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ContiZymes

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Continuous Enzyme Evolution – solving bottlenecks in enzyme engineering to desig...

Continuous Enzyme Evolution – solving bottlenecks in enzyme engineering to design next-generation biocatalysts Directed evolution has revolutionized the application of enzymes in industrial settings by allowing users to tailor the properties and activities of biocatalysts to their needs. But classic directed evolution is notoriously labor-... ver más

30/04/2029

RIJKSUNIVERSITEIT...

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

RIJKSUNIVERSITEIT GRONINGEN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 1 Participantes

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-12-18

Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:

ERC-2023-COG: ERC CONSOLIDATOR GRANTS

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RIJKSUNIVERSITEIT GRONINGEN

2.00M€ | Lider

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Duración del proyecto: 64 meses Fecha Inicio: 2023-12-18
Fecha Fin: 2029-04-30

Líder del proyecto

RIJKSUNIVERSITEIT GRONINGEN

TRL 4-5

Presupuesto del proyecto 2M€

Descripción del proyecto Directed evolution has revolutionized the application of enzymes in industrial settings by allowing users to tailor the properties and activities of biocatalysts to their needs. But classic directed evolution is notoriously labor- and time-intensive, as it manually stages mutation, selection, and amplification cycles. In contrast, continuous evolution (CE) approaches aim to achieve these steps within a replicating organism, making it possible to engineer efficient enzymes in a matter of days rather than months or years. Unfortunately, current CE approaches are typically applicable only to model enzymes with little industrial value. To unleash the full potential of CE, we will develop a scalable, low-tech CE platform, which is readily applicable to biocatalysts that provide value-added products. Toward this end, we will merge a versatile selection system we recently developed with strategies to diversify the genes of targeted enzymes in vivo and an autonomous setup to grow bacterial populations continuously. Combined the resulting CE-platform will enable us to engineer biocatalysts along many and long evolutionary trajectories. Moreover, analyzing the fate of these populations by sequencing will allow us to map the sequence-structure-function relationships of these biocatalysts. Based on the systematic datasets generated in these efforts, we will train machine-learning (ML)-models to predict functional sequences. Lastly, in a ML-directed CE approach, we will establish a design-build-test-learn cycle to improve models and guide CEs toward promising, but otherwise inaccessible sequence spaces. Overall, ContiZymes will overcome unaddressed challenges associated with the application of biocatalysts that promote sought-after C-C, C-halogen, and C-N-bond forming reactions. We will not only engineer these enzymes at an unprecedented rate and scale, but also map their fitness landscapes and take a critical step toward the on-demand design of next-generation biocatalyst

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