The effect of binary mixtures of zinc, copper, cadmium, and nickel on the growth of the freshwater diatom <i>Navicula pelliculosa</i> and comparison with mixture toxicity model predictions

Nagai, Takashi; Schamphelaere, Karel A.C. De

doi:10.1002/etc.3445

Cited by 35 publications

(30 citation statements)

References 35 publications

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“…In total, 686 individual mixture treatments covering 15 different mixture combinations and 5 different species were identified (for a detailed overview, see the Supplemental Data, Table S1.1). For Navicula pelliculosa, analyses were only based on {Me 2þ }, because exposure media contained ethylenediamine tetraacetic acid (EDTA) [30], which is a strong complexing agent and [Me diss ] values are less relevant in that situation. All data were analyzed using consistent methodologies, largely following those described in Nys et al [1].…”

Section: Meta-analysis Methodsmentioning

confidence: 99%

“…Furthermore, the mode of action may be shared between metals at one level of organization, whereas at other levels of organization they might be metal dependent. Zn-Cu; Ni-Zn; Zn-Cd; Ni-Cu; Ni-Cd; Cu-Cd 216 (6) 72-h growth rate [30] Pseudokirchneriella subcapitata (green algae) Moreover, the mode of action may differ across different groups of organisms.…”

Section: Meta-analysis Methodsmentioning

confidence: 99%

“…The analyses performed based on {Me 2þ } are given in the Supplemental Data. For Navicula pelliculosa, analyses were only based on {Me 2þ }, because exposure media contained ethylenediamine tetraacetic acid (EDTA) [30], which is a strong complexing agent and [Me diss ] values are less relevant in that situation. A more detailed description of the methodology can be found in Supplemental Data S1.…”

Section: Meta-analysis Methodsmentioning

confidence: 99%

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A framework for ecological risk assessment of metal mixtures in aquatic systems

Nys

Regenmortel

Janssen

et al. 2018

Enviro Toxic and Chemistry

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Although metal mixture toxicity has been studied relatively intensely, there is no general consensus yet on how to incorporate metal mixture toxicity into aquatic risk assessment. We combined existing data on chronic metal mixture toxicity at the species level with species sensitivity distribution (SSD)-based in silico metal mixture risk predictions at the community level for mixtures of Ni, Zn, Cu, Cd, and Pb, to develop a tiered risk assessment scheme for metal mixtures in freshwater. Generally, independent action (IA) predicts chronic metal mixture toxicity at the species level most accurately, whereas concentration addition (CA) is the most conservative model. Mixture effects are noninteractive in 69% (IA) and 44% (CA) and antagonistic in 15% (IA) and 51% (CA) of the experiments, whereas synergisms are only observed in 15% (IA) and 5% (CA) of the experiments. At low effect sizes (∼ 10% mixture effect), CA overestimates metal mixture toxicity at the species level by 1.2-fold (i.e., the mixture interaction factor [MIF]; median). Species, metal presence, or number of metals does not significantly affect the MIF. To predict metal mixture risk at the community level, bioavailability-normalization procedures were combined with CA or IA using SSD techniques in 4 different methods, which were compared using environmental monitoring data of a European river basin (the Dommel, The Netherlands). We found that the simplest method, in which CA is directly applied to the SSD (CA ), is also the most conservative method. The CA has median margins of safety (MoS) of 1.1 and 1.2 respectively for binary mixtures compared with the theoretically more consistent methods of applying CA or IA to the dose-response curve of each species individually prior to estimating the fraction of affected species (CA or IA ). The MoS increases linearly with an increasing number of metals, up to 1.4 and 1.7 for quinary mixtures (median) compared with CA and IA , respectively. When our methods were applied to a geochemical baseline database (Forum of European Geological Surveys [FOREGS]), we found that CA yielded a considerable number of mixture risk predictions, even when metals were at background levels (8% of the water samples). In contrast, metal mixture risks predicted with the theoretically more consistent methods (e.g., IA ) were very limited under natural background metal concentrations (<1% of the water samples). Based on the combined evidence of chronic mixture toxicity predictions at the species level and evidence of in silico risk predictions at the community level, a tiered risk assessment scheme for evaluating metal mixture risks is presented, with CA functioning as a first, simple conservative tier. The more complex, but theoretically more consistent and most accurate method, IA , can be used in higher tier assessments. Alternatively, the conservatism of CA can be accounted for deterministically by incorporating the MoS and MIF in the scheme. Finally, specific guidance is also given related to specific issues, such as how to deal wit...

