PPARγ-responsive luciferase reporter system for high-throughput screening of chemical toxins with potential pulmonary fibrosis effects

  • Ecotoxicol Environ Saf. 2025 Nov 15:307:119433. doi: 10.1016/j.ecoenv.2025.119433.
Xueyang Lin  1 ,  Yi Yang  2 ,  Yangyang Sun  2 ,  Weijie Yang  2 ,  Shengran Wang  2 ,  Weidong Li  2 ,  Zhenghao Bao  2 ,  Ziqi Cui  2 ,  Yufeng Yang  1 ,  Simin Lang  2 ,  Chen Yang  2 ,  Weiqiang Sun  2 ,  Xin Sui  2 ,  Wenya Feng  2 ,  Xianli Du  2 ,  Jun Yang  2 ,  Yongan Wang  3 ,  Yuan Luo  4
Affiliations
  • 1. State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100080, China; School of Pharmacy, Qingdao University, Qingdao, Shandong 266071, China.
  • 2. State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100080, China.
  • 3. State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100080, China. Electronic address: [email protected].
  • 4. State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100080, China. Electronic address: [email protected].
PMID: 41273832 DOI: 10.1016/j.ecoenv.2025.119433
Abstract

Background: Pulmonary fibrosis (PF) is a progressive and fatal lung disorder, and emerging evidence suggests that dysregulation of Peroxisome Proliferator-activated Receptor gamma (PPARγ) plays a critical role in its pathogenesis. However, high-throughput screening (HTS) models for identifying fibrogenic chemicals targeting PPARγ remain underdeveloped. This study aimed to establish a reliable HTS cellular model using a PPARγ-responsive luciferase reporter system to rapidly identify chemicals that induce PF via PPARγ dysregulation.

Methods: Hub genes associated with PF were identified through bioinformatics analysis. A stable HTS cellular model was constructed using a lentiviral vector carrying a luciferase reporter gene under the control of PPARγ-responsive elements. The model was validated using RT-qPCR and luciferase assays. To evaluate its accuracy, four known PF-inducing chemicals and ten non-PF chemicals were tested. Furthermore, to evaluate the model's predictive capability for compounds with uncharacterized PF risk, seven anti-cancer compounds were screened. Molecular docking (MOE) and surface plasmon resonance (SPR) were employed to confirm interactions between the identified chemicals and PPARγ.

Results: PPARγ was identified as the key hub gene linked to PF. The PPARγ-responsive cellular model exhibited significantly elevated PPARγ mRNA levels and luciferase activity compared to controls. PF-inducing chemicals suppressed luciferase activity, whereas non-PF chemicals had no effect. Notably, screening of anti-cancer compounds revealde a subset that markedly suppressed PPARγ activity. Molecular docking and SPR analyses demonstrated concentration-dependent binding affinities between PF-inducing chemicals and PPARγ.

Conclusion: This study developed a high-throughput luciferase-based PPARγ-responsive cellular model to screen chemicals that may contribute to PF through the inhibition of PPARγ activity. The model demonstrates potential as a useful tool for preliminary chemical evaluation. These results suggest a possible role of PPARγ-mediated mechanisms in the development of PF. This work may provide a foundational framework for future efforts in hazard screening and drug discovery aimed at mitigating the effects of PF.

Keywords
Adverse outcome pathway (AOP); High-throughput screening (HTS); Luciferase reporter; PPARγ; Pulmonary fibrosis.
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