Cardiovasc Toxicol DOI 10.1007/s12012-014-9279-6

Chronic Cardiovascular Disease-Associated Gene Network Analysis in Human Umbilical Vein Endothelial Cells Exposed to 2,3,7,8-Tetrachlorodibenzo-p-dioxin Yu Yu • Jing Qin • Di Chen • Hui Wang Junwen Wang • Ying Yu

•

Ó Springer Science+Business Media New York 2014

Abstract The association of dioxin exposure with increased morbidity or mortality of chronic cardiovascular diseases (CVDs) has been established by many epidemiological studies. However, the precise global gene expression alterations caused by 2,3,7,8-tetrachlorodibenzo-pdioxin (TCDD) in the cardiovascular system need to be further elucidated. In this study, we profiled the gene expression of human umbilical vein endothelial cells (HUVECs) exposed to different concentrations of TCDD by high-throughput sequencing. Expression of 1,838 genes was changed significantly after TCDD stimulation. The FunDO analysis suggested that some CVDs were highly associated with TCDD treatment, including atherosclerosis, thromboangiitis obliterans, pulmonary arterial hypertension (PAH), and hypertension. KEGG pathway analysis

Electronic supplementary material The online version of this article (doi:10.1007/s12012-014-9279-6) contains supplementary material, which is available to authorized users. Y. Yu
D. Chen
H. Wang
Y. Yu (&) Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 294 Taiyuan Road, Shanghai 200031, China e-mail: [email protected] Y. Yu e-mail: [email protected] D. Chen e-mail: [email protected] H. Wang e-mail: [email protected] Y. Yu
D. Chen
H. Wang
Y. Yu Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing 100021, China

showed that many genes in the signaling pathways of vascular smooth muscle contraction and apoptosis were altered distinctly. In addition, we revealed evidence regarding the gene network changes of chronic CVDs including atherosclerosis, thrombosis, myocardial infarction (MI), hypertension, and PAH in TCDD-exposed HUVECs. We found that gene expression of b1-adrenoceptors (ADRB1), b2-adrenoceptors (ADRB2), endothelin-converting enzyme 1 (ECE1), and endothelin-1 gene (EDN1) that are involved in the blood pressure regulation pathway decreased apparently under TCDD treatment. Moreover, the transcripts of interleukin 1 beta (IL-1b) and tumor necrosis factor a (TNFa), which are related to atherosclerosis, were up-regulated by TCDD stimulation. In addition, the transcripts of Homo sapiens collagen, type IV, alpha 1 (COL4A1), and isoforms that trigger the MI pathway were up-regulated after TCDD exposure. Finally, we found enhanced platelet-derived growth factor (PDGF) and signal transducer and activator of transcription 5 (Stat5) J. Qin
J. Wang (&) Department of Biochemistry, The University of Hong Kong, 21 Sassoon Road, Hong Kong SAR, China e-mail: [email protected] J. Qin e-mail: [email protected] J. Qin
J. Wang Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen 518057, China J. Wang Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Road, Hong Kong SAR, China

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expression with TCDD treatment in endothelial cells, which are involved in PAH induced by vascular injury. Keywords Dioxin
Chronic cardiovascular diseases
HUVECs
RNA-seq
Gene expression
Signaling pathway

Introduction 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), an environmental pollutant resulting from the production and combustion of chlorinated compounds, has the highest toxicity in a family of compounds known as the polyhalogenated aromatic hydrocarbons (PHAHs). The public became widely aware of TCDD and its potential toxic effects during the 1960s, when it was identified as a major contaminant in Agent Orange, an herbicide and defoliant widely used during the Vietnam War. Today, TCDD predominantly enters the environment in contaminants from incineration emissions. It has the features of extensive deposition and coexistence in the environment, persistence, and bioaccumulation [1]. TCDD can cause a wide range of biochemical and pathological changes in mammalian and non-mammalian species, including carcinogenesis, neurological symptoms, hepatotoxicity, chloracne, teratogenesis, cardiovascular diseases (CVDs), diabetes, cancers, and immunotoxicity [2, 3]. A number of epidemiological studies have established the association of dioxin exposure with high morbidity or mortality of chronic CVDs [4, 5]. For example, epidemiological studies on a population heavily exposed to dioxin in 1976 in Seveso, Italy, indicated that coronary and hypertensive diseases were increasing among the exposed population. Another study confirmed a higher incidence of hyperlipidemia, atherosclerotic plaques, increased intimamedia thickness, and ischemic heart disease in a group of former dioxin workers. Moreover, TCDD has been shown to cause cardiovascular toxicity in animals. Adult mice exposed subchronically to TCDD developed increased blood pressure, heart weight, and oxidative stress markers [6]. Increased blood pressure and triglyceride levels were also observed after exposure of an acute high dose of TCDD in mice [7]. ApoE-/- mice exposed to subchronic doses of TCDD also developed earlier and more severe atherosclerotic lesions [7]. Some of these changes might be due to altered gene expression, inflammation, key calciumsignaling pathways, oxidative stress, or mitochondrial dysfunction [8, 9]. However, the comprehensive gene networks to clarify the underlying mechanisms of atherosclerosis and hypertension induced by TCDD need to be studied further. Moreover, evidence of illustrating the relationship between TCDD and other chronic

