Rotavirus Pathogenesis, Innate Immunity and Their Immune Modulation by Probiotics in a Piglet Model and in Vitro

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ROTAVIRUS PATHOGENESIS, INNATE IMMUNITY AND THEIR IMMUNE MODULATION BY PROBIOTICS IN A PIGLET MODEL AND IN VITRO

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Lulu Shao

Graduate Program in Comparative and Veterinary Medicine

The Ohio State University

2015

Dissertation Committee:

Dr. Linda J Saif, Advisor

Dr. Anastasia N Vlasova, Co-advisor

Dr. Prosper N. Boyaka

Dr. Renukaradhya J. Gourapura

Dr. Gireesh Rajashekara

Copyrighted by

Lulu Shao

2015

Abstract

Rotavirus (RV) is a major pathogen causing acute gastroenteritis in children under 5 and in young animals. Because no specific antiviral therapy is available, effective RV vaccines are crucial to prevent morbidity and mortality. However, licensed RV vaccines for humans have low efficacy in developing countries, and emerging RV strains

(including G9) may decrease vaccine efficacy. Our goal was to improve understanding of

RV pathogenesis, cross-protection and correlates of protection and probiotics/commensals, age and tissue-specific effects on innate immunity in a pig model.

Our first objective was to assess the pathogenesis of porcine RV (PRV) G9P[13] and evaluate short-term cross-protection between G9P[13] and human RV (HRV) G1P[8] in a gnotobiotic (Gn) pig model. Gn pigs were inoculated with G9P[13] and challenged with

G1P[8], or vice versa. G9P[13] induced longer fecal virus shedding than G1P[8] and generated complete short-term cross-protection in pigs challenged with G1P[8] or

G9P[13], whereas G1P[8] induced only partial protection against G9P[13] challenge.

G9P[13] replicated more extensively in porcine monocyte-derived dendritic cells (DCs) than G1P[8]. Our results suggest that heterologous protection by the current monovalent

G1P[8] vaccine against emerging G9 strains should be evaluated in further studies to prevent wider dissemination of G9 strains.

Our second objective was to compare the influence of age, diet, microbiota and tissue origin on TLR expression in mononuclear cells (MNCs) and DCs isolated from spleen, ileum and mesenteric lymph nodes (MLNs) of germfree (GF) and conventional pigs.

TLR mRNA expression profiles were distinct between GF and conventional pigs, and were generally lower in ileal MNCs/DCs which may be due to microbiota-driven immunoregulatory/immunosuppressive mechanisms to avoid overstimulation by dampening TLR expression levels. Comparison of TLR expression profiles in GF and conventional pigs demonstrated that exposure to commensal microbiota may be of more importance than age in TLR expression, further highlighting the critical role of commensal microbiota in the development of systemic and mucosal immune systems of neonates.

Our third objective was to examine the differential effects of live probiotic bacteria on splenic, ileal and MLN MNCs from Gn pigs. MNCs were analyzed after treatment with probiotics and/or inactivated HRV (inactHRV) in vitro to determine DC frequencies and cytokine levels. We found that the Gram-positive probiotics Lactobacilus rhamnosus GG

(LGG) and Bifidobacterium lactis Bb12 (Bb12) decreased the frequencies of conventional DC (cDC) and activated (MHCII+) cDC in ileal and MLN of inactHRV- exposed or untreated MNCs. In contrast, the Gram-negative probiotic Escherichia coli

Nissle 1917 (EcN) increased plasmacytoid DC (pDC) and (MHCII+) pDC frequencies in

MLN MNCs. In inactHRV-exposed groups, EcN, LGG and Bb12 reduced cytokine levels of IL-6 (pro-inflammatory), IFN-alpha (innate/anti-viral), IL-12 (Th1), and IL-4 (Th2) in splenic MNCs; whereas, EcN increased IL-10 (T-regulatory) levels. These results

iii demonstrate that Gram-positive and Gram-negative probiotic bacteria differentially modulate DC frequencies, surface phenotypes and functions in vitro.

Collectively, these findings improve our understanding of RV pathogenesis, correlates of protection, and the development of porcine innate immunity. This knowledge should help to improve RV vaccine efficacy and aid in design of new vaccines.

This dissertation is dedicated to my parents, Huabin Shao and Lin Zhang, for the love and support. Dedication goes to my husband Zhenyu Li who encourages and supports me to

reach my goal.

Acknowledgments

I would like to express my sincere appreciation and gratitude to my advisor, Dr. Linda J.

Saif, for her guidance and mentorship. Her enthusiasm and attitude to scientific research greatly affected me. Without her support and encouragement, this dissertation would not have been possible.

Many thanks to my co-advisor, Dr. Anastasia N. Vlasova, for training me with lab techniques, discussing experimental data analyses, and revising my manuscripts and dissertation. She encouraged me to believe in myself to face challenges and guided me to reach this accomplishment.

I would also like to thank all my committee members, Drs. Prosper N. Boyaka,

Renukaradhya J. Gourapura and Gireesh Rajashekara, for the guidance and suggestions over the years.

My deep appreciation to Dr. Qiuhong Wang, Dr. David Fischer, Dr. Sukumar

Kandasamy, Dr. Kuldeep Chattha, Stephanie Neal and Zhongyan Lu with whom I encountered the struggles of research. My gratitude goes to Xiaohong Wang, Marcia Lee,

Juliet Chepngeno and Kyle Scheuer, for their technical assistance which helped me to finish my projects. To Dr. Juliette Hanson, Ronna Wood and Jeff Ogg for the help of animal experiments. To Hanna Gehman and Robin Weimer for the support and help.

Vita

2006 to 2011 ...... B. S. Veterinary Medicine, Huazhong

Agricultural University

2011 to present ...... Graduate student, Department of Veterinary

Preventive Medicine, The Ohio State

University

Publications

1. N. Vlasova, K. Chattha, S. Kandasamy, Z. Liu, M. Esseili, L. Shao, G. Rajashekara,

L. J. Saif. (2013) Lactobacilli and Bifidobacteria promote immune homeostasis and

modulate innate immune responses to human rotavirus in neonatal gnotobiotic pigs.

PLoS ONE 8(10): e76962. doi: 10.1371/journal.pone.0076962

2. L. Shao, D. D. Fischer, S. Kandasamy, A. Rauf, S. N. Langel, D. E. Wentworth, K.

M. Stucker, R. A. Halpin, H. C. Lam, D. Marthaler, L. J. Saif, A. N. Vlasova.

Comparative in vitro and in vivo studies of porcine rotavirus G9P[13] and human

rotavirus Wa G1P[8]. J Virol doi:10.1128/JVI.02401-15

3. S. Kandasamy, A. N. Vlasova, D. D. Fischer, A. Kumar, K. Chattha, A. Rauf, L.

Shao, S. N. Langel, G. Rajashekara, L. J. Saif. Differential effects of Escherichia coli

vii

Nissle and Lactobacillus rhamnosus strain GG on human rotavirus binding, infection, and B cell immunity. J Immunol accepted

viii

Published Abstracts

1. L. Shao, A.N. Vlasova, K. Chattha, S. Kandasamy, D. Fischer, L.J. Saif. Differential

effects of live probiotic bacteria and their metabolites in vitro on conventional and

plasmacytoid dendritic cells from gnotobiotic pigs. The American Society for

Virology 2013

2. L. Shao, L.J. Saif, D. Fischer, S. Kandasamy, A. Rauf, A. Vlasova. Comparative in

vivo and in vitro studies of porcine rotavirus G9P[13] and human rotavirus Wa

(G1P[8]) in gnotobiotic pigs. Conference of Research Workers in Animal Diseases

2014

3. L.J. Saif, A.N. Vlasova, S. Kandasamy, L. Shao, A. Rauf, D. Fischer, K. Chattha, A.

Kumar, G. Rajashekara. Escherichia coli (Nissle 1917) modulates innate and adaptive

immune responses and reduces human rotavirus diarrhea in a neonatal gnotobioitc pig

disease model. NIH RO1 Infant Immunity Workshop 2014

4. S. Kandasamy, A. N. Vlasova, K. Chatta, D. Fischer, L. Shao, A. Kumar, G.

Rajashekara, L.J. Saif. Escherichia coli Nissle 1917 colonization ameliorates human

rotavirus diarrhea and modulates B cell responses in a neonatal gnotobiotic pig

disease model. NIH RO1 Infant Immunity Workshop 2014

5. A.N. Vlasova, S. Kandasamy, L. Shao, A. Rauf, D. Fischer, K. Chattha, A. Kumar,

G. Rajashekara, L.J. Saif. Escherichia coli Nissle 1917 colonization upregulates

innate immunity and partially protects against human rotavirus infection in a neonatal

gnotobiotic pig model. The American Association of Immunologists 2014

6. S. Kandasamy, A. Vlasova, K. Chattha, D. Fisher, L. Shao, A. Kumar, G.

Rajashekara, L.J. Saif. Escherichia coli Nissle 1917 colonization ameliorates human

rotavirus diarrhea and modulates B cell responses in a neonatal gnotobiotic pig

disease model. The American Association of Immunologists 2014

7. L.J. Saif, A. N. Vlasova, S. Kandasamy, K. Chattha, G. Rajashekara, A. Kumar, A.

Rauf, L. Shao, D. Fischer, H. Huang and S. Neal. Tailoring probiotics as

immunomodulators to enhance neonatal mucosal immunity to rotavirus (RV)

vaccines or alleviate RV diarrhea: Evaluation in a neonatal gnotobiotic piglet model.

Conference of Research Workers in Animal Diseases 2014

8. Y. Wang, A. Vlasova, L.J. Saif, D. Fischer, K. Chattha, S. Kandasamy, L. Shao, Y.

Levin, B. Jiang. Immunogenicity and Protective Efficacy of Inactivated Rotavirus

Vaccine in Piglets. Presented at the 33rd Annual Meeting, American Society for

Virology, Ft. Collins, CO, June 2014.

9. S. Kandasamy, A. Vlasova, K. Chattha, D. Fischer, A. Rauf, L. Shao, S. Neal, A.

Kumar, G. Rajashekara, L.J. Saif. Differential effects of Escherichia coli Nissle and

Lactobacillus rhamnosus strain GG on human rotavirus infection and B cell

responses. Society for Mucosal Immunology, Berlin, Germany, July 2015.

Fields of Study

Major Field: Comparative and Veterinary Medicine

Studies in Virology and Immunology

Table of Contents

Abstract ...... ii

Acknowledgments ...... vi

Vita ...... vii

Table of Contents ...... xi

List of Tables ...... xv

List of Figures ...... xvi

Chapter 1 Rotavirus and Innate Immunity ...... 1

1.1 Introduction of rotavirus ...... 1

1.1.1 History of rotavirus ...... 1

1.1.2 The structure of RV ...... 2

1.1.3 The classification of RV ...... 4

1.1.4 The pathogenesis of RV ...... 5

1.1.5 RV vaccines for humans and animals ...... 6

1.2 Epidemiology of RV ...... 9

1.2.1 The epidemiological study of RVA in humans ...... 9

1.2.2 The epidemiological study of RVA in animals ...... 12

1.3 The host immune responses to RV infection ...... 14

1.3.1 Host innate immune responses to RV infection ...... 14

1.3.2 Host adaptive immune response to RV infection ...... 18

1.3.3 Escape strategies of RVs ...... 19

1.4 Probiotics for prevention of RV diarrhea and enhancement of vaccines ...... 22

1.4.1 The protective effect of probiotics on RV diarrhea ...... 22

1.4.2 The role of probiotics as adjuvants in RV vaccination ...... 25

1.5 The extraintestinal dissemination of RV ...... 27

1.5.1 The extraintestinal dissemination of RV ...... 27

1.5.2 The interaction between RVs and antigen-presenting cells ...... 28

1.6 Functions of DCs in immunity ...... 31

1.6.1 Introduction of DCs ...... 32

1.6.2 The classification of human and porcine DCs and surface markers on different

DC subsets ...... 33

1.6.3 The function of DCs in innate and adaptive immunity ...... 38

1.6.4 The function of DCs in regulatory immunity ...... 40

1.6.5 The function of intestinal DCs ...... 43

1.6.6 The interaction between DCs and viruses ...... 45

1.7 The role of TLRs in immune responses, gut homeostasis and immune diseases .... 48

1.7.1 The discovery and localization of TLRs ...... 48

1.7.2 The function of TLRs in immune responses ...... 49

1.7.3 The role of TLRs in gut homeostasis ...... 51

1.7.4 TLRs and immune diseases ...... 52

1.7.5 The expression and regulation of TLRs in humans, in mice and in pigs ...... 53

xii

1.8 Reference ...... 54

Chapter 2 Comparative in vitro and in vivo studies of porcine rotavirus G9P[13] and human rotavirus Wa G1P[8] ...... 92

2.1 Abstract ...... 92

2.2 Introduction ...... 93

2.3 Materials and Methods ...... 96

2.4 Results ...... 102

2.5 Discussions ...... 107

2.6 Acknowledgements ...... 114

2.7 References ...... 114

Chapter 3 Tissue-specific mRNA expression profiles of porcine Toll-like receptors at different ages in germ-free and conventional pigs ...... 130

3.1 Abstract ...... 130

3.2 Introduction ...... 131

3.3 Materials and Methods ...... 134

3.4 Results ...... 137

3.5 Discussion ...... 142

3.6 Acknowledgements ...... 148

3.7 References ...... 149

Chapter 4 Differential effects of live probiotic bacteria in vitro on conventional and plasmacytoid dendritic cells from gnotobiotic pigs ...... 166

4.1 Abstract ...... 166

xiii

4.2 Introduction ...... 167

4.3 Materials and Methods ...... 169

4.4 Results ...... 172

4.5 Discussion ...... 174

4.6 Acknowledgements ...... 177

4.7 References ...... 177

Bibliography ...... 191

xiv

List of Tables

Table 1.1 The distribution of the most prevalent serotypes/genotypes of human

rotaviruses between 1995 and 2013...... 88

Table 1.2 The distribution of the most prevalent serotypes/genotypes of porcine group A

rotaviruses between 1976 and 2013...... 89

Table 1.3 TLRs and their ligands...... 90

Table 2.1 Virus shedding and diarrhea in PRV G9[13] and HRV Wa G1P[8] post-

inoculation pigs from PID1 to PID10...... 123

Table 2.2 RVA detection in MNCs from ileum, MLNs, spleen, liver and blood of PRV

G9P[13] and HRV Wa G1P[8] inoculated pigs...... 124

Table 2.3 Diarrhea and rectal virus shedding in post-challenge pigs of different treatment

groups from PCD1 to PCD7...... 125

Table 2.4 Virus neutralizing antibody titer (and R% values) against selected RVs...... 126

Table 3.1 Primer sequences for porcine TLRs 1-10 genes...... 155

Table 3.2 Differentiation mRNA expression of porcine TLRs 1-10 in splenic and ileal

MNCs of GF newborn and young pigs...... 156

Table 4.1 Antibodies used in flow cytometry staining...... 182

List of Figures

Figure 1.1 Schematic representation of a rotavirus virion...... 91

Figure 2.1 Fecal virus shedding (A) and diarrhea scores (B) and in PRV G9P[13] and

HRV Wa G1P[8] inoculated pigs from PID1 to PID10...... 127

Figure 2.2 RV viral RNA detection in PRV G9P[13] or HRV Wa G1P[8] inoculated pig

sera on PID3 and PID5...... 128

Figure 2.3 RVA anti-NSP4 antigen detection in untreated, PRV G9P[13] or HRV Wa

G1P[8] exposed MoDCs...... 129

Figure 3.1 TLRs 1-10 mRNA expression profiles in newborn pigs...... 157

Figure 3.2 TLRs 1-10 mRNA expression profiles in germ-free and conventional young

pigs...... 158

Figure 3.3 TLRs 1-10 mRNA expression profiles in MNCs and DCs of conventional

adult pigs...... 159

Figure 3.4 TLRs 1-10 mRNA expression profiles in splenic and ileal MNCs of

conventional pigs at different ages...... 160

Figure 3.5 TLRs 1-10 mRNA expression profiles in DCs of young pigs...... 163

Figure 3.6 TLRs mRNA expression profiles in splenic and ileal DCs of conventional pigs

at different ages...... 164

Figure 4.1 Frequencies of cDC and pDC in ileal MNCs...... 183

xvi

Figure 4.2 Frequencies of MHCII+ cDC and MHCII+ pDC in ileal MNCs...... 184

Figure 4.3 Frequencies of cDC and pDC in MLN MNCs...... 185

Figure 4.4 Frequencies of MHCII+ cDC and MHCII+ pDC in MLN MNCs...... 186

Figure 4.5 Frequencies of cDC, pDC, MHCII+ cDC and MHCII+ pDC in splenic MNCs.

...... 187

Figure 4.6 IFN-alpha, IL-12, IL-6 and IL-4 levels in splenic MNCs...... 188

Figure 4.7 IL-10 levels in MLN, ileal and splenic MNCs...... 189

Figure 4.8 Frequencies of TLR2-, TLR3-, TLR4-expressing splenic MNCs after live

probiotics treatments with/without inactHRV...... 190

xvii

Chapter 1 Rotavirus and Innate Immunity

1.1 Introduction of rotavirus

1.1.1 History of rotavirus

In 1973, Bishop and colleagues identified particles of a “new” virus in the cytoplasm of duodenal epithelial cells of children with non-bacterial diarrhea (1). Before discovery of the “new” virus, no infectious agent could be identified in 80% of young children with acute dehydrating diarrhea (2). The wheel-like shape observed by electron microscopy led to the name rotavirus (RV), and RV was quickly linked to previous observations of

“identical” viruses causing severe diarrhea in newborn animals, including mice, calves and monkeys (2).

Now, RV is recognized as one of the most important enteric pathogens worldwide. It is the most common pathogen in cases of acute gastroenteritis in children under 5 years of age (3). Annually, RV causes 440,000 deaths in children, mostly in developing countries

(4). RV also causes diarrhea in domestic young animals, such as piglets and calves, and is considered as a zoonotic pathogen (3, 5). Each year, it is responsible for 7-20% and 3-

15% mortality in nursing and weaned piglets, respectively (6). Treatment of RV infection is only possible through fluid and electrolyte replacement, as no specific antiviral therapy is available (7).

1 1.1.2 The structure of RV

With the development of imaging technology, such as X-ray crystallography and single- particle reconstructions of cryo-electron microscopy images, researchers were able to show the structures of infectious RV particles to near-atomic resolution (8-10). There are three concentric layers, made from 6 types of RV structural proteins (VPs), that constitute the icosahedral infectious viral particle (10, 11). The outermost layer of the triple-layered particle is made up of VP7 and VP4 (Figure 1.1), which play critical roles in cell attachment and entry (12). VP7 is a 34kDa glycoprotein, while VP4 is an unglycosylated protease-sensitive protein of 85 kDa (13, 14). VP4 forms the spikes of the viral particle which facilitate cell binding and can be cleaved by trypsin into VP5 (58 kDa) and VP8

(27 kDa) proteins (14-18). Studies have indicated that the cell attachment protein VP8 might be related to RV host-restriction and pathogenicity, while VP5 might be involved in the virus-cell membrane fusion (10, 12, 19-21). The middle layer of the viral particle is composed of VP6 (45 kDa) which contacts with VP2 (95 kDa) and attaches to VP7; moreover, VP6 allows VP4 docking deep into the viral middle layer to prevent VP4 dissociation (Figure 1.1) (12, 14). The inner layer, also called the inner core, is primarily composed of VP2 which surrounds the 11 segment double-stranded RNA (dsRNA) genome (Figure 1.1) (9, 12). VP1 (125kDa) and VP3 (88 kDa) are located in the inner core (Figure 1.1) (14, 22). Unlike the other 4 viral proteins, they are not part of the viral particle structural composition; instead, VP1 and VP3 are an RNA polymerase enzyme and a guanylyl transferase, respectively (22, 23).

Additionally, RV has 6 nonstructural proteins (NSPs) that have unique functions during viral replication (24). NSP1 is an RNA-binding protein that is not required for viral 2 replication in vitro (25). However, NSP1 can suppress host innate immune responses by interacting with retinoic acid inducible gene I, inducing degradation of IFN regulatory factor 3, etc. (26, 27). NSP2 is also an RNA-binding protein, but it has different functions from NSP1 (24). NSP2 can prompt the formation of viroplasm-like structures with the cooperation of NSP5 and facilitates RNA packaging (28, 29). NSP3 is involved in viral mRNA translation and blockage of host cellular protein synthesis (30-32). Because RV mRNAs have a 5’ cap structure, but lack 3’ poly(A) tails, NSP3 is necessary to bind to the viral mRNAs 3’ ends and interacts with the eukaryotic initiation factor 4GI (eIF4GI) to initiate viral mRNA translation (24, 31, 33). Furthermore, the RV NSP3 homodimers have 10 times higher affinity with eIF4GI than poly(A) binding protein (PABP) that substitute the PABP-poly(A) interaction in the initiation of translation (32, 34). NSP4 is a multifunctional viral enterotoxin that is essential for RV replication, transcription and morphogenesis and is associated with virus virulence (24, 35, 36). Studies indicate that

NSP4 disrupts intracellular calcium homeostasis and limits the activity of intestinal brush border disaccharidases, resulting in diarrhea (35, 37-39). As previously described, the interactions between NSP5 and NSP2 is indispensable in the formation of viroplasm (28).

Further studies demonstrated that NSP5 also interacts with VP2, the major component of the inner core of the viral particle, and this interaction influences the inner core assembly and may also be involved in RNA encapsidation (40). Other recent studies indicate that

NSP5 can interact with proteins or RNAs other than NSP2 and that NSP5 may play other roles during viral replication (41). NSP6 is a nucleic acid binding protein, but its function during viral replication is still under investigation. Recent data suggest that NSP6 may be involved in RNA synthesis and replication in the viroplasm because there is evidence 3 demonstrating that NSP6 interacts with NSP5 and is distributed in the viroplasm (42, 43).

More studies are required to confirm the role of NSP6 during viral replication.

RV has 11 segments of dsRNA in its genome, surrounded by the inner core, that encode for 12 proteins, 6 VPs and 6 NSPs (44). The genome segments are named from segment 1 to segment 11 in the order from the largest genomic size to the smallest size (44).

Segment 1 to segment 10 code for VP1, VP2, VP3, VP4, NSP1, VP6, NSP3, NSP2, VP7,

NSP4, respectively; whereas segment 11 codes for 2 proteins, NSP5 and NSP6 (44, 45).

1.1.3 The classification of RV

The classification of RV is based on VP6, VP7 and VP4. Initially, RVs are grouped, based on VP6 serologic specificity, into different groups and subgroups (46, 47). To date, there are 8 groups of RV, group A to group H (48-50). RVs are further classified depending on the neutralizing specificity of VP7 and VP4 using a binary system that is similar to the dual system for influenza A virus classification (13). The VP7 and VP4 serotypes are designated as G (glycoprotein) serotype and P (protease sensitive) serotype, respectively (13). The neutralization assay used to classify RVs is time consuming and dependent on virus isolation in cell culture and proper immunological reagents that are not always available in all laboratories (13, 47). Therefore, with the development of molecular techniques, classifying RVs based on VP4 and VP7 genotypes has largely replaced the serotype classification, especially for new strains (13, 47). Recently, full genome-based classification of RVs was proposed and has revealed the common origin between human Wa-like and porcine RV strains and human DS-1-like and bovine RV strains (48). This system has since been accepted and implemented for uniform RV 4 classification, as this system is beneficial for detailed analysis of RV interspecies evolution, gene reassortment, and emergence of new RVs by zoonotic and interspecies transmission (47, 48).

1.1.4 The pathogenesis of RV

RVs primarily infect the mature intestinal villus enterocytes in the mid and upper part of the small intestinal villi (51-54). Studies suggest that the entry of RV is a multistep process in which sialic acid, integrins α2β1, αxβ2, αvβ3, α4β1 and heat shock protein 70

(hsp70) are involved (18, 54, 55). Many pathogenesis studies have been conducted using porcine models and the results indicate that RV infections cause a decrease of villi height in the small intestine and a reduction of mucosal thickness (56-58). Studies demonstrate that porcine RV (PRV) strains, OSU and SDSU, can induce villus atrophy and blunting in porcine small intestine (52, 54, 57). Pathogenesis studies of virulent human RV (HRV)

Wa G1P[8] in a neonatal gnotobiotic (Gn) pig model have been conducted in our lab.

Loss of normal mature absorptive cells and detachment of absorptive cells from their basement membranes were observed in the duodenum and jejunum of HRV Wa- inoculated neonatal Gn pigs (58).

The primary clinical sign of RV infection in young children and animals is watery diarrhea (59). Studies have been conducted in a variety of animal hosts to reveal the mechanisms of RV-induced diarrhea. There are several possible pathophysiological mechanisms that may contribute to the watery diarrhea. The first possible reason is the histological changes in the small intestine resulting in a malabsorptive diarrhea (53, 54,

60, 61). RV infection kills mature enterocytes resulting in decreased digestive and 5 absorptive capacities of the small intestine; while NSP4 damages the tight junctions between epithelial cells and disrupts gut integrity (51, 61, 62). A second mechanism based on the role of NSP4 as a viral enterotoxin, but only shown in mouse models, is the disruption of chloride and calcium homeostasis leading to secretory diarrhea (53, 59).

Studies indicate that NSP4 can mediate the secretion of chloride and calcium that trigger the release of water, peptides and cytokines from enterocytes (53, 54, 59, 63, 64). A third mechanism, is the activation of enteric nervous system and central nervous system (again demonstrated only in mice), inducing increased fluid and electrolyte secretion (65, 66).

Villus ischemia is another possible mechanism that contributes to RV-induced diarrhea

(61, 63). Therefore, there are multiple mechanisms, including the effects of the virus infection and the host responses that contribute to RV diarrhea.

1.1.5 RV vaccines for humans and animals

Treatment of RV infection is only possible by replacement of fluids and electrolytes, as no antiviral therapy is available (7). Therefore, effective RV vaccines are crucial to prevent morbidity and mortality in both children and young animals (7, 67). The development of RV vaccines started in the mid-1970s. Initially, researchers thought that live animal RV strains were less virulent in humans than in their original hosts and that those strains might mimic the immune response to natural infection and offer protection against RV diarrhea in children. However, some monovalent vaccine candidate strains failed to induce strong protection against heterologous strains (68). These data led researchers to study multivalent vaccines that carry several important VP7 serotypes (67,

68). RotaShield, a rhesus RV tetravalent vaccine, was the first multivalent, live, oral 6 reassortant vaccine developed (67). This multivalent vaccine contained 3 rhesus-human reassortant strains and 1 rhesus RV (RRV) strain representing serotypes G1 to G4 (69).

