From: Assessing optimal: inequalities in codon optimization algorithms
First author | Optimization algorithma (source) | Target(s) | Number of constructs | Conclusions |
---|---|---|---|---|
Burgess-Brown [40] | Proprietary (Genscript, Sigma, and MediGene) | Various | 30 | • 26% of targets show higher expression of soluble protein for optimized over native CDS in E. coli |
Kudla [27] | CAI | GFP | 154 | • Fluorescence levels span > 1000-fold across different CDSs • No correlation between fluorescence levels and CAI • Modest relationship between mRNA 2° structure and GFP fluorescence |
Welch [28] | PLSR (DNA 2.0) | φ29 DNA polymerase | 21 | • > 100-fold difference in protein yield observed by differently optimized DNAs |
Maertens [41] | CAI (GeneArt) | Various | 100 | • 24% targets showed ≥ 2× yield for optimized CDS • 20% targets showed lower expression for optimized CDS |
Spencer [42] | Undefined | Firefly Luciferase | 7 | • Optimization increased translation speeds ~ 2× with proportional decrease in functional protein • 2–2.5× yield and solubility increase when recoded for frequent codons in Drosophila melanogaster |
Trösemeier [43] | CAI (GeneArt) COSEM | ova manA | 5 11 | • COSEM optimized sequences expressed ≥ 2× the native sequence • “Ramp” inclusion was necessary for significant boost in protein expression |
Konczal [44] | CAI (GeneWiz) | KRas4B RalA Rac1 | 11 11 11 | • “Deoptimization” with ≤ 4 rare codons improves solubility ≥ 4× compared to native CDS |