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19 results for “single molecule fluorescence”
Super-Resolved FRET Imaging by Confocal Fluorescence-Lifetime Single-Molecule Localization Microscopy
<p>FRET-based methods are a special tool for detecting interactions between (bio)molecules and their immediate environment. The spatial distribution of molecular interactions and functional states can be seen using FLIM (Fluorescence Lifetime IMaging) and FRET imaging. The spatial information, accuracy, and dynamic range of the observed signals are, however, constrained by the fact that conventional FLIM and FRET imaging only provides average information over an ensemble of molecules within a diffraction-limited volume. On the other hand, conventional Single Molecule Localization Microscopy (SMLM) relies on highly sensitive multi-pixel detectors (e.g. sCMOS or EM-CCD) whose time resolution is not suitable for fluorescence lifetime measurements.</p> <p>Here, we demonstrate a method for obtaining super-resolved FRET imaging using confocal fluorescence-lifetime single-molecule localization microscopy. The proof of concept was carried out using a DNA origami sample for performing DNA-PAINT measurements in combination with fluorogenic probes for reducing background signal. With this method, We show that FRET events separated by sub-diffraction distances can be distinguished based on lifetime modifications.</p>
SupportingDataset Identification and Quantification of Within-Burst Dynamics in Singly-Labeled Single-Molecule Fluorescence Lifetime Experiments
<p>The Jupyter notebooks and resulting files used to demonstrate divisor-based mpH<sup>2</sup>MM. The analysis is demonstrated with both simulations and analyses of alpha-synuclein.</p> <ol> <li> <p><em><strong>Notebooks.zip</strong></em>:* Zip file containing the Jupyter notebooks for producing, analyzing and visualizing the simulated photon trajectories. Note: this folder contains all code needed to reproduce simulations. All other files related to the simulations are produced by one of the notebooks in this trajectory. However, as simulations can take a long time, the various results files are included in this repository so that notebooks can be run from intermediate steps.</p> <ol> <li> <p><strong>1-PIFE-pybromo-sims.ipynb</strong> : The code for producing simulated diffusion trajectories and photon-HDF5 files of two-state systems undergoing transition dynamics (the results of this notebook are stored in the sub-folder <em>PyBroMo_photonHDF5</em>)</p> </li> <li> <p><strong>2-PIFE-mpH2MM-sim-[lifetime components].ipynb </strong>: Notebooks performing divisor-based mpH<sup>2</sup>MM on simulated datasets for a given combination of lifetime states. (these notebooks store files that are contained in the sub-folder <em>H2MMresults</em>)</p> </li> <li> <p><strong>3-PIFE-mpH2MM-compiled-plots.ipynb</strong> : Jupyter notebook for producing figures comparing all results globally</p> </li> <li> <p><strong>532nm_IRF_19-10-2021.csb</strong>: the file containing the experimental IRF used in the simulations</p> </li> </ol> </li> <li> <p><em><strong>PyBroMo_photonHDF5.zip</strong></em>:* Zip file containing the simulated results of <em>1-PIFE-pybromo-sims</em> notebook as photon-HDF5 files (1 file per transition rate/lifetime combination)</p> </li> <li> <p><strong>PIFE-sim-dynamicmix_[lifetime components]_result.hdf5</strong>: special HDF5 files containing the results of each notebook in <em>Notebooks</em>, which are used by <em>3-PIFE-mpH2MM-compiled-plots</em></p> </li> <li> <p><strong>PIFE-mpH2MM-alpha-syn-vFinal.ipynb</strong>: divisor-based mpH<sup>2</sup>MM analysis of alpha-synuclein smPIFE data</p> </li> <li> <p><strong>H2MM-Lifetime_example.ipynb</strong>: A demonstration of divisor-based mpH<sup>2</sup>MM using nsALEX-smFRET data. This method could potentially demonstrate states differentiated in lifetimes independently of potential changes in E & S.</p> </li> <li> <p><strong>Template_ltH2MM.ipynb</strong>: An easy-to-follow implementation of divisor-based mpH<sup>2</sup>MM demonstrated on a single alpha-synuclein experimental data acquisition file. This can be used for learning how to implement and analyze single dye fluorescence lifetime data with mpH<sup>2</sup>MM</p> </li> </ol> <p> </p> <p>* For running these notebooks, generally, all files in <em>PyBroMo_photonHDF5.zip</em> should be placed into a single directory (i.e., the files in <em>Notebooks</em>.<em>zip</em> should be placed into the same directory as the files in <em>PyBroMo_photonHDF5</em>.<em>zip</em>) as the notebooks are set to read in files from their current directory.</p>
Benchmarking Smartphone Fluorescence-Based Microscopy with DNA Origami Nanobeads: Reducing the Gap toward Single-Molecule Sensitivity