The efficacy of RotaShield was tested in many countries, including the United States, and was shown to be highly effective in preventing severe diarrhea (67, 70, 71). This vaccine was licensed in the United States in August 1998, but was withdrawn from the market 14 months after the introduction, due to a potential high risk of intussusception after the vaccination (67, 72, 73). However, later studies demonstrated that the incidence of intussusception was associated with the age at which infants received the first dose of the vaccine, not the RotaShield vaccination (74, 75).

Currently, there are two licensed vaccines for humans: RotaTeq and Rotarix, both of which are oral, live attenuated vaccines. RotaTeq is a pentavalent human-bovine reassortant vaccine that includes four reassortants expressing VP7 proteins from G1, G2,

G3, G4 HRV parental strains with the attachment protein (P7[5]) from bovine RV (BRV) parental strain (WC3) and a fifth reassortant virus with the VP7 protein of serotype G6 from BRV parental strain and attachment protein (P1A[8]) from the HRV parental strain

(67). Rotarix, is a monovalent vaccine (G1P[8]) that represents the most common VP7 and VP4 antigen combination for HRVs (67, 76). Both licensed vaccines show high efficacy for protection of children from severe RV disease in developed countries, but less efficacy in developing countries (77-79). Also, divergent and heterologous RV strains may diminish vaccine efficacy, such as the emerging G9 and G12 strains, posing new challenges to current vaccines (80, 81). Therefore, it is important to conduct surveillance studies in humans and animals and to improve vaccine efficacy for developing countries. 7 As RV also causes diarrhea in young livestock that results in large economic losses due to morbidity and mortality in piglets and calves, the development of effective RV veterinary vaccines remains important (6). The primary strategy for the prevention and control of RV infections in young livestock is passive immunization (82). Studies show that the enhanced colostral and milk antibody titers to RV in mothers after vaccination with maternal RV vaccines can protect young animals against RV infection and disease

(82). There are several commercial vaccines available for piglets and calves, most of which are maternal RV vaccines. Guardian® (Merck Animal Health, Kenilworth, NJ,

USA) and ScourGuard® 4K (Pfizer Animal Health, Florham Park, NJ, USA) are bovine

RVA vaccines with two G-types (G6 and G10) of inactivated BRV that are used in pregnant cows and heifers. The protection of newborn and suckling calves depends on passively acquired antibodies in the colostrum and milk. Using similar mechanisms as for bovine RVA vaccines, there is one USDA-licensed vaccine ProSystem® RCE (Merck

Animal Health, Kenilworth, NJ, USA) with two serotypes of porcine RVA, G4 and G5, that is used in pregnant sows and gilts to induce high RV antibodies in colostrum and milk for piglets. Another PRV vaccine called ProSystem® Rota (Merck Animal Health,

Kenilworth, NJ, USA), is a modified live virus vaccine that is directly used in piglets before weaning to induce immunity to protect against RV infection. However, a recent study demonstrated that the A2 strain (previously identified as a G4 PRV strain) in a commercial live PRV vaccine was in fact a G9 strain (83). If so, the administration of this vaccine could have introduced G9 strain into the swine population that had no herd immunity against G9. This may have contributed to the emergence and subsequent spreading of the G9 strains in swine in the U.S. 8

1.2 Epidemiology of RV

Group A RV (RVA) is the most prevalent cause of RV diarrhea in both humans and animals worldwide (84). Overall, there are at least 27 G genotypes and 37 P genotypes of

RVA (85, 86). G1P[8], G2P[4], G4P[8], G3P[8], and G9P[8] are the most common circulating RVA strains in humans worldwide (87). G6, G8 and G10 combined with P[1],

P[5] or P[11] are the common RVA in cattle, while G3, G4, G5, G9 and G11 combined with P[6] or P[7] are the most prevalent RVA in pigs (88). There are major geographical variations and annual fluctuations in RVA diversity in both humans and animals (87, 88).

1.2.1 The epidemiological study of RVA in humans

Collecting data from 113 eligible articles from 2000 to 2011, Kawai et al., summarized that the 4 most prevalent RV strains in Asia were G1P[8] (23.6%), G3P[8] (18.9%),

G2P[4] (11.8%) and G9P[8] (7.4%) (Table 1.1) (89). However, they also found that the distribution of RV strains varied distinctly in countries such as China, India, and Vietnam

(89). Recent hospital-based surveillance of RV diarrhea conducted in China indicated that the most common strain was G3P[8] followed by G1P[8] (90-94). The surveillance study also noticed that the dominant RV strains fluctuate from year to year (90, 92). The studies also mentioned that the most common RV genotype was G1P[8] in China until 2000, but shifted to G3P[8] since 2001 (90). However, the frequency of G3P[8] was declining year by year, and the prevalent genotype had again shifted from G3 to G1 in 2011 (92). This trend was also observed in Japan, but Vietnam had the opposite situation where the proportion of G3P[8] increased (89). 9 The 5 most common HRV strains, G1P[8], G2P[4], G4P[8], G3P[8], and G9P[8], that covered 88% of typed strains worldwide between 1989 to 2004, comprised only 36.5% of the typed strains in Africa from 1997 to 2006 (87, 95). The published data collected from

1997 to 2006 showed that the most prevalent genotypes in Africa were G1P[8] (17.4%),

G2P[6] (9.6%), G8P[6] (9.4%), and G3P[8] (7%) (Table 1.1) (95). Another surveillance study from June 2006 through December 2008 in 11 African countries found a different

RV strain diversity compared to the previous review. In this later surveillance study, the 4 most dominant strains were G1P[8] (22%), G2P[4] (7%), G9P[8] (7%), and G8P[6] (5%)

(Table 1.1) (96). Those data suggested a greater circulating strain diversity in Africa than other areas of the world (95, 96). Moreover, the diversity varied markedly from country to country in Africa. For example, the samples from April 2004 to September 2005 in

Maua, Meru North district in Kenya showed that the most prevalent VP7 serotype was

G9 (47.1%) (97). Another 2-year surveillance study from 2008-2009 in Blantyre, Malawi, showed that G1P[8] (39.5%) was the first dominant RVA strain and G12P[6] (23.2%) was the second predominant strain (98).

RV surveillance study in Europe from 2005 to 2009 showed that the prevalent genotypes of RVs circulating in Europe were the same as the 5 most common genotypes worldwide, but in different percentages (87, 99, 100). In those two surveillance studies from 2005 to

2008 and 2006 to 2009, G1P[8] was the predominant G-P combination confirmed for almost 50% of the RVA-positive samples (Table 1.1) (99, 100). Of note, the second prevalent strain shifted from G9P[8] in the 2005-2008 study to G4P[8] in the 2006-2009 study, suggesting the transient prevalence of G9 in Europe and the annual fluctuations of

RV diversity (Table 1.1) (99, 100). 10 Overall, G1P[8], G2P[4], G3P[8], G4P[8] and G9P[8] comprised the majority of circulating RVs in North America (101, 102). However, the diversity was continuously changing year by year in the United States and Canada (102-104). A 9-year RV surveillance study in United States from 1996 to 2005 indicated that G1P[8] strains were still the most prevalent strains in the United States, while emerging strain G9P[6] was more common than G4P[8] and was the fourth predominant strain in the study (101).

Comparing annual results of RV diversity from 2006 to 2009, Payne et al. noticed that

G12P[8] emerged in 2007 and was detected in one third of the RVA positive samples.

Interestingly, G12P[8] was rarely detected in samples from 2006, 2008 and 2009 (103).

Moreover, they noted that G1P[8] was not the most prevalent combination in 2009, while

G3P[8], G2P[4] and G9P[8] became the most frequently detected strains (103). Those data suggested wide temporal and geographical fluctuations in RVA epidemiology in the

United States. The RV diversity in Canada had similar trends with substantial shifts year by year, especially among G1P[8], G3P[8] and G9P8] strains (102).

In Latin America, G1P[8] was predominant combination, although its prevalence was less than 50% (105, 106). Before 2004, G1P[8], G2P[4], G3P[8], and G4P[8] constituted the majority of RV cases in Latin America (105). However, G9P[8] rapidly became the second prevalent genotype combination during 2005-2007 (106). In addition, G8P[8], an unusual strain, became the fourth dominant circulating strain (106).

An annual RV surveillance study in Australia has been conducted and reported since

1999 (Table 1.1) (107). From 1999 to 2007, the annual RV surveillance only reported the

G serotype percentage while the reports from 2008 started to show both the G and P genotypes percentages. The data from 1999 to 2013 indicated that G1 was the most 11 prevalent genotype of circulating RVs, intermittently substituted by G2, G9 or G12 (108-

112). Those data highlighted the continual fluctuations in RV diversity in Australia.

When the data was separately analyzed from 1999 to 2007 and from 2008 to 2013, it showed that G1 (43.4%) was the most prevalent serotype of circulating RVs in Australia from 1999 to 2007 and G2 serotype only represented 6.2% of the circulating RVs (107-

109, 113-118). However, G2P[4] (30.8%) became the most common genotype combination in the data from 2008 to 2013, while G1P[8] strains were the second prevalent genotype (110-112, 119, 120). Interestingly, G12 was first identified in 2005 in

Australia and was rarely detected until 2012 when G12P[8] represented the third most common genotype (116, 120). In 2013, G1P[8] represented only the fourth most common genotype combination, while G12P[8] became the predominant type of strain circulating in Australia (112).

Overall, the most common RVA genotype worldwide is G1P[8], with G2P[4], G3P[8],

G4P[8] and G9P[8] composing the other prevailing circulating RVA types worldwide

(87). As the emerging G9 and G12 strains are becoming more prevalent, there is growing concern about whether introduction of vaccines (RotaTeq and Rotarix) resulted in selective pressure, altering the epidemiology of the circulating RV genotypes (112, 120-

122). However, to our knowledge, there is no evidence showing that vaccines drive the shift in circulating RVA strains in humans (123-125).

1.2.2 The epidemiological study of RVA in animals

In addition to being the major cause of RV infections in human, RVA is also responsible for the majority of RV infections in domestic animals (126). The diversity of bovine and 12 porcine RVAs is high, with substantial geographical variations and temporal fluctuations

(88). There were at least 12 G and 11 P types of bovine RVAs identified and among them, the combinations of G6, G8 and G10 in association with P[1], P[5] and P[11] account for the most RVA cases worldwide (88). In addition, G6 and G10 serotypes have been found to be the most common strains in beef and dairy herds, respectively (126). According to the study of Papp et al., G6 and P[5] were the most prevalent G and P types of bovine

RVA strains worldwide, but the other predominant G and P types varied in different continents (88).

At least 12 G types and 13 P types of porcine RVA have been identified (88, 127). G3,

G4, G5 in association with P[6] and P[7] were the most common porcine RVA strains worldwide (Table 1.2) (88). G5P[7] was the dominant combination among porcine RVAs, followed by G4P[6] (88). Of note, geographical diversity and temporal fluctuations also exist in the genotypes of porcine RVA strains (49, 88, 126).

The epidemiological study of RVA in humans and animals and further phylogenetic analysis emphasized the zoonotic potential of RVAs (3, 84). Increasing evidence has demonstrated the capacity of RVA for interspecies transmission and the occurrence of

RVA genomic segment reassortments (128-133). RVs of porcine or bovine origin, and porcine-bovine reassortants have been identified in humans in many countries (129, 130,

132, 133). Furthermore, based on the full genome-based classification of RVs, common origin between human Wa-like and porcine RV strains and human DS-1-like and bovine

RV strains were discovered (48). Collectively, these data suggest that livestock may serve as potential reservoirs for human RV infections.

13 1.3 The host immune responses to RV infection

The host immune system is a network of cells, tissues, and organs that protects the host from infectious agents and consists of 2 components – innate and adaptive immunity. The innate immune response is the first line of the host defense that includes skin, lysozymes, proteases, macrophages, dendritic cells (DCs), natural killer cells (NK cells), etc. (134).

Innate immune responses are not pathogen-specific; whereas the adaptive immune response, which includes B cells, T cells and memory cells (memory B and T cells), is highly specific to the different pathogens (134). During RV infection, the host defense system is activated to clear RVs, while RVs also have strategies to invade the host cells and escape the immune response.

1.3.1 Host innate immune responses to RV infection

The germ line-encoded pattern recognition receptors (PRRs) are the sensing part of the innate immune system that recognize conserved microbial structures, known as microbe

(or pathogen)-associated molecular patterns (MAMPs or PAMPs). The interaction between MAMPs and PRRs initiates the transcription of genes that encode proinflammatory cytokines/chemokines, type I interferons (IFNs), and antimicrobial proteins (135). There are several types of PRRs, such as Toll-like receptors (TLRs), scavenger receptors, C-type lecithin receptors, retinoic acid-inducible gene 1 (RIG-1)- like receptors (RLRs), nucleotide-oligomerization domain (NOD)-like receptors (NLRs) and cytosolic DNA receptors (136-138). The mRNA expression of TLRs 2, 3, 4 and 8 in peripheral blood mononuclear cell (PBMC) from children with acute RV diarrhea were increased and had significant association with increased IFN-γ responses during the 14 illness (139). Another study demonstrated that TLRs 7 and 9 were involved with type I

IFN responses in human plasmacytoid DCs (pDCs) after exposure to RRV or SA11 (140).

RRV also triggered the mRNA expression of TLR2, 3, 7 and 8 in HT-29 cells (human colorectal adenocarcinoma cell line) (141). Studies using Tlr3-/- mice and murine macrophage cell line RAW 264.7 found that TLR2 and TLR3 were involved in innate immune responses during RV infection (142, 143). In our lab, we found that TLRs 2, 3 and 9 were involved in Gn pig immune responses to HRV infection (144). Melanoma differentiation-associated gene 5 (MDA5) and RIG-1 also contributed to the recognition of RV in human intestinal epithelial cell lines (HCA-7 and HT-29) and murine bone marrow-derived macrophages (145, 146). Recent studies demonstrated that TLR5 and

NOD-like receptor C4 mediated the production of IL-22 and IL-18 which were involved in the prevention and cure of RV infection in mice (147).

Immune cells, such as dendritic cells (DCs) and macrophages, are activated upon RV recognition by PRRs, and higher levels of IFNs and proinflammatory cytokines are produced rapidly (146, 148, 149). IFNs are a type of innate cytokine that can bind to different cell-surface receptors, induce the expression of antiviral host effector molecules, and help uninfected cells to establish an antiviral state in mouse models or cell lines (150).

For example, the systemic treatment by IFN-λ has shown protection against RV infection in suckling mice (151). In addition, IFNs can influence the adaptive immune response through regulating cell growth, differentiation and apoptosis (150). Type I and III IFNs protected against RV infection via inhibiting RV replication in suckling mice and promoting the effector cells in human adaptive immune responses, such as effector T cells (152, 153). 15 Many studies have been conducted to assess the effects of these cytokines during RV infection. An in vitro study showed that IFN-γ and IL-1, but not IFN-α, inhibited

RRV/HRV entry into human Caco-2 and HT-29 cells (154). However, in a sucking mouse model, both type I IFN receptor and IFN-γ knockout mice developed similar RV- induced diarrhea compared to immunocompetent mice (155). Exposure of gene knockout

IFN-deficient suckling mice to various strains of RV demonstrated that the function of

IFNs to inhibit RV replication in suckling mice varied among different homologous and heterologous RV strains (152). In RV-challenged neonatal and weanling pigs, the RV excretion score was decreased by administering natural human IFN-α in a dose- dependent manner (156). However, our lab noted that increased IFN-α secretion by immune cells did not result in more efficient control over HRV infection and replication in the Gn pig model (157). The levels of proinflammatory cytokines IL-6 and IL-12 in serum were increased following infection with both virulent HRV Wa (virHRV) and attenuated HRV Wa (attHRV) strains; whereas, a higher percentage of pigs had IFN-γ and IL-10 responses after virHRV infection than after attHRV or mock infection (158).

The investigators suggested that higher protection rates might be associated with more balanced Th1- and Th2-type responses during HRV infection in Gn pigs (158). In addition, others found RRV induced the production of the proinflammatory cytokine IL-6 in mouse bone marrow-derived macrophages that stimulated immune responses (146).

Innate immunity influences the adaptive immune responses via the established cytokine milieu produced by innate immune cells during the early stages of RV infection (134).

Furthermore, activated DCs can impact adaptive immune responses via regulating RV- induced T cell and B cell responses. The in vitro interactions of RRV/HRV with human 16 peripheral blood-derived conventional DCs (cDCs) were studied by Narvaez et al. (2005).

The data showed that RVs did not inhibit the maturation of immature cDCs or change the maturation marker expression on mature cDCs (159). In addition, the interaction between cDCs and RV induced human naïve allogeneic CD4+ T cells to secrete Th1 cytokines

(159). In human blood mononuclear cells (MNCs), plasmacytoid DCs (pDCs) were the main source of IFN-α production during RRV infection and in the absence of pDCs, the frequency of RV specific IFN-γ producing T cells decreased (160). Studies of human pDC in vitro and in vivo murine models of RV infection demonstrated that pDCs could recognize RV and produce type I IFN (140). Using human in vitro and murine in vivo models, pDCs were found to promote RV-induced human and murine B cell responses

(161). Moreover, in mouse models, the small intestinal DCs promoted the expression of gut homing receptors on B and T cells (162, 163). Our lab demonstrated that intestinal pDCs were the main producer of IFN-α during HRV infection in Gn piglets and the frequencies of intestinal IFN-α+ pDC were not affected by increased doses of HRV in Gn piglets (164). In addition, live RRV induced type I IFN and TNF-α secretion from murine

RAW 264.7 cells (macrophage cell line), and the RRV-exposed RAW 264.7 cells could induce neutrophil migration via enhancing chemotaxis protein expression (165). Besides

DCs and macrophages, NK cells, a component of innate immunity, also play an important role during virus infection as they can recognize and kill the infected cells (166). In adult mice, the mature NK cells were able to eliminate RRV-infected cholangiocytes shortly after RV infection, while in neonatal mice, the NK cells were less mature and unable to clear RRV-infected cholangiocytes (167). Further studies indicated that NK cells played a role in the progression of liver disease of experimental biliary atresia (induced by RRV) 17 in newborn mice (168). More studies are required to investigate the role of NK cells in

RV infection.

1.3.2 Host adaptive immune response to RV infection

T cells and B cells, components of adaptive immunity, play important roles in clearance of RV primary infection and protection against re-infection. Through a case-control study in children aged 4-35 months with clinical rotavirus diarrhea, researchers found that serum neutralizing antibodies were not serotype-specific and suggested that other factors might be involved in immune responses to RV infection (169). Later, fecal RV-specific

IgA was proven to be associated with the protection against RV infection in children

(170, 171). To further study adaptive immune response to RV, animal models such as mice and pigs were established to examine mechanisms of RV protection (172, 173).

Two strains of B cell-deficient mice, JHD and µMT (JHD mice cannot produce functional

Ig heavy-chain, while µMT mice have a mutation in the µ-chain constant region) were used to demonstrate that both antibody and CD8+ cells were involved in clearance of murine RV (EDIM) infection (174). Extensive studies in mouse models indicated that B cells played a role in clearance of primary RV infection in a T cell-independent manner via production of RV-specific intestinal immunoglobulin A (IgA) and were necessary for the development of immunity against RV reinfection. Although cytotoxic T cells (CD8+

T cells) mediated RV clearance, they were not essential, and led to only short-term protection against reinfection (175-178). Furthermore, other studies using immunodeficient and B cell-deficient mouse models illustrated that CD4+ T cells alone could mediate the clearance of primary RV infection (179, 180). Recently, an expansion 18 of CD4+CD25+Foxp3+ regulatory T cell (Treg cell) population has been observed in mice after murine RV (EC strain) infection; however, further studies indicated that the depletion of Treg cells did not affect virus shedding and IgA RV-specific responses (181).

A series of studies on B cell and T cell responses to HRV in the Gn pig model have been conducted in our lab. Isotype-specific antibody-secreting cells (ASCs) in intestinal

(duodenal and ileal lamina propria and mesenteric lymph nodes) and systemic (spleen and blood) lymphoid tissues were enumerated using enzyme-linked immunospot assays after HRV challenge. Intestinal IgA ASC responses were reported to correlate with protective immunity to HRV in Gn pigs (182). Furthermore, a positive correlation between protection after primary virHRV infection and serum and intestinal IgA antibody titers has been reported (183). Intestinal IgGs also provided protective effects against

HRV diarrhea; whereas, neutralizing antibody titers in serum showed no correlation with protection rates (183). T cells also play an important role in protective immunity to HRV.

Studies showed that the frequencies of HRV-specific IFN-γ producing CD4+, CD8+ and

CD4+CD8+ T cells correlated significantly with protection rates against HRV-induced diarrhea in Gn piglets (184). In addition, our lab found that the probiotics Lactobacilli rhamnosus strain GG ATCC 53103 and Bifidobacterium animalis subsp. Lactis Bb12 induced higher protection against HRV challenge in Gn piglets and this higher protection was coincided with higher frequencies of ileal Treg cells (185).

1.3.3 Escape strategies of RVs

The host has developed a complicated and highly effective immune system to clear RV along with other pathogens; however, RVs have evolved multiple strategies to escape 19 host immune responses to ensure their survival. Studies indicated that NSP1 and NSP3 of

RV play a key role in inhibiting host innate immune responses (24, 186). The NSP1 of rotavirus could mediate the degradation of interferon-regulation factor 3 (IRF3), IRF5 and IRF7 which regulate the expression of IFNs that help block RV replication and infection (186). NSP1 also inhibited the activation of NF-κB and blocked signal transducer and activator of transcription (STAT) signaling pathways (186). Studies demonstrated that even after STAT activation, RRV NSP1 could bind to the nuclear import machinery to constrain IFN-induced STAT nuclear translocation in MA104 cells

(187). Barro and Patton (2005) determined that the NSP1 of SA11 RV strain interacted with and degraded IRF3 via a proteasome dependent pathway in the MA104 cells (27).

SA11 RV NSP1 also induced the degradation of IRF7 and reduced IFN-α and IFN-β gene expression (188, 189). Moreover, interactions between SA11 RV NSP1 and IRF5 down- regulated proinflammatory cytokine gene expression and prevented cell apoptosis (188).

Additionally, RV NSP1 could reduce host IFN responses via other mechanisms besides degradation of IRFs (26, 190). Qin et al. (2010) showed that the NSP1 of RV OSU strain was incapable of degrading the IRFs, but this strain could still inhibit host IFN responses by inhibiting the RIG-1-mediated type I IFN responses (26). Another study determined that NSP1 of several HRV strains (Wa, K8, DS-1, and B37) blocked the NF-κB pathway via degrading β-TrCP (a protein required for IκB degradation and NF-κB activation), but not IRF3 (190). Those data suggest that the NSP1 from different RV strains can inhibit the host IFN responses through multiple pathways.

RV NSP3 impairs the innate immune response at the translational level. Binding to eukaryotic translation initiation factor 4 gamma (eIF4G) with greater affinity than PAPB, 20 NSP3 increased the translation of viral transcripts and reduced host cellular protein synthesis (24, 191). The decreased host protein synthesis resulted in reduced IFN production. This mechanism also interrupted the unfolded protein response to prevent endoplasmic reticulum stress-mediated cell death and allowed the efficient replication of virus in the RRV-infected MA104 cells (192). Moreover, RRV and HRV Wa could block the expression of phosphorylated p65 (an NF-κB-driven reporter gene) and the nuclear accumulation of NF-κB to perturb innate immune responses (186, 193).

Recently, Rojas et al. (2010) discovered that RV could induce protein kinase R (PKR), involved in the phosphorylation of eukaryotic initiation factor 2 (eIF2), to inhibit host protein synthesis through altering the function of eIF2. They also found that the mRNA of RV could be translated and the viral protein synthesis was not influenced by eIF2 phosphorylation (194). They suggested that this strategy was a RV evasive mechanism to overcome host immunity. However, the reason why RV can still synthesize viral proteins under such conditions is unknown. A study by Gac et al. (2010) noted a possible evasive mechanism of RV in the early viral infection phase: RV infection increased mitochondrial superoxide dismutase expression and decreased reactive oxygen species production. They suggested that this was a RV evasive mechanism because reactive oxygen species promoted the death of infected cells whereas superoxide dismutase could decrease the concentration of reactive oxygen species to prolong cell survival and to allow the viral particles to accumulate in host cells (195). Genetic mutations, which may cause VP7 and VP4 structural variations, are also a kind of viral mechanism which helps to avoid host antibody protection (84, 196).

21 1.4 Probiotics for prevention of RV diarrhea and enhancement of vaccines

Lilly and Stillwell first introduced the term of “probiotics” in 1965 (197). Currently, probiotics are defined as “live microorganisms which when administered in adequate amounts confer a health benefit on the host” (198). Many studies have been conducted to understand the mechanism of these health effects of probiotics. Researchers have discovered that probiotics can promote both the innate and adaptive immune responses.

However, these data only partially explain the significant effects of probiotics on RV infection. The mechanisms involved are not fully elucidated and further studies are needed.

1.4.1 The protective effect of probiotics on RV diarrhea

A series of papers published between 1988 and 1998 introduced some possible benefits of probiotics, including prevention of diarrheal disease, reduction of serum cholesterol, and prevention of carcinogenesis and tumor growth (199). A meta-analysis of randomized controlled trials demonstrated that probiotics (Saccharomyces boulardii or

Lactobacillus GG or a combination of Bifidobacterium lactis and Streptococcus thermophilus) could reduce the risk of antibiotic-associated diarrhea in children (200).

Evidence was introduced in a review that probiotics, especially Saccharomyces boulardii and Lactobacillus GG, can prevent diarrhea acquired in day-care centers or in hospitals, as well as preventing antibiotic-associated diarrhea (201). Probiotics also have been reported to have a detoxification effect and that lactic acid bacteria and bifidobacteria can interact directly with viruses in food and water as well as toxins and toxin-producing microbes (202). 22 Many in vitro and in vivo experiments were conducted to verify the protective effects of probiotics in RV infection (203-205). Majamaa et al. (1995) compared different lactic acid bacteria for their protective abilities in children with acute RV gastroenteritis and they noted that some strains promoted serum and intestinal immune responses and shortened the duration of RV diarrhea, particularly Lactobacillus casei subsp. casei strain

GG (206). Not satisfied with studying the known probiotic bacteria, researchers also wanted to find new strains. Recently, a novel probiotic strain has been discovered –

Bifidobacterium longum subsp. infantis CECT 7210 strain which was isolated from infant feces – that can inhibit RV Wa strain (ATCC VR-2018) in vitro replication and potentially protect the host against RV infections (207). Collectively, these data show that probiotics can provide many benefits to the host.

