Open Access

Japanese encephalitis virus infection induces changes of mRNA profile of mouse spleen and brain

  • Yang Yang1, 2,
  • Jing Ye1, 2,
  • Xiaohong Yang1, 2,
  • Rong Jiang1, 2,
  • Huanchun Chen1, 2 and
  • Shengbo Cao1, 2Email author
Contributed equally
Virology Journal20118:80

https://doi.org/10.1186/1743-422X-8-80

Received: 21 December 2010

Accepted: 24 February 2011

Published: 24 February 2011

Abstract

Background

Japanese encephalitis virus (JEV) is a mosquito-borne flavivirus, leading to an acute encephalitis and damage to the central nervous system (CNS). The mechanism of JEV pathogenesis is still unclear. DNA microarray analyses have been recently employed to detect changes in host gene expression, which is helpful to reveal molecular pathways that govern viral pathogenesis. In order to globally identify candidate host genes associated with JEV pathogenesis, a systematic mRNA profiling was performed in spleens and brains of JEV-infected mice.

Results

The results of microarray analysis showed that 437 genes in spleen and 1119 genes in brain were differentially expressed in response to JEV infection, with obviously upregulated genes like pro-inflammatory chemokines and cytokines, apoptosis-related proteases and IFN inducible transcription factors. And the significant pathways of differentially expressed genes are involved in cytokine-cytokine receptor interaction, natural killer cell mediated cytotoxicity, antigen processing and presentation, MAPK signaling, and toll-like receptor signaling, etc. The differential expression of these genes suggests a strong antiviral response of host but may also contribute to the pathogenesis of JEV resulting in encephalitis. Quantitative RT-PCR (RT-qPCR) assay of some selected genes further confirmed the results of microarray assay.

Conclusions

Data obtained from mRNA microarray suggests that JEV infection causes significant changes of mRNA expression profiles in mouse spleen and brain. Most of differentially expression genes are associated with antiviral response of host, which may provide important information for investigation of JEV pathogenesis and therapeutic method.

Background

Japanese encephalitis virus (JEV), a mosquito-borne flavivirus belonging to family Flaviviridae, is responsible for an acute encephalitis and damage to the central nervous system (CNS) in wide areas of southern and eastern Asia. And recently, it has been isolated from previously non-affected areas, such as Australia [1]. Japanese encephalitis (JE) has a high fatality rate of 30% and around half of the JE survivors have severe neurological sequelae [2]. Approximately 50,000 JE cases with 10,000 deaths are reported annually [3]. Following entry into the host system through a mosquito bite, JEV may replicates in various organs such as liver and spleen, and then reaches the central nervous system, resulting in a rapid inflammatory response [4]. According to the observations from studies of other flaviviruses, specifically dengue virus, it has been proposed that JEV traverse through a lymphatic route that also involves cells of the monocyte/macrophage lineage. Recently, JEV has been shown to effectively replicate within lymphocytes and macrophages, thereby making these cell types possible carriers of the virus from the periphery to the CNS [5, 6]. However, it remains to be elucidated how JEV infects the CNS via these peripheral cells. In addition, although neurological disorders caused by JEV are often characterized by evidence of immune system recognition and the presence of inflammatory components among the neuropathological changes, the mechanisms by which this virus causes neurological disease are not fully understood [7].

Recently, multiple DNA microarray analyses have been employed to detect changes in host gene expression after viral infection, which makes it possible to reveal molecular pathways that govern viral pathogenesis. Genechip analysis of human umbilical vein endothelial cells infected with Dengue Virus (DV) detected the upregulation of 269 genes and downregulation of 126 genes [8]. Gene profiling study of West Nile Virus (WNV) infected human embryonic kidney cells, human glioma cells and mice tissues were also performed [9, 10]. Furthermore, identification of gene profiles in JEV-infected neuroblastoma cells and brain tissue have been reported recently, suggesting an increased expression of pro-inflammatory cytokines, chemokines, and anti-viral response genes after JEV infection [11, 12]. However, both of studies on JEV were restricted to CNS, and few gene profiling researches about response in peripheral immune system has been carried out.

In present study, to globally identify candidate host genes associated with JEV pathogenesis, DNA microarray technology was utilized to investigate mRNA profile in spleen and brain tissues of mice infected with JEV wild strain P3, and some of the selected genes were further confirmed by quantitative RT-PCR. It was demonstrated that JEV infection resulted in significant changes in the expression of numerous genes in spleen and brain tissues, which could be crucial messages for revealing of JEV pathogenesis.

