Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Dynamic Structure of Yeast Septin by Fast Fluctuation-Enhanced Structured Illumination Microscopy.

ABSTRACT: When Saccharomyces cerevisiae divides, a structure composed of different septin proteins arranged according to a certain rule is formed at the cell division site. The structure undergoes multiple remodeling stages during the cell cycle, thus guiding the yeast cells to complete the entire division process. Although the higher-order structure of septins can be determined using electron microscopy, the septin's dynamic processes are poorly understood because of limitations in living cell super-resolution imaging technology. Herein, we describe a high lateral resolution and temporal resolution technique, known as fast fluctuation-enhanced structured illumination microscopy (fFE-SIM), which more than doubles the SIM resolution at a frame rate of 38 Hz in living cells. This allows a highly dynamic and sparse septin structure to be observed in Saccharomyces cerevisiae.

SUBMITTER: Yao L

PROVIDER: S-EPMC8620077 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Multifocus structured illumination microscopy for fast volumetric super-resolution imaging.

Project description:We here report for the first time the synergistic implementation of structured illumination microscopy (SIM) and multifocus microscopy (MFM). This imaging modality is designed to alleviate the problem of insufficient volumetric acquisition speed in super-resolution biological imaging. SIM is a wide-field super-resolution technique that allows imaging with visible light beyond the classical diffraction limit. Employing multifocus diffractive optics we obtain simultaneous wide-field 3D imaging capability in the SIM acquisition sequence, improving volumetric acquisition speed by an order of magnitude. Imaging performance is demonstrated on biological specimens.

| S-EPMC5611928 | biostudies-literature

Fast and robust phase-shift estimation in two-dimensional structured illumination microscopy.

Project description:A method of determining unknown phase-shifts between elementary images in two-dimensional Structured Illumination Microscopy (2D-SIM) is presented. The proposed method is based on the comparison of the peak intensity of spectral components. These components correspond to the inherent structured illumination spectral content and the residual component that appears from wrongly estimated phase-shifts. The estimation of the phase-shifts is carried out by finding the absolute maximum of a function defined as the normalized peak intensity difference in the Fourier domain. This task is performed by an optimization method providing a fast estimation of the phase-shift. The algorithm stability and robustness are tested for various levels of noise and contrasts of the structured illumination pattern. Furthermore, the proposed approach reduces the number of computations compared to other existing techniques. The method is supported by the theoretical calculations and validated by means of simulated and experimental results.

| S-EPMC6697343 | biostudies-literature

Structured line illumination Raman microscopy.

Project description:In the last couple of decades, the spatial resolution in optical microscopy has increased to unprecedented levels by exploiting the fluorescence properties of the probe. At about the same time, Raman imaging techniques have emerged as a way to image inherent chemical information in a sample without using fluorescent probes. However, in many applications, the achievable resolution is limited to about half the wavelength of excitation light. Here we report the use of structured illumination to increase the spatial resolution of label-free spontaneous Raman microscopy, generating highly detailed spatial contrast from the ensemble of molecular information in the sample. Using structured line illumination in slit-scanning Raman microscopy, we demonstrate a marked improvement in spatial resolution and show the applicability to a range of samples, including both biological and inorganic chemical component mapping. This technique is expected to contribute towards greater understanding of chemical component distributions in organic and inorganic materials.

| S-EPMC4686755 | biostudies-literature

Multifocal structured illumination optoacoustic microscopy.

Project description:Optoacoustic (OA) imaging has the capacity to effectively bridge the gap between macroscopic and microscopic realms in biological imaging. High-resolution OA microscopy has so far been performed via point-by-point scanning with a focused laser beam, thus greatly restricting the achievable imaging speed and/or field of view. Herein we introduce multifocal structured illumination OA microscopy (MSIOAM) that attains real-time 3D imaging speeds. For this purpose, the excitation laser beam is shaped to a grid of focused spots at the tissue surface by means of a beamsplitting diffraction grating and a condenser and is then scanned with an acousto-optic deflector operating at kHz rates. In both phantom and in vivo mouse experiments, a 10 mm wide volumetric field of view was imaged with 15 Hz frame rate at 28 μm spatial resolution. The proposed method is expected to greatly aid in biological investigations of dynamic functional, kinetic, and metabolic processes across multiple scales.

| S-EPMC7459102 | biostudies-literature

Deep learning enables structured illumination microscopy with low light levels and enhanced speed.

Project description:Structured illumination microscopy (SIM) surpasses the optical diffraction limit and offers a two-fold enhancement in resolution over diffraction limited microscopy. However, it requires both intense illumination and multiple acquisitions to produce a single high-resolution image. Using deep learning to augment SIM, we obtain a five-fold reduction in the number of raw images required for super-resolution SIM, and generate images under extreme low light conditions (at least 100× fewer photons). We validate the performance of deep neural networks on different cellular structures and achieve multi-color, live-cell super-resolution imaging with greatly reduced photobleaching.

| S-EPMC7176720 | biostudies-literature

Fast, high-contrast imaging of animal development with scanned light sheet-based structured-illumination microscopy.

