Mutant Variants of the Substrate-Binding Protein DppA from Escherichia coli Enhance Growth on Nonstandard γ-Glutamyl Amide-Containing Peptides

The import of nonnatural molecules is a recurring problem in fundamental and applied aspects of microbiology. The dipeptide permease (Dpp) of is an ABC-type multicomponent transporter system located in the cytoplasmic membrane, which is capable of transporting a wide range of di- and tripeptides with structurally and chemically diverse amino acid side chains into the cell. Given this low degree of specificity, Dpp was previously used as an entry gate to deliver natural and nonnatural cargo molecules into the cell by attaching them to amino acid side chains of peptides, in particular, the γ-carboxyl group of glutamate residues. However, the binding affinity of the substrate-binding protein dipeptide permease A (DppA), which is responsible for the initial binding of peptides in the periplasmic space, is significantly higher for peptides consisting of standard amino acids than for peptides containing side-chain modifications. Here, we used adaptive laboratory evolution to identify strains that utilize dipeptides containing γ-substituted glutamate residues more efficiently and linked this phenotype to different mutations in DppA. characterization of these mutants by thermal denaturation midpoint shift assays and isothermal titration calorimetry revealed significantly higher binding affinities of these variants toward peptides containing γ-glutamyl amides, presumably resulting in improved uptake and therefore faster growth in media supplemented with these nonstandard peptides. Fundamental and synthetic biology frequently suffer from insufficient delivery of unnatural building blocks or substrates for metabolic pathways into bacterial cells. The use of peptide-based transport vectors represents an established strategy to enable the uptake of such molecules as a cargo. We expand the scope of peptide-based uptake and characterize in detail the obtained DppA mutant variants. Furthermore, we highlight the potential of adaptive laboratory evolution to identify beneficial insertion mutations that are unlikely to be identified with existing directed evolution strategies.