Keller Andrew, Bader Samuel L, Shteynberg David, Hood Leroy, Moritz Robert L
From the Institute for Systems Biology, Seattle, Washington 98109.
From the Institute for Systems Biology, Seattle, Washington 98109
Mol Cell Proteomics. 2015 May;14(5):1411-8. doi: 10.1074/mcp.O114.044917. Epub 2015 Feb 24.
Proteomics by mass spectrometry technology is widely used for identifying and quantifying peptides and proteins. The breadth and sensitivity of peptide detection have been advanced by the advent of data-independent acquisition mass spectrometry. Analysis of such data, however, is challenging due to the complexity of fragment ion spectra that have contributions from multiple co-eluting precursor ions. We present SWATHProphet software that identifies and quantifies peptide fragment ion traces in data-independent acquisition data, provides accurate probabilities to ensure results are correct, and automatically detects and removes contributions to quantitation originating from interfering precursor ions. Integration in the widely used open source Trans-Proteomic Pipeline facilitates subsequent analyses such as combining results of multiple data sets together for improved discrimination using iProphet and inferring sample proteins using ProteinProphet. This novel development should greatly help make data-independent acquisition mass spectrometry accessible to large numbers of users.
基于质谱技术的蛋白质组学被广泛用于肽和蛋白质的鉴定与定量。数据非依赖型采集质谱技术的出现提高了肽检测的广度和灵敏度。然而,由于碎片离子谱的复杂性(其来自多个共洗脱前体离子),对此类数据的分析具有挑战性。我们展示了SWATHProphet软件,它可在数据非依赖型采集数据中识别和定量肽碎片离子轨迹,提供准确概率以确保结果正确,并自动检测和去除干扰前体离子对定量的贡献。集成到广泛使用的开源跨蛋白质组学管道中有助于后续分析,例如使用iProphet将多个数据集的结果组合在一起以提高鉴别能力,以及使用ProteinProphet推断样品蛋白质。这一新颖的进展应极大地有助于使大量用户能够使用数据非依赖型采集质谱技术。