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 enzymes that promote the transformations. The final product is responsible for the cellular growth rate modulation. This mechanism acts in feedback at the enzymatic level, since the upstream enzyme (as well as all species) is subject to clearance, with the clearance rate proportional to growth. The upstream 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 the delay introduced by the cascade length helps in reducing the impact of enzymatic noise on to growth fluctuations. Further, if feedback is removed from the scheme, growth rate fluctuations increase, according to the same stationary values. Analytical results are supported by Monte Carlo simulations.
Noise propagation in metabolic pathways: The role of growth-mediated feedback
Borri A;Palumbo P;
2020
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 enzymes that promote the transformations. The final product is responsible for the cellular growth rate modulation. This mechanism acts in feedback at the enzymatic level, since the upstream enzyme (as well as all species) is subject to clearance, with the clearance rate proportional to growth. The upstream 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 the delay introduced by the cascade length helps in reducing the impact of enzymatic noise on to growth fluctuations. Further, if feedback is removed from the scheme, growth rate fluctuations increase, according to the same stationary values. Analytical results are supported by Monte Carlo simulations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.