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Parisi M, Lucidi M, Visca P, Cincotti G. Super-Resolution Optical Imaging of Bacterial Cells. IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS 2023; 29:1-13. [DOI: 10.1109/jstqe.2022.3228121] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2025]
Affiliation(s)
- Miranda Parisi
- Engineering Department, University Roma Tre, Rome, Italy
| | | | - Paolo Visca
- Science Department, University Roma Tre, Rome, Italy
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2
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Simon F, Tinevez JY, van Teeffelen S. ExTrack characterizes transition kinetics and diffusion in noisy single-particle tracks. J Cell Biol 2023; 222:e202208059. [PMID: 36880553 PMCID: PMC9997658 DOI: 10.1083/jcb.202208059] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 12/01/2022] [Accepted: 01/27/2023] [Indexed: 03/08/2023] Open
Abstract
Single-particle tracking microscopy is a powerful technique to investigate how proteins dynamically interact with their environment in live cells. However, the analysis of tracks is confounded by noisy molecule localization, short tracks, and rapid transitions between different motion states, notably between immobile and diffusive states. Here, we propose a probabilistic method termed ExTrack that uses the full spatio-temporal information of tracks to extract global model parameters, to calculate state probabilities at every time point, to reveal distributions of state durations, and to refine the positions of bound molecules. ExTrack works for a wide range of diffusion coefficients and transition rates, even if experimental data deviate from model assumptions. We demonstrate its capacity by applying it to slowly diffusing and rapidly transitioning bacterial envelope proteins. ExTrack greatly increases the regime of computationally analyzable noisy single-particle tracks. The ExTrack package is available in ImageJ and Python.
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Affiliation(s)
- François Simon
- Département de Microbiologie, Infectiologie, et Immunologie, Faculté de Médecine, Université de Montréal, Montréal, Quebec, Canada
- Microbial Morphogenesis and Growth Lab, Institut Pasteur, Université de Paris Cité, Paris, France
| | - Jean-Yves Tinevez
- Image Analysis Hub, Institut Pasteur, Université de Paris Cité, Paris, France
| | - Sven van Teeffelen
- Département de Microbiologie, Infectiologie, et Immunologie, Faculté de Médecine, Université de Montréal, Montréal, Quebec, Canada
- Microbial Morphogenesis and Growth Lab, Institut Pasteur, Université de Paris Cité, Paris, France
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Simon F, Tinevez JY, van Teeffelen S. ExTrack characterizes transition kinetics and diffusion in noisy single-particle tracks. J Cell Biol 2023; 222:e202208059. [PMID: 36880553 PMCID: PMC9997658 DOI: 10.1083/jcb.202208059 10.1101/2022.07.13.499913] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 12/01/2022] [Accepted: 01/27/2023] [Indexed: 03/23/2024] Open
Abstract
Single-particle tracking microscopy is a powerful technique to investigate how proteins dynamically interact with their environment in live cells. However, the analysis of tracks is confounded by noisy molecule localization, short tracks, and rapid transitions between different motion states, notably between immobile and diffusive states. Here, we propose a probabilistic method termed ExTrack that uses the full spatio-temporal information of tracks to extract global model parameters, to calculate state probabilities at every time point, to reveal distributions of state durations, and to refine the positions of bound molecules. ExTrack works for a wide range of diffusion coefficients and transition rates, even if experimental data deviate from model assumptions. We demonstrate its capacity by applying it to slowly diffusing and rapidly transitioning bacterial envelope proteins. ExTrack greatly increases the regime of computationally analyzable noisy single-particle tracks. The ExTrack package is available in ImageJ and Python.
