Regulatory on/off minimization of metabolic flux changes after genetic perturbations

TLDR

Predicting an organism’s metabolic state after a gene knockout is difficult because regulatory systems drive transient changes that converge to a steady state. The study aims to minimize the number of significant flux changes relative to wild type and to develop metrics that capture the full trajectory from initial to final steady states after genetic perturbations. ROOM is a constraint‑based algorithm that predicts post‑knockout steady‑state fluxes and is benchmarked against minimization of metabolic adjustment and flux balance analysis. ROOM accurately predicts steady‑state fluxes that preserve linearity, matches experimental measurements, identifies alternative rerouting pathways, and, unlike FBA, does not explicitly maximize growth yet still favors high‑growth distributions, suggesting regulatory mechanisms naturally minimize flux changes.

Abstract

Predicting the metabolic state of an organism after a gene knockout is a challenging task, because the regulatory system governs a series of transient metabolic changes that converge to a steady-state condition. Regulatory on/off minimization (ROOM) is a constraint-based algorithm for predicting the metabolic steady state after gene knockouts. It aims to minimize the number of significant flux changes (hence on/off) with respect to the wild type. ROOM is shown to accurately predict steady-state metabolic fluxes that maintain flux linearity, in agreement with experimental flux measurements, and to correctly identify short alternative pathways used for rerouting metabolic flux in response to gene knockouts. ROOM's growth rate and flux predictions are compared with previously suggested algorithms, minimization of metabolic adjustment, and flux balance analysis (FBA). We find that minimization of metabolic adjustment provides accurate predictions for the initial transient growth rates observed during the early postperturbation state, whereas ROOM and FBA more successfully predict final higher steady-state growth rates. Although FBA explicitly maximizes the growth rate, ROOM does not, and only implicitly favors flux distributions having high growth rates. This indicates that, even though the cell has not evolved to cope with specific mutations, regulatory mechanisms aiming to minimize flux changes after genetic perturbations may indeed work to this effect. Further work is needed to identify metrics that characterize the complete trajectory from the initial to the final metabolic steady states after genetic perturbations.