1
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Berg A, Velayuthan LP, Tågerud S, Ušaj M, Månsson A. Probing actin-activated ATP turnover kinetics of human cardiac myosin II by single molecule fluorescence. Cytoskeleton (Hoboken) 2024. [PMID: 38623952 DOI: 10.1002/cm.21858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 03/06/2024] [Accepted: 03/25/2024] [Indexed: 04/17/2024]
Abstract
Mechanistic insights into myosin II energy transduction in striated muscle in health and disease would benefit from functional studies of a wide range of point-mutants. This approach is, however, hampered by the slow turnaround of myosin II expression that usually relies on adenoviruses for gene transfer. A recently developed virus-free method is more time effective but would yield too small amounts of myosin for standard biochemical analyses. However, if the fluorescent adenosine triphosphate (ATP) and single molecule (sm) total internal reflection fluorescence microscopy previously used to analyze basal ATP turnover by myosin alone, can be expanded to actin-activated ATP turnover, it would appreciably reduce the required amount of myosin. To that end, we here describe zero-length cross-linking of human cardiac myosin II motor fragments (sub-fragment 1 long [S1L]) to surface-immobilized actin filaments in a configuration with maintained actin-activated ATP turnover. After optimizing the analysis of sm fluorescence events, we show that the amount of myosin produced from C2C12 cells in one 60 mm cell culture plate is sufficient to obtain both the basal myosin ATP turnover rate and the maximum actin-activated rate constant (kcat). Our analysis of many single binding events of fluorescent ATP to many S1L motor fragments revealed processes reflecting basal and actin-activated ATPase, but also a third exponential process consistent with non-specific ATP-binding outside the active site.
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Affiliation(s)
- Albin Berg
- Department of Chemistry and Biomedical Sciences, Faculty of Health and Life Science, Linnaeus University, Kalmar, Sweden
| | - Lok Priya Velayuthan
- Department of Chemistry and Biomedical Sciences, Faculty of Health and Life Science, Linnaeus University, Kalmar, Sweden
| | - Sven Tågerud
- Department of Chemistry and Biomedical Sciences, Faculty of Health and Life Science, Linnaeus University, Kalmar, Sweden
| | - Marko Ušaj
- Department of Chemistry and Biomedical Sciences, Faculty of Health and Life Science, Linnaeus University, Kalmar, Sweden
| | - Alf Månsson
- Department of Chemistry and Biomedical Sciences, Faculty of Health and Life Science, Linnaeus University, Kalmar, Sweden
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2
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Kalisvaart D, Hung ST, Smith CS. Quantifying the minimum localization uncertainty of image scanning localization microscopy. BIOPHYSICAL REPORTS 2024; 4:100143. [PMID: 38380223 PMCID: PMC10878846 DOI: 10.1016/j.bpr.2024.100143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 01/09/2024] [Indexed: 02/22/2024]
Abstract
Modulation enhanced single-molecule localization microscopy (meSMLM), where emitters are sparsely activated with sequentially applied patterned illumination, increases the localization precision over single-molecule localization microscopy (SMLM). The precision improvement of modulation enhanced SMLM is derived from retrieving the position of an emitter relative to individual illumination patterns, which adds to existing point spread function information from SMLM. Here, we introduce SpinFlux: modulation enhanced localization for spinning disk confocal microscopy. SpinFlux uses a spinning disk with pinholes in its illumination and emission paths, to sequentially illuminate regions in the sample during each measurement. The resulting intensity-modulated emission signal is analyzed for each individual pattern to localize emitters with improved precision. We derive a statistical image formation model for SpinFlux and we quantify the theoretical minimum localization uncertainty in terms of the Cramér-Rao lower bound. Using the theoretical minimum uncertainty, we compare SpinFlux to localization on Fourier reweighted image scanning microscopy reconstructions. We find that localization on image scanning microscopy reconstructions with Fourier reweighting ideally results in a global precision improvement of 2.1 over SMLM. When SpinFlux is used for sequential illumination with three patterns around the emitter position, the localization precision improvement over SMLM is twofold when patterns are focused around the emitter position. If four donut-shaped illumination patterns are used for SpinFlux, the maximum local precision improvement over SMLM is increased to 3.5. Localization of image scanning microscopy reconstructions thus has the largest potential for global improvements of the localization precision, where SpinFlux is the method of choice for local refinements.
