Quantum Dots for Improved Single-Molecule Localization Microscopy.
Ontology highlight
ABSTRACT:
SUBMITTER: Urban JM
PROVIDER: S-EPMC8080873 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Single-molecule localization microscopy (SMLM) has allowed the observation of various molecular structures in cells beyond the diffraction limit using organic dyes. In principle, the SMLM resolution depends on the precision of photoswitching fluorophore localization, which is inversely correlated with the square root of the number of photons released from the individual fluorophores. Thus, increasing the photon number by using highly bright fluorophores, such as quantum dots (QDs), can theoretically fundamentally overcome the current resolution limit of SMLM. However, the use of QDs in SMLM has been challenging because QDs have no photoswitching property, which is essential for SMLM, and they exhibit nonspecificity and multivalency, which complicate their use in fluorescence imaging. Here, we present a method to utilize QDs in SMLM to surpass the resolution limit of the current SMLM utilizing organic dyes. We confer monovalency, specificity, and photoswitchability on QDs by steric exclusion via passivation and ligand exchange with ptDNA, PEG, and casein as well as by DNA point accumulation for imaging in nanoscale topography (DNA-PAINT) via automatic thermally driven hybridization between target-bound docking and dye-bound complementary imager strands. QDs are made monovalent and photoswitchable to enable SMLM and show substantially better photophysical properties than Cy3, with higher fluorescence intensity and an improved resolution factor. QD-PAINT displays improved spatial resolution with a narrower full width at half maximum (FWHM) than DNA-PAINT with Cy3. In summary, QD-PAINT shows great promise as a next-generation SMLM method for overcoming the limited resolution of the current SMLM.
| S-EPMC8080769 | biostudies-literature
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.
| S-EPMC9160414 | biostudies-literature
Project description:Semiconductor quantum dots (QDs) have proven to be superior probes for single-molecule imaging compared to organic or genetically encoded fluorophores, but they are limited by difficulties in protein targeting, their larger size, and on-off blinking. Here, we report compact aqueous CdSe/CdS QDs with significantly improved bioconjugation efficiency and superior single-molecule optical properties. We have synthesized covalent protein labeling ligands (i.e., SNAP tags) that are optimized for nanoparticle use, and QDs functionalized with these ligands label SNAP-tagged proteins ?10-fold more efficiently than existing SNAP ligands. Single-molecule analysis of these QDs shows 99% of time spent in the fluorescent on-state, ?4-fold higher quantum efficiency than standard CdSe/ZnS QDs, and 350 million photons detected before photobleaching. Bright signals of these QDs enable us to track the stepping movement of a kinesin motor in vitro, and the improved labeling efficiency enables tracking of single kinesins in live cells.
| S-EPMC5891212 | biostudies-other
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.
| S-EPMC6476321 | biostudies-literature
Project description:Spectroscopic single-molecule localization microscopy (sSMLM) was used to achieve simultaneous imaging and spectral analysis of single molecules for the first time. Current sSMLM fundamentally suffers from a reduced photon budget because the photons from individual stochastic emissions are divided into spatial and spectral channels. Therefore, both spatial localization and spectral analysis only use a portion of the total photons, leading to reduced precisions in both channels. To improve the spatial and spectral precisions, we present symmetrically dispersed sSMLM, or SDsSMLM, to fully utilize all photons from individual stochastic emissions in both spatial and spectral channels. SDsSMLM achieved 10-nm spatial and 0.8-nm spectral precisions at a total photon budget of 1000. Compared with the existing sSMLM using a 1:3 splitting ratio between spatial and spectral channels, SDsSMLM improved the spatial and spectral precisions by 42% and 10%, respectively, under the same photon budget. We also demonstrated multicolour imaging of fixed cells and three-dimensional single-particle tracking using SDsSMLM. SDsSMLM enables more precise spectroscopic single-molecule analysis in broader cell biology and material science applications.
| S-EPMC7248114 | biostudies-literature
Project description:Single-molecule localization microscopy (SMLM)-based super-resolution imaging techniques (e.g., photoactivated localization microscopy (PALM)/stochastic optical reconstruction microscopy (STORM)) require that the employed optical nanoprobes possess fluorescence intensity fluctuations under certain excitation conditions. Here, we present a dual-labeled graphene quantum dot (GQD)-based Förster resonance energy transfer (FRET) nanoprobe, which is suitable for SMLM imaging. The nanoprobe is constructed by attaching Alexa Fluor 488 (AF488) and Alexa Fluor 568 (AF568) dye molecules onto GQDs. Experimental results confirmed the FRET effect of the nanoprobes. Moreover, under a single 405 nm excitation, the FRET nanoprobe exhibits excellent blinking behavior. SMLM imaging of microtubules in MRC-5 cells is realized. The presented nanoprobe shows great potential in multicolor SMLM-based super-resolution imaging.
| S-EPMC8028002 | biostudies-literature
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.
| S-EPMC6789733 | biostudies-literature
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.
| S-EPMC9854264 | biostudies-literature
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).
| S-EPMC5027599 | biostudies-literature
Project description:Quantum dots (QDs) are very attractive probes for multi-color fluorescence imaging in biological applications because of their immense brightness and reported extended photostability. We report here however that single QDs, suitable for biological applications, that are subject to continuous blue excitation from a conventional 100 W mercury arc lamp will undergo a continuous blue-switching of the emission wavelength eventually reaching a permanent dark, photobleached state. We further show that β-mercaptoethanol has a dual stabilizing effect on the fluorescence emission of QDs: 1) by increasing the frequency of time that a QD is in its fluorescent state, and 2) by decreasing the photobleaching rate. The observed QD color spectral switching is especially detrimental for multi-color single molecule applications, as we regularly observe spectral blue-shifts of 50 nm, or more even after only ten seconds of illumination. However, of significant importance for biological applications, we find that even small, biologically compatible, concentrations (25 µM) of β-mercaptoethanol has a significant stabilizing effect on the emission color of QDs, but that greater amounts are required to completely abolish the spectral blue shifting or to minimize the emission intermittency of QDs.
| S-EPMC3432116 | biostudies-literature