代谢组学
主成分分析
多元统计
数据验证
样品(材料)
多元分析
代谢物
环境化学
环境科学
数据挖掘
化学
计算机科学
色谱法
人工智能
生物化学
机器学习
作者
Mark R. Viant,Daniel W. Bearden,Jacob G. Bundy,Ian W. Burton,Timothy W. Collette,Drew R. Ekman,Vilnis Ezernieks,Tobias K. Karakach,Ching‐Yu Lin,Simone Rochfort,Jeffrey S. de Ropp,Quincy Teng,Ronald S. Tjeerdema,John A. Walter,Huifeng Wu
摘要
Several fundamental requirements must be met so that NMR-based metabolomics and the related technique of metabonomics can be formally adopted into environmental monitoring and chemical risk assessment. Here we report an intercomparison exercise which has evaluated the effectiveness of 1H NMR metabolomics to generate comparable data sets from environmentally derived samples. It focuses on laboratory practice that follows sample collection and metabolite extraction, specifically the final stages of sample preparation, NMR data collection (500, 600, and 800 MHz), data processing, and multivariate analysis. Seven laboratories have participated from the U.S.A., Canada, U.K., and Australia, generating a total of ten data sets. Phase 1 comprised the analysis of synthetic metabolite mixtures, while Phase 2 investigated European flounder (Platichthys flesus) liver extracts from clean and contaminated sites. Overall, the comparability of data sets from the participating laboratories was good. Principal components analyses (PCA) of the individual data sets yielded ten highly similar scores plots for the synthetic mixtures, with a comparable result for the liver extracts. Furthermore, the same metabolic biomarkers that discriminated fish from clean and contaminated sites were discovered by all the laboratories. PCA of the combined data sets showed excellent clustering of the multiple analyses. These results demonstrate that NMR-based metabolomics can generate data that are sufficiently comparable between laboratories to support its continued evaluation for regulatory environmental studies.
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