Abstract
Background/Aim: Chronic obstructive pulmonary disease (COPD) has become a prominent healthcare issue in recent years. Cigarette smoking (CS) and fine particulate matter (PM2.5) are important causative factors for COPD. This study assessed the aberrant lncRNA profiles in the tissue of rats with COPD caused by CS or PM2.5. Materials and Methods: A COPD rat model was developed using CS (CSM) or PM2.5 (PMM), and lung tissue RNA was extracted. The Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) were used to investigate the correlations between the distinct lncRNAs and mRNA pathways. A coding-non-coding gene co-expression network (CNC) was constructed by establishing connections between differentially expressed long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) associated with mitochondrial dysfunction and the inflammatory response. Results: A quantitative real-time reverse transcription PCR (qRT-PCR) experiment was performed to verify the expression of the particular lncRNAs. Microarray analysis of lung tissue from the COPD model revealed that 123 and 444 lncRNAs were substantially raised and reduced in PMM vs. the control group (Ctrl), respectively, as were 621 and 1,178 mRNAs. Meanwhile, 81 and 340 lncRNAs were consistently raised and lowered in CSM vs. Ctrl, respectively, as were 408 and 931 mRNAs. GO enrichment and KEGG pathway analysis indicated that the COPD model was connected to inflammatory responses, mitochondrial dysfunction, and others. Conclusion: XR_340674, ENSRNOT00000089642, XR_597045, and XR_340651 were decreased, and XR_592469 was elevated. These lncRNAs were shown to be related to mitochondrial dysfunction in the lung tissue of animals exposed to CS or PM2.5.
- Chronic obstructive pulmonary disease
- lncRNAs
- fine particulate matters
- cigarette smoke
- mitochondrial dysfunction
Chronic obstructive pulmonary disease (COPD) has been identified as a primary cause of mortality and morbidity (1). COPD is characterised by a reduction in lung performance that is irreversible, and a limitation of airflow that is incompletely reversible and persistent (2). In China, COPD was estimated to affect approximately 14.6% of the elderly and ranks third among all causes of mortality. COPD is initiated and exacerbated by various factors, including inflammatory infiltration, oxidative stress, the delicate equilibrium between protease and antiprotease activities, and dysfunction of the mitochondria (3, 4). Mitochondria serve as vital organelles for several aspects of cell homeostasis, such as energy produced via oxidative phosphorylation, etc. At present, mitochondrial dysfunction, such as excessive generation of mitochondrial reactive oxygen species (mtROS), mitochondrial fusion/fission dysregulation, mitochondrial fragmentation and mitophagy disorder (5), is implicated in the development and progress of COPD (6-9).
Cigarette smoking (CS) and air contamination are significant causes of COPD (1, 10, 11). Fine particulate matter (PM2.5) is a major constituent of ambient air pollution (12), which can affect human health and be a risk factor for many diseases, including heart disease, respiratory infections, and COPD (12-14). PM2.5 are minute airborne particulates that decrease visibility and make the air appear cloudy when concentrations are high. When airway epithelial cells are treated by cigarette smoke extraction (CSE), mitochondrial morphology and function are impaired (15). Also, mitochondrial dysfunction is driven by PM2 5-induced cellular senescence, redox imbalance, apoptosis, and autophagy in lung cells (16-18). However, the regulatory mechanism that determines the relationship between mitochondrial dysfunctions and the pathogenesis of COPD is not fully known.
Previous studies indicated that aberrant long non-coding RNA (lncRNA) expression is related to defective regulation, which eventually leads to pathological changes in several distinct issues (19, 20). Certain lncRNAs may be promising biomarkers for the diagnostic and prognosis of COPD (21, 22). There are some mitochondria-associated lncRNAs, which have been shown to play roles in the pathogenesis of cancer (23). But which roles of lncRNAs are associated with mitochondrial dysfunctions are important for COPD remains to be elucidated. Considering the potential modulatory impact of the CS or PM2.5, this assessed COPD-relevant cellular and biological functions, including cell biological processes, cellular function, and molecular function, as well as signalling pathways.
Materials and Methods
Animals and treatment. IAs previously described (24), 30 male Wistar rats weighing 175-185 g were acquired from the animal laboratory of SLAC (Shanghai, PR China). Animals were housed in a closed chamber with a 12:12 light/dark sequence and supplied with water and food ad libitum. The animals were divided into 3 groups (n=10) at random. The first group (PMM) was exposed to PM2.5 by employing a 405C medical nebulizer (Putian, PR China). The second group (CSM) was exposed to 6 Shishi cigarettes (flue-cured tobacco type, 0.7 mg of nicotine, 10 mg of tar, and 12 mg of flue gas carbon monoxide, Fujian China Tobacco Industry Co., Ltd., PR China), and the control group (Ctrl), which was injected with 0.9% sodium chloride injection (Anhui Fengyuan, Shenzhen, PR China) Treatments continued for 90 days. This set of procedures was authorized by the Affiliated Hospital of Putian University’s ethics committee (Approval No. 201924). The experimental flow chart is shown in Figure 1.
