Genotype networks, innovation, and robustness in sulfur metabolism - Quantitative Biology > Molecular NetworksReport as inadecuate

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Abstract: Metabolic networks are complex systems that comprise hundreds of chemicalreactions which synthesize biomass molecules from chemicals in an organism-senvironment. The metabolic network of any one organism is encoded by ametabolic genotype, defined by a set of enzyme-coding genes whose productscatalyze the network-s reactions. Each metabolic genotype has a metabolicphenotype, such as the ability to synthesize biomass on a spectrum of differentsources of chemical elements and energy. We here focus on sulfur metabolism,which is attractive to study the evolution of metabolic networks, because itinvolves many fewer reactions than carbon metabolism. Specifically, we studyproperties of the space of all possible metabolic genotypes, and analyzeproperties of random metabolic genotypes that are viable on different numbersof sulfur sources. We show that metabolic genotypes with the same phenotypeform large connected genotype networks that extend far through metabolicgenotype space. How far they reach through this space is a linear function ofthe number of super-essential reactions in such networks, the number ofreactions that occur in all networks with the same phenotype. We show thatdifferent neighborhoods of any genotype network harbor very different novelphenotypes, metabolic innovations that can sustain life on novel sulfursources. We also analyze the ability of evolving populations of metabolicnetworks to explore novel metabolic phenotypes. This ability is facilitated bythe existence of genotype networks, because different neighborhoods of thesenetworks contain very different novel phenotypes. In contrast tomacromolecules, where phenotypic robustness may facilitate phenotypicinnovation, we show that here the ability to access novel phenotypes does notmonotonically increase with robustness.

Author: João F. Matias Rodrigues, Andreas Wagner



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