Metabolomics

, 12:80 | Cite as

A lipidomic and metabolomic serum signature from nonhuman primates exposed to ionizing radiation

  • Evan L. Pannkuk
  • Evagelia C. Laiakis
  • Tytus D. Mak
  • Giuseppe Astarita
  • Simon Authier
  • Karen Wong
  • Albert J. FornaceJr.
Original Article

Abstract

Introduction

Due to dangers associated with potential accidents from nuclear energy and terrorist threats, there is a need for high-throughput biodosimetry to rapidly assess individual doses of radiation exposure. Lipidomics and metabolomics are becoming common tools for determining global signatures after disease or other physical insult and provide a “snapshot” of potential cellular damage.

Objectives

The current study assesses changes in the nonhuman primate (NHP) serum lipidome and metabolome 7 days following exposure to ionizing radiation (IR).

Methods

Serum sample lipids and metabolites were extracted using a biphasic liquid–liquid extraction and analyzed by ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry. Global radiation signatures were acquired in data-independent mode.

Results

Radiation exposure caused significant perturbations in lipid metabolism, affecting all major lipid species, including free fatty acids, glycerolipids, glycerophospholipids and esterified sterols. In particular, we observed a significant increase in the levels of polyunsaturated fatty acids (PUFA)-containing lipids in the serum of NHPs exposed to 10 Gy radiation, suggesting a primary role played by PUFAs in the physiological response to IR. Metabolomics profiling indicated an increase in the levels of amino acids, carnitine, and purine metabolites in the serum of NHPs exposed to 10 Gy radiation, suggesting perturbations to protein digestion/absorption, biological oxidations, and fatty acid β-oxidation.

Conclusions

This is the first report to determine changes in the global NHP serum lipidome and metabolome following radiation exposure and provides information for developing metabolomic biomarker panels in human-based biodosimetry.

Keywords

Lipidomics Metabolomics Ionizing Radiation Nonhuman Primate 

Supplementary material

11306_2016_1010_MOESM1_ESM.docx (6.5 mb)
Supplementary material 1 (DOCX 6647 kb)

