Characterizing Freshwater Ecotoxicity of More Than 9000 Chemicals by Combining Different Levels of Available Measured Test Data with In Silico Predictions.

Ecotoxicological impacts of chemicals released into the environment are characterized by combining fate, exposure, and effects. For characterizing effects, species sensitivity distributions (SSDs) estimate toxic pressures of chemicals as the potentially affected fraction of species. Life cycle assessment (LCA) uses SSDs to identify products with lowest ecotoxicological impacts. To reflect ambient concentrations, the Global Life Cycle Impact Assessment Method (GLAM) ecotoxicity task force recently recommended deriving SSDs for LCA based on chronic EC10s (10% effect concentration, for a life-history trait) and using the 20th percentile of an EC10-based SSD as a working point. However, because we lacked measured effect concentrations, impacts of only few chemicals were assessed, underlining data limitations for decision support. The aims of this paper were therefore to derive and validate freshwater SSDs by combining measured effect concentrations with in silico methods. Freshwater effect factors (EFs) and uncertainty estimates for use in GLAM-consistent life cycle impact assessment were then derived by combining three elements: (1) using intraspecies extrapolating effect data to estimate EC10s, (2) using interspecies quantitative structure-activity relationships, or (3) assuming a constant slope of 0.7 to derive SSDs. Species sensitivity distributions, associated EFs, and EF confidence intervals for 9862 chemicals, including data-poor ones, were estimated based on these elements. Intraspecies extrapolations and the fixed slope approach were most often applied. The resulting EFs were consistent with EFs derived from SSD-EC50 models, implying a similar chemical ecotoxicity rank order and method robustness. Our approach is an important step toward considering the potential ecotoxic impacts of chemicals currently neglected in assessment frameworks due to limited test data. Environ Toxicol Chem 2024;00:1-14. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Ecotoxicity characterization of chemicals: Global recommendations and implementation in USEtox.

Chemicals emitted to the environment affect ecosystem health from local to global scale, and reducing chemical impacts has become an important element of European and global sustainability efforts. The present work advances ecotoxicity characterization of chemicals in life cycle impact assessment by proposing recommendations resulting from international expert workshops and work conducted under the umbrella of the UNEP-SETAC Life Cycle Initiative in the GLAM project (Global guidance on environmental life cycle impact assessment indicators). We include specific recommendations for broadening the assessment scope through proposing to introduce additional environmental compartments beyond freshwater and related ecotoxicity indicators, as well as for adapting the ecotoxicity effect modelling approach to better reflect environmentally relevant exposure levels and including to a larger extent chronic test data. As result, we (1) propose a consistent mathematical framework for calculating freshwater ecotoxicity characterization factors and their underlying fate, exposure and effect parameters; (2) implement the framework into the USEtox scientific consensus model; (3) calculate characterization factors for chemicals reported in an inventory of a life cycle assessment case study on rice production and consumption; and (4) investigate the influence of effect data selection criteria on resulting indicator scores. Our results highlight the need for careful interpretation of life cycle assessment impact scores in light of robustness of underlying species sensitivity distributions. Next steps are to apply the recommended characterization framework in additional case studies, and to adapt it to soil, sediment and the marine environment. Our framework is applicable for evaluating chemicals in life cycle assessment, chemical and environmental footprinting, chemical substitution, risk screening, chemical prioritization, and comparison with environmental sustainability targets.

How Far Can Life Cycle Assessment Be Simplified? A Protocol to Generate Simple and Accurate Models for the Assessment of Energy Systems and Its Application to Heat Production from Enhanced Geothermal Systems.

