Three-dimensional single molecule localization close to the coverslip: a comparison of methods exploiting supercritical angle fluorescence

Molecular Level Super-Resolution Fluorescence Imaging

Over the last 30 years, fluorescence microscopy, renowned for its sensitivity and specificity, has undergone a revolution in resolving ever-smaller details. This advancement began with stimulated emission depletion (STED) microscopy and progressed with techniques such as photoactivatable localization microscopy and stochastic optical reconstruction microscopy (STORM). Single-molecule localization microscopy (SMLM), which encompasses methods like direct STORM, has significantly enhanced image resolution. Even though its speed is slower than that of STED, SMLM achieves higher resolution by overcoming photobleaching limitations, particularly through DNA point accumulation for imaging in nanoscale topography (DNA-PAINT), which continuously renews fluorescent labels. Additionally, cryo-fluorescence microscopy and advanced techniques like minimal photon fluxes imaging (MINFLUX) have pushed the boundaries toward molecular resolution SMLM. This review discusses the latest developments in SMLM, highlighting methods like resolution enhancement by sequential imaging (RESI) and PAINT-MINFLUX and exploring axial localization techniques such as supercritical angle fluorescence and metal-induced energy transfer. These advancements promise to revolutionize fluorescence microscopy, providing resolution comparable to that of electron microscopy.

Joint estimation of point spread function and molecule positions in SMLM informed from multiple planes

The advent of single molecule localization microscopy (SMLM) has transformed our capacity to investigate biological structures at the nanoscale. While the research focus has long been on improving localization precision, systematic errors caused by optical aberrations are often overlooked. In the case of 3D SMLM, such errors have the potential to significantly impair the quality of the resulting images. In this paper, we present an imaging and data processing approach that jointly estimates both, molecule positions and optical aberrations in SMLM. Therefore, the method minimizes systematic errors in SMLM reconstructions without the necessity of additional experimental calibration steps, such as the recording of fluorescent bead z-stacks. We investigate the reliability of this approach, especially in situations where the joint retrieval can be expected to be ill-posed, i.e., whenever the sample is "flat" and provides little diversity among the captured single molecule images. To enhance the reliability of the inverse problem solution, we suggest utilizing small SMLM data sets acquired at one or more slightly defocused "auxiliary" planes. We investigate the effectiveness of our approach through numerical simulations and imaging experiments of a calibration probe and nuclear pore complexes. Our method is simple and integrates seamlessly into existing SMLM setups without necessitating modifications or added complexity to the system.

Quantitatively mapping local quality of super-resolution microscopy by rolling Fourier ring correlation

In fluorescence microscopy, computational algorithms have been developed to suppress noise, enhance contrast, and even enable super-resolution (SR). However, the local quality of the images may vary on multiple scales, and these differences can lead to misconceptions. Current mapping methods fail to finely estimate the local quality, challenging to associate the SR scale content. Here, we develop a rolling Fourier ring correlation (rFRC) method to evaluate the reconstruction uncertainties down to SR scale. To visually pinpoint regions with low reliability, a filtered rFRC is combined with a modified resolution-scaled error map (RSM), offering a comprehensive and concise map for further examination. We demonstrate their performances on various SR imaging modalities, and the resulting quantitative maps enable better SR images integrated from different reconstructions. Overall, we expect that our framework can become a routinely used tool for biologists in assessing their image datasets in general and inspire further advances in the rapidly developing field of computational imaging.

Organic fluorescent probes for live-cell super-resolution imaging

The development of super-resolution technology has made it possible to investigate the ultrastructure of intracellular organelles by fluorescence microscopy, which has greatly facilitated the development of life sciences and biomedicine. To realize super-resolution imaging of living cells, both advanced imaging systems and excellent fluorescent probes are required. Traditional fluorescent probes have good availability, but that is not the case for probes for live-cell super-resolution imaging. In this review, we first introduce the principles of various super-resolution technologies and their probe requirements, then summarize the existing designs and delivery strategies of super-resolution probes for live-cell imaging, and finally provide a brief conclusion and overview of the future.

Robust and bias-free localization of individual fixed dipole emitters achieving the Cramér Rao bound for applications in cryo-single molecule localization microscopy

Single molecule localization microscopy (SMLM) has the potential to resolve structural details of biological samples at the nanometer length scale. Compared to room temperature experiments, SMLM performed under cryogenic temperature achieves higher photon yields and, hence, higher localization precision. However, to fully exploit the resolution it is crucial to account for the anisotropic emission characteristics of fluorescence dipole emitters with fixed orientation. In case of slight residual defocus, localization estimates may well be biased by tens of nanometers. We show here that astigmatic imaging in combination with information about the dipole orientation allows to extract the position of the dipole emitters without localization bias and down to a precision of 1 nm, thereby reaching the corresponding Cramér Rao bound. The approach is showcased with simulated data for various dipole orientations, and parameter settings realistic for real life experiments.

Phase optimization algorithm for 3D particle localization with large axial depth

We propose an optimization algorithm based on Fresnel approximation (FA) imaging to optimize an extended-axial-depth point spread function (PSF) for 3D particle localization. The transfer function efficiency of the PSF is improved by repeatedly imposing constraints in the object plane, the spatial domain, and the Fourier domain. During the iterative calculation, the effective photon number or Cramer-Rao lower bound is used as the termination condition of the iteration. The algorithm allows flexible adjustment of the peak intensity ratio of the two main lobes. Moreover, the transfer function efficiency can be balanced by increasing the weight of the modulation function of the expected PSF at each axial position. The twin-Airy (TA) PSF optimized by the FA optimization algorithm does not require complex post-processing, whereas post-processing is an essential step for the unoptimized TA-PSF. The optimization algorithm is significant for extended-axial-depth PSFs used for 3D particle localization, as it improves localization precision and temporal resolution.