LncRNA LOC101927514 regulates PM2.5-driven inflammation in human bronchial epithelial cells through binding p-STAT3 protein

Journal Pre-proof LncRNA LOC101927514 regulates PM2.5 -driven inflammation in human bronchial epithelial cells through binding p-STAT3 protein Yi Tan, YuYu Wang, YunFeng Zou, CaiLan Zhou, YanNi Yi, YiHui Ling, FangPing Liao, YiGuo Jiang, XiaoWu Peng

PII:

S0378-4274(19)30328-5

DOI:

https://doi.org/10.1016/j.toxlet.2019.10.009

Reference:

TOXLET 10594

To appear in:

Toxicology Letters

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LncRNA LOC101927514 regulates PM2.5-driven inflammation in Human Bronchial Epithelial Cells through binding p-STAT3 protein

Yi Tanb,1, YuYu Wanga,1, YunFeng Zoub, CaiLan Zhoub, YanNi Yic, YiHui Lingc,

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FangPing Liaob, YiGuo Jiangc,* , XiaoWu Penga,*

State Environmental Protection Key Laboratory of Environmental Pollution Health Risk

Assessment, South China Institute of Environmental Sciences. Ministry of Environmental Protection,

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Guangzhou 510655, China

School of Public Health, Guangxi Medical University, Nanning 530021, China.

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State Key Laboratory of Respiratory Disease, Institute for Chemical Carcinogenesis, Guangzhou

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Medical University, Guangzhou 511436, PR China

Corresponding author at:

State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China

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Institute of Environmental Sciences. Ministry of Environmental Protection, Guangzhou 510655, China Email addresses: [email protected] (XiaoWu. Peng),

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State Key Laboratory of Respiratory Disease, Institute for Chemical Carcinogenesis, Guangzhou Medical University, Guangzhou 511436, PR China [email protected](YiGuo Jiang) 1

These authors contributed equally to this paper.

Graphical Abstract

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Highlights

PM2.5 exposure could induce the alteration of lncRNA expression profiles.

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LOC101927514 was upregulated expression and could play a proinflammatory role

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in the process of inflammation

LOC101927514 may modulate the PM2.5-driven inflammation through binding p-

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STAT3 protein

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Abstract: Long-term exposure to fine particulate matter (PM2.5) may cause or exacerbate many diseases, including respiratory inflammation. However, the full mechanism is not yet fully understood. The newly discovered long chain non-coding RNA, though unable to encode proteins,

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regulates multiple life activities and participates in the development of inflammation. In this study, we set up a cell inflammation model by using normal bronchial 16HBE cells exposed to PM2.5. High-throughput sequencing, as well as real-time fluorescent quantitative PCR detection and validation, was performed on the inflamed cells to evaluate the expression level of long chain noncoding RNA that helped us to identify the LncRNA LOC101927514. Inhibiting LncRNA LOC101927514 expression by RNAi, reflected in a reduction in inflammation, is driven by PM2.5.

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In addition, we identify LncRNA LOC101927514 to be located within the nucleus and binds to STAT3, altering the inflammatory state of the cells and IL6 and IL8 release. This study identifies

response activated by PM2.5 in the respiratory system.

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1. Introduction

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Keywords: PM2.5, LncRNA, Inflammation

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that LncRNA LOC101927514 is a new potential target for future treatment of the inflammatory

Fine particulate matter (PM2.5) refers to inhalable particles, with an aerodynamic diameters of

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2.5 micrometers or smaller (≤2.5 μm); their main components include polycyclic aromatic hydrocarbon substances (PAHs), inorganic salts, metal oxides, and minerals (Corsini et al., 2013;

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Gualtieri et al., 2012; Qiao et al., 2014). Due to its small size and complex compositions have the potential acute and chronic health disorders (Yoon et al., 2018). Previous epidemiological studies addressed that prolonged exposure of humans to PM2.5 can lead to health impacts, such as respiratory and cardiovascular diseases (Cesaroni et al., 2013; Valavanidis et al., 2013; Vinikoor-Imler et al., 2011).

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One study determined that PM2.5 gets deposited in the human respiratory system through respiration and due to their deep penetrating abilities, they translocate into cells, tissues or circulatory system(Kim et al., 2015). In addition, previous toxicological studies indicated that PM2.5 can induce various pathological responses, such as cytotoxicity, immune and inflammatory responses, oxidative stress, DNA damages, and gene mutations(Limon-Pacheco and Gonsebatt, 2009; Thomson et al., 2015; Wei et al., 2009). Further studies showed that exposure to PM2.5 can

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also affect gene expression(Zhou et al., 2015). However, the underlying mechanisms by which PM2.5 affects the respiratory system is still not sufficiently elucidated, and the relationship between PM2.5induced epigenetic changes and the cell functions remain unknown.

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Non-coding RNAs including microRNAs and long non-coding RNAs (lncRNAs) have become

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a new topic in epigenetic. It is now clear that 98% of the human genome accounts for non-coding

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sequence (Mercer et al., 2009). Furthermore, ~90% of these non-coding sequences are transcribed to produce a large number of non-coding RNAs(Hangauer et al., 2013). Previous studies have shown

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that PM2.5 can induce alteration of the microRNA expression (Fossati et al., 2014). Although miRNAs are well characterized,lncRNAs are relatively new.The lncRNAs are defined as transcripts

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of more than 200 nucleotides that do not encode proteins(Nagano and Fraser, 2011). They can regulate gene expressions in three ways,involving epigenetic, transcriptomic and post transcription

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modifications (Nagano and Fraser, 2011). During recent years, lncRNAs have been implicated in regulating a variety of cellular functions and disease process (Wang et al., 2014) , and the abnormal expression of lncRNAs may lead to disorders in humans(Billet et al., 2007). Although previous studies have shown the effect of PM2.5 on microRNA expression(Liu et al., 2015) , their effect on lncRNAs are largely unexplored. In this study, we aimed to investigate whether PM2.5 exposure may

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affect lncRNAs regulatory functions in cytotoxicity, inflammatory response and genotoxicity. To achieve this, human bronchial epithelial cells were treated with PM2.5, and the expression profiles of lncRNAs were analyzed. We found that exposure of PM2.5 induced alteration of lncRNAs expression profiles, and caused inflammatory reactions. We identified the lncRNA, LOC101927514, which was upregulated in 16HBE cell treated with PM2.5. And we also speculated that LOC101927514 might be associated closely with the occurrence of inflammatory response by

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regulating the transcription-3 (STAT3) phosphorylation.