<p>Smartphone-based fluorescence microscopy has been rapidly developing over the last few years, enabling point-of-need detection of cells, bacteria, viruses, and biomarkers. These mobile microscopy devices are cost-effective, field-portable, and easy to use, and benefit from economies of scale. Recent developments in smartphone camera technology have improved their performance, getting closer to that of lab microscopes. Here, we report the use of DNA origami nanobeads with predefined numbers of fluorophores to quantify the sensitivity of a smartphone-based fluorescence microscope in terms of the minimum number of detectable molecules per diffraction-limited spot. With the brightness of a single dye molecule as a reference, we compare the performance of color and monochrome sensors embedded in state-of-the-art smartphones. Our results show that the monochrome sensor of a smartphone can achieve better sensitivity, with a detection limit of ∼10 fluorophores per spot. The use of DNA origami nanobeads to quantify the minimum number of detectable molecules of a sensor is broadly applicable to evaluate the sensitivity of various optical instruments.</p>
Systematic assessment of burst impurity in confocal-based single-molecule fluorescence detection using Brownian motion simulations - photon timetag simulation files
<p>Attached are the photon timestamp and channels simulated for different 3D diffusing molecules simulations at different conditions (simulation was performed by PyBroMo).</p> <p>Each of the files has, in its name, a code. The meaning of the codes are as following:</p> <pre>f32445 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a numerical PSF model </pre> <pre>a01f8f - 15 molecules at a concentration of 31 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a numerical PSF model</pre> <pre>9ff667 - 15 molecules at a concentration of 15.5 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a numerical PSF model</pre> <pre>71154a - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 22.5 micron^2/s - 60 second simulation using a numerical PSF model</pre> <pre>ad926d - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 5.625 micron^2/s - 60 second simulation using a numerical PSF model</pre> <pre>1ab235 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s - 180 second simulation using a numerical PSF model</pre> <pre>d00978 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 5.625 micron^2/s - 180 second simulation using a numerical PSF model</pre> <p> </p> <pre>2469bb - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a Gaussian PSF model </pre> <pre>4be121 - 15 molecules at a concentration of 31 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a Gaussian PSF model</pre> <pre>a7088f - 15 molecules at a concentration of 15.5 pM, with a diffusion coefficient of 90 micron^2/s - 60 second simulation using a Gaussian PSF model</pre> <pre>023983 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 22.5 micron^2/s - 60 second simulation using a Gaussian PSF model</pre> <pre>653f61 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 5.625 micron^2/s - 60 second simulation using a Gaussian PSF model</pre> <pre>4f06ee - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s - 180 second simulation using a Gaussian PSF model</pre> <pre>dec32c - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 5.625 micron^2/s - 180 second simulation using a Gaussian PSF model</pre> <p> </p> <pre>85b0a1 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s , 10 of which belong to a sub-population with a mean FRET efficiency of 0.75, and the leftover 5 belong to another sub-populations with a mean FRET efficiency of 0.50 - 60 second simulation using a Numerical PSF model</pre> <pre>964ef3 - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s , 10 of which belong to a sub-population with a mean FRET efficiency of 0.75, and the leftover 5 belong to another sub-populations with a mean FRET efficiency of 0.50 - 180 second simulation using a Numerical PSF model</pre> <p> </p> <pre>f28f6e - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s , 10 of which belong to a sub-population with a mean FRET efficiency of 0.75, and the leftover 5 belong to another sub-populations with a mean FRET efficiency of 0.50 - 60 second simulation using a Gaussian PSF model</pre> <pre>c311dd - 15 molecules at a concentration of 62 pM, with a diffusion coefficient of 90 micron^2/s , 10 of which belong to a sub-population with a mean FRET efficiency of 0.75, and the leftover 5 belong to another sub-populations with a mean FRET efficiency of 0.50 - 180 second simulation using a Gaussian PSF model</pre>
Datasets and scripts for: Single-Molecule Dynamic Structural Biology with Vertically Arranged DNA on a Fluorescence Microscope
