scholarly journals RainbowSTORM: an open-source ImageJ plug-in for spectroscopic single-molecule localization microscopy (sSMLM) data analysis and image reconstruction

2020 ◽  
Vol 36 (19) ◽  
pp. 4972-4974
Author(s):  
Janel L Davis ◽  
Brian Soetikno ◽  
Ki-Hee Song ◽  
Yang Zhang ◽  
Cheng Sun ◽  
...  
Keyword(s):  
Open Source ◽  
Single Molecule ◽  
Spectroscopic Analysis ◽  
Emission Spectra ◽  
Supplementary Information ◽  
Localization Microscopy ◽  
Spatial Locations ◽  
Fluorescent Molecules ◽  
System Designs ◽  
Single Molecule Localization Microscopy

Abstract Summary Spectroscopic single-molecule localization microscopy (sSMLM) simultaneously captures the spatial locations and full spectra of stochastically emitting fluorescent single molecules. It provides an optical platform to develop new multimolecular and functional imaging capabilities. While several open-source software suites provide subdiffraction localization of fluorescent molecules, software suites for spectroscopic analysis of sSMLM data remain unavailable. RainbowSTORM is an open-source ImageJ/FIJI plug-in for end-to-end spectroscopic analysis and visualization for sSMLM images. RainbowSTORM allows users to calibrate, preview and quantitatively analyze emission spectra acquired using different reported sSMLM system designs and fluorescent labels. Availability and implementation RainbowSTORM is a java plug-in for ImageJ (https://imagej.net)/FIJI (http://fiji.sc) freely available through: https://github.com/FOIL-NU/RainbowSTORM. RainbowSTORM has been tested with Windows and Mac operating systems and ImageJ/FIJI version 1.52. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals RainbowSTORM: An open-source ImageJ plugin for spectroscopic single-molecule localization microscopy (sSMLM) data analysis and image reconstruction

2020 ◽  
Author(s):  
Janel L. Davis ◽  
Brian Soetikno ◽  
Ki-Hee Song ◽  
Yang Zhang ◽  
Cheng Sun ◽  
...  
Keyword(s):  
Open Source ◽  
Single Molecule ◽  
Spectroscopic Analysis ◽  
Emission Spectra ◽  
Supplementary Information ◽  
Localization Microscopy ◽  
Link Type ◽  
User Friendly ◽  
Spatial Locations ◽  
Single Molecule Localization Microscopy

AbstractSummarySpectroscopic single-molecule localization microscopy (sSMLM) simultaneously captures the spatial locations and full spectra of stochastically emitting fluorescent single molecules. It provides an optical platform to develop new multi-molecular and functional imaging capabilities. While several open-source software suites provide sub-diffraction localization of fluorescent molecules, software suites for spectroscopic analysis of sSMLM data remain unavailable. RainbowSTORM is an open-source, user-friendly ImageJ/FIJI plugin for end-to-end spectroscopic analysis and visualization for sSMLM images. RainbowSTORM allows users to calibrate, preview, and quantitatively analyze emission spectra acquired using different reported sSMLM system designs and fluorescent labels.AvailabilityRainbowSTORM is a java plugin for ImageJ (https://imagej.net)/FIJI (http://fiji.sc) freely available through: https://github.com/FOIL-NU/RainbowSTORM. RainbowSTORM has been tested with Windows and Mac operating systems and ImageJ/FIJI version 1.52.Supplementary informationSupplementary data are available online.

scholarly journals Multiplane and Spectrally-Resolved Single Molecule Localization Microscopy with Industrial Grade CMOS Cameras

2017 ◽  
Author(s):  
Hazen P. Babcock
Keyword(s):  
Open Source ◽  
Single Molecule ◽  
Open Source Software ◽  
Super Resolution ◽  
Localization Microscopy ◽  
Industrial Grade ◽  
Spectrally Resolved ◽  
Imaging Plane ◽  
Single Molecule Localization Microscopy

ABSTRACTIn this work we explore the use of industrial grade CMOS cameras for single molecule localization microscopy (SMLM). We show that the performance of these cameras in single imaging plane SMLM applications is comparable to much more expensive scientific CMOS (sCMOS) cameras. We show that these cameras can be used in more demanding biplane, multiplane and spectrally resolved SMLM applications. The 10-40× reduction in camera cost makes it practical to build SMLM setups with 4 or more cameras. In addition we provide open-source software for simultaneously controlling multiple CMOS cameras and for the reduction of the movies that are acquired to super-resolution images.

