An untargeted metabolomic strategy based on liquid chromatography-mass spectrometry to study high glucose-induced changes in HK-2 cells
Authors
Marina Alegre, María LuisaIdentifiers
Permanent link (URI): http://hdl.handle.net/10017/39807DOI: https://doi.org/10.1016/j.chroma.2019.03.009
ISSN: 0021-967
Date
2019-07-05Affiliation
Universidad de Alcalá. Departamento de Química Analítica, Química Física e Ingeniería QuímicaBibliographic citation
Journal of Chromatography A, 2019, v. 1596, p. 124-133
Keywords
diabetic nephropathy
HK-2 cells
liquid chromatography-mass spectrometry
metabolomics
multivariate analysis
Description / Notes
https://www.sciencedirect.com/science/article/pii/S002196731930247X?via%3Dihub
Project
CTQ2016-76368-P (Ministry of Economy and Competitiveness (Spain))
Document type
info:eu-repo/semantics/article
Version
info:eu-repo/semantics/publishedVersion
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
© 2019 Elsevier
Access rights
info:eu-repo/semantics/openAccess
Abstract
Diabetes mellitus is a major health concern nowadays. It is estimated that 40 % of diabetics are affected by diabetic nephropathy, one of the complications derived from high glucose blood levels which can lead to chronic loss of kidney function. It is now clear that the renal proximal tubule plays a critical role in the progression of diabetic nephropathy but research focused on studying the molecular mechanisms involved is still needed. The aim of this work was to develop a liquid chromatography-mass spectrometry platform to carry out, for the first time, the untargeted metabolomic analysis of high glucose-induced changes in cultured human proximal tubular HK-2 cells. In order to find the metabolites which were affected by high glucose and to expand the metabolite coverage, intra- and extracellular fluid from HK-2 cells exposed to high glucose (25 mM), normal glucose (5.5 mM) or osmotic control (5.5 mM glucose + 19.5 mM mannitol) were analyzed by two complementary chromatographic modes: hydrophilic interaction and reversed-phase liquid chromatography. Non-supervised principal components analysis showed a good distribution among the three groups of samples. Statistically significant variables were chosen for further metabolite identification. Different metabolic pathways were affected mainly those derived from amino acidic, polyol, and nitrogenous bases metabolism.
Files in this item
Files | Size | Format |
|
---|---|---|---|
Supplementary_Material.pdf | 1.466Mb |
![]() |
|
Untargeted_BernardoBermejo_JCA ... | 1.317Mb |
![]() |
Files | Size | Format |
|
---|---|---|---|
Supplementary_Material.pdf | 1.466Mb |
![]() |
|
Untargeted_BernardoBermejo_JCA ... | 1.317Mb |
![]() |
Collections
- QUANING - Artículos [250]