DNA methylome signatures as epigenetic biomarkers of hexanal associated with lung toxicity

Vertebrate animal study

Test animal

Forty male and female Fischer 344 rats of both sexes (10 rats/group), 7 weeks of age, were purchased from ORIENT BIO INC. (Seongnam, Korea). Prior to the experiment, animals were housed in stainless-steel cages (255 W × 3465 L × 3200 H mm) and acclimated for 5 days. Purification and quarantine periods were 3 or less, and during pretest and exposure periods, 2 or less were kept in stainless-steel cages. During the acclimation period, all animals are observed once a day to see clinical symptoms caused by the disease. Animals with diseases or abnormalities observed on physical examination are euthanized through CO₂ inhalation. Animal rooms had a 12-h light/dark cycle and controlled temperature (22  ± 3 °C) and humidity (30–70%). All animals were given a sterilized commercial pellet diet (PMI Nutrition International, USA) and sterilized water. All experimental procedures were approved by the Institutional Animal Care and Use Committee (IACUC) of Korea Institute of Toxicology (IACUC No. 1311-0301).

Clinical, biochemical and histopathological examinations

Test animals were subjected to examine every day for any clinical, blood biochemical and histopathological symptoms and mortality. Total body weight was measured twice a week during the 4 weeks exposure period. Test animals surviving to the end of the exposure period received completed necropsy. Test animals were euthanized using isoflurane anesthesia. For autopsy animals, gross autopsy findings were observed before organ weight measurement. Whole blood (WB) was rapidly collected for blood biochemical analysis from the abdominal aorta under isoflurane. Serum was obtained from WB by centrifuging at 3,000× rpm for 10 min at room temperature and analyzed for AST (Aspartate aminotransferase), ALT (Alanine aminotransferase), ALP (Alkaline phosphatase), CK (Creatine phosphokinase), GLU (Glucose), TP (Total protein), ALB (Albumin), GLO (Globulin), A/G (Albumin/globulin ratio), BUN (Blood urea nitrogen), CREA (Creatinine), TG (Triglyceride), PL (Phospholipid), TCHO (Total cholesterol), TBIL (Total bilirubin), GGT (Gamma glutamyl transferase), Ca(Calcium), IP (Inorganic phosphorus), Cl (Chloride), Na (Sodium) and K (Potassium) using an autochemical analyzer, Toshiba 120FR NEO (Toshiba Co., Japan). The lung tissues were collected from all animals and preserved in 10% neutral buffered formalin and embedded with paraffin wax. Tissues were stained with hematoxylin and eosin (H&E) (Cho et al., 2016; Cho et al., 2017).

Exposure design

All animal experiments were carried in accordance with relevant guidelines and regulations. Exposure experiments were designed following the OECD guideline for the testing of chemicals No. 412 “Subacute Inhalation Toxicity” (OECD, 2009), considering animal welfare. Hexanal vapor was generated with a bubbling generator and animals were exposed to it inside a flow-past nose-only inhalation chamber. Hexanal exposure concentrations were at target levels of 600, 1,000, and 1,500 ppm, and the control group was exposed to filtered clean air. Grouped animals had a pre-exposure period of about 2 days before exposure began. During the pre-exposure period, holder adaptation training was performed in accordance with the standard operation procedure to reduce stress caused by non-inhalational exposure. Residual animals excluded from the test were euthanized with CO₂. The animals (10 rats per group) were exposed to hexanal for 4 weeks (4 h/day, 5 days/week) in the nose-only inhalation chamber. Using a GC-FID (SHIMADZU, Japan), exposure concentration of hexanal vapor was measured thrice daily. We also monitored the environment in the inhalation chamber such as chamber flow rate, temperature (°C), relative humidity (%), chamber pressure (-Pa) and oxygen concentration (%) more than 4 times during the exposure period (Cho et al., 2016; Cho et al., 2017).

DNA preparation

Genomic DNA was isolated from the homogenized lung tissue of rats, and only the supernatant was used for extraction. DNA samples of 6 rats from each group (control, low-dose, middle-dose, and high-dose group; a total of 24 DNA samples) were used for the microarray analysis for all 40 rats used in the study. Using Qiagen’s QIAamp DNA Mini kit (QIAGEN, Hilden, Germany), genomic DNA was extracted as described in our previous study (Cho et al., 2018). The genomic DNA purity and concentration were measured using ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE) and electrophoresis conducted in a 1.5% agarose gel in 1 × TAE buffer (4.8 g of Tris, 1.14 mL of acetic acid, 2 mL of 0.5 M EDTA at pH 8.0, and ethidium bromide) at a constant 100 V for 15 min.

