Effects of Genetic Variation on Urinary Small Molecule Signatures of Mice after Exposure to Ionizing Radiation: A Study of p53 Deficiency - Evan L. Pannkuk; Evagelia C. Laiakis; Pelagie Ake; Steven J. Strawn; Yi-Wen Wang; Albert J. Fornace (Metabolites, 2020)
Due to risks from potential exposures to ionizing radiation (IR), improved radiological countermeasures are required, as well as rapid high-throughput biodosimetry. Genotypic variation in the general population contributes to differences in radiosensitivity that may affect biodosimetry accuracy. Previous studies utilized radiosensitive mutant mouse models (Parp1−/− and Atm−/−) to determine the effects of genotypic deficiency on radiation signatures. Here, we extend this approach by examining changes in the urinary metabolome in a hematopoietic (HP) resistant mouse model (p53−/−) after IR exposure. As p53 is a primary regulator in radiation response and apoptosis, limited hematopoietic stem cell apoptosis leads to reduced mortality at doses of ~8–10 Gy but increased mortality at higher doses (>15 Gy) due to mitotic catastrophe in gastrointestinal (GI) crypt cells. Urine was collected from mice (wild-type (WT), p53+/−, and p53−/−) pre-irradiation and at 4 and 24 h after total body irradiation (TBI) (WT: 8 and 10 Gy; p53−/−: 10 Gy) for metabolic phenotyping using an ultra-performance liquid chromatography mass spectrometry (UPLC-MS) platform. Minimal differences were detected between unirradiated WT, p53+/−, and p53−/− mice. While similar perturbations were observed for metabolites involved in tryptophan, vitamin B6, and histamine pathways, glycine conjugation, and redox metabolism for WT and p53−/− mice after TBI, an overall dampened response was observed in p53-deficient mice. Despite comparable metabolite patterns between genotypes, differentiation was achieved through receiver operating characteristic curve analysis with high specificity and sensitivity for carnitine, N1-acetylspermidine, and creatine. These studies highlight that both attenuated and dampened metabolic responses due to genetic variability in the general population need to be addressed in biodosimetry frameworks.