Results

mRNA expression profile of JEV-infected mice

A mouse whole gene array was used to perform a systematic analysis of mRNA expression profile of spleen and brain tissues of JEV P3-infected mice which were sacrificed at day 3 and day 6 post-inoculation respectively. Genes that had ≥ |2|-fold change were identified as significantly differential expression. Of 41174 genes represented on the chip, 437 genes were differentially expressed in mouse spleens and 1119 genes were differentially regulated in brains in response to JEV infection (change fold ≥ 2.0, p value < 0.05). Unsupervised clustering (Figure 1) analysis of the expression profiles showed a distinct mRNA signature in both spleens and brains during JEV infection. To elucidate the correlation between gene expression pattern and JEV infection-induced biological processes, functional classification of mRNA transcripts and pathway analysis were performed. Differentially regulated genes in spleens of JEV-infected mice are involved in the biological processes such as cellular process, biological regulation and immune system process, etc (Figure 2A). And the significant pathways of differentially expressed genes are known to be involved in cytokine-cytokine receptor interaction, natural killer cell mediated cytotoxicity, antigen processing and presentation, and chemokine signaling, etc (Table 1). While biological processes which showed differentially regulated genes in brains of JEV infected mice are cellular process, metabolic process, and biological regulation, etc (Figure 2B). And the significant pathways of differentially expressed genes in mouse brain are cytokine-cytokine receptor interaction, MAPK signaling, neuroactive ligand-receptor interaction, and toll-like receptor signaling, etc. (Table 2).
Figure 1

Unsupervised hierarchical clustering of differentially expressed mRNAs. mRNA hybridization was performed with the use of 4 × 44 K Agilent Whole Mouse Genome Oligo Microarray. For each sample pair, the experiments were done with two independent hybridizations (Cy3 and Cy5 interchanging labeling). Genes that had ≥ |2|-fold change were identified as significantly differentially expressed. Differentially regulated genes were clustered using SAS (ShanghaiBio Analysis System) to identify significant gene expression patterns in spleens (A) and brains (B) of JEV-infected mice. Red indicates higher expression and green indicates lower expression in JEV-infected mice versus control. Black indicates no expression difference. The small figure represents color scales used in the cluster map.C indicates control group and V indicates viral-inoculated group. Each group contains 3 mice.

Figure 2

Enriched Gene Ontology terms in the biological process category among differentially expressed genes. After mRNA microarray assay, significantly enriched Gene Ontology analysis in the biological process category among differentially expressed genes (fold change ≥ 2.0) in spleens (A) and brains (B) of JEV-infected mice was performed by using SAS (ShanghaiBio Analysis System). Each color section represents a different biological process and the gene number enriched in this section was shown following the biological process name.

Table 1

Significant pathways of the differential expressed genes in spleens of JEV-infected mice.

Pathway name

No. of genes

p-Value

Antigen processing and presentation

9

0

Chemokine signaling pathway

13

0

Complement and coagulation cascades

7

0

Cytokine-cytokine receptor interaction

23

0

Natural killer cell mediated cytotoxicity

9

0

Classical Complement Pathway

3

1.00E-04

Complement Pathway

3

4.00E-04

Alternative Complement Pathway

2

0.0021

Granzyme A mediated Apoptosis Pathway

2

0.0036

Toll-like receptor signaling pathway

4

0.0071

Intestinal immune network for IgA production

3

0.009

CCR3 signaling in Eosinophils

2

0.0111

Caspase Cascade in Apoptosis

2

0.0121

NOD-like receptor signaling pathway

3

0.0121

MAPK signaling pathway

6

0.0168

ECM-receptor interaction

3

0.0232

Jak-STAT signaling pathway

4

0.0284

IFN gamma signaling pathway

1

0.0478

B Lymphocyte Cell Surface Molecules

1

0.0611

T cell receptor signaling pathway

3

0.069

Table 2

Significant pathways of the differential expressed genes in brains of JEV-infected mice.

Pathway name

No. of genes

p-value

Chemokine signaling pathway

19

0

Cytokine-cytokine receptor interaction

30

0

Jak-STAT signaling pathway

19

0

MAPK signaling pathway

19

0

NOD-like receptor signaling pathway

10

0

Purine metabolism

14

0

Toll-like receptor signaling pathway

13

0

IL-2 Receptor Beta Chain in T cell Activation

5

6.00E-04

Neuroactive ligand-receptor interaction

16

6.00E-04

NF-kB activation by Nontypeable Hemophilus influenzae

4

0.0012

Apoptosis

7

0.0023

Antigen processing and presentation

7

0.0037

IFN gamma signaling pathway

2

0.0082

Natural killer cell mediated cytotoxicity

8

0.011

T cell receptor signaling pathway

7

0.0123

IFN alpha signaling pathway

2

0.0156

FAS signaling pathway (CD95)

