Yes / Pantoea stewartii is known to be the causative agent of Stewart's wilt, which usually affects sweet corn (Zea mays) with the corn flea beetle as the transmission vector. In this work, we present the whole-genome sequence of Pantoea stewartii strain M009, isolated from a Malaysian tropical rainforest waterfall. / University of Malaya via High Impact Research Grants (UM C/625/1/HIR/MOHE/CHAN/01 no. A-000001- 50001 and UM C/625/1/HIR/MOHE/CHAN/14/1 no. H-50001-A000027)

Compared to microarray-based genotyping, next-generation whole genome-sequencing (WGS) studies have the strength to provide greater information for the identification of rare variants, which likely account for a significant portion of missing heritability of common human diseases. In WGS, family-based studies are important because they are likely enriched for rare disease variants that segregate with the disease in relatives. We propose a multilevel model to detect disease variants using family-based WGS data with longitudinal measures. This model incorporates the correlation structure from family pedigrees and that from repeated measures. The iterative generalized least squares (IGLS) algorithm was applied to estimation of parameters and test of associations. The model was applied to the data of Genetic Analysis Workshop 18 and compared with existing linear mixed effect (LME) models. The multilevel model shows higher power at practical p-value levels and a better type I error control than LME model. Both multilevel and LME models, which utilize the longitudinal repeated information, have higher power than the method that only utilize data collected at one time point.

Next-generation sequencing technologies are revolutionising our ability to characterise and investigate infectious diseases. Utilising the power of high throughput sequencing, this study reports, the development of a sensitive, non-PCR based, unbiased amplification method, which allows the rapid and accurate sequencing of multiple microbial pathogens directly from clinical samples. The method employs Φ29 DNA polymerase, a highly efficient enzyme able to produce strand displacement during the polymerisation process with high fidelity. Problems with DNA secondary structure were overcome and the method optimised to produce sufficient DNA to sequence from a single bacterial cell in two hours. Evidence was also found that the enzyme requires at least six bases of single stranded DNA to initiate replication, and is not capable of amplification from nicks. Φ29 multiple displacement amplification was shown to be suitable for a range of GC contents and bacterial cell wall types as well as for viral pathogens. The method was shown to be able to provide relative quantification of mixed cells, and a method for quantification of viruses using a known standard was developed. To complement the novel molecular biology workflow, a data analysis pipeline was developed to allow pathogen identification and characterisation without prior knowledge of input. The use of de novo assemblies for annotation was shown to be equivalent to the use of polished reference genomes. Single cell Φ29 MDA samples had better assembly and annotation than non-amplification controls, a novel finding which, when combined with the very long DNA fragments produced, has interesting implications for a variety of analytical procedures. A sampling process was developed to allow isolation and amplification of pathogens directly from clinical samples, with good concordance shown between this method and traditional testing. The process was tested on a variety of modelled and real clinical samples showing good application to sterile site infections, particularly bacteraemia models. Within these samples multiple bacterial, viral and parasitic pathogens were identified, showing good application across multiple infection types. Emerging pathogens were identified including Onchocerca volvulus within a CSF sample, and Sneathia sanguinegens within an STI sample. Use of Φ29 MDA allows rapid and accurate amplification of whole pathogen genomes. When this is coupled with the sample processing developed here it is possible to detect the presence of pathogens in sterile sites with a sensitivity of a single genome copy.

