代谢组学
质谱法
生物标志物发现
生物标志物
化学
色谱法
计算生物学
蛋白质组学
生物
生物化学
基因
作者
Wenqi Shang,Guozheng Wei,Haibo Li,Guohua Zhao,Damao Wang
标识
DOI:10.1021/acs.jafc.4c10295
摘要
Consumer concerns regarding food nutrition and quality are becoming increasingly prevalent. High-resolution mass spectrometry (HRMS)-based metabolomics stands as a cutting-edge and widely embraced technique in the realm of food component analysis and detection. It boasts the capability to identify character metabolites at exceedingly low abundances, which remain undetectable by conventional platforms. It can also enable real-time monitoring of the flux of targeted compounds in metabolic synthesis and decomposition. With the emergence of artificial intelligence and machine learning, it has become more convenient to process the vast data sets of metabolomics and identify biomarkers. The review summarizes the latest applications of HRMS-based metabolomics platforms in traditional foods, novel foods, and pharmaceutical-food homologous matrices. It compares the suitability of HRMS to nuclear magnetic resonance (NMR) in metabolomics across three dimensions and discusses the principles and application scenarios of various mass spectrometry technologies.
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