Literature DB >> 32814263

Integration of GC-MS and LC-MS for untargeted metabolomics profiling.

Özge Cansın Zeki1, Cemil Can Eylem1, Tuba Reçber1, Sedef Kır1, Emirhan Nemutlu2.   

Abstract

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.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Data analysis; GC–MS; LC–MS; Metabolomics; Sample preparation

Mesh:

Year:  2020        PMID: 32814263     DOI: 10.1016/j.jpba.2020.113509

Source DB:  PubMed          Journal:  J Pharm Biomed Anal        ISSN: 0731-7085            Impact factor:   3.935


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