Issue 3, 2022

An integrative chemometric approach and correlative metabolite networking of LC-MS and 1H NMR based urine metabolomics for radiation signatures

Abstract

The increasing threat of nuclear terrorism or radiological accident has made high throughput radiation biodosimetry a requisite for the immediate response for triage. Owing to detection of subtle alterations in biological pathways before the onset of clinical conditions, metabolomics has become an important tool for studying biomarkers and the related mechanisms for radiation induced damage. Here, we have attempted to combine two detection techniques, LC-MS and 1H NMR spectroscopy, to obtain a comprehensive metabolite profile of urine at 24 h following lethal (7.5 Gy) and sub-lethal (5 Gy) irradiation in mice. Integrated data analytics using multiblock-OPLSDA (MB-OPLSDA), correlation networking and pathway analysis was used to identify metabolic disturbances associated with radiation exposure. MB-OPLSDA revealed better clustering and separation of irradiated groups compared with controls without overfitting (p-value of CV-ANOVA: 1.5 × 10−3). Metabolites identified through MB-OPLSDA, namely, taurine, creatine, citrate and 2-oxoglutarate, were found to be dose independent markers and further support and validate our earlier findings as potential radiation injury biomarkers. Integrated analysis resulted in the enhanced coverage of metabolites and better correlation networking in energy, taurine, gut flora, L-carnitine and nucleotide metabolism observed post irradiation in urine. Our study thus emphasizes the major advantage of using the two detection techniques along with integrated analysis for better detection and comprehensive understanding of disturbed metabolites in biological pathways.

Graphical abstract: An integrative chemometric approach and correlative metabolite networking of LC-MS and 1H NMR based urine metabolomics for radiation signatures

Supplementary files

Article information

Article type
Research Article
Submitted
01 Oct 2021
Accepted
13 Dec 2021
First published
04 Jan 2022

Mol. Omics, 2022,18, 214-225

An integrative chemometric approach and correlative metabolite networking of LC-MS and 1H NMR based urine metabolomics for radiation signatures

K. Maan, R. Baghel, R. Bakhshi, S. Dhariwal, R. Tyagi and P. Rana, Mol. Omics, 2022, 18, 214 DOI: 10.1039/D1MO00399B

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