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Controlling mastitis in dairy herds relies on good prevention and detection methods. This dissertation describes two areas of research relating to mastitis control. In the first objective, the efficacy of 2 vaccines against Escherichia coli mastitis in mid-lactation dairy cows was evaluated. Secondly, in a series of 3 studies, milk and activity sensor data were used to derive models for clinical mastitis (CM) detection, and models were tested for their ability to indicate the causative pathogen type. Primiparous and multiparous animals were vaccinated with 1 of 2 commercially available J5 vaccines (V1 or V2) or served as unvaccinated controls (CTL). Intramammary challenge with E. coli approximately 84 d later resulted in few treatment differences in the clinical and behavioral responses, except that vaccinated cows exhibited fever (≥ 39.4 °C) 3 h earlier and laid down for longer periods than CTL. Although vaccinated cows had similar severity and duration of CM, V1 cows produced more serum IgG1 and IgG2 than V2 cows. Our results indicated that the effects of vaccination were diminished in mid-lactation, and that antibodies are not the limiting factor in defending against induced E. coli mastitis. Multiple regression models, incorporating the slope changes in relevant milk and activity sensor data, were developed to indicate all CM cases (ACM), or specifically, CM due to Gram-negative (GN) or Gram-positive (GP) bacteria. Gram-specific models had greater detection accuracy (> 80%) than the ACM model (75%) when evaluated using the model training dataset, but independent evaluation demonstrated reduced sensitivity (Se) of detecting CM by all models (GN, 62%, ACM, 56%, and GP, 32% Se). Data in the 3 d prior to CM were more important in detecting GN pathogens, whereas the best GP models incorporated changes more than 1 week prior to CM detection. Still, model performance was imperfect. Next, models were rederived from a dataset that better reflected the infection distribution of the herds its use was intended for. However, the Se of detecting CM in real-time, across 2 farms, was < 21% for all models, and categorization by Gram-status had no benefit. An insufficient number of CM cases was considered to contribute to the poor detection performance of models and limited repeatability across farms. Consequently, models derived in this study were inadequate for implementation as mastitis detection tools. In the future, development of new sensors and application of more sophisticated algorithms to the field of mastitis detection may improve the accuracy of models using sensor data. / Doctor of Philosophy / Mastitis is an important disease of dairy cattle that adversely affects animal welfare, productivity, and milk quality. Controlling mastitis in dairy herds relies on good prevention and detection methods. In this dissertation, we investigated two elements of mastitis control: 1) the effects of vaccination in protecting against mastitis, and 2) the ability of on-farm sensor data to detect clinical mastitis (CM) and indicate the causative pathogen type. Coliform bacteria commonly cause CM, and vaccination against these bacteria can reduce the severity of the disease. We evaluated the effect of 2 different vaccines on the clinical, behavioral, and immune response in cows with experimental mastitis caused by Escherichia coli. Our findings indicated that the effects of vaccination had diminished at the time of experimental mastitis, as vaccinated cows had no improvement in clinical recovery compared with unvaccinated controls. Although no clinical or behavioral differences were observed between the 2 different vaccines, the antibody response differed, suggesting that antibodies are not the key player underpinning the mechanisms of vaccination against induced coliform mastitis in mid-lactation. Rapid detection and diagnosis of mastitis is important to reduce effects on the cow, and to support decision making for the appropriate intervention. We aimed to develop and test mastitis detection models that utilized data collected by on-farm sensor technologies. Milk and activity parameters, which may be differentially affected by mastitis depending on the pathogen causing infection, were used in multiple regression models for detecting any CM case, or specifically CM caused by Gram-positive or Gram-negative bacteria. Gram-specific models were initially estimated to have > 80% accuracy in classifying cows with and without mastitis, but further validation demonstrated that the models were not repeatable when tested independently. Subsequently, models that were more suited to the farms they were to be implemented on were developed, and tested, revealing limited performance in detecting any case of CM, or CM due to the Gram-specific pathogens. Model derivation was limited by an insufficient number of CM cases to represent the variation in different cases of CM within the Gram-positive and Gram-positive classifications. Although our models did not show promise as a mastitis detection tool, milk and activity data may be incorporated with other sensor data for improved detection and diagnosis of mastitis.

