Open Access

Response of swine spleen to Streptococcus suis infection revealed by transcription analysis

  • Ran Li1, 2,
  • Anding Zhang1, 2,
  • Bo Chen2,
  • Liu Teng2,
  • Ya Wang2,
  • Huanchun Chen1, 2 and
  • Meilin Jin1, 2Email author
Contributed equally
BMC Genomics201011:556

DOI: 10.1186/1471-2164-11-556

Received: 4 May 2010

Accepted: 11 October 2010

Published: 11 October 2010

Astract

Background

Streptococcus suis serotype 2 (SS2), a major swine pathogen and an emerging zoonotic agent, has greatly challenged global public health. Systematical information about host immune response to the infection is important for understanding the molecular mechanism of diseases.

Results

104 and 129 unique genes were significantly up-regulated and down-regulated in the spleens of pigs infected with SS2 (WT). The up-regulated genes were principally related to immune response, such as genes involved in inflammatory response; acute-phase/immune response; cell adhesion and response to stress. The down-regulated genes were mainly involved in transcription, transport, material and energy metabolism which were representative of the reduced vital activity of SS2-influenced cells. Only a few genes showed significantly differential expression when comparing avirulent isogenic strain (ΔHP0197) with mock-infected samples.

Conclusions

Our findings indicated that highly pathogenic SS2 could persistently induce cytokines mainly by Toll-like receptor 2 (TLR2) pathway, and the phagocytosis-resistant bacteria could induce high level of cytokines and secrete toxins to destroy deep tissues, and cause meningitis, septicaemia, pneumonia, endocarditis, and arthritis.

Background

Streptococcus suis (S. suis) is an important pathogen associated with many diseases in pigs, including meningitis, septicaemia, pneumonia, endocarditis, and arthritis. S. suis serotype 2 (SS2) is considered the most pathogenic as well as the most prevalent capsular type among thirty-three serotypes (types 1 to 31, 33, and 1/2) in diseased pigs, and it is also the causative agent of serious infections in humans, especially in people in close contact with pig or pork byproducts [13]. Two recent large-scale outbreaks of human SS2 epidemics in China (one had 25 cases with 14 deaths in Jiangsu in 1998, the second had 204 cases with 38 deaths in Sichuan in 2005), featured clinical streptococcal toxic shock syndrome, have greatly challenged the global public health [47]. Recently, S. suis infection has also caused sporadic human illness in other countries, including Thailand [8, 9], United Kingdom [10], Portugal [11], Australia [12], Netherlands [13] and United States [14, 15], and been recognized as the third most common cause of community acquired bacterial meningitis in Hong Kong and as the leading cause of adult meningitis in Vietnam [5, 16].

The past pathogenesis studies were performed mainly on the pathogenic bacteria and as a result, a few virulence-associated factors have been successfully identified. Polysaccharide capsule has been considered essential for the virulence of the bacterium [17, 18], and other factors, such as suilysin, the so-called extracellular protein factor and muramidase-released protein have been shown to be linked to, but not essential for the full virulence of S. suis[19]. GapdH[20], Enolase[21, 22], FbpS[19], Adhesin [2327] have been proved to be involved in the adherence and virulence of S. suis. Recently, serum opacity-like factor [28], IgA1 protease[29], D-Alanylation of Lipoteichoic Acid [30] and pgdA [31] were identified as important factors in S. suis virulence. In addition, SalK/SalR [32] and CovR [33] were found to affect the virulence of S. suis Chinese isolates. These studies have contributed to the understanding of S. suis pathogenesis and also suggested that host responses also play essential roles in the development of the diseases.

Inducing excessive inflammation is recognized as one of the reasons why highly invasive SS2 strain could cause severe diseases [31, 34]. A few previous studies indicated that high level of cytokines and chemokines could be released by human brain microvascular endothelial cells [35], a whole-blood culture system [36], macrophages [37] and monocytes [38] stimulated by SS2, and have important roles in the initiation and development of inflammation and meningitis [39]. More direct proofs were the studies on mice with different genetic background, which indicated that IL-10 was responsible, at least in part, for the high survival, which suggested that aberrant innate immune response contributed to SS2 diseases [40].

To be aware of the information about host immune response would enable people to better understand the disease. Transcriptional response of alveolar macrophages to SS2 has been performed and the results indicated that NF-kB and MAP-kinases signaling pathways were induced upon interaction with SS2 [41]. However, it is not easy to get more information since the primary macrophages are so sensitive to the interference. Spleen plays an important role in immune response and could be an ideal target to study host immune response against infection [42, 43]. In the present study, the gene expression profiles of swine spleens which suffered from highly pathogenic SS2, avirulent isogenic strain and PBS respectively were investigated to reveal the host immune response to SS2 and the contributions of host response to SS2 diseases.

Results

Transcriptome analysis

The transcriptome analysis indicated that 14,992, 15,487 and 15,757 probe sets, corresponding to 62.1%, 64.2% and 65.3% of all probe sets, were detected in WT, ΔHP0197 and mock-infected pig spleens respectively (Additional file 1). The expression profiles of porcine spleens challenged with WT 3 days post inoculation were compared with those of the mock-infected group. After quantile normalization and statistical analysis, 1014 transcripts were identified at the global false discovery rate (FDR) of 10% (Additional file 2). Furthermore, the criteria of a two-fold or greater change in differential expression and a FDR of 10% were chosen to determine up-regulated and down-regulated genes in the WT infected replicates. Using these criteria, 120 and 132 transcripts, representing 104 and 129 unique genes, were significantly up-regulated and down-regulated respectively (Additional file 3). However, only a few genes showed significantly differential expressions when comparing ΔHP0197 with mock-infected samples (Figure 1A).
https://static-content.springer.com/image/art%3A10.1186%2F1471-2164-11-556/MediaObjects/12864_2010_Article_3253_Fig1_HTML.jpg
Figure 1

Clustering and characterization of the differential expression of genes. (A) 233 genes were selected for cluster analysis which is described in methods. Each row represents a separate transcript and each column represents a separate piglet. Color legend is on the left, the color scale ranges from saturated green for log ratios -3.0 and above to saturate red for log ratios 3.0 and above. Red indicates increased transcript expression levels, green indicates decreased levels compared with normal samples. (B) Percentage distribution of unique genes was from 233 differentially regulated transcripts after BLASTX searches and annotation. 158 unique genes had significant similarities based on BLASTX searches. 135(126+9) unique genes had been annotated by Biological Process (BP) Classification. (C) Categories of annotated genes genes based on biological process GO term. Many categories shared the same transcripts.

Of the 233 unique DE transcripts, 158 transcripts could be determined based on BLASTX searches and annotated with DAVID or by searching against the GenBank database (Figure 1B). Among these, 135 unique genes were grouped into 39 categories based on biological process Gene Ontology (GO) terms or according to their potential Biology Process Classification by referring to recent publications (Figure 1C). Unsurprisingly, the majority of genes were related to the immune response, Transcription, Transport, material and energy metabolism, etc. (Table 1).
Table 1

Different expression of genes in spleens after S. suis infection 3 days

Function classification

ENTREZ GENE_ID

Description

Fold change

Q-value (%)

Inflammatory response

    
 

929

CD14 Antigen

3.4

1.222

 

6279

S100 Calcium binding protein A8

19.3

1.508

 

6280

S100 Calcium binding protein A9

16.1

0

 

3588

Interleukin 10 receptor, beta

2.7

3.911

 

5743

Prostaglandin-Endoperoxide synthase 2

4.7

7.146

 

7057

Thrombospondin 1

2.4

6.387

 

3576

Interleukin 8

5.6

6.387

 

9547

Chemokine (C-X-C Motif) Ligand 14

2.0

8.898

 

6283

S100 Calcium binding protein A12

18.6

0

 

2908

Nuclear receptor subfamily 3, group C, member 1

0.5

6.882

 

6363

Chemokine (C-C Motif) Ligand 19

2.2

1.508

 

7097

Toll-like receptor 2

2.0

6.387

 

2920

Chemokine (C-X-C Motif) Ligand 2

7.3

3.385

 

246

Arachidonate 15-Lipoxygenase

0.2

2.181

 