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Affiliation(s)
- François Simon
- Département de Microbiologie, Infectiologie, et Immunologie, Faculté de Médecine, Université de Montréal, Montréal, Quebec, Canada
- Microbial Morphogenesis and Growth Lab, Institut Pasteur, Université de Paris Cité, Paris, France
| | - Jean-Yves Tinevez
- Image Analysis Hub, Institut Pasteur, Université de Paris Cité, Paris, France
| | - Sven van Teeffelen
- Département de Microbiologie, Infectiologie, et Immunologie, Faculté de Médecine, Université de Montréal, Montréal, Quebec, Canada
- Microbial Morphogenesis and Growth Lab, Institut Pasteur, Université de Paris Cité, Paris, France
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Choudhary D, Lagage V, Foster KR, Uphoff S. Phenotypic heterogeneity in the bacterial oxidative stress response is driven by cell-cell interactions. Cell Rep 2023; 42:112168. [PMID: 36848288 PMCID: PMC10935545 DOI: 10.1016/j.celrep.2023.112168] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 12/14/2022] [Accepted: 02/09/2023] [Indexed: 02/27/2023] Open
Abstract
Genetically identical bacterial cells commonly display different phenotypes. This phenotypic heterogeneity is well known for stress responses, where it is often explained as bet hedging against unpredictable environmental threats. Here, we explore phenotypic heterogeneity in a major stress response of Escherichia coli and find it has a fundamentally different basis. We characterize the response of cells exposed to hydrogen peroxide (H2O2) stress in a microfluidic device under constant growth conditions. A machine-learning model reveals that phenotypic heterogeneity arises from a precise and rapid feedback between each cell and its immediate environment. Moreover, we find that the heterogeneity rests upon cell-cell interaction, whereby cells shield each other from H2O2 via their individual stress responses. Our work shows how phenotypic heterogeneity in bacterial stress responses can emerge from short-range cell-cell interactions and result in a collective phenotype that protects a large proportion of the population.
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Affiliation(s)
- Divya Choudhary
- Department of Biochemistry, University of Oxford, Oxford, UK
| | | | - Kevin R Foster
- Department of Biochemistry, University of Oxford, Oxford, UK; Department of Biology, University of Oxford, Oxford, UK
| | - Stephan Uphoff
- Department of Biochemistry, University of Oxford, Oxford, UK.
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Dash S, Palma CSD, Baptista ISC, Almeida BLB, Bahrudeen MNM, Chauhan V, Jagadeesan R, Ribeiro AS. Alteration of DNA supercoiling serves as a trigger of short-term cold shock repressed genes of E. coli. Nucleic Acids Res 2022; 50:8512-8528. [PMID: 35920318 PMCID: PMC9410904 DOI: 10.1093/nar/gkac643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 07/07/2022] [Accepted: 07/20/2022] [Indexed: 11/14/2022] Open
Abstract
Cold shock adaptability is a key survival skill of gut bacteria of warm-blooded animals. Escherichia coli cold shock responses are controlled by a complex multi-gene, timely-ordered transcriptional program. We investigated its underlying mechanisms. Having identified short-term, cold shock repressed genes, we show that their responsiveness is unrelated to their transcription factors or global regulators, while their single-cell protein numbers' variability increases after cold shock. We hypothesized that some cold shock repressed genes could be triggered by high propensity for transcription locking due to changes in DNA supercoiling (likely due to DNA relaxation caused by an overall reduction in negative supercoiling). Concomitantly, we found that nearly half of cold shock repressed genes are also highly responsive to gyrase inhibition (albeit most genes responsive to gyrase inhibition are not cold shock responsive). Further, their response strengths to cold shock and gyrase inhibition correlate. Meanwhile, under cold shock, nucleoid density increases, and gyrases and nucleoid become more colocalized. Moreover, the cellular energy decreases, which may hinder positive supercoils resolution. Overall, we conclude that sensitivity to diminished negative supercoiling is a core feature of E. coli's short-term, cold shock transcriptional program, and could be used to regulate the temperature sensitivity of synthetic circuits.
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Affiliation(s)
- Suchintak Dash
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Cristina S D Palma
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Ines S C Baptista
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Bilena L B Almeida
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Mohamed N M Bahrudeen
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Vatsala Chauhan
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Rahul Jagadeesan
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland
| | - Andre S Ribeiro
- Laboratory of Biosystem Dynamics, Faculty of Medicine and Health Technology, Tampere University, Tampere 33520, Finland.,Center of Technology and Systems (CTS-Uninova), NOVA University of Lisbon 2829-516, Monte de Caparica, Portugal
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Computerized fluorescence microscopy of microbial cells. World J Microbiol Biotechnol 2021; 37:189. [PMID: 34617135 DOI: 10.1007/s11274-021-03159-3] [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: 07/27/2021] [Accepted: 09/30/2021] [Indexed: 10/20/2022]
Abstract
The upgrading of fluorescence microscopy by the introduction of computer technologies has led to the creation of a new methodology, computerized fluorescence microscopy (CFM). CFM improves subjective visualization and combines it with objective quantitative analysis of the microscopic data. CFM has opened up two fundamentally new opportunities for studying microorganisms. The first is the quantitative measurement of the fluorescence parameters of the targeted fluorophores in association with certain structures of individual cells. The second is the expansion of the boundaries of visualization/resolution of intracellular components beyond the "diffraction limit" of light microscopy into the nanometer range. This enables to obtain unique information about the localization and dynamics of intracellular processes at the molecular level. The purpose of this review is to demonstrate the potential of CFM in the study of fundamental aspects of the structural and functional organization of microbial cells. The basics of computer processing and analysis of digital images are briefly described. The fluorescent molecules used in CFM with an emphasis on fluorescent proteins are characterized. The main methods of super-resolution microscopy (nanoscopy) are presented. The capabilities of various CFM methods for exploring microbial cells at the subcellular level are illustrated by the examples of various studies on yeast and bacteria.
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Stracy M, Schweizer J, Sherratt DJ, Kapanidis AN, Uphoff S, Lesterlin C. Transient non-specific DNA binding dominates the target search of bacterial DNA-binding proteins. Mol Cell 2021; 81:1499-1514.e6. [PMID: 33621478 PMCID: PMC8022225 DOI: 10.1016/j.molcel.2021.01.039] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 11/24/2020] [Accepted: 01/27/2021] [Indexed: 12/18/2022]
Abstract
Despite their diverse biochemical characteristics and functions, all DNA-binding proteins share the ability to accurately locate their target sites among the vast excess of non-target DNA. Toward identifying universal mechanisms of the target search, we used single-molecule tracking of 11 diverse DNA-binding proteins in living Escherichia coli. The mobility of these proteins during the target search was dictated by DNA interactions rather than by their molecular weights. By generating cells devoid of all chromosomal DNA, we discovered that the nucleoid is not a physical barrier for protein diffusion but significantly slows the motion of DNA-binding proteins through frequent short-lived DNA interactions. The representative DNA-binding proteins (irrespective of their size, concentration, or function) spend the majority (58%–99%) of their search time bound to DNA and occupy as much as ∼30% of the chromosomal DNA at any time. Chromosome crowding likely has important implications for the function of all DNA-binding proteins. Protein motion was compared between unperturbed cells and DNA-free cells Protein mobility was dictated by DNA interactions rather than molecular weight The nucleoid is not a physical barrier for protein diffusion The proteins studied spend most (58%–99%) of their search time bound to DNA
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Affiliation(s)
- Mathew Stracy
- Department of Biochemistry, University of Oxford, Oxford OX1 3QU, UK.
| | - Jakob Schweizer
- Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany
| | - David J Sherratt
- Department of Biochemistry, University of Oxford, Oxford OX1 3QU, UK
| | - Achillefs N Kapanidis
- Biological Physics Research Group, Clarendon Laboratory, Department of Physics, University of Oxford, Oxford OX1 3PU, UK
| | - Stephan Uphoff
- Department of Biochemistry, University of Oxford, Oxford OX1 3QU, UK.
| | - Christian Lesterlin
- Molecular Microbiology and Structural Biochemistry (MMSB), Université Lyon 1, CNRS, INSERM, UMR5086, 69007 Lyon, France.
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Puchkov EO. Quantitative Methods for Single-Cell Analysis of Microorganisms. Microbiology (Reading) 2019. [DOI: 10.1134/s0026261719010120] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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