Exhaustive genotype-phenotype mapping in metabolic genotype space

Abstract

Genotype-phenotype mapping provides a unique opportunity to gain new insights into the underlying design principles of biological systems and their evolution. Especially informative and insightful is exhaustive genotype-phenotype mapping, which aims to determine the phenotype of every single genotype belonging to a genotype space. These types of studies have been possible with systems of RNA, lattice proteins and Boolean gene-regulatory networks. Due to astronomically large size of metabolic genotype space, the same approach has not been successful for metabolic networks, even though similar studies have been conducted for metabolic systems based on efficient sampling of metabolic genotype space. The present project aims to depart from sampling based methods towards an exhaustive approach. To accomplish this goal I focused on central carbon metabolism of Escherichia coli (E.coli), and by developing a new algorithm to efficiently explore the genotype space I obtained a complete genotype-phenotype map for this metabolic system. I analyzed the topological properties of metabolic genotype networks and showed that the metabolic genotype networks are connected. Moreover, the results revealed that genotypes with more connections or higher centrality in the genotype networks are more robust to reaction elimination. Surprisingly, I observed a strong association between robustness and biomass synthesis rate (i.e. fitness), which might shed light on the emergence of robustness in metabolic networks. Finally, I extensively examined the superessentiality of metabolic reactions and the results indicate that consecutive reactions in metabolic pathways tend to show similar super-essentiality profiles.