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CVDs including thrombosis, myocardial infarction (MI), and pulmonary arterial hypertension (PAH) is still deficient, and those gene networks involved remain to be explored. The endothelium has been recognized as a major regulator of vascular hemostasis. Endothelial cells, composing the inner lining of blood vessels, are strategically located between circulating blood and blood cells and the vascular smooth muscle. Functional integrity of the endothelium is crucial for the maintenance of blood flow and antithrombotic capacity, because the endothelium releases humoral factors that control relaxation and contraction, thrombogenesis and fibrinolysis, and platelet activation and inhibition. Thus, endothelial dysfunction contributes substantially to cardiovascular disorders such as atherosclerosis, hypertension, and heart failure, which lead to hypoperfusion, vascular occlusion, and end-organ damage [10]. In this study, we profiled whole genome transcription in TCDD-treated human umbilical vein endothelial cells (HUVECs) and analyzed the possible gene networks implicated in TCDD-related chronic CVDs by RNA sequencing. Microarray technology has been applied to study the effects of TCDD on genome-wide gene expression levels in human CD34? hemopoietic cells and in murine fetal hearts [11, 12]. The application of the advanced technology, RNA sequencing, in our study was critical to further understand the transcriptome of TCDDrelated chronic CVDs.

Materials and Methods Cell Culture HUVECs were obtained from the Cell Resource Center of Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. Cells were cultured in RPIM 1640 medium (Invitrogen) supplemented with 10 % fetal bovine serum (Hyclone), streptomycin (100 mg/mL, Sigma), and penicillin (100 U/mL, Sigma). HUVECs were maintained in 5 % CO2 at 37 °C. Cells at passages 4–8 were used for all experiments. Lungs were isolated from C57BL/6 mice. After digestion with 600 U/mL collagenase type I (Worthington) and DNase I (60 U/mL, Worthington) in DPBS (Life Technologies) at 37 °C for 30 min, lung endothelial cells were isolated with anti-mouse CD31 and CD102 antibodies, based on magnetic bead separation. CD31- and CD102positive cells were used for gene expression analysis [13]. Cell Viability Assay HUVECs were seeded into 96-well plates for 24 h and treated with TCDD at indicated concentrations (0, 5, 10,

Cardiovasc Toxicol

20, 40, and 80 nM) for an additional 24 h. The culture medium was removed and replaced with 100 lL of fresh medium, and then, 10 lL of WST-8 Assay Kit reagent (Dojindo) was added to each well. Plates were incubated at 37 °C for 2 h, and then, absorbance was measured at 450 nm using a SpectraMax 190 Microplate Reader (Molecular Devices). The reference wavelength was 600 nm. Background absorbance (from wells without cells) was subtracted from all values. All experiments were performed in triplicate. Sample Preparation and cDNA Library Construction HUVECs were seeded into 6-well plates for 24 h and treated with TCDD at different concentrations (0, 10, 20, and 40 nM) for an additional 24 h. Then, the cells were washed 3 times with PBS and collected. Total RNA was extracted with Trizol reagent. The integrity of total RNA was evaluated using an Agilent Bioanalyzer 2100 system. cDNA libraries were constructed following the manufacturer’s instructions according to the schematic described previously by Zhang et al. [14]. RNA Sequencing and Data Analysis The image files obtained from the Illumina 1G sequencer were processed to yield sequence data. Then, the raw reads were trimmed to remove adaptor sequences and were filtered by sequence quality: reads with unknown sequences ‘‘N’’ and mean phred scores \ 10 were removed. Remaining high-quality reads were mapped to the human reference genome (hg19, UCSC Genome Browser) using the TopHat program, and the fragments per kilobase of exon per million fragments (FPKM) of each gene were measured by the Cufflinks program with hg19 refseq gene annotations. The significance of digital gene expression profiles was analyzed as described previously [15]. To avoid the potential noise signal from high-throughput sequencing, we concluded that a statistical analysis was reliable when applied to genes with an FPKM value C 0.01 in at least 2 of the 4 treatments. This statistical significance was based on expected sampling distributions. The remaining 23,119 genes excluding the genes with low expression were used to calculate the fold changes and P values. One-way ANOVA was used to test the significance of difference among treatments. In this study, the absolute fold change no less than 1.5 and P value less than 0.05 were used to define the differentially expressed genes (DEGs) including the up-regulated and down-regulated genes. The expression pattern of these genes was visualized using the heat-map function in the R base package. We used Pearson correlation to test the TCDD dose-dependent effects on gene expression.

Functional Annotation and Pathway Analysis Enriched biological processes of Gene Ontology (GO) in all DEGs and DEGs with TCDD dose-dependent effects were investigated using the internet tool DAVID (http:// david.abcc.ncifcrf.gov/home.jsp). A hypergeometric test was used to select the enriched biological process in GO for each gene. GO constitutes a controlled vocabulary of approximately 20,000 terms organized in three independent hierarchies for cellular components, molecular functions, and biological processes (www.geneontology.org). The common pathways associated with these genes were analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG, www.genome.jp/kegg/pathway.html). The KEGG is a database resource for identifying the high-level functions and utilities of biological systems, such as the cell, organism, and ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies. The KEGG database records networks of molecular interactions in cells and variants specific to particular organisms. We used some known pathways of atherosclerosis, thrombosis, MI, hypertension, and PAH to investigate the chronic CVDsrelated gene networks affected by TCDD in HUVECs [16– 19].

Association Analysis To study the correlation between disease and gene expression changes, the DEGs in HUVECs were assigned to different diseases based on Disease Ontology and peer reviewed evidence from GeneRIF using the internet tool FunDO (http://django.nubic.northwestern.edu/fundo/). Then, the gene–CVDs interaction networks were visualized by Cytoscape v2.6.2 [20].

RNA Extraction and Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) Total RNA was isolated from HUVECs using Trizol reagent (Invitrogen) according to the manufacturer’s instructions and treated with DNase I (Promega). RNA concentration and purity were assessed using the NanoDrop 2000 (Thermo). RNA (2.0 lg) was reverse transcribed with M-MLV reverse transcriptase (Promega) and oligo(dT) 18 primers (Takara) as recommended. qRT-PCR was performed using a CFX96TM Real-Time System (BioRad) and iQTM SYBR Green Supermix (Bio-Rad) as described by the manufacturer. Raw data were normalized to the internal control, GAPDH, and presented as relative

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Fig. 1 Sequencing and mapping messages of mRNA profiling in TCDD-treated HUVECs. a The high-quality clean reads from highthroughput sequencing. Total RNA from TCDD-exposed HUVECs was used to prepare the high-throughput sequencing library. b The proportions of high-quality clean reads unmapped and/or mapped to unique genes, multiple genes, and genome. c The number of genes

detected in HUVECs treated by TCDD. d The top 10 abundance change genes down-regulated or up-regulated in HUVECs treated by different doses of TCDD. e The top tenfold change genes downregulated or up-regulated in HUVECs treated by different doses of TCDD

expression levels calculated by the 2DDCt method. All primers for qRT-PCR verification are described in Table S1 (Supplementary File 1). All experiments were performed in triplicate.

population [21, 22], and these doses have been commonly used in most of the studies on cell systems [11, 23]. A cell viability assay also confirmed that 10–40 nM TCDD was suitable to utilize for further gene expression analysis. (Supplementary File 2: Fig. S1). We obtained approximately 20 million reads of high-quality clean tags in each sample after sequencing (Fig. 1a). In these tags, on average, approximately 65, 12, and 52 % of the reads could be mapped to an annotated human genome, multiple genes, and unique genes, respectively (Fig. 1b). Unique genes in four groups (29,949, 29,678, 30,115, and 29,935) were detected and quantified, and these groups shared 27,759 genes in common (Fig. 1c). The top 10 up- and downregulated genes, regarding abundance changes and fold

Results Gene Expression Changes in TCDD-Treated HUVECs To survey the gene expression profile in HUVECs treated with different concentrations of TCDD, we implemented high-throughput sequencing. A total of 10–20 nM concentrations of TCDD in vivo was reachable in the exposed

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changes, induced by TCDD in HUVECs are shown in Fig. 1d, e, respectively. Among them, some are reportedly involved in pathologenesis of atherosclerosis, hypertension, aortic aneurysm, heart failure, and apoptosis, such as cyclin-dependent kinase 2-associated protein 2 (CDK2AP2), DNA-damage-inducible transcript 4 (DDIT4), disco-interacting protein 2 homolog A (DIP2A), growth differentiation factor 15 (GDF15), homocysteine-inducible endoplasmic reticulum stress-inducible ubiquitin-like domain member 1 (HERPUD1), interleukin 6 signal transducer (IL6ST), immediate early response 3 (IER3), prion protein precursor (PRNP), reticulon-4 (RTN4), solute carrier family 39 member 8 (SLC39A8), and tumor necrosis factor, alpha-induced protein 2 (TNFAIP2) (Fig. 1d, e).

Gene Annotation and Functional Categories of TCDDInduced DEGs in HUVECs Among the 29,949, 29,678, 30,115, and 29,935 unique genes detected from the control and treatment groups, the expression profile of 1,838 DEGs is shown in Table S2 (Supplementary File 3). Clustering of different treatments in the heat-map of the total DEGs showed that the gene expression patterns of the 20 and 40 nM TCDD-treated groups were more close to those of the control group than those of the 10 nM TCDD-treated group (Supplementary File 4: Fig. S2). There were 389 up-regulated genes in the 10 nM-treated group, 398 up-regulated genes in the 20 nM-treated group, and 778 up-regulated genes in the 40 nM-treated group (Fig. 2a). The numbers of downregulated genes in the 3 TCDD-treated groups were 687, 317, and 467, respectively (Fig. 2b). Thus, the total numbers of altered genes in the 3 TCDD-treated groups were 1,076, 715 and 1,245, respectively (Fig. 2c). To investigate the possible biological functions of the genes affected by TCDD, all the altered genes were analyzed by GO. The top 10 biological functions ranked by percentage are shown in Fig. 2d. These DEGs were highly enriched in regulation of transcription, RNA metabolic process, and intracellular signaling cascade. Interestingly, the DEGs were also implicated in the regulation of cell proliferation, programmed cell death, and apoptosis. In addition, we listed the CVDs-related enrichments, which were chosen from the biological functions of those 1,838 altered genes based on statistical significance (Fig. 2e). The genes altered by TCDD were associated primarily with the regulation of apoptosis, vessel development and morphogenesis, angiogenesis, lipid localization, and cholesterol metabolic process. These data suggested that endothelial cell dysfunction and lipid metabolic disorder could be the dominant pathological changes of CVDs associated with TCDD exposure.

