International Journal of Molecular Sciences (May 2022)

Raman Spectroscopy of Oral <i>Candida</i> Species: Molecular-Scale Analyses, Chemometrics, and Barcode Identification

  • Giuseppe Pezzotti,
  • Miyuki Kobara,
  • Tamaki Nakaya,
  • Hayata Imamura,
  • Nao Miyamoto,
  • Tetsuya Adachi,
  • Toshiro Yamamoto,
  • Narisato Kanamura,
  • Eriko Ohgitani,
  • Elia Marin,
  • Wenliang Zhu,
  • Ichiro Nishimura,
  • Osam Mazda,
  • Tetsuo Nakata,
  • Koichi Makimura

DOI
https://doi.org/10.3390/ijms23105359
Journal volume & issue
Vol. 23, no. 10
p. 5359

Abstract

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Oral candidiasis, a common opportunistic infection of the oral cavity, is mainly caused by the following four Candida species (in decreasing incidence rate): Candida albicans, Candida glabrata, Candida tropicalis, and Candida krusei. 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 Candida 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 Candida 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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