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

Nature methods (2017-10-31)
Anne Beghin, Adel Kechkar, Corey Butler, Florian Levet, Marine Cabillic, Olivier Rossier, Gregory Giannone, Rémi Galland, Daniel Choquet, Jean-Baptiste Sibarita
ABSTRACT

Single-molecule localization microscopy techniques have proven to be essential tools for quantitatively monitoring biological processes at unprecedented spatial resolution. However, these techniques are very low throughput and are not yet compatible with fully automated, multiparametric cellular assays. This shortcoming is primarily due to the huge amount of data generated during imaging and the lack of software for automation and dedicated data mining. We describe an automated quantitative single-molecule-based super-resolution methodology that operates in standard multiwell plates and uses analysis based on high-content screening and data-mining software. The workflow is compatible with fixed- and live-cell imaging and allows extraction of quantitative data like fluorophore photophysics, protein clustering or dynamic behavior of biomolecules. We demonstrate that the method is compatible with high-content screening using 3D dSTORM and DNA-PAINT based super-resolution microscopy as well as single-particle tracking.

MATERIALS
Product Number
Brand
Product Description

Sigma-Aldrich
Pyranose Oxidase from Coriolus sp., recombinant, expressed in E. coli, ≥2.7 units/mg solid
Sigma-Aldrich
Catalase from Aspergillus niger, ammonium sulfate suspension, ≥4,000 units/mg protein