Literature DB >> 26769129

Extending metabolome coverage for untargeted metabolite profiling of adherent cultured hepatic cells.

Juan Carlos García-Cañaveras1,2, Silvia López1,3, José Vicente Castell1,3,2, M Teresa Donato1,3,2, Agustín Lahoz4.   

Abstract

MS-based metabolite profiling of adherent mammalian cells comprises several challenging steps such as metabolism quenching, cell detachment, cell disruption, metabolome extraction, and metabolite measurement. In LC-MS, the final metabolome coverage is strongly determined by the separation technique and the MS conditions used. Human liver-derived cell line HepG2 was chosen as adherent mammalian cell model to evaluate the performance of several commonly used procedures in both sample processing and LC-MS analysis. In a first phase, metabolite extraction and sample analysis were optimized in a combined manner. To this end, the extraction abilities of five different solvents (or combinations) were assessed by comparing the number and the levels of the metabolites comprised in each extract. Three different chromatographic methods were selected for metabolites separation. A HILIC-based method which was set to specifically separate polar metabolites and two RP-based methods focused on lipidome and wide-ranging metabolite detection, respectively. With regard to metabolite measurement, a Q-ToF instrument operating in both ESI (+) and ESI (-) was used for unbiased extract analysis. Once metabolite extraction and analysis conditions were set up, the influence of cell harvesting on metabolome coverage was also evaluated. Therefore, different protocols for cell detachment (trypsinization or scraping) and metabolism quenching were compared. This study confirmed the inconvenience of trypsinization as a harvesting technique, and the importance of using complementary extraction solvents to extend metabolome coverage, minimizing interferences and maximizing detection, thanks to the use of dedicated analytical conditions through the combination of HILIC and RP separations. The proposed workflow allowed the detection of over 300 identified metabolites from highly polar compounds to a wide range of lipids.

Entities:  

Keywords:  Bioanalytical methods; HPLC; LC-MS; Mass spectrometry; Metabolomics; Process analysis; Sampling

Mesh:

Year:  2016        PMID: 26769129     DOI: 10.1007/s00216-015-9227-8

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  6 in total

Review 1.  Experimental design and reporting standards for metabolomics studies of mammalian cell lines.

Authors:  Sarah Hayton; Garth L Maker; Ian Mullaney; Robert D Trengove
Journal:  Cell Mol Life Sci       Date:  2017-07-01       Impact factor: 9.261

2.  In Vitro Tracking of Intracellular Metabolism-Derived Cancer Volatiles via Isotope Labeling.

Authors:  Dong-Kyu Lee; Euiyeon Na; Seongoh Park; Jeong Hill Park; Johan Lim; Sung Won Kwon
Journal:  ACS Cent Sci       Date:  2018-08-03       Impact factor: 14.553

3.  A metabolomics cell-based approach for anticipating and investigating drug-induced liver injury.

Authors:  Juan Carlos García-Cañaveras; José V Castell; M Teresa Donato; Agustín Lahoz
Journal:  Sci Rep       Date:  2016-06-06       Impact factor: 4.379

4.  Quantitative 1H NMR Metabolomics Reveal Distinct Metabolic Adaptations in Human Macrophages Following Differential Activation.

Authors:  Amanda L Fuchs; Sage M Schiller; Wyatt J Keegan; Mary Cloud B Ammons; Brian Eilers; Brian Tripet; Valérie Copié
Journal:  Metabolites       Date:  2019-10-24

Review 5.  Metabolomic Approaches to Study Chemical Exposure-Related Metabolism Alterations in Mammalian Cell Cultures.

Authors:  Aneta Balcerczyk; Christian Damblon; Bénédicte Elena-Herrmann; Baptiste Panthu; Gilles J P Rautureau
Journal:  Int J Mol Sci       Date:  2020-09-18       Impact factor: 5.923

6.  Pseudomonas aeruginosa Planktonic- and Biofilm-Conditioned Media Elicit Discrete Metabolic Responses in Human Macrophages.

Authors:  Amanda L Fuchs; Isaac R Miller; Sage M Schiller; Mary Cloud B Ammons; Brian Eilers; Brian Tripet; Valérie Copié
Journal:  Cells       Date:  2020-10-09       Impact factor: 7.666

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.