Radiation and Environmental Biophysics

, Volume 55, Issue 1, pp 53–59 | Cite as

In vitro RABiT measurement of dose rate effects on radiation induction of micronuclei in human peripheral blood lymphocytes

  • Antonella Bertucci
  • Lubomir B. Smilenov
  • Helen C. Turner
  • Sally A. Amundson
  • David J. Brenner
Original Article

Abstract

Developing new methods for radiation biodosimetry has been identified as a high-priority need in case of a radiological accident or nuclear terrorist attacks. A large-scale radiological incident would result in an immediate critical need to assess the radiation doses received by thousands of individuals. Casualties will be exposed to different doses and dose rates due to their geographical position and sheltering conditions, and dose rate is one of the principal factors that determine the biological consequences of a given absorbed dose. In these scenarios, high-throughput platforms are required to identify the biological dose in a large number of exposed individuals for clinical monitoring and medical treatment. The Rapid Automated Biodosimetry Tool (RABiT) is designed to be completely automated from the input of blood sample into the machine to the output of a dose estimate. The primary goal of this paper was to quantify the dose rate effects for RABiT-measured micronuclei in vitro in human lymphocytes. Blood samples from healthy volunteers were exposed in vitro to different doses of X-rays to acute and protracted doses over a period up to 24 h. The acute dose was delivered at ~1.03 Gy/min and the low dose rate exposure at ~0.31 Gy/min. The results showed that the yield of micronuclei decreases with decreasing dose rate starting at 2 Gy, whereas response was indistinguishable from that of acute exposure in the low dose region, up to 0.5 Gy. The results showed a linear-quadratic dose–response relationship for the occurrence of micronuclei for the acute exposure and a linear dose–response relationship for the low dose rate exposure.