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Affiliation(s)
- Dylan Kalisvaart
- Delft Center for Systems and Control, Delft University of Technology, Delft, the Netherlands
| | - Shih-Te Hung
- Delft Center for Systems and Control, Delft University of Technology, Delft, the Netherlands
| | - Carlas S. Smith
- Delft Center for Systems and Control, Delft University of Technology, Delft, the Netherlands
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
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3
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Stinson BM, Carney SM, Walter JC, Loparo JJ. Structural role for DNA Ligase IV in promoting the fidelity of non-homologous end joining. Nat Commun 2024; 15:1250. [PMID: 38341432 PMCID: PMC10858965 DOI: 10.1038/s41467-024-45553-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 01/25/2024] [Indexed: 02/12/2024] Open
Abstract
Nonhomologous end joining (NHEJ), the primary pathway of vertebrate DNA double-strand-break (DSB) repair, directly re-ligates broken DNA ends. Damaged DSB ends that cannot be immediately re-ligated are modified by NHEJ processing enzymes, including error-prone polymerases and nucleases, to enable ligation. However, DSB ends that are initially compatible for re-ligation are typically joined without end processing. As both ligation and end processing occur in the short-range (SR) synaptic complex that closely aligns DNA ends, it remains unclear how ligation of compatible ends is prioritized over end processing. In this study, we identify structural interactions of the NHEJ-specific DNA Ligase IV (Lig4) within the SR complex that prioritize ligation and promote NHEJ fidelity. Mutational analysis demonstrates that Lig4 must bind DNA ends to form the SR complex. Furthermore, single-molecule experiments show that a single Lig4 binds both DNA ends at the instant of SR synapsis. Thus, Lig4 is poised to ligate compatible ends upon initial formation of the SR complex before error-prone processing. Our results provide a molecular basis for the fidelity of NHEJ.
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Affiliation(s)
- Benjamin M Stinson
- Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA
- Howard Hughes Medical Institute, Boston, MA, 02115, USA
| | - Sean M Carney
- Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA
| | - Johannes C Walter
- Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA.
- Howard Hughes Medical Institute, Boston, MA, 02115, USA.
| | - Joseph J Loparo
- Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA.
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4
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Okamoto K, Fujita H, Okada Y, Shinkai S, Onami S, Abe K, Fujimoto K, Sasaki K, Shioi G, Watanabe TM. Single-molecule tracking of Nanog and Oct4 in living mouse embryonic stem cells uncovers a feedback mechanism of pluripotency maintenance. EMBO J 2023; 42:e112305. [PMID: 37609947 PMCID: PMC10505915 DOI: 10.15252/embj.2022112305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 06/13/2023] [Accepted: 06/22/2023] [Indexed: 08/24/2023] Open
Abstract
Nanog and Oct4 are core transcription factors that form part of a gene regulatory network to regulate hundreds of target genes for pluripotency maintenance in mouse embryonic stem cells (ESCs). To understand their function in the pluripotency maintenance, we visualised and quantified the dynamics of single molecules of Nanog and Oct4 in a mouse ESCs during pluripotency loss. Interestingly, Nanog interacted longer with its target loci upon reduced expression or at the onset of differentiation, suggesting a feedback mechanism to maintain the pluripotent state. The expression level and interaction time of Nanog and Oct4 correlate with their fluctuation and interaction frequency, respectively, which in turn depend on the ESC differentiation status. The DNA viscoelasticity near the Oct4 target locus remained flexible during differentiation, supporting its role either in chromatin opening or a preferred binding to uncondensed chromatin regions. Based on these results, we propose a new negative feedback mechanism for pluripotency maintenance via the DNA condensation state-dependent interplay of Nanog and Oct4.
