Genome-wide toxicogenomic study of the lanthanides sheds light on the selective toxicity mechanisms associated with critical materials.

Lanthanides are a series of critical elements widely used in multiple industries, such as optoelectronics and healthcare. Although initially considered to be of low toxicity, concerns have emerged during the last few decades over their impact on human health. The toxicological profile of these metals, however, has been incompletely characterized, with most studies to date solely focusing on one or two elements within the group. In the current study, we assessed potential toxicity mechanisms in the lanthanide series using a functional toxicogenomics approach in baker's yeast, which shares many cellular pathways and functions with humans. We screened the homozygous deletion pool of 4,291 Saccharomyces cerevisiae strains with the lanthanides and identified both common and unique functional effects of these metals. Three very different trends were observed within the lanthanide series, where deletions of certain proteins on membranes and organelles had no effect on the cellular response to early lanthanides while inducing yeast sensitivity and resistance to middle and late lanthanides, respectively. Vesicle-mediated transport (primarily endocytosis) was highlighted by both gene ontology and pathway enrichment analyses as one of the main functions disturbed by the majority of the metals. Protein-protein network analysis indicated that yeast response to lanthanides relied on proteins that participate in regulatory paths used for calcium (and other biologically relevant cations), and lanthanide toxicity included disruption of biosynthetic pathways by enzyme inhibition. Last, multiple genes and proteins identified in the network analysis have human orthologs, suggesting that those may also be targeted by lanthanides in humans.

Unsupervised identification of disease states from high-dimensional physiological and histopathological profiles.

The liver and kidney in mammals play central roles in protecting the organism from xenobiotics and are at high risk of xenobiotic-induced injury. Xenobiotic-induced tissue injury has been extensively studied from both classical histopathological and biochemical perspectives. Here, we introduce a machine-learning approach to analyze toxicological response. Unsupervised characterization of physiological and histological changes in a large toxicogenomic dataset revealed nine discrete toxin-induced disease states, some of which correspond to known pathology, but others were novel. Analysis of dynamics revealed transitions between disease states at constant toxin exposure, mostly toward decreased pathology, implying induction of tolerance. Tolerance correlated with induction of known xenobiotic defense genes and decrease of novel ferroptosis sensitivity biomarkers, suggesting ferroptosis as a druggable driver of tissue pathophysiology. Lastly, mechanism of body weight decrease, a known primary marker for xenobiotic toxicity, was investigated. Combined analysis of food consumption, body weight, and molecular biomarkers indicated that organ injury promotes cachexia by whole-body signaling through Gdf15 and Igf1, suggesting strategies for therapeutic intervention that may be broadly relevant to human disease.