A Genome-wide Functional Signature Ontology Map and Applications to Natural Product Mechanism of Action Discovery. Issue 10 (17th October 2019)

• Record Type: Journal Article
• Authors: McMillan, Elizabeth A.; Kwon, Gino; Clemenceau, Jean R.; Fisher, Kurt W.; Vaden, Rachel M.; Shaikh, Anam F.; Neilsen, Beth K.; Kelly, David; Potts, Malia B.; Sung, Yeo-Jin; Mendiratta, Saurabh; Hight, Suzie K.; Lee, Yunji; MacMillan, John B.; Lewis, Robert E.; Kim, Hyun Seok; White, Michael A.
• Is Part Of: Cell chemical biology. Volume 26:Issue 10(2019)
• Page Start: 1380
• Page End: 1392.e6
• Publication Date: 2019-10-17
• Subjects: functional genomics -- chemical genetics -- natural products -- cell regulatory networks -- network pharmacology -- mechanism of action; Biochemistry -- Periodicals; 572.05
• DOI: 10.1016/j.chembiol.2019.07.008
• Languages: English
• ISSNs: 2451-9456

Abstract

Summary: Gene expression signature-based inference of functional connectivity within and between genetic perturbations, chemical perturbations, and disease status can lead to the development of actionable hypotheses for gene function, chemical modes of action, and disease treatment strategies. Here, we report a FuSiOn-based genome-wide integration of hypomorphic cellular phenotypes that enables functional annotation of gene network topology, assignment of mechanistic hypotheses to genes of unknown function, and detection of cooperativity among cell regulatory systems. Dovetailing genetic perturbation data with chemical perturbation phenotypes allowed simultaneous generation of mechanism of action hypotheses for thousands of uncharacterized natural products fractions (NPFs). The predicted mechanism of actions span a broad spectrum of cellular mechanisms, many of which are not currently recognized as "druggable." To enable use of FuSiOn as a hypothesis generation resource, all associations and analyses are available within an open source web-based GUI (http://fusion.yuhs.ac ). Graphical Abstract: Highlights: Generation of genome-wide gene/gene and gene/chemical similarity maps Annotation of novel gene function and cooperatively among biological pathways Parallel mechanism of action predictions for thousands of NPFs with diverse cell biological effects Abstract : FuSiOn employs genome-wide integration of quantitative genetic perturbation and chemical perturbation phenotypes to assemble a biological mechanism-driven similarity network. This network can be queried to return testable mechanism of action hypotheses for genes and chemicals of unknown function, and to establish connections between those mechanisms and other cell biological processes.