Gene expression and its regulation is a nonequilibrium stochastic process. Different molecules are involved in several biochemical steps in this process  . It is observed that the stochasticity in biochemical processes is mainly due to the low copy number of the molecules present in the system. Several studies also show that the nonequilibrium biochemical processes require energy cost. But cellular system has developed itself through natural evolution by minimizing energy cost for optimum output. Here we study the origin of stochasticity qualitatively in a network of two genes using stochastic simulation method and argued that stochasticity in gene expression may be a choice of cellular system for optimum output with minimum energy cost.
Gene expression and its regulation is a nonequilibrium stochastic process. Different molecules are involved in several biochemical steps in this process with low copies . It is observed that the stochasticity in biochemical processes is mainly due to the low copy number of the molecules present in the system. Several studies also show that the nonequilibrium biochemical processes require energy cost. But cellular system has developed itself through natural evolution by minimizing energy cost for optimum output. Here we study the role of stochasticity qualitatively in a network of two genes using stochastic simulation method and approximately measure the energy consumption for the gene expression process. We find that the noise in gene expression process reduces the energy cost of protein synthesis. Therefore, we argued that the stochasticity in gene expression may be a choice of cellular system for protein synthesis with minimum energy cost.
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with low copies
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origin
role
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argued that
approximately measure the energy consumption for the gene expression process. We find that the noise in gene expression process reduces the energy cost of protein synthesis. Therefore, we argued that the
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optimum output
protein synthesis