7052

Transglutaminase 2

2.1

6.387

 

9332

CD163 antigen

11.7

0

 

6288

Serum amyloid A1

6.4

1.222

 

3553

Interleukin 1, beta

16.7

6.387

 

3569

Interleukin 6 (Interferon, Beta 2)

4.8

6.387

 

56729

Resistin

3.7

7.146

Response to stress

    
 

1153

Cold inducible rna binding protein

0.43

5.612

 

3320

Heat shock protein 90Kda alpha class A member 1

3.2

8.898

 

6916

Thromboxane A synthase 1

2.6

3.911

 

10963

Stress-induced-phosphoprotein 1

2.5

0

 

130872

AHA1, activator of heat shock 90Kda protein ATPase homolog 2

2.6

1.508

 

3337

Dnaj (Hsp40) homolog, subfamily B, member 1

2.8

1.222

 

871

Serpin peptidase inhibitor, clade H (Heat Shock Protein 47), member 1

2.7

1.222

 

10808

Heat shock 105Kda/110Kda protein 1

3.3

0

 

3301

Dnaj (Hsp40) homolog, subfamily A, member 1

2.4

0

 

3304

Heat Shock 70Kda Protein 1A

11.1

0

Coagulation

    
 

5328

Plasminogen activator, urokinase

2.0

6.387

 

2162

Coagulationfactor XIII, A1 polypeptide

6.8

3.385

Signal transduction

    
 

9465

A kinase anchor protein 7

0.5

6.698

 

8519

Interferon induced transmembrane protein 1

2.0

6.387

 

115265

Dna-damage-inducible transcript 4-like

0.3

2.181

 

9770

Ras association (Ralgds/Af-6) domain family 2

2.4

6.387

 

9510

Adamm etallopeptidase with thrombospondin type 1 motif, 1

2.3

0

 

1363

Carboxypeptidase E

0.44

6.698

 

54210

Triggering receptor expressed on myeloid cells 1

3.2

6.387

 

9289

G protein-coupled receptor 56

0.46

6.698

 

7043

Transforming growth factor, beta 3

2.1

4.116

Transcription

    
 

2353

V-Fos fbj murine osteosarcoma viral oncogene homolog

2.8

3.911

 

84969

Chromosome 20 open reading frame 100

0.3

2.541

 

55885

Lim domain only 3

0.3

2.181

 

3726

Jun B proto-oncogene

2.6

7.146

 

91

Activin a receptor, type ib

3.4

1.222

 

116448

Oligodendrocyte transcription factor 1

2.4

6.387

 

79365

Basic helix-loop-helix domain containing, class B, 3

0.4

2.181

 

64919

B-cell cll/lymphoma 11B

0.5

2.181

 

23635

Single-stranded dna binding protein 2

0.4

2.541

 

23414

Zinc finger protein, multitype 2

0.5

6.698

 

7552

Zinc finger protein 6 (Cmpx1)

0.5

3.385

 

6920

Transcription elongation factor A (SII), 3

2.2

6.387

 

4783

Nuclear factor, interleukin 3 regulated

2.4

3.911

 

1052

CCAAT/Enhancer binding protein (C/EBP), delta

3.1

0

Cell adhesion

    
 

6401

Selectin E

3.5

1.222

 

8174

Mucosal vascular addressin cell adhesion molecule 1

2.3

6.387

 

5067

Contactin 3

0.5

6.794

 

4867

Nephronophthisis 1 (Juvenile)

0.4

3.911

 

1462

Chondroitin sulfate proteoglycan 2 (Versican)

9.1

0

 

960

CD44 antigen

2.3

2.541

Ubiquitin cycle

    
 

115123

Membrane-associated ring finger (C3HC4) 3

4.4

1.222

 

7317

Ubiquitin-activating enzyme E1

0.4

2.181

 

11274

Ubiquitin specific peptidase 18

0.4

6.698

 

9666

Zinc finger daz interacting protein 3

0.5

6.882

Transport

    
 

6556

Solute carrier family 11, member 1

4.0

2.051

 

4057

Lactotransferrin

5.9

3.385

 

1356

Ceruloplasmin (Ferroxidase)

2.3

2.541

 

1410

Crystallin, alpha B

2.8

6.387

 

283652

Solute carrier family 24, member 5

0.4

2.181

 

54843

Synaptotagmin-like 2

0.4

6.698

 

6947

Haptocorrin

8.9

0

 

3949

Low density lipoprotein receptor

2.1

5.612

 

3043

Hemoglobin, beta

0.4

6.698

 

3042

Hemoglobin, alpha pseudogene 2

0.2

2.181

 

3040

Hemoglobin, alpha 1

0.2

2.181

 

2554

Gamma-aminobutyric acid (Gaba) a receptor, alpha 1

0.3

3.911

 

2288

Fk506 binding protein 4, 59Kda

2.2

1.222

 

6557

Solute carrier family 12, member 1

0.4

6.882

 

152789

Janus kinase and microtubule interacting protein 1

0.5

6.794

Nucleic acid metabolic process

    
 

401251

Muts homolog 5

0.5

6.698

 

56952

Phosphoribosyl transferase domain

0.4

2.181

 

51251

5'-Nucleotidase, cytosolic Iii

0.4

6.698

 

10492

Synaptotagmin binding, cytoplasmic rna interacting protein

0.4

4.116

 

8347

Histone 1,H2bd

2.6

6.387

 

8334

Histone 1, H2ac

5.6

1.222

 

6430

Splicing factor, arginine/serine-rich 5

0.5

0

 

4302

Myeloid/Lymphoid or mixed-lineage leukemia translocated to, 6

0.4

6.882

Response to stimulus

    
 

5806

Pentraxin-related gene, rapidly

induced by il-1 beta

14.1

1.222

 

6372

Chemokine (C-X-C motif) ligand 6

5.5

1.222

 

64135

Interferon induced with helicase c domain 1

0.4

6.698

 

3240

Haptoglobin

4.6

0

 

6648

Superoxide dismutase 2, mitochondrial

4.6

1.508

 

1843

Dual specificity phosphatase 1

2.1

6.387

Cell differentiation/development

    
 

58189

Wap four-disulfide core domain 1

2.1

1.222

 

9531

Bcl2-associated athanogene 3

3.7

0

 

51454

Gulp, engulfment adaptor ptb domain containing1

0.4

2.181

 

212

Aminolevulinate, delta-, synthase 2

0.4

6.698

 

2012

Epithelial membrane protein 1

2.0

7.146

 

79689

Steap family member 4

2.8

3.911

 

9021

Suppressor of cytokine signaling 3

2.4

3.385

 

5270

Serpin peptidase inhibitor, clade E, member 2

2.3

3.385

 

1946

Ephrin-A5

0.4

3.911

 

85444

Leucine rich repeat and coiled-coil domain containing 1

0.5

5.612

 

54873

Palmdelphin

0.4

5.612

 

10439

Olfactomedin 1

3.3

6.387

Carbohydrate metabolic process

    
 

4199

Malic enzyme 1, NADP(+)-dependent, cytosolic

0.4

3.911

 

80760

Inter-alpha (Globulin) inhibitor H5

0.3

6.698

 

152831

Klotho beta

2.5

0

 

3101

Hexokinase 3 (White Cell)

2.9

6.387

 

3099

Hexokinase 2

2.3

8.898

 

1116

Chitinase 3-like 1

2.9

8.898

Protein metabolic process

    
 

85464

Slingshot homolog 2

2.3

1.508

 

51327

Erythroid associated factor

0.06

0

 

7076

Timp metallopeptidase inhibitor 1

4.4

1.222

 

7053

Transglutaminase 3

6.1

1.222

 

114907

F-box protein 32

0.4

6.794

 

64844

Membrane-associated ring finger (C3HC4) 7

0.5

2.181

 

64172

O-sialoglycoprotein endopeptidase-like 1

0.4

2.181

 

55466

Dnaj (Hsp40) homolog, subfamily A, member 4

2.7

2.541

 

51056

Leucine aminopeptidase 3

2.0

8.898

 

2289

Fk506 binding protein 5

2.5

6.387

 

26235

F-box and leucine-rich repeat protein 4

0.5

6.698

Nitrogen compound metabolic process

    
 

383

Arginase

0.2

2.181

 

64850

Alanine-glyoxylate aminotransferase 2-like 1

0.2

6.882

 

6799

Sulfotransferase family, cytosolic, 1A, phenol-preferring, member 2

2.0

6.387

 

8974

Procollagen-proline, 2-oxoglutarate 4-dioxygenase, alpha polypeptide ii

3.2

6.387

Others

    
 

129446

Cardiomyopathy associated 3

0.3

2.181

 

128218

Transmembrane protein 125

2.0

8.898

 

57763

Ankyrin repeat, family A, 2

0.4

2.181

 

29970

Schwannomin interacting protein 1

0.5

6.794

 

23336

Desmuslin

0.5

6.882

 

590

Butyrylcholinesterase

0.5

4.116

 

84649

Diacylglycerol o-acyltransferase homolog 2

3.2

1.222

 

79887

Hypothetical protein Flj22662

3.5

6.387

DE genes which putative functions assigned based on GO term and manual annotation. Manual annotations were listed in italics. Many genes with multiple functions were only listed in one category according to specific biology processes. "FC≥2" represents up regulation (infection/control), "FC ≤ 0.5" represents down regulation.

