Integration of Computational Toxicology, Toxicogenomics Data Mining, and Omics Techniques to Unveil Toxicity Pathways

Abstract

Growing numbers of synthetic chemicals have potential endocrine-disrupting effects and cause potential ecological and health risks. However, the primary toxicity pathways and mechanisms of endocrine disruption are poorly understood and the existing risk assessment relies heavily on animal testing. Database mining, omics technology, and computer simulation can serve as an alternative approach to explore the mechanisms by building adverse outcome pathways (AOPs). The present study took a case of thyroid interference with triphenyl phosphate (TPP) to explain the potential toxic effects at levels from submolecules to cells utilizing the AOP framework developed by multiple techniques. This study retrieved the data from a comparative toxicogenomics database (CTD) and screened out the core gene. Molecular dynamics (MD) analysis was used to explore configuration changes and confirm the molecular initiating event (MIE). The transcriptomic analysis was further utilized to supplement the relationships between MIEs and key events (KEs) of the AOP. The thyroid hormone receptor beta (THRB) was identified as the core gene at submolecular levels. MD analysis found that the configuration changes of C-terminal helix 12 (H12) of thyroid hormone receptor β (TRβ) were discovered as the MIE. The transcriptomic analysis extended the related KE1 at the subcellular level, such as changes in gene expression levels for coding cycle regulation (CCND1), inflammatory response (IL1A and IL6), and cell proliferation and apoptosis (BAD, TP53, and CASP9). Then, the KE2 at cellular levels such as apoptosis, cell cycle control, and cell proliferation were influenced accordingly. As a result, these alterations led to thyroid disorder as adverse outcomes. This study provided an efficient way to facilitate the complement of possible AOPs and brought new insights into understanding the toxic mechanisms of emerging synthetic chemicals.

Carcinogenic Risk of 2,6-Di-tert-Butylphenol and Its Quinone Metabolite 2,6-DTBQ Through Their Interruption of RARβ: In Vivo, In Vitro, and In Silico Investigations

“…The production of numerous emerging contaminants is a necessity in an industrialized society but oftentimes poses environmental burden with substantial human health risks . The uncertainty of health hazards presents a critical challenge to the risk assessment and management of these emerging contaminants . In this study, we integrated transcriptomics, molecular modeling, and cytological and biochemical analysis to develop the AOP of two emerging contaminants.…”

Bioinformatic Analysis Identified Hub Genes Associated with Heterocyclic Amines Induced Cytotoxicity of Peripheral Blood Mononuclear Cells

“…In recent years, more and more novel methods have been applied in toxicology research. New methods have been emerging in the field of descriptive toxicology [ 37 ] and mechanistic toxicology [ 38 ]. Bioinformatic analysis is a battery of techniques that use computerized systems to analyze large bodies of biological data and find possible genetic relationships in various biological processes.…”

Rapid Screening of Human Transthyretin Disruptors through a Tiered in Silico Approach

“…Computational methods could be used to evaluate and screen chemicals on their potential endocrine activity, − which is significant in minimizing the adverse impacts of EDCs on human health and the environment and finally realizing the sustainable assessment and management of EDCs. To date, extensive predictive models were available for the end points related to disruption effects of nuclear receptors. − Even some models for predicting the disruption effects of nuclear receptors have been integrated into several pieces of publicly available software, e.g., VAGE () and OECD QSAR Toolbox ().…”