Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Isotropic 3D Super-resolution Imaging with a Self-bending Point Spread Function.

ABSTRACT: Airy beams maintain their intensity profiles over a large propagation distance without substantial diffraction and exhibit lateral bending during propagation1-5. This unique property has been exploited for micromanipulation of particles6, generation of plasma channels7 and guidance of plasmonic waves8, but has not been explored for high-resolution optical microscopy. Here, we introduce a self-bending point spread function (SB-PSF) based on Airy beams for three-dimensional (3D) super-resolution fluorescence imaging. We designed a side-lobe-free SB-PSF and implemented a two-channel detection scheme to enable unambiguous 3D localization of fluorescent molecules. The lack of diffraction and the propagation-dependent lateral bending make the SB-PSF well suited for precise 3D localization of molecules over a large imaging depth. Using this method, we obtained super-resolution imaging with isotropic 3D localization precision of 10-15 nm over a 3 ?m imaging depth from ?2000 photons per localization.

SUBMITTER: Jia S

PROVIDER: S-EPMC4224117 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Isotropic 3D Super-resolution Imaging with a Self-bending Point Spread Function.

Jia Shu S Vaughan Joshua C JC Zhuang Xiaowei X

Nature photonics 20140101

Airy beams maintain their intensity profiles over a large propagation distance without substantial diffraction and exhibit lateral bending during propagation1-5. This unique property has been exploited for micromanipulation of particles6, generation of plasma channels7 and guidance of plasmonic waves8, but has not been explored for high-resolution optical microscopy. Here, we introduce a self-bending point spread function (SB-PSF) based on Airy beams f ...[more]

PMID: 25383090

Similar Datasets

Super-resolution photon-efficient imaging by nanometric double-helix point spread function localization of emitters (SPINDLE).

Project description:Super-resolution imaging with photo-activatable or photo-switchable probes is a promising tool in biological applications to reveal previously unresolved intra-cellular details with visible light. This field benefits from developments in the areas of molecular probes, optical systems, and computational post-processing of the data. The joint design of optics and reconstruction processes using double-helix point spread functions (DH-PSF) provides high resolution three-dimensional (3D) imaging over a long depth-of-field. We demonstrate for the first time a method integrating a Fisher information efficient DH-PSF design, a surface relief optical phase mask, and an optimal 3D localization estimator. 3D super-resolution imaging using photo-switchable dyes reveals the 3D microtubule network in mammalian cells with localization precision approaching the information theoretical limit over a depth of 1.2 µm.

| S-EPMC3971058 | biostudies-other

Optimal point spread function design for 3D imaging.

Project description:To extract from an image of a single nanoscale object maximum physical information about its position, we propose and demonstrate a framework for pupil-plane modulation for 3D imaging applications requiring precise localization, including single-particle tracking and superresolution microscopy. The method is based on maximizing the information content of the system, by formulating and solving the appropriate optimization problem--finding the pupil-plane phase pattern that would yield a point spread function (PSF) with optimal Fisher information properties. We use our method to generate and experimentally demonstrate two example PSFs: one optimized for 3D localization precision over a 3 μm depth of field, and another with an unprecedented 5 μm depth of field, both designed to perform under physically common conditions of high background signals.

| S-EPMC4381866 | biostudies-literature

Generalized recovery algorithm for 3D super-resolution microscopy using rotating point spread functions.

Project description:Super-resolution microscopy with phase masks is a promising technique for 3D imaging and tracking. Due to the complexity of the resultant point spread functions, generalized recovery algorithms are still missing. We introduce a 3D super-resolution recovery algorithm that works for a variety of phase masks generating 3D point spread functions. A fast deconvolution process generates initial guesses, which are further refined by least squares fitting. Overfitting is suppressed using a machine learning determined threshold. Preliminary results on experimental data show that our algorithm can be used to super-localize 3D adsorption events within a porous polymer film and is useful for evaluating potential phase masks. Finally, we demonstrate that parallel computation on graphics processing units can reduce the processing time required for 3D recovery. Simulations reveal that, through desktop parallelization, the ultimate limit of real-time processing is possible. Our program is the first open source recovery program for generalized 3D recovery using rotating point spread functions.

| S-EPMC4973222 | biostudies-literature

Elucidation of synaptonemal complex organization by super-resolution imaging with isotropic resolution.

