Advances in high throughput LC/MS based metabolomics: A review
File(s)HT-UHPLC-MS METABOLICPHENOTYPING REVIEW.pdf (1.55 MB)
Published version
Author(s)
Type
Journal Article
Abstract
Properly implemented, metabolic and lipidomic profiling can provide a deeper understanding of mammalian, plant and bacterial biology. These omics-tools have developed and matured over the last 40-years and are now being deployed to provide valuable information in epidemiological studies, drug toxicology and pharmacology, disease biology and progression and patient stratification. LC/MS has become the technology of choice for both metabolic and lipid profiling, due to its speed, sensitivity and structural elucidation capabilities. In the preceding two decades there have been many technological and methodological advances in LC/MS that have facilitated the evolution of the technology into a rugged, reliable, and easily deployed tool. These advances include, but are not limited to, improvements in chromatography (phases, columns, and delivery system), instruments for mass spectrometry, optimization of sample preparation, the introduction of ion mobility, data analysis tools, metabolite databases, harmonized protocols, and the more widespread use of quality control methods and reference standards/matrices. Here, recent developments and advances in high throughput liquid chromatography/high resolution mass spectrometry for metabolic phenotyping are described. These advances which may provide improved feature detection, increased laboratory efficiency and data quality, as well as “biomarker” identification, are discussed in relation to their potential application to the analysis of large clinical studies, or biobank collections.
Date Issued
2023-03
Date Acceptance
2023-01-26
Citation
TrAC Trends in Analytical Chemistry, 2023, 160, pp.1-9
ISSN
0165-9936
Publisher
Elsevier BV
Start Page
1
End Page
9
Journal / Book Title
TrAC Trends in Analytical Chemistry
Volume
160
Copyright Statement
© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/by/4.0/).
(http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
http://dx.doi.org/10.1016/j.trac.2023.116954
Publication Status
Published
Article Number
116954
Date Publish Online
2023-01-27