Introduction

Parkinson’s disease (PD) is one of the most common neurodegenerative diseases worldwide, second only to Alzheimer’s disease. The incidence, which increases with age, is 1–2% in the population over 65-year-old and 4% for people over 85-year-old1. With rising population, China has entered an aging society, and the morbidity of PD will increase constantly and undoubtedly be a serious burden to the economy. However, the pathogenesis of PD is not completely clear.

Fine particulate matter (PM2.5) is the main pollutant that causes haze weather. With the rapid development of the economy, haze pollution has gradually developed into a prominent environmental problem in China. However, it was not until recently that people realized the seriousness of PM2.5 pollution. Animal trials indicate that the olfactory mucosa may be an entry route for air pollutants to disturb the blood–brain barrier and negatively affect the central nervous system (CNS)2,3. Considerable evidence supports a link between PM2.5 exposure and the development of CNS diseases, including PD and other neurodegenerative diseases4,5,6,7,8. Wang’s study showed that exposure to PM2.5 aggravated the symptom of PD in rotenone-treated mouse by inducing the dysfunction of mitochondria and PINK1/Parkin signaling pathways were involved in the aggravative effects of PM2.59. In addition, both Zanobetti’s and Hyewon Lee’s research indicated that PD patients required hospitalization after short-term exposure to elevated PM2.5 levels10,11.

Various PD-related genes have been identified, and knowledge about the genetics of PD has exploded12. The first gene associated with PD was identified in 1997 as a missense mutation in the α-synuclein (SNCA) gene; the gene is regulated by DNA methylation and the missense mutation increases the risk of PD13. The phosphatase and tensin homologue-induced putative kinase 1 gene (PINK1)14 and the DJ-1 gene15 are also closely related to the pathogenesis of PD. The PINK1 and DJ-1 genes16 protect mitochondrial from oxidative stress, and their downregulation aggravates the oxidative stress response and promote apoptosis. The DJ-1 gene can be regulated by DNA methylation. DNA methylation, a common type of epigenetic modification, has an important function in the pathogenesis of PD. DNA methylation can silence gene expression, thereby reducing the protective effects of genes and promoting the progress of PD. Nevertheless, it remains unclear whether PM2.5 alters DNA methylation and thereby aggravates the pathogenesis of PD by regulating expression of key genes such as PINK1 and DJ-1. Study of potential gene expression changes can provide better understanding of the disease itself and may become a therapeutic target for treatment.

In this study, we evaluated the impact of PM2.5 on expression and methylation of the key PD-related genes PINK1 and DJ-1. We measured the impact of PM2.5 on dopaminergic neurons in the substantia nigra (SN). In addition, we induced PD in rats by treating with rotenone and assessed aggravation of PD by PM2.5 in these rats. Then, we measured expression and methylation of PINK1 and DJ-1 in SN after different times of exposure to PM2.5. Finally, we verified the animal results with SH-SY5Y cells and measured the effect of PM2.5 on misregulation of DNA methylation of the PINK1 and DJ-1 genes.

Results

PM2.5 concentration description

To observe the effects of PM2.5 on animals over different time periods, we monitored atmospheric PM2.5 concentrations at 3, 6 and 12 months and found that the average daily concentrations of PM2.5, which was 54.16 μg/m3 during the first 3-month period, 52.58 μg/m3 in the 6-month period, and 44.64 μg/m3 in the 12-month period. Figure 1a shows the level of average concentration of PM2.5 monitored using an individual particle monitor. All animals in the PM2.5 group were exposed to PM2.5 levels above China’s national air quality standard (15 µg/m3) and the World Health Organization guideline (5 µg/m3).

Fig. 1
figure 1

The average concentration of PM2.5 was higher than NAAQS and PM2.5 resulted the lower body weight. (a) The level of average concentration of PM2.5 monitored using an individual particle monitor. (b) Rat body weight gained every month in both groups (n = 20). *p < 0.05 compared to control, **p < 0.01 compared to control.