Differential Dose-Dependent Responses to TCDD Next, we used cluster analysis, filtering, and correlation analysis to determine the primary dose-related response patterns elicited by increasing concentrations of TCDD (Fig. 3). There were 382 genes altered at all doses (Fig. 3a). The greatest number of genes (1,245) with altered expression occurred at the highest dose. We used GO to study the functional categories of these 382 altered genes and found that they were strongly enriched in protein localization, intracellular transport, and macromolecular complex subunit organization (Fig. 3b). The alterations of gene expression response to TCDD dosages were analyzed (Fig. 3c), and 783 genes were identified. Most of the 783 genes were involved in intracellular signaling cascade, regulation of cell proliferation, and metabolic processes (Fig. 3d). In addition, we studied the CVD-related enrichments which were chosen from the functional categories of the 783 altered genes based on statistical significance. Again, these enrichments primarily included endothelial cell dysfunction and lipid metabolic disorders (data not shown). Potential Correlation of TCDD with CVDs To further elucidate the correlations between TCDD and CVDs, we assigned the DEGs to different diseases using the FunDO tool. The data showed that 1,838 DEGs were primarily associated with breast cancer, prostate cancer, Alzheimer’s disease, lung cancer, and leukemia (data not shown), which were in line with the previous report [6]. Then, we analyzed the associations of CVDs with TCDD, which were chosen from the associations between all diseases and TCDD based on statistical significance, and found that heart failure, atherosclerosis, hyperlipidemia, thromboangiitis obliterans, PAH, hypertension, and aortic aneurysm were highly associated with TCDD exposure (Fig. 4a, b). Main Signaling Pathways Altered in TCDD-Treated HUVECs KEGG pathway analysis was performed to explain the biological functions and potential mechanisms of the TCDD-responsive DEGs. The KEGG pathways that significantly correlated with TCDD are shown in Table 1, along with their associated genes. These pathway analysis data demonstrated that the pathways altered by TCDD were mainly implicated in dilated cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy, vascular smooth muscle contraction, hypertrophic cardiomyopathy, and apoptosis. In particular, we found the expression of tumor necrosis factor a (TNFa) and interleukin 1beta (IL-

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Fig. 2 Genes and the related biological processes altered in HUVECs exposed to TCDD. a The differentially expressed genes in TCDDtreated HUVECs were separated into distinct clusters according to expression alterations by comparing to the control group. Red lines indicate the up-regulated gene cluster including 389 genes in the 10-nM treated group, 398 genes in the 20-nM treated group, and 778 genes in the 40-nM treated group. b Purple lines indicate the downregulated gene cluster including 687 genes in 10-nM treated group,

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317 genes in 20-nM treated group, and 467 genes in 40-nM treated group. c Pink lines indicate the total altered genes in the three TCDDtreated groups. d The altered genes in TCDD-treated HUVECs were assigned to different biological processes based on Gene Ontology analysis. The top 10 biological functions ranked by percentage were presented. e The biological processes related to cardiovascular diseases (P \ 0.05) and the case genes in each cluster ranked by percentage were listed (Color figure online)

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Fig. 3 TCDD dose-dependent gene expression changes in the HUVECs. a Venn diagram represented the TCDD dose-dependent changes in gene expression in the HUVECs. 1,076, 715, and 1,245 altered genes were found in HUVECs after 10, 20, and 40 nM TCDD exposure, respectively. About 382 genes were commonly changed among the three groups. b Functional annotations of 382 altered genes were analyzed, and the top 10 biological processes ranked by

percentage were displayed. c TCDD dose-dependent altered genes were analyzed by Pearson correlation and presented as the log 2 values with significantly correlation (P \ 0.05). Total 783 genes were identified. d Functional annotations of the 783 TCDD dose-dependent altered genes were performed, and the top 10 biological functions ranked by percentage were shown

1b) was up-regulated by TCDD; thus, TCDD might induce apoptosis in HUVECs through these two cytokine-mediated signaling pathways. In addition, based on the known disease-related signaling pathways, we classified the changed genes response to TCDD treatment into different CVDs pathways (Table 2). The atherosclerosis pathways were divided into 14 branches containing acute inflammation, apoptosis, B cell activation, and cytokine network. Some genes were upregulated, such as IL-1b, interleukin 6 (IL6), TNFa, CD40, and macrophage-specific colony-stimulating factor (CSF1). However, other genes were down-regulated after TCDD stimulation, including heme oxygenase-1 (HMOX1), lowdensity lipoprotein receptor (LDLR), and sterol O-acyltransferase 1 (SOAT1). Homo sapiens collagen, type IV, alpha 1 (COL4A) and isoforms, Homo sapiens Rho guanine

nucleotide exchange factor (ARHGEF) and isoforms, Homo sapiens protein phosphatase 1, and regulatory subunit (PPP1R) and isoforms play important roles in modulating thrombosis and MI, and their transcript levels were altered by TCDD treatment. The gene expression of b1adrenoceptors (ADRB1), b2-adrenoceptors (ADRB2), endothelin-converting enzyme 1 (ECE1), and endothelin-1 gene (EDN1) decreased with TCDD treatment. Based on previous observations that the growth factor signaling, notch signaling, and inflammation reactions play key roles in regulating PAH induced by vascular remodeling [17], we analyzed the effects of TCDD on those genes associated with these pathways and found that expression of 28 genes was up-regulated and expression of 30 genes expressions was down-regulated. For example, expression was altered for v-akt murine thymoma viral oncogene

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Fig. 4 TCDD is correlated with different cardiovascular diseases at a transcriptional view. a The map of cardiovascular diseases enriched with the genes altered in HUVECs treated by TCDD. About 1,838 altered genes were assigned to different diseases using the web tool

FunDO. The sizes of the disease nodes are proportional to the number of enriched genes. b The number of hit genes and P value of enriched cardiovascular diseases in (a)

homolog (AKT), matrix metalloproteinases (MMP), phosphoinositide-3-kinase (PIK3), and platelet-derived growth factor (PDGF). These results demonstrated that TCDD likely affected PAH induced by vascular remodeling through gene regulation.

