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Struyfs C, Breukers J, Spasic D, Lammertyn J, Cammue BPA, Thevissen K. Multiplex Analysis to Unravel the Mode of Antifungal Activity of the Plant Defensin HsAFP1 in Single Yeast Cells. Int J Mol Sci 2022; 23:ijms23031515. [PMID: 35163438 PMCID: PMC8836000 DOI: 10.3390/ijms23031515] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 01/24/2022] [Accepted: 01/26/2022] [Indexed: 02/04/2023] Open
Abstract
Single cell analyses have gained increasing interest over bulk approaches because of considerable cell-to-cell variability within isogenic populations. Herein, flow cytometry remains golden standard due to its high-throughput efficiency and versatility, although it does not allow to investigate the interdependency of cellular events over time. Starting from our microfluidic platform that enables to trap and retain individual cells on a fixed location over time, here, we focused on unraveling kinetic responses of single Saccharomyces cerevisiae yeast cells upon treatment with the antifungal plant defensin HsAFP1. We monitored the time between production of reactive oxygen species (ROS) and membrane permeabilization (MP) in single yeast cells for different HsAFP1 doses using two fluorescent dyes with non-overlapping spectra. Within a time frame of 2 min, only <0.3% cells displayed time between the induction of ROS and MP. Reducing the time frame to 30 s did not result in increased numbers of cells with time between these events, pointing to ROS and MP induction as highly dynamic and correlated processes. In conclusion, using an in-house developed continuous microfluidic platform, we investigated the mode of action of HsAFP1 at single cell level, thereby uncovering the close interdependency between ROS induction and MP in yeast.
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Affiliation(s)
- Caroline Struyfs
- Centre of Microbial and Plant Genetics, Department of Microbial and Molecular Systems (MS), KU Leuven, Kasteelpark Arenberg 20, 3001 Leuven, Belgium; (C.S.); (B.P.A.C.)
| | - Jolien Breukers
- Biosensors Group, Department of Biosystems (BIOSYST), KU Leuven, Willem de Croylaan 42, 3001 Leuven, Belgium; (J.B.); (D.S.); (J.L.)
| | - Dragana Spasic
- Biosensors Group, Department of Biosystems (BIOSYST), KU Leuven, Willem de Croylaan 42, 3001 Leuven, Belgium; (J.B.); (D.S.); (J.L.)
| | - Jeroen Lammertyn
- Biosensors Group, Department of Biosystems (BIOSYST), KU Leuven, Willem de Croylaan 42, 3001 Leuven, Belgium; (J.B.); (D.S.); (J.L.)
| | - Bruno P. A. Cammue
- Centre of Microbial and Plant Genetics, Department of Microbial and Molecular Systems (MS), KU Leuven, Kasteelpark Arenberg 20, 3001 Leuven, Belgium; (C.S.); (B.P.A.C.)
| | - Karin Thevissen
- Centre of Microbial and Plant Genetics, Department of Microbial and Molecular Systems (MS), KU Leuven, Kasteelpark Arenberg 20, 3001 Leuven, Belgium; (C.S.); (B.P.A.C.)
- Correspondence: ; Tel.: +32-16-32-96-88
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Shaban K, Sauty SM, Yankulov K. Variation, Variegation and Heritable Gene Repression in S. cerevisiae. Front Genet 2021; 12:630506. [PMID: 33747046 PMCID: PMC7970126 DOI: 10.3389/fgene.2021.630506] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 02/08/2021] [Indexed: 11/13/2022] Open
Abstract
Phenotypic heterogeneity provides growth advantages for a population upon changes of the environment. In S. cerevisiae, such heterogeneity has been observed as "on/off" states in the expression of individual genes in individual cells. These variations can persist for a limited or extended number of mitotic divisions. Such traits are known to be mediated by heritable chromatin structures, by the mitotic transmission of transcription factors involved in gene regulatory circuits or by the cytoplasmic partition of prions or other unstructured proteins. The significance of such epigenetic diversity is obvious, however, we have limited insight into the mechanisms that generate it. In this review, we summarize the current knowledge of epigenetically maintained heterogeneity of gene expression and point out similarities and converging points between different mechanisms. We discuss how the sharing of limiting repression or activation factors can contribute to cell-to-cell variations in gene expression and to the coordination between short- and long- term epigenetic strategies. Finally, we discuss the implications of such variations and strategies in adaptation and aging.