<p>The folder contains raw datasets (.ptu files) together with scripts and relevant results to reproduce the figures' plots of: "Single-Molecule Dynamic Structural Biology with Vertically Arranged DNA on a Fluorescence Microscope". </p>
Single-molecule Fluorescent In Situ Hybridization (smFISH) for RNA detection in the fungal pathogen Candida albicans dataset
<p><strong>This dataset is connected to the protocol article titled:</strong></p> <p>Single-molecule Fluorescent <em>In Situ</em> Hybridization (smFISH) for RNA detection in the fungal pathogen <em>Candida albicans</em></p> <p><strong>Abstract:</strong></p> <p><em>Candida albicans</em> is the most prevalent human fungal pathogen. Its pathogenicity is linked to the ability of <em>C. albicans</em> to reversibly change morphology and to grow as yeast, pseudohyphal or hyphal cells in response to environmental stimuli. Understanding the molecular regulation controlling those morphological switches remains a challenge that, if solved, could help fight <em>C. albicans</em> infections.</p> <p>While numerous studies investigated gene expression changes occurring during <em>C. albicans</em> morphological switches using bulk approaches (e.g., RNA sequencing), here we describe a single-cell and single-molecule RNA imaging and analysis protocol to measure absolute mRNA counts in morphologically intact cells. To detect endogenous mRNAs in single fixed cells, we optimized a single molecule fluorescent <em>in situ</em> hybridization (smFISH) protocol for <em>C. albicans</em>, which allows one to quantify the differential expression of mRNAs in yeast, pseudohyphae or hyphal cells. We quantified the expression of two mRNAs, cell cycle-controlled mRNA (<em>CLB2)</em> and a transcription regulator (<em>EFG1</em>), which show differential expression in the different morphological cell types and in different nutrient conditions. In this protocol we described in detail the major steps of this approach: growth and fixation, hybridization, imaging, cell-segmentation and mRNA spot analysis. Raw data is provided with the protocol to favour reproducibility. This approach could benefit the molecular characterization of <em>C. albicans</em> and other filamentous fungi, pathogenic or non-pathogenic.</p> <p><strong>Data description:</strong></p> <p>This dataset consists of a FISH experiment spanning two different mRNAs, EFG1 and CLB2, and two different nutrient condition, being SPIDER37 and TSB37 in Candida albicans. For culturing, the C. albicans wildtype strain SC5314 was inoculated at 30 degrees overnight (~15 hours) in 10 mL of TSB medium in a 30 degree (celsius) shaking incubator. Next, samples were diluted to a density of 10^5 cells/ mL and inoculated for 6 hours in either 30 mL TSB medium or Spider medium at 37 degrees in falcon tubes on an orbital microplate shaker. Then, samples were fixated by adding PFA to a final concentration of 4% to the medium. For hybridization, both mRNAs were hybridized independently by specific DNA oligo labelled with a Quasar670 dye to enable the visualisation of single mRNA molecules. As both genes are labelled by the same dye, these oligos were not co-applied to the same sample but to independent samples.</p> <p><strong>Microscopy</strong></p> <p>For smFISH imaging we use an Olympus BX-63 epifluorescence microscope equipped with Ultrasonic stage and UPlanApo 100x 1.35NA oil-immersion objective (Olympus). Lumencore SOLA FISH light source, a Hamamatsu ORCA-Fusion sCMOS camera (6.5 µm-pixel size) mounted using U-CMT C-Mount Adapter, and zero-pixel shift filter sets: F36-500 DAPI HC Brightline Bandpass Filter, F36-502 FITC HC BrightLine Filter, F36-542 Cy3 HC BrightLine Filter, and F36-523 Cy5 HC BrightLine Filter. Images are acquired across 61-81 optical sections (depending on the sample thickness) with a z-step size of 0.2 μm. The CellSens software (Olympus) is used for instrument control and image acquisition. For the DAPI channel 10-50 ms of exposure was used. Whilst, for the CY5 channel, used imaging the FISH probes, 750 ms was applied. </p> <p> </p>
Single-molecule Fluorescent In Situ Hybridization (smFISH) for RNA detection in the fungal pathogen Candida albicans small example dataset
