Clarice Lispector

Rodrigo Prado Martins

Melania Collado-Romero

Montserrat Martínez- Gomáriz

Ana Carvajal

Concepción Gil

Concepción Lucena

Ángela Moreno

Juan José Garrido

Valentina Lorenzi

Cristina Arce

Carmen Aguilar

Rocío Bautista

M Gonzalo Claros

Proteomic analysis of porcine mesenteric lymph

Keywords: Pig, Mesenteric lymph-node, Immune response, Salmonella enterica serovar Typhimurium 3.2 -nodes after Salmonella typhimurium infection Pig, Salmonella typhimurium, Mesenteric lymph nodes, DIGE, Pyroptosis, Cross-presentation 3.4 Innate and adaptive immune mechanisms are effectively induced Salmonella enterica serovar Typhimurium, laser microdissection, Peyer's patches follicles, germinal center, cross-presentation

Genetic improvement of the resistance to infectious diseases represents an essential step for the development of sustainable and economically viable animal production systems. Control of salmonellosis in swine herds generates increased production costs and public health issues due to the risk of dispersal of antibiotic resistant strains. Therefore, the breeding of resistant animals, in combination with good hygiene practices offers a promising strategy to fight against Salmonella in pigs. Recently, functional genomics approaches combining the power of gene mapping technologies, gene expression studies and modern bioinformatics tools have begun to contribute to a better understanding of the host response to microbial diseases. In light of this, this thesis aimed to identify and describe the molecular pathways and interactions involved in the porcine intestinal immune response to Salmonella enterica serovar Typhimurium (S. Typhimurium).

The first, second and third studies that constitute this thesis aimed to explore the molecular mechanisms occurring in porcine mesenteric lymph-nodes (MLN) at 1, 2 and 6 days post-infection (dpi) with S. Typhimurium. Firstly, the differential expression of immune-related genes was analysed in correlation with changes in tissue morphology and pathogen burden. Results revealed that infection resulted in a substantial infiltration of phagocytes and up-regulation of pro-inflammatory genes. Of note, host defence mechanisms led to a relevant reduction of S. Typhimurium load in tissue, but pathogen was found to maintain itself in MLN at 6 dpi. Subsequently, DIGE-based proteomics was carried out, uncovering that infection caused changes in abundance of proteins involved in diverse host cellular functions, leading to the induction of processes such as phagocyte infiltration, cytoskeleton remodelling, pyroptosis and antigen presentation in infected MLN. Finally, host response to infection was accessed by microarrays analysis and then complemented with gene expression data from pathogen found in tissue. The conjunctive analysis of both parties involved in infection revealed that although S. Typhimurium was able to express virulence factors in porcine MLN, host succeeded in counteracting pathogen strategies by modulating infected cell death and inducing an early cytotoxic response.

The forth and fifth studies reported in this thesis were focused on the role of porcine Peyer's Patches (PP) upon S. Typhimurium infection. Initially, laser microdissection coupled to qPCR technology uncovered that both innate and adaptive immunity mechanisms are effectively triggered in PP follicles during infection. Afterwards, microarray analysis was carried out to better-explain results from this preliminary approach. It could be confirmed that the bacterial challenge provoked a remarkable inflammatory response and the establishment of multiple levels of adaptive response against S. Typhimurium in PP follicles. Interestingly, several evidences of cross-presentation triggering were observed in follicles, besides the induction of humoral responses.

As conclusions, this thesis highlights that in spite of the sophisticated strategies evolved by pathogen to cause disease, swine appear to induce pyroptosis and inhibit apoptosis of infected cells in MLN to promote clearance of bacteria in the extracellular milieu during S. Typhimurium infections. This mechanism might enable MLN to act as a firewall to prevent pathogen spread beyond intestinal tract. Simultaneously, host might mediate an early cytotoxic response against Salmonella by cross-presentation of bacterial antigens in these organs, coordinating both arms of immunity in order to control infection. Additionally, it could be observed that besides eliciting B-cell-mediated immune responses, PP follicles mediate the generation of effector and memory CD8 T cells during infections by S. Typhimurium, which could represent a novel function for this PP area during Salmonella infections.

Resumen

La mejora de la resistencia genética a las enfermedades infecciosas representa una etapa fundamental para el desarrollo de sistemas de producción animal económicamente viables y sostenibles. El control de la salmonelosis porcina genera elevados costes de producción y supone un riesgo para la salud pública por la posibilidad de desarrollo y dispersión de cepas resistentes a antibióticos. Por lo tanto, la cría de animales resistentes, asociada a buenas prácticas de higiene durante la producción, representa una estrategia prometedora para la lucha contra infecciones por Salmonella en cerdos. Recientemente, la genómica funcional, al combinar la potencia de las tecnologías de mapeo genético, los estudios de expresión génica y las modernas herramientas bioinformáticas empieza a contribuir a una mejor comprensión de la respuesta del hospedador a las infecciones microbianas. Debido a esto, en esta tesis doctoral se planteó como objetivo identificar y describir las rutas e interacciones moleculares involucradas en la respuesta a la infección con Salmonella enterica serovar Typhimurium (S. Typhimurium) en la especie porcina.

Los tres primeros estudios que componen esta tesis doctoral tuvieron como objetivos explorar los mecanismos moleculares que ocurren en los nódulos linfáticos mesentéricos (NLM) porcinos tras 1, 2 y 6 días post-infección (dpi) con S. Typhimurium. Inicialmente, la expresión diferencial de genes relacionados con la respuesta inmunitaria fue analizada y correlacionada con cambios en la morfología tisular y carga de patógeno. Los resultados revelaron que la infección resultó en una abundante infiltración de fagocitos y sobre-expresión de genes pro-inflamatorios. Notablemente, una significativa reducción de la presencia de la bacteria en el tejido fue observada, en asociación con la activación de los mecanismos de defensa del hospedador. A pesar de ello, el patógeno logró mantenerse en los NLM, siendo detectado a los 6 dpi. A continuación, un análisis proteómico mediante DIGE fue llevado a cabo, poniendo de manifiesto que la infección resultó en cambios en la abundancia de proteínas involucradas en distintas funciones celulares del hospedador, promoviendo en los NLM infectados la inducción de procesos como la infiltración de fagocitos, remodelación del citoesqueleto, piroptosis y presentación antigénica. Finalmente, la respuesta del hospedador a la infección fue evaluada mediante análisis de micromatrices y los resultados obtenidos fueron complementados con datos de expresión génica procedentes del patógeno presente en tejido. En conjunto, el estudio reveló que, aunque S. Typhimurium expresa factores de virulencia en NLM porcinos, el hospedador contrarresta de forma efectiva las estrategias de virulencia del patógeno, mediante la modulación de la muerte celular de células infectadas y la inducción de una respuesta citotóxica temprana.

Los estudios cuarto y quinto reportados en esta tesis doctoral estuvieron centrados en el estudio de la función de las placas de Peyer (PP) porcinas durante la infección con S. Typhimurium. Inicialmente, la técnica de microdisección laser, asociada a ensayos de PCR cuantitativa, reveló que mecanismos de respuesta inmune innata y adaptativa son efectivamente inducidos en los folículos de las PP durante la infección. Dichos resultados fueron confirmados y ampliados mediante un análisis de micromatrices que permitió observar que la infección con S. Typhimurium provocó una notable respuesta inflamatoria en los folículos de las PP, resultando al mismo tiempo estimulada la respuesta adaptativa a diferentes niveles. Interesantemente, evidencias de la inducción de cross-presentation y desarrollo de respuesta humoral fueron también observadas.

Como conclusiones, esta tesis doctoral pone de manifiesto que, pese a las sofisticadas estrategias desarrolladas por S. Typhimurium para causar enfermedad, en los NLM porcinos se inducen de manera coordinada mecanismos innatos y específicos de defensa que tienen como objetivo el control de la infección. Entre estos mecanismos, la inducción de piroptosis y la inhibición de la apoptosis de las células infectadas podrían jugar un papel crítico en la función de los NLM porcinos como una barrera para prevenir la dispersión del patógeno más allá del tracto intestinal. A la vez, la infección determinó la activación de una respuesta citotóxica temprana contra Salmonella, mediante la cross-presentation de los antígenos bacterianos. Por otro lado, además de la estimulación de la respuesta mediada por células B, los folículos de las PP promueven la producción de células T CD8 efectoras y de memoria, lo que representa una función no observada hasta el momento en este tejido en su papel como órgano de respuesta frente a la infección con Salmonella.

The biology of Salmonella

Salmonella are Gram-negative bacilli belonging to the Enterobacteriaceae family, considered a major cause of disease in cold-blooded and warm-blooded animals [START_REF] Jacobsen | The Salmonella enterica pan-genome[END_REF]. According to the contemporary nomenclature, the genus Salmonella contains only two species: Salmonella enterica and Salmonella bongori. S. enterica subdivides into the subspecies enterica, salamae, arizonae, diarizonae, houtenae and indica, while S. bongori has no subspecies (Sánchez-Vargas et al., 2011). To date more than 2,500 different Salmonella serovars/serotypes have been characterized, being most of them classified as part of the Salmonella subsp. enterica (Andrews-Polymenis et al., 2010). The characterization of Salmonella serovars is based on their surface antigens: the O (somatic) antigens, which consist in a part of the variable long chain lipopolysaccharide, and the two H (flagellar) antigens [START_REF] Jacobsen | The Salmonella enterica pan-genome[END_REF].

Besides, Salmonella serotypes can be divided into host restricted, host specific, and generalist serotypes. Host restricted serotypes are predominantly associated with one species, but are able to infect other species as well (ex. S. enterica subsp. enterica ser. Dublin). Host specific only cause disease in one host (ex. S. enterica subsp. enterica ser. Typhi) and host generalist serotypes commonly cause disease in a broad range of hosts (ex. S. enterica subsp. enterica ser. Typhimurium) [START_REF] Hoelzer | Animal contact as a source of human non-typhoidal salmonellosis[END_REF].

Human infections by foodborne Salmonella

Disease caused by Salmonella in humans ranges from gastroenteritis to systemic infections [START_REF] Monack | Salmonella persistence and transmission strategies[END_REF]. Depending on the clinical syndromes caused in this host, strains can be classified into two groups: typhoid Salmonella and non-typhoid Salmonella. The former group comprises the causative agents of enteric fever (S. enterica subsp. enterica ser. Typhi and S. enterica subsp. enterica ser. Paratyphi), whereas the latter one includes the remaining serovars (Sánchez-Vargas et al., 2011).

Gastroenteritis by Salmonella is a major concern in developed and developing countries. Majowicz et al. (2010) estimates that each year, nontyphoid Salmonella causes 93.8 million illnesses, of which 80.3 million are foodborne, and 155,000 deaths worldwide. Additionally, these authors highlight that Salmonella infections represent approximately 3% of diarrhoeal illnesses occurring at global scale. In the United States, it is reported that Salmonella alone causes approximately 1 million foodborne infections and costs $365 million in direct medical expenditures annually (CDC, 2010). Similarly, the European Food Safety Authority (EFSA) state that Salmonella was the most frequently reported cause of foodborne outbreaks in 2011 (EFSA, 2013).

A screening by the World Health Organization Global Foodborne Infections Network revealed that S. Enterica and S. Typhimurium are respectively the most common and second most common Salmonella serovars isolated from human infections worldwide, except for North America and Oceania, where the highest prevalence is observed for S. Typhimurium [START_REF] Hendriksen | Global monitoring of Salmonella serovar distribution from the World Health Organization Global Foodborne Infections Network Country Data Bank: results of quality assured laboratories from 2001 to 2007[END_REF]. S.

Typhimurium has a broad host range, causing disease in a variety of animals. In humans, infections by this serovar generally results in a self-limiting gastroenteritis. However, multidrug resistant strains of this pathogen have been reported to cause recurrent systemic infections in humans [START_REF] Monack | Salmonella persistence and transmission strategies[END_REF].

Porcine salmonellosis and public health

Salmonella prevalence estimates for pig farms seem to differ considerably by production and management type. In the USA, average betweenherd estimates equals 53%, exceeding 80% for some farrow-to-finish production systems, while within-herd estimates range from 3.5 to 28% (Foley et al., 2008).

At EU level, 28.7% of breeding holdings are Salmonella positive but among the Member States a wide variation (0-64%) exists (De [START_REF] Busser | Salmonella control in live pigs and at slaughter[END_REF].

Salmonella serovars commonly associated with swine are a major public health concern, being S. Typhimurium is the most frequently reported serovar in pigs and pork in European countries (EFSA, 2013). Infections of pigs with S.

Typhimurium may result in long-term asymptomatic carriage of these organisms (Boyen et al., 2008a). Thus, carrier animals can act as reservoirs of pathogen and produce the cross-contamination of carcasses during slaughterhouse operations (Methner et al., 2011). In fact, human infections by this pathogen are mostly associated with the consumption of contaminated pig and meat thereof (EFSA, 2013). The risk of Salmonella infection from consumption of contaminated pork depends on factors that include the level of infection in the pig herd, hygiene during carcass processing in the slaughterhouse, meat storage and distribution conditions and finally the handling of undercooked pork by the consumer (Boyen et al., 2008a).

Pork meat is the most widely consumed meat in Europe and its consumption has grown steadily during the last years [START_REF] Resano | Consumer satisfaction with pork meat and derived products in five European countries[END_REF]. Since pigs are relevant reservoirs of Salmonella, this tendency increases the potential of exposure to this pathogen (Foley et al., 2008). Curiously, data from the EFSA Panel on Biological Hazards indicate that the contribution of pigs to the prevalence of human infection by Salmonella is currently higher than that of laying hens and eggs. Around 56.8% of the human salmonellosis cases could be attributable to pigs, while the contributions of total reservoirs associated with laying hens, broilers and turkeys are estimated to be 17%, 10.6% and 2.6%, respectively (EFSA, 2013).

Epidemiology, control and economic impact of S. Typhimurium infections in swine

S. Typhimurium can cause infection without disease and persist in the host with intermittent faecal shedding. These asymptomatic carriers are difficult to be detected by bacteriological or serological methods (Boyle et al., 2008) and represent the most important source of Salmonella introduction onto pig farms [START_REF] Hoelzer | Animal contact as a source of human non-typhoidal salmonellosis[END_REF]. However, contact with people, contaminated slurry or sharing contaminated equipment was also proven to be risk factors for the transmission of Salmonella between pig herds and from cattle to pig herds.

Additionally, Salmonella infected rodents have been identified as a source of bacteria in pig herds (Wilhelm et al., 2012). Contaminated feed is recognized as a source of Salmonella for both livestock and poultry. Nevertheless, Doyle and Erickson (2012) state that feed should play only a minor role in the swine industry. Indeed, influence of feed in the prevalence of pig salmonellosis is related to the provision of wet or dry feed in farms. It is reported that dry feed enhances the risk of Salmonella shedding compared to wet feed [START_REF] Farzan | Prevalence of Salmonella spp. on Canadian pig farms using liquid or dry-feeding[END_REF].

Salmonella transmission to pigs occurs mostly via the faeco-oral route, but oro-pharyngeal secretions can also be contaminated so allowing nose-tonose spread of disease (De [START_REF] Busser | Salmonella control in live pigs and at slaughter[END_REF]. Although all age groups are susceptible to Salmonella infection, disease is most commonly observed among weaned pigs more than eight weeks of age [START_REF] Hoelzer | Animal contact as a source of human non-typhoidal salmonellosis[END_REF]. It is inferred that the increase in Salmonella shedding by piglets at this stage of production is a consequence of feed transition and a decrease in sow colostral antibodies (Fosse et al., 2009).

Studies highlight the implication of infection status of sows on Salmonella infections in fattening pigs. A high level of seropositivity in sows was observed to be related to a progressive increase of seropositivity in pigs during farrowing, post-weaning and fattening periods (Lurette et al., 2008). Environmental contamination may also play an important role in maintaining endemic infections. A previous work demonstrated that Salmonella free finishing herds can be produced from endemically infected herds if pigs are strategically moved to clean stalls as they move through the farrow-to-finish system [START_REF] Hoelzer | Animal contact as a source of human non-typhoidal salmonellosis[END_REF]. In line with this, hygiene measures in farrowing rooms were uncovered to exert a great impact on Salmonella occurrence among all factors explaining Salmonella status in pig herds. Moreover, other factors as mixing pig batches along production, antibiotic treatment during the fattening period or a high number of animals per herd seem to increase the risk of transmission of Salmonella (Correia-Gomes et al., 2013).

Effective food safety interventions to reduce or control foodborne pathogens are needed throughout the food continuum, from the farm to the end user (Methner et al., 2011). Thus, the development of on-farm practices aiming to reduce the number of Salmonella-contaminated animals arriving at the processing plants might contribute significantly toward a reduction of Salmonella contamination of pork (Foley et al., 2008). In order to effectively accomplish this aim, attention should be paid to pig feed, cleaning and disinfection procedures at farms and purchase of animals (Wilhelm et al., 2012). Significant reductions of Salmonella in finisher swine can be further achieved by the use of vaccines that, despite of showing disadvantages of limited protection are able to reduce the length of infectious period and consequently reduce the risk of pathogen dispersal [START_REF] De Ridder | Evaluation of three intervention strategies to reduce the transmission of Salmonella Typhimurium in pigs[END_REF]Doyle and Erickson, 2012).

According to De [START_REF] Busser | Salmonella control in live pigs and at slaughter[END_REF], interventions at slaughterhouse level are, at present, more likely to produce larger reductions of human illness than actions at the level of primary production. Nevertheless, reducing the prevalence of Salmonella in herds is particularly important because prevalence at slaughter tends to be considerably higher than on farm. Stress during transport may enhance shedding of Salmonella by non-apparent carriers and subsequently, cause the infection of trucks or interinfection of pigs during lairage, increasing the risk of carcass contamination along the slaughter line. Thus, fasting procedures before slaughter, animal handling during loading and transport and lairage conditions should be critically evaluated to protect food supply from Salmonella (Fosse et al., 2009). Besides, carcass decontamination in addition to hygiene, cleaning and disinfection measures at the slaughter stage as well as education and training are essential to achieve this goal [START_REF] Botteldoorn | Salmonella on pig carcasses: positive pigs and cross contamination in the slaughterhouse[END_REF].

Efficient improvement of food safety also involves economic considerations. Using a model based on data from Danish programs, Baptista et al. (2011) assert that a substantial cost reduction of about € 400,000 per year for the finisher pig sector would be obtained if no herd surveillance activities were carried out to reduce the prevalence of Salmonella in carcass. Besides, these authors observed that interventions at slaughtering are less cost-effective in small and medium-sized abattoirs compared to large ones. Another study also carried out in Denmark uncovered that costs of pig carcass decontamination ranged from €4 to €5.4 million per year, depending on the decontamination method employed [START_REF] Lawson | Cost-effectiveness of Salmonella reduction in Danish abattoirs[END_REF]. Although measures aiming to control Salmonella represent relevant economic efforts to porcine production system, their importance is unquestionable. Failures at controlling Salmonella in the primary production could lead to the spread of bacteria to other species and the environment, resulting in an increased public health risk via direct transmission and contamination of vegetables (Baptista et al., 2011). Additionally, initiatives during slaughterhouse operations are essential to mitigate the risk of Salmonella in pork [START_REF] Goldbach | A cost-benefit analysis of Salmonella-control strategies in Danish pork production[END_REF].

Structural and functional aspects of mesenteric lymph-nodes and Peyer's Patches

In vertebrates, the immune system is subdivided into the innate and adaptive arms of immunity. The innate immune system is composed of anatomic, physiologic, phagocytic and inflammatory barriers that consist in the first line of defence against infectious disease. At the same time, innate immune components also interact extensively with adaptive components to help them to generate specific humoral response and immunologic memory [START_REF] Burkey | Board-invited review: porcine mucosal immunity of the gastrointestinal tract[END_REF]). The integration of the complex cellular interactions that trigger immune responses takes place most efficiently within the organized architecture of secondary lymphoid organs, which include the spleen, lymph nodes, Peyer Patches (PP), tonsils and adenoids [START_REF] Matsuno | The microstructure of secondary lymphoid organs that support immune cell trafficking[END_REF]. These organs are similarly organized, although differences in their vasculature, mode of antigen entrance, local environment and the stimuli they are subjected may differ. All of them exhibit a compartmentalized T and B areas, antigen presenting cells (APC), lymphoid chemokines, high endothelial venules (HEV), lymphatic vessels and in some cases M cells [START_REF] Ruddle | Secondary lymphoid organs: responding to genetic and environmental cues in ontogeny and the immune response[END_REF]. Thus, in addition to the physical barrier provided by epithelia, the intestinal mucosa immune system also uses the gut-associated lymphoid tissues (GALT) to protect the organism and to mediate subsequent innate and adaptive immune responses [START_REF] Burkey | Board-invited review: porcine mucosal immunity of the gastrointestinal tract[END_REF]. Traditionally, GALT comprises four distinct lymphoid compartments: the Peyer's patches (PP) and other lymphoid follicles associated with the follicle associated epithelium (FAE); the lamina propria; intraepithelial lymphocytes (IELs); and mesenteric lymph nodes (MLN) (Acheson and Luccioli, 2004).

Mesenteric lymph-nodes

Mesenteric lymph-nodes (MLN), as other lymph-nodes consist of the outer/superficial cortex, inner/deep cortex, medullary cord and marginal, cortical and medullary lymphatic sinuses (Figure 1). The cortical region is composed of primary follicles of densely packed naïve B cells and follicular dendritic cells (FDC), surrounded by the interfollicular area [START_REF] Matsuno | The microstructure of secondary lymphoid organs that support immune cell trafficking[END_REF]. Upon antigenic stimulus, antigen-activated B cells proliferate giving rise to secondary follicles and germinal centers [START_REF] Elmore | Histopathology of the lymph nodes[END_REF]. The inner cortex is the T cell area with DC and HEV. The medullary cord is the plasma cell area with some B cells, while the lymphatic sinuses are populated by macrophages [START_REF] Newberry | Organizing a mucosal defense[END_REF].

The collected lymph and cell contents enter the lymph-node via afferent lymphatic vessels and filter the node through the lymphatic sinuses in the medulla or move via the subcapsular sinus to leave through efferent lymphatic vessels. Cells and antigens also enter the lymph-node via an arteriole, which branches into a capillary bed [START_REF] Ruddle | Secondary lymphoid organs: responding to genetic and environmental cues in ontogeny and the immune response[END_REF].

In swine, lymph-nodes show some peculiarities when compared to other animals. Both peripheral and mucosa-associated lymph-nodes have a specific structure that is called inverted and are mostly composed of cortex and paracortex, lacking a larger medullary area [START_REF] Scharek | The porcine immune system--differences compared to man and mouse and possible consequences for infections by Salmonella serovars[END_REF]. Besides, lymphocyte trafficking in porcine also differs from that in other animals. As usual, the immigration of lymphocytes into the lymph-node takes place either by afferent lymph vessels or HEV (Rothkotter, 2009). However, in pigs very few lymphocytes leave lymph-nodes in the lymph, since they emigrate via paracortical post-capilary venules and not via efferent lymph vassels [START_REF] Scharek | The porcine immune system--differences compared to man and mouse and possible consequences for infections by Salmonella serovars[END_REF].

Peyer's Patches

PP are islands of organized lymphoid tissue located in the small intestine.

In human and swine, PP are predominantly found in the ileum show a prenatal development (Makala et al., 2002). As other secondary lymphoid organs, PP contain areas populated by B and T lymphocytes (Figure 2). Follicles are pear shaped zones composed of B-cells and FDC, which are separated by the interfollicular area (T-cell area) [START_REF] Matsuno | The microstructure of secondary lymphoid organs that support immune cell trafficking[END_REF]. These structures are overlaid with the FAE, which harbours specialized antigen-sampling M cells 12 interdigitated within the epithelium [START_REF] Burkey | Board-invited review: porcine mucosal immunity of the gastrointestinal tract[END_REF]. The PP region between the follicles and the FAE is called the dome and contains mainly T cells, plasma cells, interdigitating DC and macrophages (Makala et al., 2002).

PP are strategically integrated to intestinal surface as a forward defensive system, acting as sites of antigen sampling and induction of mucosal immune responses [START_REF] Newberry | Organizing a mucosal defense[END_REF]. Gut antigens enter this organ via uptake by M cells located in the specialized FAE (Rothkotter, 2009). Subsequently, antigens encounter numerous professional APC in the dome that prime naïve T and B cells. These lymphocytes become memory or effector cells and migrate from PP to MLN via efferent lymph and then via the thoracic duct to peripheral blood for subsequent extravasation at mucosal effector sites [START_REF] Brandtzaeg | Mucosal immunity: induction, dissemination, and effector functions[END_REF].

The biology of Salmonella Typhimurium infections 1.6.1 The murine model

Murine infections by S. Typhimurium have been largely exploited as a model for the study of typhoid and general salmonellosis. S. Typhimurium causes in mice a systemic disease with a pathogenesis resembling typhoid fever in humans (Wick, 2010). S. Typhimurium is a food-and water-borne pathogen.

Thus, following ingestion, a proportion of inoculum that succeeds in tolerating the low pH environment of the stomach enters the small intestine to establish infection (Álvarez-Ordóñez et al., 2011). At this point, S. Typhimurium must adhere itself to epithelial cells in the gut by several adhesins and fimbriae and subsequently cross the intestinal epithelium (Broz et al., 2012). As depicted in the Figure 3, multiple traversal routes are involved in Salmonella penetration of host mucosa (Tam et al., 2008).