Legionella bacteria, the causative agent of Legionaries’ disease and Pontiac fever, are ubiquitous in fresh-water environments including man-made water systems. Incidence of legionellosis is increasing in the United States resulting in thousands of cases every year. Infection via aerosols generated by showers, faucets, cooling towers, spas, fountains, and other water fixtures has been identified as the primary source of transmission. Legionella bacteria pose a significant public health threat, particularly in health care and long term care settings as Legionella can readily colonize the plumbing systems and infect the vulnerable patient population. One species, Legionella pneumophila (Lp), is responsible for over 90% of the known cases of Legionnaires’ disease. The importance of genetic diversity of Lp and non-pneumophila strains in human disease remains an area of ongoing research. Little is known in regard to the phylogenetic diversity of environmental strains, particularly strains that colonize facilities with high risk populations such as hospitals. Whole-genome sequencing (WGS) analysis, is an emerging tool used to support epidemiological investigation of cases of legionellosis and can be used to describe and establish phylogenetic relationships between environmental strains and clinical cases. The advantage of this method is the ability to differentiate bacteria down to the level of single nucleotide polymorphisms (SNPs). However, it was unknown whether current WGS methods accurately represent the potential SNP diversity among Lp isolates from the same environmental sample. It is unclear as to why certain strains tend be associated with clinical cases more than others, but certain genes referred to as virulence factors may be related to the relative pathogenicity of Legionella strains. Further investigation into virulence factors and antibiotic resistance factors could be used in future risk assessment of environmental Legionella. Additionally, Legionella have the potential for high genetic diversity due to recombination events, and gene transfer can occur between distinct Legionella species and strains. There is a lack of research on the potential sharing of virulence factor genes between Legionella strains typically associated with disease and those considered to be non-virulent. The goal of the work presented in this thesis is to describe the diversity of phylogenetic relationships between Lp isolates found in hospital premise plumbing systems, to estimate the genetic diversity among Lp found in the same environmental sample, and to identify virulence and antibiotic resistance genes shared between Legionella strains. A better understanding of the genetic diversity of environmental Lp could inform future surveillance and outbreak investigations by demonstrating the need to collect samples from multiple sites within a facility, and identifying shared virulence and antibiotic resistance genes between Legionella species and strains could apprise future risk assessment. WGS was utilized to describe the phylogenetic relationships of 81 Lp isolates from five hospitals. Individual hospitals were found to have distinct strains of Lp. For some strains, highly conserved subpopulations were collected from the same room over time, whereas other strains did not cluster by room. Using prospectively collected isolates from two hospitals, the mean number of SNP differences among isolates from the same environmental sample was found to differ between hospitals (0.4 versus 7.5). The presence of virulence factors and antibiotic resistance genes in Legionella species and strains was described. An analysis of 10 virulence factor genes revealed that Lp likely did not share these genes with Legionella anisa, a species generally considered to be non-virulent. Within Lp strains there was no clear difference between the Lp strains considered to be more virulent and those considered to be less virulent. A few antibiotic resistance genes were also identified. Following an in vitro assay, only the identified genes associated with macrolide resistance, LpeA and LpeB, were found to impact a quantifiable measure of antimicrobial resistance. The results of these studies emphasize the importance of understanding the context of an individual facility in Legionella related studies. Importantly, the observations or trends of one facility should not necessarily be applied to another. Legionella genetic diversity was highly conserved in some facilities, whereas in others there was greater diversity as measured by SNP differences. Within sample SNP differences was also variable between hospitals. The virulence findings gave a clear indication of the limited virulence capacity of L. anisa. These findings could explain the limited potential of L. anisa to cause disease in humans. However, a lack of difference among Lp strains may be cause to reassess the potential risk of these other strains especially in diagnostic practices. Finally, some strains of Lp have genes that may contribute to resistance to the leading antibiotic treatments for Legionnaires’ disease. Overall, this research further demonstrates the power of WGS as multiple questions can be addressed using this methodology.

The study of aflatoxin in Aspergillus spp. has garnered the attention of many researchers due to aflatoxin's carcinogenic properties and frequency as a food and feed contaminant. Significant progress has been made by utilizing the model organism Aspergillus nidulans to characterize the regulation of sterigmatocystin (ST), the penultimate precursor of aflatoxin. A previous forward genetic screen identified 23 A. nidulans mutants involved in regulating ST production. Six mutants were characterized from this screen using classical mapping (five mutations in mcsA) and complementation with a cosmid library (one mutation in laeA). The remaining mutants were backcrossed and sequenced using Illumina and Ion Torrent sequencing platforms. All but one mutant contained one or more sequence variants in predicted open reading frames. Deletion of these genes resulted in identification of mutant alleles responsible for the loss of ST production in 12 of the 17 remaining mutants. Eight of these mutations were in genes already known to affect ST synthesis (laeA, mcsA, fluG, and stcA), while the remaining four mutations (in laeB, sntB, and hamI) were in previously uncharacterized genes not known to be involved in ST production. Deletion of laeB, sntB, and hamI in A. flavus results in loss of aflatoxin production, confirming that these regulators are conserved in the aflatoxigenic aspergilli. This report highlights the multifaceted regulatory mechanisms governing secondary metabolism in Aspergillus. Additionally, these data contribute to the increasing number of studies showing that forward genetic screens of fungi coupled with whole-genome resequencing is a robust and cost-effective technique. IMPORTANCE In a postgenomic world, reverse genetic approaches have displaced their forward genetic counterparts. The techniques used in forward genetics to identify loci of interest were typically very cumbersome and time-consuming, relying on Mendelian traits in model organisms. The current work was pursued not only to identify alleles involved in regulation of secondary metabolism but also to demonstrate a return to forward genetics to track phenotypes and to discover genetic pathways that could not be predicted through a reverse genetics approach. While identification of mutant alleles from whole-genome sequencing has been done before, here we illustrate the possibility of coupling this strategy with a genetic screen to identify multiple alleles of interest. Sequencing of classically derived mutants revealed several uncharacterized genes, which represent novel pathways to regulate and control the biosynthesis of sterigmatocystin and of aflatoxin, a societally and medically important mycotoxin.

Naturally competent bacterial species, which self-induce the recombination mechanism of transformation, are wide spread across the bacterial tree-of-life. However, it remains unclear why competence has evolved in these bacteria. Although it is likely that exact explanations will be different for each species, a common selective factor cannot be excluded. Currently, three dominant hypotheses, which focus on the transformation function, try to explain the benefits of competence. Firstly, competence is thought to increase the rate of adaptation by combining beneficial alleles in single genotypes. Secondly, competence can repair DNA-damage by replacing the damaged DNA fragments with undamaged ones. Thirdly, the DNA uptake during competence is used to recycle environmental DNA fragments for nutrients. One of the naturally competent species is the Gram-positive Streptococcus pneumoniae, which is an opportunistic pathogen generally inhabiting the naso-pharyngeal area of young children. Competence in S. pneumoniae is regulated via density dependent extracellular signaling peptide. Here I use a combination of experiments designed around knockout mutants of the signaling mechanism and next-generation sequencing methods to test the first two hypotheses in S. pneumoniae. First, I extend on the DNA-for-repair hypothesis by showing that competent populations of S. pneumoniae are better protected not only against a DNA-damaging agent, but also against protein synthesis inhibitors. However, the mechanisms underlying this protection differ between types of stress. DNA-damage requires the full process of transformation, while protection against protein synthesis inhibitors only requires the activation of the competent cell state. This shows that benefits of competence cannot be totally explained by the benefits of transformation. Second, I use a long-term evolution experiment, where competent and non-competent strains are kept in the presence and absence of periodic stress, to determine the importance of competence for the generation of genetic variation. I find that competence does not increase the rate of adaptation in S. pneumoniae. The fitness of evolved competent populations was significantly lower than those of non-competent populations evolved over the same period of time. However, the intrinsic costs of competence are mitigated by the addition of short periods of stress exposure. These results confirm the prediction of the fitness associated recombination (FAR) hypothesis that competence is favoured in low-fitness situations. Thirdly, whole genome re-sequencing of the evolved populations allowed me to explore genomic evolution next to fitness changes. The genomic data revealed that competence reduces the mutational load of deleterious mutations rather than generating combinations of beneficial alleles. In addition I show several case of parallel genomic evolution within each treatment and across treatments. This shows that parallel evolution is not restricted by genotypic background (competence) or environment (periodic stress). Finally, these results show that competence has evolved in populations of S. pneumoniae as a mechanism to deal with various forms of stress.

Mycobacterium tuberculosis (Mtb) remains a global challenge that has been worsened by the emergence of drug resistant strains of Mtb. We used publicly available Next Generation Sequencing (NGS) and drug susceptibility (DST) data to develop “Resistance sniffer”, an online software program for the rapid prediction of lineage and Mtb drug resistance. Based on the distribution of polymorphisms in the genomes of Mtb, we calculated the power of association between the polymorphisms in different clades of Mtb and resistance to 13 anti-TB drugs. Our data suggests that the development of drug resistance in Mtb is a stepwise process that involves the accumulation of polymorphisms in the Mtb genome. We carefully curated the polymorphisms based on their association powers to create a diagnostic key that captures patterns of these polymorphisms that can be used to predict lineage and drug resistance in Mtb. This diagnosis key was incorporated into the Resistance Sniffer tool, an online software program that we developed for the rapid diagnosis of drug resistance in Mtb. The tool was tested using sequence data from the South Africa Medical Research Council (SA-MRC). Our data suggests that the majority of the strains in SA may have been brought by the arrival of European settlers while the more resistant strains may have been introduced in the region by Asian travellers later on. We next sought to determine non-random associations between polymorphic sites in genomes of Mtb. Using the attributable risk (Ra) statistical methods, we distinguished between functional associations and associations that may have been due to genetic drift events for different Mtb clades. We then integrated the (Ra) data with drug susceptibility and annotation data to generate networks in Cytoscape 3.71. These networks were then used to infer evolutionary trajectories that drive the emergence and fixation of the drug resistant phenotype in different clades of Mtb. We demonstrate that strains from the Lineage 1.2 are associated with less complex functional associations compared to the strains from other clades such as the Asian and Euro-American clades. Our data also shows that the predisposition of strains from the Asian clades to develop multi-drug resistance may be attributed to a complex network of functional interactions of mutations in genes that are involved in several aspects of Mtb physiology such as cell wall modelling, lipid metabolism, stress response and DNA repair. / Dissertation (MSc)--University of Pretoria, 2019. / Biochemistry / MSc / Unrestricted

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