Verification of Gene Expression Alterations in TCDDTreated HUVECs by qRT-PCR

Different HUVEC Functional Categories of TCDDResponsive Genes Because the important properties of endothelium on maintenance of vascular integrity, regulation of blood pressure, and inflammatory defense, we analyzed expression of endothelial markers and assigned TCDD-responsive genes to the principal categories of endothelium function. Similar to the previous report [24], the known endothelial markers were detected in our study, such as angiopoietin-2 (ANGPT2), platelet-derived growth factor A (PDGFA), intercellular adhesion molecule-2 (ICAM-2), endoglin (ENG), thrombomodulin (THBD), fibroblast growth factor receptor 4 (FGFR4), and intercellular adhesion molecule-3 (ICAM-3) (Table 3). Surprisingly, PDGFA expression increased significantly with TCDD treatment in a dosedependent manner (Table 3). Using the GO program, we then assigned TCDD-responsive genes to the principal categories of endothelium function, such as endothelium lineage and development, cell migration, angiogenesis and development of artery and lymph vessels, chemotaxis of leukocytes, blood pressure regulation, immunity, and hemostasis as described previously [25] (Supplementary File 5: Table S3).

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To validate the RNA-seq data presented in this study, we used qRT-PCR to confirm the expression of some key genes in the arylhydrocarbon receptor (AHR) pathway at four TCDD doses (Fig. 5). The RNA-seq data showed that the key genes in the AHR pathway were up-regulated by TCDD treatment, including AHR, repressor of AHR (AHRR), aryl hydrocarbon interacting protein (AIP), aryl hydrocarbon nuclear translocator (ARNT), ARNT2, cytochrome P4501A1 (CYP1A1), cytochrome P4501B1 (CYP1B1), glutathione S-transferase M3 (GSTM3), glutathione S-transferase M4 (GSTM4), and NAD(P)H: quinone oxidoreductase 1(NQO1) (Table 2), which was in line with the previous report [26]. The induction of AHR, AHRR, COX2, CYP1A1, and NQO1 genes by TCDD treatment was further validated in both HUVECs and murine primary lung endothelial cells (MLECs, Fig. 5a, b, e, f, h). In addition, we observed sharp up-regulation of CYP1B1 gene transcript in MLECs, not as in HUVECs (Fig. 5g).

Discussion Although some epidemiological studies have established the association of dioxin exposure with high morbidity or mortality of chronic CVDs, such as atherosclerosis and hypertension, and TCDD has been shown to cause cardiovascular toxicity in animals, the comprehensive gene

Cardiovasc Toxicol Table 1 The associated genes in the top 10 KEGG pathways significantly (P \ 0.1) altered in the TCDD-treated HUVECs KEGG pathway

Count

%

P value

Genes

Endocytosis

25

0.18

0.01

PRKCZ, PARD3, CLTB, LDLR, EEA1, VPS37D, PIP5K1A, HSPA1L, DAB2, HSPA2, RNF103, SH3GLB1, CXCR4, GIT2, NEDD4L, AGAP2, CBL, RAB11FIP4, EPS15, ADRB2, ADRB1, NEDD4, RAB11FIP1, ARAP2, EPN1

Dilated cardiomyopathy

15

0.11

0.01

TNF, ADCY6, DAG1, ITGB4, ITGA1, ITGA2, ITGB3, TPM1, ITGB1, TPM3, ADRB1, ATP2A2, ITGAV, DMD, PRKACB

Arrhythmogenic right ventricular cardiomyopathy (ARVC)

13

0.09

0.01

DAG1, ITGB4, ITGA1, ITGA2, GJA1, LEF1, ACTN2, ITGB3, ITGB1, ATP2A2, ITGAV, DMD, DSP

Vascular smooth muscle contraction

16

0.11

0.03

MYL6, KCNMB3, KCNMB4, ADORA2A, CALD1, PPP1R12B, ADCY6, NPR1, PRKCD, ARHGEF11, ITPR2, PRKCQ, GNAQ, PPP1R12A, PRKACB, PLCB1

ECM-receptor interaction

13

0.09

0.03

HSPG2, DAG1, ITGB4, ITGA1, ITGA2, ITGB3, ITGB1, HMMR, LAMB2, CD44, LAMA5, ITGAV, AGRN

Hypertrophic cardiomyopathy (HCM)