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Effects of PM2.5 on body weight

The animal weights were monitored monthly, and the results showed that the PM2.5 group experienced a significant decrease in weight gain from Month 1 to Month 9 compared to the FA group (Fig. 1b). However, there was no significant difference in weight gain between the two groups from Month 10 to Month 12.

PM2.5 accelerated the loss of dopaminergic neurons in the substantia nigra of PD rat model

The average value of filtered air-exposed and vehicle-administered in each month was used as the control benchmark (100%). Compared with the filtered air-exposed, TH-positive cells were significantly decreased by 6.49% in the PM2.5-exposed; compared with the vehicle-administered, TH-positive cells were significantly decreased by 22.16% in the rotenone-administered at 3 months (Fig. 2a and b). Compared with the filtered air-exposed, TH-positive cells were significantly decreased by 5.23% in the PM2.5-exposed; compared with the vehicle-administered, TH-positive cells were significantly decreased by 52.99% in the rotenone-administered at 6 months (Fig. 2c and d). Compared with the filtered air-exposed, TH-positive cells were significantly decreased by 12.24% in the PM2.5-exposed; compared with the vehicle-administered, TH-positive cells were significantly decreased by 60.17% in the rotenone-administered at 12 months (Fig. 2e and f).

Fig. 2
figure 2

PM2.5 accelerated the loss of dopaminergic neurons in the SN. TH expression in SN sections was assessed by immune-histochemistry. (a, c, e) Immune-histochemistry staining results for 3, 6, and 12 m. (b, d, f) Quantitative analysis of TH-positive neurons. Statistical analysis was performed by two-way ANOVA.

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3 months: PM2.5-exposed (n = 12) vs filtered air-exposed (n = 12): F (1, 20) = 16.21, P = 0.0007;

rotenone-administered (n = 12) vs vehicle-administered (n = 12): F (1, 20) = 189.1, P < 0.0001; interaction effect: F (1, 20) = 0.3146, P = 0.5811.


6 months: PM2.5-exposed (n = 12) vs filtered air-exposed (n = 12): F (1, 20) = 3.299, P = 0.0844;

rotenone-administered (n = 12) vs vehicle-administered (n = 12): F (1, 20) = 338.1, P < 0.0001; interaction effect: F (1, 20) = 0.9893, P = 0.3318.


12 months: PM2.5-exposed (n = 12) vs filtered air-exposed (n = 12): F (1, 20) = 34.50, P < 0.0001;

rotenone-administered (n = 12) vs vehicle-administered (n = 12): F (1, 20) = 833.9, P < 0.0001; interaction effect: F (1, 20) = 0.03124, P = 0.8615.


Significance of pairwise comparisons (n = 6): ns = non-significant; *p < 0.05; **p < 0.01; **p < 0.001; **p < 0.0001.

PM2.5 decreased the levels of DJ-1 and PINK1 mRNAs in PD rat model

To determine whether exposure to PM2.5 affected the mRNA levels of PINK1 and DJ-1, we measured PINK1 and DJ-1 mRNAs in the SN. Real-time RT-PCR results showed that 3 months of exposure induced a 60% reduction in PINK1 compared with the FA group (Fig. 3a), whereas there was no difference in DJ-1 mRNA level (Fig. 3b). However, when the exposure time was increased to 6 months, the reduction in PINK1 mRNA level was nearly 75% (Fig. 3c), and a significantly greater reduction (nearly 50%) was also found in DJ-1 (Fig. 3d). We observed still further reductions of mRNA levels of PINK1 and DJ-1 after 12 months of exposure (Fig. 3e and f).

Fig. 3
figure 3

PM2.5 down-regulated the transcription of PINK1 and DJ-1 genes in rats’ model. The mRNA levels of both genes were assessed by real-time RT-PCR. (a, c, e) The transcription level of PINK1 gene at 3, 6 and 12 m in control and PM2.5 groups. (b, d, f) The transcription level of DJ-1 gene at 3, 6, and 12 m in both groups. Statistical analysis was performed by ANOVA. Significance (n = 8): *p < 0.05 compared to control, **p < 0.01 compared to control, ***p < 0.001 compared to control.

