A Robust Growth-Based Selection Platform to Evolve an Enzyme via Dependency on Noncanonical Tyrosine Analogues

Suzanne C. Jansen, Clemens Mayer*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Growth-based selections evaluate the fitness of individual organisms at a population level. In enzyme engineering, such growth selections allow for the rapid and straightforward identification of highly efficient biocatalysts from extensive libraries. However, selection-based improvement of (synthetically useful) biocatalysts is challenging, as they require highly dependable strategies that artificially link their activities to host survival. Here, we showcase a robust and scalable growth-based selection platform centered around the complementation of noncanonical amino acid-dependent bacteria. Specifically, we demonstrate how serial passaging of populations featuring millions of carbamoylase variants autonomously selects biocatalysts with up to 90,000-fold higher initial rates. Notably, selection of replicate populations enriched diverse biocatalysts, which feature distinct amino acid motifs that drastically boost carbamoylase activity. As beneficial substitutions also originated from unintended copying errors during library preparation or cell division, we anticipate that our growth-based selection platform will be applicable to the continuous, autonomous evolution of diverse biocatalysts in the future.

Original languageEnglish
Article number4c00070
Pages (from-to)1583–1590
Number of pages8
JournalJACS Au
Volume4
Issue number4
Early online date19-Mar-2024
DOIs
Publication statusPublished - 22-Apr-2024

Keywords

  • enzyme engineering
  • directed evolution
  • growth-based selections
  • high throughput
  • carbamoylases
  • biocatalysis
  • synthetic biology

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