Deep Antimicrobial Activity and Stability Analysis Inform Lysin Sequence-Function Mapping

Daniel T. Tresnak, Benjamin J. Hackel

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Antibiotic-resistant infectious disease is a critical challenge to human health. Antimicrobial proteins offer a compelling solution if engineered for potency, selectivity, and physiological stability. Lysins, which lyse cells via degradation of cell wall peptidoglycans, have significant potential to fill this role. Yet, the functional complexity of antimicrobial activity has hindered high-throughput characterization for discovery and design. To dramatically expand knowledge of the sequence-function landscape of lysins, we developed a depletion-based assay for library-scale measurement of lysin inhibitory activity. We coupled this platform with a high-throughput proteolytic stability assay to assess the activity and stability of ∼5 × 104 lysin catalytic domain variants, resulting in the discovery of a variant with increased activity (70 ± 20%) and stability (7.2 ± 0.4 °C increased midpoint of thermal denaturation). Ridge regression of the resulting data set demonstrated that libraries with a higher average Hamming distance better informed pairwise models and that coupling activity and stability assays enabled better prediction of catalytically active lysins. The best models achieved Pearson’s correlation coefficients of 0.87 ± 0.01 and 0.61 ± 0.04 for predicting catalytic domain stability and activity, respectively. Our work provides an efficient strategy for constructing protein sequence-function landscapes, drastically increases screening throughput for engineering lysins, and yields promising lysins for further development.

Original languageEnglish (US)
Pages (from-to)249-264
Number of pages16
JournalACS Synthetic Biology
Volume12
Issue number1
DOIs
StatePublished - Jan 20 2023

Bibliographical note

Funding Information:
The research was supported by a grant from the National Institutes of Health (R01 GM121777). The authors appreciate assistance from the University of Minnesota Genomics Center and the Minnesota Supercomputing Institute.

Publisher Copyright:
© 2023 American Chemical Society.

Keywords

  • antimicrobial protein
  • lysin
  • mutational scanning
  • sequence−function mapping

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

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