The DOI matches its Crossref record; 184 of the 184 references it cites were found in a registry or an index.
Review of recent developments in GC–MS approaches to metabolomics-based research
Open accessAbstract
Metabolomics aims to identify the changes in endogenous metabolites of biological systems in response to intrinsic and extrinsic factors. This is accomplished through untargeted, semi-targeted and targeted based approaches. Untargeted and semi-targeted methods are typically applied in hypothesis-generating investigations (aimed at measuring as many metabolites as possible), while targeted approaches analyze a relatively smaller subset of biochemically important and relevant metabolites. Regardless of approach, it is well recognized amongst the metabolomics community that gas chromatography-mass spectrometry (GC–MS) is one of the most efficient, reproducible and well used analytical platforms for metabolomics research. This is due to the robust, reproducible and selective nature of the technique, as well as the large number of well-established libraries of both commercial and ‘in house’ metabolite databases available. This review provides an overview of developments in GC–MS based metabolomics applications, with a focus on sample preparation and preservation techniques. A number of chemical derivatization (in-time, in-liner, offline and microwave assisted) techniques are also discussed. Electron impact ionization and a summary of alternate mass analyzers are highlighted, along with a number of recently reported new GC columns suited for metabolomics. Lastly, multidimensional GC–MS and its application in environmental and biomedical research is presented, along with the importance of bioinformatics. The purpose of this review is to both highlight and provide an update on GC–MS analytical techniques that are common in metabolomics studies. Specific emphasis is given to the key steps within the GC–MS workflow that those new to this field need to be aware of and the common pitfalls that should be looked out for when starting in this area.
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Cites
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HMDB 4.0: the human metabolome database for 2018
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HMDB: the Human Metabolome Database
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MetaboAnalyst: a web server for metabolomic data analysis and interpretation
Xia, J., Psychogios, N., Young, N., & Wishart, D. S. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp356 · Cited by 2,266
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GMD@CSB.DB: the Golm Metabolome Database
Kopka, J., Schauer, N., Krueger, S., Birkemeyer, C., Usadel, B., Bergmuller, E., Dormann, P., Weckwerth, W., Gibon, Y., Stitt, M., et al. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti236 · Cited by 1,382
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Systems biology and multi-omics integration: viewpoints from the metabolomics research community
Pinu, F. R., Beale, D. J., Paten, A. M., Kouremenos, K., Swarup, S., Schirra, H. J., & Wishart, D. (2019) · Metabolites · doi:10.3390/metabo9040076 · Cited by 723
Self-citationSalem, M. A., Perez de Souza, L., Serag, A., Fernie, A. R., Farag, M. A., Ezzat, S. M., & Alseekh, S. (2020) · Metabolites · doi:10.3390/metabo10010037 · Cited by 361
Phytobioactive compounds as therapeutic agents for human diseases: A review
Riaz, M., Khalid, R., Afzal, M., Anjum, F., Fatima, H., Zia, S., Rasool, G., Egbuna, C., Mtewa, A. G., Uche, C. Z., et al. (2023) · Food Science & Nutrition · doi:10.1002/fsn3.3308 · Cited by 355
Chemometric-Guided Approaches for Profiling and Authenticating Botanical Materials
Abraham, E. J., & Kellogg, J. J. (2021) · Frontiers in Nutrition · doi:10.3389/fnut.2021.780228 · Cited by 64
Analytical tools to assess polymer biodegradation: A critical review and recommendations
Colachis, M., Lilly, J. L., Trigg, E., & Kucharzyk, K. H. (2024) · Science of The Total Environment · doi:10.1016/j.scitotenv.2024.176920 · Cited by 21
Metadata
- Authors
- Beale, D. J., Pinu, F. R., Kouremenos, K. A., Poojary, M. M., Narayana, V. K., Boughton, B. A., Kanojia, K., Dayalan, S., Jones, O. A. H., & Dias, D. A.
- Venue
- Metabolomics
- Published
- 2018-11
- Volume
- 14
- Issue
- 11
- Pages
- 152-152
- ISSN
- 1573-3882 (ISSN-L)
- 1573-3890
- OpenAlex
- W2900512735
- Cited by
- 531
- References
- 184
- FWCI
- 12.32
- Type
- journal article
- Language
- en
- Open access
- green
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- Beale, D. J., Pinu, F. R., Kouremenos, K. A., Poojary, M. M., Narayana, V. K., Boughton, B. A., Kanojia, K., Dayalan, S., Jones, O. A. H., & Dias, D. A. (2018). Review of recent developments in GC–MS approaches to metabolomics-based research. Metabolomics. https://doi.org/10.1007/s11306-018-1449-2
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