Next-generation engineering of gas-fermenting cell factories through large-scale...
Next-generation engineering of gas-fermenting cell factories through large-scale systems-level maps
Gas fermentation provides a unique opportunity for the circular bioeconomy by enabling carbon recycling from gaseous waste feedstocks into value-added bioproducts using microbes. Acetogens are ideal biocatalysts for gas fermentati...
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Información proyecto GENESYS
Duración del proyecto: 61 meses
Fecha Inicio: 2024-05-24
Fecha Fin: 2029-06-30
Líder del proyecto
TARTU ULIKOOL
No se ha especificado una descripción o un objeto social para esta compañía.
TRL
4-5
Presupuesto del proyecto
2M€
Descripción del proyecto
Gas fermentation provides a unique opportunity for the circular bioeconomy by enabling carbon recycling from gaseous waste feedstocks into value-added bioproducts using microbes. Acetogens are ideal biocatalysts for gas fermentation as they use gas (CO and/or CO2+H2) as their sole carbon and energy source, evidenced by the commercialisation of the waste gas-to-ethanol conversion process. Despite recent efforts, our understanding of genotype-phenotype relationships in acetogens is still minimal. This, however, is required for rational metabolic engineering and expanding the product spectrum of acetogens to unlock their full potential. GENESYS aims to engineer superior gas-fermenting cell factories through revolutionising systems-level understanding of acetogens and pioneering a new workflow for making large-scale arrayed CRISPR-engineered microbial strain libraries. First, essential genes for autotrophy of the model acetogen Clostridium autoethanogenum will be determined using a genome-wide CRISPRi screen. We then create ~750 single-gene knock-down strains of essential genes, transcription factors, and proteome dark matter using a novel pooled-to-arrayed workflow combining synthetic biology, automation, and DNA sequencing. Next, we will generate systems-level phenotype maps for up to ~750 strains through high-throughput gas fermentation and –omics analyses. Big data will be translated into a systems-level acetogen knowledgebase–A-BASE–through integrated bioinformatics and machine learning, metabolic modelling, and data engineering. Finally, we apply A-BASE to engineer acetogen cell factories from the unexplored territories of essential genes, transcription factors, and proteome dark matter for improving production of ethanol and acetone. This project will create superior gas-fermenting cell factories, advance fundamental understanding of acetogen metabolism, and pioneer a new workflow for creating large-scale arrayed engineered microbial strain libraries.