Research ArticleLong Noncoding RNA Expression Profile in BV2 Microglial CellsExposed to Lipopolysaccharide

Yajuan Li,1,2 Qingmin Li,3 CunjuanWang ,4 Shengde Li ,2 and Lingzhi Yu 1

1Department of Pain Management, Jinan Central Hospital, Shandong University, Jinan 250013, China2Department of Anesthesiology, Taian City Central Hospital, Taian 271000, China3Department of Neurosurgery, Taian City Central Hospital, Taian 271000, China4Department of Children Rehabilitation, W. F. Maternal and Child Health Hospital, Weifang 261011, China

Correspondence should be addressed to Lingzhi Yu; pain-relief@163.com

Received 13 March 2019; Accepted 26 May 2019; Published 11 June 2019

Academic Editor: Maria C. De Rosa

Copyright © 2019 Yajuan Li et al.This is an open access article distributed under the Creative Commons Attribution License, whichpermits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Neuropathic pain, which is one of themost common forms of chronic pain, seriously increases healthcare costs and impairs patients’quality of life with an incidence of 7–10%worldwide.Microglia cell activation plays a key role in the progression of neuropathic pain.Better understanding of novel molecules modulatingmicroglia cell activation and these underlying functions will extremely benefitthe exploration of new treatment. Recent studies suggested long noncodingRNAsmay be involved in neuropathic pain.However, itsunderlying functions and mechanisms in microglia cell activation remain unclear. To identify the differentially expressed lncRNAsand predict their functions in the progression of microglia cell activation, GSE103156 was analyzed using integrated bioinformaticsmethods.The expression levels of selected lncRNAs and mRNAs were determined by real-time PCR. In the present study, a total of56 lncRNAs and 298 mRNAs were significantly differentially expressed.The differentially expressed mRNAs were mainly enrichedin NF-kappa B signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, and NOD-like receptor signalingpathway. The top 10 hub genes were Tnf, Il6, Stat1, Cxcl10, Il1b, Tlr2, Irf1, Ccl2, Irf7, and Ccl5 in the PPI network. Our resultsshowed that Gm8989, Gm8979, and AV051173 may be involved in the progression of microglia cell activation. Taken together, ourfindings suggest that lots of lncRNAs may be involved in BV2 microglia cell activation in vitro. The findings may provide relevantinformation for the development of promising targets for the microglial cells activation of neuropathic pain in vivo in the future.

1. Introduction

Neuropathic pain, which is one of the most common formsof chronic pain [1, 2], seriously increased healthcare costsand impairs patients’ quality of life with an incidence of7–10% worldwide [3, 4]. Moreover, there are no effectivetreatments for patients with neuropathic pain. To designnew prophylactic and therapeutic strategies, more studiesare needed to explore the pathogenesis of neuropathic pain.Neuropathic pain often results from traumatic, infectious,chemical, metabolic, or cancerous impairments [3–5], inwhich significant features are hyperalgesia, allodynia, andspontaneous burning pain. Although the pathogenesis ofneuropathic pain is obscure, microglia cell activation hasbeen shown to be essential for neuropathic pain [6, 7]. Arecent study has shown that spinal microglia activation was

induced by peripheral nerve injury and contributed to centralsensitization [8].

Considerable advances have been made in high-throughput technology for identifying microglial factors inneuropathic pain [9–11] in the past decade. However, themechanisms of microglia activation-induced neuropathicpain are still poorly understood.

In general, ncRNAs do not encode functional proteins.It has shown that lncRNAs participate in most essentialbiological processes at the levels of posttranscription, tran-scription, and epigenetics [12–15]. Recent research has shownthat some lncRNAs may be involved in the pathophysiologyof neuropathic pain. Xiuli Zhao et al. reported that Kcna2antisense RNA was an endogenous trigger in the progressionof neuropathic pain [16]. Differentially expressed lncRNAswere identified in SNI-induced neuropathic pain using

HindawiBioMed Research InternationalVolume 2019, Article ID 5387407, 9 pageshttps://doi.org/10.1155/2019/5387407

http://orcid.org/0000-0001-9163-6335http://orcid.org/0000-0001-8591-8766http://orcid.org/0000-0001-8206-3694https://creativecommons.org/licenses/by/4.0/https://doi.org/10.1155/2019/5387407

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high-throughput sequencing techniques, identifying a seriesof potential therapeutic targets of neuropathic pain [17].However, the potential functions and mechanisms of lncR-NAs in microglia cell activation remain incompletely under-stood.

