NMR-based metabolomics: A powerful approach for characterizing the effects of environmental stressors on organism health
NMR-based metabolomics: A powerful approach for characterizing the effects of environmental stressors on organism health
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DOI：
10.1021/es034281x
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发表时间：
2003-11-01
影响因子：
11.4
通讯作者：
Tjeerdema, RS
中科院分区：
文献类型：
--
作者：
Viant, MR;Rosenblum, ES;Tjeerdema, RS
评估化学、物理和生物应激源对环境中生物体的慢性影响是很重要的。适当的方法必须能够快速、廉价和多生物标志物分析生物体健康。本文采用代谢组学方法，结合核磁共振光谱（NMR）的代谢分析能力和模式识别方法，研究了太平洋沿岸重要的野生和养殖贝类红鲍鱼（Haliotis rufescens）的枯萎综合征。采集健康鲍鱼、发育不良鲍鱼和患病鲍鱼的足部肌肉、消化腺和血淋巴样本，并对提取物进行核磁共振分析。在光谱预处理之后，进行了代谢物谱的主成分分析。我们的研究结果证实，基于核磁共振的代谢组学可以成功区分三组动物在每种类型的组织或生物流体中的生化特征。此外，这种基于发现的方法成功地鉴定了与萎蔫综合征相关的新型代谢生物标志物。讨论了这些方法在研究其他环境压力源方面的应用，以及基于核磁共振的代谢组学在生物监测方面的优势，特别是与基因和蛋白质表达谱相结合。
It is important to assess the chronic effects of chemical, physical, and biological stressors on organisms in the environment. Appropriate methods must enable rapid, inexpensive, and multibiomarker analyses of organism health. Here we investigate withering syndrome in red abalone (Haliotis rufescens), an important wild and farmed shellfish species along the Pacific coast, using a metabolomic approach that combines the metabolic profiling capabilities of nuclear magnetic resonance spectroscopy (NMR) with pattern recognition methods. Foot muscle, digestive gland, and hemolymph samples were collected from healthy, stunted, and diseased abalone, and the extracts were analyzed by NMR. Following spectral preprocessing, principal components analyses of the metabolite profiles were conducted. Our results confirm that NMR-based metabolomics can successfully distinguish the biochemical profiles of the three groups of animals, in every type of tissue or biofluid studied. Furthermore, this discovery-based approach successfully identified novel metabolic biomarker profiles associated with withering syndrome. The application of these methods for investigating other environmental stressors is discussed, as are the advantages of NMR-based metabolomics for biomonitoring, particularly in conjunction with gene and protein expression profiling.