Molecular Brain

, 11:21 | Cite as

Identification of lncRNA expression profiles and ceRNA analysis in the spinal cord of morphine-tolerant rats

  • Jiali Shao
  • Jian Wang
  • Jiangju Huang
  • Chang Liu
  • Yundan Pan
  • Qulian Guo
  • Wangyuan Zou
Open Access
Research
  • 91 Downloads

Abstract

Morphine tolerance is a challenging clinical problem that limits the use of morphine in pain treatment, but the mechanisms of morphine tolerance remain unclear. Recent research indicates that long noncoding RNAs (lncRNAs) might be a novel and promising target in the pathogeneses of diseases. Therefore, we hypothesized that lncRNAs might play a role in the development of morphine tolerance. Male Sprague-Dawley rats were intrathecally injected with 10 μg morphine twice daily for 7 consecutive days. The animals were then sacrificed for lncRNA microarray tests, and the results were validated by RT-qPCR. Next, functional predictions for the differentially expressed mRNAs (DEmRNAs) were made with the Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG), and predictions for the differentially expressed lncRNAs (DElncRNAs) were made based on competitive endogenous RNA (ceRNA) analyses. The rats successfully developed morphine tolerance. LncRNA microarray analysis revealed that, according to the criteria of a log2 (fold change) > 1.5 and a P-value < 0.05, 136 lncRNAs and 278 mRNAs were differentially expressed in the morphine tolerance group (MT) compared with the normal saline group (NS). The functions of the DEmRNAs likely involve in the processes of the ion channel transport, pain transmission and immune response. The ceRNA analysis indicated that several possible interacting networks existed, including (MRAK150340, MRAK161211)/miR-219b/Tollip.Further annotations of the potential target mRNAs of the miRNAs according to the gene database suggested that the possible functions of these mRNAs primarily involved the regulation of ubiquitylation, G protein-linked receptors, and Toll-like receptors, which play roles in the development of morphine tolerance. Our findings revealed the profiles of differentially expressed lncRNAs in morphine tolerance conditions, and among these lncRNAs, some DElncRNAs might be new therapeutic targets for morphine tolerance.

Keywords

LncRNA ceRNA Morphine tolerance Spinal cord 

Abbreviations

ceRNA

competitive endogenous

DElncRNA

Differentially expressed lncRNA

DEmRNA

Differentially expressed mRNA

GO

Gene Ontology

KEGG

Kyoto Encyclopedia of Genes and Genomes

lncRNA

Long noncoding RNA

MOR

μ-opioid receptor

MT

Morphine tolerance

NCBI

National Center for Biotechnology Information

ncRNA

Noncoding RNA

NS

Normal saline

Tollip

Toll-interacting protein

Introduction

Morphine tolerance is defined as the diminished analgesic effect and the need for a higher dose to achieve the desired analgesic effect after chronic exposure to morphine [1, 2, 3, 4]. Over the past decades, people have attempted to elaborate the mechanisms of morphine tolerance with minimal success. The recent focus of this area is the role of non-coding RNAs (ncRNAs) [5, 6]. Among ncRNAs, some studies have reported that miRNAs are involved in the development of morphine tolerance [7, 8], including the let-7 family, miR-23b [9], miR-133b, miR-339 [10], miR-365 [11] and miR-219-5p [12]. However, the research regarding long non-coding RNAs (lncRNAs) is still in its infancy.

The sequences of lncRNAs range in size from approximately 200 nt to over 100 kb, and lncRNAs can function in novel mechanisms of the modulation of the expression of genes [13, 14]. Over the past decades, lncRNAs have been the highlight of some studies of cancer, osteoarthritis, nervous system function and development [15, 16, 17]. In pain research, recent studies have claimed that Knav2 AS [18], uc.48+ [19] and some other lncRNAs [20] might play roles in the process of the development of neuropathic pain [21, 22]. The function of lncRNAs has been illustrated as follows: lncRNAs can interact with mRNAs, bind to transcription factors, modulate chromatin remodeling, and even directly regulate the functions of target proteins. Among lncRNAs, some may act as competitive endogenous RNAs (ceRNAs) that target miRNAs [14].

The ceRNA hypothesis was proposed in 2011 with the aim of further elaborating the relationships among RNAs. Salmena et al. [23] highlighted that some RNAs act as ceRNAs that participate in mutual competition for common binding sites of target miRNAs and thus modify the functions of the target miRNAs. Recent research has indicated that ceRNA analysis might shed a light on functional predictions of the effects of lncRNAs [24].

Therefore, in the present study, we hypothesized that lncRNAs might be differentially expressed and act in direct or indirect manners during the development of morphine tolerance. To address this hypothesis, we attempted to identify the lncRNA expression profiles in the spinal cords of rats under normal and morphine tolerance conditions and to predict the possible functions of differentially expressed lncRNAs (DElncRNAs).

Methods

Intrathecal injection of morphine induces a chronic morphine tolerance model in rats

Adult male Sprague-Dawley rats (weight 240–260 g) were obtained from the Hunan SJA Laboratory Animal Company (Hunan, China). The rats were housed in groups and maintained on a 12/12 light-dark cycle at a room temperature of 22 ± 1 °C with food and water freely available. The experimental procedures were approved by the Animal Care and Use Committee of Central South University and conducted in strict accordance with the guidelines of the International Association for the Study of Pain [25]. To establish the rat model of morphine tolerance, rats in the morphine tolerance group (MT, n = 8) were intrathecally injected (i.t.) with 10 μg (1 μg/1 μl) of morphine twice daily at 08:00–09:00 am and 16:00–17:00 pm for 7 consecutive days [3, 26]. The normal saline group (NS, n = 8) was injected with equal volumes of normal saline at the same time points.

Tail flick test

The tail flick test was used to measure thermal sensitivity. Before conducting this test, the rats were placed on the plantar surface for 15 min to adapt to the testing environment. Then, we tested one fixed point of the tail 2–3 cm from the tip using the Hargreaves apparatus (Italy, UGO Basile) [26, 27]. The results are expressed as the tail withdrawal latency (TWL), which was ultimately converted to the percent of the maximum possible effect (%MPE). The radiant index was set at 90, and the cut-off was 20 s to avoid tissue damage. The tests were conducted 30 min before and after the morning injection of morphine on days 1, 3, 5, and 7.

Tissue collection and RNA isolation

On day 8, after the morning injection with morphine or saline, the rats were deeply anesthetized with pentobarbital sodium (1%) one hour later. Then, we decapitated the rats, collected the lumbar enlargements and placed the collected tissues into liquid nitrogen as quickly as possible for preservation. Next, we extracted the total RNA from the spinal tissues and tested the RNA quantity and quality with a NanoDrop ND-1000 Spectrophotometer (Thermo,USA) and tested the RNA integrity with agarose gel electrophoresis (2%). Subsequently, we stored the remnant RNA at − 80 °C for later use. The RNA isolation was performed by Kangcheng Bio-tech (Shanghai, China).

Microarray assay

We employed a rat lncRNA microarray 4 × 44 k,V1.0 (Arraystar) containing approximately 9000 lncRNAs to screen the differentially expressed lncRNAs and mRNAs. The total RNAs of the MT and NS groups (n = 5) were hybridized with the gene chips. The RNA samples were transcribed into fluorescent cRNAs along the entire lengths of the transcripts without a 3′ bias utilizing random primers. The labeled cRNAs were hybridized to the rat lncRNA microarray. Next, the arrays were scanned with an Agilent DNA Microarray Scanner (part number G2505C). The array images were analyzed with Agilent Feature Extraction software (version 11.0.1.1). Quantile normalization and subsequent data processing were performed using the GeneSpring GX v12.1 software package (Agilent Technologies,USA). The microarray hybridization was performed by Kangcheng Bio-tech (Shanghai, China).

Bioinformatics analysis

We used the criteria of a log2 (fold-change) > 1.5 and a P-value < 0.05 to screen for the deregulated RNAs. Hierarchical clustering was performed with Cluster 3.0, and the heat maps were generated in Java Treeview. The DEmRNAs were analyzed according to the pathway annotations of the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) functional enrichment using CapitalBion. The -log10 (P-values) of the GO and pathway results are displayed in the histogram. The DElncRNAs were analyzed by ceRNA analyses, which were conducted with Arraystar’s homemade miRNA target prediction software, which is based on TargetScan and miRanda [28]. A lncRNA/miRNA/mRNA interaction network was generated to visualize the interactions using Cytoscape. The NCBI Database was used to annotate the functions of the potential target genes.

Real-time quantitative polymerase chain reaction (RT-qPCR)

The microarray results were confirmed by RT-qPCR. The total RNAs of the MT and NS groups (n = 5 in each group) were reverse transcribed using random hexamer primers (Arraystar Flash RNA Labeling Kit, Arraystar) according to the manufacturer’s description. The expression levels of 18 lncRNAs (MRAK080737, MRAK159688, MRAK046606, DQ266361, XR_005988, uc.48+, uc.310-, XR_009527, XR_008662, S66184, MRAK161211, MRAK150340, XR_006440, AF196267, MRAK077287, MRAK014088, MRAK141001 and MRAK038897), as well as 12 DEmRNAs (S100a8, Batf, Ccl7, RT1-Bb, RatNP-3b, Grm2 and Mmp9, Prrx2, Asb2, Fam111a, Kcnv2 and Tmem119) were examined. GAPDH was used as the house-keeping gene. The sequences of all primers are presented in Table 1. We conducted the RT-qPCR tests with a 10 μL reaction system in a ViiA 7 Real-time qPCR System according to the manufacturer’s protocol. Melting-curve analysis was performed to monitor the specificity of the production. All experiments were replicated three times. The gene expression levels in the MT and NS groups were analyzed with the 2−ΔΔCT method.
Table 1