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Affiliation(s)
- Kholoud Shaban
- Department of Molecular and Cellular Biology, University of Guelph, Guelph, ON, Canada
| | - Safia Mahabub Sauty
- Department of Molecular and Cellular Biology, University of Guelph, Guelph, ON, Canada
| | - Krassimir Yankulov
- Department of Molecular and Cellular Biology, University of Guelph, Guelph, ON, Canada
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Hellweger FL. Combining Molecular Observations and Microbial Ecosystem Modeling: A Practical Guide. ANNUAL REVIEW OF MARINE SCIENCE 2020; 12:267-289. [PMID: 31226029 DOI: 10.1146/annurev-marine-010419-010829] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
Advances in technologies for molecular observation are leading to novel types of data, including gene, transcript, protein, and metabolite levels, which are fundamentally different from the types traditionally compared with microbial ecosystem models, such as biomass (e.g., chlorophyll a) and nutrient concentrations. A grand challenge is to use these data to improve predictive models and use models to explain observed patterns. This article presents a framework that aligns observations and models along the dimension of abstraction or biological organization-from raw sequences to ecosystem patterns for observations, and from sequence simulators to ecological theory for models. It then reviews 16 studies that compared model results with molecular observations. Molecular data can and are being combined with microbial ecosystem models, but to keep up with and take advantage of the full scope of observations, models need to become more mechanistically detailed and complex, which is a technical and cultural challenge for the ecological modeling community.
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Affiliation(s)
- Ferdi L Hellweger
- Specialty Area of Water Quality Engineering (Wasserreinhaltung), Institute of Environmental Science and Engineering, Technical University of Berlin, 10623 Berlin, Germany;
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Heins AL, Weuster-Botz D. Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives. Bioprocess Biosyst Eng 2018. [PMID: 29541890 DOI: 10.1007/s00449-018-1922-3] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Population heterogeneity is omnipresent in all bioprocesses even in homogenous environments. Its origin, however, is only so well understood that potential strategies like bet-hedging, noise in gene expression and division of labour that lead to population heterogeneity can be derived from experimental studies simulating the dynamics in industrial scale bioprocesses. This review aims at summarizing the current state of the different parts of single cell studies in bioprocesses. This includes setups to visualize different phenotypes of single cells, computational approaches connecting single cell physiology with environmental influence and special cultivation setups like scale-down reactors that have been proven to be useful to simulate large-scale conditions. A step in between investigation of populations and single cells is studying subpopulations with distinct properties that differ from the rest of the population with sub-omics methods which are also presented here. Moreover, the current knowledge about population heterogeneity in bioprocesses is summarized for relevant industrial production hosts and mixed cultures, as they provide the unique opportunity to distribute metabolic burden and optimize production processes in a way that is impossible in traditional monocultures. In the end, approaches to explain the underlying mechanism of population heterogeneity and the evidences found to support each hypothesis are presented. For instance, population heterogeneity serving as a bet-hedging strategy that is used as coordinated action against bioprocess-related stresses while at the same time spreading the risk between individual cells as it ensures the survival of least a part of the population in any environment the cells encounter.
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Affiliation(s)
- Anna-Lena Heins
- Institute of Biochemical Engineering, Technical University of Munich, Boltzmannstr. 15, 85748, Garching, Germany.
| | - Dirk Weuster-Botz
- Institute of Biochemical Engineering, Technical University of Munich, Boltzmannstr. 15, 85748, Garching, Germany
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Ginovart M, Carbó R, Blanco M, Portell X. Digital Image Analysis of Yeast Single Cells Growing in Two Different Oxygen Concentrations to Analyze the Population Growth and to Assist Individual-Based Modeling. Front Microbiol 2018; 8:2628. [PMID: 29354112 PMCID: PMC5758558 DOI: 10.3389/fmicb.2017.02628] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Accepted: 12/15/2017] [Indexed: 11/22/2022] Open
Abstract
Nowadays control of the growth of Saccharomyces to obtain biomass or cellular wall components is crucial for specific industrial applications. The general aim of this contribution is to deal with experimental data obtained from yeast cells and from yeast cultures to attempt the integration of the two levels of information, individual and population, to progress in the control of yeast biotechnological processes by means of the overall analysis of this set of experimental data, and to assist in the improvement of an individual-based model, namely, INDISIM-Saccha. Populations of S. cerevisiae growing in liquid batch culture, in aerobic and microaerophilic conditions, were studied. A set of digital images was taken during the population growth, and a protocol for the treatment and analyses of the images obtained was established. The piecewise linear model of Buchanan was adjusted to the temporal evolutions of the yeast populations to determine the kinetic parameters and changes of growth phases. In parallel, for all the yeast cells analyzed, values of direct morphological parameters, such as area, perimeter, major diameter, minor diameter, and derived ones, such as circularity and elongation, were obtained. Graphical and numerical methods from descriptive statistics were applied to these data to characterize the growth phases and the budding state of the yeast cells in both experimental conditions, and inferential statistical methods were used to compare the diverse groups of data achieved. Oxidative metabolism of yeast in a medium with oxygen available and low initial sugar concentration can be taken into account in order to obtain a greater number of cells or larger cells. Morphological parameters were analyzed statistically to identify which were the most useful for the discrimination of the different states, according to budding and/or growth phase, in aerobic and microaerophilic conditions. The use of the experimental data for subsequent modeling work was then discussed and compared to simulation results generated with INDISIM-Saccha, which allowed us to advance in the development of this yeast model, and illustrated the utility of data at different levels of observation and the needs and logic behind the development of a microbial individual-based model.