2. Materials and methods

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2.1 PM2.5 sample collection and analysis

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The sample collection of PM2.5 was carried out in the GuangZhou city of China. The ambient particulate air samples were collected from the roof of the buildings for 3 months in the winter of

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2016 using a PM2.5 high volume air sampler (Whatman, USA) and glass fiber filters with a 2.5 μm

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pore size. The filter membranes were changed every 48h and stored at a constant temperature of 20°C, until further analysis. To extract the fine particles, the filters were cut into 2 cm2 size pieces

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and soaked in 50 mL of milli-Q water. Using a small ultrasonic cleaning device, thrice for 60 min, the PM2.5 components were extracted. After the water-extraction of PM2.5, the collected samples

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were stored at -80℃ overnight. Following the overnight freezing step, removal of water was performed by placing the samples in a vacuum freeze-dryer for 12-14h. The dried samples were then placed in -20℃ until further use. All the collected samples were mixed and divided into two parts.One part of PM2.5 sample was used for chemical compositional analysis, using gas chromatography - mass spectrometry (GC-MS, 7890A-5975C, Agilent, Santa Clara, CA, USA).

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Polycyclic aromatic hydrocarbons (PAHs) were determined.Further, using a commercial Behr C50 IRF carbon analyzer (Labor-Technik GmbH, Dusseldorf, Germany), the OC and EC contents were determined. And finally, using an Agilent 7500ce ICP-MS (Agilent Technologies, Santa Clara, CA, USA), the metallic elements were analysed. The second part of the samples was weighed and used to prepare a 10 mg/ml of PM2.5 solution, using sterile PBS, and stored in -20℃ for further use.

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2.2 Cell culture and PM2.5 treatment

Human bronchial epithelial cells (16HBE) were kindly provided by Dr.Yiguo Jiang

(Guangzhou Medical University). The cells were maintained in 5% CO2 at 37°C and were cultured

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using the standard Minimum Essential Medium (MEM) (Genom, Hangzhou, China) containing 10%

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FBS (Sijiqing, Hangzhou, China) and 1% penicillin-streptomycin antibiotics (Sigma-Aldrich,

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St.Louis, MO,USA). For all subsequent experiments, cells were digested using 0.25% of trypsin (Sigma-Aldrich,St.Louis,MO, USA) and then incubated for 24h. The cells were then exposed to

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different concentrations of PM2.5 (experimental groups) or sterile PBS (control group).

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2.3 Cell counting kit-8 (CCK-8) assay

To detect cell viability, the CCK-8 assay kit (Dojin Laboratories, Kumamoto, Japan) was used,

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following the manufacturer’s instructions. Briefly, 16HBE cells were seeded in a 96-well plate at a density of 1.5×104 cells/well and either PM2.5 suspensions at the concentrations of 50, 100, 200, 300 and 400 μg/mL or PBS (as control) was added. Viability was detected at 48h by measuring the absorbance at 450nm using a microplate reader (BioTek, Winooski, VT). To calculate cell viability the following formula was used: Cell viability=(absorbance of the experimental group − absorbance

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of the blank control group)/(absorbance of the control group − absorbance of the blank control group). Within each plate, five repeated wells were set for each group and the CCK-8 assay was repeated three times.

2.4 Enzyme-Linked Immunosorbent Assay (ELISA) The 16HBE cells were seeded in 6-well plate and after 48h the cells were treated with different

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concentrations of PM2.5 (50, 100 and 200 μg/mL) suspensions or PBS, the supernatant was collected, centrifuged and stored at -20˚C for subsequent assays. Concentrations of IL6 and IL8 were

determined by ELISA using Human ELISA Kits (CSB-E04638h, CSB-E04641h;Wuhan Boster

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2.5 RNA-sequencing of 16HBE cells

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Biological Technology, Ltd), following the manufacturer’s protocol.

The total RNAs were extracted from 16HBE cells after exposure to either PM2.5, at

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concentration of 50 μg/mL and 100 μg/mL, or PBS (control group) for 48h. Extracted RNA samples were send to Guangzhou RiboBio Co. (China) where lncRNA-sequencing, detection and analysis

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was performed. Fold change ≥ 2 and p ≤ 0.05 were used as a cutoff values to determine significant differential expression. Further, cluster analyses were performed to classify lncRNAs based on their

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distinguishable expression in different samples.

2.6 Cell Transfection

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The 16HBE cells were transfected with small two different interfering RNAs (siRNAs), specific for LOC101927514 or with a scrambled siRNAs (negative control), synthesized by Invitrogen (Waltham, MA, USA). The LOC101927514 siRNA sequences used were: 1. sense,5’- GCAGGAACCCUGACUAUUUTT-3’ Antisense, 5’- AAAUAGUCAGGGUUCUGCTT-3’

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2. sense,5’- GCAGCUCAUUAUGGCUCAATT-3’ Antisense, 5’- UUGAGCCAUAAUGAGCUGCTT-3’ and the siRNA control (Invitrogen 1585252).

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Transfections were performed using Lipofectamine 2000 (Invitrogen, Waltham, MA, USA)

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following the manufacturer’s instructions, for 48h and successful silencing was evaluated at gene

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2.7 RT-PCR analysis

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and protein by both RT-PCR and Western blot.

