The impact and control of malignant catarrhal fever in Tanzania

Malignant Catarrhal Fever (MCF), an often-lethal infectious disease, presents as a variable complex of lesions in susceptible ungulate species. The disease is caused by a -herpesvirus following transmission from an inapparent carrier host. Two major epidemiological forms exist: wildebeest-associated MCF (WA-MCF), in which the virus is transmitted to susceptible species by wildebeest calves less than approximately four months of age, and sheepassociated MCF (SA-MCF) in which the virus is spread by sheep (primarily adolescents). Due to the lack of an in-vitro propagation system for the causative agent of the more economically significant SA-MCF, and with the expectation that cross-protective immunity may be provided, vaccine development has focused on the more easily propagated alcelaphine herpesvirus-1 (AlHV-1) that causes WA-MCF. In 2008 a direct viral challenge trial showed that a novel vaccine, employing an attenuated AlHV-1 (atAlHV-1) `C5000 virus strain, protected British Friesian-Holstein (FH) cattle against an intranasal challenge with virulent AlHV-1 `C5000 virus. For cattle keeping people living near wildebeest calving areas in sub-Saharan Africa an effective vaccine would have value as it would release them from the costly annual disease avoidance strategy of having to move their herds away from the oncoming wildebeest. On the other hand, an effective vaccine will release herd owners from the need to avoid MCF, allowing them to graze their cattle alongside wildebeest on the highly nutritious pastures of the calving areas. As such conservationists have raised concerns that the development of a vaccine might lead to detrimental grazing competition. The principle objective of this study was to test the novel vaccine on Tanzanian shorthorn zebu cross cattle (SZC).We did this firstly using a natural challenge field trial (Chapter Two) which demonstrated that immunisation with the atAlHV-1 vaccine was well tolerated and induced an oro-nasopharyngeal AlHV-1-specific and -neutralising antibody response. This resulted in an immunity in SZC cattle that was partially protective and reduced naturally transmitted infection by 56%. We also demonstrated that non-fatal infections occurred with a much higher frequency than previously thought. Because the calculated efficacy of the vaccine was less than that seen in British FH cattle we wanted to determine whether host factors, particular to SZC cattle, had impacted the outcomes of the field trial. To do this we repeated the 2008 direct viral challenge trial using SZC cattle (Chapter Four). During this trial we also investigated whether the recombinant bacterial flagellin monomer (FliC), when used as an adjuvant, might improve the vaccine’s efficacy. The findings from this trial indicated that direct challenge with pathogenic AlHV-1 is effective at inducing MCF in SZC cattle and that FliC is not an appropriate adjuvant for this vaccine. Furthermore, with less control group cattle dying of MCF than expected we speculate that SZC cattle may have a degree of resistance to MCF that affords them protection from infection and developing fatal disease. In Chapter Three we investigated aspects of the epidemiology of MCF, specifically whether wildebeest placenta, long implicated by Maasai cattle owners as a source of MCF, might play a role in viral transmission. Additionally, through comparative sequence analysis, at two specific genes (A9.5 and ORF50) of wild-type and atAlHV-1, we investigated whether the `C5000 strain, the source of which was taken from Africa more than 40 years ago, was appropriate for vaccine development. The detection of AlHV-1 virus in approximately 50% of placentae indicated that infection can occur in-utero and that this tissue might play a role in disease transmission. And, despite describing three new alleles of the A9.5 gene (supporting previous evidence that this gene is polymorphic and encodes a secretory protein with interleukin-4 as the major homologue), the observation that the most frequently detected haplotypes, in both wild-type and attenuated AlHV-1, were identical suggests that AlHV-1 has a slow molecular clock and that the attenuated strain was appropriate for vaccine development. In Chapter Five we present the first quantitative assessment of the annual MCF avoidance costs that Maasai pastoralists incur. In particular we estimated that as a result of MCF avoidance 64% of the total daily milk yield during the MCF season was not available to be used by the 81% of the family unit remaining at the permanent boma. This represents an upper-bound loss of approximately 8% of a household0s annual income. Despite these considerable losses we concluded that, given an incidence of fatal MCF in cattle living in wildebeest calving areas of 5% to 10%, if herd owners were to stop trying to avoid MCF by allowing their cattle to graze alongside wildebeest, any gains made through increased availability of milk, improved body condition and reduced energy demands would be offset by an increase in MCF-incidence. With the development of an effective vaccine, however, this alternative strategy might become optimal. The overall conclusion we draw therefore is that, despite the substantial costs incurred each year avoiding MCF, the partial protection afforded by the novel vaccine strategy is not sufficient to warrant a wholesale change in disease avoidance strategy. Nonetheless, even the partial protection provided by this vaccine could be of value to protect animals that cannot be moved, for example where some of the herd remain at the boma to provide milk or where land-use changes make traditional disease avoidance difficult. Furthermore, the vaccine may offer a feasible solution to some of the current land-use challenges and conflicts, providing a degree of protection to valuable livestock where avoidance strategies are not possible, but with less risk of precipitating the potentially damaging environmental consequences, such as overgrazing of highly nutritious seasonal pastures, that might result if herd owners decide they no longer need to avoid wildebeest.

