Heat of reaction in individual metabolic pathways of yeast determined by mechanistic modeling in an insulated bioreactor

IF 6.1 1区 工程技术 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Biotechnology for Biofuels Pub Date : 2024-11-25 DOI:10.1186/s13068-024-02580-8
Yusmel González-Hernández, Emilie Michiels, Patrick Perré
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引用次数: 0

Abstract

Background

The yeast Saccharomyces cerevisiae, commonly used in industry, exhibits complex metabolism due to the Crabtree effect, fermenting alcohol even under aerobic conditions when glucose exceeds 0.10-0.15 g/L. The heat released by the biological activity is a signal very easy to collect, given the minimal instrumentation requirements. However, this heat depends on the activated metabolic pathways and provides only an indirect indicator, that cannot be used in a simple way. This study demonstrated the potential of a mechanistic model to control the process by measuring the heat released by the biological activity.

Results

The complexity arising from coexisting metabolic pathways was addressed by a comprehensive model of Saccharomyces cerevisiae together with the heat of reaction included in a rigorous enthalpy balance of the bioreactor. Batch cultures were performed in an insulated bioreactor to trigger a temperature signal. The heat of individual metabolic pathways was determined by inverse analysis of these tests using Particle Swarm Optimization (PSO): -101.28 ±0.02kJ/mol for anaerobic fermentation, -231.27±0.06kJ/mol for aerobic fermentation, and -662.94 ± 0.54kJ/mol for ethanol respiration. Finally, the model was successfully applied and validated for online training under different operating conditions.

Conclusions

The model demonstrates remarkable accuracy, with a mean relative error under 0.38% in temperature predictions for both anaerobic and aerobic conditions. The viscous dissipation is a key parameter specific to the bioreactor and the growth conditions. However, we demonstrated that this parameter could be fitted accurately from the early stages of the experiment for further prediction of the remaining part. This model introduces temperature, or the thermal power required to maintain temperature, as a measurable parameter for online feedback model training to provide increasingly precise feed-forward control.

Graphical Abstract

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在保温生物反应器中通过机理建模确定酵母各个代谢途径的反应热
背景工业中常用的酿酒酵母因克拉布特里效应而表现出复杂的新陈代谢,即使在有氧条件下,当葡萄糖超过 0.10-0.15 克/升时也能发酵酒精。生物活动释放的热量是一种非常容易收集的信号,因为对仪器的要求极低。然而,这种热量取决于被激活的代谢途径,只能提供一个间接指标,不能简单地加以利用。本研究通过测量生物活性释放的热量,展示了机械模型控制过程的潜力。结果通过建立一个全面的酿酒酵母模型,并将反应热纳入生物反应器的严格焓平衡中,解决了共存代谢途径带来的复杂性。批量培养在绝缘生物反应器中进行,以触发温度信号。通过使用粒子群优化(PSO)对这些测试进行反分析,确定了各个代谢途径的热量:厌氧发酵为-101.28±0.02kJ/mol,好氧发酵为-231.27±0.06kJ/mol,乙醇呼吸为-662.94±0.54kJ/mol。最后,该模型成功应用于不同运行条件下的在线训练并进行了验证。粘性耗散是生物反应器和生长条件特有的关键参数。不过,我们证明,从实验的早期阶段就可以准确地拟合这一参数,以进一步预测其余部分。该模型引入了温度或维持温度所需的热功率,作为在线反馈模型训练的可测量参数,以提供越来越精确的前馈控制。
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来源期刊
Biotechnology for Biofuels
Biotechnology for Biofuels 工程技术-生物工程与应用微生物
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审稿时长
2.7 months
期刊介绍: Biotechnology for Biofuels is an open access peer-reviewed journal featuring high-quality studies describing technological and operational advances in the production of biofuels, chemicals and other bioproducts. The journal emphasizes understanding and advancing the application of biotechnology and synergistic operations to improve plants and biological conversion systems for the biological production of these products from biomass, intermediates derived from biomass, or CO2, as well as upstream or downstream operations that are integral to biological conversion of biomass. Biotechnology for Biofuels focuses on the following areas: • Development of terrestrial plant feedstocks • Development of algal feedstocks • Biomass pretreatment, fractionation and extraction for biological conversion • Enzyme engineering, production and analysis • Bacterial genetics, physiology and metabolic engineering • Fungal/yeast genetics, physiology and metabolic engineering • Fermentation, biocatalytic conversion and reaction dynamics • Biological production of chemicals and bioproducts from biomass • Anaerobic digestion, biohydrogen and bioelectricity • Bioprocess integration, techno-economic analysis, modelling and policy • Life cycle assessment and environmental impact analysis
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