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Ewald S, Nasuhidehnavi A, Feng TY, Lesani M, McCall LI. The intersection of host in vivo metabolism and immune responses to infection with kinetoplastid and apicomplexan parasites. Microbiol Mol Biol Rev 2024; 88:e0016422. [PMID: 38299836 PMCID: PMC10966954 DOI: 10.1128/mmbr.00164-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024] Open
Abstract
SUMMARYProtozoan parasite infection dramatically alters host metabolism, driven by immunological demand and parasite manipulation strategies. Immunometabolic checkpoints are often exploited by kinetoplastid and protozoan parasites to establish chronic infection, which can significantly impair host metabolic homeostasis. The recent growth of tools to analyze metabolism is expanding our understanding of these questions. Here, we review and contrast host metabolic alterations that occur in vivo during infection with Leishmania, trypanosomes, Toxoplasma, Plasmodium, and Cryptosporidium. Although genetically divergent, there are commonalities among these pathogens in terms of metabolic needs, induction of the type I immune responses required for clearance, and the potential for sustained host metabolic dysbiosis. Comparing these pathogens provides an opportunity to explore how transmission strategy, nutritional demand, and host cell and tissue tropism drive similarities and unique aspects in host response and infection outcome and to design new strategies to treat disease.
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Affiliation(s)
- Sarah Ewald
- Department of Microbiology, Immunology, and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Azadeh Nasuhidehnavi
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, USA
| | - Tzu-Yu Feng
- Department of Microbiology, Immunology, and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Mahbobeh Lesani
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA
| | - Laura-Isobel McCall
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, USA
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA
- Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, Oklahoma, USA
- Department of Chemistry and Biochemistry, San Diego State University, San Diego, California, USA
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2
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Henrion L, Martinez JA, Vandenbroucke V, Delvenne M, Telek S, Zicler A, Grünberger A, Delvigne F. Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability. Nat Commun 2023; 14:6128. [PMID: 37783690 PMCID: PMC10545768 DOI: 10.1038/s41467-023-41917-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 09/23/2023] [Indexed: 10/04/2023] Open
Abstract
Isogenic cell populations can cope with stress conditions by switching to alternative phenotypes. Even if it can lead to increased fitness in a natural context, this feature is typically unwanted for a range of applications (e.g., bioproduction, synthetic biology, and biomedicine) where it tends to make cellular response unpredictable. However, little is known about the diversification profiles that can be adopted by a cell population. Here, we characterize the diversification dynamics for various systems (bacteria and yeast) and for different phenotypes (utilization of alternative carbon sources, general stress response and more complex development patterns). Our results suggest that the diversification dynamics and the fitness cost associated with cell switching are coupled. To quantify the contribution of the switching cost on population dynamics, we design a stochastic model that let us reproduce the dynamics observed experimentally and identify three diversification regimes, i.e., constrained (at low switching cost), dispersed (at medium and high switching cost), and bursty (for very high switching cost). Furthermore, we use a cell-machine interface called Segregostat to demonstrate that different levels of control can be applied to these diversification regimes, enabling applications involving more precise cellular responses.
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Affiliation(s)
- Lucas Henrion
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Juan Andres Martinez
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Vincent Vandenbroucke
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Mathéo Delvenne
- 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
| | - Alexander Grünberger
- Microsystems in Bioprocess Engineering, Institute of Process Engineering in Life Sciences, Karlsruhe Institute of Technology, Karlsruhe, 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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3
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Delvigne F, Martinez JA. Advances in automated and reactive flow cytometry for synthetic biotechnology. Curr Opin Biotechnol 2023; 83:102974. [PMID: 37515938 DOI: 10.1016/j.copbio.2023.102974] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 06/20/2023] [Accepted: 07/03/2023] [Indexed: 07/31/2023]
Abstract
Automated flow cytometry (FC) has been initially considered for bioprocess monitoring and optimization. More recently, new physical and software interfaces have been made available, facilitating the access to this technology for labs and industries. It also comes with new capabilities, such as being able to act on the cultivation conditions based on population data. This approach, known as reactive FC, extended the range of applications of automated FC to bioprocess control and the stabilization of cocultures, but also to the broad field of synthetic and systems biology for the characterization of gene circuits. However, several issues must be addressed before automated and reactive FC can be considered standard and modular technologies.
