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Symbiosis has been among the most important evolutionary steps to generate biological complexity. The establishment of symbiosis required an intimate metabolic link between biological systems with different complexity levels. The strict endo-cellular symbiotic bacteria of insects are beautiful examples of the metabolic coupling between organisms belonging to different kingdoms, a eukaryote and a prokaryote. The host (eukaryote) provides the endosymbiont (prokaryote) with a stable cellular environment while the endosymbiont supplements the host's diet with essential metabolites. For such communication to take place, endosymbionts' genomes have suffered dramatic modifications and reconfigurations of proteins' functions. Two of the main modifications, loss of genes redundant for endosymbiotic bacteria or the host and bacterial genome streamlining, have been extensively studied. However, no studies have accounted for possible functional shifts in the endosymbiotic proteomes. Here, we develop a simple method to screen genomes for evidence of functional divergence between two species clusters, and we apply it to identify functional shifts in the endosymbiotic proteomes. Despite the strong effects of genetic drift in the endosymbiotic systems, we unexpectedly identified genes to be under stronger selective constraints in endosymbionts of aphids and ants than in their free-living bacterial relatives. These genes are directly involved in supplementing the host's diet with essential metabolites. A test of functional divergence supports a strong relationship between the endosymbiosis and the functional shifts of proteins involved in the metabolic communication with the insect host. The correlation between functional divergence in the endosymbiotic bacterium and the ecological requirements of the host uncovers their intimate biochemical and metabolic communication and provides insights on the role of symbiosis in generating species diversity.

Genome-Wide Functional Divergence after the Symbiosis of Proteobacteria with Insects Unraveled through a Novel Computational Approach