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Ingenza Expanding codABLE® Gene Design Algorithm To Aid Recombinant Protein Production in Yeast

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Credit: Ingenza.
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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 game-changing 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 revolutionised protein expression in Bacillus subtilis by maximising expression yields of challenging proteins for its customers, including endotoxin-free manufacture of biologics. codABLE® is achieving the ‘holy grail’ of accurately predicting 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.

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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."