The flow chart of this study.
Pulmonary test of animal modelling. After the experiment, the animals were given a pentobarbital anesthetic before having 250 μl of arterial blood drawn from the abdominal aorta for analysis by a blood gas analyser (NOVA-cCX, NOVA Biomedical, Waltham, MA, USA). In addition, the animals’ lungs were collected, dissected, and cleaned with PBS, then fixed in a 10% neutral formalin fix solution for 24 h and processed for histological assessment with hematoxylin-eosin (HE). The histological changes were evaluated under a light microscope (DM1L, Leica, Wetzlar, Germany). The expression of Mfn2 and Fis1 in the lung tissue of rats was quantified using immunohistochemistry (IHC), and the sections were visualized and assessed as per the descriptions of Lin et al. (24).
RNA extraction and microarray assay. Three animals from all groups were randomly chosen. Total RNA was isolated from the whole lung tissues and used in an RNA microarray test at Shanghai Kanchen Bio-tech (Shanghai, PR China) employing the Arraystar lncRNAs microarray (Arraystar Rat LncRNA 1color V3 4x44k, Rockville, MD, USA). Briefly, the whole lung tissue was cryopulyerized using the Biopulyerizer (Biospec, Bartlesville, OK, USA) and total RNA extracted with TRIzol Reagent (Invitrogen, Carlsbad, CA, USA) then rinsed using 75% ethanol and precipitated by isopropyl before being redissolved in RNase-free water. The RNA integrity and quantity were enumerated using 1% agarose electrophoresis and Nanodrop Spectrophotometer (Thermo Fisher, ND-1000, Waltham, MA, USA). The total RNA was labelled using the Quick Amp Labeling Kit (Agilent, p/n 5190-0042) and hybridized with lncRNAs microarray (Agilent, p/n G2545A, Santa Clara, CA, USA), washed twice, and assessed with the Agilent Microarray Scanner (Agilent, p/n G2565BA). The array images were assessed utilizing the Microarray Data Processing Agilent feature extraction software (version 11.0.1.1). The actual intensity data was adjusted for normality using the quantile approach, and the data were assessed using the GeneSpring GX tool (Version 12.1). p<0.05 and fold change >2.0 were used to filter lncRNAs and mRNAs with significantly different expression among the two groups.
GO enrichment and KEGG pathway assessment. For investigating the potential biologic activities of differentially expressed mRNA, the conventional enrichment computation approach was used to conduct GO enrichment analysis in the differentially expressed mRNA database and comparisons were made between the two groups (Ctrl vs. CSM, Ctrl vs. PMM, and CSM vs. PMM). GO analysis classified the function of protein-coding genes in detail and divided them into 3 subcategories: biological process (BP), cellular component (CC), and molecular function (MF). The functional assessment technique that maps genes to KEGG pathways analysis (25) was utilized, and the level of enrichment of the genes in each pathway was analysed statistically. Both GO and KEGG analysis were tested using Fisher’s Exact test to assess the proportion of genes related to the GO and KEGG terms in the database reference genes. The enrichment score of each biological phrase was given by the −log10 (p-value).
Building a network of CNC. The CNC network was developed using correlation assessment among differentially expressed lncRNAs and mRNA to assess the mRNAs controlled by lncRNAs. The PCC and p-value were determined based on the normalised intensity of lncRNA and mRNA. The dysregulated mitophagy related to COPD development was calculated by assessing the PCC between mitophagy-related genes and lncRNA profiles and then choosing some lncRNAs from the database for further validation. The network was visualised employing Cytoscape 3.8.0.
qRT-PCR. Total RNA was extracted from the entire lung tissue with TRIzol (Invitrogen), then reverse-transcribed into cDNA utilising random primers (Generay, Shanghai, PR China) and SuperScript TM III Reverse Transcriptase (Invitrogen), and amplified. qRT-PCR was performed using SYBR green 2xPCR master mix (Arraystar, cat # AS-MR-005- 25) and ViiA 7 real-time PCR system (Applied Biosystems, Waltham, MA, USA). The level of relative expression was normalized to the reference gene GAPDH and measured as a fold change using the 2−ΔΔCt method.
