Isotope labeled 3D-Raman confocal imaging and atomic force microscopy study on epithelial cells interacting with the fungus Candida albicans.

The human pathogenic fungus Candida albicans damages epithelial cells during superficial infections. Here we use three-dimensional-sequential-confocal Raman spectroscopic imaging and atomic force microscopy to investigate the interaction of C. albicans wild type cells, the secreted C. albicans peptide toxin candidalysin and mutant cells lacking candidalysin with epithelial cells. The candidalysin is responsible for epithelial cell damage and exhibits in its deuterated form an identifiable Raman signal in a frequency region distinct from the cellular frequency region. Vibration modes at 2100-2200 cm-1 attributed to carbon­deuterium bending and at 477 cm-1, attributed to the nitrogen­deuterium out-of-plane bending, found around the nucleus, can be assigned to deuterated candidalysin. Atomic force microscopy visualized 100 nm deep lesions on the cell and force-distance curves indicate the higher adhesion on pore surrounding after incubation with candidalysin. Candidalysin targets the plasma membrane, but is also found inside of the cytosol of epithelial cells during C. albicans infection.

The Application of Handheld Near-Infrared Spectroscopy and Raman Spectroscopic Imaging for the Identification and Quality Control of Food Products.

The following investigations describe the potential of handheld NIR spectroscopy and Raman imaging measurements for the identification and authentication of food products. On the one hand, during the last decade, handheld NIR spectroscopy has made the greatest progress among vibrational spectroscopic methods in terms of miniaturization and price/performance ratio, and on the other hand, the Raman spectroscopic imaging method can achieve the best lateral resolution when examining the heterogeneous composition of samples. The utilization of both methods is further enhanced via the combination with chemometric evaluation methods with respect to the detection, identification, and discrimination of illegal counterfeiting of food products. To demonstrate the solution to practical problems with these two spectroscopic techniques, the results of our recent investigations obtained for various industrial processes and customer-relevant product examples have been discussed in this article. Specifically, the monitoring of food extraction processes (e.g., ethanol extraction of clove and water extraction of wolfberry) and the identification of food quality (e.g., differentiation of cocoa nibs and cocoa beans) via handheld NIR spectroscopy, and the detection and quantification of adulterations in powdered dairy products via Raman imaging were outlined in some detail. Although the present work only demonstrates exemplary product and process examples, the applications provide a balanced overview of materials with different physical properties and manufacturing processes in order to be able to derive modified applications for other products or production processes.

Harnessing the power of Raman spectroscopic imaging for ophthalmology.

Eye diseases can cause great inconvenience to people's daily life; therefore, it is necessary to study the causes of ocular diseases and related physiological processes. Raman spectroscopic imaging (RSI) is a non-destructive, non-contact detection technique with the advantages of label-free, non-invasive and highly specific. Compared with other mature imaging technologies, RSI can provide real-time molecular information and high-resolution imaging at relatively low cost, making it very suitable for quantitative detection of biological molecules. RSI can reflect the overall situation of the sample, revealing the content distribution of the same substance in different areas of the sample. This review focuses on the recent advances in ophthalmology, with particular emphasis on the powerful use of RSI techniques, as well as its combination with other imaging techniques. Finally, we prospect the wider application and future potential of RSI approaches in ophthalmology.

Label-Free Characterization of Macrophage Polarization Using Raman Spectroscopy.

