Stem Cells International

Stem Cells International / 2021 / Article

Research Article | Open Access

Volume 2021 |Article ID 6655526 | https://doi.org/10.1155/2021/6655526

Jia Liu, Yan Zhao, Qiannan Niu, Ni Qiu, Shuangyun Liu, Chunrong Li, Cuixia Li, Pei Miao, Libo Yan, Qiang Li, Zuolin Jin, "Long Noncoding RNA Expression Profiles of Periodontal Ligament Stem Cells from the Periodontitis Microenvironment in Response to Static Mechanical Strain", Stem Cells International, vol. 2021, Article ID 6655526, 14 pages, 2021. https://doi.org/10.1155/2021/6655526

Long Noncoding RNA Expression Profiles of Periodontal Ligament Stem Cells from the Periodontitis Microenvironment in Response to Static Mechanical Strain

Academic Editor: Yohei Hayashi
Received04 Oct 2020
Revised01 Mar 2021
Accepted08 Mar 2021
Published12 Apr 2021

Abstract

During the period of orthodontic tooth movement, periodontal ligament stem cells (PDLSCs) play an important role in transducing mechanical stimulation and tissue remodeling. However, our previous studies verified that the periodontitis microenvironment causes damage to the biological functions of PDLSCs and abnormal mechanical sensitivity. Long noncoding RNAs (lncRNAs) participate in the inflammatory pathogenesis and development of many diseases. Whether lncRNAs are abnormally expressed in PDLSCs obtained from periodontal tissues of periodontitis patients (PPDLSCs) and whether putative lncRNAs participate in the mechanotransductive process in PDLSCs remain poorly understood. First, we subjected PDLSCs obtained from healthy periodontal tissues (HPDLSCs) and PPDLSCs to static mechanical strain (SMS) with 12% elongation at 0.1 Hz frequency using an FX-4000T system and screened overall lncRNA profiles in both cell types by microarray. Among lncRNAs with a fold , 27 lncRNAs were upregulated in strained HPDLSCs, and 16 lncRNAs (9 upregulated and 7 downregulated) were detected in strained PPDLSCs. For mRNAs with , we detected 25 upregulated mRNAs and one downregulated mRNA in strained HPDLSCs and 7 upregulated and 5 downregulated mRNAs in strained PPDLSCs. Further enrichment analysis showed that, unlike HPDLSCs with annotations principally involving transduction-associated signaling pathways, dysregulated mRNAs in PPDLSCs are mainly responsible for pathological conditions. Moreover, coexpressed lncRNA-mRNA networks confirmed the pathological state and exacerbated inflammatory conditions in strained PPDLSCs. Taken together, when compared with strained HPDLSCs, various lncRNAs and mRNAs were dysregulated in PPDLSCs under mechanical forces, implicating the response of lncRNAs in PPDLSCs to mechanical stress. Moreover, we provide potential lncRNA targets, which may contribute to future intervention strategies for orthodontic treatment in periodontitis patients.

1. Introduction

Periodontitis is a chronic inflammatory disease that causes irreversible periodontal attachment damage [1]. During the pathological process, osteoblasts are distinctly suppressed, whereas osteoclastogenesis becomes hyperactive [2]. Because of the typically high morbidity rate and obvious clinical manifestation of tooth extrusion, space, and labial drifting, many adult patients with periodontitis seek orthodontic treatment to achieve both esthetic restoration and functional restoration [3]. Periodontal ligament stem cells (PDLSCs) are considered an attractive source of mesenchymal stem cells (MSCs) in the periodontium and are capable of regenerating cementum/PDL-like structures [4]. However, our previous studies revealed that PDLSCs obtained from periodontal tissues of periodontitis patients (PPDLSCs) are characterized by impaired function that leads to aberrant proliferative and osteogenic properties [5, 6].

Mechanical stimuli are another critical factor affecting tissue homeostasis and function. During orthodontic tooth movement, alveolar bone remodeling is triggered via initiation of a series of signaling cascades in the periodontal ligament (PDL) and surrounding tissues [7]. Nonetheless, inappropriate loading can cause homeostasis disruption between osteogenesis and bone resorption [8]. Our previous studies have also demonstrated that the reactions of PPDLSCs and HPDLSCs to static mechanical strain (SMS) differ due to the effect of the inflammatory microenvironment. Specifically, PPDLSCs display a sensitive pattern of both decreased proliferation and osteogenesis and an active inflammatory response to SMS at 12% elongation, while PDLSCs obtained from healthy periodontal tissues (HPDLSCs) exhibit a notable promotion of multidirectional capacities [6].

Long noncoding RNAs (lncRNAs) are an important type of molecule longer than 200 nucleotides that are transcribed by RNA polymerase II and contain a 5 cap and 3 adenylation [9]. Studies have identified that altered lncRNA levels are of functional importance in the pathogenesis and development of various diseases, including skeletal and dental diseases [10, 11]. In addition, lncRNA remodeling has been demonstrated to affect the progression of periodontitis [12]. For example, our group previously reported that the expression of lncRNA-POIR was reduced in PPDLSCs and that this was accompanied by decreased osteogenic capacity; moreover, overexpression of lncRNA-POIR promoted bone formation by competing with miR-182 [13].

Although many lncRNAs have been identified to be associated with inflammation-induced functional changes, the regulatory effects of lncRNAs on PPDLSCs in response to mechanical forces and the underlying mechanisms remain unclear [12, 14]. Therefore, this study was aimed at determining the SMS-induced lncRNA profiles of HPDLSCs and PPDLSCs and at exploring potential lncRNAs involved in the process of mechanotransduction in an inflammatory microenvironment.

2. Materials and Methods

2.1. Cell Culture

Primary PPDLSCs were obtained from premolar and/or third molar extractions of 8 donors ( years old) for therapeutic reasons who were diagnosed with chronic periodontitis. Primary HPDLSCs were isolated from 10 orthodontic patients ( years old) who underwent routine premolar and/or third molar extractions. All samples were collected at the Department of Orthodontics, School of Stomatology, the Fourth Military Medical University. Periodontitis patients were collected according to the following criteria made by the same periodontal specialist: bleeding on probe; periodontal  mm with 3-4 mm attachment loss; and/or alveolar bone absorption up to 1/3-1/2 root length horizontally on X-ray images. None of these subjects were selected with any clinical evidence of systemic disease or an acute infection in the past 6 months, and no one had a smoking history, drug utilization, or ever received maxillofacial radiotherapy and chemotherapy [6, 15]. All subjects provided written informed consent in accordance with the Declaration of Helsinki, and the study reached a consensus with the Ethics Committee of the Fourth Military Medical University (Approval Number: 2017(026)). The primary cells were cultured in α-MEM (Gibco BRL, Gaithersburg, MD, USA) with 10% fetal bovine serum (FBS) (Invitrogen, Carlsbad, CA, USA) in a humidified environment at 37°C with 5% CO2 [14]. Cell colonies were established by the limiting dilution technique [16].

2.2. SMS Loading

All cells were seeded into collagen I-coated 6-well BioFlex plates (Flexcell International, Burlington, NC, USA), and cells were serum starved for 24 h after achieving 95% confluence. Experimental cells were subjected to SMS for 12 h utilizing a Flexcell Tension Plus system (FX-4000T, Flexcell International) with 12% elongation at 0.1 Hz [6]. Static groups were cultured under the same conditions without SMS exposure.

2.3. RNA Extraction

Total RNA was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) and quantified using a NanoDrop ND-1000 (Thermo Fisher Scientific, Boston, MA, USA). RNA integrity was evaluated by standard denaturing agarose gel electrophoresis.

2.4. Microarray Analysis

Sample labeling and array hybridization were conducted using the Agilent One-Color Microarray-Based Gene Expression Analysis protocol (Agilent Technologies, Santa Clara, CA, USA) [13]. In brief, mRNA was purified from total RNA after removing rRNA (mRNA-ONLY Eukaryotic mRNA Isolation Kit; Epicenter, San Diego, CA, USA). Each sample was amplified and transcribed into fluorescent cRNA along the entire length of the transcripts without 3 bias via a random priming method (Arraystar Flash RNA Labeling Kit; Arraystar, Rockville, MD, USA). The labeled cRNAs were purified using an RNeasy Mini Kit (Qiagen, Hilden, Germany). The concentration and specific activity of the labeled cRNAs (pmol Cy3/μg cRNA) were assessed using a NanoDrop ND-1000. One microgram of each labeled cRNA was fragmented by adding 5 μl of 10× blocking agent and 1 μl of 25× fragmentation buffer; after heating at 60°C for 30 min, 25 μl of 2× GE hybridization buffer was added to dilute the labeled cRNA. Approximately 50 μl of hybridization solution was dispensed into the gasket slide and assembled onto the lncRNA expression microarray slide. The slides were incubated for 17 at 65°C in an Agilent hybridization oven (Agilent, Santa Clara, CA, USA). The hybridized arrays were washed, fixed, and scanned using an Agilent DNA Microarray Scanner (part number G2505C). Arraystar Human LncRNA Microarray V3.0 (Arraystar, Kangchen, Shanghai, China) was designed for the global profiling of human lncRNAs and mRNAs. Approximately 30,586 lncRNAs and 26,109 coding transcripts can be detected by collecting data sources from GENCODE, UCSC, Ensembl, RefSeq, and other related sources.

2.5. Real-Time qPCR Confirmation

Total RNA was assembled and reverse-converted to cDNA using a SuperScript First-Strand Synthesis Kit (Invitrogen). An Applied Biosystems ViiA 7 Real-Time PCR System was used for qPCR. The reaction system included incubation for 10 min at 95°C, followed by 40 cycles at 95°C for 10 s and 60°C for 1 min. Relative expression levels of transcripts were calculated by using the 2ΔΔCT method and normalized to GAPDH [17]. All experiments were carried out in triplicate. The specific primers (Genscript, China) used are shown in Table 1.


Gene symbolSense primer

GAPDH (HUMAN)F: 5GGGAAACTGTGGCGTGAT3
R: 5GAGTGGGTGTCGCTGTTGA3
TCONS_00008604F: 5GTTGGGCAGTAAGCCTCACA3
R: 5TGGGGTAGGTAATGGAAAAAG3
ENST00000428781F: 5AGGGGGTAAAAGAAAATGGTG3
R: 5CAGGCTCGCATTCAGACAT3
uc004arq.1F: 5ACCCCTACAGACCATAACAAAG3
R: 5AGCCGACTACAGCCACCACT3
XISTF: 5GCTGAATGAATGTGTCTTACCC3
R: 5GAGGCAAAGGCACACACGAA3
Runx2F: 5CCCGTGGCCTTCAAGGT-3
R: 5CGTTACCCGCCATGACAGTA-3

2.6. Bioinformatic Analysis of Differentially Expressed (DE) mRNAs

Gene Ontology (GO) analysis was employed to map DEmRNAs to GO terms annotated by molecular function, biological process, and cellular components (http://www.geneontology.org). Significant pathways of the DE genes were determined using Kyoto Encyclopedia of Genes and Genomes (KEGG) (http://www.genome.jp/kegg/), as previously described [18, 19].

2.7. Coexpression Network Construction (CNC)

CNC was conducted based on the top 10 DElncRNAs between strained HPDLSCs and PPDLSCs with coexpressed DEmRNAs [20]. Pearson’s correlation coefficients (PPCs) no less than 0.99 were used to identify coding genes. CNCs were accomplished using Cytoscape software version 3.0.1 (The Cytoscape Consortium, San Diego, CA, USA).

2.8. Lentivirus Transfection

The design and construction of lentiviruses were performed by GeneChem (GeneChem, Shanghai, China). The lentivirus Ubi-MCS-SV40-EGFP-IRES-puromycin was used for lncRNA-XIST overexpression, and hU6-MCS-CBh-gcGFP-IRES-puromycin was used for lncRNA-XIST interference. The sequences of primers for amplifying lncRNA-XIST were F: 5-ACAAGCAGTGCAGAGAGCT-3 and R: 5-AGAGTGCCAGGCATGTTGA-3. The sequences of lncRNA-XIST interference targets were as follows: shlncRNA-XIST (79428-1): 5-GCCATCATTAGCCACTGCACT-3; shlncRNA-XIST (79428-2): 5-GGTCAGGAGGTTCTGTCAAGA-3; and shlncRNA-XIST (79428-3): 5-GGTCCCAGATAGGAAGATAAA-3. HPDLSCs and PPDLSCs were cultured in six-well plates. When cells reached approximately 30% confluence, they were transfected with lentiviruses at a multiplicity of transfection (MOI) of 9 for 24 h and then cultured with common medium (α-MEM with 10% FBS).

2.9. Osteogenic Differentiation Assays

For osteogenesis assays, HPDLSCs and PPDLSCs were exposed to SMS with 12% elongation at 0.1 Hz for 12 h after reaching 80% confluence. Then, HPDLSCs and PPDLSCs were cultured in osteogenic medium for 21 days. Mineralized nodules were stained with alizarin red S (pH 4.2) (Kermel, Tianjin, China) for 15 min at room temperature at day 21, and calcium levels were measured quantitatively using a calcium colorimetric assay kit (BioVision, San Francisco, CA, USA).

2.10. Statistical Analysis

All experiments were performed in triplicate, and the data are presented as the (S.D.). Statistical analyses with one-way ANOVA and Student’s -test were performed using SPSS 16.0 software (SPSS, San Rafael, CA, USA). Correlated terms were performed with the PCCs, and the significance threshold was fold and and/or .

3. Results

3.1. Expression Profiles of DElncRNAs and DEmRNAs with SMS

According to the principles of and , we screened 8,847 and 9,772 DElncRNAs in strained HPDLSCs and PPDLSCs relative to static controls, respectively (Figure 1(a)). In addition, 1,624 DElncRNAs were only expressed in strained HPDLSCs, and 2,549 were only expressed in strained PPDLSCs. DElncRNAs with in each group are provided in Tables 2 and 3. Of those, ENST00000411904 was the most upregulated lncRNA in strained HPDLSCs; the most upregulated and downregulated lncRNAs in strained PPDLSCs were lncRNA-XIST and ENST00000517505, respectively. Volcano and scatter plots as well as hierarchical clustering were examined to assess the lncRNA expression differences between HPDLSCs and PPDLSCs exposed to the strain (Figures 1(b)1(d)).


Sequence nameSourceFold changeRegulation value (×10-4)

NR_038400RefSeq35.06Up0.000
ENST00000423442GENCODE35.06Up0.024
ENST00000409139GENCODE33.15Up0.229
ENST00000432511GENCODE31.93Up0.039
ENST00000433431Pseudogene31.57Up0.169
ENST00000453278GENCODE30.70Up0.358
uc003 mjk.3UCSC_knowngene29.42Up24.755
ENST00000447956GENCODE28.82Up0.047
ENST00000505532GENCODE28.06Up0.235
TCONS_00024645LincRNAs identified by Cabili et al.27.71Up0.451
TCONS_00010599LincRNAs identified by Cabili et al.24.92Up0.659
DB299803LincRNAs identified by Khalil et al.23.18Up0.115
TCONS_00008978LincRNAs identified by Cabili et al.21.99Up0.784
ENST00000506014GENCODE20.49Up1.714


Sequence nameSourceFold changeRegulation value (×10-4)

XISTGENCODE53.85Down1.089
ENST00000517505GENCODE50.01Up107.825
ENST00000583761GENCODE40.94Up5.450
TCONS_00024405LincRNAs identified by Cabili et al.37.30Down0.059
ENST00000523905GENCODE36.91Up20.468
TCONS_00008604LincRNAs identified by Cabili et al.34.05Down0.795
AA324424LincRNAs identified by Khalil et al.33.45Up0.048
ENST00000545920GENCODE33.25Down3.759
ENST00000486545GENCODE27.35Down0.003
TCONS_00019524LincRNAs identified by Cabili et al.25.44Up4.413
ENST00000428781GENCODE24.73Down0.259
uc004arq.1UCSC_knowngene22.42Down0.059
TCONS_00014003LincRNAs identified by Cabili et al.21.10Up20.461

Thousands of DEmRNAs were identified (Figure 1(e)). In total, 11,937 and 12,410 DEmRNAs were significantly altered in strained HPDLSCs and PPDLSCs, respectively. In particular, 2,170 specific DEmRNAs were detected in strained HPDLSCs and 2,643 in strained PPDLSCs. The most upregulated and downregulated mRNAs in strained HPDLSCs were ASHGA5P006667 and ASHGA5P003418, and the most upregulated and downregulated mRNAs in strained PPDLSCs were ASHGA5P009176 and ASHGA5P052412 (KIF20A) (Tables 4 and 5). The volcano and scatter plots depicted in Figures 1(f) and 1(g) demonstrate the variation in lncRNA expression between strain-induced HPDLSCs and PPDLSCs.


Sequence nameSourceFold changeRegulation value (×10-5)

ASHGA5P006667RefSeq413.31Up4.315
ASHGA5P008770RefSeq147.59Up0.0003
ASHGA5P021973RefSeq125.83Up150.671
ASHGA5P013772GENCODE70.35Up1512.671
ASHGA5P003418RefSeq63.94Down74.253
ASHGA5P011737RefSeq42.60Up494.192
ASHGA5P007165GENCODE41.99Up302.842
ASHGA5P037277RefSeq41.81Up1.06.612
ASHGA5P005733GENCODE38.72Up46.774
ASHGA5P002830GENCODE37.77Up15.020
ASHGA5P002962RefSeq36.22Up5.402
ASHGA5P013771RefSeq33.74Up46.840
ASHGA5P042689RefSeq32.07Up92.410
ASHGA5P002150RefSeq31.42Up0.128
ASHGA5P007745RefSeq30.45Up6.915
ASHGA5P003294GENCODE28.31Up0.254
ASHGA5P017399RefSeq28.24Up7.840
ASHGA5P008733GENCODE25.41Up64.712
ASHGA5P005403RefSeq23.76Up1.361
ASHGA5P054134RefSeq23.62Up245.163
ASHGA5P001729RefSeq23.04Up14.825
ASHGA5P051262RefSeq22.99Up858.448
ASHGA5P045542RefSeq22.91Up200.313
ASHGA5P050260RefSeq22.54Up0.001
ASHGA5P004313RefSeq21.00Up4.695
ASHGA5P001728RefSeq20.64Up84.501


Sequence nameSourceFold changeRegulation value (×10-5)

ASHGA5P009176RefSeq111.34Up179.785
ASHGA5P013422RefSeq59.61Up6.424
ASHGA5P010424GENCODE56.12Up0.032
ASHGA5P012978RefSeq42.19Up104.171
ASHGA5P052412RefSeq42.10Down0.001
ASHGA5P003780RefSeq34.88Up2427.963
ASHGA5P005903RefSeq31.08Down0.919
ASHGA5P017401RefSeq27.31Down0.304
ASHGA5P001619RefSeq25.51Up784.373
ASHGA5P004428RefSeq24.18Down26.041
ASHGA5P004064RefSeq21.49Down4.546
ASHGA5P034395GENCODE20.98Up55.833

3.2. Confirmation of DElncRNAs Using Real-Time qPCR

To validate the microarray results, we randomly selected four lncRNAs (TCONS_00008604, ENST00000428781, uc004arq.1, and XIST) from the top 10 DElncRNAs between strained HPDLSCs and PPDLSCs and evaluated their expression by qPCR assay (Table 6). All lncRNAs were downregulated in strained PPDLSCs compared to HPDLSCs, which was consistent with the microarray analysis results (Figure 2).


Sequence nameTotal mRNA

ENST00000505532160
ENST00000532307156
ENST00000428781126
uc021qut.1130
TCONS_0000860493
uc004arq.151
ENST0000042372789
TCONS_0001363665
XIST47
ENST0000034019612

3.3. Preliminary Analysis of DEmRNAs with SMS

To further explore the putative functions of lncRNAs, bioinformatic analysis was applied based on GO and KEGG pathway analyses. According to the results, DEmRNAs in strained HPDLSCs were mainly enriched in the regulation of stress response, signal transduction, and response to stimulus (Figures 3(a), 3(c), and 3(e)). In contrast, pathological processes such as cell-type apoptotic processes and neuronal apoptotic processes were enriched in strained PPDLSCs (Figures 3(b), 3(d), and 3(f)). Enrichment scores revealed prominent assignments for cellular function and metabolism, such as fatty acid degradation and metabolism, in strained HPDLSCs (Figure 3(g)). In strained PPDLSCs, pathological states were largely notable, including Huntington’s disease, bladder cancer, and non-small-cell lung cancer (Figure 3(h)).

3.4. Constructions of the CNC Network

By combining the top 10 DElncRNAs with coexpressed DEmRNAs, an integrated coexpression network containing 1,250 lncRNA-mRNA interactions was established (Figure 4(a)). Notably, RP11-597D13.9 (ENST00000505532) was associated with the maximum number of DEmRNAs, up to 160. XIST, the most downregulated lncRNA in strained PPDLSCs, was coexpressed with 47 DEmRNAs (Table 6). In addition, GO annotations and KEGG analyses showed that the DElncRNAs in the key module are related to chondrocyte development, fibroblast apoptotic process regulation, and cell adhesion as well as leukocyte transendothelial migration, which likely participate in tissue regeneration. Taken together, dysregulated lncRNAs are involved in the pathological modification of gene expression in PPDLSCs under mechanical conditions (Figures 4(b)4(e)).

3.5. Functional Investigation of DElncRNAs during Osteogenic Differentiation

We randomly evaluated the expression of four lncRNAs (TCONS_00008604, ENST00000428781, uc004arq.1, and XIST) from the top 10 DElncRNAs between strained HPDLSCs and PPDLSCs after osteogenic induction for 7 days and observed that the expression level of lncRNA-XIST significantly increased in HPDLSCs at day 7 after osteogenic differentiation. Although osteogenic induction upregulated the level of lncRNA-XIST in PPDLSCs, it was still lower than that in HPDLSCs (, Figure 5(a)). We also found that lncRNA-XIST was significantly increased in HPDLSCs after 12 h of SMS elongation (); however, strain-induced lncRNA-XIST expression was not obviously increased in PPDLSCs (Figure 5(b)). We also examined the relationship between lncRNA-XIST and the osteogenic gene Runx2 after 12% SMS loading by lentivirus transfection. We found that Runx2 expression in strained HPDLSCs infected with shlncRNA-XIST was decreased almost 2 times compared with strained HPDLSCs in the negative control group (NC) (, Figure 5(c)). In contrast, Runx2 expression in strained PPDLSCs increased after lncRNA-XIST overexpression (, Figure 5(d)). Similarly, alizarin red staining and calcium quantification also sustained that shlncRNA-XIST inhibited SMS-induced osteogenic differentiation in HPDLSCs and that overexpression of lncRNA-XIST rescued the osteogenic ability of PPDLSCs (, Figures 5(e) and 5(f)).

4. Discussion

Many lncRNAs play critical roles in multiple pathological processes of periodontitis, such as proliferation, differentiation, cell migration, and immune regulation [21, 22]. Excessive mechanical stimuli can cause irreversible damage to PDLSCs, especially to those in an inflammatory state [23]. However, studies on the expression of lncRNAs involved in strain-induced PDLSCs and their potential effects on cellular functions are limited. In this study, we identified thousands of DElncRNAs and DEmRNAs in HPDLSCs and PPDLSCs after SMS application, and various lncRNAs and mRNAs were found to be solely expressed in strained HPDLSCs or PPDLSCs, indicating that different mechanisms may be involved in the mechanotransductive responses of PDLSCs derived from different contexts.

Using microarray analysis, we observed that DElncRNAs in strained HPDLSCs were mainly enriched in mechanoconductive processes; pathological pathways such as cell-type apoptotic process and regulation of neuron apoptotic process were associated with dysregulated lncRNAs in strained PPDLSCs. In addition, based on KEGG pathway analysis, the DElncRNAs are largely related to pathological conditions such as Huntington’s disease [24], bladder cancer [25], and non-small-cell lung cancer [26]. Therefore, cell functions regulated by lncRNAs have a potential role in PDLSCs, and aberrant lncRNA transcripts are associated with periodontitis progression [27].

Cytoskeletal dynamics and integrity are of vital importance for cell differentiation commitment, by which the bone loss occurring in periodontitis can be alleviated [28]. By altering the expression of eukaryotic cytoskeleton proteins, which play important roles in cancer progression and cytoskeleton modulation, KIF20A is sensitive to alterations along with mechanical loadings [29]. In this study, KIF20A was most downregulated in strained PPDLSCs, suggesting that dysregulated mRNAs possibly modulate expression through interactions with intracellular cytoskeleton mechanisms. Therefore, further functional validation of these dysregulated transcripts in periodontitis is warranted.

Furthermore, to identify potential lncRNAs associated with strained PDLSCs, we integrated the coexpression networks of lncRNAs and mRNAs. A total of 1,250 pairs based on the top 10 dysregulated lncRNAs between strained PPDLSCs and HPDLSCs were established. Of those, RP11-597D13.9, an antisense lncRNA, correlated with up to 160 mRNAs, and it may affect a nearby coding gene: FAM198B [30]. FAM198B has been implicated as a tumor inhibitor, attenuating lung cancer cell invasion and thus improving the overall survival of patients with lung adenocarcinoma [31]. In our study, RP11-597D13.9 displayed an inverse trend of downregulation in strained PPDLSCs, indicating a possible pathological state for these cells. Moreover, lncRNA XIST has long been recognized as an oncogenic gene and is preferentially expressed in cancers [32, 33]. LPS-induced inflammation can increase the levels of XIST expression, which in turn suppresses acute inflammation via MAPK signaling [34]. Contrary to these results, there was a significant decrease in XIST in strained PPDLSCs together with CH1CI (Brx), one of the major downstream target genes for XIST [35]. In our study, we first found that lncRNA-XIST expression decreased in PDLSCs derived from an inflammatory microenvironment. Additionally, although SMS elongation significantly decreased the expression of lncRNA-XIST in PPDLSCs compared with HPDLSCs, the upregulation of lncRNA-XIST in strained PPDLSCs increased the process of osteogenic differentiation, indicating that lncRNA-XIST may be one of the nonnegligible reasons for the impaired osteogenesis in strained PPDLSCs.

5. Conclusions

In summary, differentially expressed lncRNA profiles between HPDLSCs and PDLSCs under mechanical exposure were first identified in this study, and many were specifically expressed. By functional analysis, we confirmed that DE transcripts in PPDLSCs participate in many pathological processes and might be involved in regulating periodontitis progression under tension. In our study, we found that the expression of lncRNA-XIST obviously decreased in PPDLSCs, and the osteogenic ability of PPDLSCs under tension loading was significantly upregulated after upregulation of lncRNA-XIST by lentivirus. These results hint us that lncRNAs could regulate the osteogenic ability of PDLSCs under tension loading. Although some lncRNAs are predicted, comprehensive analyses are still needed to elucidate the details of the relevant molecular mechanisms.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare no potential competing interests.

Authors’ Contributions

Jia Liu, Yan Zhao, and Qiannan Niu contributed equally to this work.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (grant no. 81701002 and 81970960) and the International Scientific and Technological Cooperation and Exchange Program in Shaanxi Province of China (No. 2021KW45).

