Comparison of diffusion-weighted MRI and anti-Stokes Raman scattering (CARS) measurements of the inter-compartmental exchange-time of water in expression-controlled aquaporin-4 cells.
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ABSTRACT:
SUBMITTER: Obata T
PROVIDER: S-EPMC6298983 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:PurposeThe aim of this study was to image the cellular and noncellular structures of the cornea and limbus in an intact mouse eye using the vibrational oscillation of the carbon-hydrogen bond in lipid membranes and autofluorescence as label-free contrast agents.MethodsFreshly enucleated mouse eyes were imaged using two nonlinear optical techniques: coherent anti-Stokes Raman scattering (CARS) and two-photon autofluorescence (TPAF). Sequential images were collected through the full thickness of the cornea and limbal regions. Line scans along the transverse/sagittal axes were also performed.ResultsAnalysis of multiple CARS/TPAF images revealed that corneal epithelial and endothelial cells could be identified by the lipid-rich plasma membrane CARS signal. The fluorescent signal from the collagen fibers of the corneal stroma was evident in the TPAF channel. The transition from the cornea to sclera at the limbus was marked by a change in collagen pattern (TPAF channel) and thickness of surface cells (CARS channel). Regions within the corneal stroma that lack collagen autofluorescence coincided with CARS signal, indicating the presence of stromal fibroblasts or nerve fibers.ConclusionsThe CARS technique was successful in imaging cells in the intact mouse eye, both at the surface and within corneal tissue. Multiphoton images were comparable to histologic sections. The methods described here represent a new avenue for molecular specific imaging of the mouse eye. The lack of need for tissue fixation is unique compared with traditional histology imaging techniques.
| S-EPMC3736760 | biostudies-literature
Project description:PurposeTo image the cellular and noncellular structures of the retina in an intact mouse eye without the application of exogenous fluorescent labels using noninvasive, nondestructive techniques.MethodsFreshly enucleated mouse eyes were imaged using two nonlinear optical techniques: coherent anti-Stokes Raman scattering (CARS) and two-photon autofluorescence (TPAF). Cross sectional transverse sections and sequential flat (en face) sagittal sections were collected from a region of sclera approximately midway between the limbus and optic nerve. Imaging proceeded from the surface of the sclera to a depth of ?60 ?m.ResultsThe fluorescent signal from collagen fibers within the sclera was evident in the TPAF channel; the scleral collagen fibers showed no organization and appeared randomly packed. The sclera contained regions lacking TPAF and CARS fluorescence of ?3 to 15 ?m in diameter that could represent small vessels or scleral fibroblasts. Intense punctate CARS signals from the retinal pigment epithelial layer were of a size and shape of retinyl storage esters. Rod outer segments could be identified by the CARS signal from their lipid-rich plasma membranes.ConclusionsCARS microscopy can be used to image the outer regions of the mammalian retina without the use of a fluorescent dye or exogenously expressed recombinant protein. With technical advancements, CARS/TPAF may represent a new avenue for noninvasively imaging the retina and might complement modalities currently used in clinical practice.
| S-EPMC3643396 | biostudies-literature
Project description:Coherent anti-Stokes Raman scattering (CARS) microspectroscopy has demonstrated significant potential for biological and materials imaging. To date, however, the primary mechanism of disseminating CARS spectroscopic information is through pseudocolor imagery, which explicitly neglects a vast majority of the hyperspectral data. Furthermore, current paradigms in CARS spectral processing do not lend themselves to quantitative sample-to-sample comparability. The primary limitation stems from the need to accurately measure the so-called nonresonant background (NRB) that is used to extract the chemically-sensitive Raman information from the raw spectra. Measurement of the NRB on a pixel-by-pixel basis is a nontrivial task; thus, reference NRB from glass or water are typically utilized, resulting in error between the actual and estimated amplitude and phase. In this manuscript, we present a new methodology for extracting the Raman spectral features that significantly suppresses these errors through phase detrending and scaling. Classic methods of error-correction, such as baseline detrending, are demonstrated to be inaccurate and to simply mask the underlying errors. The theoretical justification is presented by re-developing the theory of phase retrieval via the Kramers-Kronig relation, and we demonstrate that these results are also applicable to maximum entropy method-based phase retrieval. This new error-correction approach is experimentally applied to glycerol spectra and tissue images, demonstrating marked consistency between spectra obtained using different NRB estimates, and between spectra obtained on different instruments. Additionally, in order to facilitate implementation of these approaches, we have made many of the tools described herein available free for download.
