TGF-β regulates m 6 A RNA methylation after PM 2.5 exposure

doi:10.21203/rs.3.rs-1719039/v1

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TGF-β regulates m 6 A RNA methylation after PM 2.5 exposure

https://doi.org/10.21203/rs.3.rs-1719039/v1

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Atmospheric particulate matter exposure has adverse effects on human health, but its molecular mechanism is complex and need to be explored in depth over time. m⁶A RNA methylation is an important epigenetic modification that regulates gene expression at the post-transcriptional level. Our previous animal exposure studies found that PM_2.5 exposure up-regulated m⁶A RNA methylation in lung, but the regulatory pathway is currently unclear. PM_2.5 can activate transforming growth factor-β (TGF-β), and Smad2/3, a downstream factor of TGF-β, can affect m⁶A RNA methylation by binding to the RNA methyltransferase complex. Based on the above evidences, the current study aimed to investigate the role of TGF-β signal pathway in PM_2.5-induced m⁶A RNA methylation through animal and A549 cell exposure model. Our results showed that PM_2.5 could induce upregulation of m⁶A RNA methylation, accompanied by increased expression of TGF-β, Smad3, methyltransferase-like 3 (METTL3), methyltransferase-like 14 (METTL14) in both lungs of mice and A549 cell line. Furthermore, the TGF-β inhibition cellular experiments determined that PM_2.5 exposure altered the level of m⁶A RNA methylation, expression of TGF-β, Smad3. Accordingly, it is clear that TGF-β plays an indispensable role in m⁶A RNA methylation after PM_2.5 exposure. Our study demonstrates that PM_2.5 exposure influence RNA m⁶A methylation through the TGF-β signal pathway.

PM2.5

m6A

RNA methyltransferase

TGF-β

A549

Atmospheric fine particulate matter with a size of less than 2.5 µm (PM_2.5) plays a leading role in the adverse health effects(Sharma et al., 2020). Numerous epidemiological investigations have shown that PM_2.5 exposure increases the risk of cardiovascular disease and respiratory disease (Alemayehu et al., 2020). Toxicological researches have pointed out some reference pathogenesis of PM on cardiopulmonary effects, including inflammation, oxidative stress, and imbalance of the autonomic nervous system, etc. (Miller and Newby, 2019; Robertson and Miller, 2018). However, the specific molecular mechanisms and regulatory pathways of PM_2.5-induced adverse health outcomes are still being explored.

DNA methylation is a critical epigenetic modification that regulates gene expression in transcription level. Air pollution can cause acute and chronic cardiopulmonary diseases, which is determined to be involved in DNA methylation regulations (Chen et al., 2016; Shukla et al., 2019). In recently years, many studies focused on another important form of epigenetic modification, RNA methylation, which regulates gene expression at the post-transcriptional level (Meyer, 2019). N⁶-methyladenosine (m⁶A), the methylation modification of the ⁶th N of adenine on RNA, accounts for the largest proportion of RNA methylation (Yu et al., 2018). It has been well established that m⁶A RNA methylation is involved in cell apoptosis, cell proliferation and differentiation, and many other life activities(Lan et al., 2021). Our previous study showed that acute PM_2.5 exposure induced an up-regulation of RNA m⁶A levels, and increased expression of the RNA methyltransferase-like 3 (METTL3) and methyltransferase-like 14 (METTL14) in the lungs of mice(Li et al., 2019b). Besides, we also observed the dynamic and reversible process. Air purification reversed the changes in RNA m⁶A methylation and the expression of RNA methyltransferase(Li et al., 2019b).

However, the mechanisms and pathways of PM_2.5 regulation of RNA m⁶A methylation is still unclear. Bertero et al. (Bertero et al., 2018) first pointed out that activated phosphorylated Smad2/3 can enter the nucleus and bind to RNA methyltransferase complex, then induces m⁶A RNA methylation in pluripotent stem cells. Some toxicological studies have pointed out that PM exposure can induce an increase in TGF-β expression (Han et al., 2021; Kyung et al., 2012), which resulted in pulmonary fibrosis. TGF-β-Smad has been identified as a typical and important pathway that plays a role in many physiological functions. Given the above evidence, we propose the hypothesis that PM_2.5 exposure affecting downstream RNA m⁶A methylation levels through regulation of TGF-β may be a pathway to trigger adverse health effects. Therefore, this study is aimed to clarify the role of TGF-β signal pathway in PM_2.5-induced m⁶A RNA methylation. This study helps to clarify the molecular mechanism of PM_2.5 induced-adverse health endpoints and provides a scientific basis for further development of intervention measures.

2.1 Animals and ethical approval

Male C57BL/6 mice (6–8 weeks old) were purchased from the Charles river, Beijing, China. Acclimatization of mice was done in a host animal house facility for 14 days with pathogen-free cages at 24 ± 1°C and 55%-75% humidity with a 12 h light-dark cycle. Mice were provided with ad libitum commercially available diet and filtered water. The study protocol was approved by the Scientific Research Ethics Committee of Chinese Research Academy of Environmental Sciences, Beijing.

The exposure protocol was described in detail in our published article(Li et al., 2019b). Here we set the three groups of mice in the experiment: (a) the control group (Ctrl), in which mice were exposed in the chamber with high efficiency particulate air filters (HEPA) for 24 h, had a mean PM_2.5 concentration of 17.9 ± 7.8 µg/m³; (b) the PM_2.5 group (PM_2.5), in which mice were exposed to directly introduced ambient air in the chamber for 24 h, had a mean PM_2.5 concentration of 271.6 ± 84.8 µg/m³; (c) the air purification group (Reversal), mice were transferred to the Ctrl chamber after 24 hours of exposure in the PM_2.5 chamber for another 120 hours of continuous exposure, and the mean PM_2.5 concentration was 12.4 ± 4.2 µg/m³. After exposure, lungs of mice were collected and frozen in liquid nitrogen immediately for further RNA extraction.

2.2 PM_2.5 sampling and suspension preparation

PM_2.5 sampler (Dandong Better Instruments Co., Heilongjiang, China.) was set at the Chinese Research Academy of Environmental Sciences, Beijing. The sampling flow rate was 16.67 L/min. PM_2.5 were collected with Teflon membrane from November 2019–February 2020. The following is the process of PM_2.5 suspension preparation. The Teflon membranes loaded with PM_2.5 were ultrasonically extracted with ultrapure water. The mixture was then freeze-dried, and the solids were accurately weighed using a one ten-thousandth balance. Finally, the solids were mixed with DMEM medium without serum to form PM_2.5 suspension. PM_2.5 suspension was stored at 4℃ and protected from light before use.

2.3 Cell culture and PM_2.5 exposure

In this study, human lung cancer cell line A549 was used to establish a cell model. A549 cells have the advantages of easy culture and short passage period, and are widely used in PM exposure research (Sanchez-Perez et al., 2009). The A549 cell line was purchased from Shanghai Institute of Cell Biology. A549 cells were grown in DMEM (Gibco BRL, Grand Island, NY, USA) containing 10% calf serum (N-10) in a 5% CO₂ incubator at 37 ℃. The cells were seeded in a six-well plate at 1 × 10⁶ cells per well, and then were exposed to PM_2.5 suspension for 24 hours. The final concentration gradient of PM_2.5 treatment is preset to be 0, 50, 100, 200 µg/mL. The cells were collected and frozen at -80℃ for analyses after PM_2.5 exposure. All cell experiments were performed 3 times, and the results are presented as mean values ± standard deviation.

2.4 Cell membrane permeability analysis

HCS LIVE/DEAD® Green Kit (Catalog no. H10290, Invitrogen, USA) with two-color nuclear fluorescence staining assay is used to evaluate the cell viability after PM_2.5 exposure(Moore et al., 2017). The kit includes Image-iT DEAD Green™ viability stain for discrimination of dead cells and HCS NuclearMask™ Deep Red stain for total cell demarcation. The Image-iT® DEAD Green™ viability stain in the kit is impermeable to healthy cells, whereas it can enter once the membrane integrity of the cells is compromised. High-content fluorescence imaging was performed using the SpectraMax i3 platform with MiniMax Imaging Cytometer (Molecular Devices, USA).

2.5 RNA extraction and RNA m⁶A determination

Total RNA was extracted from the lung tissue of mice and cultured cells using TRIzol reagent (Invitrogen, Carlsbad, CA, USA), according to the manufacturer's instructions. RNA was quantified by a Nano Drop 2000 spectrometer (Thermo Scientific, USA). Equal amounts of genomic RNA were analyzed for m⁶A level by using the EpiQuik m⁶A RNA Methylation Quantification Kit (Epigentek, USA) according to the manufacturers' instructions.