scholarly journals Identification of caveolin-1 domain signatures via machine learning and graphlet analysis of single-molecule super-resolution data

2019 ◽  
Vol 35 (18) ◽  
pp. 3468-3475 ◽  
Author(s):  
Ismail M Khater ◽  
Fanrui Meng ◽  
Ivan Robert Nabi ◽  
Ghassan Hamarneh
Keyword(s):  
Prostate Cancer ◽  
Machine Learning ◽  
Cancer Cells ◽  
Single Molecule ◽  
Classification Accuracy ◽  
Supplementary Information ◽  
Prostate Cancer Cells ◽  
Localization Microscopy ◽  
Caveolin 1 ◽  
Single Molecule Localization Microscopy

Abstract Motivation Network analysis and unsupervised machine learning processing of single-molecule localization microscopy of caveolin-1 (Cav1) antibody labeling of prostate cancer cells identified biosignatures and structures for caveolae and three distinct non-caveolar scaffolds (S1A, S1B and S2). To obtain further insight into low-level molecular interactions within these different structural domains, we now introduce graphlet decomposition over a range of proximity thresholds and show that frequency of different subgraph (k = 4 nodes) patterns for machine learning approaches (classification, identification, automatic labeling, etc.) effectively distinguishes caveolae and scaffold blobs. Results Caveolae formation requires both Cav1 and the adaptor protein CAVIN1 (also called PTRF). As a supervised learning approach, we applied a wide-field CAVIN1/PTRF mask to CAVIN1/PTRF-transfected PC3 prostate cancer cells and used the random forest classifier to classify blobs based on graphlet frequency distribution (GFD). GFD of CAVIN1/PTRF-positive (PTRF+) and -negative Cav1 clusters showed poor classification accuracy that was significantly improved by stratifying the PTRF+ clusters by either number of localizations or volume. Low classification accuracy (<50%) of large PTRF+ clusters and caveolae blobs identified by unsupervised learning suggests that their GFD is specific to caveolae. High classification accuracy for small PTRF+ clusters and caveolae blobs argues that CAVIN1/PTRF associates not only with caveolae but also non-caveolar scaffolds. At low proximity thresholds (50–100 nm), the caveolae groups showed reduced frequency of highly connected graphlets and increased frequency of completely disconnected graphlets. GFD analysis of single-molecule localization microscopy Cav1 clusters defines changes in structural organization in caveolae and scaffolds independent of association with CAVIN1/PTRF. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A cost-efficient open source laser engine for microscopy

2019 ◽  
Author(s):  
Daniel Schröder ◽  
Joran Deschamps ◽  
Anindita Dasgupta ◽  
Ulf Matti ◽  
Jonas Ries
Keyword(s):  
Open Source ◽  
Single Molecule ◽  
High Power ◽  
Laser Diodes ◽  
Power Laser ◽  
Localization Microscopy ◽  
Diode Pumped ◽  
Cost Efficient ◽  
The Cost ◽  
Single Molecule Localization Microscopy

AbstractScientific-grade lasers are costly components of modern microscopes. For high-power applications, such as single-molecule localization microscopy, their price can become prohibitive. Here, we present an open-source high-power laser engine that can be built for a fraction of the cost. It uses affordable, yet powerful laser diodes at wavelengths of 405 nm, 488 nm and 640 nm and optionally a 561 nm diode-pumped solid-state laser. The light is delivered to the microscope via an agitated multimode fiber in order to suppress speckles. We provide the part lists, CAD files and detailed descriptions, allowing any research group to build their own laser engine.

