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Metabolic networks evolve towards states of maximum entropy production

Paper ID Volume ID Publish Year Pages File Format Full-Text
31768 44837 2011 8 PDF Available
Title
Metabolic networks evolve towards states of maximum entropy production
Abstract

A metabolic network can be described by a set of elementary modes or pathways representing discrete metabolic states that support cell function. We have recently shown that in the most likely metabolic state the usage probability of individual elementary modes is distributed according to the Boltzmann distribution law while complying with the principle of maximum entropy production. To demonstrate that a metabolic network evolves towards such state we have carried out adaptive evolution experiments with Thermoanaerobacterium saccharolyticum operating with a reduced metabolic functionality based on a reduced set of elementary modes. In such reduced metabolic network metabolic fluxes can be conveniently computed from the measured metabolite secretion pattern. Over a time span of 300 generations the specific growth rate of the strain continuously increased together with a continuous increase in the rate of entropy production. We show that the rate of entropy production asymptotically approaches the maximum entropy production rate predicted from the state when the usage probability of individual elementary modes is distributed according to the Boltzmann distribution. Therefore, the outcome of evolution of a complex biological system can be predicted in highly quantitative terms using basic statistical mechanical principles.

► Metabolic fluxes can be computed as a weighted average of Elementary Modes (EM). ► Weights are predicted from EM reaction entropies and Boltzmann distribution law. ► Adaptive evolution experiments confirm that metabolic networks evolve towards such state.

Keywords
Elementary Mode Analysis; Metabolic evolution; Entropy; Boltzmann distribution law
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Metabolic networks evolve towards states of maximum entropy production
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Publisher
Database: Elsevier - ScienceDirect
Journal: Metabolic Engineering - Volume 13, Issue 6, November 2011, Pages 666–673
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us