Multiomics Analysis of PCB126's Effect on a Mouse Chronic-Binge Alcohol Feeding Model

Abstract

Background: Environmental pollutants, including polychlorinated biphenyls (PCBs) have been implicated in the pathogenesis of liver disease. Our group recently demonstrated that PCB126 promoted steatosis, hepatomegaly, and modulated intermediary metabolism in a rodent model of alcohol-associated liver disease (ALD).

Objective: To better understand how PCB126 promoted ALD in our previous model, the current study adopts multiple omics approaches to elucidate potential mechanistic hypotheses.

Methods: Briefly, male C57BL/6J mice were exposed to $0.2\mathrm{mg}/\mathrm{kg}$ polychlorinated biphenyl (PCB) 126 or corn oil vehicle prior to ethanol (EtOH) or control diet feeding in the chronic-binge alcohol feeding model. Liver tissues were collected and prepared for mRNA sequencing, phosphoproteomics, and inductively coupled plasma mass spectrometry for metals quantification.

Results: Principal component analysis showed that PCB126 uniquely modified the transcriptome in EtOH-fed mice. EtOH feeding alone resulted in $>\mathrm{4,000}$ differentially expressed genes (DEGs), and PCB126 exposure resulted in more DEGs in the EtOH-fed group (907 DEGs) in comparison with the pair-fed group (503 DEGs). Top 20 significant gene ontology (GO) biological processes included "peptidyl tyrosine modifications," whereas top 25 significantly decreasing GO molecular functions included "metal/ion/zinc binding." Quantitative, label-free phosphoproteomics and western blot analysis revealed no major significant PCB126 effects on total phosphorylated tyrosine residues in EtOH-fed mice. Quantified hepatic essential metal levels were primarily significantly lower in EtOH-fed mice. PCB126-exposed mice had significantly lower magnesium, cobalt, and zinc levels in EtOH-fed mice.

Discussion: Previous work has demonstrated that PCB126 is a modifying factor in metabolic dysfunction-associated steatotic liver disease (MASLD), and our current work suggests that pollutants also modify ALD. PCB126 may, in part, be contributing to the malnutrition aspect of ALD, where metal deficiency is known to contribute and worsen prognosis. https://doi.org/10.1289/EHP14132.

Figure 1.

PCA for all samples ($n=6$; $n=24$). PCA plot was generated on MetaboAnalyst based on FPKM values, filtered by interquartile range, and normalized based on group median. Individual samples are identified by diet_exposure_number, where diet is either PF or EF, and exposure is either vehicle (VEH) or PCB126 (PCB). Note: EF, EtOH-fed; FPKM, fragments per kilobase per million mapped fragments; PC, principal component; PCA, principal component analysis; PF, pair-fed.

Figure 2.

Top 20 significantly enriched GO biological processes of the EF(Veh. vs. PCB126) comparison ($n=6$ vs. 6), sorted by lowest adjusted $p$-value (p.adjust). GO biological processes were determined by R package clusterProfiler, where DESeq2 differential expression analysis results were implemented for this pairwise comparison. Please refer to the Supplemental Excel file for summary data for this figure. Note: EF, EtOH-fed; GO, gene ontology; p.adjust, adjusted $p$-value.

Figure 3.

Top 25 significantly enriched GO molecular functions of the EF(Veh. vs. PCB126) comparison ($n=6$ vs. 6), sorted by lowest adjusted $p$-value (p.adjust) and decreasing signal. Enriched GO molecular functions were determined on the MetaCore platform for the EF(Veh. vs. PCB126) dataset for a false discovery rate set at 0.05. Please refer to the Supplemental Excel file for summary data for this figure. Note: EF, EtOH-fed; GO, gene ontology; p.adjust, adjusted $p$-value.

Figure 4.

Characterization of phosphoproteome dataset for all samples, excluding outlier EF_PCB3 ($n=23$). (A) PCA of each group where SD areas encircle each sample. PCA plot was generated on MetaboAnalyst where phospho-peptides were quantile normalized and then removed if $>40\%$ of the values were missing. Missing values were replaced by the limit of detection (1/5 of minimum positive value of each variable). (B) Total count of phosphorylated tyrosine for each sample. All peptides containing a phosphorylated tyrosine residue were counted if the peptide area was $>0$. Values are represented as $\text{mean}\pm \text{SD}$ with an alpha level set to 0.05. Significance was determined by two-way ANOVA and Tukey’s post hoc test, where post hoc $p$-values are provided above the figure. Please refer to the Supplemental Excel file for summary data for this figure. Note: ANOVA, analysis of variance; EF, EtOH-fed; PC, principal component; PCA, principal component analysis; PF, pair-fed; SD, standard deviation; Veh, vehicle.

Figure 5.

ICP-MS analysis of four essential micronutrient metals: (A) Na; (B) Co; (C) Mg; and (D) Zn. Values are represented as $\text{mean}\pm \text{SD}$ with an alpha level set to 0.05 ($n=15$; $n=60$). Significance was determined by two-way ANOVA and Tukey’s post hoc test, where post hoc $p$-values are provided above each graph. Please refer to the Supplemental Excel file for summary data for this figure. Note: ANOVA, analysis of variance; Co, cobalt; ICP-MS, inductively coupled plasma mass spectrometry; Mg, magnesium; Na, sodium; SD, standard deviation; Zn, zinc.