Ting Ying S, Egertson Jarrett D, Bollinger James G, Searle Brian C, Payne Samuel H, Noble William Stafford, MacCoss Michael J
Department of Genome Sciences, University of Washington, Seattle, Washington, USA.
Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA.
Nat Methods. 2017 Sep;14(9):903-908. doi: 10.1038/nmeth.4390. Epub 2017 Aug 7.
Data-independent acquisition (DIA) is an emerging mass spectrometry (MS)-based technique for unbiased and reproducible measurement of protein mixtures. DIA tandem mass spectrometry spectra are often highly multiplexed, containing product ions from multiple cofragmenting precursors. Detecting peptides directly from DIA data is therefore challenging; most DIA data analyses require spectral libraries. Here we present PECAN (http://pecan.maccosslab.org), a library-free, peptide-centric tool that robustly and accurately detects peptides directly from DIA data. PECAN reports evidence of detection based on product ion scoring, which enables detection of low-abundance analytes with poor precursor ion signal. We demonstrate the chromatographic peak picking accuracy and peptide detection capability of PECAN, and we further validate its detection with data-dependent acquisition and targeted analyses. Lastly, we used PECAN to build a plasma proteome library from DIA data and to query known sequence variants.
数据非依赖型采集(DIA)是一种新兴的基于质谱(MS)的技术,用于对蛋白质混合物进行无偏且可重复的测量。DIA串联质谱谱图通常具有高度的多重性,包含来自多个共碎裂前体的产物离子。因此,直接从DIA数据中检测肽段具有挑战性;大多数DIA数据分析需要光谱库。在此,我们介绍了PECAN(http://pecan.maccosslab.org),这是一种无需库的、以肽段为中心的工具,能够直接从DIA数据中可靠且准确地检测肽段。PECAN基于产物离子评分报告检测证据,这使得能够检测前体离子信号较弱的低丰度分析物。我们展示了PECAN的色谱峰挑选准确性和肽段检测能力,并通过数据依赖型采集和靶向分析进一步验证了其检测结果。最后,我们使用PECAN从DIA数据构建了血浆蛋白质组库,并查询已知的序列变体。