scholarly journals Artifact Formation in Single Molecule Localization Microscopy

2019 ◽  
Author(s):  
Jochen M. Reichel ◽  
Thomas Vomhof ◽  
Jens Michaelis
Keyword(s):  
Single Molecule ◽  
Ground Truth ◽  
Image Artifacts ◽  
Ground Truth Data ◽  
Localization Accuracy ◽  
Localization Microscopy ◽  
Trade Offs ◽  
Artifact Formation ◽  
Localization Behavior ◽  
Single Molecule Localization Microscopy

AbstractWe investigate the influence of different accuracy-detection rate trade-offs on image reconstruction in single molecule localization microscopy. Our main focus is the investigation of image artifacts experienced when using low localization accuracy, especially in the presence of sample drift and inhomogeneous background. In this context we present a newly developed SMLM software termed FIRESTORM which is optimized for high accuracy reconstruction. For our analysis we used in silico SMLM data and compared the reconstructed images to the ground truth data. We observe two discriminable reconstruction populations of which only one shows the desired localization behavior.

A literature review of localization methods and emergence of deep learning in single-molecule localization microscopy

2020 ◽  
Author(s):  
Anish Mukherjee
Keyword(s):  
Deep Learning ◽  
Single Molecule ◽  
Super Resolution ◽  
Point Sources ◽  
Learning Approaches ◽  
Localization Algorithm ◽  
Localization Microscopy ◽  
Trade Offs ◽  
Emitter Localization ◽  
Single Molecule Localization Microscopy

The quality of super-resolution images largely depends on the performance of the emitter localization algorithm used to localize point sources. In this article, an overview of the various techniques which are used to localize point sources in single-molecule localization microscopy are discussed and their performances are compared. This overview can help readers to select a localization technique for their application. Also, an overview is presented about the emergence of deep learning methods that are becoming popular in various stages of single-molecule localization microscopy. The state of the art deep learning approaches are compared to the traditional approaches and the trade-offs of selecting an algorithm for localization are discussed.

scholarly journals Single molecule localization microscopy with autonomous feedback loops for ultrahigh precision

2018 ◽  
Author(s):  
Simao Coelho ◽  
Jongho Baek ◽  
Matthew S. Graus ◽  
James M. Halstead ◽  
Philip R. Nicovich ◽  
...  
Keyword(s):  
Single Molecule ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
Separation Distance ◽  
Distance Measurements ◽  
Intact Cells ◽  
Localization Accuracy ◽  
Localization Microscopy ◽  
Signaling Receptors ◽  
Single Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) promises to provide truly molecular scale images of biological specimens1–5. However, mechanical instabilities in the instrument, readout errors and sample drift constitute significant challenges and severely limit both the useable data acquisition length and the localization accuracy of single molecule emitters6. Here, we developed an actively stabilized total internal fluorescence (TIRF) microscope that performs 3D real-time drift corrections and achieves a stability of ≤1 nm. Self-alignment of the emission light path and corrections of readout errors of the camera automate channel alignment and ensure localization precisions of 1-4 nm in DNA origami structures and cells for different labels. We used Feedback SMLM to measure the separation distance of signaling receptors and phosphatases in T cells. Thus, an improved SMLM enables direct distance measurements between molecules in intact cells on the scale between 1-20 nm, potentially replacing Förster resonance energy transfer (FRET) to quantify molecular interactions7. In summary, by overcoming the major bottlenecks in SMLM imaging, it is possible to generate molecular images with nanometer accuracy and conduct distance measurements on the biological relevant length scales.

scholarly journals StormGraph: A graph-based algorithm for quantitative clustering analysis of diverse single-molecule localization microscopy data

2019 ◽  
Author(s):  
Joshua M. Scurll ◽  
Libin Abraham ◽  
Da Wei Zheng ◽  
Reza Tafteh ◽  
Keng C. Chou ◽  
...  
Keyword(s):  
Single Molecule ◽  
Input Parameter ◽  
Surface Protein ◽  
Ground Truth ◽  
Antigen Receptors ◽  
Localization Microscopy ◽  
3D Data ◽  
Microscopy Data ◽  
2D And 3D ◽  
Single Molecule Localization Microscopy

AbstractClustering of proteins is crucial for many cellular processes and can be imaged at nanoscale resolution using single-molecule localization microscopy (SMLM). Ideally, molecular clustering in regions of interest (ROIs) from SMLM images would be assessed using computational methods that are robust to sample and experimental heterogeneity, account for uncertainties in localization data, can analyze both 2D and 3D data, and have practical computational requirements in terms of time and hardware. While analyzing surface protein clustering on B lymphocytes using SMLM, we encountered limitations with existing cluster analysis methods. This inspired us to develop StormGraph, an algorithm using graph theory and community detection to identify clusters in heterogeneous sets of 2D and 3D SMLM data while accounting for localization uncertainties. StormGraph generates both multi-level and single-level clusterings and can quantify cluster overlap for two-color SMLM data. Importantly, StormGraph automatically determines scale-dependent thresholds from the data using scale-independent input parameters. This makes identical choices of input parameter values suitable for disparate ROIs, eliminating the need to tune parameters for different ROIs in heterogeneous SMLM datasets. We show that StormGraph outperforms existing algorithms at analyzing heterogeneous sets of simulated SMLM ROIs where ground-truth clusters are known. Applying StormGraph to real SMLM data in 2D, we reveal that B-cell antigen receptors (BCRs) reside in a heterogeneous combination of small and large clusters following stimulation, which suggests for the first time that two conflicting models of BCR activation are not mutually exclusive. We also demonstrate application of StormGraph to real two-color and 3D SMLM data.

scholarly journals Three-Dimensional Single-Molecule Localization Microscopy in Whole-Cell and Tissue Specimens

2020 ◽  
Vol 22 (1) ◽  
pp. 155-184 ◽  
Author(s):  
Sheng Liu ◽  
Hyun Huh ◽  
Sang-Hyuk Lee ◽  
Fang Huang
Keyword(s):  
Single Molecule ◽  
Three Dimensional ◽  
Super Resolution ◽  
Three Dimensions ◽  
Whole Cell ◽  
Localization Microscopy ◽  
Trade Offs ◽  
Protein Functions ◽  
Tissue Specimens ◽  
Single Molecule Localization Microscopy

Super-resolution microscopy techniques are versatile and powerful tools for visualizing organelle structures, interactions, and protein functions in biomedical research. However, whole-cell and tissue specimens challenge the achievable resolution and depth of nanoscopy methods. We focus on three-dimensional single-molecule localization microscopy and review some of the major roadblocks and developing solutions to resolving thick volumes of cells and tissues at the nanoscale in three dimensions. These challenges include background fluorescence, system- and sample-induced aberrations, and information carried by photons, as well as drift correction, volume reconstruction, and photobleaching mitigation. We also highlight examples of innovations that have demonstrated significant breakthroughs in addressing the abovementioned challenges together with their core concepts as well as their trade-offs.

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
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