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Affiliation(s)
- Marta Ginovart
- Department of Mathematics, Universitat Politècnica de Catalunya, Barcelona, Spain
| | - Rosa Carbó
- Department of Agri-Food Engineering and Biotechnology, Universitat Politècnica de Catalunya, Barcelona, Spain
| | - Mónica Blanco
- Department of Mathematics, Universitat Politècnica de Catalunya, Barcelona, Spain
| | - Xavier Portell
- Cranfield Soil and Agrifood Institute, Cranfield University, Bedfordshire, United Kingdom
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Kreft JU, Plugge CM, Prats C, Leveau JHJ, Zhang W, Hellweger FL. From Genes to Ecosystems in Microbiology: Modeling Approaches and the Importance of Individuality. Front Microbiol 2017; 8:2299. [PMID: 29230200 PMCID: PMC5711835 DOI: 10.3389/fmicb.2017.02299] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Accepted: 11/07/2017] [Indexed: 01/04/2023] Open
Abstract
Models are important tools in microbial ecology. They can be used to advance understanding by helping to interpret observations and test hypotheses, and to predict the effects of ecosystem management actions or a different climate. Over the past decades, biological knowledge and ecosystem observations have advanced to the molecular and in particular gene level. However, microbial ecology models have changed less and a current challenge is to make them utilize the knowledge and observations at the genetic level. We review published models that explicitly consider genes and make predictions at the population or ecosystem level. The models can be grouped into three general approaches, i.e., metabolic flux, gene-centric and agent-based. We describe and contrast these approaches by applying them to a hypothetical ecosystem and discuss their strengths and weaknesses. An important distinguishing feature is how variation between individual cells (individuality) is handled. In microbial ecosystems, individual heterogeneity is generated by a number of mechanisms including stochastic interactions of molecules (e.g., gene expression), stochastic and deterministic cell division asymmetry, small-scale environmental heterogeneity, and differential transport in a heterogeneous environment. This heterogeneity can then be amplified and transferred to other cell properties by several mechanisms, including nutrient uptake, metabolism and growth, cell cycle asynchronicity and the effects of age and damage. For example, stochastic gene expression may lead to heterogeneity in nutrient uptake enzyme levels, which in turn results in heterogeneity in intracellular nutrient levels. Individuality can have important ecological consequences, including division of labor, bet hedging, aging and sub-optimality. Understanding the importance of individuality and the mechanism(s) underlying it for the specific microbial system and question investigated is essential for selecting the optimal modeling strategy.
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Affiliation(s)
- Jan-Ulrich Kreft
- Centre for Computational Biology, Institute for Microbiology and Infection, School of Biosciences, University of Birmingham, Birmingham, United Kingdom
| | - Caroline M Plugge
- Laboratory of Microbiology, Wageningen University and Research, Wageningen, Netherlands
| | - Clara Prats
- Department of Physics, School of Agricultural Engineering of Barcelona, Universitat Politècnica de Catalunya-BarcelonaTech, Castelldefels, Spain
| | - Johan H J Leveau
- Department of Plant Pathology, University of California, Davis, Davis, CA, United States
| | - Weiwen Zhang
- Laboratory of Synthetic Microbiology, Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
| | - Ferdi L Hellweger
- Civil and Environmental Engineering Department, Marine and Environmental Sciences Department, Bioengineering Department, Northeastern University, Boston, MA, United States
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Hewitt SK, Foster DS, Dyer PS, Avery SV. Phenotypic heterogeneity in fungi: Importance and methodology. FUNGAL BIOL REV 2016. [DOI: 10.1016/j.fbr.2016.09.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
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Guyot S, Gervais P, Young M, Winckler P, Dumont J, Davey HM. Surviving the heat: heterogeneity of response in Saccharomyces cerevisiae provides insight into thermal damage to the membrane. Environ Microbiol 2015; 17:2982-92. [PMID: 25845620 PMCID: PMC4676927 DOI: 10.1111/1462-2920.12866] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2014] [Accepted: 03/30/2015] [Indexed: 01/03/2023]
Abstract
Environmental heat stress impacts on the physiology and viability of microbial cells with concomitant implications for microbial activity and diversity. Previously, it has been demonstrated that gradual heating of Saccharomyces cerevisiae induces a degree of thermal resistance, whereas a heat shock results in a high level of cell death. Here, we show that the impact of exogenous nutrients on acquisition of thermal resistance differs between strains. Using single-cell methods, we demonstrate the extent of heterogeneity of the heat-stress response within populations of yeast cells and the presence of subpopulations that are reversibly damaged by heat stress. Such cells represent potential for recovery of entire populations once stresses are removed. The results show that plasma membrane permeability and potential are key factors involved in cell survival, but thermal resistance is not related to homeoviscous adaptation of the plasma membrane. These results have implications for growth and regrowth of populations experiencing environmental heat stress and our understanding of impacts at the level of the single cell. Given the important role of microbes in biofuel production and bioremediation, a thorough understanding of the impact of stress responses of populations and individuals is highly desirable.