| S-EPMC5557306 | biostudies-literature
Project description:Better understanding of the fundamental mechanisms behind metabolic diseases requires methods to monitor lipid stores on single-cell level in vivo. We have used Caenorhabditis elegans as a model organism to demonstrate the limitations of fluorescence microscopy for imaging of lipids compared with coherent anti-Stokes Raman scattering (CARS) microscopy, the latter allowing chemically specific and label-free imaging in living organisms. CARS microscopy was used to quantitatively monitor the impact of genetic variations in metabolic pathways on lipid storage in 60 specimens of C. elegans. We found that the feeding-defective mutant pha-3 contained a lipid volume fraction one-third of that found in control worms. In contrast, mutants (daf-2, daf-4 dauer) with deficiencies in the insulin and transforming growth factors (IGF and TGF-beta) signaling pathways had lipid volume fractions that were 1.4 and 2 times larger than controls, respectively. This was observed as an accumulation of small-sized lipid droplets in the hypodermal cells, hosting as much as 40% of the total lipid volume in contrast to the 9% for the wild-type larvae. Spectral CARS microscopy measurements indicated that this is accompanied by a shift in the ordering of the lipids from gel to liquid phase. We conclude that the degree of hypodermal lipid storage and the lipid phase can be used as a marker of lipid metabolism shift. This study shows that CARS microscopy has the potential to become a sensitive and important tool for studies of lipid storage mechanisms, improving our understanding of phenomena underlying metabolic disorders.
| S-EPMC1976189 | biostudies-literature
Project description:Water can pass through biological membranes via two pathways: simple diffusion through the lipid bilayer, or water-selective facilitated diffusion through aquaporins (AQPs). Although AQPs play an important role in osmotic water permeability (P(f)), the role of AQPs in diffusional water permeability remains unclear because of the difficulty of measuring diffusional water permeability (P(d)). Here, we report an accurate and instantaneous method for measuring the P(d) of a single HeLa S3 cell using coherent anti-Stokes Raman scattering (CARS) microscopy with a quick perfusion device for H(2)O/D(2)O exchange. Ultra-high-speed line-scan CARS images were obtained every 0.488 ms. The average decay time constant of CARS intensities (τ(CARS)) for the external solution H(2)O/D(2)O exchange was 16.1 ms, whereas the intracellular H(2)O/D(2)O exchange was 100.7 ± 19.6 ms. To evaluate the roles of AQP in diffusional water permeability, AQP4 fused with enhanced green fluorescent protein (AQP4-EGFP) was transiently expressed in HeLa S3 cells. The average τ(CARS) for the intracellular H(2)O/D(2)O exchange in the AQP4-EGFP-HeLa S3 cells was 43.1 ± 15.8 ms. We also assessed the cell volume and the cell surface area to calculate P(d). The average P(d) values for the AQP4-EGFP-HeLa S3 cells and the control EGFP-HeLa S3 cells were 2.7 ± 1.0 × 10(-3) and 8.3 ± 2.6 × 10(-4) cm/s, respectively. AQP4-mediated water diffusion was independent of the temperature but was dependent on the expression level of the protein at the plasma membrane. These results suggest the possibility of using CARS imaging to investigate the hydrodynamics of single mammalian cells as well as the regulation of AQPs.
