Phylogeographic reconstruction of a bacterial species with high levels of lateral gene transfer

Background Phylogeographic reconstruction of some bacterial populations is hindered by low diversity coupled with high levels of lateral gene transfer. A comparison of recombination levels and diversity at seven housekeeping genes for eleven bacterial species, most of which are commonly cited as having high levels of lateral gene transfer shows that the relative contributions of homologous recombination versus mutation for Burkholderia pseudomallei is over two times higher than for Streptococcus pneumoniae and is thus the highest value yet reported in bacteria. Despite the potential for homologous recombination to increase diversity, B. pseudomallei exhibits a relative lack of diversity at these loci. In these situations, whole genome genotyping of orthologous shared single nucleotide polymorphism loci, discovered using next generation sequencing technologies, can provide very large data sets capable of estimating core phylogenetic relationships. We compared and searched 43 whole genome sequences of B. pseudomallei and its closest relatives for single nucleotide polymorphisms in orthologous shared regions to use in phylogenetic reconstruction. Results Bayesian phylogenetic analyses of >14,000 single nucleotide polymorphisms yielded completely resolved trees for these 43 strains with high levels of statistical support. These results enable a better understanding of a separate analysis of population differentiation among >1,700 B. pseudomallei isolates as defined by sequence data from seven housekeeping genes. We analyzed this larger data set for population structure and allele sharing that can be attributed to lateral gene transfer. Our results suggest that despite an almost panmictic population, we can detect two distinct populations of B. pseudomallei that conform to biogeographic patterns found in many plant and animal species. That is, separation along Wallace's Line, a biogeographic boundary between Southeast Asia and Australia. Conclusion We describe an Australian origin for B. pseudomallei, characterized by a single introduction event into Southeast Asia during a recent glacial period, and variable levels of lateral gene transfer within populations. These patterns provide insights into mechanisms of genetic diversification in B. pseudomallei and its closest relatives, and provide a framework for integrating the traditionally separate fields of population genetics and phylogenetics for other bacterial species with high levels of lateral gene transfer.

The genetics and structure of the O-specific polysaccharide of Yersinia pseudotuberculosis serotype O:10 and its relationship with Escherichia coli O111 and Salmonella enterica O35

The O-specific polysaccharide (OPS) is a variable constituent of the lipopolysaccharide of Gram-negative bacteria. The polymorphic nature of OPSs within a species is usually first defined serologically, and the current serotyping scheme for Yersinia pseudotuberculosis consists of 21 O serotypes of which 15 have been characterized genetically and structurally. Here, we present the structure and DNA sequence of Y. pseudotuberculosis O:10 OPS. The O unit consists of one residue each of d-galactopyranose, N-acetyl-d-galactosamine (2-amino-2-deoxy-d-galactopyranose) and d-glucopyranose in the backbone, with two colitose (3,6-dideoxy-l-xylo-hexopyranose) side-branch residues. This structure is very similar to that shared by Escherichia coli O111 and Salmonella enterica O35. The gene cluster sequences of these serotypes, however, have only low levels of similarity to that of Y. pseudotuberculosis O:10, although there is significant conservation of gene order. Within Y. pseudotuberculosis, the O10 structure is most closely related to the O:6 and O:7 structures.

Prevalence and occurrence of zoonotic bacterial pathogens in surface waters determined by quantitative PCR

The prevalence and concentrations of Campylobacter jejuni, Salmonella spp. and enterohaemorrhagic E. coli (EHEC) were investigated in surface waters in Brisbane, Australia using quantitative PCR (qPCR) based methodologies. Water samples were collected from Brisbane City Botanic Gardens (CBG) Pond, and two urban tidal creeks (i.e., Oxley Creek and Blunder Creek). Of the 32 water samples collected, 8 (25%), 1 (3%), 9 (28%), 14 (44%), and 15 (47%) were positive for C. jejuni mapA, Salmonella invA, EHEC O157 LPS, EHEC VT1, and EHEC VT2 genes, respectively. The presence/absence of the potential pathogens did not correlate with either E. coli or enterococci concentrations as determined by binary logistic regression. In conclusion, the high prevalence, and concentrations of potential zoonotic pathogens along with the concentrations of one or more fecal indicators in surface water samples indicate a poor level of microbial quality of surface water, and could represent a significant health risk to users. The results from the current study would provide valuable information to the water quality managers in terms of minimizing the risk from pathogens in surface waters.

