Quantitative evaluation of yeast's requirement for glycerol formation in very high ethanol performance fed-batch process

<p>Abstract</p> <p>Background</p> <p>Glycerol is the major by-product accounting for up to 5% of the carbon in <it>Saccharomyces cerevisiae </it>ethanolic fermentation. Decreasing glycerol formation may redirect part of the carbon toward ethanol production. However, abolishment of glycerol formation strongly affects yeast's robustness towards different types of stress occurring in an industrial process. In order to assess whether glycerol production can be reduced to a certain extent without jeopardising growth and stress tolerance, the yeast's capacity to synthesize glycerol was adjusted by fine-tuning the activity of the rate-controlling enzyme glycerol 3-phosphate dehydrogenase (GPDH). Two engineered strains whose specific GPDH activity was significantly reduced by two different degrees were comprehensively characterized in a previously developed Very High Ethanol Performance (VHEP) fed-batch process.</p> <p>Results</p> <p>The prototrophic strain CEN.PK113-7D was chosen for decreasing glycerol formation capacity. The fine-tuned reduction of specific GPDH activity was achieved by replacing the native <it>GPD1 </it>promoter in the yeast genome by previously generated well-characterized <it>TEF </it>promoter mutant versions in a <it>gpd2</it>Δ background. Two <it>TEF </it>promoter mutant versions were selected for this study, resulting in a residual GPDH activity of 55 and 6%, respectively. The corresponding strains were referred to here as <it>TEFmut7 </it>and <it>TEFmut2</it>. The genetic modifications were accompanied to a strong reduction in glycerol yield on glucose; the level of reduction compared to the wild-type was 61% in <it>TEFmut7 </it>and 88% in <it>TEFmut2</it>. The overall ethanol production yield on glucose was improved from 0.43 g g^-1in the wild type to 0.44 g g^-1measured in <it>TEFmut7 </it>and 0.45 g g^-1in <it>TEFmut2</it>. Although maximal growth rate in the engineered strains was reduced by 20 and 30%, for <it>TEFmut7 </it>and <it>TEFmut2 </it>respectively, strains' ethanol stress robustness was hardly affected; i.e. values for final ethanol concentration (117 ± 4 g L^-1), growth-inhibiting ethanol concentration (87 ± 3 g L^-1) and volumetric ethanol productivity (2.1 ± 0.15 g l^-1h^-1) measured in wild-type remained virtually unchanged in the engineered strains.</p> <p>Conclusions</p> <p>This work demonstrates the power of fine-tuned pathway engineering, particularly when a compromise has to be found between high product yield on one hand and acceptable growth, productivity and stress resistance on the other hand. Under the conditions used in this study (VHEP fed-batch), the two strains with "fine-tuned" <it>GPD1 </it>expression in a <it>gpd2</it>Δ background showed slightly better ethanol yield improvement than previously achieved with the single deletion strains <it>gpd1</it>Δ or <it>gpd2</it>Δ. Although glycerol reduction is known to be even higher in a <it>gpd1</it>Δ <it>gpd2</it>Δ double deletion strain, our strains could much better cope with process stress as reflected by better growth and viability.</p

Isopropanol production with engineered Cupriavidus necator as bioproduction platform

