Body size-dependent toxicokinetics and toxicodynamics could explain intra- and interspecies variability in sensitivity

Gergs, André; Kulkarni, Devdutt; Preuß, Thomas G.

doi:10.1016/j.envpol.2015.07.045

Cited by 35 publications

(31 citation statements)

References 43 publications

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“…GUTS models have already been applied to predict survival under time-varying exposure 16 21 , model starvation resistance 57 , model combined effects of toxicity and starvation 58 , represent temporal variation in toxicity in an individual-based model 22 59 , link temporal biomarker response to survival 60 , model survival of gill cells in vitro 61 , map toxicodynamic parameters in chemical space 20 62 , approximate toxicodynamic recovery times 20 and investigate sensitivity differences between species 52 63 64 and life-stages 52 65 66 .…”

Section: Discussionmentioning

confidence: 99%

“…Some studies hypothesized that TKTD model parameters, such as those of GUTS models, could be combined with species traits or phylogenetic information to explain and predict species sensitivity differences 48 49 . Species traits such as metabolic rate, which scales with size 50 , correlated with the threshold parameter for a small set of chemicals 51 and the dominant rate constant could be related to the size of three different species 52 . These two examples suggest that predictions of species sensitivity based on phylogeny 49 53 54 could be refined to predict GUTS parameters as proxy for sensitivity.…”

Section: Study 3: Interspecies Variability Of Chemically-induced Effementioning

confidence: 99%

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Modelling survival: exposure pattern, species sensitivity and uncertainty

Ashauer

Albert

Augustine

et al. 2016

Sci Rep

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The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

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Section: Discussionmentioning

confidence: 99%

Section: Study 3: Interspecies Variability Of Chemically-induced Effementioning

confidence: 99%

Modelling survival: exposure pattern, species sensitivity and uncertainty

Ashauer

Albert

Augustine

et al. 2016

Sci Rep

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“…Relationships that link both single and also multiple traits to sensitivity have been identified. For example, Gergs et al (2015) found a relationship between sensitivity and body size, which has been linked to possible effects on TK traits for Triphenyltin hydroxide through a surface area to body mass scaling relationship (Rubach et al, 2010a). Dalhoff et al (2020) also found a strong correlation between surface area/volume and TK parameters (sorption and uptake rate constants and the resulting BCF) for a pyrethroid insecticide.…”

Section: Toxicokinetic Traits and Species Sensitivitymentioning

confidence: 99%

“…A number of studies have attempted to link variations in species anatomical or physiological traits to chemical sensitivity (Baird and Van den Brink, 2007;Rubach et al, 2012Rubach et al, , 2010aQiu et al, 2014;Gergs et al, 2015;Rico and Van den Brink, 2015;Van den Berg et al, 2019;Dalhoff et al, 2020). Most commonly the traits available and used have been either taxonomic, anatomical (e.g., body size and weight, presence of external respiratory surfaces), life-history (e.g., life-span, reproductive strategy) or ecological (life-stage specific habitat, feeding guild), although Rubach et al (2012) and Van den Berg et al (2019) both included measured TK traits and Dalhoff et al (2020) included TK and TD parameters derived from modeling.…”

Section: Toxicokinetic Traits and Species Sensitivitymentioning

confidence: 99%

Species Sensitivity to Toxic Substances: Evolution, Ecology and Applications

Spurgeon

Lahive

Robinson

et al. 2020

Front. Environ. Sci.

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Because it is only possible to test chemicals for effects on a restricted range of species and exposure scenarios, ecotoxicologists are faced with a significant challenge of how to translate the measurements in model species into predictions of impacts for the wider range of species in ecosystems. Because of this challenge, within ecotoxicology there is no more fundamental aspect than to understand the nature of the traits that determine sensitivity. To account for the uncertainties of species extrapolations in risk assessment, “safety factors” or species sensitivity distributions are commonly used. While valuable as pragmatic tools, these approaches have no mechanistic grounding. Here we highlight how mechanistic information that is increasingly available for a range of traits can be used to understand and potentially predict species sensitivity to chemicals. We review current knowledge on how toxicokinetic, toxicodynamic, physiological, and ecological traits contribute to differences in sensitivity. We go on to discuss how this information is being used to make predictions of sensitivity using correlative and trait-based approaches, including comparisons of target receptor orthologs. Finally, we discuss how the emerging knowledge and associated tools can be used to enhance theoretical and applied ecotoxicological research through improvements in mechanistic modeling, predictive ecotoxicology, species sensitivity distribution development, mixture toxicity assessment, chemical design, biotechnology application and mechanistically informed monitoring.

