Super-resolution microscopy gives researchers invaluable opportunities and continues to make great strides in terms of performance and applicability. Clever developments in stimulated emission depletion (STED) microscopy have pushed the doors open wider for many applications. Here, we discuss three examples: first, how time-resolved detection unlocks new information; then, live-cell imaging enabled by intelligent illumination schemes; and finally, deep tissue imaging with dynamic aberration correction. As an outlook, we examine MINFLUX as an approach for molecular resolution with fluorescence.

Live-cell fluorescence microscopy is an indispensable tool in biomedical and biophysical research, allowing the study of dynamic processes in living systems. Recent developments have given rise to high-end imaging systems capable of live-cell imaging on the nanometer scale. These instrumentation developments have, in turn, increased the demand for enhanced fluorophores to label target proteins within living cells. abberior offers solutions on both fronts. abberior LIVE dyes have higher cell permeability and improved specificity compared to conventional labels, making long-term live-cell imaging at extremely low probe concentrations possible. These low nanomolar working concentrations minimize cell toxic effects. abberior stimulation emission depletion (STED) microscopes offer super-resolution down to ~30 nm with minimal light exposure to the sample. This unique combination takes live-cell imaging to the next level and will make super-resolution imaging of dynamic subcellular processes a routine, easy-to-use visualization method, paving the way for fundamental biological discoveries. At the extreme, minimal emission fluxes (MINFLUX) microscopy offers molecular resolutions of a few nanometers in unprecedented temporal regimes.

The zygote is the first cell of a multicellular organism. In most angiosperms, the zygote divides asymmetrically to produce an embryo-precursor apical cell and a supporting basal cell. Zygotic division should properly segregate symbiotic organelles, because they cannot be synthesized de novo. In this study, we revealed the real-time dynamics of the principle source of ATP biogenesis, mitochondria, in Arabidopsis thaliana zygotes using live-cell observations and image quantifications. In the zygote, the mitochondria formed the extended structure associated with the longitudinal array of actin filaments (F-actins) and were polarly distributed along the apical–basal axis. The mitochondria were then temporally fragmented during zygotic division, and the resulting apical cells inherited mitochondria at higher concentration compared to the basal cells. Further observation of postembryonic organs showed that these mitochondrial behaviours are characteristic of the zygote. Overall, our results showed that the zygote has spatiotemporal regulation that unequally distributes the mitochondria.

Retrograde transport is a process in which proteins are trafficked from the plasma membrane and endosomes to biosynthetic and secretory organelles, namely the Golgi apparatus and endoplasmic reticulum (ER). A number of plant and bacterial toxins, including cholera toxin and ricin toxin, exploit retrograde transport to gain entry into host cells, although the specifics of this process have remained difficult to probe by laser scanning confocal microscopy (LSCM). Here we demonstrate the use of super-resolution and live-cell imaging [stimulated emission depletion (STED)] to visualize exogenously applied ricin toxin within the ER. The improved resolution obtained by STED, as compared with LSCM (0.09 versus 0.19 μm), provides a more accurate determination of the amount of ricin that had trafficked to the ER.

Accurate automated quantitative analysis of living cells based on fluorescence microscopy images can be very useful for fast evaluation of experimental outcomes and cell culture protocols. In this work, an algorithm is developed for fast differentiation of normal and apoptotic viable Chinese hamster ovary (CHO) cells. For effective segmentation of cell images, a stochastic segmentation algorithm is developed by combining a generalized polynomial chaos expansion with a level set function-based segmentation algorithm. This approach provides a probabilistic description of the segmented cellular regions along the boundary, from which it is possible to calculate morphological changes related to apoptosis, i.e., the curvature and length of a cell’s boundary. These features are then used as inputs to a support vector machine (SVM) classifier that is trained to distinguish between normal and apoptotic viable states of CHO cell images. The use of morphological features obtained from the stochastic level set segmentation of cell images in combination with the trained SVM classifier is more efficient in terms of differentiation accuracy as compared with the original deterministic level set method.

Acquiring and processing phase-contrast microscopy images in wide-field long-term live-cell imaging and high-throughput screening applications is still a challenge as the methodology and algorithms used must be fast, simple to use and tune, and as minimally intrusive as possible. In this paper, we developed a simple and fast algorithm to compute the cell-covered surface (degree of confluence) in phase-contrast microscopy images. This segmentation algorithm is based on a range filter of a specified size, a minimum range threshold, and a minimum object size threshold. These parameters were adjusted in order to maximize the F-measure function on a calibration set of 200 hand-segmented images, and its performance was compared with other algorithms proposed in the literature. A set of one million images from 37 myoblast cell cultures under different conditions were processed to obtain their cell-covered surface against time. The data were used to fit exponential and logistic models, and the analysis showed a linear relationship between the kinetic parameters and passage number and highlighted the effect of culture medium quality on cell growth kinetics. This algorithm could be used for real-time monitoring of cell cultures and for high-throughput screening experiments upon adequate tuning.

Confocal fluorescence microscopy is a broadly used imaging technique that enhances the signal-to-noise ratio by removing out of focal plane fluorescence. Confocal microscopes come with a variety of modifications depending on the particular experimental goals. Microscopes, illumination pathways, and light collection were originally focused upon obtaining the highest resolution image possible, typically on fixed tissue. More recently, live-cell confocal imaging has gained importance. Since measured signals are often rapid or transient, thus requiring higher sampling rates, specializations are included to enhance spatial and temporal resolution while maintaining tissue viability. Thus, a balance between image quality, temporal resolution, and tissue viability is needed. A subtype of confocal imaging, termed swept field confocal (SFC) microscopy, can image live cells at high rates while maintaining confocality. SFC systems can use a pinhole array to obtain high spatial resolution, similar to spinning disc systems. In addition, SFC imaging can achieve faster rates by using a slit to sweep the light across the entire image plane, thus requiring a single scan to generate an image. Coupled to a high-speed charge-coupled device camera and a laser illumination source, images can be obtained at greater than 1,000 frames per second while maintaining confocality.