Browse
Submit Data
Databases
API
Help

Dataset Information

27 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Deep learning with digital holographic microscopy discriminates apoptosis and necroptosis.

ABSTRACT: Regulated cell death modalities such as apoptosis and necroptosis play an important role in regulating different cellular processes. Currently, regulated cell death is identified using the golden standard techniques such as fluorescence microscopy and flow cytometry. However, they require fluorescent labels, which are potentially phototoxic. Therefore, there is a need for the development of new label-free methods. In this work, we apply Digital Holographic Microscopy (DHM) coupled with a deep learning algorithm to distinguish between alive, apoptotic and necroptotic cells in murine cancer cells. This method is solely based on label-free quantitative phase images, where the phase delay of light by cells is quantified and is used to calculate their topography. We show that a combination of label-free DHM in a high-throughput set-up (~10,000 cells per condition) can discriminate between apoptosis, necroptosis and alive cells in the L929sAhFas cell line with a precision of over 85%. To the best of our knowledge, this is the first time deep learning in the form of convolutional neural networks is applied to distinguish-with a high accuracy-apoptosis and necroptosis and alive cancer cells from each other in a label-free manner. It is expected that the approach described here will have a profound impact on research in regulated cell death, biomedicine and the field of (cancer) cell biology in general.

SUBMITTER: Verduijn J

PROVIDER: S-EPMC8413278 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Deep Learning-Based Holographic Polarization Microscopy.

Project description:Polarized light microscopy provides high contrast to birefringent specimen and is widely used as a diagnostic tool in pathology. However, polarization microscopy systems typically operate by analyzing images collected from two or more light paths in different states of polarization, which lead to relatively complex optical designs, high system costs, or experienced technicians being required. Here, we present a deep learning-based holographic polarization microscope that is capable of obtaining quantitative birefringence retardance and orientation information of specimen from a phase-recovered hologram, while only requiring the addition of one polarizer/analyzer pair to an inline lensfree holographic imaging system. Using a deep neural network, the reconstructed holographic images from a single state of polarization can be transformed into images equivalent to those captured using a single-shot computational polarized light microscope (SCPLM). Our analysis shows that a trained deep neural network can extract the birefringence information using both the sample specific morphological features as well as the holographic amplitude and phase distribution. To demonstrate the efficacy of this method, we tested it by imaging various birefringent samples including, for example, monosodium urate and triamcinolone acetonide crystals. Our method achieves similar results to SCPLM both qualitatively and quantitatively, and due to its simpler optical design and significantly larger field-of-view this method has the potential to expand the access to polarization microscopy and its use for medical diagnosis in resource limited settings.

| S-EPMC8345334 | biostudies-literature

Early cell death detection with digital holographic microscopy.

Project description:BACKGROUND: Digital holography provides a non-invasive measurement of the quantitative phase shifts induced by cells in culture, which can be related to cell volume changes. It has been shown previously that regulation of cell volume, in particular as it relates to ionic homeostasis, is crucially involved in the activation/inactivation of the cell death processes. We thus present here an application of digital holographic microscopy (DHM) dedicated to early and label-free detection of cell death. METHODS AND FINDINGS: We provide quantitative measurements of phase signal obtained on mouse cortical neurons, and caused by early neuronal cell volume regulation triggered by excitotoxic concentrations of L-glutamate. We show that the efficiency of this early regulation of cell volume detected by DHM, is correlated with the occurrence of subsequent neuronal death assessed with the widely accepted trypan blue method for detection of cell viability. CONCLUSIONS: The determination of the phase signal by DHM provides a simple and rapid optical method for the early detection of cell death.

| S-EPMC3269420 | biostudies-literature

Opposite-view digital holographic microscopy with autofocusing capability.

Project description:Digital holographic microscopy (DHM) has its intrinsic ability to refocusing a sample by numerically propagating an object wave from its hologram plane to its image plane. In this paper opposite-view digital holographic microscopy (OV-DHM) is demonstrated for autofocusing, namely, digitally determining the location of the image plane, and refocusing the object wave without human intervention. In OV-DHM, a specimen is illuminated from two sides in a 4?-alike configuration, and two holograms are generated and recorded by a CCD camera along two orthogonal polarization orientations. The image plane of the sample is determined by finding the minimal variation between the two object waves, and consequently refocusing is performed by propagating the waves to the image plane. Furthermore, the field of view (FOV) of OV-DHM can be extended by combining the two object waves which have an angle in-between. The proposed technique also has the potential to reduce speckle noise and out-of-focus background.

| S-EPMC5484697 | biostudies-literature

Simultaneous two-color imaging in digital holographic microscopy.

Project description:We demonstrate the use of two-color digital holographic microscopy (DHM) for imaging microbiological subjects. The use of two wavelengths significantly reduces artifacts present in the reconstructed data, allowing us to image weakly-scattering objects in close proximity to strongly-scattering objects. We demonstrate this by reconstructing the shape of the flagellum of a unicellular eukaryotic parasite Leishmania mexicana in close proximity to a more strongly-scattering cell body. Our approach also yields a reduction of approximately one third in the axial position uncertainty when tracking the motion of swimming cells at low magnification, which we demonstrate with a sample of Escherichia coli bacteria mixed with polystyrene beads. The two-wavelength system that we describe introduces minimal additional complexity into the optical system, and provides significant benefits.

| S-EPMC6968951 | biostudies-literature

Opposed-view dark-field digital holographic microscopy.

