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Contaminants as viral cofactors: assessing indirect population effects

Kathrine R Springman1, Gael Kurath, James J Anderson

  • 1Columbia Basin Research, School of Fisheries, University of Washington, Puget Sound Plaza, 1325 4th Avenue, Suite 1820, Seattle, WA 98101-2509, USA. kspringman@ucdavis.edu

Aquatic Toxicology (Amsterdam, Netherlands)
|January 12, 2005
PubMed

Insights

This study introduces the Vitality model to assess contaminant impacts on fish populations, revealing that prior exposure to beta-naphthoflavone (BNF) significantly affects mortality from infectious hematopoietic necrosis virus (IHNV). The model effectively quantifies sublethal, indirect toxicant effects at the population level.

Area of Science:

  • Environmental Toxicology
  • Aquatic Toxicology
  • Immunotoxicology

Background:

  • Current toxicological methods often fail to detect contaminant effects, especially those involving immune suppression.
  • Sublethal and indirect toxicant effects are frequently overlooked, limiting their applicability to population-level assessments.
  • The Vitality model offers a framework to evaluate population-level consequences of individual-level toxicant exposure.

Purpose of the Study:

  • To evaluate population-level effects of contaminants causing indirect, sublethal effects using the Vitality model.
  • To assess the impact of a model CYP1A inducer, beta-naphthoflavone (BNF), on rainbow trout (Oncorhynchus mykiss) immune response and subsequent viral challenge.
  • To demonstrate the model's utility in extrapolating individual toxicological data to population-level impacts.

Main Methods:

  • Juvenile rainbow trout were exposed to varying doses of beta-naphthoflavone (BNF) as a pre-stressor.
  • Fish were subsequently challenged with infectious hematopoietic necrosis virus (IHNV) at different concentrations.
  • Mortality data were analyzed using the Vitality model to correlate pre-stressor dose with population-level effects.

Main Results:

  • A strong correlation (R2=0.9944) was found between the average rate of vitality loss and the BNF pre-stressor dose.
  • Mortality patterns (time to death, cumulative mortality) were dependent on the BNF dose, but not significantly affected by IHNV dosage.
  • This suggests that an organism's prior exposure history is critical in determining contaminant and pathogen virulence.

Conclusions:

  • The Vitality model successfully quantifies population-level effects of contaminants with indirect, sublethal impacts, such as BNF.
  • The model allows for the extrapolation of immunosuppressive effects from environmentally relevant contaminant concentrations to target populations.
  • This approach can be applied to assess other environmental contaminants, like polycyclic aromatic hydrocarbons (PAHs), with similar biotransformation pathways.

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