Wu Jemma X, Pascovici Dana, Ignjatovic Vera, Song Xiaomin, Krisp Christoph, Molloy Mark P
Australian Proteome Analysis Facility (APAF), Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, Australia.
Hematology Research Laboratory, Murdoch Children's Research Institute, Melbourne, Australia.
Proteomics. 2017 Oct;17(19). doi: 10.1002/pmic.201700174.
Protein quantification using data-independent acquisition methods such as SWATH-MS most commonly relies on spectral matching to a reference MS/MS assay library. To enable deep proteome coverage and efficient use of existing data, in silico approaches have been described to use archived or publicly available large reference spectral libraries for spectral matching. Since implicit in the use of larger libraries is the increasing likelihood of false-discoveries, new workflows are needed to ensure high confidence in protein matching under these conditions. We present a workflow which introduces a range of filters and thresholds aimed at increasing confidence that the resulting proteins are reliably detected and their quantitation is consistent and reproducible. We demonstrated the workflow using extended libraries with SWATH data from human plasma samples and yeast-spiked human K562 cell lysate digest.
使用数据非依赖型采集方法（如SWATH-MS）进行蛋白质定量，最常见的是依赖与参考MS/MS分析文库的谱图匹配。为了实现深度蛋白质组覆盖并有效利用现有数据，已有研究描述了利用存档或公开可用的大型参考谱图库进行谱图匹配的计算机模拟方法。由于使用更大的文库意味着出现错误发现的可能性增加，因此需要新的工作流程来确保在这些条件下蛋白质匹配具有高可信度。我们提出了一种工作流程，该流程引入了一系列过滤和阈值，旨在提高对所得蛋白质被可靠检测以及其定量一致且可重复的信心。我们使用扩展文库和来自人血浆样本以及酵母加标的人K562细胞裂解物消化物的SWATH数据展示了该工作流程。
