scholarly journals Three-Dimensional Super-Resolution Imaging by Stochastic Optical Reconstruction Microscopy

Science ◽  
2008 ◽  
Vol 319 (5864) ◽  
pp. 810-813 ◽  
Author(s):  
B. Huang ◽  
W. Wang ◽  
M. Bates ◽  
X. Zhuang
Keyword(s):  
Three Dimensional ◽  
Super Resolution ◽  
Stochastic Optical Reconstruction Microscopy ◽  
Resolution Imaging ◽  
Optical Reconstruction

scholarly journals Focus on Super-Resolution Imaging with Direct Stochastic Optical Reconstruction Microscopy (dSTORM)

2014 ◽  
Vol 67 (2) ◽  
pp. 179 ◽  
Author(s):  
Donna R. Whelan ◽  
Thorge Holm ◽  
Markus Sauer ◽  
Toby D. M. Bell
Keyword(s):  
Cell Biology ◽  
Super Resolution ◽  
Diffraction Limit ◽  
Stochastic Optical Reconstruction Microscopy ◽  
Resolution Imaging ◽  
Optical Reconstruction ◽  
Set Up ◽  
Microscopy Techniques ◽  
Super Resolution Microscopy ◽  
Microscopic Techniques

The last decade has seen the development of several microscopic techniques capable of achieving spatial resolutions that are well below the diffraction limit of light. These techniques, collectively referred to as ‘super-resolution’ microscopy, are now finding wide use, particularly in cell biology, routinely generating fluorescence images with resolutions in the order of tens of nanometres. In this highlight, we focus on direct Stochastic Optical Reconstruction Microscopy or dSTORM, one of the localisation super-resolution fluorescence microscopy techniques that are founded on the detection of fluorescence emissions from single molecules. We detail how, with minimal assemblage, a highly functional and versatile dSTORM set-up can be built from ‘off-the-shelf’ components at quite a modest budget, especially when compared with the current cost of commercial systems. We also present some typical super-resolution images of microtubules and actin filaments within cells and discuss sample preparation and labelling methods.

scholarly journals A quantitative super-resolution imaging toolbox for diagnosis of motile ciliopathies

2020 ◽  
Vol 12 (535) ◽  
pp. eaay0071 ◽  
Author(s):  
Zhen Liu ◽  
Quynh P. H. Nguyen ◽  
Qingxu Guan ◽  
Alexandra Albulescu ◽  
Lauren Erdman ◽  
...  
Keyword(s):  
Lung Function ◽  
A Priori ◽  
Three Dimensional ◽  
Super Resolution ◽  
Structural Defects ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Stochastic Optical Reconstruction Microscopy ◽  
Motile Cilia ◽  
Optical Reconstruction

Airway clearance of pathogens and particulates relies on motile cilia. Impaired cilia motility can lead to reduction in lung function, lung transplant, or death in some cases. More than 50 proteins regulating cilia motility are linked to primary ciliary dyskinesia (PCD), a heterogeneous, mainly recessive genetic lung disease. Accurate PCD molecular diagnosis is essential for identifying therapeutic targets and for initiating therapies that can stabilize lung function, thereby reducing socioeconomic impact of the disease. To date, PCD diagnosis has mainly relied on nonquantitative methods that have limited sensitivity or require a priori knowledge of the genes involved. Here, we developed a quantitative super-resolution microscopy workflow: (i) to increase sensitivity and throughput, (ii) to detect structural defects in PCD patients’ cells, and (iii) to quantify motility defects caused by yet to be found PCD genes. Toward these goals, we built a localization map of PCD proteins by three-dimensional structured illumination microscopy and implemented quantitative image analysis and machine learning to detect protein mislocalization, we analyzed axonemal structure by stochastic optical reconstruction microscopy, and we developed a high-throughput method for detecting motile cilia uncoordination by rotational polarity. Together, our data show that super-resolution methods are powerful tools for improving diagnosis of motile ciliopathies.

