Eleni Siasou
An extended dose-response model for microbial responses to ionizing radiation
Siasou, Eleni; Johnson, David; Willey, Neil
Abstract
© 2017 Siasou, Johnson and Willey. An understanding of the environmental toxicology of ionizing radiation (IR) is needed because nuclear power production is expanding and there is increasing pressure to build nuclear waste repositories. The effects of IR in the environment have long been investigated but there have been fewer studies involving environmental microbiology than its importance to key ecosystems services demands. Here, we highlight some unique aspects of the relationship between microbes and IR and use them to suggest an extended dose-response model. At high doses, IR causes DNA damage and oxidative stress but some microbes have a remarkable capacity for DNA repair and are tolerant of oxidative stress. Not only is significant radioresistance increasingly being reported for microbes, but some microbes are even radiotrophic. The stressful radiative environment of the early Earth might help explain the existence of these traits, which challenge the assumptions of current dose response models for IR. We suggest that a perspective that takes into account these traits plus both dose and dose rate can be used to model an "effects landscape" that might provide insights for the environmental toxicology of IR to microbes. This might help to predict the effects of IR on key ecosystem processes and also be useful in understanding the environmental toxicology of IR in general.
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 20, 2017 |
Online Publication Date | Feb 3, 2017 |
Publication Date | Feb 3, 2017 |
Deposit Date | Jul 16, 2018 |
Publicly Available Date | Jul 16, 2018 |
Journal | Frontiers in Environmental Science |
Electronic ISSN | 2296-665X |
Publisher | Frontiers Media |
Peer Reviewed | Peer Reviewed |
Volume | 5 |
Article Number | 6 |
DOI | https://doi.org/10.3389/fenvs.2017.00006 |
Keywords | ionizing radiation, microorganisms, environmental toxicology, dose–response model, ecosystem processes |
Public URL | https://uwe-repository.worktribe.com/output/898710 |
Publisher URL | http://dx.doi.org/10.3389/fenvs.2017.00006 |
Contract Date | Jul 16, 2018 |
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