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Le Quellec L, Aristov A, Gutiérrez Ramos S, Amselem G, Bos J, Baharoglu Z, Mazel D, Baroud CN. Measuring single-cell susceptibility to antibiotics within monoclonal bacterial populations. PLoS One 2024; 19:e0303630. [PMID: 39088440 PMCID: PMC11293721 DOI: 10.1371/journal.pone.0303630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 04/30/2024] [Indexed: 08/03/2024] Open
Abstract
The emergence of new resistant bacterial strains is a worldwide challenge. A resistant bacterial population can emerge from a single cell that acquires resistance or persistence. Hence, new ways of tackling the mechanism of antibiotic response, such as single cell studies are required. It is necessary to see what happens at the single cell level, in order to understand what happens at the population level. To date, linking the heterogeneity of single-cell susceptibility to the population-scale response to antibiotics remains challenging due to the trade-offs between the resolution and the field of view. Here we present a platform that measures the ability of individual E. coli cells to form small colonies at different ciprofloxacin concentrations, by using anchored microfluidic drops and an image and data analysis pipelines. The microfluidic results are benchmarked against classical microbiology measurements of antibiotic susceptibility, showing an agreement between the pooled microfluidic chip and replated bulk measurements. Further, the experimental likelihood of a single cell to form a colony is used to provide a probabilistic antibiotic susceptibility curve. In addition to the probabilistic viewpoint, the microfluidic format enables the characterization of morphological features over time for a large number of individual cells. This pipeline can be used to compare the response of different bacterial strains to antibiotics with different action mechanisms.
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Affiliation(s)
- Lena Le Quellec
- Institut Pasteur, Université Paris Cité, Physical Microfluidics and Bioengineering, Paris, France
- LadHyX, CNRS, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau, France
| | - Andrey Aristov
- Institut Pasteur, Université Paris Cité, Physical Microfluidics and Bioengineering, Paris, France
| | - Salomé Gutiérrez Ramos
- Institut Pasteur, Université Paris Cité, Physical Microfluidics and Bioengineering, Paris, France
- LadHyX, CNRS, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau, France
| | - Gabriel Amselem
- Institut Pasteur, Université Paris Cité, Physical Microfluidics and Bioengineering, Paris, France
- LadHyX, CNRS, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau, France
| | - Julia Bos
- Institut Pasteur, Université Paris Cité, CNRS UMR3525, Bacterial Genome Plasticity Unit, Paris, France
| | - Zeynep Baharoglu
- Institut Pasteur, Université Paris Cité, CNRS UMR3525, Bacterial Genome Plasticity Unit, Paris, France
| | - Didier Mazel
- Institut Pasteur, Université Paris Cité, CNRS UMR3525, Bacterial Genome Plasticity Unit, Paris, France
| | - Charles N. Baroud
- Institut Pasteur, Université Paris Cité, Physical Microfluidics and Bioengineering, Paris, France
- LadHyX, CNRS, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau, France
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Iyengar SN, Robinson JP. Spectral analysis and sorting of microbial organisms using a spectral sorter. Methods Cell Biol 2024; 186:189-212. [PMID: 38705599 DOI: 10.1016/bs.mcb.2024.02.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
This chapter discusses the problems related to the application of conventional flow cytometers to microbiology. To address some of those limitations, the concept of spectral flow cytometry is introduced and the advantages over conventional flow cytometry for bacterial sorting are presented. We demonstrate by using ThermoFisher's Bigfoot spectral sorter where the spectral signatures of different stains for staining bacteria are demonstrated with an example of performing unmixing on spectral datasets. In addition to the Bigfoot's spectral analysis, the special biosafety features of this instrument are discussed. Utilizing these biosafety features, the sorting and patterning at the single cell level is optimized using non-pathogenic bacteria. Finally, the chapter is concluded by presenting a novel, label free, non-destructive, and rapid phenotypic method called Elastic Light Scattering (ELS) technology for identification of the patterned bacterial cells based on their unique colony scatter patterns.
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Affiliation(s)
- Sharath Narayana Iyengar
- Department of Basic Medical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, IN, United States
| | - J Paul Robinson
- Department of Basic Medical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, IN, United States; Weldon School of Biomedical Engineering, College of Engineering, Purdue University, West Lafayette, IN, United States.
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Nikolic N, Anagnostidis V, Tiwari A, Chait R, Gielen F. Droplet-based methodology for investigating bacterial population dynamics in response to phage exposure. Front Microbiol 2023; 14:1260196. [PMID: 38075890 PMCID: PMC10703435 DOI: 10.3389/fmicb.2023.1260196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 10/23/2023] [Indexed: 02/12/2024] Open
Abstract
An alarming rise in antimicrobial resistance worldwide has spurred efforts into the search for alternatives to antibiotic treatments. The use of bacteriophages, bacterial viruses harmless to humans, represents a promising approach with potential to treat bacterial infections (phage therapy). Recent advances in microscopy-based single-cell techniques have allowed researchers to develop new quantitative methodologies for assessing the interactions between bacteria and phages, especially the ability of phages to eradicate bacterial pathogen populations and to modulate growth of both commensal and pathogen populations. Here we combine droplet microfluidics with fluorescence time-lapse microscopy to characterize the growth and lysis dynamics of the bacterium Escherichia coli confined in droplets when challenged with phage. We investigated phages that promote lysis of infected E. coli cells, specifically, a phage species with DNA genome, T7 (Escherichia virus T7) and two phage species with RNA genomes, MS2 (Emesvirus zinderi) and Qβ (Qubevirus durum). Our microfluidic trapping device generated and immobilized picoliter-sized droplets, enabling stable imaging of bacterial growth and lysis in a temperature-controlled setup. Temporal information on bacterial population size was recorded for up to 25 h, allowing us to determine growth rates of bacterial populations and helping us uncover the extent and speed of phage infection. In the long-term, the development of novel microfluidic single-cell and population-level approaches will expedite research towards fundamental understanding of the genetic and molecular basis of rapid phage-induced lysis and eco-evolutionary aspects of bacteria-phage dynamics, and ultimately help identify key factors influencing the success of phage therapy.