Mechanistic insights into EGFR membrane clustering revealed by super-resolution imaging

Nanoscale ◽  
2015 ◽  
Vol 7 (6) ◽  
pp. 2511-2519 ◽  
Author(s):  
Jing Gao ◽  
Ye Wang ◽  
Mingjun Cai ◽  
Yangang Pan ◽  
Haijiao Xu ◽  
...  
Keyword(s):  
Distribution Pattern ◽  
Lipid Rafts ◽  
Essential Role ◽  
Super Resolution ◽  
Stochastic Optical Reconstruction Microscopy ◽  
Polarized Cells ◽  
Resolution Imaging ◽  
Optical Reconstruction ◽  
Cluster Maintenance

We investigate the distribution of membrane EGFR by direct stochastic optical reconstruction microscopy (dSTORM). Our results illustrate the clustering distribution pattern of EGFR in polarized cells and uncover the essential role of lipid rafts in EGFR cluster maintenance.

scholarly journals Volumetric super-resolution imaging by serial ultrasectioning and stochastic optical reconstruction microscopy in mouse neural tissue

2021 ◽  
Vol 2 (4) ◽  
pp. 100971
Author(s):  
Tarlan Vatan ◽  
Jacqueline A. Minehart ◽  
Chenghang Zhang ◽  
Vatsal Agarwal ◽  
Jerry Yang ◽  
...  
Keyword(s):  
Super Resolution ◽  
Neural Tissue ◽  
Stochastic Optical Reconstruction Microscopy ◽  
Resolution Imaging ◽  
Optical Reconstruction

scholarly journals Surface Charge Manipulation and Electrostatic Immobilization of Synaptosomes for Super-resolution Imaging: A Study on Tau Compartmentalization

2021 ◽  
Author(s):  
Ushashi Bhattacharya ◽  
Jia-Fong Jhou ◽  
Yi-Fong Zou ◽  
Gerald Abrigo ◽  
Shu-Wei Lin ◽  
...  
Keyword(s):  
Synaptic Vesicles ◽  
Protein Localization ◽  
Super Resolution ◽  
Synaptic Terminals ◽  
Stochastic Optical Reconstruction Microscopy ◽  
Neural Transmission ◽  
Resolution Imaging ◽  
Optical Reconstruction ◽  
Cortical Synapses ◽  
Induced Aggregation

Abstract Synaptosomes are subcellular fractions prepared from brain tissues that are enriched in synaptic terminals, widely used for the study of neural transmission and synaptic dysfunction. Immunofluorescence imaging is increasingly applied to synaptosomes to investigate protein localization. However, conventional methods for imaging synaptosomes over glass coverslips suffer from formaldehyde-induced aggregation. Here, we developed a simple and facile strategy to capture and image synaptosomes without aggregation artefacts. First, ethylene glycol bis(succinimidyl succinate) (EGS) is chosen as the chemical fixative to replace formaldehyde. EGS/glycine treatment makes the zeta potential of synaptosomes more negative. Second, we modified glass coverslips with 3-aminopropyltriethoxysilane (APTES) to impart positive charges. EGS-fixed synaptosomes spontaneously attach to modified glasses via electrostatic attraction while maintaining good dispersion. Individual synaptic terminals are imaged by conventional fluorescence microscopy or by super-resolution techniques such as direct stochastic optical reconstruction microscopy (dSTORM). We examined tau protein by two-color and three-color dSTORM to understand its spatial distribution within mouse cortical synapses, observing tau colocalization with synaptic vesicles as well postsynaptic densities.

scholarly journals Volumetric super-resolution imaging by serial ultrasectioning and STochastic Optical Reconstruction Microscopy (STORM) in neural tissue

2021 ◽  
Author(s):  
Tarlan Vatan ◽  
Jacqueline A. Minehart ◽  
Chenghang Zhang ◽  
Vatsal Agarwal ◽  
Jerry Yang ◽  
...  
Keyword(s):  
Single Molecule ◽  
Super Resolution ◽  
Neural Tissue ◽  
Imaging Data ◽  
Whole Cells ◽  
Stochastic Optical Reconstruction Microscopy ◽  
Tissue Scattering ◽  
Resolution Imaging ◽  
Optical Reconstruction ◽  
Chemical Synapses

Abstract Here we present a protocol for collecting large-volume, four-color, single-molecule localization imaging data from neural tissue. We have applied this technique to map the location and identities of chemical synapses across whole cells in mouse retinae. Our sample preparation approach improves 3D STORM image quality by reducing tissue scattering, photobleaching, and optical distortions associated with deep imaging. This approach can be extended for use on other tissue types enabling life scientists to perform volumetric super-resolution imaging in diverse biological models. For a detailed application of this protocol, please refer to Sigal et al., 2015.

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