The detailed information of primer sequence

Sequence name

Primer sequence

Amplicon size (bp)

GAPDH(RAT)

F:5’ GCTCTCTGCTCCTCCCTGTTCTA3’

R:5’ TGGTAACCAGGCGTCCGATA3’

124

MRAK161211

F:5’CTGACCCCAAAGTTTCACATCT3’

R:5’CCAGGAGAGGTGTTCCAAGTAA3’

63

MRAK038897

F:5’TGGCAAGAATACCAAAGAGC3’

R:5’CACAGCAAGATGTAATGCACAG3’

132

MRAK014088

F:5’GTGTCTATTTCTGGGAGTCTGTGC3’

R:5’GCCATTGGTAAGAGAATTAAGCAG3’

102

MRAK080737

F:5’GTGCCAGACCCCAAGGTAAA3’

R:5’GAGACAATAATGGAGCCGCC3’

105

MRAK159688

F:5’GTACTGTAGCTCTTCAGCGTCC3’

R:5’GTCAGAACATTCAGACCACCTC3’

78

MRAK046606

F:5’GCCAGCATCTCCTACTCACA3’

R:5’TGGACTACGGACTACAGTTTACC3’

80

MRAK150340

F:5’ACAGAGTAGGGCAGTCGCAG3’

R:5’GGTTGTGGACCATAGAAGAGTTG3’

205

DQ266361

F:5’TGTGGTTAAATCCCCATGC3’

R:5’CTTCTCCAAGTCACATCTGCTC3’

63

XR_006440

F:5’GGAGCATCAAATCGAAAGC3’

R:5’ACTCGGATCGTCTCAAGGAC3’

162

XR_005988

F:5’TGTGACACCACTGAGACCCTT3’

R:5’TGGCCCTCCACACTTTACGA3’

101

uc.48+

F:5’ AAATGCAAACTGGATGAGGA 3′

R:5’ GTTAACACTGTATGTAATTAGGG 3’

279

uc.310-

F:5’ CTAATCAAAAACTGACAGCAAGA 3′

R:5’ GATCTTTCTTAAGCAGAATTTGG 3’

128

XR_009527

F:5’ CCAAGGCCCGTATTGAGATTA 3′

R:5’ AGGGTCCAATGTGCCACGA 3’

116

XR_008662

F:5’ TAATGAGGAAGATGAGAATGGC 3′

R:5’ CCAGATAGGCTTCGTCTTATTC 3’

103

S66184

F:5’ TCTTCACATTACCATTACGAGGA 3′

R:5’ CATCGGAATGATTTTGCTGTGT 3’

51

AF196267

F:5’ GCCATCAATTTTCTCTTGACTG 3′

R:5’ TGAAGGGTCAGTTTGAAGCA 3’

135

MRAK077287

F:5’ GCTAATAATTCCTACCAGCAAA 3′

R:5’ ACCTCACACCCAGTCTCTACAT 3’

151

MRAK141001

F:5’ CTTCCCTACCAGTCTATTGAGTG 3′

R:5’ ACGCTCCACTACAAAATCAGTT 3’

87

S100a8

F:5’GGGAATCACCATGCCCTCTA3′

R:5’GCCCACCCTTATCACCAACA3’

168

Batf

F:5’GAGGACCTGGAGAAACAGAATG3’

R:5’GCTCAGCACCGATGTGAAGTA3’

87

Ccl7

F:5’GCTGCTATGTCAAGAAACAAAAGA3’

R:5’TGATGGGCTTCAGCACAGACT3’

136

RT1-Bb

F:5’GCCCTCAACCACCACAACTT3’

R:5’GGTCCAGTCCCCGTTCCTAAT3’

141

Prrx2

F:5’AAGAAGAAGCAGCGTCGGA3’

R:5’CAAAGGCGTCAGGGTAGTGT3’

97

Asb2

F:5’TGCTTTTCCTGCCTGTATGG3’

R:5’CGACAGGAACTCACAGAACTGC3’

120

RatNP-3b

F:5’ CATACGCCAAAGTCTGAAACC 3′

R:5’ AGCAGTGCCTTTATCCCCTC 3’

168

Grm2

F:5’ CCCGGAGAACTTCAACGAA 3′

R:5’ GGCTGGAAAAGGATGATGTG 3’

207

Mmp9

F:5’ CCCACTTACTTTGGAAACG 3′

R:5’ GAAGATGAATGGAAATACGC 3’

228

Fam111a

F:5’ GACTATTTCTCTCAGGTTCCCA 3′

R:5’ GTGCTGCATACAAGCTACTTGT 3’

256

Kcnv2

F:5’ GGGCTGCGGTAAGCATCTCT 3′

R:5’ TTGAGAATAATCCCAAAAGCGA 3’

106

Tmem119

F:5’ AGACAGTCGAACGGTCTAACAG 3′

R:5’ TCACAAGTAGCAGCAGAGACAG 3’

127

Statistical analysis

All data were presented as mean ± s.e.m. The statistical significance of differences between groups was analyzed with two-way repeated-measures of ANOVA followed by Bonferroni test or with Student’s t-test. P values less than 0.05 were considered statistically significant.