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PM2.5 resulted in hypermethylation of CpG islands in PINK1 and DJ-1 genes in PD rat model

By using the UCSC Genome Browser database, we found typical CpG islands around the promoters of the rat PINK1 and DJ-1 genes. There were 55 CG sites within the entire length of the CpG islands of both genes (Fig. 4a and e). Methylation status of the CpG islands was determined by bisulfite sequencing. Exposure to PM2.5 for 6 months resulted in a 6.06% increase in methylation of the PINK1 gene compared with 2.42% for the control (Fig. 4c). For the DJ-1 gene, 6 months of exposure resulted in an increased methylation level from 2.4–7.27% (Fig. 4g). For 12 months exposure to PM2.5, the methylation level was further increased, reaching 9.30% and 12.73% in the PINK1 and DJ-1 genes, respectively (Fig. 4d and h); 3 months exposure to PM2.5 had no effect on the methylation level on both genes (Fig. 4b and f).

Fig. 4
figure 4

The CpG islands and 5’ up-streamed region around PINK1 and DJ-1 promoters in rats. Methylation status of the CpG islands was analyzed using Bisulfite sequencing. (a, e) 55 CpG sites in the CpG islands of PINK1 and DJ-1, respectively. (b, c, d) Methylation level of PINK1 CpG islands at 3, 6, and 12 m in both control and PM2.5 groups. (f, g, h) Methylation level of DJ-1 CpG islands. Significance (n = 5): *p < 0.05 compared to control, **p < 0.01 compared to control.

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DEP resulted in decreased cell viability in PD cell model

We treated human neuroblastoma SH-SY5Y cells with DEP at 2.5, 5, 10, 20, 40, 80, 160, and 320 μg/ml for 24 h. The LD50 (median lethal dose) was 40 μg/ml by viable cells counting (Fig. 5a) and LDH assay (Fig. 5b).

Fig. 5
figure 5

DEP reduced cell viability Optimal PM2.5 treated concentration was determined in SH-SY5Y cells by evaluating cell viability and cytotoxicity with viable cells counting and LDH assays, respectively. (a, b) Cell viability and cytotoxicity were detected in SH-SY5Y cells with viable cells counting (a) and LDH (b) assays. Significance (n = 3): *p < 0.05 compared to control, **p < 0.01 compared to control, ***p < 0.001 compared to control. DEP: Diesel exhaust PM2.5.

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DEP repressed transcription of PINK1 and DJ-1 genes in PD cell model

In the forgoing animal study, we found that PM2.5 resulted in a decrease in expression of the PINK1 and DJ-1 genes. To confirm this effect in vitro, we performed quantitative RT-PCR to measure the PINK1 and DJ-1 mRNA levels in SH-SY5Y cells. Under the condition of DEP concentration of 40 g/ml, the level of PINK1 mRNA was significantly reduced at 6 h and 24 h (Fig. 6a), while the level of DJ-1 mRNA was also significantly reduced at 24 h (Fig. 6b).

Fig. 6
figure 6

DEP down-regulated the transcription of PINK1 and DJ-1 genes in SH-SY5Y cells. SH-SY5Y cells were treated with 40 μg/ml of PM2.5 for 1.5, 6, and 24 h. The mRNA levels of PINK1 (a) and DJ-1(b) were assessed by real-time RT-PCR. Statistical analysis was performed by ANOVA. Significance (n = 3): *p < 0.05 compared to control, **p < 0.01 compared to control, ***p < 0.001 compared to control. DEP: Diesel exhaust PM2.5.

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DEP resulted in hypermethylation of CpG islands in PINK1 and DJ-1 genes in PD cell model

Using the UCSC Genome Browser database, we identified 69 and 55 CG sites in the entire length of human PINK1 and DJ-1 CpG islands (Fig. 7a and c). Compared with the methylation level of the control group (2.42%), after 6 and 24 h of DEP treatment, the methylation level of the PINK1 gene significantly increased to 6.28% and 11.59%, respectively (Fig. 7b). Likewise, in comparison with the methylation level of the control group (1.82%), the methylation level of the DJ-1 gene significantly rose to 8.48% after 24 h of DEP treatment (Fig. 7d).