The host-Salmonella interaction is dominated by the broad array of sophisticated weaponry used by bacteria to overcome host defences (Andrews-Polymenis et al., 2010). S. Typhimurium preferentially targets the M cells located in the PP follicle-associated epithelium, manipulates their function and moves through them, accessing lymphoid cells of GALT (Martinoli et al., 2007). However, this pathogen can also induce its internalization in enterocytes through its virulence-associated type III secretion system (TTSS) encoded by Salmonella pathogenicity Island 1 (SPI-1) [START_REF] Ly | Mechanisms of Salmonella entry into host cells[END_REF]. TTSS encode needle-like complexes that inject bacterial effector proteins that are able to hijack host cell functions, including those associated with cytoskeleton remodelling and immunomodulatory activity [START_REF] Garai | Salmonella enterica serovars Typhimurium and Typhi as model organisms: revealing paradigm of hostpathogen interactions[END_REF]. Invasion also has been proposed to occur by paracellular pathways following disruption of epithelia tight junctions and via DC intercalated between epithelial cells. However, the importance of these invasion-independent alternative pathways remains to be determined (Broz et al., 2012). (7) passing through or between compromised epithelial cells. After the bacteria reach the lamina propria, they can access the MLN within migrating DCs, which are abundant in the lamina propria. Finally, the bacteria may be able to reach the blood stream, presumably transported by CD18+ phagocytes, as shown in (8). In addition to being transported to the MLN via lymph within DCs, it remains possible that free bacteria could be transported in lymph. (9) Bacteria can exit the MLN as free bacteria or possibly associated with cells and seed other tissues in the body (Tam et al., 2008).

After crossing the epithelium, Salmonella is taken by phagocytes located in the PP dome that work to remove invading microbes by phagocytosis and alert other immune cells of the infection, either directly or by releasing proinflammatory cytokines (Tam et al., 2008). Indeed, a rapid recruitment of neutrophils to infected tissue is the pathological hallmark of gastroenteritis caused by non-typhoidal Salmonella serovars (Andrews-Polymenis et al., 2010).

For initiation of responses against microbes, macrophages and dendritic cells express multiple pathogen recognition receptors, including the cytosolic nucleotide-binding and oligomerization domain (NOD)-like receptors (NLR) and the Toll-like receptors (TLR) located on the cell surface or within a vacuolar compartment (Wick, 2011). Furthermore, a subset of NLR induces the assembly of a large multiprotein signaling complex called the inflammasome, which in cooperation with the adaptor protein ASC and activated caspase-1 (CASP1), leads to production and secretion of mature interleukin-1β and IL18 (Figure 4). CASP1 activation also initiates a proinflammatory cell-death called pyroptosis (Miao and Rajan, 2011).

Although pyroptosis and apoptosis are both programmed forms of cell death, pyroptosis is not considered immunulogically silent, since it causes the release of cellular contents and proinflamatory cytokines (Duprez et al., 2009). Of note, induction of pyroptosis was proved to be a mechanism that benefits host during Salmonella infections by eliminating the intracellular niche of the pathogen and re-exposing it to extracellular immune defenses, mainly clearance by neutrophils (Miao et al., 2010). Indeed, this evidence justifies the crucial role of neutrophils to prevent the dissemination of bacteria from the gut during salmonellosis, despite the fact that this S. Typhimurium is mainly considered an intracellular pathogen (Broz et al., 2012). Despite innate mechanisms are triggered by host to fight against infection, Salmonella is able to maintain itself in an intracellular compartment named the Salmonella containing vacuole (SCV) following phagocytosis. To establish this niche, pathogen expresses its SPI-2-efectors that act stabilizing the vacuolar membrane, modulating endocytic trafficking and inducing delayed host cell death [START_REF] Garai | Salmonella enterica serovars Typhimurium and Typhi as model organisms: revealing paradigm of hostpathogen interactions[END_REF]. The SPI-2 TTSS plays an essential role in preventing rapid pathogen clearance by promoting its survival within mononuclear phagocytes [START_REF] Srikanth | Salmonella effector proteins and host-cell responses[END_REF].

From intestine, Salmonella can reach the MLN via the draining lymph as free extracellular bacteria or be transported by cells, presumably DC, from the lamina propria and/or Peyer's patches. At this stage of an orally acquired infection, pathogen is still confined to intestine and associated lymphoid tissue.

However, in mice infections virulent Salmonella disseminate and reach other tissues such as the liver, spleen and bone marrow. To cause this systemic dissemination, Salmonella reach bloodstream via lymph that empties into the blood in the thoracic duct or possibly via CD18 + phagocytes infected in the gut (Tam et al., 2008).

Continuous spread of the bacteria from infected cells to new infection foci is one of the key features of murine systemic Salmonella infections. This spread avoids high intracellular bacterial densities within the phagosomal compartment, a situation that would render the bacteria either nutritionally or spatially constricted. Moreover, bacterial spread from established foci to new infection foci at immunologically unprimed sites is also likely to be a mechanism that allows Salmonella to stay one step ahead of the progressive local activation of the inflammatory response (Haimovich and Venkatesan, 2006). S.

Typhimurium can be recovered from systemic sites up to one year after infection from asymptomatic mice. Although persisting bacteria sequestered within macrophages appear to enter a dormant-like state, S. Typhimurium survival and replication in hemophagocytic macrophages may play a key role in the establishment of persistent infections [START_REF] Monack | Salmonella persistence and transmission strategies[END_REF].

Effective control and eventual eradication of bacteria during the late phases of a primary infection and the generation of protective immunity against subsequent infections require the development and active recruitment of adaptive immunity mediators [START_REF] Dougan | Immunity to salmonellosis[END_REF]. However, accumulation evidences have shown that Salmonella is able to inhibit T-cell activation by interfering with the presentation of antigens on the DC surface (Bueno et al., 2012). Since DC are important APC linking innate and adaptive immunity, interfering with their capacity to stimulate naïve T cells may allow pathogens evading adaptive immunity. Such interference would promote pathogen survival and dissemination, both crucial events in Salmonella pathogenesis [START_REF] Swart | Interactions of Salmonella enterica with dendritic cells[END_REF].

Differences between infections in mouse and other hosts

When considering host response to salmonellosis, it is important to stress that most of available knowledge was accessed by the study of mouse model, as this has been worked on most extensively. Nevertheless, observations from this approach do not always correlate with human (Tsolis, 2011) and farm animals infections (Bearson and Bearson, 2011). In different hosts, the outcome of infection differs in terms of local versus systemic spread, influence of infecting isolate properties and specific breed responses to pathogen [START_REF] Dougan | Immunity to salmonellosis[END_REF]. While septicemic episodes have been reported for Salmonella in mice, colonization by S. Typhimurium in food-producing animals is usually limited to the gastrointestinal tract [START_REF] Hoelzer | Animal contact as a source of human non-typhoidal salmonellosis[END_REF].

Natural or experimental infection of calves with serotype Typhimurium results in an enteric disease with clinical and pathological features that parallel the disease in man. The intestinal pathology and the predominant influx of PMN leucocytes observed in infected calves are strikingly similar to that of S.

Typhimurium-induced enteritis in humans. In both species, PMN leukocytes are proposed to play a decisive role in the pathogenesis of serotype Typhimuriuminduced diarrhoea [START_REF] Santos | Animal models of Salmonella infections: enteritis versus typhoid fever[END_REF]. Pig infections with S. Typhimurium are also clinically similar to those observed in human. However, besides some evidences indicating the influx of PMN cells to the porcine gut during S.

Typhimurium infections, information on processes behind the induction of diarrhoea is still scarce (Boyen et al., 2008a). S. Typhimurium triggers the up-regulation of pro-inflammatory genes and a Th1 oriented immune response in porcine jejunal gut loops (Meurens et al., 20 2009). Moreover, swine jejunum, ileum and colon respond differently to in vivo infections with S. typhimurium. In spite of the up-regulation of genes coding for innate immunity mediators, ileum showed a down-regulation of IL12 and CASP1, both relevant molecules in the response of host to Salmonella. This result could represent an advantage to pathogen during pig infections and was inferred to be related to the preference of S. Typhimurium for invading intestinal mucosa through ileum (Collado-Romero et al., 2010).

In pigs, S. Typhimurium is sporadically present in liver and spleen shortly after experimental inoculation but does not seem to replicate and is cleared from these organs a few days after inoculation. However, bacteria are able to persist in the gut and gut-associated lymph nodes (Boyen et al., 2008a). Gut-associated lymph-nodes are considered important niches for S. Typhimurium during swine infections. In fact, Salmonella prevalence in lymph-nodes of slaughter pigs from EU countries ranges from 0% to 29% (Baptista et al., 2011). Basing on data from mouse infections, it could be inferred that S. Typhimurium reach MLN via intestinal lymph, being shuttled by infected phagocytes or as extracellular bacteria. Nevertheless, this issue has never been addressed to date by any available report. Uthe et al. (2007) observed that S. Typhimurium could be isolated from pig MLN at 8 hours post oral infection and verified that pathogen was able to maintain itself in these organs at least 21 days post infection.

Macrophages located in mesenteric lymph nodes are considered to be important players in the induction of long-term persistence of S. Typhimurium in infected pigs (Boyen et al. 2008a). Epidemiological analysis has established that Salmonella persistent carriers are crucial targets for disease control, because they shed the pathogen in high enough numbers to transmit disease (Gopinath et al., 2012). Indeed, asymptomatic carriers represent the most important source of Salmonella introduction onto pig farms [START_REF] Hoelzer | Animal contact as a source of human non-typhoidal salmonellosis[END_REF]. For this reason, a comprehensive view of the processes involved in the maintenance of pathogen in host lymphoid organs and the conversion of infected pigs to carriers consist in an essential step for controlling salmonellosis.

As previously discussed, SPI-2 effector are indispensable for systemic infection of mice, since they support the intracellular survival of Salmonella inside host cell, especially macrophages [START_REF] Garai | Salmonella enterica serovars Typhimurium and Typhi as model organisms: revealing paradigm of hostpathogen interactions[END_REF]). Curiously, S. Typhimurium strains mutants for SPI-2 were found to be fully capable of colonizing the intestines of pigs and to establish a long-term intestinal persistent infection after oral inoculation (Boyen et al., 2008b), suggesting that S. Typhimurium might employ different strategies to promote the carrier state during mouse and pig infections. Therefore, this divergence highlights the need of models other than murine infections to elucidate the mechanisms involved in the induction of persistent infections by Salmonella and reinforces the notion that the extrapolation of data from murine model to other species should be done with prudence.

Swine as a model for the study of Salmonella Typhimurium infections

Animal models are valuable tools for a better understanding of pathogenesis mechanisms behind human diseases. To date, mouse has been widely used to provide novel knowledge in distinct fields of biology and medicine. However, mouse disease models often do not faithfully mimic the relevant human conditions, bringing to light the need of better animal models (Luney, 2007).

Swine are increasingly appreciated for their potential to model human disease and this tendency was further reinforced by the recent advances in pig genomics and proteomics [START_REF] Prather | Pig genomics for biomedicine[END_REF]Bendixen et al., 2010). Besides, pigs and humans are remarkably similar in terms of physiology. Interestingly, the porcine immune system shows a higher level of similarity to human one than murine. Genomic comparisons between human, murine and porcine sequences also demonstrate more resemblances between human and porcine than human and murine sequences (Luney, 2007).

The swine model has been used to study as a model for many human infectious diseases and represent a valuable intermediate species to validate the applicability of knowledge obtained using rodent models to human (Meurens et al., 2012). However, although former reports of experimental infections of pig with Salmonella can be found in the literature (Williams et al. 1978[START_REF] Baskerville | Ultrastructure of phagocytosis of Salmonella cholerae-suis by pulmonary macrophages in vivo[END_REF], it was the 1990s when the use of this species for the study of salmonellosis became more current.

Advances in mammalian models of Salmonella infection are expected to result in new understanding of salmonellosis pathogenesis, contributing to the control and cure of human cases (Gopinath et al., 2012). Upon infection with S.

Typhimurium, swine undergo a self-limiting enterocolitis which parallels the clinical manifestation observed in man (Sanchez-Vargas et al. 2011; Boyen et al., 2008a). In light of this and the potential of swine as models of human disease, pigs can be stressed as an ideal model for investigating the pathogenesis of human non-typhoidal salmonellosis.

Use of functional genomics to identify target molecules and mechanisms for the improvement of resistance to infectious diseases in animals

Resistance and tolerance to infectious pathogens are important characteristics of livestock to counteract the potential detrimental impact of pathogens on animal health and production (Doeschl-Wilson et al., 2012a).

Strong evidence has accumulated that livestock species from birds to mammals, harbour genes that control protective responses to the various classes of pathogen from viruses to nematodes. However, there remains a gap for traits linked to disease resistance and tolerance because the main polymorphisms that underpin these traits have not been identified. This is partly because hostpathogen interactions are highly complex, involving many different molecules and cell types which interact together over time [START_REF] Glass | The molecular pathways underlying host resistance and tolerance to pathogens[END_REF].

Disease traits have been difficult to target by traditional selection, but recent developments in high throughput genomics provide opportunities to dissect host responses to infectious pathogens and to increase the accuracy of selection (Doeschl-Wilson et al., 2012b). Knowledge obtained from the complete genome sequencing of many species has enabled discovery of new aspects of the host-pathogen interaction. Moreover, the development of genomics, transcriptomics, proteomics and computational biology has resulted in the systematic study of the host-pathogen interaction. Thus, functional genomics approaches have enabled the integration of experimental data from the diverse high-throughput methods to create a global picture of host-pathogen interplay in space and time (Hartlova et al., 2011).

In order to gain access to the host environment, a pathogen must cross the mucosal surfaces of the gut, respiratory tract, mammary gland and genital tract. After invading, these organisms should be able to tolerate and overcome host immunity. Thus, genetic variance in molecules taking part in the distinct partners of host defence against invaders might play an important role in the development of resistance or tolerance to infections. Strikingly, some examples have been described in veterinary. Recently, genetic variants in bovine CD46 have been shown to influence cell permissiveness for bovine viral diarrhoea virus and thus carriers of CD46 alleles might vary in resistance to this pathogen. Besides, the gut receptor for E. coli F18 encoded by the FUT1 gene in pigs was found to confer complete resistance to E. coli [START_REF] Glass | The molecular pathways underlying host resistance and tolerance to pathogens[END_REF]. Another report, exploring the genetic resistance of bovine to the tick-borne protozoan Theileria annulata, demonstrated that an up-regulation of SIRPβ and TGFβ2, both mediators of inflammatory response, is associated to greater virulence and also higher propensity for invasion observed Holstein cows compared to the Bos indicus cattle breed Sahiwal (Chauessepied et al., 2010).

In the case of S. Typhimurium infections, genetic resistance to systemic disease in mice has been linked to many factors including the major histocompatibility complex (MHC), Toll-like receptor 4 and the natural resistance associated macrophage protein (NRAMP1). NRAMP1 is the most studied of all these factors and exerts effects on macrophage activation including MHC expression, release of pro-inflammatory cytokines and the production of antimicrobial effectors such as nitric oxide and oxidative burst. Mutations in this gene result in mice susceptible to S. Typhimurium and other intracellular pathogens such as Leishmania and Mycobacterium (Wigley, 2004). In fowl, comparisons of different models have successfully identified the genomic regions carrying the genes TLR4, NRAMP1 and the QTL SAL1 as having roles in phenotypic variations related to Salmonella resistance [START_REF] Calenge | Genetic control of resistance to salmonellosis and to Salmonella carrier-state in fowl: a review[END_REF]. Control of salmonellosis in swine herds generates increased production costs and public health issues in the use of prophylactic antibiotic potentially leading to development of antibiotic resistant strains. Therefore, the breeding of resistant animals, in combination with good hygiene practices offers a promising low risk strategy to fight against Salmonella in this species. In pigs, NRAMP1 is strongly expressed on macrophages and neutrophils following stimulation with LPS, but any role for this gene in Salmonella infection is yet to be described In spite of the association between genetic variation and resistance to salmonellosis in swine, selective breeding for resistance traits aiming to control the disease or the carriage of Salmonella in this species is still not feasible. In fact, targeting of the key host molecules and mechanisms involved in bacterial pathogenesis is indispensable to address this issue and a robust analysis of S. Genetic improvement of the resistance to infectious diseases represents an essential step for the development of sustainable and economically viable animal production systems. This issue is of particular importance in the case of zoonotic diseases, since a safe food supply largely depends on controlling the infection in livestock hosts. Functional genomics approaches combining the power of gene mapping technologies, gene expression studies and modern bioinformatics tools have begun to contribute very recently to a better understanding of the host response to microbial diseases. The knowledge provided may reveal new tools, therapeutics, and improved strategies for the establishment of future programs to develop disease-resistant livestock breeds, which should be aimed at improving health and welfare of animals, and as a result, improved quality and food safety.

The overall objective of this thesis is to identify and describe molecular pathways and the interactions involved in the porcine intestinal immune response to Salmonella enterica serovar Typhimurium. To achieve this objective, an in vivo experimental infection model was established and the following five specific objectives were set up:

1. Evaluate the differential expression of immune-related genes in the MLN of S. Typhimurium infected pigs, in correlation with changes in tissue cellularity and pathogen burden (Martins et

Experimental studies

Introduction

Salmonella is one of the most frequent causes of food-borne outbreaks in Europe, with 108,614 confirmed cases of human salmonellosis in 2009 [1].

Worldwide, Salmonella causes 94 million cases of acute gastroenteritis, including 155,000 that are fatal, with children in particular falling victim to the disease [2].

Among more than 2500 serovariants, the host-generalist Salmonella enterica serovar Typhimurium (herein S. typhimurium) is reported as the serovar most frequently associated with human illness, with S. typhimurium cases mostly associated with the consumption of contaminated pig and poultry meat [3].

Infections by S. typhimurium in pigs lead to a localized enterocolitis and, in general, infected swine evolve into healthy carriers in which bacteria are able to persist without triggering clinical signs [3]. The existence of asymptomatic carriers is a major threat to public health given that such animals cannot be detected easily and thus serves as source of contamination in food industry [4]. In addition to its importance as zoonotic disease, salmonellosis has an important impact in porcine health and negative implications in the efficiency and economy of the porcine production systems [5].

As a result of food poisoning, Salmonella enters the body through the gastrointestinal tract. After location in intestinal lumen and attachment in epithelial cells, Salmonella actively invade intestinal cells, colonize the lamina propria and Peyer's patches and rapidly invade host cells, especially macrophages, but also dendritic cells and neutrophils [6]. Consequently, these innate immune cells produce and release chemoattractant cytokines to recruit additional inflammatory cells into the site of invasion and initiate a T helper 1 (Th1) response [7]. From intestine, Salmonella reaches mesenteric lymph nodes (MLN), can enter the bloodstream and spread to internal organs [8]. To prevent 40 systemic infection, MLN form a life-saving firewall that protects the host from rapid pathogen dissemination beyond the intestine to others organs, such as liver and spleen [9].

One way to learn about the molecular interactions during Salmonella infection is to analyze the host response. To this end, infection experiments using isolated primary cells or cell lines have been carried out to generate most of the knowledge currently available on the molecular events during Salmonella-host interaction [10][11][12]. However, although these in vitro models can provide valuable information, it is clear that this approach does not enable the interaction of pathogens with a multitude of different interacting cells involved in the invasion process in vivo [13]. Moreover, in mammals, studies on the host mechanisms against Salmonella have been largely focused on mice infection models [14,15], although accumulating evidences suggest differences in virulence mechanisms, pathogen colonization and disease susceptibility in food-producing animals infections compared to the murine model of systemic disease [16]. Thus, while in mice S. typhimurium moves into the mesenteric lymph nodes, and from there bacteria spread via the efferent lymph to the circulatory system, causing a systemic disease [17], in pigs usually causes a self-limiting intestinal disease enterocolitis which is similar to gastroenteritis in humans [6]. Factors that could cause these differences have not been sufficiently clarified, but make the pig an ideal model for investigating enteric salmonellosis in humans.

In swine, in vitro and in vivo studies have generated valuable insight in the crosstalk between Salmonella and porcine tissues and cells [18][19][20].

Nevertheless, few studies have addressed the requirements for the gutassociated lymph nodes in the development of immune responses, their effect on the protective immunity against Salmonella infection and the relationship between changes in MLN transcriptome, tissue cellularity and level of pathogen invasion. In order to contribute to improved knowledge on the role of porcine 41 MLN on S. typhimurium infection, in the current study we use a model of in vivo experimental challenge to evaluate changes in gene expression and tissue morphological alterations that occur in these organs following infection.

Materials and methods

Experimental infection

The experimental infection design was described elsewhere [19]. Briefly, sixteen weaned piglets of approximately 4 weeks of age and fecal-negative for Salmonella were penned in an environmentally controlled isolation facility at 25°C with ad libitum access to feed and water. All the animals were randomly allocated to control group (4 piglets) or infected group (12 piglets). The four noninfected pigs were necropsied 2 h before the experimental infection. The animals belonging to the infected group were orally challenged with 108 CFU of S. typhimurium phagetype DT104. Afterwards, four infected pigs were randomly sampled and necropsied at 1, 2 and 6 days post infection (dpi). Fecal samples from the infected group were cultured for Salmonella to ensure the effectiveness of the experimental challenge. Furthermore, rectal temperature and clinical signs were daily recorded for each animal to observe the evolution of the infection. All procedures involving animals were performed in accordance with the European regulations regarding the protection of animals used for experimental and other scientific purposes.

Histopathology and immunohistochemistry

Samples of MLN from all experimental animals were fixed in 10% neutral buffered formalin for 24 h and embedded in paraffin-wax for histological processing. Afterwards, 5 μm tissue sections were routinely processed as previously described [21], and stained with hematoxylin and eosin (H&E).

Presence of bacteria in the tissue samples was demonstrated by using an anti-Salmonella polyclonal antibody raised by immunization of a New Zealand rabbit with a formalin fixed bacterial suspension. Quantification of tissue infiltration of macrophages was carried out by using a monoclonal antibody specific for porcine macrophages (clone 4E9/11) [22]. Immunohistochemical staining of formalinfixed, paraffin-embedded sections of porcine MLN samples, subjected to heatmediated antigen retrieval in 0.01 M citric acid, with Salmonella antiserum and 4E9 monoclonal antibody was performed by using the immunoperoxidase method as has been described elsewhere [21]. Neutrophils identify by morphology and immunolabeled macrophages were counted in 50 randomly selected high magnification fields (400×) in sections of two different MLN samples from each infected and control animal. Results were expressed as the mean number of cells per field.

Nucleic acids purification

Samples of MLN from control and infected animals were aseptically collected after necropsies and immediately frozen in liquid nitrogen for DNA and RNA isolation. Then, after treatment with RNAlater-ICE (Ambion), a volume of 0.6 ml of RLT buffer (Qiagen) was added per 30 mg of tissue followed by disruption in a rotor-stator homogenizer. DNA and RNA were isolated by using the AllPrep DNA/RNA/Protein Mini Kit (Qiagen) and eluted RNA was treated with RNase-Free DNase Set (Qiagen) according to manufacturer instructions. Afterwards, purified RNA and DNA were routinely precipitated with ethanol. RNA and DNA quality was checked by agarose gel electrophoresis before being quantified using a Nanodrop ND-1000 spectrophotometer (Thermo Scientific).

Quantitative real-time PCR

Real-time quantitative PCR (qPCR) technology was used to determine the relative expression of 42 immune-related genes along the time course of infection (1, 2 and 6 dpi). Total RNA (1.5 μg) from infected and control animals was reverse transcribed to cDNA using the iScript cDNA Synthesis kit (Biorad) in a total volume of 30 μl. cDNA solutions were diluted by adding 70 μl of UHQ water and stored at -20 °C. The qPCR assays were performed on an iQ5 Thermo Cycler (BioRad) using 96 well PCR plates. All samples were amplified in duplicate in the same PCR plate and plates were repeated at least twice. Twenty microliters qPCR reactions were prepared using 2 μl of cDNA as template and iQ SYBR® Green Supermix (BioRad) according to manufacturer's instructions. Final concentration of the primers in the PCR reactions was 0.4 μM. Primers (Table 1) were designed using Beacon Designer (Biosoft International) as previously described [19]. The qPCR conditions were as follows: 95 °C for 5 min, 35 cycles of 94 °C for 30 s, 57 °C for 30 s and 72 °C for 45 s. After amplification, a melting program was run to ensure correct amplification of the expected amplicons.

Table 1 -List of genes and primer sequences for quantitative PCR analysis.

Gene Name

Foward Primer (5' → 3') Reverse Primer (5' → 3') Accesion number

βActin CAGGTCATCACCATCGGCAACG GACAGCACCGTGTTGGCGTAGAGGT U07786 CASP1 CTCTCCACAGGTTCACAATC GAAGACGCAGGCTTAACTGG NM_214162 CCL2 ACCAGCAGCAAGTGTCCTAAAG GTCAGGCTTCAAGGCTTCGG NM_214214 CCL3 TCTCGCCATCCTCCTCTG TGGCTGCTGGTCTCAAAATA AY643423 CCL4 CAGCACCAATGGGCTCAGA TTCCGCACGGTGTATGTGA EF107667 CCL5 CCAGCAGCAAGTGCTCCAT ACACCTGGCGGTTCTTTCTG NM_001129946.1 CCL28 AACATCACAGCAAGAGGAACAG TGGCACAAAGGAACATTCACC NM_001024695 CD11b GCGAGGACTCCCACGGAACTC GAAGATGGGGTGGTTTATGC Y11618.1 CD14 ACCACCCTCAGACTCCGTAATG TTGCGCCACTTTCAGTACCTT EF051626 CD40 TGGTTTCCAGAGTCGGATGAG ACAGGATCCCCAGCGTGAT NM_214194.1 CD40L CAACACCCACAGTTCCTCCAA AGACTCCGCCCAAGTGAATG AB040443.1
CXCL2 GGATAGCACGCTGTACCATC ACTGTCTCAATAAATAACAACCGAC AY578786 CXCL8 TTCGATGCCAGTGCATAAATA CTGTACAACCTTCTGCACCCA M86923 Cyclophilin-A CCTGAAGCATACGGGTCCT AACTGGGAACCGTTTGTGTTG AY266299 DEFB1 ACCGCCTCCTCCTTGTATTC GGTGCCGATCTGTTTCATCT NM_213838 DEFB2 CTGTCTGCCTCCTCTCTTCC CAGGTCCCTTCAATCCTGTT NM_214442 IFNγ CAAAGCCATCAGTGAACTCATCA TCTCTGGCCTTGGAACATAGTCT X53085 IL1β GGCCGCCAAGATATAACTGA GGACCTCTGGGTATGGCTTTC NM_214055 IL4 TTGCTGCCCCAGAGAAC TGTCAAGTCCGCTCAGG AY294020 IL5 TGGTGGCAGAGACCTTGACA CCATCGCCTATCAGCAGAGTT NM_214205.1 IL6 TGGCTACTGCCTTCCCTACC CAGAGATTTTGCCGAGGATG NM_214399 IL10 CAGATGGGCGACTTGTTG ACAGGGCAGAAATTGATGAC L20001 IL12p40 GGAGTATAAGAAGTACAGAGTGG GATGTCCCTGATGAAGAAGC U08317 IL13 AAGTGGCCCAGTTCGTAAAAGA ACCCGTGGCGAAAAATCA NM_213803.1 IL18 AGGGACATCAAGCCGTGTTT CGGTCTGAGGTGCATTATCTGA EU118362.1 IL23p19 GCTTGCAAAGGATCCACCAA GGCTCCCCTGTGAAAATGTC NM_001130236.1 MyD88 TGGTGGTGGTTGTCTCTGATGA TGGAGAGAGGCTGAGTGCAA NM_002468 NFB1 CTCGCACAAGGAGACATGAA ACTCAGCCGGAAGGCATTAT DQ834921 NOD1 ACCGATCCAGTGAGCAGATA AAGTCCACCAGCTCCATGAT AB187219 NOD2 CCTTTTGAAGATGCTGCCTG GATTCTCTGCCCCATCGTAG NM_001105295 SELL CGCTTCCCTTCAGTCGTAG CCACACAGTCCTCCTTAGTC NM_001112678 SLC11A1 CCAAAGCAGAGCAGAAC GGTCCAGGTAAGCAATG AF132037 TLR1 TGCTGGATGCTAACGGATGTC AAGTGGTTTCAATGTTGTTCAAAGTC AB219564 TLR2 TCACTTGTCTAACTTATCATCCTCTTG TCAGCGAAGGTGTCATTATTGC AB085935 TLR3 AGTAAATGAATCACCCTGCCTAGCA GCCGTTGACAAAACACATAAGGACT DQ266435 TLR4 GCCATCGCTGCTAACATCATC CTCATACTCAAAGATACACCATCGG AB188301 TLR5 CAGCGACCAAAACAGATTGA TGCTCACCAGACAGACAACC NM_001123202 TLR6 AACCTACTGTCATAAGCCTTCATTC GTCTACCACAAATTCACTTTCTTCAG AB085936 TLR7 TCAGTCAACCGCAAGTTCTG GATGGATCTGTAGGGGAGCA NM_001097434 TLR8 AAGACCACCACCAACTTAGCC GACCCTCAGATTCTCATCCATCC AB092975 TLR9 CACGACAGCCGAATAGCAC GGGAACAGGGAGCAGAGC AY859728 TLR10 CCTGTCCAACTGCCTCATTTG CTAAGTGTTCTAAGGATGTGTTTCTG AB219565 TNFα CCTCTTCTCCTTCCTCCTG CCTCGGCTTTGACATTGG NM_214022

Salmonella quantification assay

TaqMan qPCR assays were used for quantifying the S. typhimurium load in MLN samples, following the method previously described by Park et al. [23].

DNA from the Salmonella strain employed in the experimental infection was extracted using DNeasy Blood & Tissue Kit (Qiagen) and subsequently diluted to final concentrations of 1.0x10 4 , 5.0x10 3 , 1.0x10 3 , 5.0x10 2 , 2.5x10 2 , 1.0x10 2 , 5.0x10 1 and 0 genome equivalents (GE) per 1 μl. One genome equivalent of S.

typhimurium corresponded to 5.46904 fg of DNA [23]. A 19-mer forward primer Results were shown as the number of genome equivalents of S. typhimurium per 800 ng of MLN DNA (GE/800 ng DNA).

Isolation of S. typhimurium from MLN samples

In order to verify the presence of live S. typhimurium in MLN samples, 1 g of tissue was drenched in 9 ml of buffered peptone water (Oxoid) and disrupted with sterile mortars and pestles. Tissue suspensions were transferred to sterile tubes and incubated at 37 °C with shaking at 200 rpm for 12 h. Afterwards, 10 μl of the resulting culture was streaked on XLD agar (Oxoid) plates and incubated at

Data analysis

The relative gene expression was assessed by the 2 -ΔΔCq method [24] as previously described [19].

Results

Experimental infection

Animals experimentally infected were observed daily for development of clinical disease. The analysis of S. typhimurium fecal carriage revealed that all animals were positive after the bacterial challenge. In addition, infected pigs manifested clinical signs characterized as lethargy, weight loss and diarrhea.

Rectal temperature changed significantly among groups (p = 0.000), fever began at 1 dpi (40.58±0.17

Histopathology and immunohistochemistry

Lymphadenitis, marked by a strong infiltration of inflammatory cells was observed at 2 dpi (Fig. 1A). Similar pathological alterations were observed at 1 and 6 dpi, although to a lesser extent than those seen at 2 dpi. Significant changes in neutrophil count were observed along the time course of the infection (p = 0.005). Thus, the number of neutrophils peaked at 2 dpi (Fig. 1C) and a broad infiltration of these cells around trabeculae was uncovered at this time point.

Immunohistochemistry revealed that the presence of macrophages in MLN also changed significantly after S. typhimurium infection (p = 0.036). As shown in Fig. 1D, macrophages count peaked at 2 dpi, being predominantly found in lymph nodes capsule and within the T-cell area near trabeculae (Fig. 1B).

48

Immunohistochemistry was also carried out to verify the level of tissue invasion by S. typhimurium.

As shown in Fig. 2A-C, bacterial labeling was observed in the cytoplasm of mononuclear cells. In addition, infiltrated neutrophils were located in the diffuse lymphatic tissue around trabeculae. Again, our results demonstrated that labeled cells were more prevalent in lymph nodes at 2 dpi than in groups of animals infected at 1 and 6 dpi.

Expression of immune-related genes during S. typhimurium infection

In order to evaluate the porcine MLN response to S. typhimurium, qPCR expression profiling was performed on a panel of 42 immune-related genes encoding pattern recognition receptors, immune cells markers, innate/inflammatory and T cell response mediators. Statistically significant expression changes were observed in 26 genes along the time course analyzed (Table 2). Overall, the higher number of differentially expressed genes was observed at 2 and 6 dpi (20 and 14 genes, respectively) whereas only 6 genes had

50

their expression changed at 1 dpi. Interestingly, all the significant observed changes at 6 dpi consisted in down-regulation of gene transcripts (Fig. 3). Changes in expression of genes coding for different innate/inflammatory response mediators were uncovered mainly at 2 dpi. Thus, significant mRNA upregulation of IL1β, CXCL2, CXCL8, CASP1, SLC11A and DEFB2 was observed at this time point, whereas expression of CCL28 and SELL resulted down-regulated.

Moreover, mRNA expression of IL1β and CXCL2 were also significantly upregulated at 1 dpi whereas CXCL8 and CASP1 showed down-regulation at 6 dpi.

In spite of the absence of significant difference in mRNA expression at 1 or 2 dpi compared to control, genes coding for TNFα and CCL2 showed downregulation at 6 dpi. Many of the proinflammatory mediators up-regulated at 1 and 2 dpi have their mRNA expression under the control of the transcription factor NFκB.

However, NFκB mRNA expression was significantly downregulated at 2 and 6 dpi.

52

A down-regulation of genes coding for cytosolic and transmembrane pattern-recognition receptors (PRR) was asserted in our study, except for TLR8 and NOD2, which were up-regulated at 2 dpi.

53

Expression of genes coding for other cell surface proteins described as phenotype markers of swine immune cells was checked to estimate changes in MLN cellularity after infection. Changes in gene expression were not found out for CD14 or CD40. However, genes coding for CD11b and CD209 showed significant down-regulation at 2 dpi and CD40L at 1 and 2 dpi.

Finally, a diverse mRNA expression profile was observed among Th1 related genes. Although an up-regulation of IFNγ mRNA could be observed at 2 dpi, statistically significant changes in expression were not observed for IL12p40 and IL18 was down-regulated during the infection period studied. Concerning to Th2 response, down-regulation was verified for IL4 transcripts at 2 and 6 dpi and IL13 at 2 dpi. Furthermore, IL5 did not exhibited changes in expression after infection. Other genes encoding T cell costimulatory molecules were also studied.

Thus, changes in IL23p19 mRNA expression were not detected and IL10 showed down-regulation at 6dpi. typhimurium in MLN of all animals belonging to groups 1, 2 and 6 dpi.

54

Nevertheless, the presence of bacteria was not detected in control animals, confirming their previously established Salmonella free status.

Conjunctive analysis of S. typhimurium burden, phagocyte count and immune-related genes expression

Spearman's rank correlation indicated a strong positive association between Salmonella burden and neutrophil count (Table 3 and Supplementary data file 1). Transcripts level of IFNγ, CXCL2, IL1β, CCL3 and SLC11a was also positively associated with the pathogen load in infected MLN, at a high level of significance (p < 0.01). Among genes which expression was negatively associated with Salmonella burden, TLR3, IL18, CD40L and CD11b could be highlighted.

Expression of IFNγ, CXCL2 and IL1β was also positively associated with neutrophil count, whereas, mRNA levels of CD40L, IL4 and TLR3 were negatively associated.

Differently from Salmonella load and neutrophil count, macrophages count showed a higher frequency of significant negative associations. Interleukin 13, CD209 and CD11b should be cited as genes which expression showed the most significant associations with macrophages count.

Discussion

MLN are important sites for the induction of immune response against invading pathogens in the gut [26]. In this work, we applied an in vivo approach to obtain insight into the response of porcine MLN to S. typhimurium. The effectiveness of the performed bacterial challenge was confirmed by the manifestation of typical clinical signs of pig salmonellosis by infected animals.

Moreover, the presence of S. typhimurium in MLN at 1, 2 and 6 dpi was demonstrated employing microbiological and DNA based techniques. Higher S. typhimurium loads were observed at 2 dpi, when a peak of corporal temperature was recorded and most of changes in gene expression were observed. In addition, histological analysis confirmed the existence of bacteria in the tissue and detected changes in MLN cellularity as a consequence of the infection.

Consistent with the latter, we observed that infection led to a strong infiltration of macrophages and neutrophils in MLN, which was highly correlated with S. typhimurium burden in the tissue. The recruitment of monocytes and neutrophils from blood to infected tissues is a requirement for controlling pathogens replication and ensuring host survival to infection [27]. L-Selectin (SELL), a glycoprotein constitutively expressed by porcine leucocytes [28], was down-regulated at 2 and 6 dpi. Negative correlations observed between the level of SELL transcripts and neutrophil/macrophage count in MLN confirms previous reports of SELL down-regulation by recruited monocytes [27] and neutrophils [29]. Chemokines are the main mediators involved in the recruitment and migration of leukocytes to and within tissues [30]. According with previously reported data [31,32], our experimental infection produced an up-regulation of chemokines in MLN. Moreover, significant correlations were observed between mRNA levels of CXCL8, CXCL2, and tissue neutrophil count. However, changes in expression of these chemokines were not significantly correlated to macrophages count. Interestingly, changes in expression of SLC11A1 showed positive 57 correlations with mRNA levels of most of pro-inflammatory genes, such as CXCL2, CXCL8, IFNγ, IL1β and CASP1 (Supplementary data file 1). SLC11A1 is an important innate host resistance factor to S. typhimurium, specially expressed in phagocytic cells, such as dendritic cells (DC) [33], macrophages and neutrophils [34]. In mice, the impact of SLC11A1 on the severity and outcome of S.

typhimurium infection is determined by its influence on the speed and intensity of the host inflammatory response, facilitating the rapid activation of host defense [35]. In this work, we observed a strong up-regulation of SLC11A1 at 2 dpi and its expression was significantly correlated to the grade of tissue invasion by Salmonella and neutrophils infiltration. Consequently, this could indicate that regulation of SLC11A1 acts as a mechanism of orchestration of inflammatory response in MLN of S. typhimurium infected pigs, as has been previously reported in mice [33].

Herein, Salmonella infection resulted in downregulation of CD11b and its mRNA level was negatively correlated with pathogen burden as well as macrophages and neutrophils count in MLN. Differently from human, swine CD11b is only expressed by a subpopulation of granulocytes and lacks expression by monocytes and macrophages [36]. In addition, among the four DC subpopulations found throughout the porcine intestinal immune system, DC from Peyer's patches (PP) have been described as CD11b-, whereas DC in MLN are predominantly CD11b+ [37]. Previous reports highlight S. typhimurium transport from intestine to the draining MLN via PP DC as the most predominant penetration route in infection models [9,35,38]. Therefore, down-regulation of CD11b could be attributed to an increase in MLN of cells that do not express this cell marker such as macrophages, and probably DC from PP.

Activated caspase 1 (CASP1) contribute to the control of Salmonella infection by processing and maturating the pro-inflammatory cytokines IL1β and IL18 [39]. In this study, CASP1 exhibited up-regulation at 2 dpi, followed by down-58 regulation at 6 dpi. However, its substrates showed a different expression pattern: IL1β was strongly upregulated at 1 and 2 dpi, whereas IL18 was downregulated all along infection. In murine MLN and spleen, IL18 is the predominant CASP1 substrate that mediates resistance to oral S. typhimurium infection [40].

IL18 acts synergistically with IL12 in the induction of IFNγ production by antigen stimulated T cells in human and mice [41]. Nevertheless, we uncovered an increase of IFNγ expression, in spite of the absence of significant changes in IL12p40 regulation along infection. The lack of significant associations between mRNA levels of IL12p40/IL18 and IFNγ (Supplementary data file 1) could confirm the independence of IFNγ expression respect IL12p40 or IL18 regulation.

Moreover, up-regulation of IFNγ could be explained by the fact that NK cells are important producers of this cytokine in pigs [41]. Together, these results might indicate that in porcine infections by S. typhimurium, IL18 and IL12 do not play the same role as in human and mice salmonellosis. It could also be inferred that repression of this cytokines is a mechanism whereby Salmonella may limit the protective cell-mediated immune response early in infection, as has been previously proposed [42].

Our results also evidenced a decrease in mRNA levels of genes coding for cytokines and receptors related to DC-T-cell interaction. CD40L expression is induced shortly after T-cell activation and represents an early activation marker of T lymphocytes [43]. Activated T cells enhance IL-12 production by interaction of their receptor ligand CD40L with CD40 on DCs or macrophages [44]. Since CD40L was down-regulated at 1 and 2 dpi, this could also be related to the expression profile uncovered for IL12p40. CD209 was also down-regulated at 2 dpi. This gene codes for a C-type lectin which mediates strong adhesion between DC to resting T cells and is essential in establishing the DC induced T cell proliferation [45]. Besides, it has been reported that CD209-driven interaction 59 between activated neutrophils and DC induce maturation of the latter and enable these cells to trigger an intense T cells proliferation and Th 1 polarization [46].

Since MLN underwent substantial changes in cellularity after infection, neutrophil extravasation primarily, downregulation CD40L and CD209 could be attributed to the infiltration of cells that do not express these molecules.

However, the decrease in mRNA levels of IL12p40, which production is induced by activated T cells, as well as reports asserting the prevention of T cells activation as a strategy used by Salmonella to evade immune response [8] lead as to infer that this machinery could be employed by the bacteria in swine MLN infection.

TLRs and NODs function as sentinels of infection via recognition of pathogen-associated molecular patterns (PAMPs) and induction of appropriate innate and adaptive immune responses to invaders [47]. In this work, we found that except TLR-8 and NOD2, which were up-regulated at 2 dpi, most of the PRR were significantly down-regulated after Salmonella challenge. Rydstrom and Wick [30] relate that the absence of signaling through TLR4, TLR5 or both TLR4/5 simultaneously did not compromise phagocytes recruitment to PP and MLN.

These authors inferred that such deficiency is probably compensated by recognition of bacterial ligands by other PRR. The occurrence of the TLR signaling at the very first moments of the bacterial challenge should not be excluded.

According with both assumptions, we also observed an increase of phagocytes in MLN, in spite of repression of TLR2, TLR3, TLR4 TLR6 and TLR7.

Together, our results suggest a possible synergy between TLR8 and NOD2 in the recognition of S. typhimurium in pig infections. TLR8 and NOD2 are expressed by monocytes, macrophages and DC [48][49][50]. Yrlid et al. [51] state that the application of the agonistic TLR7/8 ligand R848 triggered a massive migration of intestinal DC into MLN. Intriguingly, our results revealed a highly significant correlation (p < 0.01) between mRNA levels of TLR8 and NOD2 (Supplementary

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data file 1). Moreover, expression of none of these genes was correlated with macrophage or neutrophil count in MLN. Therefore, upregulation of NOD2 and TLR8 at 2 dpi could be attributed to the migration of Salmonella infected DC from intestine to MLN. The higher tissue pathogen load observed at 2dpi, in addition to previous reports asserting DC-carriage as the most important mechanism of Salmonella dissemination from gut to MLN [9,35,38], cooperate with this hypothesis.

Different methods were employed in this work to assure the presence of Salmonella in the tissue and elucidate its influence in immune response. Results revealed that the Salmonella burden in the tissue fluctuated during infection depending on host immune response. A coincident up-regulation of proinflammatory mediators and infiltration of phagocytes at 2 dpi reduced substantially the pathogen burden in MLN at 6 dpi. In spite of this, isolation of S.

typhimurium from samples of pigs belonging to 6 dpi group revealed that the pathogen maintained itself in MLN. These findings are in agreement with published observations demonstrating that, after oral infection, S. typhimurium persists in myeloid cells in the MLN, despite host immune response [52].

In summary, our results sustain MLN as a vital barrier preventing systemic dissemination of S. typhimurium and controlling infection in pigs. According with our previously published proteomic data [53], the presence of Salmonella in these organs triggered the induction of innate immune response, marked by a substantial infiltration of phagocytes and up-regulation of pro-inflammatory genes. Such response resulted in a relevant decrease in pathogen burden, but host mechanisms were not able to eliminate S. typhimurium from tissue completely. Although porcine salmonellosis by S. typhimurium result in milder disease compared to mice, our results also lead us to infer that, in swine infections, S. typhimurium might interferes with the DC-T-cells interaction. This 61 strategy could be related to the maintenance of infected animals as bacterial carriers.

Introduction

European pig herd is acknowledged as the second largest in the world, taking charge of the production of the most consumed meat in Europe [1].

Among the wide range of hazards transmitted to humans by the consumption of pork or pork products, Salmonella is considered a major health threat worldwide [2,3]. According to the European Food Safety Authority (EFSA), Salmonella is the most frequently reported cause of food-borne outbreaks in the European Union (EU) [4]. Besides, it is supposed that approximately 30% of the human salmonellosis cases are caused by Salmonella enterica serovar Typhimurium (herein, S. typhimurium) from pork or pork products [2]. In spite of extensive contributions exploring the murine salmonellosis, the pathogenesis of pig infections with broad host range serotypes of Salmonella was largely neglected until recently [5]. Pigs are typically asymptomatic carriers of S. typhimurium and this commensal-like state establishes a significant reservoir for Salmonella contamination of food during harvest and processing [6]. Although the persistence of Salmonella in gut-associated lymph nodes of infected pigs has been previously reported, the extraintestinal part of a S. typhimurium infection in swine is not well-documented [5]. A recent report demonstrated that the prevalence of Salmonella in the lymph nodes of slaughter pigs ranged from 0%to 39.6% in EU, being infected pigs the dominant route of transmission in countries with high Salmonella prevalence [4]. Therefore, a thorough knowledge of how S.

typhimurium interacts with the porcine lymphoid organs and consequently maintains itself in infected hosts consists in an essential step for the development of efficient control measures aiming to protect our food supply in the farm-fork process. Infection induces changes in mRNA and protein expression profiles of host cells. Basing on this, comparative proteome analyses are often used to generate more detailed understanding of molecular mechanisms behind diseases [7]. In fact, in vivo models combined with proteomic technological advances represent unprecedented means of characterizing host-pathogen interactions [8]. This approach enables a systematic identification and classification of host proteins involved in infection, providing new targets for disease prevention and treatment strategies [9]. For these reasons, in this study we employed a model of in vivo experimental infection followed by DIGE proteomics and bioinformatic data analysis to elucidate the molecular mechanisms undergone by swine porcine mesenteric lymph nodes (MLN) upon S. typhimurium infection.

Material and methods

In vivo Salmonella infection and tissue sampling

The experimental infection design was described elsewhere [10]. Briefly, sixteen weaned piglets of approximately four weeks of age and fecal-negative for Salmonella were randomly allocated to control (4 piglets) or infected groups (12 piglets). Control (0 day post-infection -dpi) pigs were necropsied 2 h before the experimental infection and those ones belonging to the infected groups were orally challenged with 108 cfu of S. typhimurium phagetype DT104. Afterwards, infected pigs were randomly sampled and necropsied at 1, 2 and 6 dpi (four animals at each time point). Finally, MLN from all experimental animals were collected after necropsies and immediately frozen in liquid nitrogen for protein isolation or fixed in 10% neutral buffered formalin for histological processing. All procedures involving animals were performed in accordance with the European regulations regarding the protection of animals used for experimental and other scientific purposes. Piglets were housed in experimental isolation facilities of the University of León (Spain). Animal care and procedures were in accordance with the guidelines of the Good Experimental Practices (GEP), under the supervision of the Ethical and Animal Welfare Committee of the University of León (Spain).

Protein extraction and labeling

Samples were homogenized on ice in a proportion of 1.5 mL of buffer per 100 mg of tissue using a glass tissue-lyser. Lysis buffer was composed of 7 M urea, 2 M thiourea, 4% w/v CHAPS, 0.5 mM PMSF and protease inhibitor cocktail (Roche, Basel, Switzerland). After sonication (3×20 s pulses on ice, with cooling intervals of 2 min in between) and centrifugation (14,000 g for 10 min, at 4 °C),

supernatants were precipitated with 2D-Clean-Up Kit (GE Healthcare, Buckinghamshire, UK) and resuspended in 100 μL of DIGE buffer (10mMTris, 7

Murea, 2 M thiourea, 2% w/v CHAPS). Subsequently, protein concentration was determined using Bradford Protein Assay (Bio-Rad, Hercules, CA, USA). CyDye labeling was performed following the manufacturer's instructions (GE Healthcare). Briefly, 50 μg of protein per sample was minimally labeled with 400 pmol of Cy3 or Cy5 fluorochromes (dissolved in 99.8% DMF) for 30min on ice in the dark. Then, reactions were quenched with lysine (10mM/50 μg of protein).

An internal standard, which was included in all DIGE gels, was prepared by pooling equal amounts of protein from each biological sample and labelling with Cy2 dye in the same conditions of separate samples.

DIGE

Sixteen individual samples were randomly distributed across eight DIGE gels. To produce unbiased results and minimize system variation, half of samples from each time point were labeled with Cy5 and the remaining ones with Cy3 (for details, see Supplementary data file 1). For each gel, the same amount of internal

Image acquisition and DIGE analysis

Proteins were visualized using a Typhoon 9400 scanner (GE Healthcare)

with CyDye filters. For the Cy3, Cy5 and Cy2 image acquisition, the 532 nm/580 nm, 633 nm/670 nm and 488 nm/520 nm excitation/emission wavelengths were used, respectively, and 100 μm as pixel size. Image cropping and filtering were carried out with Image Quant v.5.1 software (GE Healthcare). Analyses for detection of different abundance between spots from different replicates were performed with the DIA (differential in gel analysis) module of the DeCyder 6.5 package (GE Healthcare). Inter-gel variability was corrected by matching and normalization of the internal standard spot maps using the Biological Variance Analysis (BVA) module. The internal standard image gel with the greatest number of spots was used as a master gel. BVA module was also employed for comparative cross-gel statistical analyses, basing on spot normalized volume ratio (Cy3:Cy2 and Cy5:Cy2). Variation in abundance among all experimental conditions was accessed by One-way ANOVA. For paired comparisons, independent Student's t-test was carried out. Spots present in at least 85% of gels and exhibiting changes in abundancewith a p-value less than 0.05 were considered as differentially abundant spots.

Mass spectrometry and protein identification

Differentially abundant spots were excised from gels for subsequent ingel reduction, alkylation and digestion with trypsin [11]. Briefly, spots were MASCOT as significant with a p-value less than 0.05.

