Dataset Information

Correlation analysis framework for localization-based superresolution microscopy.

ABSTRACT: Superresolution images reconstructed from single-molecule localizations can reveal cellular structures close to the macromolecular scale and are now being used routinely in many biomedical research applications. However, because of their coordinate-based representation, a widely applicable and unified analysis platform that can extract a quantitative description and biophysical parameters from these images is yet to be established. Here, we propose a conceptual framework for correlation analysis of coordinate-based superresolution images using distance histograms. We demonstrate the application of this concept in multiple scenarios, including image alignment, tracking of diffusing molecules, as well as for quantification of colocalization, showing its superior performance over existing approaches.

SUBMITTER: Schnitzbauer J

PROVIDER: S-EPMC5879654 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Correlation analysis framework for localization-based superresolution microscopy.

Schnitzbauer Joerg J Wang Yina Y Zhao Shijie S Bakalar Matthew M Nuwal Tulip T Chen Baohui B Huang Bo B

Proceedings of the National Academy of Sciences of the United States of America 20180312 13

Superresolution images reconstructed from single-molecule localizations can reveal cellular structures close to the macromolecular scale and are now being used routinely in many biomedical research applications. However, because of their coordinate-based representation, a widely applicable and unified analysis platform that can extract a quantitative description and biophysical parameters from these images is yet to be established. Here, we propose a conceptual framework for correlation analysis ...[more]

PMID: 29531072

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Project description:Fluorescent proteins are used extensively for biological imaging applications; photoactivatable and photoconvertible fluorescent proteins (PAFPs) are used widely in superresolution localization microscopy methods such as fluorescence photoactivation localization microscopy and photoactivated localization microscopy. However, their optimal use depends on knowledge of not only their bulk fluorescence properties, but also their photophysical properties at the single molecule level. We have used fluorescence correlation spectroscopy and cross-correlation spectroscopy to quantify the diffusion, photobleaching, fluorescence intermittency, and photoconversion dynamics of Dendra2, a well-known PAFP used in localization microscopy. Numerous dark states of Dendra2 are observed both in inactive (green fluorescent) and active (orange fluorescent) forms; the interconversion rates are both light- and pH-dependent, as observed for other PAFPs. The dark states limit the detected count rate per molecule, which is a crucial parameter for localization microscopy. We then developed, to our knowledge, a new mathematical estimate for the resolution in localization microscopy as a function of the measured photophysical parameters of the probe such as photobleaching quantum yield, count rate per molecule, and intensity of saturation. The model was used to predict the dependence of resolution on acquisition parameters such as illumination intensity and time per frame, demonstrating an optimal set of acquisition parameters for a given probe for a variety of measures of resolution. The best possible resolution was then compared for Dendra2 and other widely used probes, including Alexa dyes and quantum dots. This work establishes a framework for determination of the best possible resolution using a localization microscope to image a particular fluorophore, and suggests that development of probes for use in superresolution localization microscopy must consider the count rate per molecule, the saturation intensity, the photobleaching yield, and, crucially, management of bright/dark state transitions, to optimize image resolution.

Project description:To be able to resolve molecular-clusters it is crucial to access vital information (such as, molecule density, cluster-size, and others) that are key in understanding disease progression and the underlying mechanism. Traditional single-molecule localization microscopy (SMLM) techniques use molecules of variable sizes (as determined by its localization precision (LP)) to reconstruct a super-resolution map. This results in an image with overlapping and superimposing PSFs (due to a wide size-spectrum of single-molecules) that undermine image resolution. Ideally, it should be possible to identify the brightest molecules (also termed as the fortunate molecules) to reconstruct ultra-superresolution map, provided sufficient statistics is available from the recorded data. Probabilistic Optically-Selective Single-molecule Imaging Based Localization Encoded (POSSIBLE) microscopy explores this possibility by introducing a narrow probability size-distribution of single-molecules (narrow size-spectrum about a predefined mean-size). The reconstruction begins by presetting the mean and variance of the narrow distribution function (Gaussian function). Subsequently, the dataset is processed and single-molecules are filtered by the Gaussian function to remove unfortunate molecules. The fortunate molecules thus retained are then mapped to reconstruct an ultra-superresolution map. In-principle, the POSSIBLE microscopy technique is capable of infinite resolution (resolution of the order of actual single-molecule size) provided enough fortunate molecules are experimentally detected. In short, bright molecules (with large emissivity) holds the key. Here, we demonstrate the POSSIBLE microscopy technique and reconstruct single-molecule images with an average PSF sizes of σ ± Δσ = 15 ± 10 nm, 30 ± 2 nm & 50 ± 2 nm. Results show better-resolved Dendra2-HA clusters with large cluster-density in transfected NIH3T3 fibroblast cells as compared to the traditional SMLM techniques. Cluster analysis indicates densely-packed HA molecules, HA-HA interaction, and a surge in the number of HA molecules per cluster post 24 Hrs of transfection. The study using POSSIBLE microscopy introduces new insights in influenza biology. We anticipate exciting applications in the multidisciplinary field of disease biology, oncology, and biomedical imaging.

Dataset Information

Correlation analysis framework for localization-based superresolution microscopy.

Publications

Correlation analysis framework for localization-based superresolution microscopy.

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