Probiotics play a protective role in RV infections in vivo. The most significant protective effects of probiotics on RV infection is decreasing RV shedding and shortening the duration of acute diarrhea (208). The data show that Lactobacillus GG and

Saccharomyces boulardii are two of the most effective strains in probiotic treatment of

RV infectious diarrhea (201). The distribution and frequencies of monocytes/macrophages and dendritic cells in neonatal gnotobiotic (Gn) pigs after human RV infection, with or without probiotic colonization, were evaluated to investigate the protective effects of probiotics (149). According to Zhang et al. (2008c), the lactic acid bacteria, Lactobacillus acidophilus and L. reuteri [orally fed pigs at 3, 5, 7 and 9 days of age with 103, 104, 105 and 106 colony forming units (CFU), respectively], could limit the inflammation induced by human RV infection to protect the intestinal epithelium from being damaged by inflammatory cytokines. In addition, our lab 23 established the colonization of Lactobacilli rhamnosus GG (LGG) and Bifidobacterium animalis subsp. lactis Bb12 (Bb12) in neonatal gnotobiotic (Gn) pigs by orally feeding 1

× 105 CFU of Bb12 at day 3 of age and feeding LGG and Bb12 at 1:1 ratio (1 × 105 CFU or 2 × 105 CFU of each per pig) at day 5 of age (185, 209, 210). We found that the colonization of LGG and Bb12 in neonatal Gn pigs reduced diarrhea scores and virus shedding, compared to the uncolonized pigs, after virulent HRV (virHRV) challenge.

LGG and Bb12 colonization promoted immunomaturation in intestinal tissues and blood of Gn piglets post-challenge, such as increased MHC class II expressing mononuclear cells and conventional DCs in the intestinal tissues, as well as higher ileal regulatory T cells (Treg cells) (185, 209). In addition, the colonization promoted intestinal IgA antibody titers and induced higher frequencies of HRV-specific IgA antibody secreting cells in the intestine (210).

The probiotic protective effect is not only strain-dependent, but also dose-dependent and nutrition-dependent (206, 211, 212). Fang et al. (2009) evaluated the quantitative reduction of RV shedding in children after different doses (receiving 2 × 108 CFU/day or

6 × 108 CFU/day for 3 days) of Lactobacillus rhamnosus 35 and found that the effect of

Lactobacillus rhamnosus 35 was dose-dependent. An experiment was performed to detect host responses to probiotics (Lactobacillus reuteri DSM 17938 and L. reuteri

ATCC PTA 6475, 108 CFU/day from days 5 to 14 of age) in RV-infected neonatal mice of differing nutritional status (overweight, normal and underweight) (212). They noted that nutritional status could influence the enterocyte proliferation and migration, the concentration of proinflammatory cytokines, and RV-specific antibodies that were correlated with the magnitude of reduction of RV diarrhea duration. It is well known that 24 probiotics have protective effects on RV infections, although the mechanisms are not clear. The optimal strain and dosage for treatment in the context of various host species also requires further research.

1.4.2 The role of probiotics as adjuvants in RV vaccination

Many studies have been conducted to test the immunomodulatory effect of probiotics and to verify whether probiotics can influence vaccine responses. Kukkonen et al. (2006) conducted a randomized placebo-controlled double-blind trial to test the effect of probiotics (a mixture of probiotics which contained Lactobacillus rhamnosus GG ATCC

53103, L. rhamnosus LC 705, Bifidobacterium breve Bbi99 and Propionobacterium freudenreichii spp. Shermanii JS) on antibody responses of infants to vaccines

(diphtheria, tetanus and Haemophilus inflenzae type b vaccines). They noted that giving mother twice a day with one capsule containing the mixture of probiotics (Lactobacillus rhamnosus GG ATCC 53103 5 × 109 CFU, L. rhamnosus LC 705 5 × 109 CFU,

Bifidobacterium breve Bbi99 2 × 108 CFU and Propionobacterium freudenreichii spp.

Shermanii JS 2 × 109 CFU) 4 weeks before expected delivery and giving infants one opened capsule daily containing the same mixture of probiotics for 6 months after birth could improve specific antibody responses to Haemophilus influenza type b vaccine in atopy prone infants (213). Another experiment was conducted to verify the effect of probiotics on specific antibody responses to infant Hepatitis B vaccine (214). According to the data, Soh et al. (2010) reported that probiotics (Bifidobacterium longum BL999 and

Lactobacillus rhamnosus LPR), given at least 2.8 × 108 CFU per day to infants for 6

25 months after birth, promoted specific antibody responses in infants given Hepatitis B vaccine.

The probiotic beneficial effects on RV vaccination have also been investigated. In studies from our lab, Zhang et al. (2008b) found that Lactobacillus acidophilus (pigs were orally fed with 103, 104, 105, 106 and 106 CFU of at days of 3, 5, 7, 9, 11 of age, respectively) enhanced the immunogenicity of an oral RV vaccine in gnotobiotic (Gn) pigs and suggested it might be used as an oral adjuvant for RV vaccines in neonates. They detected the virus-specific B and T cell responses which were induced by a human oral

RV vaccine (Wa strain) with or without Lactobacillus acidophilus in neonatal Gn pigs

(215). The frequencies of human RV specific IFN-γ producing CD8+ T cells in ileum and spleen were significantly increased and the titers of human rotavirus specific IgA and IgG antibodies were higher in RV vaccinated pigs with probiotic colonization compared to vaccinated pigs alone. Because probiotic effects on RV treatment are dose-dependent, the variance of dose may influence probiotic adjuvant effects after RV vaccination. Wen et al. (2012) evaluated the frequencies of IFN-γ producing CD4+ and CD8+ T cell and IL-

10 and TGF-β producing regulatory T cells in the Gn pig model of RV vaccination with different and multiple doses of Lactobacillus acidophilus (low dose: 5 feedings, up to 106

CFU/dose vs. high dose: 14 feedings, up to 109 CFU/dose). They reported that low dose of Lactobacillus acidophilus elevated IFN-γ producing T cell responses and decreased

Treg cell responses; whereas, high dose of Lactobacillus acidophilus increased the frequencies of Treg cells compared to the control groups (216). However, it was not clarified how dose affects responses in Gn pigs without a microflora, since the intestinal bacterial load reached an equilibrium in both low and high dose fed Gn pigs. In addition, 26 both low dose and high dose probiotic inoculation did not enhance the protection induced by attenuated HRV vaccine in pigs (216). However, the optimal dose of probiotic remains uncertain or may vary depending on the strain, host and microbial status of the host. Furthermore, the mechanism of the adjuvant effect of probiotics has not been elucidated. More studies are needed to clarify the mechanisms.

1.5 The extraintestinal dissemination of RV

1.5.1 The extraintestinal dissemination of RV

The primary target cells of RV are the mature intestinal epithelial cells (56). However, investigators found that non-epithelial cells were permissive for RV replication in humans and rats (217, 218). Multiple clinical cases showed that RV infections were associated with acute hemorrhagic infantile edema, cutaneous vasculitis, rhabdomyolysis, etc. in infants and children (219). Rotaviral RNA was found in cerebrospinal fluid (CSF) and blood of some RV-induced diarrhea cases (220, 221). Rotaviral antigens VP6, NSP4,

NSP3 and NSP1 were detected in heart, liver and brain using immunohistochemistry

(222). Our lab found that 100% of Gn piglets infected with virulent HRV Wa had transient antigenemia in serum (223). Using a neonatal mouse model, investigators suggested that RV spread outside of the intestine via a lymphatic route, sequentially being detected in the Peyer’s patches, the mesenteric lymph nodes (MLNs), and the peripheral tissues (224).

Previous studies indicated that immune cells are potential target cells for RV replication.

RV-specific proteins have been detected in murine macrophages in both intestinal and extraintestinal tissues (225). Using flow cytometry, NSP4 was detected in RRV-treated 27 adult healthy human PBMC-derived DCs (159). Using strand-specific quantitative reverse transcription-PCR (ssQRT-PCR) and an immunofluorescent assay (IFA), Fenaux et al. detected RRV (+) strand and (-) strand RNA and NSP4 in MLNs, livers, lungs, blood, and kidneys of RV infected newborn mice (226). Moreover, they suggested that

DCs, and potentially B cells and macrophages in the MLNs were the cells supporting RV replication (226). After intragastric inoculation of RRV in five-day-old rat pups, RV antigens and infectious virus were detected in multiple extraintestinal organs, such as liver, lung, spleen, kidney, pancreas, thymus and bladder (218). Moreover, RV was also detected in macrophages from lung and blood vessels suggesting a possible RV extraintestinal dissemination mechanism (218). 2-day-old colostrum-derived Holstein calves were inoculated with RV KJ9-1 strain (a G6P[7] reassortant bovine RVA) and RV antigens were detected in lymphoid cells of MLN, liver, lung and choroid plexus on post- inoculation days 2 to 4 (227). Another study indicated that RRV and HRV Wa strain could differentially infect human B cells in vitro depending on the B cell differentiation state and tissue of origin (228). However, because DCs, B cells and macrophages are professional antigen presenting cells, these cells can take up and process antigen directly from the environment. More detailed studies need to be designed and conducted to verify the capability of RV to internalize and replicate in those immune cells and be released from these cells to infect other cells.

1.5.2 The interaction between RVs and antigen-presenting cells

There are numerous studies regarding interactions between antigen-presenting cells

(APCs) and viruses. Epstein-Barr Virus infected memory B cells and utilized the memory 28 B cells to escape T cell responses (229). Some viruses also employed macrophages and

DCs to help spread from these cells throughout an organism, such as HIV-1 and Ebola virus (230). RV viral antigens and RNA have been found in these APCs, but more studies are required to elucidate if RVs use these APCs to aid in extraintestinal spread.

After treatment with RRV, NSP4 expression in human PBMC-derived immature DCs and poly(I:C)-induced mature DCs was evaluated using flow cytometry by Narváez et al.

(2005) They found that mature DCs were more susceptible to RV than immature DCs, but RV did not induce cell death or inhibit DC maturation (159). Using staphylococcal enterotoxin B (SEB)-treated RRV-infected mature DCs or uninfected cells to stimulate

CD4+ T cells, they showed that frequencies of SEB-activated T cells secreting IFN-γ, IL-

2, IL-10 and IL-13 were similar whether stimulated with RRV-infected DCs or uninfected DCs (159). Another study, using human peripheral pDCs, found that only a small portion of pDCs were susceptible to RRV infection and the majority of human pDCs were resistant to RRV replication (140). Furthermore, they indicated that RRV replication did not inhibit pDC maturation and activation via evaluating CD86 and CD83 expression, respectively; however, RRV replication affected pDC cytokine production

(140). They demonstrated that RRV replication in pDCs impaired IFN-α production and that NSP2 expression in pDCs led to less IFN-α production. A similar trend was observed in IFN-β production (140). These studies indicated that RRV replication in DCs did not modify their capacity to stimulate cytokine secretion in polyclonal T cells, but impaired their secretion of IFN-α and IFN-β (140, 159).

After RRV exposure in vitro, Mesa et al. detected NSP4 in B cells of PBMCs from a human adult who was admitted with gastroenteritis to the emergency room (160). In this 29 study, they reported that human adult B cells, monocytes and DCs were susceptible to the initial steps of RRV and HRV Wa infections (160). However, they did not investigate if

RV infection could change immune cell function. In a recent study, the effects of RV infection of human circulating B cells (CBC) from the Stanford University blood bank and intestinal B cells (IBC) from obesity patients undergoing bariatric surgery in vitro were compared (228). They found that IBC were more susceptible than CBC to both

RRV and HRV Wa infections, and naïve B cells were more resistant than memory B cells to RV infection (228). Although, IBCs were more susceptible to RV infection compared to CBC, RRV exposure caused significantly higher frequencies of cell death in CBC compared with the frequencies in IBC (228). RRV and inactivated RRV significantly induced the secretion of IL-6 from CBC but not from IBC (228). Currently, we know that

B cells are possible targets for RV infection depending on B cell status and tissue origin, although the mechanisms of susceptibility to RV in different types of B cells are unknown.

RV antigens were observed in morphologically identified macrophages in lungs and blood vessels in rat pups by immunohistochemistry (218). RV antigens were also detected in murine hepatic macrophages by flow cytometry (165). Using a murine macrophage cell line RAW 264.7, they confirmed that RRV-infected RAW 264.7 cells could induce secretion of IFN-α, IFN-β and TNF-α and migration of neutrophils.

However, it is not known if RV infection promotes or diminishes RAW 264.7 cell responses to RV. More studies are needed to verify if RV can infect macrophages and to determine if RV infection can change macrophage immune responses.

30 There is increasing evidence suggesting that RV can infect mononuclear cells, such as

DCs, B cells and macrophages. However, as these cells are professional antigen presenting cells which are able to take up antigens, it is necessary to verify further if the

RV antigen observed in these immune cells was due to active infection of the cell or antigen presenting cell engulfment and processing. To answer the question, first, in exposed immune cells, the expression of NSPs and/or single-stranded RNA should be detected; second, after replication, it is necessary to verify if RV can assemble and/or release infectious viral particles. Another remaining question is if RV infection can affect/alter the immune responses of the infected-immune cells. Because immune cells are not the main targets of RV infection and the infection rate is relatively low, it has been difficult to examine this hypothesis. With the help of advanced technology, such as flow cytometry, we are now better able to detect surface marker expression and cytokine secretion in RV-infected immune cells to help answer these questions.

1.6 Functions of DCs in immunity

DCs play an important role in linking innate and adaptive immunity and are pivotal in the control of intestinal immunity which is tolerant to intestinal commensal bacteria, yet responds to infectious pathogens (231, 232). There are many subsets of dendritic cells, expressing different surface markers and presenting diverse capacities (233). After capture by immature DCs, antigens will be presented to T cells by mature DCs followed by elimination via adaptive immune responses (234, 235). Mucosal immunity is a special component of immunity, because mucosal surfaces are exposed, not only infectious pathogens, but also to food particles and commensals (236). Adequate responses to 31 different antigens are very important to maintain body health, especially at the intestinal mucosal interface that is continuously exposed to commensal bacteria and food antigens

(236, 237). Many studies have examined the mechanisms by which dendritic cells, particularly intestinal dendritic cells, modulate the immune response.

1.6.1 Introduction of DCs

As the sentinel of innate immunity, many DCs are located at the body’s primary natural barrier surfaces that are intended to protect against pathogens, including the skin and the mucosa of the gastrointestinal, respiratory and urogenital tracts (238). These DCs can capture or detect pathogens and initiate appropriate specific immune responses (238).

DCs are unique APCs as they are able not only to induce primary immune responses, but also are able to efficiently stimulate memory responses (239). Once they capture foreign antigens, DCs can present them to T cells, which activates naïve T cells to proliferate and differentiate (240). DCs can also interact directly with naïve B cells to transfer antigen and initiate class switching in primary T cell-dependent antibody responses (241). Not only do they have the capacity to initiate immune responses, DCs also have the ability to induce specific unresponsiveness or tolerance in both central lymphoid organs and in the periphery (242). Some researchers have suggested that DCs can induce different types of

T cell-mediated immune responses, depending on their lineage, maturation stage and activation signals (243).

There are two major populations of DCs: conventional DCs (also called myeloid DCs) and plasmacytoid DCs, with the classification based on the surface markers, functions, and origins of the DCs (239, 244). Conventional DCs (cDCs) contain all DC subsets with 32 professional antigen presenting function, while plasmacytoid DCs (pDCs) have the capacity to produce large amount of IFN-α (245). Researchers have also found that DCs at different maturation stages have different functions. Banchereau and Steinman reviewed the difference in function between immature and mature DCs and suggested that most immature DCs are potent at antigen capture and presentation, while mature DCs are more efficient in T cell stimulation (235). Since DCs play an important role in immune control and surveillance, it is necessary and critical to understand the classification of DCs, the interaction between DCs and pathogens, and the mechanism of

DC regulatory function of immune responses. Although both human and porcine DCs are grouped into cDCs and pDCs, the surface markers are not always homogenous (244,

246). This review will discuss similarities and differences between human and porcine

DCs in regard to both surface markers and functions.

Both cDCs and pDCs are crucial in generating and maintaining antiviral immunity

(Larsson et al., 2004). Many viruses have evolved the ability to avoid or subvert DC immunity (238). Multiple studies have been performed to investigate the interaction between DCs and viruses, in mice, swine and humans (247-249). The interaction between rotavirus and human DCs has been studied, but little is known about the interaction of rotavirus with porcine DCs (149, 159, 160, 164).

1.6.2 The classification of human and porcine DCs and surface markers on different DC subsets

To understand the biology of DCs, a consideration of the heterogeneity and dependence of DCs on functional plasticity is required (244). Numerous studies show that DCs can be 33 found in almost every body compartment and DCs from different sites have diverse surface markers and functions (239, 244, 250). There is controversy on the origin of DCs.

Based on human and mouse in vitro DC differentiation assays, DCs can be generated from monocytes or intermediate myeloid precursors (251, 252); while lymphoid precursors can also differentiate into DCs (251, 253). Myeloid-derived DCs are called myeloid DCs or conventional DCs; while lymphoid-derived DCs are called plasmacytoid

DCs. The frequency of DCs in the body is low (1-2% of the total leukocytes) (254).

Because serum sample sizes obtained from humans are very limited, there are relatively few studies of human DCs, especially in neonates, compared with the extensive research on mouse DCs (233). Pigs, as a surrogate animal model for human medical research are receiving more attention by research groups. Examples include use of gnotobiotic pigs as a model to study the pathogenesis and immunity to human rotavirus (173). This well characterized model allows researchers to study the biology of porcine DCs to investigate the interaction of human rotavirus with intestinal DCs and probiotics. This review will compare and outline common features and differences between human and porcine DCs.

Because DCs are very scarce in the body, the isolation procedures for DCs are time consuming and yield very low cell numbers (233). To overcome this, researchers developed methods to generate DCs in vitro. There are two different precursors that have been used to generate human DCs in culture: the CD34+ fraction isolated from bone marrow and umbilical cord blood, which can differentiate into either cDCs or pDCs, and blood monocytes which mainly develop into pDCs (246, 255, 256). Human blood monocytes, the most commonly used precursor cells for generating human pDCs, when cultured with granulocyte-macrophage colony-stimulating factor (GM-CSF) and IL-4 34 differentiate into immature conventional DCs (256). Similar to human DCs, porcine DCs can be generated by stimulating blood monocytes with GM-CSF and IL-4 (257). Porcine

DCs can also be generated from bone marrow hematopoietic cells by stimulating with

GM-CSF and TNF-α, or GM-CSF alone (257). In addition to these, researchers found that fms-like tyrosine kinase 3 ligand (Flt3L) could induce the generation of DCs in mice

(258). Recently, researchers demonstrated that Flt3L stimulation could induce the generation of DCs from both human and porcine bone marrow hematopoietic cells (244,

259).

Both cDCs and pDCs produce IL-12 and TNF-α to drive innate immune responses (260).

However, they have distinct functions in immune responses: cDCs usually drive Th1 responses, whereas pDCs drive Th2 responses, depending on the inflammatory environment (261, 262). The human cDC phenotype is CD4+CD1a+CD11c+, while the human pDC phenotype is CD4+CD11c-CD45RA+CD123+ILT3+ILT1- (233).

Distinguishing porcine cDCs and pDCs primarily depends on CD172 (SWC3a), CD4 and

CD11R1 (CD11b) expression with porcine cDCs defined as CD172a+CD4-CD11R1+ while porcine pDCs are defined as CD172a+CD4+CD11R1- (239, 263). CD14, which is mainly expressed by macrophages and neutrophil granulocytes, is used to differentiate the in vitro generated DCs from in vivo blood DCs, the latter of which lack CD14 expression (244).

There are four phenotypically distinct subsets of mucosal DCs based on the expression of

CD11R1 and CD172a in swine (264). Those four distinct subsets, having MHC class II marker, are located in different sites: lamina propria cDCs are mainly

CD172a+CD11R1+; Peyer’s patches cDCs are mostly CD172a+CD11R1- in 35 subepithelial domes and CD172a-CD11R1- in interfollicular regions, and mesenteric lymph node cDCs are mainly CD172a-CD11R1+ (244, 264). Compared to diverse surface markers of porcine mucosal cDCs, porcine mucosal pDCs were defined as

CD172a+CD4+ (239). More detailed phenotyping of pDCs in different sites requires further studies. Compared with porcine and murine DCs in the intestine, we know little about human intestinal DCs because most studies of human DCs are using DCs generated in vitro from blood monocytes or CD34+ precursors from either cord blood or bone marrow (250). In Johansson and Kelsall’s (2005) review, MHC class II+S-100 protein+ cells were identified as DCs in human Peyer’s patches; while in human mesenteric lymph nodes, DCs expressed CD40, CD54, CD80/86 and CD83, but lack CD1a. Additional studies are needed to accurately classify human DCs in the intestine.

The classification of human DCs in blood has been approved by the Nomenclature

Committee of the International Union of Immunological Societies (265). Human blood

DCs are classified into three subsets: plasmacytoid blood DCs which are defined by

CD303 (BDCA-2: blood dendritic cell antigen2, a novel plasmacytoid dendritic cell- specific type II C-type lectin (266)); the other two conventional blood DCs subsets are defined by CD1c and CD141(thrombomodulin, also called BDCA-3, expressed by cDCs

(267)), respectively (265). However, in Mittag’s et al. (2011) research, human blood DCs are classified into four groups: three subsets of cDCs and one subset of pDCs. Human blood cDCs, identified as CD11c+HLA-DR+, are distinguished into three subsets according to CD1b/c, CD141 and CD16 (identified as Fc receptor FcγRIII); while human blood pDCs are defined as CD11c-CD123+CD304(BDCA-4/Neuropilin-1)+ (268). They also suggested that all four DC subsets present in human blood could be detected in 36 human spleen. However, the DC subset markers used in the experiment were originally identified as blood DC subsets and might not distinguish spleen resident DCs (268). They only hypothesized that the spleen DC subsets might have similar phenotypes and functions as the blood DC subsets. Further studies are required to identify human spleen

DC subsets.

Compared with human blood and spleen DCs, there is less data about porcine blood and spleen DCs. There are three subsets of porcine CD172a+ peripheral blood mononuclear cells (PBMCs): the first dominant subset is CD4-CD14+CD16+ (CD14 is a co-receptor for the detection of bacterial lipopolysaccharide preferentially expressed on monocytes/macrophages) which can differentiate into macrophages or monocyte-derived

DCs; the second subset is CD4-CD14- porcine blood cDCs which can be divided into

CD16+ and CD16- subpopulations; the last subset is the CD1-CD4++CD14- porcine blood pDCs (263). The classification of porcine DCs in secondary lymphoid organs is even more blurred. Jamin et al. (2006) first identified two distinct DC subsets in spleen, tonsil and lymph nodes of specific pathogen free pigs. One subset was defined as

CD172a+CD11R1+CD1+/-CD80/86+/- cells and would correspond to cDCs, while the other subset was defined as CD172a+CD4+CD1+/-CD80/86+/-IFN-α+/- cells and would correspond to pDCs (239).

Depending on the expression of CD207 (langerin, a type II transmembrane cell surface receptor produced by Langerhans cell and some DCs (269)), CD11b and CD103 (integrin

αEβ7), human DCs in non-inflammatory dermis were classified into five distinct subsets

(270). The major dermal DC (DDC) subset was defined as CD207-CD11b+; while the other three minor subpopulations were defined as CD207+CD103+, CD207+CD103- and 37 CD207-CD11b-, respectively (271). The last subset is CD207+CD103- DC which could be found in the dermis and corresponds to migratory Langerhan’s cells en route to cutaneous lymph nodes (271). Compared with human dermal DCs, we know little about porcine dermal DCs.

There are many studies on the classification of cDCs, whereas, pDCs are usually defined as one subset (268, 271). Recently, human pDCs were classified into two distinct subsets according to CD2 expression (272). Both of them have the capacity of type I IFN secretion; however, CD2high pDCs show some unique characteristics: they can express lysozyme, secrete high levels of IL12p40 and CD80, and are more efficient at promoting naïve T cell proliferation (272). Those different functions may be related to the different expression level of CD2. There may be some interactions between CD2 and possible molecules on other immune cells to induce those unique functions. Further studies are required to explain the phenomena.

1.6.3 The function of DCs in innate and adaptive immunity

DCs are professional antigen presenting cells that are distributed in most tissues and, in particular, at sites that interface with the external environment, such as the gastrointestinal and respiratory tracts (273, 274). DCs are sentinels of the immune system that can capture, process and present antigens; furthermore, they have the unique capacity to activate naïve T cells, distinguishing DCs from all other antigen presenting cells (235,

274). Not only do they have the capacity to activate naïve T cells, but DCs are also able to enhance the activation of B cells and skew the isotype switching of CD40-activated naïve B cells (275, 276). The development of T cell type 1 or type 2 immune pathogen- 38 specific responses relies on the regulation of DCs which can induce the corresponding T cell differentiation (277, 278). At the intersection of innate and adaptive immunity, DCs have an indispensable capacity to induce tolerogenic immune responses, especially the intestinal DC (234, 279). According to Banchereau and Steinman (1998), “Signals from

DCs can determine whether tolerance or an active immune response occurs to a particular antigen”. Recent studies found that DCs are required for homing of immune effector cells

(280, 281). There was a subpopulation of gut DC could produce retinoic acid (RA) from vitamin A and RA, in turn, primed DCs to induce gut homing of immune cells (282, 283).

Using prenatally acquired vitamin A deficient Gn pig model, our lab found that vitamin

A sufficient pigs had significantly higher frequencies of CD103 (integrin αEβ7) expressing DCs in ileum, duodenum and spleen compared to vitamin A deficient pigs

(157). And this observation was consistent with significantly higher TLR3+ MNC frequencies in ileum, duodenum and spleen of vitamin A sufficient pigs than vitamin A deficient pigs (157).

Researchers noted that DCs in different developmental stages have different functions: immature DCs could capture foreign antigens and process them, while mature DCs present those antigens via their major histocompatibility complex (MHC) to T cells

(284). The functional difference between those two stages of DCs is reflected by the different phenotypes of DC surface molecules. Immature DCs express low levels of surface MHC class II and CD86 which are critical in antigen presentation (285). In contrast, mature DCs have different features: they express high levels of MHC class II and co-stimulatory molecules such as CD40, CD80 and CD86 (286, 287). The maturation of DCs with several phenotypic changes contributes to the increased capacity to process 39 antigens and activate T cells (242). When pathogens are present in peripheral tissues, resident immature DCs are activated to become mature DCs and migrate through the draining lymph nodes to present antigens to T cells (240). When immature DCs capture an antigen and recognize it by pattern recognition receptors (PRR), such as toll-like receptors, signals to mature will be produced (235). Mature DCs will assemble antigen-

MHC class II complexes to present and activate a variety of T cells which affect the immune responses depending on the micro-environmental conditions (235). In the presence of IL-12, mature DCs can induce naïve T cells to differentiate into interferon-γ- producing T helper (Th) 1 cells; while mature DCs with IL-4 will induce naïve T cell differentiation into Th 2 cells which can secrete IL-4 and IL-5 (235, 288). Based on the presence of different cytokines, maturation will lead to different T cell responses as well.

