scholarly journals Efficient Cross-Correlation Filtering of One- and Two-Color Single Molecule Localization Microscopy Data

2021 ◽  
Vol 1 ◽  
Author(s):  
Angel Mancebo ◽  
Dushyant Mehra ◽  
Chiranjib Banerjee ◽  
Do-Hyung Kim ◽  
Elias M. Puchner
Keyword(s):  
Single Molecule ◽  
Cross Correlation ◽  
Pair Correlation ◽  
Diffraction Limit ◽  
Optical Diffraction ◽  
Data Sets ◽  
Oligomeric State ◽  
Localization Microscopy ◽  
Cross Correlation Analysis ◽  
Single Molecule Localization Microscopy

Single molecule localization microscopy has become a prominent technique to quantitatively study biological processes below the optical diffraction limit. By fitting the intensity profile of single sparsely activated fluorophores, which are often attached to a specific biomolecule within a cell, the locations of all imaged fluorophores are obtained with ∼20 nm resolution in the form of a coordinate table. While rendered super-resolution images reveal structural features of intracellular structures below the optical diffraction limit, the ability to further analyze the molecular coordinates presents opportunities to gain additional quantitative insights into the spatial distribution of a biomolecule of interest. For instance, pair-correlation or radial distribution functions are employed as a measure of clustering, and cross-correlation analysis reveals the colocalization of two biomolecules in two-color SMLM data. Here, we present an efficient filtering method for SMLM data sets based on pair- or cross-correlation to isolate localizations that are clustered or appear in proximity to a second set of localizations in two-color SMLM data. In this way, clustered or colocalized localizations can be separately rendered and analyzed to compare other molecular properties to the remaining localizations, such as their oligomeric state or mobility in live cell experiments. Current matrix-based cross-correlation analyses of large data sets quickly reach the limitations of computer memory due to the space complexity of constructing the distance matrices. Our approach leverages k-dimensional trees to efficiently perform range searches, which dramatically reduces memory needs and the time for the analysis. We demonstrate the versatile applications of this method with simulated data sets as well as examples of two-color SMLM data. The provided MATLAB code and its description can be integrated into existing localization analysis packages and provides a useful resource to analyze SMLM data with new detail.

scholarly journals FOCAL3D: A 3-dimensional clustering package for single-molecule localization microscopy

2020 ◽  
Vol 16 (12) ◽  
pp. e1008479
Author(s):  
Daniel F. Nino ◽  
Daniel Djayakarsana ◽  
Joshua N. Milstein
Keyword(s):  
Single Molecule ◽  
Clustering Algorithm ◽  
Spatial Clustering ◽  
Cluster Complex ◽  
Nuclear Pore ◽  
Data Sets ◽  
Localization Microscopy ◽  
Biological Dataset ◽  
Open Source Software Package ◽  
Single Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) is a powerful tool for studying intracellular structure and macromolecular organization at the nanoscale. The increasingly massive pointillistic data sets generated by SMLM require the development of new and highly efficient quantification tools. Here we present FOCAL3D, an accurate, flexible and exceedingly fast (scaling linearly with the number of localizations) density-based algorithm for quantifying spatial clustering in large 3D SMLM data sets. Unlike DBSCAN, which is perhaps the most commonly employed density-based clustering algorithm, an optimum set of parameters for FOCAL3D may be objectively determined. We initially validate the performance of FOCAL3D on simulated datasets at varying noise levels and for a range of cluster sizes. These simulated datasets are used to illustrate the parametric insensitivity of the algorithm, in contrast to DBSCAN, and clustering metrics such as the F1 and Silhouette score indicate that FOCAL3D is highly accurate, even in the presence of significant background noise and mixed populations of variable sized clusters, once optimized. We then apply FOCAL3D to 3D astigmatic dSTORM images of the nuclear pore complex (NPC) in human osteosaracoma cells, illustrating both the validity of the parameter optimization and the ability of the algorithm to accurately cluster complex, heterogeneous 3D clusters in a biological dataset. FOCAL3D is provided as an open source software package written in Python.

