12,241 research outputs found
Real-Time analysis and visualization for single-molecule based super-resolution microscopy
Accurate multidimensional localization of isolated fluorescent emitters is a time consuming process in single-molecule based super-resolution microscopy. We demonstrate a functional method for real-time reconstruction with automatic feedback control, without compromising the localization accuracy. Compatible with high frame rates of EM-CCD cameras, it relies on a wavelet segmentation algorithm, together with a mix of CPU/GPU implementation. A combination with Gaussian fitting allows direct access to 3D localization. Automatic feedback control ensures optimal molecule density throughout the acquisition process. With this method, we significantly improve the efficiency and feasibility of localization-based super-resolution microscopy
Cross-Talk-Free Multi-Color STORM Imaging Using a Single Fluorophore
Multi-color stochastic optical reconstruction microscopy (STORM) is routinely performed; however, the various approaches for achieving multiple colors have important caveats. Color cross-talk, limited availability of spectrally distinct fluorophores with optimal brightness and duty cycle, incompatibility of imaging buffers for different fluorophores, and chromatic aberrations impact the spatial resolution and ultimately the number of colors that can be achieved. We overcome these complexities and develop a simple approach for multi-color STORM imaging using a single fluorophore and sequential labelling. In addition, we present a simple and versatile method to locate the same region of interest on different days and even on different microscopes. In combination, these approaches enable cross-talk-free multi-color imaging of sub-cellular structures.Peer ReviewedPostprint (published version
Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting
We present an analytical method to quantify clustering in super-resolution
localization images of static surfaces in two dimensions. The method also
describes how over-counting of labeled molecules contributes to apparent
self-clustering and how the effective lateral resolution of an image can be
determined. This treatment applies to clustering of proteins and lipids in
membranes, where there is significant interest in using super-resolution
localization techniques to probe membrane heterogeneity. When images are
quantified using pair correlation functions, the magnitude of apparent
clustering due to over-counting will vary inversely with the surface density of
labeled molecules and does not depend on the number of times an average
molecule is counted. Over-counting does not yield apparent co-clustering in
double label experiments when pair cross-correlation functions are measured. We
apply our analytical method to quantify the distribution of the IgE receptor
(Fc{\epsilon}RI) on the plasma membranes of chemically fixed RBL-2H3 mast cells
from images acquired using stochastic optical reconstruction microscopy (STORM)
and scanning electron microscopy (SEM). We find that apparent clustering of
labeled IgE bound to Fc{\epsilon}RI detected with both methods arises from
over-counting of individual complexes. Thus our results indicate that these
receptors are randomly distributed within the resolution and sensitivity limits
of these experiments.Comment: 22 pages, 5 figure
Super-Resolution Microscopy: A Virus’ Eye View of the Cell
It is difficult to observe the molecular choreography between viruses and host cell components, as they exist on a spatial scale beyond the reach of conventional microscopy. However, novel super-resolution microscopy techniques have cast aside technical limitations to reveal a nanoscale view of virus replication and cell biology. This article provides an introduction to super-resolution imaging; in particular, localisation microscopy, and explores the application of such technologies to the study of viruses and tetraspanins, the topic of this special issue
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