An important aspect of systems biology is the elucidation of the protein-protein interactions (PPIs) that control important biological processes within a cell and between organisms. In particular, at the cellular and molecular level, interactions between a pathogen and its host play a vital role in initiating infection and a successful pathogenesis. Despite recent successes in the advancement of the systems biology of model organisms to understand complex diseases, the analysis of infectious diseases at the systems-level has not received as much attention. Since pathogen related disease is responsible for millions of deaths and billions of dollars in damage to crops and livestock, understanding the mechanisms employed by pathogens to infect their hosts is critical in the development of new and effective therapeutic strategies. The research presented here is one of the first computational approaches to studying host-pathogen PPI networks. This dissertation has two main aims. First, we discuss analytical tools for studying host-pathogen networks to identify common pathways perturbed and manipulated by pathogens. We present the first global comparison of the host-pathogen PPI networks of 190 different pathogens and their interactions with human proteins. We also present the construction and analysis of three highly infectious human-bacterial PPI networks: <i>Bacillus anthracis</i>, <i>Francislla tularensis</i>, and <i>Yersinia pestis</i>. The second aim of the research presented here is the development of predictive models for identifying PPIs between host and pathogen proteins. We present two methods: (i) a domain-based approach that uses frequency of domain-pairs in intra-species PPIs, and (ii) a supervised machine learning method that is trained on known inter-species PPIs. The techniques developed in this dissertation, along with the informative datasets presented, will serve as a foundation for the field of computational pathosystems biology. / Ph. D.

Chytridiomycosis is a fungal skin disease in amphibians that is primarily caused by Batrachochytrium dendrobatidis (Bd). We analyzed whole genome sequences of 40 bacterial isolates that had been previously cultured from the skin of four amphibian species from Virginia, USA, and tested for their ability to inhibit Bd growth via an in vitro challenge assay. These 40 isolates spanned 11 families and 13 genera. The aim of this study was to identify genomic differences among the amphibian skin bacterial isolates and generate hypotheses about possible differences that could contribute to variation in their ability to inhibit the growth of Bd. We identified sixty-five gene families that were present in all 40 isolates. We also looked for the presence of biosynthetic gene clusters. While this set of isolates contained a wide variety of biosynthetic gene clusters, the two most abundant clusters with potential anti-fungal activity were siderophores (N=17) and Type III polyketide synthases (N=20). We then analyzed the isolates belonging to the phylum Proteobacteria in more detail. We identified 197 gene families that were present in all 22 Proteobacteria. We examined various subsets of the Proteobacteria for genes for specific compounds with known activity against fungi, including chitinase and violacein. We identified a difference in the number, as well as amino acid sequences, of predicted chitinases found in two isolates belonging to the genus Agrobacterium that varied in their inhibition of Bd. After examining the annotated genomes, we identified a predicted chitinase in a Sphingomonas isolate that inhibited the growth of Bd that was absent from the five Sphingomonas isolates that did not inhibit Bd growth. The genes vioA, vioB, vioC, vioD and vioE are necessary to produce violacein, a compound which inhibits the growth of Bd. Differences in these genes were identified in three out of the four Janthinobacterium isolates. Of these three isolates, two showed strong inhibition of Bd growth, while the third inhibited Bd growth to a lesser extent. Using comparative genomics, we generated several testable hypotheses about differences among bacterial isolates that could contribute to variation in ability to inhibit Bd growth. Further work is necessary to test the various mechanisms utilized by amphibian skin bacterial isolates to inhibit Bd. / Master of Science / Many amphibian population declines around the world have been caused by chytridiomycosis, a skin disease. This disease is caused by the fungus Batrachochytrium dendrobatidis (Bd). The skin of amphibians is also home to many bacteria that can provide important functions for the amphibian host, like preventing infection by Bd. To understand how these bacteria might provide protection, we examined the entire genomes of 40 bacterial isolates that reside on the skin of four amphibian species from Virginia, USA. These bacteria were previously tested for their ability to prevent Bd growth and 40 of them were chosen for sequencing based on selecting closely related isolates that varied in their ability to inhibit Bd growth. This allowed us to compare their genomes and generate hypotheses about possible genomic differences that could contribute to the variation in Bd growth inhibition. We identified sixty-five gene families that were present in all 40 bacteria. We also looked for sets of genes (biosynthetic gene clusters) that are known to produce secondary metabolites, which are compounds that can include antifungals. The two most abundant clusters we identified that had the potential to produce compounds that inhibit fungal growth were siderophores and Type III polyketide synthases. We then looked for genes that were not part of biosynthetic gene clusters that could produce specific compounds that can inhibit Bd growth, such as chitinase and violacein. We found variation in chitinase genes in several isolates that seemed to be associated with the ability to inhibit Bd growth. In addition, there were some differences in violacein genes that should be examined more in future studies. Overall, we suggest that using comparative genomic approaches can be valuable for identifying key bacterial functions in the microbiome.