Vieira et al. (2000) concluded that DCs maturing in the presence of IFN-α can induce

Th1 responses, whereas DCs in the presence of prostaglandin E2 [PGE2, a homeostatic factor, can promote TH2, Th17 and regulatory T cell responses, but suppress Th1 responses (289)] can drive Th2 responses (290).

1.6.4 The function of DCs in regulatory immunity

Besides having the capacity to activate immune responses to foreign antigens, researchers discovered that DCs also contributed to T cell tolerance to self-antigens and food antigens (242). Until 2002, most researchers thought that immature DCs contributed to the induction of regulatory T cells. Jonuleit et al. (2000) reported that mature human DCs could induce inflammatory Th1 cells and immature DCs could contribute to the induction of IL-10-producing T regulatory 1- like cells (291). Lutz and Schuler (2002) discovered 40 that immature murine DCs generated with low doses of GM-CSF in the absence of IL-4 were maturation resistant and those DCs could prolong allograft survival in vivo (234).

However, other researchers found that mature DCs might play a role in CD4+ T cell tolerance (292, 293). Akbari et al. (2001) discovered that murine pulmonary dendritic cells producing IL-10 mediate tolerance induced by respiratory exposure to antigen

(292); while Menges et al. (2002) used repetitive injections of murine dendritic cells maturated in the presence of tumor necrosis factor-α (TNF-α) to induce antigen-specific protection of mice from autoimmunity (293). Then the third development stage of DCs was discovered -- semi-mature DCs (234). Lutz and Schuler (2002) concluded that the semi-maturation of DCs induced by pro-inflammatory cytokines (TNF-α) represented a unique developmental tolerogenic stage of DCs, and could induce T cell tolerance to self- antigens. They noted that those semi-mature DCs acquired part of the characteristics of fully mature DCs, such as the expression of co-stimulatory molecules, whereas those DCs lacked the ability to produce polarizing signals to drive naïve T cells to differentiate into

Th1 or Th2 T cells. However, in 2003, some researchers determined that mature DCs could interrupt the suppressive effects of CD4+CD25+ Treg cell generation and promote

T cell proliferation (294). Though this data did not deny the possible roles of immature and semi-mature DCs in the development of T cell tolerance, it suggests that mature DCs could promote the expansion of existing Treg cells (295). There is no fully accepted conclusion for now; however, it is clear that DC-derived IL-10 has an important role in the development of T regulatory 1 cells (296). Further studies are needed to define the exact role of DCs in different maturation stages.

41 As described above, DCs can be divided into two major groups: conventional DCs

(cDCs) and plasmacytoid DCs (pDCs) with different functions (245). Primarily expressing toll-like receptor (TLR) 2-6 and 8, cDCs have the ability to produce large amounts of IL-12 during antibacterial and antiviral responses; whereas, pDCs, expressing

TLR7 (recognizes single stranded RNA in endosomes) and TLR9 (recognizes unmethylated CpG sequences in DNA molecules), can produce large amounts of type I interferons (IFNs) in antiviral immune responses (262, 297, 298). Furthermore, some researchers thought that the cDC specific cytokine network mainly drives Th1 responses, while pDCs induce Th2 responses through IL-4 and IL-10 (261, 299). However, others thought that the induction of Th1 or Th2 responses attributed to human cDCs was not an intrinsic function and depended on environmental instruction (290). They suggested that the capacity to produce IL-12 by mature DCs was influenced by the ratio of IFN-γ to

PGE2 concentrations and that high-level IL-12 production by mature cDCs depended mainly on the presence of IFN-γ at an earlier development stage. In addition, some researchers indicated that human and porcine pDCs, like cDCs can secrete IL-12, although not as much as cDCs, and also drive Th1 differentiation (148, 239). There is no widely acknowledged conclusion as to which type of DCs mainly contributes to the

Th1/Th2 polarization induction. More investigation is needed to resolve these questions.

In addition to the function of Th1/Th2 polarization, those two types of DCs have other different effects. Ito et al. (2007) discovered that maturing pDCs strongly up-regulated inducible co-stimulator ligand (ICOS-L), down-regulated by maturing cDCs, which could drive the generation of IL-10-producing T regulatory cells regardless of the activation pathway. An important pDC regulatory function of adaptive immunity is to induce 42 human B cells to differentiate into plasma cells and produce immunoglobulins, through type I IFN and IL-6 (148). Whether swine DCs have the same function as human and murine DCs or have other particular functions is not known.

1.6.5 The function of intestinal DCs

Recent studies suggest that intestinal DCs are pivotal in regulation of gut immunity. They are important in the balance between tolerance and active immune responses to commensal microorganisms that is fundamental to avoid inflammatory conditions (274).

To investigate the mechanism of intestinal DC regulatory functions, researchers discovered some unique characteristics of intestinal DCs, from antigen sampling to regulatory effects. There are three main antigen sampling routes of murine intestinal

DCs: 1) murine DCs can express tight junction proteins and penetrate gut epithelial monolayers to sample bacteria (300); 2) murine DCs can transport apoptotic intestinal epithelial cells to the T cell area of the mesenteric lymph nodes (MLNs) (248, 301); 3) murine DCs directly interact with antigenic material in underlying tissue (274). Using diverse sampling routes, DCs can distinguish between closely related microbial structures and organisms and through release of different cytokines, they can induce different immune responses (274).

Iwasaki and Kelsall (1999) noted that DCs in different anatomical locations had different functions. For example, naïve CD4+ T cells activated by DCs from the Peyer’s patches produce higher levels of IL-4 and IL-10 than those activated by splenic DCs (302). Even the DCs in the same organ, but of a different subpopulation may have different functions

(303). As the classification of DCs in the intestine is complicated and there is a lack of 43 data for humans and mice, we do not know the exact function of all subpopulations of

DCs in intestine (250). However, researchers summarized some unique properties of mucosal DCs in recent studies (273, 304): 1) mucosal DCs can express some integrin receptors for T and B cell homing, such as α4β7 and L-selectin (280, 305); 2) mucosal

DCs can induce generation of Foxp3+ regulatory T cells via TGF-β and retinoic acid

(306, 307); 3) mucosal DCs can promote the differentiation of Th17 cells (308); 4) mucosal DCs contribute to IgA B cell class switching (309). All these properties are attributed to the regulatory function of DCs in mucosal immunity.

Intestinal DCs play a very important role in intestinal immunity which can protect against infection while avoiding the development of inflammatory responses to commensal microorganisms or food antigens (237). Like DCs in other organs, intestinal DCs can capture and present antigens to T cells to activate immune responses; however, they can control immune tolerance as well (237). Bilsborough and Viney (2004) summarized three mechanisms that DCs utilize to control tolerance: 1) use of DCs at different developmental stages to present antigens (310); 2) utilization of novel receptor ligand interactions for signaling (311); and 3) production of immunosuppressive cytokines to control T cell proliferation, such as IL-10 and TGF-β (312, 313). It is still not clear what mechanisms allow DCs to distinguish between commensal bacteria and infectious pathogens. One possibility is a triggering of DCs through different pattern recognition receptors and different signaling pathways. Because of a lack of gut samples, research on human DCs is limited. Because research on pigs as models for studying human immunity is relatively focused on a few pathogens (173); data on porcine intestinal DCs is also

44 limited. Investigation of porcine intestinal DCs may give researchers new insights into human intestinal immunity.

1.6.6 The interaction between DCs and viruses

There are numerous studies regarding interactions between DCs and viruses. Bhardwaj et al. (1994) noted that influenza virus (strain PR8)-infected human DCs could stimulate strong proliferative and cytolytic responses from human CD8+ T cells. They also found that human DCs can induce CD4+ influenza virus-specific cytolytic T lymphocytes, but only when CD8+ T cells were depleted (247). Another study showed that CD8α-

/CD11blow murine DCs in the Peyer’s patch subepithelial dome could process reovirus strain type 1 Lang antigen from infected apoptotic epithelial cells for presentation to

CD4+ T cells (248). These data indicate the important role of murine DCs in protecting the body from viral infections. However, researchers also observed that many viruses have evolved multiple methods to avoid DC recognition, and evade the immune system

(238). Researchers found that in human immunodeficiency virus (HIV) infection, the decreased number of DCs due to apoptosis and the change of signaling to T cells by infected DCs might play a role in the altered immune responses to HIV infection (314).

Moreover, Boonnak et al. (2008) investigated the antibody-dependent enhancement

(ADE) of dengue virus (the Burma DV2 isolate S16803) infection and found that it was inversely correlated with surface expression of DC-SIGN (DC-specific intercellular adhesion molecule-3-grabbing nonintegrin) and requires Fc gamma receptor IIa

(FcγRIIa). ADE, exhibited by mature human DCs with lower level of DC-SIGN compared with immature human DCs, increased intracellular de novo dengue virus 45 protein synthesis and promoted viral production and release in vitro (315). These data indicate that different viruses can utilize different mechanisms to interact with DCs to evade or suppress the immune system.

Swine DCs also are under investigation to assess interactions with viruses and as surrogate model for human DCs(164). The interaction of classical swine fever virus

(CSFV) with porcine DCs was investigated (316). The data showed that CSFV (the virulent Brescia strain) replicated in both monocyte-derived and bone marrow-derived porcine DCs and suppressed the production of IFN-α, while the capacity of CSFV- infected DCs to stimulate T cells was not affected, and infection modulated neither MHC nor CD80/86 expression (316). Foot-and-mouth disease virus (FMDV) (A24 Cruzeiro and 01 Campos) produced viral leader protease which could cleave elongation factor G4 to inhibit the translation of cellular mRNA that resulted in the inhibition of type I IFN expression in infected porcine DCs (317). The investigators discovered that FMDV- infected porcine DCs could not synthesize new MHC molecules containing viral peptides; however, they also indicated that the antigen-presenting capacity of infected

DCs was normal. It is known that MHC class I and class II are the main antigen- presenting molecules. It is perplexing that the antigen-presenting function of FMDV- infected DCs was not affected, but they could no longer synthesize new MHC molecules containing viral peptides. More studies are needed to explain the mechanisms involved. A recent study showed that a circulating strain of H3N2 swine influenza virus could infect porcine bone marrow derived DCs, and viral particles from infected DCs induced cytopathic effects in susceptible cells only when cell-to-cell interaction was favored

46 (249). The study of interactions between porcine DCs and viruses is at an initial stage and more detailed investigations are required to explain the complex mechanisms.

As a potential zoonotic pathogen, rotavirus can cause death and economic losses in both neonatal humans and swine (5, 6). The interaction of rotavirus with DCs has become a research focus in recent years. To investigate the interaction of rotavirus (rhesus rotavirus and Wa rotavirus) with human conventional DCs generated from peripheral blood mononuclear cells, replication of rotavirus in DCs and different cytokines in cell culture supernatants from mature and immature DCs were investigated (159). The investigators found that rotavirus did not induce death of human conventional immature and mature

DCs, it did not inhibit the maturation of immature DCs or change the expression of maturation markers on DCs. Furthermore, they noted that immature DCs treated with rotavirus could strongly stimulate naïve allogeneic CD4+ T cells to secrete Th1 cytokines. According to the data, they concluded that although rotavirus did not seem to be a strong maturation stimulus for human DCs, it promoted their capacity to prime Th1 cells. However, the same lab published a later paper which indicated that it was difficult to determine whether rotavirus could induce death of human monocytes and/or DCs

(160). Further studies are needed to clarify this matter. Another paper revealed the role of

IFN regulatory factor (IRF) 3 in type I IFN responses in rotavirus-infected bone marrow- derived murine cDCs (318). Their results demonstrated that, in contrast to RRV-infected mice, embryonic fibroblasts in which the production of type I IFN was blocked via IRF3 degradation by rotavirus, that rotavirus induced type I IFN production in cDCs and promoted their activation. The induction of type I IFN in rhesus rotavirus-treated cDCs from MyD88-/- and TLR3-/- mice was examined. The data showed that type I IFN 47 induction by cDCs in response to RRV infection was not induced through a TLR- dependent pathway. More studies are required to explain the TLR independent pathway of IFN induction utilized by cDCs.

1.7 The role of TLRs in immune responses, gut homeostasis and immune diseases

TLRs are a type of pattern recognition receptors (PRRs) that interact with microbe- associated molecular patterns (MAMPs) and activate signaling pathways to initiate specific adaptive immune responses (231, 319). TLRs recognize different microbial molecules (Table 1.3) and play a crucial role in linking innate and adaptive immune responses (231, 320). There is increasing evidence to demonstrate that TLRs are indispensable in gut homeostasis and may be related to some autoimmune diseases and chronic inflammatory infections (232, 321, 322). Therefore, it is necessary to study the mechanisms of TLRs linking and regulating innate and adaptive immune responses and to investigate why TLRs are associated with autoimmune diseases.

1.7.1 The discovery and localization of TLRs

The motifs of TLRs in the cytosolic domain have been noted to be homologous to the cytosolic domain of a Drosophila melanogaster protein termed Toll in 1991, but were not named TLRs until 1998 (323-325). To date, 13 TLR family members have been identified in mammals (TLR1-TLR13); and TLR1 to TLR10 have been found in humans, while TLR1 to TLR9, TLR11 to TLR13 have been found in mice (320). The 10 TLR genes identified in humans have been also cloned in pigs (326). In humans, those 10

TLRs are divided into two subpopulations according to their cellular localizations (319, 48 327). TLR1, 2, 4, 5, 6 and 10 are localized to the cell surface, while TLR3, 7, 8, 9 are localized in intracellular vesicles such as endosome and endoplasmic reticulum (319,

320, 328). The murine TLRs 11 to 13 are localized within endosomal compartments

(329). The MAMPs for all TLRs have been determined except for TLR10 in humans

(320, 330). Recent studies showed that TLR10 was involved in innate immune responses to influenza virus infection, but more studies are required to identify the ligand for

TLR10 (331).

TLRs are mainly detected in tissues and cells involved in immune function, such as mesenteric lymph nodes (MLNs), spleen, as well as those exposed to the exterior environment such as epithelial cells in the intestine and the lung. The expression profiles differ among tissues and cell types (332-334). Among all different types of cells which express TLRs, DCs are critical mediators for TLRs to achieve their functions (335, 336).

DCs are a type of professional antigen presenting cell armed with TLRs to recognize different self and foreign antigens (336). They play an indispensable role in initiating innate immune responses and shaping adaptive immune responses via TLR signaling

(235, 337).

1.7.2 The function of TLRs in immune responses

TLRs are type I transmembrane proteins that share similar extracellular leucine-rich repeats, but recognize different microbial molecules (319, 338). TLRs can recognize a wide range of MAMPs, including lipids, lipoproteins, proteins and nucleic acids, from bacteria, viruses, fungi, protozoa and parasites (339-341). The interaction between TLRs and MAMPs initiates the TLR signaling pathway resulting in the activation of the 49 transcription factors NF-κB, IRF3, IRF7, etc. to further launch the host immune response

(338, 342). There are two TLR signaling pathways: MyD88-dependent pathway and

TRIF-dependent pathway, and studies have indicated that the signaling pathway is cell type-specific and distinctively determines the cell immunological properties (339, 343,

344).

As a part of innate immunity, the activation of TLRs not only directly kills pathogens via recruitment and activation of neutrophils, macrophages and NK cells, but it also shapes pathogen-specific humoral and cellular adaptive immune responses via influencing DC responses, such as DC-derived cytokines and IFNs (299, 340, 342, 345). Activation of

TLRs induces the release of chemokines, a group of chemotactic cytokines that control the immune cell migration and position (342, 346, 347). In addition, TLRs trigger the maturation of DCs that are associated with T cell and B cell activation (342). The activated DCs present antigens to T cells and induce the antigen-specific T cell responses

(348). Studies indicate that DCs govern the Th1/Th2 CD4+ T cell differentiation and the generation of CD8+/CD4+ regulatory T cells via cytokine induction and ligand interaction (294, 349-353). The activated T helper cells interact with naïve B cells to initiate the B cell class switching and induce the differentiation of B cells into plasma cells (354). Some data also suggests that DCs can directly skew the B cell class switching

(241, 276, 355). In summary, TLRs control adaptive immunity via activating DC response (231, 342).

50 1.7.3 The role of TLRs in gut homeostasis

Numerous studies have demonstrated that TLR signaling in both intestinal epithelial cells and immune cells plays a crucial role in maintaining gut homeostasis (324, 356). TLRs regulate the proliferation of epithelial cells during chemical-induced and radiation- induced injuries in mouse models (357). Moreover, TLRs can promote the expression of tight junction proteins, antimicrobial peptides and lectins and shape the mucosal immune response (232, 357). To investigate the role of TLRs in gut homeostasis, chemical- induced colitis mouse models and gene knockout mouse models have been used (356,

358, 359). Using oral administration of dextran sulfate sodium (DSS) in mice to establish a model of intestinal injury and inflammation in wild type and Myd88-/- mice, as well as

TLR2 (recognizes peptidoglycans) and TLR4 (recognizes lipopolysaccharides) deficient mice, Rakoff-Nahoum et al. (2004) found that DSS-treated MyD88 deficient mice showed severe mortality and morbidity compared with DSS-treated wild type mice.

Additionally, TLR2 or TLR4 deficient mice had lower mortality after the DSS administration compared with MyD88 deficient mice, but higher mortality compared with DSS-treated wild type mice (360). In another study, 20 µg poly(I:C) was given to wild type and TLR3 (recognizes double-stranded RNA) knockout mice subcutaneously 2 hours before the DSS administration, and the results showed that poly(I:C) protected against DSS-induced colitis in wild type mice, but not the TLR3 knockout mice, suggesting the involvement of TLR3 in the protection (359). Furthermore, TLR9

(recognizes CpG DNA) activation also has been demonstrated to be involved in protection against DSS-induced colitis in TLR9 deficient mice (358). Lack of TLR signaling causes the intestine to be more susceptible to chemical injury, and also affects 51 host metabolism via changing the composition of the gut microbiota (361). TLR5

(recognizes bacterial flagella) knockout mice exhibited higher body mass and blood glucose with increased proinflammatory gene expression (361). TLR activation also regulates gut homeostasis via affecting immune cell responses. Studies indicated that

CD11chigh CD11bhigh lamina propria DCs (LPDCs) were able to induce the differentiation of Th17 and Th1 cells, while the capacity was compromised in Tlr5-/- CD11chigh

CD11bhigh LPDCs and was abolished in Myd88-/- CD11chigh CD11bhigh LPDCs (356).

These data suggest that TLR signals are important for CD11chigh CD11bhigh LPDCs- mediated activation of gut immunity. In all the ways noted, TLRs play a key role in maintenance of gut homeostasis.

1.7.4 TLRs and immune diseases

Although TLRs are important for host defense, increasing evidence suggest that inappropriate TLR signals are associated with systemic autoimmune diseases, such as kidney disease and cardiovascular disease, and chronic inflammatory disease (322, 362,

363). The mechanisms of TLR-induced immune diseases are still under investigation.

There are several clues showing that some autoimmune diseases are related to misrecognition of self-antigens as foreign antigens. Normally, TLR7, TLR8 and TLR9 recognize bacterial and viral DNA or RNA; but if they recognize host DNA, RNA, and

DNA- or RNA-associated proteins, autoantibodies will be produced and result in autoimmune diseases (322). Autoreactive B cells and plasmacytoid DCs activated via ligands of TLR7 and TLR9 have been reported to be associated with systemic autoimmune diseases (321, 364, 365). Improper TLR activation can disrupt gut 52 homeostasis and cause chronic inflammation (232). Distinctive decreased TLR3 and increased TLR4 expression have been found in the epithelial cells of inflammatory bowel disease specimens (366). Studies of TLR4 deficient mice indicated that TLR4 promoted the development of DSS-induced neoplasia, while the activation of TLR5 induced antitumor immunity (367, 368). More studies are needed to understand the contribution of TLRs to autoimmune diseases and chronic inflammatory diseases.

1.7.5 The expression and regulation of TLRs in humans, in mice and in pigs

Because growing evidence illustrates the potential role of TLRs in autoimmune and chronic diseases, TLRs are now used as therapeutic targets for those diseases; however, most studies are still in the in vitro stage or undergoing testing in mouse models (369,

370). Unfortunately, the mouse model is not an ideal model for studies of human TLR function since the expression and regulation of TLRs differ between mice and humans

(371, 372). Several studies have demonstrated these differences. One study showed species-specific variances of human and murine TLR3 in tissue expression and responses to LPS according to divergent promoter sequences (373). Another demonstrated that although cells of myeloid origin showed the highest levels of TLR4 expression in both mice and humans, such as monocytes and macrophages, the expression pattern was remarkably different in LPS-treated monocytes and macrophages between the two species (374).

An alternative to the mouse model, the pig model has become a more common model for studies of infectious disease and human innate immunity, especially for studies of enteric pathogens and the human gastrointestinal tract (164, 182, 375-378). While there is 53 limited information related to porcine TLR expression and function, existing evidence suggests that the pig may be closer to humans than mice (374, 379). For instance, there is

65-77% similarity between porcine and human TLR4 nucleotide sequences and the porcine TLR4 promoter possess more features in common with the human TLR4 promoter than the mouse TLR4 promoter (380, 381). The porcine TLR system has been insufficiently investigated due to the concentration on the study of murine and human

TLR systems (379). More studies of porcine TLR expression and function are needed to evaluate if the pig model can mimic and predict the human condition.

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118) -

(89) (95) (96) (99) (100) (101) (105) (106) 109, 113 109, 112, 119, 120) 119, 112, (102, 103) - - References (107 (110

G9P[8] (7.4%) G9P[6] (1.8%) (5.9%) G12P[8] , G2P[4] (10.1%)

, G8P[6] (5.0%) , G9P[8] (7.0%) , G2P[4] (9.3%), G4P[8] (7.4%) G9P[8] (3.6%) G9P[8] (11.6%) , G2P[4] (18.3%), G8P[8] (9.5%) (11.0%), G2(6.2%), G4 (5.1%) serotype/genotype of RVs of serotype/genotype , G3 G9P[8] (21.3%) , G2P[6] (9.6%), G8P[6] (9.4%), G3P[8] (7.0%) , G2P[4] (7.0%), , G2P[4] (9.2%), , G2P[4] (29.9%), G4P[8] (6.9%), G3P[8] (6.1%) , G9P[8] (20.9%) , G3P[8] (10.5%), G2P[4] (6.1%), , G1P[8] (26.0%), G3P[8] (14.3%), G4P[8] (2.2%) , G3P[8] (18.9%), G2P[4] (11.8%), G9 (22.7%) G9 , G4P[8] (15.1%), , , Most prevalent prevalent Most G1 (43.4%) G1 G1P[8] (17.4%) G1P[8] G1P[8] (22.0%) G1P[8] G1P[8] (78.5%) G1P[8] G1P[8](32%) G1P[8] (40.1%) G1P[8] G1P[8] (48.4%) G1P[8] G1P[8] (53.2%) G1P[8] (30.8%) G2P[4] G1P[8] (23.6%) G1P[8] G1P[8] (48.4%) G1P[8]

2011 2006 2008 200 2009 2005 2009 2004 2007 2007 2013 ------Years 2000 1997 2006 2005 2006 1996 2006 1995 2005 1999 2008

The distribution of the most prevalent serotypes/genotypes of human theserotypes/genotypesofof 2013 distributionrotaviruses 1995 most betweenThe prevalent and

Asia 1 . Africa Europe 1 Australia Location Latin America Latin North America North Table

(88) (382) References

(3.6%), G9(2.3%) , G3 (30.0%), G4 (20.0%) , P[13] (11.1%), P[6] (5.6%) , G4 (8.2%), G3 , G4 (17.4%),G3 (14.5%), G6 (8.7%) , G3 (25.5%), G9 (11.4%), G4 (8.6%) , P[7] (13.2%), P[5] (8.4%), P[8] (7.0%) , P[6] (12.1%), P[3] (0.9%), P[4] (0.9%) , P[23] (8.73%), P[26] (7.9%), P[19] (7.1%) G5 (40.0%) G5 P[8] (83.3%) P[8] Most prevalent serotype/genotype of RVs of serotype/genotype prevalent Most G5 (71.4%) G5 G5 (20.3%) G5 G5 (29.4%) G5 P[6] (26.7%) P[6] (77.2%) P[7] P[7] (41.7%) P[7]

2011 - 2013 Years 1976

The distribution of the most prevalent serotypes/genotypes of porcine the serotypes/genotypesofof distribution and A most The group prevalent rotaviruses 1976 between

Asia 2 . Africa Europe 1 Australia Location Americas

. Table 2013

TLRs MAMPs/Ligands Reference

TLR1 Triacyl lipopeptides

TLR2 Peptidoglycan

TLR3 Double-stranded RNA

TLR4 Lipopolysaccharide

TLR5 Flagellin

TLR6 Diacyl lipopeptides

TLR7 Single-stranded RNA (319, 320, 345)

TLR8* Single-stranded RNA

TLR9 CpG DNA

TLR10 Unknown

TLR11* Profilin, flagellin

TLR12* Profilin

TLR13* Bacterial 23 S ribosomal RNA

Table 1.3 TLRs and their ligands. * TLR8 expressed in human, not in mouse; TLRs 11-13 expressed in mouse, not in human

Figure 1.1 Schematic representation of a rotavirus virion.

Chapter 2 Comparative in vitro and in vivo studies of porcine rotavirus G9P[13] and human rotavirus Wa G1P[8]

2.1 Abstract

The changing epidemiology of group A rotavirus (RV) strains in humans and swine, including emerging G9 strains, poses new challenges to current vaccines. In this study, we comparatively assessed the pathogenesis of porcine RV (PRV) G9P[13] and evaluated the short-term cross-protection between this strain and human RV (HRV) Wa G1P[8] in gnotobiotic pigs. Complete genome sequencing demonstrated that PRV G9P[13] possessed a human-like G9 VP7 genotype but shared higher overall nucleotide identity with historic PRV strains. PRV G9P[13] induced longer rectal virus shedding and RV

RNAemia in pigs than HRV Wa G1P[8] and generated complete short-term cross- protection in pigs challenged with HRV or PRV, whereas HRV Wa G1P[8] induced only partial protection against PRV challenge. Moreover, PRV G9P[13] replicated more extensively in porcine monocyte-derived dendritic cells (MoDCs) than HRV Wa G1P[8].

The cross-protection was likely not dependent on serum virus neutralizing (VN) antibodies as the heterologous VN antibody titers in the G9P[13]-inoculated pig sera were low. Thus, our results suggest that heterologous protection by the current monovalent G1P[8] HRV vaccine against the emerging G9 strains should be evaluated in clinical and experimental studies to prevent further dissemination of the G9 strains.

Differences in the pathogenesis of these two strains may be partially attributable to their variable abilities to replicate and persist in porcine immune cells, including DCs. 92 Additional studies are needed to evaluate the emerging G9 strains as potential vaccine candidates and to test the susceptibility of various immune cells to infection by G9 and other common HRV/PRV genotypes.

