A Major Controversy in Codon-Anticodon Adaptation Resolved by a New Codon Usage Index

Abstract

Two alternative hypotheses attribute different benefits to codon-anticodon adaptation. The first assumes that protein production is rate limited by both initiation and elongation and that codon-anticodon adaptation would result in higher elongation efficiency and more efficient and accurate protein production, especially for highly expressed genes. The second claims that protein production is rate limited only by initiation efficiency but that improved codon adaptation and, consequently, increased elongation efficiency have the benefit of increasing ribosomal availability for global translation. To test these hypotheses, a recent study engineered a synthetic library of 154 genes, all encoding the same protein but differing in degrees of codon adaptation, to quantify the effect of differential codon adaptation on protein production in Escherichia coli. The surprising conclusion that “codon bias did not correlate with gene expression” and that “translation initiation, not elongation, is rate-limiting for gene expression” contradicts the conclusion reached by many other empirical studies. In this paper, I resolve the contradiction by reanalyzing the data from the 154 sequences. I demonstrate that translation elongation accounts for about 17% of total variation in protein production and that the previous conclusion is due to the use of a codon adaptation index (CAI) that does not account for the mutation bias in characterizing codon adaptation. The effect of translation elongation becomes undetectable only when translation initiation is unrealistically slow. A new index of translation elongation ITE is formulated to facilitate studies on the efficiency and evolution of the translation machinery.

Rapid Sampling of Escherichia coli After Changing Oxygen Conditions Reveals Transcriptional Dynamics

“…In our data, the estimated TERs negatively correlate with CAI (Table 1). The same holds for the more recent ITE [40]). All other correlations concerning expression levels, sequence features, sigma factors, and regulators were not significant ( p value > 0.05).…”

“…The index of translation elongation (ITE) was calculated as stated in [40] using the provided data set. Folding energies were calculated from sequences using the ViennaRNA package [41,42].…”

Bioinformatics and Drug Discovery

“…Transcriptomic data once spawned the hope that proteomic data can be predicted from transcriptomic data, but differential translation efficiencies among mRNA [168, 184] and degradation efficiencies among proteins distort the relationship between mRNA abundance and protein abundance. However, ribosome profiling data, coupled with transcriptomic data, are expected to generate good predictions of protein production rate.…”

Bioinformatics and Drug Discovery

“…Proteomic data have been obtained from nearly all model organisms and deposited in public databases such as PaxDB [170]. Such data have greatly facilitated the development [168] and application of indices predicting translation efficiency [171][172][173].…”

“…However, for an mRNA with poor codon usage, ribosomes may move slowly and become densely packed along the mRNA. For this reason, elongation efficiency needs to be controlled for, e.g., by regressing ribosome density on the index of translate elongation [168]. Ribosome profiling data are useful in characterizing regulatory motifs such as poly(A) tract that modulate translation efficiency [167], e.g., short poly(A) at 5' UTR may facilitate the recruitment of translation initiation factors and enhance translation, but long poly(A) may bind to poly(A)-binding proteins and inhibit translation.…”