Statistical assessment. The statistical value was calculated using R programming and visualized with the ggplot2 packages. The captions of the figures provide details on statistical methodologies. Data are presented as mean±SEM. For the evaluation of three groups, a one-way ANOVA was employed, with p<0.05 regarded as statistically significant.
Results
The pulmonary injury test. The findings of the arterial blood gas test revealed that the CSM and PMM groups had considerably greater blood gas levels than the Ctrl group (Figure 2A-D). Hematoxylin-eosin (HE) staining of lung tissues in the CSM group and the PMM groups revealed that the bronchus lumen was seriously destroyed, and the wall of the bronchus was damaged and thickened (Figure 2E). IHC analysis (Figure 2F) showed that the CSM and PMM groups had substantially lower expression of Mfn2 (p<0.05) and Fis1 (p<0.05) in comparison to the Ctrl group (Figure 2G-H), which may be a significant factor in the pathological manifestation of COPD (26, 27), indicating that the CSM and PMM groups developed mitochondrial dysfunction and dynamics disorder compared with the Ctrl group. Taken together, the above evidence shows that the COPD rat model was constructed successfully.
Pulmonary injury in experimental animals. (A-D) The results of arterial-blood gas test suggested that the PMM and CSM groups had bad pulmonary function compared with the Ctrl group (ANOVA test, N=6); (E) HE staining of experimental rat lung tissue viewed under the light microscope (magnification ×100, scale bars=50 μm or magnification ×400, scale bars=10 μm). (F) Image of IHC processing of rat lung tissue viewed under a light microscope (magnification ×400, scale bars=20 μm); (G) The expression of Mfn2 in the PMM and CSM groups was lower than that in the Ctrl group, N=3; (H) The expression of Fis1 in the PMM and CSM groups was lower than that in the Ctr group, N=3. Values are described as the mean±SEM, *p<0.05, ***p<0.001 vs. Ctrl.
The biological function of lncRNA in COPD. lncRNAs are pivotal regulators in multiple cell types and tissues (28). However, the significance of lncRNAs in COPD is elusive. The lncRNA expression profiles of the 3 groups were analysed. In the PMM group, 123 and 444 lncRNAs were significantly elevated and down-regulated, with p<0.05 and fold change >2, compared to the Ctrl group, whereas 621 and 1,178 mRNAs were substantially elevated and down-regulated, respectively (Figure 3A and B). Furthermore, 81 and 340 lncRNAs were consistently up-regulated and down-regulated, respectively, in the CSM group, and 408 and 931 mRNAs were up-regulated and down-regulated Figure 3C and D. Following this, a comprehensive evaluation was undertaken to explore the correlation between lncRNAs, and the variations in gene expression were analysed in both the PMM and CSM groups. The Venn diagrams showed that 38 lncRNAs up-regulated in both the PMM and CSM groups, and 262 lncRNAs were down-regulated. Additionally, the analysis of corresponding mRNAs in the CSM and the PMM groups indicated that 131 mRNAs were increased and 641 mRNAs were decreased (Figure 3E-H).
Microarray expression profiles of lncRNAs and mRNAs in the lung tissues. Volcano plot: (A) and (B). The differential expression of lncRNAs and mRNAs in the PMM group vs. the Ctrl group. (C) and (D) The differential expression of lncRNAs and mRNAs in the CSM group vs. the Ctrl group. (E) and (F) Venn diagram of up-regulated lncRNAs expression and down-regulated lncRNAs in the CSM and the PMM groups; (G) and (H) Venn diagram of up-regulated mRNA expression and down-regulated mRNA expression in the CSM and PMM groups.
The significance of differentially expressed mRNAs in the CSM and PMM groups was explored using GO enrichment and KEGG pathway assessment. The p value from Fisher’s exact test indicates the importance of GO term enriched in the differentially expressed genes. The more important the GO terms, the lesser the p-value (p<0.05 was suggested). In a comparison of the PMM group with the Ctrl group, the up-regulated mRNAs were enriched in 1,425 BP terms, 42 CC terms, and 106 MF terms. The down-regulated mRNAs were enriched in 1,158 BP terms, 130 CC terms, and 154 MF terms. GO enrichment analysis showed that the different transcripts between the PMM and the Ctrl group were mainly associated with metabolic processes (ontology: BP), intracellular processes (ontology: CC), and RNA polymerase II (ontology: MF) (Figure 4A and B). In the comparison of the CSM and the Ctrl group, the up-regulated mRNAs were enriched in 913 BP terms, 49 CC terms, and 75 MF terms, whereas the down-regulated mRNAs were enriched in 737 BP terms, 126 CC terms, and 112 MF terms. As demonstrated in Figure 4C and D, the substantially differentially expressed mRNAs between the CSM and Ctrl groups were also associated with inflammatory response (ontology: BP), mitochondrial envelope (ontology: CC), and ion binding (ontology: MF). KEGG pathway analysis was used to enrich pathway clusters containing our differentially expressed mRNAs on the gene interaction and reaction networks. The results indicated that there were 47 up-regulated pathways and 64 down-regulated pathways in the PMM group versus the Ctrl group. Furthermore, there were 32 up-regulated pathways and 47 down-regulated pathways in CSM versus Ctrl. The top 10 pathways corresponding to significantly differentially expressed transcripts were selected for graphical display (Figure 4E-H).
