title: Differential sensing for the regio- and stereoselective identification and quantitation of glycerides.
abstract: Glycerides are of interest to the areas of food science and medicine because they are the main component of fat. From a chemical sensing perspective, glycerides are challenging analytes because they are structurally similar to one another and lack diversity in terms of functional groups. Furthermore, because animal and plant fat consists of a number of stereo- and regioisomeric acylglycerols, their components remain challenging analytes for chromatographic and mass spectrometric determination, particularly the quantitation of species in mixtures. In this study, we demonstrated the use of an array of cross-reactive serum albumins and fluorescent indicators with chemometric analysis to differentiate a panel of mono-, di-, and triglycerides. Due to the difficulties in identifying the regio- and stereochemistry of the unsaturated glycerides, a sample pretreatment consisting of olefin cross-metathesis with an allyl fluorescein species was used before array analysis. Using this simple assay, we successfully discriminated 20 glycerides via principal component analysis and linear discriminant analysis (PCA and LDA, respectively), including stereo- and regioisomeric pairs. The resulting chemometric patterns were used as a training space for which the structural characteristics of unknown glycerides were identified. In addition, by using our array to perform a standard addition analysis on a mixture of triglycerides and using a method introduced herein, we demonstrated the ability to quantitate glyceride components in a mixture.
authors.affiliation: Department of Chemistry, University of Texas at Austin, Austin, TX 78712;
authors.forename: Katharine L
authors.initials: KL
authors.lastname: Diehl
authors.affiliation: Department of Chemistry, University of Texas at Austin, Austin, TX 78712;
authors.forename: Michelle Adams
authors.initials: MA
authors.lastname: Ivy
authors.affiliation: Institute for Computational Engineering and Science, University of Texas at Austin, Austin, TX 78712;
authors.forename: Scott
authors.initials: S
authors.lastname: Rabidoux
authors.affiliation: Sanofi-Aventis Deutschland GmbH, 65926 Frankfurt, Germany;
authors.forename: Stefan Matthias
authors.initials: SM
authors.lastname: Petry
authors.affiliation: Institute for Diabetes and Obesity, Helmholtz Diabetes Center at Helmholtz Zentrum München, 85764 Neuherberg, Germany.
authors.forename: Günter
authors.initials: G
authors.lastname: Müller
authors.affiliation: Department of Chemistry, University of Texas at Austin, Austin, TX 78712; anslyn@austin.utexas.edu.
authors.forename: Eric V
authors.initials: EV
authors.lastname: Anslyn
mesh_terms: D000465:Algorithms; D000475:Alkenes / Q000737:chemistry; D000818:Animals; D003924:Diabetes Mellitus, Type 2 / Q000378:metabolism; D005456:Fluorescent Dyes / Q000737:chemistry; D005989:Glycerides / Q000737:chemistry*; D006801:Humans; D050356:Lipid Metabolism; D013058:Mass Spectrometry; D009765:Obesity / Q000378:metabolism; D025341:Principal Component Analysis; D011506:Proteins / Q000737:chemistry; D012709:Serum Albumin / Q000737:chemistry; D013237:Stereoisomerism; D014280:Triglycerides / Q000737:chemistry
chemical_list: D000475:Alkenes; D005456:Fluorescent Dyes; D005989:Glycerides; D011506:Proteins; D012709:Serum Albumin; D014280:Triglycerides
keywords: array sensing; chemometrics; differential sensing; glyceride; serum albumin