Introduction: A large scale population exposure to ionizing radiation during intentional or unintentional nuclear accidents undoubtedly generates a complex scenario with partial-body as well as total-body irradiated victims. A high throughput technique based rapid assessment method is an urgent necessity for stratification of exposed subjects independent of whether exposure is uniform total-body or non-homogenous partial-body.
Objective: Here, we used Nuclear Magnetic Resonance (NMR) based metabolomics approach to compare and identify candidate metabolites differentially expressed in total and partially irradiated mice model.
Methods: C57BL/6 male mice (8-10 weeks) were irradiated total-body or locally to thoracic, hind limb or abdominal regions with 10 Gy of gamma radiation. Urine samples collected at 24 h post irradiation were examined using high resolution NMR spectroscopy and the datasets were analysed using multivariate analysis.
Results: Multivariate and metabolic pathway analysis in urine samples collected at 24 h post-radiation exhibited segregation of all irradiated groups from controls. Metabolites associated with energy metabolism, gut flora metabolism and taurine were common to partial and total-body irradiation, thus making them potential candidates for radiation exposure. Nevertheless, a distinct metabolic pattern was observed in partial-body exposed groups with maximum changes observed in the hind limb region indicating differential tissue associated radiation sensitivity. The organ-specific changes may provide an early warning regarding the physiological system at risk after radiation injury.
Conclusion: The study affirms potentiality of metabolite markers and comparative analysis could be an important piece of information for an integrated solution to a complex research question in terms of radiation biomarkers.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s11306-020-01742-7 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!