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Staphylococcus aureus is a notorious human pathogen associated with severe nosocomial and community-acquired infections. In addition, S. aureus is a major cause of animal diseases including skeletal infections of poultry and bovine and ovine mastitis, which are a large economic burden on the broiler chicken and dairy farming industries. The population structure of S. aureus associated with humans has been well studied. However, despite the prevalence of S. aureus infections in broiler flocks, our understanding of the diversity of poultry S. aureus is very limited. In this study, multilocus sequence typing was performed on 48 strains of S. aureus isolated from broiler chickens on farms in 6 countries on 4 different continents, in addition to 9 isolates from different species of reared game and wild birds in Scotland. This was followed by fine scale population genetic analysis of a subset of strains by single nucleotide polymorphism discovery. These studies reveal that the majority of S. aureus isolates from broiler chickens are the descendants of a single human-to-poultry host jump by a subtype of the worldwide human clonal complex 5 (CC5) clonal lineage unique to Poland. In contrast to human subtypes of the CC5 radiation, which demonstrate strong geographic clustering, the poultry CC5 clade was distributed in different continents, consistent with wide dissemination via the global poultry industry distribution network. In order to establish the molecular basis for avian specificity in the CC5 poultry clade, whole genome sequences were determined for a sequence type 5 (ST5) poultry isolate from Ireland and a basal human associated ST5 MRSA strain from Poland. Sequence analysis revealed that the poultry CC5 clade has undergone genetic diversification from its human progenitor strain by acquisition of novel mobile genetic elements from an avian-specific accessory gene pool, and by the inactivation of several proteins important for human disease pathogenesis. In order to examine the importance of positive selection in the adaptation of S. aureus to poultry and for S. aureus evolution, in general, genome-wide analysis of the ratio of synonymous to non-synonymous substitutions was performed on 30 strains from 3 humans and other animals, from diverse lineages. Positive selection has affected proteins from the majority of functional categories, resulting in diversification of the proteome, metabolome and replication capacity, which may be associated with adaptation of S. aureus to diverse environments. For several proteins, an elevated rate of non-synonymous substitutions unique to animal-associated lineages is consistent with a role for these proteins in host adaptation. Taken together, the results of this study have determined the evolutionary history of a major new animal pathogen that has undergone rapid avian host adaptation and intercontinental dissemination. The data highlight the importance of gene acquisition and loss and positive selection in the adaptive evolution of S. aureus.

Marek’s disease virus (MDV), the causative agent of Marek’s disease in chicken, is an important oncogenic avian pathogen which leads to world-wide economic losses in the poultry industry. It targets the chicken's immune system by initially causing a lytic infection in B-lymphocytes in lymphoid organs (spleen, bursa of Fabricius and thymus), followed by a latent infection of T-lymphocytes, which may lead to tumour formation. Despite the presence of well-established vaccination programs against MDV, it is still a major concern for the poultry industry due to the emergence of more virulent strains. As MDV is also considered an excellent model for herpesvirusinduced oncogenicity and immunosuppression, a better understanding of its pathogenesis, including the functional roles of individual MDV proteins, is of both biomedical as well as economical importance. All open reading frames (ORFs) of the CVI988 vaccine strain and the RB1B virulent strain were PCR-amplified from BAC DNA and cloned into the pDONR 207 entry vector by recombinatorial cloning (Gateway® system). Subsequently, all ORFs were subcloned into the yeast-two-hybrid (Y2H) vectors pGBKT7–DEST (bait) and pGADT7-DEST (prey), as well as other expression vectors. The Y2H bait and prey vector clone collections were transformed into the yeast strains AH109 and Y187, respectively. More than 140 ORFs, or ORF fragments, were analysed against each other in a comprehensive Y2H assay. Of > 20.000 interactions tested, 435 positive interactions between 115 ORFs were observed. Several of these interactions have previously been reported in other species of herpesvirus indicating that they may be conserved within the family. A subset of the positive interactions were confirmed using co-immunoprecipitation and LUMIER pull-down assays as a second independent assay. In the second part of the project all MDV proteins were tested for their ability to inhibit the chicken interferon-alpha (chIFN-α)-induced immune response. In functional luciferase reporter assay with a chicken Mx1 promoter containing an interferon stimulated responsive element (ISRE), four MDV-encoded chIFN-α inhibitors were identified, including UL12, UL26, UL50, and Meq, the main MDV oncoprotein. Both isoforms Meq and L-Meq derived from the oncogenic and the non-oncogenic vaccine strain, respectively, similarly inhibited the interferon response in a dose-dependent way, and Meq deletion mutants revealed that the Cterminal, proline-rich transactivating domain is not required for this inhibitory effect. In transient transfection experiments, Meq induced a dose-dependent proteasomal degradation of the chicken interferon regulatory factor 7 (chIRF7), which is required for chIFN-α- induced activation of ISRE. Over-expression of chIRF7 lead to a dosedependent degradation of Meq and its accumulation in the cytoplasm, suggesting that proteasomal degradation of both Meq and chIRF-7 is linked. Consistent with these findings, MDV deletion mutant lacking both copies of the Meq gene was more sensitive to chIFN-α treatment compared to wild-type virus.

To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.

Au, Chun Hang. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 124-146). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

One of the key research topics of post-genome study is annotation of the gene with regards to specific function and biological processes. This can help us to understand the precise role that a gene or a group of genes carries. In this thesis, I developed techniques to automatically annotate genes on single gene and a group of genes levels. It is shown that these techniques improve our understanding of biological systems/diseases, and will aid drug discovery. In the first project, I attempted to achieve precise annotation for single genes. In the second and third projects, I performed annotations of a group of genes using pathway knowledge. I examined this problem from supervised and unsupervised learning aspects, respectively. The main contributions of the work are organized as follows: In gene annotation project, I built up an automated scheme to reconcile the term differences arising from the different automated annotation services. The method leaves less than 20% of the annotations for manual work. The generalization performance across other species is of a similar standard, again leaving less than 20% of the annotations for manual inspection. In addition, less than 10% of the results have different functions from EcoCyc results in E.coli genome annotation task. Overall, this method can significantly reduce human effort involvement (6 months’ work by several biologists for a bacterial genome) to resolve inconsistent gene annotations. Then I started from the current limitations of pathway analysis and presented a novel approach for pathway discovery. Enrichment analysis is the most popular approach to map gene expression profiling from genes to biological pathways. It is a powerful tool to identify pathways enriching of differentially expressed gene; however, it is unable to discover active/inhibitive pathways. In this study, I attempted to resolve this issue by integrative classification of KEGG and TF gene sets. I assumed that the pathways with good classification performance should be considered as the active/inhibitive pathways. Based on this hypothesis, I built up a generic approach to incorporate two types of biological data for active pathway discovery. The experimental results show that integration of transcription factor data boosts classification performance. In addition, this method identified relevant biological pathways, which are highly associated with tumour genesis and development. But they are ignored by Gene Set Enrichment Analysis, such as cancer pathway, inflammation and metabolic pathways. Furthermore, this method achieves comparable classification performance with the best-reported results. Lastly, I performed subtyping analysis of Rheumatoid Arthritis patients based on gene expression profiling. I revalidated the two clusters of patients based on two independent cohorts. The experimental results indicate that the subgroup structure does not correspond to the drug response status. In addition, I developed a pathway subtyping approach and achieved the same number of clusters as gene-level clustering results. The pathway clustering results show that one group of the patients has high proliferation and low inflammation response, while the other group has the reverse trend. It suggests that designing drugs with better trade-off between anti-inflammation and anti-proliferation for specific subgroup of patients may achieve better clinical outcomes.

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