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Model-guided development of an evolutionarily stable yeast chassis

  • 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.
Metadaten
Author:Filipa PereiraORCiD, Helder LopesORCiD, Paulo MaiaORCiD, Britta MeyerGND, Justyna NoconORCiD, Paula JouhtenORCiDGND, Dimitrios KonstantinidisORCiDGND, Eleni KafkiaORCiDGND, Miguel RochaORCiDGND, Peter KötterORCiD, Isabel RochaORCiD, Kiran Raosaheb PatilORCiDGND
URN:urn:nbn:de:hebis:30:3-628217
DOI:https://doi.org/10.15252/msb.202110253
ISSN:1744-4292
Parent Title (English):Molecular systems biology
Publisher:EMBO Press
Place of publication:Heidelberg
Document Type:Article
Language:English
Date of Publication (online):2021/07/22
Date of first Publication:2021/07/22
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2023/01/20
Tag:adaptive laboratory evolution; chassis cell; metabolic engineering; multi-objective optimization; systems biology
Volume:17
Issue:7, art. e10253
Article Number:e10253
Page Number:18
First Page:1
Last Page:18
Note:
Corresponding author: Rocha, Isabel; Tel: +351 214469608; E-mail: irocha@itqb.unl.pt
Corresponding author: Patil, Kiran Raosaheb; Tel: +44 1223 3 35640; E-mail: kp533@cam.ac.uk
Note:
This study was supported by national funds through FCT/MCTES (Portugal, Ref. ERA-IB-2/0003/2013) and BMBF (Germany, Grant number: 031A343A, Ref. ERA-IB-2/0003/2013). The Portuguese Foundation for Science and Technology (FCT) supported HL through grant ref. PD/BD/52336/2013. FCT also supported this study under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and through the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462). Open Access funding enabled and organized by Projekt DEAL.
HeBIS-PPN:507172965
Institutes:Biowissenschaften / Biowissenschaften
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 4.0