Identification of lipid profile on γ-irradiated primary cultured human diploid fibroblasts by UPLC-ESI-QTOF-MS

The study of biomarkers in normal-tissue radiobiology is of great importance to people subjected to non-destructive testing, to nuclear power industry, and to radiological terrorism. Cytogenetics has remained the 'gold standard' for the detection of chromosomal changes, but this method is cumbersome and time consuming. Therefore, it is necessary to establish a rapid, high-throughput biological monitoring protocol to determine the exposure radiation dose in order to rapidly triage mass casualties. Metabolomics studies is an effective platform for identification and quantification of the complete set of metabolites in a biological system, and it has been successfully provides important insights into physiological and disease states and facilitate in depth understanding of underlying biochemical pathways. Radiation metabolomics has been used to identify radiation effects at the metabolite levels in cells and in urine or serum collected from laboratory animals such as mouse, rat and monkey. Recently, a few radiation metabolomics studies showed that multiple metabolites related to the purine, inositol or pyrimidine metabolism, fatty acid biosynthesis and glycolysis/gluconeogenesis could be potential minimal-invasive markers for radiation exposure. However, there is little consistency in these studies due to differences in analyzed sample (cells, urine, serum), animal models (mouse, rat and monkey). Furthermore, the biological effects of ionizing radiation (IR) were differently regulated in the different absorbed doses, dose-rates and type of IR. Thus, it is necessary to explore the entire biosphere profiling of metabolic markers to make reasonable biological explanation under radiation exposure. We hypothesized that the variations in lipid expression in IR-induced cells would result in a unique lipid profile in human diploid fibroblasts (HDF), which can be detected with the targeted and quantitative metabolomics approach. Irradiated HDF cells showed the dose-dependent clustering of irradiated group. As a result of radiation exposure, a total of 9 differential lipid metabolites were identified, including lysophosphatidylcholine and lysophosphatidylethanol -amine. Almost no significantly changed metabolites were found to be associated with 1 Gy irradiation, while 7 metabolite features were detected with 5 Gy irradiation. These data suggest that the UPLC-ESI-QTOF-MS approach has aided in the advance for finding common biomarkers of ionizing radiation exposure