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

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

Journal Name: Current Analytical Chemistry

Volume 15 , Issue 6 , 2019

Become EABM
Become Reviewer

Graphical Abstract:


Abstract:

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).

[1]
Galli, C.; Simopoulos, A.P.; Tremoli, E. Effects of fatty acids and lipids in health and disease; Karger: Berlin, 1994.
[2]
Joffe, Y.; Collins, M.; Goedecke, J. The relationship between dietary fatty acids and inflammatory genes on the obese phenotype and serum lipids. Nutrients, 2013, 5(5), 1672.
[3]
Soardo, G.; Donnini, D.; Domenis, L.; Catena, C.; De Silvestri, D.; Cappello, D.; Dibenedetto, A.; Carnelutti, A.; Bonasia, V.; Pagano, C.; Sechi, L.A. Oxidative stress is activated by free fatty acids in cultured human hepatocytes. Metab. Syndr. Relat. Disord., 2011, 9(5), 397-401.
[4]
Morgan, A.; Mooney, K.; Mc Auley, M. Obesity and the dysregulation of fatty acid metabolism: implications for healthy aging. Exp Rev. Endocrinol. Metabol., 2016, 11(6), 501-510.
[5]
Eder, K. Gas chromatographic analysis of fatty acid methyl esters. J. Chromatogr. B Biomed. Appl., 1995, 671(1-2), 113-131.
[6]
Chen, S-H.; Chuang, Y-J. Analysis of fatty acids by column liquid chromatography. Anal. Chim. Acta, 2002, 465(1-2), 145-155.
[7]
Zaikin, V.G.; Halket, J.M. Derivatization in mass spectrometry--8. Soft ionization mass spectrometry of small molecules. Eur. J. Mass Spectrom. (Chichester), 2006, 12(2), 79-115.
[8]
Qi, B-L.; Liu, P.; Wang, Q-Y.; Cai, W-J.; Yuan, B-F.; Feng, Y-Q. Derivatization for liquid chromatography-mass spectrometry. TrAC Trend. Anal. Chem., 2014, 59, 121-132.
[9]
Brooks, C.J.W.; Edmonds, C.G.; Gaskell, S.J.; Smith, A.G. Derivatives suitable for GC-MS. Chem. Phys. Lipid, 1978, 21(4), 403-416.
[10]
Amos, W.H.; Neal, R.A. Gas chromatography-mass spectrometry of the trimethylsilyl derivatives of various thiamine metabolites. Anal. Biochem., 1970, 36(2), 332-337.
[11]
Niessen, W.M. Advances in instrumentation in liquid chromatography-mass spectrometry and related liquid-introduction techniques. J. Chromatogr. A, 1998, 794(1-2), 407-435.
[12]
Ho, C.S.; Lam, C.W.; Chan, M.H.; Cheung, R.C.; Law, L.K.; Lit, L.C.; Ng, K.F.; Suen, M.W.; Tai, H.L. Electrospray ionisation mass spectrometry: principles and clinical applications. Clin. Biochem. Rev., 2003, 24(1), 3-12.
[13]
Jemal, M.; Ouyang, Z.; Teitz, D.S. High performance liquid chromatography mobile phase composition optimization for the quantitative determination of a carboxylic acid compound in human plasma by negative ion electrospray high performance liquid chromatography tandem mass spectrometry. Rapid Commun. Mass Spectr., 1998, 12(8), 429-434.
[14]
Ko, B.J.; Brodbelt, J.S. Enhanced electron transfer dissociation of peptides modified at C-terminus with fixed charges. J. Am. Soc. Mass Spectrom., 2012, 23(11), 1991-2000.
[15]
Frey, B.L.; Krusemark, C.J.; Ledvina, A.R.; Coon, J.J.; Belshaw, P.J.; Smith, L.M. Ion-ion reactions with fixed-charge modified proteins to produce ions in a single, very high charge state. Int. J. Mass Spectrom., 2008, 276(2-3), 136-143.
[16]
Chambers, E.; Wagrowski-Diehl, D.M.; Lu, Z.; Mazzeo, J.R. Systematic and comprehensive strategy for reducing matrix effects in LC/MS/MS analyses. J. Chromatogr. B , 2007, 852(1–2), 22-34.
[17]
Neises, B.; Steglich, W. Simple method for the esterification of carboxylic acids. Angewandte. Chem. Int. Ed. Engl., 1978, 17(7), 522-524.
[18]
Yang, W.C.; Adamec, J.; Regnier, F.E. Enhancement of the LC/MS analysis of fatty acids through derivatization and stable isotope coding. Anal. Chem., 2007, 79(14), 5150-5157.
[19]
Pluskal, T.; Castillo, S.; Villar-Briones, A.; Oresic, M. MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics, 2010, 11, 395.
[20]
Yeung, K.Y.; Ruzzo, W.L. Principal component analysis for clustering gene expression data. Bioinformatics, 2001, 17(9), 763-774.
[21]
Bylesjö, M.; Rantalainen, M.; Cloarec, O.; Nicholson, J.K.; Holmes, E.; Trygg, J. OPLS discriminant analysis: Combining the strengths of PLS-DA and SIMCA classification. J. Chemometr., 2006, 20(8-10), 341-351.
[22]
Ismail, R.; Lee, H.Y.; Mahyudin, N.A.; Abu Bakar, F. Linearity study on detection and quantification limits for the determination of avermectins using linear regression. J. Food Drug Anal., 2014, 22(4), 407-412.
[23]
Perez-Enciso, M.; Tenenhaus, M. Prediction of clinical outcome with microarray data: A partial least squares discriminant analysis (PLS-DA) approach. Hum. Genet., 2003, 112(5-6), 581-592.
[24]
Sem, D.S. Spectral Techniques in Proteomics; CRC Press: Florida, 2007.


Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 15
ISSUE: 6
Year: 2019
Page: [642 - 647]
Pages: 6
DOI: 10.2174/1573411014666180516093353

Article Metrics

PDF: 16
HTML: 2
EPUB: 1
PRC: 1