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Evolved sequence contexts for highly efficient amber suppression with noncanonical amino acids.

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Researchers identified specific DNA sequence contexts that significantly improve the efficiency of incorporating noncanonical amino acids (ncAA) into proteins using amber codon suppression in E. coli. These optimized contexts enhance protein expression and offer robust genetic code expansion strategies.

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Area of Science:

  • Biochemistry
  • Molecular Biology
  • Synthetic Biology

Background:

  • The genetic code can be expanded using noncanonical amino acids (ncAA) for precise protein engineering.
  • Incorporating ncAA via nonsense codon suppression is less efficient than standard translation and its efficiency is poorly understood.
  • The amber stop codon is frequently used for ncAA incorporation.

Purpose of the Study:

  • To identify specific mRNA sequence contexts that enhance amber codon suppression efficiency in E. coli.
  • To understand how local sequence context influences the efficiency of noncanonical amino acid incorporation.
  • To develop general design rules for engineering amber codons for robust genetic code expansion.

Main Methods:

  • In vivo selection of libraries with random codons flanking an amber codon in E. coli.
  • Utilizing orthogonal tRNA/aminoacyl-tRNA-synthetase pairs (e.g., Methanocaldococcus jannaschii tRNA(Tyr)/TyrRS and Methanosarcina mazei tRNA(Pyl)/PylRS).
  • Comparing selection results from amber codons versus sense codons to identify context preferences.

Main Results:

  • Identified sequence contexts with strong preferences for specific mRNA nucleotides and amino acids, differing from sense codon contexts.
  • Achieved highly efficient amber codon suppression (70-110% protein expression) with minimal ncAA dependence.
  • Demonstrated that these optimized contexts are transferable between different proteins.

Conclusions:

  • Specific sequence contexts significantly enhance amber codon suppression efficiency for noncanonical amino acid incorporation in E. coli.
  • These contexts act as stable tags for robust protein expression and genetic code expansion.
  • Provides general design rules for engineering amber codons into genes for improved protein synthesis.