Genotype networks in metabolic reaction spaces

Abstract

BackgroundA metabolic genotype comprises all chemical reactions an organism can catalyze via enzymes encoded in its genome. A genotype is viable in a given environment if it is capable of producing all biomass components the organism needs to survive and reproduce. Previous work has focused on the properties of individual genotypes while little is known about how genome-scale metabolic networks with a given function can vary in their reaction content.ResultsWe here characterize spaces of such genotypes. Specifically, we study metabolic genotypes whose phenotype is viability in minimal chemical environments that differ in their sole carbon sources. We show that regardless of the number of reactions in a metabolic genotype, the genotypes of a given phenotype typically form vast, connected, and unstructured sets -- genotype networks -- that nearly span the whole of genotype space. The robustness of metabolic phenotypes to random reaction removal in such spaces has a narrow distribution with a high mean. Different carbon sources differ in the number of metabolic genotypes in their genotype network; this number decreases as a genotype is required to be viable on increasing numbers of carbon sources, but much less than if metabolic reactions were used independently across different chemical environments.ConclusionsOur work shows that phenotype-preserving genotype networks have generic organizational properties and that these properties are insensitive to the number of reactions in metabolic genotypes.

Genotype networks shed light on evolutionary constraints

“…The current known 'universe' of metabolic reactions comprises more than 5000 such reactions, each of which could be present or absent in any one network. Thus, metabolic genotype space is a vast hyperastronomical space comprising more than 2 5000 metabolic networks [11,12].…”

“…They are also of interest in their own right, because they are involved in most, if not all, macroscopic phenotypic characters and thus also in evolutionary innovations. The genotype-phenotype relationships of these systems share several important features that facilitate such innovations [11][12][13][14][15][16][17][18][19][20]. For these reasons, these systems are attractive subjects to study evolutionary constraints.…”

“…One reason is that sufficiently large amounts of empirical data exist to analyze this relationship, as in the case of proteins. Another reason is that the ability to model biological systems quantitatively has improved [12,15,16,. Below, I summarize insights from recent work on these system classes [11][12][13][14][15][16][17][18][19][20].…”

“…The current known 'universe' of metabolic reactions comprises more than 5000 such reactions, each of which could be present or absent in any one network. Thus, metabolic genotype space is a vast hyperastronomical space comprising more than 2 5000 metabolic networks [11,12].The genotypes of regulatory circuits are usefully represented as patterns of regulatory interactions.Such regulatory interactions can be enormously complex, involving cooperative interactions among multiple regulators. However, models of specific kinds of regulatory circuit can make accurate predictions under sensible simplifying assumptions, such as assuming that most regulatory interactions involve pairs of molecular species [41].…”

“…The space of all circuits then comprises all possible pairwise patterns of interactions between a given set of genes [14][15][16]48,49]. These interactions give rise to the gene expression phenotype of a circuit.The genotypes of molecules also exist in a space of amino acid and nucleotide sequences.Characterization of this genotype space has the longest research history [17,19,50].The genotype spaces of these three system classes share several similarities [11][12][13][14][15][17][18][19][20]. The first pertains to the neighbors of a genotype.…”