Project description:Scattering and absorption belong to the major problems in imaging the internal layers of a biological specimen. Due to the structural inhomogeneity of the specimen, the distribution of the structures in the upper layers of a given internal structure of interest is different from the lower layers that may result in different interception of scattered light, falling into the angular aperture of the microscope objective, from the object in each imaging view. Therefore, different spatial frequencies of the scattered light can be acquired from different (top and bottom) views. We have arranged an opposed-view dark-field digital holographic microscope (DHM) to collect the scattered light concurrently from both views with the aim to increase the contrast of internal structures and improve the signal-to-noise ratio. Implementing a DHM system gives the possibility to implement digital refocusing process and obtain multilayer images from each side without a depth scan of the object. The method is explained and the results are presented exemplary for a Drosophila embryo.

| S-EPMC3959838 | biostudies-other

Genetically Encoded Phase Contrast Agents for Digital Holographic Microscopy.

Project description:Quantitative phase imaging and digital holographic microscopy have shown great promise for visualizing the motion, structure, and physiology of microorganisms and mammalian cells in three dimensions. However, these imaging techniques currently lack molecular contrast agents analogous to the fluorescent dyes and proteins that have revolutionized fluorescence microscopy. Here we introduce the first genetically encodable phase contrast agents based on gas vesicles. The relatively low index of refraction of the air-filled core of gas vesicles results in optical phase advancement relative to aqueous media, making them a "positive" phase contrast agent easily distinguished from organelles, dyes, or microminerals. We demonstrate this capability by identifying and tracking the motion of gas vesicles and gas vesicle-expressing bacteria using digital holographic microscopy, and by imaging the uptake of engineered gas vesicles by mammalian cells. These results give phase imaging a biomolecular contrast agent, expanding the capabilities of this powerful technology for three-dimensional biological imaging.

| S-EPMC7685204 | biostudies-literature

Two-step phase shifting differential-recording digital holographic microscopy.

Project description:We present two-step phase-shifting differential-recording digital holographic microscopy (TPD-DH in microscopy) for phase imaging of microscopic transparent elements. Two CCDs are employed to record two interferograms at two different defocusing distances. The interferograms on the two CCD cameras are shifted for a phase retarder 0 and π via an all-optics phase shifting unit. A novel algorithm is proposed to reconstruct both amplitude and phase distributions of the object wave from the recorded interferograms. This method has the same spectrum bandwidth and measurement accuracy with those of conventional four-step phase-shifting interferometry (FS-PSI), whereas it reduces the measurement time by half.

| S-EPMC5434033 | biostudies-literature

In-line digital holographic microscopy using a consumer scanner.

Project description:We demonstrate an in-line digital holographic microscopy using a consumer scanner. The consumer scanner can scan an image with 4,800 dpi. The pixel pitch is approximately 5.29 μm. The system using a consumer scanner has a simple structure, compared with synthetic aperture digital holography using a camera mounted on a two-dimensional moving stage. In this demonstration, we captured an in-line hologram with 23, 602 × 18, 023 pixels (≈0.43 gigapixels). The physical size of the scanned hologram is approximately 124 mm × 95 mm. In addition, to accelerate the reconstruction time of the gigapixel hologram and decrease the amount of memory for the reconstruction, we applied the band-limited double-step Fresnel diffraction to the reconstruction.

| S-EPMC3773619 | biostudies-literature

Digital holographic microscopy: a quantitative label-free microscopy technique for phenotypic screening.

Project description:Digital Holographic Microscopy (DHM) is a label-free imaging technique allowing visualization of transparent cells with classical imaging cell culture plates. The quantitative DHM phase contrast image provided is related both to the intracellular refractive index and to cell thickness. DHM is able to distinguish cellular morphological changes on two representative cell lines (HeLa and H9c2) when treated with doxorubicin and chloroquine, two cytotoxic compounds yielding distinct phenotypes. We analyzed parameters linked to cell morphology and to the intracellular content in endpoint measurements and further investigated them with timelapse recording. The results obtained by DHM were compared with other optical label-free microscopy techniques, namely Phase Contrast, Differential Interference Contrast and Transport of Intensity Equation (reconstructed from three bright-field images). For comparative purposes, images were acquired in a common 96-well plate format on the different motorized microscopes. In contrast to the other microscopies assayed, images generated with DHM can be easily quantified using a simple automatized on-the-fly analysis method for discriminating the different phenotypes generated in each cell line. The DHM technology is suitable for the development of robust and unbiased image-based assays.

| S-EPMC3894694 | biostudies-literature

Quantitative assessment of cancer cell morphology and motility using telecentric digital holographic microscopy and machine learning.

Project description:The noninvasive, fast acquisition of quantitative phase maps using digital holographic microscopy (DHM) allows tracking of rapid cellular motility on transparent substrates. On two-dimensional surfaces in vitro, MDA-MB-231 cancer cells assume several morphologies related to the mode of migration and substrate stiffness, relevant to mechanisms of cancer invasiveness in vivo. The quantitative phase information from DHM may accurately classify adhesive cancer cell subpopulations with clinical relevance. To test this, cells from the invasive breast cancer MDA-MB-231 cell line were cultured on glass, tissue-culture treated polystyrene, and collagen hydrogels, and imaged with DHM followed by epifluorescence microscopy after staining F-actin and nuclei. Trends in cell phase parameters were tracked on the different substrates, during cell division, and during matrix adhesion, relating them to F-actin features. Support vector machine learning algorithms were trained and tested using parameters from holographic phase reconstructions and cell geometric features from conventional phase images, and used to distinguish between elongated and rounded cell morphologies. DHM was able to distinguish between elongated and rounded morphologies of MDA-MB-231 cells with 94% accuracy, compared to 83% accuracy using cell geometric features from conventional brightfield microscopy. This finding indicates the potential of DHM to detect and monitor cancer cell morphologies relevant to cell cycle phase status, substrate adhesion, and motility. © 2017 International Society for Advancement of Cytometry.

| S-EPMC8245299 | 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