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Host-Symbiont Interaction Model Explains Non-monotonic Response of Soybean Growth and Seed Production to Nano-CeO2 Exposure.

Tin KlanjščekErik B MullerPatricia A HoldenRoger M Nisbet
Published in: Environmental science & technology (2017)
Recent nanotoxicity studies have demonstrated non-monotonic dose-response mechanisms for planted soybean that have a symbiotic relationship with bacteroids in their root nodules: reduction of growth and seed production was greater for low, as compared to high, exposures. To investigate mechanistic underpinnings of the observed patterns, we formulated an energy budget model coupled to a toxicokinetic module describing bioaccumulation, and two toxicodynamic modules describing toxic effects on host plant and symbionts. By fitting data on plants exposed to engineered CeO2 nanoparticles to the newly formulated model, we show that the non-monotonic patterns can be explained as the interaction of two, individually monotonic, dose-response processes: one for the plant and the other for the symbiont. We further validate the newly formulated model by showing that, without the need for additional parameters, the model successfully predicts changes in dinitrogen fixation potential as a function of exposure (dinitrogen fixation potential data not used in model fitting). The symbiont buffers overall toxicity only when, in the absence of exposure to a toxicant, it has a parasitic interaction with the host plant. If the interaction is mutualistic or commensal, there is no buffering and only monotonic toxic responses are possible. Because the model is based on general biological principles, we expect it to be applicable to other similar symbiotic systems, especially other nodule-forming legumes.
Keyphrases
  • air pollution
  • machine learning
  • deep learning
  • heavy metals
  • big data