Photoacoustic Tomography with Temporal Encoding Reconstruction (PATTERN) for cross-modal individual analysis of the whole brain.

Cross-modal analysis of the same whole brain is an ideal strategy to uncover brain function and dysfunction. However, it remains challenging due to the slow speed and destructiveness of traditional whole-brain optical imaging techniques. Here we develop a new platform, termed Photoacoustic Tomography with Temporal Encoding Reconstruction (PATTERN), for non-destructive, high-speed, 3D imaging of ex vivo rodent, ferret, and non-human primate brains. Using an optimally designed image acquisition scheme and an accompanying machine-learning algorithm, PATTERN extracts signals of genetically-encoded probes from photobleaching-based temporal modulation and enables reliable visualization of neural projection in the whole central nervous system with 3D isotropic resolution. Without structural and biological perturbation to the sample, PATTERN can be combined with other whole-brain imaging modalities to acquire the whole-brain image with both high resolution and morphological fidelity. Furthermore, cross-modal transcriptome analysis of an individual brain is achieved by PATTERN imaging. Together, PATTERN provides a compatible and versatile strategy for brain-wide cross-modal analysis at the individual level.

DETECTOR: structural information guided artifact detection for super-resolution fluorescence microscopy image.

Super-resolution fluorescence microscopy, with a spatial resolution beyond the diffraction limit of light, has become an indispensable tool to observe subcellular structures at a nanoscale level. To verify that the super-resolution images reflect the underlying structures of samples, the development of robust and reliable artifact detection methods has received widespread attention. However, the existing artifact detection methods are prone to report false alert artifacts because it relies on absolute intensity mismatch between the wide-field image and resolution rescaled super-resolution image. To solve this problem, we proposed DETECTOR, a structural information-guided artifact detection method for super-resolution images. It detects artifacts by computing the structural dissimilarity between the wide-field image and the resolution rescaled super-resolution image. To focus on structural similarity, we introduce a weight mask to weaken the influence of strong autofluorescence background and proposed a structural similarity index for super-resolution images, named MASK-SSIM. Simulations and experimental results demonstrated that compared with the state-of-the-art methods, DETECTOR has advantages in detecting structural artifacts in super-resolution images. It is especially suitable for wide-field images with strong autofluorescence background and super-resolution images of single molecule localization microscopy (SMLM). DETECTOR has extreme sensitivity to the weak signal region. Moreover, DETECTOR can guide data collection and parameter tuning during image reconstruction.

pHmScarlet is a pH-sensitive red fluorescent protein to monitor exocytosis docking and fusion steps.

pH-sensitive fluorescent proteins (FPs) are highly advantageous for the non-invasive monitoring of exocytosis events. Superecliptic pHluorin (SEP), a green pH-sensitive FP, has been widely used for imaging single-vesicle exocytosis. However, the docking step cannot be visualized using this FP, since the fluorescence signal inside vesicles is too low to be observed during docking process. Among the available red pH-sensitive FPs, none is comparable to SEP for practical applications due to unoptimized pH-sensitivity and fluorescence brightness or severe photochromic behavior. In this study, we engineer a bright and photostable red pH-sensitive FP, named pHmScarlet, which compared to other red FPs has higher pH sensitivity and enables the simultaneous detection of vesicle docking and fusion. pHmScarlet can also be combined with SEP for dual-color imaging of two individual secretory events. Furthermore, although the emission wavelength of pHmScarlet is red-shifted compared to that of SEP, its spatial resolution is high enough to show the ring structure of vesicle fusion pores using Hessian structured illumination microscopy (Hessian-SIM).

Live-SIMBA: an ImageJ plug-in for the universal and accelerated single molecule-guided Bayesian localization super resolution microscopy (SIMBA) method.

Live-cell super-resolution fluorescence microscopy techniques allow biologists to observe subcellular structures, interactions and dynamics at the nanoscale level. Among of them, single molecule-guided Bayesian localization super resolution microscopy (SIMBA) and its derivatives produce an appropriate 50 nm spatial resolution and a 0.1-2s temporal resolution in living cells with simple off-the-shelf total internal reflection fluorescence (TIRF) equipment. However, SIMBA and its derivatives are limited by the requirement for dual-channel dataset or single-channel dataset with special design, the time-consuming calculation for extended field of view and the lack of real-time visualization tool. Here, we propose a universal and accelerated SIMBA ImageJ plug-in, Live-SIMBA, for time-series analysis in living cells. Live-SIMBA circumvents the requirement of dual-channel dataset using intensity-based sampling algorithm and improves the computing speed using multi-core parallel computing technique. Live-SIMBA also better resolves the weak signals inside the specimens with adjustable background estimation and distance-threshold filter. With improved fidelity on reconstructed structures, greatly accelerated computation, and real-time visualization, Live-SIMBA demonstrates its extended capabilities in live-cell super-resolution imaging.

mEosEM withstands osmium staining and Epon embedding for super-resolution CLEM.

