Identifying yeasts using surface enhanced Raman spectroscopy.


Journal

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
ISSN: 1873-3557
Titre abrégé: Spectrochim Acta A Mol Biomol Spectrosc
Pays: England
ID NLM: 9602533

Informations de publication

Date de publication:
05 Jul 2019
Historique:
received: 22 01 2019
revised: 05 04 2019
accepted: 07 04 2019
pubmed: 22 4 2019
medline: 27 8 2019
entrez: 22 4 2019
Statut: ppublish

Résumé

The molecular fingerprints of yeasts Saccharomyces cerevisiae, Dekkera bruxellensis, and Wickerhamomyces anomalus (former name Pichia anomala) have been examined using surface-enhanced Raman spectroscopy (SERS) and helium ion microscopy (HIM). The SERS spectra obtained from cell cultures (lysate and non-treated cells) distinguish between these very closely related fungal species. Highly SERS active silver nano-particles suitable for detecting complex biomolecules were fabricated using a simple synthesis route. The yeast samples mixed with aggregated Ag nanoparticles yielded highly enhanced and reproducible Raman signal owing to the high density of the hot spots at the junctions of two or more Ag nanoparticles and enabled to differentiate the three species based on their unique features (spectral fingerprint). We also collected SERS spectra of the three yeast species in beer medium to demonstrate the potential of the method for industrial application. These findings demonstrate the great potential of SERS for detection and identification of fungi species based on the biochemical compositions, even in a chemically complex sample.

Identifiants

pubmed: 31005737
pii: S1386-1425(19)30385-3
doi: 10.1016/j.saa.2019.04.010
pii:
doi:

Substances chimiques

Silver 3M4G523W1G

Types de publication

Journal Article

Langues

eng

Pagination

299-307

Informations de copyright

Copyright © 2019 Elsevier B.V. All rights reserved.

Auteurs

Tibebe Lemma (T)

Faculdade de Clências e Tecnologia (FCT)-Universidade Estadual Paulista (UNESP)-Presidente Prudente, SP 19060-900, Brazil. Electronic address: tlemma@gmail.com.

Jin Wang (J)

Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui 230031, PR China.

Kai Arstila (K)

NanoScience Center, Department of Physics, P.O. Box 35 (YN), FI-40014, University of Jyväskylä, Finland.

Vesa P Hytönen (VP)

Faculty of Medicine and Health Technology, BioMediTech, Tampere University, Arvo Ylpön katu 34, FI-33520 Tampere, Finland; Fimlab Laboratories, Biokatu 4, FI-33520 Tampere, Finland.

J Jussi Toppari (JJ)

NanoScience Center, Department of Physics, P.O. Box 35 (YN), FI-40014, University of Jyväskylä, Finland.

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Classifications MeSH