3

0.0173

Genes with differential expression in spleens of JEV-infected mice

In spleens of mice with JEV infection, 263 genes were detected to be significantly upregulated and 174 genes were downregulated (Table 3). Genes with increased expression in spleens of JEV infected mice mainly fell into the function of immune response to viral infections. These include pro-inflammatory cytokine IFN-γ, IFN response transcription factor IRF7, IFN-induced proteins like IFIT1, IFITM3 and IFITM7, protein degradation gene ubiquitin-specific protease Usp29 and Usp18, apoptosis related genes granzymA, granzymeB, Porferin, and IMNB2, killer cell lectin-like receptors KLRC1, KLRC2 and KLRC3, and chemokines such as CXCL10, CXCL11, CCL12, CCL2 and CCL9. The marked increase in expression of these genes implies the occurrence of a strong antiviral protective response to JEV infection. The significantly downregulated genes are mainly involved in cell adhesion molecules such as monocyte/macrophage-lineage cell marker CD163, transmembrane cell surface receptor of Langerhans cells CD207, and ligand for myeloid cells receptor CD200. Evidence was also found for decreased expression of interferon transcription factor IRF6 and interleukin 7 receptor, which may contribute to JEV pathogenesis as well.
Table 3

Differentially-regulated genes of our interest in spleens of mice with JEV Infection

Genbank Accession

Gene symbol

Gene description

Fold change

p-Value

Up-regulated

    