GO enrichment analysis of differentially expressed mRNAs. (A) Top ten GO terms of up-regulated mRNAs in the PMM group; (B) Top ten GO terms of down-regulated mRNAs in the PMM group; (C) Top ten GO terms of up-regulated mRNAs in the CSM group; (D) Top ten GO terms of down-regulated mRNAs in the CSM group; KEGG pathway enrichment of dysregulated mRNAs. (E) Top ten pathway terms of up-regulated mRNAs in the PMM group; (F) Top ten pathway terms of down-regulated mRNAs in the PMM group; (G) Top ten pathway terms of up-regulated mRNAs in the CSM group; (H) Top ten pathway terms of down-regulated mRNAs in the CSM group.
Overview of CNC network. CNC networks were constructed to investigate the relationship and potential modulation pattern between the lncRNA expression profile and the mRNA expression profile. Previously, research demonstrated that the formation and progression of COPD were correlated with mitochondrial dysfunction and inflammatory reactions (28). Therefore, 4 mRNAs were chosen related to mitochondrial dysfunction (Fis1, Mfn2, Ambra1, and Usp15) and 3 mRNAs related to the inflammatory response (Pck1, II1B, and Ripk3) (Table I). The constructed CNC network was established using a Pearson correlation coefficient (PCC) of PCC≥0.885 or PCC≤-0.885, P≤0.05 and False Discovery Rate (FDR)≤0.1. Through the intersection with differentially expressed lncRNAs (Figure 5), a total of 483 co-expressed lncRNAs were identified for the 7 mRNAs.
Expression of four down-regulated mitochondrial dysfunction related genes and three up-regulated inflammation related genes.
LncRNA-mRNA co-expression network based on lncRNAs and mRNA expression level in the three groups.
The expression of lncRNA in animal modelling. Depending on fold change and p-value in the microarray dataset, 6 lncRNAs (XR_340674, ENSRNOT00000091354, ENSRNOT000000 89642, XR_592469, XR_597045, and XR_340651) in lung tissue of the 3 groups were selected; their primer sequence is shown in Table II. First, because microarray assessment might have false positive results, qRT-PCR was used to corroborate the microarray assessment results for the chosen lncRNAs. The results showed that the chosen lncRNAs tend to be similar to those in the microarray based on the p-value (Figure 6A and B). However, there were also a lot of differences between the findings of microarray analysis and the results of qRT-PCR (Figure 6C).
qRT-PCR primer sequence.
LncRNAs expression was validated by qRT-PCR. (A) The fold change of six selected lncRNAs from the microarray using PCR in the PMM group versus the Ctrl group; (B) The fold change of the six selected lncRNAs from the microarray using PCR in the CSM group versus the Ctrl group; (C) The PCR validated true change of four lncRNAs in both the PMM group and the CSM group. Values are described as the mean±SEM (N=3), *p<0.05, ***p<0.001 vs. Ctrl.
The findings demonstrated a statistically significant difference in the expression of XR_340674, ENSRNOT00 00089642, XR_592469, XR_597045, and XR_340651 among the CSM group and the PMM group compared to the Ctrl group (p<0.05), but ENSRNOT00000091354 was not statistically significantly different between the three groups (p>0.05).
Discussion
At present, PM2.5 exposure represents a serious and major threat to the general population (29-32). It has been a significant COPD risk factor (33). However, no cohort investigation has been performed to examine how PM2.5 alone affected the onset and progression of COPD, because it was difficult to diagnose COPD patients without any other exposure factor in clinical settings. Hence, the animal trial was the most effective method of studying the toxicity of PM2.5 in vivo. This research established a COPD model in rats exposed to PM2.5 for 90 days, and positive control was developed by exposing rats to CS (30).
