 TMT(shTMT)等内标的干扰样品,证明在复杂背景下使用 TOMAHAQ 可实现约 10-200 attomol 的定量下限。