References

  1. J. B. Guo, J. Q. Weng, Q. Rong et al., “Investigation of multipotent postnatal stem cells from human maxillary sinus membrane,” Scientific Reports, vol. 5, no. 1, article 11660, 2015. View at: Publisher Site | Google Scholar
  2. T. Crotti, M. D. Smith, R. Hirsch et al., “Receptor activator NF kappaB ligand (RANKL) and osteoprotegerin (OPG) protein expression in periodontitis,” Jouranl of Periodontal Research, vol. 38, no. 4, pp. 380–387, 2003. View at: Publisher Site | Google Scholar
  3. C. Ren, C. McGrath, M. Gu et al., “Low-level laser-aided orthodontic treatment of periodontally compromised patients: a randomised controlled trial,” Lasers in Medical Science, vol. 35, no. 3, pp. 729–739, 2020. View at: Publisher Site | Google Scholar
  4. R. X. Wu, C. S. Bi, Y. Yu, L. L. Zhang, and F. M. Chen, “Age-related decline in the matrix contents and functional properties of human periodontal ligament stem cell sheets,” Acta Biomaterialia, vol. 22, pp. 70–82, 2015. View at: Publisher Site | Google Scholar
  5. J. Liu, L. Y. Wang, W. J. Liu, Q. Li, Z. Jin, and Y. Jin, “Dental follicle cells rescue the regenerative capacity of periodontal ligament stem cells in an inflammatory microenvironment,” PLoS One, vol. 9, no. 10, article e108752, 2014. View at: Publisher Site | Google Scholar
  6. J. Liu, Q. Li, S. Y. Liu et al., “Periodontal ligament stem cells in the periodontitis microenvironment are sensitive to static mechanical strain,” Stem Cells International, vol. 2017, Article ID 1380851, 13 pages, 2017. View at: Publisher Site | Google Scholar
  7. M. Wolf, S. Lossdörfer, P. Römer et al., “Short-term heat pre-treatment modulates the release of HMGB1 and pro-inflammatory cytokines in hPDL cells following mechanical loading and affects monocyte behavior,” Clinical Oral Investigations, vol. 20, no. 5, pp. 923–931, 2016. View at: Publisher Site | Google Scholar
  8. R. Jia, Y. J. Yi, J. Liu et al., “Cyclic compression emerged dual effects on the osteogenic and osteoclastic status of LPS-induced inflammatory human periodontal ligament cells according to loading force,” BMC Oral Health, vol. 20, no. 1, p. 7, 2020. View at: Publisher Site | Google Scholar
  9. J. S. Mattick, “RNA regulation: a new genetics?” Nature Reviews Genetics, vol. 5, no. 4, pp. 316–323, 2004. View at: Publisher Site | Google Scholar
  10. L. W. Harries, “Long non-coding RNAs and human disease,” Biochemical Society Transactions, vol. 40, no. 4, pp. 902–906, 2012. View at: Publisher Site | Google Scholar
  11. Y. G. Zou, C. Li, F. P. Shu et al., “lncRNA expression signatures in periodontitis revealed by microarray: the potential role of lncRNAs in periodontitis pathogenesis,” Journal of Cellular Biochemistry, vol. 116, no. 4, pp. 640–647, 2015. View at: Publisher Site | Google Scholar
  12. W. Peng, W. Deng, J. Zhang, G. W. Pei, Q. Rong, and S. X. Zhu, “Long noncoding RNA ANCR suppresses bone formation of periodontal ligament stem cells via sponging miRNA-758,” Biochemical and Biophysical Research Communications, vol. 503, no. 2, pp. 815–821, 2018. View at: Publisher Site | Google Scholar
  13. L. Wang, F. Wu, Y. Song et al., “Long noncoding RNA related to periodontitis interacts with miR-182 to upregulate osteogenic differentiation in periodontal mesenchymal stem cells of periodontitis patients,” Cell Death & Disease, vol. 7, no. 8, article e2327, 2016. View at: Publisher Site | Google Scholar
  14. R. R. Meng, M. Song, and J. S. Pan, “Rho is involved in periodontal tissue remodelling with experimental tooth movement in rats,” Archives of Oral Biology, vol. 60, no. 6, pp. 923–931, 2015. View at: Publisher Site | Google Scholar
  15. W. Liu, Y. B. Cao, L. Dong et al., “Periodontal therapy for primary or secondary prevention of cardiovascular disease in people with periodontitis,” The Cochrane Database of Systematic Reviews, vol. 12, no. 12, article CD009197, 2019. View at: Publisher Site | Google Scholar
  16. Z. H. Yang, F. Jin, X. J. Zhang et al., “Tissue engineering of cementum/periodontal-ligament complex using a novel three-dimensional pellet cultivation system for human periodontal ligament stem cells,” Tissue Engineering. Part C. Methods, vol. 15, no. 4, pp. 571–581, 2009. View at: Publisher Site | Google Scholar
  17. T. D. Schmittgen and K. J. Livak, “Analyzing real-time PCR data by the comparative C(T) method,” Nature Protocals, vol. 3, no. 6, pp. 1101–1108, 2008. View at: Publisher Site | Google Scholar
  18. M. Guttman and J. L. Rinn, “Modular regulatory principles of large non-coding RNAs,” Nature, vol. 482, no. 7385, pp. 339–346, 2012. View at: Publisher Site | Google Scholar
  19. R. Chen, J. Liu, M. Xiao, F. Wang, and X. Lin, “Microarray expression profile analysis of long noncoding RNAs in premature brain injury: a novel point of view,” Neuroscience, vol. 319, pp. 123–133, 2016. View at: Publisher Site | Google Scholar
  20. M. A. Pujana, J. D. Han, L. M. Starita et al., “Network modeling links breast cancer susceptibility and centrosome dysfunction,” Nature Genetics, vol. 39, no. 11, pp. 1338–1349, 2007. View at: Publisher Site | Google Scholar
  21. X. Q. Zhang, L. H. Ren, X. Y. Yan et al., “Identification of immune-related lncRNAs in periodontitis reveals regulation network of gene-lncRNA-pathway-immunocyte,” International Immunopharmacology, vol. 84, article 106600, 2020. View at: Publisher Site | Google Scholar
  22. Y. Liu, C. P. Liu, A. K. Zhang et al., “Down-regulation of long non-coding RNA MEG3 suppresses osteogenic differentiation of periodontal ligament stem cells (PDLSCs) through miR-27a-3p/IGF1 axis in periodontitis,” Aging, vol. 11, no. 15, pp. 5334–5350, 2019. View at: Publisher Site | Google Scholar
  23. C. X. Zhang, Y. Q. Lu, L. K. Zhang et al., “Influence of different intensities of vibration on proliferation and differentiation of human periodontal ligament stem cells,” Archives of Medical Science. AMS, vol. 3, no. 3, pp. 638–646, 2015. View at: Publisher Site | Google Scholar
  24. R. Johnson, “Long non-coding RNAs in Huntington's disease neurodegeneration,” Neurobiology of Disease, vol. 46, no. 2, pp. 245–254, 2012. View at: Publisher Site | Google Scholar
  25. Y. H. Zhan, Z. C. Chen, S. M. He et al., “Long non-coding RNA SOX2OT promotes the stemness phenotype of bladder cancer cells by modulating SOX2,” Molecular Cancer, vol. 19, no. 1, p. 25, 2020. View at: Publisher Site | Google Scholar
  26. F. Li, Q. Y. Zhang, Y. G. Gong, and J. X. Yu, “The lncKLF6/KLF6 feedback loop regulates the growth of non-small cell lung cancer,” American Journal of Cancer Research, vol. 8, no. 8, pp. 1427–1439, 2018. View at: Google Scholar
  27. Y. D. Liu, Q. F. Liu, Z. P. Li et al., “Long non-coding RNA and mRNA expression profiles in peri-implantitis vs periodontitis,” Journal of Periodontal Research, vol. 55, no. 3, pp. 342–353, 2020. View at: Publisher Site | Google Scholar
  28. I. Binderman, N. Gadban, and A. Yaffe, “Cytoskeletal disease: a role in the etiology of adult periodontitis,” Oral Diseases, vol. 20, no. 1, pp. 10–16, 2014. View at: Publisher Site | Google Scholar
  29. J. Schiewek, U. Schumacher, T. Lange et al., “Clinical relevance of cytoskeleton associated proteins for ovarian cancer,” Journal of Cancer Research and Clinical Oncology, vol. 144, no. 11, pp. 2195–2205, 2018. View at: Publisher Site | Google Scholar
  30. H. Wang, Z. Y. Fu, C. C. Dai et al., “LncRNAs expression profiling in normal ovary, benign ovarian cyst and malignant epithelial ovarian cancer,” Scientific Reports, vol. 6, no. 1, article 38983, 2016. View at: Publisher Site | Google Scholar
  31. C. Y. Hsu, G. C. Chang, Y. J. Chen et al., “FAM198B is associated with prolonged survival and inhibits metastasis in lung adenocarcinoma via blockage of ERK-mediated MMP-1 expression,” Clinical Cancer Research, vol. 24, no. 4, pp. 916–926, 2018. View at: Publisher Site | Google Scholar
  32. N. N. Sun, G. Z. Zhang, and Y. Y. Liu, “Long non-coding RNA XIST sponges miR-34a to promotes colon cancer progression via Wnt/β-catenin signaling pathway,” Gene, vol. 665, pp. 141–148, 2018. View at: Publisher Site | Google Scholar
  33. Y. Zhang, H. Zhang, W. Zhang, Y. J. Zhang, W. Wang, and L. Nie, “LncRNA XIST modulates 5-hydroxytrytophan-induced visceral hypersensitivity by epigenetic silencing of the SERT gene in mice with diarrhea-predominant IBS,” Cellular Signalling, vol. 73, article 109674, 2020. View at: Publisher Site | Google Scholar
  34. B. B. Shenoda, S. Ramanathan, R. Gupta et al., “Xist attenuates acute inflammatory response by female cells,” Cellular and Molecular Life Sciences, vol. 78, no. 1, pp. 299–316, 2021. View at: Publisher Site | Google Scholar
  35. M. C. Simmler, E. Heard, C. Rougeulle, C. Cruaud, J. Weissenbach, and P. Avner, “Localization and expression analysis of a novel conserved brain expressed transcript, Brx/BRX, lying within the Xic/XIC candidate region,” Mammalian Genome, vol. 8, no. 10, pp. 760–766, 1997. View at: Publisher Site | Google Scholar

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