NM_177261

Kndc1

kinase non-catalytic C-lobe domain (KIND) containing 1

21.440

0.0252

NM_019494

Cxcl11

chemokine (C-X-C motif) ligand 11

19.752

0.0084

NM_013542

Gzmb

granzyme B

6.202

0.0286

NM_031167

Il1rn

interleukin 1 receptor antagonist (Il1rn), transcript variant 1

6.060

0.0015

AK157531

LOC629091

activated spleen cDNA, RIKEN full-length enriched library, clone:F830221E13

5.500

0.0154

NM_001033228

Itga1

integrin alpha 1

5.482

0.0308

NM_013584

Lifr

leukemia inhibitory factor receptor

5.319

0.0109

NM_177923

H2-M10.2

histocompatibility 2, M region locus 10.2

5.276

0.0009

NM_008198

Cfb

complement factor B

5.188

0.0019

NM_001005858

LOC667370

similar to interferon-induced protein with tetratricopeptide repeats 3

4.949

0.0459

NM_145153

Oas1f

2'-5' oligoadenylate synthetase 1F

4.619

0.0013

NM_011331

Ccl12

chemokine (C-C motif) ligand 12

4.539

0.0308

NM_027893

Pvrl4

poliovirus receptor-related 4

4.429

0.0352

NM_010741

Ly6c

lymphocyte antigen 6 complex, locus C

4.287

0.0042

NM_010370

Gzma

granzyme A

4.236

0.0010

NM_009152

Sema3a

sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3A

4.132

0.0358

AF229257

Usp29

ubiquitin-specific processing protease 29

4.033

0.0093

NM_133871

Ifi44

interferon-induced protein 44

3.843

0.0053

NM_009912

Ccr1

chemokine (C-C motif) receptor 1

3.734

0.0013

BC025535

Fcgr1

Fc receptor, IgG, high affinity I

3.668

0.0096

NM_145226

Oas3

2'-5' oligoadenylate synthetase 3

3.531

0.0017

NM_008331

Ifit1

interferon-induced protein with tetratricopeptide repeats 1

3.433

0.0460

NM_021274

Cxcl10

chemokine (C-X-C motif) ligand 10

3.418

0.0307

NM_016850

Irf7

interferon regulatory factor 7

3.378

0.0083

NM_008530

Ly6f

lymphocyte antigen 6 complex, locus F

3.313

0.0027

NM_011940

Ifi202b

interferon activated gene 202B

3.296

0.0266

NM_145211

Oas1a

2'-5' oligoadenylate synthetase 1A

3.283

0.0082

NM_145227

Oas2

2'-5' oligoadenylate synthetase 2

3.178

0.0083

NM_144559

Fcgr4

Fc receptor, IgG, low affinity IV

3.069

0.0067

NM_027835

Ifih1

interferon induced with helicase C domain 1

2.940

0.0258

NM_008462

Klra2

killer cell lectin-like receptor, subfamily A, member 2

2.906

0.0001

NM_021792

Iigp1

interferon inducible GTPase 1

2.535

0.0232

L38281

Irg1

immune-responsive gene 1

2.496

0.0329

NM_008329

Ifi204

interferon activated gene 204

2.422

0.0290

NM_025378

Ifitm3

interferon induced transmembrane protein 3

2.401

0.0002

NM_021378

Klrc3

killer cell lectin-like receptor subfamily C, member 3

2.396

0.0063

NM_011909

Usp18

ubiquitin specific peptidase 18

2.333

0.0473

NM_011333

Ccl2

chemokine (C-C motif) ligand 2

2.314

0.0356

NM_028968

Ifitm7

interferon induced transmembrane protein 7

2.246

0.0014

NM_008337

Ifng

interferon gamma

2.229

0.0054

NM_011338

Ccl9

chemokine (C-C motif) ligand 9

2.155

0.0065

NM_010653

Klrc2

killer cell lectin-like receptor subfamily C, member 2

2.131

0.0076

NM_009909

Il8rb

interleukin 8 receptor, beta

2.077

0.0036

NM_010555

Il1r2

interleukin 1 receptor, type II

2.069

0.0248

NM_010652

Klrc1

killer cell lectin-like receptor subfamily C, member 1

2.025

0.0125

NM_011073

Prf1

perforin 1 (pore forming protein)

1.820

0.0326

NM_010722

Lmnb2

lamin B2

1.381

0.1976

Down-regulated

    

NM_025989

Gp2

glycoprotein 2 (zymogen granule membrane)

0.048

0.0005

NM_053094

Cd163

CD163 antigen

0.060

0.0171

NM_177261

Kndc1

kinase non-catalytic C-lobe domain (KIND) containing 1

0.085

0.0070

NM_144943

Cd207

CD 207 antigen

0.159

0.0441

NM_010378

H2-Aa

histocompatibility 2, class II antigen A, alpha

0.184

0.0055

NM_028135

Tmem163

transmembrane protein 163

0.211

0.0196

NM_007720

Ccr8

chemokine (C-C motif) receptor 8

0.242

0.0150

NM_016851

Irf6

interferon regulatory factor 6

0.261

0.0037

NM_013509

Eno2

enolase 2, gamma neuronal (Eno2)

0.276

0.0234

NM_011780

Adam23

a disintegrin and metallopeptidase domain 23 (Adam23)

0.281

0.0009

U96752

H2-Q1

major histocompability complex Q1b

0.282

0.0247

NM_008341

Igfbp1

insulin-like growth factor binding protein 1

0.289

0.0144

NM_010565

Inhbc

inhibin beta-C (Inhbc)

0.304

0.0307

AK089361

AK089361

B6-derived CD11 +ve dendritic cells cDNA

0.307

0.0417

NM_013517

Fcer2a

Fc receptor, IgE, low affinity II, alpha polypeptide

0.315

0.0318

NM_016808

Usp2

ubiquitin specific peptidase 2 (Usp2), transcript variant 1

0.319

0.0266

AK041838

Il7r

interleukin 7 receptor

0.319

0.0256

NM_001033126

Cd27

CD antigen 27 (Cd27), transcript variant 1

0.326

0.0158

NM_009142

Cx3cl1

chemokine (C-X3-C motif) ligand 1

0.343

0.0227

NM_010215

Il4i1

interleukin 4 induced 1

0.387

0.0129

NM_207105

H2-Ab1

histocompatibility 2, class II antigen A, beta 1

0.520

0.0255

NM_033217

Ngfr

nerve growth factor receptor (TNFR superfamily, member 16)

0.440

0.0110

AK041345

Xlr4a

X-linked lymphocyte-regulated 4A

0.460

0.0074

NM_033042

Tnfrsf25

tumor necrosis factor receptor superfamily, member 25

0.465

0.0366

NM_198297

Trat1

T cell receptor associated transmembrane adaptor 1

0.476

0.0334

NM_011161

Mapk11

mitogen-activated protein kinase 11

0.478

0.0128

NM_007549

Blk

B lymphoid kinase

0.483

0.0103

NM_010818

Cd200

Cd200 antigen

0.494

0.0156

Genes with differential expression in brains of JEV-infected mice

Compared to the expression after mock infection, 551 genes were detected to be significantly upregulated and 568 genes were downregulated in brains of JEV-infected mice (Table 4). Consistent to the results of spleen, chemokines CCL2, CCL3, CCL4 and CXCL10, IFN response transcription factor IRF7, IFN-induced proteins like Ifit1, Ifit2 and Ifit3, protein degradation gene Usp18 were obviously upregulated, and CD163 and IRF6 showed decreased expression upon JEV infection. In addition, increased expression of IFN-inducible transcription factors STAT1 and STAT2, TNF-α induced protein TNFAIP3, apoptosis-related proteins caspase3 and caspase4, suppressors of cytokine signaling Socs1 and Socs3, pro-inflammatory cytokines IL-1 and IL-6, TLR7, as well as IFN response antiviral genes of OAS family were also observed in microarray analysis. These results suggested the occurrence of a strong inflammatory response in mouse brain.
Table 4

Differentially-regulated genes of our interest in brains of mice with JEV Infection.