2.2 Introduction

Rotavirus (RV), a member of Reoviridae family, has a double-stranded RNA genome with 11 segments (1). It is the most common pathogen in cases of acute gastroenteritis in children under 5 years of age (1, 2). In the U.S., it causes approximately $1 billion in annual costs due to RV-associated physician visits, emergency department visits and hospitalizations (3-5). Annually, RV causes 440,000 deaths in children under 5 years of age worldwide, with most occurring in developing countries (4). RVs also infect young domestic animals, including calves and piglets (1). RV is responsible for 7-20% and 3-

15% annual mortality in nursing and weaned piglets, respectively (6). The high prevalence of RV in swine results in large economic losses to the pork industry (6).

Treatment of RV infection is only possible by replacing fluids and electrolyte losses, because no specific antiviral therapy is available. Therefore, effective RV vaccines are crucial to prevent morbidity and mortality in both young children and animals (7, 8).

RVs are classified into 8 groups, A to H, as determined by the viral structural protein 6

(VP6) (9-11). Based on the outer capsid VP4 (P genotype)- and VP7 (G genotype)- encoding genes, a binary classification system has been established for RVs (12).

Overall, there are at least 26 G genotypes and 33 P genotypes of group A RVs (RVA)

(13, 14). Globally, the G1-G4, P[4], P[6] and P[8] genotypes are the most prevalent human RVAs (15). RVA G1P[8] is a common human strain worldwide and constitutes 93 more than 70% of prevalent strains in North America, Australia and Europe, but only 20-

35% of circulating strains in South America, Asia and Africa (5, 15-17). G5 and P[7] are historically considered the most prevalent G and P RVA genotypes in swine, respectively

(18). However, recent studies have shown that RVA G9 and G12 genotypes are emerging worldwide in humans and swine (2, 19-23).

Originally reported in human cases in the early to mid-1980s, G9 RV strains spread quickly to all continents in the mid-1990s (24). We recently found that G9 strains are also prevalent in Ohio swine (23). Genetic analyses of the emerging G9 RVs in humans have confirmed that some G9 RV strains are phylogenetically more similar to PRV than the earlier human G9 genotypes (22, 25). The emergence of porcine-like G9 RVs in children in developing countries, in addition to the evidence that G1P[8] may be of swine origin, illustrates the zoonotic potential of animal RVs and collectively suggests that PRVs are a potential source of heterologous RV infections in humans (25).

Recently, a classification system encompassing all 11 RV genome segments was developed using standardized nucleotide identity cut-off values and the notation Gx-P[x]-

Ix-Rx-Cx-Mx-Ax-Nx-Tx-Ex-Hx, which refers to the VP7-VP4-VP6-VP1-VP2-VP3-

NSP1-NSP2-NSP3-NSP4-NSP5/6 gene segments, respectively (9, 12). This system allows for international standardization for analyzing RVA interspecies evolutionary relationships, gene reassortment events, emerging RVA strains and RVA host-range restriction (9, 12). Thus, full genomic sequencing and characterization of G9P[13] viruses allows whole-genome characterization and suggests their zoonotic potential by defining which gene segments are likely of swine or human origin. Knowledge of the pathogenesis

94 and cross-protection potential of G9 RV strains will help to understand mechanisms for the rapid global spread of G9 strains and their ability to infect diverse host species.

Because VP7 and VP4 are targets for neutralizing antibodies which elicit serotype- specific protection, they are critical for vaccine development (8, 26). Currently, two RV vaccines are licensed for humans, Rotarix and RotaTeq. Rotarix is a live attenuated HRV vaccine that has high efficacy in preventing G1, G3 and G4 serotype-induced RV gastroenteritis, while RotaTeq is a live human-animal pentavalent vaccine that has been shown to be highly efficacious in preventing G1-G4 serotype-induced RVA gastroenteritis in developed countries (8). However, the emergence of the G9 and G12 strains may compromise RV vaccine efficacy, as available vaccines do not provide homotypic protection against these emerging strains (26, 27). Therefore, it is critical to assess the ability of historic and emerging RV strains to elicit heterotypic immune responses against emerging and less frequent genotypes of RV to identify potential candidate vaccine strains (15, 27).

There is increasing evidence suggesting that RV can spread extraintestinally (28, 29).

RVs have been shown to cause persistent infection in immunodeficient mice, as well as immunodeficient young children, resulting in diseases such as encephalitis in children

(30, 31). This may be due to the ability of certain RVs to infect non-epithelial cells leading to extraintestinal spread. Our lab has previously confirmed that gnotobiotic (Gn) piglets are susceptible to infection and disease with the virulent HRV Wa G1P[8] strain and infected piglets have transient viremia (32). Others have suggested that in rhesus macaques, rhesus RV (RRV) escapes the intestine via a lymphatic route, with the viral non-structural proteins (NSPs) being sequentially detected in the Peyer’s patches, the 95 mesenteric lymph nodes (MLNs) and spleen and liver (33). RV NSPs have been observed in mouse macrophages, as well as human macrophages, dendritic cells (DCs) and B cells

(34-36). These results suggest that immune cells may be permissive to RV infection and may play a role in RV persistence and extraintestinal dissemination. In this study, we compared the ability of PRV G9P[13] and HRV Wa G1P[8] strains to infect porcine B cells, T cells and monocyte-derived DCs (MoDCs).

Our previous pathogenesis studies have demonstrated that HRV Wa G1P[8] infection of

Gn piglets results in similar clinical disease and comparable levels of pathogenesis, including similar levels of intestinal lesions, to those observed in homologous PRV infections with the OSU and SB1A strains (37); however, only limited pathogenesis studies of G9 PRV strains have been conducted in neonatal piglets. In this study, we inoculated Gn pigs with PRV G9P[13] or HRV Wa G1P[8] to comparatively assess their pathogenesis and cross-protection.

2.3 Materials and Methods

Viruses for inoculation and challenge

The Gn pig-adapted (passage 23) HRV Wa G1P[8] strain (38) and the Gn pig passaged

(passage 2) PRV G9P[13] strain (23) were used at a dose of 105 fluorescent-forming units

(FFUs) for Gn pig inoculation and challenge as described previously (38).

Complete genomic sequencing of PRV G9P[13]

Stool samples from Gn piglets infected with the PRV G9P[13] strain were processed as described elsewhere (23). Viral RNA was then extracted using the RNeasy kit (Qiagen, 96 Valencia, CA, USA) following the manufacturer's instructions. The complete genome sequencing of PRV G9P[13] was conducted as previously described (39).

The complete genomic sequences of this PRV G9P[13] strain was deposited in GenBank under the strain name RVA/Pig-hhp/USA/LS00009-RV0084/2011G9P[13] (accession numbers KR052730 through KR052740). BLAST (blastn) searches

(http://www.ncbi.nlm.nih.gov/) and/or the RotaC v2.0 (http://rotac.regatools.be/) automated genotyping tool classified the full genomic constellations for this strain. The

GenBank accession numbers for the genomic sequences of HRV Wa G1P[8] strain used in this study are FJ423113 through FJ423123.

Animals and experimental design

Gn pigs were hysterectomy-derived and maintained in sterile isolation units as described previously (40, 41). One-week-old piglets (derived from 3 Landrace x Yorkshire sows)

[post-inoculation day (PID) 0] were inoculated with 105 FFU each of PRV G9P[13]

[groups 1 (n=5) and 2 (n=4)] or HRV Wa G1P[8] [group 3 (n=7)] in 3 ml of minimum essential media (MEM) (Life technologies, Grand Island, NY, USA), immediately after administration of 3 ml of 100 mM sodium bicarbonate to reduce gastric acidity. A mock group (n=5) was inoculated with 3 ml of MEM after the sodium bicarbonate inoculation.

Two pigs, from groups 1 and 3, were euthanized one day after diarrhea onset. Three weeks post inoculation [PID 21, post-challenge day (PCD) 0], pigs of group 2 were challenged with 105 FFU HRV Wa G1P[8] and pigs of groups 1, 3 and 4 were challenged with 105 FFU PRV G9P[13], immediately after the administration of 3 ml of 100 mM sodium bicarbonate. All pigs were euthanized 10 days post challenge. All animal 97 experiments were conducted following protocol 2010A00000088 approved by the

Animal Care and Use Committee of The Ohio State University.

Detection of rectal shedding of virus by CCIF

Rectal swabs were collected on PIDs 1-10, 14, and 21, as well as on PCDs 1-7, from all pigs for evaluation of diarrhea and rectal virus shedding as described previously (42). The rectal swab fluid samples were tested by a cell culture immunofluorescence test (CCIF) to quantitate infectious PRV G9P[13] and HRV Wa G1P[8], as described previously (42).

Detection of PRV G9P[13] homologous/heterologous neutralizing antibody titers in convalescent sera using the fluorescent focus neutralization test (FFN)

The homologous/heterologous virus neutralizing (VN) antibody titers in convalescent/hyperimmune sera against PRV G9P[13], HRV Wa G1P[8], PRV OSU

G5P[7] and PRV Gottfried G4P[6] were determined by FFN, as previously described

(43). The VN titer was expressed as the reciprocal of the highest dilution of the serum that reduced the number of infected cell foci by 80%.

Detection of viral RNA in serum by real-time RT-PCR

Blood samples were collected on PIDs 0, 3, 5, 7, 9, and 14, as well as PCDs 3 and 5, from pigs of all treatment groups. Blood samples were centrifuged at 1850 × g for 15 minutes, and sera were collected and stored at -20ºC until tested. An RNeasy Mini Kit

(Qiagen, Valencia, CA, USA) was used to extract RNA from 250µL of each serum sample as per manufacturer’s recommendations. The extracted RNA was stored at -70ºC 98 until tested. Real-time RT-PCR was used for the detection of RVA RNA using NSP3F and NSP3R primers and a QuantiTect SYBR® Green RT-PCR kit (Qiagen, Valencia, CA,

USA) (44). For the real-time RT-PCR the following conditions were applied: incubation for 20 minutes at 50ºC for the reverse transcription reaction and a preheating step at 95ºC for 15 minutes for initial denaturation, followed by 40 PCR cycles at 94ºC for 15 seconds, 56ºC for 30 seconds, and 72ºC for 30 seconds. A melting curve analysis was then performed at 95ºC for 5 seconds, 65ºC for 1 minute and slowly increasing temperatures up to 97ºC over 20 minutes, followed by a 40ºC hold. RNA extraction from a validated RVA-positive sample was used as positive control, while RNA-free water was used as a negative control.

Detection of RV RNA tissue distribution in vivo by real-time RT-PCR

Two pigs, inoculated with PRV G9P[13] or HRV Wa G1P[8], were euthanized one day after diarrhea onset to evaluate tissue distribution of the RV RNA. One Gn pig without

RVA inoculation was used as a negative control. Isolation of mononuclear cells (MNCs) from the ileum, spleen, liver, MLNs and blood was conducted as previously described

(45, 46). RNA extraction was done on 2x106 MNCs from each tissue sample using an

RNeasy Mini Kit (Qiagen, Valencia, CA, USA) following manufacturer’s recommendations. The real-time RT-PCR was conducted as described above.

Examination of PRV/HRV infection of porcine T cells and B cells in vitro

Isolation of MNCs from the ileum, MLNs, spleen and blood of 4-week-old uninoculated

Gn piglets was conducted as previously described (45). Ileal, MLN, splenic and blood T 99 cells were purified by positive selection with mouse anti-porcine CD3 mAb (IgG1)

(Southern Biotech, Birmingham, AL, USA) and goat anti-mouse IgG MicroBeads

(Miltenyi Biotec, San Diego, CA, USA) following the manufacturer’s instructions.

Porcine B cells were purified following the same instructions with mouse anti-porcine

CD21 mAb (IgG1) (Southern Biotech, Birmingham, AL) and goat anti-mouse IgG

MicroBeads. Isolated porcine T cells and B cells were exposed to HRV Wa G1P[8] or

PRV G9P[13] at an MOI=0.4 for 24 hrs in 5% CO2 at 37ºC. Untreated porcine T cells and B cells were cultured for 24 hrs without RV exposure as a negative control. Cells were washed twice and fixed with fixation and permeabilization solution (BD Bioscience,

San Jose, CA, USA) for 20 min. They were then incubated with anti-NSP4 mAb (IgG2a)

(hybridoma cells B4-2 supplied by Dr. H. B. Greenberg) for 40 min at 4ºC and stained by goat anti-mouse IgG2a-RPE (Life Technologies, Grand Island, NY, USA) for 20 min at

4ºC. T cells were washed and stained by mouse anti-porcine CD3-FITC (Southern

Biotech, Birmingham, AL, USA), while B cells were stained by mouse anti-porcine

CD21-FITC (Southern Biotech, Birmingham, AL, USA). Mouse IgG2a-PE and mouse

IgG1-FITC (Southern Biotech, Birmingham, AL, USA) were used as isotype controls.

Acquiring 20,000 events was done using an AccuriC6 flow cytometer (BD Bioscience,

San Jose, CA, USA). Analyses were conducted using CFlow software (BD Bioscience,

San Jose, CA, USA).

Examination of PRV/HRV infection of porcine MoDCs in vitro

Porcine blood from healthy adult pigs was collected with 30% acid citrate dextrose (ACD) anticoagulant. Blood monocytes were isolated using density centrifugation over Ficoll- 100 Paque Premium (1.084 g/ml; GE Healthcare Life Sciences, Uppsala, Sweden) as previously described and then suspended in RPMI Media 1640 (Life Technologies,

Grand Island, NY, USA) and placed in 175 cm2 cell culture flasks (47, 48). After 3-hr incubation at 37ºC, non-adherent cells were removed by washing with cold RPMI Media

1640. The remaining adherent monocytes were cultured in Dulbecco’s Modified Eagle

Medium (DMEM) (Life Technologies, Grand Island, NY, USA) supplemented with 10% heat-inactivated fetal bovine serum (FBS) (Atlanta Biologicals, Flowery Branch, GA,

USA), 1% antibiotic-antimycotic (Anti-Anti) (Life Technologies, Grand Island, NY,

USA), 100 ng/ml of recombinant swine granulocyte-macrophage colony stimulating factor (GM-CSF) (Life Technologies, Grand Island, NY, USA) and 20 ng/ml of recombinant swine interleukin-4 (IL-4) (Life Technologies, Grand Island, NY) in 5%

CO2 at 37ºC for 6 days to differentiate into MoDCs. The cells showed increased size and changes in morphology from round to irregular shapes with cytoplasmic projections as previously described (48). In addition, more than 90% of the cells were determined to be swine workshop cluster 3 (SWC3)-positive by flow cytometry. The MoDCs were exposed to HRV Wa G1P 1A[8] or PRV G9P[13] at an MOI=0.4 for 24 hr. The plates were then fixed with 80% acetone for 10 min at room temperature (RT) and air dried.

Anti-NSP4 mAb was added to each well and incubated at 4ºC overnight. FITC-labeled goat anti-mouse IgG+IgM+IgA (AbD Serotec, Raleigh, NC, USA) diluted 1: 500 was added to each well as a secondary antibody. The plates were incubated at 37ºC for 2 hours and viewed using a fluorescent microscope Olympus IX70 microscope (B&B

Microscopes, Pittsburgh, PA, USA).

101 Statistical analysis

Mean days to onset of virus shedding, average peak virus shedding titer, daily fecal virus shedding, mean days to onset of diarrhea and mean duration days of diarrhea in post- inoculation pigs were analyzed by two-tailed t test. Mean days to onset of virus shedding, mean duration days of virus shedding, average peak virus shedding titer, mean duration days of diarrhea in post-challenge pigs were analyzed by one-way ANOVA. Mean cumulative fecal scores in different treatment groups were compared using the area under the curve as previously described (49, 50). Statistical analyses were performed by

GraphPad Prism 6.0c software (GraphPad Software, La Jolla, CA, USA).

2.4 Results

PRV G9P[13] had high overall identity with historic PRV strains, but possessed a human- like VP7 (G9) genotype.

Complete genomic sequencing of PRV G9P[13] was conducted. Using BLAST (blastn) searches and the RotaC v2.0 automated genotyping tool, the complete genomic constellation for this PRV G9P[13] strain was identified as G9-P13-I5-R1-C1-M1-A8-

N1-T1-E1-H1. Analyses of the complete genomic nucleotide sequences (except for VP7 and VP4) of the PRV G9P[13] demonstrated that this strain shared the highest overall nucleotide identity to OSU strain (RVA/Pig-tc/USA/OSU/1977/G5P7) (89.5%-95.6%) and Mexican YM strain (RVA/Pig-tc/MEX/YM/1983/G11P7) (89.9%-97.7%), followed by Gottfried strain (RVA/Pig-tc/USA/Gottfried/1983/G4P6) (91.3%-92%). A previous phylogenetic tree of the partial (nt 73 to 388) sequence of G9P[13] VP7 gene compared

102 with available VP7 gene sequences for human and porcine RVA G genotypes indicated that this PRV G9P[13] strain shared higher identity with human RVA G9 strains (23).

The nucleotide sequence of the PRV G9P[13] VP7 segment shared the highest nucleotide identity with G9-RVA/Human-wt/BEL/B3458/2003/G9P8 (92.5%).

PRV G9P[13] induced increased fecal virus shedding (longer duration and higher virus loads) compared with HRV Wa G1P[8], but had similar diarrhea severity.

The fecal virus shedding and diarrhea in PRV G9P[13] and HRV Wa G1P[8] inoculated pigs from PIDs 1-10 are summarized in Table 2.1 and shown in Figure 2.1. PRV

G9P[13]- and HRV Wa G1P[8]-inoculated pigs had similar mean days to onset of virus shedding and diarrhea. Interestingly, HRV Wa G1P[8] induced a slightly higher average peak titer (at PID2) of virus shedding in pigs than PRV G9P[13], while PRV G9P[13] induced a numerically higher mean cumulative fecal diarrhea score in pigs than HRV Wa

G1P[8] (Table 2.1).

Fecal virus shedding peaked at PID2 (2.56E+06 FFUs/ml) and then again at PID5 in the

HRV Wa G1P[8]-inoculated pigs [as observed in previous studies (51, 52)] decreasing overall in the following days (PIDs 3-10); whereas, the fecal virus shedding of the PRV

G9P[13]-inoculated pigs peaked at PID 3 (6.73E+05 FFUs/ml), which then maintained higher and at relatively constant levels (1.02E+05 – 1.14E+06 FFUs/ml) through PID 10

(Figure 2.1A). The PRV G9P[13]-inoculated pigs had significantly higher fecal virus shedding titers on PID 6 and PID 10 than the HRV Wa G1P[8]-inoculated pigs (p=0.019 and p=0.021, respectively) (Figure 2.1A). On PID 14, two (out of 8) PRV G9P[13]- inoculated pigs still had detectable levels of fecal virus shedding, while none of the pigs 103 in the HRV Wa G1P[8]-inoculated group still shed virus (data not shown). On PID 21, neither PRV G9P[13]- nor HRV Wa G1P[8]-inoculated pigs had detectable fecal virus shedding (data not shown).

PRV G9P[13] caused higher frequencies of and more prolonged RV RNAemia in piglets, whereas HRV Wa G1P[8] caused only transient RV RNAemia.

In PRV G9P[13]-inoculated pigs, 87.5% and 62.5% of the serum samples were positive for RV RNA on PIDs 3 and 5, respectively (Figure 2.2). In HRV Wa G1P[8]-inoculated pigs, viral RNA was detected only in 50% of serum samples on PID3 and 0% on PID5

(Figure 2.2). None of the serum samples on PIDs 7, 9, or 14, or on PCDs 3 and 5 had detectable levels of RV RNA (data not shown). PRV G9P[13] caused a higher frequency of RV RNAemia in pigs on PID 3 compared with HRV Wa G1P[8] (87.5% vs. 50%), which then persisted for a longer time (PID 5) compared with HRV Wa G1P[8] (PID 5)

(Figure 2.2).

PRV G9P[13] and HRV Wa G1P[8] RNA were detected in extraintestinal tissues of the inoculated-Gn pigs in vivo.

To validate if prolonged RV RNAemia and increased fecal RV shedding were associated with increased extraintestinal spread of PRV G9P[13], two pigs were euthanized one day following diarrhea onset after PRV/HRV inoculation. PRV G9P[13]- and HRV Wa

G1P[8]-inoculated pigs developed diarrhea on PIDs 1 and 2, respectively, and were euthanized on PIDs 2 and 3, respectively. Results of real-time RT-PCR detection of RV

RNA in MNCs of extraintestinal tissues are summarized in Table 2.2. PRV G9P[13] and 104 HRV Wa G1P[8] RNA were detected in MNCs of the ileum and found in MNCs from extraintestinal tissues, including the MLNs, spleen and liver. Only PRV G9P[13] RNA was detected in blood MNCs. These data suggest that PRV G9P[13] and HRV Wa

G1P[8] may induce systemic dissemination that is possibly dependent on circulating

MNCs.

PRV G9P[13] conferred complete short-term (PCDs1-7) protection against homologous/heterologous RV infection and diarrhea.

The virus shedding and diarrhea post-challenge are summarized for all groups in Table

2.3. No pigs from groups 1 (PRV G9P[13]-inoculated pigs) and 2 (HRV Wa G1P[8]- inoculated pigs) shed virus or had diarrhea after PRV G9P[13] (homologous strain) or

HRV Wa G1P[8] (heterologous strain) challenge. Hence, PRV G9P[13] successfully protected against homologous and heterologous RV infection. Five of 6 (83.3%) group 3

(HRV Wa G1P[8]-inoculated) pigs and 5 of 5 (100%) group 4 (mock) pigs shed virus after PRV G9P[13] challenge. HRV Wa G1P[8] did not completely prevent PRV G9P[13] infection, but significantly shortened the duration of virus shedding (p<0.005) and decreased the peak shedding titer (p<0.05) compared to the mock group. None of 4 (0%) group 1 (PRV G9[13]/PRV G9P[13]) pigs, 0 of 4 (0%) group 2 (PRV G9P[13]/HRV Wa

G1P[8]) pigs, 2 of 6 (33.3%) group 3 (HRV Wa G1P[8]/PRV G9P[13]) pigs, and 3 of 5

(60%) group 4 pigs (controls) developed diarrhea. PRV G9P[13] completely protected against homologous/heterologous RV diarrhea; whereas, HRV Wa G1P[8] resulted in a

66.7% protection rate against diarrhea. Therefore, PRV G9P[13] conferred 100% short-

105 term protection against homologous/heterologous RV challenge and diarrhea, whereas

HRV Wa G1P[8] induced lower heterologous protection.

PRV G9P[13] induced low heterologous VN antibody titers against selected porcine and human RVs.

To determine if PRV G9P[13]-induced protection/cross-protection was mediated by systemic (serum) VN antibody against homologous or heterologous HRV Wa G1P[8] challenge, we used FFN to measure the levels of cross-neutralizing antibodies in convalescent/hyperimmune sera against PRV G9P[13] and other selected RVs (HRV Wa

G1P[8], PRV OSU G5P[7], PRV Gottfried G4P[6]) isolated in our lab (53). The VN antibody titers and the relatedness (R%) values for convalescent or hyperimmune sera against selected RVs are summarized in Table 2.4. The PRV G9P[13] convalescent sera showed weak reactivity with other historic porcine or human RVs, suggesting that the heterologous protection against HRV Wa G1P[8] was not dependent on the heterotypic serum VN antibody titers. Similarly, HRV Wa G1P[8] hyperimmune sera had low titers of heterologous VN antibody that varied for the different PRVs.

In vitro, both PRV G9P[13] and HRV Wa G1P[8] NSP4 viral antigens were detected in porcine MoDCs at an MOI=0.4, but not in porcine T cells and B cells.

MoDCs were used in this study to determine if PRV G9P[13] and HRV Wa G1P[8] replicate in porcine DCs based on detection of RVA NSP4 antigen by immunofluorescence assay. The untreated MoDCs had distinct branched projections which are typical morphologic characteristics of DCs (Figure 2.3A) (48, 54). Four hours 106 after RV exposure, no distinct immunofluorescence was observed in PRV G9P[13]- or

HRV Wa G1P[8]-exposed MoDCs (Figure 2.3 B and C). Twenty four hours after RV exposure, granular immunofluorescence was observed in both PRV G9P[13]-exposed

MoDCs and HRV Wa G1P[8]-exposed MoDCs (Figure 2.3 D-G). A population of PRV

G9P[13]-exposed MoDCs exhibited distinct granular immunofluorescence with perinuclear cytoplasmic distribution (Figure 2.3 D and E), while HRV Wa G1P[8]- exposed MoDCs exhibited less immunofluorescence in the cytoplasm of the infected cells and there were lower frequencies of HRV Wa G1P[8]-infected MoDCs than PRV

G9P[13]-infected MoDCs (Figure 2.3 F and G). In the PRV G9P[13]-positive MoDCs and HRV G1P[8]-positive MoDCs, the immunofluorescence was concentrated in cytoplasmic granules that might correspond to viroplasmic inclusions (Figure 2.3 D and

E). The results suggested that PRV G9P[13] replicated in MoDCs to a greater extent than

HRV Wa G1P[8]. After RV exposure, no NSP4-positive (NSP4+) T cells were detected in RV-exposed T cells or T cells of the untreated group (data not shown). Similar result was observed for porcine B cells (data not shown), suggesting that porcine T cells and B cells were not susceptible to infection by PRV G9P[13] or HRV Wa G1P[8] in vitro.

2.5 Discussions

Increasing RV group A strain diversity, including the worldwide emergence of G9 strains, poses new challenges to existing RV vaccines for humans and swine (19, 55).

Therefore, it is necessary to genetically and biologically characterize the emerging G9 strains and to investigate whether the current human RV vaccines could elicit sufficient heterotypic protection against the heterologous G- and P- type emerging strains. In this 107 study, we chose the dominant G-P combination strain in Ohio swine, PRV G9P[13], and a prevalent human strain and the G-P combination used in the Rotarix vaccine, HRV Wa

G1P[8], to comparatively study their pathogenesis and cross-protection in Gn piglets and to examine the factors influencing PRV G9P[13] pathogenicity and spread.

The high overall nucleotide identity between PRV G9P[13] and historic PRV strains suggests the relative genetic stability of PRVs. Therefore, the human-like G9 VP7 genotype of this PRV G9P[13] strain is likely emerged from reassortment events (56, 57).

Recent studies have confirmed that some emerging G9 RVs in humans were phylogenetically more similar to PRVs than to the earlier human G9 genotypes, suggesting that PRVs are probable sources of heterologous RV infections in humans (22,

25). Since the majority of serotype-specific antigenic regions of VP7 were expected to be conserved among RVs of the same G type (58), and the VP7 nucleotide of this PRV

G9P[13] strain was most similar to a human G9 strain, it is plausible to extrapolate our data obtained by evaluating the cross-protection of PRV G9P[13] and HRV Wa G1P[8] in Gn pigs to predict if current vaccines can confer heterotypic protection against the emerging G9 strains in humans. We found that PRV G9P[13] inoculation conferred complete short-term protection against homologous (PRV G9P[13]) and heterologous

(HRV Wa G1P[8]) RV infection and diarrhea, whereas HRV Wa G1P[8] inoculation provided partial heterologous protection against diarrhea and minimum heterologous protection against virus shedding after PRV G9P[13] challenge. Our results suggest that the current vaccine (Rotarix) for humans might not protect sufficiently against the emerging G9 strains.