Macrophages are important cells of the innate immune system that play many different roles in host defense, a fact that is reflected by their polarization into many distinct subtypes. Depending on their function and phenotype, macrophages can be grossly classified into classically activated macrophages (pro-inflammatory M1 cells), alternatively activated macrophages (anti-inflammatory M2 cells), and non-activated cells (resting M0 cells). A fast, label-free and non-destructive characterization of macrophage phenotypes could be of importance for studying the contribution of the various subtypes to numerous pathologies. In this work, single cell Raman spectroscopic imaging was applied to visualize the characteristic phenotype as well as to discriminate between different human macrophage phenotypes without any label and in a non-destructive manner. Macrophages were derived by differentiation of peripheral blood monocytes of human healthy donors and differently treated to yield M0, M1 and M2 phenotypes, as confirmed by marker analysis using flow cytometry and fluorescence imaging. Raman images of chemically fixed cells of those three macrophage phenotypes were processed using chemometric methods of unmixing (N-FINDR) and discrimination (PCA-LDA). The discrimination models were validated using leave-one donor-out cross-validation. The results show that Raman imaging is able to discriminate between pro- and anti-inflammatory macrophage phenotypes with high accuracy in a non-invasive, non-destructive and label-free manner. The spectral differences observed can be explained by the biochemical characteristics of the different phenotypes.

Lipid Droplet Composition Varies Based on Medaka Fish Eggs Development as Revealed by NIR-, MIR-, and Raman Imaging.

In fertilized fish eggs, lipids are an energy reservoir for the embryo development and substrate for organogenesis. They occur in the cytoplasmic area and form lipid droplets (LDs), but also the yolk egg is composed of lipids and proteins. Insight on the LD formation and distribution and their interactions with other cellular organelles could provide information about the role based on the egg development. For non-destructive, macro-scale visualization of biochemical components of fish eggs, such as lipids proteins and water, near-infrared (NIR) imaging is the method of choice. Mid-infrared (MIR) and Raman spectroscopy imaging were used to provide details on chemical composition of LDs and other egg organelles. NIR imaging illustrated main compartments of the egg including membrane, LDs, yolk, relative protein, and lipid content in well-localized egg structures and their interactions with water molecules. In the yolk, a co-existence of lipids and proteins with carotenoids and carbohydrates was detected by Raman spectroscopy. Results showed a prominent decrease of unsaturated fatty acids, phospholipids, and triglycerides/cholesteryl esters content in the eggs due to the embryo development. An opposite trend of changes was observed by MIR spectroscopy for the glycogen, suggesting that consumption of lipids occurred with production of this carbohydrate. The comprehensive vibrational spectroscopic analysis based on NIR, MIR, and Raman imaging is a unique tool in studying in situ dynamic biological processes.

Recent Advances in Spontaneous Raman Spectroscopic Imaging: Instrumentation and Applications.

BACKGROUND: Spectroscopic imaging based on the spontaneous Raman scattering effects can provide unique fingerprint information in relation to the vibration bands of molecules. Due to its advantages of high chemical specificity, non-invasive detection capability, low sensitivity to water, and no special sample pretreatment, Raman Spectroscopic Imaging (RSI) has become an invaluable tool in the field of biomedicine and medicinal chemistry. METHODS: There are three methods to implement RSI, including point scanning, line scanning and wide-field RSI. Point-scanning can achieve two-and three-dimensional imaging of target samples. High spectral resolution, full spectral range and confocal features render this technique highly attractive. However, point scanning based RSI is a time-consuming process that can take several hours to map a small area. Line scanning RSI is an extension of point scanning method, with an imaging speed being 300-600 times faster. In the wide-field RSI, the laser illuminates the entire region of interest directly and all the images then collected for analysis. In general, it enables more accurate chemical imaging at faster speeds. RESULTS: This review focuses on the recent advances in RSI, with particular emphasis on the latest developments on instrumentation and the related applications in biomedicine and medicinal chemistry. Finally, we prospect the development trend of RSI as well as its potential to translation from bench to bedside. CONCLUSION: RSI is a powerful technique that provides unique chemical information, with a great potential in the fields of biomedicine and medicinal chemistry.

Confocal Raman spectroscopic imaging for in vitro monitoring of active ingredient penetration and distribution in reconstructed human epidermis model.