| S-EPMC3207164 | biostudies-literature
Project description:BackgroundCannabis possesses a rich spectrum of phytochemicals i.e. cannabinoids, terpenes and phenolic compounds of industrial and medicinal interests. Most of these high-value plant products are synthesised in the disk cells and stored in the secretory cavity in glandular trichomes. Conventional trichome analysis was so far based on optical microscopy, electron microscopy or extraction based methods that are either limited to spatial or chemical information. Here we combine both information to obtain the spatial distribution of distinct secondary metabolites on a single-trichome level by applying Coherent anti-Stokes Raman scattering (CARS), a microspectroscopic technique, to trichomes derived from sepals of a drug- and a fibre-type.ResultsHyperspectral CARS imaging in combination with a nonlinear unmixing method allows to identify and localise ?9-tetrahydrocannabinolic acid (THCA) in the secretory cavity of drug-type trichomes and cannabidiolic acid (CBDA)/myrcene in the secretory cavity of fibre-type trichomes, thus enabling an easy discrimination between high-THCA and high-CBDA producers. A unique spectral fingerprint is found in the disk cells of drug-type trichomes, which is most similar to cannabigerolic acid (CBGA) and is not found in fibre-type trichomes. Furthermore, we differentiate between different cell types by a combination of CARS with simultaneously acquired two-photon fluorescence (TPF) of chlorophyll a from chloroplasts and organic fluorescence mainly arising from cell walls enabling 3D visualisation of the essential oil distribution and cellular structures.ConclusionHere we demonstrate a label-free and non-destructive method to analyse the distribution of secondary metabolites and distinguish between different cell and chemo-types with high spatial resolution on a single trichome. The record of chemical fingerprints of single trichomes offers the possibility to optimise growth conditions as well as guarantee a direct process control for industrially cultivated medicinal Cannabis plants. Moreover, this method is not limited to Cannabis related issues but can be widely implemented for optimising and monitoring all kinds of natural or biotechnological production processes with simultaneous spatial and chemical information.
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Project description:Stokes and anti-Stokes Raman scattering are performed on atomic layers of hexagonal molybdenum ditelluride (MoTe2), a prototypical transition metal dichalcogenide (TMDC) semiconductor. The data reveal all six types of zone center optical phonons, along with their corresponding Davydov splittings, which have been challenging to see in other TMDCs. We discover that the anti-Stokes Raman intensity of the low energy layer-breathing mode becomes more intense than the Stokes peak under certain experimental conditions, and find the effect to be tunable by excitation frequency and number of atomic layers. These observations are interpreted as a result of resonance effects arising from the C excitons in the vicinity of the Brillouin zone center in the photon-electron-phonon interaction process.
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Project description:Nanoparticles have attracted enormous attention for biomedical applications as optical labels, drug-delivery vehicles and contrast agents in vivo. In the quest for superior photostability and biocompatibility, nanodiamonds are considered one of the best choices due to their unique structural, chemical, mechanical and optical properties. So far, mainly fluorescent nanodiamonds have been utilized for cell imaging. However, their use is limited by the efficiency and costs in reliably producing fluorescent defect centres with stable optical properties. Here, we show that single non-fluorescing nanodiamonds exhibit strong coherent anti-Stokes Raman scattering (CARS) at the sp(3) vibrational resonance of diamond. Using correlative light and electron microscopy, the relationship between CARS signal strength and nanodiamond size is quantified. The calibrated CARS signal in turn enables the analysis of the number and size of nanodiamonds internalized in living cells in situ, which opens the exciting prospect of following complex cellular trafficking pathways quantitatively.
| S-EPMC4990125 | biostudies-literature
Project description:We propose a Bayesian statistical model for analyzing coherent anti-Stokes Raman scattering (CARS) spectra. Our quantitative analysis includes statistical estimation of constituent line-shape parameters, the underlying Raman signal, the error-corrected CARS spectrum, and the measured CARS spectrum. As such, this work enables extensive uncertainty quantification in the context of CARS spectroscopy. Furthermore, we present an unsupervised method for improving spectral resolution of Raman-like spectra requiring little to no a priori information. Finally, the recently proposed wavelet prism method for correcting the experimental artifacts in CARS is enhanced by using interpolation techniques for wavelets. The method is validated using CARS spectra of adenosine mono-, di-, and triphosphate in water, as well as equimolar aqueous solutions of d-fructose, d-glucose, and their disaccharide combination sucrose.
| S-EPMC7458428 | biostudies-literature
Project description:Coherent anti-Stokes Raman scattering (CARS) is an emerging tool for label-free characterization of living cells. Here, unsupervised multivariate analysis of CARS datasets was used to visualize the subcellular compartments. In addition, a supervised learning algorithm based on the "random forest" ensemble learning method as a classifier, was trained with CARS spectra using immunofluorescence images as a reference. The supervised classifier was then used, to our knowledge for the first time, to automatically identify lipid droplets, nucleus, nucleoli, and endoplasmic reticulum in datasets that are not used for training. These four subcellular components were simultaneously and label-free monitored instead of using several fluorescent labels. These results open new avenues for label-free time-resolved investigation of subcellular components in different cells, especially cancer cells.
| S-EPMC4017266 | biostudies-literature