Manually curated transcriptomics data collection for toxicogenomic assessment of engineered nanomaterials

Area of Science:

• Environmental toxicology
• Nanomaterial safety assessment
• Transcriptomics and omics data analysis

Background:

• Engineered nanomaterials (ENMs) require robust toxicity assessments.
• Toxicogenomics (TGx) and omics data offer insights into chemical mechanisms of action.
• Existing transcriptomics data for ENMs is fragmented and lacks standardization.

Purpose of the Study:

• To address the lack of a unified data repository for ENM transcriptomics.
• To improve the Findability, Accessibility, Interoperability, and Reusability (FAIR) of existing ENM omics data.
• To facilitate the understanding of ENM toxicity mechanisms and predictive toxicology.

Main Methods:

• Curated transcriptomics data from in vitro and in vivo studies involving human, mouse, and rat models.
• Homogenized data to ensure consistency and comparability.
• Included physicochemical characteristics of the ENMs used in each study.

Main Results:

• Established a homogenized collection of transcriptomics data for ENM exposures.
• Integrated data from diverse exposure scenarios (in vitro/in vivo, species).
• Linked transcriptomics data with detailed ENM properties.

Conclusions:

• The curated dataset enhances the accessibility and reusability of ENM transcriptomics data.
• This resource supports mechanistic toxicity studies and the development of predictive models for ENM safety.
• Improved data FAIRness is crucial for advancing nanomaterial risk assessment.