Inferring causal metabolic signals that regulate the dynamic TORC1-dependent transcriptome
Oliveira, Ana P.
Busetto, Alberto G.
Dechant, Reinhard C.
Falter, Laura B.
Haghir Chehreghani, Morteza
Schulz, Juliane C.
Buhmann, Joachim M.
Hall, Michael N.
Sauer, Uwe H.
- Journal Article
Rights / licenseCreative Commons Attribution 4.0 International
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 1 (TORC1) pathway in budding yeast. Dynamic transcriptomic, proteomic, and metabolomic measurements along shifts in nitrogen quality yielded a consistent dataset that demonstrated extensive re‐wiring of cellular networks during adaptation. Our inference method identified putative downstream targets of TORC1 and putative metabolic inputs of TORC1, including the hypothesized glutamine signal. The work provides a basis for further mechanistic studies of nitrogen metabolism and a general computational framework to study cellular processes Show more
Journal / seriesMolecular Systems Biology
Pages / Article No.
SubjectCausal inference; Network motifs; Nutrient signaling; Target of rapamycin pathway
Organisational unit03595 - Peter, Matthias / Peter, Matthias
03699 - Stelling, Jörg / Stelling, Jörg
03713 - Sauer, Uwe / Sauer, Uwe
03663 - Aebersold, Rudolf / Aebersold, Rudolf
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