13

0.09

0.03

TNF, PRKAG2, DAG1, ITGB4, ITGA1, ITGA2, ITGB3, TPM1, ITGB1, TPM3, ATP2A2, ITGAV, DMD

Inositol phosphate metabolism

9

0.06

0.06

ISYNA1, IMPA2, PIK3C2A, PI4KA, PLCD1, INPP5E, INPP4A, PIP5K1A, PLCB1

12

0.09

0.06

CCNE2, LAMB2, LAMA5, ITGAV, SKP2, TP53, ITGA2, APAF1, BIRC3, BIRC2, ITGB1, AKT3

Small cell lung cancer Notch signaling pathway Apoptosis

8

0.06

0.07

NOTCH2, EP300, APH1A, NUMB, CREBBP, MAML3, RBPJ, NCOR2

12

0.09

0.07

IRAK4, TNF, MYD88, ENDOG, IL1RAP, TP53, IL1B, APAF1, PRKACB, BIRC3, BIRC2, AKT3

networks to clarify the underlying mechanisms of chronic CVDs induced by TCDD were not explored. In this study, we analyzed global gene expression profiles in TCDDexposed HUVECs by high-throughput sequencing and tried to predict the gene networks involved in TCDD-associated chronic CVDs. The use of a high-throughput RNA sequencing approach to measure gene expression levels greatly increased our ability to quantitatively detect mRNA levels in a relatively unbiased manner. We chose 10–40 nM concentrations of TCDD to treat HUVECs, which is similar to treatment of CD34? hemopoietic cells as previously described [11]. We revealed the top 10 altered genes in endothelial cells induced by TCDD at different dosages. Among these genes, RTN4 may be a candidate modulator in vascular cell apoptosis and atherosclerosis [27] and vascular remodeling response to injury [28]. Among those down-regulated genes, SLC39A8 is negatively associated with blood pressure and has been associated with high-density lipoprotein cholesterol levels [29]. Therefore, RTN4 and SLC39A8 might be potential target genes involved in TCDD-associated chronic CVDs such as atherosclerosis and hypertension. The results of GO functional analysis showed 1,838 DEGs were strongly enriched in the regulation of transcription, RNA metabolic process, and intracellular signaling cascade and , interestingly, in the regulation of cell proliferation, programmed cell death, and apoptosis. Moreover, apoptosis, endothelial cell dysfunction, and lipid metabolic disorder were the main pathological changes of

CVDs associated with TCDD. Atherosclerosis is considered a chronic inflammatory disease of the vessel wall characterized by chemokine-driven mononuclear cell recruitment entering the subendothelial space where the cells differentiate into macrophages [30]. Vascular endothelial cell apoptosis has been implicated in the pathophysiology and progression of atherosclerosis [31]. Therefore, the GO annotation indicated that TCDDresponsive DEGs might be implicated in the CVDs development by inducing apoptosis. TCDD toxicity has been linked to atherosclerosis, hyperlipidemia, and hypertension [32, 33]. Through the FunDO analysis, our data verified the altered genes related to atherosclerosis, hyperlipidemia, and hypertension in TCDD-treated endothelium cells. In addition, we also uncovered the DEGs related to pathogenesis of heart failure, thromboangiitis obliterans, PAH, and aortic aneurysm, indicating that TCDD exposure may increase the risk for heart failure, thromboangiitis obliterans, PAH, and aortic aneurysm. TCDD toxicity is believed to drive specific gene transcription via activation of the AHR. The AHR is a cytosolic protein with high affinity for TCDD and other PHAHs. Upon ligand activation, the AHR translocates into the nucleus, dimerizes with ARNT, binds to dioxin responsive elements (DRE) in the upstream regions of regulated genes, and modulates gene expression [34]. In our study, RNA-seq results showed that the transcript levels of AHR, AHRR, AIP, ARNT, ARNT2, CYP1A1, CYP1B1, GSTM3, GSTM4, and NQO1 were all up-

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Cardiovasc Toxicol Table 2 The expressions of genes participated in the chronic CVDs-related biological pathway in the TCDD-exposed HUVECs Biological pathway

