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Updated: Jun 12, 2026

Directed Evolution Method in Saccharomyces cerevisiae: Mutant Library Creation and Screening
10:50

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Published on: April 1, 2016

Evolution and Active Learning Identify Terminal and Distal Determinants for Improved TAL in P-Coumaric Acid

Huiru Yuan1,2,3, Yiting Shen1,2,3, Donglian Lai1,2,3

  • 1Zhejiang Key Laboratory of Bioorganic Synthesis, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, People's Republic of China.

Biotechnology and Bioengineering
|June 11, 2026
PubMed
Summary

We engineered tyrosine ammonia-lyase (TAL) for sustainable p-coumaric acid (p-CA) production. Our "evolution-to-design" approach significantly improved enzyme efficiency and stability for industrial applications.

Keywords:
N‐terminal modulationprotein engineeringp‐Coumaric acidtyrosine ammonia‐lyase

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Published on: October 24, 2016

Area of Science:

  • Biocatalysis and Enzyme Engineering
  • Synthetic Biology
  • Metabolic Engineering

Background:

  • p-Coumaric acid (p-CA) is a valuable phenylpropanoid platform chemical with diverse industrial applications.
  • Microbial biosynthesis offers a sustainable alternative to plant extraction for p-CA production.
  • Tyrosine ammonia-lyase (TAL) enzymes catalyze the conversion of L-tyrosine to p-CA but often exhibit low efficiency and poor stability.

Purpose of the Study:

  • To optimize Rhodotorula glutinis TAL (RglTAL) for enhanced activity and robustness using an integrated "evolution-to-design" strategy.
  • To investigate the impact of terminal-region engineering and rational design on RglTAL performance.
  • To develop a generalizable framework for enzyme optimization in bioprocesses.

Main Methods:

  • Evolutionary analysis to identify regions under selection pressure.
  • Terminal-region engineering, including N-terminal truncation and replacement.
  • Active learning-guided semi-rational design combined with AI-assisted screening.
  • Molecular dynamics simulations to elucidate mechanisms of improvement.

Main Results:

  • N-terminal truncation of RglTAL increased whole-cell activity by 31.0% and thermal stability (Tm) by 1.0°C.
  • AI-identified triple substitution (G30N, Q387A, L609A) enhanced specific activity by 63.7% and Tm by 3.4°C.
  • Combining N-terminal truncation with the triple mutation yielded a final specific activity of 0.36 U/mg.

Conclusions:

  • The optimized RglTAL exhibits significantly improved catalytic efficiency and stability.
  • The "evolution-to-design" workflow effectively integrates evolutionary insights with data-driven design for enzyme optimization.
  • This study provides a robust TAL biocatalyst and a versatile strategy for developing enzymes for bioprocess applications.