nHHDPCs (Innoprot, Biscay, Spain) were cultured in Dulbecco’s modified Eagle’s medium (Gibco Life Technologies, Grand Island, NY, USA) supplemented with 10% fetal bovine serum (Gibco Life Technologies) and 1% penicillin-streptomycin (Gibco Life Technologies) at 37°C in an atmosphere of 5% CO₂. PPD was purchased from Sigma-Aldrich (St. Louis, MO, USA).

Cell viability was monitored using the water-soluble tetrazolium salt (WST-1) assay (EZ-Cytox Cell Viability Assay kit; ITSbio, Seoul, Korea). A total of 5×10³ nHHDPCs were seeded into 96-well plates and treated with various concentrations of PPD (0, 100, 200, 300, 400, 500 and 600 μM) for 24 h. Following treatment, nHHDPCs were mixed with 10 μl WST-1 solution and incubated at 37°C for 0.5 h. Cell viability was then determined by measuring absorbance at 450 nm using an iMark plate reader (Bio-Rad Laboratories, Inc., Hercules, CA, USA).

The cell cycle was analyzed using PI (Sigma-Aldrich) staining of DNA. nHHDPCs were plated and treated with various concentrations of PPD (0, 200, 400 and 600 μM) for 24 h. Cells were then trypsinized (using 0.25% trypsin-EDTA; Gibco Life Technologies), centrifuged (3,500 × g, 2 min), washed with phosphate-buffered saline (PBS; Gibco Life Technologies) and fixed in 70% ethanol (Merck Millipore, Darmstadt, Germany) at 4°C for 3 h. The fixed cells were incubated with staining solution [50 μg/ml PI, 0.1 μg/ml RNase (Life Technologies, Grand Island, NY, USA) and 0.05% Triton X-100 (Sigma-Aldrich) in PBS] at 37°C for 1 h and then analyzed using a FACSCalibur flow cytometer (BD Biosciences, San Jose, CA, USA). The mean PI fluorescence intensity was determined based on analysis of 10,000 cells using the FLH-2 detection channel (585±42 nm).

For the assessment of cellular senescence, nHHDPCs (2×10⁶) were seeded into 60-mm cell culture dishes and treated with 0 or 400 μM PPD. Following 48 h of treatment, cells were fixed using Fixative solution (included in Senescence Detection kit; BioVision, Inc., Milpitas, CA, USA) and senescence-associated-β-galactosidase (SA-β-gal) activity was measured using the Staining Solution Mix, including Staining Solution, Staining Supplements and X-gal substrate for (SA-β-gal) within the Senescence Detection kit, according to the manufacturer’s instructions. Cells stained for SA-β-gal were counted under a light microscope (CKX41; Olympus Corporation, Tokyo, USA) (magnification, ×200) and the percentage of SA-β-gal positive cells were calculated.

Staining for ROS in cultured cells was conducted using a 2′,7′-dichlorodihydrofluorescein diacetate (DCF-DA; Sigma-Aldrich) assay. Briefly, 2×10⁶ nHHDPCs were plated in 60-mm culture dishes and treated with PPD. Following treatment for 24 h, the cells were stained by adding DCF-DA to the culture medium to a final concentration of 20 μM and then incubating for 1 h. Distribution of the stained cell population was determined using a FACSCalibur flow cytometer.

In order to analyze the miRNA expression profile, nHHDPCs (2×10⁶) were seeded into 60-mm culture dishes and treated with 400 μM PPD. Following 24 h of treatment, total RNA was purified using TRIzol reagent (Life Technologies) according to the manufacturer’s instructions. Total RNA was dephosphorylated and labeled with pCp-Cy3 using an Agilent miRNA Labeling kit (Agilent Technologies, Inc., Santa Clara, CA, USA). Labeled RNAs were hybridized using a SurePrint G3 Human v16 miRNA 8×60K microarray (Agilent Technologies, Inc.) at 65°C for 20 h. The miRNA expression profile was digitized using Feature Extraction version 10.7 software (Agilent Technologies). Fold changes in miRNA expression levels were determined using GeneSpring GX software, version 11.5 (Agilent Technologies).

Potential target genes of PPD-regulated miRNAs were predicted using the DNA Intelligent Analysis (DIANA) microT-CDS version 5.0 bioinformatics tool (http://diana.cslab.ece.ntua.gr/). GO of each putative target gene was identified using the Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatics resource, version 6.7 (http://david.abcc.ncifcrf.gov). Target genes were categorized into four GO terms: Aging, skin development, apoptosis and cell proliferation. Furthermore, target gene-associated signaling pathways were determined using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway algorithm (http://david.abcc.ncifcrf.gov/summary.jsp) within the DAVID resource.

Values are expressed as the mean ± standard error of the mean of three independent experiments. Statistical significance was determined by Student’s t-test and P<0.05 was considered to indicate a statistically significant difference between values.