Super-resolution correlative light and electron microscopy (SR-CLEM) is a powerful approach for imaging specific molecules at the nanoscale in the context of the cellular ultrastructure. Epon epoxy resin embedding offers advantages for SR-CLEM, including ultrastructural preservation and high quality sectioning. However, Epon embedding eliminates fluorescence from most fluorescent proteins. We describe a photocontrollable fluorescent protein, mEosEM, that can survive Epon embedding after osmium tetroxide (OsO4) treatment for improved SR-CLEM.

Fast Super-Resolution Imaging Technique and Immediate Early Nanostructure Capturing by a Photoconvertible Fluorescent Protein.

Low temporal resolution and limited photocontrollable fluorescent protein probes have restricted the widespread application of single-molecule localization microscopy (SMLM). In the current study, we developed a new photoconvertible fluorescent protein (PCFP), pcStar, and quick single molecule-guided Bayesian localization microscopy (Quick-SIMBA). The combination of pcStar and Quick-SIMBA achieved the highest temporal resolution (0.1-0.25 s) with large field-of-view (76 × 9.4 µm2 -76 × 31.4 µm2) among the SMLM methods, which enabled the dynamic movements of the endoplasmic reticulum dense tubular matrix to be resolved. Moreover, pcStar extended the application of SMLM to imaging the immediate early nanostructures in Drosophila embryos and revealed a specific "parallel three-pillar" structure in the neuronal-glial cell junction, helping to elucidate glial cell "locking" and support of neurons during Drosophila embryogenesis.

New observations in neuroscience using superresolution microscopy.

Superresolution microscopy (SM) techniques are among the revolutionary methods for molecular and cellular observations in the 21st century. SM techniques overcome optical limitations, and several new observations using SM lead us to expect these techniques to have a large impact on neuroscience in the near future. Several types of SM have been developed, including structured illumination microscopy (SIM), stimulated emission depletion microscopy (STED), and photoactivated localization microscopy (PALM)/stochastic optical reconstruction microscopy (STORM), each with special features. In this Minisymposium, experts in these different types of SM discuss the new structural and functional information about specific important molecules in neuroscience that has been gained with SM. Using these techniques, we have revealed novel mechanisms of endocytosis in nerve growth, fusion pore dynamics, and described quantitative new properties of excitatory and inhibitory synapses. Additional powerful techniques, including single molecule-guided Bayesian localization SM (SIMBA) and expansion microscopy (ExM), alone or combined with super-resolution observation, are also introduced in this session.

Hessian single-molecule localization microscopy using sCMOS camera.

Single-molecule localization microscopy (SMLM) has the highest spatial resolution among the existing super-resolution imaging techniques, but its temporal resolution needs further improvement. An sCMOS camera can effectively increase the imaging rate due to its large field of view and fast imaging speed. Using an sCMOS camera for SMLM imaging can significantly improve the imaging time resolution, but the unique single-pixel-dependent readout noise of sCMOS cameras severely limits their application in SMLM imaging. This paper develops a Hessian-based SMLM (Hessian-SMLM) method that can correct the variance, gain, and offset of a single pixel of a camera and effectively eliminate the pixel-dependent readout noise of sCMOS cameras, especially when the signal-to-noise ratio is low. Using Hessian-SMLM to image mEos3.2-labeled actin was able to significantly reduce the artifacts due to camera noise.

Theoretical study on the bactericidal nature of nanopatterned surfaces.

A natural biomaterial has been discovered with bactericidal activities, which is mainly attributed to its nanopatterned surface structure. The surface of Clanger cicada (Psaltoda claripennis) wings has been identified as a natural bactericidal material, which has lead to the emergence of research on the development of novel antibacterial surfaces. From the interactions between bacterial biofilms and nanopatterned surface structures, a new mechanical model is proposed that investigates the rupture of bacterial cells within the framework of the "stretching" theory. The effect of surface nanoroughness on the survival of bacterial cells is evaluated by determining the stretching ability of their cell walls. The results, calculated using Gram-positive and Gram-negative bacteria as examples, show a correlation between the stretching of the cell wall and the geometric parameters of the surface structures. The theoretical results indicate that for a given cell rigidity, the bactericidal nature of the surface is determined by the geometric parameters of the surface structures.