P value

Biological pathway

P value

Biological pathway

P value

Biological pathway

P value

Biological pathway

P value

0.04

IL6a

0.00

CALM2

0.00

PRKCZa

0.01

PDK1a

0.03

0.05

LDLR

0.01

CALM3

0.09

PSEN1

0.04

PIK3AP1a

0.00

AIPa

0.01

SOAT1

0.01

CCL5a

0.00

PSENENa

0.03

PIK3C2A

0.01

ARNTa

0.07

Matrix metalloproteinases

CREBBP

0.03

SGCB

0.00

PIK3C2Ba

0.02

CX3CL1a

0.00

SOCS1a

0.06

PIK3C3a

0.05

DECR1

0.07

SOS1

0.08

PIK3CA

0.01

AHR AHRa AHRR

a

ARNT2a

0.08

TIMP1a

a

0.03

Metabolic syndrome

CYP1B1a

0.03

TNFa

GSTM3a

0.09

PPARa pathway

GSTM4a

0.06

SRA1a

CYP1A1

a

NQO1

0.00

TNF

0.01 0.00

a

EDN1

0.05

SOS2

0.02

PIK3CB

0.05

FGF1

0.03

STAT5Aa

0.01

PIK3CDa

0.01

0.09

FGF2

0.04

TGFB1a

0.00

PIK3R1

0.07

0.00

FGF5

0.00

TRPC3

0.00

PIK3R2a

0.00

GRB10a

0.01

VEGFAa

0.00

PIK3R4

0.00

0.06

PLA2G15

0.06

PLA2G4Ca

0.08

Atherosclerosis

Prostaglandins, leukotrienes

Acute inflammation

ALOX5AP

0.06

GRB7a

0.07

ZHX2a

CSF1a

0.04

GTF2E2a

0.08

Thrombosis

C3a

0.00

a

a

IL6

0.00

IL6

TNFa

0.00

Th1/Th2 development

0.00

CD40a

Apoptosis

0.05

CD40a

0.05

TNFa signaling

TNFa

0.00

TNFa

TNFRSF1A

a

0.02

B cell activation

0.00

TNFRSF1A

a

0.02

Hypertension

a

a

HSPG2

0.01

AKT1

0.01

PLA2G6

0.06

IL6a

0.00

ARHGEF10

0.04

PLCB1a

0.01

JUN

0.05

ARHGEF10La

0.08

PLCB3a

0.00

MAML1

0.05

ARHGEF11a

0.00

PLCB4a

0.01

MAP2K1

0.09

ARHGEF12

0.04

PPP1R10a

0.01

a

a

0.05

MAPK1

0.00

ARHGEF16

0.00

PPP1R11

MMP15a

0.00

ARHGEF17a

0.00

PPP1R12A

0.04

0.02

PPP1R12Ca

0.05

HMOX1

0.03

ADRB1

0.01

MMP17a

0.01

ARHGEF3

IL6a

0.00

ADRB2

0.01

MMP19a

0.02

ARHGEF35

0.02

PPP1R13Ba

0.08

a

0.08

PPP1R13La

0.09

a

TNF

0.00

Cytokine network

ECE1

0.03

MMP3

0.02

ARHGEF4

EDN1

0.05

NCSTN

0.03

ARHGEF40a

0.00

PPP1R14Ba

0.01

PDGFAa

0.01

ARHGEF5

0.01

PPP1R15Aa

0.04

0.00

EGFR

0.05

PPP1R16Aa

0.01

0.00

GNA12

0.01

PPP1R1Ca

0.01

IL6a

0.00

Myocardial infraction

TNFa

0.00

COL4A1a

Glycolipid metabolism LIPCa PAFAH1B3

a

PIK3AP1

0.01

COL4A5a

0.00

PIK3C2A

0.01

GNA13

0.01

PPP1R3C

0.02

0.00

HSPG2

0.01

PIK3C2Ba

0.02

GNAQ

0.04

PPP1R7a

0.02

PLATa

0.04

PIK3C3a

0.05

ITGA1

0.00

PPP1R8

0.07

a

0.08

PIK3CA

0.01

ITGA2Ba

0.09

PRKCA

0.09

0.01

PIK3CB

0.05

ITGA3a

0.03

PRKCDa

0.00

a

HMOX1

0.03

PROC

IL6a

0.00

PROS1

TNF

0.00

Inflammatory response CSF1a a

PDGFBa

0.01

COL4A2

IL-10 signaling

a

0.02

a

TFPI

a

0.02

0.01

ITGAE

0.06

PRKCQ

0.02

PIK3R1

0.07

ITGAV

0.00

PRKCZa

0.01

0.06

PIK3R2a

0.00

ITPR2

0.02

PTK2

0.02

Pulmonary arterial hypertension 0.04

ADAM17 a

PIK3CD

a

a

IL1B

0.04

AKT1

0.01

PIK3R4

0.00

ITPR3

0.00

ROCK1

0.01

IL6a

0.00

ALDH7A1a

0.00

PRH2

0.04

MAP2K1

0.09

RPS6KB1

0.03

TNFa LDLR pathway

0.00

APH1Ba BMP6

0.07 0.07

PRKCA PRKCDa

0.09 0.00

MAP2K2a MAPK1

0.00 0.00

SHC1a SOS1

0.01 0.08

123

Cardiovasc Toxicol Table 2 continued Biological pathway

P value

Biological pathway

P value

Biological pathway

P value

Biological pathway

P value

Biological pathway

P value

CSF1a

0.04

CALM1a

0.09

PRKCQ

0.02

MPRIP

0.07

SRCa

0.01

Note: The superscript ‘‘a’’ indicates the gene expressions were up-regulated significantly (P \ 0.1) by TCDD treatment, while no any superscript indicates the genes expressions were down-regulated significantly (P \ 0.1) by TCDD treatment

Table 3 Expression levels of well-established endothelial markers in the HUVECs treated by TCDD (P \ 0.05)

Gene

mRNA expression Control

10 nM

Log2(T10/C)

ANGPT2

0.02

0.02

0.01

0.02

PDGFA

2.69

2.57

-0.07

2.93

0.12

4.17

0.63

0.01

FGFR4

6.47

4.29

-0.59

4.76

-0.44

7.24

0.16

0.42

ICAM2 ENG

0.17 17.52

0.11 18.20

-0.60 0.05

0.11 16.08

-0.60 -0.12

0.05 16.89

-1.80 -0.05

0.31 0.59

ICAM3

4.06

4.73

0.22

3.14

-0.37

4.17

0.04

0.09

THBD

1.28

1.38

0.12

1.35

0.08

1.14

-0.17

0.68

regulated by TCDD stimulation. qRT-PCR data further confirmed that the expression of AHR, AHRR, CYP1A1, COX2, and NQO1 in HUVEC and MLEC all increased with TCDD exposure. The CYP1B1 transcript was upregulated only in MLEC. These results are in agreement with previous data [26, 35]. It was notable that the mRNA expression levels of some genes were not TCDD dose dependent. The RNA-seq data showed that expression alterations in 783 genes out of 1,838 DEGs were TCDD dose dependent, but the others were not. These results obtained in HUVECs and MLECs are analogous to those from fetal heart of murine administrated by TCDD [12]. The regulatory effects of TCDD on expression of different genes, such as COX2, AHR, and AHRR in HUVECs, might be due to different transcriptional signaling or gene networks [36]. Vogel et al. [37] demonstrated that the mRNA levels of COX2, IL-1b, and TNFa increased in U937 macrophages treated with TCDD in a time- and dosedependent manners, accompanied by significantly elevated levels of matrix-degrading metalloproteinases (MMP)-1, MMP-3, MMP-12, and MMP-13 through screening expression patterns of typical genes involved in atherosclerosis and foam cell generation. Wu et al. [38] found that exposure of ApoE-/- mice to TCDD causes a timedependent progression of atherosclerosis, which is associated with induction of interleukin (IL)-8 as well as F4/80 and MMP-12. Treatment with a C-X-C chemokine receptor type 2 (CXCR2) inhibitor reduced the TCDD-induced progression of early atherosclerotic lesions in ApoE-/mice. We also found the expression of IL-1b and TNFa could be up-regulated by TCDD in HUVECs and observed

20 nM

Log2(T20/C) -0.03

40 nM 0.02

Log2(T40/C) 0.01

P value 0.79

alterations of other genes associated with atherosclerosis by TCDD treatment. CSF-1, which is known to be present in atherosclerotic lesions, may contribute to plaque progression [39]. We observed enhanced CSF-1 expression with TCDD stimulation. In addition, many epidemiological and animal studies have shown TCDD exposure results in hypertension [40, 41]. Sustained AHR activation by TCDD increases blood pressure and induces cardiac hypertrophy, which may be mediated by increased superoxide. Increased aortic superoxide results in endothelial dysfunction as demonstrated by significant impairment of acetylcholineinduced vasorelaxation in TCDD-exposed mice, which was restored by tempol, a superoxide dismutase (SOD) mimetic [42]. ADRB1, ADRB2, ECE1, and EDN1 can make blood pressure go down by regulation of natriuretic peptide (NPP) A, NPPB, or NPPC [19]. We found the expression of ADRB1, ADRB2, ECE1, and EDN1 was down-regulated by TCDD, which possibly contributes to the hypertensive response to TCDD. Our data revealed a potential pathway to explain hypertension induced by TCDD, which differs from previous studies focusing on the reactive oxygen species (ROS) pathway. Finally, the data presented in Table 2 indicate the possible gene networks involved in the regulation of thrombosis, MI, and PAH related to TCDD exposure, and we uncovered many interesting genes. For example, the expression of COL4A1 and isoforms increased significantly after TCDD exposure. Previous single nucleotide polymorphism (SNP) mutation findings demonstrate that COL4A1 is associated with coronary heart disease [43] and brain small-vessel disease with hemorrhage. Therefore, it is possible that COL4A1 is involved in

123

Cardiovasc Toxicol

123

Cardiovasc Toxicol b Fig. 5 AHR-targeted genes in TCDD-treated HUVECs and MLECs

were validated. The relative mRNA levels of AHR (a), AHRR (b), ARNT (c), COX1 (d), COX2 (e), CYP1A1 (f), CYP1B1 (g), NQO1 (h) in HUVECs, and MLECs treated by different doses of TCDD were analyzed by qRT-PCR. Results were normalized to the GAPDH internal control and presented as relative expression level calculated by the 2DDCt method. All data in the treatment group were normalized to those values in the control group. All data were expressed as mean ± SEM for n = 4–6

the formation of MI associated with TCDD. Growth factor signaling, notch signaling, and inflammation reaction play important roles in the development of PAH induced by vascular remodeling [17]. We found enhanced PDGF and Stat5 expression with TCDD treatment in endothelial cells, which could activate PI3 K and notch signaling and lead to smooth muscle cell proliferation and migration. AKT is a serine–threonine kinase that contributes to signaling and activation responses of human platelets, and it supports thrombus formation in mouse models [44]. In our study, the AKT signaling pathway was activated in HUVECs after TCDD exposure, indicating that TCDD implicated in thrombosis formation through regulating the AKT signaling pathway. TCDD has been demonstrated to alter endothelial function and extracellular matrix proteins expression. Specifically, four genes involved in angiogenesis are consistently down-regulated by TCDD treatment: endothelin-3 gene (EDN3), fibroblast growth factor 1 (FGF1), mesenchyme forkhead 1 (FOXC2), and basic helix-loophelix transcription factor (HAND2) [11]. In our study, we indeed found FGF1 decreased in HUVECs exposed to TCDD. In addition, Wikenheiser et al. [45] showed that hypoxia-inducible factor 1 (HIF-1) a levels and thus HIF1 signaling in the developing myocardium can be reduced by TCDD treatment in vivo during critical stages in chick heart morphogenesis and coronary vessel development. This inadequate HIF signaling could in turn lead to the misexpression of HIFs and abnormal coronary vasculature development. Pelclova´ et al. [32] found that microvascular reactivity in subjects with long-term high TCDD exposure decreased significantly and progressively using laser-Doppler flowmetry. Biochemical analysis of Cu, ZnSOD, E-selectin, ICAM-1, and inhibitor of tissue plasminogen activator (PAI-1) supplied the evidences for the presence of endothelial dysfunction and oxidative stress in these subjects. We observed alterations with TCDD treatment in the transcript levels of many other genes probably related to endothelial functions. Whether TCDD had relation with endothelial dysfunction by modulation of these genes expression levels needs to be explored further. Taken together, we examined global gene expression profiles in HUVECs treated with different doses of TCDD

and systematically analyzed potential gene networks and signal pathways involved in TCDD-associated CVDs. Endothelial dysfunction is the hallmark of many CVDs such as atherosclerosis, PAH, and hypertension. Given the high prevalence of environmental or occupational TCDD exposure and the increased risk of CVDs, our findings will provide new clues for further investigation of the underlying mechanisms and allow for further exploration of better intervention for TCDD-associated CVDs. Acknowledgments This work was supported by grants from the Ministry of Science and Technology of China (2012CB945100, 2012BAK01B00), and the National Natural Science Foundation of China (81030004, 31371154), NSFC-CIHR joint grant (NSFC81161120538 and CIHR-CCI117951), The Knowledge Innovation Program of the Chinese Academy of Sciences (KSCX2-EW-R09). Y.Y. was supported by the One Hundred Talents Program of the Chinese Academy of Sciences (2010OHTP10). He is a Fellow at the Jiangsu Collaborative Innovation Center for Cardiovascular Disease Translational Medicine.

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