Results

Construction of the rat morphine tolerance model

The tail flick test data revealed that there were no significant changes in the thermal sensitivities of NS group (n = 8 in each group). However, comparisons between the two groups revealed that, on day 1 post-injection, the %MPE of the MT group (n = 8 in each group) was significantly higher than that of the NS group (P<0.05). On day 3 post-injection, the % MPE of the MT group began to decline but remained higher than that of the NS group (P<0.05). On day 5 post-injection, the %MPEs did not significantly differ between the two groups (P>0.05), and this state continued to day 7 (Fig. 1a), which suggested that a stable morphine tolerance model had been established.
Fig. 1

(a) Continuous injection of morphine for 7 days induced the formation of morphine analgesic tolerance. The data are expressed as the mean ± s.e.m. (n = 8 in each group). **P < 0.01, ***P < 0.001, Two-way repeated-measures of ANOVA followed by Bonferroni test. Ten samples (n = 5 in each group) were subjected to microarray analysis. b-c The entire and partial hierarchical clusterings of the lncRNAs and mRNAs, respectively; the up- and down-regulated genes are colored in red and green, respectively. d Scatter plot displaying the lncRNAs and mRNAs that exhibited expression differences between the MT and NS groups that exceeded 1.5-fold

Overview of the lncRNA and mRNA expression profiles

First, we created an overview of the lncRNA and mRNA expression profiles using a using scatter plot, which revealed that large numbers of lncRNAs and mRNAs were differentially expressed between the MT and NS groups (n = 5; Fig. 1d). Next, hierarchical cluster analyses of all of the lncRNAs and mRNAs was applied and revealed that the 5 NS and 5 MT samples clustered independently, and the results also indicated high degrees of consistency in both the NS and MT groups (Fig. 1b, c). All of the microarray results have been uploaded to the GEO database (GSE110115).

Differentially expressed lncRNAs and mRNAs in morphine tolerance

According to the criteria of a log2 (fold change) > 1.5 and a P-value< 0.05, the microarray data identified 136 lncRNAs, including 84 up-regulated and 52 down-regulated lncRNAs, which were significantly altered in the MT group compared with the NS group. The lncRNAs that exhibited the greatest up-regulations were XR_005988, DQ266361, and MRAK046606 with XR_005988 exhibiting the largest up-regulation [log2 (fold change) =12.4243]. The lncRNAs that exhibited the greatest down-regulations were AF196267, XR_009493, and MRAK150340 with AF196267 exhibiting the largest down-regulation [log2 (fold change) =2.2025]. Detailed information, including the top 40 up-regulated and top 40 down-regulated lncRNAs, is provided in Table 2.
Table 2

The detailed information of top 40 up-regulated and 40 down-regulated lncRNAs

Up-regulated lncRNAs

Fold change(MT/NS)

P-value

Down-regulated lncRNAs

Fold change(MT/NS)