In this study, we investigated the expression profile oflncRNAs andmRNAs in BV2microglial cells stimulated withLPS and predicted the potential functions and mechanismsof differentially expressed lncRNAs. Due to opportunitiesto identify novel promising targets of BV2 microglial cellsactivation, our results may provide relevant information forfuture study of microglial cells activation of neuropathic painin vivo.

2. Materials and Methods

2.1. Cell Culture, LPS Treatment, and RNA Isolation. BV2microglial cells were purchased from ATCC (Manassas,VA, USA) and cultured according to the manufacturer’sinstructions. BV2 microglial cells were stimulated for 24 hwith LPS (1 𝜇g/ml) or vehicle control (HBSS) in DMEM highglucose media containing 2.5% FBS. Total RNA was isolatedand identified as previously described.

2.2. Microarray Data. Raw data of GSE103156 (AffymetrixMouse Gene 2.1 ST Array) were downloaded from the GEOdata repository [18, 19]. In the present study, three BV2control samples and three BV2 LPS samples were used forbioinformatic analysis.

2.3. Identification of Differentially Expressed lncRNAs andmRNAs. Using Transcriptome Analysis Console (TAC) 4.01(Affymetrix, Santa Clara, CA, USA), differentially expressedlncRNAs and differentially expressed genes (DEGs) wereidentified. 2.0-fold or greater and an adjusted p value < 0.01were selected as a threshold.

2.4. Gene Ontology (GO) and Pathway Enrichment Analyses.The Database for Annotation, Visualization and IntegratedDiscovery (DAVID; http://david.ncifcrf.gov) (version 6.8)was used to analyze the biological function of differentiallyexpressed genes [20–24]. p value < 0.05 was selected as athreshold.

2.5. Protein-Protein Interactions (PPI) Network and Mod-ule Analysis. The interactions of DEGs were predicted bySTRING online database (http://string-db.org, version 10.5)[25]. PPI networkwas drawn byCytoscape (version 3.7.1) [26]and its plugin (MCODE [27] and CytoNCA [28]).

2.6. Transcription Factor (TF) Regulatory Network Analysis.IRegulon plugin in Cytoscape was used to predict TFs ofselected DEGs [29]. Normalized enrichment score (NES) >10 was used as the thresholds.

2.7. LncRNA-mRNACoexpression Network. LncRNA-mRNAcoexpression network was constructed to analyze theinteractions between lncRNA and mRNA by weighted

correlation network analysis (WGCNA) as describedpreviously [30].

2.8. Real-Time PCR. SuperReal PreMix Plus (Tiangen, Bei-jing, China) was used to perform real-time PCR in the Ari-aMx Real-time PCR System (Agilent Technologies, Palo Alto,CA). The reaction conditions were as follows: incubation at95∘C for 10 min, followed by 40 cycles of 95∘C for 15 s, 61∘Cfor 20 s, and 72∘C for 30 s. The 2-ΔΔCt method was usedto calculate the relative expression levels of selected lncRNAsand mRNA normalizing to GAPDH levels.

2.9. Statistical Analysis. All data were expressed as the mean± SEM. Unpaired Student’s t-test for parametric data andMann-Whitney’s U-test for nonparametric data were utilizedfor comparisons between 2 groups. GraphPad Prism 7.04(GraphPad Software, San Diego, CA, USA) was used for allstatistical analyses. p value < 0.05 was considered statisticallysignificant.

3. Results

3.1. Identification of Differentially Expressed lncRNAs andmRNAs. In total, 56 lncRNAs and 298 mRNAs were signifi-cantly differentially expressed in BV2microglial cells exposedto LPS. The top 30 most significantly differentially expressedlncRNAs (Figure 1(a)) and mRNAs (Figure 1(b)) were shownon heat map.

3.2. GO and Pathway Enrichment Analyses. DEGs weremainly enriched in the following functions: immune systemprocess, innate immune response, inflammatory response,and response to lipopolysaccharide (Figures 2(a)–2(c)). Ourresults also suggested that DEGs were mainly enriched in thefollowing pathways: Herpes simplex infection, NF-kappa Bsignaling pathway, TNF signaling pathway, Toll-like receptorsignaling pathway, and NOD-like receptor signaling pathway(Figure 2(d)).