108 The introduction of RV vaccines may result in an additional selective pressure on circulating RV strains and affect their evolutionary rates (20). If vaccine-induced selective pressure against G9 strains is lacking, then this could facilitate the rapid global spread of the G9 strains. As the commercially available PRV vaccines include only G4 and G5 PRV strains, a similar scenario may occur in swine, that the current PRV vaccines may be lack of effective protection against the emerging G9 strains and contribute to the dominance of G9 strain in Ohio swine and the fourth dominance in the swine population of Americas (18, 23). However, a recent study demonstrated that the A2 strain (previously identified as a G4 PRV strain) in a commercial PRV vaccine was in fact a G9 strain (59). If so, the prolonged administration of this vaccine could have introduced G9 strain into the swine population that had no herd immunity against G9.

This may provide a potential explanation for the emergence and subsequent widespread of the G9 strains in swine in the U.S and even a potential zoonotic transfer of reassortant

G9 variants to humans.

The short-term cross-protection observed in pigs was likely not dependent on serum VN antibody titers. Similarly, previous studies indicated that protection against RV diarrhea was not dependent on EDIM-specific neutralizing antibody (60-62). Consistent with previous studies, we also observed that PRV G9P[13] induced low heterologous VN antibody titers in convalescent sera. The results suggest that there are other factors associated with the high levels of cross-protection, including up-regulated innate and mucosal or cellular immune responses possibly enhanced by the extended and significantly higher magnitude of PRV G9P[13] replication in vivo (61). Recent studies demonstrated that interferon-lambda (IFN-λ) played a role in the intestinal epithelial 109 antiviral responses to RV infection in neonatal mice (63, 64). Moreover, IFN-λ had a more important role in restricting the early replication of heterologous RV strains in suckling mice compared to the effects of controlling homologous RV replication (65).

Small intestinal mature enterocytes are the main target for RVs, which infect and destroy them, causing diarrhea (66, 67). Pathogenic RVs replicated faster in piglets and calves than apathogenic RVs, with the enterocyte losses from pathogenic RV infection surpassing their physiologic replacement (68-70). The similar diarrhea severity between

PRV G9P[13]- and HRV Wa G1P[8]-inoculated pigs indicated that these two RVA strains might have similar replication rates in the mature enterocytes of the small intestine causing similar damage to the gut epithelium. In one study, RV antigen (VP6) and infectious virus (using NSP4 detection as an indicator of virus replication) were detected in multiple organs of RRV-inoculated neonatal rats (29). In a retrospective study, 34 of

353 (9.6%) children with confirmed RV gastroenteritis had extraintestinal RV infection and central nervous system complications (71). Moreover, an in vitro study indicated that

RV NSPs were expressed in human PBMCs after in vitro exposure to RRV, and the expression levels of the RRV NSPs varied in T cells, B cells, NK cells, monocytes, and

DCs (35). Our studies indicated that PRV G9P[13] and/or HRV Wa G1P[8] may infect

MNCs in the small intestine and/or adjacent lymph nodes, facilitating subsequent RV extraintestinal spread.

We observed prolonged RV RNAemia (suggestive of viremia) in PRV G9P[13]- inoculated pigs (at least from PIDs 3 and 5), and transient RV RNAemia in HRV Wa

G1P[8] inoculated pigs (only on PID 3). Our current results are consistent with a previous study from our lab showing that HRV Wa G1P1[8] caused transient RV RNAemia in Gn 110 pigs (32). However, we detected HRV Wa G1P[8] RV RNAemia at a lower frequency compared to the previous study. This may be due to the use of a lower inoculation dose

(105 FFUs vs. 106 FFUs) or the different time points selected for RV RNAemia detection

(PID 3 vs. PID 1). In addition to in sera, PRV G9P[13] and HRV Wa G1P[8] RNA was also detected in MNCs from the MLNs, spleen and liver. This result is in accordance with the detection of extraintestinal RRV in the neonatal mouse model after oral inoculation

(33). Furthermore, we found viral RNA in blood MNCs of PRV G9P[13]-inoculated pigs, but surprisingly not in blood MNCs from HRV Wa G1P[8]-inoculated pigs. The RV extraintestinal spread assessment in the neonatal mouse model after oral inoculation with

RRV, SA11-clone 4 and several single-segment reassortant viruses confirmed the ability of RVs to spread beyond the gut, which was primarily determined by the NSP3 phenotype and secondarily modified by VP6 (33, 72). Therefore, the different disseminating modes between the two RVA strains in our study might due to different

VP6 (I5 vs. I1) genotypes and variations within the NSP3 sequences (T1).

Recent studies demonstrated that RRV and HRV Wa could infect human intestinal and blood B cells, and the susceptibility was dependent on the B cell state and tissue origin

(73). In our study, however, we failed to detected RV NSP4 antigen using flow cytometry in T cells and B cells isolated from different tissues (ileum, MLNs, spleen and blood) of uninoculated Gn pigs after exposed to PRV G9P[13] and HRV Wa G1P[8] in vitro (data not shown). In the study conducted by Narváez et al., an MOI of 5 was used to infect human B cells with primarily mature B cell subsets being infected, whereas the MOI we used was only 0.4, the neonatal Gn pig B cells we used may be less mature and not in the same status (73). Conversely, we found RV NSP4 antigen in PRV G9P[13]-exposed 111 MoDCs (same MOI of 0.4) using immunofluorescence. As a type of professional antigen presenting cells (APCs), DCs can take up and digest pathogens to present antigen to other immune cells to activate the adaptive immune responses (74, 75). After phagocytosis, the acidification of the phagosomal and lysosomal fusion in mouse bone marrow-derived macrophages was achieved within 15 minutes and 2 hours, respectively, suggesting the rapid antigen degradation in macrophages (76). However, the antigen degradation capacity in either bone marrow-derived DCs in vitro or splenic and lymph node DCs in vivo indicates that the activity of phagosomal acidification and degradation is much lower in DCs than in macrophages and neutrophils, especially in immature DCs (77-79).

Conflictingly, recent studies found that human MoDCs in contrast to other types of human DCs, had similar lysosomal proteolysis levels and antigen degradation capacities as macrophages (80). Additionally, MoDCs could rapidly and efficiently take up antigens from the environment (81). Therefore, we hypothesized that if RVs were unable to replicate in MoDCs, RVs would be taken up and rapidly digested by the MoDCs. In our study, we did not detect any RV NSP4 antigen in MoDCs after 4 hours exposure to PRV

G9P[13] or HRV Wa G1P[8], but we found NSP4 antigen in DCs 24 hours after exposure. This result suggested that the RV NSP4 antigen that we detected in DCs after

24 hours of RV exposure was not accumulated by DC engulfment, but was due to RV replication in DCs. In studies of NSP4 using enhanced green fluorescent protein (NSP4-

EGFP) in HEK 293 “Tet-on” cells, Berkova et al. found that NSP4-EGFP was expressed and distributed in novel vesicular structures throughout the cytoplasm and associated with viroplasms (82). This evidence supports our findings that PRV G9P[13] likely replicated and formed viroplasms in MoDCs. However, we do not know if RV infectious 112 particles can be efficiently released from DCs to facilitate viral dissemination. More studies are required to verify this hypothesis.

In this study, we demonstrated that PRV G9P[13] induced prolonged fecal virus shedding and RV RNAemia compared to HRV Wa G1P[8]. This may be associated with the capacity of PRV G9P[13] to spread more efficiently beyond the gut and to replicate more in porcine immune cells (MoDCs) than HRV Wa G1P[8]. These characteristics of the G9 strain may contribute to its dominance in Ohio swine. To our knowledge, this is the first report of heterologous protection between an emerging G9 strain and a HRV vaccine-like

G1 strain. Our data suggest that heterologous protection by the current monovalent

G1P[8] HRV vaccine against the current worldwide emerging RVA G9 strains should be evaluated further in relevant clinical and experimental studies. A similar scenario may be observed in swine populations, where current G4 and G5 based PRV vaccines may be ineffective against emerging porcine G9 strains, which also requires further studies. This may facilitate the increased global spread of RVA G9 strains. However, another study demonstrated that the A2 strain in the commercial PRV vaccine in the U.S. in fact included the G9 PRV strain and not a G4 strain (59). We hypothesize that the use of this vaccine might have contributed to the diversity of G9 strains in the swine populations.

Moreover, the potent short-term heterotypic protection induced by PRV G9P[13] was not dependent on the heterologous serum VN antibody titer, but might rely on its potential to evoke IFN-λ responses or other mucosal or cellular immune responses. More studies on the long-term protection and immunogenicity of attenuated and virulent PRV G9P[13] using higher numbers of Gn piglets, and vaccination regimens allowing booster vaccinations (as done for current RV vaccines) are required to confirm and elucidate the 113 mechanisms of heterotypic protection. Such data will aid in candidate vaccine strain selection and provide strategies for future RV vaccine design.

2.6 Acknowledgements

We thank Dr. Juliette Hanson, Ronna Wood, Jeff Ogg for animal care. This work was supported in part by the Ohio Agricultural Research and Development Center (OARDC),

Ohio State University SEED grant (2011-077), and a National Pork Board grant (NPB

12-094) and the OARDC student SEED grant (2013-090). Genomic sequencing was supported in part with US federal funds from the National Institute of Allergy and

Infectious Diseases, National Institutes of Health, Department of Health and Human

Services under contract number HHSN272200900007C (Genome Sequencing Center for

Infectious Diseases) and grant number U19AI110819 (Genomic Centers for Infectious

Diseases).

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122

16.9 13.8 Mean Mean cumulative fecalscore ere scored as ere scored as

5.5 4.7 days Mean Mean duration culation)/N]

Diarrhea ino inoculation pigsfromtoPID1inoculation

- - 1.9 1.7 diarrhea to onset of Mean days Mean

100 100 % with with % diarrhea

1.66E+06 3.30E+06

(FFU/ml) titershed Avg. peak peak Avg.

days 1.4 1.8 shedding to onset of Mean Mean Virus shedding Virus

100 100 % shed %

8 6 N

Virus shedding and diarrhea in PRV G9[13] and HRV WaHRVdiarrheaG1P[8] PRV post Virus G9[13] and and inshedding

1 .

. 2 Inoculation PRV G9P[13] Mean cumulative of days[(sumcumulative consistency scorefor fecal Mean10 score = fecal post withdiarrheaby daysof w ofscore≥ 2. Fecal Durationdetermined numberdiarrheadiarrhea was HRV Wa G1P[8] Wa HRV

Table PID10 a follows: pasty;2 liquid.1 normal;3 0 = = = semiliquid; = b

123

MNCs from different tissues Virus Ileum MLNs Spleen Liver Blood

PRV G9P[13] + + + + +

HRV WA G1P[8] + + + + -

Table 2.2 RVA detection in MNCs from ileum, MLNs, spleen, liver and blood of PRV G9P[13] and HRV Wa G1P[8] inoculated pigs.

124

- 100 100 (%)

66.7 . against against ion rate rate ion Protect diarrhea

- 100 100 (%) 16.7 against against ion rate rate ion Protect shedding

5 7 4.3 6.2 fecal Mean Mean score cumulative

0 0 0.7 1.2 days Mean Mean inoculation)/N] Diarrhea - duration

0 0 60 33.3 % with with % diarrhea

titer shed shed Avg. Avg. peak ≤ 12.5 ≤ 12.5 3.33E+03 4.26E+05 (FFU/ml)

challenge pigs PCD1 topigs different groups challengeof treatmentfrom PCD7 0 0 - 1.3 5.4 days Mean Mean duration

Virus shedding Virus - - 2.8 1.2 Mean Mean days to onset of of onset shedding shedding.offecal determined numberdetectable wasvirus withby days

0 0 % 100 83.3 shed

4 4 6 5 N

PRV PRV G9P[13] G9P[13] G9P[13] HRV WaHRV lative fecal score = [(sum of fecal consistency score for 10 score= fecal post oflative days[(sumconsistency score for fecal Treatment Treatment G1P[8] Wa Mock/PRV /challenge) (inoculation G1P[8]/PRV G1P[8]/PRV G9P[13]/PRV G9P[13]/PRV G9P[13]/HRV G9P[13]/HRV Diarrhea andin sheddingrectal Diarrhea virus post

3 . 2

1 2 3 4 Group scoredasseverity withdiarrheaby dayswasof ofscore≥ 2. Diarrhea0 Duration determined numberdiarrhea was follows: Virus shedding mean duration Virus mean shedding days cumu Mean

Table a b = = = semiliquid; = pasty; 2 liquid. 1 normal; 3 c

125 ), ), 2 r

× 1 r √ ( ×

%=100 R 8(1.5) 71(15) heterologous titeris the 64(3.5)

2 2000(100) r G4P[6] (HI) G4P[6] @PRV Gottfried Gottfried @PRV

37(4.2) 254(1.5) 1024(12) 4400(100) G5P[7] (HI) G5P[7] @PRV OSU OSU @PRV logous titer strain logous oftiter 1, and

5(0.12) 4436(15) 1437(4.2) 6856(100) G1P[8] (C) G1P[8] @HRV Wa Wa @HRV % values) against selected selected values)against%RVs R Convalescent (C) or hyperimmune (HI) sera (HI) hyperimmune or (C) Convalescent

8(0.12) @PRV @PRV 256(12) 156(3.5) 4096 (100) 4096 G9P[13] (C) G9P[13]

Virus neutralizing antibody titer (and titer Virus antibody neutralizing

Virus is the heterologous titer of strain divided theheterologousstrain oftiterhomo 2 by is the

4 1 . r 2 PRV G9P[13] HRV Wa G1P[8] Wa HRV PRV OSU G5P[7] PRV OSU % values are indicated in parentheses in cases where they were possible to calculate, astowere are caseswhere possible valuesparentheses %calculate, indicated they infollows: in PRV Gottfried G4P[6] PRV Gottfried Table R where 2. divided the strain of homologous strain 1 by of titer

126

Figure 2.1 Fecal virus shedding (A) and diarrhea scores (B) and in PRV G9P[13] and HRV Wa G1P[8] inoculated pigs from PID1 to PID10. Gnotobiotic pigs were orally inoculated with 105 FFU PRV G9P[13] or HRV Wa G1P[8]. Mocks were inoculated with virus suspension media (MEM). Rectal swabs were collected daily. Fecal consistency was scored as followed: 0 = normal, 1 = pasty, 2 = semiliquid, 3 = liquid, with scores of ≥ 2 considered diarrhea. Virus shedding was determined by CCIF. * p ≤ 0.05.

127

Figure 2.2 RV viral RNA detection in PRV G9P[13] or HRV Wa G1P[8] inoculated pig sera on PID3 and PID5. Serum was extracted from blood collected from piglets on PIDs 0, 3 and 5. Viral RNA was extracted and detected by real-time RT-PCR.

128

Figure 2.3 RVA anti-NSP4 antigen detection in untreated, PRV G9P[13] or HRV Wa G1P[8] exposed MoDCs. (A) MoDCs were incubated without RV for 24 hours. (B) MoDCs were exposed to PRV G9P[13] for 4 hours. (C) MoDCs were exposed to HRV G1P[8] for 4 hours. (D, E) MoDCs were exposed to PRV G9P[13] for 24 hours. (F, G) MoDCs were exposed to HRV G1P[8] for 24 hours. (H, I) NSP4-positive of PRV G9P[13]-exposed MoDCs visualized by fluorescent and light microscopy, respectively. The protracting dendrites (A) and (D, E, G, H, I) NSP4-positive cells are labeled with white arrows. The condensed green fluorescent granular particles in the cytoplasm surrounding the nucleus may represent viroplasmic inclusions. The white scale bars represent 200 µm.

129

Chapter 3 Tissue-specific mRNA expression profiles of porcine Toll-like receptors at different ages in germ-free and conventional pigs

3.1 Abstract

Toll-like receptors (TLRs), key initiators of innate immune responses, recognize antigens and are essential in linking innate and adaptive immune responses. Misrecognition and over-stimulation/expression of TLRs may contribute to the development of chronic inflammatory diseases and autoimmune diseases. However, appropriate and mature TLR responses are associated with the establishment of resistance against some infectious diseases. In this study, we assessed the mRNA expression profile of TLRs 1-10 in splenic and ileal mononuclear cells (MNCs) and dendritic cells (DCs) of germ-free (GF) and conventional pigs at different ages. We found that the TLR mRNA expression profiles were distinct between GF and conventional pigs. The expression profiles were also significantly different between splenic and ileal MNCs/DCs. Comparison of the TLR expression profiles in GF and conventional newborn and young pigs demonstrated that exposure to commensal microbiota may play a more important role than age in TLR mRNA expression profiles. To our knowledge, this is the first report that systematically assesses porcine TLRs 1-10 mRNA expression profiles in MNCs and DCs from GF and conventional pigs at different ages. These results further highlighted that the commensal microbiota of neonates play a critical role through TLR signaling in the development of systemic and mucosal immune systems.

130

3.2 Introduction

Toll-like receptors (TLRs) are a type of pattern recognition receptor (PRR) that interact with microbe-associated molecular patterns (MAMPs) and activate signaling pathways to induce innate immune response and also to initiate specific adaptive immune responses

(1, 2). There are 11 TLR family members in humans, among them, TLR11 is a pseudogene (3, 4). Human TLRs 1 to 10 are divided into two subpopulations according to their cellular localization (2, 3). TLRs 1, 2, 4, 5, 6 and 10 are localized to the cell surface, while TLRs 3, 7, 8, 9 are primarily localized in intracellular vesicles such as the endosome and the endoplasmic reticulum (2, 5, 6). To date, MAMPs for all human TLRs, with the exception of TLR 10, have been identified (6, 7). The MAMPs for human TLRs

1-9 are triacyl lipopeptides, peptidoglycan, double-stranded RNA, lipopolysaccharide, flagellin, diacyl lipopeptides, single-stranded RNA (TLR7/8), CpG DNA, respectively

(6). After recognizing specific MAMPs, signaling pathways downstream of the TLRs are triggered and type I interferon (IFN) and inflammatory cytokines are produced (1, 8).

Moreover, TLRs recognize numerous synthetic (imiquimod) and endogenous ligands

[danger-associated molecular patterns and products of damaged tissue (heat shock proteins, endoplasmin)] and play a crucial role in shaping intestinal immune function and maintaining gut homeostasis (9, 10).

TLRs are mainly found in tissues and cells involved in immune function, such as mesenteric lymph nodes (MLNs) and the spleen, as well as those exposed to the exterior environment such as mucosa (including epithelial cells and subepithelial components) in the intestine and the lung (11). The expression profiles of TLRs differ among tissues and 131 cell types (11-13). For example, the TLR4 mRNA expression was higher in murine

CD11c+ splenic DCs than in CD11c+ lamina propria DCs, whereas the TLR5 mRNA expression showed the opposite trend (14). Among these immune cells, dendritic cells

(DCs) are critical mediators to achieve TLR signaling functions (15, 16). Additionally,

DCs in different anatomical locations have varying functions, which may be associated with the different TLR mRNA expression profiles (14, 17). For instance, murine naïve

CD4+ T cells activated by DCs from the Peyer’s patches (PP) produced higher levels of interleukin 4 (IL-4) and IL-10 than those activated by splenic DCs (17); mucosal DCs promoted the differentiation of Th17 cells and contributed to IgA B cell class switching

(18, 19). Therefore, it is necessary to assess and compare the TLR expression in DCs from different anatomical sites.

Although TLRs are important for host defense, recognition of self-molecules by TLRs and loss of negative balancing of TLR signals are associated with pathological (chronic) inflammation and autoimmune disease (20-22). This has led to an increase in the study of

TLRs as therapeutic targets for immune disorders (23, 24). Currently, most models tested are in vitro or murine models in vivo (24). However, as demonstrated by the different expression patterns of TLR4 in monocytes and macrophages after LPS treatment, the expression and regulation of TLR function differs between mice and humans (25-27).

This suggests that the murine model may not be adequate for studies of human TLRs and highlights the need for alternative animal models. Pigs are being increasingly recognized and used as a relevant model for studies of infectious disease and human immunity (28-

33); however, knowledge of the porcine TLR expression and function is limited in comparison to mice and humans. Existing evidence suggests that the pig TLR system 132 may be closer to that of humans than the murine system is (27, 34). Although, porcine, human and murine TLR4 promoter sequences were similar, murine TLR4 promoter exhibited significant differences in the regulation of gene expression; whereas porcine

TLR4 promoter shared more common features with the human TLR4 promoter (35, 36).

More studies of porcine TLR expression and function are needed to evaluate if the pig model can effectively mimic and predict human conditions and outcomes.

The immune system of the neonate is less developed than that of the adult and this may extend to TLR expression (37-39). There are two important periods during the development of the immune system – immediately after birth and after weaning. In the former period, neonates are exposed to non-sterile environments, and in the later period, the organism undergoes extensive exposure to new antigens due to the introduction of solid food and non-milk based diets (37). Therefore, in addition to adulthood, birth and weaning were chosen as two important time points for examination in this study.

Additionally, this study used germ-free (GF) animals to provide a comparative control to define how the microbiota/diet affects the developing immune system (38, 40, 41).

We assessed the TLR1-10 mRNA expression profiles in mononuclear cells (MNCs) and

DCs from spleen, ileum and MLNs in GF and conventional pigs at newborn, weaning and adult stages to compare the difference of TLR mRNA expression in tissue-specific and age-dependent manner.

133 3.3 Materials and Methods

Animals and experimental design

GF pigs (Landrace × Yorkshire × Duroc) were hysterectomy-derived, fed with cow milk and maintained in sterile isolation units as described previously (42, 43). Specific pathogen-free conventional pigs (Landrace × Yorkshire × Duroc) were naturally derived from Landrace × Yorkshire sows bred to Duroc boars, nursed on the sows until 3 weeks then switched to plant based solid diet. One- to 4-day-old and 4-week-old GF and conventional piglets were euthanized and ileum, spleen and MLNs were collected

Additionally ileum, spleen and MLNs were collected from conventional adult pigs

(Landrace × Yorkshire) (at the average age of 10 – 11 months). As no GF adult pigs were available due to facility limitations (inability to maintain adult pigs in GF isolators); there was no GF adult pig group. 4 pigs were used for each group.

Isolation of MNCs and DCs from spleen, ileum and MLNs

MNCs were isolated from spleen, ileum and MLNs as described previously (28). MNC numbers were too low to yield adequate amounts of DCs from newborn pigs for further study. Cell separation buffer (MACS buffer) consisted of PBS, 2 mM EDTA and 0.5%

BSA, filtered sterilized and stored at 4ºC. MNCs were counted and centrifuged at 300g for 10 min at 4ºC. The pellet was resuspended in 1 mL MACS buffer per unit (107

MNCs/unit), centrifuged at 300g for 10 min at 4ºC. The cell pellet was resuspended in 80

µL MACS buffer per unit, followed by the addition of 10 µL of mouse anti- porcine CD3 antibody (Ab) (IgG1) (SouthernBiotec, Birmingham, Alabama, USA), 10 µL of mouse anti-porcine CD21 Ab (IgG1) (SouthernBiotec, Birmingham, Alabama, USA), 2.5 µL of 134 mouse anti-porcine SWC1 Ab (IgG2b) (AbD Serotec, Raleigh, NC, USA), and 2.5 µL of mouse anti-porcine SWC9 Ab (IgG1) (AbD Serotec, Raleigh, NC, USA), that binding with the surface marker of T cell, B cell, granulocyte/monocyte and macrophage respectively, then mixed gently and incubated at 4ºC for 20 min. The cells were then washed with 1 mL MACS buffer per unit of MNCs and centrifuged at 300g for 10 min at

4ºC. The cell pellet was resuspended in 80 µL of MACS buffer, followed by the addition of 20 µL of anti-mouse IgG MicroBeads (Miltenyi Biotec, San Diego, CA, USA) per unit of MNCs, and gently mixed and incubated at 4ºC for 20 min. The cells were washed with

1 mL MACS buffer per unit of MNCs and centrifuged at 300g for 10 min at 4ºC, followed by resuspension in 500 µL of MACS buffer. LD columns (Miltenyi Biotec, San

Diego, CA, USA) were placed on QuadroMACSTM separator (Miltenyi Biotec, San

Diego, CA, USA) followed by adding the MNCs for DC negative selection, following the manufacturer’s recommendations.

Examination of isolated DC purity by flow cytometry

As described previously, 105 cells were stained with mouse anti-porcine CD3e-FITC

(SouthernBiotec, Birmingham, Alabama, USA), mouse anti-porcine CD21-FITC

(SouthernBiotec, Birmingham, Alabama, USA), mouse anti-porcine SWC1-FITC (AbD

Serotec, Raleigh, NC, USA) and mouse anti-porcine SWC9-FITC (AbD Serotec,

Raleigh, NC, USA) monoclonal antibodies (mAb) to characterize the frequencies of T cell, B cell, granulocyte/monocyte and macrophage and to determine the purity of isolated DCs by flow cytometry (44). Acquisition of 50,000 events was conducted using

MACSQuant® Analyzer flow cytometer (Miltenyi Biotec, San Diego, CA, USA). 135 Analyses were performed using MACSQuantifyTM software (Miltenyi Biotec, San Diego,

CA, USA).

RNA extraction and cDNA synthesis

RNA extraction was conducted on isolated MNCs or DCs from each tissue sample using a RNeasy Mini Kit (Qiagen, Valencia, CA, USA) following the manufacturer’s recommendations. Concentration and purity of RNA were assessed by NanoDrop 2000c spectrophotometer (Thermo Scientific, Wilmington, DE, USA). RNA was stored at -80ºC until used. SuperScript® III First-Strand synthesis kit (Life Technologies, Carlsbad, CA,

USA) was used to synthesize cDNA from the sample RNA. 30 ng total RNA was used in

20 µL of the reaction system following the manufacturer’s recommendations. The synthesized cDNA was stored at -20ºC until used.

TLR mRNA expression detection by real-time PCR

Construction of plasmid vector pUC57 with target mRNA sequences of porcine TLR1-10 was conducted by GenScript (Piscataway, NJ, USA). Standard curves of TLRs were calculated depending on known concentrations of plasmid at the PCR cycle and the relative Ct value. Real time PCR was conducted to detect the porcine TLR mRNA expression in different tissue origin MNCs/DCs using LightCycler® 480 SYBR Green I

Master (Roche, Indianapolis, IN, USA). 1 µL of synthesized cDNA was used in every real-time PCR reaction. The primers used in this experiment are listed in Table 3.1. For the real-time PCR, the following conditions were applied: 95ºC for 15 min for initial denaturation, followed by 40 PCR cycles at 94ºC for 10 sec, 57ºC for 15 sec, and 70ºC 136 for 20 sec. A melting curve analysis was then performed. RNA-free water was used as a negative control. All samples were tested in duplicate.

