Single-molecule-localization-microscopy (SMLM) enables superresolution imaging of biological samples down to ~ 10-20 nm and in single molecule detail. However, common SMLM reconstruction largely disregards information embedded in the entire intensity trajectories of individual emitters. Here, we develop and demonstrate an approach, termed time-correlated-SMLM (tcSMLM), that uses such information for enhancing SMLM reconstruction. Specifically, tcSMLM is shown to increase the spatial resolution and fidelity of SMLM reconstruction of both simulated and experimental data; esp. upon acquisition under stringent conditions of low SNR, high acquisition rate and high density of emitters. We further provide detailed guidelines and optimization procedures for effectively applying tcSMLM to data of choice. Importantly, our approach can be readily added in tandem to multiple SMLM and related superresolution reconstruction algorithms. Thus, we expect that our approach will become an effective and readily accessible tool for enhancing SMLM and superresolution imaging.
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http://dx.doi.org/10.1038/s41598-020-72812-y | DOI Listing |
Commun Biol
December 2024
Department of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore, 560012, India.
Single-molecule localization microscopy (SMLM) can decipher fine details that are otherwise impossible using diffraction-limited microscopy. Often, the reconstructed super-resolved images suffer from noise, strong background and are prone to false detections that may impact quantitative imaging. To overcome these limitations, we propose a technique (corrSMLM) that recognizes and detects fortunate molecules (molecules with long blinking cycles) from the recorded data.
View Article and Find Full Text PDFBiomed Opt Express
November 2024
Academy for Engineering and Technology, Fudan University, Shanghai 200433, China.
Super-solution fluorescence microscopy, such as single-molecule localization microscopy (SMLM), is effective in observing subcellular structures and achieving excellent enhancement in spatial resolution in contrast to traditional fluorescence microscopy. Recently, deep learning has demonstrated excellent performance in SMLM in solving the trade-offs between spatiotemporal resolution, phototoxicity, and signal intensity. However, most of these researches rely on sufficient and high-quality datasets.
View Article and Find Full Text PDFAnal Chem
October 2024
Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
The current limitations of single-molecule localization microscopy (SMLM) in deep tissue imaging, primarily due to depth-dependent aberrations caused by refractive index (RI) mismatch, present a significant challenge in achieving high-resolution images at greater depths. To extend the imaging depth, we optimized the imaging buffer of SMLM with the RI matched to that of the objective immersion medium and systematically evaluated five different RI-matched buffers, focusing on their impact on the blinking behavior of red-absorbing dyes and the quality of reconstructed super-resolution images. Particularly, we found that clear unobstructed brain imaging cocktails-based imaging buffer could match the RI of oil and was able to clear the tissue samples.
View Article and Find Full Text PDFCells
August 2024
Rudolf Schönheimer Institute of Biochemistry, Division of General Biochemistry, Medical Faculty, Leipzig University, D-04103 Leipzig, Germany.
Super-resolution single-molecule localization microscopy (SMLM) of presynaptic active zones (AZs) and postsynaptic densities contributed to the observation of protein nanoclusters that are involved in defining functional characteristics and in plasticity of synaptic connections. Among SMLM techniques, stochastic optical reconstruction microscopy (STORM) depends on organic fluorophores that exert high brightness and reliable photoswitching. While multicolor imaging is highly desirable, the requirements necessary for high-quality STORM make it challenging to identify combinations of equally performing, spectrally separated dyes.
View Article and Find Full Text PDFACS Nano
August 2024
Department of Electrical Engineering, National Taiwan University, Taipei 10617, Taiwan.
Understanding cellular functions, particularly in their intricate complexity, can greatly benefit from the spatial mapping of diverse molecules through multitarget single-molecule localization microscopy (SMLM). Existing methodologies, primarily restricting the encoding dimensions to color and lifetime or requiring cyclic staining, often involve broad chromatic detection, specialized optical configurations, or sophisticated labeling techniques. Here, we propose a simple approach called buffer-exchange stochastic optical reconstruction microscopy (beSTORM), which introduces an additional dimension to differentiate between single molecules irrespective of their spectral properties.
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