Life cycle assessments (LCAs) quantify environmental impacts of systems and support decision-making processes. LCAs are however time-consuming and difficult to conduct for nonexperts, thus calling for simplified approaches for multicriteria environmental assessments. In this paper, a five-step protocol is presented to generate simplified arithmetic equations from a reference parametrized LCA model of an energy system and its application illustrated for an enhanced geothermal system for heat generation with very low direct emissions in continental Europe. The simplified models estimate seven environmental impacts (climate change, freshwater ecotoxicity, human health, minerals and metals, and fossil resources depletion, and acidification) based on six technological parameters: number of injection and production wells, power of the production and injection pump, average well length, thermal power output, and eight background parameters defining the European electricity mix. A global sensitivity analysis identified these parameters as influencing the variance of the environmental impacts the most. Ensuring the representativeness of the reference LCA model and the validity of the simplified models requires thorough assessment. This protocol allows to develop relevant alternatives to detailed LCAs for quick and multicriteria environmental impact assessments of energy systems, showing that LCAs can be simplified to system-specific equations based on few, easily quantified, parameters.

Mean Species Abundance as a Measure of Ecotoxicological Risk.

Chemical pollution of surface waters is considered an important driver for recent declines in biodiversity. Species sensitivity distributions (SSDs) are commonly used to evaluate the ecological risks of chemical exposure, accounting for variation in interspecies sensitivity. However, SSDs do not reflect the effects of chemical exposure on species abundance, considered an important endpoint in biological conservation. Although complex population modeling approaches lack practical applicability when it comes to the routine practice of lower tier chemical risk assessment, in the present study we show how information from widely available laboratory toxicity tests can be used to derive the change in mean species abundance (MSA) as a function of chemical exposure. These exposure-response MSA relationships combine insights into intraspecies exposure-response relationships and population growth theory. We showcase the practical applicability of our method for cadmium, copper, and zinc, and include a quantification of the associated statistical uncertainty. For all 3 metals, we found that concentrations hazardous for 5% of the species (HC5 s) based on MSA relationships are systematically higher than SSD-based HC5 values. Our proposed framework can be useful to derive abundance-based ecological protective criteria for chemical exposure, and creates the opportunity to assess abundance impacts of chemical exposure in the context of various other anthropogenic stressors. Environ Toxicol Chem 2020;39:2304-2313. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

A regression-based model to predict chemical migration from packaging to food.

Packaging materials can be a source of chemical contaminants in food. Process-based migration models (PMM) predict the chemical fraction transferred from packaging materials to food (FC) for application in prioritisation tools for human exposure. These models, however, have a relatively limited applicability domain and their predictive performance is typically low. To overcome these limitations, we developed a linear mixed-effects model (LMM) to statistically relate measured FC to properties of chemicals, food, packaging, and experimental conditions. We found a negative relationship between the molecular weight (MW) and FC, and a positive relationship with the fat content of the food depending on the octanol-water partitioning coefficient of the migrant. We also showed that large chemicals (MW > 400 g/mol) have a higher migration potential in packaging with low crystallinity compared with high crystallinity. The predictive performance of the LMM for chemicals not included in the database in contact with untested food items but known packaging material was higher (Coefficient of Efficiency (CoE) = 0.21) compared with a recently developed PMM (CoE = -5.24). We conclude that our empirical model is useful to predict chemical migration from packaging to food and prioritise chemicals in the absence of measurements.

Reliable and representative in silico predictions of freshwater ecotoxicological hazardous concentrations.

