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Integration of GC–MS and LC–MS for untargeted metabolomics profiling

代谢组学 代谢物 化学 代谢组 色谱法 生物流体 气相色谱-质谱法 代谢物分析 计算生物学 质谱法 生物化学 生物
作者
Özge Cansın Zeki,Cemil Can Eylem,Tuba Reçber,Sedef Kır,Emirhan Nemutlu
出处
期刊:Journal of Pharmaceutical and Biomedical Analysis [Elsevier BV]
卷期号:190: 113509-113509 被引量:264
标识
DOI:10.1016/j.jpba.2020.113509
摘要

Recently, metabolomics analyses have become increasingly common in the general scientific community as it is applied in several researches relating to diseases diagnosis. Identification and quantification of small molecules belonging to metabolism in biological systems have an important role in diagnosis of diseases. The combination of chromatography with mass spectrometry is used for the accurate and reproducible analysis of hundreds to thousands of metabolites in biological fluids or tissue samples. The number of metabolites that can be identified in biological fluids or tissue varies according to the gas (GC) or liquid (LC) chromatographic techniques used. The cover of these chromatographic techniques also differs from each other based on the metabolite group (polar, lipids, organic acid etc.). Consequently, some of the metabolites can only be analyzed using either GC or LC. However, more than one metabolite or metabolite group may be found altered in a particular disease. Thus, in order to find these alterations, metabolomics analyses that cover a wide range of metabolite groups are usually applied. In this regard, GC–MS and LC–MS techniques are mostly used together to identify completely all the altered metabolites during disease diagnosis. Using these combined techniques also allows identification of metabolite(s) with significantly altered phenotype. This review sheds light on metabolomics studies involving the simultaneous use of GC–MS and LC–MS. The review also discusses the coverage, sample preparation, data acquisition and data preprocessing for untargeted metabolomics studies. Moreover, the advantages and disadvantages of these methods were also evaluated. Finally, precautions and suggestions on how to perform metabolomics studies in an accurate, precise, complete and unbiased way were also outlined.
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