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

International Journal of Molecular Sciences

Giuseppe Pezzotti¹  Elia Marin¹  Wenliang Zhu¹  Hayata Imamura¹  Tamaki Nakaya¹  Toshiro Yamamoto²  Narisato Kanamura²  Tetsuya Adachi²  Nao Miyamoto²  Osam Mazda³  Eriko Ohgitani³  Ichiro Nishimura⁴  Miyuki Kobara⁵  Tetsuo Nakata⁵  Koichi Makimura⁶ 

[1] Ceramic Physics Laboratory, Kyoto Institute of Technology, Sakyo-ku, Matsugasaki, Kyoto 606-8585, Japan;Department of Dental Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan;Department of Immunology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kamigyo-ku, 465 Kajii-cho, Kyoto 602-8566, Japan;Division of Advanced Prosthodontics, The Jane and Jerry Weintraub Center for Reconstructive Biotechnology, UCLA School of Dentistry, Los Angeles, CA 90095, USA;Division of Pathological Science, Department of Clinical Pharmacology, Kyoto Pharmaceutical University, 5 Misasagi Nakauchi-cho, Yamashina-ku, Kyoto 607-8414, Japan;Medical Mycology, Graduate School of Medicine, Teikyo University, Itabashi-ku, Tokyo 173-8605, Japan;

关键词: Raman spectroscopy;    Candida;    chemometrics;    barcode;    molecular analyses;   

DOI  :  10.3390/ijms23105359

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown