Analysis of Long Noncoding RNA Expression Profile in Human Pulmonary Microvascular Endothelial Cells Exposed to Lipopolysaccharide
Dong Wang Changping Gu Mengjie Liu Ge Liu Huan Liu
Yuelan Wang
Department of Anesthesiology, Qianfoshan Hospital, Shandong University, Jinan, China
Key Words
Long noncoding RNA • Expression profile • Acute lung injury • Lipopolysaccharide • Human pulmonary microvascular endothelial cell
Abstract
Background/Aims: Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are a continuum of life-threatening lung changes. Pulmonary vascular injury is one of the most important initial causes of ALI and ARDS. However, the functions of long noncoding RNAs (lncRNAs) in pulmonary endothelial injury remain largely unknown. The aim of the present study was to determine the lncRNA expression profile of human pulmonary microvascular endothelial cells (HPMECs) exposed to lipopolysaccharide (LPS) and explore the potential functions of differentially expressed lncRNAs. Methods: Microarray analysis was used to identify differentially expressed lncRNAs and mRNAs. Bioinformatics analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, lncRNA-mRNA coexpression network and transcription factor (TF)-lncRNA network analyses, were performed to predict the functions of significantly differentially expressed lncRNAs and mRNAs. Real-time polymerase chain reaction (PCR) was used to determine the expression of selected lncRNAs and mRNAs. Results: In this study, we found that 213 lncRNAs and 212 mRNAs were significantly differentially expressed in HPMECs exposed to LPS (fold change > 2.0, p < 0.05). Furthermore, we found that mRNAs co-expressed with lncRNAs were significantly enriched in the TNF signaling pathway, the NF-κB signaling pathway, cell adhesion molecules (CAMs), cytokine-cytokine receptor interactions, and extracellular matrix (ECM)-receptor interactions. The expression levels of all but one of the selected lncRNAs and mRNAs detected by real-time PCR were similar to those detected by microarray analysis. Conclusion: Our data indicate that lncRNAs play an important role in LPS-induced pulmonary endothelial inflammation and barrier dysfunction and may be potential preventive and therapeutic targets for ALI and ARDS.
Introduction
Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are part of a continuum of life-threatening lung changes that interfere with the diffusion of oxygen from alveoli into the blood [1-4]. Sepsis and pneumonia are the most common causes of ARDS, and pulmonary vascular injury is one of the most important initial causes of ALI and ARDS. ARDS accounts for 10% of intensive care unit admissions globally. Despite years of basic and clinical studies, the global mortality of ARDS has been as high as 40% in recent years [5, 6]. For these reasons, the identification of key molecules involved in ARDS is highly demanded for improving the clinical outcome of this syndrome.
It is now generally accepted that the majority of mammalian RNA transcripts are noncoding RNAs (ncRNAs). Long noncoding RNAs (lncRNAs), which are longer than 200 nucleotides, are generally not translated into proteins [7-10]. By regulating gene expression at posttranscriptional, transcriptional and epigenetic stages, lncRNAs participate in most essential biological processes. Over the past decade, the study of lncRNAs has become a hot spot in basic and clinical research of ALI and ARDS. Recent studies have shown that miRNAs are involved in the pathophysiology of ARDS and may be interesting diagnostic biomarkers and therapeutic targets [11-20]. However, less is known about the role of lncRNAs in the pathogenesis of ALI and ARDS.
To study the function of lncRNAs in the pathogenesis of ALI and ARDS, we established an experimental model of pulmonary endothelial inflammation and barrier dysfunction by stimulating HPMECs with LPS [21-24] and investigated the expression profile of lncRNAs and mRNAs by microarray analysis. We found that 213 lncRNAs and 212 mRNAs were significantly differentially expressed. Bioinformatics analyses indicated that the differentially expressed lncRNAs might play an important role in LPS-induced pulmonary endothelial inflammation and barrier dysfunction. These findings will serve to increase the understanding of the pathogenesis of pulmonary endothelial dysfunction. Moreover, due to opportunities to identify novel therapeutic and preventive targets, our results may provide relevant information for future clinical interventions of ALI and ARDS.
Materials and Methods
Cell culture, LPS treatment, and RNA isolation
Human pulmonary microvascular endothelial cells (HPMECs, ScienCell, San Diego, CA, USA) were cultured in endothelial cell medium (ECM, ScienCell, San Diego, CA, USA) in a humidified 5% CO2 incubator at 37°C. LPS (Sigma, St Louis, MO, USA) from Escherichia coli O111:B4 was dissolved in sterile water and prepared fresh at the time of use. At approximately 90% confluence in culture, HPMECs were starved for 1 hour (h) in serum-free medium and then stimulated for 4 h with LPS (1 µg/ml) or vehicle control (PBS) in ECM containing 1% FBS as previously described [14] [21] [25]. HPMECs were used in passage numbers 4 to 6. Total RNA was isolated using TRIzol reagent (Invitrogen, Carlsbad, CA, USA). The quality of the RNA preparations was verified on an Agilent 2100 bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
Microarray analysis
Total RNA was hybridized to Affymetrix Human Transcriptome Array 2.0 (Affymetrix, Santa Clara, CA, USA). Hybridized data were preprocessed and statistically analyzed as described previously [26, 27]. Differentially expressed lncRNAs and mRNAs were identified by fold-change screening at a threshold of 2.0-fold or greater and a p value < 0.05.
GO and KEGG pathway analyses
GO analysis (http://www.geneontology.org) was performed to explore functions of genes based on the biological pathway, cellular component and molecular function categories; Kyoto Encyclopedia of Genes and Genomes (KEGG) (http://www.genome.jp/kegg/) analysis was performed to determine pathways significantly enriched in genes. P < 0.05 and FDR < 0.05 were used as thresholds to define significantly enriched GO terms or pathways.
Real-time PCR
A FastQuant RT Kit (Tiangen, Beijing, China) was used to reverse transcribe total RNA into cDNA following the manufacturer's directions. Real-time PCR was performed using SuperReal PreMix Plus (SYBR Green) (Tiangen, Beijing, China) in the Applied Biosystems GeneAmp® PCR System 9700. The reaction conditions were as follows: incubation at 95°C for 15 min, followed by 40 cycles of 95°C for 10 s and 60°C for 20 s. The relative expression levels of lncRNAs were calculated using the 2-ΔΔCt method and normalized to GAPDH levels [28]. The primers for each lncRNA and mRNA are listed in Table 1.
LncRNA-mRNA coexpression network
A lncRNA-mRNA coexpression network was constructed to identify the interactions between lncRNA and mRNA according to the normalized signal intensity of specific mRNA and lncRNA expression levels as described previously [29, 30].
TF-lncRNA network
Transcription factors (TFs) and DNA sequence motifs from 2.0 kilobase upstream of the transcription start site of differentially expressed lncRNAs were predicted with the TRANSFACT professional database (http://gene-regulation.com/). TFs with a matrix score and core score equal to 1 were selected.
Statistical analysis
All data are expressed as the mean ± SEM. For comparisons between 2 groups, unpaired Student's t-test for parametric data and Mann-Whitney's U-test for nonparametric data were used. All statistical analyses were performed with GraphPad Prism 7.04 (GraphPad Software, San Diego, CA, USA). A p value < 0.05 was considered statistically significant.
Results
Profiles of the differentially expressed lncRNAs and mRNAs
To evaluate the differential expression of lncRNAs in HPMECs stimulated with LPS, we performed microarray analysis of the lncRNA expression profile using Affymetrix Human Transcriptome Array 2.0, which covers 245, 349 coding transcripts and 40, 914 noncoding transcripts.
We found that 213 lncRNAs were significantly differentially expressed (fold change > 2.0, p < 0.05). Of these, 189 lncRNAs were upregulated and 28 lncRNAs were downregulated (Fig. 1A, Fig. 1C). The top 20 most significantly upregulated (Table 2) and downregulated (Table 3) lncRNAs are listed below. At the same time, 212 mRNAs were significantly differentially expressed (fold change > 2.0, p < 0.05), including 183 upregulated mRNAs and 29 downregulated mRNAs (Fig. 1B, Fig. 1D). The top 20 most significantly upregulated (Table 4) and downregulated (Table 5) mRNAs are listed below.
Although differentially expressed lncRNAs and mRNAs were widely scattered among all chromosomes, the distribution was not equal (Fig. 1E, Fig. 1F). Chromosome 1 and chromosome 6 had the largest number of differentially expressed mRNAs and lncRNAs, respectively. Chromosome X had the largest number of downregulated lncRNAs. Fifty-two differentially expressed lncRNAs could not be assigned to corresponding chromosomes.
GO and KEGG enrichment analyses
To explore the role of differentially expressed mRNAs in HPMECs treated with LPS, we performed GO and KEGG pathway enrichment analysis.
The results showed that upregulated genes were mainly associated with the following functions: response to lipopolysaccharide (ontology: biological process), integrin complex (ontology: cellular component), and cytokine activity (ontology: molecular function) (Fig. 2A). Downregulated genes were mainly associated with the following functions: male pronucleus (ontology: cellular component), C-terminal protein deglutamylation (ontology: biological process), and exopeptidase activity (ontology: molecular function) (Fig. 2B). The results also indicated that upregulated genes were mainly associated with the following pathways: TNF signaling pathway, cytokine-cytokine receptor interaction, rheumatoid arthritis, NOD-like receptor signaling pathway, and cell adhesion molecules (CAMs) (Fig. 2C). The five most enriched pathways of downregulated genes were mineral absorption, progesterone-mediated oocyte maturation, riboflavin metabolism, cell cycle, and systemic lupus erythematosus (Fig. 2D).
These data suggested that upregulated mRNAs may directly participate in the process of pulmonary endothelial inflammation and barrier dysfunction.
LncRNA-mRNA coexpression networks with GO and KEGG enrichment analysis
To explore the potential biological functions of lncRNAs in HPMECs treated with LPS, we constructed a lncRNA-mRNA coexpression network based on 72 differentially expressed lncRNAs and 132 interacting differentially expressed mRNAs (Fig. 3A). Then, we performed GO and KEGG pathway enrichment analysis on the 132 mRNAs. We found that the most enriched GOs were leukocyte migration (ontology: biological process), cytokine activity (ontology: molecular function), and external side of plasma membrane (ontology: cellular component) (Fig. 3B). The results also indicated that the 132 mRNAs were mainly associated with the following pathways: TNF signaling pathway, NF-κB signaling pathway, CAMs, cytokine-cytokine receptor interaction, and ECM-receptor interaction (Fig. 3C).
Real-time PCR validation of the microarray data
To validate the reliability of the microarray analysis results and to provide a research basis for further study, the expression levels of 6 lncRNAs (MIR3142HG, n344917, XLOC_l2_015215, n340107, n407205 and XIST) and 8 mRNAs (SELE, IL8, VCAM1, ICAM1, CXCL10, MMP10, ABI3BP and TRPC6) were determined by real-time PCR (Fig. 4). The results showed that MIR3142HG, XLOC_l2_015215, n340107 and n407205 were upregulated, whereas XIST was significantly downregulated. The expression of n344917 showed no significant change. SELE, IL8, VCAM1, ICAM1, CXCL10, MMP10, ABI3BP and TRPC6 were upregulated. These data suggest that the expression levels of selected lncRNAs and mRNAs, except for n344917, detected by real-time PCR were similar to those detected by microarray analysis.
TF-lncRNA regulatory network
To understand the reason for the differential expression of the five validated lncRNAs (MIR3142HG, XLOC_l2_015215, n340107, n407205 and XIST), we predicted TFs mapping to these lncRNAs in the TRANSFACT professional database. The results showed that of the 214 TFs mapping to these lncRNAs (Fig. 5), 17 out of the 214 TFs were differently expressed (fold change > 1.2, p < 0.05). Seven differentially expressed TFs were predicted to regulate the transcription of XIST (Table 6), including 2 upregulated TFs (POU2F2 and BCL6) and 5 downregulated mRNAs (SOX18, MEF2C, SOX17, HOXB5 and ETS2). These findings indicate that differently expressed TFs might be one of the causes of the differential expression of lncRNAs.
Discussion
In
this study, we
established an experimental
model of pulmonary endothelial inflammation and barrier dysfunction by
stimulating HPMECs with LPS and investigated the expression profile of lncRNAs and
mRNAs by microarray analysis. The results indicate that lncRNAs play an
important role in LPS-induced pulmonary endothelial inflammation and barrier
dysfunction. An overwhelming
majority of the transcriptions of the human genome are ncRNAs, which act as
important transcriptional regulators in pathophysiologic processes [31-33]. In
contrast to miRNAs, which regulate target genes by a posttranscriptional
mechanism [34, 35], lncRNAs have the potential to regulate gene expression at posttranscriptional,
transcriptional and epigenetic levels [36-39]. Furthermore, many lncRNAs have shown developmental
stage-specific and tissue-specific expression patterns [40, 41]. The roles of
ncRNAs in the pathogenesis of ALI and ARDS have
attracted increasing
attention.
Recent studies have demonstrated that several miRNAs, such as miR-146, miR-155,
and miR-221, serve as important
regulators of inflammation-related mediators [33]. Hongbin Li et al. reported that the lncRNA CASC2 improved ALI by
reducing lung epithelial cell apoptosis [42]. However, the function of lncRNA
has not been investigated in pulmonary vascular injury associated with ALI and ARDS.
Unlike two previous studies that analyzed the lncRNA
expression profile in human umbilical vein endothelial cells [43] and human dermal
microvascular endothelial cells [44] exposed to LPS, we identified the expression of LPS-responsive lncRNAs in
HPMECs to investigate the role of lncRNAs in pulmonary endothelial injury. In the present
study, we determined the expression of 6 lncRNAs and 8 mRNAs
by real-time
PCR. The
selection of these lncRNAs and mRNAs was based on the fold change
and degree data in the lncRNA-mRNA coexpression network. Our results
showed that the lncRNA and mRNA expression results determined by microarray
analysis had good reliability and reproducibility. LPS successfully activated
HPMECs because the expression of SELE, IL-8,
VCAM-1, CCL20 and ICAM-1 increased significantly in the experimental model
[45-47]. In
addition,
GO and KEGG pathway enrichment analyses also suggested that the differentially
expressed mRNAs participated in pulmonary endothelial inflammation and barrier
dysfunction. Notably, based on GO and KEGG pathway enrichment analyses of the lncRNA-mRNA
coexpression network, we found that 72 differentially expressed lncRNAs might
be mainly involved in the TNF signaling
pathway, NF-κB signaling pathway, CAMs, cytokine-cytokine
receptor interactions, and ECM-receptor interactions [48, 49]. Thus, we
speculated that these lncRNAs might be associated with pulmonary endothelial
inflammation and barrier dysfunction. Furthermore, we predicted differentially expressed TFs
mapping to five selected lncRNAs that had been verified by real-time PCR with the
help of the TRANSFAC professional database. The results suggested that
differently expressed TFs might be one of the causes of the differential
expression of lncRNAs. The
understanding of the diversity of gene regulation has greatly expanded in the
past decade. There is increasing recognition that ncRNAs are important
components of the gene regulatory network [50]. As the roles of
lncRNAs become clearer, the knowledge acquired by this research will enable the
understanding of how lncRNAs affect the initiation, progression, and resolution
of pulmonary endothelial dysfunction associated with ALI and ARDS. Our data
still need to be further validated in both vitro and vivo. XIST, which is the
master regulator of X chromosome inactivation, has been reported to play an important role in the pathogenesis of many
diseases [51,
52].
H Yu et al. reported that XIST inhibition increased the blood-tumor barrier
permeability in glioma endothelial cells [53]. Here, we found that XIST
was significantly downregulated in HPMECs exposed to LPS by both microarray
data and real-time PCR. This is the first study to determine the expression of
XIST in HPMECs. The results may be helpful for further insights into the
underlying role and mechanism of XIST in pulmonary
endothelial inflammation and barrier dysfunction. The detailed function of XIST
in pulmonary
endothelial injury still needs to be further investigated. Although not a
genetic disease, ARDS has a certain hereditary susceptibility [54]. Three
retrospective studies reported that men were at higher risk than women of
incidence and mortality from ARDS [55-57]. In this study, we found that the
distribution of differentially expressed lncRNAs was not equal. Interestingly, most
differentially expressed lncRNAs on chromosome X were downregulated, while all
differentially expressed lncRNAs on chromosome Y were upregulated. We speculate that the differential expression of lncRNAs on chromosomes X and Y may be
one of the causes of sex-related differences in the morbidity and mortality of
ARDS. Of course, this subject still requires more clinical research and further
investigations. Conclusion In conclusion, we
investigated the expression of lncRNAs and mRNAs in HPMECs treated with LPS by
microarray analysis. We found that lncRNAs may be involved in LPS-induced pulmonary
endothelial inflammation and barrier dysfunction. This is the first study to reveal the expression
profile and potential role of lncRNAs in HPMECs. These findings provide a novel
direction for both basic and clinical research for ALI and ARDS. Due to
opportunities to identify novel therapeutic and preventive targets, our results
may provide relevant information for future clinical interventions of ALI and
ARDS. Acknowledgements This work was
supported by the National Natural Science Foundation of China (No. 81770076,
No. 81570074 and No. 81600054) and Joint Project of Shandong Natural Science
Foundation (ZR2015HL002). Disclosure
Statement The authors
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