Saw Swee Hock School of Public Health, National University of Singapore, Singapore.
J Proteome Res. 2012 Apr 6;11(4):2619-24. doi: 10.1021/pr201185r. Epub 2012 Mar 2.
We present a statistical method SAINT-MS1 for scoring protein-protein interactions based on the label-free MS1 intensity data from affinity purification-mass spectrometry (AP-MS) experiments. The method is an extension of Significance Analysis of INTeractome (SAINT), a model-based method previously developed for spectral count data. We reformulated the statistical model for log-transformed intensity data, including adequate treatment of missing observations, that is, interactions identified in some but not all replicate purifications. We demonstrate the performance of SAINT-MS1 using two recently published data sets: a small LTQ-Orbitrap data set with three replicate purifications of single human bait protein and control purifications and a larger drosophila data set targeting insulin receptor/target of rapamycin signaling pathway generated using an LTQ-FT instrument. Using the drosophila data set, we also compare and discuss the performance of SAINT analysis based on spectral count and MS1 intensity data in terms of the recovery of orthologous and literature-curated interactions. Given rapid advances in high mass accuracy instrumentation and intensity-based label-free quantification software, we expect that SAINT-MS1 will become a useful tool allowing improved detection of protein interactions in label-free AP-MS data, especially in the low abundance range.
我们提出了一种基于亲和纯化质谱（AP-MS）实验无标记 MS1 强度数据的蛋白质-蛋白质相互作用评分的统计方法 SAINT-MS1。该方法是基于谱计数数据的 Significance Analysis of INTeractome（SAINT）的扩展。我们重新制定了对数转换强度数据的统计模型，包括对缺失观测值的适当处理，即，在一些但不是所有重复纯化中鉴定到的相互作用。我们使用两个最近发表的数据集来演示 SAINT-MS1 的性能：一个具有三个重复纯化的单个人类诱饵蛋白和对照纯化的 LTQ-Orbitrap 小数据集，以及一个使用 LTQ-FT 仪器生成的针对胰岛素受体/雷帕霉素信号通路的更大的果蝇数据集。使用果蝇数据集，我们还比较和讨论了基于谱计数和 MS1 强度数据的 SAINT 分析在回收同源和文献策交互作用方面的性能。鉴于高质量精度仪器和基于强度的无标记定量软件的快速发展，我们预计 SAINT-MS1 将成为一种有用的工具，可提高无标记 AP-MS 数据中蛋白质相互作用的检测能力，特别是在低丰度范围内。
