Skip to main content
Log in

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

  • Original Article
  • Published:
Metabolomics Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Astarita, G., & Langridge, J. (2013). An emerging role for metabolomics in nutrition science. J Nutrigenet Nutrigenomics, 6(4–5), 181–200.

    Article  CAS  PubMed  Google Scholar 

  • Braverman, N. E., & Moser, A. B. (2012). Functions of plasmalogen lipids in health and disease. Biochimica et Biophysica Acta, 1822(9), 1442–1452.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Calder, P. C. (2006). n-3 polyunsaturated fatty acids, inflammation, and inflammatory diseases. American Journal of Clinical Nutrition, 83(6 Suppl), 1505S–1519S.

    CAS  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  Google Scholar 

  • Dicarlo, A. L., Ramakrishnan, N., & Hatchett, R. J. (2010). Radiation combined injury: overview of NIAID research. Health Physics, 98(6), 863–867.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    PubMed  PubMed Central  Google Scholar 

  • Fahy, E., Sud, M., Cotter, D., & Subramaniam, S. (2007). LIPID MAPS online tools for lipid research. Nucleic Acids Research, 35, W606–W612.

    Article  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  Google Scholar 

  • Fruhwirth, G. O., Loidl, A., & Hermetter, A. (2007). Oxidized phospholipids: from molecular properties to disease. Biochimica et Biophysica Acta, 1772(7), 718–736.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hall, E. C., & Giaccia, A. J. (2012). Radiobiology for the Radiologist (7th ed.). Philadelphia: Lippincott Williams & Wilkins.

    Google Scholar 

  • Hannun, Y. A., & Obeid, L. M. (2011). Many ceramides. Journal of Biological Chemistry, 286(32), 27855–27862.

    Article  CAS  PubMed  PubMed Central  Google 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(4), 328–340.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  Google Scholar 

  • Kanehisa, M., & Goto, S. (2000). KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Research, 28(1), 27–30.

    Article  CAS  PubMed  PubMed Central  Google 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(1), 91–97.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google 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(2), 198–212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mansour, H. H. (2006). Protective role of carnitine ester against radiation-induced oxidative stress in rats. Pharmacological Research, 54(3), 165–171.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Reichenbächer, M., & Popp, J. (2012). Challenges in molecular structure determination. Berlin: Springer.

    Book  Google Scholar 

  • 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.

    Article  CAS  PubMed  Google Scholar 

  • Schrier, R. W. (2006). Diseases of the kidney and urinary tract (diseases of the kidney [Schrier]). Philadelphia: Lippincott Williams & Wilkins.

    Google Scholar 

  • Serhan, C. N., & Savill, J. (2005). Resolution of inflammation: the beginning programs the end. Nature Immunology, 6(12), 1191–1197.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Vihervaara, T., Suoniemi, M., & Laaksonen, R. (2014). Lipidomics in drug discovery. Drug Discov Today, 19(2), 164–170.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Yin, H., Xu, L., & Porter, N. A. (2011). Free radical lipid peroxidation: mechanisms and analysis. Chemical Reviews, 111(10), 5944–5972.

    Article  CAS  PubMed  Google Scholar 

  • 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

The authors acknowledge Lombardi Comprehensive Cancer Proteomics and Metabolomics Shared Resource (PMSR) for data acquisition. Content is the responsibility of authors and does not necessarily represent official views of NCI/NIH.

Funding

National Institutes of Health (National Institute of Allergy and Infectious Diseases) grant 1R01AI101798 (P.I. Albert J. Fornace, Jr.) and Lombardi Comprehensive Cancer Proteomics and Metabolomics Shared Resource (PMSR); partial support National Cancer Institute grant P30CA051008 (P.I. Louis Weiner).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Albert J. Fornace Jr..

Ethics declarations

Conflict of Interest

Evan L. Pannkuk, Evagelia C. Laiakis, Tytus D. Mak, Giuseppe Astarita, Simon Authier, Karen Wong, and Albert J. Fornace Jr. declare that they have no conflict of interest.

Ethics Approval

NHP studies were conducted by CiToxLAB: North America Safety and Health Research Laboratories (Laval, Québec, Canada; study # 5013-0193) and was approved by the Institutional Animal Care and Use Committee.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 6647 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pannkuk, E.L., Laiakis, E.C., Mak, T.D. et al. A lipidomic and metabolomic serum signature from nonhuman primates exposed to ionizing radiation. Metabolomics 12, 80 (2016). https://doi.org/10.1007/s11306-016-1010-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11306-016-1010-0

Keywords

Navigation