P-value

XR_005988

12.34156

0.003685

AF196267

2.202529

0.012181

DQ266361

2.486278

0.000882

XR_009493

2.115125

0.019025

MRAK046606

2.367485

0.020344

MRAK150340

2.060765

0.000308

uc.167-

2.199281

0.002987

MRAK037188

1.956905

0.000066

uc.468+

2.137996

0.000249

XR_006440

1.952104

0.003301

XR_009482

2.065426

0.022224

AF196206

1.938910

0.015500

AF305713

2.052460

0.001121

BC126091

1.906750

0.020304

MRAK165072

2.020835

0.015095

uc.370+

1.900405

0.000477

MRAK159688

2.009110

0.008496

MRAK156916

1.879795

0.013478

uc.28-

1.957873

0.033513

XR_008800

1.872603

0.022847

DQ223059

1.911577

0.043779

MRAK077287

1.816863

0.000017

uc.48+

1.897821

0.005311

MRAK014088

1.773360

0.000324

XR_006726

1.887222

0.008923

MRAK161211

1.765669

0.014718

XR_009483

1.883845

0.020077

BC158785

1.742858

0.005583

MRAK013672

1.849562

0.027735

MRuc009dux

1.721422

0.014515

MRAK018927

1.848401

0.025469

MRAK135122

1.718807

0.009117

uc.482-

1.827252

0.000618

MRAK141001

1.690469

0.000352

MRAK138235

1.824250

0.005928

MRuc007nwi

1.688666

0.043028

uc.156-

1.810205

0.037932

uc.264-

1.687839

0.023742

XR_008353

1.802395

0.008201

EF088428

1.673345

0.001656

uc.462+

1.791152

0.001958

uc.363+

1.672870

0.011181

MRAK134839

1.770980

0.033987

BC169026

1.665411

0.007442

MRAK054291

1.760502

0.037076

MRAK008891

1.659204

0.018204

BC093392

1.758918

0.030404

MRAK135686

1.656007

0.005067

MRuc007cgx

1.756746

0.023148

MRAK051195

1.625373

0.000267

MRAK050995

1.742487

0.032134

BC097960

1.619298

0.003837

XR_009527

1.742256

0.022408

MRAK169397

1.617138

0.030259

uc.395-

1.733383

0.035051

MRAK046121

1.614043

0.005023

XR_005532

1.732123

0.042440

MRAK080238

1.594013

0.000840

uc.158-

1.723747

0.010144

BC061963

1.592978

0.002208

MRuc007jeg

1.722591

0.006501

MRAK013677

1.592863

0.000261

XR_008662

1.716865

0.020951

XR_009137

1.575140

0.014863

XR_008674

1.695926

0.047672

BC086373

1.561696

0.008523

S66184

1.680145

0.026505

MRAK083715

1.557152

0.004611

M81783

1.670161

0.011349

MRAK038897

1.555085

0.007252

MRAK083472

1.662885

0.008172

MRAK041309

1.554516

0.000067

XR_009489

1.660491

0.002298

MRAK147844

1.551990

0.000730

XR_008266

1.654757

0.012200

MRAK051810

1.549681

0.022164

uc.310-

1.653784

0.013204

uc.185+

1.545991

0.024361

uc.463-

1.651362

0.021613

BC079474

1.544677

0.000147

Regarding the DEmRNAs, there were 278 genes (176 up-regulated and 102 down-regulated) whose changes met the criteria. These DEmRNAs contained many genes that are known to be involved in pain processing, including Ccl7, Batf, S100a8, Kcnv2, Rgs1, Prrx2, Mmp9, etc. Detailed information about the top 30 up-regulated and top 30 down-regulated mRNAs is listed in Table 3.
Table 3

The detailed information of top 30 up-regulated and 30 down-regulated mRNAs

Gene symbol

Description

Fold change(MT/NS)

P-value

Up-regulated genes

 RT1-Bb

RT1 class II, locus Bb

26.0600137

0.03123893

 RatNP-3b

defensin RatNP-3 precursor

4.6945682

0.00237615

 Lilrb3

leukocyte immunoglobulin-like receptor, subfamily B (with TM and ITIM domains), member 3

4.3359795

0.00815228

 Defa7

alpha-defensin 7

4.2552547

0.00156229

 Clecsf9

macrophage-inducible C-type lectin

3.4622832

0.01864872

 Ccl7

chemokine (C-C motif) ligand 7

3.3728046

0.01483951

 Sele

selectin, endothelial cell

3.3632425

0.03028204

 Slpi

secretory leukocyte peptidase inhibitor

3.2118152

0.00024306

 Lilrc2

leukocyte immunoglobulin-like receptor

3.1471364

0.01375120

 V1rj4

vomeronasal 1 receptor, J4

2.9047312

0.03220865

 Gja5

gap junction membrane channel protein alpha 5

2.8707048

0.02230140

 Mmp9

matrix metallopeptidase 9

2.832538

0.02991875

 Batf

basic leucine zipper transcription factor

2.7432184

0.00125327

 S100a8

S100 calcium binding protein A8 (calgranulin A)

2.7009035

0.00561932

 Birc3

baculoviral IAP repeat-containing 3

2.6968995

0.01058921

 Bcl3

B-cell CLL/lymphoma 3

2.6847827

0.00419171

 Ccr1

chemokine (C-C motif) receptor 1

2.5775393

0.00007731

 Olr463

olfactory receptor 463 (predicted)

2.5772986

0.01425058

 Np4

defensin NP-4 precursor

2.4883044

0.00271115

 Grm2

glutamate receptor, metabotropic 2

2.4429944

0.00113554

 Slpil2

antileukoproteinase-like 2

2.4380328

0.00066484

 Cnn1

calponin 1

2.4269788

0.02918954

 Olr139

olfactory receptor Olr139

2.4268332

0.01332394

 Obp3

alpha-2u globulin PGCL4

2.3723118

0.03995990

 Crisp4

cysteine-rich secretory protein 4

2.3633549

0.00810051

 Olr1454_predicted

olfactory receptor 1454 (predicted)

2.3350625

0.00247670

 Napsa

napsin A aspartic peptidase

2.2770041

0.00035275

 Olr1374_predicted

olfactory receptor 1374 (predicted)