Fig. 7
figure 7

The CpG islands and 5’ up-streamed region around PINK1 and DJ-1 promoters in human cells. Methylation status of the CpG islands was analyzed using Bisulfite sequencing. (a, c) 69 and 55 CpG sites in the CpG islands of PINK1 and DJ-1, respectively. (b, d) Methylation level of PINK1 and DJ-1 CpG islands at 1.5, 6 and 24 h treated DEP. Significance (n = 3): *p < 0.05 compared to control, **p < 0.01 compared to control. DEP: Diesel exhaust PM2.5.

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Discussion

Epidemiological studies indicate that exposure to PM2.5 is associated with an increased risk of developing Parkinson’s disease and other neurological disorders6,17. Despite extensive research on the relationship between PM2.5 and Parkinson’s disease, the underlying molecular mechanisms remain largely unexplored. Therefore, our objective was to elucidate the mechanisms through which PM2.5 exacerbates Parkinson’s disease. In this study, we provide robust evidence that PM2.5 can accelerate development of PD. The effect is based on the dysregulation of key PD-related genes, notably PINK1 and DJ-1. Further, abnormal gene expression may be related to increased DNA methylation. First, we found that PM2.5 caused the loss of dopaminergic neurons in the SN. The neurotoxin rotenone can damage dopaminergic neurons, and PM2.5 can lead to further dopaminergic neurons loss induced by rotenone. Second, PM2.5 decreased PINK1 and DJ-1 expression and increased methylation of the CpG islands of the PINK1 and DJ-1 genes. Third, treating SH-SY5Y cells with DEP produced similar effects as observed in animal experiment.

Our study shows that the weight of the PM2.5 group significantly decreased during the first to ninth month, which is consistent with previous research findings. In an animal experiment using C57BL/6 J mice as in vivo models, the researchers administered PM2.5 (2.5 mg/kg, inhalation) and rotenone (30 mg/kg, intraperitoneal injection) to the mice for 28 days9. The study found that the weight of the rotenone group mice was significantly lower than that of the control group from 4 to 28 days. Furthermore, there was a significant difference between the rotenone group and the PM2.5 + rotenone group, indicating that PM2.5 affects the body weight of PD mice. Although the observation period was only 28 days, the result is consistent with our findings. The potential mechanism by which PM2.5 affects body weight may involve metabolic disorders caused by air pollution, which are closely related to body weight18. However, in epidemiological studies, the impact of air pollution on weight remains highly controversial and may vary depending on factors such as gender, age group, and type of air pollutant19,20,21. Therefore, further in-depth research is needed to clarify this issue.

Previous studies have indicated that PM2.5 can trigger neuroinflammation, leading to the loss of dopaminergic neurons and the formation of Lewy bodies, while inducing mitochondrial dysfunction to stimulate the production of reactive oxygen species (ROS), thereby aggravating neuronal damage9,22,23,24. In this study, we found that, similar to neurotoxin rotenone, PM2.5 causes the loss of dopaminergic neurons in the SN, and PM2.5 can further exacerbate the loss of dopaminergic neurons caused by rotenone. In addition, similar studies have observed that short-term PM2.5 exposure can worsen animal behavior9, but this aspect was not tested in our study. Therefore, the behavioral changes caused by long-term exposure to PM2.5 still need further investigation.