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Affiliation(s)
- Frank Delvigne
- Terra Research and Teaching Center, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.
| | - Juan A Martinez
- Terra Research and Teaching Center, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
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4
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Wang C, Jin L. Microbial persisters and host: recent advances and future perspectives. Crit Rev Microbiol 2023; 49:658-670. [PMID: 36165023 DOI: 10.1080/1040841x.2022.2125286] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 09/07/2022] [Accepted: 09/12/2022] [Indexed: 11/03/2022]
Abstract
Microbial persisters are defined as the tiny sub-population of microorganisms that develop intrinsic strategies for survival with high tolerance to various antimicrobials. Currently, persister research remains in its infancy, and it is indeed a great challenge to precisely distinguish persister cells from other drug tolerant ones. Notably, the existence of persisters crucially contributes to prolonged antibiotic exposure time and treatment failure, yet there is the formation of antibiotic-resistant mutants. Further understanding on persisters is of profound importance for effective prevention and control of chronic infections/inflammation. The past two decades have witnessed rapid advances on the science, technologies and methodologies for persister investigations, along with deep knowledge about persisters and numerous anti-persister approaches developed. Whereas, various critical issues remain unsolved, such as what are the potential interaction profiles of persisters and host cells, and how to apply what we know about persisters to translational studies and clinical practice. Importantly, it is highly essential to better understand the multifaceted and complex cross-talk of microbial persisters with the host to develop novel tackling strategies for precision healthcare in the near future.
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Affiliation(s)
- Chuan Wang
- Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China
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5
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Mermans F, Mattelin V, Van den Eeckhoudt R, García-Timermans C, Van Landuyt J, Guo Y, Taurino I, Tavernier F, Kraft M, Khan H, Boon N. Opportunities in optical and electrical single-cell technologies to study microbial ecosystems. Front Microbiol 2023; 14:1233705. [PMID: 37692384 PMCID: PMC10486927 DOI: 10.3389/fmicb.2023.1233705] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 08/03/2023] [Indexed: 09/12/2023] Open
Abstract
New techniques are revolutionizing single-cell research, allowing us to study microbes at unprecedented scales and in unparalleled depth. This review highlights the state-of-the-art technologies in single-cell analysis in microbial ecology applications, with particular attention to both optical tools, i.e., specialized use of flow cytometry and Raman spectroscopy and emerging electrical techniques. The objectives of this review include showcasing the diversity of single-cell optical approaches for studying microbiological phenomena, highlighting successful applications in understanding microbial systems, discussing emerging techniques, and encouraging the combination of established and novel approaches to address research questions. The review aims to answer key questions such as how single-cell approaches have advanced our understanding of individual and interacting cells, how they have been used to study uncultured microbes, which new analysis tools will become widespread, and how they contribute to our knowledge of ecological interactions.
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Affiliation(s)
- Fabian Mermans
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
- Department of Oral Health Sciences, KU Leuven, Leuven, Belgium
| | - Valérie Mattelin
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Ruben Van den Eeckhoudt
- Micro- and Nanosystems (MNS), Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium
| | - Cristina García-Timermans
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Josefien Van Landuyt
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Yuting Guo
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Irene Taurino
- Micro- and Nanosystems (MNS), Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium
- Semiconductor Physics, Department of Physics and Astronomy, KU Leuven, Leuven, Belgium
| | - Filip Tavernier
- MICAS, Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium
| | - Michael Kraft
- Micro- and Nanosystems (MNS), Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium
- Leuven Institute of Micro- and Nanoscale Integration (LIMNI), KU Leuven, Leuven, Belgium
| | - Hira Khan
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Nico Boon
- Center for Microbial Ecology and Technology (CMET), Department of Biotechnology, Ghent University, Ghent, Belgium
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Wang X, Ren L, Diao Z, He Y, Zhang J, Liu M, Li Y, Sun L, Chen R, Ji Y, Xu J, Ma B. Robust Spontaneous Raman Flow Cytometry for Single-Cell Metabolic Phenome Profiling via pDEP-DLD-RFC. Adv Sci (Weinh) 2023; 10:e2207497. [PMID: 36871147 DOI: 10.1002/advs.202207497] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 02/08/2023] [Indexed: 06/04/2023]
Abstract
A full-spectrum spontaneous single-cell Raman spectrum (fs-SCRS) captures the metabolic phenome for a given cellular state of the cell in a label-free, landscape-like manner. Herein a positive dielectrophoresis induced deterministic lateral displacement-based Raman flow cytometry (pDEP-DLD-RFC) is established. This robust flow cytometry platform utilizes a periodical positive dielectrophoresis induced deterministic lateral displacement (pDEP-DLD) force that is exerted to focus and trap fast-moving single cells in a wide channel, which enables efficient fs-SCRS acquisition and extended stable running time. It automatically produces deeply sampled, heterogeneity-resolved, and highly reproducible ramanomes for isogenic cell populations of yeast, microalgae, bacteria, and human cancers, which support biosynthetic process dissection, antimicrobial susceptibility profiling, and cell-type classification. Moreover, when coupled with intra-ramanome correlation analysis, it reveals state- and cell-type-specific metabolic heterogeneity and metabolite-conversion networks. The throughput of ≈30-2700 events min-1 for profiling both nonresonance and resonance marker bands in a fs-SCRS, plus the >5 h stable running time, represent the highest performance among reported spontaneous Raman flow cytometry (RFC) systems. Therefore, pDEP-DLD-RFC is a valuable new tool for label-free, noninvasive, and high-throughput profiling of single-cell metabolic phenomes.