References

  1. Astarita, G., Kendall, A. C., Dennis, E. A., & Nicolaou, A. (2015). Targeted lipidomic strategies for oxygenated metabolites of polyunsaturated fatty acids. Biochimica et Biophysica Acta, 1851(4), 456–468.CrossRefPubMedPubMedCentralGoogle Scholar
  2. Astarita, G., & Langridge, J. (2013). An emerging role for metabolomics in nutrition science. J Nutrigenet Nutrigenomics, 6(4–5), 181–200.CrossRefPubMedGoogle Scholar
  3. Braverman, N. E., & Moser, A. B. (2012). Functions of plasmalogen lipids in health and disease. Biochimica et Biophysica Acta, 1822(9), 1442–1452.CrossRefPubMedGoogle Scholar
  4. Broin, P. Ó., Vaitheesvaran, B., Saha, S., Hartil, K., Chen, E. I., Goldman, D., et al. (2015). Intestinal microbiota-derived metabolomic blood plasma markers for prior radiation injury. International Journal of Radiation Oncology Biology Physics, 91(2), 360–367.CrossRefGoogle Scholar
  5. Calder, P. C. (2006). n-3 polyunsaturated fatty acids, inflammation, and inflammatory diseases. American Journal of Clinical Nutrition, 83(6 Suppl), 1505S–1519S.PubMedGoogle Scholar
  6. Caspi, R., Altman, T., Billington, R., Dreher, K., Foerster, H., Fulcher, C. A., et al. (2014). The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases. Nucleic Acids Research, 42, D459–D471.CrossRefPubMedPubMedCentralGoogle Scholar
  7. Cox, D. G., Oh, J., Keasling, A., Colson, K. L., & Hamann, M. T. (2014). The utility of metabolomics in natural product and biomarker characterization. Biochimica et Biophysica Acta, 1840(12), 3460–3474.CrossRefPubMedPubMedCentralGoogle Scholar
  8. Croft, D., Mundo, A. F., Haw, R., Milacic, M., Weiser, J., Wu, G., et al. (2014). The Reactome pathway knowledgebase. Nucleic Acids Research, 42, D472–D477.CrossRefPubMedPubMedCentralGoogle Scholar
  9. Dawson, L. A., Kavanagh, B. D., Paulino, A. C., Das, S. K., Miften, M., Li, X. A., et al. (2010). Radiation-associated kidney injury. International Journal of Radiation Oncology Biology Physics, 76(3 Suppl), S108–S115.CrossRefGoogle Scholar
  10. Degtyarenko, K., De Matos, P., Ennis, M., Hastings, J., Zbinden, M., Mcnaught, A., et al. (2008). ChEBI: a database and ontology for chemical entities of biological interest. Nucleic Acids Research, 36, D344–D350.CrossRefPubMedPubMedCentralGoogle Scholar
  11. Dicarlo, A. L., Jackson, I. L., Shah, J. R., Czarniecki, C. W., Maidment, B. W., & Williams, J. P. (2012). Development and licensure of medical countermeasures to treat lung damage resulting from a radiological or nuclear incident. Radiation Research, 177(5), 717–721.CrossRefPubMedGoogle Scholar
  12. Dicarlo, A. L., Ramakrishnan, N., & Hatchett, R. J. (2010). Radiation combined injury: overview of NIAID research. Health Physics, 98(6), 863–867.CrossRefPubMedGoogle Scholar
  13. Fahy, E., Subramaniam, S., Murphy, R. C., Nishijima, M., Raetz, C. R., Shimizu, T., et al. (2009). Update of the LIPID MAPS comprehensive classification system for lipids. Journal of Lipid Research, 50(Suppl), S9–14.PubMedPubMedCentralGoogle Scholar
  14. Fahy, E., Sud, M., Cotter, D., & Subramaniam, S. (2007). LIPID MAPS online tools for lipid research. Nucleic Acids Research, 35, W606–W612.CrossRefPubMedPubMedCentralGoogle Scholar
  15. Feurgard, C., Bayle, D., Guezingar, F., Serougne, C., Mazur, A., Lutton, C., et al. (1998). Effects of ionizing radiation (neutrons/gamma rays) on plasma lipids and lipoproteins in rats. Radiation Research, 150(1), 43–51.CrossRefPubMedGoogle Scholar
  16. Fruhwirth, G. O., Loidl, A., & Hermetter, A. (2007). Oxidized phospholipids: from molecular properties to disease. Biochimica et Biophysica Acta, 1772(7), 718–736.CrossRefPubMedGoogle Scholar
  17. Goudarzi, M., Mak, T. D., Chen, C., Smilenov, L. B., Brenner, D. J., & Fornace, A. J. (2014). The effect of low dose rate on metabolomic response to radiation in mice. Radiation and Environmental Biophysics, 53(4), 645–657.CrossRefPubMedPubMedCentralGoogle Scholar
  18. Goudarzi, M., Weber, W. M., Mak, T. D., Chung, J., Doyle-Eisele, M., Melo, D. R., et al. (2015). Metabolomic and Lipidomic Analysis of Serum from Mice Exposed to an Internal Emitter, Cesium-137, Using a Shotgun LC-MSE Approach. Journal of Proteome Research, 14(1), 374–384.CrossRefPubMedPubMedCentralGoogle Scholar
  19. Hall, E. C., & Giaccia, A. J. (2012). Radiobiology for the Radiologist (7th ed.). Philadelphia: Lippincott Williams & Wilkins.Google Scholar
