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. 2020 Jan;128(1):15001.
doi: 10.1289/EHP6104. Epub 2020 Jan 17.

The Promises and Challenges of Toxico-Epigenomics: Environmental Chemicals and Their Impacts on the Epigenome

Felicia Fei-Lei Chung  1 , Zdenko Herceg  1
Affiliations

The Promises and Challenges of Toxico-Epigenomics: Environmental Chemicals and Their Impacts on the Epigenome

Felicia Fei-Lei Chung et al. Environ Health Perspect. 2020 Jan.

Abstract

Background: It has been estimated that a substantial portion of chronic and noncommunicable diseases can be caused or exacerbated by exposure to environmental chemicals. Multiple lines of evidence indicate that early life exposure to environmental chemicals at relatively low concentrations could have lasting effects on individual and population health. Although the potential adverse effects of environmental chemicals are known to the scientific community, regulatory agencies, and the public, little is known about the mechanistic basis by which these chemicals can induce long-term or transgenerational effects. To address this question, epigenetic mechanisms have emerged as the potential link between genetic and environmental factors of health and disease.

Objectives: We present an overview of epigenetic regulation and a summary of reported evidence of environmental toxicants as epigenetic disruptors. We also discuss the advantages and challenges of using epigenetic biomarkers as an indicator of toxicant exposure, using measures that can be taken to improve risk assessment, and our perspectives on the future role of epigenetics in toxicology.

Discussion: Until recently, efforts to apply epigenomic data in toxicology and risk assessment were restricted by an incomplete understanding of epigenomic variability across tissue types and populations. This is poised to change with the development of new tools and concerted efforts by researchers across disciplines that have led to a better understanding of epigenetic mechanisms and comprehensive maps of epigenomic variation. With the foundations now in place, we foresee that unprecedented advancements will take place in the field in the coming years. https://doi.org/10.1289/EHP6104.