Systems biology analysis

Protein data sets were uploaded into ArrayUnlock (AU, Integromics, Granada, Spain) and Ingenuity Pathway Analysis (IPA, Ingenuity Systems, www.ingenuity.com) for bioinformatic analysis. The AU "Biological Enrichment" tool was used to find biological annotations associated to the list of differently abundant proteins. To this end, AU applies a statistical test based on the hypergeometric distribution to compute p-values and the false discovery ratio (FDR) of Benjamini and Hochberg to correct them. GO terms and KEGG pathways were chosen as annotations to be evaluated in the analysis (refer to AU manual for detailed information: http://www.integromics.com). Protein interaction networks were automatically generated, ranked by score and depicted on IPA as follows: each node in the network diagram represented a protein and its relationship with other molecules was represented by a line (solid and dotted lines represent direct and indirect association respectively). Nodes with a colored background were input proteins detected in this study while non-colored nodes were proteins inserted by IPA based upon the Ingenuity Knowledge Base to produce a highly connected network. Fisher's exact test was used to calculate a p-value determining the probability that each biological function assigned to the data set was due to change alone. Score estimated the probability that a collection of proteins equal to or greater than the number in a network could be achieved by chance alone. Scores of 3 or higher were considered to have a 99.9% confidence of not being generated by random chance alone. IPA Knowledge Base was used as a reference set for statistical analysis of enriched functions/pathways.

Western blot analysis

Equivalent amounts of total protein (30 μg) from control and infected animals were electrophoretically fractionated in 12% (w/v) SDS-PAGE gels and transferred onto a PVDF membrane (Millipore, Bedford, MA, USA). After blockage with 5% skimmed milk in TBS-T (10mMTris pH 7.4, 150mMNaCl, 0.05%Tween-20)

for 1 h at room temperature, membrane was incubated overnight at 4 °C with some of the following antibodies: antivimentin, clone V9 monoclonal antibody (Chemicon/Millipore, Billerica,MA, USA); rabbit polyclonal to FKBP52 (ab97306, Abcam, Cambridge, UK); anti-14-3-3 β (K-19) rabbit polyclonal antibody (Santa Cruz Biotechnologies, Santa Cruz, CA, USA) and anti-L plastin polyclonal antibody (kindly gifted by Dr. Francisco Rivero from University of Hull, UK). Secondary peroxidase-linked antirabbit or anti-mouse antibodies were used to generate immunocomplexes that were visualized with an enhanced chemiluminescence reagent (Chemiluminescent HRP substrate, Millipore). Membranes were scanned in a FLA-5100 imager (Fujifilm, Tokyo, Japan) and signal intensity was determined 78 using Multigauge software (Fujifilm, Tokyo, Japan). Student's t test was conducted between control and infected groups using SPSS 15.0 for Windows (SPSS Inc, Chicago, IL, USA). A p-value below 0.05 was considered statistically significant. To confirm equal sample loading, allmembranes were reblotted with anti-GAPDH monoclonal antibody (GenScript, Picastaway, NJ, USA).

Histological analysis

Paraffin sections (5 μm) of formalin fixed sampleswere routinely processed and stained with hematoxylin and eosin (H&E). For immunohistochemistry, heat-mediated antigen retrieval in 0.01M citric acid and labeling were performed as described elsewhere [12], employing the antivimentin monoclonal antibody (Chemicon/Millipore), a monoclonal antibody specific for porcine macrophages (clone 4E9/11) [13] and a rabbit antiserum against the somatic antigen of S. typhimurium.

Real-time quantitative PCR

Real-time quantitative PCR (qPCR) technology was used to determine the relative expression of the genes coding for CASP1, IL1β, CXCL2, CXCL8 and IFNγ.

RNA extractions, cDNA synthesis and qPCR assays were carried out according to Collado-Romero et al. [10]. Primer pairs used for amplifications can be found as supporting information (Supplementary data file 2). The relative gene expression was assessed by the 2 -ΔΔCq method [14] using cyclophilin-A and beta-actin as reference genes [15]. Afterwards, fold change values were standardized as proposed by Willems et al. [16]. Fold changes of 1 denoted no change in gene expression. Values lower than 1 and higher than 1 denoted down and upregulation respectively. Standardized data were analyzed by Kruskal-Wallis and Mann-Whitney tests using the software SPSS 15.0 for Windows (SPSS Inc).

Results

Experimental infection and histological analysis

Clinical signs characterized as fever, lethargy, weight loss and diarrhea were observed in infected pigs. Although symptoms peaked at 2 dpi, a clinical improvement of disease was noticed along the time of infection, since animals showed normal feces and corporal temperature at 6 dpi. Lymphadenitis marked by a strong infiltration of neutrophils and macrophages was observed in infected animals (Fig. 1A,B). Besides, immunohistochemistry assays confirmed the presence of S. typhimurium in MLN after infection. In the same way of the clinical profile observed, Salmonella was more evident at 2 dpi and poorly detected at 6 dpi (Fig. 1C-F). Labeling of S. typhimurium antigens was observed in the cytoplasm of mononuclear cells and neutrophils located mainly in the diffuse lymphatic tissue around trabeculae.

DIGE analysis and identification of differently abundant proteins

DIGE approach was employed to detect changes in the proteome of porcine MLN after oral infection with S. typhimurium. Differential in gel analysis uncovered 54 spots exhibiting significant abundance changes as a consequence of the bacterial challenge (Fig. 2A). Paired analyses between infected and control groups detected 16, 43 and 16 differently changed spots at 1, 2 and 6 dpi, respectively. Furthermore, a predominance of spots that were significantly more abundant in relation to controls was observed in all infected groups (Fig. 2B).

Among the screened spots, 48 could be identified and corresponded to 38 unique proteins (Table 1, see Additional information). In some cases multiple spots were identified as the same protein, thus indicating the occurrence of posttranslational modifications or different isoforms. proteins: VIM, plastin-2 (LCP1), 14-3-3 (YWHAZ) and peptidyl-prolyl cis-trans isomerase FKBP4 (FKBP4). All of them showed the same abundance trends revealed by differential in gel analysis (Fig. 3B-I). Additionally, we also checked changes in abundance of VIM by immunohistochemistry assays (Fig. 3A).

Consistent with DIGE, immunohistochemistry demonstrated that VIM was less abundant in infected animals when compared to controls. Besides difference in abundance, distribution of VIM in tissue was markedly different before and after infection. At 0 dpi, VIM was diffusely labeled in lymph nodes whereas at 2 dpi, staining was restricted to germinal centers and large irregularly-shaped mononuclear cells located near trabeculae.

Quantification of immune-related genes by qPCR

In order to confirm the regulation of host immune response mechanisms upon infection with S. typhimurium, qPCR expression profiling was performed for some genes encoding innate/ inflammatory and T cell response mediators. In general, screened genes showed a similar expression trend, which was marked by up-regulation at 2 dpi and decrease of mRNA levels or absence of significant changes at 6 dpi (Fig. 4).

Biological data interpretation

Bioinformatic tools were employed to biologically interpret protein list obtained from DIGE analysis, aiming to gain an insight into networks, biological processes, molecular functions and pathways associated with the proteome response of porcine MLN to S. typhimurium. Three interaction networks were generated by IPA data analysis (Table 2) and the nature of relationships displayed by the molecules integrated in each network was accessed based on the scientific information contained in the Ingenuity Knowledge Criteria. The major network depicted the existence of 83 direct and 39 indirect relationships which integrated 20 of the proteins differently altered after S. typhimurium infection (Fig. 5).

Furthermore, "Posttranslational modification", "Protein folding" and "Cellular assembly and organization" were identified as putative functions associated to the proteins included in this network. Network 1 also demonstrated the central role of the heat shock proteins in the proteome response of porcine MLN to S.

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Gene ontology (GO) annotations associated to differently abundant proteins were found out by the AU "Biological Enrichment" tool. "Cell motility" and "Antiapoptosis" were the top enriched biological processes identified (Supplementary data file 4). In addition, "Protein folding" and "Rho GDPdissociation inhibitor activity" were uncovered as the molecular functions more related to the differently abundant proteins (Supplementary data file 5). Pathway analysis was based on the Ingenuity Canonical Pathways Libraries and KEGG

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database. The top canonical and KEGG pathways significantly altered after the bacterial challenge are described in Table 3. Corroborating data from network analysis, heat shock proteins were observed to take part in different molecular routes. We also detected a similar tendency in DIGE analysis for differently abundant proteins associated to the "Antigen processing and presentation pathway" (Fig. 6A). Interestingly, all of them exhibited an increase of abundance at 2 dpi (Fig. 6B).

Discussion

Proteome approaches are being increasingly used in many different systems to investigate host-microbe interactions. In this context, in vivo models are crucial to reflect the multiple events undergone by host upon pathogen infection. Although the systemic pathology induced by S. typhimurium has been extensively studied using the mouse model [6], the complex molecular mechanisms underlying the intestinal infection caused by bacteria in foodproducing animals are still not fully understood [17]. To address this issue, in this work we employed for the first time an in vivo approach coupled to DIGE based proteomic analysis to detect changes in the porcine MLN proteome in response to S. typhimurium infection.

After bacteria challenge, the effectiveness of the experimental infection was confirmed by the observation of clinical signs of enteric disease in all infected animals. Distinct to mice, S. typhimurium generally causes little or no systemic involvement in pigs [17]. Nevertheless, in our in vivo model we observed in MLN the presence of the pathogen associated to the cytoplasm of infiltrated phagocytes, in concordance with previously reported evidences that, in mice, S.

typhimurium is shuttled to MLN by infected phagocytes [18,19]. Since major protein changes were detected at 2 dpi, coinciding with a higher presence of S.

typhimurium in infiltrated phagocytes, it could be inferred that proteome response of porcine MLN to the infection is strongly related to changes in tissue cellularity and pathogen burden. Consistent with this, we found that "Cell motility" was the most significantly enriched biological process after S.

typhimurium infection (see Supplementary data file 4).

In general, our results indicated a modulation of diverse normal host functions upon S. typhimurium infection. This can be related with the complex 95 interplay between Salmonella and its host that involves the coordinated stimulation and downregulation of cell functions by type III secretion systems 1 and 2 (T3SS1 and T3SS2) effectors for benefits of bacteria [20]. Firstly, bacterial internalization involves manipulation of the Rho family GTPases resulting in actin cytoskeleton rearrangements [21,22]. In our study, we observed that regulators of Rho protein signaling such as GDP dissociation inhibitors (GDI)ARHGDIA (Rho GDI-1) and ARHGDIB (Rho GDI-2) were less abundant after Salmonella infection.

Because GDI hinder the dissociation of guanosine diphosphate from Rho proteins,maintaining GTPases in an inactive form [23], our proteomic data suggest an increasing of GTPases activity in porcine infected MLN as a result of the repression of Rho GDI activity. Although T3SS effectors modulate host Rho

GTPases activity for the benefit of the bacteria, mechanisms of host immune response, such as phagocytosis and chemotaxis, are driven by extensive local reorganization of the actin cytoskeleton dependent on Rho GTPase activity.

Therefore, cytoskeletal changes undergone by MLN in response to infection reflect amix of outcomes induced by both Salmonella and host. Following actin polymerization by activation of the Rho GTPases, recovery of normal cellular architecture was observed once S. enterica has completely invaded target cells [24]. However, after bacterial uptake, Salmonella can initiate a second round of actin polymerization, resulting in formation of an F-actin coat around replicating intracellular bacteria [20]. In line with this, we observed changes in proteins involved in processes such as actin filament binding and bundle formation. Thus, PDLIM1, a kinase known for their critical role in regulating actin polymerization downstream of the Rho GTPase cascade [25], was more abundant at 1, 2 and 6 dpi. On the other hand, ACTB exhibited a decrease of abundance along the whole time course. According to Galan and Zhou [22] the Salmonella effector SipA binds to actin promoting a significant reduction in the concentration of its monomeric conformation. In addition, SipA increases the stability of actin bundles by 96 modulating plastin actin-bundling activity [26]. Interestingly, we observed that Lplastin was more abundant in the beginning of infection and this result could consist in another evidence of SipA activity in MLN. In the same way of ACTB, VIM, one of the constituents of cytoskeletal intermediate filaments (IF) network, exhibited a decrease of abundance after infection. Moreover, immunohistochemistry assays revealed that this protein was evidently accumulated in cells which morphology and localization in tissue were equivalent to Salmonella infected phagocytes. Protective IF cages similar to those composed by F-actin also coalesce around Salmonella-containing vacuoles [27]. Assembly of both proteins during Salmonella intracellular replication is reported to be interdependent and disruption of either leads to release of bacteria in the cytoplasm [28]. Moreover, annexin A1 (ANXA1), which was initially related to anti-inflammatory functions [29], appears to be involved in controlling association of F-actin with phagosomes thereby affecting phagosome formation.

ANXA1 binds to, bundles and colocalizes with F-actin during phagocytic cup formation and on mature phagosomes [30]. Intriguingly, this protein exhibited the most prominent increase of abundance in the porcine MLN after infection.

Thus, the uncovered reduction of monomeric forms of actin and vimentin as well as the augment of PDLIM1 and ANXA1 in MLN probably causes rearrangements in the cytoskeleton of infected cells that are necessary for phagosome formation and Salmonella replication. Triggering of GTPase activity in MLN was also disclosed by the abundance increase of GTP-binding nuclear protein Ran (RAN), found in this study. RAN is a major regulator of nucleocytoplasmic transport, controlling its rate and directionality by cycling between inactive (GDP-bound)

and active (GTP-bound) conformations [31]. Recent studies assert that RAN is noticeably upregulated in fish after viral or bacterial infection [32] and its activity is associated to the enhancement of phagocytosis [31]. Evidences inmammals demonstrate that RAN is also involved in LPS endotoxin response [33] and nuclear import of STAT3 [34]. The increase of RAN abundance observed in this study could consist in a GTPase response carried out by the host against S.

typhimurium. However, the role of this protein in Salmonella infections has not been elucidated so far.

In addition to cytoskeleton rearrangements, S. typhimurium infection induced cell death mechanisms, which in combination to the inflammatory cell infiltration observed in our study, could point toward the occurrence of pyroptosis in porcine MLN. Pyroptosis is a CASP1 dependent inflammatory form of cell death induced by Salmonella and other intracellular microorganisms that is characterized by the release of potent mediators of inflammation such as IL1b and IL18 [35]. Although our proteomic study did not allow for an observation of the changes in CASP1, we do see it at mRNA level at 2 dpi accompanied by a high increase of IL1b gene expression (Fig. 4). In agreement with that finding, functional analysis of the proteomic results disclosed an enrichment of the mitogenactivated protein kinase (MAPK) signaling pathway upon infection (Table 3), additionally verified bymRNA quantification of the downstream proinflammatory chemokines CXCL2 and CXCL8, which were both up-regulated at 2 dpi. These results represent a further indication of pyroptosis induction, since the production of pro-inflammatory cytokines is carried out via activation of MAPK and consequent regulation of the transcription factors NF-κB and AP1 [22,36].

Although pyroptosis represents an important innate immune effector mechanism against intracellular bacteria, Salmonella has developed strategies to overcome it [37,38]. Apparently, this pathogen voids pyroptosis effectiveness by delaying its onset and infecting new macrophages after escaping from lysed cells [35]. However, released bacteria should be able to survive to neutrophil uptake and killing by reactive oxygen species, in order to re-infect cells and maintain their replicative cycle in tissue [38]. Intriguingly, our results indicate that Salmonella burden in MLN was reduced along infection. This is probably related 98 to the strong infiltration of phagocytic cells observed at 2 dpi that could be causing the substantial decrease of S. typhimurium labeling in tissue at 6 dpi. In addition, we observed an enrichment of the anti-apoptosis process after infection. Although the role of each protein associated to this mechanism is unknown for us, we speculate that apoptosis is avoided by swine, hampering cellto-cell spread of bacteria through subsequent rounds of macrophage infection.

Therefore, our results could demonstrate that in spite of manipulating host machinery, S. typhimurium is not able to effectively evade the porcine MLN response. Nevertheless, the presence of live S. typhimurium in tissue at 6 dpi (datanot shown) reinforces the hypothesis that this pathogen develops some mechanism to maintain itself in MLN at low levels. Further research will be necessary to bring significant insight into how and how long S. typhimurium persists in porcine MLN after infection.

Changes in proteins related to the modulation of host second line of defense were also identified after infection. Thus, we uncovered an increase in abundance of proteins involved in different steps of the antigen processing and presenting pathway (Table 3). Strikingly, these proteins exhibited similar quantitative changes, being all of them more abundant at 2 dpi, when S.

typhimurium and proteome changes were more evident. Additionally, activation of T-cells was also deduced by the increase in mRNA levels of IFNγ (see Fig. 4), a cytokine that promotes Th1 differentiation leading to cellular immunity.

Therefore, our data suggest that the process of antigen presentation properly functions in porcine MLN after S. typhimurium infection.

It is known that antigenic peptides presented by MHC-I are produced through cytosolic degradation of intracellular proteins by proteasome [39].

Otherwise, presentation of exogenous antigens has been classically attributed to MHC class II [40]. Additionally, the term cross-presentation was introduced as an alternative mechanism to define a process in which antigens acquired from the 99 extracellular environment are present by antigen-presenting cells (APCs) to CD8+

T cells via their own MHC-I molecules [41]. Interestingly, this mechanism could explain the clear indications of adaptive immunity induction via MHC-I which is derived from the proteomic results obtained in our work. Since Salmonella is confined in host cell inside phagosomes, its antigens theoretically would be protected from cytosolic degradation by proteasome, unless the phagosome is a competent organelle for antigen cross-presentation as has been previously stated by Houde et al. [42]. In this alternative scenario, phagocytosed proteins reach cytosol by chaperone retrotranslocation mechanisms, subsequently degradated by proteasomes located in the cytoplasmic side of phagosomes and then, the BRp57/PDIA) [43] were detected at higher levels in infected samples. Also, the proteasome subunit beta type-8 (PSMB8 or LMP7) was also found to be more abundant in MLN after infection. The hydrolyzing activities of proteasomes are conferred upon stimulation of cells with IFNγ [39]. This process results in the replacement of its 20S core subunits by LMP2 (iβ1), MECL1 (iβ2) and LMP7 (iβ5), constituting the so-called immunoproteasome [42]. In line with the direct activation/inhibition relationship between IFNγ and PSMB8 depicted in network 3

(see Supplementary data file 3) and the previously referred reports [39,41], we found out that the highest levels of PSMB8 in tissue is coinciding with the increase of IFNγ mRNA at 2 dpi. Since proteasomal activity is dependent on the ubiquitination of its targets [41], the significant enrichment of the "Protein ubiquitination pathway" uncovered by IPA analysis gives an additional evidence

Introduction

Infections by Salmonella are a major health problem in the developing and developed world. In the European Union, despite the current decreasing trend of human cases, Salmonella persists as the main cause of food-borne outbreaks [1]. Pork is considered to be a significant source of Salmonella to humans next to eggs and poultry meat [2]. In fact, according to the European food safety authority (EFSA), Salmonella enterica serovar Typhimurium (herein Salmonella Typhimurium) is the second serovar most frequently reported in human salmonellosis and infection by this pathogen is mostly associated with the consumption of contaminated pork [1].

Since food industry and direct contact with infected animals represent the main sources of non-typhoid Salmonella [3], prevention of human disease depends significantly on controlling infection in livestock hosts [4]. Salmonella

Typhimurium infected pigs generally carry this serotype asymptomatically in the tonsils, intestines and gut-associated lymphoid tissue, posing an important threat to animal and human health [5]. Epidemiological studies assert that Salmonella prevalence in slaughter swine lymph nodes varies widely at country level, ranging from 0 to 29% [2]. Although salmonellosis in pigs has been subject of research [5],

a thorough knowledge of the pathogenesis of porcine infections with broadhost range Salmonella serotypes is still necessary and a better understanding of the biological processes that control host-pathogen interaction and Salmonella persistence in porcine lymphatic tissue could provide new targets for treatment and control of salmonellosis in this species.

Combination of system-wide approaches and in vivo infection models is expected to generate precise and novel data to the study of porcine salmonellosis [6]. In fact, whole-genome expression analysis has been used to 110 identify genes and molecular pathways involved in the pig response to Salmonella infections [7,8]. More recently, proteomic techniques were employed by us as a step towards a detailed understanding of the disease mechanisms [9,10]. Thus, the objective of the current study was to expand the available knowledge by investigating the early processes carried out in the mesenteric lymph-nodes (MLN) of pigs experimentally infected with Salmonella Typhimurium. To achieve that, host response was monitored by several approaches including microarray gene expression, bioinformatic data enrichment, western blot, quantitative real-time PCR, immunohistochemistry and confocal microscopy analysis. In addition, selective capture of transcribed sequences (SCOTS) technique [11] was performed to analyze the in vivo expression of some Salmonella Typhimurium genes in order to investigate important pathogenesis determinants on the pathogen side.

Materials and methods

Experimental infection and tissue sampling

Sixteen crossbred weaned piglets of approximately four weeks of age, serologically and fecal-negative for Salmonella were used in an experimental infection described elsewhere [12]. Briefly, twelve piglets were orally infected with 10 8 cfu of a Salmonella Typhimurium phagetype DT104 strain isolated from a naturally infected pig [12], whereas control group (4 animals) received sterile medium. Non-infected control pigs were necropsied prior to the experimental infection (0 day post-infection -dpi) and four randomly chosen infected piglets were necropsied at 1, 2 or 6 dpi. Samples of MLN were collected from all experimental animals and immediately frozen in liquid nitrogen for RNA and protein isolation or fixed in 10% neutral buffered formalin for histological 112 cRNA targets were then cleaned up, fragmented, and hybridized with the GeneChip Porcine Genome Array following Affymetrix recommended protocols.

Chips were washed, stained with a GeneChip Fluidics Station 450 (Affymetrix) using the standard fluidics protocol and scanned with an Affymetrix GeneChip Scanner 3000 (Affymetrix). Probe signal intensities were captured and processed with the GeneChip Operating Software 1.4.0.036 (Affymetrix) and the resulting CEL files were reprocessed using robust multi-array average normalization (RMA) [13]. Because the aim of analysis was to detect changes in gene expression along the time-course, differentially expressed (DE) genes were accessed by the BATS (Bayesian Analysis of Time Series) software package [14], using default settings.

Bayes Factor (BF) value of 0.05 was used as cutoff to rank significantly regulated transcripts. Since the Affymetrix Porcine GeneChip is not fully annotated in all the features, it was re-annotated with Blast2GO [15] with a minimum E-value of 10 -10 and a minimum similarity of 50%.

Systems biology analysis

The list of genes that showed significant changes in expression was uploaded into Ingenuity Pathway Analysis (IPA, Ingenuity Systems, www.ingenuity.com) for bioinformatic analysis. Additionally, DAVID Bioinformatic Database [16] was used applying the default settings to refine some data from IPA analysis. Gene interaction networks were automatically generated, ranked by score and depicted on IPA as follows: each node in the network diagram represented a gene and its relationship with other molecules was represented by a line (solid and dotted lines represent direct and indirect association respectively). Nodes with a red background were input genes detected in this study while grey nodes were molecules inserted by IPA based upon the Ingenuity Knowledge Base to produce a highly connected network. Score estimated the probability that a collection of genes equal to or greater than the number in a network could be achieved by chance alone. Scores of 3 or higher were considered to have a 99.9% confidence of not being generated by random chance alone. For statistical analysis of enriched functions/pathways, IPA Knowledge

Base was used as a reference set and Fisher's exact test was employed to estimate the significance of association. P-values bellow 0.05 were considered statistically significant. For canonical pathways graphical representation, ratio indicated the percentage of genes taking part in a pathway that could be found in uploaded data set and -log(p-value) meant the level of confidence of association.

Threshold line represented a p-value of 0.05.

Relative gene expression analysis by qPCR

Real-time quantitative PCR (qPCR) assays were performed as previously described [12]. Fold change values were calculated by the 2 -ΔΔCq method [17] using beta-actin as reference gene. Afterwards, data were standardized as proposed by Willems et al. [18] and analyzed by Kruskal-Wallis and Mann-Whitney tests using the software SPSS 15.0 for Windows (SPSS Inc, Chicago, IL, USA). Fold changes of 1 denoted no change in gene expression. Values lower and higher than 1 denoted down and up-regulation respectively. To be represented in Table 1, fold change of down-regulated genes was calculated as -1/2 -ΔΔCq . Primer pairs used for amplifications can be found as supporting information [see Additional File 1].

Western blot analysis

For protein extractions, MLN samples from all experimental animals were separately homogenized on ice with lysis buffer (7 M urea, 2 M thiourea, 4% w/v CHAPS, 0.5 mM PMSF) using a glass tissue-lyser and protein lysate concentration was determined using Bradford Protein Assay (Bio-Rad). Subsequently, protein from individual replicates belonging to the same group was pooled (30 ug total), electrophoretically fractionated in 12% (w/v) SDS-PAGE gels and transferred onto a PVDF membrane (Millipore, Bedford, MA, USA). Western blot assays were carried out as described by Martins et al. [10] employing the following primary antibodies: 4B7/8 (anti-SLAI) [19], 1F12 (anti-SLAII) [19], anti-CTLA4 (Epitomics,Burlingame, CA, USA) and anti-Clathrin light chain (ab24579, Abcam, Cambridge, UK). To confirm equal sample loading, membranes were reblotted with anti-GAPDH monoclonal antibody (GenScript, Picastaway, NJ, USA) and no statistical differences for GAPDH abundance were observed between groups in all assays. Membranes were scanned in a FLA-5100 imager (Fujifilm, Tokyo, Japan)

and signal intensity was determined using Multigauge software (Fujifilm, Tokyo,Japan) as previously described [10].

Histopathology, immunohistochemistry and confocal microscopy analysis

Paraffin sections (5 μm) of formalin fixed samples were routinely processed and stained with hematoxylin and eosin (H&E) to evaluate tissue morphology. For immunohistochemistry assays, a standard avidin-biotin peroxidase method was performed as described elsewhere [20] employing 1F12 monoclonal antibody for swine histocompatibility class II antigen detection and a biotinylated anti-mouse Ig (Dako, Barcelona, Spain) as secondary antibody.