3.3. PPI Network Analysis. To identify hub genes of microgliacell activation, we used STRING to look for interactions ofDEGs in BV2 microglial cells stimulated with LPS. In thepresent study, we constructed a PPI network of 210 nodes and1842 interaction pairs (Figure 3). In the PPI network, the top10 most significantly hub genes were Tnf, Il6, Stat1, Cxcl10,Il1b, Tlr2, Irf1, Ccl2, Irf7, and Ccl5.

3.4. TF Regulatory Network Analysis. The TFs of the top 30hub genes in the PPI network were predicted.With NES > 10,nine TFs (Irf1, Irf2, Irf4, Irf5, Irf8, Irf9, Stat1, Nfkb1, and Rela)were predicted in the TF regulatory network (Figure 4).

3.5. LncRNA-mRNA Coexpression Network. We constructedthe lncRNA-mRNA coexpression network of 26 differentiallyexpressed lncRNAs and 127 interacting DEGs to predictthe functions and mechanisms of differentially expressedlncRNAs in BV2 microglial cells treated with LPS (Figure 5).

http://david.ncifcrf.govhttp://string-db.org

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Gm3170H2-Q5Gm69046530402F18RikGm13822Mir221LOC100041057Gm16181Mir147Gm21188Gm26527Rnf213Gm38718Gm10719Gm6665Gm23722Gm23442Gm8989Gm10719Gm8979Gm8995Gm41656Pstpip2Gm23514Gm18853Gm17757Gm7609Gm7592Ms4a14Mir155

3.5

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SpicZfp811Cxcl10Gbp7Slamf7MarcoCcrl2Cxcl2I16Clec4a1SlpiBcl3Vnn3FasRtp4Clec4eTxnrd1Saa3Zc3h12cCalcrlSlIfn2AoahNfkbiaC3SIc7a11ll1all1bLcn2Rsad2Irg1

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Figure 1: Hierarchical clustering of differentially expressed lncRNAs (a) andmRNAs (b). Red and blue columns refer to high and low relativeexpression, respectively.

The top 5 hub lncRNAs were Gm8989, Gm8979, Gm8995,AV051173, and Gm7609 in the coexpression network.

3.6. Real-TimePCR. Five lncRNAs (6530402F18Rik,AV051173,Gm8979, Gm8989, and Gm18853) and IL6 mRNA wereselected to determine their relative expression levels by real-time PCR (Figure 6). Our results showed that Gm8979,Gm8989, AV051173, 6530402F18Rik, and IL6 were upreg-ulated. The expression of Gm18853 showed no significantchange.

4. Discussion

Neuropathic pain seriously increases healthcare costs andimpairs patients’ quality of life with an incidence of 7–10%worldwide [3, 4]. Microglia cell activation is essential to theprogression of neuropathic pain in vivo [6, 7].The research ofmicroglia cell activation provides opportunities to reveal themolecular and cellular basis of neuropathic pain [6–8].

It has shown that lncRNAs participate in most essentialbiological processes at the levels of posttranscription, tran-scription, and epigenetics [12–15, 31]. Over the past decade,there have been several lncRNA transcriptome researchesin chronic pain. Differentially expressed lncRNAs wereidentified in SNI-induced neuropathic pain using high-throughput sequencing techniques, revealing a series ofpotential therapeutic targets of neuropathic pain [17]. Unlikethe previous study, which made the spinal cord as a whole,we downloaded and analysed raw data of GSE103156, whichestablished microglia cell activation model by stimulating

BV2 microglial cells with LPS. In addition to common prop-erties of immortalized cell lines (e.g., increased proliferationand adherence), BV2 cells retain most crucial functions ofmicroglia in immune response and inflammation [32, 33].BV2 cells stimulatedwith LPS in vitro resemble themicroglialresponse in vivo to some extent.

In the present study, we identified 56 differentiallyexpressed lncRNAs and 298 DEGs in BV2 microglialcells stimulated with LPS. DEGs were mainly enriched inthe following functions: immune system process, innateimmune response, inflammatory response, and response tolipopolysaccharide. Pathway analysis results showed thatDEGs mainly involved in Herpes simplex infection, NF-kappa B signaling pathway, TNF signaling pathway, Toll-likereceptor signaling pathway, and NOD-like receptor signalingpathway.The experimentalmodel was successfully developedsince the mRNA expression levels of Il6, Il1a, Il1b, Tnf, andCxcl10 increased in BV2 microglial cells stimulated withLPS [34, 35]. The expression levels of IL6 mRNAs in themicroarray were similar to those detected by real-time PCR.