2.2313479

0.00040213

 LOC497796

Ly49 inhibitory receptor-like

2.2302475

0.00022859

 Slpil3

antileukoproteinase-like 3

2.2153032

0.00045886

Down-regulated genes

 Fam111a

hypothetical protein LOC499322

5.1287218

0.02433528

 Kcnv2

“potassium channel, subfamily V, member 2”

2.8837136

0.00586212

 Fkbp6

FK506 binding protein 6

2.8648794

0.00576975

 Nlrp10

“NLR family, pyrin domain containing 10”

2.6101210

0.00386452

 Rgs1

regulator of G-protein signaling 1

2.4933037

0.00327101

 Ly49i8

Ly49 inhibitory receptor 8

2.3732515

0.01051908

 Tmem119

transmembrane protein 119

2.3374630

0.00064129

 Cldn14

Rattus norvegicus claudin 14”

2.3184480

0.00751794

 Dyrk1a

dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 1A

2.2472669

0.00077705

 Ckmt2

sarcomeric mitochondrial creatine kinase

2.2142101

0.00051314

 Asb2

ankyrin repeat and SOCS box-containing protein 2

2.1709796

0.00039719

 Art2b

ADP-ribosyltransferase 2b

2.1680042

0.00124959

 LOC498335

similar to Small inducible cytokine B13 precursor (CXCL13)

2.1501415

0.00012158

 Prrx2

paired related homeobox 2

2.1294428

0.01452534

 LOC364773

aldo-keto reductase family 1, member C12

2.1023343

0.00302323

 Cdkn2b

cyclin-dependent kinase inhibitor 2B (p15, inhibits CDK4)

2.0882944

0.00336651

 Cd22

CD22 molecule

2.0855279

0.01215534

 Nhlrc2

NHL repeat containing 2

2.0426710

0.00054605

 Fcrls

Fc receptor-like S, scavenger receptor

2.0407116

0.00627688

 Clca3

chloride channel calcium activated 3

2.0188429

0.01580260

 Dntt

deoxynucleotidyltransferase, terminal

2.0019106

0.00547055

 Grap2

GRB2-related adaptor protein 2

1.9900082

0.00968363

 Thrsp

thyroid hormone responsive protein

1.9814822

0.02740488

 Plek2

pleckstrin 2

1.9662998

0.00879852

 Alox12

arachidonate 12-lipoxygenase

1.9121487

0.00631083

 Tnfsf4

tumor necrosis factor (ligand) superfamily, member 4

1.8804698

0.00229007

 Mpzl2

myelin protein zero-like 2

1.8783013

0.00003750

 Prkag3

protein kinase, AMP-activated, gamma 3

1.8643095

0.00970172

 Nr0b2

nuclear receptor subfamily 0, group B, member 2

1.8348501

0.00251892

 Traf3ip3

TRAF3 interacting protein 3

1.8326037

0.02787730

Validation of the lncRNA and mRNA expressions

To validate the reliability of the microarray results, 18 DElncRNAs and 12 DEmRNAs were selected and validated by RT-qPCR. The data shown that 11 of 18 selected DElncRNAs (XR_005988, DQ266361, MRAK159688, XR_008662, XR_009527, S66184, MRAK150340, MRAK161211, MRAK038897, AF196267 and MRAK141001) and 7 of 12 selected DEmRNAs (Batf, Ccl7, RatNP-3b, Mmp9, Kcnv2, Tmem119 and Asb2) exhibited the same trends in altered expressions and the same significant differences in the microarray and RT-qPCR analyses. On the other hand, the other altered mRNAs and lncRNAs exhibited the trends in changes, but the differences between the two groups were not significant, possibly due to the small sample size (Fig. 2a, b).
Fig. 2

RT-qPCR validation of eighteen deregulated lncRNAs (a) and twelve deregulated mRNAs (b) in the lumbar enlargements of both groups. Student’s t-test. *P < 0.05, **P < 0.01, ***P < 0.001. Distribution of the various types of DElncRNAs. c Five classes (bidirectional lncRNAs, antisense lncRNAs, sense lncRNAs, intergenic lncRNAs and the other lncRNAs) were analyzed

Class distributions of the DElncRNAs

The examined lncRNAs were categorized into five groups according to their associations with coding genes: intergenic lncRNAs, antisense overlap lncRNAs, sense overlap lncRNAs, bidirectional lncRNAs, and other. One of the mechanisms by which lncRNAs act is through the interplay with adjacent coding genes [20, 29]; therefore, it was important to classify the locations of the lncRNAs. Our data revealed that, among these DElncRNAs, intergenic lncRNAs and sense overlap lncRNAs accounted for the majority, and only five lncRNAs belonged to the bidirectional category. The concrete data are presented in Fig. 2c.

