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RNA-seq analysis of model-guided engineered Saccharomyces cerevisiae chassis for improved dicarboxylic acids (malic, succinic and fumaric acid) production.

ABSTRACT: RNA-seq analysis of model-guided engineered Saccharomyces cerevisiae chassis for improved dicarboxylic acids (malic, succinic and fumaric acid) production.

PROVIDER: PRJEB40099 | ENA |

REPOSITORIES: ENA

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RNA-seq analysis of model-guided engineered Saccharomyces cerevisiae chassis for improved dicarboxylic acids (malic, succinic and fumaric acid) production.

Project description:Model-guided chassis strain design has the potential to accelerate cellfactory development. In this experiment genetic targets were identified in silico and implemented in vivo to design a yeast chassis strain for enhanced production of succinic, malic and fumaric acid. The phenotype of engineered chassis strains was further optimised through adaptive laboratory evolution. RNA-seq analysis of engineered yeast chassis strains, evolved strains and wild-type (CEN.PK background)was performed to determine the effect of engineered gene deletions and evolution on the transcriptome.

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Project description:<p>Chassis strain suitable for producing multiple compounds is a central concept in synthetic biology. Design of a chassis using computational, first-principle, models is particularly attractive due to the predictability and control it offers, including against phenotype reversal due to adaptive mutations. Yet, the theory of model-based chassis design has rarely been put to rigorous experimental test and assessed at multiomics level. Here, we report two <em>Saccharomyces cerevisiae</em> chassis strains for dicarboxylic acid production based on genome-scale metabolic modelling. The chassis strain, harbouring gene knockouts in serine biosynthesis and in pentose-phosphate pathway, is geared for higher flux towards three target products - succinate, fumarate and malate - but does not appreciably secrete any. Introducing modular product-specific mutations resulted in improved secretion of the corresponding acid as predicted by the model. Adaptive laboratory evolution of the chassis-derived producer cells further improved production for succinate and fumarate attesting to the evolutionary robustness of the underlying growth-product coupling. In the case of malate, which exhibited decreased production during evolution, the multiomics analysis revealed flux bypass at peroxisomal malate dehydrogenase that was not accounted in the model. Integration of transcriptomics, proteomics and metabolomics data showed overall concordance with the flux re-routing predicted by the model. Together, our results provide experimental evidence for model-based design of microbial chassis and have implications for computer-aided design of microbial cell factories.</p>

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Project description:Chassis strain suitable for producing multiple compounds is a central concept in synthetic biology. Design of a chassis using computational, first-principle, models is particularly attractive due to the predictability and control it offers, including against phenotype reversal due to adaptive mutations. Yet, the theory of model-based chassis design has not been put to experimental test. Here, we report two Saccharomyces cerevisiae chassis strains for dicarboxylic acid production based on genome-scale metabolic modelling. The chassis strain, harboring gene knockouts in serine biosynthesis and in pentose-phosphate pathway, is geared for higher flux towards three target products - succinate, fumarate and malate - but does not appreciably secrete any. Introducing modular product-specific mutations resulted in improved secretion of the corresponding acid as predicted by the model. Adaptive laboratory evolution of the chassis-derived producer cells further improved production for succinate and fumarate attesting to the evolutionary robustness of the underlying growth-product coupling. In the case of malate, which exhibited decreased production during evolution, the multi-omics analysis revealed flux bypass at peroxisomal malate dehydrogenase not accounted in the model. Transcriptomics, proteomics and metabolomics analysis showed overall concordance with the flux re-routing predicted by the model. Together, our results provide experimental evidence for model-based design of microbial chassis and have implications for computer-aided design of microbial cell factories.

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