  20. Hannun, Y. A., & Obeid, L. M. (2011). Many ceramides. Journal of Biological Chemistry, 286(32), 27855–27862.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 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(4), 328–340.CrossRefPubMedPubMedCentralGoogle Scholar
  22. Johnson, C. H., Patterson, A. D., Krausz, K. W., Lanz, C., Kang, D. W., Luecke, H., et al. (2011). Radiation metabolomics. 4. UPLC-ESI-QTOFMS-Based metabolomics for urinary biomarker discovery in gamma-irradiated rats. Radiation Research, 175(4), 473–484.CrossRefPubMedPubMedCentralGoogle Scholar
  23. Jones, J. W., Tudor, G., Bennett, A., Farese, A. M., Moroni, M., Booth, C., et al. (2014). Development and validation of a LC-MS/MS assay for quantitation of plasma citrulline for application to animal models of the acute radiation syndrome across multiple species. Analytical and Bioanalytical Chemistry, 406(19), 4663–4675.CrossRefPubMedGoogle Scholar
  24. Kanehisa, M., & Goto, S. (2000). KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Research, 28(1), 27–30.CrossRefPubMedPubMedCentralGoogle Scholar
  25. 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(1), 91–97.CrossRefPubMedGoogle Scholar
  26. Kurland, I. J., Broin, P. O., Golden, A., Su, G., Meng, F., Liu, L., et al. (2015). Integrative metabolic signatures for hepatic radiation injury. PLoS One, 10(6), e0124795.CrossRefPubMedPubMedCentralGoogle Scholar
  27. Laiakis, E. C., Hyduke, D. R., & Fornace, A. J. (2012). Comparison of mouse urinary metabolic profiles after exposure to the inflammatory stressors gamma radiation and lipopolysaccharide. Radiation Research, 177(2), 187–199.CrossRefPubMedPubMedCentralGoogle Scholar
  28. Laiakis, E. C., Mak, T. D., Anizan, S., Amundson, S. A., Barker, C. A., Wolden, S. L., et al. (2014a). Development of a metabolomic radiation signature in urine from patients undergoing total body irradiation. Radiation Research, 181, 350–361.CrossRefPubMedPubMedCentralGoogle Scholar
  29. Laiakis, E. C., Strassburg, K., Bogumil, R., Lai, S., Vreeken, R. J., Hankemeier, T., et al. (2014b). Metabolic phenotyping reveals a lipid mediator response to ionizing radiation. Journal of Proteome Research, 13(9), 4143–4154.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 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(2), 198–212.CrossRefPubMedPubMedCentralGoogle Scholar
  31. Li, H. H., Tyburski, J. B., Wang, Y. W., Strawn, S., Moon, B. H., Kallakury, B. V., et al. (2014). Modulation of fatty acid and bile acid metabolism by peroxisome proliferator-activated receptor alpha protects against alcoholic liver disease. Alcoholism, Clinical and Experimental Research, 38(6), 1520–1531.CrossRefPubMedPubMedCentralGoogle Scholar
  32. Liu, H., Wang, Z., Zhang, X., Qiao, Y., Wu, S., Dong, F., et al. (2013). Selection of candidate radiation biomarkers in the serum of rats exposed to gamma-rays by GC/TOFMS-based metabolomics. Radiation Protection Dosimetry, 154(1), 9–17.CrossRefPubMedGoogle Scholar
  33. Macvittie, T. J., Bennett, A., Booth, C., Garofalo, M., Tudor, G., Ward, A., et al. (2012a). The prolonged gastrointestinal syndrome in rhesus macaques: the relationship between gastrointestinal, hematopoietic, and delayed multi-organ sequelae following acute, potentially lethal, partial-body irradiation. Health Physics, 103(4), 427–453.CrossRefPubMedPubMedCentralGoogle Scholar
  34. Macvittie, T. J., Farese, A. M., Bennett, A., Gelfond, D., Shea-Donohue, T., Tudor, G., et al. (2012b). The acute gastrointestinal subsyndrome of the acute radiation syndrome: a rhesus macaque model. Health Physics, 103(4), 411–426.CrossRefPubMedGoogle Scholar
  35. Mak, T. D., Laiakis, E. C., Goudarzi, M., & Fornace, A. J, Jr. (2014). MetaboLyzer: A novel statistical workflow for analyzing postprocessed LC-MS metabolomics data. Analytical Chemistry, 86(1), 506–513.CrossRefPubMedPubMedCentralGoogle Scholar
  36. Mak, T. D., Laiakis, E. C., Goudarzi, M., & Fornace, A. J. J. (2015). Selective paired ion contrast analysis: A novel algorithm for analyzing postprocessed LC-MS metabolomics data possessing high experimental noise. Analytical Chemistry, 87(6), 3177–3186.CrossRefPubMedPubMedCentralGoogle Scholar
