Pseudo-transition Analysis Identifies the Key Regulators of Dynamic Metabolic Adaptations from Steady-State Data.

Autor:	Gerosa L; Institute of Molecular Systems Biology, ETH Zurich, Zurich 8093, Switzerland; Systems Biology Graduate School, Zurich 8057, Switzerland. Electronic address: gerosa@fas.harvard.edu., Haverkorn van Rijsewijk BR; Institute of Molecular Systems Biology, ETH Zurich, Zurich 8093, Switzerland; Systems Biology Graduate School, Zurich 8057, Switzerland., Christodoulou D; Institute of Molecular Systems Biology, ETH Zurich, Zurich 8093, Switzerland; Systems Biology Graduate School, Zurich 8057, Switzerland., Kochanowski K; Institute of Molecular Systems Biology, ETH Zurich, Zurich 8093, Switzerland; Systems Biology Graduate School, Zurich 8057, Switzerland., Schmidt TS; Institute of Molecular Systems Biology, ETH Zurich, Zurich 8093, Switzerland., Noor E; Institute of Molecular Systems Biology, ETH Zurich, Zurich 8093, Switzerland., Sauer U; Institute of Molecular Systems Biology, ETH Zurich, Zurich 8093, Switzerland. Electronic address: sauer@imsb.biol.ethz.ch.
Jazyk:	angličtina
Zdroj:	Cell systems [Cell Syst] 2015 Oct 28; Vol. 1 (4), pp. 270-82. Date of Electronic Publication: 2015 Oct 22.
DOI:	10.1016/j.cels.2015.09.008
Abstrakt:	Hundreds of molecular-level changes within central metabolism allow a cell to adapt to the changing environment. A primary challenge in cell physiology is to identify which of these molecular-level changes are active regulatory events. Here, we introduce pseudo-transition analysis, an approach that uses multiple steady-state observations of (13)C-resolved fluxes, metabolites, and transcripts to infer which regulatory events drive metabolic adaptations following environmental transitions. Pseudo-transition analysis recapitulates known biology and identifies an unexpectedly sparse, transition-dependent regulatory landscape: typically a handful of regulatory events drive adaptation between carbon sources, with transcription mainly regulating TCA cycle flux and reactants regulating EMP pathway flux. We verify these observations using time-resolved measurements of the diauxic shift, demonstrating that some dynamic transitions can be approximated as monotonic shifts between steady-state extremes. Overall, we show that pseudo-transition analysis can explore the vast regulatory landscape of dynamic transitions using relatively few steady-state data, thereby guiding time-consuming, hypothesis-driven molecular validations. (Copyright © 2015 Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu