1
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Moores AN, Uphoff S. Robust Quantification of Live-Cell Single-Molecule Tracking Data for Fluorophores with Different Photophysical Properties. J Phys Chem B 2024; 128:7291-7303. [PMID: 38859654 DOI: 10.1021/acs.jpcb.4c01454] [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] [Indexed: 06/12/2024]
Abstract
High-speed single-molecule tracking in live cells is becoming an increasingly popular method for quantifying the spatiotemporal behavior of proteins in vivo. The method provides a wealth of quantitative information, but users need to be aware of biases that can skew estimates of molecular mobilities. The range of suitable fluorophores for live-cell single-molecule imaging has grown substantially over the past few years, but it remains unclear to what extent differences in photophysical properties introduce biases. Here, we tested two fluorophores with entirely different photophysical properties, one that photoswitches frequently between bright and dark states (TMR) and one that shows exceptional photostability without photoswitching (JFX650). We used a fusion of the Escherichia coli DNA repair enzyme MutS to the HaloTag and optimized sample preparation and imaging conditions for both types of fluorophore. We then assessed the reliability of two common data analysis algorithms, mean-square displacement (MSD) analysis and Hidden Markov Modeling (HMM), to estimate the diffusion coefficients and fractions of MutS molecules in different states of motion. We introduce a simple approach that removes discrepancies in the data analyses and show that both algorithms yield consistent results, regardless of the fluorophore used. Nevertheless, each dye has its own strengths and weaknesses, with TMR being more suitable for sampling the diffusive behavior of many molecules, while JFX650 enables prolonged observation of only a few molecules per cell. These characterizations and recommendations should help to standardize measurements for increased reproducibility and comparability across studies.
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Affiliation(s)
- Amy N Moores
- Department of Biochemistry, University of Oxford, South Parks Rd, Oxford OX1 3QU, U.K
| | - Stephan Uphoff
- Department of Biochemistry, University of Oxford, South Parks Rd, Oxford OX1 3QU, U.K
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2
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Pérez-Mitta G, Sezgin Y, Wang W, MacKinnon R. Freestanding bilayer microscope for single-molecule imaging of membrane proteins. SCIENCE ADVANCES 2024; 10:eado4722. [PMID: 38905330 PMCID: PMC11192074 DOI: 10.1126/sciadv.ado4722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 05/16/2024] [Indexed: 06/23/2024]
Abstract
Integral membrane proteins (IMPs) constitute a large fraction of organismal proteomes, playing fundamental roles in physiology and disease. Despite their importance, the mechanisms underlying dynamic features of IMPs, such as anomalous diffusion, protein-protein interactions, and protein clustering, remain largely unknown due to the high complexity of cell membrane environments. Available methods for in vitro studies are insufficient to study IMP dynamics systematically. This publication introduces the freestanding bilayer microscope (FBM), which combines the advantages of freestanding bilayers with single-particle tracking. The FBM, based on planar lipid bilayers, enables the study of IMP dynamics with single-molecule resolution and unconstrained diffusion. This paper benchmarks the FBM against total internal reflection fluorescence imaging on supported bilayers and is used here to estimate ion channel open probability and to examine the diffusion behavior of an ion channel in phase-separated bilayers. The FBM emerges as a powerful tool to examine membrane protein/lipid organization and dynamics to understand cell membrane processes.
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Affiliation(s)
- Gonzalo Pérez-Mitta
- Laboratory of Molecular Neurobiology and Biophysics, Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
| | - Yeliz Sezgin
- Laboratory of Molecular Neurobiology and Biophysics, Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
| | | | - Roderick MacKinnon
- Laboratory of Molecular Neurobiology and Biophysics, Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA
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3
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Martens KJA, Turkowyd B, Hohlbein J, Endesfelder U. Temporal analysis of relative distances (TARDIS) is a robust, parameter-free alternative to single-particle tracking. Nat Methods 2024; 21:1074-1081. [PMID: 38225387 DOI: 10.1038/s41592-023-02149-7] [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: 05/03/2023] [Accepted: 12/08/2023] [Indexed: 01/17/2024]
Abstract
In single-particle tracking, individual particles are localized and tracked over time to probe their diffusion and molecular interactions. Temporal crossing of trajectories, blinking particles, and false-positive localizations present computational challenges that have remained difficult to overcome. Here we introduce a robust, parameter-free alternative to single-particle tracking: temporal analysis of relative distances (TARDIS). In TARDIS, an all-to-all distance analysis between localizations is performed with increasing temporal shifts. These pairwise distances represent either intraparticle distances originating from the same particle, or interparticle distances originating from unrelated particles, and are fitted analytically to obtain quantitative measures on particle dynamics. We showcase that TARDIS outperforms tracking algorithms, benchmarked on simulated and experimental data of varying complexity. We further show that TARDIS performs accurately in complex conditions characterized by high particle density, strong emitter blinking or false-positive localizations, and is in fact limited by the capabilities of localization algorithms. TARDIS' robustness enables fivefold shorter measurements without loss of information.
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Affiliation(s)
- Koen J A Martens
- Institute for Microbiology and Biotechnology, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany.
- Department of Physics, Carnegie Mellon University, Pittsburgh, PA, USA.
- Laboratory of Biophysics, Wageningen University and Research, Wageningen, the Netherlands.
| | - Bartosz Turkowyd
- Institute for Microbiology and Biotechnology, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
- Department of Physics, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Johannes Hohlbein
- Laboratory of Biophysics, Wageningen University and Research, Wageningen, the Netherlands
- Microspectroscopy Research Facility, Wageningen University and Research, Wageningen, the Netherlands
| | - Ulrike Endesfelder
- Institute for Microbiology and Biotechnology, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
- Department of Physics, Carnegie Mellon University, Pittsburgh, PA, USA
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4
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Olivi L, Bagchus C, Pool V, Bekkering E, Speckner K, Offerhaus H, Wu W, Depken M, Martens KA, Staals RJ, Hohlbein J. Live-cell imaging reveals the trade-off between target search flexibility and efficiency for Cas9 and Cas12a. Nucleic Acids Res 2024; 52:5241-5256. [PMID: 38647045 PMCID: PMC11109954 DOI: 10.1093/nar/gkae283] [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: 11/16/2023] [Revised: 03/25/2024] [Accepted: 04/04/2024] [Indexed: 04/25/2024] Open
Abstract
CRISPR-Cas systems have widely been adopted as genome editing tools, with two frequently employed Cas nucleases being SpyCas9 and LbCas12a. Although both nucleases use RNA guides to find and cleave target DNA sites, the two enzymes differ in terms of protospacer-adjacent motif (PAM) requirements, guide architecture and cleavage mechanism. In the last years, rational engineering led to the creation of PAM-relaxed variants SpRYCas9 and impLbCas12a to broaden the targetable DNA space. By employing their catalytically inactive variants (dCas9/dCas12a), we quantified how the protein-specific characteristics impact the target search process. To allow quantification, we fused these nucleases to the photoactivatable fluorescent protein PAmCherry2.1 and performed single-particle tracking in cells of Escherichia coli. From our tracking analysis, we derived kinetic parameters for each nuclease with a non-targeting RNA guide, strongly suggesting that interrogation of DNA by LbdCas12a variants proceeds faster than that of SpydCas9. In the presence of a targeting RNA guide, both simulations and imaging of cells confirmed that LbdCas12a variants are faster and more efficient in finding a specific target site. Our work demonstrates the trade-off of relaxing PAM requirements in SpydCas9 and LbdCas12a using a powerful framework, which can be applied to other nucleases to quantify their DNA target search.
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Affiliation(s)
- Lorenzo Olivi
- Laboratory of Microbiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Cleo Bagchus
- Laboratory of Microbiology, Wageningen University & Research, Wageningen, The Netherlands
- Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands
| | - Victor Pool
- Laboratory of Microbiology, Wageningen University & Research, Wageningen, The Netherlands
- Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands
| | - Ezra Bekkering
- Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands
| | - Konstantin Speckner
- Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands
| | - Hidde Offerhaus
- Department of Bionanoscience, Kavli Institute of Nanoscience, Delft University of Technology, Delft, The Netherlands
| | - Wen Y Wu
- Laboratory of Microbiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Martin Depken
- Department of Bionanoscience, Kavli Institute of Nanoscience, Delft University of Technology, Delft, The Netherlands
| | - Koen J A Martens
- Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands
| | - Raymond H J Staals
- Laboratory of Microbiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Johannes Hohlbein
- Laboratory of Biophysics, Wageningen University & Research, Wageningen, The Netherlands
- Microspectroscopy Research Facility, Wageningen University & Research, Wageningen, The Netherlands
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5
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Ling YH, Ye Z, Liang C, Yu C, Park G, Corden JL, Wu C. Disordered C-terminal domain drives spatiotemporal confinement of RNAPII to enhance search for chromatin targets. Nat Cell Biol 2024; 26:581-592. [PMID: 38548891 PMCID: PMC11210292 DOI: 10.1038/s41556-024-01382-2] [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: 08/01/2023] [Accepted: 02/21/2024] [Indexed: 04/09/2024]
Abstract
Efficient gene expression requires RNA polymerase II (RNAPII) to find chromatin targets precisely in space and time. How RNAPII manages this complex diffusive search in three-dimensional nuclear space remains largely unknown. The disordered carboxy-terminal domain (CTD) of RNAPII, which is essential for recruiting transcription-associated proteins, forms phase-separated droplets in vitro, hinting at a potential role in modulating RNAPII dynamics. In the present study, we use single-molecule tracking and spatiotemporal mapping in living yeast to show that the CTD is required for confining RNAPII diffusion within a subnuclear region enriched for active genes, but without apparent phase separation into condensates. Both Mediator and global chromatin organization are required for sustaining RNAPII confinement. Remarkably, truncating the CTD disrupts RNAPII spatial confinement, prolongs target search, diminishes chromatin binding, impairs pre-initiation complex formation and reduces transcription bursting. The present study illuminates the pivotal role of the CTD in driving spatiotemporal confinement of RNAPII for efficient gene expression.
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Affiliation(s)
- Yick Hin Ling
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Ziyang Ye
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Chloe Liang
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Chuofan Yu
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Giho Park
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Jeffry L Corden
- Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Carl Wu
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA.
- Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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6
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Costa AR, van den Berg DF, Esser JQ, Muralidharan A, van den Bossche H, Bonilla BE, van der Steen BA, Haagsma AC, Fluit AC, Nobrega FL, Haas PJ, Brouns SJJ. Accumulation of defense systems in phage-resistant strains of Pseudomonas aeruginosa. SCIENCE ADVANCES 2024; 10:eadj0341. [PMID: 38394193 PMCID: PMC10889362 DOI: 10.1126/sciadv.adj0341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 01/22/2024] [Indexed: 02/25/2024]
Abstract
Prokaryotes encode multiple distinct anti-phage defense systems in their genomes. However, the impact of carrying a multitude of defense systems on phage resistance remains unclear, especially in a clinical context. Using a collection of antibiotic-resistant clinical strains of Pseudomonas aeruginosa and a broad panel of phages, we demonstrate that defense systems contribute substantially to defining phage host range and that overall phage resistance scales with the number of defense systems in the bacterial genome. We show that many individual defense systems target specific phage genera and that defense systems with complementary phage specificities co-occur in P. aeruginosa genomes likely to provide benefits in phage-diverse environments. Overall, we show that phage-resistant phenotypes of P. aeruginosa with at least 19 phage defense systems exist in the populations of clinical, antibiotic-resistant P. aeruginosa strains.
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Affiliation(s)
- Ana Rita Costa
- Department of Bionanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
- Kavli Institute of Nanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
| | - Daan F. van den Berg
- Department of Bionanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
- Kavli Institute of Nanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
| | - Jelger Q. Esser
- Department of Bionanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
- Kavli Institute of Nanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
| | - Aswin Muralidharan
- Department of Bionanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
- Kavli Institute of Nanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
| | - Halewijn van den Bossche
- Department of Bionanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
- Kavli Institute of Nanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
| | - Boris Estrada Bonilla
- Department of Bionanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
- Kavli Institute of Nanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
| | - Baltus A. van der Steen
- Department of Bionanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
- Kavli Institute of Nanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
| | - Anna C. Haagsma
- Department of Bionanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
- Kavli Institute of Nanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
| | - Ad C. Fluit
- Medical Microbiology, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, Netherlands
| | - Franklin L. Nobrega
- School of Biological Sciences, University of Southampton, SO17 1BJ Southampton, UK
| | - Pieter-Jan Haas
- Medical Microbiology, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, Netherlands
| | - Stan J. J. Brouns
- Department of Bionanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
- Kavli Institute of Nanoscience, Delft University of Technology, 2629 HZ Delft, Netherlands
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7
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Prindle JR, de Cuba OIC, Gahlmann A. Single-molecule tracking to determine the abundances and stoichiometries of freely-diffusing protein complexes in living cells: Past applications and future prospects. J Chem Phys 2023; 159:071002. [PMID: 37589409 PMCID: PMC10908566 DOI: 10.1063/5.0155638] [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: 04/21/2023] [Accepted: 07/06/2023] [Indexed: 08/18/2023] Open
Abstract
Most biological processes in living cells rely on interactions between proteins. Live-cell compatible approaches that can quantify to what extent a given protein participates in homo- and hetero-oligomeric complexes of different size and subunit composition are therefore critical to advance our understanding of how cellular physiology is governed by these molecular interactions. Biomolecular complex formation changes the diffusion coefficient of constituent proteins, and these changes can be measured using fluorescence microscopy-based approaches, such as single-molecule tracking, fluorescence correlation spectroscopy, and fluorescence recovery after photobleaching. In this review, we focus on the use of single-molecule tracking to identify, resolve, and quantify the presence of freely-diffusing proteins and protein complexes in living cells. We compare and contrast different data analysis methods that are currently employed in the field and discuss experimental designs that can aid the interpretation of the obtained results. Comparisons of diffusion rates for different proteins and protein complexes in intracellular aqueous environments reported in the recent literature reveal a clear and systematic deviation from the Stokes-Einstein diffusion theory. While a complete and quantitative theoretical explanation of why such deviations manifest is missing, the available data suggest the possibility of weighing freely-diffusing proteins and protein complexes in living cells by measuring their diffusion coefficients. Mapping individual diffusive states to protein complexes of defined molecular weight, subunit stoichiometry, and structure promises to provide key new insights into how protein-protein interactions regulate protein conformational, translational, and rotational dynamics, and ultimately protein function.
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Affiliation(s)
- Joshua Robert Prindle
- Department of Chemistry, University of Virginia, Charlottesville, Virginia 22904, USA
| | - Olivia Isabella Christiane de Cuba
- Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, Virginia 22903, USA
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8
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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: 0] [Impact Index Per Article: 0] [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: 03/08/2023] 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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9
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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: 1.0] [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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10
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Wolf A, Volz-Rakebrand P, Balke J, Alexiev U. Diffusion Analysis of NAnoscopic Ensembles: A Tracking-Free Diffusivity Analysis for NAnoscopic Ensembles in Biological Samples and Nanotechnology. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2023; 19:e2206722. [PMID: 36670094 DOI: 10.1002/smll.202206722] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/16/2022] [Indexed: 06/17/2023]
Abstract
The rapid development of microscopic techniques over the past decades enables the establishment of single molecule fluorescence imaging as a powerful tool in biological and biomedical sciences. Single molecule fluorescence imaging allows to study the chemical, physicochemical, and biological properties of target molecules or particles by tracking their molecular position in the biological environment and determining their dynamic behavior. However, the precise determination of particle distribution and diffusivities is often challenging due to high molecule/particle densities, fast diffusion, and photobleaching/blinking of the fluorophore. A novel, accurate, and fast statistical analysis tool, Diffusion Analysis of NAnoscopic Ensembles (DANAE), that solves all these obstacles is introduced. DANAE requires no approximations or any a priori input regarding unknown system-inherent parameters, such as background distributions; a requirement that is vitally important when studying the behavior of molecules/particles in living cells. The superiority of DANAE with various data from simulations is demonstrated. As experimental applications of DANAE, membrane receptor diffusion in its natural membrane environment, and cargo mobility/distribution within nanostructured lipid nanoparticles are presented. Finally, the method is extended to two-color channel fluorescence microscopy.
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Affiliation(s)
- Alexander Wolf
- Department of Physics, Freie Universität Berlin, Arnimallee 14, 14195, Berlin, Germany
| | - Pierre Volz-Rakebrand
- Department of Physics, Freie Universität Berlin, Arnimallee 14, 14195, Berlin, Germany
| | - Jens Balke
- Department of Physics, Freie Universität Berlin, Arnimallee 14, 14195, Berlin, Germany
| | - Ulrike Alexiev
- Department of Physics, Freie Universität Berlin, Arnimallee 14, 14195, Berlin, Germany
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11
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Holub M, Birnie A, Japaridze A, van der Torre J, Ridder MD, de Ram C, Pabst M, Dekker C. Extracting and characterizing protein-free megabase-pair DNA for in vitro experiments. CELL REPORTS METHODS 2022; 2:100366. [PMID: 36590691 PMCID: PMC9795359 DOI: 10.1016/j.crmeth.2022.100366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 09/29/2022] [Accepted: 11/16/2022] [Indexed: 12/15/2022]
Abstract
Chromosome structure and function is studied using various cell-based methods as well as with a range of in vitro single-molecule techniques on short DNA substrates. Here, we present a method to obtain megabase-pair-length deproteinated DNA for in vitro studies. We isolated chromosomes from bacterial cells and enzymatically digested the native proteins. Mass spectrometry indicated that 97%-100% of DNA-binding proteins are removed from the sample. Fluorescence microscopy analysis showed an increase in the radius of gyration of the DNA polymers, while the DNA length remained megabase-pair sized. In proof-of-concept experiments using these deproteinated long DNA molecules, we observed DNA compaction upon adding the DNA-binding protein Fis or PEG crowding agents and showed that it is possible to track the motion of a fluorescently labeled DNA locus. These results indicate the practical feasibility of a "genome-in-a-box" approach to study chromosome organization from the bottom up.
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Affiliation(s)
- Martin Holub
- Department of Bionanoscience & Kavli Institute for Nanoscience, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, the Netherlands
| | - Anthony Birnie
- Department of Bionanoscience & Kavli Institute for Nanoscience, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, the Netherlands
| | - Aleksandre Japaridze
- Department of Bionanoscience & Kavli Institute for Nanoscience, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, the Netherlands
| | - Jaco van der Torre
- Department of Bionanoscience & Kavli Institute for Nanoscience, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, the Netherlands
| | - Maxime den Ridder
- Department of Biotechnology, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, the Netherlands
| | - Carol de Ram
- Department of Biotechnology, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, the Netherlands
| | - Martin Pabst
- Department of Biotechnology, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, the Netherlands
| | - Cees Dekker
- Department of Bionanoscience & Kavli Institute for Nanoscience, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, the Netherlands
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12
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Etheridge TJ, Carr AM, Herbert AD. GDSC SMLM: Single-molecule localisation microscopy software for ImageJ. Wellcome Open Res 2022; 7:241. [PMID: 37351368 PMCID: PMC10282564 DOI: 10.12688/wellcomeopenres.18327.1] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/15/2022] [Indexed: 08/03/2023] Open
Abstract
Single-molecule localisation microscopy (SMLM) uses software to extract super-resolved positions from microscope images of fluorescent molecules. These localisations can then be used to render super-resolution images or analysed to extract information about molecular behaviour. The GDSC SMLM software provides a set of tools for analysing SMLM data in a single cross-platform environment. The software identifies fluorescent molecules in raw microscope images and localises their positions using stages of spot detection, spot fitting and spot rejection. The resulting localisation data set can then be visualised, cropped and filtered. A suite of downstream analysis tools enable the user to perform single-particle tracking, cluster analysis and drift correction. In addition, GDSC SMLM also provides utility tools that enable modelling of EM-CCD and sCMOS cameras as well as point spread functions (PSFs) for data simulation. The software is written in Java and runs as a collection of plugins for the ImageJ software.
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Affiliation(s)
- Thomas J. Etheridge
- Genome Damage and Stability Centre, School of Life Sciences, University of Sussex, Falmer, BN1 9RQ, UK
| | - Antony M. Carr
- Genome Damage and Stability Centre, School of Life Sciences, University of Sussex, Falmer, BN1 9RQ, UK
| | - Alex D. Herbert
- Genome Damage and Stability Centre, School of Life Sciences, University of Sussex, Falmer, BN1 9RQ, UK
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Metelev M, Lundin E, Volkov IL, Gynnå AH, Elf J, Johansson M. Direct measurements of mRNA translation kinetics in living cells. Nat Commun 2022; 13:1852. [PMID: 35388013 PMCID: PMC8986856 DOI: 10.1038/s41467-022-29515-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Accepted: 03/17/2022] [Indexed: 01/09/2023] Open
Abstract
Ribosome mediated mRNA translation is central to life. The cycle of translation, however, has been characterized mostly using reconstituted systems, with only few techniques applicable for studies in the living cell. Here we describe a live-cell ribosome-labeling method, which allows us to characterize the whole processes of finding and translating an mRNA, using single-molecule tracking techniques. We find that more than 90% of both bacterial ribosomal subunits are engaged in translation at any particular time, and that the 30S and 50S ribosomal subunits spend the same average time bound to an mRNA, revealing that 30S re-initiation on poly-cistronic mRNAs is not prevalent in E. coli. Instead, our results are best explained by substantial 70S re-initiation of translation of poly-cistronic mRNAs, which is further corroborated by experiments with translation initiation inhibitors. Finally, we find that a variety of previously described orthogonal ribosomes, with altered anti-Shine-Dalgarno sequences, show significant binding to endogenous mRNAs.
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Affiliation(s)
- Mikhail Metelev
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Erik Lundin
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Ivan L Volkov
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Arvid H Gynnå
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Johan Elf
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Magnus Johansson
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.
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14
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Martens KJA, Turkowyd B, Endesfelder U. Raw Data to Results: A Hands-On Introduction and Overview of Computational Analysis for Single-Molecule Localization Microscopy. FRONTIERS IN BIOINFORMATICS 2022; 1:817254. [PMID: 36303761 PMCID: PMC9580916 DOI: 10.3389/fbinf.2021.817254] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 12/28/2021] [Indexed: 09/28/2023] Open
Abstract
Single-molecule localization microscopy (SMLM) is an advanced microscopy method that uses the blinking of fluorescent molecules to determine the position of these molecules with a resolution below the diffraction limit (∼5-40 nm). While SMLM imaging itself is becoming more popular, the computational analysis surrounding the technique is still a specialized area and often remains a "black box" for experimental researchers. Here, we provide an introduction to the required computational analysis of SMLM imaging, post-processing and typical data analysis. Importantly, user-friendly, ready-to-use and well-documented code in Python and MATLAB with exemplary data is provided as an interactive experience for the reader, as well as a starting point for further analysis. Our code is supplemented by descriptions of the computational problems and their implementation. We discuss the state of the art in computational methods and software suites used in SMLM imaging and data analysis. Finally, we give an outlook into further computational challenges in the field.
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Affiliation(s)
- Koen J. A. Martens
- Department of Physics, Carnegie Mellon University, Pittsburgh, PA, United States
- Institute for Microbiology and Biotechnology, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Bartosz Turkowyd
- Department of Physics, Carnegie Mellon University, Pittsburgh, PA, United States
- Institute for Microbiology and Biotechnology, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
- Department of Systems and Synthetic Microbiology, Max Planck Institute for Terrestrial Microbiology, LOEWE Center for Synthetic Microbiology (SYNMIKRO), Marburg, Germany
| | - Ulrike Endesfelder
- Department of Physics, Carnegie Mellon University, Pittsburgh, PA, United States
- Institute for Microbiology and Biotechnology, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
- Department of Systems and Synthetic Microbiology, Max Planck Institute for Terrestrial Microbiology, LOEWE Center for Synthetic Microbiology (SYNMIKRO), Marburg, Germany
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15
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Cassaro CJ, Uphoff S. Super-Resolution Microscopy and Tracking of DNA-Binding Proteins in Bacterial Cells. Methods Mol Biol 2022; 2476:191-208. [PMID: 35635706 DOI: 10.1007/978-1-0716-2221-6_15] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The ability to detect individual fluorescent molecules inside living cells has enabled a range of powerful microscopy techniques that resolve biological processes on the molecular scale. These methods have also transformed the study of bacterial cell biology, which was previously obstructed by the limited spatial resolution of conventional microscopy. In the case of DNA-binding proteins, super-resolution microscopy can visualize the detailed spatial organization of DNA replication, transcription, and repair processes by reconstructing a map of single-molecule localizations. Furthermore, DNA-binding activities can be observed directly by tracking protein movement in real time. This allows identifying subpopulations of DNA-bound and diffusing proteins, and can be used to measure DNA-binding times in vivo. This chapter provides a detailed protocol for super-resolution microscopy and tracking of DNA-binding proteins in Escherichia coli cells. The protocol covers the genetic engineering and fluorescent labeling of strains and describes data acquisition and analysis procedures, such as super-resolution image reconstruction, mapping single-molecule tracks, computing diffusion coefficients to identify molecular subpopulations with different mobility, and analysis of DNA-binding kinetics. While the focus is on the study of bacterial chromosome biology, these approaches are generally applicable to other molecular processes and cell types.
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Affiliation(s)
- Chloé J Cassaro
- Department of Biochemistry, University of Oxford, Oxford, UK
| | - Stephan Uphoff
- Department of Biochemistry, University of Oxford, Oxford, UK.
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16
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A Protocol for Studying Transcription Factor Dynamics Using Fast Single-Particle Tracking and Spot-On Model-Based Analysis. Methods Mol Biol 2022; 2458:151-174. [PMID: 35103967 DOI: 10.1007/978-1-0716-2140-0_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Single-particle tracking (SPT) makes it possible to directly observe single protein diffusion dynamics in living cells over time. Thus, SPT has emerged as a powerful method to quantify the dynamics of nuclear proteins such as transcription factors (TFs). Here, we provide a protocol for conducting and analyzing SPT experiments with a focus on fast tracking ("fastSPT") of TFs in mammalian cells. First, we explore how to engineer and prepare cells for SPT experiments. Next, we examine how to optimize SPT experiments by imaging at low densities to minimize tracking errors and by using stroboscopic excitation to minimize motion-blur. Next, we discuss how to convert raw SPT data into single-particle trajectories. Finally, we illustrate how to analyze these trajectories using the kinetic modeling package Spot-On. We discuss how to use Spot-On to fit histograms of displacements and extract useful information such as the fraction of TFs that are bound and freely diffusing, and their associated diffusion coefficients.
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17
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Rahm JV, Malkusch S, Endesfelder U, Dietz MS, Heilemann M. Diffusion State Transitions in Single-Particle Trajectories of MET Receptor Tyrosine Kinase Measured in Live Cells. FRONTIERS IN COMPUTER SCIENCE 2021. [DOI: 10.3389/fcomp.2021.757653] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Single-particle tracking enables the analysis of the dynamics of biomolecules in living cells with nanometer spatial and millisecond temporal resolution. This technique reports on the mobility of membrane proteins and is sensitive to the molecular state of a biomolecule and to interactions with other biomolecules. Trajectories describe the mobility of single particles over time and provide information such as the diffusion coefficient and diffusion state. Changes in particle dynamics within single trajectories lead to segmentation, which allows to extract information on transitions of functional states of a biomolecule. Here, mean-squared displacement analysis is developed to classify trajectory segments into immobile, confined diffusing, and freely diffusing states, and to extract the occurrence of transitions between these modes. We applied this analysis to single-particle tracking data of the membrane receptor MET in live cells and analyzed state transitions in single trajectories of the un-activated receptor and the receptor bound to the ligand internalin B. We found that internalin B-bound MET shows an enhancement of transitions from freely and confined diffusing states into the immobile state as compared to un-activated MET. Confined diffusion acts as an intermediate state between immobile and free, as this state is most likely to change the diffusion state in the following segment. This analysis can be readily applied to single-particle tracking data of other membrane receptors and intracellular proteins under various conditions and contribute to the understanding of molecular states and signaling pathways.
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18
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Boka AP, Mukherjee A, Mir M. Single-molecule tracking technologies for quantifying the dynamics of gene regulation in cells, tissue and embryos. Development 2021; 148:272071. [PMID: 34490887 DOI: 10.1242/dev.199744] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
For decades, we have relied on population and time-averaged snapshots of dynamic molecular scale events to understand how genes are regulated during development and beyond. The advent of techniques to observe single-molecule kinetics in increasingly endogenous contexts, progressing from in vitro studies to living embryos, has revealed how much we have missed. Here, we provide an accessible overview of the rapidly expanding family of technologies for single-molecule tracking (SMT), with the goal of enabling the reader to critically analyse single-molecule studies, as well as to inspire the application of SMT to their own work. We start by overviewing the basics of and motivation for SMT experiments, and the trade-offs involved when optimizing parameters. We then cover key technologies, including fluorescent labelling, excitation and detection optics, localization and tracking algorithms, and data analysis. Finally, we provide a summary of selected recent applications of SMT to study the dynamics of gene regulation.
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Affiliation(s)
- Alan P Boka
- Biochemistry and Molecular Biophysics Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Apratim Mukherjee
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Mustafa Mir
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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