Validation of microarray data by quantitative real-time PCR (qPCR)

The qPCR was performed to validate the expression patterns during infection for specific genes identified in the microarray assay. In order to validate the differential expression of various identified genes, 16 up-regulated genes, with the increase ranging from 2.0-fold to 18.6-fold, and 3 down-regulated genes, with the decrease ranging from 2.5-fold to 5.9-fold, were selected for qPCR analysis. All the selected down-regulated genes could be amplified from the control samples but failed to achieve significant detectable signs from WT-infected spleens, except for ALOX15 which showed 3.2-fold down-regulated expression. All selected up-regulated genes showed higher expression in WT-infected samples than in the control samples (Table 2). Though variation in fold changes could be observed between qPCR and microarray (Table 2), the differential expression patterns were coincident between the results of the two techniques, which indicated the reliability of the microarray analysis.
Table 2

Validation of microarray results by qPCR

Gene

Accession

Microarray fold

change

qPCR fold change

(p-value)

IL1B

CK468468

16.7

258.3 (0.0117)

S100A9

BI402402

16.1

137.2(0.0007)

S100A12

CB475695

18.6

76.7 (< 0.0001)

HSP90

CF180819

3.18

48.5 (0.0321)

IL8

NM_213867

5.58

35.5 (0.0066)

HSP70

NM_213766

11.06

31.4 (0.0099)

TIMP1

NM_213857

4.4

14.6 (0.0023)

IL6

AF493992

4.8

10.5 (0.0074)

SOD2

NM_214127

4.6

10.0 (< 0.0001)

NRAMP1

U55068

3.97

7.2 (0.0035)

SELE

NM_214268

3.5

5.9 (0.0002)

PLAU

NM_213945

2.0

5.5 (0.0415)

CCL19

BX672579

2.16

4.2 (0.0004)

haptocorrin

CB472702

3.78

2.1(0.0388)

TLR-2

NM_213761

2.0

2.1 (< 0.0001)

ALOX15

NM_213931

0.2

0.3 (0.038)

Induction of inflammasomes and acute phase proteins by SS2 infection

Highly pathogenic SS2 infection could cause up-regulated expression of a large set of genes involved in the inflammatory response and acute phase proteins by microarray analysis. IL-1B, IL-6 and IL-8 could be induced by foreign pathogens and play essential roles in controlling infections [5, 44]. However, they may also cause pathology when these productions are excessive or uncontrolled [45]. Ye et al. also found that significantly high level of cytokines could be induced by highly pathogenic SS2 strain and play important roles in sepsis [34], which is in coincidence with ours. In addition, quite a few genes related to inflammatory response were found up-regulated, such as S100 family proteins (S100A8, S100A9 and S100A12) [46], Pentraxin 3 [47] and Resistin [48, 49]. They play important roles in mediating inflammatory responses, recruiting inflammatory cells to sites of tissue damage or contributing to resisting the invasion of various pathogens.

Acute phase proteins (APPs), such as Lactotransferrin [50], Haptoglobin [51], Serum amyloid A 2 [52] and coagulation factor XIII, were involved in physiologic reactions initiated early in the inflammatory process [53], and could be a response to S. suis infection [54]. CEBPD belonging to the CCAAT-enhancer binding protein (CEBP) family which is crucial in the regulation of genes involved in immunity and inflammation. These up-regulated genes are the representative of host acute response struggling to eliminate invading pathogens.

Induction of genes related in cell adhesion and stress response

Cell adhesion molecules (CAMs) have been implicated in the regulation of a wide variety of fundamental cellular processes, such as cell adhesion, cell polarization, survival, movement, and proliferation [55]. E-selectin is a cell adhesion molecule expressed on endothelial cells activated by cytokines, and plays an important role in recruiting leukocytes to the site of injury [56]. Versican can bind adhesion molecules on the surface of inflammatory leukocytes [57] and act as a TLR2 agonist in inducing the release of proinflammatory cytokines [58]. Thrombospondin 1 is an adhesive glycoprotein that mediates cell-to-cell and cell-to-matrix interactions and it could interact with numerous proteases involved in angiogenesis [59]. Mucosal vascular addressin cell adhesion molecule 1 is predominantly expressed on high endothelial venules in inflamed tissues, and could assist the extravasations of leucocyte [60]. The up-regulation of cell adhesion molecules after SS2 infection would contribute to recruiting leukocytes to the site of infection, which could control infection.

Genes related to oxidative stress and homeostasis were also identified to be up-regulated. SOD2 provides vital protection against reactive oxygen species (ROS), thus protecting tissues from damage in a broad range of disease states. The secretion of PGE2, together with nitric oxide production, is involved in disruption of the blood-brain barrier(BBB) in an experimental model of bacterial meningitis [61]. S. suis-mediated PGE2 production by human macrophages was also noticed by Jobin and contributed to the BBB disruption [62].

Toll-like receptors (TLRs) pathway analysis

Activation of the innate immune response is controlled in large part by the Toll-like receptor (TLR) family of pattern-recognition receptors. The previous study showed that S. suis was mainly recognized via TLR2 by THP-1 monocytes, which was associated with CD14 [38] and led to the release of pro-inflammatory mediators [63]. The strong activation of TLR2 and CD14 was also observed in murine brain parenchyma after the presence of S. suis bacteremia [39]. A recent research indicated that components released during S. suis infection as well as penicillin-treated whole bacteria could induce NF-kB activation through TLR2/6 [64]. The obvious elevation of TLR2 (2.0 fold) and CD14 (3.4 fold) was noticed at transcript level in spleens after highly pathogenic SS2 infection. Unsurprisingly, MyD88, an adaptor molecule in downstream signaling events with TLRs and CD14, was up-regulated at the level of 1.5 fold (q < 10%). In contrast, the effect could not be seen with avirulent SS2 infection.

Down-regulated transcripts following S. suis infection

The majority of down-regulated genes were related to transcription, transport, material and energy metabolism (Table 1). Highly pathogenic strain could show high level of toxicity to host cells [34], and as a result, the influenced cells could hardly to be active. So these down regulations could be regarded the representative of the reduced vital activity of SS2-influenced cells.

Discussion

Two recent SS2 outbreaks in China not only seriously challenged public health but also shocked the scientific community, calling for the basic and translational studies of S. suis. Until now, several proteins were identified as vaccine candidates [65, 66] and drug targets [67, 68] for controlling SS2. In addition, emphasis is also extended to the pathogenesis study. Several pathogenic factors were successfully identified and strengthened the understanding for the virulence of the bacterium. As infectious disease resulted from the interplay between pathogens and the defense of the hosts they infect, host immune response was especially essential for understanding the diseases [41, 69].

In the present study, we tried to compare the gene expression profiles of spleens from swine suffering from highly pathogenic SS2, from swine infected with the avirulent isogenic strain, and from swine inoculated with PBS respectively to reveal the host immune response to SS2 and the contributions of host response to SS2 diseases. It is not accidental that significant changes of gene expression profiles could be noticed when infected with highly pathogenic SS2 compared with mock-infected samples, while avirulent isogenic strain would cause similar profiles to mock-infected samples (Figure 1A). These indicated that avirulent isogenic strain could hardly cause significant gene expression which was coincident with the fact that no significant clinical symptoms could be noticed in pigs. Moreover, the obvious changes in gene expression profiles were highly associated with significant clinical signs on day 3 post-inoculation with highly pathogenic strain. Further analysis of the present study indicated that the majority of down-regulated genes were mainly involved in transcription, transport, material and energy metabolism which were representative of the reduced vital activity of SS2-influenced cells. However, the up-regulated genes were principally related to immune response, such as genes involved in inflammatory response; acute-phase/immune response; cell adhesion and response to stress. Undoubtedly, it would be meaningful to explore the roles of these genes in SS2-caused diseases.

First of all, it is necessary to know how SS2 induces immune response. It is well acknowledged that TLRs are transmembrane proteins that could recognize specific PAMPs and eventually result in the activation of NF-kB and MAP kinases to elicit regulatory response [70]. Among these transmembrane proteins, TLR-2 could recognize bacterial LAM, BLP and PGN by following their initial interaction with CD14. Previous reports indicated that S. suis mainly induced proinflammatory cytokines by TLR2 of human macrophages and murine brain [39, 63], and several proinflammatory cytokines, such as IL-1B, IL-6, IL-8, TNF-a and MCP-1 could be triggered [35, 36, 38, 41]. In our study, large doses of bacteria could be isolated from spleens of WT-infected pigs while no bacterium could be found to exist in pigs infected with ΔHP0197. In coincidence with these, TLR-2 pathway and several proinflammatory cytokines were induced only in WT-infected pigs. ΔHP0197 showed similar transcript profile as control pigs due to either failing to invading or being easily eliminated by host. In contrast, the large doses of bacteria effected maximal cytokines release in WT-infected pigs [37]. The exaggerated high levels of cytokines perhaps exacerbate the inflammation and were considered to be responsible for S. suis caused diseases [39]. So the successful lethal pathogens could persistently induce cytokines secreted originally to clear the foreign invader, and as a result, the host's defense was utilized by S. suis to cause diseases, and to some extent to death.

As we all know that the secreted cytokine is an important part of a host defense system, which could recruit inflammatory cells to sites of tissue damage and help to eliminate the pathogens. However, this innate defense system is a double edged sword. If the recruiting inflammatory cells could kill the invader, the disease could be controlled. On the opposite side, if the recruiting phagocytes could not efficiently kill the bacteria, the tide would be turned to pathogen's favor, and the persistently induced cytokines would result in the exacerbated inflammation and lead to the death during the septic phase of infection. These might be the reason why the survival rate could be elevated when inflammation was inhibited by IL-10 [40], and why the level of cytokine was correlated inversely with survival time in patients with sepsis [45]. In coincidence with our analysis, pathogenic S. suis could effectively resist the uptake by phagocytes and CPS could inhibit activation of signaling pathways involved in phagocytosis [17, 71, 72]. In addition, several virulence-associated proteins such as FBPS[19], PDGA[31], LTA[30], HP0197 (unpublished data), serine protease [73] etc. were also contributed to the phagocytosis resistance, and the up-regulation of these proteins in vivo may suggest the better phagocytosis resistance [31, 74, 75]. Due to failing phagocytosis, bacteria could not only cause exacerbated inflammation but also contribute to its survival in the bloodstream in "modified Trojan Horse" theory in which bacteria travel extracellularly while attached to, but not phagocytosed [17, 72], and then cause bacteremia and even septemia.

One of the key questions to be answered is how S. suis crosses the blood-brain barrier to cause meningitis, which was observed in all WT-infected pigs. The findings of the reported study presented that suilysin-positive strain could show toxin to produce functional alteration and increase the permeability of BBB; and Suilysin-negative strain might stimulate the production of proinflammatory cytokines resulting in alteration of BBB permeability [76, 77]. And they also indicated that this highly pathogenic strain could produce high level of toxins in vivo-Suilysin, MRP, hyl [74], and undoubtedly it would contribute to the penetration of deep tissue and BBB. In addition, the stimulated production of proinflammatory cytokines would result in the alteration of BBB permeability, and it would be more feasible for S. suis to break through BBB. From our understanding, WT strain could utilize the synergic effect of toxins and high level of cytokines to accelerate the penetration of deep tissue and BBB. These might be the reason why the strain could cause severe human diseases in Sichuan, 2005.

Conclusions

Microarray technology has been used to analyse the globle porcine transcriptional response to infection with various pathogenic microorganisms recently. Study on the transcriptional response to the Gram-positive bacterium SS2 by using the Affymetrix GeneChip Porcine Genome Array has not been reported until now. Although great efforts have been made to understand the molecular basis of this infection, the response to SS2 infection is still largely unknown. Transcriptome analysis based on S. suis-infected spleens could improved the interference received by the cells analysis, and also supply the solid supplementary for analysis on alveolar macrophages. Highly pathogenic S. suis could persistently induce cytokines mainly by TLR2 pathway, and eventually the high level of cytokines and toxins secreted by phagocytosis-resistant bacteria could destroy deep tissues, and cause meningitis, septicaemia, pneumonia, endocarditis, and arthritis.

Methods

Bacterial strains

SS2 strain 05ZY (WT) which was isolated from the brain of a diseased piglet collected in Sichuan outbreak in China 2005 showed high virulence to pigs [4, 78], and was applied to infect pigs. An isogenic HP0197 mutant (ΔHP0197) derived strain 05ZY showed no obvious virulence to pigs (unpublished data) was applied as a control.

Animals infection and tissue collection

All the experimental protocols were approved by the Laboratory Animal Monitoring Committee of Hubei Province and performed accordingly. A total of 12 pigs of high-health status (ages 4-5 weeks) were assigned to three groups, within four in each. The pigs were determined to be SS2-free by antibody-based ELISA and nasal swabs-based bacteriologic test. One hour before inoculation, all pigs were given 2 ml of 1% acetic acid (pH 2.9) intranasally to enhance the sensitivity of the S. suis challenge. Two groups were inoculated intranasally with 1 ml of 2×106CFU of WT strain or ΔHP0197 respectively, and the rest group inoculated with PBS was served as control. All pigs inoculated with WT showed typical symptoms at day 3 while pigs inoculated with ΔHP0197 or PBS showed no significant clinical signs. Blood samples from each group were detected for bacterial burden. Bacteria could be found in the blood of pigs in the WT group at day 3 post-inoculation while no bacterium was found from the blood of pigs inoculated with isogenic mutant strain or PBS at the same time point. All pigs were sacrificed at day 3, and their tissue samples were cultured to prove in vivo bacterial burden. Bacteria were found in the spleens of the WT group, and no bacterium was found in the other two groups. Spleen samples were aseptically collected and immediately frozen in liquid nitrogen for future RNA isolation. Total RNA was isolated from approximately 200 mg of each sample by using the TRIzol (Invitrogen) and RNeasy Midi kit (QIAGEN) based on the manufacturer's protocols. The integrity, quality, and quantity of RNA were assessed using the Agilent Bioanalyser 2100.

Microarray hybridizations and data analysis

The RNA labelling and hybridization were conducted by a commercial Affymetrix array service (CapitalBio Corp. Beijing, China). An aliquot of 2 μg of total RNA was converted to double-stranded cDNA with the one-cycle cDNA Synthesis Kit (Affymetrix), and then biotin-tagged cRNA was produced with MessageAmp™ II aRNA Amplification Kit. The resulting bio-tagged cRNA was fragmented to strands of 35 to 200 bases in length according to Affymetrix's protocols and then it was hybridized to GeneChip Porcine Genome Array. Hybridization was performed at 45°C with rotation for 16 h (Affymetrix GeneChip Hybridization Oven 640). The GeneChip arrays were washed and then stained (streptavidin-phycoerythrin) on an Affymetrix Fluidics Station 450 followed by scanning on GeneChip Scanner 3000.

