Exploratory Metabolomic Analysis Based on Reversed-Phase Liquid Chromatography-Mass Spectrometry to Study an In Vitro Model of Hypoxia-Induced Metabolic Alterations in HK-2 Cells
Autores
Bernardo Bermejo, Samuel; Sánchez López, Elena; Tan, Lei; Benito Martínez, Selma; Jiang, Z.; [et al.]Identificadores
Enlace permanente (URI): http://hdl.handle.net/10017/52210DOI: https://doi.org/10.3390/ijms22147399
ISSN: 1422-0067
Fecha de publicación
2021-07Filiación
Universidad de Alcalá. Departamenteo de Biología de Sistemas; Universidad de Alcalá. Departamento de Química Analítica, Química Física e Ingeniería QuímicaCita bibliográfica
International Journal of Molecular Sciences, 2021, v. 22, n. 14, p. 7399-
Palabras clave
HK-2 cells
hypoxialiquid chromatography-mass spectrometry
untargeted metabolomics
multivariate analysis
Tipo de documento
info:eu-repo/semantics/article
Versión
info:eu-repo/semantics/publishedVersion
Derechos
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Derechos de acceso
info:eu-repo/semantics/openAccess
Resumen
Oxygen deficiency in cells, tissues, and organs can not only prevent the proper development of biological functions but it can also lead to several diseases and disorders. In this sense, the kidney deserves special attention since hypoxia can be considered an important factor in the pathophysiology of both acute kidney injury and chronic kidney disease. To provide better knowledge to unveil the molecular mechanisms involved, new studies are necessary. In this sense, this work aims to study, for the first time, an in vitro model of hypoxia-induced metabolic alterations in human proximal tubular HK-2 cells because renal proximal tubules are particularly susceptible to hypoxia. Different groups of cells, cultivated under control and hypoxia conditions at 0.5, 5, 24, and 48 h, were investigated using untargeted metabolomic approaches based on reversed-phase liquid chromatography-mass spectrometry. Both intracellular and extracellular fluids were studied to obtain a large metabolite coverage. On the other hand, multivariate and univariate analyses were carried out to find the differences among the cell groups and to select the most relevant variables. The molecular features identified as affected metabolites were mainly amino acids and Amadori compounds. Insights about their biological relevance are also provided.
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