Latent variable models in statistical genetics

Understanding the complexities that are involved in the genetics of multifactorial diseases is still a monumental task. In addition to environmental factors that can influence the risk of disease, there is also a number of other complicating factors. Genetic variants associated with age of disease onset may be different from those variants associated with overall risk of disease, and variants may be located in positions that are not consistent with the traditional protein coding genetic paradigm. Latent Variable Models are well suited for the analysis of genetic data. A latent variable is one that we do not directly observe, but which is believed to exist or is included for computational or analytic convenience in a model. This thesis presents a mixture of methodological developments utilising latent variables, and results from case studies in genetic epidemiology and comparative genomics. Epidemiological studies have identified a number of environmental risk factors for appendicitis, but the disease aetiology of this oft thought useless vestige remains largely a mystery. The effects of smoking on other gastrointestinal disorders are well documented, and in light of this, the thesis investigates the association between smoking and appendicitis through the use of latent variables. By utilising data from a large Australian twin study questionnaire as both cohort and case-control, evidence is found for the association between tobacco smoking and appendicitis. Twin and family studies have also found evidence for the role of heredity in the risk of appendicitis. Results from previous studies are extended here to estimate the heritability of age-at-onset and account for the eect of smoking. This thesis presents a novel approach for performing a genome-wide variance components linkage analysis on transformed residuals from a Cox regression. This method finds evidence for a dierent subset of genes responsible for variation in age at onset than those associated with overall risk of appendicitis. Motivated by increasing evidence of functional activity in regions of the genome once thought of as evolutionary graveyards, this thesis develops a generalisation to the Bayesian multiple changepoint model on aligned DNA sequences for more than two species. This sensitive technique is applied to evaluating the distributions of evolutionary rates, with the finding that they are much more complex than previously apparent. We show strong evidence for at least 9 well-resolved evolutionary rate classes in an alignment of four Drosophila species and at least 7 classes in an alignment of four mammals, including human. A pattern of enrichment and depletion of genic regions in the profiled segments suggests they are functionally significant, and most likely consist of various functional classes. Furthermore, a method of incorporating alignment characteristics representative of function such as GC content and type of mutation into the segmentation model is developed within this thesis. Evidence of fine-structured segmental variation is presented.

Bacterial proteases from the intracellular vacuole niche ; protease conservation and adaptation for pathogenic advantage

Proteases with important roles for bacterial pathogens which specifically reside within intracellular vacuoles are frequently homologous to those which have important virulence functions for other bacteria. Research has identified that some of these conserved proteases have evolved specialised functions for intracellular vacuole residing bacteria. Unique proteases with pathogenic functions have also been described from Chlamydia, Mycobacteria, and Legionella. These findings suggest that there are further novel functions for proteases from these bacteria which remain to be described. This review summarises recent findings of novel protease functions from the intracellular human pathogenic bacteria which reside exclusively in vacuoles.

A functional screen identifies lateral transfer of beta-glucuronidase (gus) from bacteria to fungi

Lateral gene transfer (LGT) from prokaryotes to microbial eukaryotes is usually detected by chance through genome-sequencing projects. Here, we explore a different, hypothesis-driven approach. We show that the fitness advantage associated with the transferred gene, typically invoked only in retrospect, can be used to design a functional screen capable of identifying postulated LGT cases. We hypothesized that beta-glucuronidase (gus) genes may be prone to LGT from bacteria to fungi (thought to lack gus) because this would enable fungi to utilize glucuronides in vertebrate urine as a carbon source. Using an enrichment procedure based on a glucose-releasing glucuronide analog (cellobiouronic acid), we isolated two gus(+) ascomycete fungi from soils (Penicillium canescens and Scopulariopsis sp.). A phylogenetic analysis suggested that their gus genes, as well as the gus genes identified in genomic sequences of the ascomycetes Aspergillus nidulans and Gibberella zeae, had been introgressed laterally from high-GC gram(+) bacteria. Two such bacteria (Arthrobacter spp.), isolated together with the gus(+) fungi, appeared to be the descendants of a bacterial donor organism from which gus had been transferred to fungi. This scenario was independently supported by similar substrate affinities of the encoded beta-glucuronidases, the absence of introns from fungal gus genes, and the similarity between the signal peptide-encoding 5' extensions of some fungal gus genes and the Arthrobacter sequences upstream of gus. Differences in the sequences of the fungal 5' extensions suggested at least two separate introgression events after the divergence of the two main Euascomycete classes. We suggest that deposition of glucuronides on soils as a result of the colonization of land by vertebrates may have favored LGT of gus from bacteria to fungi in soils.

Bayesian methodology for genetics of complex diseases

Genetic research of complex diseases is a challenging, but exciting, area of research. The early development of the research was limited, however, until the completion of the Human Genome and HapMap projects, along with the reduction in the cost of genotyping, which paves the way for understanding the genetic composition of complex diseases. In this thesis, we focus on the statistical methods for two aspects of genetic research: phenotype definition for diseases with complex etiology and methods for identifying potentially associated Single Nucleotide Polymorphisms (SNPs) and SNP-SNP interactions. With regard to phenotype definition for diseases with complex etiology, we firstly investigated the effects of different statistical phenotyping approaches on the subsequent analysis. In light of the findings, and the difficulties in validating the estimated phenotype, we proposed two different methods for reconciling phenotypes of different models using Bayesian model averaging as a coherent mechanism for accounting for model uncertainty. In the second part of the thesis, the focus is turned to the methods for identifying associated SNPs and SNP interactions. We review the use of Bayesian logistic regression with variable selection for SNP identification and extended the model for detecting the interaction effects for population based case-control studies. In this part of study, we also develop a machine learning algorithm to cope with the large scale data analysis, namely modified Logic Regression with Genetic Program (MLR-GEP), which is then compared with the Bayesian model, Random Forests and other variants of logic regression.

Occurrence of iron and associated bacterial populations in soils of a forested subtropical coastal catchment

Iron (Fe) biogeochemistry is potentially of environmental significance in plantation-forested, subtropical coastal ecosystems where soil disturbance and seasonal water logging may lead to elevation of Fe mobilization and associated water quality deterioration. Using wet-chemical extraction and laboratory cultivation, we examined the occurrence of Fe forms and associated bacterial populations in diverse soils of a representative subtropical Australian coastal catchment (Poona Creek). Total reactive Fe was abundant throughout 0e30 cm soil cores, consisting primarily of crystalline forms in well-drained sand soils and water-logged loam soils, whereas in water-logged, low clay soils, over half of total reactive Fe was present in poorly-crystalline forms due to organic and inorganic complexation, respectively. Forestry practices such as plantation clear-felling and replanting, seasonal water logging and mineral soil properties significantly impacted soil organic carbon (C), potentially-bioavailable Fe pools and densities of S-, but not Fe-, bacterial populations. Bacterial Fe(III) reduction and abiotic Fe(II) oxidation, as well as chemolithotrophic S oxidation and aerobic, heterotrophic respiration were integral to catchment terrestrial FeeC cycling. This work demonstrates bacterial involvement in terrestrial Fe cycling in a subtropical coastal circumneutral-pH ecosystem.