Genbank Accession

Gene symbol

Gene description

Fold change

p-Value

Up-regulated

    

NM_021274

Cxcl10

chemokine (C-X-C motif) ligand 10

1760.024

0.0020

NM_011333

Ccl2

chemokine (C-C motif) ligand 2

1387.794

0.0320

NM_013652

Ccl4

chemokine (C-C motif) ligand 4

336.804

0.0151

NM_010846

Mx1

myxovirus (influenza virus) resistance 1

229.188

0.0136

NM_145209

Oasl1

2'-5' oligoadenylate synthetase-like 1

209.863

0.0242

NM_011940

Ifi202b

interferon activated gene 202B

201.477

0.0317

NM_008329

Ifi204

interferon activated gene 204

165.395

0.0404

NM_021792

Iigp1

interferon inducible GTPase 1

159.817

0.0168

NM_011337

Ccl3

chemokine (C-C motif) ligand 3

111.943

0.0429

NM_008176

Cxcl1

chemokine (C-X-C motif) ligand 1

107.659

0.0158

AK085407

Ifi44

interferon gamma inducible protein 44

91.009

0.0062

NM_010555

Il1r2

interleukin 1 receptor, type II

89.273

0.0297

NM_021893

Cd274

CD274 antigen

87.250

0.0337

NM_008330

Ifi47

interferon gamma inducible protein 47

83.552

0.0286

NM_172648

Ifi205

interferon activated gene 205

82.479

0.0416

NM_194336

Mpa2l

macrophage activation 2 like

77.279

0.0464

NM_007609

Casp4

caspase 4, apoptosis-related cysteine peptidase

77.077

0.0451

NM_017466

Ccrl2

chemokine (C-C motif) receptor-like 2

74.783

0.0071

NM_008332

Ifit2

interferon-induced protein with tetratricopeptide repeats 2

65.247

0.0222

NM_011331

Ccl12

chemokine (C-C motif) ligand 12

65.192

0.0079

NM_033601

Bcl3

B-cell leukemia/lymphoma 3

53.003

0.0138

NM_029803

Ifi27

interferon, alpha-inducible protein 27

47.264

0.0403

NM_031168

Il6

interleukin 6

44.884

0.0106

NM_016850

Irf7

interferon regulatory factor 7

42.752

0.0463

NM_145211

Oas1a

2'-5' oligoadenylate synthetase 1A

41.831

0.0497

NM_011909

Usp18

ubiquitin specific peptidase 18

40.804

0.0052

NM_010501

Ifit3

interferon-induced protein with tetratricopeptide repeats 3

39.282

0.0008

NM_007707

Socs3

suppressor of cytokine signaling 3

36.912

0.0087

NM_008331

Ifit1

interferon-induced protein with tetratricopeptide repeats 1

32.115

0.0013

NM_013606

Mx2

myxovirus (influenza virus) resistance 2

31.018

0.0003

NM_011854

Oasl2

2'-5' oligoadenylate synthetase-like 2

29.655

0.0131

NM_009896

Socs1

suppressor of cytokine signaling 1

28.609

0.0492

NM_009140

Cxcl2

chemokine (C-X-C motif) ligand 2

24.678

0.0392

NM_010397

H2-T22

histocompatibility 2, T region locus 22

21.010

0.0473

NM_027835

Ifih1

interferon induced with helicase C domain 1

19.804

0.0233

NM_009397

Tnfaip3

tumor necrosis factor, alpha-induced protein 3

19.385

0.0300

NM_009283

Stat1

signal transducer and activator of transcription 1

18.134

0.0348

NM_001083925

Oas1b

2'-5' oligoadenylate synthetase 1B

17.574

0.0342

NM_008361

Il1b

interleukin 1 beta

15.753

0.0043

NM_133211

Tlr7

toll-like receptor 7

9.880

0.0343

NM_027450

Glipr2

GLI pathogenesis-related 2

9.275

0.0405

NM_008562

Mcl1

myeloid cell leukemia sequence 1

9.054

0.0336

NM_029419

Apol3

apolipoprotein L 3

8.806

0.0165

NM_001008700

Il4ra

interleukin 4 receptor, alpha

8.639

0.0360

NM_013730

Slamf1

signaling lymphocytic activation molecule family member 1

8.274

0.0435

NM_009841

Cd14

CD14 antigen

6.666

0.0034

NM_033541

Oas1c

2'-5' oligoadenylate synthetase 1C

6.596

0.0120

NM_009810

Casp3

caspase 3, apoptosis-related cysteine peptidase

2.119

0.0117

Down-regulated

    

