Engineering antimicrobial peptides and enzymes: Realizing opportunities to combat antibiotic resistance through high-throughput, data-driven design and testing

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Engineering antimicrobial peptides and enzymes: Realizing opportunities to combat antibiotic resistance through high-throughput, data-driven design and testing

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The increase in occurrence of antibiotic resistant infections around the world as a result of overuse of broad-spectrum antibiotics in both agriculture and healthcare poses a significant threat to human health and societal productivity. When most antibiotics were discovered in the mid 20th century, biotechnology as a rigorous science was still far-off. Today, advances across a wide range of disciplines is finally permitting the detailed description and, more importantly, alteration of biological systems. Enabled by this rapidly progressing domain exist alternatives to traditional broad-spectrum antibiotics; of interest here are antimicrobial proteins, which are ribosomally synthesized. Being encoded for in DNA permits the sequences of these proteins to be mutagenized and their sequence-function landscapes rapidly explored. Such exploration was utilized herein to optimize specificity, activity, and stability of three antimicrobial proteins. During this exploration computational and experimental methods permitting high-throughput characterization were developed and applied. First, a small-lasso antimicrobial protein, microcin J25, was engineered for improved specificity towards pathogenic Salmonella in contrast to commensal Escherichia coli, which were isolated from human patients. To accomplish this a plasmid containing a synthetic gene cluster encoding for the precursor peptide of microcin J25, under inducible expression, with three enzymes necessary for maturation and secretion was modified to facilitate mutation of the precursor of microcin J25. A collection of 207 point-mutants across 12 positions was evaluated for activity against a panel of pathogenic Salmonella and E. coli serotypes. Point-mutants demonstrating retention of activity and improvements in specificity were then integrated and screened as a combinatorial library. Multi-mutants demonstrated significant reduction in efficacy, with only 3.5% of sequences in the library having detectable activity against Salmonella enterica serovar Enteritidis. At the project’s conclusion, a point mutant was identified which retained a high level of activity against the target Salmonella species, while reducing the off-target activity towards human commensal E. coli by an average of 81%. Second, a large multi-domain antimicrobial protein which binds to and degrades the cell wall of pathogenic Clostridium perfringens, LysCP2, was validated and stabilized. Owing to its origin, thousands of homologous protein sequences, with structure and function similar to LysCP2, were readily identifiable from genomic databases. We hypothesized that this wealth of homologous information could be utilized to guide the design of combinatorial libraries of LysCP2 to improve its poor stability. Using coevolutionary models, which incorporate pairwise and sitewise information from the homologous sequences, a collection of ten multi-position libraries were designed and generated at different positions of LysCP2. From these libraries, nearly 10,000 variants of LysCP2 were experimentally assayed for stability. These data revealed that the fraction of stable variants for 8 out of 10 designed libraries was greater than fully-random libraries at the same positions in the protein. In addition, post-facto analysis incorporating a structural homology model of LysCP2 implied that structural features, such as contact number and secondary structure, may be reasonable filters to use for a priori selection of residues for which the predictions of the coevolutionary model are most accurate. Finally, due to the high functionality of the designed libraries, the experimental data was used directly to inform the generation of a five designs of LysCP2, with between five and six mutations, of which: all retained enzymatic activity; four demonstrated an increase in melting temperature; three demonstrated increased retention of activity after thermal shock. Of the designs, the highest performing improved the melting temperature of LysCP2 from approximately 38 C to 42 C. Third, similar to LysCP2, another cell-wall-degrading enzyme with rich homologous sequence information was optimized for both activity and stability. This enzyme, LysEFm5, has activity against pathogenic and vancomycin-resistant Enterococcus faecium. Again, using coevolutionary models informed from homologous sequences, a collection of combinatorial libraries was generated focusing mutagenesis on sites supporting residues directly involved in interacting with the cell wall. These models were predictive of activity retention across 873 experimentally tested variants (AUC = 0.840 – 0.894). In addition, the accuracy of these models was assessed when systematically varying the type and amount of sequence information utilized, supporting the utility of using pairwise features and providing guidelines for the value of different types of sequences. Lastly, further exploration of random members of these libraries revealed an enhanced clone with 2x higher specific activity in addition to an 11 °C increase in melting temperature in comparison with wild-type LysEFm5. This work provides evidence and methods which support the application of protein engineering to the optimization of antimicrobial proteins to improve their utility as next-generation antimicrobials.


University of Minnesota Ph.D. dissertation. 2019. Major: Chemical Engineering. Advisor: Benjamin Hackel. 1 computer file (PDF); 182 pages.

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Ritter, Seth. (2019). Engineering antimicrobial peptides and enzymes: Realizing opportunities to combat antibiotic resistance through high-throughput, data-driven design and testing. Retrieved from the University Digital Conservancy,

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