A reliable quantification of the potential effects of chemicals on freshwater ecosystems requires ecotoxicological response data for a large set of species which is typically not available in practice. In this study, we propose a method to estimate hazardous concentrations (HCs) of chemicals on freshwater ecosystems by combining two in silico approaches: quantitative structure activity relationships (QSARs) and interspecies correlation estimation (ICE) models. We illustrate the principle of our QSAR-ICE method by quantifying the HCs of 51 chemicals at which 50% and 5% of all species are exposed above the concentration causing acute effects. We assessed the bias of the HCs, defined as the ratio of the HC based on measured ecotoxicity data and the HC based on in silico data, as well as the statistical uncertainty, defined as the ratio of the 95th and 5th percentile of the HC. Our QSAR-ICE method resulted in a bias that was comparable to the use of measured data for three species, as commonly used in effect assessments: the average bias of the QSAR-ICE HC50 was 1.2 and of the HC5 2.3 compared to 1.2 when measured data for three species were used for both HCs. We also found that extreme statistical uncertainties (>105) are commonly avoided in the HCs derived with the QSAR-ICE method compared to the use of three measurements with statistical uncertainties up to 1012. We demonstrated the applicability of our QSAR-ICE approach by deriving HC50s for 1,223 out of the 3,077 organic chemicals of the USEtox database. We conclude that our QSAR-ICE method can be used to determine HCs without the need for additional in vivo testing to help prioritise which chemicals with no or few ecotoxicity data require more thorough assessment.

Confronting variability with uncertainty in the ecotoxicological impact assessment of down-the-drain products.

The use of down-the-drain products and the resultant release of chemicals may lead to pressures on the freshwater environment. Ecotoxicological impact assessment is a commonly used approach to assess chemical products but is still influenced by several uncertainty and variability sources. As a result, the robustness and reliability of such assessments can be questioned. A comprehensive and systematic assessment of these sources is, therefore, needed to increase their utility and credibility. In this study, we present a method to systematically analyse the uncertainty and variability of the potential ecotoxicological impact (PEI) of chemicals using a portfolio of 54 shampoo products. We separately quantified the influence of the statistical uncertainty in the prediction of physicochemical properties and freshwater toxicity as predicted from Quantitative Structure-Property Relationships (QSPRs) and Quantitative Structure-Activity Relationships (QSARs) respectively, and of various sources of spatial and technological variability as well as variability in consumer habits via 2D Monte Carlo simulations. Overall, the variation in the PEIs of shampoo use was mainly the result of uncertainty due to the use of toxicity data from three species only. All uncertainty sources combined resulted in PEIs ranging on average over seven orders of magnitude (ratio of the 90th to the 10th percentile) so that an absolute quantification of the ecological risk would not be meaningful. In comparison, variation in shampoo composition was the most influential source of variability, although less than compared to uncertainty, leading to PEIs ranging over three orders of magnitude. Increasing the number of toxicity data by increasing the number of species, either through additional measurements or ecotoxicological modelling (e.g. using Interspecies Correlation Equations), should get priority to improve the reliability of PEIs. These conclusions are not limited to shampoos but are applicable more generally to the down-the-drain products since they all have similar data limitations and associated uncertainties relating to the availability of ecotoxicity data and variability in consumer habits and use.

Quantifying variability in removal efficiencies of chemicals in activated sludge wastewater treatment plants - a meta-analytical approach.

Large variations in removal efficiencies (REs) of chemicals have been reported for monitoring studies of activated sludge wastewater treatment plants (WWTPs). In this work, we conducted a meta-analysis on REs (1539 data points) for a set of 209 chemicals consisting of fragrances, surfactants, and pharmaceuticals in order to assess the drivers of the variability relating to inherent properties of the chemicals and operational parameters of activated sludge WWTPs. For a reduced dataset (n = 542), we developed a mixed-effect model (meta-regression) to explore the observed variability in REs for the chemicals using three chemical specific factors and four WWTP-related parameters. The overall removal efficiency of the set of chemicals was 82.1% (95% CI 75.2-87.1%, N = 1539). Our model accounted for 17% of the total variability in REs, while the process-based model SimpleTreat did not perform better than the average of the measured REs. We identified that, after accounting for other factors potentially influencing RE, readily biodegradable compounds were better removed than non-readily biodegradable ones. Further, we showed that REs increased with increasing sludge retention times (SRTs), especially for non-readily biodegradable compounds. Finally, our model highlighted a decrease in RE with increasing KOC. The counterintuitive relationship to KOC stresses the need for a better understanding of electrochemical interactions influencing the RE of ionisable chemicals. In addition, we highlighted the need to improve the modelling of chemicals that undergo deconjugation when predicting RE. Our meta-analysis represents a first step in better explaining the observed variability in measured REs of chemicals. It can be of particular help to prioritize the improvements required in existing process-based models to predict removal efficiencies of chemicals in WWTPs.

