Self‐labeling enzymes (SLE) such as the HaloTag have emerged as powerful tools in high and super‐resolution fluorescence microscopy. Newly developed fluorogenic SLE substrates enable imaging in the presence of excess dye. To exploit this feature for reversible labeling, we engineered two variants of HaloTag7 with restored dehalogenase activity. Kinetic studies in vitro showed different turnover kinetics for reHaloTagS (≈0.006 s−1) and reHaloTagF (≈0.055 s−1). Imaging by confocal and stimulated emission depletion microscopy yielded 3‐5‐time enhanced photostability of reHaloTag labeling. Prominently, single molecule imaging with reHaloTags enabled controlled and stable labeling density over extended time periods. By combination with structured illumination, simultaneous visualization of single molecule diffusion and organellar dynamics was achieved. These applications highlight the potential of reHaloTag labeling for pushing the limits of advanced fluorescence microscopy techniques.
The minimum requirement for mitochondrial apoptosis has been controversial ever since the discovery of BCL-2 as a cell death regulator. In this issue of Genes & Development, O'Neill and colleagues (pp. 973–988) end a long-standing debate by creating a cellular system free of BCL-2 family proteins, thereby identifying the outer mitochondrial membrane rather than BH3-only proteins as the only requirement for BAX/BAK activation and mitochondrial outer membrane permeabilization (MOMP).
Motivation
Imaging single molecules has emerged as a powerful characterization tool in the biological sciences. The detection of these under various noise conditions requires the use of algorithms that are dependent on the end-user inputting several parameters, the choice of which can be challenging and subjective.
Results
In this work, we propose DeepSinse, an easily-trainable and useable deep neural network that can detect single molecules with little human input and across a wide range of signal-to-noise ratios. We validate the neural network on the detection of single bursts in simulated and experimental data and compare its performance with the best-in-class, domain-specific algorithms.
Availability
Ground truth ROI simulating code, neural network training, validation code, classification code, ROI picker, GUI for simulating, training and validating DeepSinse as well as pre-trained networks are all released under the MIT License on www.github.com/jdanial/DeepSinse.The dSTORM dataset processing code is released under the MIT License on www.github.com/jdanial/StormProcessor
Supplementary information
Supplementary data are available at Bioinformatics online.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.