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High-Throughput Transcriptomics Differentiates Toxic versus Non-Toxic Chemical Exposures Using a Rat Liver Model
Venkat R Pannala1,2, Anders Wallqvist3, Deepak Mav3
1Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, Frederick, MD 21702, USA.
High-throughput transcriptomics (HTT) and a 5-day rat model identify gene signatures for liver toxicity. This approach offers a faster, more accurate method for chemical safety assessment and understanding liver disease progression.
Area of Science:
- Toxicology
- Genomics
- Environmental Health
Background:
- Traditional toxicity testing has limitations in throughput and efficiency.
- High-throughput transcriptomics (HTT) offers a promising alternative for assessing chemical exposures.
- In vivo rat models provide valuable data for toxicological endpoint estimation.
Purpose of the Study:
- To develop and validate a 5-day in vivo rat model combined with HTT for liver toxicity assessment.
- To identify gene expression signatures that differentiate between toxic and non-toxic liver responses.
- To explore potential histopathological endpoints for chemical exposure evaluation.
Main Methods:
- Utilized a 5-day oral gavage exposure of male Sprague Dawley rats to 18 environmental chemicals.
- Performed HTT analysis to measure gene expression changes on the sixth day.
- Analyzed gene expression patterns to identify dose-dependent responses and differentiate hepatotoxic from non-hepatotoxic compounds.
Main Results:
- Identified distinct gene expression patterns differentiating hepatotoxic from non-hepatotoxic chemicals in a dose-dependent manner.
- Found that toxic chemicals predominantly upregulate genes and pathways involved in amino acid and lipid metabolism.
- Liver injury module analysis revealed common phenotypes of cellular inflammation and proliferation among toxic compounds.
Conclusions:
- The 5-day rat model with HTT is effective for identifying liver toxicity and potential gene signatures.
- Gene expression patterns can predict hepatotoxicity and offer insights into metabolic pathway alterations.
- Identified molecular initiating processes, such as inflammation and proliferation, linked to specific end-stage liver diseases.
