Vaccine Models
The chronic nature of paratuberculosis, as well as the difficulties in reproducing the clinical disease, together with the need to assay different approaches to better know the disease, its diagnosis, and the ways to prevent and eradicate it have required the development of experimental models (Hines et al., 2007).
In particular, the development of new vaccines or the design of novel vaccination strategies against paratuberculosis must be followed by a thorough evaluation involving experimental trials in the target species, which can be technically challenging, time consuming and very expensive. Accordingly, in addition to experimental models in the susceptible species cattle, sheep and goats, more convenient models have been developed. In vitro and ex vivo models can be useful for vaccine prototype testing in initial phases of vaccine development and experimental challenge models are essential for screening potential candidates that can be subsequently assessed in field trials with natural challenge. Finally, simulation studies based on computerized models can also be useful for vaccination programme designing.22.4.1 In vivo models
Classical methods in the target species have been the standard since the first trials (Vallee et al., 1941; Sigurdsson and Tryggvadottir, 1949; Sigurdsson, 1960). However, the more recent research has been increasingly carried out on the mouse and rabbit model because of new animal experimentation rules and the need of higher numbers of individuals for testing more alternatives and to more strongly support conclusions (see Chapter 23 this volume). Small laboratory animal models also offer many other advantages that include thorough characterization of the immune response in immunologically defined animals, faster development of infection and disease, ease of handling and reduced cost. The mouse model has been used for vaccine evaluation of live-attenuated vaccines (Scandurra et al., 2010; Chen et al., 2012) against MAP and, although lesions do not develop in the intestine, histological and immunological changes similar to those observed in ruminants occur (Shin et al., 2006; Scandurra et al., 2010).
The low cost and availability of reagents of this species make this model useful for preliminary analysis of vaccine candidates (Chiodini and Buergelt, 1993). On the other hand, rabbits are naturally susceptible to infection with MAP (Fuentes and Cebrian, 1988; Angus, 1990) and they develop granulomatous lesions in gut-associated lymphoid tissue as early as 20 weeks after oral challenge (Arrazuria et al., 2015) providing an attractive animal to study aspects that cannot be studied in the mouse model. The rabbit model has been used to evaluate vaccination sequence (Arrazuria et al., 2016a) and vaccination routes Ladero et al. (2018).After initial screening of vaccines in small animal models, final testing should be done in ruminants. Ruminant challenge models include bovine, caprine, ovine and cervine (see Chapter 16, this volume). Subunit vaccines have been tested in cattle and sheep (Sechi et al., 2006; Kathaperumal et al., 2008). Nowadays, the goat model is the most widely used ruminant model for vaccination evaluation as it provides a direct homologue of the disease in cattle. It has been used to study live-attenuated vaccines (Scandurra et al., 2010; Park et al., 2011; Faisal et al., 2013; Hines et al., 2014; Shippy et al., 2017), to evaluate protection and interference with bovine tuberculosis (Perez de Val et al., 2012) and also to evaluate vaccination sequence (Arrazuria et al., 2016b).
22.4.2 In vitro and ex vivo models
It has been suggested that in vitro screening results do not translate to in vivo efficacy. Ex vivo assays combine both in vivo and in vitro aspects, since they begin with the vaccination of animals so that the immune response is mounted in vivo and then immune cells are isolated from these animals and an in vitro MAP infection assay is run. Monocytes are the main cell type used in these assays (Park et al., 2011), although cocultures of monocytes with autologous lymphocytes have shown to be promising predictors of vaccine non-response (Pooley et al., 2018).
22.4.3 Mathematical modelling and simulation studies
The availability of powerful computing capabilities has led to attempts to reproduce the main epidemiological characteristics of infectious diseases through mathematical modelling. Paratuberculosis is a good candidate for modelling studies aimed at designing improved control approaches, given the low sensitivity of conventional diagnostics and the slow nature of infection and disease. Thus, the first published model was based on a relatively simple matrix calculation method that allowed estimation of prevalence evolution and costs of two control strategies vs inaction. It clearly demonstrated that, although eradication could be reached by the two approaches, vaccination was by far more cost-effective than testing and culling (Juste and
Casal, 1993). Mathematical models have shown that they can aid in designing paratuberculosis control programmes bringing out critical issues and indicating the ideal way to integrate vaccination in control plans (Groenendaal et al., 2002; Lu et al., 2013a). Simulation studies with hypothetical vaccines have been used to increase knowledge on MAP transmission dynamics in the herds and to evaluate whether vaccination is able to prevent MAP invasion (Lu et al., 2013b). Other models have confirmed this conclusion with more sophisticated methods (Groenendaal et al., 2015). The drawback is that these predictive models need to be fuelled by data in order to be developed. However, they are useful and complementary to experimental challenge and field trial studies.
22.5
More on the topic Vaccine Models:
- Assessing Vaccine Efficacy in Different Animal Models
- Vaccine Types
- COUNSELING AND VACCINE HESITANCY
- Vaccine Regulatory and Production Issues
- Vaccine development
- Cervid Models
- Rodent Models
- 3. Models and definitions
- Competition in other 2-consumer-l-resource models
- Bovine Models
- Lottery and neutral models rely on equality and chance
- A brief guide to externalities in growth models