SAINT-MS1: protein-protein interaction scoring using label-free intensity data in affinity purification – mass spectrometry experiments

摘要

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 the log-transformed intensity data, including adequate treatment of missing observations, i.e. interactions whose quantitative data are inconsistent over replicate purifications. We demonstrate the performance of SAINT-MS1 using two recently published datasets: a small LTQ-Orbitrap dataset with three replicate purifications of single human bait protein and control purifications, and a larger drosophila dataset targeting insulin receptor/target of rapamycin signaling pathway generated using an LTQ-FT instrument. Using the drosophila dataset, 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.