Project description:Synaptonemal complexes (SCs) are meiosis-specific multiprotein complexes that are essential for synapsis, recombination, and segregation of homologous chromosomes, but the molecular organization of SCs remains unclear. We used immunofluorescence labeling in combination with super-resolution imaging and average position determination to investigate the molecular architecture of SCs. Combination of 2D super-resolution images recorded from different areas of the helical ladder-like structure allowed us to reconstruct the 3D molecular organization of the mammalian SC with isotropic resolution. The central element is composed of two parallel cables at a distance of ∼ 100 nm, which are oriented perpendicular to two parallel cables of the lateral element arranged at a distance of ∼ 220 nm. The two parallel cable elements form twisted helical structures that are connected by transversal filaments by their N and C termini. A single-cell preparation generates sufficient localizations to compile a 3D model of the SC with nanometer precision.

| S-EPMC4343094 | biostudies-literature

Three-Dimensional Super-Resolution in Eukaryotic Cells Using the Double-Helix Point Spread Function.

Project description:Single-molecule localization microscopy, typically based on total internal reflection illumination, has taken our understanding of protein organization and dynamics in cells beyond the diffraction limit. However, biological systems exist in a complicated three-dimensional environment, which has required the development of new techniques, including the double-helix point spread function (DHPSF), to accurately visualize biological processes. The application of the DHPSF approach has so far been limited to the study of relatively small prokaryotic cells. By matching the refractive index of the objective lens immersion liquid to that of the sample media, we demonstrate DHPSF imaging of up to 15-μm-thick whole eukaryotic cell volumes in three to five imaging planes. We illustrate the capabilities of the DHPSF by exploring large-scale membrane reorganization in human T cells after receptor triggering, and by using single-particle tracking to image several mammalian proteins, including membrane, cytoplasmic, and nuclear proteins in T cells and embryonic stem cells.

| S-EPMC5390298 | biostudies-literature

Deep learning-based point-scanning super-resolution imaging.

Project description:Point-scanning imaging systems are among the most widely used tools for high-resolution cellular and tissue imaging, benefiting from arbitrarily defined pixel sizes. The resolution, speed, sample preservation and signal-to-noise ratio (SNR) of point-scanning systems are difficult to optimize simultaneously. We show these limitations can be mitigated via the use of deep learning-based supersampling of undersampled images acquired on a point-scanning system, which we term point-scanning super-resolution (PSSR) imaging. We designed a 'crappifier' that computationally degrades high SNR, high-pixel resolution ground truth images to simulate low SNR, low-resolution counterparts for training PSSR models that can restore real-world undersampled images. For high spatiotemporal resolution fluorescence time-lapse data, we developed a 'multi-frame' PSSR approach that uses information in adjacent frames to improve model predictions. PSSR facilitates point-scanning image acquisition with otherwise unattainable resolution, speed and sensitivity. All the training data, models and code for PSSR are publicly available at 3DEM.org.

| S-EPMC8035334 | biostudies-literature

3D Isotropic Super-resolution Prostate MRI Using Generative Adversarial Networks and Unpaired Multiplane Slices.