The hybridization data were analyzed using GeneChip Operating software (GCOS 1.4). A global scaling factor of 500 was used to normalize the different arrays. We identified the differentially expressed genes according to change p-value calculated by GCOS 1.4, and 2-fold change as an empirical criterion. Then all DE genes were performed for hierarchical cluster (Ver.3.0) and TreeView (Ver.1.1.1) analyses. Genes with significant similarities to transcripts in nr database based on BLASTX searches were selected for GO analysis with DAVID http://david.abcc.ncifcrf.gov/home.jsp. Annotation results were obtained by inputting the gene list of ENTREZ_GENE_ID as identifier. All microarray results from this study were deposited in NCBI's Gene Expression Omnibus (GEO) database, accession numbers are: Platform, GPL3533; Series, GSE23596; Samples, GSM578704, GSM578705, GSM578706, GSM578707, GSM578708, GSM578709, GSM578710, GSM578711, GSM578712.

qPCR analysis

All tested RNAs from swine spleens were reversely transcribed to cDNA with the M-MLV Reverse Transcriptase (Promega). Each cDNA sample was used as a template for qPCR and the amplification mixture contained SYBR Green (TOYOBO, Japan), forward and reverse primers. Some primers were designed by the program Primer 5.0, the primer names, accession number, primer sequence and product size are shown in Table 3. The efficiency of the PCR reaction was 91-99% for all reactions (slope standard line between -3.3 and -3.6). The standard line consisted of five 10-fold dilutions of the samples. Analysis was performed using the ABI7500 Software (Applied Biosystems). PCRs were performed in ABI PRISM 7500 sequence detection system as follows: 1 cycle at 95°C for 10 min; 45 cycles at 95°C for 30 s, 60°C for 30 s and 72°C for 30 s. Melting curves were performed at the end of amplification for validating data quality by increasing the temperature from 65°C to 95°C, read every 0.2°C, hold 2 sec, then cooling at 25°C for 30 s. The PCR products were confirmed using agarose gel electrophoresis (1.5%). Amplification of the gapdh gene was used as internal control. All the tested genes are shown in Table 3. All reactions were performed in triplicate. For each run, to normalize the amount of sample cDNA added to each reaction, the Ct value of each test gene was subtracted by the Ct value of the endogenous control gapdh gene (delta Ct = Ct tested gene - Ct gapdh), and then for a comparison between the expression of the gene in treated samples and in control samples. The delta Ct values of the gene in treated samples were subtracted by the delta Ct value of the gene in control samples (delta-delta Ct = delta Ct treatment - delta Ct control). The fold changes were calculated by the formula of 2-delta-delta Ctdescribed by Livak & Schmittgen [79]. Data were means ± SD of triplicate reactions for each gene transcript.
Table 3

Primers for qPCR

primer

Accession

number

Sequence

Product

size

Plau

NM_213945

Forward: CGAACTGTGGCTGTCT

Reverse: AGCAGGTTTGCGATGTG

126 bp

S100A9 a

BI402402

Forward: CCAGGATGTGGTTTATGGCTTTC

Reverse: CGGACCAAATGTCGCAGA

186 bp

S100A12 a

CB475695

Forward: GGCATTATGACACCCTTATC

Reverse: GTCACCAGGACCACGAAT

169 bp

Hsp70

NM_213766

Forward: AGGCGGAGAAGTACAAAGCG

Reverse: GATGGGGTTACACACCTGCTC

257 bp

Timp1

NM_213857

Forward: CGCCTCGTACCAGCGTTAT

Reverse: GTGGAAGTATCCGCAGACGC

127 bp

SOD2

NM_214127

Forward: TCTGGACAAATCTGAGCCCT

Reverse: GACGGATACAGCGGTCAACTT

119 bp

Il6 b

AF493992

Forward: GACAAAGCCACCACCCCTAA

Reverse: CTCGTTCTGTGACTGCAGCTTATC

69 bp

Sele

NM_214268

Forward: GGATTTGAACTCATCGGACCT

Reverse: CATTCTGAGGATGGCCGAC

115 bp

Il1b b

NM_214055

Forward: GGCCGCCAAGATATAACTGA

Reverse: GGACCTCTGGGTATGGCTTTC

70 bp

Nramp1

U55068

Forward: CGTGGTGACAGGCAAGGACT

Reverse: TAGCCGTGCCGATGACTTC

131 bp

Hsp90

CF180819

Forward: CCCAGTTGATGTCGTTG

Reverse: CCGTCAGGCTTTCGTAT

117 bp

Il8 b

NM_213867

Forward: TTCGATGCCAGTGCATAAATA

Reverse: CTGTACAACCTTCTGCACCCA

176 bp

CCL19

BX672579

Forward: GCTAAGCCTCTGGACT

Reverse: AATGAGCAGGTAGCGA

121 bp

Haptocorrin

CB472702

Forward: ATTCTCAGGGAGTATTCCGTCT

Reverse: CTTTGGGGACAAGTAGCAGTT

105 bp

Alox15

NM_213931

Forward: ACCGAGGGTTTCCTGTCT

Reverse: AGGTGGTTGGAGGAGTGC

100 bp

TLR2 b

NM_213761

Forward:TCACTTGTCTAACTTATCATCCTCTTG

Reverse: TCAGCGAAGGTGTCATTATTGC

162 bp

GAPDH b

AF017079

Forward: TGCCAACGTGTCGGTTGT

Reverse: TGTCATCATATTTGGCAGGTTTCT

62 bp

a: primers from reference [43];

b: primers from reference [41].

Notes

Abbreviations

SS2: 

Streptococcus suis serotype 2

DE: 

differentially expressed

FC: 

fold change

GO: 

Gene Ontology

FDR: 

false discovery rate

qPCR: 

quantitative real-time PCR

TLR: 

Toll-like receptors

PRRs: 

pattern-recognition receptors

Declarations

Acknowledgements

We thank Professor Yanxiu Liu for her revision of the language of this manuscript.

This work was supported by National Basic Research Program of China (program 973, grant 2006CB504404), the National Transgenic Major Program (2009ZX08009-141B), the National Natural Science Foundation of China (30871870), and Program for Changjiang Scholars and Innovative Research Team in University (IRT0726).

Authors’ Affiliations

(1)
Unit of Animal Infectious Diseases, National Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University
(2)
College of Veterinary Medicine, Huazhong Agricultural University

References

  1. Staats JJ, Feder I, Okwumabua O, Chengappa MM: Streptococcus suis: past and present. Vet Res Commun. 1997, 21 (6): 381-407. 10.1023/A:1005870317757.PubMedView ArticleGoogle Scholar
  2. Lun ZR, Wang QP, Chen XG, Li AX, Zhu XQ: Streptococcus suis: an emerging zoonotic pathogen. Lancet Infect Dis. 2007, 7 (3): 201-209. 10.1016/S1473-3099(07)70001-4.PubMedView ArticleGoogle Scholar
  3. Hill JE, Gottschalk M, Brousseau R, Harel J, Hemmingsen SM, Goh SH: Biochemical analysis, cpn60 and 16S rDNA sequence data indicate that Streptococcus suis serotypes 32 and 34, isolated from pigs, are Streptococcus orisratti. Vet Microbiol. 2005, 107 (1-2): 63-69. 10.1016/j.vetmic.2005.01.003.PubMedView ArticleGoogle Scholar
  4. Tang J, Wang C, Feng Y, Yang W, Song H, Chen Z, Yu H, Pan X, Zhou X, Wang H: Streptococcal toxic shock syndrome caused by Streptococcus suis serotype 2. PLoS Med. 2006, 3 (5): e151-10.1371/journal.pmed.0030151.PubMed CentralPubMedView ArticleGoogle Scholar
  5. Vanier G, Segura M, Lecours MP, Grenier D, Gottschalk M: Porcine brain microvascular endothelial cell-derived interleukin-8 is first induced and then degraded by Streptococcus suis. Microb Pathog. 2009, 46 (3): 135-143. 10.1016/j.micpath.2008.11.004.PubMedView ArticleGoogle Scholar
  6. Haas G, Karaali G, Ebermayer K, Metzger WG, Lamer S, Zimny-Arndt U, Diescher S, Goebel UB, Vogt K, Roznowski AB: Immunoproteomics of Helicobacter pylori infection and relation to gastric disease. Proteomics. 2002, 2 (3): 313-324. 10.1002/1615-9861(200203)2:3<313::AID-PROT313>3.0.CO;2-7.PubMedView ArticleGoogle Scholar
  7. Holden MT, Hauser H, Sanders M, Ngo TH, Cherevach I, Cronin A, Goodhead I, Mungall K, Quail MA, Price C: Rapid evolution of virulence and drug resistance in the emerging zoonotic pathogen Streptococcus suis. PLoS One. 2009, 4 (7): e6072-10.1371/journal.pone.0006072.PubMed CentralPubMedView ArticleGoogle Scholar
  8. Wangsomboonsiri W, Luksananun T, Saksornchai S, Ketwong K, Sungkanuparph S: Streptococcus suis infection and risk factors for mortality. J Infect. 2008, 57 (5): 392-396. 10.1016/j.jinf.2008.08.006.PubMedView ArticleGoogle Scholar
  9. Rusmeechan S, Sribusara P: Streptococcus suis meningitis: the newest serious infectious disease. J Med Assoc Thai. 2008, 91 (5): 654-658.PubMedGoogle Scholar
  10. Watkins EJ, Brooksby P, Schweiger MS, Enright SM: Septicaemia in a pig-farm worker. Lancet. 2001, 357 (9249): 38-10.1016/S0140-6736(00)03570-4.PubMedView ArticleGoogle Scholar
  11. Taipa R, Lopes V, Magalhaes M: Streptococcus suis meningitis: first case report from Portugal. J Infect. 2008, 56 (6): 482-483. 10.1016/j.jinf.2008.03.002.PubMedView ArticleGoogle Scholar
  12. Tramontana AR, Graham M, Sinickas V, Bak N: An Australian case of Streptococcus suis toxic shock syndrome associated with occupational exposure to animal carcasses. Med J Aust. 2008, 188 (9): 538-539.PubMedGoogle Scholar
  13. van de Beek D, Spanjaard L, de Gans J: Streptococcus suis meningitis in the Netherlands. J Infect. 2008, 57 (2): 158-161. 10.1016/j.jinf.2008.04.009.PubMedView ArticleGoogle Scholar
  14. Smith TC, Capuano AW, Boese B, Myers KP, Gray GC: Exposure to Streptococcus suis among US swine workers. Emerg Infect Dis. 2008, 14 (12): 1925-1927. 10.3201/eid1412.080162.PubMed CentralPubMedView ArticleGoogle Scholar
  15. Fittipaldi N, Collis T, Prothero B, Gottschalk M: Streptococcus suis Meningitis, Hawaii. Emerg Infect Dis. 2009, 15 (12): 2067-2069. 10.3201/eid1512.090825.PubMed CentralPubMedView ArticleGoogle Scholar
  16. Wertheim HF, Nguyen HN, Taylor W, Lien TT, Ngo HT, Nguyen TQ, Nguyen BN, Nguyen HH, Nguyen HM, Nguyen CT: Streptococcus suis, an important cause of adult bacterial meningitis in northern Vietnam. PLoS One. 2009, 4 (6): 10.1371/journal.pone.0005973. e5973Google Scholar
  17. Chabot-Roy G, Willson P, Segura M, Lacouture S, Gottschalk M: Phagocytosis and killing of Streptococcus suis by porcine neutrophils. Microb Pathog. 2006, 41 (1): 21-32. 10.1016/j.micpath.2006.04.001.PubMedView ArticleGoogle Scholar
  18. Smith HE, Damman M, van der Velde J, Wagenaar F, Wisselink HJ, Stockhofe-Zurwieden N, Smits MA: Identification and characterization of the cps locus of Streptococcus suis serotype 2: the capsule protects against phagocytosis and is an important virulence factor. Infect Immun. 1999, 67 (4): 1750-1756.PubMed CentralPubMedGoogle Scholar
  19. de Greeff A, Buys H, Verhaar R, Dijkstra J, van Alphen L, Smith HE: Contribution of fibronectin-binding protein to pathogenesis of Streptococcus suis serotype 2. Infect Immun. 2002, 70 (3): 1319-1325. 10.1128/IAI.70.3.1319-1325.2002.PubMed CentralPubMedView ArticleGoogle Scholar
  20. Brassard J, Gottschalk M, Quessy S: Cloning and purification of the Streptococcus suis serotype 2 glyceraldehyde-3-phosphate dehydrogenase and its involvement as an adhesin. Vet Microbiol. 2004, 102 (1-2): 87-94. 10.1016/j.vetmic.2004.05.008.PubMedView ArticleGoogle Scholar
  21. Esgleas M, Li Y, Hancock MA, Harel J, Dubreuil JD, Gottschalk M: Isolation and characterization of alpha-enolase, a novel fibronectin-binding protein from Streptococcus suis. Microbiology. 2008, 154 (Pt 9): 2668-2679. 10.1099/mic.0.2008/017145-0.PubMedView ArticleGoogle Scholar
  22. Zhang A, Chen B, Mu X, Li R, Zheng P, Zhao Y, Chen H, Jin M: Identification and characterization of a novel protective antigen, Enolase of Streptococcus suis serotype 2. Vaccine. 2009, 27 (9): 1348-1353. 10.1016/j.vaccine.2008.12.047.PubMedView ArticleGoogle Scholar
  23. Haataja S, Tikkanen K, Hytonen J, Finne J: The Gal alpha 1-4 Gal-binding adhesin of Streptococcus suis, a gram-positive meningitis-associated bacterium. Adv Exp Med Biol. 1996, 408: 25-34.PubMedView ArticleGoogle Scholar
  24. Haataja S, Tikkanen K, Liukkonen J, Francois-Gerard C, Finne J: Characterization of a novel bacterial adhesion specificity of Streptococcus suis recognizing blood group P receptor oligosaccharides. J Biol Chem. 1993, 268 (6): 4311-4317.PubMedGoogle Scholar
  25. Haataja S, Tikkanen K, Nilsson U, Magnusson G, Karlsson KA, Finne J: Oligosaccharide-receptor interaction of the Gal alpha 1-4Gal binding adhesin of Streptococcus suis. Combining site architecture and characterization of two variant adhesin specificities. J Biol Chem. 1994, 269 (44): 27466-27472.PubMedGoogle Scholar
  26. Tikkanen K, Haataja S, Francois-Gerard C, Finne J: Purification of a galactosyl-alpha 1-4-galactose-binding adhesin from the gram-positive meningitis-associated bacterium Streptococcus suis. J Biol Chem. 1995, 270 (48): 28874-28878. 10.1074/jbc.270.48.28874.PubMedView ArticleGoogle Scholar
  27. Tikkanen K, Haataja S, Finne J: The galactosyl-(alpha 1-4)-galactose-binding adhesin of Streptococcus suis: occurrence in strains of different hemagglutination activities and induction of opsonic antibodies. Infect Immun. 1996, 64 (9): 3659-3665.PubMed CentralPubMedGoogle Scholar