NM_053094

Cd163

CD163 antigen

0.066

0.0007

XM_898059

Cd209f

CD209f antigen

0.088

0.0271

NM_026972

Cd209b

CD209b antigen

0.132

0.0149

NM_033042

Tnfrsf25

tumor necrosis factor receptor superfamily, member 25

0.196

0.0288

NM_016708

Npy5r

neuropeptide Y receptor Y5 (Npy5r)

0.242

0.0351

NM_019577

Ccl24

chemokine (C-C motif) ligand 24 (Ccl24)

0.302

0.0132

NM_008409

Itm2a

integral membrane protein 2A

0.302

0.0075

AK042749

D230046B21Rik

7 days neonate cerebellum cDNA, RIKEN full-length enriched library, clone:A730020N04

0.311

0.0358

NM_030143

Ddit4l

DNA-damage-inducible transcript 4-like

0.318

0.0004

NM_022723

Scube1

signal peptide, CUB domain, EGF-like 1

0.319

0.0400

AK144387

4732444A12Rik

21 days neonate cerebellum cDNA, RIKEN full-length enriched library, clone:G630051C23

0.319

0.0000

AK082652

Tmem44

transmembrane protein 44

0.324

0.0108

NM_175106

Tmem177

transmembrane protein 177 (Tmem177)

0.330

0.0346

NM_175564

Tmem169

transmembrane protein 169

0.336

0.0371

NM_027016

Tloc1

translocation protein 1

0.336

0.0276

NM_027163

Il1f8

interleukin 1 family, member 8

0.421

0.0267

NM_022986

Irak1bp1

interleukin-1 receptor-associated kinase 1 binding protein 1

0.422

0.0169

NM_016851

Irf6

interferon regulatory factor 6

0.447

0.0303

NM_145826

Il17re

interleukin 17 receptor E (Il17re), transcript variant 1

0.477

0.0403

Confirmation of microarray data by RT-qPCR

To confirm the microarray hybridization results, quantitative RT-PCR was performed on eight selected differentially expressed mRNAs in mouse spleen and brain respectively. As shown in the RT-qPCR result of spleen, granzymA, granzymeB, Porferin, IRF7, IFN-γ, CXCL10, and ILIR2 were significantly upregulated, while CD163 was downregulated (Table 5). Out of eight tested mRNAs in brains of mice infected with JEV, CCL2, CCL4, CXCL10, Casp3, Casp4, SOCS1 and SOCS3 showed increased expression, and CD163 was also found to have an obviously decreased expression (Table 5). Although absolute values are not identical due to the different sensitivity between the techniques, all genes showed a well comparative expression pattern with microarray data.
Table 5

Comparison of expression changes of some selected genes between microarray and qRT-PCR

Gene name

Gene description

Fold change

  

Microarray

qRT-PCR

Spleen

   

Cxcl10

chemokine (C-X-C motif) ligand 10

3.418

3.375 (±1.065)

Ifng

interferon gamma

2.229

3.062 (±0.507)

Gzmb

granzyme B

6.202

7.285 (±0.311)

Gzma

granzyme A

4.236

3.815 (±0.127)

Prf1

Porferin 1

1.820

2.287 (±0.643)

Irf7

interferon regulatory factor 7

3.378

4.926 (±0.309)

Il1r2

Interleukin 1 receptor, type II

2.069

2.078 (±0.105)

Cd163

CD163 antigen

0.060

0.083 (±0.017)

Brain

   

Cxcl10

chemokine (C-X-C motif) ligand 10

1760.024

13.492 (±1.690)

Ccl2

chemokine (C-C motif) ligand 2

1387.794

188.549 (±8.931)

Ccl4

chemokine (C-C motif) ligand 4

336.804

61.007 (±3.735)

Casp3

Caspase3, apoptosis-related cysteine peptidase

2.119

1.207 (±0.073)

Casp4

caspase4, apoptosis-related cysteine peptidase

77.077

19.969 (±0.050)

Socs1

suppressor of cytokine signaling 1

28.609

11.182 (±0.845)

Socs3

suppressor of cytokine signaling 3

36.912

4.672 (±0.464)

Cd163

CD163 antigen

0.066

0.065 (±0.012)

Discussion

Spleen is one of the major peripheral immunity organs and CNS is the ultimate infection target of JEV. Therefore, identification of the JEV-related host genes in spleens and brains of mice infected with JEV may be helpful for understanding of JEV pathogenesis. To this end, profiles of mRNA expression in both spleen and brain tissues of JEV-infected mice were analyzed systematically in this study.

