Experimental Exposure Assessment of Ionizable Organic Chemicals in <i>In Vitro</i> Cell-Based Bioassays

Huchthausen, Julia; Mühlenbrink, Marie; König, Maria; Escher, Beate I.; Henneberger, Luise

doi:10.1021/acs.chemrestox.0c00067

Cited by 14 publications

(44 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The IC10s and effect concentrations ECIR1.5 in AREc32 or EC10 in PPARγ‐BLA or AhR‐CALUX were previously measured in our laboratory (Neale et al 2017a; Escher et al 2019; Huchthausen et al 2020; Neale et al 2020a) for 121 chemicals in AREc32, 52 chemicals in PPARγ‐BLA, and 89 chemicals in AhR‐CALUX (H4L7.5c2) and are listed in Supplemental Data, Table S1. In Supplemental Data, Table S1, 55 data points (20 chemicals in AREc32, 12 chemicals in PPARγ‐BLA, and 23 chemicals in AhR‐CALUX) were newly measured according to methods described in Neale et al (2020a).…”

Section: Methodsmentioning

confidence: 99%

Effect‐Based Trigger Values for Mixtures of Chemicals in Surface Water Detected with In Vitro Bioassays

Escher

Neale

2021

Enviro Toxic and Chemistry

Self Cite

View full text Add to dashboard Cite

Effect-based trigger (EBT) values for in vitro bioassays are important for surface water quality monitoring because they define the threshold between acceptable and poor water quality. EBTs have been derived for highly specific This article is protected by copyright. All rights reserved. Accepted Article bioassays, such as hormone-receptor activation in reporter gene bioassays, by reading across from existing chemical guideline values. This read-across method is not easily applicable to bioassays indicative of adaptive stress responses, which are triggered by many different chemicals, and activation of nuclear receptors for xenobiotic metabolism, to which many chemicals bind with rather low specificity. We propose an alternative approach to define the EBT from the distribution of specificity ratios of all active chemicals. Specificity ratios are the ratio between the predicted baseline toxicity of a chemical in a given bioassay and its measured specific endpoint. Unlike many previous read-across methods to derive EBTs, the proposed method accounts for mixture effects and includes all chemicals, not only high-potency chemicals. The EBTs were derived from a cytotoxicity EBT that was defined as equivalent to 1% of cytotoxicity in a native surface water sample. The cytotoxicity EBT was scaled by the median of the log-normal distribution of specificity ratios to derive the EBT for effects specific for each bioassay. We illustrate the new approach using the example of the AREc32 assay indicative of the oxidative stress response and two nuclear receptor assays targeting the peroxisome proliferator activated receptor PPAR and the arylhydrocarbon receptor AhR. The EBTs were less conservative than previously proposed but were able to differentiate untreated and insufficiently treated wastewater from wastewater treatment plant effluent with secondary or tertiary treatment and surface water.

show abstract

Section: Methodsmentioning

confidence: 99%

Effect‐Based Trigger Values for Mixtures of Chemicals in Surface Water Detected with In Vitro Bioassays

Escher

Neale

2021

Enviro Toxic and Chemistry

Self Cite

View full text Add to dashboard Cite

show abstract

“…The freely dissolved concentration is the bioavailable concentration and the best experimentally accessible dose-metric because it can be directly compared between different assay types that use different formats and media (Table 9.1, Figure 9.11). The freely dissolved concentrations has been quantified for more than a decade in specific applications (Heringa and Hermens, 2003;Kramer et al, 2012) but has only recently become available for 96-well plate assays thanks to versatile solidphase microextraction (SPME) fibres with low coating volume (Henneberger et al, 2019;Huchthausen et al, 2020). SPME fibres coated with polymers and C18 that sorb charged chemicals have very recently become available in multiplexed plate format, allowing in the future more routine and HT quantification of freely dissolved concentrations.…”