PPI network analysis results showed that many differ-entially expressed genes, such as Irf1, Irf7, Stat1, and Tlr2,acted as hub genes in microglia cell activation. Recent studieshave revealed a crosstalk between Tlr2 and microglia cellactivation [6, 36]. Although further experimental validationwas needed, our results suggested new directions for futureexperimental research. We predicted 9 TFs (Irf1, Irf2, Irf4,Irf5, Irf8, Irf9, Stat1, Nfkb1, andRela)mapping to 32 hug genesin PPI network. Notably, IRF1, IRF9, Stat1, and Nfkb1 weresignificantly upregulated in BV2 microglial cells exposed toLPS in the microarray analysis results.

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BP

intrinsic apoptotic signaling pathwaypositive regulation of interleukin−6 production

lipopolysaccharide−mediated signaling pathwaynegative regulation of viral genome replicationdefense response to Gram−positive bacterium

cellular response to interleukin−1cellular response to interferon−gamma

transcription factor activitypositive regulation of NF−kappaB

positive regulation of ERK1 and ERK2 cascaderegulation of cell proliferation

regulation of apoptotic processpositive regulation of apoptotic process

response to lipopolysaccharideimmune responseresponse to virus

cellular response to lipopolysaccharidedefense response to virus

inflammatory responseinnate immune responseimmune system process

1020

3040

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10152025

-log(p value)

Gene ratio0.025 0.050 0.075 0.100 0.125

(a)

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CC

semaphorin receptor complexsymbiont-containing vacuole membrane

MHC class I protein complex

extrinsic component of cytoplasmic sideof plasma membrane

phagocytic vesicle membranelysosome

external side of plasma membraneprotein complex

cytoplasmic vesicleperinuclear region of cytoplasm

integral component of plasma membranecell surface

endoplasmic reticulumGolgi apparatus

extracellular spaceextracellular region

cytosolextracellular exosome

membranecytoplasm

0.0 0.1 0.2 0.3

23456

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Count255075

100125

(b)

MF

Gene ratio

hydrolase activity, acting on acid anhydridesCCR5 chemokine receptor binding

tumor necrosis factor-activated receptor activitychannel activity

BH domain bindingsemaphorin receptor activity

chemokine activitymanganese ion binding

non-membrane spanning proteintyrosine kinase activity

peptide antigen binding2'-5'-oligoadenylate synthetase activity

ubiquitin protein ligase bindingdouble-stranded RNA binding

cytokine activityprotein heterodimerization activity

receptor bindingoxidoreductase activity

hydrolase activityATP binding

protein binding

0.00 0.05 0.10 0.15 0.20

234567

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Gene ratio

Cytosolic DNA-sensing pathwayLeishmaniasis

Allograft rejectionType I diabetes mellitus

PertussisNOD-like receptor signaling pathway

Graft-versus-host diseaseHepatitis BHepatitis C

Osteoclast differentiationToll-like receptor signaling pathway

Transcriptional misregulation in cancerEpstein-Barr virus infection

Viral carcinogenesisTuberculosis

MeaslesTNF signaling pathway

NF-kappa B signaling pathwayInfluenza A

Herpes simplex infection

0.04 0.06 0.08

7.510.012.515.017.5

-log(p value)

Count101520

2530

(d)

Figure 2: GO and KEGG enrichment analyses of differentially expressed mRNAs (Top 20, p < 0.05). GO functional analysis includes threecategories: biological process (BP) (a), cellular component (CC), (b) and molecular function (MF) (c). Red to green colors indicate high tolow -log (p value) levels. Point size indicates the number of differentially expressed genes in the corresponding pathway.

Many studies have indicated that interferon regulatoryfactor (IRF) family was involved in the pathophysiology ofmicroglial activation and neuropathic pain [37–39]. IRF8,interacted with IRF1 and IRF5, played an important regu-latory role in the progression of neuropathic pain [40–42].Recent studies have shown that Stat1 and Nfkb1 were closelyrelated to neuropathic pain [43–46]. However, the regulatorymechanisms of the IRF family and other transcriptionalfactors in microglia cell activation should be further studiedto determine their therapeutic effects in neuropathic pain invivo.

Based on fold change and degree in the lncRNA-mRNAcoexpression network, five lncRNAs (AV051173, Gm8979,Gm8989, 6530402F18Rik, and Gm18853) were selected toevaluate the expression levels using real-time PCR. Therelative expression levels of selected lncRNAs, except forGm18853,were consistentwith these trends in themicroarray.The variation between real-time PCR and microarray mayrelate to differences between the methods [47].

LncRNAs often transcribed together with their adjacentor overlapping target genes and regulate their expressionthrough cis-regulation. Integrated bioinformatics analysis

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Rtn2

Dtx2Cd40

Ifi205

Cd52Sgms2

C1qc

Acp5

Rab11fip1Bik

Il1b

Saa3Cxcr4 Ebi3Irf7 Ddx58Gpr84

Cd14

Fut8

Parp14

Wdtc1Mina

Hp

Rhou

Il1rnCcdc88a

Thbs1

Id3Fosl1

Tlr3

Pilrb1Tnfrsf8Ifih1

HckTnfaip3

H2-M2

Abcc5 Plxna1

Rgs11

Traf1

Cysltr1Ampd3

Lrrc25Mef2cPlk2

Oasl2

Syk

Clec4eLamc1 Nos2Sqrdl Cd274Ccrl2

Sqstm1

Lcn2

Zc3h12a

Casp4 Sepp1

Mx2

Slfn2

Cfb

Sod2Plau Il1a

Srxn1 Ifit2Stat1

Birc3

Il6Epsti1

Slc2a6Me1

St3gal1Tlr2

Clec4d

Mpeg1

Stx11Tnf

BC006779

Gbp5

Gclm

Ccl2Src Irf1

Cp F13a1

Aqp9

Cxcl10

Ifi44

Ccdc41

Ppap2b

Serp1

Cfl2Ehd1Bcl2a1a

Calcrl Rsad2

Bcl2a1d

Pou2f2

Malt1

Ms4a6d

Cxcl2

Zbp1

Ripk2

PilraMycIrak3

Isg15

Gch1

Creb5

Ptgs1

Plxnd1

Rab20

Rtp4

Apol9a

Pim1Hdc

H2-Q4

Osbp2Prdx1

Ikbke

Herc6

Jak2

Dtx4

Nfkb2 Nlrp3Slc11a2

Tnfrsf1b

Met

Plxna2

Ms4a7Ccl4

Nrp2Tnip1

Ppp2r5bTm9sf4

Serpinb1a

Smurf1

Hdac9 Usp18

Hspa4l

Xaf1Ppp3cc

H2-T23Isg20

Gbp7Gbp2

Ifitm3Cybb

Plagl2

Ddx60

Adora2a

Itga5Lilrb3

Prdm1Cd80

Gpd2

Cmpk2

Nod2

EsdNol10

Cd69

Ifit1

Irak2 Tnfaip2

Traf2

Gsr

FasNfkbiz

Ttpal

Uchl1

Pde4b

Txnrd1

Ccl9

Bcl3

Ptgir

Oas1g

Oas1a

Sp100

Ets2Parp12

Rel

Gadd45g

Oas3

Gbp3

Grap

Irgm1

Prkar2b

Ccl5

Bcl2a1cPhf11b

Procr

Ptgs2

Oasl1

Tnip3

Oas2

Gadd45a

C3

Dhx58Agrn

Skil

Irg1

Nfkbia

Slc15a3Mmp9

Mrc1

Gtpbp2

Nfkbie

Slpi

Tyk2

Figure 3: PPI network of 210 differentially expressed mRNAs with 1842 interaction pairs. Blue dots and red dots indicate downregulated andupregulated mRNAs, respectively. Circle size indicates the node degree.

Ifit1

Ifit2

Nos2Ifih1

Ifi44SrcStat1

Tnf

RelaNfkb1

Ccl2

Nfkbia

Irf9

Irf8

Irf7

Oasl2

Irf5

Irf2

Irf1

Mx2

Irf4Rsad2

Ddx58Il1b

Tlr3

Usp18Myc

Tlr2

Cxcl10

Ccl5Zbp1

Il6

Cd40 Jak2

Oas2

Isg15

Oasl1

Rel

Figure 4: TF regulatory network of the top 30 hub genes in the PPI network. Green octagons represent TFs, and purple circles represent theircorrelated mRNAs.

