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Inferring causal metabolic signals that regulate the dynamic TORC1-dependent transcriptome.
Oliveira, Ana Paula; Dimopoulos, Sotiris; Busetto, Alberto Giovanni; Christen, Stefan; Dechant, Reinhard; Falter, Laura; Haghir Chehreghani, Morteza; Jozefczuk, Szymon; Ludwig, Christina; Rudroff, Florian; Schulz, Juliane Caroline; González, Asier; Soulard, Alexandre; Stracka, Daniele; Aebersold, Ruedi; Buhmann, Joachim M; Hall, Michael N; Peter, Matthias; Sauer, Uwe; Stelling, Jörg.
Afiliação
  • Oliveira AP; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Dimopoulos S; Department of Biosystems Science and Engineering and SIB Swiss Institute of Bioinformatics, ETH Zurich, Basel, Switzerland.
  • Busetto AG; Department of Computer Science, ETH Zurich, Zurich, Switzerland.
  • Christen S; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Dechant R; Department of Biology, Institute of Biochemistry, ETH Zurich, Zurich, Switzerland.
  • Falter L; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Haghir Chehreghani M; Department of Computer Science, ETH Zurich, Zurich, Switzerland.
  • Jozefczuk S; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Ludwig C; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Rudroff F; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • Schulz JC; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
  • González A; Biozentrum, University of Basel, Basel, Switzerland.
  • Soulard A; Biozentrum, University of Basel, Basel, Switzerland UMR5240 MAP, Université Lyon 1, Villeurbanne, France.
  • Stracka D; Biozentrum, University of Basel, Basel, Switzerland.
  • Aebersold R; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland Faculty of Science, University of Zurich, Zurich, Switzerland.
  • Buhmann JM; Department of Computer Science, ETH Zurich, Zurich, Switzerland.
  • Hall MN; Biozentrum, University of Basel, Basel, Switzerland.
  • Peter M; Department of Biology, Institute of Biochemistry, ETH Zurich, Zurich, Switzerland.
  • Sauer U; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland sauer@ethz.ch joerg.stelling@bsse.ethz.ch.
  • Stelling J; Department of Biosystems Science and Engineering and SIB Swiss Institute of Bioinformatics, ETH Zurich, Basel, Switzerland sauer@ethz.ch joerg.stelling@bsse.ethz.ch.
Mol Syst Biol ; 11(4): 802, 2015 Apr 17.
Article em En | MEDLINE | ID: mdl-25888284
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 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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saccharomyces cerevisiae / Fatores de Transcrição / RNA Fúngico / Regulação Fúngica da Expressão Gênica / Proteínas de Saccharomyces cerevisiae / Transcriptoma Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saccharomyces cerevisiae / Fatores de Transcrição / RNA Fúngico / Regulação Fúngica da Expressão Gênica / Proteínas de Saccharomyces cerevisiae / Transcriptoma Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2015 Tipo de documento: Article