Our study found that exposure to PM2.5 also leads to the loss of dopaminergic neurons, as well as downregulation of PINK1 and DJ-1 mRNA expression. Previous studies have found that the loss of dopaminergic neurons is correlated with low expression of PINK1. In previous studies on animals, cells, and organoids, PINK1 deficiency impairs adult neurogenesis of dopaminergic neurons25,26,27. In a robust vertebrate model of PINK1 deficiency, the PINK1-/- zebrafish, Th1 + neurons of the TPp and PVO are found in comparable numbers to those in young adult wild-type fish, but thereafter showed a significant decline25. Similarly, impaired dopaminergic neurogenesis was observed in human tissue organoid models with PINK1 deficiency25. PINK1 and NOTCH interact non-classically in mitochondria, and PINK1 deficiency significantly inhibits the proliferation of human neural stem cells (NSCs)26. Growth inhibition was also observed in mouse PINK1 knockout NSCs, which was associated with mitochondrial dysfunction32. For DJ-1, previous studies have shown that reducing DJ-1 expression can affect the function of dopaminergic neurons, and the dopaminergic neurons in the substantia nigra of DJ-1 mutant mice are functionally impaired28,29. DJ-1 protein has characteristics such as molecular chaperone, protease, glutathione peroxidase, transcriptional regulator, and DJ-1 protein prevents neurodegenerative diseases by regulating oxidative stress and mitochondrial function, as well as its role in transcription and signal transduction30,31,32. Based on the above studies, we can conclude that the downregulation of PINK1 mRNA expression leads to a decrease in the number of dopaminergic neurons, while the downregulation of DJ-1 mRNA expression affects the function of dopaminergic neurons. Therefore, we hypothesize that the loss of dopaminergic neurons observed in our study, which was caused by exposure to PM2.5, may be due to the downregulation of PINK1 mRNA expression. In addition, PM2.5-induced DJ-1 mRNA is likely to exert an influence on the function of dopaminergic neurons. Previously studies have proven that DNA methylation has been shown to be pivotal to the occurrence and development of PD33,34, including the regulatory role of PD-related genes such as α-synuclein, Parkin, PINK1, DJ-1. Yang’s study showed that CpG demethylation was induced by MPP+ mediated up-regulation of SNCA transcription in neurotoxin-induced PD35. Tarale et al. performed chronic manganese exposure of human SH-SY5Y cells and found that integration of DNA methylation data with gene expression revealed epigenetic alterations to PINK1 and Parkin genes that were critical for the onset of Parkinsonism36. Both short and long-term exposure to ambient air pollution resulted in global changes to DNA methylation37,38. In our study, we found that rats which received more than 6 months of PM2.5 exposure had elevated DNA methylation of CpG islands of the PINK1 and DJ-1 genes, and cells-based data showed that long-term (6 or 24 h) treated with DEP resulted in increased DNA methylation of CpG islands. Thus, our results confirmed that long-term exposure to PM2.5 can lead to changes in DNA methylation for some genes. Further, the decreased gene expression associated with the aforesaid treatments can be explained by increased DNA methylation.

Our study had several limitations. First, in the cell-based experiment, we did not test an inhibitor of DNA methylation such as 5-Aza to determine whether DNA methylation changes could be reversed. Second, other investigators have found that neurotoxins can induce misregulation of DNA methylation35. However, we did not determine whether rotenone itself affected DNA methylation. Third, although much evidence confirms that DNA methylation has a key function in the occurrence and development of PD, studies on specific regulatory mechanisms are still limited. For example, we did not determine which DNA methyltransferase(s) was responsible for the increased methylation of the PINK1 and DJ-1 genes or which signaling pathways were involved in the process.

In summary, our study revealed that exposure to PM2.5 leads to the loss of dopaminergic neurons in the substantia nigra, aggravates the development of PD by inducing dysregulation of DNA methylation, resulting in decreased expression of the PD-related genes PINK1 and DJ-1.

Methods

PD rat model

The animal protocols in this study were approved by the Ethics Committee for Animal Experimentation at Capital Medical University (Beijing, China), and all experimental procedures were performed in accordance with the National Institute of Health Guide for the Care and Use of Laboratory Animals. 4-week-old male Sprague–Dawley rats were purchased from Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China) and randomly distributed into PM2.5-exposed (n = 72) or filtered air (FA) groups (n = 72). Each group was subdivided into a rotenone-administered group (2 mg/kg) for 4 w (n = 36) or a vehicle-administered group (n = 36). The rats were housed in a controlled room at a temperature of 24 °C with a standard 12-h light/dark cycle and had free access to food and water. The rats were housed for 3 months, 6 months, and 12 months, respectively. The diagram of the experimental design is in Fig. 8.

Fig. 8
figure 8

The diagram of the experimental design.

