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Mitochondrial morphology provides unique insights into their integrity and function. Among fluorescence microscopy techniques, 3D super-resolution microscopy uniquely enables the analysis of mitochondrial morphological features individually. However, there is a lack of tools to extract morphological parameters from super-resolution images of mitochondria. We report a quantitative method to extract mitochondrial morphological metrics, including volume, aspect ratio, and local protein density, from 3D single-molecule localization microscopy images, with single-mitochondrion sensitivity. We validated our approach using simulated ground-truth SMLM images of mitochondria. We further tested our morphological analysis on mitochondria that have been altered functionally and morphologically in controlled manners. This work sets the stage to quantitatively analyze mitochondrial morphological alterations associated with disease progression on an individual basis.

We developed a multiscale optical imaging workflow, integrating and correlating visible-light optical coherence tomography, confocal laser scanning microscopy, and single-molecule localization microscopy to investigate mouse cornea damage from thein-vivotissue level to the nanoscopic single-molecule level. We used electron microscopy to validate the imaged nanoscopic structures. We imaged wild-type mice and mice with acute ocular hypertension and examined the effects of Rho-kinase inhibitor application. We defined four types of intercellular tight junction structures as healthy, compact, partially-distorted, and fully-distorted types by labeling the zonula occludens-1 protein in the corneal endothelial cell layer. We correlated the statistics of the four types of tight junction structures with cornea thickness and intraocular pressure. We found that the population of fully-distorted tight junctions correlated well with the level of corneal edema, and applying Rho-kinase inhibitor reduced the population of fully-distorted tight junctions under acute ocular hypertension. Together, these data point to the utility of multiscale optical imaging in revealing fundamental biology relevant to disease and therapeutics.

Spectroscopic single-molecule localization microscopy (sSMLM) generates super-resolution images of single molecules while simultaneously capturing the spectra of their fluorescence emissions. However, sSMLM splits photons from single-molecule emissions into a spatial channel and a spectral channel, reducing both channels’ precisions. It is also challenging in transmission grating-based sSMLM to achieve a large field-of-view (FOV) and avoid overlap between the spatial and spectral channels. The challenge in FOV has further significance in single-molecule tracking applications. In this work, we analyzed the correlation between the spatial and spectral channels in sSMLM to improve its spatial precision, and we developed a split-mirror assembly to enlarge its FOV. We demonstrate the benefits of these improvements by tracking quantum dots. We also show that we can reduce particle-identification ambiguity by tagging each particle with its unique spectral characteristics.

Spectroscopic single-molecule localization microscopy (sSMLM) simultaneously provides spatial localization and spectral information of individual single-molecules emission, offering multicolor super-resolution imaging of multiple molecules in a single sample with the nanoscopic resolution. However, this technique is limited by the requirements of acquiring a large number of frames to reconstruct a super-resolution image. In addition, multicolor sSMLM imaging suffers from spectral cross-talk while using multiple dyes with relatively broad spectral bands that produce cross-color contamination. Here, we present a computational strategy to accelerate multicolor sSMLM imaging. Our method uses deep convolution neural networks to reconstruct high-density multicolor super-resolution images from low-density, contaminated multicolor images rendered using sSMLM datasets with much fewer frames, without compromising spatial resolution. High-quality, super-resolution images are reconstructed using up to 8-fold fewer frames than usually needed. Thus, our technique generates multicolor super-resolution images within a much shorter time, without any changes in the existing sSMLM hardware system. Two-color and three-color sSMLM experimental results demonstrate superior reconstructions of tubulin/mitochondria, peroxisome/mitochondria, and tubulin/mitochondria/peroxisome in fixed COS-7 and U2-OS cells with a significant reduction in acquisition time.