2.6 RT-PCR

The PrimeScript RT Master Mix (TaKaRa, Dalian, China) was used to synthesize cDNA. Real-time PCR validation was conducted using the Maxima® SYBR® Green qPCR Master Mix kit (CWBIOtech, China) according to the manufacturer's instructions, in an ABI Prism 7500 Sequence Detection System 288 (Applied Biosystems Inc), with the following procedures: 95°C for 10 minutes; 95°C for 30s, 60°C for 1 min, and 72°C for 1 min; 40cycles. β-actin is used as a standardized internal control. The primers are shown in Table 1. Each sample was repeated in triplicate and the fold change in gene expression was calculated according to the 2^−ΔΔCt method.

Table 1

Sequence of primers of used for RT-PCR
Gene	sequence of primer (5’→3’)
Gene	Forward	Reverse
	C57 BL/6J mice
TGF-β1	AGCTGCGCTTGCAGAGATTA	AGCCCTGTATTCCGTCTCCT
Smad2	AGGATGATGGGGACGGGAAT	AGCCCGGTAAATCTACCCAGAA
Smad3	AGGAGAAGTGGTGCGAGAAG	CCATCCAGTGACCTGGGGAT
β-actin	CACTGTCGAGTCGCGTCC	TCATCCATGGCGAACTGGTG
	A549 cell
TGF-β1	CAAGTGGACATCAACGGGTTC	TCCGTGGAGCTGAAGCAATAG
Smad2	ACCAAGCACTTGCTCTGAAA	ACGACCATCAAGAGACCTGG
Smad3	TAATTTATTGCCGCCGCTCG	ATCCAGGGACTCAAACGTGG
METTL3	GTGATCGTAGCTGAGGTTCGT	GGGTTGCACATTGTGTGGTC
METTL14	GGACCTTGGAAGAGTGTGTTT	GATCCCCATGAGGCAGTGTT
WTAP	GCTTCTGCCTGGAGAGGATT	GTGTACTTGCCCTCCAAAGC
ALKBH5	TGACTGTGCTCAGTGGATATG	TGACAGGCGATCTGAAGCAT
FTO	GAGCGCGAAGCTAAGAAACTG	TGGGGGTCAGATAAGGGAGC
β-actin	GCCGCCAGCTCACCAT	TCGTCGCCCACATAGGAATC

2.7 ELISA analysis

The collected cells were thoroughly mixed with the lysate NP-40 (Beyotime, shanghai, China) and centrifuged, and the supernatant lysate was taken for protein expression analysis. In this study, enzyme-linked immunosorbent assay (ELISA) was used to analyze the expression level of target protein in A549 cells. The ELISA kits were all purchased from Abcam (TGF-β1: ab100647; Smad2: ab260065; Smad3: ab264624; METTL3: ab163377; METTL14: ab163640; WTAP: ab100647; ALKBH5: ab162879; FTO: ab253759). All reagents, samples, and standards were prepared following the manufacturer’s instructions.

2.8 Statistical analysis

The result is expressed as mean ± standard deviation. The statistical test uses the one-way analysis of variance. All statistics were calculated with GraphPad Prism 8.0 and p values less than 0.05 were considered as significant.

3.1 TGF-β1/Smad2/3 levels in lungs of mice after real-world PM_2.5 exposure in chambers

Our previous study showed that acute PM_2.5 exposure induced a reversible change of RNA m⁶A levels and METTL3 and METTL14 in lungs of mice (Li et al., 2019b). Considering the change patterns of RNA m⁶A levels and METTL3 and METTL14, the expression of TGF-β1 and Smad2/3 was also analyzed to explore whether TGF-β-Smad pathway is involved in PM_2.5 exposure-induced m⁶A RNA methylation modification and to clarify its up and downstream relationships. We found that the expression of TGF-β1 gene was significantly increased in the lung tissues of mice in the PM_2.5 exposed group (p < 0.05) (Fig. 1a). Meanwhile, the expression of Smad2 and Smad3 gene were also elevated significantly compared to the control group (p < 0.05) (Fig. 1b, c). All these alterations returned to normal with being transferred to purified air and continuing to live for 120 h.