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Rotenone administration

The rotenone was dissolved in DMOS and diluted in sterile sunflower oil (2% final DMSO concentration and 98% final sunflower oil concentration)39. The rotenone-administered group received supplementation of rotenone (2 mg/kg/d) for 30 days before tissue extraction respectively at 3, 6 and 12 months. The rotenone solution was given by intragastric administration. The final working concentration of rotenone is re-prepared every two days and stored in a light-protected ambient temperature environment.

Exposure to PM2.5

Animals were exposed to PM2.5 or FA for 24/7 for 3 months (from October 11, 2018 to January 10, 2019), 6 months (from October 11, 2018 to April 10, 2019), and 12 months (from October 11, 2018 to October 10, 2019) using our real-world PM2.5 exposure system described previously40. The mean daily PM2.5 concentration in each chamber was monitored by an individual portable fine particulate monitor. PM2.5 was monitored using a portable fine particulate monitor (pDR1500, Thermo Fisher Scientific Inc., USA) at Peking Union Medical College Hospital (located at 116°22′05″E, 39°54′50″N) in Beijing, China. The condition of FA rats in the experiment was the same as that of PM2.5 rats in all aspects; the difference was that the improvement of air quality caused by the placement of a high-efficiency particulate air filter in the intake valve position leads to the removal of all PM2.5 from the FA flow. The annual average PM2.5 National Ambient Air Quality Standard (NAAQS) in China was recorded.

Immunohistochemistry and quantitative image analyses

At the end of the treatment animals (n = 6/group) were sacrificed under general anesthesia induced by a combination of ketamine hydrochloride (80 mg/kg) and xylazine hydrochloride (4 g/kg) through intraperitoneal administration and transcardially perfused with 0.9% sodium saline (room temperature), followed by 4% paraformaldehyde (PFA)/phosphate-buffered saline (PBS) (pH 7.4, ice-cold). Brains were post fixed for 12 h in 4% PFA and dehydrated in 20% and 30% sucrose in PBS, respectively. Brains were frozen and sectioned coronally (30 μm) and placed into a tissue collection solution (50% 0.01 M PBS/50% glycerol) and stored at − 20 °C. The sections were permeabilized in PBS containing 0.3% Triton X-100, blocked in 5% normal horse serum, and then incubated overnight at 4 °C with an anti-TH antibody (1:2000, Sigma). After washing three times with PBS, sections were respectively incubated with a biotinylated second antibody (1:200; Zhongshan Golden Bridge Biotechnology Co., Beijing, China) and an AB work solution (1:1:100) for 30 min at 37 °C (Vector Laboratories, USA). DAB solutions (a drop of DAB to 2 ml substrate liquid) were used to visualize the antibody. Sections were fixed on slides and cover slipped with a water-soluble mounting medium. The sections were imaged with a bright-field microscope. The estimated number of TH + cells was calculated based on the neuronal count and the corresponding sampling probabilities. The quantity of TH immunoreactive cell bodies in the SN was quantified using Stereo Investigator software, Version 2017.02.2 (09/27/2017) (MBF Bioscience, USA)39,41,42. The average number of SN sections was six in a 1:6 series. The number of TH cell bodies in each counting frame was determined by focusing each part with a 20-times objective lens. The total count of TH cell bodies in each section was computed by the software. A coefficient of error below 0.10 was deemed acceptable. Quantitative results for TH cell bodies were expressed as a percentage relative to the control side. Blind statistical analysis utilizing stereology methods was conducted for each experiment.

Cell culture and DEP treatment

SH-SY5Y neuroblastoma cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM, Hyclone, Logan, UT, USA) supplemented with 10% FBS (Cat# SV30087.02, Hyclone, Logan, UT, USA), 100 IU/ml penicillin, and 100 μg/ml streptomycin (Gibco, Grand Island, NY, USA) in a 5% CO2 humidified atmosphere at 37 °C. The medium was routinely changed every 2 days, and cells were passaged every 4 days. Diesel exhaust PM2.5 (DEP, a source of fine particle pollution that contains a high proportion of ultrafine particles) was obtained from the National Institute of Standards and Technology (SRM 2975, NIST, Gaithersburg, MD, USA). According to the analysis certificate of the standard reference material 2975, the average particle size distribution of DEP2975 was approximately 1.62 µm. DEP was suspended in the DMEM cell culture medium. To minimize aggregation to the greatest extent, the particle suspension was subjected to sonication for 15 min and rotation before dilution and administration.

