Analysis abstract
Nature Biotechnology 25, 1001 - 1006 (2007)
Published online: 10 September 2007 | doi:10.1038/nbt1330
Ensemble modeling for analysis of cell signaling dynamics
Lars Kuepfer1,2,5, Matthias Peter3,4, Uwe Sauer1,4 & Jörg Stelling2,4
Abstract
Systems biology iteratively combines experimentation with mathematical modeling. However, limited mechanistic knowledge, conflicting hypotheses and scarce experimental data severely hamper the development of predictive mechanistic models in many areas of biology. Even under such high uncertainty, we show here that ensemble modeling, when combined with targeted experimental analysis, can unravel key operating principles in complex cellular pathways. For proof of concept, we develop a library of mechanistically alternative dynamic models for the highly conserved target-of-rapamycin (TOR) pathway of Saccharomyces cerevisiae. In contrast to the prevailing view of a de novo assembly of type 2A phosphatases (PP2As), our integrated computational and experimental analysis proposes a specificity factor, based on Tap42p-Tip41p, for PP2As as the key signaling mechanism that is quantitatively consistent with all available experimental data. Beyond revising our picture of TOR signaling, we expect ensemble modeling to help elucidate other insufficiently characterized cellular circuits.
- Institute of Molecular Systems Biology, ETH Zurich, 8092 Zurich, Switzerland.
- Institute of Computational Science, ETH Zurich, 8092 Zurich, Switzerland.
- Institute of Biochemistry, ETH Zurich, 8092 Zurich, Switzerland.
- Competence Center for Systems Physiology and Metabolic Disease, ETH Zurich, 8092 Zurich, Switzerland.
- Present address: Bayer Technology Services, 51368 Leverkusen, Germany.
Correspondence to: Jörg Stelling2,4 e-mail: joerg.stelling@inf.ethz.ch
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