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

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 (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.

Design principles of autocatalytic cycles constrain enzyme kinetics and force low substrate saturation at flux branch points

“…Out of these 13 interactions, 8 interactions follow our expectations and 5 do not. The lack of significant agreement between the expected regulation direction and the actual regulation found for this cycle is consistent with the observation in Gerosa et al (2015) that TCA cycle fluxes are regulated mainly by transcription and not by reactants levels.…”

“…We find that these predictions hold for the cycle using the PTS, that is known to be allosterically controlled, but not for the glyoxylate cycle, which is known to be transcriptionally controlled (Gerosa et al, 2015).…”

“…We used the data from (Gerosa et al, 2015) to identify the major branch points in each functioning cycle and the actual flux in them under each of the relevant conditions. The results are presented in Figure 6 and are provided, with the relevant calculations, in Supplementary file 1.…”

“…For each reaction, under every condition, we divide the flux the reaction carries (obtained from Gerosa et al, 2015) by the amount of the corresponding enzyme expressed under that condition (obtained from Schmidt et al, 2016). We thus get a flux per enzyme estimate for the given reaction under each of the conditions.…”

Distinct transcriptional regulation of the two Escherichia coli transhydrogenases PntAB and UdhA

“…Despite their physiological relevance and genetic evidence that both transhydrogenases are not constitutively expressed in E. coli (Edgar et al, 2002;Faith et al, 2008;Sherlock et al, 2001;Liu et al, 2005), transcriptional regulation of transhydrogenases and the signals that trigger their expression are poorly understood. Based on reported E. coli mRNA expression, metabolite levels and 13 Cbased flux data under eight nutritional conditions (Gerosa et al, 2015), we first demonstrate that transhydrogenase transcription does not correlate with the cellular NADPH demand but suggest rather a growth-related biosynthetic function for PntAB. Using GFP reporter plasmids in 62 transcription factor knockouts, we then systematically identify factors that regulate transhydrogenase expression and demonstrate the availability of extracellular amino acids and growth rate, which, in turn, both affect redox metabolism, as the primary regulation factors.…”