Estimation of chemical emissions from down-the-drain consumer products using consumer survey data at a country and wastewater treatment plant level.

Deriving reliable estimates of chemical emissions to the environment is a key challenge for impact and risk assessment methods and typically the associated uncertainty is not characterised. We have developed an approach to spatially quantify annual chemical emission loads to the aquatic environment together with their associated uncertainty using consumer survey data and publicly accessible and non-confidential data sources. The approach is applicable for chemicals widely used across a product sector. Product usage data from consumer survey studies in France, the Netherlands, South Korea and the USA were combined with information on typical product formulations, wastewater removal rates, and the spatial distribution of populations and wastewater treatment plants (WWTPs) in the four countries. Results are presented for three chemicals common to three types of personal care products (shampoo, conditioner, and bodywash) at WWTP and national levels. Uncertainty in WWTP-specific emission estimates was characterised with a 95% confidence interval and ranged up to a factor of 4.8 around the mean, mainly due to uncertainty associated with removal efficiency. Estimates of whole country product usage were comparable to total market estimates derived from sectorial market sales data with differences ranging from a factor 0.8 (for the Netherlands) to 5 (for the USA). The proposed approach is suitable where measured data on chemical emissions is missing and is applicable for use in risk assessments and chemical footprinting methods when applied to specific product categories.

Are Wave and Tidal Energy Plants New Green Technologies?

Wave and tidal energy plants are upcoming, potentially green technologies. This study aims at quantifying their various potential environmental impacts. Three tidal stream devices, one tidal range plant and one wave energy harnessing device are analyzed over their entire life cycles, using the ReCiPe 2008 methodology at midpoint level. The impacts of the tidal range plant were on average 1.6 times higher than the ones of hydro-power plants (without considering natural land transformation). A similar ratio was found when comparing the results of the three tidal stream devices to offshore wind power plants (without considering water depletion). The wave energy harnessing device had on average 3.5 times higher impacts than offshore wind power. On the contrary, the considered plants have on average 8 (wave energy) to 20 (tidal stream), or even 115 times (tidal range) lower impact than electricity generated from coal power. Further, testing the sensitivity of the results highlighted the advantage of long lifetimes and small material requirements. Overall, this study supports the potential of wave and tidal energy plants as alternative green technologies. However, potential unknown effects, such as the impact of turbulence or noise on marine ecosystems, should be further explored in future research.

Quantitative Proteomics Reveals Dynamic Interactions of the Minichromosome Maintenance Complex (MCM) in the Cellular Response to Etoposide Induced DNA Damage.

The minichromosome maintenance complex (MCM) proteins are required for processive DNA replication and are a target of S-phase checkpoints. The eukaryotic MCM complex consists of six proteins (MCM2-7) that form a heterohexameric ring with DNA helicase activity, which is loaded on chromatin to form the pre-replication complex. Upon entry in S phase, the helicase is activated and opens the DNA duplex to recruit DNA polymerases at the replication fork. The MCM complex thus plays a crucial role during DNA replication, but recent work suggests that MCM proteins could also be involved in DNA repair. Here, we employed a combination of stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics with immunoprecipitation of green fluorescent protein-tagged fusion proteins to identify proteins interacting with the MCM complex, and quantify changes in interactions in response to DNA damage. Interestingly, the MCM complex showed very dynamic changes in interaction with proteins such as Importin7, the histone chaperone ASF1, and the Chromodomain helicase DNA binding protein 3 (CHD3) following DNA damage. These changes in interactions were accompanied by an increase in phosphorylation and ubiquitination on specific sites on the MCM proteins and an increase in the co-localization of the MCM complex with γ-H2AX, confirming the recruitment of these proteins to sites of DNA damage. In summary, our data indicate that the MCM proteins is involved in chromatin remodeling in response to DNA damage.

Developmentally regulated elimination of damaged nuclei involves a Chk2-dependent mechanism of mRNA nuclear retention.

The faithful execution of embryogenesis relies on the ability of organisms to respond to genotoxic stress and to eliminate defective cells that could otherwise compromise viability. In syncytial-stage Drosophila embryos, nuclei with excessive DNA damage undergo programmed elimination through an as-yet poorly understood process of nuclear fallout at the midblastula transition. We show that this involves a Chk2-dependent mechanism of mRNA nuclear retention that is induced by DNA damage and prevents the translation of specific zygotic mRNAs encoding key mitotic, cytoskeletal, and nuclear proteins required to maintain nuclear viability. For histone messages, we show that nuclear retention involves Chk2-mediated inactivation of the Drosophila stem loop binding protein (SLBP), the levels of which are specifically depleted in damaged nuclei following Chk2 phosphorylation, an event that contributes to nuclear fallout. These results reveal a layer of regulation within the DNA damage surveillance systems that safeguard genome integrity in eukaryotes.

The MEK/ERK pathway promotes NOTCH signalling in pancreatic cancer cells.

Activation of the NOTCH receptors relies on their intracellular proteolysis by the gamma-secretase complex. This cleavage liberates the NOTCH intracellular domain (NIC) thereby allowing the translocation of NIC towards the nucleus to assemble into a transcriptional platform. Little information is available regarding the regulatory steps operating on NIC following its release from the transmembrane receptor up to its association with transcriptional partners. Interfering with these regulatory steps might potentially influences the nuclear outcome of NOTCH signalling. Herein, we exploited a reliable model to study the molecular events occurring subsequent to NOTCH1 cleavage. In pancreatic cancer cells, pulse of NOTCH1 activation led to increased expression of NOTCH target genes namely HES1 and c-MYC. We uncovered that, upon its release, the NOTCH1 intracellular domain, NIC1, undergoes a series of post-translational modifications that include phosphorylation. Most interestingly, we found that activation of the MEK/ERK pathway promotes HES1 expression. Inhibition of the gamma-secretase complex prevented the MEK/ERK-induced HES1 expression suggesting a NOTCH-dependent mechanism. Finally, higher levels of NIC1 were found associated with its transcriptional partners [CBF1, Su(H) and LAG-1] (CSL) and MASTERMIND-LIKE 1 (MAML1) upon MEK/ERK activation providing a potential mechanism whereby the MEK/ERK pathway promotes expression of NOTCH target genes. For the first time, our data exposed a signalling pathway, namely the MEK/ERK pathway that positively impacts on NOTCH nuclear outcome.

Polo kinase regulates mitotic chromosome condensation by hyperactivation of condensin DNA supercoiling activity.

A defining feature of mitosis is the reorganization of chromosomes into highly condensed structures capable of withstanding separation and large-scale intracellular movements. This reorganization is promoted by condensin, an evolutionarily conserved multisubunit ATPase. Here we show, using budding yeast, that condensin is regulated by phosphorylation specifically in anaphase. This phosphorylation depends on several mitotic regulators, and the ultimate effector is the Polo kinase Cdc5. We demonstrate that Cdc5 directly phosphorylates all three regulatory subunits of the condensin complex in vivo and that this causes a hyperactivation of condensin DNA supercoiling activity. Strikingly, abrogation of condensin phosphorylation is incompatible with viability, and cells expressing condensin mutants that have a reduced ability to be phosphorylated in vivo are defective in anaphase-specific chromosome condensation. Our results reveal the existence of a regulatory mechanism essential for the promotion of genome integrity through the stimulation of chromosome condensation in late mitosis.

A KSR/CNK complex mediated by HYP, a novel SAM domain-containing protein, regulates RAS-dependent RAF activation in Drosophila.

