Get Help Sign In

Using a codon optimization tool—how it works and advantages

IDT Codon Optimization Tool

Different organisms exhibit bias towards using certain codons over others for the same amino acid. Taking this fact into account is particularly important for expression studies carried out in a heterologous system. Use the IDT Codon Optimization Tool to rebalance codon usage in your sequence and take advantage of its other benefits.

What is codon optimization?

Codon optimization is defined here as a technique that aims to improve protein expression and reduce sequence complexity in a recombinant gene that may be conserved within certain species without changing the amino acid sequence.

Living cells use a set of rules called the “genetic code” to translate genetic information encoded in DNA and mRNA into proteins. The code consists of nucleotide triplets, called codons, that specify which amino acid should be added to the growing chain of a peptide during protein synthesis.

Why rebalance codon usage?

There are 64 different codons. 61 of them encode the 20 standard amino acids, while another 3 functions as stop codons. The greater number of codons relative to the number of amino acids they code for, means that a single amino acid can be encoded by more than one codon. Indeed, some common amino acids, such as arginine and leucine, are encoded by as many as 6 codons.

Different organisms exhibit bias towards use of certain codons over others for the same amino acid. Some species are known to avoid certain codons almost entirely. The effect codon use has on protein expression is complex and not completely understood; however, they can impact expression significantly. Therefore, it is important to consider codon optimization when performing expression studies.

While numerous factors contribute to the success of protein expression, codon optimization plays a role, particularly when proteins are expressed in a heterologous system.

Codon optimization in Escherichia coli

As an example, if a human gene is to be expressed in E. coli, choosing codons preferentially used by the bacterium can increase the success of protein expression [1,2]. This is particularly true when rare codons are eliminated.

Why is codon optimization important?

Studies also show that translationally efficient codons can increase elongation rate, accuracy of translation, or both [3]. However, it is noteworthy that there are also studies showing no or weak correlations between codon bias and gene expression [4]. These findings suggest that we do not have a comprehensive understanding of the effect of codon usage in all systems. Alternative strategies may have different levels of success in distinct organisms and with different types of expression. While codon optimization can improve protein expression, it does not provide a guarantee.

This is because protein expression levels can be influenced by many factors, including tRNA copies [5], mRNA stability [6], protein folding kinetics [7], protein stability, protein transport, toxicity of the protein within the expression cell environment, and a host of other factors that vary for each protein and organism. As a result, any optimization demands experimental verification.

How does the IDT Codon Optimization Tool work?

The IDT Codon Optimization Tool was developed to optimize a DNA or protein sequence from one organism for expression in another by reassigning codon usage based on the frequencies of each codon’s usage in the new organism. For example, valine is encoded by 4 different codons (GUG, GUU, GUC, and GUA). In human cell lines, however, the GUG codon is preferentially used (46% use vs. 18, 24, and 12%, respectively).

Table 1. Human codon table [8]. Stars (*) denote stop codons.

The codon optimization tool takes this information into account and assigns valine codons with those same frequencies. In addition, the tool algorithm eliminates codons with less than 10% frequency and re-normalizes the remaining frequencies to 100%. Moreover, our optimization tool reduces complexities that can interfere with manufacturing and downstream expression, such as repeats, hairpins, and extreme GC content.

Other advantages provided by IDT Codon Optimization Tool

The IDT Codon Optimization Tool provides several additional features:

  • Input sequence options. You can enter either DNA or amino acid sequences. You can also codon optimize IDT Genes or Gene Fragments (gBlocks™, eBlocks™, gBlocks HiFi Gene Fragments, Megamer™ ssDNA Fragments).
  • Sequence complexity check. You are notified of sequence complexities such as hairpins, repeats, or extreme GC content. The algorithm then provides the best sequence option with minimum complexity.
  • Manual optimization capability. You can use manual mode to have full control over the optimization process.

Contact Us

To order codon optimized sequences or obtain more information about the tool, visit Codon Optimization Tool.

If you are working with an organism not listed in the Codon Optimization Tool’s Organism list, or do not see the information you need, We may be able to accept non-standard optimizations that fall outside of the rules used by the tool.


  1. Burgess-Brown NA, Sharma S, Sobott F, Loenarz C, Oppermann U, Gileadi O. Codon optimization can improve expression of human genes in Escherichia coli: A multi-gene studyProtein Expr Purif. 2008;59(1):94-102. doi:10.1016/j.pep.2008.01.008
  2. Maertens B, Spriestersbach A, von Groll U, et al. Gene optimization mechanisms: a multi-gene study reveals a high success rate of full-length human proteins expressed in Escherichia coliProtein Sci. 2010;19(7):1312-1326. doi:10.1002/pro.408
  3. Plotkin JB, Kudla G. Synonymous but not the same: the causes and consequences of codon bias. Nat Rev Genet. 2011;12(1):32-42. doi:10.1038/nrg2899
  4. Kudla G, Murray AW, Tollervey D, Plotkin JB. Coding-sequence determinants of gene expression in Escherichia coli. Science. 2009;324(5924):255-258. doi:10.1126/science.1170160
  5. Cannarozzi G, Schraudolph NN, et al. (2010) A role for codon order in translation dynamics. Cell, 141:355–367.
  6. Wang Y, Liu CL, et al. (2002) Precision and functional specificity in mRNA decay. Proc Natl Acad Sci USA, 99:5860–5865.
  7. Data for Table 1 taken from Accessed Oct 25, 2022.


Published Jul 14, 2018
Revised/updated Oct 25, 2022