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暴露于动态pH值和葡萄糖环境下的酵母的生理学与稳健性

Physiology and Robustness of Yeasts Exposed to Dynamic pH and Glucose Environments.

作者信息

Torello Pianale Luca, Blöbaum Luisa, Grünberger Alexander, Olsson Lisbeth

机构信息

Department of Life Sciences, Industrial Biotechnology Division, Chalmers University of Technology, Gothenburg, Sweden.

Multiscale Bioengineering, Technical Faculty, Bielefeld University, Bielefeld, Germany.

出版信息

Biotechnol Bioeng. 2025 Jul;122(7):1656-1668. doi: 10.1002/bit.28984. Epub 2025 Apr 11.

DOI:10.1002/bit.28984
PMID:40219637
Abstract

Gradients negatively affect performance in large-scale bioreactors; however, they are difficult to predict at laboratory scale. Dynamic microfluidics single-cell cultivation (dMSCC) has emerged as an important tool for investigating cell behavior in rapidly changing environments. In the present study, dMSCC, biosensors of intracellular parameters, and robustness quantification were employed to investigate the physiological response of three Saccharomyces cerevisiae strains to substrate and pH changes every 0.75-48 min. All strains showed higher sensitivity to substrate than pH oscillations. Strain-specific intracellular responses included higher relative glycolytic flux and oxidative stress response for strains PE2 and CEN.PK113-7D, respectively. Instead, the Ethanol Red strain displayed the least heterogeneous populations and the highest robustness for multiple functions when exposed to substrate oscillations. This result could arise from a positive trade-off between ATP levels and ATP stability over time. The present study demonstrates the importance of coupling physiological responses to dynamic environments with simultaneous characterization of strains, conditions, individual regimes, and robustness analysis. All these tools are a suitable add-on to traditional evaluation and screening workflows at both laboratory and industrial scale, and can help bridge the gap between these two.

摘要

梯度会对大规模生物反应器中的性能产生负面影响;然而,在实验室规模下却很难预测这些梯度。动态微流控单细胞培养(dMSCC)已成为研究细胞在快速变化环境中行为的重要工具。在本研究中,采用dMSCC、细胞内参数生物传感器和稳健性量化方法,每隔0.75 - 48分钟研究三种酿酒酵母菌株对底物和pH变化的生理反应。所有菌株对底物的敏感性均高于对pH振荡的敏感性。菌株特异性的细胞内反应分别包括PE2菌株较高的相对糖酵解通量和CEN.PK113 - 7D菌株较高的氧化应激反应。相反,乙醇红菌株在暴露于底物振荡时,表现出最少的异质群体和最高的多功能稳健性。这一结果可能源于ATP水平与ATP随时间稳定性之间的正向权衡。本研究证明了将生理反应与动态环境相耦合,同时对菌株、条件、个体状态和稳健性分析进行表征的重要性。所有这些工具都是对实验室和工业规模传统评估与筛选工作流程的合适补充,有助于弥合这两者之间的差距。

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本文引用的文献

1
Quantifying microbial robustness in dynamic environments using microfluidic single-cell cultivation.利用微流控单细胞培养技术定量研究动态环境中的微生物鲁棒性。
Microb Cell Fact. 2024 Feb 9;23(1):44. doi: 10.1186/s12934-024-02318-z.
2
Four ways of implementing robustness quantification in strain characterisation.在应变表征中实现稳健性量化的四种方法。
Biotechnol Biofuels Bioprod. 2023 Dec 19;16(1):195. doi: 10.1186/s13068-023-02445-6.
3
Performance and robustness analysis reveals phenotypic trade-offs in yeast.性能和稳健性分析揭示了酵母中的表型权衡。
Life Sci Alliance. 2023 Oct 30;7(1). doi: 10.26508/lsa.202302215. Print 2024 Jan.
4
Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability.与细胞表型转换相关的适应代价驱动种群多样化动态和可控性。
Nat Commun. 2023 Oct 2;14(1):6128. doi: 10.1038/s41467-023-41917-z.
5
EnSor Kit for Engineering and Biosensor-Driven Investigation of the Intracellular Environment.EnSor 试剂盒,用于工程和生物传感器驱动的细胞内环境研究。
ACS Synth Biol. 2023 Aug 18;12(8):2493-2497. doi: 10.1021/acssynbio.3c00124. Epub 2023 Aug 8.
6
Protocol to perform dynamic microfluidic single-cell cultivation of C. glutamicum.动态微流控谷氨酸棒杆菌单细胞培养的方案。
STAR Protoc. 2023 Sep 15;4(3):102436. doi: 10.1016/j.xpro.2023.102436. Epub 2023 Aug 6.
7
Mimicked Mixing-Induced Heterogeneities of Industrial Bioreactors Stimulate Long-Lasting Adaption Programs in Ethanol-Producing Yeasts.模拟工业生物反应器的混合诱导异质性刺激了产乙醇酵母的长期适应程序。
Genes (Basel). 2023 Apr 27;14(5):997. doi: 10.3390/genes14050997.
8
Apparent diameter and cell density of yeast strains with different ploidy.不同倍性酵母菌株的表观直径和细胞密度。
Sci Rep. 2023 Jan 27;13(1):1513. doi: 10.1038/s41598-023-28800-z.
9
An analysis of organism lifelines in an industrial bioreactor using Lattice-Boltzmann CFD.使用格子玻尔兹曼计算流体动力学对工业生物反应器中的生物体生命线进行分析。
Eng Life Sci. 2022 Mar 16;23(1):e2100159. doi: 10.1002/elsc.202100159. eCollection 2023 Jan.
10
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Microb Biotechnol. 2023 Jan;16(1):148-168. doi: 10.1111/1751-7915.14188. Epub 2022 Dec 8.