Kiran Maan1,2, Ritu Tyagi1, Ajaswrata Dutta3, Radhika Bakhshi2, Poonam Rana4. 1. Metabolomics Research Facility, Division of Behavioral Neuroscience, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, Delhi, India. 2. Department of Biomedical Science, Shaheed Rajguru College of Applied Sciences for Women, University of Delhi, Delhi, India. 3. Division of Radiation Biodosimetry, Department of Radiation Epigenetics, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, Delhi, India. 4. Metabolomics Research Facility, Division of Behavioral Neuroscience, Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, Delhi, India. poonam@inmas.drdo.in.
Abstract
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.
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.
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