Using Trizol reagent (Invitrogen, Carlsbad, CA), total RNA was extracted from cells according

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to manufacturer’s instructions, complementary DNA (cDNA) was synthesized using the RNA with GoScript™ Reverse Transcription System (Promega, Madison, WI, USA). The PCR reactions were

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performed in an ABI prism 7500 Thermal Cycler Sequence Detection System (Applied Biosystems, Foster City, CA, USA ) with GoTaq® qPCR Master Mix (Promega). The level of GAPDH was used as the internal standard to normalize the expression of target genes, 2-ΔΔCT was used to calculate the expression results obtained from ABI 7500HT. The list of all primers synthesized by Sangon Biotech and used in this study are presented in TableS1.

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2.8 Western blot Total proteins from pre-treated 16HBE cells were extracted using RIPA buffer containing protease inhibitors according to manufacturer instructions. Samples containing equal amount of proteins (30μg) were separated with 10% SDS-PAGE and transferred to polyvinylidene fluoride membrane (Millipore). Primary polyclonal antibodies including STAT3 antibody (ab32518) and P-

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STAT3 antibody (ab133462) were purchased from Abcam (Cambridge,UK). Anti-rabbit secondary antibodies were used (Santa Cruz Biotechnology). The blots were developed using Odyssey CLX

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using β-actin antibody (Abcam, Cambridge, UK).

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reagent (Li-Cor, Lincoln, NE, USA). Equal amount of protein loading in each lane was confirmed

2.9 Detection of gene cytoplasm and nuclear localization

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GAPDH and U6 were used as reference genes in cytoplasm and nucleus respectively. PARIS@

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Kit (Ambion,Austin,TX,USA) was used to isolate the cytoplasmic nucleus of 16HBE cells,as described previously. And then, cytoplasmic and nuclear RNAs were then converted to cDNA and

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analyzed by q-PCR.

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2.10 RNA pull down assay

The interaction between LOC101927514 gene and STAT3 was detected by BrSiBiOTm RNA

dropdown kit. Firstly,The gene LOC101927514 was transfected into the pcDNA3.1 plasmid as the RNA probe template, which was completed by Suzhou Senhong Biotechnology Co., LTD. After the LOC101927514 gene sequence was designed and synthesized based on biotin labeled specific drop

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probe and then biotin-labeled RNA probes were denatured to form a secondary structure. The probebead complex was prepared by adding 40μl magnetic beads.16HBE cells were collected and whole cell proteins were extracted for RNA pull-down test. According to the kit instructions for RNA pulldown.Collection of samples,each sample 50μl for polyacrylamide gel electrophoresis. After electrophoresis, silver staining and WB verification were performed.

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2.11 Statistical analysis

SPSS 16.0 statistical software was used for data analyses.One-way analysis of variance (ANOVA) and least significant difference post hoc tests were used to compare mean values among

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experimental groups. The data was expressed as the mean ± standard deviation of the three

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independent experiments and a p-value less than 0.05 was considered statistically significant.

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3 Results

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3.1 Chemical composition of PM2.5

The toxicity of PM2.5 is closely related to its chemical compositions,so the chemical

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composition of PM2.5 samples were analyzed firstly. The results showed that polycyclic aromatic hydrocarbons (PAHs) contributed to the PM2.5 mass concentration (9.05±6.82 ng/m3), mainly

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including benzo[ghi]perylene, Benzo(b)fluoranthene and a typical carcinogen Benzo(a)pyrene. The analysis of metals showed that there were mainly Si , K and Na. In addition, there was a minimal presence of highly cytotoxic metals, such as lead, nickel, arsenic and chromium (Table 1). The mass contributions of water soluble ions content in PM2.5 mainly included SO42-，NO3- and NH4+ (Table 2).The OC and EC contents were determined in PM2.5, showing the presence of organic carbon

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(OC;8.76±4.81μg/m3) and elemental carbon (EC;3.91±2.67 μg/m3), and an OC/EC ratio greater than 2.2 (Table 3). Table 1

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Table 3

3.2 Effect of PM2.5 on cell viability

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Human bronchial epithelial cells (16HBEs) were treated with different concentrations of PM2.5

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(from 50 μg/mL to 400 μg/mL) or PBS for 48h, CCK-8 assay confirmed that: a concentrationdependent decrease of cell viability was observed 48h after PM2.5 exposure (Fig.1), while cell **

P <0.01,compared with PBS group). 100 μg/mL、

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viability was not altered by PBS (* P <0.05,

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200 μg/mL、300 μg/mL and 400 μg/mL PM2.5 exposured, 16HBE Cell viability were decreased by 13.3%、20%、22.5% and 28%. The result indicate that PM2.5 reduce cell viability, Based on the

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viability results, we decided to use the PM2.5 concentration of 100 μg/mL to ensure that cell viability

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was no less than 80%.

Fig. 1

Effects of PM2.5 on cell viability. CCK-8 assay cell viability of 16HBE cells were treated with increasing concentrations of PM2.5 (from 50 μg/mL to 400 μg/mL). Data are expressed as mean± SD (n=3), * P <0.05, ** P <0.01 vs. Control,one-way ANOVA.

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3.3 Effect of PM2.5 on inflammatory cytokines Increased expression and release of inflammatory cytokines is considered one of the main pathogenic mechanisms leading to local tissue or systemic damage in lung diseases. Many studies have shown that PM2.5 can induce a large body of inflammatory cytokines. To elucidate the effect of PM2.5 on expression of cytokines and release,We firstly treated 16HBE cells with 100μg/mL of

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PM2.5 for different time points (0h, 6h, 12h, 24h and 48h) and evaluated IL6 and IL8 secretion. As

shown in (Fig.2A-B), PM2.5 upregulated the secretion of IL6 in a time-dependent fashion, without altering IL8 secretion. In addition, the effect of increasing dose of PM2.5 (50-200 μg/mL) on IL6

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and IL8 release were also measured (Fig. 2C-D). Resulted showed that IL6 and IL8 release were

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also significantly upregulated following PM2.5 in a dose-dependent manner. And then we assessed IL6 and IL8 (known inflammatory cytokines in the lung) gene expression by qRT-PCR in cells

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treated with different concentration of PM2.5 (50 μg/mL and 100 μg/mL) for 48h (Fig.2E-F). PM2.5

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increased the mRNA expressions of inflammatory cytokines IL6 and IL8 in a dose-dependent fashion. Altogether, these data indicated that in response to PM2.5 exposure, both mRNA levels and

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protein levels of inflammatory cytokines (IL6 and IL8) were increasing in 16HBE cells, suggesting

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an increase in inflammation.

