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Linking molecular responses to organismal outcomes under complex contaminant stress: a systems biology approach for predictive ecotoxicology

ABSTRACT: Ecological risk assessments have traditionally relied on simplified models that expose single species to individual chemicals under controlled laboratory conditions. However, real-world ecosystems are subject to multiple, interacting stressors, particularly from anthropogenic sources, that challenge the predictive power of these conventional approaches. To address this gap, we investigated the effects of coal ash, a complex mixture of heavy metals, on the freshwater invertebrate Daphnia magna. We quantified both suborganismal (transcriptomic) and individual-level (survival, growth, reproduction) responses to coal ash exposure. These data were integrated into a Dynamic Energy Budget (DEB) model to simulate physiological modes of action (pMoAs). Using machine learning, we identified gene sets predictive of DEB state variables and prioritized differentially expressed genes to determine the most plausible bioenergetic disruption. This study demonstrates a scalable framework for linking molecular perturbations to organismal outcomes, offering a mechanistic basis for assessing the ecological impact of complex chemical mixtures. Our approach advances predictive ecotoxicology by moving beyond chemical-specific assays toward integrative, systems-level models that better reflect environmental realities.

ORGANISM(S): Daphnia magna

PROVIDER: GSE328764 | GEO | 2026/07/01

REPOSITORIES: GEO

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Project description:Coal-fired power plant is a major method of electricity generation worldwide with serious concerns relating to air pollution. In recent years, fly ash from coal-fired power plants has become a major target of pollution control by worldwide regulatory agencies. In this present study, fly ash particulate matter (PM) obtained from the electrostatic precipitator of Mae Moh Coal-fired Power Plant (Lampang, Thailand) was selected as a model for determination of physicochemical characteristics and toxicological profiles in mice. The average size of the fly ash PM was 4.29 ± 1.85 µm as determined by electron microscopy. Major heavy metal was iron at 101,067.31 ± 8,246.12 mg/kg as detected by ICPMS. Acenaphthene was the most abundant polyaromatic hydrocarbon at 40.77 ± 0.003 mg/kg as analyzed by GCMS. The toxicological profiles of the characterized fly ash PM were conducted in Balb/c mice by intratracheal instillation at 1 and 10 mg/kg/day for 7 days, compared to vehicle as negative control and standard PM 2.5 as positive control. The fly ash PM and the standard PM induced significant pulmonary inflammation in mice lungs compared to vehicle control. In addition, molecular toxicology of mice lungs investigated by proteomics demonstrated 3 inflammation associated pathways, which include leukocyte transendothelial migration, phagosome, and neutrophil extracellular trap formation. Furthermore, only high dose (10 mg/kg/day) standard PM and high dose fly ash PM showed high expression of NCF2, which potentially promotes cancer in the long run. This study is the first to report on the physicochemical characterization, histopathology, and proteomic-associated toxicological profiles of the fly ash PM obtained from the largest coal-fired power plant in Thailand. Information obtained from this study is useful for academic researchers, electricity enterprises, and policymakers to develop appropriate strategies to manage air pollution from coal-fired power plants worldwide.

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Linking molecular responses to organismal outcomes under complex contaminant stress: a systems biology approach for predictive ecotoxicology

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