Project description:Recording light-microscopy images of large, nontransparent specimens, such as developing multicellular organisms, is complicated by decreased contrast resulting from light scattering. Early zebrafish development can be captured by standard light-sheet microscopy, but new imaging strategies are required to obtain high-quality data of late development or of less transparent organisms. We combined digital scanned laser light-sheet fluorescence microscopy with incoherent structured-illumination microscopy (DSLM-SI) and created structured-illumination patterns with continuously adjustable frequencies. Our method discriminates the specimen-related scattered background from signal fluorescence, thereby removing out-of-focus light and optimizing the contrast of in-focus structures. DSLM-SI provides rapid control of the illumination pattern, exceptional imaging quality and high imaging speeds. We performed long-term imaging of zebrafish development for 58 h and fast multiple-view imaging of early Drosophila melanogaster development. We reconstructed cell positions over time from the Drosophila DSLM-SI data and created a fly digital embryo.

| S-EPMC4418465 | biostudies-literature

Full-color structured illumination optical sectioning microscopy.

Project description:In merits of super-resolved resolution and fast speed of three-dimensional (3D) optical sectioning capability, structured illumination microscopy (SIM) has found variety of applications in biomedical imaging. So far, most SIM systems use monochrome CCD or CMOS cameras to acquire images and discard the natural color information of the specimens. Although multicolor integration scheme are employed, multiple excitation sources and detectors are required and the spectral information is limited to a few of wavelengths. Here, we report a new method for full-color SIM with a color digital camera. A data processing algorithm based on HSV (Hue, Saturation, and Value) color space is proposed, in which the recorded color raw images are processed in the Hue, Saturation, Value color channels, and then reconstructed to a 3D image with full color. We demonstrated some 3D optical sectioning results on samples such as mixed pollen grains, insects, micro-chips and the surface of coins. The presented technique is applicable to some circumstance where color information plays crucial roles, such as in materials science and surface morphology.

| S-EPMC4586488 | biostudies-literature

Deep learning for blind structured illumination microscopy.

Project description:Blind-structured illumination microscopy (blind-SIM) enhances the optical resolution without the requirement of nonlinear effects or pre-defined illumination patterns. It is thus advantageous in experimental conditions where toxicity or biological fluctuations are an issue. In this work, we introduce a custom convolutional neural network architecture for blind-SIM: BS-CNN. We show that BS-CNN outperforms other blind-SIM deconvolution algorithms providing a resolution improvement of 2.17 together with a very high Fidelity (artifacts reduction). Furthermore, BS-CNN proves to be robust in cross-database variability: it is trained on synthetically augmented open-source data and evaluated on experiments. This approach paves the way to the employment of CNN-based deconvolution in all scenarios in which a statistical model for the illumination is available while the specific realizations are unknown or noisy.

| S-EPMC9124205 | biostudies-literature

Fast objective coupled planar illumination microscopy.

Project description:Among optical imaging techniques light sheet fluorescence microscopy is one of the most attractive for capturing high-speed biological dynamics unfolding in three dimensions. The technique is potentially millions of times faster than point-scanning techniques such as two-photon microscopy. However light sheet microscopes are limited by volume scanning rate and/or camera speed. We present speed-optimized Objective Coupled Planar Illumination (OCPI) microscopy, a fast light sheet technique that avoids compromising image quality or photon efficiency. Our fast scan system supports 40 Hz imaging of 700 μm-thick volumes if camera speed is sufficient. We also address the camera speed limitation by introducing Distributed Planar Imaging (DPI), a scaleable technique that parallelizes image acquisition across cameras. Finally, we demonstrate fast calcium imaging of the larval zebrafish brain and find a heartbeat-induced artifact, removable when the imaging rate exceeds 15 Hz. These advances extend the reach of fluorescence microscopy for monitoring fast processes in large volumes.

| S-EPMC6775063 | biostudies-literature

Concepts for structured illumination microscopy with extended axial resolution through mirrored illumination.

Project description:Wide-field fluorescence microscopy, while much faster than confocal microscopy, suffers from a lack of optical sectioning and poor axial resolution. 3D structured illumination microscopy (SIM) has been demonstrated to provide optical sectioning and to double the resolution limit both laterally and axially, but even with this the axial resolution is still worse than the lateral resolution of unmodified wide-field microscopy. Interferometric schemes using two high numerical aperture objectives, such as 4Pi confocal and I5M microscopy, have improved the axial resolution beyond that of the lateral, but at the cost of a significantly more complex optical setup. Here, we theoretically and numerically investigate a simpler dual-objective scheme which we propose can be easily added to an existing 3D-SIM microscope, providing lateral and axial resolutions in excess of 125 nm with conventional fluorophores and without the need for interferometric detection.

| S-EPMC7173891 | 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