The Problem

Codon optimization is an indispensable process in modern biotechnology and biomedicine tackling low expression yields of recombinant proteins, which has long hampered biomedical research and product development. The root cause of codon bias in each organism is attributed to the degeneracy of the genetic code, and codon optimisation resolves this through the strategy of using synonymous codons whilst maintaining the original protein sequence. To make the most out of this strategy, efficient algorithms are needed to calculate a coding sequence, combining different requirements, such as adapted codon usage (substituting rare codons with more frequent ones) or avoidance of restriction sites, in the best possible way.

Current optimization tools are plagued with numerous problems. Free codon optimization provided by synthetic gene companies perform unreliably and does not provide the customer with insights on the intricate workings of the software. This black box hinders scientists from knowing what has been done to their sequences; it is not good scientific practice to press a button in a piece of software and interpret the results without understanding what the software does.

The Solution

Codon Usage Optimizer (CUO) focuses on providing usability, performance and flexibility to molecular biologists. It features modular codon optimization tools that can be created, posted, reused, revised, improved and shared without any limitation. The open source platform provides a melting pot for the evolution of sequence optimization technology, which is steadily taking off owing to the falling price of gene sequencing and synthesis.

In addition, services are included such as one-on-one & group training, consulting, and technical support tailored to tackle issues around the genome optimization project.

With the price of DNA sequencing and synthesis falling rapidly, codon optimisation will gradually become a more attractive protocol for academia and industry to adopt. One of the main advantages of de novo gene synthesis is the fact that researchers are freed from any limitations imposed by the use of natural templates. Below is a summary of CUO’s advantages:

• Reliable expression
• Increased protein yield
• Protein solubility unaffected
• Unaltered functionality

Apart from that, optimised synthetic genes have also become an invaluable tool in RNAi work. By performing gene ‘silencing and rescue’ experiments, researchers can differentiate between a true cellular phenotype and so-called off-target effects, since siRNA may conjointly trigger a multitude of unspecific secondary mechanisms. Optimised genes have also contributed a fair share to HIV research, by increasing the stability of certain mRNAs by orders of magnitude.

References

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