Fragmentation of DNA

To extract only methylated DNA, the genomic DNA size should be about 200 bp to 1,000 bp. Therefore, genomic DNA was fragmented into 200 bp to 1,000 bp sections using a Sonic Dismembrator 550 (Fisher Scientific, Waltham, MA, USA) with 3 cycles comprising 4 cycles of 20 s ‘ON’ and 1 cycle of 20 s ‘OFF’. To determine the size of the fragmented DNA, agarose gel electrophoresis and ethidium bromide staining were performed using DNA size markers of 500–10,000 base pairs in size.

Methylated DNA immunoprecipitation (MeDIP)

As described in our previous study (Cho et al., 2018), MeDIP was performed with MethylMiner Methylated DNA Enrichment Kit (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. Fragmented DNA 1 µg and untreated control DNA (Input) 3 µg were used for quality and labelling procedures. Briefly, Dynabeads M-280 Streptavidin 10 µl was combined with 7 µl of MBD (methyl-CpG binding domain)-Biotin Protein. The MBD-magnetic bead conjugates were washed thrice and resuspended in 1 volume of 1X bind/wash buffer. The capture reaction was conducted by adding of 1 µg sonicated DNA to the MBD magnetic beads on a rotating mixer for 1 h at room temperature. Next, the beads were washed three times with 1 × bind/wash buffer. The methylated DNA was eluted as a single fraction with a high-salt elution buffer (2,000 mM NaCl). Consequently, each fraction was concentrated by ethanol precipitation using 1 µL glycogen (20 µg/µL), 1/10th volume of 3 M sodium acetate (pH 5.2), and two volumes of 100% ethanol, and then resuspended in 60 µL of DNase-free water. The eluted methylated DNA immunoprecipitation samples were stored at −20 °C until further use. This experiment protocol was referred from out previous research in Cho et al. (2018).

Epigenome-wide DNA methylation

First, whole genome amplification kit (GenomePlex Complete Whole Genome Amplification Kit, SIGMA-ALDRICH, USA) was used to amplify DNA and methylated immunoprecipitation (IP) samples according to the manufacturer’s instructions. The amplified samples were purified using the QIAQuick PCR clean-up kit (QIAGEN, Hilden, Germany). The amplified DNA and 4 µg of the methylated IP sample were labeled using the Bioprime labeling kit from Invitrogen according to the manufacturer’s instructions. The IP sample was labeled with Cy5-dUTP and the input DNA sample was labeled with Cy3-dUTP and 50 µl of master mix(dNTPs-dATP, dGTP, dCTP; 120 µM, dTTP; 60 µM, Cy5-dUTP or Cy3-dUTP; 60 µM). After labeling the sample, the concentration was measured using an ND-1000 spectrometer (NanoDrop Technologies, Inc., Wilmington, DE).

Second, After checking labeling efficiency, each 2.5ug to 5ug of cyanine 3-labeled and cyanine 5-labeled DNA target were mixed and then resuspended with 2X hybridization buffer, Cot-1 DNA, and Agilent 10X blocking agent, and de-ionized formamide. Before hybridization to the array, the 260ul hybridization mixtures were denatured at 95 °C for 3min and incubated at 37 °C for 30 min. The hybridization mixtures were was centrifuged at 17,900× g for 1min and directly pipetted onto the Customized Rat Methylation Microarray (400 K). The arrays hybridized at 65oC for 40 h using Agilent Hybridization oven (Agilent Technology, USA). The hybridized microarrays were washed as the manufacturer’s washing protocol (Agilent Technology, Santa Clara, CA, USA).

Third, after washing, hybridization images on the slides were scanned using the Agilent DNA microarray scanner (Agilent Technologies) and signals were extracted from each probe using Agilent Feature Extraction software (v10.7.3.1). All data were normalized using Agilent’s Workbench software v7.0 according to the manufacturer’s instructions (Agilent Technologies). The background-corrected intensity data were normalized with blank subtraction followed by intra-array LOWESS normalization. The peak detection was performed with Pre-defined Peak Shape detection v2.0 with a p-value <0.01 for non-parametric test and a peak-score >5 for EVD-based score. The data were normalized by dividing the average of the signal intensity of the exposed group by the normalized average of the control group. The differentially methylated probes were selected using the 3.0-fold change cutoff and p-value <0.05. For reference, the intensity dependent normalization is a technique that is used to eliminate dye-related artifacts in two-color experiments that cause the cy5/cy3 ratio to be affected by the total intensity of the spot. This normalization process attempts to correct for artifacts caused by non-linear rates of dye incorporation as well as inconsistencies in the relative fluorescence intensity between some red and green dyes.