<p><strong>This small example dataset is connected to the protocol article titled:</strong></p> <p>Single-molecule Fluorescent <em>In Situ</em> Hybridization (smFISH) for RNA detection in the fungal pathogen <em>Candida albicans</em></p> <p><strong>Abstract:</strong></p> <p><em>Candida albicans</em> is the most prevalent human fungal pathogen. Its pathogenicity is linked to the ability of <em>C. albicans</em> to reversibly change morphology and to grow as yeast, pseudohyphal or hyphal cells in response to environmental stimuli. Understanding the molecular regulation controlling those morphological switches remains a challenge that, if solved, could help fight <em>C. albicans</em> infections.</p> <p>While numerous studies investigated gene expression changes occurring during <em>C. albicans</em> morphological switches using bulk approaches (e.g., RNA sequencing), here we describe a single-cell and single-molecule RNA imaging and analysis protocol to measure absolute mRNA counts in morphologically intact cells. To detect endogenous mRNAs in single fixed cells, we optimized a single molecule fluorescent <em>in situ</em> hybridization (smFISH) protocol for <em>C. albicans</em>, which allows one to quantify the differential expression of mRNAs in yeast, pseudohyphae or hyphal cells. We quantified the expression of two mRNAs, cell cycle-controlled mRNA (<em>CLB2)</em> and a transcription regulator (<em>EFG1</em>), which show differential expression in the different morphological cell types and in different nutrient conditions. In this protocol, we described in detail the major steps of this approach: growth and fixation, hybridization, imaging, cell-segmentation and mRNA spot analysis. Raw data is provided with the protocol to favour reproducibility. This approach could benefit the molecular characterization of <em>C. albicans</em> and other filamentous fungi, pathogenic or non-pathogenic.</p> <p><strong>Data description:</strong></p> <p>This dataset consists of a FISH experiment spanning two different mRNAs, EFG1 and CLB2, and one nutrient condition, SPIDER37, in Candida albicans. For culturing, the C. albicans wildtype strain SC5314 was inoculated at 30 degrees overnight (~15 hours) in 10 mL of TSB medium in a 30 °C shaking incubator. Next, samples were diluted to a density of 10^5 cells/ mL and inoculated for 6 hours in 30 mL Spider medium at 37 °C in falcon tubes on an orbital microplate shaker. Then, samples were fixated by adding PFA to a final concentration of 4% to the medium. For hybridization, both mRNAs were hybridized independently by specific DNA oligo labelled with a Quasar670 dye to enable the visualisation of single mRNA molecules. As both genes are labelled by the same dye, these oligos were not co-applied to the same sample but to independent samples.</p> <p><strong>Microscopy</strong></p> <p>For smFISH imaging we use an Olympus BX-63 epifluorescence microscope equipped with Ultrasonic stage and UPlanApo 100x 1.35NA oil-immersion objective (Olympus). Lumencore SOLA FISH light source, a Hamamatsu ORCA-Fusion sCMOS camera (6.5 µm-pixel size) mounted using U-CMT C-Mount Adapter, and zero-pixel shift filter sets: F36-500 DAPI HC Brightline Bandpass Filter, F36-502 FITC HC BrightLine Filter, F36-542 Cy3 HC BrightLine Filter, and F36-523 Cy5 HC BrightLine Filter. Images are acquired across 61-81 optical sections (depending on the sample thickness) with a z-step size of 0.2 μm. The CellSens software (Olympus) is used for instrument control and image acquisition. For the DAPI channel 10-50 ms of exposure was used. Whilst, for the CY5 channel, used for imaging the FISH probes, 750 ms was applied. </p>
Bayesian machine learning analysis of single-molecule fluorescence colocalization images
<p>Data files for the "Bayesian machine learning analysis of single-molecule fluorescence colocalization images" manuscript.</p>
Reference genes for quantitative Arabidopsis single molecule RNA fluorescence in situ hybridization
Abstract Subcellular mRNA quantities and spatial distributions are fundamental for driving gene regulatory programmes. Single molecule RNA fluorescence in situ hybridization (smFISH) uses fluorescent probes to label individual mRNA molecules, thereby facilitating both localization and quantitative studies. Validated reference mRNAs function as positive controls and are required for calibration. Here we present selection criteria for the first set of Arabidopsis smFISH reference genes. Following sequence and transcript data assessments, four mRNA probe sets were selected for imaging. Transcript counts per cell, correlations with cell size, and corrected fluorescence intensities were all calculated for comparison. In addition to validating reference probe sets, we present sample preparation steps that can retain green fluorescent protein fluorescence, thereby providing a method for simultaneous RNA and protein detection. In summary, our reference gene analyses, modified protocol, and simplified quantification method together provide a firm foundation for future quantitative single molecule RNA studies in Arabidopsis root apical meristem cells.
Single-molecule and bulk fluorescence and biolayer interferometry on the NAD-II riboswitch and its interactions with NMN
Open the record for dataset details and reuse information.
Reference genes for quantitative Arabidopsis single molecule RNA fluorescence in situ hybridization
Open the record for dataset details and reuse information.
