Oral candidiasis, a common opportunistic infection of the oral cavity, is mainly caused by the following four species (in decreasing incidence rate): , , , and . This study offers in-depth Raman spectroscopy analyses of these species and proposes procedures for an accurate and rapid identification of oral yeast species. We first obtained average spectra for different species and systematically analyzed them in order to decode structural differences among species at the molecular scale. Then, we searched for a statistical validation through a chemometric method based on principal component analysis (PCA). This method was found only partially capable to mechanistically distinguish among species. We thus proposed a new Raman barcoding approach based on an algorithm that converts spectrally deconvoluted Raman sub-bands into barcodes. Barcode-assisted Raman analyses could enable on-site identification in nearly real-time, thus implementing preventive oral control, enabling prompt selection of the most effective drug, and increasing the probability to interrupt disease transmission.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141024 | PMC |
| http://dx.doi.org/10.3390/ijms23105359 | DOI Listing |
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