Chemometric evaluation of Saccharomyces cerevisiae metabolic profiles using LC–MS

A new Liquid Chromatography Mass Spectrometry (LC-MS) metabolomics strategy coupled to chemometric evaluation, including variable and biomarker selection, has been assessed as a tool to discriminate between control and stressed Saccharomyces cerevisiae yeast samples. Metabolic changes occurring duri...

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Detalles Bibliográficos
Autores: Farrés, Mireia, Piña, Benjamín, Tauler, Romà
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2014
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/108371
Acceso en línea:http://hdl.handle.net/10261/108371
Access Level:acceso abierto
Palabra clave:LC-MS
Liquid Chromatography Mass Spectrometry
chemometric evaluation
Saccharomyces cerevisiae
Descripción
Sumario:A new Liquid Chromatography Mass Spectrometry (LC-MS) metabolomics strategy coupled to chemometric evaluation, including variable and biomarker selection, has been assessed as a tool to discriminate between control and stressed Saccharomyces cerevisiae yeast samples. Metabolic changes occurring during yeast culture at different temperatures (30 ºC and 42 ºC) were analysed and the complex data generated in profiling experiments were evaluated by different chemometric multivariate approaches. Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) was applied to full spectral scan LC-MS preprocessed data multisets arranged in augmented column-wise data matrices. The results showed that sectioning the MS-chromatograms in different windows and analysing them by MCR-ALS enabled the proper resolution of very complex coeluted chromatographic peaks. The investigation of possible relationships between MCR-ALS resolved chromatographic peak areas and culture temperature was then investigated by Partial Least Squares Discriminant Analysis (PLS-DA). Selection of most relevant resolved chromatographic peaks associated to yeast culture temperature changes was achieved according to PLS-DA- Variable Importance in Projection (VIP) scores. A metabolite identification workflow was developed utilizing MCR-ALS resolved pure MS spectra and high-resolution accurate mass measurements to confirm assigned structures based on entries in metabolite databases. A total of 65 metabolites were identified. A preliminary interpretation of these results indicates that the strategy described in this study can be proposed as a general tool to facilitate biomarker identification and modelling in similar untargeted metabolomic studies.