From bit to it: How a complex metabolic network transforms information into living matter

Wagner, Andreas

doi:10.1186/1752-0509-1-33

Cited by 24 publications

(12 citation statements)

References 45 publications

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“…Here, we analyze a yeast metabolic network resulting from a highquality genome-wide reconstruction (29). This network is suitable for FBA (29)(30)(31), a powerful computational tool for connecting genotypes, phenotypes, and the environment in evolutionary studies (28,(32)(33)(34)(35)(36)(37)(38). Assuming a steady state of metabolism, one can maximize the biomass production rate or Darwinian fitness of the cell by balancing all fluxes simultaneously.…”

Section: Resultsmentioning

confidence: 99%

Impact of gene expression noise on organismal fitness and the efficacy of natural selection

Wang

Zhang²

2011

Proc. Natl. Acad. Sci. U.S.A.

188

187

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Gene expression noise is a universal phenomenon across all life forms. Although beneficial under certain circumstances, expression noise is generally thought to be deleterious. However, neither the magnitude of the deleterious effect nor the primary mechanism of this effect is known. Here, we model the impact of expression noise on the fitness of unicellular organisms by considering the influence of suboptimal expressions of enzymes on the rate of biomass production and the energetic cost associated with imprecise amounts of protein synthesis. Our theoretical modeling and empirical analysis of yeast data show four findings. (i) Expression noise reduces the mean fitness of a cell by at least 25%, and this reduction cannot be substantially alleviated by gene overexpression. (ii) Higher sensitivity of fitness to the expression fluctuations of essential genes than nonessential genes creates stronger selection against noise in essential genes, resulting in a decrease in their noise. (iii) Reduction of expression noise by genome doubling offers a substantial fitness advantage to diploids over haploids, even in the absence of sex. (iv) Expression noise generates fitness variation among isogenic cells, which lowers the efficacy of natural selection similar to the effect of population shrinkage. Thus, expression noise renders organisms both less adapted and less adaptable. Because expression noise is only one of many manifestations of the stochasticity in cellular molecular processes, our results suggest a much more fundamental role of molecular stochasticity in evolution than is currently appreciated.flux balance analysis | metabolic network M any cellular processes are subject to substantial stochastic variation, because they depend on interactions among a small number of molecules. For example, the transcriptional initiation of a gene in a haploid cell relies on the binding of the transcriptional machinery to a single DNA molecule. The stochastic nature of this and other molecular interactions results in a large variation in the expression of the same gene by different isogenic cells under the same environment (1-3). How and to what extent such molecule-level stochasticity affects the wellbeing of organisms and their evolution is not well-understood. Recent experimental characterization of gene expression noise in multiple species (4-9) provides necessary empirical data for addressing these fundamental but wide-open questions.In this work, gene expression noise refers to the stochastic variation in the protein expression level of a gene among isogenic cells in a homogenous environment (10). Expression noise arises from both intrinsic and extrinsic variations (2,6,8,10,11). Stochastic events in gene expression, including those in transcriptional initiation, mRNA degradation, translational initiation, and protein degradation, generate intrinsic noise (10). Differences among cells, either in local environment or the concentration or activity of any factor influencing gene expression, generate extrinsic noise (10). Extrin...

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Section: Resultsmentioning

confidence: 99%

Impact of gene expression noise on organismal fitness and the efficacy of natural selection

Wang

Zhang²

2011

Proc. Natl. Acad. Sci. U.S.A.

188

187

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“…bacteria, have the attributes of a Turing Machine, capable of a general-purpose computation [30,32,33], and von Neumann's Universal Constructor, i.e. computer making computers [32] (DNA molecule acts as nonvolatile memory of the cell computer, while many proteins in cell's cytoplasm have as their primary function the transfer and processing of information, and are therefore can be regarded as logical elements of the biological cell processor [34,35,36,37]). The Universal Constructor Table 1 [38]).…”

Section: Open Issues and Conclusionmentioning

confidence: 99%

Minimum Energy of Computing, Fundamental Considerations

Zhirnov¹,

Cavin²,

Gammaitoni³

2014

ICT - Energy - Concepts Towards Zero - Power Information and Communication Technology

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“…It should be noted that the idea of GRNs and other biological regulatory networks have been cast in terms of information theory previously [46,47].…”

Section: Self-organization Of Creating Cellsmentioning

confidence: 99%

Signal‐regulated systems and networks

Zyl

Ehlers

2010

Complexity

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The article presents the use of signal regulatory networks (SRNs), a biologically inspired model based on gene regulatory networks. SRNs are a way of understanding a class of self-organizing IT systems, signal-regulated systems (SRSs). This article builds on the theory of SRSs and introduces some formalisms to clarify the discussion. An exemplar SRS that can be evaluated using SRNs is presented. Finally, an implementation of an adaptive and robust solution, built on a theory of SRSs and analyzed as a SRN, is shown to be plausible.

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From bit to it: How a complex metabolic network transforms information into living matter

Cited by 24 publications

References 45 publications

Impact of gene expression noise on organismal fitness and the efficacy of natural selection

Impact of gene expression noise on organismal fitness and the efficacy of natural selection

Minimum Energy of Computing, Fundamental Considerations

Signal‐regulated systems and networks

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