Lens-based optical microscopy failed to discern fluorescent features closer than 200 nm for decades, but the recent breaking of the diffraction resolution barrier by sequentially switching the fluorescence capability of adjacent features on and off is making nanoscale imaging routine. Reported fluorescence nanoscopy variants switch these features either with intense beams at defined positions or randomly, molecule by molecule. Here we demonstrate an optical nanoscopy that records raw data images from living cells and tissues with low levels of light. This advance has been facilitated by the generation of reversibly switchable enhanced green fluorescent protein (rsEGFP), a fluorescent protein that can be reversibly photoswitched more than a thousand times. Distributions of functional rsEGFP-fusion proteins in living bacteria and mammalian cells are imaged at <40-nanometre resolution. Dendritic spines in living brain slices are super-resolved with about a million times lower light intensities than before. The reversible switching also enables all-optical writing of features with subdiffraction size and spacings, which can be used for data storage.

The nanoscale organization of the F-actin cytoskeleton in neurons comprises membrane-associated periodical rings, bundles, and longitudinal fibers. The F-actin rings have been observed predominantly in axons but only sporadically in dendrites, where fluorescence nanoscopy reveals various patterns of F-actin arranged in mixed patches. These complex dendritic F-actin patterns pose a challenge for investigating quantitatively their regulatory mechanisms. We developed here a weakly supervised deep learning segmentation approach of fluorescence nanoscopy images of F-actin in cultured hippocampal neurons. This approach enabled the quantitative assessment of F-actin remodeling, revealing the disappearance of the rings during neuronal activity in dendrites, but not in axons. The dendritic F-actin cytoskeleton of activated neurons remodeled into longitudinal fibers. We show that this activity-dependent remodeling involves Ca 2+ and NMDA receptor-dependent mechanisms. This highly dynamic restructuring of dendritic F-actin based submembrane lattice into longitudinal fibers may serve to support activity-dependent membrane remodeling, protein trafficking and neuronal plasticity.

Traditional approaches for finding well-performing parameterizations of complex imaging systems, such as super-resolution microscopes rely on an extensive exploration phase over the illumination and acquisition settings, prior to the imaging task. This strategy suffers from several issues: it requires a large amount of parameter configurations to be evaluated, it leads to discrepancies between well-performing parameters in the exploration phase and imaging task, and it results in a waste of time and resources given that optimization and final imaging tasks are conducted separately. Here we show that a fully automated, machine learning-based system can conduct imaging parameter optimization toward a trade-off between several objectives, simultaneously to the imaging task. Its potential is highlighted on various imaging tasks, such as live-cell and multicolor imaging and multimodal optimization. This online optimization routine can be integrated to various imaging systems to increase accessibility, optimize performance and improve overall imaging quality.

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Up to now, all demonstrations of reversible saturable optical fluorescence transitions (RESOLFT) superresolution microscopy of living cells have relied on the use of reversibly switchable fluorescent proteins (RSFP) emitting in the green spectral range. Here we show RESOLFT imaging with rsCherryRev1.4, a new red‐emitting RSFP enabling a spatial resolution up to four times higher than the diffraction barrier. By co‐expressing green and red RSFPs in living cells we demonstrate two‐color RESOLFT imaging both for single (“donut”) beam scanning and for parallelized versions of RESOLFT nanoscopy where an array of >23 000 “donut‐like” minima are scanned simultaneously.

Light-assisted manipulation of cells to control membrane activity or intracellular signaling has become a major avenue in life sciences. However, the ability to perform subcellular light stimulation to investigate localized signaling has been limited. Here, we introduce an all optical method for the stimulation and the monitoring of localized Ca2+ signaling in neurons that takes advantage of plasmonic excitation of gold nanoparticles (AuNPs). We show with confocal microscopy that 800 nm laser pulse application onto a neuron decorated with a few AuNPs triggers a transient increase in free Ca2+, measured optically with GCaMP6s. We show that action potentials, measured electrophysiologically, can be induced with this approach. We demonstrate activation of local Ca2+ transients and Ca2+ signaling via CaMKII in dendritic domains, by illuminating a single or few functionalized AuNPs specifically targeting genetically-modified neurons. This NP-Assisted Localized Optical Stimulation (NALOS) provides a new complement to light-dependent methods for controlling neuronal activity and cell signaling.

Li et al. (Research Articles, 28 August 2015, aab3500) purport to present solutions to longstanding challenges in live-cell microscopy, reporting relatively fast acquisition times in conjunction with improved image resolution. We question the methods' reliability to visualize specimen features at sub-100-nanometer scales, because the mandatory mathematical processing of the recorded data leads to artifacts that are either difficult or impossible to disentangle from real features. We are also concerned about the chosen approach of subjectively comparing images from different super-resolution methods, as opposed to using quantitative measures.(1) extend structured illumination microscopy (SIM) (2, 3) by exploiting a higher numerical aperture (NA) lens and using standing light waves to switch reversibly switchable fluorescent proteins (RSFPs). The patterned on-switching of RSFPs yields a spatially controlled distribution of fluorophores in the fluorescent "on" state, adding spatial frequencies of higher order to the fluorescence emission. These higher-order frequencies improve SIM resolution, provided that they can be disentangled from the low-frequency signals. According to Li et al., even moderate illumination intensities lead to higher frequencies of enhanced amplitudes, making their method more applicable to living cells than other super-resolution approaches. Employing Skylan-NS, an apparently quite photostable-but undisclosed-RSFP, recordings of a few tens of images were made. The resolution was reportedly improved to nominally 84 nm by SIM with an NA 1.7 lens and improved to nominally 62 nm when performing the RSFP switching with sinusoidal on-switching and readout patterns. By saturating the on-switching of the fluorescent proteins, Li et al. extended the resolution to nominally 45 nm.

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