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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;
[email protected]
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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2 BioMed Research International
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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BioMed Research International 3
Gm3170H2-Q5Gm69046530402F18RikGm13822Mir221LOC100041057Gm16181Mir147Gm21188Gm26527Rnf213Gm38718Gm10719Gm6665Gm23722Gm23442Gm8989Gm10719Gm8979Gm8995Gm41656Pstpip2Gm23514Gm18853Gm17757Gm7609Gm7592Ms4a14Mir155
3.5
1.75
0
CtrlLPS
lncRNA
(a)
SpicZfp811Cxcl10Gbp7Slamf7MarcoCcrl2Cxcl2I16Clec4a1SlpiBcl3Vnn3FasRtp4Clec4eTxnrd1Saa3Zc3h12cCalcrlSlIfn2AoahNfkbiaC3SIc7a11ll1all1bLcn2Rsad2Irg1
4
2.28
0.55
mRNA
CtrlLPS
(b)
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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4 BioMed Research International
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
Count
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
(c)
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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BioMed Research International 5
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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6 BioMed Research International
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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tive e
xpre
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Gm8979
Ctrl LP
S0
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2
1
Rela
tive e
xpre
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Gm8989
Ctrl
LPS
0.0
2.0
1.5
1.0
0.5Rela
tive e
xpre
ssio
n
AV051173
Ctrl LP
S
0
8
6
4
2Relat
ive e
xpre
ssio
n
6530402F18Rik
Ctrl LP
S
Relat
ive e
xpre
ssio
nGm18853
Ctrl LP
S0
20
15
10
5Rel
ativ
e exp
ress
ion
IL6
Ctrl LP
S
∗∗
∗∗∗
∗
∗
0.0
2.0
1.5
1.0
0.5
NS
25∗∗
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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