Related Experiment Video
Updated: Oct 13, 2026

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
Published on: March 14, 2019
Cell painting-based high-throughput assay for whole wastewater toxicity testing
Yuting Yuan1, Jun Shi1, Qing Wang2
1State Key Laboratory of Water Pollution Control and Green Resource Recycling, School of Environment, Nanjing University, Nanjing, Jiangsu, 210023, China.
Abstract:
Microalgae are well-established model organisms for whole wastewater toxicity (WWT) assessment owing to their ease of cultivation and high sensitivity. However, the inherently low throughput and labor-intensive workflows of conventional microalga-based bioassays, such as ISO 8692:2012, prevent their application in large-scale WWT monitoring. To overcome these limitations, this study introduces a scalable, high-throughput assay that integrates cell painting-based morphological profiling and supervised machine learning, which is validated using 25 individual chemicals, their mixture, and 578 real wastewater samples. By characterizing features associated with DNA, RNA, chloroplasts, the endoplasmic reticulum, the F-actin cytoskeleton, Golgi apparatus, and plasma membrane, cell painting provided a multidimensional phenotypic basis for model development. Compared to the ISO 8692:2012 standard, the proposed assay increases testing throughput by ∼21.7-fold and reduces testing time by ∼67.5%, enabling a comprehensive assessment of 100 wastewater treatment plants across China. Notably, greater treatment-process complexity was not consistently associated with higher WWT removal efficiency, challenging the prevailing practice of improving effluent risk control through additional treatment units. The proposed high-throughput assay offers a practical framework for WWT testing and large-scale water quality risk assessments.

