Inferring causal metabolic signals that regulate the dynamic TORC1-dependent transcriptome.

ABSTRACT: Cells react to nutritional cues in changing environments via the integrated action of signaling, transcriptional, and metabolic networks. Mechanistic insight into signaling processes is often complicated because ubiquitous feedback loops obscure causal relationships. Consequently, the endogenous inputs of many nutrient signaling pathways remain unknown. Recent advances for system-wide experimental data generation have facilitated the quantification of signaling systems, but the integration of multi-level dynamic data remains challenging. Here, we co-designed dynamic experiments and a probabilistic, model-based method to infer causal relationships between metabolism, signaling, and gene regulation. We analyzed the dynamic regulation of nitrogen metabolism by the target of rapamycin complex

SUBMITTER: Oliveira AP 

PROVIDER: S-EPMC4422559 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature