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Super-resolution Fluorescence Microscopy

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...

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Updated: Feb 19, 2026

High Content Screening in Neurodegenerative Diseases

High Content Screening in Neurodegenerative Diseases

Published on: January 6, 2012

Localization-based super-resolution imaging meets high-content screening.

Anne Beghin^1,2, Adel Kechkar³, Corey Butler^1,2,4

¹Université de Bordeaux, Institut interdisciplinaire de Neurosciences, Bordeaux, France.

|October 31, 2017

Summary

This summary is machine-generated.

We developed an automated super-resolution microscopy method for high-throughput analysis of biological processes. This technique enables quantitative single-molecule imaging in multiwell plates, overcoming previous limitations in throughput and automation for cellular assays.

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Last Updated: Feb 19, 2026

High Content Screening in Neurodegenerative Diseases

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Area of Science:

Biophysics
Cell Biology
Microscopy

Background:

Single-molecule localization microscopy (SMLM) offers high spatial resolution for biological studies.
Current SMLM methods suffer from low throughput and lack automation for complex cellular assays.
Challenges include massive data generation and insufficient data-mining software.

Purpose of the Study:

To develop an automated, quantitative, single-molecule-based super-resolution methodology.
To enable high-throughput, multiparametric cellular assays using SMLM.
To integrate SMLM with high-content screening and data-mining approaches.

Main Methods:

Implementation of an automated workflow for SMLM in standard multiwell plates.
Utilized high-content screening and data-mining software for analysis.
Compatibility with both fixed- and live-cell imaging.

Main Results:

Extraction of quantitative data including fluorophore photophysics and protein clustering.
Demonstrated dynamic behavior analysis of biomolecules.
Validated compatibility with 3D dSTORM, DNA-PAINT, and single-particle tracking for high-content screening.

Conclusions:

The developed methodology significantly enhances the throughput and automation of SMLM.
Enables quantitative analysis of biomolecular processes in a high-content screening format.
Advances the application of super-resolution microscopy in drug discovery and biological research.