Deducing the mechanism of action of compounds identified in phenotypic screens by integrating their multiparametric profiles with a reference genetic screen.

Cell-based high-content screens are increasingly used to discover bioactive small molecules. However, identifying the mechanism of action of the selected compounds is a major bottleneck. Here we describe a protocol consisting of experimental and computational steps to identify the cellular pathways modulated by chemicals, and their mechanism of action. The multiparametric profiles from a 'query' chemical screen are used as constraints to select genes with similar profiles from a 'reference' genetic screen. In our case, the query screen is the intracellular survival of mycobacteria and the reference is a genome-wide RNAi screen of endocytosis. The two disparate screens are bridged by an 'intermediate' chemical screen of endocytosis, so that the similarity in the multiparametric profiles between the chemical and the genetic perturbations can generate a testable hypothesis of the cellular pathways modulated by the chemicals. This approach is not assay specific, but it can be broadly applied to various quantitative, multiparametric data sets. Generation of the query system takes 3-6 weeks, and data analysis and integration with the reference data set takes an 3 additional weeks.