Fig.2

Effects of PM2.5 on pro-inflammatory cytokines levels in 16HBE cells. (A-B) 16HBE cells were treated with PM2.5 (100 μg/mL) at different time points (0, 6, 12, 24 and 48h). Using ELISA detected the production of IL6 and IL8 in the cell culture supernatant. *p<0.05,

**p<0.01

vs.

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Control,one-way ANOVA.(C-D)16HBE cells were treated with different doses of PM2.5 ( 0, 50, 100 and 200 μg/ml) for 48h. The production of IL6 and IL8 concentrations in cell culture supernatant were examined using ELISA.*P<0.05, **p<0.01 vs. Control,one-way ANOVA. (E-F) 16HBE cells were treated with different doses of PM2.5 (0, 50 and 100 μg/ml) for 48h. IL6 and IL8 mRNA

3.4 Effects of PM2.5 on STAT3 phosphorylation in 16HBE cells

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expression was determined by qRT-PCR,*P<0.05 **p<0.01 vs. Control,Student's t-test.

In order to investigate the upstream signaling pathway involved in the upregulation of IL6/IL8

proteins, STAT-3 phosphorylation was elucidated by western blot. Cells treated with increased

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control, which indicate an activation of STAT3 (Fig.3).

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concentration of PM2.5 showed an increased phosphorylation STAT3 protein when compared to

Fig.3

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Effect of PM2.5 on protein expression of cell STAT3/ p-stat3.

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3.5 PM2.5 regulation of lncRNA expression profile and lncRNA screening The lncRNA high throughput sequencing technology was utilized to investigate the effect of

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PM2.5 on lncRNA expression changes on 16HBE cells treated 48h with 50 μg/ml and 100 μg/ml of PM2.5 or PBS. Results showed that 50 μg/ml and 100 μg/ml of PM2.5 resulted in a different clustering with respect to control, in particular 58 and 308 lncRNAs were found respectively upregulated, and 13 and 15 lncRNAs were instead downregulated. The overall distribution of the differentially expressed genes in the gene heat map (Fig. 4A-B), and the volcano map( Fig. 4C-D) , indicated that

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the high concentration of PM2.5 resulted in more changes in the expression of lncRNA. In this study, details of the lncRNA-Seq data have been deposited in NCBI’s Gene Expression Omnibus and are accessible

through

GEO

Series

accession

number

GSE113071

(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE113071) To validate these data, we randomly selected 11 lncRNAs which were regulated by PM2.5 treatment, and analysed them by qRT-PCR in 16HBE cells treated with PM2.5 (50 μg/ml and 100

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μg/ml). The results were consistent with the RNA-seq results, showing similar gene regulation

(Fig.4E). Among the genes whose expressions were altered by PM2.5,LOC101927514 (HGNC:101927514) was the one most upregulated, and therefore was chosen for further

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investigation.

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Fig.4

PM2.5 exposure regulates lncRNA expression. (A-B) Hierarchical clustering analysis of the

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differentially expressed lncRNAs,comparing the 50 μg/ml PM2.5 treatment group and the control group (A) and comparing the 100 μg/ml PM2.5 treatment group and the control group (B), Each

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column in (A) and (B) represents an individual sample, and each row represents a single lncRNA. Red represents high expression lncRNAs and blue represents low expression lncRNAs. (C-D)

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Volcano map shoring lncRNAs regulation. (E) Validation of selective genes by RT-qPCR.

3.6 RNAi for LncRNA LOC101927514 To investigate the role of LOC101927514 in PM2.5-treated cells, we used RNA interference technology to knock down LOC101927514 expression and detect the functional changes in

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inflammatory markers. Two lncRNA-specific siRNAs were used and their efficiencies were evaluated, the SiRNA-2 showed a greater gene silencing and was therefore used for the following experiments (Fig.5A ). Cells were transfected with LOC101927514-specific siRNA-2 for 6h and then treated with PM2.5 (100 μg/mL) for 48h, secretion of inflammatory cytokines IL6 and IL8 was then evaluated in cell supernatant by ELISA. The results showed that in cells with lower level of LOC101927514, PM2.5 regulation of IL6 and IL8 release was strongly decreased compared to the

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control group transfected with the scrambled RNAi (Fig.5B), suggesting LOC101927514 is

Fig.5

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required for PM2.5 regulation of IL6 and IL8.

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LOC101927514 RNAi in 16HBE cells. (A)16HBE cells were transfected with

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LOC101927514-specific siRNA for 6h and then treated with PM2.5 (100 μg/ml) for 48h, expression level of LOC101927514 was analyzed using RT-PCR. (B) Release of IL6 and IL8 in cell culture

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supernatant were measured using ELISA, *P<0.05, **p<0.01 vs. Control,one-way ANOVA. (C) IL6 and IL8 mRNA expression was determined by qRT-PCR. The data are expressed as mean ± SD,

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and each experiment was replicated three times*P<0.05 ,**p<0.01 vs. Control.

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3.7 LncRNA LOC101927514 directly interacted with phosphorylated STAT3 (Tyr705) The subcellular localization of long chain non coded RNA is closely related to its function. We

first investigated the location of LOC101927514 in 16HBE cells by a RT-PCR in separated cytoplasm RNA and nuclear RNA. The results showed that LOC101927514 was mainly located in the cell nuclear fraction, suggesting that the site of its function is nuclear (Fig.6A).

