VLUME: 3D virtual reality for single-molecule localization microscopy.
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ABSTRACT:
SUBMITTER: Spark A
PROVIDER: S-EPMC7612967 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Single-molecule localization microscopy (SMLM) describes a family of powerful imaging techniques that dramatically improve spatial resolution over standard, diffraction-limited microscopy techniques and can image biological structures at the molecular scale. In SMLM, individual fluorescent molecules are computationally localized from diffraction-limited image sequences and the localizations are used to generate a super-resolution image or a time course of super-resolution images, or to define molecular trajectories. In this Primer, we introduce the basic principles of SMLM techniques before describing the main experimental considerations when performing SMLM, including fluorescent labelling, sample preparation, hardware requirements and image acquisition in fixed and live cells. We then explain how low-resolution image sequences are computationally processed to reconstruct super-resolution images and/or extract quantitative information, and highlight a selection of biological discoveries enabled by SMLM and closely related methods. We discuss some of the main limitations and potential artefacts of SMLM, as well as ways to alleviate them. Finally, we present an outlook on advanced techniques and promising new developments in the fast-evolving field of SMLM. We hope that this Primer will be a useful reference for both newcomers and practitioners of SMLM.
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Project description:The past decade has witnessed an explosion in the use of super-resolution fluorescence microscopy methods in biology and other fields. Single-molecule localization microscopy (SMLM) is one of the most widespread of these methods and owes its success in large part to the ability to control the on-off state of fluorophores through various chemical, photochemical, or binding-unbinding mechanisms. We provide here a comprehensive overview of switchable fluorophores in SMLM including a detailed review of all major classes of SMLM fluorophores, and we also address strategies for labeling specimens, considerations for multichannel and live-cell imaging, potential pitfalls, and areas for future development.
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Project description:We present a statistical framework to model the spatial distribution of molecules based on a single-molecule localization microscopy (SMLM) dataset. The latter consists of a collection of spatial coordinates and their associated uncertainties. We describe iterative parameter-estimation algorithms based on this framework, as well as a sampling algorithm to numerically evaluate the complete posterior distribution. We demonstrate that the inverse computation can be viewed as a type of image restoration process similar to the classical image deconvolution methods, except that it is performed on SMLM images. We further discuss an application of our statistical framework in the task of particle fusion using SMLM data. We show that the fusion algorithm based on our model outperforms the current state-of-the-art in terms of both accuracy and computational cost.
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Project description:Spectroscopic single-molecule localization microscopy (sSMLM) captures the full emission spectra of individual molecules while simultaneously localizing their spatial locations at a precision greatly exceeding the optical diffraction limit. To achieve this, sSMLM uses a dispersive optical component to separate the emitted photons into dedicated spatial and spectral imaging channels for simultaneous acquisition. While adding a cylindrical lens in the spatial imaging channel enabled three-dimensional (3D) imaging in sSMLM, the inherent astigmatism leads to technical hurdles in spectral calibration and nonuniform lateral resolution at different depths. We found that implementing the biplane method based on the already established spatial and spectral imaging channels offers a much more attractive solution for 3D sSMLM. It allows for more efficient use of the limited photon budget and provides homogeneous lateral resolution compared with the astigmatism-based method using a cylindrical lens. Here we report 3D biplane sSMLM and demonstrate its multi-color 3D imaging capability by imaging microtubules and mitochondria in fixed COS-7 cells immunostained with Alexa Fluor 647 and CF 660C dyes, respectively. We showed a lateral localization precision of 20 nm at an average photon count of 550, a spectral precision of 4 nm at an average photon count of 1250, and an axial localization resolution of 50 nm.
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Project description:Single molecule localization microscopy (SMLM) is on its way to become a mainstream imaging technique in the life sciences. However, analysis of SMLM data is biased by user provided subjective parameters required by the analysis software. To remove this human bias we introduce here the Auto-Bayes method that executes the analysis of SMLM data automatically. We demonstrate the success of the method using the photoelectron count of an emitter as selection characteristic. Moreover, the principle can be used for any characteristic that is bimodally distributed with respect to false and true emitters. The method also allows generation of an emitter reliability map for estimating quality of SMLM-based structures. The potential of the Auto-Bayes method is shown by the fact that our first basic implementation was able to outperform all software packages that were compared in the ISBI online challenge in 2015, with respect to molecule detection (Jaccard index).
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