  28. Baums CG, Kaim U, Fulde M, Ramachandran G, Goethe R, Valentin-Weigand P: Identification of a novel virulence determinant with serum opacification activity in Streptococcus suis. Infect Immun. 2006, 74 (11): 6154-6162. 10.1128/IAI.00359-06.PubMed CentralPubMedView ArticleGoogle Scholar
  29. Zhang A, Mu X, Chen B, Liu C, Han L, Chen H, Jin M: Identification and characterization of IgA1 protease from Streptococcus suis. Vet Microbiol. 2010, 140 (1-2): 171-175. 10.1016/j.vetmic.2009.06.034.PubMedView ArticleGoogle Scholar
  30. Fittipaldi N, Sekizaki T, Takamatsu D, Harel J, Dominguez-Punaro Mde L, Von Aulock S, Draing C, Marois C, Kobisch M, Gottschalk M: D-alanylation of lipoteichoic acid contributes to the virulence of Streptococcus suis. Infect Immun. 2008, 76 (8): 3587-3594. 10.1128/IAI.01568-07.PubMed CentralPubMedView ArticleGoogle Scholar
  31. Fittipaldi N, Sekizaki T, Takamatsu D, Dominguez-Punaro Mde L, Harel J, Bui NK, Vollmer W, Gottschalk M: Significant contribution of the pgdA gene to the virulence of Streptococcus suis. Mol Microbiol. 2008, 70 (5): 1120-1135. 10.1111/j.1365-2958.2008.06463.x.PubMedView ArticleGoogle Scholar
  32. Li M, Wang C, Feng Y, Pan X, Cheng G, Wang J, Ge J, Zheng F, Cao M, Dong Y: SalK/SalR, a two-component signal transduction system, is essential for full virulence of highly invasive Streptococcus suis serotype 2. PLoS ONE. 2008, 3 (5): e2080-10.1371/journal.pone.0002080.PubMed CentralPubMedView ArticleGoogle Scholar
  33. Pan X, Ge J, Li M, Wu B, Wang C, Wang J, Feng Y, Yin Z, Zheng F, Cheng G: The orphan response regulator CovR: a globally negative modulator of virulence in Streptococcus suis serotype 2. J Bacteriol. 2009, 191 (8): 2601-2612. 10.1128/JB.01309-08.PubMed CentralPubMedView ArticleGoogle Scholar
  34. Ye C, Zheng H, Zhang J, Jing H, Wang L, Xiong Y, Wang W, Zhou Z, Sun Q, Luo X: Clinical, Experimental, and Genomic Differences between Intermediately Pathogenic, Highly Pathogenic, and Epidemic Streptococcus suis. J Infect Dis. 2009, 199 (1): 97-107. 10.1086/594370.PubMedView ArticleGoogle Scholar
  35. Vadeboncoeur N, Segura M, Al-Numani D, Vanier G, Gottschalk M: Pro-inflammatory cytokine and chemokine release by human brain microvascular endothelial cells stimulated by Streptococcus suis serotype 2. FEMS Immunol Med Microbiol. 2003, 35 (1): 49-58. 10.1111/j.1574-695X.2003.tb00648.x.PubMedView ArticleGoogle Scholar
  36. Segura M, Vanier G, Al-Numani D, Lacouture S, Olivier M, Gottschalk M: Proinflammatory cytokine and chemokine modulation by Streptococcus suis in a whole-blood culture system. FEMS Immunol Med Microbiol. 2006, 47 (1): 92-106. 10.1111/j.1574-695X.2006.00067.x.PubMedView ArticleGoogle Scholar
  37. Segura M, Stankova J, Gottschalk M: Heat-killed Streptococcus suis capsular type 2 strains stimulate tumor necrosis factor alpha and interleukin-6 production by murine macrophages. Infect Immun. 1999, 67 (9): 4646-4654.PubMed CentralPubMedGoogle Scholar
  38. Segura M, Vadeboncoeur N, Gottschalk M: CD14-dependent and -independent cytokine and chemokine production by human THP-1 monocytes stimulated by Streptococcus suis capsular type 2. Clin Exp Immunol. 2002, 127 (2): 243-254. 10.1046/j.1365-2249.2002.01768.x.PubMed CentralPubMedView ArticleGoogle Scholar
  39. Dominguez-Punaro MC, Segura M, Plante MM, Lacouture S, Rivest S, Gottschalk M: Streptococcus suis serotype 2, an important swine and human pathogen, induces strong systemic and cerebral inflammatory responses in a mouse model of infection. J Immunol. 2007, 179 (3): 1842-1854.PubMedView ArticleGoogle Scholar
  40. Dominguez-Punaro Mde L, Segura M, Radzioch D, Rivest S, Gottschalk M: Comparison of the susceptibilities of C57BL/6 and A/J mouse strains to Streptococcus suis serotype 2 infection. Infect Immun. 2008, 76 (9): 3901-3910. 10.1128/IAI.00350-08.PubMed CentralView ArticleGoogle Scholar
  41. de Greeff A, Benga L, Wichgers Schreur PJ, Valentin-Weigand P, Rebel JM, Smith HE: Involvement of NF-kappaB and MAP-kinases in the transcriptional response of alveolar macrophages to Streptococcus suis. Vet Microbiol. 2009, 141 (1-2): 59-67. 10.1016/j.vetmic.2009.07.031.PubMedView ArticleGoogle Scholar
  42. Zhao SH, Kuhar D, Lunney JK, Dawson H, Guidry C, Uthe JJ, Bearson SM, Recknor J, Nettleton D, Tuggle CK: Gene expression profiling in Salmonella Choleraesuis-infected porcine lung using a long oligonucleotide microarray. Mamm Genome. 2006, 17 (7): 777-789. 10.1007/s00335-005-0155-3.PubMedView ArticleGoogle Scholar
  43. Chen H, Li C, Fang M, Zhu M, Li X, Zhou R, Li K, Zhao S: Understanding Haemophilus parasuis infection in porcine spleen through a transcriptomics approach. BMC Genomics. 2009, 10: 64-10.1186/1471-2164-10-64.PubMed CentralPubMedView ArticleGoogle Scholar
  44. van der Poll T, Keogh CV, Guirao X, Buurman WA, Kopf M, Lowry SF: Interleukin-6 gene-deficient mice show impaired defense against pneumococcal pneumonia. J Infect Dis. 1997, 176 (2): 439-444. 10.1086/514062.PubMedView ArticleGoogle Scholar
  45. Norrby-Teglund A, Pauksens K, Norgren M, Holm SE: Correlation between serum TNF alpha and IL6 levels and severity of group A streptococcal infections. Scand J Infect Dis. 1995, 27 (2): 125-130. 10.3109/00365549509018991.PubMedView ArticleGoogle Scholar
  46. Foell D, Wittkowski H, Vogl T, Roth J: S100 proteins expressed in phagocytes: a novel group of damage-associated molecular pattern molecules. J Leukoc Biol. 2007, 81 (1): 28-37. 10.1189/jlb.0306170.PubMedView ArticleGoogle Scholar
  47. Hojo K, Tamura A, Mizoguchi C, Kato D, Ohshima T, Maeda N: Predominant bacteria recovered from a periodontitis site in a hamster model raised by silk-ligature with Porphyromonas gingivalis infection. Biosci Biotechnol Biochem. 2008, 72 (5): 1348-1351. 10.1271/bbb.70653.PubMedView ArticleGoogle Scholar
  48. Patel L, Buckels AC, Kinghorn IJ, Murdock PR, Holbrook JD, Plumpton C, Macphee CH, Smith SA: Resistin is expressed in human macrophages and directly regulated by PPAR gamma activators. Biochem Biophys Res Commun. 2003, 300 (2): 472-476. 10.1016/S0006-291X(02)02841-3.PubMedView ArticleGoogle Scholar
  49. Bokarewa M, Nagaev I, Dahlberg L, Smith U, Tarkowski A: Resistin, an adipokine with potent proinflammatory properties. J Immunol. 2005, 174 (9): 5789-5795.PubMedView ArticleGoogle Scholar
  50. Ward PP, Conneely OM: Lactoferrin: role in iron homeostasis and host defense against microbial infection. Biometals. 2004, 17 (3): 203-208. 10.1023/B:BIOM.0000027693.60932.26.PubMedView ArticleGoogle Scholar
  51. Knura-Deszczk S, Lipperheide C, Petersen B, Jobert JL, Berthelot-Herault F, Kobisch M, Madec F: Plasma haptoglobin concentration in swine after challenge with Streptococcus suis. J Vet Med B Infect Dis Vet Public Health. 2002, 49 (5): 240-244.PubMedView ArticleGoogle Scholar
  52. Thorn CF, Lu ZY, Whitehead AS: Tissue-specific regulation of the human acute-phase serum amyloid A genes, SAA1 and SAA2, by glucocorticoids in hepatic and epithelial cells. Eur J Immunol. 2003, 33 (9): 2630-2639. 10.1002/eji.200323985.PubMedView ArticleGoogle Scholar
