Post on 17-Feb-2021
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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0
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SpicZfp811Cxcl10Gbp7Slamf7MarcoCcrl2Cxcl2I16Clec4a1SlpiBcl3Vnn3FasRtp4Clec4eTxnrd1Saa3Zc3h12cCalcrlSlIfn2AoahNfkbiaC3SIc7a11ll1all1bLcn2Rsad2Irg1
4
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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)
Gene ratio
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
-log(p value)
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
-log(p value)
Count2040
6080
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KEGG
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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