Previous studies reported that exposure to >250 μM and >60 μM PPD resulted in considerable cytotoxicity in dendritic cells (17) and keratinocytes (18), respectively. Therefore, the current study aimed to determine the cytotoxic effects of PPD on nHHDPCs at concentrations of 0, 100, 200, 300, 400, 500 and 600 μM using a WST-1-based cell viability assay. As shown in Fig. 1, the viability of nHHDPCs was significantly reduced following exposure to PPD for 24 h. Maximal toxicity was observed at 600 μM, at which concentration cell viability was reduced to 58.33±2.39% of the control value (n=3; P<0.05). The IC₂₅ (a 25% reduction in viability) of PPD was 400 μM, at which concentration cell viability was reduced to 74.42±6.08% of control value (P<0.05) (Fig. 1).

The present study investigated whether PPD-induced loss of cell viability occurred due to cell cycle arrest and cell death. Cells were treated with PPD (0, 200, 400 and 600 μM) for 24 h and the distribution of cells in the different cell cycle phases was analyzed using flow cytometry. As shown in Fig. 2, treatment with 200, 400 and 600 μM PPD led to significant accumulation in the sub-G₁ phase, compared with that of control DMSO-treated cells (P<0.05). In addition, the proportion of cells in G₁/G₂ was significantly reduced by PPD (P<0.05), indicating that PPD increased the G₂ population. These data therefore demonstrated that PPD induced cell death and G₂ arrest in nHHDPCs.

Chye et al (8) observed that PPD increased intracellular ROS and induced apoptosis in Chang normal human liver cells. Therefore, the current study investigated the effects of PPD on the regulation of intracellular ROS production in nHHDPCs. Intracellular ROS levels were determined using an DCF-DA probe, which is oxidized to fluorescent DCF in the presence of ROS. As presented in Fig. 3A, exposure to PPD resulted in a marked increase in fluorescent DCF-positive cells compared with that of the control cells, indicating that PPD increased intracellular ROS production in nHHDPCs. As ROS have been implicated in cellular senescence (19), the present study investigated whether the PPD-mediated increase in ROS was associated with increased senescence by analyzing the activity of SA-β-gal, a marker of cellular senescence. Consistent with the observed ROS increase, PPD was identified to promote an increase in SA-β-gal activity (Fig. 3B), indicating that PPD induces cellular senescence in nHHDPCs.

Fig. 2 and 3 demonstrated that cell cycle arrest in G₂ phase and PPD-mediated cell death were characterized by increased ROS production. Therefore, in order to determine whether ROS-mediated cell cycle arrest and cell death are associated with miRNA expression, miRNA microarray analysis was conducted using the SurePrint G3 Human v16 miRNA 8×60K microarray, which contained 2,006 human miRNA probes. Significant miRNAs exhibiting a ≥2.0-fold increase or reduction in expression were selected using GeneSpring GX software. As presented in Table I, PPD differentially regulated the expression levels of 74 miRNAs. Notably, 16 of 74 miRNAs were significantly upregulated and 58 miRNAs were significantly downregulated. In particular, miR-425-3p exhibited the greatest increase in expression (230.60-fold) and miR-3656 the greatest reduction (112.15-fold), compared with the corresponding miRNAs in control cells. These results suggested that the PPD-mediated cellular effects were associated with alterations in expression of specific miRNAs.

As miRNAs perform their biological functions through regulation of target mRNA translation (11), the present study aimed to predict the target genes of the miRNAs deregulated in response to PPD. The biological functions of the upregulated and downregulated genes were then determined following categorization into the four groups: Aging, apoptosis, cell proliferation and skin development, using DAVID (Tables II and III, respectively). In addition, in order to identify the specific signaling pathways of the deregulated miRNAs, the correlation between KEGG pathway-associated genes and the target genes of each miRNA were analyzed. The meaningful KEGG pathways with a value >1% (percentage of target genes/total genes involved in each pathway) were selected. The analysis identified a wide distribution of cellular functions, which are presented in Tables IV and V. The results indicated that the upregulated miRNAs were implicated in signaling pathways in cancer, ubiquitin-mediated proteolysis, melanogenesis, cell cycle, Wnt signaling, MAPK signaling, neurotrophin signaling, cell adhesion molecules (CAMs), long-term potentiation, natural killer cell-mediated cytotoxicity, calcium signaling, neuroactive ligand-receptor interactions, glycosphingolipid biosynthesis, arrhythmogenic right ventricular cardiomyopathy, axon guidance, ErbB signaling, gonadotropin-releasing hormone signaling, tight junctions and viral myocarditis (Table IV). In addition, PPD-induced downregulated miRNAs were implicated in signaling pathways in cancer, regulation of actin cytoskeleton, Wnt signaling, oocyte meiosis, glycerolipid metabolism, MAPK signaling, insulin signaling, chemokine signaling, cytokine-cytokine receptor interaction, Janus kinase-signal transducer and activator of transcription signaling, calcium signaling, mammalian target of rapamycin signaling, axon guidance, cell cycle, ubiquitin mediated proteolysis, regulation of actin cytoskeleton, ErbB signaling, melanogenesis, TGF-β signaling, vascular smooth muscle contraction, tight junction, neuroactive ligand-receptor interactions, CAMs, glycerophospholipid metabolism, adipocytokine signaling and neurotrophin signaling (Table V).