Functional predictions for the DEmRNAs in the morphine-tolerant rats

To explore the molecular functions of the DEmRNAs in morphine tolerance conditions, we further performed GO and pathway analyses genes that differentially regulated in the MT and NS groups. The pathway analyses indicated that the most significantly enriched pathways of the up-regulated genes included the TNF metabolic pathway and phagocytic processes, and the down-regulated genes were involved in synaptic vesicle activity, the arachidonic acid metabolic pathway, etc. (Fig. 3a, b). The GO results revealed that the most significantly enriched molecular functions of the up-regulated genes in the MT group were peptidase activity, G-protein-coupled receptor activity, and biological processes concentrated on the cytokine response, defense and the immune response. The cell components primarily belonged to extracellular domains and intercellular domains. The most significantly enriched molecular functions of the down-regulated genes in the MT group were voltage-gated channel activity, ion transmembrane activity, and biological processes concentrated on potassium ion transport. The cell components were associated with the sarcolemma, cytoplasmic membrane, and ion channel complexes (Fig. 3c-h).
Fig. 3

Pathway analyses of the 176 up-regulated and 102 down-regulated mRNAs with fold changes > 1.5. a The significant pathways of the up-regulated genes in the MT group. b The significant pathways of the down-regulated genes in the MT group. The biological functions of the differentially expressed mRNAs with fold changes > 1.5 are listed. The significant biological processes (c) cellular components (e) and molecular functions (g) of the up-regulated mRNAs. The significant biological processes (d), cellular components (f) and molecular functions (h) of the down-regulated mRNAs

Functional predictions of the DElncRNAs lncRNA/miRNA/mRNA interactions

We performed coding-noncoding gene co-expression (CNC) analysis, but we found no DEmRNA-associated DElncRNAs, which meant that we were unable to make forecasts about the functions of the DElncRNAs according to the related DEmRNAs. However, ceRNA analysis allowed us to predict the possible functions of the DElncRNAs regardless of their adjacent coding genes. According to the ceRNA analysis, we obtained an overview of the potential lncRNA/miRNA/mRNA interactions (Fig. 4a), and we then further identified several promising networks of lncRNA/miRNA/mRNA interactions (Fig. 4b), which included (MRAK161211, MRAK150340)/miR-219b/Tollip and XR_006440/(miR-365, let7)/(Usp31, Usp42, Clcn4–2) networks, and we used these networks to create functional annotations of the predicted target mRNAs by searching the Gene database. The results indicated that the predicted target mRNAs mainly functioned in the process of ubiquitinylation, the GRCP and TLR signaling pathways, and the modulations of transcription, translation and post-translational modification, and these functions might constitute the foundation of morphine tolerance.
Fig. 4

ceRNA analyses indicated the potential lncRNA/miRNA/mRNA interactions. a The potential binding target miRNAs of the verified lncRNAs. The red nodes mean down-regulated lncRNAs, the gray nodes mean up-regulated lncRNAs, the blue squares mean down-regulated miRNAs we are interested in, the green squares mean up-regulated miRNA we are interested in, and the pink nodes mean the other miRNAs and mRNAs. b The lncRNA/miRNA/mRNA networks that we are interested in are displayed. The green nodes represent lncRNAs, the yellow pentagons represent miRNAs and the pink nodes represent mRNAs we forecasted

Discussion

In the present study, we detected 136 DElncRNAs and 278 DEmRNAs overall and we found that compared with normal rats, DElncRNAs and DEmRNAs were present in the spinal cords of morphine-tolerant rats; GO and KEGG pathway analyses revealed that the potential functions of the DEmRNAs may be concentrated on the processes that are thought be involved in the formation of morphine tolerance; and the ceRNA analysis identified several potential lncRNA/miRNA/mRNA interaction networks that might modulate the development of morphine tolerance.

To identify as many DElncRNAs and DEmRNAs candidates as possible, we set the criteria at a log2 (fold change) > 1.5 and a P-value < 0.05 [30]. Next, we considered several criteria to select lncRNAs and mRNAs from our microarray data for validation. Firstly, we attempted to select the relevant candidates that might be related to our previous studies of morphine tolerance and miRNAs [11, 12]. Secondly, for validation, we chose the lncRNA candidates that exhibited higher fold changes and greater raw expression intensities and had adjacent mRNA that was related to morphine tolerance.

Among the DElncRNAs that we detected, XR_005988 exhibited the most significant up-regulation and was classified as a long intergenic non-coding RNA (lincRNA). Although we obtained no information about XR_005988 or its associated genes through searches of all types of gene databases, it is well known that lncRNAs account for the main portion of lncRNAs and exhibit the most substantial biological functions [31], which indicates that XR_005988 is still a promising lncRNA molecule for further study. Additionally, XR_005988 might bind to some miRNAs according to the ceRNA analysis, which indicates its potential action as a ceRNA. Of course, additional in vivo and in vitro functional research is needed.