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Affiliation(s)
- Kazuko Okamoto
- Laboratory for Comprehensive BioimagingRIKEN Center for Biosystems Dynamics Research (BDR)KobeJapan
- Amphibian Research CenterHiroshima UniversityHiroshimaJapan
| | - Hideaki Fujita
- Department of Stem Cell Biology, Research Institute for Radiation Biology and MedicineHiroshima UniversityHigashi‐HiroshimaJapan
| | - Yasushi Okada
- Laboratory for Cell Polarity RegulationRIKEN Center for Biosystems Dynamics Research (BDR)OsakaJapan
- Department of Cell BiologyGraduate School of Medicine, The University of TokyoTokyoJapan
- Department of PhysicsUniversal Biology Institute (UBI)Graduate School of Science, The University of TokyoTokyoJapan
- International Research Center for Neurointelligence (WPI‐IRCN)Institutes for Advanced Study, The University of TokyoTokyoJapan
| | - Soya Shinkai
- Laboratory for Developmental DynamicsRIKEN Center for Biosystems Dynamics Research (BDR)KobeJapan
- Research Center for the Mathematics on Chromatin Live Dynamics (RcMcD)Hiroshima UniversityHiroshimaJapan
| | - Shuichi Onami
- Laboratory for Developmental DynamicsRIKEN Center for Biosystems Dynamics Research (BDR)KobeJapan
| | - Kuniya Abe
- Technology and Development Team for Mammalian Genome DynamicsRIKEN BioResource Research Center (BRC)TsukubaJapan
| | - Kenta Fujimoto
- Department of Stem Cell Biology, Research Institute for Radiation Biology and MedicineHiroshima UniversityHigashi‐HiroshimaJapan
| | - Kensuke Sasaki
- Laboratory for Comprehensive BioimagingRIKEN Center for Biosystems Dynamics Research (BDR)KobeJapan
| | - Go Shioi
- Laboratory for Comprehensive BioimagingRIKEN Center for Biosystems Dynamics Research (BDR)KobeJapan
| | - Tomonobu M Watanabe
- Laboratory for Comprehensive BioimagingRIKEN Center for Biosystems Dynamics Research (BDR)KobeJapan
- Department of Stem Cell Biology, Research Institute for Radiation Biology and MedicineHiroshima UniversityHigashi‐HiroshimaJapan
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5
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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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6
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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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7
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Hung ST, Cnossen J, Fan D, Siemons M, Jurriens D, Grußmayer K, Soloviev O, Kapitein LC, Smith CS. SOLEIL: single-objective lens inclined light sheet localization microscopy. BIOMEDICAL OPTICS EXPRESS 2022; 13:3275-3294. [PMID: 35781973 PMCID: PMC9208595 DOI: 10.1364/boe.451634] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 04/19/2022] [Accepted: 04/20/2022] [Indexed: 06/15/2023]
Abstract
High-NA light sheet illumination can improve the resolution of single-molecule localization microscopy (SMLM) by reducing the background fluorescence. These approaches currently require custom-made sample holders or additional specialized objectives, which makes the sample mounting or the optical system complex and therefore reduces the usability of these approaches. Here, we developed a single-objective lens-inclined light sheet microscope (SOLEIL) that is capable of 2D and 3D SMLM in thick samples. SOLEIL combines oblique illumination with point spread function PSF engineering to enable dSTORM imaging in a wide variety of samples. SOLEIL is compatible with standard sample holders and off-the-shelve optics and standard high NA objectives. To accomplish optimal optical sectioning we show that there is an ideal oblique angle and sheet thickness. Furthermore, to show what optical sectioning delivers for SMLM we benchmark SOLEIL against widefield and HILO microscopy with several biological samples. SOLEIL delivers in 15 μm thick Caco2-BBE cells a 374% higher intensity to background ratio and a 54% improvement in the estimated CRLB compared to widefield illumination, and a 184% higher intensity to background ratio and a 20% improvement in the estimated CRLB compared to HILO illumination.
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Affiliation(s)
- Shih-Te Hung
- Delft Center for Systems and Control, Delft University of Technology, Delft, Netherlands
| | - Jelmer Cnossen
- Delft Center for Systems and Control, Delft University of Technology, Delft, Netherlands
| | - Daniel Fan
- Delft Center for Systems and Control, Delft University of Technology, Delft, Netherlands
| | - Marijn Siemons
- Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Daphne Jurriens
- Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Kristin Grußmayer
- Department of Bionanoscience and Kavli Institute of Nanoscience Delft, Delft University of Technology, Delft, Netherlands
| | - Oleg Soloviev
- Delft Center for Systems and Control, Delft University of Technology, Delft, Netherlands
- Flexible Optical B.V., Polakweg 10-11, 2288 GG Rijswijk, Netherlands
| | - Lukas C. Kapitein
- Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Carlas S. Smith
- Delft Center for Systems and Control, Delft University of Technology, Delft, Netherlands
- Department of Imaging Physics, Delft University of Technology, Delft, Netherlands
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8
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Precision in iterative modulation enhanced single-molecule localization microscopy. Biophys J 2022; 121:2279-2289. [PMID: 35614851 DOI: 10.1016/j.bpj.2022.05.027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 04/14/2022] [Accepted: 05/19/2022] [Indexed: 11/22/2022] Open
Abstract
Modulation enhanced single-molecule localization microscopy (meSMLM) methods improve the localization precision by using patterned illumination to encode additional position information. Iterative meSMLM (imeSMLM) methods iteratively generate prior information on emitter positions, used to locally improve the localization precision during subsequent iterations. The Cramér-Rao lower bound (CRLB) cannot incorporate prior information to bound the best achievable localization precision, because it requires estimators to be unbiased. By treating estimands as random variables with a known prior distribution, the Van Trees inequality (VTI) can be used to bound the best possible localization precision of imeSMLM methods. An imeSMLM method is considered, where the positions of in-plane standing wave illumination patterns are controlled over the course of multiple iterations. Using the VTI, we analytically approximate a lower bound on the maximum localization precision of imeSMLM methods that make use of standing wave illumination patterns. In addition, we evaluate the maximally achievable localization precision for different illumination pattern placement strategies using Monte Carlo simulations. We show that in the absence of background and under perfect modulation, the information content of signal photons increases exponentially as a function of the iteration count. However, the information increase is no longer exponential as a function of the iteration count under non-zero background, imperfect modulation or limited mechanical resolution of the illumination positioning system. As a result, imeSMLM with two iterations reaches at most a 5-fold improvement over SMLM at 8 expected background photons per pixel and 95% modulation contrast. Moreover, the information increase from imeSMLM is balanced by a reduced signal photon rate. Therefore, SMLM outperforms imeSMLM when considering an equal measurement time and illumination power per iteration. Finally, the VTI is an excellent tool for the assessment of the performance of illumination control and is therefore the method of choice for optimal design and control of imeSMLM methods.
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9
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Jouravleva K, Vega-Badillo J, Zamore PD. Principles and pitfalls of high-throughput analysis of microRNA-binding thermodynamics and kinetics by RNA Bind-n-Seq. CELL REPORTS METHODS 2022; 2:100185. [PMID: 35475222 PMCID: PMC9017153 DOI: 10.1016/j.crmeth.2022.100185] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 01/18/2022] [Accepted: 02/25/2022] [Indexed: 12/24/2022]
Abstract
RNA Bind-n-Seq (RBNS) is a cost-effective, high-throughput method capable of identifying the sequence preferences of RNA-binding proteins and of qualitatively defining relative dissociation constants. Although RBNS is often described as an unbiased method, several factors may influence the outcome of the analysis. Here, we discuss these biases and present an analytical strategy to estimate absolute binding affinities from RBNS data, extend RBNS to kinetic studies, and develop a framework to compute relative association and dissociation rate constants. As proof of principle, we measured the equilibrium binding properties of mammalian Argonaute2 (AGO2) guided by eight microRNAs (miRNAs) and kinetic parameters for let-7a. The miRNA-binding site repertoires, dissociation constants, and kinetic parameters calculated from RBNS data using our methods correlate well with values measured by traditional ensemble and single-molecule approaches. Our data provide additional quantitative measurements for Argonaute-bound miRNA binding that should facilitate development of quantitative targeting rules for individual miRNAs.
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Affiliation(s)
- Karina Jouravleva
- RNA Therapeutics Institute, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA
| | - Joel Vega-Badillo
- RNA Therapeutics Institute, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA
| | - Phillip D. Zamore
- RNA Therapeutics Institute, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA
- Howard Hughes Medical Institute, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA 01605, USA
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10
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Ober-Reynolds B, Becker WR, Jouravleva K, Jolly SM, Zamore PD, Greenleaf WJ. High-throughput biochemical profiling reveals functional adaptation of a bacterial Argonaute. Mol Cell 2022; 82:1329-1342.e8. [PMID: 35298909 PMCID: PMC9158488 DOI: 10.1016/j.molcel.2022.02.026] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 01/10/2022] [Accepted: 02/16/2022] [Indexed: 12/29/2022]
Abstract
Argonautes are nucleic acid-guided proteins that perform numerous cellular functions across all domains of life. Little is known about how distinct evolutionary pressures have shaped each Argonaute's biophysical properties. We applied high-throughput biochemistry to characterize how Thermus thermophilus Argonaute (TtAgo), a DNA-guided DNA endonuclease, finds, binds, and cleaves its targets. We found that TtAgo uses biophysical adaptations similar to those of eukaryotic Argonautes for rapid association but requires more extensive complementarity to achieve high-affinity target binding. Using these data, we constructed models for TtAgo association rates and equilibrium binding affinities that estimate the nucleic acid- and protein-mediated components of the target interaction energies. Finally, we showed that TtAgo cleavage rates vary widely based on the DNA guide, suggesting that only a subset of guides cleaves targets on physiologically relevant timescales.
