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Yeast cell wall - Silver nanoparticles interaction: A synergistic approach between surface-enhanced Raman scattering and computational spectroscopy tools.

Abstract

Candida species are becoming one of the pathogens developing antifungal resistance due to inappropriate treatment and overuse of antimycotic drugs in building construction and agriculture. Further, fungal infections are often difficult to detect, also due to slow in vitro growth of the organisms from clinical specimens. Thus, fast detection and discrimination of yeast cells in direct patient materials is essential for an adequate treatment and success rate. In this work, we investigated Candida species isolated from patients, by using surface-enhanced Raman scattering (SERS) combined with computational spectroscopy tools, aiming to detect and discriminate between the three considered species, Candida albicans, Candida glabrata, and Candida parapsilosis. Density functional theory (DFT) was used to calculate Raman spectra of yeasts' main cell wall components for elucidating the origin of the observed bands. Accurate assignments of normal modes helped for a better understanding of the interaction between silver nanoparticles with yeasts' cell wall. Further, SERS spectra were used as samples in a database on which we performed multivariate analyses. By Principal component analysis (PCA), we obtained a maximum variation of 79% between the three samples. Linear discriminant analysis (LDA) was successfully used to discriminate between the three species.

Authors+Show Affiliations

Department of Molecular and Biomolecular Physics, National Institute of R&D of Isotopic and Molecular Technologies, Donat 67-103, 400293 Cluj-Napoca, Romania; Faculty of Physics, Babeș-Bolyai University, Kogălniceanu 1, 400084 Cluj-Napoca, Romania.Department of Molecular and Biomolecular Physics, National Institute of R&D of Isotopic and Molecular Technologies, Donat 67-103, 400293 Cluj-Napoca, Romania. Electronic address: nicoleta.dina@itim-cj.ro.Faculty of Physics, Babeș-Bolyai University, Kogălniceanu 1, 400084 Cluj-Napoca, Romania.Max von Pettenkofer-Institut für Hygiene und Medizinische Mikrobiologie, Ludwig-Maximilians-University, Marchinoninistr. 17, 82377 Munich, Germany; Division of Infectious Diseases and Tropical Medicine, Medical Center of the University of Munich (LMU), Leopoldstr. 5, 80802 Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, D-80802 Munich, Germany.Chair for Analytical Chemistry, Institute of Hydrochemistry, Technische Universität München, Marchioninistrasse 17, 81377 Munich, Germany.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31177002

Citation

Gherman, Ana Maria Raluca, et al. "Yeast Cell Wall - Silver Nanoparticles Interaction: a Synergistic Approach Between Surface-enhanced Raman Scattering and Computational Spectroscopy Tools." Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy, vol. 222, 2019, p. 117223.
Gherman AMR, Dina NE, Chiș V, et al. Yeast cell wall - Silver nanoparticles interaction: A synergistic approach between surface-enhanced Raman scattering and computational spectroscopy tools. Spectrochim Acta A Mol Biomol Spectrosc. 2019;222:117223.
Gherman, A. M. R., Dina, N. E., Chiș, V., Wieser, A., & Haisch, C. (2019). Yeast cell wall - Silver nanoparticles interaction: A synergistic approach between surface-enhanced Raman scattering and computational spectroscopy tools. Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy, 222, p. 117223. doi:10.1016/j.saa.2019.117223.
Gherman AMR, et al. Yeast Cell Wall - Silver Nanoparticles Interaction: a Synergistic Approach Between Surface-enhanced Raman Scattering and Computational Spectroscopy Tools. Spectrochim Acta A Mol Biomol Spectrosc. 2019 Nov 5;222:117223. PubMed PMID: 31177002.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Yeast cell wall - Silver nanoparticles interaction: A synergistic approach between surface-enhanced Raman scattering and computational spectroscopy tools. AU - Gherman,Ana Maria Raluca, AU - Dina,Nicoleta Elena, AU - Chiș,Vasile, AU - Wieser,Andreas, AU - Haisch,Christoph, Y1 - 2019/05/31/ PY - 2018/11/03/received PY - 2019/05/29/revised PY - 2019/05/29/accepted PY - 2019/6/10/pubmed PY - 2019/6/10/medline PY - 2019/6/10/entrez KW - Candida species KW - Density functional theory KW - Linear discriminant analysis KW - Principal component analysis KW - Surface-enhanced Raman scattering SP - 117223 EP - 117223 JF - Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy JO - Spectrochim Acta A Mol Biomol Spectrosc VL - 222 N2 - Candida species are becoming one of the pathogens developing antifungal resistance due to inappropriate treatment and overuse of antimycotic drugs in building construction and agriculture. Further, fungal infections are often difficult to detect, also due to slow in vitro growth of the organisms from clinical specimens. Thus, fast detection and discrimination of yeast cells in direct patient materials is essential for an adequate treatment and success rate. In this work, we investigated Candida species isolated from patients, by using surface-enhanced Raman scattering (SERS) combined with computational spectroscopy tools, aiming to detect and discriminate between the three considered species, Candida albicans, Candida glabrata, and Candida parapsilosis. Density functional theory (DFT) was used to calculate Raman spectra of yeasts' main cell wall components for elucidating the origin of the observed bands. Accurate assignments of normal modes helped for a better understanding of the interaction between silver nanoparticles with yeasts' cell wall. Further, SERS spectra were used as samples in a database on which we performed multivariate analyses. By Principal component analysis (PCA), we obtained a maximum variation of 79% between the three samples. Linear discriminant analysis (LDA) was successfully used to discriminate between the three species. SN - 1873-3557 UR - https://www.unboundmedicine.com/medline/citation/31177002/Yeast_cell_wall_-_Silver_nanoparticles_interaction:_A_synergistic_approach_between_surface-enhanced_Raman_scattering_and_computational_spectroscopy_tools L2 - https://linkinghub.elsevier.com/retrieve/pii/S1386-1425(19)30613-4 DB - PRIME DP - Unbound Medicine ER -