Raman spectroscopy can be used to measure the chemical composition of a sample, which can in turn be used to extract biological information. Many materials have characteristic Raman spectra, which means that Raman spectroscopy has proven to be an effective analytical approach in geology, semiconductor, materials and polymer science fields. The application of Raman spectroscopy and microscopy within biology is rapidly increasing because it can provide chemical and compositional information, but it does not typically suffer from interference from water molecules. Analysis does not conventionally require extensive sample preparation; biochemical and structural information can usually be obtained without labeling. In this protocol, we aim to standardize and bring together multiple experimental approaches from key leaders in the field for obtaining Raman spectra using a microspectrometer. As examples of the range of biological samples that can be analyzed, we provide instructions for acquiring Raman spectra, maps and images for fresh plant tissue, formalin-fixed and fresh frozen mammalian tissue, fixed cells and biofluids. We explore a robust approach for sample preparation, instrumentation, acquisition parameters and data processing. By using this approach, we expect that a typical Raman experiment can be performed by a nonspecialist user to generate high-quality data for biological materials analysis.

Raman microscopy is employed to spectroscopically image biological cells previously exposed to fluorescently labelled polystyrene nanoparticles and, in combination with Kmeans clustering and Principal Component Analysis (PCA), is demonstrated to be capable of localising the nanoparticles and identifying the subcellular environment based on the molecular spectroscopic signatures. The neutral nanoparticles of 50 nm or 100 nm, as characterised by dynamic light scattering, are shown to be non-toxic to a human lung adenocarcinoma cell-line (A549), according to a range of cytotoxicity assays including Neutral Red, Alamar Blue, Coomassie Blue and (3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). Confocal fluorescence microscopy identifies intracellular fluorescence due to the nanoparticle exposure, but the fluorescence distribution is spatially diffuse, potentially due to detachment of the dye from the nanoparticles, and the technique fails to unambiguously identify the distribution of the nanoparticles within the cells. Raman spectroscopic mapping of the cells in combination with K-means cluster analysis is used to clearly identify and localise the polystyrene nanoparticles in exposed cells, based on their characteristic spectroscopic signatures. PCA identifies the local environment as rich in lipidic signatures which are associated with localisation of the nanoparticles in the endoplasmic reticulum. The importance of optimised cell growth conditions and fixation processes is highlighted. The preliminary study demonstrates the potential of the technique to unambiguously identify and locate nonfluorescent nanoparticles in cells and to probe not only the local environment but also changes to the cell metabolism which may be associated with cytotoxic responses.

Three dimensional collagen gels have been used as matrices for the imaging of live cells by Raman spectroscopy. The study is conducted on a human lung adenocarcinoma (A549) and a spontaneously immortalized human epithelial keratinocyte (HaCaT) cell line. The lateral resolution of the system has been estimated to be <1.5 μm making it possible to access the subcellular organization.

Raman spectroscopy (RS) is a powerful technique that permits the non‐destructive chemical analysis of cells and tissues without the need for expensive and complex sample preparation. To date, samples have been routinely mounted onto calcium fluoride (CaF2) as this material possesses the desired mechanical and optical properties for analysis, but CaF2 is both expensive and brittle and this prevents the technique from being routinely adopted. Furthermore, Raman scattering is a weak phenomenon and CaF2 provides no means of increasing signal. For RS to be widely adopted, particularly in the clinical field, it is crucial that spectroscopists identify an alternative, low‐cost substrate capable of providing high spectral signal to noise ratios with good spatial resolution. Results show that these desired properties are attainable when using mirrored stainless steel as a Raman substrate. When compared with CaF2, data show that stainless steel has a low background signal and provides an average signal increase of 1.43 times during tissue analysis and 1.64 times when analyzing cells. This result is attributed to a double‐pass of the laser beam through the sample where the photons from the source laser and the forward scattered Raman signal are backreflected and retroreflected from the mirrored steel surface and focused towards collection optics. The spatial resolution on stainless steel is at least comparable to that on CaF2 and it is not compromised by the reflection of the laser. Steel is a fraction of the cost of CaF2 and the reflection and focusing of photons improve signal to noise ratios permitting more rapid mapping. The low cost of steel coupled with its Raman signal increasing properties and robust durability indicates that steel is an ideal substrate for biological and clinical RS as it possesses key advantages over routinely used CaF2. © 2016 The Authors. Journal of Raman Spectroscopy Published by John Wiley & Sons Ltd.

SummaryThis chapter outlines some developments in the applications of vibrational spectroscopy for disease diagnostics and demonstrates how the applications of the spectroscopic techniques can be extended to the analysis and evaluation of disease aetiology and the mechanisms of interaction with and the cellular and subcellular responses to, for example, chemotherapeutic agents and nanoparticles. The primary emphasis is on Raman spectroscopy, although some examples are based on infrared absorption spectroscopy. The studies presented are chosen to illustrate how a range of multivariate analytical techniques can be employed to maximize the potential benefits of the complex spectral information obtained from tissue or cells.