Our new research, “Metabolite correlation networks reveal complex phenotypes of adaptation-driving mutations”, is now available on EcoEvoRxiv!

In this study, we show that adaptive evolution can reshape the structure of metabolic networks, creating complex phenotypes that link mutations to fitness. As part of a collaboration with Shimon Bershtein’s lab, our student evolved a metabolically impaired E. coli strain, and demonstrated that fitness gains arise from large-scale rewiring of metabolite correlation networks, producing smaller, more cohesive, and better-connected clusters. These results highlight metabolite correlation networks as a powerful framework for uncovering emergent phenotypes that drive metabolic adaptation.

Read the full paper here: EcoEvoRxiv