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作者（2019）在《Metabolomic Fingerprint of the Model Ciliate, Tetrahymena thermophila Determined by Untargeted Profiling Using Gas Chromatography-Mass Spectrometry》一文中研究指出：The ciliate Tetrahymena is a valuable model organism in the studies of ecotoxicology. Changes in intracellular metabolism are caused by exogenous chemicals in the environment. Intracellular metabolite changes signify toxic effects and can be monitored by metabolomics analysis. In this work, a protocol for the GC-MS-based metabolomic analysis of Tetrahymena was established. Different extraction solvents showed divergent effects on the metabolomic analysis of Tetrahymena thermophila. The peak intensity of metabolites detected in the samples of extraction solvent Formula 1(F1) was the strongest and stable, while 61 metabolites were identified. Formula 1 showed an excellent extraction performance for carbohydrates. In the samples of extraction solvent Formula 2(F2), 66 metabolites were characterized, and fatty acid metabolites were extracted. Meanwhile, 57 and 58 metabolites were characterized in the extraction with Formula 3(F3) and Formula 4(F4), respectively. However, the peak intensity of the metabolites was low, and the metabolites were unstable. These results indicated that different extraction solvents substantially affected the detected coverage and peak intensity of intracellular metabolites. A total of 74 metabolites(19 amino acids, 11 organic acids, 2 inorganic acids, 11 fatty acids, 11 carbohydrates, 3 glycosides, 4 alcohols, 6 amines, and 7 other compounds) were identified in all experimental groups. Among these metabolites, amino acids, glycerol, myoinositol, and unsaturated fatty acids may become potential biomarkers of metabolite set enrichment analysis for detecting the ability of T. thermophila against environmental stresses.
Abstract
The ciliate Tetrahymena is a valuable model organism in the studies of ecotoxicology. Changes in intracellular metabolism are caused by exogenous chemicals in the environment. Intracellular metabolite changes signify toxic effects and can be monitored by metabolomics analysis. In this work, a protocol for the GC-MS-based metabolomic analysis of Tetrahymena was established. Different extraction solvents showed divergent effects on the metabolomic analysis of Tetrahymena thermophila. The peak intensity of metabolites detected in the samples of extraction solvent Formula 1(F1) was the strongest and stable, while 61 metabolites were identified. Formula 1 showed an excellent extraction performance for carbohydrates. In the samples of extraction solvent Formula 2(F2), 66 metabolites were characterized, and fatty acid metabolites were extracted. Meanwhile, 57 and 58 metabolites were characterized in the extraction with Formula 3(F3) and Formula 4(F4), respectively. However, the peak intensity of the metabolites was low, and the metabolites were unstable. These results indicated that different extraction solvents substantially affected the detected coverage and peak intensity of intracellular metabolites. A total of 74 metabolites(19 amino acids, 11 organic acids, 2 inorganic acids, 11 fatty acids, 11 carbohydrates, 3 glycosides, 4 alcohols, 6 amines, and 7 other compounds) were identified in all experimental groups. Among these metabolites, amino acids, glycerol, myoinositol, and unsaturated fatty acids may become potential biomarkers of metabolite set enrichment analysis for detecting the ability of T. thermophila against environmental stresses.
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