Project description:We developed a deep learning-based super-resolution model for prostate MRI. 2D T2-weighted turbo spin echo (T2w-TSE) images are the core anatomical sequences in a multiparametric MRI (mpMRI) protocol. These images have coarse through-plane resolution, are non-isotropic, and have long acquisition times (approximately 10-15 min). The model we developed aims to preserve high-frequency details that are normally lost after 3D reconstruction. We propose a novel framework for generating isotropic volumes using generative adversarial networks (GAN) from anisotropic 2D T2w-TSE and single-shot fast spin echo (ssFSE) images. The CycleGAN model used in this study allows the unpaired dataset mapping to reconstruct super-resolution (SR) volumes. Fivefold cross-validation was performed. The improvements from patch-to-volume reconstruction (PVR) to SR are 80.17%, 63.77%, and 186% for perceptual index (PI), RMSE, and SSIM, respectively; the improvements from slice-to-volume reconstruction (SVR) to SR are 72.41%, 17.44%, and 7.5% for PI, RMSE, and SSIM, respectively. Five ssFSE cases were used to test for generalizability; the perceptual quality of SR images surpasses the in-plane ssFSE images by 37.5%, with 3.26% improvement in SSIM and a higher RMSE by 7.92%. SR images were quantitatively assessed with radiologist Likert scores. Our isotropic SR volumes are able to reproduce high-frequency detail, maintaining comparable image quality to in-plane TSE images in all planes without sacrificing perceptual accuracy. The SR reconstruction networks were also successfully applied to the ssFSE images, demonstrating that high-quality isotropic volume achieved from ultra-fast acquisition is feasible.

| S-EPMC8555005 | biostudies-literature

3D super-resolution imaging with blinking quantum dots.

Project description:Quantum dots are promising candidates for single molecule imaging due to their exceptional photophysical properties, including their intense brightness and resistance to photobleaching. They are also notorious for their blinking. Here we report a novel way to take advantage of quantum dot blinking to develop an imaging technique in three-dimensions with nanometric resolution. We first applied this method to simulated images of quantum dots and then to quantum dots immobilized on microspheres. We achieved imaging resolutions (fwhm) of 8-17 nm in the x-y plane and 58 nm (on coverslip) or 81 nm (deep in solution) in the z-direction, approximately 3-7 times better than what has been achieved previously with quantum dots. This approach was applied to resolve the 3D distribution of epidermal growth factor receptor (EGFR) molecules at, and inside of, the plasma membrane of resting basal breast cancer cells.

| S-EPMC3874875 | biostudies-literature

3D ATAC-PALM: Super-resolution Imaging of the Accessible Genome

Project description:Spatial genome organization is essential to direct fundamental DNA-templated biological processes (e.g. transcription, replication, and repair), but the 3D in situ nanometer-scale structure of accessible cis-regulatory DNA elements within the crowded nuclear environment remains elusive. Here, we combined the recently developed Assay for Transposase-Accessible Chromatin with visualization (ATAC-see), PALM super-resolution imaging and lattice light-sheet microscope (a method termed 3D ATAC-PALM) to selectively image and quantitatively analyze key features of the 3D accessible genome in single cells. 3D ATAC-PALM reveals that accessible chromatin are non-homogeneously organized into spatially segregated clusters or accessible chromatin domains (ACDs). To directly link imaging and genomic data, we optimized multiplexed imaging of 3D ATAC-PALM with Oligopaint DNA-FISH, RNA-FISH and protein fluorescence. We found that ACDs colocalize with active chromatin and enclose transcribed genes. By applying these methods to analyze genetically purterbed cells, we demonstrated that genome architectural protein CTCF prevents excessive clustering of accessible chromatin and decompacts ACDs. These results highlight the 3D ATAC-PALM as a useful tool to probe the structure and organizing mechanism of the genome.

2020-01-29 | GSE126112 | GEO

3D ATAC-PALM: super-resolution imaging of the accessible genome.

Project description:To image the accessible genome at nanometer scale in situ, we developed three-dimensional assay for transposase-accessible chromatin-photoactivated localization microscopy (3D ATAC-PALM) that integrates an assay for transposase-accessible chromatin with visualization, PALM super-resolution imaging and lattice light-sheet microscopy. Multiplexed with oligopaint DNA-fluorescence in situ hybridization (FISH), RNA-FISH and protein fluorescence, 3D ATAC-PALM connected microscopy and genomic data, revealing spatially segregated accessible chromatin domains (ACDs) that enclose active chromatin and transcribed genes. Using these methods to analyze genetically perturbed cells, we demonstrated that genome architectural protein CTCF prevents excessive clustering of accessible chromatin and decompacts ACDs. These results highlight 3D ATAC-PALM as a useful tool to probe the structure and organizing mechanism of the genome.

| S-EPMC7207063 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data