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Affiliation(s)
| | - Winston R Becker
- Program in Biophysics, Stanford University, Stanford, CA 94305, USA
| | - Karina Jouravleva
- Howard Hughes Medical Institute and RNA Therapeutics Institute, University of Massachusetts Chan Medical School, 368 Plantation Street, Worcester, MA 01605, USA
| | - Samson M Jolly
- Howard Hughes Medical Institute and RNA Therapeutics Institute, University of Massachusetts Chan Medical School, 368 Plantation Street, Worcester, MA 01605, USA
| | - Phillip D Zamore
- Howard Hughes Medical Institute and RNA Therapeutics Institute, University of Massachusetts Chan Medical School, 368 Plantation Street, Worcester, MA 01605, USA.
| | - William J Greenleaf
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Applied Physics, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA.
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11
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Ordabayev YA, Friedman LJ, Gelles J, Theobald DL. Bayesian machine learning analysis of single-molecule fluorescence colocalization images. eLife 2022; 11:73860. [PMID: 35319463 PMCID: PMC9183235 DOI: 10.7554/elife.73860] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 03/19/2022] [Indexed: 01/07/2023] Open
Abstract
Multi-wavelength single-molecule fluorescence colocalization (CoSMoS) methods allow elucidation of complex biochemical reaction mechanisms. However, analysis of CoSMoS data is intrinsically challenging because of low image signal-to-noise ratios, non-specific surface binding of the fluorescent molecules, and analysis methods that require subjective inputs to achieve accurate results. Here, we use Bayesian probabilistic programming to implement Tapqir, an unsupervised machine learning method that incorporates a holistic, physics-based causal model of CoSMoS data. This method accounts for uncertainties in image analysis due to photon and camera noise, optical non-uniformities, non-specific binding, and spot detection. Rather than merely producing a binary 'spot/no spot' classification of unspecified reliability, Tapqir objectively assigns spot classification probabilities that allow accurate downstream analysis of molecular dynamics, thermodynamics, and kinetics. We both quantitatively validate Tapqir performance against simulated CoSMoS image data with known properties and also demonstrate that it implements fully objective, automated analysis of experiment-derived data sets with a wide range of signal, noise, and non-specific binding characteristics.
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Affiliation(s)
| | - Larry J Friedman
- Department of Biochemistry, Brandeis UniversityWalthamUnited States
| | - Jeff Gelles
- Department of Biochemistry, Brandeis UniversityWalthamUnited States
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12
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Cnossen J, Cui TJ, Joo C, Smith C. Drift correction in localization microscopy using entropy minimization. OPTICS EXPRESS 2021; 29:27961-27974. [PMID: 34614938 DOI: 10.1364/oe.426620] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 07/05/2021] [Indexed: 06/13/2023]
Abstract
Localization microscopy offers resolutions down to a single nanometer but currently requires additional dedicated hardware or fiducial markers to reduce resolution loss from the drift of the sample. Drift estimation without fiducial markers is typically implemented using redundant cross correlation (RCC). We show that RCC has sub-optimal precision and bias, which leaves room for improvement. Here, we minimize a bound on the entropy of the obtained localizations to efficiently compute a precise drift estimate. Within practical compute-time constraints, simulations show a 5x improvement in drift estimation precision over the widely used RCC algorithm. The algorithm operates directly on fluorophore localizations and is tested on simulated and experimental datasets in 2D and 3D. An open source implementation is provided, implemented in Python and C++, and can utilize a GPU if available.
