This study demonstrated the strengths of invivo molecular staining coupled with automated imaging analysis in Daphnia magna. A multiwell plate protocol was developed to assess mitochondrial membrane potential using the JC-1 dye. The suitability of five common anesthetics was initially tested, and 5% ethanol performed best in terms of anesthetic effects and healthy recovery. The staining conditions were optimized to 30min staining with 2 μM JC-1 for best J-aggregate formation. The protocol was validated with the model compound carbonyl cyanide 3-chlorophenylhydrazone (CCCP) and used to measure the effect of four environmental contaminants, 2,4-dinitrophenol, triclosan, n-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine (6PPD), and ibuprofen, on mitochondrial health. Test organisms were imaged using anautomated confocal microscope, and fluorescence intensities were automatically quantified. The effect concentrations for CCCP were lower by a factor of 30 compared with the traditional OECD 202 acute toxicity test. Mitochondrial effects were also detected at lower concentrations for all tested environmental contaminants compared to the OCED 202 test. For 2,4-dinitrophenol, mitochondria effects were detectable after 2h exposure to environmentally relevant concentrations and predicted organism death was observed after 24h. The high sensitivity and time efficiency of this novel automated imaging method make it a valuable tool for advancing ecotoxicological testing.

There is an increasing need for new approach methodologies (NAMs) to generate relevant ecotoxicological data. This study demonstrates the strengths of calcein AM, a highly sensitive fluorescent stain for esterase activity, in an automated image-based multiwell plate assay for detecting sublethal effects in Daphnia magna. Sample processing and feeding conditions were optimized to ensure a uniform dye distribution. The protocol was validated using two esterase inhibitors, triphenyl phosphate and netilmicin sulfate, and subsequently applied to test the environmental contaminants methoxychlor, lindane, tributyltin chloride, pentachlorophenol, diuron, and ethofumesate. The test organisms were imaged in vivo using automated confocal microscopy, and fluorescence intensity was quantified to generate concentration–response curves. The effects of triphenyl phosphate and netilmicin sulfate were observed at concentrations 3-fold and 6-fold lower, respectively, than in the OECD 202 immobilization test. All tested contaminants also inhibited esterase activity, with concentrations resulting in no esterase activity at 48 h, correlating with mortality observed at 48 h. This method provides a new sensitive fluorescent tool for detecting sublethal chemical effects in D. magna, with the added advantage of visualizing intracellular processes in vivo.

Sublethal effects of contaminants are crucial for understanding ecosystem health but are often missed by conventional ecotoxicological tests. This study demonstrates a high-content screening approach that combines automated fluorescence microscopy with deep learning–based image analysis in live Daphnia magna. Three subcellular endpoints were assessed simultaneously: multixenobiotic resistance (MXR) system activity, mitochondrial membrane potential, and esterase activity, using Rhodamine B, BioTracker 405 blue mitochondrial dye, and Calcein AM, respectively. Cyclosporin A, carbonyl cyanide 3-chlorophenylhydrazone, and triphenyl phosphate were used to validate the method, with each compound significantly affecting its primary target endpoint while also affecting additional endpoints. Segmentation of head and thorax regions revealed spatial differences in toxicological responses, highlighting the ability of the method to localize effects to specific tissues. Moreover, exposure to mixtures of the three model compounds induced significant responses across all endpoints with some effects occurring at lower concentrations than observed for the individual compounds, underscoring the importance of multi-endpoint approaches for assessing mixture toxicity. Overall, this approach enables sensitive and reproducible detection of multiple sublethal effects simultaneously and provides deeper insight into toxic mechanisms in D. magna, supporting the use of multiplexed imaging and deep learning as powerful tools for ecotoxicological research.

Rivers in highly anthropogenic areas contain complex mixtures of chemicals that cannot be fully assessed by chemical analysis alone, highlighting the need for effect-based methods to identify the presence of toxic mixtures. Dhaka, Bangladesh, is a megacity with chemical-intensive industries along its urban river system and limited wastewater treatment. Despite extensive chemical contamination, the ecotoxicological effects of these waters remain poorly characterized. Here, multiplexed high-content imaging was used to characterize toxicity profiles of river-water extracts in Daphnia magna neonates. Organic chemical mixtures were concentrated by solid-phase extraction from the urban Turag, Buriganga, and Shitalakshya rivers as well as from the Upper Meghna River east of Dhaka. Extracts were tested for effects on multixenobiotic resistance system (MXR)-associated transport, mitochondrial membrane potential, and esterase activity after 48 h exposure to 0.1× to 2.0× the original field-water concentration. All urban river extracts induced significant sublethal effects, in some cases below field-equivalent concentrations, whereas no significant effects were detected for the less impacted Upper Meghna. Extracts from the Turag and Shitalakshya rivers primarily affected mitochondrial membrane potential, while Buriganga showed a distinctive profile characterized by altered MXR-associated transport. Chemical profiles and land-use information suggested substantial contributions from industrial pollution in the Turag and Shitalakshya and from pharmaceuticals in the Buriganga. These findings demonstrate that multiplexed high-content imaging in D. magna can distinguish sublethal toxicity profiles in complex environmental samples at relevant environmental concentrations. As a complement to chemical monitoring, this sensitive and mechanistically informative effect-based tool can support improved monitoring and hazard assessment of contaminated surface waters.