3.2 Permeability of A549 Membrane after PM_2.5 exposure

Membrane permeability is an effective indicator of cellular damage and can be visualized by the two-color nuclear staining assay with high-content fluorescence imaging. The green fluorescent signal represents damaged cells, while the red fluorescent signal indicates normal cells. In the present study we found that the intensity of green signal increased and the density of cell decreased as we elevated the concentration of PM_2.5 (Fig. 2). When the PM_2.5 concentration reached 200 ug/mL, the field of view was almost entirely filled with green signals, which meant that the cell membrane was completely permeated and cell survival was extremely low (Fig. 1d). Therefore, the subsequent molecular biology analyses were performed at low to moderate concentrations of PM_2.5 (0, 50, 100 µg/mL).

3.3 RNA m⁶A and TGF-β1 levels in A549 after PM_2.5 exposure

We determined the concentration of m⁶A RNA methylation in cultured A549 cells after PM_2.5 treatment. The level of RNA m⁶A in A549 cells gradually increased with the increasing of PM_2.5 concentration gradients (0, 50, 100 µg/mL) (Fig. 3). When the concentration of PM_2.5 reached 100 µg/mL, the level of RNA m⁶A was significantly up-regulated (p < 0.05). Therefore, 100 µg/mL of PM_2.5 was selected as the representative exposure concentration for subsequent study.

The expression level of TGF-β1 gene and protein were detected. The results of qPCR and ELISA analysis showed that the expression of TGF-β1 gene and protein in the A549 cell lysate treated with PM suspension was significantly higher than that in the absence of PM_2.5 (p < 0.05) (Fig. 4). These results indicate that TGF-β1 may be a mediator of PM_2.5-induced RNA m⁶A methylation in A549 cells.

3.4 Effect of TGF-β inhibition on m⁶A RNA methylation of A549 after PM_2.5 exposure

To further examine the role of TGF-β in PM_2.5-induced RNA m⁶A methylation, the TGF-β inhibitor fresolimumab (GC 1008) was added to the cell culture medium alone or together with PM_2.5. Fresolimumab is a high-affinity, fully human monoclonal antibody that neutralizes the active forms of human TGF-β1, β2, and β3(Lacouture et al., 2015). The experimental group consisted of four groups: control group without any treatment (C); TGF-β inhibitor added group (G); PM_2.5 added group (P); PM_2.5 and TGF-β inhibitor simultaneously added group (PG). First, the TGF-β1 gene and protein expression levels of each experimental group were detected. The results showed that the PM_2.5-induced up-regulation of TGF-β1 gene and protein expression was reversed after treatment with TGF-β inhibitor (p < 0.05) (Fig. 5), indicating that the inhibitor did suppress TGF-β1 expression. Go further, the RNA m⁶A levels of each experimental group were analyzed. The results showed that the PM_2.5-induced up-regulation of RNA m⁶A level was reversed after treatment with TGF-β inhibitor (p < 0.05) (Fig. 6), which directly indicated that TGF-β1 was involved in PM_2.5-induced m⁶A RNA methylation.

3.5 Effect of TGF-β inhibition on the Smad2/3 in A549 after PM_2.5 exposure

The result showed that there was no significant change in Smad2 gene and protein expression in A549 after PM_2.5 exposure, while Smad2 expression was significantly downregulated in the group treated with both PM_2.5 and TGF-β inhibitors compared with the PM_2.5 added group (Fig. 7a, b). Furthermore, PM_2.5 induced up-regulation of Smad3 gene and protein expression in A549 was reversed after TGF-β inhibitor treatment (p < 0.05) (Fig. 7c, d). These results indicated that TGF-β affected Smad3 expression in A549 after PM_2.5 exposure.

3.6 Effect of TGF-β inhibition on the RNA (de)methyltransferase in A549 after PM_2.5 exposure.

m⁶A RNA methylation is directly mediated by RNA methyltransferase and demethyltransferase. Therefore, we analyzed the expression of RNA methyltransferase like-3 (METTL3), methyltransferase like-14 (METTL14), wilms tumor 1 associated protein (WTAP), and demethyltransferase ALKB homolog 5 (ALKBH5), fat mass and obesity-associated protein (FTO). The results showed that PM_2.5 induced up-regulated gene and protein expression of METTL3 and METTL14 in A549 were reversed after TGF-β inhibitor treatment (p < 0.05) (Fig. 8a, b, c, d). WTAP gene and protein expression did not change significantly after PM_2.5 exposure (Fig. 8e, f).

In addition, at the gene level, PM_2.5 induced up-regulation of ALKBH5 expression in A549 was reversed after TGF-β inhibitor treatment (Fig. 9a), while no significant changes were observed at the protein level (Fig. 9b). Similarly, FTO gene and protein expression did not change significantly after PM_2.5 exposure (Fig. 9c, d).

