Dataset Information

Explicit Consideration of Temperature Improves Predictions of Toxicokinetic-Toxicodynamic Models for Flupyradifurone and Imidacloprid in Gammarus pulex.

ABSTRACT: In the face of global climate change, where temperature fluctuations and the frequency of extreme weather events are increasing, it is needed to evaluate the impact of temperature on the ecological risk assessment of chemicals. Current state-of-the-art mechanistic effect models, such as toxicokinetic-toxicodynamic (TK-TD) models, often do not explicitly consider temperature as a modulating factor. This study implemented the effect of temperature in a widely used modeling framework, the General Unified Threshold model for Survival (GUTS). We tested the model using data from toxicokinetic and toxicity experiments with Gammarus pulex exposed to the insecticides imidacloprid and flupyradifurone. The experiments revealed increased TK rates with increasing temperature and increased toxicity under chronic exposures. Using the widely used Arrhenius equation, we could include the temperature influence into the modeling. By further testing of different model approaches, differences in the temperature scaling of TK and TD model parameters could be identified, urging further investigations of the underlying mechanisms. Finally, our results show that predictions of TK-TD models improve if we include the toxicity modulating effect of temperature explicitly.

SUBMITTER: Mangold-Doring A

PROVIDER: S-EPMC9671055 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Explicit Consideration of Temperature Improves Predictions of Toxicokinetic-Toxicodynamic Models for Flupyradifurone and Imidacloprid in <i>Gammarus pulex</i>.

Mangold-Döring Annika A Huang Anna A van Nes Egbert H EH Focks Andreas A van den Brink Paul J PJ

Environmental science & technology 20221025 22

In the face of global climate change, where temperature fluctuations and the frequency of extreme weather events are increasing, it is needed to evaluate the impact of temperature on the ecological risk assessment of chemicals. Current state-of-the-art mechanistic effect models, such as toxicokinetic-toxicodynamic (TK-TD) models, often do not explicitly consider temperature as a modulating factor. This study implemented the effect of temperature in a widely used modeling framework, the General U ...[more]

PMID: 36281980

Similar Datasets

Project description:So far, ecotoxicological studies used biomarkers of exposure or of effects in order to investigate the impacts of contaminated areas on biota (Peakall, 1994 [6]). However, although these results are important in the ecotoxicological risk assessment, biomarkers are very specific and only provide information on the biological processes or physiological pathways targeted by the biomarkers experimenters choose to test (Monsinjon and Knigge, 2007 [5]). In recent years, proteomics have become a major tool in ecotoxicology, as they provide a global insight into the mechanism of action of pollutants without the need of hypothesis testing or any preconception on the biological processes likely impacted (Gismondi et al., 2015; Trapp et al., 2015 [7]; Truebano, 2016 [8]). However, the analysis of proteomic results is often limited due to the lack of database, especially for non-model organisms, such as Gammarus sp, commonly used as biological model in ecotoxicology (Sornom et al., 2012 [11]; Vellinger et al., 2013 [9]; Gismondi and Thomé, 2014 [1]; Lebrun et al., 2014 [3]). Here, we performed Illumina HiSeq sequencing to total RNA isolated from the hepatopancreas (i.e. detoxification tissue) of Gammarus pulex males and females coming from uncontaminated river and contaminated river (e.g. PCB, benzo(a)pyrene). Approximately 290 M paired-end reads were assembled, filtered and sorted into 39,801 contigs whose 10.878 were similar of proteins available in databases. The assembled contigs could represent a reference hepatopancreas transcriptome for G. pulex, and constitute an important resource for future investigations on the impacts of pollutants on invertebrate biota, since it would improve the understanding of the mechanisms of action involved in toxicity. In addition, the hepatopancreas transcriptome will also allow the identification of new potential biomarkers for the ecotoxicological risk assessments. Assembled contigs were deposited in the European Nucleotide Archive under the BioProject number PRJEB13055, with accession numbers FJVI01000001-FJVI01039801.

Project description:Providing reliable environmental quality standards (EQSs) is a challenging issue in environmental risk assessment (ERA). These EQSs are derived from toxicity endpoints estimated from dose-response models to identify and characterize the environmental hazard of chemical compounds released by human activities. These toxicity endpoints include the classical x% effect/lethal concentrations at a specific time t (EC/LC(x, t)) and the new multiplication factors applied to environmental exposure profiles leading to x% effect reduction at a specific time t (MF(x, t), or denoted LP(x, t) by the EFSA). However, classical dose-response models used to estimate toxicity endpoints have some weaknesses, such as their dependency on observation time points, which are likely to differ between species (e.g., experiment duration). Furthermore, real-world exposure profiles are rarely constant over time, which makes the use of classical dose-response models difficult and may prevent the derivation of MF(x, t). When dealing with survival or immobility toxicity test data, these issues can be overcome with the use of the general unified threshold model of survival (GUTS), a toxicokinetic-toxicodynamic (TKTD) model that provides an explicit framework to analyse both time- and concentration-dependent data sets as well as obtain a mechanistic derivation of EC/LC(x, t) and MF(x, t) regardless of x and at any time t of interest. In ERA, the assessment of a risk is inherently built upon probability distributions, such that the next critical step is to characterize the uncertainties of toxicity endpoints and, consequently, those of EQSs. With this perspective, we investigated the use of a Bayesian framework to obtain the uncertainties from the calibration process and to propagate them to model predictions, including LC(x, t) and MF(x, t) derivations. We also explored the mathematical properties of LC(x, t) and MF(x, t) as well as the impact of different experimental designs to provide some recommendations for a robust derivation of toxicity endpoints leading to reliable EQSs: avoid computing LC(x, t) and MF(x, t) for extreme x values (0 or 100%), where uncertainty is maximal; compute MF(x, t) after a long period of time to take depuration time into account and test survival under pulses with different periods of time between them.

Dataset Information

Explicit Consideration of Temperature Improves Predictions of Toxicokinetic-Toxicodynamic Models for Flupyradifurone and Imidacloprid in Gammarus pulex.

Publications

Explicit Consideration of Temperature Improves Predictions of Toxicokinetic-Toxicodynamic Models for Flupyradifurone and Imidacloprid in <i>Gammarus pulex</i>.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets