Exposure to ionizing radiation reveals global dose- and time-dependent changes in the urinary metabolome of rat
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The potential for exposures to ionizing radiation (IR) has increased in recent years. Although advances have been made, understanding the global metabolic response as a function of both dose and exposure time is challenging considering the complexity of the responses. Herein we report our findings on the dose- and time-dependency of the urinary response to IR in the male rat using radiation metabolomics. Urine samples were collected from adult male rats, exposed to 0.5–10 Gy γ-radiation, both before from 6 to 72 h following exposures. Samples were analyzed by liquid chromatography coupled with time-of-flight mass spectrometry, and deconvoluted mass chromatographic data were initially analyzed by principal component analysis. However, the breadth and complexity of the data necessitated the development of a novel approach to summarizing biofluid constituents after exposure, called Visual Analysis of Metabolomics Package (VAMP). VAMP revealed clear urine metabolite profile differences to as little as 0.5 Gy after 6 h exposure. Via VAMP, it was discovered that the response to radiation exposure found in rat urine is characterized by an overall net down-regulation of ion excretion with only a modest number of ions excreted in excess over pre-exposure levels. Our results show both similarities and differences with the published mouse urine response and a dose- and time-dependent net decrease in urine ion excretion associated with radiation exposure. These findings mark an important step in the development of minimally invasive radiation biodosimetry. VAMP should have general applicability in metabolomics to visualize overall differences and trends in many sample sets.
KeywordsRadiation Biodosimetry Bioinformatics
Differential mobility spectrometry–mass spectrometry
Armed Forces Radiobiology Research Institute
Ultra-performance liquid chromatography–time of flight mass spectrometry
Principal component analysis
Parts per million
Visual Analysis of Metabolomics Package
This study was supported by the National Institute of Health (National Institute of Allergy and Infectious Diseases) Grant U19 A1067773. F.J.G. is supported by the National Cancer Instititue Intramural Research Program in the Center for Cancer Research. J.F.K. was supported in part by Grant DARPA-FY08-0004 from the Defense Advanced Research Projects Agency. The views expressed are those of the authors and do not reflect the official policy or position of the Armed Forces Radiobiology Research Institute, the Uniformed Services University, the Department of Defense, or the United States Government. The authors would like to thank Drs. Andrew D. Patterson (Penn. State Univ.) and David J. Brenner for helpful discussions and their support.
Conflict of interest
The authors have no conflicts of interest to report.
All animal experiments were approved by the Armed Forces Radiobiology Research Institute’s Animal Care and Use Committee prior to initiation. Animals were maintained in a facility accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International in accordance with the Guide for the Care and Use of Laboratory Animals.
- Amendola, R., Basso, E., Pacifici, P. G., Piras, E., Giovanetti, A., Volpato, C., et al. (2006). Ret, Abl1 (cAbl) and Trp53 gene fragmentations in comet-FISH assay act as in vivo biomarkers of radiation exposure in C57BL/6 and CBA/J mice. Radiation Research, 165, 553–561.CrossRefPubMedGoogle Scholar
- Castro-Perez, J., Plumb, R., Granger, J. H., Beattie, I., Joncour, K., & Wright, A. (2005). Increasing throughput and information content for in vitro drug metabolism experiments using ultra-performance liquid chromatography coupled to a quadrupole time-of-flight mass spectrometer. Rapid Communications in Mass Spectrometry, 19, 843–848.CrossRefPubMedGoogle Scholar
- Coy, S. L., Krylov, E. V., Schneider, B. B., Covey, T. R., Brenner, D. J., Tyburski, J. B., et al. (2010). Detection of radiation-exposure biomarkers by differential mobility prefiltered mass spectrometry (DMS-MS). International Journal of Mass Spectrometry, 291, 108–117.PubMedCentralCrossRefPubMedGoogle Scholar
- Johnson, C. H., Patterson, A. D., Krausz, K. W., Kalinich, J. F., Tyburski, J. B., Kang, D. W., et al. (2012). Radiation Metabolomics. 5. Identification of urinary biomarkers of ionizing radiation exposure in nonhuman primates by mass spectrometry-based metabolomics. Radiation Research, 178, 328–340.PubMedCentralCrossRefPubMedGoogle Scholar
- Khan, A. R., Rana, P., Devi, M. M., Chaturvedi, S., Javed, S., Tripathi, R. P., et al. (2011). Nuclear magnetic resonance spectroscopy-based metabonomic investigation of biochemical effects in serum of gamma-irradiated mice. International Journal of Radiation Biology, 87, 91–97.CrossRefPubMedGoogle Scholar
- Lanz, C., Patterson, A. D., Slavik, J., Krausz, K. W., Ledermann, M., Gonzalez, F. J., et al. (2009). Radiation metabolomics. 3. Biomarker discovery in the urine of gamma-irradiated rats using a simplified metabolomics protocol of gas chromatography-mass spectrometry combined with random forests machine learning algorithm. Radiation Research, 172, 198–212.PubMedCentralCrossRefPubMedGoogle Scholar
- Tyburski, J. B., Patterson, A. D., Krausz, K. W., Slavik, J., Fornace, A. J. J., Gonzalez, F. J., et al. (2008). Radiation metabolomics. 1. Identification of minimally invasive urine biomarkers for gamma-radiation exposure in mice. Radiation Research, 170, 1–14.PubMedCentralCrossRefPubMedGoogle Scholar
- Tyburski, J. B., Patterson, A. D., Krausz, K. W., Slavik, J., Fornace, A. J, Jr, Gonzalez, F. J., et al. (2009). Radiation metabolomics. 2. Dose- and time-dependent urinary excretion of deaminated purines and pyrimidines after sublethal gamma-radiation exposure in mice. Radiation Research, 172, 42–57.PubMedCentralCrossRefPubMedGoogle Scholar