Abstract
The stratum corneum (SC) is the uppermost tissue of the skin. It protects the body against external impacts and prevents it from desiccation. The stratum corneum is a thin tissue of ∼20 µm, which is mainly composed of two fractions: lipids and proteins. The proteins are located in the corneocytes and these cells are embedded in a continuous lipid matrix.Stratum corneum has not yet been examined in detail by infrared spectroscopy at a lateral spatial resolution of 20 × 20 µm, which is required for resolutions at the level of individual cells. The current study reports mid Fourier transform infrared microspectroscopic (M-FTIR-MSP) analyses of porcine SC and single corneocyte cells with the aim to identify the specific molecular components that contribute to its infrared spectrum. In contrast to standard light microscopy based procedures, the infrared approach requires neither time consuming sample staining nor fixation. It is therefore, a non-invasive and rapid bio-analytical method.In addition to this, the different SC fractions were also analysed by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy.Characteristic biomarker bands have been recognized. The lipid fraction can easily be identified by the strong methylene stretching vibrations as well as by the carbonyl ester band, which were absent in the M-FTIR-MSP spectra obtained from single corneocytes. The amide I and II as well as the symmetric methyl absorptions are clearly assigned to the protein fraction and can be used for tissue protein identification. In addition to this, the corneocyte fraction can also be characterised by a band located around 3070 cm−1, which is attributed to the amide B vibration.The analysis of the IR data reveals a high sensitivity of the infrared spectroscopy approach toward changes in tissue biochemistry and variation in SC tissue architecture and organisation. This study is a prerequisite for future studies aimed at the development of infrared microspectroscopic imaging techniques as a complementing diagnostic tool for the characterisation of tissues.
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