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13
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Tibbs J, Ghoneim M, Caldwell CC, Buzynski T, Bowie W, Boehm EM, Washington MT, Tabei SMA, Spies M. KERA: analysis tool for multi-process, multi-state single-molecule data. Nucleic Acids Res 2021; 49:e53. [PMID: 33660771 PMCID: PMC8136784 DOI: 10.1093/nar/gkab087] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 01/17/2021] [Accepted: 02/24/2021] [Indexed: 12/16/2022] Open
Abstract
Molecular machines within cells dynamically assemble, disassemble and reorganize. Molecular interactions between their components can be observed at the single-molecule level and quantified using colocalization single-molecule spectroscopy, in which individual labeled molecules are seen transiently associating with a surface-tethered partner, or other total internal reflection fluorescence microscopy approaches in which the interactions elicit changes in fluorescence in the labeled surface-tethered partner. When multiple interacting partners can form ternary, quaternary and higher order complexes, the types of spatial and temporal organization of these complexes can be deduced from the order of appearance and reorganization of the components. Time evolution of complex architectures can be followed by changes in the fluorescence behavior in multiple channels. Here, we describe the kinetic event resolving algorithm (KERA), a software tool for organizing and sorting the discretized fluorescent trajectories from a range of single-molecule experiments. KERA organizes the data in groups by transition patterns, and displays exhaustive dwell time data for each interaction sequence. Enumerating and quantifying sequences of molecular interactions provides important information regarding the underlying mechanism of the assembly, dynamics and architecture of the macromolecular complexes. We demonstrate KERA's utility by analyzing conformational dynamics of two DNA binding proteins: replication protein A and xeroderma pigmentosum complementation group D helicase.
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Affiliation(s)
- Joseph Tibbs
- Department of Physics, University of Northern Iowa, Cedar Falls, IA 50614, USA
| | - Mohamed Ghoneim
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Colleen C Caldwell
- Department of Biochemistry, University of Iowa, Iowa City, IA 52242, USA
| | - Troy Buzynski
- Department of Physics, University of Northern Iowa, Cedar Falls, IA 50614, USA
| | - Wayne Bowie
- Department of Physics, University of Northern Iowa, Cedar Falls, IA 50614, USA
| | - Elizabeth M Boehm
- Department of Biochemistry, University of Iowa, Iowa City, IA 52242, USA
| | - M Todd Washington
- Department of Biochemistry, University of Iowa, Iowa City, IA 52242, USA
| | - S M Ali Tabei
- Department of Physics, University of Northern Iowa, Cedar Falls, IA 50614, USA
| | - Maria Spies
- Department of Biochemistry, University of Iowa, Iowa City, IA 52242, USA
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14
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Kinz-Thompson CD, Ray KK, Gonzalez RL. Bayesian Inference: The Comprehensive Approach to Analyzing Single-Molecule Experiments. Annu Rev Biophys 2021; 50:191-208. [PMID: 33534607 DOI: 10.1146/annurev-biophys-082120-103921] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Biophysics experiments performed at single-molecule resolution provide exceptional insight into the structural details and dynamic behavior of biological systems. However, extracting this information from the corresponding experimental data unequivocally requires applying a biophysical model. In this review, we discuss how to use probability theory to apply these models to single-molecule data. Many current single-molecule data analysis methods apply parts of probability theory, sometimes unknowingly, and thus miss out on the full set of benefits provided by this self-consistent framework. The full application of probability theory involves a process called Bayesian inference that fully accounts for the uncertainties inherent to single-molecule experiments. Additionally, using Bayesian inference provides a scientifically rigorous method of incorporating information from multiple experiments into a single analysis and finding the best biophysical model for an experiment without the risk of overfitting the data. These benefits make the Bayesian approach ideal for analyzing any type of single-molecule experiment.
