Metabolic Network Properties: Comprehensive Analysis Across Domains

Abstract

Metabolic networks play pivotal roles in understanding the evolution of organisms, microbiome dynamics and disease prevention and treatment. This study presents a comprehensive analysis of metabolic network properties across 10912 organisms spanning Bacteria, Archaea, and Eukarya domains. A novel method for the network construction is introduced, emphasizing the chemical transformations of metabolites. Unlike conventional approaches that link every substrate to every product in all chemical reactions, this method aligns more closely with metabolic pathways, linking products only to their generating substrates. Emphasis is placed on investigating the community structure within metabolic networks, employing the Surprise quality function that better addresses some limitations of previous approaches. Through comparisons between real and randomized versions of the networks, we identify characteristics that cannot be explained solely by the network degree distribution, thus identifying topological properties and community structures that arise from additional evolutionary pressures. This highlights the need for evolutionary models to incorporate additional mechanisms beyond the replication of the degree distribution.