Sequence similarity network and protein structure prediction offer insights into the evolution of microbial pathways for ferrous iron oxidation.

Microbial Fe(II) oxidation is a crucial process that harnesses and converts the energy available in Fe, contributing significantly to global element cycling. However, there are still many aspects of this process that remain unexplored. In this study, we utilized a combination of comparative genomics, sequence similarity network analysis, and artificial intelligence-driven structure modeling methods to address the lack of structural information on Fe(II) oxidation proteins and offer a comprehensive perspective on the evolution of Fe(II) oxidation pathways. Our findings suggest that several microbial Fe(II) oxidation pathways currently known may have originated within classes Gammaproteobacteria and Betaproteobacteria.