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Affiliation(s)
- Colin D Kinz-Thompson
- Department of Chemistry, Columbia University, New York, New York 10027, USA; .,Department of Chemistry, Rutgers University-Newark, Newark, New Jersey 07102, USA
| | - Korak Kumar Ray
- Department of Chemistry, Columbia University, New York, New York 10027, USA;
| | - Ruben L Gonzalez
- Department of Chemistry, Columbia University, New York, New York 10027, USA;
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15
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Jolly SM, Gainetdinov I, Jouravleva K, Zhang H, Strittmatter L, Bailey SM, Hendricks GM, Dhabaria A, Ueberheide B, Zamore PD. Thermus thermophilus Argonaute Functions in the Completion of DNA Replication. Cell 2020; 182:1545-1559.e18. [PMID: 32846159 PMCID: PMC7502556 DOI: 10.1016/j.cell.2020.07.036] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 06/25/2020] [Accepted: 07/24/2020] [Indexed: 01/06/2023]
Abstract
In many eukaryotes, Argonaute proteins, guided by short RNA sequences, defend cells against transposons and viruses. In the eubacterium Thermus thermophilus, the DNA-guided Argonaute TtAgo defends against transformation by DNA plasmids. Here, we report that TtAgo also participates in DNA replication. In vivo, TtAgo binds 15- to 18-nt DNA guides derived from the chromosomal region where replication terminates and associates with proteins known to act in DNA replication. When gyrase, the sole T. thermophilus type II topoisomerase, is inhibited, TtAgo allows the bacterium to finish replicating its circular genome. In contrast, loss of gyrase and TtAgo activity slows growth and produces long sausage-like filaments in which the individual bacteria are linked by DNA. Finally, wild-type T. thermophilus outcompetes an otherwise isogenic strain lacking TtAgo. We propose that the primary role of TtAgo is to help T. thermophilus disentangle the catenated circular chromosomes generated by DNA replication.
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Affiliation(s)
- Samson M Jolly
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605, USA; Howard Hughes Medical Institute and RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Ildar Gainetdinov
- Howard Hughes Medical Institute and RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Karina Jouravleva
- Howard Hughes Medical Institute and RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Han Zhang
- Howard Hughes Medical Institute and RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Lara Strittmatter
- Department of Radiology, Division of Cell Biology and Imaging, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Shannon M Bailey
- Howard Hughes Medical Institute and RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Gregory M Hendricks
- Department of Radiology, Division of Cell Biology and Imaging, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Avantika Dhabaria
- Proteomics Laboratory, Division of Advanced Research Technologies, New York University School of Medicine, New York, NY 10016, USA
| | - Beatrix Ueberheide
- Proteomics Laboratory, Division of Advanced Research Technologies, New York University School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY 10016, USA; Center for Cognitive Neurology, Department of Neurology, New York University School of Medicine, New York, NY 10016, USA
| | - Phillip D Zamore
- Howard Hughes Medical Institute and RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605, USA.
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16
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White DS, Goldschen-Ohm MP, Goldsmith RH, Chanda B. Top-down machine learning approach for high-throughput single-molecule analysis. eLife 2020; 9:e53357. [PMID: 32267232 PMCID: PMC7205464 DOI: 10.7554/elife.53357] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 04/08/2020] [Indexed: 12/16/2022] Open
Abstract
Single-molecule approaches provide enormous insight into the dynamics of biomolecules, but adequately sampling distributions of states and events often requires extensive sampling. Although emerging experimental techniques can generate such large datasets, existing analysis tools are not suitable to process the large volume of data obtained in high-throughput paradigms. Here, we present a new analysis platform (DISC) that accelerates unsupervised analysis of single-molecule trajectories. By merging model-free statistical learning with the Viterbi algorithm, DISC idealizes single-molecule trajectories up to three orders of magnitude faster with improved accuracy compared to other commonly used algorithms. Further, we demonstrate the utility of DISC algorithm to probe cooperativity between multiple binding events in the cyclic nucleotide binding domains of HCN pacemaker channel. Given the flexible and efficient nature of DISC, we anticipate it will be a powerful tool for unsupervised processing of high-throughput data across a range of single-molecule experiments.
