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RESEARCH PRODUCT

Identifying yeasts using surface enhanced Raman spectroscopy

Kai ArstilaJin WangVesa P. HytönenTibebe LemmaJ. Jussi Toppari

subject

SilverPichia anomalaWickerhamomyces anomalusSurface PropertiesSaccharomyces cerevisiaeMetal Nanoparticles02 engineering and technologySaccharomyces cerevisiaeheliumyeast010402 general chemistrySpectrum Analysis Raman01 natural sciencesSilver nanoparticlePichiaAnalytical ChemistryBiokemia solu- ja molekyylibiologia - Biochemistry cell and molecular biologysymbols.namesakehiivaYeastsaggregaatitMycological Typing TechniquesInstrumentationSpectroscopychemistry.chemical_classificationChromatographyta114biologyDekkeraChemistrySERSBiomoleculehopeasilver nanoparticleSurface-enhanced Raman spectroscopy021001 nanoscience & nanotechnologybiology.organism_classificationAtomic and Molecular Physics and OpticsYeastYeast0104 chemical sciences3. Good healthaggregatesymbolshelium ion microscopynanohiukkaset0210 nano-technologyRaman spectroscopy

description

Made available in DSpace on 2019-10-06T15:40:09Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-07-05 Tekes Academy of Finland Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) 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. Faculdade de Clências e Tecnologia (FCT)-Universidade Estadual Paulista (UNESP)-Presidente Prudente Institute of Intelligent Machines Chinese Academy of Sciences NanoScience Center Department of Physics University of Jyväskylä, P.O. Box 35 (YN) Faculty of Medicine and Health Technology BioMediTech Tampere University, Arvo Ylpön katu 34 Fimlab Laboratories, Biokatu 4 Faculdade de Clências e Tecnologia (FCT)-Universidade Estadual Paulista (UNESP)-Presidente Prudente Tekes: 1185/31/2013 Academy of Finland: 136288 FAPESP: 2013/14262-7 FAPESP: 2016/06424-5 Academy of Finland: 263526

yearjournalcountryeditionlanguage
2019-01-01
http://urn.fi/URN:NBN:fi:jyu-201904232240