Improved quantitation of short-chain carboxylic acids in human biofluids using 3-nitrophenylhydrazine derivatization and liquid chromatography with tandem mass spectrometry (LC-MS/MS)
OA Location
Author(s)
Valdivia-Garcia, Maria
Chappell, Katie
Camuzeaux, Stephane
Olmo-García, Lucía
Horneffer-van der Sluis, Verena
Type
Working Paper
Abstract
Short-chain carboxylic acids (SCCAs) produced by gut microbial fermentation may reflect gastrointestinal health. Their concentrations in serum and urine are indicative of specific metabolic pathway activity; therefore, accurate quantitation of SCCAs in different biofluids is desirable. However, it is often challenging to quantitate SCCAs since matrix effects, induced by the presence of a vast variety of other compounds other than SCCAs in complex biofluids, can suppress or enhance signals. Materials used for sample preparation may introduce further analytical challenges. This study reports for the first time a LC-MS/MS-based method to quantitate ten SCCAs (lactate, acetate, 2-hydroxybutyrate, propionate, isobutyrate, butyrate, 2-methylbutyrate, isovalerate, valerate and hexanoate) and evaluates the matrix effects in five human biofluids: serum, urine, stool, and contents from the duodenum and intestinal stoma bags. The optimized method, using 3-Nitrophenylhydrazone as a derivatization agent and a Charge Surface Hybrid reverse phase column, showed clear separation for all SCCAs at a concentration range of 0.1 -100 µM, in a 10.5- minute run without carry-over effects. The validation of the method showed a good linearity (R2 > 0.99) and reproducibility (CV ≤ 15%) assessed by intra- and inter-day monitoring. Quantitative accuracy in all biofluids for most compounds was <±15%. In summary, this methodology has the advantages over other techniques for its simple and fast sample preparation and a high level of selectivity, reproducibility, and robustness for SCCA quantification. It also reduced interferences from the matrix or sample containers, making it ideal for use in high-throughput analyses of biofluid samples from large-scale studies.
Date Issued
2022-07-15
Citation
2022
Publisher
Elsevier BV
Copyright Statement
© 2022 The Author(s)
Identifier
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4163686
Publication Status
Published