DMD-based software-configurable spatially-offset Raman spectroscopy for spectral depth-profiling of optically turbid samples

Spectral depth-profiling of optically turbid samples is of high interest to a broad range of applications. We present a method for measuring spatially-offset Raman spectroscopy (SORS) over a range of length scales by incorporating a digital micro-mirror device (DMD) into a sample-conjugate plane in the detection optical path. The DMD can be arbitrarily programmed to collect/reject light at spatial positions in the 2D sample-conjugate plane, allowing spatially offset Raman measurements. We demonstrate several detection geometries, including annular and simultaneous multi-offset modalities, for both macro- and micro-SORS measurements, all on the same instrument. Compared to other SORS modalities, DMD-based SORS provides more flexibility with only minimal additional experimental complexity for subsurface Raman collection

Holographic optical trapping Raman micro-spectroscopy for non-invasive measurement and manipulation of live cells

We present a new approach for combining holographic optical tweezers with confocal Raman spectroscopy. Multiple laser foci, generated using a liquid-crystal spatial light modulator, are individually used for both optical trapping and excitation of spontaneous Raman spectroscopy from trapped objects. Raman scattering from each laser focus is spatially filtered using reflective apertures on a digital micro-mirror device, which can be reconfigured with flexible patterns at video rate. We discuss operation of the instrument, and performance and viability considerations for biological measurements. We then demonstrate the capability of the instrument for fast, flexible, and interactive manipulation with molecular measurement of interacting live cell systems

Ex-vivo Raman spectroscopy mapping of lung tissue: label-free molecular characterisation of non-tumorous and cancerous tissues

Raman spectroscopy mapping was used to study ex vivo fresh lung tissues and compare to histology sections. The Raman mapping measurements revealed differences in the molecular composition of normal lung tissue, adenocarcinoma, and squamous cell carcinoma (SCC). Molecular heterogeneity of the tissue samples was well captured by the k-means clustering analysis of the Raman datasets, as confirmed by the correlation with the adjacent haematoxylin and eosin (H&E) stained tissue sections. The results indicate that the fluorescence background varies considerably even in samples that appear structurally uniform in the H&E images, both for normal and tumor tissue. The results show that characteristic Raman bands can be used to discriminate between tumorous and nontumorous lung tissues and between adenocarcinoma and SCC tissues. These results indicate the potential to develop Raman classifications models for lung tissues based on the Raman spectral differences at the microscopic level, which can be used for tissue diagnosis or treatment stratification

Raman spectroscopy for medical diagnostics - From in-vitro biofluid assays to in-vivo cancer detection

This is the final version of the article. Available from the publisher via the DOI in this record.Raman spectroscopy is an optical technique based on inelastic scattering of light by vibrating molecules and can provide chemical fingerprints of cells, tissues or biofluids. The high chemical specificity, minimal or lack of sample preparation and the ability to use advanced optical technologies in the visible or near-infrared spectral range (lasers, microscopes, fibre-optics) have recently led to an increase in medical diagnostic applications of Raman spectroscopy. The key hypothesis underpinning this field is that molecular changes in cells, tissues or biofluids, that are either the cause or the effect of diseases, can be detected and quantified by Raman spectroscopy. Furthermore, multivariate calibration and classification models based on Raman spectra can be developed on large "training" datasets and used subsequently on samples from new patients to obtain quantitative and objective diagnosis. Historically, spontaneous Raman spectroscopy has been known as a low signal technique requiring relatively long acquisition times. Nevertheless, new strategies have been developed recently to overcome these issues: non-linear optical effects and metallic nanoparticles can be used to enhance the Raman signals, optimised fibre-optic Raman probes can be used for real-time in-vivo single-point measurements, while multimodal integration with other optical techniques can guide the Raman measurements to increase the acquisition speed and spatial accuracy of diagnosis. These recent efforts have advanced Raman spectroscopy to the point where the diagnostic accuracy and speed are compatible with clinical use. This paper reviews the main Raman spectroscopy techniques used in medical diagnostics and provides an overview of various applications

Monitoring the mineralisation of bone nodules in vitro by space- and time-resolved Raman micro-spectroscopy.

Raman microscopy was used as a label-free method to study the mineralisation of bone nodules formed by mesenchymal stem cells cultured in osteogenic medium in vitro. Monitoring individual bone nodules over 28 days revealed temporal and spatial changes in the crystalline phase of the hydroxyapatite components of the nodules

Label-free Raman hyperspectral imaging of single cells cultured on polymer substrates

While Raman hyper-spectral imaging has been widely used for label-free mapping of biomolecules in cells, these measurements require the cells to be cultured on weakly Raman scattering substrates. However, many applications in biological sciences and engineering require the cells to be cultured on polymer substrates that often generate large Raman scattering signals. Here, we discuss the theoretical limits of the signal-to-noise ratio in the Raman spectra of cells in the presence of polymer signals and how optical aberrations may affect these measurements. We show that Raman spectra of cells cultured on polymer substrates can be obtained using automatic subtraction of the polymer signals and demonstrate the capabilities of these methods in two important applications: tissue engineering and in-vitro toxicology screening of drugs. Apart from their scientific and technological importance, these applications are examples of the two most common measurement configurations: 1) cells cultured on an optically thick polymer substrate measured using an immersion/dipping objective; 2) cells cultured on a transparent polymer substrate and measured using an inverted optical microscope. In these examples we show that Raman hyperspectral datasets with sufficient quality can be successfully acquired to map the distribution of common biomolecules in cells, such as nucleic acids, proteins and lipids, as well as detecting the early stages of apoptosis. We also discuss strategies for further improvements that could expand the application of Raman hyperspectral imaging on polymer substrates even further in biomedical sciences and engineering

Applications of Raman micro-spectroscopy to stem cell technology: label-free molecular discrimination and monitoring cell differentiation.