Data from "Single-molecule fluorescence multiplexing by multi-parameter spectroscopic detection of nanostructured FRET labels"
<p>Source data for all figures; full table of all nucleic acid sequences used; Supplementary Video 1 showing rotating view of Fig. 4e.</p>
Dataset supporting the book chapter entitled "Ratiometric Fluorescent Safranin-O staining allows the quantification of lignin contents in muro" and published in "Histochemistry of Single Molecules"
<p>This dataset aims to test the algorithms presented in the book chapter entitled</p> <p><strong>“Ratiometric Fluorescent Safranin-O staining allows the quantification of lignin contents <em>in muro</em>” </strong></p> <p>and published in “Histochemistry of Single Molecules”</p> <p><strong>Are available:</strong></p> <p>-The algorithm, provided has an ImageJ macro ("safranine_ratio_segmentation")</p> <p>- A representative image for testing (“safranine wt-60x.nd2”)</p>
Systematic assessment of burst impurity in confocal-based single-molecule fluorescence detection using Brownian motion simulations - raw figures of all quantities from all simulations
<p>We performed many simulations in many conditions, calculated many quantities and reported them in the main paper. However, the journal manuscript did not place for so many figures. Nevertheless, the reported values of all simulations rely on the results that were also summarized in the figures. These figures were produced by the Jupyter notebooks analyzing the simulation results.</p> <p>Each figure file has the following nomenclature:</p> <p>TypeOfFigure_concentration_diffusionCoefficient_1or2pop_simulationDuration(long)_Type of PSF.</p> <p>For example:</p> <p><em>molecule_positions_pure_and_impure_bursts_varying_F_C62_D22_5_psfNumeric</em> - report on the molecular position histograms of pure and impure bursts for varying F values, in the simulation with C=62pM, D=22.5 um^2/s, a NUmerical PSF model and 60s duration of simulation (if nothing appears, it was 60s; if the word <em>long</em> appears, it was 180s).</p>
Experimental data supporting the paper "Fluorescence from a single-molecule probe directly attached to a plasmonic STM tip"
<p>Experimental STM, STS and STML data studying the fluorescent behaviour of a PTCDA molecule attached to the metallic apex of a scanning tunneling microscope.</p> <p> </p> <p>Treated source data of all Figures included in the publication.</p>
Data from: Nanoaperture fabrication via colloidal lithography for single molecule fluorescence analysis
<p>In single molecule fluorescence studies, background emission from labeled substrates often restricts their concentrations to non-physiological nanomolar values. One approach to address this challenge is the use of zero-mode waveguides (ZMWs), nanoscale holes in a thin metal film that physically and optically confine the observation volume allowing much higher concentrations of fluorescent substrates. Standard fabrication of ZMWs utilizes slow and costly E-beam nano-lithography. Herein, ZMWs are made using a self-assembled mask of polystyrene microspheres, enabling fabrication of thousands of ZMWs in parallel without sophisticated equipment. Polystyrene 1 μm dia. microbeads self-assemble on a glass slide into a hexagonal array, forming a mask for the deposition of metallic posts in the inter-bead interstices. The width of those interstices (and subsequent posts) is adjusted within 100–300 nm by partially fusing the beads at the polystyrene glass transition temperature. The beads are dissolved in toluene, aluminum or gold cladding is deposited around the posts, and those are dissolved, leaving behind an array ZMWs. Parameter optimization and the performance of the ZMWs are presented. By using colloidal self-assembly, typical laboratories can make use of sub-wavelength ZMW technology avoiding the availability and expense of sophisticated clean-room environments and equipment.</p>
Probing DNA - transcription factor interactions using single-molecule fluorescence detection in nanofluidic devices
<p>Readme.txt, 16.07.2021<br> Fontana et al.<br> “Probing DNA - transcription factor interactions using single-molecule fluorescence detection in nanofluidic devices”</p> <p>pre-print: https://doi.org/10.1101/2021.05.12.443786 (BioRxiv)</p> <p>The repository contains the raw data ("*.tif") files, data from subsequent analysis steps performed in Matlab ("*.mat") and obtained histograms.</p> <p>For further information, please contact<br> dr. Johannes Hohlbein @ Wageningen University & Research<br> (johannes.hohlbein@wur.nl)</p>
Data from: Nanoaperture fabrication via colloidal lithography for single molecule fluorescence analysis
Open the record for dataset details and reuse information.
A framework to validate fluorescently labeled DNA-binding proteins for single-molecule experiments
GEO Series GSE212751. Bacillus subtilis PY79. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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