Metabolomics profiling to investigate nanomaterial toxicity in vitro and in vivo

Abstract

Nanomaterials (NMs) can be produced in plenty of variants posing several challenges for NM hazard and risk assessment. Metabolomic profiling of NM-treated cells and tissues allows for insights into underlying Mode-of-Action (MoA) and offers several advantages in this context. It supports the description of Adverse Outcome Pathways (AOPs) and, therefore, tailored AOP-based hazard testing strategies. Moreover, it bears great potential for biomarker discovery supporting toxicity prediction. Here, we applied metabolomics profiling to cells treated with four well-selected SiO₂ variants, differing in structure, size and surface charge. TiO₂ NM-105 served as a benchmark. Responses were studied in vitro in rat lung epithelial cells (RLE-6TN) and alveolar macrophages (NR8383) and compared to in vivo responses in rat lung tissues obtained from in vivo instillation and short-term inhalation studies (STIS). Time- and concentration-dependent changes were observed in both in vitro models but with cell-type specific responses. Overall, the levels of lipids and biogenic amines (BAs) tended to increase in epithelial cells but decreased in macrophages. Many identified metabolites like Met-SO, hydroxy-Pro and spermidine were related to oxidative stress, indicating that oxidative stress contributes to the MoA for the selected NMs. Several biomarker candidates such as Asp, Asn, Ser, Pro, spermidine, putrescine and LysoPCaC16:1 were identified in vitro and verified in vivo. In this study, we successfully applied a metabolomics workflow for in vitro and in vivo samples, which proved to be well suited to identify potential biomarkers, to gain insights into NM structure–activity relationship and into the underlying MoA.

Keywords:

• Nanoparticles
• metabolomics
• mechanistic toxicology
• biomarker

Acknowledgements

The authors would like to take this opportunity to thank all institutions for their support of this project. In addition, the authors want to thank Antje Bergert, Doreen Wittke and Nadine Dreiack for technical assistance.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data will be available from the corresponding author upon reasonable request.

Additional information

Funding

This project is part of the SIINN ERA-NET and is funded under the ERA-NET scheme of the Seventh Framework Program of the European Commission, BMBF Grant Agreement No. 03XP0008. The STIS performed at the University of Namur with funding provided by BfR (grant agreement number 1329-561).