Photoswitching Reagent for Super-Resolution Fluorescence Microscopy.

Single-molecule localization microscopy (SMLM) has revolutionized optical microscopy by exceeding the diffraction limit and revealing previously unattainable nanoscale details of cellular structures and molecular dynamics. This super-resolution imaging capability relies on fluorophore photoswitching, which is crucial for optimizing the imaging conditions and accurately determining the fluorophore positions. To understand the general on and off photoswitching mechanisms of single dye molecules, various photoswitching reagents were evaluated. Systematic measurement of the single-molecule-level fluorescence on and off rates (kon and koff) in the presence of various photoswitching reagents and theoretical calculation of the structure of the photoswitching reagent-fluorophore pair indicated that the switch-off mechanism is mainly determined by the nucleophilicity of the photoswitching reagent, and the switch-on mechanism is a two-photon-induced dissociation process, which is related to the power of the illuminating laser and bond dissociation energy of this pair. This study contributes to a broader understanding of the molecular photoswitching mechanism in SMLM imaging and provides a basis for designing improved photoswitching reagents with potential applications extending to materials science and chemistry.

Bacteria detection and species identification at the single-cell level using super-resolution fluorescence imaging and AI analysis.

The skin microbiome is thought to play a critical role in maintaining skin health and protecting against infection. While most microorganisms that live on the skin are harmless or even beneficial, some can cause skin infections or other health problems, emphasizing the importance of diagnosis of the composition and diversity of the skin flora. However, conventional diagnostic methods for evaluation of the skin microbiome are not sensitive enough to detect bacteria at low concentrations and suffer from poor specificity, thus limiting early diagnosis of bacterial infections. In this study, we developed novel approaches for bacterial species detection and identification methods with single-cell sensitivity using super-resolution microscopy and AI-based image analysis: a protein quantification-based method and an AI-based bacterial image analysis method. We demonstrate that these methods can differentiate between common bacterial members of the skin flora, including Staphylococcus aureus and Staphylococcus epidermidis, and different ribotypes of Cutibacterium acnes, both in purified bacterial samples and in scaling skin samples. The advantages of these methods, including the lack of time-consuming amplification or purification steps and single-cell level detection sensitivity, allow early diagnosis of bacterial infections, even from bacterial samples at extremely low concentrations, thus showing promise as a next-generation platform for microbiome detection as single-cell diagnostics.

Super-Resolution Fluorescence Imaging for Semiconductor Nanoscale Metrology and Inspection.

The increase in the number and complexity of process levels in semiconductor production has driven the need for the development of new measurement methods that can evaluate semiconductor devices at the critical dimensions of fine patterns and simultaneously inspect nanoscale contaminants or defects. However, conventional optical inspection methods often fail to resolve device patterns or defects at the level of tens of nanometers required for device development owing to their diffraction-limited resolutions. In this study, we used the stochastic optical reconstruction microscopy (STORM) technique to image semiconductor nanostructures with feature sizes as small as 30 nm and detect individual 20 nm-diameter contaminants. STORM imaging of semiconductor nanopatterns is based on the development of a selective labeling method of fluorophores for a negative silicon oxide surface using the charge interaction of positive polyethylenimine molecules. This study demonstrates the potential of STORM for nanoscale metrology and in-line defect inspection of semiconductor integrated circuits.

Polarity Nano-Mapping of Polymer Film Using Spectrally Resolved Super-Resolution Imaging.

With the rapid development of the nanofabrication of polymer materials, the local measurement of the chemical properties of polymer nanostructures has become crucial because they can be highly heterogeneous at the nanoscale. We developed a spectroscopic imaging approach to characterize the nanoscale local polarity of polymer films via spectrally resolved super-resolution microscopy. We demonstrate the capability of the recently developed single-molecule sensing and imaging method to probe the polarity of polymers either inside a polymer matrix or on the external surface of a polymer. The nanoscale polarity sensing capability of our method facilitates the differentiation of various polymer surfaces based on chemical polarities, and it can further differentiate the polarity of functional side chain groups. Moreover, we demonstrate that a two-component polymer mixture can be locally distinguished based on the contrasting polarities of the lateral phase separation, further allowing for the investigation of nanoscale phase separation depending on the composition of the polymer blend film. This approach is anticipated to open the door to further characterizations of various nanocomposite materials.

Development of a New Approach for Low-Laser-Power Super-Resolution Fluorescence Imaging.

The development of super-resolution fluorescence microscopy over the past decade has drastically improved the resolution of light microscopy to ∼10 nm. Stochastic optical reconstruction microscopy (STORM) can be used to achieve subdiffraction-limit resolution by sequentially imaging and localizing individual fluorophores. In principle, the super-resolution of STORM can be obtained by high-accuracy localization of photoswitchable fluorophores, which require fast photoswitching and bright fluorescence intensity from a single emitter. It is known that the switching rate of photoswitchable fluorophores depends on the laser power─a high laser power being required for the enhancement of imaging resolution. However, high laser power is usually harmful to biological specimens and limits the imaging time because of its photobleaching effects and high phototoxicity. In this study, we attempted to overcome this problem by improving the STORM resolution at a lower laser power. Through the quantitative analysis of the photoswitching behavior of single fluorophores under different laser power conditions, we developed a new approach to achieve super-resolution fluorescence images at a laser power 10 times lower than had previously been reported. This approach is expected to play an increasingly significant role in super-resolution imaging of power-sensitive samples.