A Comprehensive Mechanistic Yeast Model Able to Switch Metabolism According to Growth Conditions

This paper proposes a general approach for building a mechanistic yeast model able to predict the shift of metabolic pathways. The mechanistic model accounts for the coexistence of several metabolic pathways (aerobic fermentation, glucose respiration, anaerobic fermentation and ethanol respiration)...

Full description

Bibliographic Details
Main Authors: Yusmel González-Hernández, Emilie Michiels, Patrick Perré
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Fermentation
Subjects:
Online Access:https://www.mdpi.com/2311-5637/8/12/710
_version_ 1797459144471478272
author Yusmel González-Hernández
Emilie Michiels
Patrick Perré
author_facet Yusmel González-Hernández
Emilie Michiels
Patrick Perré
author_sort Yusmel González-Hernández
collection DOAJ
description This paper proposes a general approach for building a mechanistic yeast model able to predict the shift of metabolic pathways. The mechanistic model accounts for the coexistence of several metabolic pathways (aerobic fermentation, glucose respiration, anaerobic fermentation and ethanol respiration) whose activation depends on growth conditions. This general approach is applied to a commercial strain of <i>Saccharomyces cerevisiae</i>. Stoichiometry and yeast kinetics were mostly determined from aerobic and completely anaerobic experiments. Known parameters were taken from the literature, and the remaining parameters were estimated by inverse analysis using the particle swarm optimization method. The optimized set of parameters allows the concentrations to be accurately determined over time, reporting global mean relative errors for all variables of less than 7 and 11% under completely anaerobic and aerobic conditions, respectively. Different affinities of yeast for glucose and ethanol tolerance under aerobic and anaerobic conditions were obtained. Finally, the model was successfully validated by simulating a different experiment, a batch fermentation process without gas injection, with an overall mean relative error of 7%. This model represents a useful tool for the control and optimization of yeast fermentation systems. More generally, the modeling framework proposed here is intended to be used as a building block of a digital twin of any bioproduction process.
first_indexed 2024-03-09T16:47:13Z
format Article
id doaj.art-b43bdac03f40487e939e2c336d278133
institution Directory Open Access Journal
issn 2311-5637
language English
last_indexed 2024-03-09T16:47:13Z
publishDate 2022-12-01
publisher MDPI AG
record_format Article
series Fermentation
spelling doaj.art-b43bdac03f40487e939e2c336d2781332023-11-24T14:45:28ZengMDPI AGFermentation2311-56372022-12-0181271010.3390/fermentation8120710A Comprehensive Mechanistic Yeast Model Able to Switch Metabolism According to Growth ConditionsYusmel González-Hernández0Emilie Michiels1Patrick Perré2CentraleSupélec, Laboratoire de Génie des Procédés et Matériaux, SFR Condorcet FR CNRS 3417, Centre Européen de Biotechnologie et de Bioéconomie (CEBB), Université Paris-Saclay, 3 Rue des Rouges Terres, 51110 Pomacle, FranceCentraleSupélec, Laboratoire de Génie des Procédés et Matériaux, SFR Condorcet FR CNRS 3417, Centre Européen de Biotechnologie et de Bioéconomie (CEBB), Université Paris-Saclay, 3 Rue des Rouges Terres, 51110 Pomacle, FranceCentraleSupélec, Laboratoire de Génie des Procédés et Matériaux, SFR Condorcet FR CNRS 3417, Centre Européen de Biotechnologie et de Bioéconomie (CEBB), Université Paris-Saclay, 3 Rue des Rouges Terres, 51110 Pomacle, FranceThis paper proposes a general approach for building a mechanistic yeast model able to predict the shift of metabolic pathways. The mechanistic model accounts for the coexistence of several metabolic pathways (aerobic fermentation, glucose respiration, anaerobic fermentation and ethanol respiration) whose activation depends on growth conditions. This general approach is applied to a commercial strain of <i>Saccharomyces cerevisiae</i>. Stoichiometry and yeast kinetics were mostly determined from aerobic and completely anaerobic experiments. Known parameters were taken from the literature, and the remaining parameters were estimated by inverse analysis using the particle swarm optimization method. The optimized set of parameters allows the concentrations to be accurately determined over time, reporting global mean relative errors for all variables of less than 7 and 11% under completely anaerobic and aerobic conditions, respectively. Different affinities of yeast for glucose and ethanol tolerance under aerobic and anaerobic conditions were obtained. Finally, the model was successfully validated by simulating a different experiment, a batch fermentation process without gas injection, with an overall mean relative error of 7%. This model represents a useful tool for the control and optimization of yeast fermentation systems. More generally, the modeling framework proposed here is intended to be used as a building block of a digital twin of any bioproduction process.https://www.mdpi.com/2311-5637/8/12/710yeastfermentationCrabtree effectswitching metabolismmodelingcalibration
spellingShingle Yusmel González-Hernández
Emilie Michiels
Patrick Perré
A Comprehensive Mechanistic Yeast Model Able to Switch Metabolism According to Growth Conditions
Fermentation
yeast
fermentation
Crabtree effect
switching metabolism
modeling
calibration
title A Comprehensive Mechanistic Yeast Model Able to Switch Metabolism According to Growth Conditions
title_full A Comprehensive Mechanistic Yeast Model Able to Switch Metabolism According to Growth Conditions
title_fullStr A Comprehensive Mechanistic Yeast Model Able to Switch Metabolism According to Growth Conditions
title_full_unstemmed A Comprehensive Mechanistic Yeast Model Able to Switch Metabolism According to Growth Conditions
title_short A Comprehensive Mechanistic Yeast Model Able to Switch Metabolism According to Growth Conditions
title_sort comprehensive mechanistic yeast model able to switch metabolism according to growth conditions
topic yeast
fermentation
Crabtree effect
switching metabolism
modeling
calibration
url https://www.mdpi.com/2311-5637/8/12/710
work_keys_str_mv AT yusmelgonzalezhernandez acomprehensivemechanisticyeastmodelabletoswitchmetabolismaccordingtogrowthconditions
AT emiliemichiels acomprehensivemechanisticyeastmodelabletoswitchmetabolismaccordingtogrowthconditions
AT patrickperre acomprehensivemechanisticyeastmodelabletoswitchmetabolismaccordingtogrowthconditions
AT yusmelgonzalezhernandez comprehensivemechanisticyeastmodelabletoswitchmetabolismaccordingtogrowthconditions
AT emiliemichiels comprehensivemechanisticyeastmodelabletoswitchmetabolismaccordingtogrowthconditions
AT patrickperre comprehensivemechanisticyeastmodelabletoswitchmetabolismaccordingtogrowthconditions