scholarly journals ShareLoc – an open platform for sharing localization microscopy data

2021 ◽  
Author(s):  
Jiachuan Bai ◽  
Wei Ouyang ◽  
Manish Kumar Singh ◽  
Christophe Leterrier ◽  
Paul Barthelemy ◽  
...  
Keyword(s):  
Single Molecule ◽  
Super Resolution ◽  
Data Sets ◽  
Localization Microscopy ◽  
Open Platform ◽  
Machine Learning Methods ◽  
Microscopy Data ◽  
Analytical Tools ◽  
Existing Data ◽  
Single Molecule Localization Microscopy

Novel insights and more powerful analytical tools can emerge from the reanalysis of existing data sets, especially via machine learning methods. Despite the widespread use of single molecule localization microscopy (SMLM) for super-resolution bioimaging, the underlying data are often not publicly accessible. We developed ShareLoc (https://shareloc.xyz), an open platform designed to enable sharing, easy visualization and reanalysis of SMLM data. We discuss its features and show how data sharing can improve the performance and robustness of SMLM image reconstruction by deep learning.

scholarly journals Improved localization precision via restricting confined biomolecule stochastic motion in single-molecule localization microscopy

Nanophotonics ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jielei Ni ◽  
Bo Cao ◽  
Gang Niu ◽  
Danni Chen ◽  
Guotao Liang ◽  
...  
Keyword(s):  
Single Molecule ◽  
Direct Evidence ◽  
Diffraction Limit ◽  
Drift Correction ◽  
Stochastic Motion ◽  
Localization Microscopy ◽  
Alexa Fluor ◽  
Biological Studies ◽  
Localization Precision ◽  
Single Molecule Localization Microscopy

Abstract Single-molecule localization microscopy (SMLM) plays an irreplaceable role in biological studies, in which nanometer-sized biomolecules are hardly to be resolved due to diffraction limit unless being stochastically activated and accurately located by SMLM. For biological samples preimmobilized for SMLM, most biomolecules are cross-linked and constrained at their immobilizing sites but still expected to undergo confined stochastic motion in regard to their nanometer sizes. However, few lines of direct evidence have been reported about the detectability and influence of confined biomolecule stochastic motion on localization precision in SMLM. Here, we access the potential stochastic motion for each immobilized single biomolecule by calculating the displacements between any two of its localizations at different frames during sequential imaging of Alexa Fluor-647-conjugated oligonucleotides. For most molecules, localization displacements are remarkably larger at random frame intervals than at shortest intervals even after sample drift correction, increase with interval times and then saturate, showing that biomolecule stochastic motion is detected and confined around the immobilizing sizes in SMLM. Moreover, localization precision is inversely proportional to confined biomolecule stochastic motion, whereas it can be deteriorated or improved by enlarging the biomolecules or adding a post-crosslinking step, respectively. Consistently, post-crosslinking of cell samples sparsely stained for tubulin proteins results in a better localization precision. Overall, this study reveals that confined stochastic motion of immobilized biomolecules worsens localization precision in SMLM, and improved localization precision can be achieved via restricting such a motion.

scholarly journals Blinking Statistics and Molecular Counting in direct Stochastic Reconstruction Microscopy (dSTORM)

2019 ◽  
Author(s):  
Lekha Patel ◽  
Dylan M. Owen ◽  
Edward A.K. Cohen
Keyword(s):  
Probability Distribution ◽  
Single Molecule ◽  
Diffraction Limit ◽  
Training Data ◽  
Switching Behavior ◽  
Cellular Structures ◽  
Exact Probability ◽  
Localization Microscopy ◽  
Exact Probability Distribution ◽  
Single Molecule Localization Microscopy