Immunofluorescence using confocal microscopy was performed employing the mouse anti-SLAII 1F12 antibody, rabbit anti-Salmonella somatic antigen [10] and rabbit anti-Salmonella Typhimurium flagellin [21]. Fluorescein isothiocyanate

Results

Overview of gene expression in porcine MLN upon Salmonella

Typhimurium infection

Microarray technology coupled to a Bayesian analysis was employed to explore the transcriptional response of porcine MLN to Salmonella Typhimurium at 1, 2 and 6 dpi. BATS method was specifically designed for the analysis of time series microarray data [10]. For this reason, this strategy was established aiming to provide a general panorama of changes undergone by tissue at the mRNA level

Validation of microarray data by qPCR

To validate microarray data, qPCR assays were performed on a panel of fourteen genes identified by BATS analysis. As expected, all of them were confirmed to be significantly regulated (p<0.05) after infection (Table 1).

Furthermore, an identical expression trend along time was observed for most of the screened genes by qPCR and microarray analysis.

Biological interpretation of microarray data

To translate microarray data into functional biological information, IPA analysis generated 17 gene interaction networks integrated by molecules associated to mechanisms that play a relevant role in infectious processes, such as cell-mediated immune response, cell-to-cell signalling and interaction, tissue morphology, cell movement and cell death. Significantly, networks 1 and 4 (Figure 1) revealed direct relationships between molecules taking part in five of the ten top enriched canonical pathways after infection (Figure 2). Moreover, network 4 demonstrated the central role of heat shock proteins and MHC encoding genes in the establishment of different mechanisms carried out in MLN in response to Salmonella Typhimurium.

1.0 -1.1 -1.2 0.00023747 -1.4 -1.4 -1.9 0.047 HLA-DRB5 b 1.0 -1.1 1.0 0.0000311 -1.4 -1.6 -2 0.036 HSPA1B a 3.3 1.4 -1.1 0.0001166 2.5 1.4 -1.3 0.025 HSPH1 2.3 1.7 -1.0 0.00000424 1.5 1.1 -2 0.003 IL16 -1.0 -1.2 -1.1 8.

Network 1 Network 4

Network 1 120

IPA also ascertained the enrichment of biological functions other than those identified by network analysis (Table 2). Thus, "Inflammatory disease" was the Ingenuity biofunction more significantly related to the differently expressed genes, followed by "Protein synthesis" and "Antigen presentation". Thus, "Inflammatory disease" was the Ingenuity biofunction more significantly related to the differently expressed genes, followed by "Protein synthesis" and "Antigen presentation".

Modulation of immune response mechanisms

Wide transcriptomic data analysis by bioinformatics tools revealed an enrichment of distinct mechanisms involved in the triggering of immune response in porcine MLN upon Salmonella Typhimurium infection. Furthermore, network analysis demonstrated a possible connection between them and regulation of common genes (Figure 1). To explain in depth the significance of these results, a series of assays including western blot, qPCR, immunohistochemistry and confocal analysis was performed.

As illustrated in Figure 3A, the association between pathways "CTLA-4 signaling in cytotoxic T lymphocytes" and "Clathrin-mediated endocytosis signaling" was confirmed by the regulation of shared genes. Thus, we checked by western blot the abundance along time of cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and clathrin light chain A (CLTA), the key molecules in each pathway. An opposite trend was observed for these proteins, since CLTA was more abundant in infected animals whereas CTLA4 showed reduced levels after infection (Figure 3B). Since changes in CTLA4 expression could not be detected by microarray analysis, we verified CTLA4 mRNA levels by qPCR (Figure 3C). In accordance with western blot assays, CTLA4 was observed to be significantly System biology analysis accomplished in this study also revealed the involvement of MHC encoding genes in many mechanisms triggered in MLN in response to Salmonella Typhimurium. For this reason, changes undergone by these molecules were evaluated employing different approaches. As shown in Figure 4A, western blot analysis demonstrated that major histocompatibility antigens class I (MHCI) and class II (MHCII) were more abundant in tissue at 1 dpi.

Similarly, immunohistochemistry revealed a higher expression of MHCII at initial stages of infection, being labeling mainly detected in large irregularly-shaped mononuclear cells (Figure 4B-E). Interestingly, Salmonella location in MLN was previously observed by us in the cytoplasm of mononuclear phagocytes and neutrophils [10,21]. So, confocal microscopic analysis was subsequently carried out to address the hypothesis that the increase of MHCII positive cells and the presence of Salmonella Typhimurium in tissue could be closely related events. As depicted in Figure 4H-K, Salmonella Typhimurium was detected in the cytoplasm of MHCII positive cells, morphologically identical to those identified by immunohistochemistry. Curiously, MHCI and MHCII (annotated in data sets as HLA-B and HLA-DRB, respectively) mRNA expression were found to be downregulated by microarray analysis. Furthermore, as exposed in Table 1 and Figure 4F-G, similar results were uncovered by qPCR, confirming a divergence between transcriptomic and proteomic data obtained in MLN for these receptors.

Tissue morphology and cell death

"Cell death" was one of the most significantly altered biological functions after infection and integrated the highest number of differently expressed genes 124 (n=78). In order to find GO subcategories associated to genes implicated in this function, data set arranged into "Cell death" by IPA was loaded in DAVID Bioinformatic Database. As expected, enriched terms were related to cell proliferation, differentiation and death [see Additional file 5]. Among them, "Negative regulation of apoptosis" and "Antiapoptosis" could be highlighted CASP1 mRNA was significantly up-regulated at 2 dpi and down-regulated at 6 dpi (Figure 5J), whereas no significant changes were observed for CASP3 (Figure 5K).

Finally, lymph-node sections were additionally H&E-stained to analyse the structural changes undergone by tissue as a consequence of infection (Figure 5E-H). Besides the loss of the typical lymph-node micro-architecture, phagocytes infiltration was the main tissue alteration revealed after infection, being observed mainly at 1 and 2 dpi.

Salmonella Typhimurium localization and gene expression in vivo

Confocal microscopy analysis was performed to localize Salmonella Typhimurium in tissue. Although bacteria were detected in MLN along the whole time course, higher Salmonella labelling was observed at 2 dpi (data not shown), agreeing with our previous observations [10,21]. Pathogen was labelled as spherical structures located in the perinuclear zone of mononuclear cells (Figure 6A) as observed for bacteria confirmed to be localized in MHCII positive cells (Figure 4H-K). Conversely, in some cases, staining of regular bacilli shaped structures was uncovered (Figure 6B) and z-stack images suggested that

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hypothesis. Ultimately, expression of some Salmonella genes in vivo was also studied by SCOTS approach and compared to in vitro condition. Type III secretion systems (TTSS) encoded genes (sopB, avrA, sifA, sseL and prgJ) and spvB were found to be expressed by Salmonella Typhimurium in porcine MLN. Notably, comparing to in vivo condition, lower expression of these genes was detected in early log growth phase cultures. Similarly, higher levels of sifA, spvB and sseL mRNA expression were found in MLN when compared to late log growth phase culture. Results regarding genes coding for flagella components and regulators showed higher expression levels in vitro for fliA, fliC whereas fljA mRNA was observed more expressed in vivo (Figure 6C).

Discussion

Gut-associated lymphoid tissues have been proved to be an important niche for Salmonella Typhimurium during pig infections [5]. For this reason, in this work we aimed to dissect host response mechanisms occurring in the porcine MLN upon interaction with Salmonella Typhimurium. Besides, attempting to integrate information from both parties involved in disease, expression in tissue of some Salmonella genes was also studied after pig oral inoculation. It is known that Salmonella pathogenicity island 1 and 2 (SPI-1 and SPI-2) TTSS genes are required for intestinal and systemic infection respectively [25,26]. Here, we found that both SPI-1 (sopB and avrA) and SPI-2 (sifA and sseL) encoded virulence factors were expressed in infected tissue, suggesting that invasion and intracellular survival inducers were employed by Salmonella to adapt itself to MLN milieu and cause infection.

Furthermore, system biology analysis reported in this study uncovered the enrichment of different endocytosis pathways, according to accumulating observations that Salmonella interacts extensively with host endocytic pathways [27]. Thus, "Macropinocytosis pathway" was found by us to be implicated in the response of MLN to infection, in agreement with available knowledge that Salmonella TTSS effectors promote massive actin polymerization and lead to bacterial internalization by macropinocytic membrane extensions [28]. In addition, "Clathrin-mediated endocytosis signalling" was identified as the second most significantly affected canonical pathway upon infection. Although studies have demonstrated that clathrin-mediated endocytosis is used in bacterialinduced internalization, Salmonella is not able to employ this machinery to invade [29]. Therefore, we speculated that the enrichment of this process, added to the disclosed mediation of the "Protein ubiquitination pathway" after infection, is related to preceding evidences that Salmonella employ its SPI encoded effector SifA to remove mature MHCII complexes from cell surface, by enhancing their ubiquitination, in a clathrin and AP2-dependent way [30,31,32].

We observed that the Salmonella Typhimurium strain used in this work was able to express sifA in porcine MLN, suggesting that this evasion strategy could be triggered by pathogen to circumvent host response. Salmonella is expected to induce a strong immune response through specific antigen presentation to CD4 restricted T cells in the context of MHCII antigens [33].

Nevertheless, by reducing MHCII levels in antigen presenting cells, this pathogen may limit the induction of host T helper 1 (Th1) response. In line with this, it was previously observed by us [21] and others [34] that pig infections with Salmonella Typhimurium do not produce an up-regulation of Th1 response inducers in MLN.

The disclosed involvement of MHC molecules in several enriched mechanisms highlighted the central role of these receptors in the pig response to Salmonella. Curiously, both MHCI and MHCII encoding genes were observed to be down-regulated in porcine MLN after infection, although results from western blot and microscopy analysis revealed a significant increase in the abundance of these receptors at initial stages of infection. We envisage that these finds could 130 be attributed to infected antigen presenting cells that, upon contact with bacteria in intestine, express high levels of MHC and migrate to MLN. As depicted here and previously [10,21], infection results in substantial changes in tissue cellularity, marked mainly by infiltration of phagocytes. Additionally, we were able to detect Salmonella Typhimurium in the cytoplasm of cells showing high levels of MHCII and the enrichment of "Dendritic Cell maturation" pathway as a consequence of the bacterial challenge. Our inference could be further supported by previous studies that report shuttle of Salmonella Typhimurium from intestine to mesenteric lymph-nodes by infected antigen presenting cells [5,35].

In spite of the sophisticated strategies evolved by Salmonella Typhimurium to modulate host defence, our data indicated that the induction of some components of porcine adaptive immunity appears not to be repressed in infected MLN. Network analysis also associated "Clathrin-mediated endocytosis signaling" to "CTLA4 signaling in cytotoxic T lymphocytes pathway", bringing to light the role of the former process in adaptive immunity triggering. CTLA-4, an important negative regulator of the T cell immune response [36], is endocytosed via a clathrin and dynamin-dependent route in activated T-cells [37]. According to Johanns et al. [38], up-regulation of CTLA-4 in regulatory T cells restrains effector T cell activation at early infection time points and allows the increase of bacterial burden during murine salmonellosis. Similarly, Inoue et al. [36] High MHCI levels observed by western blot reinforce our previous evidences that Salmonella antigens are cross-presented in swine MLN [10],

bringing out the induction of other adaptive immunity process upon infection.

Cross-presentation results in CD8+ T cells priming by antigen presenting cells via their own MHCI molecules [33]. Interestingly, it has been reported that Salmonella is not able to reduce MHCI surface expression of infected cells and consequently avoid host early cytotoxic response [30,31,32]. Therefore, crosspresentation might contribute to Salmonella Typhimurium clearance in porcine MLN, in agreement with the stimulation of Salmonella-specific CD8 T cells readily observed in mice and human infections [40]. In addition, an evidence of humoral response induction was also uncovered by us. CD180, an inducer of B cells proliferation, activation and differentiation [41], was up-regulated all along infection. So, besides cellular immunity, humoral response seems to be promptly carried out in porcine MLN after Salmonella Typhimurium infection.

Among several layers of immune defence developed by mammals, cell death is a key component of host response aginst infection. Elimination of an infected cell can be beneficial or detrimental to both host and pathogen. Thus, each party utilizes a number of strategies to regulate the outcome of this process in its favour [42]. In a previous study, we suggested that apoptosis is avoided and infected cell undergoes pyroptosis in MLN of Salmonella Typhimurium infected swine [10]. Cells dying by pyroptosis have biochemical and morphological features of both apoptotic and necrotic cells [43]. As in apoptosis, pyroptotic cells show DNA fragmentation, nuclear condensation and positive TUNEL staining [42].

However, pyroptosis inherently results in inflammation due to caspase-1mediated maturation of pro-IL-1β and pro-IL-18 and release of the cytoplasmic content, whereas apoptotic cell is considered to be immunologically silent [44].

Evidences of pyroptosis induction and apoptosis dampening in infected

MLN were disclosed in the current study, supporting our previous reports [10,21]. Besides the increase of TUNEL positive labelling at 1 dpi and infiltration of inflammatory cells observed in tissue, microarray data mining detected an enrichment of processes such as "Negative regulation of apoptosis" and "Antiapoptosis" after the bacterial challenge, in addition to up-regulation of genes encoding for inhibitor of apoptosis proteins (IAP) like XIAP and PDCL3.

Induction of apoptosis has been asserted as a strategy that facilitates Salmonella cell-to-cell spread during systemic infection [45]. Nevertheless, it has also been reported that AvrA, a Salmonella effector protein, prevents the apoptotic elimination of host cell niche as a pathogen evasion mechanism [46]. Intriguingly, we observed in vivo expression of SpvB and SseL, both major Salmonella Typhimurium apoptosis inducers, and the apoptosis inhibitor AvrA, indicating that Salmonella appeared to execute virulence mechanisms to modulate apoptosis in porcine MLN in its favour. However, the balance of pathogen and host processes apparently avoided apoptosis induction and resulted in infected cell death by pyroptosis, producing pathogen discharge to the extracellular milieu and clearance of bacteria by innate mechanisms. In consequence of this response, swine MLN might be able to act as a barrier to dissemination of infection, as suggested by the notable reduction of pathogen burden in tissue previously reported by us [21].

Concordant with this, an elegant study by Miao et al. [47] stated that Salmonella Typhimurium is able to damper pyroptosis for its own advantage by avoiding flagellin expression during infection of mice. Interestingly, we found out expression of Salmonella Typhimurium flagella component (FliC) and regulators (FliA and FljA) in infected MLN. Additionally, flagella expression by infecting bacteria found in tissue was also corroborated by labelling using a specific polyclonal antibody. S. enterica alternately expresses two different flagellar filament proteins, FljB and FliC, in a process known as flagellar phase variation. In spite of the high homology level found between these proteins, their middle surface exposed sequence of amino acids are divergent, resulting in distinct antigenicities [48]. Of note, our results demonstrated higher expression levels for fliC and its regulator fliA in vitro than in vivo. On the other hand, fljA, which is cotranscribed with fljB, was more expressed in Salmonella Typhimurium found in vivo. Moreover, this gene was notably less expressed than fliA and fliC in both early and late logarithmic phase cultures. Basing on this, we deduced a skewing toward FliC flagellin expression by bacteria in vitro. Besides, we drew the inference that a more heterogeneous flagellin expression is found in Salmonella Typhimurium replicating in vivo and that induction of flagellar phase variation could be a strategy adopted by this pathogen to hinder pig immune response.

Expression of prgJ was also uncovered in swine MLN. Curiously, repression of this efector has been reported as a mechanism of pyroptosis inhibition in vivo [49].

Thus, it could be inferred that absence of flagellin and prgJ repression by Salmonella Typhimurium found in tissue might enable pig to use pyroptosis to clear bacteria in gut associated lymph-nodes, protecting itself from pathogen dissemination.

Nevertheless, an issue that should be addressed by our assumption is why pathogen burden in tissue peaks after pyroptosis triggering. Miao and Rajan [49] state that in a single cell, pyroptosis only takes place at late times of infection, following bacteria replication. So, we speculated that increase of pathogen load at 2 dpi is resultant of release of replicated Salmonella from cells dead by pyroptosis. This could justify the detection of bacteria by confocal microscopy that, differently from structures labelled inside MHCII positive cells, showed a regular rod shape and appeared to be out of host cells. Extracellular localization of pathogen could be further supported by a previous report [50],

which asserts that Salmonella Typhimurium predominantly survives in an extracellular niche in the tonsils of infected pigs.

Notably, the presence of TUNEL positive cells in tissue was significantly reduced at 2 and 6 dpi, suggesting a decrease of cell death by apoptosis or pyroptosis. As with any physiological process, excessive pyroptosis is detrimental to host [42]. So, modulation of this pathway by host aiming to restore tissue integrity should be expected. Actually, we observed up-regulation of MAP3K7

and TRAF7, both involved in NF-kB and survival pathways activation, at 2 and 6 dpi. However, evidences indicate that inhibition of caspase-dependent apoptosis primes cells towards programmed necrosis [51]. Since mechanisms that dictate the cellular decision to survive by activating NF-kB or to die through apoptosis or necroptosis are still unclear [52], further research is necessary to clarify these results.

In conclusion, provided results led us to infer that although the Salmonella Typhimurium strain employed in this study was able to express some of its major virulence effectors in porcine MLN, a combination of host triggered innate immunity mechanisms and an early T-cell cytotoxic response might overcome virulence strategies employed by pathogen. Besides preventing apoptosis, swine appears to take advantage of flagellin and prgJ expression by pathogen to induce pyroptosis in MLN. In this context, pyroptosis might consist in a host protective mechanism that prevents pathogen spread beyond gutassociated lymph-nodes. Furthermore, clathrin-mediated endocytosis appears to take part in the pathogenesis of infection. Nevertheless, role of this process in host and pathogen mediated processes remains to be clarified.

Introduction

Despite the current improvement in sanitation and hygiene, Salmonella

persists

Bioinformatic data analysis

Ingenuity Pathway Analysis (IPA, Ingenuity Systems, www.ingenuity.com) Downstream Effects tool was used to identify functions that are expected to be activated in tissue, given the observed gene expression patterns. Predictions were made by z-score algorithm and values higher and lower than 2 meant that activation state was statistically increased and decreased respectively. IPA Path

148

Designer was also employed to illustrate some mechanisms modulated by genes evaluated in this study.

Immunohistochemistry

To verify the presence of S. typhimurium in PP, paraffin sections (5 μm) of formalin fixed samples were routinely processed and immunostained as described elsewhere (Martins et al., 2013), employing a specific anti-Salmonella rabbit antiserum.

Results and discussion

Ileal loops models have provided valuable information regarding the other immune-related molecules (Table 1). Proinflammatory genes such as IL1b, CXCL2 and TNFa were found to be upregulated as a consequence of infection.

This response could be associated to recognition of invading Salmonella via PRR by macrophages and dendritic cells in PP, resulting in pathogen phagocytosis, secretion of chemokines and recruitment of additional inflammatory cells into the site of invasion (Broz et al., 2012). In line with this, a strong up-regulation was uncovered for all screened PRR (TLR2, 4, 5, 8 and NOD2) and pathogen labeling was mainly observed in the cytoplasm of large irregular-shaped mononuclear cells and some polymorphonuclear cells (Fig. 1F). Inflammation induced by IL1 has been considered a key mechanism in Salmonella pathogenesis at mucosa level (Raupach et al., 2006). However, a previous report employing porcine gut loops did not detect up-regulation of IL1β and chemokines encoding genes in PP upon S. typhimurium infection (Meurens et al., 2009). Although we believe that this discrepancy could be attributed to differences between approaches, PP areas not analyzed by us, such as dome and interfollicular zones, might affect the response of these organs to infection. Thus, this fact could also justify the observed differences between current study and others on the whole PP.

In general, results indicated that similarly to the murine typhoid model

152

The same was observed for molecules required for T-cell mediated processes (IFNγ, CD40L, CD28, CCL19 and IL21). Of note, high mRNA levels were observed for IFNγ and IL12p40, despite the absence of IL18 up-regulation.

Although this interleukin act synergistically with IL12 in the induction of IFNγ production and cell-mediated immunity, a previous study demonstrated that IL-18 is relevant for resistance to the systemic infection but not during the intestinal phase of salmonellosis (Raupach et al., 2006). Concurrently, down-regulation or absence of expression was uncovered for Th2 (IL4 and IL13) and Th17 (IL17A) inducers, suggesting a trend to Th1 orientation in S. typhimurium infected PP (Fig. 1G). In accordance with these observations

Materials and methods

Experimental infection and tissue sampling

Eight crossbred weaned piglets of approximately four weeks of age and confirmed to be fecal-negative for Salmonella were randomly allocated to control or infected groups (four animals each). Control (0 day post-infection -dpi) pigs were necropsied 2 h before the experimental infection, whereas infected group was orally challenged with 10 E-value of 10 -10 and a minimum similarity of 50%.

Systems biology analysis

For bioinformatic analysis of microarray data, the list of genes found to be significantly regulated after infection was uploaded into Ingenuity Pathway Analysis (IPA, Ingenuity Systems, www.ingenuity.com). Gene interaction networks were automatically generated, ranked by score and depicted on IPA.

Score estimated the probability that a collection of genes equal to or greater than the number in a network could be achieved by chance alone and values of 3 or higher were considered to have a 99.9% confidence of not being generated by random chance alone. For statistical analysis of enriched functions/pathways, IPA Knowledge Base was used as a reference set and Fisher's exact test was employed to estimate the significance of association. P-values bellow 0.05 were considered statistically significant. The Activation z-score was employed to predict the activation state of enriched functions and upstream regulators.

Predictions with z-score values higher or lower than 2 and a p-value ≤0.05 denoted a statistically increased or decreased activation state respectively. In pathways and networks diagrams, nodes represented a gene and its relationship with other molecules was represented by a line (solid and dashed lines represented direct and indirect associations respectively). Nodes with a red or green background were input genes found to be up or down-regulated respectively. Grey and white nodes were molecules inserted by IPA basing on the Ingenuity Knowledge Base to produce diagrams. Grey highlighted molecules without significant changes and white indicated genes not included in the analysis. In the canonical pathways bar graph, ratio indicated the percentage of genes taking part in a pathway that could be found in the uploaded data set and -log(p-value) meant the level of confidence of association. Threshold line represented a p-value of 0.05.

Real-time quantitative PCR (qPCR)

RNA from infected and control samples was reverse transcribed to cDNA using the qScript cDNA Synthesis kit (Quanta BioSciences, Gaithersburg, MD, USA) and real-time quantitative PCR (qPCR) assays were performed to access gene relative expression by the 2

Results

Genes are mostly up-regulated in Peyer patches follicles after S.

Typhimurium infection

Microarray technology coupled to Rank Products analysis [START_REF] Breitling | Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments[END_REF]) was employed to explore the transcriptional response carried out in PP Typhimurium infected PP follicles (Table 2). Besides, terms related to activation of lymphocytes, and especially T-lymphocytes, were uncovered to show the highest activation z-score values [see Supplementary File 3]. Thus, we carried out a series of assays to validate the predictions accessed by the bioinformatic engine. Firstly, hematoxylin-eosin staining disclosed a notably increase of phagocytes, mainly neutrophils, in PP upon infection (Figure 1C andD). This find could be further related to the presence of pathogen in tissue, being S.

Typhimurium antigens detected mostly in the cytoplasm of polymorphonuclear cells (Figure 1E and F) found in areas of PP follicles where an accumulation of neutrophils was observed. Lastly, we checked the induction of lymphocytes activation in follicles by western blot assays, which uncovered higher levels of CD5 in infected samples (Figure 1G). IFNγ up-regulation mostly lead to the activation of connected genes (Figure 3A).

Interestingly, functional analysis of only IFNγ-target molecules revealed an enrichment of biological processes including migration of phagocytes and antigen presenting cells, bacterial infection of mammalia and activation of leukocytes, similarly to results observed for the whole dataset [see Supplementary File 3, worksheet 6]. Although significant changes in IFNγ mRNA levels were not detected by microarray analysis, we observed by qPCR that this gene was 18 times more expressed in infected than control samples. Moreover, results of bioinformatic data mining could be further confirmed by the expression profile observed by qPCR for a panel of IFNγ-target genes (Figure 3B) and the uncovered abundance changes in tissue of two IFNγ-regulated molecules after infection (Figure 3C). Of note, STAT1 and STAT3, both transcriptional factors involved in interferon signalling, and IFNα were also detected among the upstream regulators most significantly implicated in tissue response to infection (Table 2).

NLRC5 activates different molecules of the antigen presentation via

MHCI pathway in Peyer patches follicles of S. Typhimurium infected swine NLRC5 was also disclosed as a relevant mediator of host response to NTS.

Network analysis followed by the IPA Molecule Activity Predictor tool revealed 174 that NLRC5 up-regulation induces the activation of genes coding for molecules involved in different stages of the antigen presentation via MHCI pathway (Figure 4A) Notably, all these genes were up-regulated after infection (Figure 4B). In order to clarify these results, we initially checked changes in the abundance of NLRC5 and MHCI in tissue by western blot. In accordance with transcriptomic data (Table 1), bacterial challenge also resulted in an increase of both molecules in tissue at protein level (Figure 5). Then, immunohistochemistry assays were carried out to verify the distribution of NLRC5 and MHCI in tissue. Higher levels of NLRC5 were detected at 2 dpi and labelling was observed in the cytoplasm and nucleus of mononuclear and polymorphonuclear cells (Figure 6A andB). Similarly, MHCI was also more detected in infected PP follicles, being mainly localized in the cytoplasm of mononuclear phagocytes (Figure 6C andD). Finally, immunofluorescence followed by confocal was executed to deepen and sharpen the role of NLRC5 and MHCI in the context of NTS. In spite of the diffuse labelling observed for NLRC5 over the whole follicle, high levels of this molecule were uncovered in polymorphonuclear cells located in the periphery of infected PP follicles (Figure 6E). Regarding MHCI, we observed that S. Typhimurium infected cells showed high levels of MHCI (Figure 6F).