Single-Molecule Imaging of Active Mitochondrial Nitroreductases using a Photo-Crosslinking Fluorescent Sensor

2019 ◽  
Author(s):  
Zacharias Thiel ◽  
Pablo Rivera-Fuentes
Keyword(s):  
Subcellular Localization ◽  
Fluorescent Probe ◽  
Single Molecule ◽  
Mammalian Cells ◽  
Fluorescent Sensor ◽  
Biological Functions ◽  
Localization Microscopy ◽  
Drug Activation ◽  
Nitroreductase Activity ◽  
Single Molecule Localization Microscopy

Many biomacromolecules are known to cluster in microdomains with specific subcellular localization. In the case of enzymes, this clustering greatly defines their biological functions. Nitroreductases are enzymes capable of reducing nitro groups to amines and play a role in detoxification and pro-drug activation. Although nitroreductase activity has been detected in mammalian cells, the subcellular localization of this activity remains incompletely characterized. Here, we report a fluorescent probe that enables super-resolved imaging of pools of nitroreductase activity within mitochondria. This probe is activated sequentially by nitroreductases and light to give a photo-crosslinked adduct of active enzymes. In combination with a general photoactivatable marker of mitochondria, we performed two-color, threedimensional, single-molecule localization microscopy. These experiments allowed us to image the sub-mitochondrial organization of microdomains of nitroreductase activity.<br>

Single-Molecule Imaging of Active Mitochondrial Nitroreductases using a Photo-Crosslinking Fluorescent Sensor

2019 ◽  
Author(s):  
Zacharias Thiel ◽  
Pablo Rivera-Fuentes
Keyword(s):  
Subcellular Localization ◽  
Fluorescent Probe ◽  
Single Molecule ◽  
Mammalian Cells ◽  
Fluorescent Sensor ◽  
Biological Functions ◽  
Localization Microscopy ◽  
Drug Activation ◽  
Nitroreductase Activity ◽  
Single Molecule Localization Microscopy

Many biomacromolecules are known to cluster in microdomains with specific subcellular localization. In the case of enzymes, this clustering greatly defines their biological functions. Nitroreductases are enzymes capable of reducing nitro groups to amines and play a role in detoxification and pro-drug activation. Although nitroreductase activity has been detected in mammalian cells, the subcellular localization of this activity remains incompletely characterized. Here, we report a fluorescent probe that enables super-resolved imaging of pools of nitroreductase activity within mitochondria. This probe is activated sequentially by nitroreductases and light to give a photo-crosslinked adduct of active enzymes. In combination with a general photoactivatable marker of mitochondria, we performed two-color, threedimensional, single-molecule localization microscopy. These experiments allowed us to image the sub-mitochondrial organization of microdomains of nitroreductase activity.<br>

scholarly journals Single-molecule localization microscopy

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Mickaël Lelek ◽  
Melina T. Gyparaki ◽  
Gerti Beliu ◽  
Florian Schueder ◽  
Juliette Griffié ◽  
...  
Keyword(s):  
Single Molecule ◽  
Localization Microscopy ◽  
Single Molecule Localization Microscopy

scholarly journals Three-dimensional total-internal reflection fluorescence nanoscopy with nanometric axial resolution by photometric localization of single molecules

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Alan M. Szalai ◽  
Bruno Siarry ◽  
Jerónimo Lukin ◽  
David J. Williamson ◽  
Nicolás Unsain ◽  
...  
Keyword(s):  
Single Molecule ◽  
Total Internal Reflection ◽  
Single Molecules ◽  
Fluorescence Microscope ◽  
Internal Reflection ◽  
Total Internal Reflection Fluorescence ◽  
Axial Position ◽  
Localization Microscopy ◽  
Localization Precision ◽  
Single Molecule Localization Microscopy

AbstractSingle-molecule localization microscopy enables far-field imaging with lateral resolution in the range of 10 to 20 nanometres, exploiting the fact that the centre position of a single-molecule’s image can be determined with much higher accuracy than the size of that image itself. However, attaining the same level of resolution in the axial (third) dimension remains challenging. Here, we present Supercritical Illumination Microscopy Photometric z-Localization with Enhanced Resolution (SIMPLER), a photometric method to decode the axial position of single molecules in a total internal reflection fluorescence microscope. SIMPLER requires no hardware modification whatsoever to a conventional total internal reflection fluorescence microscope and complements any 2D single-molecule localization microscopy method to deliver 3D images with nearly isotropic nanometric resolution. Performance examples include SIMPLER-direct stochastic optical reconstruction microscopy images of the nuclear pore complex with sub-20 nm axial localization precision and visualization of microtubule cross-sections through SIMPLER-DNA points accumulation for imaging in nanoscale topography with sub-10 nm axial localization precision.

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