International audience

Hydrothermal carbonization is considered a powerful technology to convert sewage sludge (SS) into a valuable carbonaceous solid known as hydrochar (HC). Up to now criteria for landfill application of SS and HC are based only on physicochemical properties and levels of pollutant residues. Nevertheless, to ensure their safe environmental applications it is mandatory to develop biosensors which can provide relevant information on their toxic potential for natural ecosystems. Therefore, this study aimed to assess the suitability of a contact assay using zebrafish embryo/larvae combined with sub-lethal end-points to evaluate the hazard associated with SS and related HC exposure. A suite of biomarkers was also applied on larvae, related to detoxification and oxidative stress as the activity of Ethoxyresorufin-O-deethylase, glutathione-S-transferase, and catalase, the content of reactive oxygen species and the behavioral assay using the DanioVision™ chamber. Legacy priority pollutants were also measured either in SS and HC tested samples and in contact waters. The exposure to SS caused higher lethality compared to HC. No significant changes in the activity of oxidative stress markers was observed upon exposure to both matrices. The behavioral test showed a hypoactivity condition in larvae exposed to both SS and HC with the effects of SS stronger than HC. Chemical analysis revealed the presence of trace elements and halogenated compounds in either SS, HC. Heavy metals were also released in contact waters, while volatile hydrocarbons (C6–C10) and halogenated compounds resulted below LOD (<0.05 μ L⁻¹). Our study highlights the suitability of zebrafish embryotoxicity test, coupled with behavioral traits, as screening tool for assessing potential risks, associated with the landfill application of both SS and HC, for aquatic wildlife.

We investigated the biological response of soluble organic fraction (SOF) and water-soluble fraction (WSF) extracted from particulate matter (PM) emitted by an automotive diesel engine operating in a representative urban driving condition. The engine was fueled with ultra-low sulfur diesel (ULSD), and its binary blends by volume with 13% of butanol (Bu13), and with hydrotreated vegetable oil (HVO) at 13% (HVO13) and 20% (HVO20). Cytotoxicity, genotoxicity, oxidative DNA damage and ecotoxicity tests were carried out, and 16 polycyclic aromatic hydrocarbons (PAH) expressed as tbenzo(a)pyrene total toxicity equivalent (BaP-TEQ) were also analyzed. The Hepatocarcinoma epithelial cell line (HepG2) was exposed to SOF for 24 h and analyzed using comet assay, with the inclusion of formamidopyrimidine DNA glycosylase (FPG) and endonuclease III (Endo III) to recognize oxidized DNA bases. The WSF was evaluated through acute ecotoxicity tests with the aquatic microcrustacean Daphnia pulex (D. Pulex). Results showed that there was no cytotoxic activity for all tested SOF concentrations. Genotoxic responses by all the SOF samples were at same level, except for the HVO13 which was weaker in the absence of the enzymes. The addition of the FPG and Endo III enzymes resulted in a significant increase in the comet tail, indicating that the DNA damage from SOF for all tested fuel blends involves oxidative damage including a higher level of oxidized purines for ULSD and Bu13 in comparison with HVO blends, but the oxidized pyrimidines for HVO blends were slightly higher compared to Bu13. The WSF did not show acute ecotoxicity for any of the fuels. Unlike other samples, Bu13-derived particles significantly increase the BaP-TEQ. The contribution to the genotoxic activity and oxidative DNA from SOF was not correlated to BaP-TEQ, which means that the biological activity of PM might be affected also by other toxic compounds present in particulate phase.

With the rapid development of nanotechnology in agriculture, there is increasing urgency to assess the impacts of nanoparticles (NPs) on the soil environment. This study merged raw high-throughput sequencing (HTS) data sets generated from 365 soil samples to reveal the potential ecological effects of NPs on soil microbial community by means of metadata analysis and machine learning methods. Metadata analysis showed that treatment with nanoparticles did not have a significant impact on the alpha diversity of the microbial community, but significantly altered the beta diversity. Unfortunately, the abundance of several beneficial bacteria, such as Dyella, Methylophilus, Streptomyces, which promote the growth of plants, and improve pathogenic resistance, was reduced under the addition of synthetic nanoparticles. Furthermore, metadata demonstrated that nanoparticles treatment weakened the biosynthesis ability of cofactors, carriers, and vitamins, and enhanced the degradation ability of aromatic compounds, amino acids, etc. This is unfavorable for the performance of soil functions. Besides the soil heterogeneity, machine learning uncovered that a) the exposure time of nanoparticles was the most important factor to reshape the soil microbial community, and b) long-term exposure decreased the diversity of microbial community and the abundance of beneficial bacteria. This study is the first to use a machine learning model and metadata analysis to investigate the relationship between the properties of nanoparticles and the hazards to the soil microbial community from a macro perspective. This guides the rational use of nanoparticles for which the impacts on soil microbiota are minimized.

Microplastics (MPs) have become an emerging threat for organisms. However, the toxicity mechanisms on biota, especially soil biota remain largely unclear. This study distinguished the effects of five types of MPs and their extractable additives on a typical soil oligochaete Enchytraeus crypticus using a traditional ecotoxicological approach combined with gut microbiota analysis. A variety of inorganic and organic compounds were screened in extractable solutions. Both MPs and their extractable additives decreased the growth and survival rates of the worms and shifted the gut microbiota, and the effects were type-specific. The differences between the effects of MPs and their extractable additives on traditional ecotoxicological parameters were insignificant, suggesting that extractable additives were the main toxicity pathways on soil fauna. The type-specific effects of MPs were attributed to the varied chemical compositions of extractable additives, and the compounds responsible for the shift of gut microbiota were further identified. The distinguishable effects on gut microbiota between MPs and their extractable additives together with the significant regressions between gut microbiota and traditional ecotoxicological parameters confirmed that gut microbiota could be a more sensitive indicator of organism's health conditions. Combined, the study provided an important insight into the toxicity mechanisms of MPs on soil fauna and extractable additives of MPs may be a hidden threat.

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment.

With several observable responses and sensitivity of protozoans to nitrofurazone (NFZ), the toxic effects of NFZ on protozoans can be an early warning signal of NFZ contamination in the aquatic environment. To evaluate the toxic dynamics induced by NFZ, protozoan samples were collected using microscopy glass slides and exposed to the five concentrations of NFZ: 0, 1, 2, 4, and 8 mg ml⁻¹. Substantial differences in the species composition and toxic-dynamics patterns were observed among all concentrations. Briefly, periphytic euplotids and pleurostomatids were the most prevalent at each concentration level, while dysteriids were less dominant among all treatments. Multivariate analysis revealed significant (P < 0.05) differences in the taxonomic patterns of the test organisms among the five treatments. Furthermore, significant deviation of protozoan communities from the expected taxonomic breadth was observed to occur in a dose-dependent manner. Based on these findings, it is suggested that protozoan periphytons could be used as bioindicators to assess the ecotoxicity of NFZ in the marine environment.

International audience | A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, microorganisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment.