Campylobacter species in dogs and cats and significance to public health in New Zealand : a thesis in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Veterinary Science at Massey University, Palmerston North, New Zealand

Campylobacter spp. are a major cause of bacterial gastroenteritis in people in the developed world, including New Zealand. Many sources and transmission routes exist, as these bacteria are common in animals and the environment. C. jejuni is most frequently associated with poultry whereas C. upsaliensis and C. helveticus with dogs and cats, respectively. Published data on Campylobacter in dogs and cats in New Zealand and on the pathogenic potential of C. upsaliensis and C. helveticus are very limited. This thesis investigated the prevalence of Campylobacter spp. in household dogs and cats in Manawatu region, New Zealand, and in raw meat pet food commercially available in Palmerston North, New Zealand. Five Campylobacter spp. were isolated and the prevalence rates were significantly influenced by the culture methods used. C. upsaliensis and C. helveticus were most frequently detected from dogs and cats, respectively and C. jejuni in pet food samples. An expanded panel of culture methods was used to screen working farm dogs and their home-kill raw meat diet in Manawatu. This study reported three Campylobacter spp. and Helicobacter winghamensis as being isolated from dogs for the first time. The culture methods were again shown to bias the prevalence estimates. The isolates of C. upsaliensis and C. helveticus from the household pets study and C. hyointestinalis from locally farmed deer were used in a study to investigate the analytical sensitivity in spiked human clinical faecal samples using the ProSpecTTM Campylobacter Microplate Assay test that was developed for detection of C. jejuni/coli. The results showed the ability of the test to detect all three species and showed the influence of bacterial dose, faecal consistency and of the individual faecal samples on the test results. Further studies investigated the pathogenic potential of C. upsaliensis and C. helveticus in comparison to C. jejuni using an insect model of disease, Galleria mellonella, and whole-genome analyses, respectively. The results of the survival analysis in the G. mellonella study indicated that C. upsaliensis and C. helveticus have pathogenic potential, but to a lesser extent than C. jejuni. Additionally, several variables of experimental design were shown to significantly influence estimates of hazard rates in survival analysis. Whole genome analyses also showed indications of the pathogenic potential of C. upsaliensis and C. helveticus relative to C. jejuni, and how it varies between and within species in association with the core and accessory genomes, functional gene content profiles, and documented and predicted pathogenic proteins. This thesis has furthered our understanding of the epidemiology, detection, and pathogenicity of Campylobacter spp. in dogs, cats and humans, and confirmed raw meat animal food as a potential source of Campylobacter spp. for both people and animals

Understanding the Evolutionary Relationships and Major Traits of \u3cem\u3eBacillus\u3c/em\u3e through Comparative Genomics

Background: The presence of Bacillus in very diverse environments reflects the versatile metabolic capabilities of a widely distributed genus. Traditional phylogenetic analysis based on limited gene sampling is not adequate for resolving the genus evolutionary relationships. By distinguishing between core and pan-genome, we determined the evolutionary and functional relationships of known Bacillus. Results: Our analysis is based upon twenty complete and draft Bacillus genomes, including a newly sequenced Bacillus isolate from an aquatic environment that we report for the first time here. Using a core genome, we were able to determine the phylogeny of known Bacilli, including aquatic strains whose position in the phylogenetic tree could not be unambiguously determined in the past. Using the pan-genome from the sequenced Bacillus, we identified functional differences, such as carbohydrate utilization and genes involved in signal transduction, which distinguished the taxonomic groups. We also assessed the genetic architecture of the defining traits of Bacillus, such as sporulation and competence, and showed that less than one third of the B. subtilis genes are conserved across other Bacilli. Most variation was shown to occur in genes that are needed to respond to environmental cues, suggesting that Bacilli have genetically specialized to allow for the occupation of diverse habitats and niches. Conclusions: The aquatic Bacilli are defined here for the first time as a group through the phylogenetic analysis of 814 genes that comprise the core genome. Our data distinguished between genomic components, especially core vs. pan-genome to provide insight into phylogeny and function that would otherwise be difficult to achieve. A phylogeny may mask the diversity of functions, which we tried to uncover in our approach. The diversity of sporulation and competence genes across the Bacilli was unexpected based on previous studies of the B. subtilis model alone. The challenge of uncovering the novelties and variations among genes of the non-subtilis groups still remains. This task will be best accomplished by directing efforts toward understanding phylogenetic groups with similar ecological niches

Characterisation of dairy strains of Geobacillus stearothermophilus and a genomics insight into its growth and survival during dairy manufacture : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Microbiology at Massey University, Palmerston North, New Zealand

The thermophilic bacilli, such as G. stearothermophilus, are an important group of contaminants in the dairy industry. Although these bacilli are generally not pathogenic, their presence in dairy products is an indicator of poor hygiene and high numbers are unacceptable to customers. In addition, their growth may result in milk product defects caused by the production of acids or enzymes, potentially leding to off-flavours. These bacteria are able to grow in sections of dairy manufacturing plants where temperatures reach 40 – 65 °C. Furthermore, because they are spore formers, they are difficult to eliminate. In addition, they exhibit a fast growth rate and tend to readily form biofilms. Many strategies have been tested to prevent the formation of thermophilic bacilli biofilms in dairy manufacture, but with limited success. This is, in part, because little is known about the diversity of strains found in dairy manufacture, the structure of thermophilic bacilli biofilms and how these bacteria have adapted to grow in a dairy environment. In Chapters 2 and 3, phenotypic approaches were taken to understand the diversity of strains within a manufacturing plant. Specifically in Chapter 2, strains of the most dominant thermphilic bacilli, G. stearothermophilus, were isolated from the surface of various locations within the evaporator section and ten strains were evaluated for different phenotypic characteristics. Biochemical profiling, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and fatty profiling demonstrated that the population was diverse. In Chapter 3, it was shown that the same ten strains varied in their ability to form biofilms and produce spores. Three strains of G. stearothermophilus, A1, P3 and D1, were selected for further analysis. SEM demonstrated that there were differences in biofilm morphologies between the three strains, particularly D1 versus the other two strains, A1 and P3. In Chapters 4, 5 and 6 a comparative genomics approach was taken to determine how these bacteria are able to grow and survive within a dairy manufacturing environment, as well as how they differ from other strains of Geobacillus. In Chapter 4 draft genome sequences were generated for three strains of G.stearothermophilus. Identification of a putative lactose operon in the three dairy strains provided evidence of dairy adaptation. In Chapter 5 a phylogenomics approach was taken to resolve relationships within the Geobacillus genus and to identify differences within the G. stearothermophilus group itself. Finally in Chapter 6 comparison with the model organism B. subtilis, gave a genomics insight into the potential mechanisms of sporulation for Geobacillus spp

Comparative Genomics of a Parthenogenesis-Inducing Wolbachia Symbiont.

Wolbachia is an intracellular symbiont of invertebrates responsible for inducing a wide variety of phenotypes in its host. These host-Wolbachia relationships span the continuum from reproductive parasitism to obligate mutualism, and provide a unique system to study genomic changes associated with the evolution of symbiosis. We present the genome sequence from a parthenogenesis-inducing Wolbachia strain (wTpre) infecting the minute parasitoid wasp Trichogramma pretiosum The wTpre genome is the most complete parthenogenesis-inducing Wolbachia genome available to date. We used comparative genomics across 16 Wolbachia strains, representing five supergroups, to identify a core Wolbachia genome of 496 sets of orthologous genes. Only 14 of these sets are unique to Wolbachia when compared to other bacteria from the Rickettsiales. We show that the B supergroup of Wolbachia, of which wTpre is a member, contains a significantly higher number of ankyrin repeat-containing genes than other supergroups. In the wTpre genome, there is evidence for truncation of the protein coding sequences in 20% of ORFs, mostly as a result of frameshift mutations. The wTpre strain represents a conversion from cytoplasmic incompatibility to a parthenogenesis-inducing lifestyle, and is required for reproduction in the Trichogramma host it infects. We hypothesize that the large number of coding frame truncations has accompanied the change in reproductive mode of the wTpre strain

Codon Bias Patterns of E.coliE.coli's Interacting Proteins

Synonymous codons, i.e., DNA nucleotide triplets coding for the same amino acid, are used differently across the variety of living organisms. The biological meaning of this phenomenon, known as codon usage bias, is still controversial. In order to shed light on this point, we propose a new codon bias index, $CompAI$, that is based on the competition between cognate and near-cognate tRNAs during translation, without being tuned to the usage bias of highly expressed genes. We perform a genome-wide evaluation of codon bias for $E.coli$, comparing $CompAI$ with other widely used indices: $tAI$, $CAI$, and $Nc$. We show that $CompAI$ and $tAI$ capture similar information by being positively correlated with gene conservation, measured by ERI, and essentiality, whereas, $CAI$ and $Nc$ appear to be less sensitive to evolutionary-functional parameters. Notably, the rate of variation of $tAI$ and $CompAI$ with ERI allows to obtain sets of genes that consistently belong to specific clusters of orthologous genes (COGs). We also investigate the correlation of codon bias at the genomic level with the network features of protein-protein interactions in $E.coli$. We find that the most densely connected communities of the network share a similar level of codon bias (as measured by $CompAI$ and $tAI$). Conversely, a small difference in codon bias between two genes is, statistically, a prerequisite for the corresponding proteins to interact. Importantly, among all codon bias indices, $CompAI$ turns out to have the most coherent distribution over the communities of the interactome, pointing to the significance of competition among cognate and near-cognate tRNAs for explaining codon usage adaptation

Identification of Orthologous Gene Groups Using Machine Learning

Identification of genes that show similarity between different organisms, a.k.a orthologous genes, is an open problem in computational biology. The purpose of this thesis is to create an algorithm to group orthologous genes using machine learning. Following an optimization step to find the best characterization based on training data, we represented sequences of genes or proteins with kmer vectors. These kmer vectors were then clustered into orthologous groups using hierarchical clustering. We optimized the clustering phase with the same training data for the method and parameter selection. Our results indicated that use of protein sequences with k=2 and scaling the data for each kmer provided the best results. We employed Pearson’s correlation as the distance metric and used complete linkage in the agglomeration step. The number of clusters are calculated based on four different approaches that evaluates optimum number of clusters. This algorithm was pitted against OrthoDB which is an orthologous gene grouping algorithm that has been proven to work well. The results show that when small datasets were used, our algorithm performed better than OrthoDB. When larger genome-level datasets were used, OrthoDB outperformed our algorithm as long as the input data to OrthoDB was divided based on organism count. Our algorithm has an advantage over OrthoDB in that the data doesn’t have to be divided by organism; it can be given as one file. The proposed algorithm runs much faster than OrthoDB and is the first approach, to the best of our knowledge, that uses unsupervised machine learning techniques that does not rely on sequence alignment or phylogeny to identify orthologues genes. Overall, our algorithm provides a novel solution that is fast, practical, and unlike existing approaches can be applied to data sets such as metagenomics where the underlying number of organisms is unknown. Adviser: Hasan H. Ot

Clusters of orthologous genes for 41 archaeal genomes and implications for evolutionary genomics of archaea

<p>Abstract</p> <p>Background</p> <p>An evolutionary classification of genes from sequenced genomes that distinguishes between orthologs and paralogs is indispensable for genome annotation and evolutionary reconstruction. Shortly after multiple genome sequences of bacteria, archaea, and unicellular eukaryotes became available, an attempt on such a classification was implemented in Clusters of Orthologous Groups of proteins (COGs). Rapid accumulation of genome sequences creates opportunities for refining COGs but also represents a challenge because of error amplification. One of the practical strategies involves construction of refined COGs for phylogenetically compact subsets of genomes.</p> <p>Results</p> <p>New Archaeal Clusters of Orthologous Genes (arCOGs) were constructed for 41 archaeal genomes (13 Crenarchaeota, 27 Euryarchaeota and one Nanoarchaeon) using an improved procedure that employs a similarity tree between smaller, group-specific clusters, semi-automatically partitions orthology domains in multidomain proteins, and uses profile searches for identification of remote orthologs. The annotation of arCOGs is a consensus between three assignments based on the COGs, the CDD database, and the annotations of homologs in the NR database. The 7538 arCOGs, on average, cover ~88% of the genes in a genome compared to a ~76% coverage in COGs. The finer granularity of ortholog identification in the arCOGs is apparent from the fact that 4538 arCOGs correspond to 2362 COGs; ~40% of the arCOGs are new. The archaeal gene core (protein-coding genes found in all 41 genome) consists of 166 arCOGs. The arCOGs were used to reconstruct gene loss and gene gain events during archaeal evolution and gene sets of ancestral forms. The Last Archaeal Common Ancestor (LACA) is conservatively estimated to possess 996 genes compared to 1245 and 1335 genes for the last common ancestors of Crenarchaeota and Euryarchaeota, respectively. It is inferred that LACA was a chemoautotrophic hyperthermophile that, in addition to the core archaeal functions, encoded more idiosyncratic systems, e.g., the CASS systems of antivirus defense and some toxin-antitoxin systems.</p> <p>Conclusion</p> <p>The arCOGs provide a convenient, flexible framework for functional annotation of archaeal genomes, comparative genomics and evolutionary reconstructions. Genomic reconstructions suggest that the last common ancestor of archaea might have been (nearly) as advanced as the modern archaeal hyperthermophiles. ArCOGs and related information are available at: <url>ftp://ftp.ncbi.nih.gov/pub/koonin/arCOGs/</url>.</p> <p>Reviewers</p> <p>This article was reviewed by Peer Bork, Patrick Forterre, and Purificacion Lopez-Garcia.</p

Towards a genome-wide transcriptogram: the Saccharomyces cerevisiae case

A genome modular classification that associates cellular processes to modules could lead to a method to quantify the differences in gene expression levels in different cellular stages or conditions: the transcriptogram, a powerful tool for assessing cell performance, would be at hand. Here we present a computational method to order genes on a line that clusters strongly interacting genes, defining functional modules associated with gene ontology terms. The starting point is a list of genes and a matrix specifying their interactions, available at large gene interaction databases. Considering the Saccharomyces cerevisiae genome we produced a succession of plots of gene transcription levels for a fermentation process. These plots discriminate the fermentation stage the cell is going through and may be regarded as the first versions of a transcriptogram. This method is useful for extracting information from cell stimuli/responses experiments, and may be applied with diagnostic purposes to different organisms