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Helz2

Apol9a Gm13213

Gbp5

Ms4a7Gm21188

Oas1a

Gm14636

Zbp1

Epsti1

Tlr3

LOC100041903

Ifi44

D130040H23Rik

Ifi205

Usp18

Myc

Oas1g

Gm7592

Gm15433Ifitm3

Sp100

Oasl2

Gm18853

Cd302

Gm17757

Abcc5Procr

Src

Ifit1

Prdx1Plxna1

Clec4d

H2-M2

Ebi3

Tm9sf4

Mx2

H2-Q4Gm38718

Xaf1Slc11a2

Ms4a6d

Gm7609

Ifit2Oas2

Casp4

Met

Herc6Pilrb1

Srxn1

Itga5

Sqrdl

Ddx60Gdf15

LOC102633783

Mcoln2Irf1

Eid3

Phf11d

Isg20

Cd274Pirb

Isg15

Gm5424Tnfaip3

Car13

Gm3170

Plk2

H2-T23

Gm4070

Gm8979Irgm1

Gm23514Gm8995

Blvrb

Rtp4 Stx11

Gm8989Acp5

Rnf213Slc22a4

Ifih1Oas3

Stat1

Ddx58

Ppt2

Dhx58

Gsap

Slc15a3

Susd6

Parp14Adora2aAim1

Clec4e

Snora44 Tma16 Oasl1

Rasa4Slamf7 Traf2

Phf11b

Gbp2Plpp1St5

Gm25160

AV051173

Lrrc25Cfb

Cmpk2

Gbp7

Gbp3

Mir221Plpp3Nfkbie

Cyb561a3

C3Creb5

Gclm

Ddhd1

Ms4a14Tnfrsf1b St3gal1Traf1

Ccl5

Fam20c

Mapkbp1

Aoah

RhouGm6665

Gm39969

Ampd3 Bcl2a1a

Ralgps1

Ccl4

Cd40

Plagl2

Irf7Slfn2Zcchc2

Parp12

Sqstm1

Zc3h12a

Trim12a

Zscan29

Cd52

Tnip1

Gtpbp2

Gadd45g

Mpeg1 Ehd1

Slc2a6

H2-T22

Tnfaip2

Figure 5: Coexpression network of 26 differentially expressed lncRNAs and 127 interacting differentially expressed mRNAs. The diamondswith blue represent lncRNAs; the circles with red represent their correlated mRNAs. Circle size indicates the node degree.

showed that AV051173 was coexpressed with Prdx1, with itslocation next to the Prdx1 gene on the same chromosome.Notably, Prdx1 was upregulated in BV2 microglial cellsexposed to LPS. Prdx 1 regulated NF-𝜅B-mediated microglialactivation as an antioxidant [48]. AV051173might be involvedin microglia cell activation by cis-regulatory role in theexpression of Prdx1.

In contrast to cis-regulating lncRNAs, trans-regulatinglncRNAs regulate gene expression far away from the siteof primary locus of transcription [49, 50]. Gm8979 andGm8989 are Gvin1 pseudogene, located on Chromosome 7.In the lncRNA-mRNA coexpression network, Gm8979 andGm8989 were significantly coexpressed with mRNAs (Stat1and Tlr3) via trans-acting mechanism. Stat1 and TLR3 playedan important regulatory role in BV2 cell activation [44, 51].Gm8979 and Gm8989 might be involved in microglial cellactivation by regulating the expression of Stat1 and Tlr3through a trans-acting mechanism.

Despite the results obtained above, there were somelimitations in this study. Firstly, even with the similarity toprimary microglia, BV2 microglial cells contain oncogeneswhich render them different from primarymicroglia in someways, such as proliferation, adhesion, and the variance of

morphologies. Secondary, the vitro model of microglia cellactivation has limitations because the condition is encom-passed bymultiple cell types and responses in vivo.Therefore,it needs to be considered with caution about the associationbetween the findings and the microglial cells activation ofneuropathic pain in vivo.

5. Conclusions

In conclusion, we downloaded raw data of GSE103156from the GEO data repository and identified differentiallyexpressed lncRNAs and DEGs in BV2 microglia cell acti-vation. The findings suggested that differentially expressedlncRNAs may regulate the expression of target genes actingas cis-acting or trans-acting factors. The findings may pro-vide relevant information for the development of promisingtargets for the microglial cells activation of neuropathic painin vivo in the future.

Data Availability

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

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Figure 6: Real-time PCR of five lncRNAs and IL6 mRNA in BV2 microglial cells exposed to LPS. All data are means ± SEM (n=3), Student’st-test. ∗ P < 0.05; ∗∗ P < 0.01; ∗ ∗ ∗ P < 0.001; NS, not significant.

Conflicts of Interest

The authors declare that there is no conflict of interestregarding the publication of this paper.

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