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Affiliation(s)
- Xixian Wang
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lihui Ren
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
- College of Information Science & Engineering, Ocean University of China, Qingdao, 266100, China
| | - Zhidian Diao
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuehui He
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jiaping Zhang
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Min Liu
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuandong Li
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lijun Sun
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Rongze Chen
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuetong Ji
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
- Qingdao Single-Cell Biotech. Co., Ltd, Qingdao, 266100, China
| | - Jian Xu
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bo Ma
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
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Shan Y, Guo Y, Jiao W, Zeng P. Single-Cell Techniques in Environmental Microbiology. Processes (Basel) 2023. [DOI: 10.3390/pr11041109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023] Open
Abstract
Environmental microbiology has been an essential part of environmental research because it provides effective solutions to most pollutants. Hence, there is an interest in investigating microorganism behavior, such as observation, identification, isolation of pollutant degraders, and interactions between microbial species. To comprehensively understand cell heterogeneity, diverse approaches at the single-cell level are demanded. Thus far, the traditional bulk biological tools such as petri dishes are technically challenging for single cells, which could mask the heterogeneity. Single-cell technologies can reveal complex and rare cell populations by detecting heterogeneity among individual cells, which offers advantages of higher resolution, higher throughput, more accurate analysis, etc. Here, we overviewed several single-cell techniques on observation, isolation, and identification from aspects of methods and applications. Microscopic observation, sequencing identification, flow cytometric identification and isolation, Raman spectroscopy-based identification and isolation, and their applications are mainly discussed. Further development on multi-technique integrations at the single-cell level may highly advance the research progress of environmental microbiology, thereby giving more indication in the environmental microbial ecology.
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Affiliation(s)
- Yongping Shan
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yuting Guo
- Flow Cytometry Center, National Institute of Biological Sciences, Beijing 102206, China
| | - Wentao Jiao
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Ping Zeng
- Department of Urban Water Environmental Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
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Martinez JA, Delvenne M, Henrion L, Moreno F, Telek S, Dusny C, Delvigne F. Controlling microbial co-culture based on substrate pulsing can lead to stability through differential fitness advantages. PLoS Comput Biol 2022; 18:e1010674. [PMID: 36315576 PMCID: PMC9648842 DOI: 10.1371/journal.pcbi.1010674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 11/10/2022] [Accepted: 10/22/2022] [Indexed: 11/12/2022] Open
Abstract
Microbial consortia are an exciting alternative for increasing the performances of bioprocesses for the production of complex metabolic products. However, the functional properties of microbial communities remain challenging to control, considering the complex interaction mechanisms occurring between co-cultured microbial species. Indeed, microbial communities are highly dynamic and can adapt to changing environmental conditions through complex mechanisms, such as phenotypic diversification. We focused on stabilizing a co-culture of Saccharomyces cerevisiae and Escherichia coli in continuous cultures. Our preliminary data pointed out that transient diauxic shifts could lead to stable co-culture by providing periodic fitness advantages to the yeast. Based on a computational toolbox called MONCKS (for MONod-type Co-culture Kinetic Simulation), we were able to predict the dynamics of diauxic shift for both species based on a cybernetic approach. This toolbox was further used to predict the frequency of diauxic shift to be applied to reach co-culture stability. These simulations were successfully reproduced experimentally in continuous bioreactors with glucose pulsing. Finally, based on a bet-hedging reporter, we observed that the yeast population exhibited an increased phenotypic diversification process in co-culture compared with mono-culture, suggesting that this mechanism could be the basis of the metabolic fitness of the yeast. Being able to manipulate the dynamics of microbial co-cultures is a technical challenge that need to be addressed in order to get a deeper insight about how microbial communities are evolving in their ecological context, as well as for exploiting the potential offered by such communities in an applied context e.g., for setting up more robust bioprocesses relying on the use of several microbial species. In this study, we used continuous cultures of bacteria (E. coli) and yeast (S. cerevisiae) in order to demonstrate that a simple nutrient pulsing strategy can be used for adjusting the composition of the community with time. As expected, during growth on glucose, E. coli quickly outcompeted S. cerevisiae. However, when glucose is pulsed into the culture, increased metabolic fitness of the yeast was observed upon reconsumption of the main side metabolites i.e., acetate and ethanol, leading to a robust oscillating growth profile for both species. The optimal pulsing frequency was predicted based on a cybernetic version of a Monod growth model taking into account the main metabolic routes involved in the process. Considering the limited number of metabolic details needed, this cybernetic approach could be generalized to other communities.
