This note investigates how noise propagates in cascades of metabolic transformations. Motivation stems from recent single cell experiments that have shown that noise generated in gene expression and enzymes fluctuations propagates to growth rate through metabolic fluxes. A stochastic approach based on Continuous-Time Markov Chains (CTMC) is exploited to model all reactions, with a special interest in the substrate production, assumed to happen in bursts. Different noise features are dealt with, including correlation of intermediate players, noise impact on the end-product and the role of a feedback from the end-product that may control the substrate production. Most results are given in terms of analytical solutions of the CTMC, in some cases exploiting linear approximations; in all these cases, the findings are validated via Monte Carlo stochastic simulations. The proposed results highlight how substrate production in bursts, cascade length and distance among species affect fluctuations and correlations, with the feedback possibly playing a crucial role in favor of noise propagation.

Borri, A., Palumbo, P., Singh, A. (2022). A general framework for noise propagation in a cascade of metabolic transformations. In 1st IFAC Workshop on Control of Complex Systems, COSY 2022 - Proceedings (pp.121-126). Elsevier BV [10.1016/j.ifacol.2023.01.059].

A general framework for noise propagation in a cascade of metabolic transformations

Palumbo P.
;
2022

Abstract

This note investigates how noise propagates in cascades of metabolic transformations. Motivation stems from recent single cell experiments that have shown that noise generated in gene expression and enzymes fluctuations propagates to growth rate through metabolic fluxes. A stochastic approach based on Continuous-Time Markov Chains (CTMC) is exploited to model all reactions, with a special interest in the substrate production, assumed to happen in bursts. Different noise features are dealt with, including correlation of intermediate players, noise impact on the end-product and the role of a feedback from the end-product that may control the substrate production. Most results are given in terms of analytical solutions of the CTMC, in some cases exploiting linear approximations; in all these cases, the findings are validated via Monte Carlo stochastic simulations. The proposed results highlight how substrate production in bursts, cascade length and distance among species affect fluctuations and correlations, with the feedback possibly playing a crucial role in favor of noise propagation.
paper
Biomedical Systems & Control; Stochastic Systems & Control;
English
1st IFAC Workshop on Control of Complex Systems, COSY 2022
2022
Perdon, AM; Zattoni, E; Loiseau, JJ
1st IFAC Workshop on Control of Complex Systems, COSY 2022 - Proceedings
2022
55
40
121
126
none
Borri, A., Palumbo, P., Singh, A. (2022). A general framework for noise propagation in a cascade of metabolic transformations. In 1st IFAC Workshop on Control of Complex Systems, COSY 2022 - Proceedings (pp.121-126). Elsevier BV [10.1016/j.ifacol.2023.01.059].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/440169
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