Cell viability

Viable cells counting: Cells were harvested and stained with 0.04% Typan blue (Life Technologies, Inc., Gaithersburg, MD, USA). Viable cells were counted under a microscope using a blood cell counter. And the cell viability (%) was determined as the number of living cells/total number of cells (viable + non-viable cells) × 100. The experiment was carried out in triplicate.

Lactate dehydrogenase (LDH) assays: The LDH assay was carried out using a cytotoxicity detection kit (Roche Diagnostics, Mannheim, Germany) according to the manufacturer’s instructions. LDH release was measured in a 100 μl aliquot of supernatant, with 100 μl preservation solution used as a blank to correct the optical density reading at 490 nm. The experiment was carried out in triplicate.

Quantitative RT-PCR analysis

To measure PINK1 and DJ-1 mRNA expression, total RNA was extracted from the SH-SY5Y cells and tissues using TRIzol reagent (Cat# 15596-026, Life Technologies, California, USA) according to the manufacturer’s instructions. The purified RNA was then reverse-transcribed into cDNA using the PrimeScript™ RT reagent Kit with gDNA Eraser (RR047B, TaKaRa). PCR primers were designed and synthesized by Invitrogen Company; the sequences are shown in Table 1. Quantitative RT-PCR analysis of the mRNA levels of PINK1 and DJ-1 was performed using the SYBR®Premix Ex Taq™ II (TliRNaseH Plus), ROX plus, (RR82LR, TaKaRa). GAPDH was chosen as the housekeeping gene. The real-time PCR program steps were: 95 °C for 5 min, 45 cycles at 95 °C for 5 s, 60 °C for 5 s, and 72 °C for 10 s, followed by 72 °C for 1 min.

Table 1 Primers used in RT-PCR.
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DNA methylation analysis

Predication of the PINK1 and DJ-1 CpG islands was performed using the UCSC Genome Browser database (http://genome.ucsc.edu/). Briefly, genomic DNA was extracted using a QIAamp DNA mini kit (Cat# 51304, QIAGEN, Hilden, Germany) according to the manufacturer’s instructions. The integrity and purity of DNA were spectrophotometrically examined according to its A260/A280 absorption. A total of 50 ng of genomic DNA from each sample was bisulfite-treated with the Methylamp DNA Modification Kit (Epigentek, Farmingdale, NY, USA). To assay methylation status, the CpG islands of PINK1 and DJ-1 were divided into three segments amplified by PCR. PCR primers were designed and synthesized by Invitrogen Company; the sequences are shown in Tables 2, 3. The quality of bisulfite conversion was evaluated using the PCR products without methyl groups as the control. The methylation status was assayed by the Sequenom Mass ARRAY platform (JIAMEI Biolab, Beijing, China). Design methylated and unmethylated primers using Meth Primer software for PCR amplification of sequence differences before and after modification. The methylation ratios were generated by Epityper software version 1.0 (Sequenom, San Diego, CA, USA). The generated data were put into the EPI 3.1 Database (EpiData Association, Odense, Denmark) and analyzed with SPSS 11.5 software (McGraw-Hill Inc, New York, NY). Methylation frequency = Number of methylation of all clones measured in each sample/total CpG of that sample35,43.

Table 2 Primers used in BSP methylation assay in rat study.
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Table 3 Primers used in BSP methylation assay in cell study.
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Statistical analyses

Statistical analysis was performed using Prism10 (GraphPad software, Inc., La Jolla, USA). Values were represented as means ± SEM. Data were analyzed using one-way ANOVA followed by a Tukey’s multiple paired comparison test as a post hoc test. A p value of < 0.05 was considered as statistically significant.