Numerous studies have pointed out that epigenetic modification is involved in the adverse health effects after PM_2.5 exposure(Real et al., 2021). At present, most studies have found that, at the transcriptional level, particulate matter exposure induces DNA hypomethylation, and our research also confirmed this(Li et al., 2019a). m⁶A RNA methylation is a newly discovered and important modification method in recent years, which regulates gene expression at the post-transcriptional level(Zhao et al., 2017). However, at present only a relatively small number of studies have begun to focus on the changes in m⁶A RNA methylation after PM_2.5 exposure. The previous animal experiments of our team found that acute PM_2.5 exposure can induce changes in RNA m⁶A, and this process is reversible(Li et al., 2019b). Cayir et al.(Cayir et al., 2019) found that exposure to PM at concentrations of > 62 µg/mL induced significant changes in m⁶A methylation in A549. In order to verify the effect of PM_2.5 exposure on m⁶A RNA methylation and explore the possible regulatory mechanisms, this study was further investigated by an existing animal exposure model and a newly established cellular exposure model.

In the present study, we analyzed the level of global RNA m⁶A, the expression levels of RNA (de)methyltransferase, TGF-β, and Smad2/3 after PM_2.5 exposure in both animal and cellular studies. Our results showed that compared with the untreated group (control group), acute PM_2.5 exposure resulted in increased global RNA m⁶A levels accompanied with increased expression of METTL3, METTL14, TGF-β, Smad3 in both lungs of mice and A549 cells. It is worth noting that PM_2.5-induced changes in RNA m⁶A and the expression of METTL3, METTL14, TGF-β and Smad3 could be reversed to normal when both TGF-β inhibitor and PM_2.5 were added to the cell medium.

TGF-β superfamily is responsible for initiation of the intracellular signaling pathways(Morikawa et al., 2016). Cellular homeostasis, regulation of inflammation and immunity, extracellular matrix (ECM) synthesis and many essential physiological processes depend on intact and appropriate TGF-β signaling(Aschner and Downey, 2016). Generally, the commonly accepted model of TGF-β signal transduction is that the TGF-β dimer binds to the TGF-β receptor, then sequentially transfers phosphate groups to Smad2 and Smad3 proteins which are translocated to the target gene DNA sequence to activate or inhibit the expression of the target gene(Budi et al., 2017; Derynck R and Budi EH, 2019). The core of this signal pathway is the Smad transcription factor.

To explore the possible regulatory role of TGF-β on m⁶A RNA methylation after PM_2.5 exposure, we performed in vivo and in vitro experiments. The expression of TGF-β and key downstream factors of Smad2/3 in lungs of mice after PM_2.5 exposure were analyzed. We found that the expression of TGF-β1 and Smad2/3 genes were significantly increased in the lungs of mice in the PM_2.5 exposed group, while the expression of TGF-β1 and Smad2/3 genes returned to normal after they were transferred to clean air and continued to be fed for 120 hours. Thus, at the animal level, the reversible changes between m⁶A RNA methylation and TGF-β and Smad2/3 gene expression after PM_2.5 exposure are consistent, confirming a role for TGF-β in PM_2.5-induced m⁶A RNA methylation. In order to clarify the role of TGF-β in the induction of m⁶A RNA methylation by PM_2.5, we further carried out an experiment at the cellular level. Through the cell mortality and permeability studies, we determined PM_2.5 at 100 µg/mL for 24 h as the follow up study concentration. Consistent with our animal exposure study, PM_2.5 exposure also induced a significant increase in m⁶A RNA methylation, TGF-β gene and protein in A549. These results were similar to the results of most previous studies. Zheng et al.(Zheng et al., 2018) found after 21 days of exposure to PM_2.5, Balb/c mice showed increased TGF-β1 levels in the bronchoalveolar lavage fluid of lung. Dysart et al.(Dysart et al., 2014) found that exposure to PM_2.5 resulted in increased activation of TGF-β in ATII cells. The results of the more convincing TGF-β inhibitor study showed that when PM_2.5 and TGF-β inhibitor were simultaneously added to the cell culture medium, compared with control group, the expression of TGF-β gene and protein did not increase significantly, and the RNA m⁶A level did not increase. These results fully demonstrateed the indispensable role of TGF-β in PM_2.5-induced m⁶A RNA methylation. That is, PM_2.5 exposure induces an increase in TGF-β, which in turn regulates m⁶A RNA methylation. Our research complements the understanding of the association between TGF-β and epigenetic modification after PM_2.5 exposure.

