Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis

TL;DR

This study uses energy balance analysis and Monte Carlo sampling to estimate E. coli's metabolic turnover times at a genome scale, revealing faster intermediate metabolism than previous net flux-based estimates.

Contribution

It introduces a method combining energy balance and fluctuation theorem to more accurately estimate metabolic turnover times in E. coli.

Findings

Turnover times are often an order of magnitude lower with energy-based calculations.

Metabolic intermediates are turned over faster than previously estimated.

The approach challenges assumptions made when using net fluxes near thermodynamic equilibrium.

Abstract

In this article the notion of metabolic turnover is revisited in the light of recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo methods we perform an exact uniform sampling of the steady state fluxes in a genome scale metabolic network of E Coli from which we infer the metabolites turnover times. However the latter are inferred from net fluxes, and we argue that this approximation is not valid for enzymes working nearby thermodynamic equilibrium. We recalculate turnover times from total fluxes by performing an energy balance analysis of the network and recurring to the fluctuation theorem. We find in many cases values one of order of magnitude lower, implying a faster picture of intermediate metabolism.