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“…In case of survival, the General Unified Threshold Model of Survival (GUTS, Jager et al ) has been used to address many unresolved questions. Examples of applications include predicting effects from time‐varying exposure (Nyman et al ; Ashauer et al ), modeling combined effects of toxicity and starvation (Nyman et al ), representing the temporal variation in toxicity of the different organisms within a population (Gergs et al ; Gabsi et al ), or investigating differences in sensitivity between species (Beaudouin et al ; Kon Kam King et al ; Gergs et al ) and life‐stages (Kulkarni et al ; Gergs et al ). In 2015, an international workshop involving scientists and representatives from regulatory authorities was held on the use of GUTS in environmental risk assessment.…”

Section: Introductionmentioning

confidence: 99%

Short‐term to long‐term extrapolation of lethal effects of an herbicide on the marine mysid shrimpAmericamysis Bahiaby use of the General Unified Threshold Model of Survival (GUTS)

Gabsi¹,

Solga

Bruns

et al. 2018

Integr Envir Assess & Manag

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Risk assessments for plant protection products and their active ingredients that are based on standard laboratory tests performed under constant exposure conditions may result in an overestimation of risks because exposure in the environment is often characterized by a few short peaks. Here, the General Unified Threshold Model of Survival (GUTS) was used to conduct a refined risk assessment for the herbicide tembotrione and its effects on the marine invertebrate Americamysis bahia, for which the standard chronic effect assessment failed. The GUTS model was first calibrated with time-to-effect and concentration-response data from 2 independent acute experiments with A. bahia. Model parameters for both toxicodynamic assumptions of stochastic death (SD) and individual tolerance (IT) were estimated with the reduced GUTS model (GUTS-RED) using the scaled internal concentration as a dose metric. Both the calibrated GUTS-RED-SD and GUTS-RED-IT models described survival dynamics well. Model validation using datasets of 2 independent chronic tests yielded robust predictions of long-term toxicity of tembotrione on A. bahia, with GUTS-RED-IT being more reliable than GUTS-RED-SD. The validated model was subsequently used to predict survival from time-variable exposure profiles, as derived from the FOrum for Co-ordination of pesticide fate models and their USe (FOCUS). Because ecotoxicological independence of peaks had not been empirically verified, the link between exposure and effects was assessed with complete exposure profiles. Effect thresholds resulting from different peak exposure concentrations and durations were determined with GUTS and directly compared with the exposure concentrations from the FOCUS surface water scenarios. The derived values were higher than the predicted FOCUS critical concentrations. Additionally, comparing the areas under the curve (AUCs) derived with GUTS for multiple peak exposure profiles to those from FOCUS revealed significant additional safety margins, demonstrating that only unrealistically high exposure concentrations would produce significant effects. In conclusion, no unacceptable effects of tembotrione on aquatic invertebrates under realistic environmental exposure conditions are expected. Integr Environ Assess Manag 2018;00:000-000. © 2018 SETAC.

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Body size-dependent toxicokinetics and toxicodynamics could explain intra- and interspecies variability in sensitivity

Cited by 35 publications

References 43 publications

Modelling survival: exposure pattern, species sensitivity and uncertainty

Modelling survival: exposure pattern, species sensitivity and uncertainty

Species Sensitivity to Toxic Substances: Evolution, Ecology and Applications

Short‐term to long‐term extrapolation of lethal effects of an herbicide on the marine mysid shrimpAmericamysis Bahiaby use of the General Unified Threshold Model of Survival (GUTS)

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