Meso-Raman approach for rapid yeast cells identification

Abstract

An increasing effort is currently devoted to developing Raman spectroscopy for identification of microorganisms. Micro-Raman setups are typically used for this purpose with the limit that the intra-species and inter-species spectral variability are comparable, thus limiting the identification capability. To overcome this limit a meso-Raman approach is here implemented. Thin films of planktonic cells are analyzed throughout the collection of back-scattered light providing a Raman signal already averaged over tens of cells. The collecting of unpolarized (VU) and depolarized (HV) Raman signals increased the spectral information obtainable from the data, demonstrating the ability of the principal component analysis to differentiate the most common Candida species, namely C. glabrata, C. albicans, C. parapsilosis and C. tropicalis. The proposed method can contribute to bring Raman spectroscopy closer to its potential clinical use for fast identification of yeast cells.