Discussion

Until recently, the pathogenesis of infections by NTS was largely overlooked due to the dominance of the murine model of typhoid fever and the lack of alternative models for the study of salmonellosis (Tsolis et al., 2011). PP follicles underwent a marked infiltration of phagocytes upon infection, in line with the increased expression levels uncovered by microarray analysis for distinct chemokine encoding genes. Curiously, S. Typhimurium was predominantly labelled in the cytoplasm of polymorphonuclear cells (PMN) that were presumed to be neutrophils due to the notable presence of these cells in infected follicles. In spite of the accumulating evidences that the recruitment of neutrophils is crucial to prevent Salmonella dissemination (Broz et al., 2012), the infiltration of inflammatory cells is usually observed in the PP subepithelial dome as well as interfollicular area during mice Salmonella infections (Tam et al., 2008).

Therefore, the remarkable infiltration of neutrophils observed by us in PP follicles led us to speculate that apart from killing of bacteria, these cells could also take part in the induction of adaptive immune responses during infections by NTS.

Indeed, it has been reported that neutrophils may influence adaptive immunity by acting either directly on T cells or indirectly through DC modulation [START_REF] Beauvillain | Neutrophils efficiently cross-prime naive T cells in vivo[END_REF]. Thus, the first hypothesis considered by us was that infected neutrophils could carry Salmonella to follicles for further processing.

i vi 3 . 5 . 1 3 . 5 . 2 3 . 5 . 2 . 1 3 . 5 . 2 . 2 3 . 5 . 2 . 3 3 . 5 . 2 . 4 3 . 5 . 3 . 1 3 . 5 . 3 . 2 3 . 5 . 3 . 4

 3513523521352235233524353135323534 Introduction.................................................................................... Materials and methods................................................................... Experimental infection and tissue sampling............................. Laser microdissection and RNA preparations........................... Microarray analysis.................................................................. Systems biology analysis.......................................................... 3.5.2.5 Real-time quantitative PCR (qPCR) .......................................... 3.5.2.6 Western blot analysis............................................................... 3.5.2.7 Histopathology, immunohistochemistry and confocal microscopy ............................................................................................................ 3.5.3 Results ............................................................................................ Genes are mostly up-regulated in Peyer patches follicles after S. Typhimurium infection ........................................................................ Processes related to cell movement and activation are primarily induced in Salmonella infected follicles............................................... 3.5.3.3 Adaptive immune responses are properly induced in Peyer's patches follicles during infections by NTS............................................ IFNγ is the main upstream regulator of the transcriptional response carried out in Peyer's patches during non-typhoidal salmonellosis ....................................................................................... 3.5.3.5 NLRC5 activates different molecules of the antigen presentation via MHCI pathway in Peyer patches follicles of S. Typhimurium infected swine ................................................................................................... 3.5.4 Discussion.......................................................................................

Figure 1 -

 1 Figure 1 -Schematic drawing of the structure of the lymph-node and trafficking routes for T cells (T) and B cells (B). Numbers in the square indicate the direction of the lymph flow from the initial lymphatic capillary in peripheral organs to the draining lymph-node and then to the blood circulation via the central thoracic duct. A: artery, DC: interdigitating dendritic cell, HEV: high endothelial venule, Mf: sinus macrophage, MM: marginal macrophage, P: plasma cell, V: vein (Matsuno et al., 2000).

Figure 2 -

 2 Figure 2 -Schematic drawing of the structure of Peyer's patches and trafficking route of T cells (T), B cells (B). HEV: high endothelial venule (Matsuno et al., 2010).

Figure 3 -

 3 Figure 3 -Entry and capture of orally acquired Salmonella. Salmonella can cross the intestinal epithelium and enter the host at different sites, mostly at the distal ileum. Two of these sites are organized lymphoid structures, Peyer's patches (PP) and solitary intestinal lymphoid tissue (SILT). The third site is the intestinal villus. Salmonella can also invade using different mechanisms, which are indicated with numbers. Within PP, Salmonella can traverse the intestinal barrier through: (1) M cells in the follicle-associated epithelium (FAE); (2) epithelial cells forming the FAE, in particular after bacteria compromise M cells and the intestinal barrier; (3) DCs located in the FAE, could capture Salmonella. Once bacteria cross the FAE they can be captured by DCs located in the subepithelial dome (SED). DCs containing Salmonella can then initiate an adaptive immune response by stimulating T cells in the PP (marked T in the figure) or migrate to the mesenteric lymph node (MLN) to initiate adaptive immunity. In addition, Salmonella can cross the intestinal barrier through SILT, probably in a similar manner as in PP, as represented in (4). At villi, Salmonella can enter in different ways: (5) through M cells; (6) captured by DCs extending dendrites; or(7) passing through or between compromised epithelial cells. After the bacteria reach the lamina propria, they can access the MLN within migrating DCs, which are abundant in the lamina propria. Finally, the bacteria may be able to reach the blood stream, presumably transported by CD18+ phagocytes, as shown in(8). In addition to being transported to the MLN via lymph within DCs, it remains possible that free bacteria could be transported in lymph. (9) Bacteria can exit the MLN as free bacteria or possibly associated with cells and seed other tissues in the body(Tam et al., 2008).

Figure 4 -

 4 Figure 4 -The intestinal innate immune response to Salmonella. (A) Following the invasion of the mucosa, the presence of Salmonella is detected by pattern recognition receptors. Extracellular Salmonella are detected by Toll-like receptors inducing a transcriptional response leading to the expression of proinflammatory cytokines such as IL-23. Intracellular Salmonella activate NOD-like receptors that can induce IL-23 expression, as well as the assembly of NLRC4/NLRP3 inflammasomes that activate Caspase-1, promoting the secretion of mature IL-1β and IL-18. (B) IL-18 and IL-23 amplify the inflammatory response by paracrine signaling. IL-18 induces the release of IFNγ from T cells, while IL-23 induces the release of IL-22 and IL-17. These cytokines induce the increased production of mucins and antimicrobial peptides, and promote the release of CXC chemokines leading to an influx of neutrophils into the mucosa. (C) Infiltrating neutrophils are crucial for the killing of extracellular Salmonella. Although considered an intracellular pathogen, Salmonella can be found extracellularly following transcytosis through M cells or after pyroptosis induced host cell lysis. Besides clearing the pathogen, neutrophil influx can also lead to damage to intestinal tissue, resulting in the loss of epithelial cell barrier function and promoting diarrhea (Broz et al., 2012).

  Existing data from the mouse model support that the Peyer's patch route predominates in traversal of Salmonella. Nevertheless, little is known about how Salmonella penetrates the mucosa in man and other species (Dougan et al., 2011). According to Costa et al. (2012), S. Typhimurium induces ruffling of the plasma membrane at the apical side of intestinal epithelial cells during bovine infections, invading M cells and absorptive enterocytes. Similarly, it has been shown that Salmonella can invade porcine absorptive enterocytes, M-cells and even goblet cells (Boyen et al., 2008a). In a study by scanning and transmission electron microscopy, Meyerholz et al. (2002) demonstrate a preferential adherence of S. Typhimurium to M cells within 5 minutes post infection of swine ileum. In addition, these authors demonstrated that this pathogen may use sites of cell extrusion as an additional mechanism for early invasion. Moreover, in accordance to evidences from murine infections, Boyen et al. (2006) asserted that SPI-1 is necessary to promote the invasion of porcine intestinal epithelial cells by S. Typhimurium, thereby contributing to the efficient short-term colonization of the porcine gut and to the induction of influx of neutrophils into the intestinal lumen.

(

  Wigley, 2004). On the other hand, other authors have demonstrated the influence of genetic variance in the outcome of S. Typhimurium infections in porcine. Uthe et al. (2009) asserted a positive association between genetic polymorphisms in the CCT7 gene with Salmonella shedding in swine. Besides, another report by Tuggle et al (2010) detected transcriptional changes in blood of persistent Salmonella shedder pigs which resulted in increased levels of intracellular-oriented responses compared to low shedder animals.

3. 1

 1 Exploring the immune response of porcine mesenteric lymph nodes to Salmonella enterica serovar Typhimurium: an analysis of transcriptional changes, morphological alterations and pathogen burden Rodrigo Prado Martins a , Melania Collado-Romero a , Cristina Arce a , Concepción Lucena a , Ana Carvajal b , Juan J. Garrido a * a Grupo de Genómica y Mejora Animal, Departamento de Genética, Universidad de Córdoba, Campus de Rabanales, Edificio Gregor Mendel C5, 14071 Córdoba, Spain b Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad de León, 24071 León, Spain Comparative Immunology, Microbiology and Infectious Diseases 36 (2013) 149-

  MGB/NFQ) were used in the quantification assays. Each 25 μl PCR reaction contained 12.5 μl IQ Supermix 2X (Biorad), 0.4 μm of each primer, 0.2 μM probe, 1 μM MgCl2, 1μl DNA (at 800 ng/μl for porcine samples) and 10 μl UHQ water. PCR amplifications were performed on an iQ5 Thermo Cycler (Biorad) under the following conditions: 95 °C for 10 min and 35 cycles of 95 °C for 15 s and 60 °C for 1 min. Each MLN sample was tested by triplicate in three independent assays. Number of genome equivalents was deduced from the standard curve employing the quantification cycle (Cq) obtained for each sample.

  Afterwards, fold change values (2 -ΔΔCq ) were standardized by a series of sequential corrections proposed by Willems et al. [25], which included log transformation, mean centering and autoscaling. A fold change of 1 denoted no change in gene expression. Values lower than 1 and higher than 1 denoted up and down-regulation, respectively. Standardized data were analyzed using the software SPSS 15.0 for Windows® (SPSS, Inc). Data were tested for normality and variance homogeneity by Shapiro-Wilk and Levene's tests, respectively. Those data assumed to be from a normal distribution and which within-group variances were constant across groups were analyzed by oneway ANOVA and Duncan post hoc test. Remaining data were analyzed by Kruskal-Wallis and Mann-Whitney tests. Differences in the rectal temperature among groups were assessed by ANOVA and Duncan post hoc test. Data from S. typhimurium quantification as well as neutrophil and macrophage count were analyzed by Kruskal-Wallis and Mann-Whitney tests. Spearman's rank correlation test was used to examine the association among S. typhimurium load, neutrophil and macrophage count and gene expression. A p-value below 0.05 was considered statistically significant.

  ) and peaked at 2 dpi (40.88±0.46 •C). However, at 6 dpi the rectal temperature declined to normal values (39.15±0.35 •C), not significantly different from those observed in control animals.

Figure 1 .

 1 Figure 1. Histological analysis of MLN from S. typhimurium infected pigs. (A) Tissue-infiltrating phagocytes were visualized around trabeculae by H&E staining at 2 dpi. (B) 4E9/11 labeling shows the presence of macrophages within the lymph nodes T-cell area at 2 dpi. (C and D) Quantification of neutrophils and macrophages in tissue, respectively. Data are shown as the number of neutrophils or macrophages per microscope field. Different letters mean significant difference among groups (p < 0.05).

Figure 2 .

 2 Figure 2. S. typhimurium labeling in MLN of infected pigs. (A) 100×, (B) 400× and (C) 1000×. (D) Quantification of S. typhimurium by TaqMan real-time PCR assay. Data are shown as the number of genome equivalents (GE) of S. typhimurium per 800 ng of MLN genomic DNA. Different letters mean significant difference among groups (p < 0.05).

Figure 3 .

 3 Figure 3. Expression of immune-related genes in MLN of pigs experimentally infected with S. typhimurium by qPCR. Data are shown as the fold change in gene expression in infected pigs compared to controls. Values lower than 1 were calculated as 1/fold change.

3. 1 . 3 . 4 .

 134 Fig. 2D, S. typhimurium burden changed significantly (p = 0.005) along the time course of infection. Pathogen load could be quantified at 1 dpi (85.4± 79.7 GE/800 ng DNA), peaked at 2 dpi (310.5± 171.1 GE/800 ng DNA), and decreased to unquantifiable levels at 6 dpi (0 GE/800 ng DNA), indicating the efficient clearance of most of bacteria from the tissue. Although Salmonella was not detected at 6 dpi or in one animal necropsied at 1 dpi, the screening by microbiological methods allowed us to determine the presence of live S.

  washed twice with water, shrunk for 15min with 100% acetonitrile and dried in a Savant SpeedVac for 30min. Samples were then reduced with 10mM DTT in 25mM ammonium bicarbonate(56 °C, 30min) and alkylated with 55mM iodoacetamide in 25mM ammonium bicarbonate for 15 min in the dark. Finally, samples were digested overnight with 12.5 ng/μL sequencing-grade trypsin (Roche) in 25mMammoniumbicarbonate (pH8.5) at 37 °C. After digestion, the supernatant was collected, and 1 μL was spotted onto a MALDI target plate and allowed to air-dry at room temperature. Matrix (0.4 μL of a 3mg/mL) solution of α-cyano-4-hydroxy-cinnamic acid (CHCA; Sigma-Aldrich, St. Louis, USA) in 50%acetonitrilewas added to the dried peptide digest spots and allowed again to air-dry at room temperature. MALDI-TOF MS analysis was performed in a 4800 Proteomics Analyzer MALDITOF/TOF mass spectrometer (Applied Biosystems, Framingham, MA, USA) operated in positive reflector mode, with an accelerating voltage of 20,000 V. All mass spectra were calibrated internally using peptides from the autodigestion of trypsin. MALDI-TOF MS analysis produced peptide mass fingerprints and the peptides observed were collected and represented as a list of monoisotopic molecular weights with an S/N greater than 15. The suitable precursors for MS/MS sequencing analyses were selected and fragmentation was carried out using the CID on (atmospheric gas was used) 1 KV ion reflector mode and precursor mass Windows±5 Da. The plate model and default calibration were optimized for the MS/MS spectra processing. For protein identification, the UniProtKB/Swiss-Prot Data Base was searched in batch mode using GPS Explorer v3.6 software (Applied Biosystems) with a licensed version 2.1 of MASCOT.Search parameters were: carbamidomethyl cystein as fixed modification, methionine oxidation as variable modification, peptide mass tolerance 50-100 ppm, peptide charge state +1, one missed trypsin cleavage site and MS/MS fragments tolerance 0.3 Da. The parameters for the combined search (peptide mass fingerprint and MS/MS spectra) were the same described above. In all protein identification, the probability scores were greater than the score fixed by

Figure 1 -B

 1 Figure 1 -Histological analysis of porcine mesenteric lymph nodes (MLN) upon Salmonella typhimurium infection. (A) H&E staining demonstrates an evident phagocyte infiltration around trabeculae at 2 days post infection (dpi). (B) Infiltration of macrophages after infection was also observed by immunohistochemistry. (C-F) S. typhimurium labeling at 0 (C), 1(D), 2 (E) and 6 (F) dpi. Labeling was more observed at 2 dpi and poorly detected at 6 dpi.

Figure. 2 -

 2 Figure. 2 -DIGE analysis of mesenteric lymph node proteins from controls and Salmonella typhimurium infected pigs. (A) Representative DIGE gel. Spots showing significant changes in abundance are indicated by numbers. (B) Bars demonstrate the number of spots exhibiting significant increase or decrease of abundance at 1, 2 and 6 days post-infection (dpi). (C) Venn diagram depicts the number of differently abundant proteins at each time point (1, 2 or 6 dpi) and commonly identified along the whole time course.

Figure 3 -

 3 Figure 3 -Data validation by Western blot and immunohistochemistry. (A) Immunohistochemistry shows a decrease of VIM abundance in MLN and labeling of large irregularly-shaped mononuclear cells located near trabeculae after infection. (B-I) Standard abundance by DIGE and Western blot analysis of validated proteins at 1, 2 and 6 dpi. (B, C) VIM, (D, E) YWHAZ, (F, G) LCP1, (H, I) FKBP4.

Figure 4 -

 4 Figure 4 -Expression profiling of immune-related genes in mesenteric lymph nodes of pigs experimentally infected with Salmonella typhimurium by qPCR. Data are shown as the fold change in gene expression in infected pigs compared to controls Values lower than 1 and higher than 1 denote down and up-regulation respectively. The same letters above the bars indicate no significant differences (p<0.05).

Figure 5 -

 5 Figure 5 -Gene network analysis of porcine MLN after S. typhimurium infection. "Posttranslational modification, Protein folding, Cellular assembly and organization" gene networks. Activation relationships are highlighted in yellow. Blue lines represent interactions entailing heat shock proteins. Light blue lines represent interactions between heat shock proteins and other molecules.

Figure 6 -

 6 Figure 6 -Antigen processing and presentation pathway. Differently abundant proteins associated to this pathway are highlighted in red (A) and their standard abundance after infection by DIGE is depicted in (B). Dotted line indicates a pathway detail from Ingenuity Pathway Analysis. The image was generated by Kegg pathways from the Kanehisa laboratories and is subject to their copyright conditions.

  generated peptides gain access to the phagosome lumen via TAP, bind MHC-I molecules and activate CD8+ T-cells [40,42]. Transcriptomic analysis carried out by us (Martins et al., unpublished data) highlighted the upregulation of TAP and MHC-I mRNA in MLN of S. typhimurium infected pigs. In the proteomic study present here, HSP90 and other three chaperones associated with degradation and retrotranslocation of proteins to cytosol (HSP70, BiP/HSPA5 and

  during the early response to infection. Taking into account the entire studied time course, a total of 290 transcripts, representing 285 unique genes, showed levels of expression that changed significantly (BF<0.05) over time as a result of the bacterial challenge [see Additional file 3].

  bioinformatics tools were employed to gain an insight into networks, functions and pathways associated to the transcriptomic response of porcine MLN to Salmonella Typhimurium [see Additional file 4].

  analysis are mean values from two different probes. bAmplified with SLA-B and SLA-DRB5 primers.

Figure 1 (

 1 Figure 1 (previous page) -Gene network analysis by Ingenuity Pathway Analysis (IPA) Visual representation of networks 1 and 4. Red and grey nodes are input and IPA-inserted molecules respectively. Colored lines highlight genes that take part in an enriched Canonical Pathway.

Figure 2 -

 2 Figure 2 -Top 10 enriched canonical pathways. Blue bars and yellow squares denote -log(pvalue) and ratio respectively. Threshold line represents a p-value of 0.05.

Figure 3

 3 Figure 3 Interaction between CTLA-4 signaling in cytotoxic T lymphocytes and Clathrin-mediated endocytosis signaling pathways. A: visual representation of CTLA-4 signaling in cytotoxic T lymphocytes pathway stressing the regulation of molecules taking part in Clathrin-mediated endocytosis signaling. Red and grey nodes are input and IPA-inserted molecules respectively. B: western blot analysis of CTLA4 and CLTA in MLN at 1, 2 and 6 dpi. C: mRNA quantification of CTLA4 by qPCR. D: expression pattern of CLTA mRNA by microarray analysis.

Figure 4

 4 Figure 4 Analysis of MHC molecules in porcine MLN after Salmonella Typhimurium infection. A: western blot analysis of MHC class I and II at 1, 2 and 6 dpi. B-E: MHCII labeling in tissue at 0 (B), 1(C), 2 (D) and 6 (E) dpi by immunohistochemistry. Scale bar = 20 μm. F-G: mRNA quantification of SLA-DRB5 (MHCII) (F) and SLA-B (MHCI) (G) by qPCR. H-K: confocal analysis of Salmonella Typhimurium infected MLN demonstrate the presence of the pathogen in MHCII positive cells. Salmonella Typhimurium-FITC (H), MHCII-Alexa Fluor® 594 (I), DAPI (J) and merge (K).

  genes taking part in these processes were overexpressed all along the time course, suggesting an inhibition of apoptosis. To deepen and sharpen these results, TUNEL analysis followed by confocal microscopy was performed aiming to elucidate the mechanisms of cell death in MLN after Salmonella Typhimurium infection. As shown in Figure5A-D and 5I, DNA damage detected by TUNEL staining peaked at 1 dpi and decreased at 2 and 6 dpi compared to controls. Afterwards, expression level of the main pyroptosis and apoptosis inducers (CASP1 and CASP3, respectively) was quantified by qPCR.

SalmonellaFigure 5 Figure 6

 56 Figure 5 Cell death and histopathologic analysis of MLN from Salmonella Typhimurium infected pigs. A-D: Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) analysis at 0 (A), 1(B), 2 (C) and 6 (D) dpi. Scale bar = 100 μm. E-H: H&E staining of at 0 (E), 1(F), 2 (G) and 6 (H) dpi. Scale bar = 50 μm. I: Quantification of TUNEL fluorescent labeling shows an increase of positive nuclei at 1 dpi and decrease to levels inferior to controls at 2 and 6 dpi. J-K: mRNA quantification of CASP1 (J) and CASP3 (K) by qPCR.

state that CTLA- 4 mediated

 4 Treg immunosuppression is critical in preventing host from eliminating certain invasive pathogens. Given that, CTLA-4 down-regulation observed in this study, concurrent with clathrin up-regulation after the bacterial challenge could indicate the repression of a mechanism of T cell inhibition in porcine MLN upon Salmonella Typhimurium infection. However, since clathrin appears to be involved in the establishment of both host immunity mechanisms and virulence strategies evolved by pathogen, a deeper investigation of processes mediated by this molecule during infection could provide novel knowledge on the pathogenesis of porcine salmonellosis.

3. 4 . 2 . 3 .

 423 Real-time quantitative PCR (qPCR)Amplified RNA from infected and control animals was reverse transcribed to cDNA using the qScript cDNA Synthesis kit (Quanta BioSciences, Gaithersburg, MD, USA) and qPCR assays were performed according toMartins et al. (2013) to determine the relative expression of 30 genes coding for molecules taking part in distinct immune response processes such as inflammation, DC-T cell interaction and T helper cell response. Primers used for amplifications can be found as supporting information (see Supplementary File 1). Afterwards, relative gene expression was assessed by the 2 -ΔΔCq method(Livak and Schmittgen, 2001). In this analysis, qPCR data were presented as the fold change in gene expression normalized to an endogenous reference gene and relative to the uninfected controls. Fold change values higher than 1 meant upregulation. Values inferior to 1 were calculated as -1/fold change and denoted down-regulation. Data were analyzed by Student's t-test using the software SPSS 15.0 for Windows® (SPSS, Inc). A p-value bellow 0.05 was considered statistically significant.

Figure 1 .

 1 Figure 1. -Laser-capture microdissection, pathogen detection and gene expression analysis in Peyer's patches of S. typhimurium infected pigs. (A-C) LCM: After their identification in tissue (A), PP follicles were selected (B) and collected by Auto-Laser Pressure Catapulting mode (C). (D-F) Immunohistochemistry: S. typhimurium was immunolabeled in control (D) and infected tissue (E-F). Yellow, white and blue bars correspond to 500, 200 and 50 lm respectively. (G) Visual representation of T-helper cell

(

  Tam et al., 2008), mechanisms of innate immune response are effectively induced in PP during swine oral infections by S. typhimurium. Apart from contributing to bacterial clearance in tissue, as suggested by our previous observations(Martins et al.,2013), this response could be related to triggering of host second line of defense. Genes coding for molecules involved in DC activation (CD80, CD83, CD40, IL12p40, IL23p19 and CCR7) were found to be up-regulated in infected PP (Supplementary File 2).

167 3 . 5 . 3 . 2

 3532 Processes related to cell movement and activation are primarily induced in Salmonella infected folliclesBioinformatic tools were used to translate microarray data into biological information. It was revealed that infection mainly resulted in an enrichment of genes involved in cellular movement, followed by other host functions such as immune cell trafficking, inflammatory response and cell-to-cell signalling and interaction [see SupplementaryFile 3]. Subsequently, IPA z-score was employed to predict the effect of the uncovered gene expression changes on distinct biological processes. Results indicated that processes related to migration and activation of phagocytes and leukocytes were most significantly activated in S.

3. 5 . 3 . 3

 533 Adaptive immune responses are properly induced in Peyer's patches follicles during infections by NTS Network analysis depicted direct and indirect relationships between genes involved in distinct processes of immune response [see Supplementary File

  168

Figure 1 -

 1 Figure 1 -Laser microdissection, histological analysis and CD5 quantification in PP follicles upon infection with S. Typhimurium. A-B: After their identification (A), PP follicles were microdissected by Auto-Laser Pressure Catapulting. C-D: H/E staining of ileum sections demonstrating PP follicles before (C) and after (D) the bacterial challenge. A highlighted in (D), infection resulted in a relevant infiltration of neutrophils. E: fluorescent labelling of S. Typhimurium in tissue. Pathogen was mainly detected in the perinuclear zone of polymorphonuclear cells. F: western blot assays uncovered increased levels of CD5 in infected tissue.

Figure 2 - 3 . 5 . 3 . 4

 23534 Figure 2 -Network analysis of microarray data and qPCR assays in S. Typhimurium infected PP follicles. A: major generated network depicted a common up-regulation of genes taking part in communication between innate and adaptive immune cells and dendritic cell maturation pathways. B: differential gene expression analysis by qPCR revealed an up-regulation of molecules involved in the formation of geminal centers in infected PP follicles.

Figure 3 -

 3 Figure 3 -IFNγ is the main regulator of transcriptional response of PP follicles to nontyphoid Salmonella.A: network analysis disclosed that IFNγ upregulation resulted in the activation or inhibition (orange and blue lines respectively) of 53 genes differently expressed after infection. Data were inconsistent for genes liked with yellow lines and effect could not be predicted for those linked with grey lines. B: differential gene expression analysis of a sort of IFNγ-target genes by qPCR confirmed the effect of this gene in the expression of downstream molecules.C: immunohistochemistry assays further corroborated that upregulation of IFNγ gene also resulted in increase or decrease of target molecules at protein level.