  53. Baumann H, Gauldie J: The acute phase response. Immunol Today. 1994, 15 (2): 74-80. 10.1016/0167-5699(94)90137-6.PubMedView ArticleGoogle Scholar
  54. Sorensen NS, Tegtmeier C, Andresen LO, Pineiro M, Toussaint MJ, Campbell FM, Lampreave F, Heegaard PM: The porcine acute phase protein response to acute clinical and subclinical experimental infection with Streptococcus suis. Vet Immunol Immunopathol. 2006, 113 (1-2): 157-168. 10.1016/j.vetimm.2006.04.008.PubMedView ArticleGoogle Scholar
  55. Rikitake Y, Takai Y: Interactions of the cell adhesion molecule nectin with transmembrane and peripheral membrane proteins for pleiotropic functions. Cell Mol Life Sci. 2008, 65 (2): 253-263. 10.1007/s00018-007-7290-9.PubMedView ArticleGoogle Scholar
  56. Al-Numani D, Segura M, Dore M, Gottschalk M: Up-regulation of ICAM-1, CD11a/CD18 and CD11c/CD18 on human THP-1 monocytes stimulated by Streptococcus suis serotype 2. Clin Exp Immunol. 2003, 133 (1): 67-77. 10.1046/j.1365-2249.2003.02189.x.PubMed CentralPubMedView ArticleGoogle Scholar
  57. Wight TN: Versican: a versatile extracellular matrix proteoglycan in cell biology. Curr Opin Cell Biol. 2002, 14 (5): 617-623. 10.1016/S0955-0674(02)00375-7.PubMedView ArticleGoogle Scholar
  58. Wang W, Xu GL, Jia WD, Ma JL, Li JS, Ge YS, Ren WH, Yu JH, Liu WB: Ligation of TLR2 by versican: a link between inflammation and metastasis. Arch Med Res. 2009, 40 (4): 321-323. 10.1016/j.arcmed.2009.04.005.PubMedView ArticleGoogle Scholar
  59. Simantov R, Silverstein RL: CD36: a critical anti-angiogenic receptor. Front Biosci. 2003, 8: s874-882. 10.2741/1168.PubMedView ArticleGoogle Scholar
  60. Nakache M, Berg EL, Streeter PR, Butcher EC: The mucosal vascular addressin is a tissue-specific endothelial cell adhesion molecule for circulating lymphocytes. Nature. 1989, 337 (6203): 179-181. 10.1038/337179a0.PubMedView ArticleGoogle Scholar
  61. Tilley SL, Coffman TM, Koller BH: Mixed messages: modulation of inflammation and immune responses by prostaglandins and thromboxanes. J Clin Invest. 2001, 108 (1): 15-23.PubMed CentralPubMedView ArticleGoogle Scholar
  62. Jobin MC, Gottschalk M, Grenier D: Upregulation of prostaglandin E2 and matrix metalloproteinase 9 production by human macrophage-like cells: synergistic effect of capsular material and cell wall from Streptococcus suis. Microb Pathog. 2006, 40 (1): 29-34. 10.1016/j.micpath.2005.10.003.PubMedView ArticleGoogle Scholar
  63. Graveline R, Segura M, Radzioch D, Gottschalk M: TLR2-dependent recognition of Streptococcus suis is modulated by the presence of capsular polysaccharide which modifies macrophage responsiveness. Int Immunol. 2007, 19 (4): 375-389. 10.1093/intimm/dxm003.PubMedView ArticleGoogle Scholar
  64. Schreur PJ, Rebel JM, Smits MA, van Putten JP, Smith HE: Differential activation of the Toll-like receptor 2/6 complex by lipoproteins of Streptococcus suis serotypes 2 and 9. Vet Microbiol. 143 (2-4): 363-370. 10.1016/j.vetmic.2009.12.010.
  65. Baums CG, Valentin-Weigand P: Surface-associated and secreted factors of Streptococcus suis in epidemiology, pathogenesis and vaccine development. Anim Health Res Rev. 2009, 10 (1): 65-83. 10.1017/S146625230999003X.PubMedView ArticleGoogle Scholar
  66. Feng Y, Zhang H, Ma Y, Gao GF: Uncovering newly emerging variants of Streptococcus suis, an important zoonotic agent. Trends Microbiol. 2010, 18 (3): 124-31. 10.1016/j.tim.2009.12.003.PubMedView ArticleGoogle Scholar
  67. Zhang Q, Peng H, Gao F, Liu Y, Cheng H, Thompson J, Gao GF: Structural insight into the catalytic mechanism of gluconate 5-dehydrogenase from Streptococcus suis: Crystal structures of the substrate-free and quaternary complex enzymes. Protein Sci. 2009, 18 (2): 294-303. 10.1002/pro.32.PubMed CentralPubMedView ArticleGoogle Scholar
  68. Zhang Q, Gao F, Peng H, Cheng H, Liu Y, Tang J, Thompson J, Wei G, Zhang J, Du Y: Crystal structures of Streptococcus suis mannonate dehydratase (ManD) and its complex with substrate: genetic and biochemical evidence for a catalytic mechanism. J Bacteriol. 2009, 191 (18): 5832-7. 10.1128/JB.00599-09.PubMed CentralPubMedView ArticleGoogle Scholar
  69. Goldmann O, von Kockritz-Blickwede M, Holtje C, Chhatwal GS, Geffers R, Medina E: Transcriptome analysis of murine macrophages in response to infection with Streptococcus pyogenes reveals an unusual activation program. Infect Immun. 2007, 75 (8): 4148-4157. 10.1128/IAI.00181-07.PubMed CentralPubMedView ArticleGoogle Scholar
  70. Akira S, Uematsu S, Takeuchi O: Pathogen recognition and innate immunity. Cell. 2006, 124 (4): 783-801. 10.1016/j.cell.2006.02.015.PubMedView ArticleGoogle Scholar
  71. Segura M, Gottschalk M: Streptococcus suis interactions with the murine macrophage cell line J774: adhesion and cytotoxicity. Infect Immun. 2002, 70 (8): 4312-4322. 10.1128/IAI.70.8.4312-4322.2002.PubMed CentralPubMedView ArticleGoogle Scholar
  72. Segura M, Gottschalk M, Olivier M: Encapsulated Streptococcus suis inhibits activation of signaling pathways involved in phagocytosis. Infect Immun. 2004, 72 (9): 5322-5330. 10.1128/IAI.72.9.5322-5330.2004.PubMed CentralPubMedView ArticleGoogle Scholar
  73. Hu Q, Liu P, Yu Z, Zhao G, Li J, Teng L, Zhou M, Bei W, Chen H, Jin M: Identification of a cell wall-associated subtilisin-like serine protease involved in the pathogenesis of Streptococcus suis serotype 2. Microb Pathog. 2010, 48 (3-4): 103-9. 10.1016/j.micpath.2009.11.005.PubMedView ArticleGoogle Scholar
  74. Tan C, Liu M, Jin M, Liu J, Chen Y, Wu T, Fu T, Bei W, Chen H: The key virulence-associated genes of Streptococcus suis type 2 are upregulated and differentially expressed in vivo. FEMS Microbiol Lett. 2008, 278 (1): 108-114. 10.1111/j.1574-6968.2007.00980.x.PubMedView ArticleGoogle Scholar
  75. Zhang A, Chen B, Li R, Mu X, Han L, Zhou H, Chen H, Meilin J: Identification of a surface protective antigen, HP0197 of Streptococcus suis serotype 2. Vaccine. 2009, 27 (38): 5209-5213. 10.1016/j.vaccine.2009.06.074.PubMedView ArticleGoogle Scholar
  76. Gottschalk M, Segura M: The pathogenesis of the meningitis caused by Streptococcus suis: the unresolved questions. Vet Microbiol. 2000, 76 (3): 259-272. 10.1016/S0378-1135(00)00250-9.PubMedView ArticleGoogle Scholar
  77. Vanier G, Segura M, Friedl P, Lacouture S, Gottschalk M: Invasion of porcine brain microvascular endothelial cells by Streptococcus suis serotype 2. Infect Immun. 2004, 72 (3): 1441-1449. 10.1128/IAI.72.3.1441-1449.2004.PubMed CentralPubMedView ArticleGoogle Scholar
  78. Zhang A, Xie C, Chen H, Jin M: Identification of immunogenic cell wall-associated proteins of Streptococcus suis serotype 2. Proteomics. 2008, 8 (17): 3506-3515. 10.1002/pmic.200800007.PubMedView ArticleGoogle Scholar
  79. Livak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001, 25 (4): 402-408. 10.1006/meth.2001.1262.PubMedView ArticleGoogle Scholar

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