Statistical analysis

All quantitative real-time PCR data were transferred from the mean Ct value of replicated samples to copy number according to the established standard curve. Differences in mean values between groups were analyzed by two-tailed t test and were defined as significant at p < 0.05. Statistical analyses were performed by GraphPad Prism 6.0c software

(GraphPad Software, La Jolla, CA, USA).

3.4 Results

The purity of DCs in negative selected cells was high.

The percentages of T cells, B cells, monocytes/granulocytes and macrophages in the negatively selected cells were assessed using CD3, CD21, SWC1 and SWC9 mAbs, respectively. The percentage of T cells in the negatively selected cells was 0.78%-3.06%.

B cells presented 1.46%-4.21% in the selected cells. There were 0.15%-0.75% and

0.36%-1.43% of monocytes/granulocytes and macrophages in the selected cells. The low amount of T cells, B cells, monocytes/granulocytes and macrophages in the negative selected MNCs demonstrated the high purity of isolated DCs.

TLR mRNA expression profiles differed between GF and conventional pigs.

The mRNA expression levels of TLRs 1-10 in splenic MNCs were generally higher in newborn conventional piglets as compared to newborn GF piglets, whereas, the 137 expression levels were greater in young GF pigs than young conventional pgs. In the newborn (1-4 day-old) pigs, TLRs 1, 2, 4, 6, 7, and 8 mRNA expression levels in splenic

MNCs were higher in conventional pigs compared to GF pigs, particularly TLR2 and

TLR4 which showed statistically significant differences between the two groups (Figure

3.1A). In contrast, TLRs 3, 5, 9 and 10 had equal or lower expression levels in the conventional pigs compared to GF pigs (Figure 3.1A). However, the expression levels in ileal MNCs did not show any significant differences between newborn conventional and

GF pigs (data not shown). In young (4-week-old) GF and conventional (weaned at 3- week-old) pigs, splenic MNCs of GF pigs had significantly higher TLR mRNA expression levels, with the exception of TLR9 which, while still higher in GF pigs, showed no statistically significant difference between the two groups (Figure 3.2A).

Interestingly, the TLR mRNA expression profile in ileal MNCs of young pigs displayed the opposite trend to what was observed in splenic MNCs. Ileal MNCs from conventional young pigs generally had higher (TLRs 3, 5, 7 and 8) and significantly higher (TLRs 1, 2,

4, 6, 9 and 10) TLR mRNA expression levels than in GF young pigs (Figure 3.2B).

Most TLR mRNA expression levels were higher in splenic MNCs than in ileal MNCs of conventional newborn pigs, GF young pigs and conventional adult pigs.

In conventional newborn pigs, most of the TLR mRNA expression levels were higher in splenic MNCs than in ileal MNCs, particularly those of TLR 1, 2 and 4, which had significantly higher expression levels in splenic MNCs; whereas, the expression of TLRs

3, 5 and 9 was greater in ileal MNCs (Figure 3.1B). However, there was no significant difference in the expression levels between splenic MNCs and ileal MNCs in GF 138 newborn pigs (data not shown). In young GF and conventional pigs, there were significant differences of TLRs mRNA expression profile between splenic and ileal

MNCs. In GF young pigs, TLR mRNA expression levels were statistically higher in splenic MNCs than ileal MNCs, with the exception of TLR5 (Figure 3.2C). In conventional young pigs, mRNA expression levels of TLRs 1, 5 and 9 were significantly higher in ileal MNCs than in splenic MNCs, whereas, TLRs 2, 3, 4 and 8 mRNA expression levels were lower in ileal MNCs than in splenic MNCs (Figure 3.2D). In conventional adult pigs, ileal MNCs, except TLR5, showed the lowest TLR mRNA expression levels among three different tissue-derived MNCs (spleen, ileum and MLNs)

(Figure 3.3A). There was no statistical difference of TLR5 mRNA expression level among splenic, ileal and MLN MNCs (Figure 3.3A). In addition, splenic MNCs had significantly higher mRNA expression levels of TLRs 2, 3, 4, 8 and 9 than MLN MNCs in adult conventional pigs (Figure 3.3A).

TLR mRNA expression levels were increased in splenic MNCs, but decreased in ileal

MNCs of young compared to adult conventional pigs.

TLR mRNA expression levels in splenic MNCs of conventional newborn pigs showed inconsistent trends when compared to the expression levels in conventional young pigs and adult pigs. The mRNA expression levels of TLR2 and TLR4 in splenic MNCs of newborn pigs were statistically greater than in young and adult pigs (Figures 3.4B and

3.4D). However, TLR9 expression levels in splenic MNCs of newborn pigs were significantly lower than the levels in young and adult pigs (Figure 3.4I). TLRs 6, 7 and

10 mRNA expression levels in conventional newborn pigs did not show statistical 139 differences with either conventional young or adult pigs (Figures 3.4F, 3.4G and 3.4J).

TLRs 1, 2, 3, 4, 6, 7 and 10 mRNA expression levels in splenic MNCs of young pigs were statistically lower than the levels in adult pigs (Figures 3.4A-3.4D, 3.4F, 3.4G and

3.4J); whereas no significant differences were found in TLRs 5 and 8 (3.4E and 3.4H).

Overall, the TLR mRNA expression levels in splenic MNCs showed an increasing trend from conventional young pigs to adult pigs.

Interestingly, in ileal MNCs, the overall TLRs mRNA expression levels presented a decreasing trend from conventional young pigs to adult pigs. Except for TLR5, the mRNA expression levels of TLRs in ileal MNCs of young pigs were significantly higher than the levels in adult pigs (Figure 3.4). The expression levels in ileal MNCs of conventional newborn pigs also showed variable trends (Figure 3.4).

In GF pigs, only the expression levels of TLRs 5, 6 and 8 in splenic MNCs and TLR 8 in ileal MNCs differed significantly between newborn and young pig groups (Table 3.2).

Ileal DCs of young GF and conventional pigs had different mRNA expression profiles, whereas, splenic DCs had similar expression profiles in these two groups.

As initial MNC numbers were too low to yield adequate amounts of DCs from newborn pigs for further study, the TLR mRNA expression profile in DCs of newborn pigs could not be examined. Furthermore, as no GF adult pigs were available due to facility limitations (inability to maintain adult pigs in GF isolators), the TLR mRNA expression profiles of DCs of GF adult pigs were not studied. Generally, the mRNA expression levels of the TLRs in ileal DCs were greater in GF young pigs than in the conventional young pigs with TLRs 1, 3, 4, 5, 6 and 7 mRNA expression levels in ileal DCs being 140 significantly higher (Figure 3.5A). However, there was no difference in splenic DCs between the young GF pigs and conventional pigs (data not shown).

TLRs 1, 2, 6 and 10 mRNA expression levels in ileal DCs of adult pigs were significantly lower than those in splenic and MLN DCs.

Only TLR5 mRNA expression levels showed a statistically difference between splenic and ileal DCs in young GF pigs, while the expression levels of other TLRs were similar in the two groups (data not shown). However, in conventional young pigs, several TLRs showed higher mRNA expression levels in splenic DCs than ileal DCs, with TLRs 1, 6, 7 and 10 significantly so (Figure 3.5B). In conventional adult pigs, the mRNA expression levels of TLRs 1, 2, 3, 6 and 10 in ileal DCs were statistically lower than the levels in splenic DCs (Figure 3.3B). Additionally, TLR 1, 2, 6 and 10 mRNA expression levels in ileal DCs were significantly lower compared with the levels in MLN DCs (Figure 3.3B).

Interestingly, TLR3 mRNA expression level in MLN DCs was similar to ileal DCs and was also significantly lower than in splenic DCs (Figure 3.3B).

Most of the TLR mRNA expression levels in ileal DCs were higher in conventional young pigs than adult pigs; while the TLR expression profiles in splenic DCs from these groups showed variable trends.

In splenic DCs, TLR1 and TLR3 mRNA expression levels were significantly lower in conventional young pigs than adult pigs (Figure 3.6A and 3.6C); whereas, the expression levels of TLR 2 and 8 were significantly higher in young pigs than adult pigs (Figure

3.6B and 3.6D). In ileal DCs, the majority of TLR mRNA expression levels in 141 conventional young pigs were similar to those of adult pigs (data not shown). TLRs 2, 6 and 9 in ileal DCs had significantly greater expression levels in conventional young pigs than adult pigs (Figure 3.6E-3.6G), while the expression levels of TLR4 exhibited a higher trend in young pigs (p = 0.0678) (Figure 3.6H).

3.5 Discussion

Birth and weaning are two key developmental milestones of the immune system of mammals (45, 46). During these two periods of time, animals experience antigen exposure as the result of contact with non-sterile environment and a new diet (37). In interacting with microorganisms and food antigens, TLRs play a key role shaping the immune system (9, 47, 48). To investigate how microbiota/diet affect the development of the immune system, GF animals were used to provide a comparative control for conventional animals (38, 41). To understand how microbiota/diet impacts TLR expression, we compared the porcine TLRs mRNA expression profiles in GF and conventional pigs at birth (1-4 days of age) and 1-week post weaning (4 weeks of age) in this study.

Others have compared TLR expression profiles in intestinal epithelial cells of GF and conventional pigs. One study examined the mRNA expression of TLRs 2, 4 and 9 using real-time RT-PCR in whole caudal small intestinal tissues and enterocytes at 14 days of age between GF and GF pigs conventionalized with sow feces and then kept in GF conditions (49). They found that the expression of TLRs 2, 4 and 9 was increased in conventional pigs compared to GF pigs in both enterocytes and whole intestinal tissue, particularly TLR2. However, another study using similar methods failed to find a 142 difference in TLRs 4 and 9 mRNA expression between GF and conventionalized pigs

(50). In a recent study, the TLRs 2, 4, 5 and 9 mRNA expression levels in caudal ileal tissue did not differ significantly between GF and conventional pigs at 5 weeks of age

(51). In our study, we did not find statistically significant differences of TLRs 1-10 mRNA expression in ileal MNCs between newborn (1-4 days of age) GF and conventional pigs (data not shown), suggesting that priming of intestinal TLR responses with commensal microbiota requires some time. However, mRNA expression levels of

TLRs 1, 2, 4, 6, 9 and 10 in ileal MNCs were significantly higher in conventional young

(4 weeks of age) pigs than the levels in GF young (4 weeks of age) pigs (Figure 3.2B).

The discordant results between our and other studies may due to the different types of cells (small intestinal epithelial cells vs. ileal MNCs) and time points (14 days of age vs.

5 weeks of age vs. 4 weeks of age) used in the studies. Furthermore, the conventionalized pigs used in the other studies were kept in GF conditions and did not receive sow colostrum and milk, which may have affected the experimental results. There is increasing evidence demonstrate that breast milk play an crucial role in shaping mucosal immunity (52).

In this study, we demonstrated that the mRNA expression profiles of TLRs differed in

MNCs/DCs from different tissues. Generally, expression levels of most TLRs were higher in splenic MNCs/DCs compared to ileal MNCs/DCs in conventional pigs, regardless of the age (newborn, young and adult). Our data in adult pigs is consistent with a recent study of TLR expression along the intestinal tract in 70-day-old pigs in that most of the TLR mRNA expression levels was higher in MLN than ileal PP (53). Using

Taqman real-time PCR, mRNA expression of human TLRs 1-10 was assessed in human 143 adult tissue cDNA pools (Clontech) and compared amongst the different tissues (11).

This data showed that the TLR expression levels were higher in spleen than small intestine, except for TLR5, for which similar expression levels were observed. Another group of investigators found similar results in adult human tissues where the TLR mRNA expression levels were greater in spleen than small intestine, with the exception of TLR3 and TLR5 (54). In our study, we found a similar trend where TLR mRNA expression levels were greater in splenic MNCs than ileal MNCs, except TLR5. Similar results were also found in another study using a mouse model where most of the murine TLR mRNA expression was higher in splenic DCs than intestinal PP DCs after LPS stimulation in vitro (55). They suggested that the lower TLR mRNA expression in PP DCs might be one of the mechanisms exploited by PP DCs to regulate immune responses to commensal bacterial inducing tolerogenic state (55). The upregulated TLR expression in splenic

MNCs of adult pigs than young pigs, in contrast may represent the more mature state of the immune system of the former group. In addition, studies showed that flagellin- induced activation of TLR5 on dendritic cells elicited production of the cytokine IL-22 to induce a protective gene expression program in intestinal epithelial cells (56). This may indicate that TLR5 signaling is critical to induce antiviral effects in the gut and may contribute to the different expression profile of TLR5 compared to other TLRs. More studies are needed to understand the mechanisms of this phenomenon. Of all TLRs recognizing numerous microbial, synthetic and endogenous ligands, only TLR5 appears to be specific for a single protein moiety, flagellin of invasive bacteria (57). This specificity may require the increased TLR5 expression in the gut mucosa versus spleen observed in our study and by others (10, 58). Further, exclusive association of TLR5 144 activation with pro-inflammatory stimuli/signaling (57) may result in the decreased expression levels of TLR5 mRNA (compared to other TLRs) under homeostatic conditions as we observed in our study. However, as we were not able to collect relative data in neonatal or young animals, no comparison of our data for newborn and young pig data could be made with others.

As the intestine is continuously exposed to various antigens, such as food, commensal bacteria, and enteric pathogens, it is critical to avoid over stimulation and maintain the homeostasis in the intestine (59). Increasing evidence suggests that over-stimulation of intestinal TLRs correlates with the development of certain gastrointestinal diseases, such as Crohn’s disease, in which the TLR 2 and 4 expression (mRNA and protein) levels were up-regulated in both colon and immune cells of MLNs (60, 61). Studies of systemic lupus erythematosus (SLE) in a mouse model indicated that the over-expression of systemic TLR7 may be associated with the development of this autoimmune disease (62).

Therefore, we assume that the lower mRNA expression levels of TLRs in ileal

MNCs/DCs than splenic MNCs/DCs in conventional pigs may be effect of the microbiota-driven immunoregulatory/immunosuppressive mechanisms to avoid overt stimulation via controlling the expression (dampening) levels of TLRs. The microbiota directly interact with gut immune cells, which may exert regulatory effect on expression of TLRs where as such effect is minimal in spleen. Our data in GF pigs further supports this idea as there is no statistical difference in mRNA expression between splenic and ileal MNCs of GF newborn pigs or between splenic and ileal DCs of GF young pigs, except for TLR5 expression levels in DCs of GF young pigs. Furthermore, most of the

TLR expression levels in MLN MNCs/DCs of adult pigs are also greater than in ileal 145 MNCs/DCs. The different sets of data between conventional and GF pigs also demonstrate that colostrum and milk, as well as microbiota, have effects on the immune development in neonates (37, 63, 64).

Many studies have been conducted to demonstrate the age-dependent expression of TLRs in humans and animals, such as cattle and pigs (65-67). The comparison of TLR mRNA expression profiles in newborn, young and adult pigs in this study demonstrated that most of the TLR mRNA expression levels in ileal MNCs were significantly higher in young pigs than adult pigs, except TLR5 (Figure 3.4). This may be representative of different maturation stages of the immune system: with TLR responses activated during weaning

(adaptation to a new diet and discontinued passive protection via sow milk) with a subsequent decrease in the adult animals to achieve/maintain immune homeostasis. A study of TLR mRNA expression in the gastrointestinal tract of dairy calves showed similar results to ours in that the expression of TLRs 2 and 4-10 in the ileum was significantly down-regulated with increasing age (3-week-old to 6-month-old), except

TLRs 1 and 3, in which the expression was not associated with increasing age (67).

However, another study using1-day-old, 2-month-old and 5-month old pigs reported different results where TLRs 1, 5, 7, 9 and 10 expression levels in ileum were highest in

2-month-old pigs but not statistically different (65). Furthermore, they found the highest expression of TLR3 in ileum of 5-month-old pigs. The discordant results may be due to the different time points (4-week-old vs. 2-month-old). As the 4-week-old conventional pigs we used in this study were just weaned for one week, while the 2-month-old pigs were weaned for a month, it is very likely that the weaned pigs are still adapting to the introduction of new diet and have distinct TLR mRNA expression profiles compared to 146 the 2-month-old pigs. Additionally, we failed to observe significant differences of TLR mRNA expression levels in ileal MNCs between GF newborn and young pigs, except

TLR8 (Table 3.2). We concluded that most of the TLR mRNA expression in ileal MNCs was not age-dependent and may be explained by the exposure to non-sterile environment, removal of passive protection via maternal milk and new diet in the conventional vs. GF pigs. In addition, although TLR 7 and 8 recognize same major ligands, there are different populations of cells expressing TLR 7 and 8 and their signaling pathways do not overlap completely (68), which might have contributed to the different mRNA expression profiles between TLR 7 and 8 observed in our study.

The TLR expression levels in splenic MNCs were significantly higher in adult pigs than in young pigs, except TLRs 5, 8 and 9 (Figure 3.4). This result was opposite to what we observed in ileal MNCs. It may be due to minimal interaction between microbiota and spleen that results in exertion of less immunoregulatory/immunosuppressive effects on spleen than on gut. Studies indicated that the proportion of lymphocyte subsets were distinct in different human lymphoid tissues (69, 70). Furthermore, the TLR expression profiles were divergent in different types of lymphocytes, and even dissimilar among distinct subsets (11, 12, 71). Therefore, it is very likely that the expression profile in splenic MNCs contrasts to that of ileal MNCs. Additionally, we noted that TLRs 2 and 4 mRNA in splenic MNCs were expressed significantly higher in newborn pigs than young and adult pigs (Figure 3.4B and 3.4D). Studies using SPF mice with intraperitoneal injection of LPS for 14 days showed a decrease of TLRs 2 and 4 protein expression in spleen (72). Combined with our data showing that the TLRs 2 and 4 mRNA expression in splenic MNCs were unchanged in GF newborn and young pigs (Table 3.2), we assumed 147 that the decrease of TLRs 2 and 4 expression might be mediated by the microbiota exposure after birth and during the weaning period.

To our knowledge, this is the first report that systematically assesses porcine TLRs 1-10 mRNA expression profiles in MNCs and DCs from GF and conventional pigs at different ages. Our study showed that porcine TLR gene expression differs significantly in

MNCs/DCs from different tissues at different ages and according to microbiota/diet status. These data suggest that the uptake of colostrum and/or sow milk and the encounter with environmental commensal microbiota after birth and/or during weaning may be essential for the development of the innate immune system. Studies of the expression pattern of porcine TLR genes will help to understand the interaction between the commensal microbiota and the host systemic and mucosal immune system. Currently, there is a lack of specific anti-porcine TLR antibodies, thus, we were unable to examine the respective TLRs protein expression profiles. Therefore, studying the mRNA expression profile can provide insights as to the effects of microbiota and diet on immune system development.

3.6 Acknowledgements

We thank Dr. Juliette Hanson, Ronna Wood, Megan Strother, Dennis Hartzler and Jeffrey

Ogg for animal care assistance. This work was supported by a grant from the NIH,

NIAID # R01 A1099451.

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154 Gene Genebank accession Primer sequence (5’ à 3’) Reference number

F: AGATTTCGTGCCACCCTATG TLR1 NM_001031775.1 R: CCTGGGGGATAAACAATGTG

F: TGCTATGACGCTTTCGTGTC TLR2 NM_213761.1 R: CGATGGAGTCGATGATGTTG

F: GAGCAGGAGTTTGCCTTGTC TLR3 NM_001097444.1 R: GGAGGTCATCGGGTATTTGA

F: TCATCCAGGAAGGTTTCCAC TLR4 NM_001113039.2 R: TGTCCTCCCACTCCAGGTAG

F: GGTCCCTGCCTCAGTATCAA (Uddin et TLR5 NM_001123202.1 R: TGTTGAGAAACCAGCTGACG al., 2013)

F: TCAAGCATTTGGACCTCTCA TLR6 NM_213760.1 R: TTCCAAATCCAGAAGGATGC

F: TCTGCCCTGTGATGTCAGTC TLR7 NM_001097434.1 R: GCTGGTTTCCATCCAGGTAA

F: CTGGGATGCTTGGTTCATCT TLR8 NM_214187.1 R: CATGAGGTTGTCGATGATGG

F: AGGGAGACCTCTATCTCCGC TLR9 NM_213958.1 R: AAGTCCAGGGTTTCCAGCTT

F: GTCTCCCAATTTCGTCCAGA TLR10 NM_00103534.1 Author R: TGAGAGCTTTCAGTGCAGGA

Table 3.1 Primer sequences for porcine TLRs 1-10 genes.

155

5 5 5 4 4 4 4 3

E+ E+ E+ E+ E+ E+ E+ E+ ± ± ± ± 0.596 0.722 TLR10 2.06 1.46 1.64 2.53 7.39 3.70 8.10 8.46

3 3 3 3 3 3 3 2

E+ E+ E+ E+ E+ E+ E+ E+ ± ± ± ± 0.168 0.966 TLR9 2.15 2.97 4.80 1.37 2.84 2.19 2.89 3.83

± ± ± ± 0.020 TLR8 <0.001 3.23E+3 3.23E+3 4.06E+3 2.14E+4 6.80E+2 2.70E+3 2.49E+3 8.31E+3 3.17E+3

5 5 5 4 5 5 5 4

E+ E+ E+ E+ E+ E+ E+ E+ ± ± ± ± 0.434 0.235 TLR7 4.51 4.70 2.52 4.92 2.79 2.35 1.24 2.37

5 5 4 3

E+ E+ E+ E+ ± ± ± ±

0.018 0.670 TLR6 1.05 1.35 7.44 4.88 5.63E+4 5.63E+4 5.48E+4 1.46E+5 8.85E+3

4 4 3 3

10 in pigs.MNCsGF ofand and 10 splenicyoung ileal newborn in E+ E+ E+ E+ - ± ± ± ± 0.025 0.159 TLR5 8.45 9.56 8.08 2.44 9.83E+3 9.83E+3 1.54E+3 6.30E+3 1.42E+3

4 4 4 3 3 3 3 2

E+ E+ E+ E+ E+ E+ E+ E+ ± ± ± ± 0.965 0.172 TLR4 1.11 1.10 1.08 1.58 1.40 1.07 2.26 3.56

4 4 4 3 4 4 4 3

E+ E+ E+ E+ E+ E+ E+ E+ ± ± ± ± 0.096 0.230 TLR3 1.50 1.77 3.29 3.90 5.87 6.15 1.76 4.15

4 4 5 4 4 4 4 3

E+ E+ E+ E+ E+ E+ E+ E+ ± ± ± ± 0.154 0.361 TLR2 9.67 7.21 1.57 1.36 8.77 9.34 4.13 7.26

5 5 5 4 4 4 4 3

E+ E+ E+ E+ E+ E+ E+ E+ ± ± ± ± 0.376 0.562 TLR1 1.75 1.34 2.46 5.92 9.85 6.61 7.80 6.37

copy number with standard deviation for each group of and standard splenic deviation ileal pigs TLR wascopy mRNA withinof for MNCs GF group number each of

Differentiation mRNA expression porcine Differentiation of1 mRNA expression TLRs

Young Young P value P value P 2 Newborn Newborn . 3

Spleen Ileum Table meanof The difference.the < defined P intable. 0.05 wasshown significant as value

156

A TLR mRNA expression profiles in splenic MNCs B TLR mRNA expression profiles in splenic and of germ-free and convetional newborn pigs ileal MNCs of conventional newborn pigs 7 1×10 1×107

6 1×10 1×106 b a a a b 5 1×10 b 1×105 a b b a a 1×104 1×104 b GF pigs Splenic MNCs Log 10 copy number copy Log 10 Log 10 copy number copy Log 10 1×103 Conv pigs 1×103 Ileal MNCs

TLR1 TLR2 TLR3 TLR4 TLR5 TLR6 TLR7 TLR8 TLR9 TLR1 TLR2 TLR3 TLR4 TLR5 TLR6 TLR7 TLR8 TLR9 TLR10 TLR10

A TLR mRNA expression profiles in splenic MNCs B TLR mRNA expression profiles in splenic and of germ-free and convetional newborn pigs ileal MNCs of conventional newborn pigs 7 1×10 1×107

6 1×10 1×106 b a a a b 5 1×10 b 1×105 a b b a a 1×104 1×104 b GF pigs Splenic MNCs Log 10 copy number copy Log 10 Log 10 copy number copy Log 10 1×103 Conv pigs 1×103 Ileal MNCs

TLR1 TLR2 TLR3 TLR4 TLR5 TLR6 TLR7 TLR8 TLR9 TLR1 TLR2 TLR3 TLR4 TLR5 TLR6 TLR7 TLR8 TLR9 TLR10 TLR10

Figure 3.1 TLRs 1-10 mRNA expression profiles in newborn pigs. (A) The expression profiles in splenic MNCs of newborn pigs; (B) The expression profile in splenic and ileal MNCs of conventional newborn pigs. Bars with different letters in each TLR are significant difference (p < 0.05). GF: germ-free; Conv: conventional.

157 free; free; -

A) The expression (

R R are significant difference (p < 0.05). Gn: germ free and conventional young pigs. - free pigs; (D) The expression profiles in splenic and ileal MNCs of - (B) The expression profiles in ileal MNCs of young pigs; (C) The expression 10 mRNA expression profiles in germ

- TLRs TLRs 1

2 . 3 Figure profiles in splenic MNCs of young pigs; profiles in splenic and ileal MNCs of young germ young conventional pigs. Bars with different letters in each TL Conv: conventional.

158

Figure 3.3 TLRs 1-10 mRNA expression profiles in MNCs and DCs of conventional adult pigs. (A) The expression profiles in MNCs of conventional adult pigs; (B) The expression profiles in DCs of conventional adult pigs. Bars with different letters in each TLR are significant difference (p < 0.05).

159

Figure 3.4 TLRs 1-10 mRNA expression profiles in splenic and ileal MNCs of conventional pigs at different ages. (A) TLR1; (B) TLR2; (C) TLR3; (D) TLR4; (E) TLR5; (F) TLR6; (G) TLR7; (H) TLR8; (I) TLR9; (J) TLR10 expression profiles in conventional pigs at different ages. * p < 0.05; ** p < 0.01; *** p < 0.001.

