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Current Analytical Chemistry


ISSN (Print): 1573-4110
ISSN (Online): 1875-6727

Research Article

Tagging Fatty Acids Via Choline Coupling for the Detection of Carboxylic Acid Metabolites in Biological Samples

Author(s): Murad N. Abualhasan* and David G. Watson

Volume 15 , Issue 6 , 2019

Page: [642 - 647] Pages: 6

DOI: 10.2174/1573411014666180516093353

open access plus


Background: Fatty acids and other metabolites containing a carboxyl group are of high interest in biomedicine because of their major role in many metabolic pathways and, particularly in the case of oxidised fatty acids, their high biological activity. Tagging carboxylic acid compounds with a permanent positive charge such as a quaternary ammonium compound could increase the LC-MS detection sensitivity and selectivity. This paper describes a new and novel strategy for analysing carboxylcontaining compounds in biological samples by ESI-MS through coupling to choline.

Methods: Coupling of carboxylic acid derivatives in biological samples was performed by coupling to 2-Fluoro-1, 3 dimethyl –pyridinium (FDMP). The variation in the fatty acid profile of five different plasma samples was studied and was illustrated by using principal components analysis (PCA) to group the samples. Orthogonal partial least squares discriminant analysis (OPLS-DA) modelling was then applied to identify the fatty acids that were responsible for the variation.

Results: The test results showed that choline coupling reactions were successful in detecting fatty acids, oxidised fatty acids and other compounds containing carboxylic acid groups in biological samples. The PCA results showed loadings of different fatty acids according to the plasma sample allowing identification of the fatty acids responsible for the observed variation.

Conclusion: A new and easy tagging method was developed to detect carboxylic acids in plasma samples. The method proved to be precise and reproducible and can quantify fatty acid compounds to 50 ng/ml.

Keywords: Fatty acids, choline, plasma, mass spectrometry, LC-MS, principal components analysis (PCA).

Graphical Abstract
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