Alleviating our society’s dependence on petroleum-based chemicals has been highly emphasized due to fossil fuel shortages and increasing greenhouse gas emissions. Isopropanol is a molecule of high potential to replace some petroleum-based chemicals, which can be produced through biological platforms from renewable waste carbon streams such as carbohydrates, fatty acids, or CO2. In this study, for the first time, the heterologous expression of engineered isopropanol pathways were evaluated in a Cupriavidus necator strain Re2133, which was incapable of producing poly-3-hydroxybutyrate [P(3HB)]. These synthetic production pathways were rationally designed through codon optimization, gene placement, and gene dosage in order to efficiently divert carbon flow from P(3HB) precursors toward isopropanol. Among the constructed pathways, Re2133/pEG7c overexpressing native C. necator genes encoding a β-ketothiolase, a CoA-transferase, and codon-optimized Clostridium genes encoding an acetoacetate decarboxylase and an alcohol dehydrogenase produced up to 3.44 g l[superscript -1] isopropanol in batch culture, from fructose as a sole carbon source, with only 0.82 g l[superscript -1] of biomass. The intrinsic performance of this strain (maximum specific production rate 0.093 g g[superscript -1] h[superscript -1], yield 0.32 Cmole Cmole[superscript -1]) corresponded to more than 60 % of the respective theoretical performance. Moreover, the overall isopropanol production yield (0.24 Cmole Cmole[superscript -1]) and the overall specific productivity (0.044 g g[superscript -1] h[superscript -1]) were higher than the values reported in the literature to date for heterologously engineered isopropanol production strains in batch culture. Strain Re2133/pEG7c presents good potential for scale-up production of isopropanol from various substrates in high cell density cultures.United States. Dept. of EnergyMIT-France Seed FundUnited States. Advanced Research Projects Agency-EnergyFrance. Ministère de l'éducation nationale, de l'enseignement supérieur et de la recherche (Post-Doctoral grant)Centre National de la Recherche Scientifique (France

Minimization of Glycerol Production during the High-Performance Fed-Batch Ethanolic Fermentation Process in Saccharomyces cerevisiae, Using a Metabolic Model as a Prediction Tool

On the basis of knowledge of the biological role of glycerol in the redox balance of Saccharomyces cerevisiae, a fermentation strategy was defined to reduce the surplus formation of NADH, responsible for glycerol synthesis. A metabolic model was used to predict the operating conditions that would reduce glycerol production during ethanol fermentation. Experimental validation of the simulation results was done by monitoring the inlet substrate feeding during fed-batch S. cerevisiae cultivation in order to maintain the respiratory quotient (RQ) (defined as the CO(2) production to O(2) consumption ratio) value between 4 and 5. Compared to previous fermentations without glucose monitoring, the final glycerol concentration was successfully decreased. Although RQ-controlled fermentation led to a lower maximum specific ethanol production rate, it was possible to reach a high level of ethanol production: 85 g · liter(−1) with 1.7 g · liter(−1) glycerol in 30 h. We showed here that by using a metabolic model as a tool in prediction, it was possible to reduce glycerol production in a very high-performance ethanolic fermentation process

Multi-objective particle swarm optimization (MOPSO) of lipid accumulation in Fed-batch cultures

Dynamic optimization of fermentation processes could demand the use of multiple criteria to attain certain objectives, which in most cases are conflicting to each other. The use of Pareto optimal sets supplies the necessary information to take decisions about the trade-offs between objectives. In this work, a multi-objective optimization algorithm based on particle swarm optimization (MOPSO) is used to optimize lipid contents in fermentations with Yarrowia lipolytica. A reduced model was developed to shorten the computation time of MOPSO. A pattern search algorithm was sequentially coupled to MOPSO to execute a dynamic optimization handling physical constraints. Three cases are analyzed to emphasize the response of our control strategy. Simulation results showed that MOPSO - pattern search algorithm achieved high lipid fraction and productivity

Dynamic metabolic modeling of lipid accumulation and citric acid production by Yarrowia lipolytica

International audienceYarrowia lipolytica has the capacity to accumulate large amounts of lipids triggered by a depletion of nitrogen in excess of carbon source. However, under similar conditions this yeast also produces citric acid decreasing the lipid conversion yield. Three dynamic metabolic models are presented to describe lipid accumulation and citric acid production by Yarrowia lipolytica. First and second models were respectively based on the Hybrid Cybernetic Modeling (HCM) and the Macroscopic Bioreaction Modeling (MBM) approaches. The third model was a new approach based on the coupling between MBM and fuzzy sets. Simulation results of the three models fitted acceptably the experimental data sets for calibration and validation. However, MBM is time-dependent to consider metabolic shifts, and thus impractical for further applications. HCM and Fuzzy MBM adequately managed and described metabolic shifts presenting highlighting features for control and optimization. HCM and Fuzzy MBM were statistically compared reflecting similar results