AbstractMany recent advancements in single molecule localization microscopy exploit the stochastic photo-switching of fluorophores to reveal complex cellular structures beyond the classical diffraction limit. However, this same stochasticity makes counting the number of molecules to high precision extremely challenging. Modeling the photo-switching behavior of a fluorophore as a continuous time Markov process transitioning between a single fluorescent and multiple dark states, and fully mitigating for missed blinks and false positives, we present a method for computing the exact probability distribution for the number of observed localizations from a single photo-switching fluorophore. This is then extended to provide the probability distribution for the number of localizations in a dSTORM experiment involving an arbitrary number of molecules. We demonstrate that when training data is available to estimate photo-switching rates, the unknown number of molecules can be accurately recovered from the posterior mode of the number of molecules given the number of localizations.

scholarly journals vLUME: 3D Virtual Reality for Single-molecule Localization Microscopy

2020 ◽  
Author(s):  
Alexander Spark ◽  
Alexandre Kitching ◽  
Daniel Esteban-Ferrer ◽  
Anoushka Handa ◽  
Alexander R. Carr ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Single Molecule ◽  
3D Visualization ◽  
Super Resolution ◽  
Rapid Identification ◽  
Data Sets ◽  
Localization Microscopy ◽  
Cloud Data ◽  
Global Quality ◽  
Single Molecule Localization Microscopy

AbstractSuper-Resolution (SR) Microscopy based on 3D Single-Molecule Localization Microscopy (SMLM) is now well established1,2 and its wide-spread adoption has led to the development of more than 36 software packages, dedicated to quantitative evaluation of the spatial and temporal detection of fluorophore photoswitching3. While the initial emphasis in the 3D SMLM field has clearly been on improving resolution and data quality, there is now a marked absence of 3D visualization approaches that enable the straightforward, high-fidelity exploration of this type of data. Inspired by the horological phosphorescence points that illuminate watch-faces in the dark, we present vLUME (Visualization of the Universe in a Micro Environment, pronounced ‘volume’) a free-for-academic-use immersive virtual reality-based (VR) visualization software package purposefully designed to render large 3D-SMLM data sets. vLUME enables robust visualization, segmentation and quantification of millions of fluorescence puncta from any 3D SMLM technique. vLUME has an intuitive user-interface and is compatible with all commercial VR hardware (Oculus Rift/Quest and HTC Vive, Supplementary Video 1). vLUME accelerates the analysis of highly complex 3D point-cloud data and the rapid identification of defects that are otherwise neglected in global quality metrics.

scholarly journals Quantitative super-resolution single molecule microscopy dataset of YFP-tagged growth factor receptors

2018 ◽  
Author(s):  
Tomáš Lukeš ◽  
Jakub Pospíšil ◽  
Karel Fliegel ◽  
Theo Lasser ◽  
Guy M. Hagen
Keyword(s):  
Data Analysis ◽  
Growth Factor ◽  
Single Molecule ◽  
Super Resolution ◽  
Growth Factor Receptors ◽  
Data Sets ◽  
Localization Microscopy ◽  
Super Resolution Microscopy ◽  
Resolution Single ◽  
Single Molecule Localization Microscopy

BackgroundSuper-resolution single molecule localization microscopy (SMLM) is a method for achieving resolution beyond the classical limit in optical microscopes (approx. 200 nm laterally). Yellow fluorescent protein (YFP) has been used for super-resolution single molecule localization microscopy, but less frequently than other fluorescent probes. Working with YFP in SMLM is a challenge because a lower number of photons are emitted per molecule compared to organic dyes which are more commonly used. Publically available experimental data can facilitate development of new data analysis algorithms.FindingsFour complete, freely available single molecule super-resolution microscopy datasets on YFP-tagged growth factor receptors expressed in a human cell line are presented including both raw and analyzed data. We report methods for sample preparation, for data acquisition, and for data analysis, as well as examples of the acquired images. We also analyzed the SMLM data sets using a different method: super-resolution optical fluctuation imaging (SOFI). The two modes of analysis offer complementary information about the sample. A fifth single molecule super-resolution microscopy dataset acquired with the dye Alexa 532 is included for comparison purposes.ConclusionThis dataset has potential for extensive reuse. Complete raw data from SMLM experiments has typically not been published. The YFP data exhibits low signal to noise ratios, making data analysis a challenge. These data sets will be useful to investigators developing their own algorithms for SMLM, SOFI, and related methods. The data will also be useful for researchers investigating growth factor receptors such as ErbB3.