Integrating DNA methylation and gene expression

To identify the anti-correlated methylated genes, we conducted a comparative analysis of DNA methylation and mRNA expression patterns using GeneSpring GX. mRNA profiles from the hexanal-exposed rats were obtained from our previous study (Cho et al., 2017). We used Pearson’s correlation analysis, the most appropriate statistical coefficient for a small number of measures, to estimate the degree of anti-correlation (e.g., hyper methylation vs. down-regulated c mRNA expression or vice versa) between any putative pairs of DNA methylation and mRNA. The raw data are available from the NCBI GEO under accession number GSE60118. We considered the methylated genes with methylation differences of at least 3.0-fold and mRNA expression differences of at least 1.5-fold on p-value <0.05.

DAVID functional enrichment analysis

Using the DAVID functional annotation bioinformatics tool, we performed GO enrichment analyses to understand biological functions associated with hexanal exposure. It was used to determine significant biological pathways for anti-correlated target genes between DNA methylation and mRNA expression associated with hexanal exposure. Fisher’s exact test was used to detect significant enrichment of pathways, and the resulting p-value were adjusted using the Benjamini–Hochberg algorithm.

Statistical analysis

In all cases, the differences between the control and exposure group were evaluated using the unpaired t-test. The p-value criterion was set at p-value <0.05 as the level of statistical significance.

Animal ethics

The experiment protocol was authorized by the Institutional Animal Care and Use Committee of Korea Institute of Toxicology (IACUC No. 1311-0301).

Monitoring of inhalation exposure concentration, environmental conditions, and histopathologic alterations

As mentioned in our previous studies (Cho et al., 2016; Cho et al., 2017), inhalation hexanal exposure concentrations were monitored in rats using online gas chromatography (GC) every 10 min during the exposure period. SPF (Specific-pathogen-free) Fischer-344 derived (CRL:CD) rats of both sexes were used at the age of 7 weeks (n=10/group). The average exposure concentrations were 646.03 (± 80.06; low-dose), 999.06 (± 162.08; middle-dose), and 1,525.31 (± 199.02; high- dose) ppm. The conditions of the inhalation chamber such as temperature, relative humidity, chamber pressure, and oxygen concentration were also measured (Cho et al., 2016).

Compared with the control group, no significant body weight, organ weight and histopathologic alterations were observed after 4 weeks of hexanal exposure (Cho et al., 2017). In middle-dose group, increased total bilirubin compared to control group in the male rats and decreased total protein, albumin and triglyceride in the female rats were identified. These results showed no significant dose-dependent changes related to hexanal exposure (Cho et al., 2017). Therefore, to predict the potential adverse health effects of hexanal exposure we aimed to identify the hexnal-associated genetic and epigenetic alterations using microarray-based mRNA and DNA methylation to address the molecular basis of hexanal exposure relevant to respiratory system.

