In fluctuation-based optical nanoscopy, investigating high-density labeled subcellular structures with high fidelity has been a significant challenge. In this study, based on super-resolution radial fluctuation (SRRF) microscopy, the joint tagging (JT) strategy is employed to enable fast high-density nanoscopic imaging and tracking. In fixed cell experiment, multiple types of quantum dots with distinguishable fluorescence spectra are jointly tagged to subcellular microtubules. In each spectral channel, the decrease in labeling density guarantees the high-fidelity super-resolution reconstruction using SRRF microscopy. Subsequently, the combination of all spectral channels achieves high-density super-resolution imaging of subcellular microtubules with a resolution of similar to 62 nm using JT assisted SRRF technique. In the live-cell experiment, 3-channel JT is utilized to track the dynamic motions of high-density toxin-induced lipid clusters for 1 minute, achieving the simultaneous tracking of many individual toxin-induced lipid clusters spatially distributed significantly below the optical diffraction limit in living cells.
To investigate three-dimensional (3D) genome organization in prokaryotic and eukaryotic cells, three main strategies are employed, namely nuclear proximity ligation-based methods, imaging tools (such as fluorescence in situ hybridization (FISH) and its derivatives), and computational/visualization methods. Proximity ligation-based methods are based on digestion and re-ligation of physically proximal cross-linked chromatin fragments accompanied by massively parallel DNA sequencing to measure the relative spatial proximity between genomic loci. Imaging tools enable direct visualization and quantification of spatial distances between genomic loci, and advanced implementation of (super-resolution) microscopy helps to significantly improve the resolution of images. Computational methods are used to map global 3D genome structures at various scales driven by experimental data, and visualization methods are used to visualize genome 3D structures in virtual 3D space-based on algorithms. In this review, we focus on the introduction of novel imaging and visualization methods to study 3D genomes. First, we introduce the progress made recently in 3D genome imaging in both fixed cell and live cells based on long-probe labeling, short-probe labeling, RNA FISH, and the CRISPR system. As the fluorescence-capturing capability of a particular microscope is very important for the sensitivity of bioimaging experiments, we also introduce two novel super-resolution microscopy methods, SDOM and low-power super-resolution STED, which have potential for time-lapse super-resolution live-cell imaging of chromatin. Finally, we review some software tools developed recently to visualize proximity ligation-based data. The imaging and visualization methods are complementary to each other, and all three strategies are not mutually exclusive. These methods provide powerful tools to explore the mechanisms of gene regulation and transcription in cell nuclei.
Raman scattering provides key information of the biological environment through light-molecule interaction; yet, it is generally very weak to detect. Surface-enhanced Raman scattering (SERS) can boost the Raman signal by several orders-of-magnitude, and thus is highly attractive for biochemical sensing. However, conventional super-resolution imaging of SERS is challenging as the Raman signal is generated from the virtual state which cannot be easily modulated as fluorescence. Here, we demonstrate super-resolution microscopy with a surface-enhanced Raman scattering (SERS) signal, with a resolution of approximately 50 nm. By modulating the polarization angle of the excitation laser, the SERS nanorods display a dramatic anisotropy effect, allowing nanoscale orientation determination of multiple dipoles with dense concentration. Furthermore, a well-established defocused analysis was performed to reconfirm the orientation accuracy of super-resolved SERS nanorods. Sub-diffraction resolution was achieved in the imaging of SERS nanorod labeled vesicles in fixed macrophages. Finally, we demonstrate dynamic SERS nanorod tracking in living macrophages, which provides not only the particle trajectory with high spatial resolution but also the rotational changes at the nanometer scale. This pioneering study paves a new way for subcellular super-resolution imaging with the SERS effect, shedding light on wider biological applications.
To increase the temporal resolution and maximal imaging time of super-resolution (SR) microscopy, we have developed a deconvolution algorithm for structured illumination microscopy based on Hessian matrixes (Hessian-SIM). It uses the continuity of biological structures in multiple dimensions as a priori knowledge to guide image reconstruction and attains artifact-minimized SR images with less than 10% of the photon dose used by conventional SIM while substantially outperforming current algorithms at low signal intensities. Hessian-SIM enables rapid imaging of moving vesicles or loops in the endoplasmic reticulum without motion artifacts and with a spatiotemporal resolution of 88 nm and 188 Hz. Its high sensitivity allows the use of sub-millisecond excitation pulses followed by dark recovery times to reduce photobleaching of fluorescent proteins, enabling hour-long time-lapse SR imaging of actin filaments in live cells. Finally, we observed the structural dynamics of mitochondrial cristae and structures that, to our knowledge, have not been observed previously, such as enlarged fusion pores during vesicle exocytosis.
We review the use of luminescent nanoparticles in super-resolution imaging and single-molecule tracking, and showcase novel approaches to super-resolution imaging that leverage the brightness, stability, and unique optical-switching properties of these nanoparticles. We also discuss the challenges associated with their use in biological systems, including intracellular delivery and molecular targeting. In doing so, we hope to provide practical guidance for biologists and continue to bridge the fields of super-resolution imaging and nanoparticle engineering to support their mutual advancement.
Fluorescence polarization is related to the dipole orientation of chromophores, making fluorescence polarization microscopy possible to reveal structures and functions of tagged cellular organelles and biological macromolecules. Several recent super resolution techniques have been applied to fluorescence polarization microscopy, achieving dipole measurement at nanoscale. In this review, we summarize both diffraction limited and super resolution fluorescence polarization microscopy techniques, as well as their applications in biological imaging.
Multiphoton fluorescence microscopy (MPM), using near infrared excitation light, provides increased penetration depth, decreased detection background, and reduced phototoxicity. Using stimulated emission depletion (STED) approach, MPM can bypass the diffraction limitation, but it requires both spatial alignment and temporal synchronization of high power (femtosecond) lasers, which is limited by the inefficiency of the probes. Here, we report that upconversion nanoparticles (UCNPs) can unlock a new mode of near-infrared emission saturation (NIRES) nanoscopy for deep tissue super-resolution imaging with excitation intensity several orders of magnitude lower than that required by conventional MPM dyes. Using a doughnut beam excitation from a 980 nm diode laser and detecting at 800 nm, we achieve a resolution of sub 50 nm, 1/20th of the excitation wavelength, in imaging of single UCNP through 93 mu m thick liver tissue. This method offers a simple solution for deep tissue super resolution imaging and single molecule tracking.
The broad applicability of super-resolution microscopy has been widely demonstrated in various areas and disciplines. The optimization and improvement of algorithms used in super-resolution microscopy are of great importance for achieving optimal quality of super-resolution imaging. In this review, we comprehensively discuss the computational methods in different types of super-resolution microscopy, including deconvolution microscopy, polarization-based super-resolution microscopy, structured illumination microscopy, image scanning microscopy, super-resolution optical fluctuation imaging microscopy, single-molecule localization microscopy, Bayesian super-resolution microscopy, stimulated emission depletion microscopy, and translation microscopy. The development of novel computational methods would greatly benefit super-resolution microscopy and lead to better resolution, improved accuracy, and faster image processing.