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Having shown that LOC101927514 was up-regulated in 16HBE cells treated with PM2.5 and had a role in inflammation, we sought to investigate the specific signalling pathway involved. With the help of the prediction software analysis of (http://service.tartaglialab.com/Page/catrapid _group),we discovered that LOC101927514 had high affinity with STAT3 (Fig.6B). The transcription factors STAT3 is a key molecule that mediates inflammatory response,which can be activated by many factors, and then encodes a series of inflammatory related proteins in the cell,

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promotes the release of these inflammatory related proteins, and amplifies the inflammatory

response(Yang et al., 2013). In order to explore whether LOC101927514 and STAT3 interacted directly, we performed RNA pull down studies. RNA pull down silver staining results showed that

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the purpose of LOC101927514 group and LOC101927514 control group and set the background

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group there was significant difference compared with the differences between bands, WB assay,

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molecular weight size of 75~100KD. The antisense group and beads group were set as a negative control, LOC101927514 combined with the phosphorylation of STAT3 resulted in the sense group

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(Fig.6C).These data indicated that p-STAT3 was pulled LOC101927514. The expression and phosphorylation level of STAT3 protein were detected by knocking down the expression of

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LOC101927514, The results (Fig.6D) indicate that LOC101927514 is involved in PM2.5-induced

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inflammation by direct binding to p-STAT3 protein.

Fig.6

LOC101927514 sub localization and interaction with STAT3. (A) The subcellular location of LOC101927514 was examined by RT-PCR in cytoplasm RNA and nuclear RNA. GAPDH was used as the control for cytoplasmic expression and U6 for nuclear. Data are expressed as mean ± SD. (B)

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Prediction of LOC101927514 binding to STAT3 protein.The red grid shows the binding area.(C) Silver staining of RNA pull down experiment with 16HBE cells extract in different groups. M: protein marker; Sense: the pull down result of the justice chain of LOC101927514; Anti-sense: the pull down result of antisense chain of LOC101927514; Beads: the pull down results of hollow magnetic beads. WB detection of LOC101927514 with P-STAT3 protein. (D)16HBE cells was

the levels of STAT3 and p-STAT3 were detected by Western Blot.

3. Discussion

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transfected with SiRNA for LOC101927514 for 6h and exposed to 100 μg/ml PM2.5 for another 48h,

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A large number of epidemiological investigations and toxicology experiments reported that the

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long-term or short-term exposure to PM2.5 has a great harm to people's health, showing a clear toxic

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effect on human and animal health (Bener et al., 1996; Gualtieri et al., 2012; Pope et al., 2002), however mechanisms that impart toxicity is not entirely clear.

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PM2.5 composition is complicated to evaluated, due to its large surface area and the strong adsorption ability to carry a variety of material. The surface adsorption of heavy metals, water-

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soluble ions and toxic organic matter (such as polycyclic aromatic hydrocarbons) is the main source of toxicity (Billet et al., 2007; Kouassi et al., 2010; Roubicek et al., 2007; Vargas, 2003). In this

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study the main components of PM2.5, collected from Guangzhou, include PAHs, metal elements, water-soluble ions and carbon components,and the Bap content was ( 0.97±0.82) ng/m3. Study on 16HBE cells vitality with the CCK8 method, showed that PM2.5 can inhibit cell survival rate, in a dose-dependent fashion. This trend is in agreement with existing literature(Han et al., 2011; Mo et al., 2009; Zhao et al., 2011). With the use of electron microscopy, cells combined

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with CCK8 method, we were able to identify a concentration of PM2.5 processing with cells survival rate of more than 80% which was still exerting inflammatory effects (100 μg/mL). It has been previously reported that the chemical composition of PM2.5 can promote inflammation (Coogan et al., 2016; Kowalska and Kocot, 2016; Riva et al., 2011; Solimini et al., 2015; Valavanidis et al., 2013), although the specific biological mechanisms have not been yet fully investigated. Studies have reported that exposure of BEAS-2B cells to three types of fine

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atmospheric particulate matter in rural, urban and industrial areas can cause increased expression of inflammatory mediators (IL6/IL8)(Marques-Rocha et al., 2015). In accordance with this observation, we found that increasing concentrations of PM2.5 on 16 HBE cells led to an enhanced

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production of IL6 and IL8 cytokines in supernatant fluid secretion, as well an upregulation at mRNA

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level, this is consistent with a previous study(Skuland et al., 2017).The secretion of IL6 was time-

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and dose-dependent, while IL8 regulation had no obvious dose dependence, but was still significantly increased when compared to the control group. IL6 and IL8 are known important

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inflammatory mediators. IL6 is an effective pro-inflammatory factor and participates in numerous inflammatory diseases. In addition, it has been shown that in the acute stage of body trauma, the

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level of IL6 is higher than CRP, which is the most sensitive marker of tissue damage(Hysi et al., 2015). IL8 cytokine can start and trigger inflammatory reactions and reflects the intensity of the

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inflammatory response to a certain exten(Carney et al., 1999). Both have been proved to play a central regulatory role in inflammation and infection(Mkhoian et al., 2009). Gene analysis is a new effective means to explore the mechanism of inflammation induced by PM2.5 exposure. MicroRNA has an important role in regulating the function of the cell, however long non-coding RNAs (lncRNA) have been identified as the new research hotspot(Ma et al., 2013).

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The role of lncRNA in human disease has been explored for instance in inflammatory bowel disease, where an abnormal expression of lncRNA could be prevented by gene expression and signaling pathway activation. Different reports suggest that PM2.5 can alter mRNA and microRNA gene expression level, regulating cell function(Ponting et al., 2009), but so far the effect on PM2.5 on lncRNA regulation has not been fully explored. In this work, we evaluated the changes in lncRNA following PM2.5 exposure through lncRNA high-throughput sequencing technology, CCK8 and

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ELISA experiments found that the cell survival rate was more than 80% under the condition of PM2.5 ≤100 μg/mL concentration, and the inflammatory biological effect was found in the cells

exposed to the same concentration of PM2.5. Based on this study, we selected 50 μg/mL and 100

high-throughput LncRNA

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μg/mL concentration of PM2.5 to treat 16HBE cells for

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sequencing, and selected long chain non-coding RNA which changed expression after treatment

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with 50μg/mL and 100μg/mL concentration groups. which allowed us to identify the LOC101927514 and to further investigate its role in functional studies.