Three studies relating to the vector competency of several species of ticks and <i>Simulium</i> spp. (blackflies) for <i>Ehrlichia risticii</i>, causative agent of Potomac horse fever (PHF) and <i>Amblyomma variegatum</i> for <i>Cowdria ruminantium</i>, causative agent of heartwater, are described. <i>Dermacentor variabilis, Rhipicephalus sanguineus, Amblyomma americanum and Ixodes scapularis</i> ticks were investigated for their ability to acquire and transmit PHF. Larval and nymphal ticks were exposed to <i>E. risticii</i> by feeding on mice inoculated with the organism. Molted exposed ticks were then allowed to feed on susceptible ponies or mice and were examined by light and electron microscopy. No evidence of transmission, either clinically or by seroconversion in mice or ponies was observed. Blackflies (<i>Simulium</i> spp.) were trapped in an area endemic for PHF and inoculated into mice in an attempt to demonstrate <i>I. risticii</i>. No evidence of seroconversion by mice to <i>E. risticii</i> was observed. Two laboratory colonies of <i>Amblyomma variegatum</i> ticks were investigated for their ability to acquire and transmit C. <i>ruminantium</i> and was febrile. Nymphs from both laboratory groups were simultaneously fed on a goat that had been infected with C. <i>ruminantium</i> and was febrile. Engorged nymphs from both groups were replete from feeding on three consecutive days. Nymphs from both groups were then incubated under identical conditions until molting. / Ph. D.

Anaerobic digestion and struvite precipitation are two effective ways of treating dairy manure for recovering biogas and phosphorus. Anaerobic digestion of dairy manure is commonly limited by slow fiber degradation, while one of the limitations to struvite precipitation is the availability of orthophosphate. The aim of this work was to study the use of microwave-based thermochemical pretreatment to simultaneously enhance manure anaerobic digestibility (through fiber degradation) and struvite precipitation (through phosphorus solubilization). Microwave heating combined with different chemicals (NaOH, CaO, H₂SO₄, or HCl) enhanced solubilization of manure and degradation of glucan/xylan in dairy manure. However, sulfuric acid-based pretreatment resulted in a low anaerobic digestibility, probably due to the sulfur inhibition and side reactions. The pretreatments released 20-40% soluble phosphorus and 9-14% ammonium. However, CaO-based pretreatment resulted in lower orthophosphate releases and struvite precipitation efficiency as calcium reacts with phosphate to form calcium phosphate. Collectively, microwave heating combined with NaOH or HCl led to a high anaerobic digestibility and phosphorus recovery. Using these two chemicals, the performance of microwave- and conventional-heating in thermochemical pretreatment was further compared. The microwave heating resulted in a better performance in terms of COD solubilization, glucan/xylan reduction, phosphorus solubilization and anaerobic digestibility. Lastly, temperature and heating time used in microwave treatment were optimized. The optimal values of temperature and heating time were 147°C and 25.3 min for methane production, and 135°C and 26 min for orthophosphate release, respectively. Applying manure or slurry directly to the land can contribute to pathogen contamination of land, freshwater and groundwater. Thus it is important to study the fate of pathogens in diary manure anaerobic digestion systems. The goal of the project was to establish a molecular based quantitative method for pathogen identification and quantification, compare the molecular based method with culture based method and study pathogen fate in dairy manure and different anaerobic digesters. Result showed that molecular based method detected more E.coli than the culture based method with less variability. Thermophilic anaerobic digestion can achieve more than 95% pathogen removal rate while mesophilic anaerobic digester had increased E.coli number than fresh manure, indicating temperature is a key factor for pathogen removal. In general, the overall goal of the study is to develop an integrated dairy manure treatment system. The microwave based pretreatment enhanced the subsequent biogas production and struvite precipitation, and the molecular tool based method provided a more precise and faster way to study the pathogen fate in various anaerobic digestions. / Ph. D.

Allergic inflammatory disorders of the airway like asthma and atopic asthma are complex, often long-term diseases that generate large public health and socioeconomic footprints especially in developed countries like US, UK and Australia. In 2009, approximately 8.2%, 24.6 million people in United States were affected by asthma. Currently 235 million people are affected by asthma worldwide and about 90% of those have allergic (atopic) asthma. An important factor in patients with allergic respiratory tract diseases is sensitization to fungi. Other risk factors for asthma include inhaled allergens that irritate the airways. Up to 70% of mold allergic patients have skin test reactivity to Alternaria. Alta1, an allergen produced by A. alternata also produces a prolonged and intense IgE mediated reaction in sensitized patients. Therefore A. alternata is not only a risk factor in development of asthma but also can lead to exacerbation of severe and potentially lethal asthma than any other fungus. Despite the well-documented clinical importance of Alternaria in allergic airway diseases, little knowledge exists about the role of individual fungal genes and gene products in theses pathological states besides a small repertoire of allergens and proteolytic enzymes. Moreover, the importance of small, secreted molecules of fungal origin has not been explored whatsoever in regards to immune responses triggered by Alternaria. This study addresses the hypothesis that Alternaria derived small molecule's have immune modulatory properties. A major thrust of this project was to assess the role of Alternaria secondary metabolites that are synthesized by genes called polyketide synthases (PKS) in immune responses of lung epithelial cells. / Master of Science