scholarly journals Resolving Biology Beyond the Diffraction Limit with Single-Molecule Localization Microscopy

2016 ◽  
Author(s):  
Nafiseh Rafiei ◽  
Daniel Nino ◽  
Joshua N. Milstein
Keyword(s):  
Optical Imaging ◽  
Single Molecule ◽  
Fluorescent Proteins ◽  
Diffraction Limit ◽  
Review Article ◽  
Localization Microscopy ◽  
Short Overview ◽  
The Future ◽  
Microscopic World ◽  
Single Molecule Localization Microscopy

Optical imaging provides a window into the microscopic world, but the level of observable detail is ultimately limited by the wavelength of light being employed. By harnessing the physics of photoswitchable dyes and fluorescent proteins, single-molecule localization microscopy (SMLM) provides a window into the nano-world of biology. This mini-review article provides a short overview of SMLM and discusses some of its prospects for the future.

scholarly journals Quantitative live-cell PALM reveals nanoscopic Faa4 redistributions and dynamics on lipid droplets during metabolic transitions of yeast

2020 ◽  
Author(s):  
Santosh Adhikari ◽  
Joe Moscatelli ◽  
Elias M. Puchner
Keyword(s):  
Stationary Phase ◽  
Single Molecule ◽  
Lipid Droplets ◽  
Fold Increase ◽  
Diffraction Limit ◽  
Optical Diffraction ◽  
Yeast Cells ◽  
Lipid Homeostasis ◽  
Localization Microscopy ◽  
Live Yeast

AbstractLipid droplets (LDs) are dynamic lipid storage organelles needed for lipid homeostasis. Cells respond to metabolic changes by regulating the spatial distribution of LDs, as well as enzymes required for LD growth and turnover. Due to LD size below the optical diffraction limit, bulk fluorescence microscopy cannot observe the density and dynamics of specific LD enzymes. Here, we employ quantitative photo-activated localization microscopy (PALM) to study the density of the fatty acid activating protein Faa4 on LDs during log, stationary and lag phases in live yeast cells with single-molecule sensitivity and 30 nm resolution. During the log phase LDs co-localize with the Endoplasmic Reticulum (ER) where the highest Faa4 densities are measured. During transition to the stationary phase LDs translocate to the vacuolar surface and lumen with a ~2-fold increased surface area and a ~2.5-fold increase in Faa4 density, suggesting its role in LD expansion. The increased Faa4 density on LDs is caused by its ~5-fold increased expression level. When lipolysis is induced in stationary-phase cells by diluting them for 2 hrs in fresh medium, Faa4 shuttles to the vacuole through the two observed routes of ER- and lipophagy. The observed vacuolar localization of Faa4 may help activating fatty acids for membrane expansion and reduces Faa4 expression to levels found in the log phase.

scholarly journals Nanoscopic Stoichiometry and Single-Molecule Counting

2019 ◽  
Author(s):  
Daniel Nino ◽  
Daniel Djayakarsana ◽  
Joshua N. Milstein
Keyword(s):  
Nucleic Acids ◽  
Single Molecule ◽  
Organic Dyes ◽  
Spatial Scales ◽  
Diffraction Limit ◽  
Dna Origami ◽  
Localization Microscopy ◽  
Practical Guide ◽  
Genomic Analyses ◽  
Single Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) has the potential to revolutionize proteomic and genomic analyses by providing information on the number and stoichiometry of proteins or nucleic acids aggregating at spatial scales below the diffraction limit of light. Here we present a method for molecular counting with SMLM built upon the exponentially distributed blinking statistics of photoswitchable fluorophores, with a focus on organic dyes. We provide a practical guide to molecular counting, highlighting many of the challenges and pitfalls, by benchmarking the method on fluorescently labeled, surface mounted DNA origami grids. The accuracy of the results illustrates SMLM’s utility for optical ‘-omics’ analysis.

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