Transmission electron tomography: quality assessment and enhancement for three-dimensional imaging of nanostructures

Nanotechnology has revolutionised humanity's capability in building microscopic systems by manipulating materials on a molecular and atomic scale. Nan-osystems are becoming increasingly smaller and more complex from the chemical perspective which increases the demand for microscopic characterisation techniques. Among others, transmission electron microscopy (TEM) is an indispensable tool that is increasingly used to study the structures of nanosystems down to the molecular and atomic scale. However, despite the effectivity of this tool, it can only provide 2-dimensional projection (shadow) images of the 3D structure, leaving the 3-dimensional information hidden which can lead to incomplete or erroneous characterization. One very promising inspection method is Electron Tomography (ET), which is rapidly becoming an important tool to explore the 3D nano-world. ET provides (sub-)nanometer resolution in all three dimensions of the sample under investigation. However, the fidelity of the ET tomogram that is achieved by current ET reconstruction procedures remains a major challenge. This thesis addresses the assessment and advancement of electron tomographic methods to enable high-fidelity three-dimensional investigations. A quality assessment investigation was conducted to provide a quality quantitative analysis of the main established ET reconstruction algorithms and to study the influence of the experimental conditions on the quality of the reconstructed ET tomogram. Regular shaped nanoparticles were used as a ground-truth for this study. It is concluded that the fidelity of the post-reconstruction quantitative analysis and segmentation is limited, mainly by the fidelity of the reconstructed ET tomogram. This motivates the development of an improved tomographic reconstruction process. In this thesis, a novel ET method was proposed, named dictionary learning electron tomography (DLET). DLET is based on the recent mathematical theorem of compressed sensing (CS) which employs the sparsity of ET tomograms to enable accurate reconstruction from undersampled (S)TEM tilt series. DLET learns the sparsifying transform (dictionary) in an adaptive way and reconstructs the tomogram simultaneously from highly undersampled tilt series. In this method, the sparsity is applied on overlapping image patches favouring local structures. Furthermore, the dictionary is adapted to the specific tomogram instance, thereby favouring better sparsity and consequently higher quality reconstructions. The reconstruction algorithm is based on an alternating procedure that learns the sparsifying dictionary and employs it to remove artifacts and noise in one step, and then restores the tomogram data in the other step. Simulation and real ET experiments of several morphologies are performed with a variety of setups. Reconstruction results validate its efficiency in both noiseless and noisy cases and show that it yields an improved reconstruction quality with fast convergence. The proposed method enables the recovery of high-fidelity information without the need to worry about what sparsifying transform to select or whether the images used strictly follow the pre-conditions of a certain transform (e.g. strictly piecewise constant for Total Variation minimisation). This can also avoid artifacts that can be introduced by specific sparsifying transforms (e.g. the staircase artifacts the may result when using Total Variation minimisation). Moreover, this thesis shows how reliable elementally sensitive tomography using EELS is possible with the aid of both appropriate use of Dual electron energy loss spectroscopy (DualEELS) and the DLET compressed sensing algorithm to make the best use of the limited data volume and signal to noise inherent in core-loss electron energy loss spectroscopy (EELS) from nanoparticles of an industrially important material. Taken together, the results presented in this thesis demonstrates how high-fidelity ET reconstructions can be achieved using a compressed sensing approach.