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Duveau F, Cordier C, Chiron L, Le Bec M, Pouzet S, Séguin J, Llamosi A, Sorre B, Di Meglio JM, Hersen P. Yeast cell responses and survival during periodic osmotic stress are controlled by glucose availability. eLife 2024; 12:RP88750. [PMID: 38568203 PMCID: PMC10990491 DOI: 10.7554/elife.88750] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2024] Open
Abstract
Natural environments of living organisms are often dynamic and multifactorial, with multiple parameters fluctuating over time. To better understand how cells respond to dynamically interacting factors, we quantified the effects of dual fluctuations of osmotic stress and glucose deprivation on yeast cells using microfluidics and time-lapse microscopy. Strikingly, we observed that cell proliferation, survival, and signaling depend on the phasing of the two periodic stresses. Cells divided faster, survived longer, and showed decreased transcriptional response when fluctuations of hyperosmotic stress and glucose deprivation occurred in phase than when the two stresses occurred alternatively. Therefore, glucose availability regulates yeast responses to dynamic osmotic stress, showcasing the key role of metabolic fluctuations in cellular responses to dynamic stress. We also found that mutants with impaired osmotic stress response were better adapted to alternating stresses than wild-type cells, showing that genetic mechanisms of adaptation to a persistent stress factor can be detrimental under dynamically interacting conditions.
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Affiliation(s)
- Fabien Duveau
- Laboratoire Matière et Systèmes Complexes, UMR 7057 CNRS & Université Paris Diderot, 10 rue Alice Domon et Léonie DuquetParisFrance
- Laboratoire de Biologie et Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, UMR 5239, Inserm, U1293, Université Claude Bernard Lyon 1, 46 allée d'Italie F-69364LyonFrance
| | - Céline Cordier
- Laboratoire Physico Chimie Curie, UMR168, Institut Curie, 16 rue Pierre et Marie Curie, 75005ParisFrance
| | - Lionel Chiron
- Laboratoire Physico Chimie Curie, UMR168, Institut Curie, 16 rue Pierre et Marie Curie, 75005ParisFrance
| | - Matthias Le Bec
- Laboratoire Physico Chimie Curie, UMR168, Institut Curie, 16 rue Pierre et Marie Curie, 75005ParisFrance
| | - Sylvain Pouzet
- Laboratoire Physico Chimie Curie, UMR168, Institut Curie, 16 rue Pierre et Marie Curie, 75005ParisFrance
| | - Julie Séguin
- Laboratoire Matière et Systèmes Complexes, UMR 7057 CNRS & Université Paris Diderot, 10 rue Alice Domon et Léonie DuquetParisFrance
| | - Artémis Llamosi
- Laboratoire Matière et Systèmes Complexes, UMR 7057 CNRS & Université Paris Diderot, 10 rue Alice Domon et Léonie DuquetParisFrance
| | - Benoit Sorre
- Laboratoire Matière et Systèmes Complexes, UMR 7057 CNRS & Université Paris Diderot, 10 rue Alice Domon et Léonie DuquetParisFrance
- Laboratoire Physico Chimie Curie, UMR168, Institut Curie, 16 rue Pierre et Marie Curie, 75005ParisFrance
| | - Jean-Marc Di Meglio
- Laboratoire Matière et Systèmes Complexes, UMR 7057 CNRS & Université Paris Diderot, 10 rue Alice Domon et Léonie DuquetParisFrance
| | - Pascal Hersen
- Laboratoire Matière et Systèmes Complexes, UMR 7057 CNRS & Université Paris Diderot, 10 rue Alice Domon et Léonie DuquetParisFrance
- Laboratoire Physico Chimie Curie, UMR168, Institut Curie, 16 rue Pierre et Marie Curie, 75005ParisFrance
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Kumar S, Khammash M. Platforms for Optogenetic Stimulation and Feedback Control. Front Bioeng Biotechnol 2022; 10:918917. [PMID: 35757811 PMCID: PMC9213687 DOI: 10.3389/fbioe.2022.918917] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 05/06/2022] [Indexed: 11/13/2022] Open
Abstract
Harnessing the potential of optogenetics in biology requires methodologies from different disciplines ranging from biology, to mechatronics engineering, to control engineering. Light stimulation of a synthetic optogenetic construct in a given biological species can only be achieved via a suitable light stimulation platform. Emerging optogenetic applications entail a consistent, reproducible, and regulated delivery of light adapted to the application requirement. In this review, we explore the evolution of light-induction hardware-software platforms from simple illumination set-ups to sophisticated microscopy, microtiter plate and bioreactor designs, and discuss their respective advantages and disadvantages. Here, we examine design approaches followed in performing optogenetic experiments spanning different cell types and culture volumes, with induction capabilities ranging from single cell stimulation to entire cell culture illumination. The development of automated measurement and stimulation schemes on these platforms has enabled researchers to implement various in silico feedback control strategies to achieve computer-controlled living systems—a theme we briefly discuss in the last part of this review.
