Literature DB >> 28153450

Tailored liquid chromatography-mass spectrometry analysis improves the coverage of the intracellular metabolome of HepaRG cells.

Matthias Cuykx1, Noelia Negreira2, Charlie Beirnaert3, Nele Van den Eede2, Robim Rodrigues4, Tamara Vanhaecke4, Kris Laukens3, Adrian Covaci5.   

Abstract

Metabolomics protocols are often combined with Liquid Chromatography-Mass Spectrometry (LC-MS) using mostly reversed phase chromatography coupled to accurate mass spectrometry, e.g. quadrupole time-of-flight (QTOF) mass spectrometers to measure as many metabolites as possible. In this study, we optimised the LC-MS separation of cell extracts after fractionation in polar and non-polar fractions. Both phases were analysed separately in a tailored approach in four different runs (two for the non-polar and two for the polar-fraction), each of them specifically adapted to improve the separation of the metabolites present in the extract. This approach improves the coverage of a broad range of the metabolome of the HepaRG cells and the separation of intra-class metabolites. The non-polar fraction was analysed using a C18-column with end-capping, mobile phase compositions were specifically adapted for each ionisation mode using different co-solvents and buffers. The polar extracts were analysed with a mixed mode Hydrophilic Interaction Liquid Chromatography (HILIC) system. Acidic metabolites from glycolysis and the Krebs cycle, together with phosphorylated compounds, were best detected with a method using ion pairing (IP) with tributylamine and separation on a phenyl-hexyl column. Accurate mass detection was performed with the QTOF in MS-mode only using an extended dynamic range to improve the quality of the dataset. Parameters with the greatest impact on the detection were the balance between mass accuracy and linear range, the fragmentor voltage, the capillary voltage, the nozzle voltage, and the nebuliser pressure. By using a tailored approach for the intracellular HepaRG metabolome, consisting of three different LC techniques, over 2200 metabolites can be measured with a high precision and acceptable linear range. The developed method is suited for qualitative untargeted LC-MS metabolomics studies.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  HepaRG; Hydrophilic liquid interaction chromatography; Ion pairing; Liquid chromatography–Mass spectrometry; Metabolomics; Optimization

Mesh:

Year:  2017        PMID: 28153450     DOI: 10.1016/j.chroma.2017.01.050

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  7 in total

1.  Integrating a generalized data analysis workflow with the Single-probe mass spectrometry experiment for single cell metabolomics.

Authors:  Renmeng Liu; Genwei Zhang; Mei Sun; Xiaoliang Pan; Zhibo Yang
Journal:  Anal Chim Acta       Date:  2019-03-11       Impact factor: 6.558

2.  Mass Spectrometry-Based Untargeted Metabolomics and Lipidomics Platforms to Analyze Cell Culture Extracts.

Authors:  Elias Iturrospe; Katyeny Manuela da Silva; Maria van de Lavoir; Rani Robeyns; Matthias Cuykx; Tamara Vanhaecke; Alexander L N van Nuijs; Adrian Covaci
Journal:  Methods Mol Biol       Date:  2023

3.  Integrated transcriptomics and metabolomics reveal signatures of lipid metabolism dysregulation in HepaRG liver cells exposed to PCB 126.

Authors:  Robin Mesnage; Martina Biserni; Sucharitha Balu; Clément Frainay; Nathalie Poupin; Fabien Jourdan; Eva Wozniak; Theodoros Xenakis; Charles A Mein; Michael N Antoniou
Journal:  Arch Toxicol       Date:  2018-06-14       Impact factor: 5.153

4.  Exposure of HepaRG Cells to Sodium Saccharin Underpins the Importance of Including Non-Hepatotoxic Compounds When Investigating Toxicological Modes of Action Using Metabolomics.

Authors:  Matthias Cuykx; Charlie Beirnaert; Robim Marcelino Rodrigues; Kris Laukens; Tamara Vanhaecke; Adrian Covaci
Journal:  Metabolites       Date:  2019-11-04

5.  Confirmation of neurometabolic diagnoses using age-dependent cerebrospinal fluid metabolomic profiles.

Authors:  Tessa M A Peters; Udo F H Engelke; Siebolt de Boer; Ed van der Heeft; Cynthia Pritsch; Purva Kulkarni; Ron A Wevers; Michèl A A P Willemsen; Marcel M Verbeek; Karlien L M Coene
Journal:  J Inherit Metab Dis       Date:  2020-05-23       Impact factor: 4.982

6.  Protective Mechanism of Gandou Decoction in a Copper-Laden Hepatolenticular Degeneration Model: In Vitro Pharmacology and Cell Metabolomics.

Authors:  Fengxia Yin; Mengnan Nian; Na Wang; Hongfei Wu; Huan Wu; Wenchen Zhao; Shijian Cao; Peng Wu; An Zhou
Journal:  Front Pharmacol       Date:  2022-03-23       Impact factor: 5.810

7.  Next-generation metabolic screening: targeted and untargeted metabolomics for the diagnosis of inborn errors of metabolism in individual patients.

Authors:  Karlien L M Coene; Leo A J Kluijtmans; Ed van der Heeft; Udo F H Engelke; Siebolt de Boer; Brechtje Hoegen; Hanneke J T Kwast; Maartje van de Vorst; Marleen C D G Huigen; Irene M L W Keularts; Michiel F Schreuder; Clara D M van Karnebeek; Saskia B Wortmann; Maaike C de Vries; Mirian C H Janssen; Christian Gilissen; Jasper Engel; Ron A Wevers
Journal:  J Inherit Metab Dis       Date:  2018-02-16       Impact factor: 4.982

  7 in total

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