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RNAi experiments, showed that a reduction in LOC101927514 expression was sufficient to mitigate PM2.5 pro-inflammatory effect on IL6 and IL8 mRNA and protein expression. Li

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xinyang(Derrien et al., 2012) and other studies reported that lncRNA played a regulatory role in the exposure of PM2.5 in lung cancer.At present, there are many studies on the specific mechanism of

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PM2.5 in the pathogenesis and development of inflammation, focusing on proteins and known signaling molecules and cellular pathways, but rarely on lncRNA. Our research on inflammation induced by PM2.5 pays more attention to the emerging biomolecules such as long chain noncoding RNA. Therefore,we hypothesized that LOC101927514 may play a role in the inflammatory signaling activated by PM2.5 and confirmed that it plays a regulatory role in promoting inflammation

19

also a critical link between Inflammatory factors IL6 and IL8. Further,we detected the location of LOC101927514 through the cytoplasmic nuclear separation and localization experiment in 16HBE cells. We found that LOC101927514 is mainly located in the nucleus, which indicates that it mainly plays a role in promoting inflammatory reaction in the nucleus.To explore the mechanism of nucleus gene function, RNA pull down experiments, showed that LOC101927514 could interact with STAT3 and influence STAT3 phosphorylation, as seen with the use of RNAi technology. Our study

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found that 16HBE cells treated with increased concentration of PM2.5 (50~200ug/ml concentration) showed an increased phosphorylation STAT3 protein which suggests that PM2.5 exposure can activate the STAT3 protein pathway. STAT3 is an important signal transduction pathways

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downstream of a variety of inflammatory cytokines, and its phosphorylation occurs after dimer

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formation and nuclear translocation, which regulate the expression of multiple genes(Kolarz and

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Majdan, 2017). A large number of literature reports that STAT3 directly regulates the downstream production of IL6(Marques-Rocha et al., 2015), which supports our observation of LOC101927514

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regulation of IL6 release. We hypothesize that PM2.5 leads to activation of STAT pathway and sub sequential phosphorylation of STAT3, which translocate to the nucleus, and binds to lncRNA

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LOC101927514, which is significantly increased in nucleus, this event leads to the further increased secretion of the downstream inflammatory factor IL6 and IL8, which further perpetuate the

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inflammatory reaction. Overall, this manuscript identifies a new inflammatory signaling pathway activated after PM2.5 exposure, and it suggests that lncRNA LOC101927514 has a regulatory role in PM2.5 induced inflammatory effects.

Acknowledgements

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This work was supported by the National Natural Science Foundation of China (grant no.21477045, No.91643204), the Natural Science Foundation of Guangdong (grant no. 2014A030313714), Central fund supporting nonprofit scientific institutes for basic research and development (No.: PM-zx021-201311-039 ),the science and technology planning project of Guangdong (grant no. 2017A020216026).

Reference

ro of

Bener, A., Abdulrazzaq, Y.M., Al-Mutawwa, J., Debuse, P., 1996. Genetic and environmental factors associated with asthma. Human biology 68, 405-414.

Billet, S., Garcon, G., Dagher, Z., Verdin, A., Ledoux, F., Cazier, F., Courcot, D., Aboukais, A., Shirali,

P., 2007. Ambient particulate matter (PM2.5): physicochemical characterization and metabolic

-p

activation of the organic fraction in human lung epithelial cells (A549). Environmental research 105, 212-223.

re

Carney, D.E., Lutz, C.J., Picone, A.L., Gatto, L.A., Schiller, H.J., Finck, C.M., Searles, B., Paskanik, A.M., Snyder, K.P., Edwards, C., Nieman, G.F., 1999. Soluble tumor necrosis factor receptor

lP

prevents post-pump syndrome. The Journal of surgical research 83, 113-121. Cesaroni, G., Badaloni, C., Gariazzo, C., Stafoggia, M., Sozzi, R., Davoli, M., Forastiere, F., 2013. Long-

na

term exposure to urban air pollution and mortality in a cohort of more than a million adults in Rome. Environmental health perspectives 121, 324-331. Coogan, P.F., White, L.F., Yu, J., Burnett, R.T., Seto, E., Brook, R.D., Palmer, J.R., Rosenberg, L., Jerrett,

ur

M., 2016. PM2.5 and Diabetes and Hypertension Incidence in the Black Women's Health Study. Epidemiology (Cambridge, Mass) 27, 202-210.

Jo

Corsini, E., Budello, S., Marabini, L., Galbiati, V., Piazzalunga, A., Barbieri, P., Cozzutto, S., Marinovich, M., Pitea, D., Galli, C.L., 2013. Comparison of wood smoke PM2.5 obtained from the combustion of FIR and beech pellets on inflammation and DNA damage in A549 and THP-1 human cell lines. Archives of toxicology 87, 2187-2199. Derrien, T., Johnson, R., Bussotti, G., Tanzer, A., Djebali, S., Tilgner, H., Guernec, G., Martin, D., Merkel, A., Knowles, D.G., Lagarde, J., Veeravalli, L., Ruan, X., Ruan, Y., Lassmann, T., Carninci, P., Brown, J.B., Lipovich, L., Gonzalez, J.M., Thomas, M., Davis, C.A., Shiekhattar, R., Gingeras, 21

T.R., Hubbard, T.J., Notredame, C., Harrow, J., Guigo, R., 2012. The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression. Genome research 22, 1775-1789. Fossati, S., Baccarelli, A., Zanobetti, A., Hoxha, M., Vokonas, P.S., Wright, R.O., Schwartz, J., 2014. Ambient particulate air pollution and microRNAs in elderly men. Epidemiology (Cambridge, Mass) 25, 68-78. Gualtieri, M., Longhin, E., Mattioli, M., Mantecca, P., Tinaglia, V., Mangano, E., Proverbio, M.C., Bestetti, G., Camatini, M., Battaglia, C., 2012. Gene expression profiling of A549 cells exposed to

ro of

Milan PM2.5. Toxicology letters 209, 136-145. Han, W., Dan, W., Shuo, Y., Fang, Z., Wenjun, D., 2011. Oxidative stress induced by urban fine particles in cultured EA.hy926 cells. Human & experimental toxicology 30, 579-590.