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Affiliation(s)
- Sant Kumar
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Basel, Switzerland
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Basel, Switzerland
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Henrion L, Delvenne M, Bajoul Kakahi F, Moreno-Avitia F, Delvigne F. Exploiting Information and Control Theory for Directing Gene Expression in Cell Populations. Front Microbiol 2022; 13:869509. [PMID: 35547126 PMCID: PMC9081792 DOI: 10.3389/fmicb.2022.869509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 04/06/2022] [Indexed: 11/13/2022] Open
Abstract
Microbial populations can adapt to adverse environmental conditions either by appropriately sensing and responding to the changes in their surroundings or by stochastically switching to an alternative phenotypic state. Recent data point out that these two strategies can be exhibited by the same cellular system, depending on the amplitude/frequency of the environmental perturbations and on the architecture of the genetic circuits involved in the adaptation process. Accordingly, several mitigation strategies have been designed for the effective control of microbial populations in different contexts, ranging from biomedicine to bioprocess engineering. Technically, such control strategies have been made possible by the advances made at the level of computational and synthetic biology combined with control theory. However, these control strategies have been applied mostly to synthetic gene circuits, impairing the applicability of the approach to natural circuits. In this review, we argue that it is possible to expand these control strategies to any cellular system and gene circuits based on a metric derived from this information theory, i.e., mutual information (MI). Indeed, based on this metric, it should be possible to characterize the natural frequency of any gene circuits and use it for controlling gene circuits within a population of cells.
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Affiliation(s)
- Lucas Henrion
- Microbial Processes and Interactions (MiPI), Terra Research and Teaching Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Mathéo Delvenne
- Microbial Processes and Interactions (MiPI), Terra Research and Teaching Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Fatemeh Bajoul Kakahi
- Microbial Processes and Interactions (MiPI), Terra Research and Teaching Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Fabian Moreno-Avitia
- Microbial Processes and Interactions (MiPI), Terra Research and Teaching Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Frank Delvigne
- Microbial Processes and Interactions (MiPI), Terra Research and Teaching Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
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Nguyen TM, Telek S, Zicler A, Martinez JA, Zacchetti B, Kopp J, Slouka C, Herwig C, Grünberger A, Delvigne F. Reducing phenotypic instabilities of a microbial population during continuous cultivation based on cell switching dynamics. Biotechnol Bioeng 2021; 118:3847-3859. [PMID: 34129251 DOI: 10.1002/bit.27860] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 06/11/2021] [Accepted: 06/12/2021] [Indexed: 12/19/2022]
Abstract
Predicting the fate of individual cells among a microbial population (i.e., growth and gene expression) remains a challenge, especially when this population is exposed to very dynamic environmental conditions, such as those encountered during continuous cultivation. Indeed, the dynamic nature of a continuous cultivation process implies the potential diversification of the microbial population resulting in genotypic and phenotypic heterogeneity. The present work focused on the induction of the arabinose operon in Escherichia coli as a model system to study this diversification process in continuous cultivations. As a preliminary step, the green fluorescent protein (GFP) level triggered by an arabinose-inducible ParaBAD promoter was tracked by flow cytometry in chemostat cultivations with glucose-arabinose co-feeding. For a wide range of glucose-arabinose co-feeding concentrations in the chemostats, the simultaneous occurrence of GFP positive and negative subpopulation was observed. In the second set of experiments, continuous cultivation was performed by adding glucose continuously and arabinose based on the capability of individual cells to switch from low GFP to high GFP expression states, performed with a technology setup called segregostat. In the segregostat cultivation mode, on-line flow cytometry analysis was used for adjusting the arabinose/glucose transitions based on the phenotypic switching profiles of the microbial population. This strategy allowed finding an appropriate arabinose pulsing frequency, leading to prolonged maintenance of the induction level with a limited increase in the phenotypic diversity for more than 60 generations. The results suggest that the steady forcing of individual cells into a given phenotypic trajectory may not be the best strategy for controlling cell populations. Instead, allowing individual cells to switch periodically around a predefined threshold seems to be a more robust strategy leading to oscillations, but within a predictable cell population behavior range.
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Affiliation(s)
- Thai M Nguyen
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Samuel Telek
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Andrew Zicler
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Juan A Martinez
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Boris Zacchetti
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Julian Kopp
- Christian Doppler Laboratory for Mechanistic and Physiological Methods for Improved Bioprocesses, Institute of Chemical, Environmental and Biological Engineering, Vienna University of Technology, Vienna, Austria
| | - Christoph Slouka
- Christian Doppler Laboratory for Mechanistic and Physiological Methods for Improved Bioprocesses, Institute of Chemical, Environmental and Biological Engineering, Vienna University of Technology, Vienna, Austria
| | - Christoph Herwig
- Christian Doppler Laboratory for Mechanistic and Physiological Methods for Improved Bioprocesses, Institute of Chemical, Environmental and Biological Engineering, Vienna University of Technology, Vienna, Austria.,Research Division Biochemical Engineering, Institute of Chemical Environmental and Bioscience Engineering, Vienna University of Technology, Vienna, Austria
| | - Alexander Grünberger
- Multiscale Bioengineering, Technical Faculty, Bielefeld Germany & CeBiTec, Bielefeld University, Bielefeld, Germany
| | - Frank Delvigne
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
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