  37. Manna, S. K., Patterson, A. D., Yang, Q., Krausz, K. W., Li, H., Idle, J. R., et al. (2010). Identification of noninvasive biomarkers for alcohol-induced liver disease using urinary metabolomics and the Ppara-null mouse. Journal of Proteome Research, 9, 4176–4188.CrossRefPubMedPubMedCentralGoogle Scholar
  38. Mansour, H. H. (2006). Protective role of carnitine ester against radiation-induced oxidative stress in rats. Pharmacological Research, 54(3), 165–171.CrossRefPubMedGoogle Scholar
  39. Mapstone, M., Cheema, A. K., Fiandaca, M. S., Zhong, X., Mhyre, T. R., Macarthur, L. H., et al. (2014). Plasma phospholipids identify antecedent memory impairment in older adults. Nature Medicine, 20, 415–418.CrossRefPubMedGoogle Scholar
  40. Mukherjee, D., Coates, P. J., Lorimore, S. A., & Wright, E. G. (2014). Responses to ionizing radiation mediated by inflammatory mechanisms. The Journal of Pathology, 232(3), 289–299.CrossRefPubMedGoogle Scholar
  41. Pannkuk, E. L., Laiakis, E. C., Authier, S., Wong, K., & Fornace, A. J, Jr. (2015). Global metabolomic identification of longer-term dose dependent urinary biomarkers in non-human primates exposed to ionizing radiation. Radiation Research, 184(2), 121–133.CrossRefPubMedPubMedCentralGoogle Scholar
  42. Patti, G. J., Yanes, O., & Siuzdak, G. (2012). Innovation: Metabolomics: the apogee of the omics trilogy. Nature Reviews Molecular Cell Biology, 13(4), 263–269.CrossRefPubMedPubMedCentralGoogle Scholar
  43. Reichenbächer, M., & Popp, J. (2012). Challenges in molecular structure determination. Berlin: Springer.CrossRefGoogle Scholar
  44. Ringseis, R., Keller, J., & Eder, K. (2013). Mechanisms underlying the anti-wasting effect of L-carnitine supplementation under pathologic conditions: evidence from experimental and clinical studies. European Journal of Nutrition, 52(5), 1421–1442.CrossRefPubMedGoogle Scholar
  45. Schrier, R. W. (2006). Diseases of the kidney and urinary tract (diseases of the kidney [Schrier]). Philadelphia: Lippincott Williams & Wilkins.Google Scholar
  46. Serhan, C. N., & Savill, J. (2005). Resolution of inflammation: the beginning programs the end. Nature Immunology, 6(12), 1191–1197.CrossRefPubMedGoogle Scholar
  47. Subbanagounder, G., Watson, A. D., & Berliner, J. A. (2000). Bioactive products of phospholipid oxidation: isolation, identification, measurement and activities. Free Radical Biology and Medicine, 28(12), 1751–1761.CrossRefPubMedGoogle Scholar
  48. Sugimoto, M., Kawakami, M., Robert, M., Soga, T., & Tomita, M. (2012). Bioinformatics tools for mass spectroscopy-based metabolomic data processing and analysis. Current Bioinformatics, 7(1), 96–108.CrossRefPubMedPubMedCentralGoogle Scholar
  49. Tyburski, J. B., Patterson, A. D., Krausz, K. W., Slavik, J., Fornace, A. J, Jr, 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), 1–14.CrossRefPubMedPubMedCentralGoogle Scholar
  50. Vihervaara, T., Suoniemi, M., & Laaksonen, R. (2014). Lipidomics in drug discovery. Drug Discov Today, 19(2), 164–170.CrossRefPubMedGoogle Scholar
  51. Wishart, D. S., Knox, C., Guo, A. C., Eisner, R., Young, N., Gautam, B., et al. (2009). HMDB: a knowledgebase for the human metabolome. Nucleic Acids Research, 37, D603–D610.CrossRefPubMedPubMedCentralGoogle Scholar
  52. Yin, H., Xu, L., & Porter, N. A. (2011). Free radical lipid peroxidation: mechanisms and analysis. Chemical Reviews, 111(10), 5944–5972.CrossRefPubMedGoogle Scholar
  53. Zhang, G., Panigrahy, D., Mahakian, L. M., Yang, J., Liu, J. Y., Stephen Lee, K. S., et al. (2013). Epoxy metabolites of docosahexaenoic acid (DHA) inhibit angiogenesis, tumor growth, and metastasis. Proceedings of the National Academy of Sciences of the United States of America, 110(16), 6530–6535.CrossRefPubMedPubMedCentralGoogle Scholar
  54. Zhang, A., Sun, H., & Wang, X. (2012). Serum metabolomics as a novel diagnostic approach for disease: a systematic review. Analytical and Bioanalytical Chemistry, 404(4), 1239–1245.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Biochemistry and Molecular & Cellular BiologyGeorgetown University Medical CenterWashingtonUSA
  2. 2.Mass Spectrometry Data CenterNational Institute of Standards and TechnologyGaithersburgUSA
  3. 3.Health SciencesWaters CorporationMilfordUSA
  4. 4.CiToxLAB North AmericaLavalCanada
  5. 5.Lombardi Comprehensive Cancer CenterWashingtonUSA
  6. 6.Center of Excellence in Genomic Medicine Research (CEGMR)King Abdulaziz UniversityJeddahSaudi Arabia

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