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Affiliation(s)
- Nela Nikolic
- Living Systems Institute, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
- Department of Physics and Astronomy, Faculty of Environment, Science and Economy, University of Exeter, Exeter, United Kingdom
- Translational Research Exchange @ Exeter, University of Exeter, Exeter, United Kingdom
| | - Vasileios Anagnostidis
- Living Systems Institute, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
- Department of Physics and Astronomy, Faculty of Environment, Science and Economy, University of Exeter, Exeter, United Kingdom
| | - Anuj Tiwari
- Living Systems Institute, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
| | - Remy Chait
- Living Systems Institute, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
- Department of Biosciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
| | - Fabrice Gielen
- Living Systems Institute, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
- Department of Physics and Astronomy, Faculty of Environment, Science and Economy, University of Exeter, Exeter, United Kingdom
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Pinto C, Shimakawa K. A compressed logistic equation bacteria growth: Inferring time-dependent growth rate. Phys Biol 2022; 19. [PMID: 35998621 DOI: 10.1088/1478-3975/ac8c15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 08/23/2022] [Indexed: 11/12/2022]
Abstract
We propose a compressed logistic model for bacterial growth by invoking a time-dependent rate instead of the intrinsic growth rate (constant), which was adopted in traditional logistic models. The new model may have a better physiological basis than the traditional ones, and it replicates experimental observations, such as the case example for E. coli, Salmonella, and Staphylococcus aureus. Stochastic colonial growth at a different rate may have a fractal-like nature, which should be an origin of the time-dependent reaction rate. The present model, from a stochastic viewpoint, is approximated as a Gaussian time evolution of bacteria (error function).
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Affiliation(s)
- Carlito Pinto
- Informatics Department, Universidade Nacional Timor Lorasa'e, Avenida Hera, Dili, Timor-Leste, Dili, no zip code in , TIMOR-LESTE
| | - Koichi Shimakawa
- Department of Electrical and Electronic Engineering, Gifu University, Gifu 501-1193, Gifu Prefecture, Gifu, 501-1193, JAPAN
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Taylor D, Verdon N, Lomax P, Allen RJ, Titmuss S. Tracking the stochastic growth of bacterial populations in microfluidic droplets. Phys Biol 2022; 19. [PMID: 35042205 DOI: 10.1088/1478-3975/ac4c9b] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 01/18/2022] [Indexed: 11/11/2022]
Abstract
Bacterial growth in microfluidic droplets is relevant in biotechnology, in microbial ecology, and in understanding stochastic population dynamics in small populations. However, it has proved challenging to automate measurement of absolute bacterial numbers within droplets, forcing the use of proxy measures for population size. Here we present a microfluidic device and imaging protocol that allows high-resolution imaging of thousands of droplets, such that individual bacteria stay in the focal plane and can be counted automatically. Using this approach, we track the stochastic growth of hundreds of replicate Escherichia coli populations within droplets. {We find that, for early times, the statistics of the growth trajectories obey the predictions of the Bellman-Harris model, in which there is no inheritance of division time. Our approach should allow further testing of models for stochastic growth dynamics, as well as contributing to broader applications of droplet-based bacterial culture.
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Affiliation(s)
- Daniel Taylor
- The University of Edinburgh School of Physics and Astronomy, JCMB, Edinburgh, EH9 3FD, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Nia Verdon
- The University of Edinburgh School of Physics and Astronomy, JCMB, Edinburgh, EH9 3FD, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Peter Lomax
- School of Engineering, University of Edinburgh, The University of Edinburgh Institute for Integrated Micro and Nano Systems, Scottish Microelectronics Centre, King's Buildings, Alexander Crum Brown Road, Edinburgh, Edinburgh, EH9 3FF, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Rosalind J Allen
- Theoretical Microbial Ecology, Friedrich-Schiller-Universität Jena, Buchaer Strasse 6, Jena, Thüringen, 07749, GERMANY
| | - Simon Titmuss
- The University of Edinburgh School of Physics and Astronomy, JCMB, Edinburgh, EH9 3FD, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
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Genthon A, Lacoste D. Fluctuation relations and fitness landscapes of growing cell populations. Sci Rep 2020; 10:11889. [PMID: 32681104 PMCID: PMC7367869 DOI: 10.1038/s41598-020-68444-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 06/25/2020] [Indexed: 11/20/2022] Open
Abstract
We construct a pathwise formulation of a growing population of cells, based on two different samplings of lineages within the population, namely the forward and backward samplings. We show that a general symmetry relation, called fluctuation relation relates these two samplings, independently of the model used to generate divisions and growth in the cell population. These relations lead to estimators of the population growth rate, which can be very efficient as we demonstrate by an analysis of a set of mother machine data. These fluctuation relations lead to general and important inequalities between the mean number of divisions and the doubling time of the population. We also study the fitness landscape, a concept based on the two samplings mentioned above, which quantifies the correlations between a phenotypic trait of interest and the number of divisions. We obtain explicit results when the trait is the age or the size, for age and size-controlled models.
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Affiliation(s)
- Arthur Genthon
- Gulliver, CNRS, ESPCI Paris, PSL University, 75005, Paris, France.
| | - David Lacoste
- Gulliver, CNRS, ESPCI Paris, PSL University, 75005, Paris, France
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