Hangauer, M.J., Vaughn, I.W., McManus, M.T., 2013. Pervasive transcription of the human genome

-p

produces thousands of previously unidentified long intergenic noncoding RNAs. PLoS genetics 9, e1003569.

re

Hysi, I., Juthier, F., Fabre, O., Fouquet, O., Rousse, N., Banfi, C., Pincon, C., Prat, A., Vincentelli, A., 2015. Aortic root surgery improves long-term survival after acute type A aortic dissection.

lP

International journal of cardiology 184, 285-290.

Kim, K.H., Kabir, E., Kabir, S., 2015. A review on the human health impact of airborne particulate matter.

na

Environment international 74, 136-143.

Kolarz, B., Majdan, M., 2017. Epigenetic aspects of rheumatoid arthritis: contribution of non-coding RNAs. Seminars in arthritis and rheumatism 46, 724-731.

ur

Kouassi, K.S., Billet, S., Garcon, G., Verdin, A., Diouf, A., Cazier, F., Djaman, J., Courcot, D., Shirali, P., 2010. Oxidative damage induced in A549 cells by physically and chemically characterized air

Jo

particulate matter (PM2.5) collected in Abidjan, Cote d'Ivoire. Journal of applied toxicology : JAT 30, 310-320.

Kowalska, M., Kocot, K., 2016. Short-term exposure to ambient fine particulate matter (PM2,5 and PM10) and the risk of heart rhythm abnormalities and stroke. Postepy higieny i medycyny doswiadczalnej (Online) 70, 1017-1025. Limon-Pacheco, J., Gonsebatt, M.E., 2009. The role of antioxidants and antioxidant-related enzymes in protective responses to environmentally induced oxidative stress. Mutation research 674, 137-147. 22

Liu, C., Guo, H., Cheng, X., Shao, M., Wu, C., Wang, S., Li, H., Wei, L., Gao, Y., Tan, W., Cheng, S., Wu, T., Yu, D., Lin, D., 2015. Exposure to airborne PM2.5 suppresses microRNA expression and deregulates target oncogenes that cause neoplastic transformation in NIH3T3 cells. Oncotarget 6, 29428-29439. Ma, L., Bajic, V.B., Zhang, Z., 2013. On the classification of long non-coding RNAs. RNA biology 10, 925-933. Marques-Rocha, J.L., Samblas, M., Milagro, F.I., Bressan, J., Martinez, J.A., Marti, A., 2015. Noncoding RNAs, cytokines, and inflammation-related diseases. FASEB journal : official publication of the

ro of

Federation of American Societies for Experimental Biology 29, 3595-3611. Mercer, T.R., Dinger, M.E., Mattick, J.S., 2009. Long non-coding RNAs: insights into functions. Nature reviews Genetics 10, 155-159.

Mkhoian, G.G., Ter-Pogosian, Z.R., Gasparian, M.G., Dzhagatspanian, N.G., Karalian, Z.A., Ovanesian,

-p

G.G., 2009. [Immune reactivity and cytokine status in polytrauma]. Anesteziologiia i reanimatologiia, 60-65.

re

Mo, Y., Wan, R., Chien, S., Tollerud, D.J., Zhang, Q., 2009. Activation of endothelial cells after exposure to ambient ultrafine particles: the role of NADPH oxidase. Toxicology and applied pharmacology

lP

236, 183-193.

Nagano, T., Fraser, P., 2011. No-nonsense functions for long noncoding RNAs. Cell 145, 178-181.

629-641.

na

Ponting, C.P., Oliver, P.L., Reik, W., 2009. Evolution and functions of long noncoding RNAs. Cell 136,

Pope, C.A., 3rd, Burnett, R.T., Thun, M.J., Calle, E.E., Krewski, D., Ito, K., Thurston, G.D., 2002. Lung

ur

cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. Jama 287, 1132-1141.

Jo

Qiao, L., Cai, J., Wang, H., Wang, W., Zhou, M., Lou, S., Chen, R., Dai, H., Chen, C., Kan, H., 2014. PM2.5 constituents and hospital emergency-room visits in Shanghai, China. Environmental science & technology 48, 10406-10414.

Riva, D.R., Magalhaes, C.B., Lopes, A.A., Lancas, T., Mauad, T., Malm, O., Valenca, S.S., Saldiva, P.H., Faffe, D.S., Zin, W.A., 2011. Low dose of fine particulate matter (PM2.5) can induce acute oxidative stress, inflammation and pulmonary impairment in healthy mice. Inhalation toxicology 23, 257-267.

23

Roubicek, D.A., Gutierrez-Castillo, M.E., Sordo, M., Cebrian-Garcia, M.E., Ostrosky-Wegman, P., 2007. Micronuclei induced by airborne particulate matter from Mexico City. Mutation research 631, 9-15. Skuland, T.S., Refsnes, M., Magnusson, P., Oczkowski, M., Gromadzka-Ostrowska, J., Kruszewski, M., Mruk, R., Myhre, O., Lankoff, A., Ovrevik, J., 2017. Proinflammatory effects of diesel exhaust particles from moderate blend concentrations of 1st and 2nd generation biodiesel in BEAS-2B bronchial epithelial cells-The FuelHealth project. Environmental toxicology and pharmacology 52, 138-142. Solimini, A.G., D'Addario, M., Villari, P., 2015. Ecological correlation between diabetes hospitalizations

ro of

and fine particulate matter in Italian provinces. BMC public health 15, 708. Thomson, E.M., Breznan, D., Karthikeyan, S., MacKinnon-Roy, C., Charland, J.P., Dabek-Zlotorzynska, E., Celo, V., Kumarathasan, P., Brook, J.R., Vincent, R., 2015. Cytotoxic and inflammatory potential of size-fractionated particulate matter collected repeatedly within a small urban area. Particle and

-p

fibre toxicology 12, 24.