Figure 4 -

 4 Figure 4 -NLRC5 activates the antigen presentation via MHCI pathway after infection with non-typhoid Salmonella. Network analysis (A) disclosed direct relationships between NLCR5 and distinct molecules involved in the antigen presentation via MHCI (B).

Figure 5 -Figure 6 -

 56 Figure 5 -Western blot assays of NLRC5 and MHCI in infected and control follicles.

  Porcine immune system show a high level of resemblance with human(Meurens et al., 2012) and differently from rodents, human and swine PP share common anatomical and physiological peculiarities such as a predominant localization in the ileum and prenatal development(Makala et al., 2002). In light of this and the similarity of disease caused by S. Typhimurium in human and pig (Sanchez-Vargas et al 2011,Boyen et al., 2008), in the current study we coupled our swine model of non-typhoid salmonellosis to LM and microarrays analysis to dissect the mechanisms carried out in PP follicles upon infection with S. Typhimurium.PP follicles are aggregations of B cells and follicular dendritic cells (FDC)that after antigenic stimulus form the germinal center (GC). These specialized structures contain large B lymphoblasts, follicular T cells, macrophages and a tight network of FDC, playing a relevant role in the generation of protective antibody production and memory B-cells (El Shikh and Pitzalis, 2012). We observed that infection triggered in PP follicles the migration and activation of lymphocytes as well as the up-regulation of distinct genes involved in the formation of GC. Thus, it could be suggested that antibody responses and longlived humoral immunity are triggered at a short time (2dpi) in PP follicles during NTS infections. During primary immune responses in PP, protein antigens are processed and presented by antigen presenting cells (APCs) which activate Ag-specific Th cells in the PP T-cell zones (Acheson and Luccioli.2004). These cells expand and differentiate into effector Th cells that move towards PP follicles to regulate the development of Ag primed B-cells and lead to the formation of a germinal center Traditionally, T-cell help to B-cell has been attributed to the type-2 helper CD4 + T cells (Th2) (Coquerelle and Moser, 2010). However, T-follicular helper cells (Tfh) were recently described as CD4 + mature cells that are capable of providing help to B-cells during the GC reaction and switched Ag-specific antibody responses via IL21 (through STAT3 and STAT1), IL4 (through STAT6), IL10 and IFNγ (Cerutti et al., 2012, El Shikh and Pitzalis., 2012,Coquerelle and Moser, 2010). IL21 production by naïve CD4 + T cells is induced by IL6 and IL12 released by DC located out of the follicle (Ma et al. 2012). However, FDC also stimulates Tfh differentiation by producing IL6 upon type I interferon signaling (Coquerelle and Moser, 2010) and collaborate with B-cell activation by releasing large amounts of active TGF-β (Cerutti et al., 2012). Interestingly, all these cytokines were found to be up-regulated, indicating that the cytokine environment necessary for B cell differentiation was established in infected PP follicles. Apart from this, the fate of a responding B cell is determined by the interaction between T-cell and B-cell through mediators also uncovered by us to be up-regulated. A cognate interaction between T cell receptor and peptide-MHCII on B cells must be assembled, as well as ligation of CD40 on B cells by CD40L and provision of CD80 and CD86 by B cells to ligate CD28 on T cells (Zotos and Tarlinton, 2012). B cells thereafter differentiate along the follicular pathway generating GC B cells that further differentiate into long-lived memory B cells and plasma cells producing high-affinity antibodies (Cerutti et al., 2012).

6 . 7 . 8 . 9 .

 6789 Previously, Mengiovanni et al. (2006) and Morel et al. (2008) uncovered that physical interactions involving neutrophils, DC and T cells play a major role in the human immune response to Candida and Mycobacterium respectively, resulting in T cell activation following DC acquisition of antigens delivered by polymorphonuclear cells (PMN). More recently, Alfaro et al. (2011) found out that DC can uptake viable PMN and subsequently cross-present antigens previously internalized by these cells.Cross-presentation defines the process by which professional APC present peptides from extracellular antigens via their own MHCI molecules to CD8 + T cells(Houde et al., 2003). Notably, several evidences of the induction of cross-presentation were found out in this study. Firstly, bioinformatic mining of microarray data disclosed an up-regulation of genes encoding molecules involved in different steps of the antigen presentation pathway via MHCI. BATF3, a transcription factor required for development of DC subsets capable of priming CD8 T-cell responses[START_REF] Tussiwand | Compensatory dendritic cell development mediated by BATF-IRF interactions[END_REF] was also found to be up-regulated and IFNγ, followed by IFNα and their signal transducers STAT1 and STAT3 were identified as the most relevant upstream regulators of the transcriptional response carried out in follicles upon infection. Types I and II IFN up-regulate multiple functions within the class I antigen presentation pathway to increase the quantity and diversity of peptides presented in the context of MHCI[START_REF] Schroder | Interferon-gamma: an overview of signals, mechanisms and functions[END_REF]). Infected tissue also showed increased levels of CD5, a marker of T-cell activation[START_REF] Soldevila | The immunomodulatory properties of the CD5 lymphocyte receptor in health and disease[END_REF] and over-expression of CXCL9 and CXCL11, both strong inducers of cytotoxic lymphocytes (CTL) and type-1 helper CD4+ T cells (Th1) activation and migration[START_REF] Groom | CXCR3 in T cell function[END_REF]. Additionally, we confirmed by western blot analysis and immunohistochemistry assays that MHCI was more abundant in tissue after the bacterial challenge and demonstrated by confocal analysis that S. Typhimurium infected phagocytes expressed high levels of this molecule. Therefore, on the whole, our results suggested that Salmonella antigens are cross-presented in infected PP follicles, in line with our previous observations in S. Typhimurium infected mesenteric lymph nodes(Martins et al., 2012). These finds, supported by previous evidences[START_REF] Alfaro | Dendritic cells take up and present antigens from viable and apoptotic polymorphonuclear leukocytes[END_REF][START_REF] Morel | Mycobacterium bovis BCG-infected neutrophils and dendritic cells cooperate to induce specific T cell responses in humans and mice[END_REF][START_REF] Megiovanni | Polymorphonuclear neutrophils deliver activation signals and antigenic molecules to dendritic cells: a new link between leukocytes upstream of T lymphocytes[END_REF], could highlight a relevant role for infected neutrophils in the response to S. Typhimurium, since these cells would be able to modulate DC function while transferring to them antigens to be employed in acquired immunity mechanisms.However, the induction of cross-presentation in infected PP through other mechanisms/cells should not be dismissed. Interestingly, we observed that PMN cells located in the boundary of infected PP showed high levels of NLRC5, a NOD-like receptor newly identified as a key transcriptional regulator of genes involved in the MHCI antigen presentation pathway[START_REF] Yao | Expression regulation and function of NLRC5[END_REF].Immunohistochemistry and western blot assays demonstrated that NLRC5 was increased at protein level in infected tissue and network analysis of microarray data also related the up-regulation of this gene with the activation of molecules involved in the Ag presentation via MHCI. Moreover, S. Typhimurium was found by us to induce up-regulation of NLRC5 and MHCI in porcine neutrophils infected in vitro (Data not shown). In light of this, we infer that infected neutrophils could directly cross-present S. Typhimurium antigens to CD8 + T cells. This presumption can be further supported by a previous demonstration that neutrophils are able to cross-prime CD8 + T cells in vivo[START_REF] Beauvillain | Neutrophils efficiently cross-prime naive T cells in vivo[END_REF]. Finally, we envisaged that cross-presentation in PP follicles could also be triggered by activated B cells. De Wit et al. (2010) reported that upon BCRmediated phagocytosis of Salmonella, human B-cell boosts antibody production and in addition, cross-present bacterial antigens in a proteasome-dependent manner. Nevertheless, besides the direct interaction with CD8 + T-cells, the functionality of B cells as professional APC could also enable them to work in synergy with infected neutrophils, to initiate and/or amplify T cell cytotoxic response to exogenous antigens. As previously discussed, this hypothesis could also justify the notably presence of infiltrating neutrophils in an area of PP mostly composed of B-cells, but further research is necessary to elucidate it. Although we have discussed the distinct mechanisms that could trigger cross-presentation separately, it is probable that all of them occur simultaneously during infections. If true, this redundancy in cross-presentation induction could enhance the potency and efficiency of host cell-mediated immunity against Salmonella. Indeed, suicide cross-presentation of S. Typhi by DC is reported to generate mostly CD8 + effector memory T cells (Salermo-Gonçalves and Sztein 2009), whereas infected B-cells are capable of activating both the central and effector memory CD8 + compartments (De Wit et al., 2010). In summary, this study disclosed a prominent role for PP follicles in the establishment of immune responses against S. Typhimurium. It was demonstrated that infection resulted in the assembling of different mediators of immune response in PP follicles, aiming to induce early antibody responses and long-lived humoral immunity at a short time after infection. Interestingly, several evidences of cross-presentation triggering were found out by us, suggesting that besides eliciting B-cell-mediated immune responses, PP follicles might mediate the generation effector and memory CD8 T cells during infections by NTS. The S. Typhimurium strain used in this work expressed both invasion and intracellular survival inducers in MLN during pig infections. Besides, genes coding for two different flagellar filament proteins were found to be expressed in MLN, suggesting that pathogen could employ flagellar phase variation to hinder pig immune response (Martins et al. Vet Res. Under review); Swine might take advantage of flagellin and prgJ expression by S. Typhimurium to induce pyroptosis of infected cells in MLN and consequently promote clearance of pathogen by innate mechanisms in the extracellular milieu. This process, concurrent with the inhibition of apoptosis might consist in a host protective response that prevents pathogen spread beyond gut-associated lymph-nodes (Martins et al. Vet Res. Under review; Martins et al. J Proteomics. 2012. 75:4457-4470); Transcriptomic and proteomic analysis conjunctively indicated that S. Typhimurium antigens are cross-presented via MHCI in a proteasome-dependent manner in MLN of infected pigs, which might enable host to trigger an early CD8 T cell mediated response to control infection (Martins et al. Vet Res. Under review; Martins et al. J Proteomics. 2012. 75:4457-4470); Combination of an in vivo infection model with laser microdissection and gene expression analysis proved to be a promising strategy to clarify the role of specific cell populations during infectious processes (Martins et al. Dev Com Immunol. 2013. 41:100-104); 10. S. Typhimurium induced a remarkable infiltration of phagocytes, mainly neutrophils, in PP follicles of infected pigs. Additionally, these structures were found to assemble distinct immunity mediators upon infection, enabling host to

Table 1 -

 1 Continued

	Gene Name	Foward Primer (5' → 3')	Reverse Primer (5' → 3')	Accesion number
	CD209	CTGACTTGGCCCCTCCTTCT	GAGACTGGTGGATCCTGGAAAC	NM_001129972.1

  37 °C for 24 h. The identification of the suspected colonies was confirmed by PCR assays. For this, 20 colonies with typical Salmonella morphology were collected from each plate, mixed in 300 μl of UHQ water and their DNA extracted by boiling. PCR was carried out in a final volume of 20 μl, containing 2 μl of DNA template, 400 nM of each primer, 200 nM of each dNTP, 2 mM MgCl2, 2 μl of 10X reaction buffer and 0.75 U Tth DNA polymerase (Biotools). Primers employed in this assay were the same used in the procedure of S. typhimurium quantification by TaqMan qPCR. PCR cycling protocol consisted of a denaturing step at 94 •C for 5 min, followed by 35 cycles of 94 °C for 30 s, 60 °C for 30 s, 72 °C for 30 s, and a final step of 6 min at 72 °C.

Table 2 -

 2 Changes in gene expression relative to uninfected controls (0 dpi) in porcine MLN at 1, 2 and 6 days after S. typhimurium infection. Fold change (FC) values with the same letters above are not significantly different (p < 0.05).

		0 dpi		1 dpi		2 dpi		6 dpi
	Gene	F. change	SD	F. change	SD	F. change	SD	F. change	SD
	CASP1	1.00a	0.19	0.76ab	0.19	1.53c	0.17	0.54b	0.09
	CCL2	1.00a	0.14	1.17ab	0.42	1.23a	0.27	0.62b	0.12
	CCL3	1.00	0.29	1.06	0.20	1.64	0.22	1.05	0.24
	CCL4	1.00	0.26	1.35	0.22	1.23	0.22	0.77	0.24
	CCL5	1.00	0.24	0.95	0.18	0.89	0.12	1.26	0.34
	CCL28	1.00a	0.25	0.74ab	0.24	0.35b	0.08	1.16a	0.14
	CD11b	1.00a	0.17	0.69ab	0.23	0.43b	0.11	0.76a	0.16
	CD14	1.00	0.24	1.32	0.36	1.79	0.56	0.92	0.33
	CD40	1.00	0.14	0.95	0.24	1.26	0.20	0.82	0.14
	CD40L	1.00a	0.18	0.71b	0.04	0.53c	0.03	0.90ab	0.16
	CD209	1.00a	0.28	0.72a	0.36	0.13b	0.02	0.46a	0.22
	CXCL2	1.00a	0.20	3.11b	1.22	2.85b	1.17	1.34ab	0.55
	CXCL8	1.00a	0.20	1.18a	0.15	2.84b	0.41	0.49c	0.09
	DEFB1	1.00	0.38	2.06	0.49	0.78	0.24	1.70	0.81
	DEFB2	1.00a	0.14	0.98a	0.26	2.52b	0.59	1.05a	0.41
	IFNγ	1.00a	0.31	1.91ab	0.66	3.50b	1.32	1.08a	0.41
	IL1β	1.00a	0.20	6.85b	3.36	10.07b	4.43	1.03a	0.28
	IL4	1.00a	0.27	0.50ab	0.12	0.23b	0.05	0.42b	0.11
	IL5	1.00	0.20	0.66	0.23	0.61	0.14	0.84	0.22
	IL6	1.00	0.35	0.97	0.42	0.93	0.32	0.62	0.10
	IL10	1.00ab	0.16	0.76bc	0.18	1.14a	0.15	0.63c	0.09
	IL12p40	1.00	0.24	0.63	0.22	0.37	0.17	0.47	0.17
	IL-13	1.00a	0.28	0.55ab	0.27	0.24b	0.03	0.39ab	0.17
	IL-18	1.00a	0.08	0.76b	0.11	0.51c	0.10	0.53c	0.08
	IL-23p19	1.00	0.19	0.93	0.22	0.94	0.06	0.84	0.24
	MyD88	1.00	0.15	0.85	0.17	0.80	0.14	0.67	0.07
	NFkB1	1.00a	0.17	1.00a	0.24	0.62b	0.16	0.61b	0.13

Table 2 -

 2 Continued

		0 dpi		1 dpi		2 dpi		6 dpi
	Gene	F . change	SD	F. change	SD	F. change	SD	F. Change	SD
	NOD1	1.00	0.26	0.89	0.30	1.19	0.21	0.60	0.20
	NOD2	1.00ab	0.24	1.16bc	0.32	1.70c	0.26	0.68ª	0.17
	SELL	1.00a	0.23	0.76ab	0.18	0.56b	0.10	0.58b	0.12
	SLC11A1	1.00a	0.43	1.80a	0.58	8.40b	1.22	0.90ª	0.37
	TLR1	1.00	0.10	0.69	0.15	0.75	0.15	0.75	0.10
	TLR2	1.00a	0.09	1.01a	0.27	1.07a	0.21	0.59b	0.08
	TLR3	1.00a	0.07	0.73ab	0.18	0.51b	0.13	0.61b	0.16
	TLR4	1.00a	0.06	0.93a	0.22	0.82ab	0.22	0.58b	0.08
	TLR5	1.00	0.29	0.45	0.19	0.64	0.15	0.57	0.23
	TLR6	1.00a	0.12	0.58b	0.10	0.75ab	0.15	0.73b	0.11
	TLR7	1.00a	0.04	0.55b	0.08	0.58b	0.06	0.56b	0.08
	TLR8	1.00a	0.12	0.78a	0.12	1.30b	0.08	0.77ª	0.15
	TLR9	1.00	0.22	1.22	0.22	0.97	0.21	1.11	0.16
	TLR10	1.00	0.14	0.73	0.17	0.71	0.15	0.78	0.14
	TNFα	1.00a	0.23	1.41a	0.36	1.14a	0.23	0.65b	0.09

Table 3 -

 3 Statistical association between mRNA gene expression and S. typhimurium load and neutrophil and macrophage count.

		S. Typhimurium	Neutrophils	Macrophages
	S. Typhimurium	---	0.844**	0.517*
	Neutrophils	0.844**	---	0.594*
	Macrophages	0.517*	0.594*	---
	CASP1	0.415	0.288	0.059
	CCL2	0.452	0.226	-0.247
	CCL3	0.645**	0.518*	0.252
	CCL4	0.429	0.321	0.029
	CCL5	-0.088	-0.129	0.112
	CCL28	-0.311	-0.531	-0.392
	CD11b	-0.712**	-0.571*	-0.710**
	CD14	0.519*	0.550*	0.085
	CD40	0.520*	0.338	0.091
	CD40L	-0.731**	-0.759**	-0.616*
	CD209	-0.473	-0.547*	-0.730**
	CXCL2	0.630**	0.624**	0.181
	CXCL8	0.605*	0.547*	0.203
	DEFB1	0.006	-0.026	-0.110
	DEFB2	0.541*	0.515*	0.423
	IFNγ	0.668**	0.703**	0.202
	IL1β	0.750**	0.650**	0.367
	IL4	-0.622*	-0.720**	-0.706*
	IL5	-0.595*	-0.432	-0.286
	IL6	0.064	-0.100	-0.169
	IL10	0.312	0.144	0.108
	IL12p40	-0.515*	-0.297	-0.602*
	IL13	-0.426	-0.397	-0.772**
	IL18	-0.739**	-0.609*	-0.638**
	IL23p19	0.035	-0.115	-0.286
	MyD88	-0.155	-0.294	-0.392
	NFκb	-0.225	-0.365	-0.511*
	NOD1	0.290	0.053	0.066
	NOD2	0.550*	0.391	0.230
	SELL	-0.436	-0.591*	-0.549*
	SLC11A1	0.727**	0.594*	0.424
	TLR1	-0.201	-0.371	-0.418
	TLR2	0.388	0.235	-0.236
	TLR3	-0.771**	-0.624**	-0.521*
	TLR4	0.033	0.029	-0.498*
	TLR5	-0.163	-0.129	-0.395
	TLR6	-0.304	-0.347	-0.355

Table 1 -

 1 List of differently expressed protein in porcine MLN after oral infection with S. typhimurium.

	1 vs 0	2 vs 0	6 vs 0

Table 1 -

 1 Continued

	1 vs 0	2 vs 0	6 vs 0

Table 1 -

 1 Continued

	1 vs 0	2 vs 0	6 vs 0

Table 1 -

 1 Continued

	1 vs 0	2 vs 0	6 vs 0

Validation of selected proteins by Western blot and immunohistochemistry

To validate DIGE results, we performed Western blot analysis for four

Table 2 -

 2 Protein interaction networks associated to the response of porcine MLN to S. typhimurium infection.

	ID Score 1	Focus molecule 2	Molecules in the network 3	Top Functions
				14-3-3, ACTB, Actin, ACTR3, Alpha
				tubulin, ANXA1, ARHGDIA, ARHGDIB,
				Arp2/3, Caspase, Ck2, EIF4A3, F Actin,	Post-Translational
				FKBP4, HBB, Hsp70, Hsp90, HSP,	Modification, Protein
	1	54	20	HSP90AA1, HSP90B1, HSPA5, HSPA8,	Folding, Cellular
				HSPA1B, LASP1, LCP1, MHC Class I	Assembly and
				(complex), NFkB (complex), PDIA3,	Organization
				PYCARD, RNA polymerase II, STMN1,
				TUBA1B, TUBG1, Tubulin, YWHAZ
				Akt, ALDH2, ALDOA, Ap1, APOA1,
				CaMKII, ERK1/2, FAM59A, FSH, GNB1,
				GRB2, Histone h3, Histone h4, IG9,
				Insulin, Jnk, LDL, Lh, LOC81691,	Cellular Movement,
	2	20	10	MAP2K1/2, Mapk, MIR155HG, Nfat	Cell Cycle, Lipid
				(family), P38 MAPK, PCMT1, PCNA,	Metabolism
				PDGF BB, PDLIM1, PI3K (complex),
				Pkc(s), PLC gamma, Rac, SYNCRIP,
				Trypsin, VIM
				BPNT1, CDC37L1, CEACAM3, CHI3L2,
				CLEC5A, DEFB104A/DEFB104B,
				DNAJB7, EIF4H, FKBP6, Gbp4, GBP6,	Cell Death, Cell-To-Cell
				H60a, HSP90AB1, IFNG, IKBKE,	Signaling and
	3	14	7	KCTD12, KMO, MDH1, MLEC, Myhs,	Interaction,
				NDRG4, PGRMC2, PPID, PSMB8,	Inflammatory
				Raet1b, RAN, SLC28A1, SLC5A2,	Response
				TALDO1, Taok2 (mouse), TGFB1, TNF,
				TRAF6, TREM3, TTC28

Table 3 -

 3 Top four enriched canonical and Kegg pathways in porcine MLN after S. typhimurium infection.

	Pathways	p-value 1 Ratio 2	Input molecules
	Kegg Pathways
	Antigen processing and presentation	1.4E-06	5.7E-02	PDIA3, HSP90AA1, HSPA8, HSPA5, HSPA1B
	Pathogenic Escherichia coli infection	2.7E-04	6.1E-02	TUBA1B, ACTB, YWHAZ
	MAPK signaling pathway	3.3E-04	1.8E-02	HSPA1B, HSPA5, HSPA8, GRB2, STMN1
	Shigellosis	4E-04	6.1E-02	TUBA1B, ACTB, YWHAZ
	Ingenuity Canonical Pathways
				HSPA8, HSP90B1, HSPA1B,
	Glucocorticoid Receptor Signaling	5.9E-08	2.7E-02	GRB2, ANXA1, FKBP4,
				HSP90AA1, HSPA5
	14-3-3-mediated Signaling	1.4E-07	5E-02	GRB2, PDIA3, TUBG1, YWHAZ, VIM, TUBA1B
	Aldosterone Signaling in Epithelial Cells 9.8E-07	3.5E-02	HSPA8, HSP90B1, HSPA1B, PDIA3, HSP90AA1, HSPA5
	Protein Ubiquitination Pathway	1.5E-05	2.2E-02	HSPA8, HSP90B1, HSPA1B, HSP90AA1, PSMB8, HSPA5

1 Fisher's exact test; 2 Ratio (number of input molecules in a given pathway, divided by total number of molecules that make up that pathway)

9 Selective capture of transcribed sequences (SCOTS)

  Selective capture of Salmonella transcripts from MLN of pigs at 2 dpi was performed by the SCOTS method[11], following the procedure described by

	as secondary antibodies. Immunostaining was performed as described by Robertson et al. [22]. Briefly, deparaffinized sections of formalin fixed MLN were blocked for 30 min with 1% bovine serum albumin and 2% foetal calf serum in PBS. Then, sections were overnight incubated at 4°C with primary antibodies, 3.3.2.Sheikh et al. [24]. Briefly,5 μg of total RNA from infected MLN samples was
	three times washed with PBS for 5 min and incubated for 1 h at 37°C with
	converted into first strand cDNA by using random priming and Superscript III
	fluorescent secondary antibodies. For negative controls, primary antibody was
	reverse transcription (Life Technologies). Subsequently second strand cDNA was
	omitted. Finally, sections were three times washed for 5 min in PBS containing
	produced employing DNA polymerase I (Klenow fragment, Life Technologies). To
	1.43 μM 4',6-diamidino-2-phenylindole (DAPI, Life Technologies). Samples were
	create a corresponding in vitro Salmonella Typhimurium cDNA sample for
	subsequently evaluated and imaged using a LSM 5 Exciter confocal microscope
	comparison, the same bacterial isolate employed in the experimental infection
	(Carl Zeiss, Jena, Germany).
	was grown to early-log growth phase (OD 600 =0.3) and late-log growth phase
	3.3.2.8 Cell death analysis
	Formalin fixed MLN samples were evaluated for cell death by Terminal
	deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), employing the
	TUNEL Apoptosis Detection Kit for Paraffin-embedded Tissue Sections (GenScript,
	Picastaway, NJ, USA) according to manufacturer instructions. Briefly, proteinase K
	treated samples were permeabilized with 0.1% Triton X-100 and 0.1% sodium
	citrate for 10 minutes and incubated with Blocking Solution II (GenScript) for 30
	minutes. Subsequently, tissues were covered with 50 µl of TUNEL Reaction
	Mixture (GenScript), incubated at 37 ºC for 1 h in a dark humidified chamber and
	washed in PBS. Sections were examined in a LSM 5 Exciter confocal microscope
	(Carl Zeiss MicroImaging GmbH, Jena, Germany) using excitation wave 450-500
	nm and emission wave 515-565 nm (green). Fluorescence intensity was
	quantified with the ImageJ software 1.46r [23] and data were analyzed by ANOVA
	(p-value cutoff of 0.05) using SPSS 15.0 for Windows (SPSS Inc).
	(FITC)-conjugated goat anti-rabbit IgG (Sigma-Aldrich, St. Louis, MO, USA) and
	Alexa Fluor 594 anti-mouse IgG (Life Technologies, Carlsbad, CA, USA) were used
	116	115

(OD 600 =0.8) in Luria Bertani (LB) broth. Afterwards, Salmonella Typhimurium transcripts were selectively captured from in vivo and in vitro double stranded cDNA by hybridization to sonicated biotinylated genomic Salmonella DNA, which was previously blocked with Salmonella ribosomal DNA fragments. Microbial cDNA-genomic DNA hybrids were then captured by binding to streptavidincoated beads (Dynabeads M-280 streptavidin, Invitrogen) and bacterial transcripts were eluted by alkaline denaturation. Eluted bacterial cDNA was then PCR-amplified with conserved primers and finally purified using Qiagen PCR column purification kit (Qiagen). After that, one round captured and purified cDNA from both in vitro and in vivo conditions were quantified by spectrophotometry and used as template (10 ng) for qPCR assays as described above. Primer pairs used for amplifications can be found as supporting information [see Additional file 2]. Gene expression levels were estimated employing gyrA as reference gene. Since tissue from uninfected pigs was negative for Salmonella, those samples could not be used as reference for fold change calculations of pathogen gene expresion. Besides, most of screened genes showed Cq values inferior to those observed for gyrA in infected MLN. For these 117 reasons, gene expression levels were alternatively estimated as follows: gyrA Cq -target gene Cq. Higher values meant higher expression levels and vice-versa.

