Quantification of Sugars and Organic Acids in Biological Matrices Using GC-QqQ-MS

Jayasinghe, N, Mendis, H, Roessner, U and Dias, D 2018, 'Quantification of Sugars and Organic Acids in Biological Matrices Using GC-QqQ-MS' in Carla Antonio (ed.) Plant Metabolomics, Humana Press, New York, USA, pp. 207-223.

Document type: Book Chapter
Collection: Book Chapters

Title Quantification of Sugars and Organic Acids in Biological Matrices Using GC-QqQ-MS
Author(s) Jayasinghe, N
Mendis, H
Roessner, U
Dias, D
Year 2018
Title of book Plant Metabolomics
Publisher Humana Press
Place of publication New York, USA
Editor(s) Carla Antonio
Start page 207
End page 223
Subjects Analytical Biochemistry
Medical Biochemistry and Metabolomics not elsewhere classified
Summary Gas chromatography coupled with triple quadrupole mass spectrometry (GC-QqQ-MS) can be used to accurately quantify endogenous small molecules extracted from biological samples such as plants and human fluids including sera and urine. In order to quantify primary metabolites typically from central carbon metabolism such as sugars from glycolysis and the pentose phosphate pathway; and organic acids involved in the tricarboxylic acid (TCA) cycle; polar endogenous metabolites must be extracted from the samples of interest, chemically derivatized and quantified against a linear calibration curve to a corresponding authentic standard. This chapter describes how to quantify a combination of 48 primary metabolites belonging to classes of sugars, sugar alcohols, sugar acids, sugar phosphates, and organic acids using a robust, optimized, multiple reaction monitoring (MRM)-based GC-QqQ-MS method.
Copyright notice © Springer Science+Business Media, LLC, part of Springer Nature 2018
Keyword(s) GC-QqQ-MS
Organic acids
Carbon central metabolism
DOI - identifier 10.1007/978-1-4939-7819-9_15
ISBN 9781493978182
Version Filter Type
Altmetric details:
Access Statistics: 17 Abstract Views  -  Detailed Statistics
Created: Thu, 21 Feb 2019, 12:10:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us