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Figures

Figure 1A is a diagram representing DNA methylation and its relationship with repressive and active chromatin states. Pol II is included in the diagram in close proximity to the illustration of active chromatin. A curved arrow across the top of the figure represents the addition of methyl groups (Me) by DNMT enzymes, and a curved arrow in the opposite direction across the bottom of the figure represents the removal of methyl groups by TET enzymes. Figure 1B is a diagram illustrating the deposition of active and repressive histone marks and their effect on histone states (repressed, bivalent or active). A double-headed arrow illustrates the conversion between active and repressive histone marks by the enzymes HDACs, KDMs, HATs, and HMTs. A diagram of a hypothetical gene illustrates examples of active and repressive histone marks that can occur on the enhancer (e.g. H3K4me1 and H3K27ac active marks; H3K27me3 repressive mark), promoter (e.g. H3K4me3 active mark, H3K27me3 repressive mark), and gene body (e.g. H3K36me3 active mark, H3K9me3 repressive mark). Figure 1C is a diagram illustrating the modes of action of microRNAs, which interact with AGO proteins to trigger the inhibition of the eIF4F complex (left), mRNA cleavage (middle), and mRNA deadenylation followed by degradation by XRN1 (right). Figure 1D is a diagram illustrating the modes of action of lncRNAs, namely mRNA stabilization; miRNA or TF sequestration; TF recruitment or inhibition (with TFs represented by an ellipse or rectangle); and chromatin remodeling by recruitment of chromatin remodeling factors (CRFs).
Figure 1.
Diagrammatical summary of epigenetic modes on action. (A) The deposition of methyl groups is mediated by the DNA methyltransferases (DNMTs), and their removal is mediated by the ten-eleven translocation (TET) family proteins (reviewed by Greenberg and Bourc’his 2019; Wu and Zhang 2010). Increased deposition of methyl groups promotes the condensation of chromatin, whereas reduced DNA methylation is associated with increased accessibility to transcription machinery [represented by RNA polymerase II (Pol II)]. DNA hypermethylation generally leads to the silencing of gene expression when it occurs at gene promoters (reviewed by Greenberg and Bourc’his 2019; Wu and Zhang 2010). (B) Histone modifications are deposited by multiple classes of enzymes [histone acetyltransferases (HATs), histone methyltransferases (HMTs), histone deacetylases (HDACs), and histone lysine demethylases (KDMs)] (reviewed by Chen et al. 2017). Examples of histone modifications illustrated here are histone H3 lysine 27 trimethylation (H3K27me3) and H3 lysine 9 trimethylation (H3K9me3), which are usually associated with repression of gene transcription, and H3 lysine 4 monomethylation (H3K4me1), H3 lysine 4 trimethylation (H3K4me3), H3 lysine 36 trimethylation (H3K36me3), and H3 lysine 27 acetylation (H3K27ac) marks that are typically associated with activation of transcription. Simultaneous deposition of opposing histone marks is associated with poised or bivalent chromatin, which is in a transitional state poised to be resolved into active or repressed states (reviewed by Chen et al. 2017). (C) microRNAs (miRNAs) bound to the Argonaute (AGO) protein make up the miRNA-induced silencing complex (miRISC). miRNAs direct the miRISC to target mRNAs base-pairing partially to complementary binding sites, which will be cleaved by catalytically active AGO proteins (O’Brien et al. 2018). Alternatively, AGO proteins can recruit additional protein partners, initiating the process of deadenylation, decapping and 5ʹ-to-3ʹ mRNA degradation by 5ʹ-to-3ʹ exoribonuclease 1 (XRN1) (reviewed by Jonas and Izaurralde 2015). There has also been evidence that miRNAs inhibit translation by inhibiting the eukaryotic initiation factor 4F (eIF4F) complex, although this process has yet to be fully elucidated (reviewed by Jonas and Izaurralde 2015). 5ʹ polyA tails are denoted by circles labeled A. (D) Long noncoding RNAs (lncRNAs) may influence gene expression by increasing or decreasing target mRNA stability, by acting as decoys to miRNA and transcription factors (TFs), thus sequestering them from their cognate promoters, or they may recruit or inhibit TF binding to their target sites on the chromatin (reviewed by Angrand et al. 2015). lncRNAs may also recruit chromatin remodeling factors (CRFs) such as the polycomb repressive complexes or cohesin proteins that recruit histone modifier complexes or initiate long-range chromatin looping (reviewed by Angrand et al. 2015). The Xist lncRNA triggers stable repression of the presumptive inactive X-chromosome by physically coating the X-chromosome (reviewed by Lee and Bartolomei 2013).
Figure 2 is a scatterplot, plotting scalability across direct biological relevance to compare major techniques for epigenetics analyses against a hypothetical, ideal technique for screening that is highly scalable and biologically relevant, marking in silico methods (molecular docking); global methods (in vitro reporters, repetitive element sequencing, ELISA, HPLC, mass spectrometry, and dot blots; locus-specific methods include in vitro reporters, amplicon sequencing, bisulfite pyrosequencing, in vivo reporters, and IAP animal models); epigenome-wide methods include miRNA arrays, methylation arrays, RRBS, histone ChIP-seq, and WGBS; and higher order chromatin structure assessments include super-resolution imaging and ATAC-seq.
Figure 2.
Comparison of major techniques for epigenetics analyses on subjective scales for scalability and direct biological relevance. Axes are in arbitrary scales, with scalability denoting how amenable a given technique is to be implemented in a high-throughput screening setting. Direct biological relevance denotes how information-rich the results of a given technique are. Note: ATAC-seq, assay for transposase-accessible chromatin using sequencing; ChIP, chromatin immunoprecipitation sequencing; ELISA, enzyme-linked immunosorbent assay; HPLC, high-performance liquid chromatography; RRBS, reduced-representation bisulfite sequencing; WGBS, whole-genome bisulfite sequencing.
Figure 3A is a flow diagram with eight steps, which, from the top to bottom, are as follows: 1. Exposures, 2. Molecular changes, 3. Cell-level changes, 4. Tissue-level changes, 5. Individual health effects, 6. Transgenerational effects and 7. Early life effects, and 8. Population health effects. In silico, in vitro experiments, in vivo experiments, and cohort studies travel from top to bottom, covering the range till 2. molecular changes, 3. cell level changes, 6. transgenerational and early life effects, and 8. Population health effects, respectively. Case control studies from the bottom to the top, covering the range till either 2. molecular changes or 1. exposures. Adverse outcomes pathways move both from the top to the bottom and from the bottom to the top, covering different ranges. Figure 3B shows that Tier 1 screen and mixtures of the HTS screen cover the range till 2. molecular changes. Tier 1 screen extends to tier 2 screen and mixtures extend, both covering the range till 4. tissue-level changes. Systems toxicology covers the entire range, moving both from the top to the bottom and from the bottom to the top.
Figure 3.
An integrative method for investigating the impact of environmental chemicals on the epigenome and a proposed approach for toxico-epigenomic screening. (A) Comparison of in silico, in vitro, in vivo, population-based, and integrative methods in fully understanding the potential effects of environmental chemicals on the epigenome. Dotted arrows indicate situations where evidence can be inferred but not directly proved by the described methods. (B) An illustration of a proposed approach for toxicoepigenomic screening. A high-throughput screen (HTS) using in vitro and in silico methods can be conducted using single compounds and mixtures. Hits identified from the Tier 1 screen can be characterized more extensively using relevant in vitro and in vivo experiments. Finally, a systems toxicology approach could be used to integrate all data, including human data, to generate a complete profile of epigenotoxicology.
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