Protein production

In order to produce proteins, a cell must first translate the relevant mRNA strand. Following transcription, the mRNA exits the nucleus where each group of three nucleotides is matched to a tRNA molecule carrying an amino acid (Figure 1A). These groups of 3 nucleotides are codons, and each corresponds to an amino acid. Because there are only 20 amino acids and many more possible combinations of nucleotides, there is redundancy in this code (Figure 1B).

Figure 1. Formation of a protein through transcription and translation (A) of codons. Each codon corresponds to an amino acid or direction (start/stop).

Codon bias

Although there are multiple options for making each amino acid, their usage is not based on chance. This is because each species exhibits codon bias, the preference for making an amino acid with a certain codon. For instance, alanine (Ala) is coded by GCU, GCC, GCA, and GCG (Figure 1B), but in humans, GCC is used about 40% of the time. Different organisms have different codon preferences, which influences RNA processing and therefore protein folding and function. This creates complications when expressing one gene in another organism, i.e. heterologous gene expression.

The Codon Adaptation Index (CAI) is a measure of how well given codons match with the biases of an organism, ranging from 0 to 1. A CAI of 1 reflects a coding sequence where all amino acids reflect the most frequently used codons in that organism. Our Codon Optimization tool presents a sequence that balances an optimal CAI with other factors that can influence molecular experiments.

Enhancing cloning efficiency

Codon optimization can also aid in increasing cloning efficiency based on the distribution of nucleotides across the sequence. GC content is an important variable to consider when designing and troubleshooting experiments. If GC content is too high or too low, stability of the query sequence is negatively affected. Our GC Content Calculator tool allows for independent GC analysis over an entire sequence and within segments of a sequence. However, our Codon Optimization tool incorporates this analysis to optimize this variable by finding synonymous codons that increase or decrease GC content as needed.

Additionally, sequences that have a high frequency of repeats can present complications in cloning efforts due to the lack of unique primer binding sites, and sequences with recognition sites for restriction enzymes can present challenges in experimental design. Using our Codon Optimization tool allows for all of these factors to be optimized in unison with codon bias to provide a sequence that is most likely to efficiently produce your protein in your system.