2018/01/25 by Fabrizio Pucci, Marianne Rooman, Pucci, Fabrizio +1
Biochemistry, Genetics and Molecular Biology · #FOS: Biological sciences #Gene Regulatory Network Analysis #Microbial Metabolic Engineering and Bioproduction #Molecular Networks (q-bio.MN)
paper · pdf · doi:10.48550/arxiv.1801.08515
openalex publication_date 2018/01/25 · openalex created_date 2022/08/14 · openalex updated_date 2026/07/28
The impact of random fluctuations on the dynamical behavior a complex\nbiological systems is a longstanding issue, whose understanding would shed\nlight on the evolutionary pressure that nature imposes on the intrinsic noise\nlevels and would allow rationally designing synthetic networks with controlled\nnoise. Using the It =o stochastic differential equation formalism, we performed\nboth analytic and numerical analyses of several model systems containing\ndifferent molecular species in contact with the environment and interacting\nwith each other through mass-action kinetics. These systems represent for\nexample biomolecular oligomerization processes, complex-breakage reactions,\nsignaling cascades or metabolic networks. For chemical reaction networks with\nzero deficiency values, which admit a detailed- or complex-balanced steady\nstate, all molecular species are uncorrelated. The number of molecules of each\nspecies follow a Poisson distribution and their Fano factors, which measure the\nintrinsic noise, are equal to one. Systems with deficiency one have an\nunbalanced non-equilibrium steady state and a non-zero S-flux, defined as the\nflux flowing between the complexes multiplied by an adequate stoichiometric\ncoefficient. In this case, the noise on each species is reduced if the flux\nflows from the species of lowest to highest complexity, and is amplified is the\nflux goes in the opposite direction. These results are generalized to systems\nof deficiency two, which possess two independent non-vanishing S-fluxes, and we\nconjecture that a similar relation holds for higher deficiency systems.\n