Investigating the Implications of ALE Mutations on the E. coli Metalloproteome with GPS-2M: A Structural and Evolutionary Perspective

Data-centric approaches that describe the functional and three-dimensional characteristics of prokaryotic metalloproteomes are limited, as are analytical approaches that explore the relationships between metalloproteins and adaptive mutations. Analyzing the reconstructed E. coli Gene-Protein Structure-Metal/Mutations (GPS-2M) dataset addresses these gaps by scrutinizing the spatial relationships between adaptive mutations on metalloproteins and their potential physiological impacts. GPS-2M integrates protein structures from protein crystallography data of known metal-binding positions and a meta-analysis of both adaptive laboratory evolution (ALE) and long-term evolutionary experiments (LTEE). This combinatory analysis reveals trends in close-range ALE-induced amino acid property changes related to metal binding sites, thus informing potential targets for metalloprotein design. Associating ALE mutants and experiments with metalloproteins has identified specific functional pathways, post-translational modifications, and downstream mutation targets for follow-up microbial strain design optimization. Specifically, we identified a range of close ALE mutations (0-5 Å) in relation to metal-binding sites on proteins, suggesting mutation targets of ALE experiments that can influence the coordination between metal ions and their residues. Mutations clustered around Zn-binding proteins PyrC, the Hg-binding uvrD, and Mo-binding narG, among numerous others, are pinpointed as optimal target sites for enhancing strain design efficacy. The proximity of ALE mutations to metal-binding sites underscores their potential significance in maintaining and improving physiological homeostasis. Our data-driven approach provides supplemental knowledge to the structural and adaptive dynamics of the E. coli metalloproteome, with implications for future studies to design ALE experiments to optimize metal-binding sites to develop evolutionary-inspired biotechnology.