Publication details
Možnosť rozlíšenia klinicky významných kvasiniek pomocou Ramanovej spektroskopie
| Title in English | Resolution of clinically significant yeasts by Raman spectroscopy |
|---|---|
| Authors | |
| Year of publication | 2023 |
| Type | Appeared in Conference without Proceedings |
| MU Faculty or unit | |
| Citation | |
| Description | Raman spectroscopy is an important analytical method of vibrational spectroscopy. It is based on the so-called Raman phenomenon - inelastic scattering of monochromatic radiation, which incident on the sample under examination. This method is used in various disciplines in the analysis of a wide range of organic and inorganic samples. Increasing attention and space in recent years in the field of microbiology, where it is used for various analyses microorganisms. This thesis focuses on the possibilities of using Raman spectroscopy for discriminating between species of clinically important yeasts of the genus Candida. In this work, approximately 300 yeast strains belonging to 23 clinically important species of the genus Candida. Candida were cultured on Mueller-Hinton agar for 24 h at 37°C. The grown colonies were directly on the medium were analysed using a commercial inVia Raman microspectrometer (Renishaw plc., Wotton-under-Edge, UK) using a diode laser with a wavelength of 785 nm as the excitation source. The Raman spectra obtained were then processed using machine learning methods for identification. The resulting identification of each strain was then was compared with the identification result using MALDI-TOF mass spectrometry. The results obtained demonstrated the very good ability of Raman spectroscopy to discriminate between clinically important species of the genus Candida. Therefore, it can be said that Raman spectroscopy has the potential to become a suitable method for identification and discrimination of clinically important yeast species. Application of this method in routine laboratory work could help to speed up the diagnosis of yeast infections. |
| Related projects: |