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© Ce graphique présente, pour chaque date d'observation depuis 2018, le taux d'accès ouvert des publications scientifiques de l'Institut Pasteur, avec un DOI Crossref, parues durant l'année précédente.
Publication : Biophysical journal

Calibrating Evanescent-Wave Penetration Depths for Biological TIRF Microscopy.

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Biophysical journal - 03 Sep 2019

Oheim M, Salomon A, Weissman A, Brunstein M, Becherer U,

Link to Pubmed [PMID] – 31439287

Link to DOI – S0006-3495(19)30664-210.1016/j.bpj.2019.07.048

Biophys J 2019 09; 117(5): 795-809

Roughly half of a cell’s proteins are located at or near the plasma membrane. In this restricted space, the cell senses its environment, signals to its neighbors, and exchanges cargo through exo- and endocytotic mechanisms. Ligands bind to receptors, ions flow across channel pores, and transmitters and metabolites are transported against concentration gradients. Receptors, ion channels, pumps, and transporters are the molecular substrates of these biological processes, and they constitute important targets for drug discovery. Total internal reflection fluorescence (TIRF) microscopy suppresses the background from the cell’s deeper layers and provides contrast for selectively imaging dynamic processes near the basal membrane of live cells. The optical sectioning of TIRF is based on the excitation confinement of the evanescent wave generated at the glass/cell interface. How deep the excitation light actually penetrates the sample is difficult to know, making the quantitative interpretation of TIRF data problematic. Nevertheless, many applications like superresolution microscopy, colocalization, Förster resonance energy transfer, near-membrane fluorescence recovery after photobleaching, uncaging or photoactivation/switching as well as single-particle tracking require the quantitative interpretation of evanescent-wave-excited images. Here, we review existing techniques for characterizing evanescent fields, and we provide a roadmap for comparing TIRF data across images, experiments, and laboratories.