Meanwhile, we found statistically significant upregulation of Smad3 gene and protein expression in A549 after PM_2.5 exposure, while Smad2 gene and protein expression also tended to be upregulated. The study by Xu et al.(Xu et al., 2019) got similar results with us. They found chronic PM_2.5 exposure on human bronchial epithelial cell line BEAS-2B cells led to the activation of TGF-β1/Smad3 pathway. Singh et al.(Singh and Arora, 2021) also showed that the TGF-β/Smad3 pathway was activated in diesel exhaust-exposed mice model. Notably, when PM_2.5 and TGF-β inhibitors were added to the medium simultaneously, the expression of Smad3 gene and protein was significantly upregulated compared to the control group, while Smad2 was not. This result indicates that PM_2.5 exposure would increase TGF-β, which in turn regulates the expression of Smad3. That is, after PM_2.5 exposure, TGF-β induces m⁶A RNA methylation changes by regulating Smad3, and independent of Smad2.

The m⁶A RNA methylation is directly mediated by RNA methyltransferase METTL3 and METTL14 and other cofactors such as WTAP(Gu et al., 2021). RNA demethylation transferase as ALKBH5 and FTO can demethylate the modified m⁶A RNA(Zaccara et al., 2019). For better explaining the regulatory pathway of PM_2.5-induced m⁶A RNA methylation, the effects of PM_2.5 exposure on RNA methyltransferase and demethyltransferase were also examined. The animal study showed that PM_2.5 induced significant increase in the expression of RNA methyltransferase METTL3 and METTL14, and that the change was reversible(Li et al., 2019b). The A549 cell exposure experiment also showed the same results. Besides, there was no significant change in the expression of ALKBH5 and FTO protein after PM_2.5 exposure. These results suggest that PM_2.5-induced m⁶A RNA methylation is mainly affected by METTL3 and METTL14. In other words, PM_2.5 exposure is more likely to increase RNA m⁶A levels by adding methyl groups to RNA. Furthermore, when PM_2.5 and TGF-β inhibitors were simultaneously added to the medium, compared with the control group, METTL3 and METTL14 was not increased significantly. This result suggests that TGF-β induced by PM_2.5 regulates the expression of METTL3 and METTL14, and thus m⁶A RNA methylation.

Two points about the limitations of this study are as follows: (1) The chemical composition of PM_2.5 is critical to its health effects. Different components often have different effects. Therefore, whether the same research results can be obtained for PM_2.5 collected from other places needs to be further studied. However, in our study, both the animal exposure study we reported before and this cellular exposure study showed the same results, i.e., PM_2.5 exposure induced an increase in the level of m⁶A RNA methylation and METTL3 and METTL14. Thus, it is reasonable to acknowledge the accuracy of our results. (2) The previous published study suggested that phosphorylated Smad2/3 can interact with RNA methyltransferase complex to induce m⁶A RNA methylation (Bertero et al., 2018). In the present study, limited by the experimental conditions, we were temporarily unable to investigate the phosphorylation level of Smad2/3 and the interaction between Smad2/3 and RNA methyltransferase complex after PM_2.5 exposure, which needs to be further explored in the future. However, in any case, we have clarified that TGF-β plays an indispensable role in RNA methylation after PM_2.5 exposure. Moreover, TGF-β regulation of Smad3, METTL3 and METTL14 may be one of the regulatory pathways of m⁶A RNA methylation after PM_2.5 exposure.

By reusing the existed animal exposure model and establishing an A549 cell exposure model, we confirmed that PM_2.5 induced m⁶A RNA methylation, accompanied by increased expression of TGF-β, Smad3, METTL3, METTL14. The TGF-β inhibitor experiments showed that TGF-β plays an indispensable role in RNA methylation triggered by PM_2.5 exposure. Therefore, we suggest that TGF-β regulates m⁶A RNA methylation by regulating the pathway of Smad3, METTL3, and METTL14 after PM_2.5 exposure.

Ethics approval and consent to participate

All animal experimentations were conducted in compliance with the guidelines of ethical animal research. The study protocol was approved by Scientific Research Ethics Committee of Chinese Research Academy of Environmental Sciences.

