Noise propagation in metabolic pathways: the role of growth-mediated feedback

Abstract

Metabolic networks are known to deal with the chemical reactions responsible to fuel cellular activities with energy and carbon source and, as a matter of fact, to set the growth rate of the cell. To this end, feedback and regulatory networks play a crucial role to handle adaptation to external perturbations and internal noise. In this work, a cellular resource is assumed to be activated at the end of a metabolic pathway, by means of a cascade of transformations. Such a cascade is triggered by the catalytic action of an enzyme that promotes the first transformation. The final product is responsible for the cellular growth rate modulation. This mechanism acts in feedback at the enzymatic level, since the enzyme (as well as all species) is subject to dilution, with the dilution rate set by growth. Enzymatic production is modeled by the occurrence of noisy bursts: a Stochastic Hybrid System is exploited to model the network and to investigate how such noise propagates on growth fluctuations. A major biological finding is that, differently from other models of metabolic pathways disregarding growth-mediated feedback, fluctuations in enzyme levels do not produce only local effects, but propagate up to the final product (hence to the growth rate). Furthermore, the delay provided by the cascade length helps in reducing the impact of enzymatic noise on to growth fluctuations. Analytical results are supported by Monte Carlo simulations.

AI-Assisted Identification of Primary and Secondary Metabolomic Markers for Post-Operative Delirium

“…Generally, the pairwise correlations observed between metabolites are insignificant, even when the pairs are part of the same metabolic pathway [22][23][24] . This phenomenon could be attributed to the inherent stochasticity of metabolic processes [25][26][27][28] . Thus, explicit relationships between metabolites may be hidden, adding another layer of complexity to the analysis.…”