Table 1 Microarray data validation by qPCR -

 1

				MICROARRAY		qPCR
	Gene		Fold change 1 dpi 2 dpi 6 dpi	BF	Fold change 1 dpi 2 dpi 6 dpi	p-value
	CD180	1.7	2.6	1.5	0.0000429	1.1	1.8	1.2	0.010
	CD1A		1.1	-1.4	1.2 0.00047793	-1.4	-2.5	1.2	0.013
	DAB2		-1.2	-2.6	-1.2	6.62E-13	-3.1	-6.5 -2.6 0.001
	EIF4H		-1.1	-1.1	-1.1 0.0000101	-1.5	-1.4 -1.8 0.021
	ENPP6	1.3	2.0	-1.2 0.0000448	1.2	1.8	-1.7 0.000
	F13A1	1.4	2.2	-1.1 0.00000227	1	1.7	-2.2 0.012
	HLA-B	b

Table 2 -

 2 Top five biological functions enriched in MLN of pigs infected with Salmonella Typhimurium.

	Annotations	p-Value a	Input genes (n)
	Inflammatory Disease	4,64E-05 -2,65E-02	13
	Protein Síntesis	6,52E-05 -1,86E-02	32
	Antigen Presentation	1,8E-04 -1,68E-02	5
	Cell Death	1,8E-04 -2,67E-02	78
	Cell-To-Cell Signaling and Interaction	1,8E-04 -2,67E-02	27

  as a significant cause of disease worldwide. Data from the Centers for

	technology and bioinformatic analysis to provide an accurate view of the immune with RNase-Free DNase Set (Qiagen) and RNA quality was checked by Experion
	mechanisms modulated in PP of pigs orally infected with S. typhimurium. RNA analysis (Bio-Rad, Hercules, CA, USA). Finally, RNA was amplified using the
	SuperScript™ RNA Amplification System (Invitrogen, Carlsbad, CA, USA), as
	3.4.2. Material and methods indicated by manufacturer.
	Disease Control (CDC) assert that Salmonella alone causes approximately 1 3.4.2.1. Experimental infection
	million foodborne infections annually in the United States (CDC, 2011). Similarly,
	Salmonella is reported as the main cause of food-borne outbreaks in the Eight crossbred piglets of approximately four weeks of age, confirmed to
	European Union, being Salmonella enterica serovar Typhimurium (herein be fecal-negative for Salmonella, were randomly allocated to control or infected
	Salmonella typhimurium) the second most frequently isolated serovar from groups (four animals each), being control (0 day post-infection -dpi) pigs
	human infections (EFSA, 2012). necropsied 2 h before the experimental infection. Pigs belonging to the infected
	Advances in mammalian models of Salmonella infection are expected to group were orally challenged with 108 cfu of S. typhimurium phagetype DT104
	result in new understanding of salmonellosis pathogenesis, contributing to the and euthanized at 2 dpi. Ileum samples were collected from all piglets and
	control and cure of human cases (Gopinath et al., 2012). In this context, pigs can immediately frozen in liquid nitrogen for RNA isolation or fixed in 10% neutral
	be stressed as an ideal model for investigating human non-typhoidal buffered formalin for immunohistochemistry
	salmonellosis, since upon infection with S. typhimurium swine undergo a self-
	3.4.2.2. Laser-capture microdissection and RNA preparations
	limiting enterocolitis similar to the clinical manifestation observed in man.
	Studies on the murine model of typhoid fever state that to cause Frozen gut samples from all experimental animals were embedded in
	infection, ingested S. typhimurium primarily invade M cells in the small intestine optimal cutting temperature compound (Sakura Finetek USA, Torrance, CA, USA)
	and then accesses Peyer's patches (PP), resulting in a massive inflammatory and cut into serial 20 lm sections. Before microdissection, eight cryostat sections
	response in these organs (Broz et al.,2012). Therefore, besides their role in the from each pig were mounted on glass slides and treated with RNAlater-ICE
	immune surveillance of the intestinal lumen, PP are relevant mediators of (Ambion) according to manufacturer instructions. Subsequently, PP follicles were
	infections by S. typhimurium. Although previous studies have employed gut loops laser-microdissected and captured from terminal ileum sections avoiding
	models to extrapolate the response of PP to S. typhimurium (Meurens et al., contamination by adjacent cells with a PALM Micro-Beam device (Carl Zeiss
	2009; Nunes et al., 2010), the function of these organs in the context of oral non-MicroImaging GmbH, Jena, Germany), by Auto-Laser Pressure Catapulting (LPC)
	typhoidal infections has never been explored to date. To address this issue, we mode (Fig. 1A-C). Catapulted tissue was soaked in 15 ll of RLT buffer (Qiagen,
	employed for the first time laser-capture microdissection (LCM) coupled to qPCR Valencia, CA, USA) poured in 200 ll microtubes caps and RNA purifications were
	carried out employing the RNeasy Mini Kit (Qiagen). Eluted RNA was digested
	146

Table 1 -

 1 Relative gene expression in Peyer's Patches of pigs experimentally infected with S.typhimurium, at 2 dpi.

	Gene	FC a	0 dpi	SD	FC	2 dpi	SD	p-value b
	CASP1	1		1.26	2.66		3.51	0.266
	CCL19	1		0.12	3.47		0.81	0.000
	CCL21	1		0.72	2.98		3.09	0.292
	CCR7	1		0.57	5.98		2.16	0.002
	CD11b	1		0.32	6.53		1.51	0.000
	CD28	1		1.01	6.96		3.38	0.028
	CD40	1		0.29	3.66		0.89	0.001
	CD40L	1		0.27	2.02		0.56	0.020
	CD80	1		0.62	9.69		6.34	0.006
	CD83	1		0.20	2.07		0.41	0.012
	CD86	1		0.34	1.19		0.50	0.710
	CTLA4	1		0.69	3.96		2.91	0.142
	CXCL2	1		0.33	5.78		2.85	0.002
	IL1β	1		1.29	79.22		43.06	0.004
	IL4	1		1.02	1.38		1.05	0.868
	IL12p40	1		0.97	20.22		19.15	0.007
	IL13	n.a.		n.a.	n.a.		n.a.	n.a.
	IL16	1		0.73	1.43		1.41	0.902
	IL17A	n.a.		n.a.	n.a.		n.a.	n.a.
	IL18	1		0.42	1.07		0.52	0.940
	IL21	1		0.32	3.93		2.97	0.032
	IL23	1		0.16	2.58		0.25	0.000
	IFNγ	1		0.96	17.66		9.94	0.005
	NOD2	1		0.72	16.48		20.82	0.042
	SELL	1		0.13	-2.5		0.026	0.000
	TLR2	1		0.82	17.14		8.37	0.013
	TLR4	1		0.11	2.23		0.92	0.015
	TLR5	1		0.38	14.05		7.45	0.001
	TLR8	1		0.56	4.67		2.17	0.005
	TNFα	1		0.24	2.41		0.51	0.002
	a Fold change mean values (n = 4 per group). Values higher than 1 meant upregulation.
	Those inferior to 1 were calculated as _1/fold change and denoted down-regulation. b p-
	values bellow 0.05 were considered statistically significant. n.a.: not amplified.

  Besides, it could be deduced that inhibition of T-cell activation by DCs, largely reported as an evasion mechanism evolved by S. typhimurium(Bueno et al., 2012), might not be induced in swine PP or is effectively counteracted by host response.In short, combination of an in vivo infection model with LCM and gene expression analysis proved to be a promising strategy to clarify the role of specific cell populations during infectious processes. This approach enabled us to gain an insight into the immunity mechanisms carried out in PP during non-typhoidal salmonellosis. Results pointed to an effective induction of innate and adaptive immune responses in this organs, inferred to be different from those observed in MLN and closely related to the processes carried out at intestinal mucosa after infection. Data provided here could represent useful information for the establishment of control and therapeutic strategies focused on the enhancement of immunity against Salmonella at gut level.PP are the main portal of Salmonella host entry into host mucosa(Broz et al., 2012; Tam et al., 2008). These organs are clusters of organized lymphoid tissue located in the small intestine, which act as sites of antigen sampling and

	3.5.1 Introduction
	Salmonella species are a leading bacterial cause of disease, exerting induction of mucosal immune responses (Makala et al., 2002). Upon infection, PP
	considerable impact on global human health. It is estimated that 93.8 million follicles undergo substantial changes that involve numerous cellular and cell
	cases of gastroenteritis due Salmonella occur worldwide leading to 155,000 surface components, giving rise to the formation of germinal centers (GC). These
	deaths each year (Majowicz et al., 2010). Data from the Centers for Disease structures are intimately associated with the production of B cell humoral
	Control (CDC) uncovered Salmonella as the main cause of hospitalization due to immune response and host cell interactions which consist in a fundamental
	foodborne disease in the United States (CDC, 2013). Similarly, the European Food aspect of adaptive immunity and generation of immunological memory (El Shikh
	, Collado-Romero et al. (2012) Safety Authority (EFSA) reported salmonellosis as the second most notified and Pitzalis., 2012).
	detected a general trend toward down-regulation of Th2 and Th17 responses in zoonotic disease in the European Union (EFSA, 2013).
	ileum mucosa of S. typhimurium infected pigs, validating the importance of
	processes carried out by PP in the development of immune response at mucosal
	level during non-typhoidal salmonellosis. To further confirm results from
	differential expression analysis, a bioinformatic algorithm was used to predict the
	modulation of some immunity mechanisms after infection, by combining results
	disclosed for the screened genes and relating them with the available literature.
	Processes such leukocytes recruitment, stimulation of DC and macrophages, DC
	maturation and influx of neutrophils were predicted to be activated as a
	consequence of infection. The same was detected for mechanisms of T
	lymphocytes proliferation, priming and differentiation (see Supplementary File 3).
	Intriguingly, up-regulation of Th1 response was not observed by us in Accumulating evidences demonstrate the anatomic and physiological
	mesenteric lymph nodes (MLN) of S. typhimurium infected pigs. Furthermore, similarities between pig and human, highlighting swine as a valuable model for a
	contrary to the clear induction of DC and T-cell activity uncovered by current number of infectious diseases relevant to human health (Meurens et al 2012).
	results, DC-T-cells interaction was inferred to be compromised in these organs Indeed, pigs are ideal models for the study of salmonellosis by NTS, since upon
	after infection (Martins et al., 2013). Therefore, it is tempting to speculate that, in infection with S. Typhimurium, swine undergo a self-limiting gastroenteritis which

spite of their similar functions as components of gut associated lymphoid tissue, PP trigger mechanisms distinct from those occurring in MLN upon oral infection 153 with S. typhimurium. Salmonella enterica serovar Typhimurium (herein S. Typhimurium), referred to as a non-typhoid Salmonella (NTS), is the second most commonly isolated serovar from human infections (Sanchez-Vargas et al 2011). Although the pathogenesis of infections caused by this pathogen has been extensively studied using the mouse model of systemic disease

(Tsolis et al., 2011)

, one limitation of the murine typhoid model is that S. Typhimurium typically causes a self-limiting gastroenteritis rather than typhoid fever in humans

(Majowicz et al., 2010)

. For this reason, the pathogenesis of NTS gastroenteritis remained largely unexplored until recently, when alternative animal models of infection became more widely used

(Tsolis et al., 2011)

. parallels the clinical manifestation observed in man

(Boyen et al., 2008)

.

160

Recently, laser microdisssection coupled to qPCR technology was successfully used to provide a preliminary view of the immune response carried out by Peyer's patches (PP) follicles during oral infections with NTS (Martins et al 2013b). Thus, in the current study, laser microdissection followed by microarray analysis and bioinformatic data mining was applied to our swine model of gastroenteritis by S. Typhimurium to generate a broader view of the biological processes carried out by PP follicles upon infection.

  8 cfu of Salmonella Typhimurium phagetype DT104 and subsequently necropsied at 2 dpi. Ileum samples were collected from all experimental animals and immediately frozen in liquid nitrogen for RNA and protein isolation or fixed in 10% neutral buffered formalin for histological processing. Piglets were housed in experimental isolation facilities of the University of León (Spain). All procedures involving animals were performed in accordance with the European regulations regarding the protection of animals used for experimental and other scientific purposes, under the supervision of the Ethical and Animal Welfare Committee of the University of León (Spain).Regenerative Medicine, Seville, Spain). This chip contains 23,937 probe sets to interrogate 23,256 transcripts in pig, which represents 20,201 genes. The One-

	Cycle Eukaryotic Target Labeling Assay was used to obtain biotinylated cRNA to
	be used in the subsequent chip hybridization according to manufacturer
	instructions (Expression Analysis Technical Manual, Affymetrix). The biotinylated
	cRNA targets were then cleaned up, fragmented, and hybridized with the
	GeneChip Porcine Genome Array following Affymetrix recommended protocols.
	Chips were washed, stained with a GeneChip Fluidics Station 450 (Affymetrix)
	3.5.2.2 Laser microdissection and RNA preparations using the standard fluidics protocol and scanned with an Affymetrix GeneChip
	Frozen gut samples from all experimental animals were embedded in Scanner 3000 (Affymetrix). Probe signal intensities were captured and processed
	optimal cutting temperature compound (Sakura Finetek USA, Torrance, CA, USA) with the GeneChip Operating Software 1.4.0.036 (Affymetrix) and the resulting
	and cut into serial 20 μm sections. Before microdissection, eight cryostat sections CEL files were reprocessed using robust multi-array average normalization (RMA)
	from each pig were mounted on glass slides and treated with RNAlater-ICE
	(Ambion) according to manufacturer instructions. Afterwards, PP cells were laser-
	microdissected and captured from terminal ileum sections by Auto-Laser
	Pressure Catapulting (LPC) mode (Figure 1A and B) with a PALM MicroBeam
	device (Carl Zeiss MicroImaging GmbH, Jena, Germany). Catapulted tissue was
	soaked in 15 μl of RLT buffer (Qiagen, Valencia, CA, USA) poured in 200 μl
	microtubes caps and RNA purifications were carried out employing the RNeasy
	Mini Kit (Qiagen). Eluted RNA was digested with RNase-Free DNase Set (Qiagen)
	and RNA quality was checked by Experion RNA analysis (Bio-Rad, Hercules, CA,
	USA).
	3.5.2.3 Microarray analysis
	Gene expression analysis was carried out using the GeneChip Porcine

Genome Array by Affymetrix platform (Affymetrix Inc., Santa Clara, CA, USA) at the Genomics Unit of CABIMER (Andalusian Center for Molecular Biology and 162

(Irizarry et al., 2003)

. Then, differentially expressed (DE) genes were accessed by the Rank Products (RP) method

[START_REF] Breitling | Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments[END_REF]

, using default settings. A FDR adjusted p-value of 0.05 was used as cutoff to rank significantly regulated transcripts. Since the Affymetrix Porcine GeneChip is not fully annotated in all the features, it was re-annotated with Blast2GO

(Conesa et al, 2005)

with a minimum

Table 2 -

 2 Predicted activation state of biological functions and upstream regulators enriched in PP follicles during infections by S. Typhimurium

	Category	Predicted Activation State	Activation z-score	p-value
	Downstream effect
	Migration of phagocytes	Increased	2,930	6,33E-13
	Cell movement of phagocytes	Increased	2,928	4,09E-11
	Cell movement of leukocytes	Increased	2,342	4,54E-10
	Cell movement of myeloid cells	Increased	3,012	9,53E-10
	Leukocyte migration	Increased	2,498	3,35E-09
	Activation of leukocytes	Increased	3,213	4,77E-09
	Activation of blood cells	Increased	3,514	4,96E-09
	Activation of cells	Increased	3,378	1,80E-08
	Quantity of leukocytes	Increased	2,564	1,92E-08
	Homing of leukocytes	Increased	2,604	2,64E-08
	Upstream regulator
	IFNG	Activated	4,211	1,04E-26
	lipopolysaccharide	Activated	4,918	6,03E-23
	poly rI:rC-RNA	Activated	4,291	4,60E-22
	Interferon alpha	Activated	2,541	5,35E-21
	TNF	Activated	4,107	1,46E-18
	IL1B	Activated	4,096	1,05E-17
	STAT3	Activated	3,039	1,43E-17
	STAT1	Activated	3,110	2,58E-17
	IL6	Activated	2,861	4,18E-17
	NFkB (complex)	Activated	4,092	6,77E-16

Objectives

Calculated with Right-tailed Fisher's Test;

Number of imput molecules in the network;

Input molecules are highlighted in bold.

Acknowledgements................................................................................. vii Acknowledgements We thank Erena Ruiz-Mora and Reyes Alvarez for skilful technical assistance. This work was supported by EU funds provided by EADGENE and SABRE Projects, by the Excellence Project of the Junta de Andalucía Government P07-AGR-02672 and by two National R&D Program Grant of the Spanish Ministry of Education and Science (AGL2008-00400 and AGL2011-28904). RPM is a predoctoral researcher supported by the FPU Research Program of the Spanish Ministry of Education and Science. Acknowledgments We thank Erena Ruiz-Mora and Reyes Alvarez for skilful technical assistance. This research was supported by EU funds provided by EADGENE and SABRE Projects, by the Excellence Project of the Junta de Andalucía Government P07-AGR-02672 and by the National R&D Program of the Spanish Ministry of Science and Innovation (grants AGL2008-00400 and AGL2011-28904). Right to use AU and IPA bioinformatic tools was granted by the Andalusian Platform of Bioinformatics (University of Málaga, Spain

). RPM is a predoctoral researcher supported by the FPU Research Programof the SpanishMinistry of Education. Additional MS/MS information is available in http://www.uco.es/servicios/scai/id_proteomics.html. Acknowledgements We thank Erena Ruiz Mora, Juana Molina and Reyes Alvarez for skilful technical assistance, Esther Peralbo for technical support in confocal microscopy analysis (IMIBIC) and Eloisa Andújar and Mónica Pérez from the Genomic Unit of CABIMER for their excellent array technical assistance. This work was supported by the Junta de Andalucía (P07-AGR-02672), the Spanish Ministry of Science and Innovation (AGL2008-00400 and AGL2011-28904) and EU funds through SABRE project and EADGENE network. RPM and CA are predoctoral researchers supported by the FPU Research Program of the Spanish Ministry of Education and Science. Acknowledgements We thank Erena Ruiz-Mora and Reyes Alvarez for skillful technical assistance. This work was supported by EU funds provided by EADGENE and SABRE Projects, by the Excellence Project of the Junta de Andalucía Government P07-AGR-02672 and by two National R&D Program Grant of the Spanish Ministry of Education and Science (AGL2008-00400 and AGL2011-28904). RPM is a predoctoral researcher supported by the FPU Research Program of the Spanish Ministry of Education and Science. Acknowledgements We thank Erena Ruiz Mora, Juana Molina and Reyes Alvarez for skilful technical assistance, Esther Peralbo for technical support in confocal microscopy analysis (IMIBIC) and Eloisa Andújar and Mónica Pérez from the Genomic Unit of CABIMER for their excellent array technical assistance. This work was supported by the Junta de Andalucía (P07-AGR-02672), the Spanish Ministry of Science and Innovation (AGL2008-00400 and AGL2011-28904) and EU funds through SABRE project and EADGENE network. RPM and CA are predoctoral researchers supported by the FPU Research Program of the Spanish Ministry of Education and Science.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.cimid.2012.11.003. 100 of the enhancement of protein degradation by immunoproteasome as a result of infection.

In conclusion, our results suggest that, in spite of modulating normal host functions and replicating intracellularly, S. typhimurium fails to effectively damper immune response elements during infections in pigs. The proteome response of porcine MLN to infection was associated to the induction of innate immunity processes such as phagocyte infiltration and pyroptosis. Moreover, we could infer that S. typhimurium antigens are cross-presented via MHC-I in a proteasome-dependent manner and this mechanism probably triggers an early cytotoxic response against bacteria. Although both innate and adaptive immune responses might control pathogen dissemination, further research will be necessary to elucidate the strategies exploited by S. typhimurium to establish the asymptomatic-carrier state in swine infections.

Supplementary material related to this article can be found online at doi:10.1016/j.jprot.2012.03.045.

Abstract

In this study, we sought to elucidate the early mechanisms triggered in porcine mesenteric lymph-nodes (MLN) upon in vivo Salmonella Typhimurium infection.

For this, a robust approach was employed to analyse host response and verify the expression of virulence genes by pathogen found in tissue. Salmonella Typhimurium strain used in this bacterial challenge was able to express the screened virulence effectors in MLN, suggesting that the development of a mild disease in infected swine is not attributed to an absence of virulence strategies triggering by pathogen. In fact, results indicate that despite its capacity of hampering immune response, a combination of host triggered innate immunity mechanisms and early T-cell cytotoxic response might overcome virulence strategies employed by pathogen. Clathrin-mediated endocytosis appears to take part in the pathogenesis of infection, but the role of this pathway in host and pathogen-mediated processes remains to be clarified. Furthermore, we infer that due to an inability of Salmonella Typhimurium to suppress flagellin and prgJ expression in porcine MLN, host is able to induce infected cell death by pyroptosis, protecting itself of pathogen spread beyond gut-associated lymphnodes.

Keywords: Pig, Salmonella enterica serovar Typhimurium, mesenteric lymph nodes, immune response, in vivo pathogen gene expression.

111

processing. All procedures involving animals were performed in accordance with the European regulations regarding the protection of animals used for experimental and other scientific purposes. Piglets were housed in experimental isolation facilities of the University of León (Spain). Animal care and procedures were in accordance with the guidelines of the Good Experimental Practices (GEP), under the supervision of the Ethical and Animal Welfare Committee of the University of León (Spain).

RNA purification

After treatment with RNAlater-ICE (Ambion, Inc, Austin, TX, USA), MLN samples were soaked in RLT buffer (Qiagen, Valencia, CA, USA) and disrupted in a rotor-stator homogenizer. RNA was isolated by using the AllPrep DNA/RNA/Protein Mini Kit (Qiagen), digested with the RNase-Free DNase Set (Qiagen) according to manufacturer instructions and routinely precipitated with ethanol. RNA integrity was evaluated using the Experion RNA chips (Bio-Rad, Hercules, CA, USA) before being quantified using a ND-1000 spectrophotometer (Nanodrop Technologies, Wilminton, USA).

Microarray analysis

Gene expression analysis was carried out using the GeneChip Porcine

Genome Array by Affymetrix platform (Affymetrix Inc., Santa Clara, CA, USA) at the Genomics Unit of CABIMER (Andalusian Center for Molecular Biology and Regenerative Medicine, Seville, Spain). This chip contains 23,937 probe sets to interrogate 23,256 transcripts in pig, which represents 20,201 genes. The One-Cycle Eukaryotic Target Labeling Assay was used to obtain biotinylated cRNA to be used in the subsequent chip hybridization according to manufacturer instructions (Expression Analysis Technical Manual, Affymetrix). The biotinylated

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

RPM was responsible for the whole study, including lab work, data analysis and interpretation, as well as the writing of the manuscript. CA participated in the confocal analysis. JEG collaborated with SCOTS analysis. AC performed the experimental infection and collected the tissue samples. RB and MGC performed microarray data processing. JJG conceived and designed the project and participated in the interpretation and discussion of results, as well as in the writing of the manuscript. All authors read and approved the final manuscript.

Abstract

In this report we employed laser-capture microdissection (LCM) coupled to qPCR technology and bioinformatic analysis to characterize, for the first time, the response of Peyer's patches (PP) from orally infected animals to Salmonella typhimurium, in a model of non-typhoidal salmonellosis. Pathogen was highly found in the cytoplasm of phagocytes in PP and differential gene expression analysis indicated an up-regulation of proinflammatory molecules, establishment of a Th1 driven response and triggering of DC and T-cell activity. Furthermore, predictions by bioinformatic analysis pointed to an activation of processes regarding stimulation and maturation of DC, influx of leukocytes in tissue and T lymphocytes priming and differentiation. In short, the approach used in this study proved to be a promising strategy to explore infectious processes. Indeed, it revealed an effective induction of innate and adaptive immune mechanisms in swine PP which appear to be distinct from those observed in mesenteric lymph nodes and closely related to response of gut mucosa.

Keywords -Peyer's patches, Salmonella typhimurium, Laser-capture microdissection, Immune response.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.dci.2013.04.020. follicles at 2 dpi with S. Typhimurium. A total of 164 transcripts, corresponding to 152 unique genes, were found to be differently expressed as a consequence of infection (FDR adjusted p<0.05). Among them, 37 genes were down-regulated whereas 115 were up-regulated. [see Supplementary File 2] To validate microarray data, qPCR assays were performed on a panel of 22 genes filtered by Rank Products analysis. As expected, all of them were confirmed to be significantly regulated (p<0.05) after infection and showed the same expression pattern observed by microarray analysis (Table 1).