MRAK-159688, which was another up-regulated lncRNA identified in our study, is associated with the Fos gene and was named the Fos downstream transcript (FosDT) in a report from Mehta et al. [32] Mehta et al. reported that, in an ischemia/reperfusion model, FosDT interacts with the chromatin-modifying proteins Sin3a and co-repressor of the transcription factor REST (coREST) and subsequently represses REST-downstream genes. Moreover, other researchers have indicated that MOR is one of the downstream targets of REST and is negatively modulated by REST in specific neuronal cells [33, 34]. Therefore, the dysregulated MRAK-159688 might be involved in the development of morphine tolerance through interactions with REST.

Since the ceRNA hypothesis was proposed, it has been verified in some tumor diseases. For example, the FER1L4/miRNA106a-5p/PTEN pathway constitutes a novel regulatory pathway that is involved in the occurrence and progression of gastric cancer [35]. Currently, ceRNA analysis is a novel method for predicting the functions of lncRNAs. In our study, we found that several possible interacting pathways among ceRNAs exist, including the following: MRAK161211, MRAK150340/miR-219b/mRNAs (e.g., Tollip, and Ubqln4); XR_006440/miR-365, let7/mRNAs (e.g., Usp31, Usp42, Clcn4–2); and MRAK161211/miR-133/Usp13.

In our previous study, We have confirmed that miR-219-5p can attenuate morphine tolerance by targeting CaMKIIγ [12]. Furthermore, other researchers have also reported that miR-219 is down-regulated following the continuous application of morphine and can regulate NMDA receptor signaling [36]. Whereas in the present study, we predicted that miR-219b, rather than miR-219-5p, would exert this function. Recent research about miR-219 has mainly concentrated on the functions of miR-219-5p, and the other isoform, i.e., miR-219b, has not been studied in detail. However, on the one hand, we identified miR-219-5p and miR-219b, which have both previously been reported to function in the suppression of the proliferation, migration and invasion of cells [37, 38]. On the other hand, when we forecasted the downstream targets of miR-219b, we found that their functions were mainly related to the ubiquitination process, G-protein-coupled receptors, alterations in ion channels, and Toll-like receptor signaling pathway regulation, and these function are all involved in the mechanisms of morphine tolerance. Therefore, given its possible target mRNAs, miR-219b is likely to be a new target related to morphine tolerance.

Toll-interacting protein (Tollip) is a potential downstream target of miR-219b and can modulate the expression of the Toll-like receptor (TLR) via its action as an endogenous inhibitor and regulate the IL-1β-induced activation of NF-κB; thus, miR-219b plays an inhibitory role in inflammatory signaling [39, 40]. Previous studies have demonstrated that the TLR-mediated activation of glial cells and TLR4-mediated NF-κB activation might influence the development of morphine tolerance [41, 42]. Therefore, further study is required and we presumed that the MRAK150340, MRAK161211 (i.e., down-regulated lncRNAs)/miRNA-219b/Tollip interaction network potentially functions in morphine tolerance.

On the one hand, previous studies have suggested that let-7 can suppress the expression of MOR [43], and our previous results suggest miR-365 can modulate morphine tolerance by targeting the beta-arrestin 2 protein [11]. On the other hand, Law et al [44] reported that opioid receptor agonists (such as morphine) promote the ubiquitylation of scaffold proteins and thereby change the expression pattern of the receptor signaling pathway. In the present study, the potential downstream genes that we predicted, i.e., Usp31 and Usp42, are both ubiquitylation-related genes. Therefore, the XR_006440/(let7, miR-365)/(Usp31, Usp42) pathway is likely to be responsible for the formation of morphine tolerance. Moreover, there are other interested candidates other than the validated lncRNAs and mRNAs, and further studies will be needed.

In summary, although our study is preliminary and lacks additional functional experiments, our research has revealed that hundreds of lncRNAs, especially XR_005988 and MRAK159688, are differentially expressed in the spinal cords of morphine-tolerant rats. Further ceRNA analysis revealed that several possible lncRNA/miRNA/mRNA interaction networks exist, and among these networks, the (MRAK150340, MRAK161211)/miR-219b/Tollip network holds the most potential for further studies.

Notes

Funding

This work was supported by grants from the National Natural Science Foundation of China (81471135 and 81771206) and the Natural Science Funds for Distinguished Young Scholars of Hunan Province (2017JJ1036).

Availability of data and materials

Please contact author for data requests.

Authors’ contributions

WZ designed the experiments. JS, JW, JH, CL, YP and WZ performed experiments and analyzed data; JS, QG and WZ drafted the manuscript and finished the final vision of the manuscript. All authors read and approved the final manuscript.

Ethics approval

All experiments were performed in accordance with the Animal Care and Use Committee of Central South University and the guidelines of the International Association for the Study of Pain.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Authors and Affiliations

  1. 1.Department of Anesthesiology, Xiangya HospitalCentral South UniversityChangshaChina

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