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Affiliation(s)
- David S White
- Department of Neuroscience, University of Wisconsin-MadisonMadisonUnited States
- Department of Chemistry, University of Wisconsin-MadisonMadisonUnited States
| | | | - Randall H Goldsmith
- Department of Chemistry, University of Wisconsin-MadisonMadisonUnited States
| | - Baron Chanda
- Department of Neuroscience, University of Wisconsin-MadisonMadisonUnited States
- Department of Biomolecular Chemistry University of Wisconsin-MadisonMadisonUnited States
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17
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Cui TJ, Klein M, Hegge JW, Chandradoss SD, van der Oost J, Depken M, Joo C. Argonaute bypasses cellular obstacles without hindrance during target search. Nat Commun 2019; 10:4390. [PMID: 31558728 PMCID: PMC6763497 DOI: 10.1038/s41467-019-12415-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Accepted: 09/09/2019] [Indexed: 12/13/2022] Open
Abstract
Argonaute (Ago) proteins are key players in both gene regulation (eukaryotes) and host defense (prokaryotes). Acting on single-stranded nucleic-acid substrates, Ago relies on base pairing between a small nucleic-acid guide and its complementary target sequences for specificity. To efficiently scan nucleic-acid chains for targets, Ago diffuses laterally along the substrate and must bypass secondary structures as well as protein barriers. Using single-molecule FRET in conjunction with kinetic modelling, we reveal that target scanning is mediated through loose protein-nucleic acid interactions, allowing Ago to slide short distances over secondary structures, as well as to bypass protein barriers via intersegmental transfer. Our combined single-molecule experiment and kinetic modelling approach may serve as a platform to dissect search processes and study the effect of sequence on search kinetics for other nucleic acid-guided proteins.
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Affiliation(s)
- Tao Ju Cui
- Kavli Institute of Nanoscience and Department of Bionanoscience, Delft University of Technology, Delft, The Netherlands
| | - Misha Klein
- Kavli Institute of Nanoscience and Department of Bionanoscience, Delft University of Technology, Delft, The Netherlands
| | - Jorrit W Hegge
- Laboratory of Microbiology, Department of Agrotechnology and Food Sciences, Wageningen University, Wageningen, The Netherlands
| | - Stanley D Chandradoss
- Kavli Institute of Nanoscience and Department of Bionanoscience, Delft University of Technology, Delft, The Netherlands.,Oxford NanoImaging, Oxford, UK
| | - John van der Oost
- Laboratory of Microbiology, Department of Agrotechnology and Food Sciences, Wageningen University, Wageningen, The Netherlands
| | - Martin Depken
- Kavli Institute of Nanoscience and Department of Bionanoscience, Delft University of Technology, Delft, The Netherlands.
| | - Chirlmin Joo
- Kavli Institute of Nanoscience and Department of Bionanoscience, Delft University of Technology, Delft, The Netherlands.
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18
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de Oliveira LR, Jaqaman K. FISIK: Framework for the Inference of In Situ Interaction Kinetics from Single-Molecule Imaging Data. Biophys J 2019; 117:1012-1028. [PMID: 31443908 DOI: 10.1016/j.bpj.2019.07.050] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Revised: 06/27/2019] [Accepted: 07/22/2019] [Indexed: 12/12/2022] Open
Abstract
Recent experimental and computational developments have been pushing the limits of live-cell single-molecule imaging, enabling the monitoring of intermolecular interactions in their native environment with high spatiotemporal resolution. However, interactions are captured only for the labeled subset of molecules, which tends to be a small fraction. As a result, it has remained a challenge to calculate molecular interaction kinetics, in particular association rates, from live-cell single-molecule tracking data. To overcome this challenge, we developed a mathematical modeling-based Framework for the Inference of in Situ Interaction Kinetics (FISIK) from single-molecule imaging data with substoichiometric labeling. FISIK consists of (I) devising a mathematical model of molecular movement and interactions, mimicking the biological system and data-acquisition setup, and (II) estimating the unknown model parameters, including molecular association and dissociation rates, by fitting the model to experimental single-molecule data. Due to the stochastic nature of the model and data, we adapted the method of indirect inference for model calibration. We validated FISIK using a series of tests in which we simulated trajectories of diffusing molecules that interact with each other, considering a wide range of model parameters, and including resolution limitations, tracking errors, and mismatches between the model and the biological system it mimics. We found that FISIK has the sensitivity to determine association and dissociation rates, with accuracy and precision depending on the labeled fraction of molecules and the extent of molecule tracking errors. For cases where the labeled fraction is too low (e.g., to afford accurate tracking), combining dynamic but sparse single-molecule imaging data with almost-whole population oligomer distribution data improves FISIK's performance. All in all, FISIK is a promising approach for the derivation of molecular interaction kinetics in their native environment from single-molecule imaging data with substoichiometric labeling.
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Affiliation(s)
| | - Khuloud Jaqaman
- Department of Biophysics, UT Southwestern Medical Center, Dallas, Texas; Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, Texas.
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