160

Figure 3.4

Continued 161 Figure 3.4 continued

162 TLR mRNA expression profiles in ileal DCs TLR mRNA expression profiles in splenic A of germ-free and conventional young pigs B and ileal DCs of young conventional pigs 6 1×10 a 1×107

b a 6 a a 1×10 a a b a b a a 1×105 b b 5 b b a 1×10 b b 1×104 Log 10 copy number copy Log 10 Log 10 copy number copy Log 10 GF pigs Splenic DCs 1×104 b Conv pigs Ileal DCs 1×103

TLR1 TLR2 TLR3 TLR4 TLR5 TLR6 TLR7 TLR8 TLR9 TLR1 TLR2 TLR3 TLR4 TLR5 TLR6 TLR7 TLR8 TLR9 TLR10 TLR10 TLR mRNA expression profiles in ileal DCs TLR mRNA expression profiles in splenic A of germ-free and conventional young pigs B and ileal DCs of young conventional pigs 6 1×10 a 1×107 b a 6 a a 1×10 a a b a b a a 1×105 b b 5 b b a 1×10 b b 1×104 Log 10 copy number copy Log 10 Log 10 copy number copy Log 10 GF pigs Splenic DCs 1×104 b Conv pigs Ileal DCs 1×103

TLR1 TLR2 TLR3 TLR4 TLR5 TLR6 TLR7 TLR8 TLR9 TLR1 TLR2 TLR3 TLR4 TLR5 TLR6 TLR7 TLR8 TLR9 TLR10 TLR10

Figure 3.5 TLRs 1-10 mRNA expression profiles in DCs of young pigs. (A) The expression profiles in ileal DCs of young pigs; (B) The expression profiles in splenic and ileal DCs of conventional young pigs. Bars with same letter in each TLR are not significant difference (p > 0.05). Bars with different letters in each TLR are significant difference (p < 0.05).

163

Figure 3.6 TLRs mRNA expression profiles in splenic and ileal DCs of conventional pigs at different ages. (A) TLR1 expression profile in splenic DCs; (B) TLR2 expression profile in splenic DCs; (C) TLR3 expression profile in splenic DCs; (D) TLR8 expression profile in splenic DCs; (E) TLR2 expression profile in ileal DCs; (F) TLR 6 expression profile in ileal DCs; (G) TLR9 expression profile in ileal DCs; (H) TLR4 expression profile in ileal DCs. The significant differences between two groups were indicated with star(s). * p < 0.05; ** p < 0.01.

164 Figure 3.6

165

Chapter 4 Differential effects of live probiotic bacteria in vitro on conventional and plasmacytoid dendritic cells from gnotobiotic pigs

4.1 Abstract

Probiotics represent a potentially effective approach for the treatment of rotavirus diarrhea; however, the mechanisms are not clearly elucidated. Dendritic cells (DCs) interact with probiotics and may play a role in regulating immune responses. After treatment with live probiotics and/or inactivated human rotavirus (inactHRV) in vitro, splenic, ileal and mesenteric lymph node (MLN) mononuclear (MNCs) from gnotobiotic pigs (model for rotavirus diarrhea) were analyzed by flow cytometry and ELISA to assess how different probiotic strains [Escherichia coli Nissle 1917 (EcN), Lactobacillus rhamnosus GG (LGG) and Bifidobacterium lactis Bb12 (Bb12)] affect DC frequencies, their phenotypes and MNC cytokine production. We found that LGG and Bb12 decreased the frequencies of cDC and MHCII+ cDC in ileal and MLN MNCs compared to inactHRV-exposed or untreated groups; while EcN increased pDC and MHCII+ pDC frequencies in MLN MNCs. Comparing the cytokine levels among inactHRV-exposed

MNC groups, EcN, LGG and Bb12 reduced the levels of innate (IFN-alpha), proinflammatory (IL-6), Th1 (IL-12), and Th2 (IL-4) cytokines in splenic MNCs; whereas,

EcN increased T-regulatory cytokine (IL-10) levels. In addition, without inactHRV- exposure, EcN significantly increased levels of IFN-alpha, IL-12 and IL-10 in splenic

MNCs. EcN, LGG and Bb12 reduced frequencies of TLRs 2-, 3- and 4-expressing MNCs;

166 furthermore, they reduced the expression of TLR 2, 3 and 4 of inactHRV-exposed MNCs.

These results demonstrate that gram-positive and gram-negative probiotic bacteria differentially modulate DC frequencies, their surface phenotypes and functions in vitro.

Additionally, our results indicate that probiotics modify MNC responses (cytokine levels) to inactHRV via different bacterial stimuli and to different TLRs.

4.2 Introduction

Rotavirus (RV) is one of the most important enteric pathogens worldwide. It is the most common pathogen in cases of acute gastroenteritis in children under 5 years of age and can also infect many kinds of domestic young animals, including calves and piglets (1, 2).

In the U.S., the direct and indirect costs of physician visits, emergency department visits and hospitalizations due to RV infection is estimated to be approximately $1 billion (3, 4).

RV is also responsible for 7-20% and 3-15% annual mortality in nursing and weaned piglets, respectively (5). Treatment of RV diarrhea is only possible by replacement of fluids and electrolyte losses, as no antiviral therapy is available (6). Therefore, effective

RV vaccines are crucial to prevent morbidity and mortality in both young children and animals (6, 7). Currently, there are two licensed vaccines for humans: Rotarix and

RotaTeq. With reportedly high protective effects in developed countries, these two vaccines are only marginally effective, in developing countries. This necessitates better treatments and optimized vaccines (8).

“Probiotics are live microorganism which when administered in adequate amounts confer a health benefit on the host” (9). The impact of probiotics on the gut involves inhibition of pathogen growth, alleviation of intestinal inflammation, normalization of the gut 167 mucosal dysfunction, and down-regulation of hypersensitivity reactions (10). Moreover, probiotics decrease RV shedding, shorten the duration of RV diarrhea and promote immune responses to RV vaccines (11-13). Probiotics provide protective effects against

RV infection in strain-, dose- and nutrition-dependent manners (14-16). Studies evaluating innate immunity and adaptive immunity, both in vitro and in vivo, illustrate that multiple complex mechanisms may be involved in the beneficial effects of a range of probiotics. However, these mechanisms have not been fully elucidated.

Dendritic cells (DCs) are sentinels of the immune system and interact with microbes via pattern-recognition receptors (PRRs), such as Toll-like receptors (TLRs). After DCs identify pathogens, they can capture, process and present antigens to other immune cells to initiate immune responses (17). TLRs are pivotal PRRs that can recognize diverse microbes via identifying different microbe-associated molecular patterns (MAMPs).

Studies have shown that peptidoglycan (PGN), a main constituent of Gram-positive (G+) bacterial cell wall is responsible for the stimulation of TLR2, and lipopolysaccharide

(LPS), a main component of Gram-negative (G-) bacterial cell wall is a main ligand for

TLR4 (18-20). The stimulation of TLR2 and TLR4 signaling pathways results in distinct profiles of IL-10 and IL-12 production in DCs leading to differential immune responses

(21, 22).

Studies on the interactions between Bifidobacterium spp. (a group of G+ probiotics) and

DCs have been conducted by co-culturing bacterial cell wall components with enriched human blood DCs (23). The data indicated that B. longum Y10, B. infantis Y1 and B. breve Y8 induced the most significant anti-inflammatory responses by up-regulating IL-

10 production in DCs and decreasing expression of the costimulatory molecule CD80. On 168 the other hand, the G- probiotic Escherichia coli Nissle 1917 (EcN) has been shown to activate mouse blood mononuclear cell-derived DCs via the TLR4 signaling pathway

(24). In addition, EcN induced the production of IL-6, IL-10 and IL-12 in DCs and up- regulated the membrane expression of CD40, CD80 and CD86 on DCs. Although several reports have shown that probiotics can influence the cytokine production and modulate the expression of certain molecules on DCs via signaling through PRRs, more detailed studies are needed to fully characterize their effects.

In this study, we used mononuclear cells (MNCs) from spleen, ileum and mesenteric lymph nodes (MLNs) of 4-week-old gnotobiotic (Gn) pigs to co-culture with selected probiotics strains [EcN, Lactobacilus rhamnosus GG (LGG) and Bifidobacterium animalis subsp. lactis Bb12 (Bb12)] and/or inactivated human rotavirus (inactHRV) and assessed how different probiotic strains affect MNCs or DC frequencies, their phenotypes and functions in vitro.

4.3 Materials and Methods

Virus

The Gn pig-adapted (passage 23) HRV Wa G1P[8] strain (25) was used to prepare the inactivated virus for in vitro treatment. The virulent Wa HRV was inactivated by using binary ethylenimine as described previously (26). The protein concentration of inactivated HRV Wa G1P[8] (inactHRV) was examined by Bradford protein assay (Bio-

Rad, Hercules, CA, USA) following the manufacturer’s instructions.

169 Bacteria

EcN was propagated in Luria broth (LB) and LGG strain ATCC 53103 (ATCC,

Manassas, VA, USA) and Bb12 (Christian Hansen Ltd., Hørsholm, Denmark) were propagated in Man-Rogosa-Sharpe (MRS) broth as described previously (24, 27).

Bacteria were washed twice with sterile 1 × PBS and diluted to the required concentration for further use.

Isolation of mononuclear cells (MNCs)

The Gn pigs were hysterectomy-derived from Large White × York x Duroc sows and maintained in sterile isolation units as described previously (28, 29). Piglets were euthanized at 4-weeks of age. Spleen, MLNs and ileum were collected immediately after euthanasia. Isolation of MNCs from the spleen, MLNs and ileum was conducted as previously described (30). After MNC isolation, cell viability was assessed using

CellometerTM Auto T4 (Nexcelom Bioscience, Lawrence, MA, USA), following the manufacturer’s recommendations.

MNCs co-culture with bacteria +/- inactHRV

2 × 106 MNCs were co-cultured with 2 × 107 of EcN, LGG or Bb12 in enriched RPMI-

1640 medium [E-RPMI prepared as previously described (31)] for 24 hours under 5%

CO2 at 37ºC, then exposed to inactHRV (12 µg/ml) for another 24 hours under the same conditions. Supernatants were collected and stored at -20ºC until tested for cytokine levels. The MNC suspensions were collected for flow cytometry staining immediately.

170 Detection of cytokine levels in the co-culture supernatants by ELISA

The levels of porcine innate cytokine (IFN-alpha), pro-inflammatory cytokines (IL-6,

TNF-α), Th1 cytokine (IL-12), Th2 cytokine (IL-4), and T-regulatory cytokines (IL-10,

TGF-β) in the collected supernatants were examined by ELISA using anti-swine cytokine antibodies as previously described (32).

Flow cytometry staining

MNCs were stained with porcine specific monoclonal antibodies (mAbs) or human cross- reactive mAbs to cell-surface or intracellular proteins or cell surface molecules (Table

4.1). Secondary Abs and isotype controls used in this study are listed in Table 4.1 as well.

Porcine cDCs were defined as SWCa+CD4-CD11R1+ and porcine pDCs were defined as

SWC3a+CD4+CD11R1- (33). MHC class II was assessed in both cDC and pDC populations as a DC activation marker (Table 4.1). Porcine TLR2, 3 and 4 frequencies were also evaluated in these two DC populations. The flow cytometry staining procedure was conducted as described previously (31).

Statistical analyses

The cytokine levels, frequencies of cDCs/pDCs, frequencies of MHCII+ cDC/pDC and frequencies of TLR2-4 expressing MNCs were compared between different treatment groups using the Kruskal-Wallis rank-sum test. Statistical analyses were performed using

GraphPad Prism 6.0c software (GraphPad Software, La Jolla, CA, USA). Statistical significance was determined at p ≤ 0.05 for all comparisons.

171 4.4 Results

G+ (LGG and Bb12) probiotics reduced cDC frequencies in MNCs of ileum and MLN in the presence or absence of inactHRV, while the G- (EcN) probiotic increased pDC frequencies in MLN MNCs.

LGG (significantly) and Bb12 and, to a lesser extent, EcN decreased cDC and MHCII+ cDC frequencies in untreated and inactHRV-exposed ileal MNCs (Figures 4.1A and

4.2B). None of the selected probiotics (EcN, LGG and Bb12) affected pDC (Figure 4.1B) or MHCII+ pDC frequencies (Figure 4.2B) in ileal MNCs with or without exposure to inactHRV. As shown in Figure 4.3B and 4.4B, EcN (±inactHRV) increased pDC and

MHCII+ pDC frequencies in the untreated or inactHRV-treated MLN MNCs; while all three probiotics decreased cDC and MHCII+ cDC frequencies among MLN MNCs with or without inactHRV treatment. None of the selected G- and G+ probiotics affected the frequencies of MHCII+/- cDC or MHCII+/- pDC in splenic MNCs compared to the untreated or the inactHRV-treated MNCs (Figure 4.5).

G+ (LGG and Bb12) probiotics reduced cytokine levels in inactHRV-exposed splenic

MNCs; while the G- (EcN) probiotic induced IFN-alpha and IL-12 production in splenic

MNCs in the absence of inactHRV.

The levels of porcine innate cytokine (IFN-alpha), pro-inflammatory cytokines (IL-6,

TNF-α), Th1 cytokine (IL-12), Th2 cytokine (IL-4), and T-regulatory cytokines (IL-10,

TGF-β) induced by probiotic ± inactHRV in splenic MNCs were assessed using ELISA.

In the absence of inactHRV, EcN significantly increased innate/pro-inflammatory cytokine (IFN-alpha) and Th1/pro-inflammatory cytokine (IL-12) levels produced by 172 splenic MNCs; while LGG and Bb12 did not affect splenic MNC cytokine levels (Figure

4.6). All selected probiotics tended to reduce cytokine levels in inactHRV-exposed MNC compared to MNCs exposed to inactHRV alone (Figure 4.6). However, EcN significantly reduced IL-6 levels; Bb12 significantly reduced IL-6 and IL-12 levels, while LGG had the greatest suppressive effect, significantly reducing IL-4, IL-6 and IL-12 levels (Figure

4.6).

EcN increased the T-regulatory IL-10 cytokine levels in splenic, ileal and MLN MNCs with or without inactHRV-exposure, while LGG and Bb12 decreased levels of IL-10 in inactHRV-exposed ileal and MLN, but not splenic MNCs.

EcN increased IL10 levels produced by MLN or ileal MNCs numerically, but not significantly, compared with untreated or inactHRV exposed MNCs (Figures 4.7A and

4.7B). Further, EcN significantly increased the IL-10 levels of splenic MNCs compared with the untreated group and it also statistically increased the IL-10 levels in the inactHRV-treated group (Figure 4.7C). Both LGG and Bb12 decreased IL-10 levels in

MLN/ileal MNCs compared with the untreated and inactHRV-treated group (Figures

4.7A and 4.7B), the IL-10 levels were decreased significantly by LGG treatment in inactHRV-exposed ileal MNCs. However, both LGG and Bb12 slightly increased IL10 levels produced by splenic MNCs with or without inactHRV exposure.

173 Selected probiotics suppressed the TLR 2, 3 and 4 expressions in inactHRV-exposed splenic MNCs.

The ligands for TLR 2, 3 and 4 are PGN, double-stranded RNA and LPS, respectively

(34). The 2 G+ (LGG, Bb12) and, to a lesser extent, the G- (EcN) (except for TLR3 with inactHRV) probiotics decreased the frequencies of TLR2, TLR3 and TLR4 expressing splenic MNCs compared with the untreated or inactHRV-treated groups (Figure 4.8).

4.5 Discussion

In this study, G+ (LGG and Bb12) significantly decreased the cDC frequencies in ileal

MNCs in the presence of inactHRV. Moreover, LGG and Bb12 showed a trend to decreased MHCII+ cDC frequencies in ileal MNCs. In contrast, G- (EcN) treatment showed a trend for increased pDC and MHCII+ pDC frequencies in MLN MNCs. These results suggest that probiotics confer their immunoregulatory effects affecting frequencies of different DC subsets in a strain-dependent manner in different lymphoid tissues sets. The result is consistent with the in vivo studies in our lab which indicate that

EcN significantly increased frequencies of pDCs, but not cDCs in systemic (spleen) and gut tissue post virHRV challenge (Vlasova et al., unpublished). DCs are essential in linking innate and adaptive immunity and are classified into two types: cDC and pDC. cDC plays an important role in initiation of Th1/Th2 responses, while pDC stimulates both Th1/Th2 induction and tolerogenic function, depending on their status (mature or immature) (35, 36). Therefore, G+ and G- probiotics may influence the frequencies or function of different types of DCs to down-regulate or up-regulate immune responses.

174 We found that inactHRV induced higher levels of several cytokines compared with the untreated group that were down-regulated by LGG and Bb12, especially for IL-12, IL-6 and IL-4. In studies by Hosoya et al. (2011), a clonal porcine intestinal epithelial cell line

(PIE cells) were co-cultured with ileal Peyer’s patches immunocompetent cells, pre- treated with L. casei MEP 221106 or L. casei MEP221103 for 48 hours and then stimulated with poly(I:C). The mRNA expression of IFN-alpha, IFN-beta, IFN-gamma,

IL-12p40, TNF-alpha, IL-1β, IL-2, IL-6, IL-10 and TGF-beta in the immune cells were examined after 3 hours, 6 hours and 12 hours of poly(I:C) stimulation (37). Although L. casei MEP221106 induced significantly higher levels of IFN-alpha, IFN-beta, IFN- gamma, IL-2, IL-12p40 and IL-1β after hour 3, this strain induced down-regulation of

IFN-alpha, IL-1β, IL-6, IFN-gamma and IL-12 at hour 12 (37). Moreover, L.casei

MEP221103 induced a down-regulation of IFN-alpha, IL-1β, IL-6, IFN-gamma and IL-2 at hour 3 and 12 (37). The two strains of lactic acid producing bacteria, LGG and Bb12, used in our studies showed a similar trend as reported by Hosoya et al. (2011) and had the ability to down-regulate inactHRV-induced cytokine expression by splenic MNCs.

However, compared with L. casei MEP221106 which increased the mRNA expression level of IL-10, LGG + inactHRV significantly reduced the IL-10 cytokine levels compared with only inactHRV-treated ileal MNCs. This may be due to the strain- dependent effects of probiotics on immune responses (38-40). In the absence of inactHRV, EcN significantly increased the IL-12 and IL-10 levels produced by splenic

MNCs compared with the untreated group. This result is consistent with Adam et al.

(2010) who indicated that EcN could significantly increase IL-12 and IL-10 levels in mouse bone marrow derived DCs (bacteria to cell ratio was from 0.01 to 100) (24). In 175 addition, EcN showed the greatest effects in up-regulating IL-12 levels when the bacteria to MNC ratio was 10 (24).

After pre-treatment which selected probiotics for 24 hours and then stimulation with inactHRV for another 24 hours, the frequencies of TLR2-, TLR3- and TLR4-expressing splenic MNCs were evaluated by flow cytometry. We found that LGG and Bb12 decreased frequencies of TLRs 2, 3 and 4 expressing MNCs with inactHRV treatment; whereas EcN had less effect on those frequencies. This is consistent with our lab in vivo studies showing that colonization of LGG and Bb12 decreased frequencies of TLR2- and

TLR4-expressing MNCs from attenuated HRV-vaccinated pigs (41). However, in our in vivo study, we also found that the frequencies of TLR3-expressing MNCs of duodenum increased in the LGG and Bb12 colonized pigs compared with control pigs after HRV challenge. This is not the same as what we observed in this study. There are several possible reasons for the difference: 1) single probiotic strain treatment vs. co-culture

(simultaneous) treatment; 2) inactHRV vs. attenuated live virulent HRV; 3) probiotics interaction with splenic MNCs in vitro vs. probiotics interaction with the complex gut immune system.

We found that G+ (LGG and Bb12) decreased cDC and MHCII+ cDC frequencies in ileal MNCs and down-regulated cytokine production in splenic MNCs induced by inactHRV, especially the levels of IL-4, IL-6 and IL-12. This suggests that the G+ probiotics effects are more down-regulatory in the presence of inactHRV. On the contrary, EcN increased pDC and MHCII+ pDC frequencies in MLN MNCs and enhanced IFN-alpha, IL-10 and IL-12 levels produced by splenic MNCs. The results suggest that G- effects are mostly immunostimulatory/immunoregulatory in the absence 176 or presence of inactHRV. The different effects on immune responses of G+ and G- probiotics may due to the different structural components of G+ and G- bacterial cell walls. The G+ cell wall contains a high percentage of PGN, while the cell wall of G- contains mostly LPS. PGN and LPS can be recognized by TLR2 and TLR4, respectively

(19, 42). Since LGG and Bb12 exert more down-regulatory effects in the presence of inactHRV, they may be used as a complementary treatment during RV infection.

Whereas, because EcN showed more immunostimulatory/immunoregulatory effects on

MNCs in the absence of inactHRV, it may be a candidate adjuvant to induce more robust immune responses to RV vaccine. However, it may also limit (or curtail) HRV infection via potent upregulation of innate immunity (IFN-alpha). More in vitro and in vivo studies are needed to expand and confirm our current findings.

4.6 Acknowledgements

We thank Dr. Juliette Hanson, Ronna Wood, Megan Strother, Dennis Hartzler and Jeffrey

Ogg for animal care assistance. This study was funded in part by the NIH, NCCAM grant

# R21AT004716, NIH, NIAID grant # R01 A1099451 and the OARDC research enhancement competitive grants program student SEEDS grant # 2013-090.

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181

reactivity - porcine TLR2 porcine TLR3 porcine TLR4 porcine Cross Cross reacts with with reacts Cross with reacts Cross with reacts Cross

IgG1 IgG1 IgG1 IgG1 IgG1 IgG2a IgG2a IgG2a IgG2a IgG2b IgG2b IgG2b IgG2b Isotype

Ab/Vendor pig CD11R1/AbD Serotec CD11R1/AbD pig

- mouse IgG1/Biosciences mouse /SouthernBiotech - porcine monocyte/granulocyte monocyte/granulocyte porcine porcine CD4a/SouthernBiotech porcine - - pig SLA class II DR/AbD Serotec DR/AbD II class SLA pig FITC/SouthernBiotech - SPRD/SouthernBiotech anti Mouse IgG2b isotype control control isotype IgG2b Mouse control isotype IgG2b Mouse human CD282 (TLR2)/eBioscience CD282 human (TLR3)/eBioscience CD283 human (TLR4)/eBioscience CD284 human - - - IgG2aisotype controlAPC/eBioscience Rat anti Rat - Mouse anti Mouse Anti Anti Anti Mouse Mouse Mouse anti Mouse Mouse anti Mouse Mouse Mouse IgG2a isotype control FITC/eBioscience control isotype IgG2a Mouse Mouse IgG1 isotype control PE/SouthernBiotech control isotype IgG1 Mouse

PE PE PE APC APC APC None FITC FITC FITC FITC SPRD SPRD Fluorescence

PE APC FITC FITC Antibodies used in flow in Antibodies usedstaining. cytometry - SPRD - - - - 1 . CD4 TLR2 TLR3 TLR4 4 SWC3a IgG1 mouse Marker CD11R1 IgG1 - IgG2a IgG2a IgG2b MHC class II class MHC IgG2b Secondary Ab, Isotypecontrol, Isotypecontrol, Isotypecontrol, Isotypecontrol, Isotypecontrol, anti Table

182

Figure 4.1 Frequencies of cDC and pDC in ileal MNCs. Ileum MNCs (2 × 106) were co- cultured with live probiotics (2 × 107 CFU) for 24 hours, and exposed to inactHRV (12µg/ml) for another 24 hours. Then cells were collected for DC frequencies assessment. (A) cDC frequencies in ileal MNCs, (B) pDC frequencies in ileal MNCs (n=3). * p < 0.05.

183

Figure 4.2 Frequencies of MHCII+ cDC and MHCII+ pDC in ileal MNCs. Ileal MNCs (2 × 106) were co-cultured with live probiotics (2 × 107 CFU) for 24 hours, and exposed to inactHRV (12µg/ml) for another 24 hours. Then cells were collected for MHCII+ DC frequencies assessment. (A) MHCII+ cDC frequencies in ileal MNCs, (B) MHCII+ pDC frequencies in ileal MNCs (n=3).

184

Figure 4.3 Frequencies of cDC and pDC in MLN MNCs. MLN MNCs (2 × 106) were co-cultured with live probiotics (2 × 107 CFU) for 24 hours, and exposed to inactHRV (12µg/ml) for another 24 hours. Then cells were collected for DC frequencies assessment. (A) cDC frequencies in MLN MNCs, (B) pDC frequencies in MLN MNCs (n=2).

185

Figure 4.4 Frequencies of MHCII+ cDC and MHCII+ pDC in MLN MNCs. MLN MNCs (2 × 106) were co-cultured with live probiotics (2 × 107 CFU) for 24 hours, and exposed to inactHRV (12µg/ml) for another 24 hours. Then cells were collected for MHCII+ DC frequencies assessment. (A) MHCII+ cDC frequencies in MLN MNCs, (B) MHCII+ pDC frequencies in MLN MNCs (n=2)

186

Figure 4.5 Frequencies of cDC, pDC, MHCII+ cDC and MHCII+ pDC in splenic MNCs. Splenic MNCs (2 × 106) were co-cultured with live probiotics (2 × 107 CFU) for 24 hours, and exposed to inactHRV (12µg/ml) for another 24 hours. Then cells were collected for MHCII+ DC frequencies assessment. (A) cDC frequencies in splenic MNCs, (B) pDC frequencies in splenic MNCs, (C) MHCII+ cDC frequencies in splenic MNCs, (D) MHCII+ pDC frequencies in splenic MNCs (n=4).

187

Figure 4.6 IFN-alpha, IL-12, IL-6 and IL-4 levels in splenic MNCs. Splenic MNCs (2 × 106) were co-cultured with live probiotics (2 × 107 CFU) for 24 hours, and exposed to inactHRV (12µg/ml) for another 24 hours. Growth supernatants were collected and cytokine levels of IFN-alpha (A), IL-12 (B), IL-6 (C) and IL-4 (D) in the supernatants were assessed by ELISA (n=4). * p < 0.05; ** p < 0.01; *** p < 0.001.

188

cultured with live probiotics (2 × 10 - ) were ) were co 6 MNCs MNCs (2 × 10

g/ml) g/ml) for another 24 hours. Growth supernatants were collected and µ

NCs (A), ileal MNCs (B), splenic MNCs (C) in the supernatants were assessed by 10 in MLN M - * p < 0.05; *** p < 0.001. p * < 0.05; *** < p 10 levels in MLN, ileal and splenic MNCs. - IL

7 . 4 Figure CFU) for 24 hours, and exposed to inactHRV (12 cytokine levels of IL (n=4). ELISA

189

- TLR4 expressing (B) and(B) expressing - probiotics treatments with/without CFU) for 24 hours, and exposed to

7 expressing (A), expressing TLR3 -

expressing splenic MNCs after live - cultured with live probiotics (2 × 10 - , TLR4 - ) were co 6 , TLR3 - g/ml) for another 24 hours. The 24 TLR2 g/ml) frequencies offor The another hours. µ Splenic MNCs (2 × 10

Frequencies of TLR2

8 . 4 Figure inactHRV. (12inactHRV MNCs flow(C)were expressing assessed by (n=2). cytometry

190

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