Consent for publication

All authors have consented for publication.

Availability of data and materials

The datasets used and/or analyzed during this study are available from the corresponding authors on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This work was supported by grants from the National Natural Science Foundation of China (21477119), the fundamental research funds for central public welfare research institutes of China (2016YSKY-021) and the cooperative research programs of the Institute of Nature and Environmental Technology, Kanazawa University, Japan (20019, 21016).

Authors' contributions

Study design: ZL/YW. Data collection: KX/ZL. Data analysis and interpretation: KX/ZL/YW. Manuscript draft: KX/YW. Supervision and coordination of the study: YZ/NT/YW. Critical revision and final decision to submit: all authors. The author(s) read and approved the final manuscript.

Acknowledgements

The authors wish to acknowledge Professor Zhongsheng Sun, Ms Yuanyuan Li of Institute of Genetics and Developmental Biology, Chinese Academy of Sciences.

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No competing interests reported.

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TGF-β regulates m 6 A RNA methylation after PM 2.5 exposure

Status:

Version 1

Abstract

Figures

1. Introduction

2. Material And Method

2.1 Animals and ethical approval

2.2 PM_2.5 sampling and suspension preparation

2.3 Cell culture and PM_2.5 exposure

2.4 Cell membrane permeability analysis

2.5 RNA extraction and RNA m⁶A determination

2.6 RT-PCR

2.7 ELISA analysis

2.8 Statistical analysis

3. Results

3.1 TGF-β1/Smad2/3 levels in lungs of mice after real-world PM_2.5 exposure in chambers

3.2 Permeability of A549 Membrane after PM_2.5 exposure

3.3 RNA m⁶A and TGF-β1 levels in A549 after PM_2.5 exposure

3.4 Effect of TGF-β inhibition on m⁶A RNA methylation of A549 after PM_2.5 exposure

3.5 Effect of TGF-β inhibition on the Smad2/3 in A549 after PM_2.5 exposure

3.6 Effect of TGF-β inhibition on the RNA (de)methyltransferase in A549 after PM_2.5 exposure.

4. Discussion

5. Conclusion

Declarations

Ethics approval and consent to participate

Consent for publication

Availability of data and materials

Competing interests

Funding

Authors' contributions

Acknowledgements

References

Additional Declarations

Status:

Version 1

TGF-β regulates m 6 A RNA methylation after PM 2.5 exposure

Status:

Version 1

Abstract

Figures

1. Introduction

2. Material And Method

2.1 Animals and ethical approval

2.2 PM2.5 sampling and suspension preparation

2.3 Cell culture and PM2.5 exposure

2.4 Cell membrane permeability analysis

2.5 RNA extraction and RNA m6A determination

2.6 RT-PCR

2.7 ELISA analysis

2.8 Statistical analysis

3. Results

3.1 TGF-β1/Smad2/3 levels in lungs of mice after real-world PM2.5 exposure in chambers

3.2 Permeability of A549 Membrane after PM2.5 exposure

3.3 RNA m6A and TGF-β1 levels in A549 after PM2.5 exposure

3.4 Effect of TGF-β inhibition on m6A RNA methylation of A549 after PM2.5 exposure

3.5 Effect of TGF-β inhibition on the Smad2/3 in A549 after PM2.5 exposure

3.6 Effect of TGF-β inhibition on the RNA (de)methyltransferase in A549 after PM2.5 exposure.

4. Discussion

5. Conclusion

Declarations

Ethics approval and consent to participate

Consent for publication

Availability of data and materials

Competing interests

Funding

Authors' contributions

Acknowledgements

References

Additional Declarations

Status:

Version 1

2.2 PM_2.5 sampling and suspension preparation

2.3 Cell culture and PM_2.5 exposure

2.5 RNA extraction and RNA m⁶A determination

3.1 TGF-β1/Smad2/3 levels in lungs of mice after real-world PM_2.5 exposure in chambers

3.2 Permeability of A549 Membrane after PM_2.5 exposure

3.3 RNA m⁶A and TGF-β1 levels in A549 after PM_2.5 exposure

3.4 Effect of TGF-β inhibition on m⁶A RNA methylation of A549 after PM_2.5 exposure

3.5 Effect of TGF-β inhibition on the Smad2/3 in A549 after PM_2.5 exposure

3.6 Effect of TGF-β inhibition on the RNA (de)methyltransferase in A549 after PM_2.5 exposure.