Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/73774

TítuloModel-guided development of an evolutionarily stable yeast chassis
Autor(es)Pereira, Filipa
Lopes, Hélder
Maia, Paulo
Meyer, Britta
Nocon, Justyna
Jouhten, Paula
Konstantinidis, Dimitrios
Kafkia, Eleni
Rocha, Miguel
Kötter, Peter
Rocha, I.
Patil, Kiran R
Palavras-chaveAdaptive laboratory evolution
Chassis cell
Metabolic engineering
Multi-objective optimization
Systems biology
DataJul-2021
EditoraWiley-Blackwell
RevistaMolecular Systems Biology
CitaçãoPereira, Filipa; Lopes, Hélder; Maia, Paulo; Meyer, Britta; Nocon, Justyna; Jouhten, Paula; Konstantinidis, Dimitrios; Kafkia, Eleni; Rocha, Miguel; Kötter, Peter; Rocha, Isabel; Patil, Kiran R, Model-guided development of an evolutionarily stable yeast chassis. Molecular Systems Biology, 17(7), e10253, 2021
Resumo(s)Abstract First-principle metabolic modelling holds potential for designing microbial chassis that are resilient against phenotype reversal due to adaptive mutations. Yet, the theory of model-based chassis design has rarely been put to rigorous experimental test. Here, we report the development of Saccharomyces cerevisiae chassis strains for dicarboxylic acid production using genome-scale metabolic modelling. The chassis strains, albeit geared for higher flux towards succinate, fumarate and malate, do not appreciably secrete these metabolites. As predicted by the model, introducing product-specific TCA cycle disruptions resulted in the secretion of the corresponding acid. Adaptive laboratory evolution further improved production of succinate and fumarate, demonstrating the evolutionary robustness of the engineered cells. In the case of malate, multi-omics analysis revealed a flux bypass at peroxisomal malate dehydrogenase that was missing in the yeast metabolic model. In all three cases, flux balance analysis integrating transcriptomics, proteomics and metabolomics data confirmed the flux re-routing predicted by the model. Taken together, our modelling and experimental results have implications for the computer-aided design of microbial cell factories.
TipoArtigo
URIhttps://hdl.handle.net/1822/73774
DOI10.15252/msb.202110253
ISSN1744-4292
Versão da editorahttps://www.embopress.org/journal/17444292
Arbitragem científicayes
AcessoAcesso restrito UMinho
Aparece nas coleções:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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