Valavanidis, A., Vlachogianni, T., Fiotakis, K., Loridas, S., 2013. Pulmonary oxidative stress,

re

inflammation and cancer: respirable particulate matter, fibrous dusts and ozone as major causes of lung carcinogenesis through reactive oxygen species mechanisms. International journal of

lP

environmental research and public health 10, 3886-3907.

Vargas, V.M., 2003. Mutagenic activity as a parameter to assess ambient air quality for protection of the

na

environment and human health. Mutation research 544, 313-319. Vinikoor-Imler, L.C., Davis, J.A., Luben, T.J., 2011. An ecologic analysis of county-level PM2.5 concentrations and lung cancer incidence and mortality. International journal of environmental

ur

research and public health 8, 1865-1871. Wang, P., Xue, Y., Han, Y., Lin, L., Wu, C., Xu, S., Jiang, Z., Xu, J., Liu, Q., Cao, X., 2014. The STAT3-

Jo

binding long noncoding RNA lnc-DC controls human dendritic cell differentiation. Science (New York, NY) 344, 310-313.

Wei, Y., Han, I.K., Shao, M., Hu, M., Zhang, O.J., Tang, X., 2009. PM2.5 constituents and oxidative DNA damage in humans. Environmental science & technology 43, 4757-4762. Yang, Y., Duan, W., Jin, Z., Yi, W., Yan, J., Zhang, S., Wang, N., Liang, Z., Li, Y., Chen, W., Yi, D., Yu, S., 2013. JAK2/STAT3 activation by melatonin attenuates the mitochondrial oxidative damage induced by myocardial ischemia/reperfusion injury. Journal of pineal research 55, 275-286. 24

Yoon, S., Han, S., Jeon, K.J., Kwon, S., 2018. Effects of collected road dusts on cell viability, inflammatory response, and oxidative stress in cultured human corneal epithelial cells. Toxicology letters 284, 152-160. Zhao, J., Xie, Y., Jiang, R., Kan, H., Song, W., 2011. Effects of atorvastatin on fine particle-induced inflammatory response, oxidative stress and endothelial function in human umbilical vein endothelial cells. Human & experimental toxicology 30, 1828-1839. Zhou, Z., Liu, Y., Duan, F., Qin, M., Wu, F., Sheng, W., Yang, L., Liu, J., He, K., 2015. Transcriptomic Analyses of the Biological Effects of Airborne PM2.5 Exposure on Human Bronchial Epithelial

Jo

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Cells. PloS one 10, e0138267.

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Fig.1 Effects of PM2.5 on cell viability

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Fig.2 Effects of PM2.5 on pro-inflammatory cytokines levels in 16HBE cells

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Fig.3 Effect of PM2.5 on protein expression of cell STAT3/ p-STAT3. B

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Control 100μg/mL

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Fig.4 PM2.5-induced Alteration of the lncRNA expression profileand in 16HBE cells and lncRNA screening

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Fig.5Decreased level of LOC101927514 and increase a promotion of inflammation during

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PM2.5 exposure after LOC101927514 was konck down in 16HBE cells.

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p-STAT3

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Fig.6 Nuclear located LOC101927514 was increased in PM2.5-induced 16HBE cells and STAT3 was identified as a binding target of LOC101927514

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Table1 Concentrations of polycyclic aromatic hydrocarbons (PAHs) and Metal Elements in PM2.5 Concentration(ng/m3)

PAHs

Metals

Concentration 1.620±1.230

0.020±0.010

Mgb

0.370±0.310

0.003±0.002

Alb

0.940±0.880

0.040±0.020

Sib

3.650±2.360

0.310±0.240

Kb

1.730±0.960

0.030±0.020

Cab

1.520±1.470

Fluorene

0.590±0.550

Tia

18.54±20.17

Pyrene

0.570±0.530

Cra

19.26±18.74

Benz[a]anthracene

0.410±0.460

Mna

58.69±24.35

Chrysene

0.630±0.560

Feb

0.870±0.760

1.460±1.250

Nia

0.600±0.470

Cua

0.970±0.820

Znb

0.630±0.390

1.420±0.910

Asa

21.43±15.38

Cda

4.570±2.860

Pba

91.34±73.27

ΣMetals

11.621±8.568

Acenaphthylene Acenaphthene Fluoranthene Phenanthrene Anthracene

Benzo[b]fluoranthene Benzo[k]fluoranthene Benzo[a]pyrene Indeno[123-cd]pyrene

0.240±0.180

Benzo[ghi]perylene

1.630±1.270

ΣPAHs

9.050±6.820

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Dibenz[a,h]anthracene

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Naphthalene

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0.120±0.070

Nab

72.45±50.12

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ang/m3 ; bμg/m3

8.410±6.170

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Table 2 Concentrations of water soluble ions in PM2.5 Water soluble ions

Concentration(μg/m3)

F-

0.060±0.030

Cl-

0.590±0.480

2-

10.820±4.760

NO3

-

5.910±5.340

Na+

1.230±0.570

NH4+

3.740±2.210

K+

0.540±0.330

Mg2+

0.070±0.030

Ca2+

0.590±0.470

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Table 3 Concentrations of organic(OC) and elemental carbon (EC) in PM2.5 Concentration（μg/m3） 8.760±4.810

EC

3.910±2.670

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OC

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