RAF is a critical effector of the small GTPase RAS in normal and malignant cells. Despite intense scrutiny, the mechanism regulating RAF activation remains partially understood. Here, we show that the scaffold KSR (kinase suppressor of RAS), a RAF homolog known to assemble RAF/MEK/ERK complexes, induces RAF activation in Drosophila by a mechanism mediated by its kinase-like domain, but which is independent of its scaffolding property or putative kinase activity. Interestingly, we found that KSR is recruited to RAF prior to signal activation by the RAF-binding protein CNK (connector enhancer of KSR) in association with a novel SAM (sterile alpha motif) domain-containing protein, named Hyphen (HYP). Moreover, our data suggest that the interaction of KSR to CNK/HYP stimulates the RAS-dependent RAF-activating property of KSR. Together, these findings identify a novel protein complex that controls RAF activation and suggest that KSR does not only act as a scaffold for the MAPK (mitogen-activated protein kinase) module, but may also function as a RAF activator. By analogy to catalytically impaired, but conformationally active B-RAF oncogenic mutants, we discuss the possibility that KSR represents a natural allosteric inducer of RAF catalytic function.

Src42 binding activity regulates Drosophila RAF by a novel CNK-dependent derepression mechanism.

Connector enhancer of KSR (CNK), an essential component of Drosophila receptor tyrosine kinase/mitogen-activated protein kinase pathways, regulates oppositely RAF function. This bimodal property depends on the N-terminal region of CNK, which integrates RAS activity to stimulate RAF and a bipartite element, called the RAF-inhibitory region (RIR), which binds and inhibits RAF catalytic activity. Here, we show that the repressive effect of the RIR is counteracted by the ability of Src42 to associate, in an RTK-dependent manner, with a conserved region located immediately C-terminal to the RIR. Strikingly, we found that several cnk loss-of-function alleles have mutations clustered in this area and provide evidence that these mutations impair Src42 binding. Surprisingly, the derepressing effect of Src42 does not appear to involve its catalytic function, but critically depends on the ability of its SH3 and SH2 domains to associate with CNK. Together, these findings suggest that the integration of RTK-induced RAS and Src42 signals by CNK as a two-component input is essential for RAF activation in Drosophila.

Bimodal regulation of RAF by CNK in Drosophila.

Connector enhancer of KSR (CNK) is a multidomain-containing protein previously identified as a positive regulator of the RAS/MAPK pathway in Drosophila. Using transfection experiments and an RNAi-based rescue assay in Drosophila S2 cells, we demonstrate that CNK has antagonistic properties with respect to RAF activity. We show that CNK's N-terminal region contains two domains (SAM and CRIC) that are essential for RAF function. Unexpectedly, we also report that the C-terminal region of CNK contains a short bipartite element that strongly inhibits RAF catalytic function. Interestingly, CNK's opposite properties appear to prevent signaling leakage from RAF to MEK in the absence of upstream signals, but then transforms into a potent RAF activator upon signal activation. Together, these findings suggest that CNK not only participates in the elusive RAF activation process, but might also contribute to the switch-like behavior of the MAPK module.

KSR is a scaffold required for activation of the ERK/MAPK module.

Mechanisms that regulate signal propagation through the ERK/MAPK pathway are still poorly understood. Several proteins are suspected to play critical roles in this process. One of these is Kinase Suppressor of Ras (KSR), a component previously identified in RAS-dependent genetic screens in Drosophila and Caenorhabditis elegans. Here, we show that KSR functions upstream of MEK within the ERK/MAPK module. In agreement with this, we found that KSR facilitates the phosphorylation of MEK by RAF. We further show that KSR associates independently with RAF and MEK, and that these interactions lead to the formation of a RAF/MEK complex, thereby positioning RAF in close proximity to its substrate MEK. These findings suggest that KSR functions as a scaffold that assembles the RAF/MEK functional pair.