Keywords

Biodosimetry Micronuclei RABiT High throughput Nuclear accident 

References

  1. Bhat NN, Rao BS (2003) Dose rate effect on micronuclei induction in cytokinesis blocked human peripheral blood lymphocytes. Radiat Prot Dosim 106(1):45–52CrossRefGoogle Scholar
  2. Boreham DR et al (2000) Dose-rate effects for apoptosis and micronucleus formation in gamma-irradiated human lymphocytes. Radiat Res 153(5 Pt 1):579–586CrossRefADSGoogle Scholar
  3. Coy SL et al (2011) Radiation metabolomics and its potential in biodosimetry. Int J Radiat Biol 87(8):802–823CrossRefGoogle Scholar
  4. DiCarlo AL et al (2011) Radiation injury after a nuclear detonation: medical consequences and the need for scarce resources allocation. Disaster Med Public Health Prep 5(Suppl 1):S32–S44CrossRefGoogle Scholar
  5. Fenech M (2006) Cytokinesis-block micronucleus assay evolves into a “cytome” assay of chromosomal instability, mitotic dysfunction and cell death. Mutat Res 600(1–2):58–66CrossRefGoogle Scholar
  6. Fenech M (2007) Cytokinesis-block micronucleus cytome assay. Nat Protoc 2(5):1084–1104CrossRefGoogle Scholar
  7. Fenech M (2010) The lymphocyte cytokinesis-block micronucleus cytome assay and its application in radiation biodosimetry. Health Phys 98(2):234–243CrossRefGoogle Scholar
  8. Garty G et al (2010) The RABIT: a rapid automated biodosimetry tool for radiological triage. Health Phys 98(2):209–217CrossRefGoogle Scholar
  9. Garty G et al (2011) The RABiT: a rapid automated biodosimetry tool for radiological triage. II. Technological developments. Int J Radiat Biol 87(8):776–790CrossRefGoogle Scholar
  10. Garty G et al (2015) An automated imaging system for radiation biodosimetry. Microsc Res Tech 78(7):587–598CrossRefGoogle Scholar
  11. Geard CR, Chen CY (1990) Micronuclei and clonogenicity following low- and high-dose-rate gamma irradiation of normal human fibroblasts. Radiat Res 124(1 Suppl):S56–S61CrossRefGoogle Scholar
  12. Goudarzi M et al (2014a) The effect of low dose rate on metabolomic response to radiation in mice. Radiat Environ Biophys 53(4):645–657CrossRefMathSciNetGoogle Scholar
  13. Goudarzi M et al (2014b) Development of urinary biomarkers for internal exposure by cesium-137 using a metabolomics approach in mice. Radiat Res 181(1):54–64CrossRefGoogle Scholar
  14. Hall EJ (1991) Weiss lecture. The dose-rate factor in radiation biology. Int J Radiat Biol 59(3):595–610CrossRefGoogle Scholar
  15. Jaworska A et al (2015) Operational guidance for radiation emergency response organisations in Europe for using biodosimetric tools developed in EU MULTIBIODOSE project. Radiat Prot Dosim 164(1–2):165–169CrossRefGoogle Scholar
  16. Knebel AR et al (2011) Allocation of scarce resources after a nuclear detonation: setting the context. Disaster Med Public Health Prep 5(Suppl 1):S20–S31CrossRefGoogle Scholar
  17. Kulka U et al (2015) Realising the European network of biodosimetry: RENEB—status quo. Radiat Prot Dosim 164(1–2):42–45CrossRefGoogle Scholar
  18. Laiakis EC et al (2014) Metabolic phenotyping reveals a lipid mediator response to ionizing radiation. J Proteome Res 13(9):4143–4154CrossRefGoogle Scholar
  19. Lyulko OV et al (2014) Fast image analysis for the micronucleus assay in a fully automated high-throughput biodosimetry system. Radiat Res 181(2):146–161CrossRefGoogle Scholar
  20. Marchetti F et al (2006) Candidate protein biodosimeters of human exposure to ionizing radiation. Int J Radiat Biol 82(9):605–639CrossRefGoogle Scholar
  21. Padovani L et al (1993) Cytogenetic study in lymphocytes from children exposed to ionizing radiation after the Chernobyl accident. Mutat Res 319(1):55–60CrossRefGoogle Scholar
  22. Paul S, Amundson SA (2008) Development of gene expression signatures for practical radiation biodosimetry. Int J Radiat Oncol Biol Phys 71(4):1236–1244CrossRefGoogle Scholar
  23. Pellmar TC, Rockwell S, G. Radiological/Nuclear Threat Countermeasures Working (2005) Priority list of research areas for radiological nuclear threat countermeasures. Radiat Res 163(1):115–123CrossRefGoogle Scholar
  24. Ramakrishnana N, Brenner D (2008) Predicting individual radiation sensitivity: current and evolving technologies. Radiat Res 170(5):666–675CrossRefGoogle Scholar
  25. Redon CE et al (2009) γ-H2AX as a biomarker of DNA damage induced by ionizing radiation in human peripheral blood lymphocytes and artificial skin. Adv Space Res 43(8):1171–1178CrossRefADSGoogle Scholar
  26. Repin M et al (2014) Next generation platforms for high-throughput biodosimetry. Radiat Prot Dosim 159(1–4):105–110CrossRefGoogle Scholar
  27. Rothkamm K et al (2013) Comparison of established and emerging biodosimetry assays. Radiat Res 180(2):111–119CrossRefGoogle Scholar
  28. Scott D, Hu Q, Roberts SA (1996) Dose-rate sparing for micronucleus induction in lymphocytes of controls and ataxia-telangiectasia heterozygotes exposed to 60Co gamma-irradiation in vitro. Int J Radiat Biol 70(5):521–527CrossRefGoogle Scholar
  29. Sorensen KJ et al (2000) The in vivo dose rate effect of chronic gamma radiation in mice: translocation and micronucleus analyses. Mutat Res 457(1–2):125–136CrossRefGoogle Scholar
  30. Swartz HM et al (2014) Comparison of the needs for biodosimetry for large-scale radiation events for military versus civilian populations. Health Phys 106(6):755–763CrossRefGoogle Scholar
  31. Thierens H, Vral A (2009) The micronucleus assay in radiation accidents. Ann Ist Super Sanita 45(3):260–264Google Scholar
  32. Thierens H et al (2005) Cytogenetic biodosimetry of an accidental exposure of a radiological worker using multiple assays. Radiat Prot Dosim 113(4):408–414CrossRefGoogle Scholar
  33. Thierens H et al (2014) Is a semi-automated approach indicated in the application of the automated micronucleus assay for triage purposes? Radiat Prot Dosim 159(1–4):87–94CrossRefGoogle Scholar
  34. Turesson I (1990) Radiobiological aspects of continuous low dose-rate irradiation and fractionated high dose-rate irradiation. Radiother Oncol 19(1):1–15CrossRefGoogle Scholar
  35. Turner HC et al (2011) Adapting the gamma-H2AX assay for automated processing in human lymphocytes. 1. Technological aspects. Radiat Res 175(3):282–290CrossRefGoogle Scholar
  36. Vilenchik MM, Knudson AG (2006) Radiation dose-rate effects, endogenous DNA damage, and signaling resonance. Proc Natl Acad Sci USA 103(47):17874–17879CrossRefADSGoogle Scholar
  37. Voisin P et al (2001) The cytogenetic dosimetry of recent accidental overexposure. Cell Mol Biol (Noisy-le-grand) 47(3):557–564Google Scholar
  38. Voisin P et al (2004) Criticality accident dosimetry by chromosomal analysis. Radiat Prot Dosim 110(1–4):443–447CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Antonella Bertucci
    • 1
  • Lubomir B. Smilenov
    • 1
  • Helen C. Turner
    • 1
  • Sally A. Amundson
    • 1
  • David J. Brenner
    • 1
  1. 1.Center for Radiological ResearchColumbia University Medical CenterNew YorkUSA

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