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Section: Meta-analysis Methodsmentioning

confidence: 99%

Section: Meta-analysis Methodsmentioning

confidence: 99%

Section: Meta-analysis Methodsmentioning

confidence: 99%

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A framework for ecological risk assessment of metal mixtures in aquatic systems

Nys

Regenmortel

Janssen

et al. 2018

Enviro Toxic and Chemistry

Self Cite

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“…where C her is the herbicide concentration (micrograms per liter). Then, relative growth rate under the herbicide mixture effect was calculated as [26] Retative growth rate CA ¼ 1…”

Section: Predicting Mixture Effectmentioning

confidence: 99%

Predicting herbicide mixture effects on multiple algal species using mixture toxicity models

Nagai

2017

Enviro Toxic and Chemistry

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The validity of the application of mixture toxicity models, concentration addition and independent action, to a species sensitivity distribution (SSD) for calculation of a multisubstance potentially affected fraction was examined in laboratory experiments. Toxicity assays of herbicide mixtures using 5 species of periphytic algae were conducted. Two mixture experiments were designed: a mixture of 5 herbicides with similar modes of action and a mixture of 5 herbicides with dissimilar modes of action, corresponding to the assumptions of the concentration addition and independent action models, respectively. Experimentally obtained mixture effects on 5 algal species were converted to the fraction of affected (>50% effect on growth rate) species. The predictive ability of the concentration addition and independent action models with direct application to SSD depended on the mode of action of chemicals. That is, prediction was better for the concentration addition model than the independent action model for the mixture of herbicides with similar modes of action. In contrast, prediction was better for the independent action model than the concentration addition model for the mixture of herbicides with dissimilar modes of action. Thus, the concentration addition and independent action models could be applied to SSD in the same manner as for a single-species effect. The present study to validate the application of the concentration addition and independent action models to SSD supports the usefulness of the multisubstance potentially affected fraction as the index of ecological risk. Environ Toxicol Chem 2017;36:2624-2630. © 2017 SETAC.

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“…In ecotoxicological studies, growth endpoints such as biomass, growth rate (Vendrell et al, 2009;Bergtold and Dohmen, 2011;Pérez et al, 2011;Nagai and De Schamphelaere, 2016) or photosystem II (PSII) quantum yield (Magnusson et al, 2008;Sjollema et al, 2014) are often used to evaluate effects on microalgae. These endpoints measured by using time-and cost-effective short-term assays allow the toxicity of single substances or mixtures to be assessed and have proven very useful for identifying which substances are the most toxic.…”

Section: A C C E P T E Dmentioning

confidence: 99%

Toxicity of binary mixtures of pesticides to the marine microalgae Tisochrysis lutea and Skeletonema marinoi: Substance interactions and physiological impacts

et al. 2019

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This study screened binary mixtures of pesticides for potential synergistic interaction effects on growth of the marine microalgae Tisochrysis lutea and Skeletonema marinoi. It also examined the single and combined effects of three of the most toxic substances on microalgal physiology.Single substances were first tested on each microalgal species to determine their respective EC 50 and concentration-response relationships. The toxicity of six and seven binary mixtures was then evaluated in microplate experiments on the growth of T. lutea and S. marinoi, respectively, using two mixture modelling approaches: isobolograms and the MIXTOX tool, based on Concentration Addition (CA) or Independent Action (IA) models. Significant cases of antagonism (for both species) and synergism (for S. marinoi) were observed for the mixtures of isoproturon and spiroxamine, and isoproturon and metazachlor, respectively.These two mixtures, together with that of isoproturon and diuron, for which additivity was observed, were further studied for their impacts on the physiology of each species. Exposures were thus made in culture flasks at three concentrations, or concentration combinations for mixtures, selected to cause 25%, 50% and 75% growth rate inhibition. The effects of the selected pesticides singly and in combination were evaluated at three perceived effect concentrations on esterase metabolic activity, relative lipid content, cytoplasmic membrane potential and reactive oxygen species (ROS) content by flow cytometry, and on photosynthetic quantum yield (ϕ' M ) by PAM-fluorescence.Isoproturon and diuron singly and in mixtures induced 20-40% decreases in ϕ' M which was in turn responsible for a significant decrease in relative lipid content for both species. Spiroxamine and metazachlor were individually responsible for an increase in relative lipid content (up to nearly 300% for Highlights ► The toxicity of binary pesticide mixtures was evaluated on two microalgal species. ► Effects of three selected mixtures were then examined on five physiological functions. ► Effects on microalgal physiology were linked to the pesticide's toxic mode of action. ► Mixed isoproturon and metazachlor had significant synergistic effects on S. marinoi. ► Observed synergy could be due to a combined effect on the photosynthetic apparatus.

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The effect of binary mixtures of zinc, copper, cadmium, and nickel on the growth of the freshwater diatom Navicula pelliculosa and comparison with mixture toxicity model predictions

Cited by 35 publications

References 35 publications

A framework for ecological risk assessment of metal mixtures in aquatic systems

A framework for ecological risk assessment of metal mixtures in aquatic systems

Predicting herbicide mixture effects on multiple algal species using mixture toxicity models

Toxicity of binary mixtures of pesticides to the marine microalgae Tisochrysis lutea and Skeletonema marinoi: Substance interactions and physiological impacts

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