In mRNA profiling assay, we found chemokines like CCL2 and CXCL10 were significantly up-regulated in both mouse spleen and brain in response to JEV-infection, suggesting a strong inflammatory response of host. Monocyte chemoattractant protein-1 (MCP-1/CCL2) is one of the key chemokines that regulate migration and infiltration of monocytes/macrophages. It was involved in neurological disorders such as encephalitis-related neuronal death, where its levels were elevated in astrocytes leading to neuronal death [13]. Previous study has demonstrated that the WNV-infection stimulated the expression of CCL2 in mice livers, suggesting a consistent result to our study of JEV [10]. CXCL10 is also found to play a crucial role in the host defense response against various viral infection of the CNS by enhancing innate immune responses [14, 15], and our result of up-regulated CXCL10 mRNA has a good agreement with that was reported by Gupta et al. and Biswas et al. [11, 12].

In addition, a strong IFN-pathway-related response was evident in mouse spleen and brain infected with JEV, with increased expression of IFN-γ, IFN response transcription factor IRF7, IFN-induced proteins IFIT1,IFITM3 and IFITM7 in spleen, and IRF7, IFN-inducible transcription factors STAT1 and STAT2, IFN-induced proteins IFIT1, IFIT2 and IFIT3 in brain, implying the occurrence of a protective response of host. Similar results were shown in previous reports as the upregulation of IFN-γ, STAT1 and STAT2 in JEV-infected mice brain [12], and increased expression of STAT1 and IFIT3 in JEV-infected N2A cells [11]. The reason why no increase in expression of IFN-γ was found in brains of JEV-infected mice in our study may be related to the difference of time points with Biswas' study [11]. IRF7 is activated in the presence of double stranded RNA following virus infection, which is functional as one of the regulators of the IFN-α/β gene promoter and the IFN-α/β responsive genes to create an antiviral state [16]. The increased expression of IRF7 has also been demonstrated in WNV infected mice, but wasn't found in JEV infected cells [17, 18]. This may be due to the different signal pathways between intact host and cell culture.

Pore-forming protein perforin and the family of granzymes have been demonstrated to form an antiviral arsenal central to the function of cytotoxic T lymphocyte (CTL) and natural killer (NK) cells [1921]. After JEV infection, pro-apoptotic genes found to have significant enhancement in mouse spleen, including porferin, granzyme A and granzymeB, which suggested a strong cytotoxic response against JEV infection. The consistent result as increased expression of granzyme A and B was also shown in the report about WNV infection [17]. Granzyme B is the most characterized granyzme which plays an important role in inducing apoptosis, and it is generally accepted that granzyme A can trigger a distinct nonapoptotic form of cell death [22]. The high expression of granzyme A and B in spleen could help clear virus infection, but may also involve lymphocyte injury. The upregulation of apoptosis-related proteins Caspase3 and 4 were also detected in brains of mice infected with JEV, indicating an inflammation-related neuronal apoptosis. Caspase 3 is an effector caspase that function as a central regulator of apoptosis. It has been reported that JEV infection triggers apoptosis in different cells, such as baby hamster kidney BHK-21 cells, mouse neuroblastoma N18 cells, human neuronal NT-2 cells, and human medulloblastoma cells, resulting in caspase 3 activation [2325]. The function of caspase 4 is not fully known, but it is believed to be an inflammatory caspase, with a role in the immune system [26].

Pro-inflammatory cytokines like IL-1 and IL-6 were found to have increased expression in the brain, which was consistent with the results of the studies on DV and WNV [8, 17]. IL-1α and IL-1β has been known to form an important part of the inflammatory response of the body against infection. IL-6 together with IL-1 and TNF-α acts as an endogenous pyrogen by causing fever following viral infections [27]. It's also associated with an unfavorable outcome following yellow fever virus infection [28]. Evidence suggests that circulating IL-6 can activate CNS mechanisms resulting in the development of the febrile response during disease [29]. Upregulation of IL-1 and IL-6 in brain may thus be protective against harmful JEV infection, but also have a pathogenic role in CNS.

The 2', 5'-oligoadenylate synthetase (OAS) and its downstream effector RNase L play important roles in host defense against virus infection. The OAS1b protein has been described as a flavivirus resistance factor, and OASl1 as a WNV-resistance factor in wild mice because a truncated version of the protein is expressed in laboratory mice which are susceptible to infection [3032]. Human OAS1 p42/p46 and OAS3 p100 are likely to contribute to host defense against DEN infection and play a role in determining the outcomes of DEN disease severity [33]. Further, the activated expression of OAS2 has been demonstrated in mouse brain in response to JEV infection [34]. In present study, there was increased expression of various members of the OAS family in the brains of JEV-infected mice, including OAS1a, OAS1b, OAS1c, OAS1e, and OAS2. Therefore, the ability of these proteins to protect against JEV infection should also be further studied.