Anthropozoonotic diseases, defined as infectious diseases caused by pathogens transmitted from humans to wildlife, pose a significant health threat to wildlife populations. Many of these pathogens are also able to move from wildlife reservoirs to humans, termed zoonotic diseases, creating the possibility for bi-directional transmission between humans and wildlife. Recent studies show that a significant proportion of emerging infectious diseases in humans originate in wildlife reservoirs and that the frequency of emergence is increasing, yet the specific transmission pathways still remain speculative in most cases. Human fecal waste is persistent across human-modified landscapes and has been identified as a potential source of disease exposure for wildlife populations living near humans. As part of a long-term study of banded mongoose (Mungos mungo) that live in close association with humans and human fecal waste I used Escherichia coli and banded mongoose (Mungos mungo) for evaluating exchange of fecal waste-borne microorganisms at the human-wildlife interface. Antibiotic resistance was found in 57.5% ° 10.3% (n=87) of mongoose fecal samples and 37.2% ° 5.9% of isolates (n=253). Multidrug resistance was detected in 13.8% ° 4.2% of isolates (n=253). Mongoose and human fecal waste isolates consistently clustered together in phylogenetic analyses and statistical analysis of genetic variation showed no significant differences (p=0.18) between E. coli from human and mongoose populations. These results suggest that human fecal waste contamination is an important mechanism for the transmission of pathogens to both humans and animals, including the spread of antibiotic resistance in the environment, an emerging global health threat. / Master of Science

The interaction between Arabidopsis and its natural downy mildew pathogen, Hyaloperonospora arabidopsidis (Hpa), provides a model for understanding how oomycetes colonize plants. Hpa is a model organism for many highly destructive oomycete pathogens and transcriptomics of this interaction have been well-documented. However, the material in these studies has been derived from infected leaves that contain a mix of pathogen-proximal and pathogen-distal plant cells. The most direct interactions between Arabidopsis and Hyaloperonospora arabidopsidis occur in haustoriated cells- where the pathogen can secrete effectors and acquire nutrients needed for successful colonization and reproduction. These cells are difficult to isolate due to their limited number and ephemeral nature. I have developed a method to isolate the translatome (i.e., mRNAs associated with ribosomes) of pathogen-proximal cells. This method utilizes translating ribosome immuno-purification technology (TRAP), regulated by both pathogen-responsive and tissue-specific promoters, to isolate mRNAs that are being translated in pathogen-proximal cells. Compared to "bulk" transcriptomics of material isolated from homogenized leaves, this method will enrich for transcripts that are differentially expressed, and translated, in pathogen-proximal cells. From this method, RNA was isolated in amount and quality sufficient for sequencing. This sequencing data will enable the discovery of plant genes that may be manipulated by the pathogen to suppress defense responses and extract nutrients. / Ph. D. / The interactions between plants and the pathogens that feed on them are complex and at times difficult to study. Among the many different types of plant pathogens, oomycetes (a class of fungus-like organisms) are especially destructive. Using Arabidopsis and its natural downy mildew pathogen, Hyaloperonospora arabidopsidis (Hpa) as model for understanding how oomycetes colonize plants, I hope to learn more about plant-pathogen interactions. Hpa is a model organism for many highly destructive oomycete pathogens and several aspects of this interaction have been well-documented. However, the material in these studies has been derived from infected leaves that contain a mix of plant cells that are both in direct contact with the pathogen, or from uninfected areas of the plant. The most direct interactions between Arabidopsis and Hpa occur in cells that have been invaginated with a pathogen feeding structure called a haustorium. These cells are difficult to isolate due to their limited number and ephemeral nature. I have developed a method to isolate the translatome (i.e., mRNAs that are being translated by and are associated with ribosomes) of pathogen-proximal cells. This method utilizes translating ribosome immuno-purification technology (TRAP), regulated by both pathogen-responsive and tissue-specific promoters, to isolate mRNAs that are being translated in pathogen-proximal cells. Compared to “bulk” transcriptomics of material isolated from homogenized leaves, this method will enrich for transcripts that are differentially expressed, and translated, in pathogen-proximal cells. From this method, RNA was isolated in amount and quality sufficient for sequencing. This sequencing data will enable the discovery of plant genes that may be manipulated by the pathogen to suppress defense responses and extract nutrients.