TY - JOUR
T1 - Model-guided development of an evolutionarily stable yeast chassis
AU - Pereira, Filipa
AU - Lopes, Helder
AU - Maia, Paulo
AU - Meyer, Britta
AU - Nocon, Justyna
AU - Jouhten, Paula
AU - Konstantinidis, Dimitrios
AU - Kafkia, Eleni
AU - Rocha, Miguel
AU - Kötter, Peter
AU - Rocha, Isabel
AU - Patil, Kiran R.
N1 - Funding Information:
We would like to acknowledge the support of R. Mattel and F. Stein from the Proteomics Core Facility and the Genomics Core Facility at the European Molecular Biology Laboratory (EMBL Heidelberg, Germany). 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.
Publisher Copyright:
©2021 The Authors. Published under the terms of the CC BY 4.0 license
PY - 2021/7
Y1 - 2021/7
N2 - 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.
AB - 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.
KW - adaptive laboratory evolution
KW - chassis cell
KW - metabolic engineering
KW - multi-objective optimization
KW - systems biology
UR - http://www.scopus.com/inward/record.url?scp=85111502988&partnerID=8YFLogxK
U2 - 10.15252/msb.202110253
DO - 10.15252/msb.202110253
M3 - Article
C2 - 34292675
AN - SCOPUS:85111502988
SN - 1744-4292
VL - 17
JO - MOLECULAR SYSTEMS BIOLOGY
JF - MOLECULAR SYSTEMS BIOLOGY
IS - 7
M1 - e10253
ER -