Applying a multiscale systems biology approach to study the effect of chronic low-dose exposure to uranium in rat kidneys.

To examine the effects of low-dose exposure to uranium with a systems biology approach, a multiscale high-throughput multi-omics analysis was applied with a protocol for chronic exposure to the rat kidney. Male and female rats were contaminated for nine months through their drinking water with a nontoxic solution of uranyl nitrate. A multiscale approach enabled clinical monitoring associated with metabolomic and transcriptomic (mRNA and microRNA) analyses. A sex-interaction effect was observed in the kidney, urine, and plasma metabolomes of contaminated rats. Moreover, urine and kidney metabolic profiles correlated and confirmed that the primary dysregulated metabolisms are those of nicotinate-nicotinamide and of unsaturated fatty acid biosynthesis. Upstream of the metabolic pathways, transcriptomic profiles of the kidney reveal gene activity focused on gene regulation mechanisms, cell signaling, cell structure, developmental processes, and cell proliferation. Examination of epigenetic post-transcriptional gene regulation processes showed significant dysregulation of 70 micro-RNAs. The multi-omics approach highlighted the activities of the cells' biological processes on multiple scales through analysis of gene expression, confirmed by changes observed in the metabolome. Our results showed changes in multi-omic profiles of rats exposed to low doses of uranium contamination, compared with controls. These changes involved gene expression as well as modifications in the transcriptome and the metabolome. The metabolomic profile confirmed that the main molecular targets of uranium in kidney cells are the metabolism of nicotinate-nicotinamide and the biosynthesis of unsaturated fatty acids. Additionally, gene expression analysis showed that the metabolism of fatty acids is targeted by processes associated with cell function. These results demonstrate that multiscale systems biology is useful in elucidating the most discriminative pathways from genomic to metabolomic levels for assessing the biological impact of this low-level environmental exposure, i.e. the exposome.