Institute of Molecular Systems Biology

Search

en

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

The Sauer Lab developed an experimental-computational approach to identify regulatory needles in metabolic haystacks. By using steady-state 13C flux, metabolites and transcript data, the approach revealed the sparse and transition-dependent regulators that drive transitions between carbon sources in Escherichia coli. Thus, pseudo-transition analysis is a novel approach to efficiently explore the vast regulatory landscape of dynamic adaptations using relatively few stationary observations.

by Dimitrios Christodoulou
Abstract 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 13C-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. Reference Luca Gerosa*, Bart R.B. Haverkorn van Rijsewijk*, Dimitris Christodoulou, Karl Kochanowski, Thomas S.B. Schmidt, Elad Noor, and Uwe Sauer, Pseudo-transition Analysis Identifies the Key Regulators of Dynamic Metabolic Adaptations from Steady-State Data, Cell Systems, 2015 * Equal contribution

Abstract

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 13C-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.

Reference

Luca Gerosa*, Bart R.B. Haverkorn van Rijsewijk*, Dimitris Christodoulou, Karl Kochanowski, Thomas S.B. Schmidt, Elad Noor, and Uwe Sauer, Pseudo-transition Analysis Identifies the Key Regulators of Dynamic Metabolic Adaptations from Steady-State Data, Cell Systems, 2015

* Equal contribution

JavaScript has been disabled in your browser