Mitochondrial dysfunction is a pathogenic characteristic of the development and progression of COPD, including CS or PM2.5 exposure (34). Li et al. (17) showed that high-dose of PM2.5 exposure to Sprague–Dawle (SD) rats resulted in mitochondrial fission/fusion dysfunction, changes in the expression of OPA1, Mfn1, Mfn2, Fis1, and Drp1, decreased activities of MnSOD, Na+K+-ATPase, and Ca2+-ATPase and increased levels of malondialdehyde (MDA). This investigation revealed that the expression Mfn2, Drp1, and Fis1 was changed, which indicated mitochondrial dysfunctions are a feature of COPD. However, the mechanism of CS- or PM2.5-induced mitochondrial dysfunction is not yet clear. lncRNAs are involved in the mechanism of toxicity of environmental risk factors (32). Bi et al. (20) found that patients with COPD showed alterations in hundreds of lncRNAs in non-smokers without COPD, smokers without COPD and smokers with COPD. Wang et al. (34) discovered that when the dosage of PM2.5 rose, aberrant expression of lncRNAs was also increased. The mechanism through which different risk factors induce lncRNAs associated with mitochondrial dysfunction in COPD is not fully understood.
The results of microarray datasets showed that there are hundreds of differentially expressed lncRNAs and mRNAs compared with the Ctrl group, which suggested that CS and PM2.5 altered the expression of many human genes. In this study, there were 38 lncRNAs up-regulated and 262 lncRNAs down-regulated following both PM2.5 and CS exposure. Also, there were 131 mRNAs up-regulated and 641 mRNAs down-regulated. In order to identify multiple cellular mediators and signalling pathways involved in the interaction between CS and PM2.5, a comprehensive investigation is required. Our microarray findings revealed that the mitophagy pathway mainly included 3 mRNAs, Mfn2, MAPK10, and USP15. Next, the expression of three mRNAs was considerably lower in both the PMM and CSM groups: Mfn2, Fis1, and USP15.
To study lncRNAs that may regulate mitochondrial dysfunction in COPD, CNC networks for Mfn2, Fis1, and USP15 were constructed. XR_340674, ENSRNOT00000 091354, ENSRNOT0000089642, XR_592469, XR_597045, and XR_340651 were selected based on PCC, P-value, and FDR. To confirm the abnormal expression of lncRNAs in the microarray dataset, qRT-PCR was performed. The results showed that XR_340674, ENSRNOT00000089642, XR_592469, XR_597045, and XR_340651 were potential biomarkers and therapeutic targets for COPD.
This study has limitations. First, in an experimental model exposed to PM2.5 or CS, it is difficult to realize PM2.5 exposure. For PM2.5 exposure modelling, the exposed dose is often higher than the actual PM2.5 concentration, which cannot simulate the real world. Second, rats were used to construct a COPD model and perform a microarray analysis. There are homology differences between rats’ lncRNAs and human genes, and it is difficult to find a homologous gene with the selected lncRNAs. Third, dysregulated lncRNAs associated with mitochondrial dysfunction were chosen; however, there were hundreds of lncRNAs differentially expressed in the COPD model. In theory, these lncRNAs might have potential effects on COPD pathogenesis and need further research.
Conclusion
The lncRNAs XR_340674, ENSRNOT00000089642, XR_597045, XR_340651, and XR_592469 were selected as being associated with mitochondrial dysfunction in the lung tissue of Wistar rats after exposure to PM2.5 or CS. The expression patterns of lncRNAs and mRNAs in the lung tissue of the COPD rat model were contrasted to those of the control group using RNA microarray assessment. Then bioinformatics analysis was conducted to predict the associated protein-coding gene sets of differentially expressed lncRNAs, analyse differentially expressed protein-coding gene biological functions, and indicate their impact on COPD-relevant cellular and biological processes, including cell biological processes, cellular function, and molecular function, as well as signalling pathways.
Acknowledgements
The Authors thank KangChen Biotech Inc. (Shanghai, China) for their assistance in providing the lncRNAs microarray service.
Footnotes
Authors’ Contributions
QL and CFZ contributed equally, CFZ and JYC performed the experiments. ZKG, QL and JYC performed animal modelling assessment. SYW, HYL and QL were involved in analysing the data. HYL and QL supervised and revised the research manuscript.
Funding
The General Program of the Natural Science Foundation of Fujian Province, China (2020J011251) and Training project for Young and Middle-aged Key Talents of Fujian Provincial Health Commission, China (2020GGA078) supported this study.
Conflicts of Interest
The Authors stated that they have no competing interests in relation to this study.
Data Availability
The data of this study have uploaded to Gene Expression Omnibus (GEO) and are openly available in GSE178513 at: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178513
- Received June 24, 2023.
- Revision received July 25, 2023.
- Accepted July 26, 2023.
- Copyright © 2023, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).