Conventional methods focus mostly on maximizing translation speed by using the host’s most-preferred codons, which may not be optimal for protein quality or expression efficiency.
The PCO uniquely considers preserving protein conformation and strategically balances it with improving translation efficiency and other desirable properties to generate optimal sequences for different platforms and applications.
The PCO consistently outperforms leading alternatives in both protein quantity and quality across different platforms including mRNA, providing a powerful and versatile tool for optimizing protein expression processes.
Codon optimization is a crucial technology for many protein manufacturing and vaccine platforms, such as recombinant and mRNA vaccines, due to its ability to modulate gene expression levels without changing the amino-acid sequence. Without proper optimization for native genome sequences, protein expression in host cells can be severely limited or nonexistent. Conversely, codon deoptimization is an effective method for attenuating harmful viral activities, such as toxin production or replication ability, to create safe and effective live-attenuated vaccine candidates.
In gene translation, only 2 amino-acids are encoded by a single unique codon, while the other 18 amino-acids have more than one corresponding codon, known as synonymous codons. In a host cell, the tRNA molecules corresponding to the different codons for the same amino-acid mostly do not present in equal abundance, causing differences in translation efficiency depending on the chosen codon. This phenomenon of specific synonymous codons used more than randomly is known as codon usage bias. Codon (de)optimization refers to the process of substituting synonymous codons to achieve desired effect on both gene expression and the properties of nucleic acid molecules, which is important in almost all protein expression processes. In particular, codon replacement also alters the minimum free energy of gene molecules, thereby affecting their stability and half-life after entering host cells.
Conventional codon optimization methods focus primarily on switching most codons to the host’s preferred codons, which typically correspond to the tRNAs with the highest availability, and thereby theoretically maximizes gene translation efficiency. However, in practical applications, this approach often produces suboptimal and even at times completely opposite effects to protein expression. In some cases, proteins are expressed in large quantities but may not be functional.
BethBio’s scientists discovered that maximizing translation efficiency is not always beneficial for expression in terms of protein conformation. Changes in translation speed also affect protein folding. Excessive and reckless increases in translation speed can lead to errors in conformation of expressed proteins. Strategic and precise replacement of codons at different positions with the host’s more-preferred – but not necessarily the most preferred – could preserve protein conformation better and improve yield. Based on this principle, BethBio developed the Protein Codon Optimization (PCO) algorithm, which uniquely considers preserving protein conformation when deciding the substitution of codon for each position on the sequence. The PCO also additionally considers and balances other important aspects of codon optimization such as splicing sites and reducing minimum free energy for mRNA molecules, to produce the optimal sequence that is tailored to meet the specific requirements of different platforms and applications.
By optimizing protein expression levels while preserving correct protein structure, the PCO algorithm enhances protein quality on top of improved manufacturing speed and efficiency. With more functional proteins, increased expression efficiency, and potentially longer half-life for nucleic acid molecules for continuous expression, the PCO also delivers qualitative improvements to vaccines in forms such as reduced dosage, lower side effects, and fewer administration cycles for therapeutic vaccine recipients.
The PCO algorithm consistently outperforms competing codon optimization methods in both quality and quantity. In one experiment using DNA platform, the PCO-optimized sequence achieved expression levels in Western Blot that were 2.2 times and 1.9 times of representative methods A and B in the field, respectively, and 2.1 times of our client’s in-house optimized sequence.
In another experiment using mRNA platform, the PCO-optimized sequence achieved in Western Blot 2.2 times and 1.7 times of the expression level of methods A and representative method C respectively. Conducting ELISA using the same sets of optimized sequences, the PCO sequence generated 1.9 to 2.8 times expression level compared to one of the alternative methods, while the sequence of the other method generated expression levels similar to the negative control, indicating the absence of functional proteins.
In the ELISA result of a mRNA in vivo experiment conducted by our client, the PCO-optimized sequence generated 2.3 times and 1.9 times the response compared to wildtype and alternative methods’ codon optimization respectively after administering first dose; then generated 2.4 times and 1.6 times that of wildtype and the alternative sequences respectively after booster dose. The results were also confirmed by Western Blot. These outcomes align with the scientific rationale behind the PCO, which emphasizes maintaining correct protein conformation while enhancing expression efficiency to ensure protein quality and functionality.
With BethBio’s Protein Codon Optimization (PCO) algorithm, you can achieve superior protein expression that balances quantity, quality, and functionality. Whether you’re developing vaccines, therapeutic proteins, or other biotechnology products, our technology will help obtain optimal results for your applications. Contact us today at business@bethbio.com to explore how PCO can transform your protein expression processes and advance your innovations.