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Affiliation(s)
- Stéphane Guyot
- UMR A 02.102 Procédés Alimentaires et Microbiologiques (PAM), Equipe Procédés Microbiologiques et Biotechnologiques (PMB)1 Esplanade Erasme, 21000, Dijon, France
| | - Patrick Gervais
- UMR A 02.102 Procédés Alimentaires et Microbiologiques (PAM), Equipe Procédés Microbiologiques et Biotechnologiques (PMB)1 Esplanade Erasme, 21000, Dijon, France
| | - Michael Young
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth UniversityPenglais, Aberystwyth, Wales, SY23 3DA, UK
| | - Pascale Winckler
- Spectral Imagerie Resource Center, Agrosup Dijon/Université de Bourgogne1 Esplanade Erasme, 21000, Dijon, France
| | - Jennifer Dumont
- UMR A 02.102 Procédés Alimentaires et Microbiologiques (PAM), Equipe Procédés Microbiologiques et Biotechnologiques (PMB)1 Esplanade Erasme, 21000, Dijon, France
| | - Hazel Marie Davey
- Spectral Imagerie Resource Center, Agrosup Dijon/Université de Bourgogne1 Esplanade Erasme, 21000, Dijon, France
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Aviziotis IG, Kavousanakis ME, Boudouvis AG. Effect of Intrinsic Noise on the Phenotype of Cell Populations Featuring Solution Multiplicity: An Artificial lac Operon Network Paradigm. PLoS One 2015; 10:e0132946. [PMID: 26185999 PMCID: PMC4506119 DOI: 10.1371/journal.pone.0132946] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2015] [Accepted: 06/21/2015] [Indexed: 11/19/2022] Open
Abstract
Heterogeneity in cell populations originates from two fundamentally different sources: the uneven distribution of intracellular content during cell division, and the stochastic fluctuations of regulatory molecules existing in small amounts. Discrete stochastic models can incorporate both sources of cell heterogeneity with sufficient accuracy in the description of an isogenic cell population; however, they lack efficiency when a systems level analysis is required, due to substantial computational requirements. In this work, we study the effect of cell heterogeneity in the behaviour of isogenic cell populations carrying the genetic network of lac operon, which exhibits solution multiplicity over a wide range of extracellular conditions. For such systems, the strategy of performing solely direct temporal solutions is a prohibitive task, since a large ensemble of initial states needs to be tested in order to drive the system--through long time simulations--to possible co-existing steady state solutions. We implement a multiscale computational framework, the so-called "equation-free" methodology, which enables the performance of numerical tasks, such as the computation of coarse steady state solutions and coarse bifurcation analysis. Dynamically stable and unstable solutions are computed and the effect of intrinsic noise on the range of bistability is efficiently investigated. The results are compared with the homogeneous model, which neglects all sources of heterogeneity, with the deterministic cell population balance model, as well as with a stochastic model neglecting the heterogeneity originating from intrinsic noise effects. We show that when the effect of intrinsic source of heterogeneity is intensified, the bistability range shifts towards higher extracellular inducer concentration values.
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Affiliation(s)
- Ioannis G. Aviziotis
- School of Chemical Engineering, National Technical University of Athens, Athens, Greece
| | | | - Andreas G. Boudouvis
- School of Chemical Engineering, National Technical University of Athens, Athens, Greece
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