The significant downregulation of CD163 was detected both in mouse spleen and brain in response to JEV infection. CD163 is a novo identified marker for perivascular macrophages in humans, monkeys, and mice. And previously studies have found that perivascular CD163 expression is upregulated and the number of CD163-positive cells increases in HIV and SIV encephalitis (HIVE and SIVE) brains [35, 36]. However, CD163 is not a "classical" activation marker, because peripheral blood monocytes and most tissues macrophages of normal uninfected controls all express it and because in vitro pro-inflammatory stimuli largely down-regulate its expression. These findings suggest that CD163 expression is regulated in association with a certain stage of differentiation. Here, our results showed a downregulated CD163 mRNA level in response to acute JEV infection, which probably suggested a decreased number of activated perivascular macrophages resulted by inflammatory disorder-related apoptosis response.

Conclusions

In summary, our findings suggested that JEV infection resulted in significant changes in the expression of multiple genes in mouse spleen and brain, including inflammatory cytokines, chemokines, IFN inducible genes, IFN regulators, and apoptosis related genes, etc. These genes may play a critical role on antiviral response of host against JEV infection but could also contribute to the pathogenesis of JEV resulting in encephalitis. The mRNA profile obtained by microarray analysis in this study may provide a foundation for future investigation of JEV pathogenesis and therapeutic method.

Methods

Virus production

JEV wide type strain P3 was propagated in brains of suckling mice and titered in BHK-21 cells which was grown and maintained in Dulbecco's Modified Eagle's Medium (DMEM) supplemented with 10% heated-inactivated fetal bovine serum (FBS, Hyclone, Logan, UT, USA), 100 g/ml streptomycin and 100 IU/ml penicillin (Sigma-Aldrich, MO, USA) at 37°C with 5% CO2.

Virus infection of mice

Four-weeks-old naive female BALB/c mice were purchased from Wuhan Institute of Biologic Products (Hubei Province, China) and inoculated subcutaneously (s.c.) with 5 × 106 PFU of JEV P3 strain. Dilutions were performed in serum-free DMED and experimental controls were mock injected with diluent. A part of JEV-infected mice were sacrificed at day 3 post-inoculation (the day before the neurological symptoms appeared), and spleens were harvested. The left mice were sacrificed at day 6 post-inoculation (the day before the mice started to die), and brains of mice were harvested. Spleen and brain homogenate was made in DMEM for RNA extraction.

Microarrays and bioinformatics

The total RNA was isolated from mouse spleens and brains respectively with trizol reagent (Invitrogen) for mRNA Microarray. mRNA hybridization was performed by shanghaiBio Corporation (shanghai, China) with the use of 4 × 44 K Agilent Whole Mouse Genome Oligo Microarray (total 41,174 oligo probes from 41,174 mouse genes). For each sample pair, the experiments were done with two independent hybridizations (Cy3 and Cy5 interchanging labeling). Hybridized arrays were scanned at 5 μm resolution on an Agilent DNA Microarray Scanner (Model G2565BA). Data extraction from images was done by using Agilent Feature Extraction software. Hierarchical cluster, gene ontology and pathway analysis were analyzed by using SAS (ShanghaiBio Analysis System).

Quantitative real-time RT-PCR (RT-qPCR)

For selected mRNA RT-qPCR, total RNA from the same samples used in microarray analysis was tested by using ABI 7500 FAST real-time PCR system. PCR primers were designed with Primer Express 2.0 software (Invitrogen). Results are shown as fold change. For mRNA RT-qPCR, experiments were carried out with the PrimerScript RT reagent Kit (TaKaRa) and SYBR Green Realtim PCR Master Mix (TaKaRa) according to manufacture's instruction. The housekeeping gene GHDAP was used for standardization of the initial RNA content of a sample. Relative changes of gene expression were calculated by the following formula, and the data are represented as fold upregulation/downregulation. fold change = 2-ΔΔCt, whereΔΔCt =(Ct of gene of interest, treated -Ct of HK gene, treated)-(Ct of gene of interest, control-Ct of HK gene, control), Ct is the threshold cycle number and HK is the house keeping gene.

Statistical analysis

Each gene in each infection group was subjected to a Student's t test to detect large expression differences relative to the mock-infected group. p-values <0.05 were considered to be statistically significant.

Notes

Declarations

Acknowledgements

This work was supported by the 973 Project of China (No. 2010CB530100), Transregional Collaborative Research Centre TRR 60 and PCSIRT (IRT0726).

Authors’ Affiliations

(1)
State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Hubei
(2)
Laboratory of Animal Virology, College of Veterinary Medicine, Huazhong Agricultural University, Hubei

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© Yang et al; licensee BioMed Central Ltd. 2011

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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