Evolutionary signals in metabolic networks of insect endosymbionts revealed through comparative topological modeling

Understanding the organization and evolution of metabolic networks is essential for uncovering how organisms adapt to changing environments. Whereas free-living bacteria typically maintain robust and redundant metabolic systems, endosymbiotic bacteria undergo extreme genome reduction during their adaptation to intracellular life. This process results in highly streamlined and interconnected metabolic networks, in some cases smaller than the theoretical minimum required for sustaining independent cellular function.

Using a large-scale comparative framework, we analyzed 101 genomes of insect endosymbiotic bacteria by computing two metabolic network models: metabolite- and reaction-based. We found strong correlations between genome size and key topological properties, including clustering coefficient, network diameter, and number of nodes, indicating that genome reduction directly constrains metabolic network architecture. Despite extensive gene loss, endosymbiotic metabolic networks retain scale-free organization, suggesting the preservation of essential connectivity and robustness. Furthermore, clustering analyses revealed that network topology reflects phylogenetic relationships across bacterial taxa, demonstrating that metabolic organization retains evolutionary signals even in the most reduced genomes.

Our findings show that the metabolic networks of insect endosymbiotic bacteria preserve clear evolutionary imprints, revealing a deep connection between genomic reduction, network structure, and phylogenetic history. The complementary use of metabolite- and reaction-based models provide a powerful framework for exploring how symbiotic evolution reshapes metabolic systems while maintaining essential biological organization.