Authors: Lorenz DR; Cantor CR; Collins JJ
Abstract: In this study, a reverse-engineering strategy was used to infer and analyze the structure and function of an aging and glucose repressed gene regulatory network in the budding yeast Saccharomyces cerevisiae. The method uses transcriptional perturbations to model the functional interactions between genes as a system of first-order ordinary differential equations. The resulting network model correctly identified the known interactions of key regulators in a 10-gene network from the Snf1 signaling pathway, which is required for expression of glucose-repressed genes upon calorie restriction. The majority of interactions predicted by the network model were confirmed using promoter-reporter gene fusions in gene-deletion mutants and chromatin immunoprecipitation experiments, revealing a more complex network architecture than previously appreciated. The reverse-engineered network model also predicted an unexpected role for transcriptional regulation of the SNF1 gene by hexose kinase enzyme/transcriptional repressor Hxk2, Mediator subunit Med8, and transcriptional repressor Mig1. These interactions were validated experimentally and used to design new experiments demonstrating Snf1 and its transcriptional regulators Hxk2 and Mig1 as modulators of chronological lifespan. This work demonstrates the value of using network inference methods to identify and characterize the regulators of complex phenotypes, such as aging.
Keywords: Gene Expression Profiling; Gene Expression Regulation, Fungal; *Gene Regulatory Networks; Models, Genetic; Protein-Serine-Threonine Kinases/genetics/metabolism; RNA, Messenger/genetics/metabolism; Regression Analysis; Reproducibility of Results; Saccharomyces cerevisiae/*genetics/*growth & development; Time Factors; Transcription, Genetic|
Journal: Proceedings of the National Academy of Sciences of the United States of America Volume: 106 Issue: 4 Pages: 1145-50 Date: Jan. 24, 2009 PMID: 19164565 |
Network
Lorenz DR, Cantor CR, Collins JJ (2009) A network biology approach to aging in yeast. Proceedings of the National Academy of Sciences of the United States of America 106: 1145-50.
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