DNA methylation pattern after hexanal exposure

Aberrant DNA methylation has been linked to the abnormalities or disorders that induced by environmental stressors including environmental chemicals (Kubota, 2016). Therefore, the framework of epigenome for environmental risk assessment has been rapidly developed. First, we extracted from rats exposed to hexanal of three concentrations (Low dose, 600 ppm; Middle dose, 1,000 ppm; High dose, 1,500 ppm), and then genomic DNA using sonication to extract only methylated DNA using immunoprecipitation. The cleaved methylated DNA was confirmed using gel electrophoresis, and as a result, it was confirmed that the DNA of all groups was sheared to about 150 bp to 500 bp, so that the optimal DNA for immunoprecipitation was secured (Fig. S1). After methylated DNA was extracted from aldehyde-exposed rat lung tissues through methylated DNA immunoprecipitation, the concentration was measured and the quantitative analysis of methylated DNA was performed through gel electrophoresis. As a result, it was confirmed that the concentration and state of methylated DNA are suitable for DNA methylation microarray (Fig. S2). In the current study, using a custom-designed Agilent 400K CpG methylation microarray, we investigated DNA methylation profiles in CpG islands gene promoter sequences of hexanal-exposed lung tissues of F344 rats and compared with those from rats exposed to clean filtered air (control group) (n=6/group). For reference, the DNA Methylation Microarray are designed to interrogate known CpG islands and related sites. It is designed for analysis of methylated DNA derived from affinity-based isolation methods including methylated DNA immunoprecipitation (MeDIP). We analyzed methylation patterns for approximately 389,347 probes on the arrays. Compared with the control group, all three hexanal-exposed groups showed distinctly different methylation patterns (Fig. 1). The data is the averaged signal that is acquired from normalizing the signal intensity by dividing the average of the signal intensity of the control group. In the low dose exposure group, 661 methylated sites and 571 differentially methylated genes (hyper-methylated: 464, hypo-methylated: 107) were identified. In the middle dose exposure group, 4,181 methylated sites and 3,268 differentially methylated genes (hyper-methylated: 2,513, hypo-methylated: 755) were identified, and 11,744 methylated sites and 7,477 differentially methylated genes (hyper-methylated: 4,851, hypo-methylated: 2,662) were identified in the high dose exposure group. In all groups change was noted at ≥ 3.0-fold change, p-value <0.05. Overall, the methylation sites increased as the exposure concentration increased. (Table 1).

Among these differentially methylated sites and genes, 79 sites and 73 genes (hyper-methylated: 69, hypo-methylated: 4) showed commonly methylated expression patterns in the three hexanal exposure groups (Fig. 2, Table 2). Furthermore, we identified 36 dose-dependent methylated genes (34 hyper-methylated and 2 hypo-methylated) in the common methylated genes of three hexanal exposure group using line-plot analysis (Fig. 3A, Table 3). The dose-dependent genes are illustrated as a heatmap (Fig. 3B). These dose–response relationships have the potential to serve as quantitative epigenetic biomarkers of hexanal exposure. Raw data are available online at Gene Expression Omnibus (GEO accession number GSE129313).

Gene expression profiles induced by hexanal exposure

To investigate the gene expression signatures response to hexanal inhalation exposure, we previously investigated the gene expression profiling of lung tissues of hexanal-exposed F344 rats using the Rat Oligo Microarray (44 K). The raw data are available at GEO/NCBI GSE 60118. The gene expression profiles were analyzed by comparing them to the control group using 1.5-fold change and unpaired t-test p value <0.05 as statistical significance (Table 4). In the previous study, we identified hexanal specific genes that were involved in diverse biological processes including apoptosis, cell proliferation, and mitogen-activated protein kinase (MAPK) cascade. These genes were also associated with disease such as respiratory and nervous system diseases (Cho et al., 2017). It suggests that hexanal exposure may have potential adverse health effects on humans. Therefore, we aimed to analyze DNA methylation signatures in hexanal- exposed F344 rats to understand the epigenetic effects of hexanal exposure.

Comparative analysis of DNA methylation and mRNA expression profiles

DNA methylation was involved in transcriptional regulation and gene activity. Promoter hyper-methylation can leads to silencing of gene expression, whereas hypo-methylation can leads to gene activation. The investigation of the implication of DNA methylation in the regulation of gene expression and identification of key genes that regulated by both DNA methylation and gene expression using integrative analysis is important. Therefore, we conducted an integrated analysis of DNA methylation (Table 1) and mRNA expression data (Table 4). As shown in Table 5, we identified the hyper-methylated vs. down-regulated genes and hypo-methylated vs. up-regulated genes in the hexanal exposure groups. These results suggest potential core DNA methylation-based epigenetic biomarkers for exposure/risk assessment of hexanal.

Gene Ontology (GO) analysis of putative DNA methylation biomarkers of hexanal

We next investigated the relevant molecular and cellular processes controlled by hexanal exposure-specific inversely correlated target genes based on GO biological processes terms using the DAVID bioinformatics tool (Table 6). The key GO terms were related to the lactation (GO:0007595), skeletal muscle cell differentiation (GO:0035914), Positive regulation of synapse assembly (GO:0051965), sodium ion transport (GO:0006814), and regulation of tumor necrosis factor production (GO:0032680). These results indicated that putative epigenetic biomarkers of hexanal are involved in skeletal muscle cell differentiation, synapse assembly, and TNF production. Further studies are necessary to determine hexanal-induced toxicological mechanisms based on functional enrichment analysis.