Topically applied active cosmetic ingredients (ACI) or active pharmaceutical ingredients (API) efficacy is directly related to their efficiency of penetration in the skin. In vitro reconstructed human epidermis surrogate models offer in vivo like skin samples for transdermal studies. Using Delipidol®, an ACI currently used in the cosmetics industry, the capabilities to deliver accurate distribution maps and penetration profiles of this molecule by means of confocal Raman spectroscopic imaging have been demonstrated. Using a non-negative constrained least squares (NCLS) approach, contribution of specific molecules can be estimated at each point of spectral maps in order to deliver semi-quantitative heat maps representing the ACI levels in the different skin layers. The concentration profiles obtained are approximately single exponential for all 3 time points evaluated, with a consistent decay constant, which is independent of the sublayer structure. Notably, however, there is no significant penetration into the lower basal layers until a critical concentration is built up, after 3 hours. Combination of Raman confocal imaging with spectral unmixing methods such as NCLS is demonstrated to be a relevant approach for in vitro biological evaluation of cosmetic and pharmaceutical active ingredients and could easily be implemented as a screening tool for industrial use.

Lipid Desaturation Is a Metabolic Marker and Therapeutic Target of Ovarian Cancer Stem Cells.

Lack of sensitive single-cell analysis tools has limited the characterization of metabolic activity in cancer stem cells. By hyperspectral-stimulated Raman scattering imaging of single living cells and mass spectrometry analysis of extracted lipids, we report here significantly increased levels of unsaturated lipids in ovarian cancer stem cells (CSCs) as compared to non-CSCs. Higher lipid unsaturation levels were also detected in CSC-enriched spheroids compared to monolayer cultures of ovarian cancer cell lines or primary cells. Inhibition of lipid desaturases effectively eliminated CSCs, suppressed sphere formation in vitro, and blocked tumor initiation capacity in vivo. Mechanistically, we demonstrate that nuclear factor κB (NF-κB) directly regulates the expression levels of lipid desaturases, and inhibition of desaturases blocks NF-κB signaling. Collectively, our findings reveal that increased lipid unsaturation is a metabolic marker for ovarian CSCs and a target for CSC-specific therapy.

Quantitative multi-image analysis for biomedical Raman spectroscopic imaging.

Imaging by Raman spectroscopy enables unparalleled label-free insights into cell and tissue composition at the molecular level. With established approaches limited to single image analysis, there are currently no general guidelines or consensus on how to quantify biochemical components across multiple Raman images. Here, we describe a broadly applicable methodology for the combination of multiple Raman images into a single image for analysis. This is achieved by removing image specific background interference, unfolding the series of Raman images into a single dataset, and normalisation of each Raman spectrum to render comparable Raman images. Multivariate image analysis is finally applied to derive the contributing 'pure' biochemical spectra for relative quantification. We present our methodology using four independently measured Raman images of control cells and four images of cells treated with strontium ions from substituted bioactive glass. We show that the relative biochemical distribution per area of the cells can be quantified. In addition, using k-means clustering, we are able to discriminate between the two cell types over multiple Raman images. This study shows a streamlined quantitative multi-image analysis tool for improving cell/tissue characterisation and opens new avenues in biomedical Raman spectroscopic imaging.

Novel workflow for combining Raman spectroscopy and MALDI-MSI for tissue based studies.

Molecular heterogeneity of cancer is a major obstacle in tumor diagnosis and treatment. To deal with this heterogeneity, a multidisciplinary combination of different analysis techniques is of urgent need because a combination enables the creation of a multimodal image of a tumor. Here, we develop a computational workflow in order to combine matrix-assisted laser desorption/ionization mass spectrometric (MALDI-MS) imaging and Raman microspectroscopic imaging for tissue based studies. The computational workflow can be used to confirm a spectral histopathology (SHP) based on one technique with another technique. In this contribution, we confirmed a Raman spectroscopic based SHP with MALDI-imaging. Owing to this combination, we could demonstrate, for a larynx carcinoma sample, that tissue types and different metabolic states could be extracted from the Raman spectra. Further investigations with the help of MALDI spectra yield a better characterization of variable epithelial differentiation and a better understanding of ongoing dysplastic alterations.