Environmental metal toxicity assessment by the combined application of metallomics and metabolomics

Metabolomics as a valid analytical technique in environmental exposure research: application and progress

BACKGROUND

In recent years, studies have shown that exposure to environmental pollutants (e.g., radiation, heavy metal substances, air pollutants, organic pollutants) is a leading cause of human non-communicable diseases. The key to disease prevention is to clarify the harmful mechanisms and toxic effects of environmental pollutants on the body. Metabolomics is a high-sensitivity, high-throughput omics technology that can obtain detailed metabolite information of an organism. It is a crucial tool for gaining a comprehensive understanding of the pathway network regulation mechanism of the organism. Its application is widespread in many research fields such as environmental exposure assessment, medicine, systems biology, and biomarker discovery.

AIM OF REVIEW

Recent findings show that metabolomics can be used to obtain molecular snapshots of organisms after environmental exposure, to help understand the interaction between environmental exposure and organisms, and to identify potential biomarkers and biological mechanisms.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review focuses on the application of metabolomics to understand the biological effects of radiation, heavy metals, air pollution, and persistent organic pollutants exposure, and examines some potential biomarkers and toxicity mechanisms.

Identification of the hormetic dose-response and regulatory network of multiple metals co-exposure-related hypertension via integration of metallomics and adverse outcome pathways

Environmental stressors, including heavy metals, can be associated with hypertension development. However, little information regarding the dose-response relationship and toxicity mechanisms of metal mixtures with hypertension development is currently available. Therefore, we recruited 940 participants from six factories in northeastern China and measured the urinary concentrations of 19 metals. Then, we used Bayesian kernel machine regression (BKMR) to explore associations between metals co-exposure and hypertension. The BKMR model indicated a hermetic dose-response relationship between eight urinary metals (Co, Cr, Ni, Cd, As, Fe, Zn, and Pb) and hypertension risk. Moreover, heterogeneous and non-linear association patterns were detected across different metals/metalloids concentrations. Next, for the first time, we analyzed data of chemicals containing specific metal elements in the Comparative Toxicogenomics Database (CTD) from a disease perspective and provided insights from various biological levels to explain heavy metal co-exposure-related hypertension. On the molecular scale, 43 chemical components and 112 potential target genes were detected for metal exposure-related hypertension. Further, the network topology analysis indicated that target genes such as insulin (INS, degree = 78), albumin (ALB, degree = 74), renin (REN, degree = 71), interleukin-6 (IL6, degree = 70), endothelin 1 (EDN1, degree = 70), and endothelial nitric oxide synthase (NOS3, degree = 69) have a strong correlation with heavy metals co-exposure. Finally, we used integrative analyses in the adverse outcome pathway (AOP) wiki to analyze the co-exposure of heavy metals and hypertension and support an integrated metallomics approach. We selected the AOP 149 as the framework and found that the molecular initiating events (MIEs) of hypertension stems from the oxidation of AA residues on critical peptides of the NO pathway. The NOS3 was particularly promising since its subunit has three metal ion cross-linking domains with Zn²⁺, Fe²⁺, and Ga³⁺, which might serve as a binding site for heavy metal ions.