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Affiliation(s)
- J. Andres Martinez
- TERRA Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liége, Gembloux, Belgium
| | - Matheo Delvenne
- TERRA Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liége, Gembloux, Belgium
| | - Lucas Henrion
- TERRA Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liége, Gembloux, Belgium
| | - Fabian Moreno
- TERRA Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liége, Gembloux, Belgium
| | - Samuel Telek
- TERRA Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liége, Gembloux, Belgium
| | - Christian Dusny
- Microscale Analysis and Engineering, Department of Solar Materials, Helmholtz-Centre for Environmental Research- UFZ Leipzig, Leipzig, Germany
| | - Frank Delvigne
- TERRA Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liége, Gembloux, Belgium
- * E-mail:
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Kukolj T, Lazarević J, Borojević A, Ralević U, Vujić D, Jauković A, Lazarević N, Bugarski D. A Single-Cell Raman Spectroscopy Analysis of Bone Marrow Mesenchymal Stem/Stromal Cells to Identify Inter-Individual Diversity. Int J Mol Sci 2022; 23:4915. [PMID: 35563306 PMCID: PMC9103070 DOI: 10.3390/ijms23094915] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 04/21/2022] [Accepted: 04/25/2022] [Indexed: 12/15/2022] Open
Abstract
The heterogeneity of stem cells represents the main challenge in regenerative medicine development. This issue is particularly pronounced when it comes to the use of primary mesenchymal stem/stromal cells (MSCs) due to a lack of identification markers. Considering the need for additional approaches in MSCs characterization, we applied Raman spectroscopy to investigate inter-individual differences between bone marrow MSCs (BM-MSCs). Based on standard biological tests, BM-MSCs of analyzed donors fulfill all conditions for their characterization, while no donor-related specifics were observed in terms of BM-MSCs morphology, phenotype, multilineage differentiation potential, colony-forming capacity, expression of pluripotency-associated markers or proliferative capacity. However, examination of BM-MSCs at a single-cell level by Raman spectroscopy revealed that despite similar biochemical background, fine differences in the Raman spectra of BM-MSCs of each donor can be detected. After extensive principal component analysis (PCA) of Raman spectra, our study revealed the possibility of this method to diversify BM-MSCs populations, whereby the grouping of cell populations was most prominent when cell populations were analyzed in pairs. These results indicate that Raman spectroscopy, as a label-free assay, could have a huge potential in understanding stem cell heterogeneity and sorting cell populations with a similar biochemical background that can be significant for the development of personalized therapy approaches.
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Affiliation(s)
- Tamara Kukolj
- Group for Hematology and Stem Cells, Institute for Medical Research, National Institute of Republic of Serbia, University of Belgrade, 11129 Belgrade, Serbia; (A.J.); (D.B.)
| | - Jasmina Lazarević
- Center for Solid State Physics and New Materials, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia; (J.L.); (U.R.); (N.L.)
| | - Ana Borojević
- Mother and Child Health Care Institute of Serbia ‘’Dr Vukan Čupić’’, 11000 Belgrade, Serbia; (A.B.); (D.V.)
| | - Uroš Ralević
- Center for Solid State Physics and New Materials, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia; (J.L.); (U.R.); (N.L.)
| | - Dragana Vujić
- Mother and Child Health Care Institute of Serbia ‘’Dr Vukan Čupić’’, 11000 Belgrade, Serbia; (A.B.); (D.V.)
- School of Medicine, University of Belgrade, 11000 Belgrade, Serbia
| | - Aleksandra Jauković
- Group for Hematology and Stem Cells, Institute for Medical Research, National Institute of Republic of Serbia, University of Belgrade, 11129 Belgrade, Serbia; (A.J.); (D.B.)
| | - Nenad Lazarević
- Center for Solid State Physics and New Materials, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia; (J.L.); (U.R.); (N.L.)
| | - Diana Bugarski
- Group for Hematology and Stem Cells, Institute for Medical Research, National Institute of Republic of Serbia, University of Belgrade, 11129 Belgrade, Serbia; (A.J.); (D.B.)
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Kukal G, Vasdekis AE, Mcdonald AG. Raman-probes for monitoring metabolites and nutrient fate in Yarrowia lipolytica using deuterated glucose. Biocatalysis and Agricultural Biotechnology 2022; 39:102241. [DOI: 10.1016/j.bcab.2021.102241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Gupta G, Ndiaye A, Filteau M. Leveraging Experimental Strategies to Capture Different Dimensions of Microbial Interactions. Front Microbiol 2021; 12:700752. [PMID: 34646243 PMCID: PMC8503676 DOI: 10.3389/fmicb.2021.700752] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 08/31/2021] [Indexed: 12/27/2022] Open
Abstract
Microorganisms are a fundamental part of virtually every ecosystem on earth. Understanding how collectively they interact, assemble, and function as communities has become a prevalent topic both in fundamental and applied research. Owing to multiple advances in technology, answering questions at the microbial system or network level is now within our grasp. To map and characterize microbial interaction networks, numerous computational approaches have been developed; however, experimentally validating microbial interactions is no trivial task. Microbial interactions are context-dependent, and their complex nature can result in an array of outcomes, not only in terms of fitness or growth, but also in other relevant functions and phenotypes. Thus, approaches to experimentally capture microbial interactions involve a combination of culture methods and phenotypic or functional characterization methods. Here, through our perspective of food microbiologists, we highlight the breadth of innovative and promising experimental strategies for their potential to capture the different dimensions of microbial interactions and their high-throughput application to answer the question; are microbial interaction patterns or network architecture similar along different contextual scales? We further discuss the experimental approaches used to build various types of networks and study their architecture in the context of cell biology and how they translate at the level of microbial ecosystem.
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Affiliation(s)
- Gunjan Gupta
- Département des Sciences des aliments, Université Laval, Québec, QC, Canada
- Institut sur la Nutrition et les Aliments Fonctionnels (INAF), Québec, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, QC, Canada
| | - Amadou Ndiaye
- Département des Sciences des aliments, Université Laval, Québec, QC, Canada
- Institut sur la Nutrition et les Aliments Fonctionnels (INAF), Québec, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, QC, Canada
| | - Marie Filteau
- Département des Sciences des aliments, Université Laval, Québec, QC, Canada
- Institut sur la Nutrition et les Aliments Fonctionnels (INAF), Québec, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, QC, Canada
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Schlembach I, Grünberger A, Rosenbaum MA, Regestein L. Measurement Techniques to Resolve and Control Population Dynamics of Mixed-Culture Processes. Trends Biotechnol 2021; 39:1093-1109. [PMID: 33573846 PMCID: PMC7612867 DOI: 10.1016/j.tibtech.2021.01.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 01/15/2021] [Accepted: 01/15/2021] [Indexed: 12/22/2022]
Abstract
Microbial mixed cultures are gaining increasing attention as biotechnological production systems, since they offer a large but untapped potential for future bioprocesses. Effects of secondary metabolite induction and advantages of labor division for the degradation of complex substrates offer new possibilities for process intensification. However, mixed cultures are highly complex, and, consequently, many biotic and abiotic parameters are required to be identified, characterized, and ideally controlled to establish a stable bioprocess. In this review, we discuss the advantages and disadvantages of existing measurement techniques for identifying, characterizing, monitoring, and controlling mixed cultures and highlight promising examples. Moreover, existing challenges and emerging technologies are discussed, which lay the foundation for novel analytical workflows to monitor mixed-culture bioprocesses.
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Affiliation(s)
- Ivan Schlembach
- Leibniz Institute for Natural Product Research and Infection Biology, Hans-Knöll-Institute, Adolf-Reichwein-Str. 23, 07745 Jena, Germany; Faculty for Biological Sciences, Friedrich-Schiller-University Jena, Bachstrasse 18K, 07743 Jena, Germany
| | - Alexander Grünberger
- Multiscale Bioengineering, Faculty of Technology, Bielefeld University, Universitätsstraße 25, 33615 Bielefeld, Germany
| | - Miriam A Rosenbaum
- Leibniz Institute for Natural Product Research and Infection Biology, Hans-Knöll-Institute, Adolf-Reichwein-Str. 23, 07745 Jena, Germany; Faculty for Biological Sciences, Friedrich-Schiller-University Jena, Bachstrasse 18K, 07743 Jena, Germany
| | - Lars Regestein
- Leibniz Institute for Natural Product Research and Infection Biology, Hans-Knöll-Institute, Adolf-Reichwein-Str. 23, 07745 Jena, Germany.
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