Abstract
In this paper, we present an optimized procedure for metabolomic analysis of endogenous metabolites in mouse fibroblast (L929) cell line using gas chromatography/time-of-flight mass spectrometry with multivariate statistics. The optimization of metabolite extraction was performed using three solvents: methanol, water, and chloroform, and then followed by methoxymation and silylation. This method was subsequently validated using 29 reference standards and cell line samples. The intra- and inter-day relative standard deviations (RSDs) of the standard compounds were lower than 15.0 and 25.0 %, respectively. As for most of the tested metabolites in cell line samples, RSDs were below 20.0 % for reproducibility and stability, respectively. We applied this approach in metabolomic study of L929 cells obtained from TiO2 nanoparticle-induced cytotoxicity model samples (n = 5) and control samples (n = 5). Metabolite markers associated with TiO2 nanoparticle-induced cytotoxicity were identified and validated by statistical methods and reference standards. Our work highlights the potential of this method for cell metabolomic study.
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This work was financially supported by Shanghai Natural Science Foundation of the Science and Technology Commission of Shanghai Municipal Government (No. 09ZR1415100), two Fundamental Key Project (No. YG2010MS92; YG2011MS66) of Shanghai Jiaotong University.
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Liu, Y., Cheng, Y., Chen, T. et al. GC/TOFMS Analysis of Endogenous Metabolites in Mouse Fibroblast Cells and Its Application in TiO2 Nanoparticle-Induced Cytotoxicity Study. Chromatographia 75, 1301–1310 (2012). https://doi.org/10.1007/s10337-012-2315-4
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DOI: https://doi.org/10.1007/s10337-012-2315-4