Section: Dose-metrics In Cell Assaysmentioning

confidence: 99%

Bioanalytical Tools in Water Quality Assessment

Neale¹,

Leusch²,

Escher³

2021

View full text Add to dashboard Cite

The first edition of Bioanalytical Tools in Water Quality Assessment was released in 2012. The field has exploded since and the second edition updates and reviews the application of bioanalytical tools for water quality assessment including surveillance monitoring. The book focuses on applications to water quality assessment ranging from wastewater to drinking water, including recycled water, as well as treatment processes and advanced water treatment. Emerging applications for other environmental matrices are also included. Bioanalytical Tools in Water Quality Assessment, Second Edition, not only demonstrates applications but also fills in the background knowledge in toxicology/ecotoxicology needed to appreciate these applications. Each chapter summarises fundamental material in a targeted way so that information can be applied to better understand the use of bioanalytical tools in water quality assessment. The book can be used by lecturers teaching academic and professional courses and also by risk assessors, regulators, experts, consultants, researchers and managers working in the water sector. It can also be a reference manual for environmental engineers, analytical chemists and toxicologists. ISBN: 9781789061970 (Paperback) ISBN: 9781789061987 (eBook)

show abstract

“… a Ref . b Experimental data of the present study (±SD). c Calculated using predicted IC 10,nom for baseline toxicity (SR baseline ) d SR free was assumed to be equal to SR nom . e C free,plasma reported, and C total,plasma calculated by eq . …”

Section: Methodsmentioning

confidence: 99%

“…Mass balance models that consider protein, lipid, and well plate plastic binding − can be used to derive C free of a given chemical in an in vitro assay system. However, these models fail if C free is not constant, but a function of the concentration of the test chemical due to saturable binding to medium proteins, for example, for organic acids, or a function of time due to volatilization or chemical degradation by abiotic processes or cellular metabolism, for example, as recently shown for benzo[ a ]pyrene . Nonlinear protein binding, abiotic degradation, volatilization, and cellular metabolism limit the possibility of retrospective correction of published nominal in vitro effect data.…”

Section: Introductionmentioning

confidence: 99%

“…Two in vitro reporter gene assays were used to illustrate the approach, the TOX21_PPARg_BLA_Agonist_ratio assay (in short PPARγ assay) and the AREc32 assay, which is very similar to the TOX21_ARE_BLA_Agonist_ratio assay . These two assays are not necessarily the most relevant end points for the chemicals investigated, but there were measured freely dissolved concentrations in these bioassays available …”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Quantitative In Vitro-to-In Vivo Extrapolation: Nominal versus Freely Dissolved Concentration

Henneberger

Huchthausen

Wojtysiak

et al. 2021

Chem. Res. Toxicol.

Self Cite

View full text Add to dashboard Cite

Discussions are ongoing on which dose metric should be used for quantitative in vitro-to-in vivo extrapolation (QIVIVE) of in vitro bioassay data. The nominal concentration of the test chemicals is most commonly used and easily accessible, while the concentration freely dissolved in the assay medium is considered to better reflect the bioavailable concentration but is tedious to measure. The aim of this study was to elucidate how much QIVIVE results will differ when using either nominal or freely dissolved concentrations. QIVIVEnom and QIVIVEfree ratios, that is, the ratios of plasma concentrations divided by in vitro effect concentrations, were calculated for 10 pharmaceuticals using previously published nominal and freely dissolved effect concentrations for the activation of the peroxisome proliferator-activated receptor gamma (PPARγ) and the activation of oxidative stress response. The QIVIVEnom ratios were higher than QIVIVEfree ratios by up to a factor of 60. The risk of in vivo effects was classified as being high or low for four chemicals using the QIVIVEnom and for three chemicals using QIVIVEfree ratios. Unambiguous classification was possible for nine chemicals by combining the QIVIVEnom or QIVIVEfree ratios with the respective specificity ratios (SRnom or SRfree) of the in vitro effect data, which helps to identify whether the specific effect was influenced by cytotoxicity. QIVIVEfree models should be preferred as they account for differences in bioavailability between in vitro and in vivo, but QIVIVEnom may still be useful for screening the effects of large numbers of chemicals because it is generally more conservative. The use of SR of the in vitro effect data as a second classification factor is recommended for QIVIVEnom and QIVIVEfree models because a clearer picture can be obtained with respect to the likelihood that a biological effect will occur and that it is not caused by nonspecific cytotoxicity.

show abstract

Experimental Exposure Assessment of Ionizable Organic Chemicals in In Vitro Cell-Based Bioassays

Cited by 14 publications

References 41 publications

Effect‐Based Trigger Values for Mixtures of Chemicals in Surface Water Detected with In Vitro Bioassays

Effect‐Based Trigger Values for Mixtures of Chemicals in Surface Water Detected with In Vitro Bioassays

Bioanalytical Tools in Water Quality Assessment

Quantitative In Vitro-to-In Vivo Extrapolation: Nominal versus Freely Dissolved Concentration

Contact Info

Product

Resources

About