Scottish CRDMO Ingenza has secured innovation funding to adapt its codABLE machine learning platform to precisely control recombinant protein expression in the industrial yeast Pichia pastoris.
This project will accelerate the development of therapeutics, enzymes and other proteins by harnessing machine learning to fine-tune codon usage, ensuring seamless compatibility with the production host and maximising production yields.
Ingenza’s codABLE platform has already enhanced protein expression in Bacillus subtilis by maximising expression yields of challenging proteins for its customers, including endotoxin-free manufacture of biologics.
codABLE is able to accurately predict protein expression from specific gene design, outperforming codon optimisation algorithms operated by commercial DNA synthesis providers. This offers a unique advantage in controlling protein expression without altering regulatory regions, such as promoters or ribosome binding sequences.
Ingenza will use this award from InnovateUK to establish its proven algorithm in P. pastoris, a powerhouse of protein biomanufacturing. To achieve this, the company is deploying rapid, ultra-high throughput screening and next generation sequencing (NGS) to dive deep into millions of gene variants, generating a dataset that will enable codABLE to uncover the link between codon context and protein expression for valuable protein targets.
Rita Cruz, Head of Strain Development at Ingenza, commented: “Ingenza's codABLE machine learning algorithm represents a step change in designing genes for predictable and optimised recombinant expression, a challenge that has hindered engineering biology until now. This approach combines cutting-edge computational technology with Ingenza’s broad expertise in over a dozen biomanufacturing hosts. It is undoubtedly increasing our business competitiveness and accelerating innovations in bio-based manufacturing."