Stem cell therapy is widely acknowledged as a key medical technology of the 21st century which may provide treatments for many currently incurable diseases. These cells have an enormous potential for cell replacement therapies to cure diseases such as Parkinson's disease, diabetes and cardiovascular disorders, as well as in tissue engineering as a reliable cell source for providing grafts to replace and repair diseased tissues. Nevertheless, the progress in this field has been difficult in part because of lack of techniques that can measure non-invasively the molecular properties of cells. Such repeated measurements can be used to evaluate the culture conditions during differentiation, cell quality and phenotype heterogeneity of stem cell progeny. Raman spectroscopy is an optical technique based on inelastic scattering of laser photons by molecular vibrations of cellular molecules and can be used to provide chemical fingerprints of cells or organelles without fixation, lysis or use of labels and other contrast enhancing chemicals. Because differentiated cells are specialized to perform specific functions, these cells produce specific biochemicals that can be detected by Raman micro-spectroscopy. This mini-review paper describes applications of Raman micro-scpectroscopy to measure moleculare properties of stem cells during differentiation in-vitro. The paper focuses on time- and spatially-resolved Raman spectral measurements that allow repeated investigation of live stem cells in-vitro

Towards quantitative molecular mapping of cells by Raman microscopy: Using AFM for decoupling molecular concentration and cell topography

Raman micro-spectroscopy (RMS) is a non-invasive technique for imaging live cells in vitro. However, obtaining quantitative molecular information from Raman spectra is difficult because the intensity of a Raman band is proportional to the number of molecules in the sampled volume, which depends on the local molecular concentration and the thickness of the cell. In order to understand these effects, we combined RMS with atomic force microscopy (AFM), a technique that can measure accurately the thickness profile of the cells. Solution-based calibration models for RNA and albumin were developed to create quantitative maps of RNA and proteins in individual fixed cells. The maps were built by applying the solution-based calibration models, based on partial least squares fitting (PLS), on raster-scan Raman maps, after accounting for the local cell height obtained from the AFM. We found that concentrations of RNA in the cytoplasm of mouse neuroprogenitor stem cells (NSCs) were as high as 25 ± 6 mg ml-1, while proteins were distributed more uniformly and reached concentrations as high as ∼50 ± 12 mg ml-1. The combined AFM-Raman datasets from fixed cells were also used to investigate potential improvements for normalization of Raman spectral maps. For all Raman maps of fixed cells (n = 10), we found a linear relationship between the scores corresponding to the first component (PC1) and the cell height profile obtained by AFM. We used PC1 scores to reconstruct the relative height profiles of independent cells (n = 10), and obtained correlation coefficients with AFM maps higher than 0.99. Using this normalization method, qualitative maps of RNA and protein were used to obtain concentrations for live NSCs. While this study demonstrates the potential of using AFM and RMS for measuring concentration maps for individual NSCs in vitro, further studies are required to establish the robustness of the normalization method based on principal component analysis when comparing Raman spectra of cells with large morphological differences

In-situ fabrication of gold nanoparticle functionalized probes for tip-enhanced Raman spectroscopy by dielectrophoresis

We report the use of dielectrophoresis to fabricate in-situ probes for tip-enhanced Raman spectroscopy (TERS) based on Au nanoparticles. A typical conductive atomic force microscope (AFM) was used to functionalize iridium-coated conductive silicon probes with Au nanoparticles of 10-nm diameter. Suitable TERS probes can be rapidly produced (30 to 120 s) by applying a voltage of 10 Vpp at a frequency of 1 MHz. The technique has the advantage that the Au-based probes are ready for immediate use for TERS measurements, minimizing the risks of tip contamination and damage during handling. Scanning electron microscopy and energy dispersive x-ray spectroscopy were used to confirm the quality of the probes, and used samples of p-ATP monolayers on silver substrates were used to demonstrate experimentally TERS measurements

Cytoplasmic RNA in undifferentiated neural stem cells: a potential label-free Raman spectral marker for assessing the undifferentiated status

Raman microspectroscopy (rms) was used to identify, image, and quantify potential molecular markers for label-free monitoring the differentiation status of live neural stem cells (NSCs) in vitro. Label-free noninvasive techniques for characterization of NCSs in vitro are needed as they can be developed for real-time monitoring of live cells. Principal component analysis (PCA) and linear discriminant analysis (LDA) models based on Raman spectra of undifferentiated NSCs and NSC-derived glial cells enabled discrimination of NSCs with 89.4% sensitivity and 96.4% specificity. The differences between Raman spectra of NSCs and glial cells indicated that the discrimination of the NSCs was based on higher concentration of nucleic acids in NSCs. Spectral images corresponding to Raman bands assigned to nucleic acids for individual NSCs and glial cells were compared with fluorescence staining of cell nuclei and cytoplasm to show that the origin of the spectral differences were related to cytoplasmic RNA. On the basis of calibration models, the concentration of the RNA was quantified and mapped in individual cells at a resolution of ~700 nm. The spectral maps revealed cytoplasmic regions with concentrations of RNA as high as 4 mg/mL for NSCs while the RNA concentration in the cytoplasm of the glial cells was below the detection limit of our instrument (~1 mg/mL). In the light of recent reports describing the importance of the RNAs in stem cell populations, we propose that the observed high concentration of cytoplasmic RNAs in NSCs compared to glial cells is related to the repressed translation of mRNAs, higher concentrations of large noncoding RNAs in the cytoplasm as well as their lower cytoplasm volume. While this study demonstrates the potential of using rms for label-free assessment of live NSCs in vitro, further studies are required to establish the exact origin of the increased contribution of the cytoplasmic RNA