INTRODUCTION: It is widely but erroneously believed that drugs get into cells by passing through the phospholipid bilayer portion of the plasma and other membranes. Much evidence shows, however, that this is not the case, and that drugs cross biomembranes by hitchhiking on transporters for other natural molecules to which these drugs are structurally similar. Untargeted metabolomics can provide a method for determining the differential uptake of such metabolites. OBJECTIVES: Blood serum contains many thousands of molecules and provides a convenient source of biologically relevant metabolites. Our objective was to detect and identify metabolites present in serum, but to also establish a method capable of measure their uptake and secretion by different cell lines. METHODS: We develop an untargeted LC-MS/MS method to detect a broad range of compounds present in human serum. We apply this to the analysis of the time course of the uptake and secretion of metabolites in serum by several human cell lines, by analysing changes in the serum that represents the extracellular phase (the 'exometabolome' or metabolic footprint). RESULTS: Our method measures some 4000-5000 metabolic features in both positive and negative electrospray ionisation modes. We show that the metabolic footprints of different cell lines differ greatly from each other. CONCLUSION: Our new, 15-min untargeted metabolome method allows for the robust and convenient measurement of differences in the uptake of serum compounds by cell lines following incubation in serum. This will enable future research to study these differences in multiple cell lines that will relate this to transporter expression, thereby advancing our knowledge of transporter substrates, both natural and xenobiotic compounds.
An untargeted metabolomics strategy to measure differences in metabolite uptake and excretion by mammalian cell lines.
一种非靶向代谢组学策略,用于测量哺乳动物细胞系对代谢物的吸收和排泄差异
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作者:Wright Muelas Marina, Roberts Ivayla, Mughal Farah, O'Hagan Steve, Day Philip J, Kell Douglas B
| 期刊: | Metabolomics | 影响因子: | 3.300 |
| 时间: | 2020 | 起止号: | 2020 Oct 7; 16(10):107 |
| doi: | 10.1007/s11306-020-01725-8 | 研究方向: | 代谢 |
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