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tRNA Availability

The intracellular supply of charged transfer RNA molecules, which determines translational speed and accuracy for each codon.

tRNA Availability refers to the cellular concentration of aminoacylated (charged) transfer RNA molecules for each codon, which directly governs the speed and fidelity of mRNA translation 1.

How It Works

Each codon in an mRNA is decoded by a cognate tRNA carrying the appropriate amino acid. When a codon is read by a ribosome but its cognate tRNA is scarce, the ribosome stalls at that position. Prolonged stalling can trigger ribosome collisions, mRNA degradation, and premature translation termination.

In E. coli, tRNA gene copy numbers range from one to seven, creating a heterogeneous supply. Highly expressed native genes have evolved to preferentially use codons matched to abundant tRNAs. When a heterologous gene contains many codons decoded by rare tRNAs, it competes for a limited pool, slowing not only its own translation but also that of native essential genes.

Strategies to address tRNA limitation include codon optimization to avoid rare codons, co-expression of rare tRNA genes (as in BL21-CodonPlus or Rosetta strains), and codon harmonization that preserves translational pausing patterns from the donor organism.

Computational Considerations

Ribosome-flow models simulate translation elongation as a function of tRNA concentrations and codon sequence. These models predict queuing bottlenecks and estimate the impact of adding rare-tRNA supplementation plasmids, enabling rational strain design for multi-gene expression systems 2.


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Computational Angle

Codon-level translation simulators model tRNA competition and ribosome queuing to predict how tRNA pools limit heterologous expression and where bottlenecks arise.

Related Terms

References

  1. Dong H. et al.. Co-variation of tRNA abundance and codon usage in Escherichia coli at different growth rates . Journal of Molecular Biology (1996) DOI
  2. Tuller T. et al.. An evolutionarily conserved mechanism for controlling the efficiency of protein translation . Cell (2010) DOI