title: Combining near infrared spectroscopy and multivariate analysis as a tool to differentiate different strains of Saccharomyces cerevisiae: a metabolomic study.
abstract: Near-infrared (NIR) spectroscopy has gained wide acceptance within the food and agriculture industries as a rapid analytical tool. NIR spectroscopy offers the advantage of rapid, non-destructive analysis and routine operation is simple and opens the possibility of using spectra to obtain the 'fingerprint' of a sample. The aim of this study was to explore the potential of combining visible (VIS) and near-infrared (NIR) spectroscopy, together with multivariate analysis, in establishing the function of genes, by investigating the metabolic profiles produced by Saccharomyces cerevisiae deletion strains sourced from the EUROSCARF yeast collection. Spectra (400-2500 nm) were acquired with a FOSS NIRSystems6500 (Foss NIRSystems), in transmittance mode. Principal component analysis (PCA) and linear discriminant analysis (LDA) were used in order to visualize graphically the relative differences and similarities of yeast deletion strains. VIS and NIR spectroscopy showed great promise as a screening tool for both discriminating between yeast strains and grouping strains with deletions in genes that disturb similar metabolic pathways. These results indicate that the methods may be useful in defining the function of genes that produce no obvious phenotype.
authors.affiliation: The Australian Wine Research Institute, Glen Osmond, SA, Australia. daniel.cozzolino@awri.com.au
authors.forename: D
authors.initials: D
authors.lastname: Cozzolino
authors.forename: L
authors.initials: L
authors.lastname: Flood
authors.forename: J
authors.initials: J
authors.lastname: Bellon
authors.forename: M
authors.initials: M
authors.lastname: Gishen
authors.forename: M
authors.initials: M
authors.lastname: De Barros Lopes
mesh_terms: D016002:Discriminant Analysis; D016018:Least-Squares Analysis; D015999:Multivariate Analysis; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism*; D012680:Sensitivity and Specificity; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D014920:Wine