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dc.contributor.advisorJamal-Ally, Sumaiya.
dc.contributor.advisorLaing, Mark Delmege.
dc.creatorBurgdorf, Richard Jörn.
dc.date.accessioned2019-02-13T10:35:49Z
dc.date.available2019-02-13T10:35:49Z
dc.date.created2016
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/10413/16116
dc.descriptionDoctor of Philosophy in Microbiology. University of KwaZulu-Natal. Pietermaritzburg, 2016.en_US
dc.description.abstractFungal endophytes are of interest due to their diverse taxonomy and biological functions. A range of definitions exists based on their identity, morphology, location and relationship with their host. Fungal endophytes belong to a wide range of taxa and they are categorized by a variety of characteristics. The detection and identification of these fungal endophytes can be performed using culture-dependent and culture-independent methods. These organisms have a range of application in pharmaceutical discovery and agriculture. Agricultural applications include the exploitation of the growth promoting and protective properties of fungal endophytes in crops such as wheat. This important crop is grown in South Africa where biotic and environmental stresses pose a challenge to its cultivation. Fungal endophytes have demonstrated potential to ameliorate these challenges. Future research will reveal how they can be harnessed to fight food insecurity brought about by stress factors such as climate change. Extraneous DNA interferes with PCR studies of endophytic fungi. A procedure was developed with which to evaluate the removal of extraneous DNA. Wheat (Triticum aestivum) leaves were sprayed with Saccharomyces cerevisiae and then subjected to physical and chemical surface treatments. The fungal ITS1 products were amplified from whole tissue DNA extractions. ANOVA was performed on the DNA bands representing S. cerevisiae on the agarose gel. Band profile comparisons using permutational multivariate ANOVA (PERMANOVA) and non-metric multidimensional scaling (NMDS) were performed on DGGE gel data, and band numbers were compared between treatments. Leaf surfaces were viewed under Variable Pressure Scanning Electron Microscopy (VPSEM). Yeast band analysis of the agarose gel showed that there was no significant difference in the mean band DNA quantity after physical and chemical treatments, but they both differed significantly (p < 0.05) from the untreated control. PERMANOVA revealed a significant difference between all treatments (p < 0.05). The mean similarity matrix showed that the physical treatment results were more reproducible than those from the chemical treatment results. The NMDS showed that the physical treatment was the most consistent. VPSEM indicated that the physical treatment was the most effective treatment to remove surface microbes and debris. The use of molecular and microscopy methods for the post-treatment detection of yeast inoculated onto wheat leaf surfaces demonstrated the effectiveness of the surface treatment employed, and this can assist researchers in optimizing their surface sterilization techniques in DNA-based fungal endophyte studies. Denaturing gel electrophoresis (DGE) can be used in culture-independent studies of microbial community composition and the technique has several variants. This work compared two of these variants, namely denaturing gradient gel electrophoresis (DGGE) and temporal temperature gradient electrophoresis (TTGE), to establish their relative performance in terms of resolution and detection, as well as cost and preparation time. Per gel reagent and material costs and preparation times were recorded for comparison. Conversion formulae were developed to standardize denaturing conditions for comparison of DGGE and TTGE gels. For all gel samples, band numbers, positions, peak height and base width were recorded. Samples run on DGGE gels tended to be clearer and more distinct from each other and DGGE tended to provide higher band numbers and better resolution. However, TTGE was quicker and cheaper to prepare. The TTGE and DGGE gel data were strongly correlated but DGGE provided more accurate dendrograms for comparisons of pure fungal isolates. Non-metric multidimensional scaling showed that TTGE data profiles were more heterogeneous, while DGGE produced tighter clustering of replicate samples. Although TTGE could be an acceptable technique for resolving DNA sequences in certain applications, DGGE is preferable for fungal wheat endophyte studies. Fungal endophyte community composition can be affected by various factors, such as the host genome. Research into the host genome effects on fungal endophyte composition can assist in harnessing the potential benefits of such relationships in agro-ecosystems. Several culture-based studies have investigated the presence of a cultivar effect on endophyte composition. However, a culture-based approach can only detect organisms that can be isolated and grown. Culture-independent methods can detect both culturable and non-culturable fungal endophytes for comparisons of fungal endophyte community composition (ECC) between wheat cultivars. Denaturing gradient gel electrophoresis (DGGE), high-resolution melt (HRM) analysis of community profiles, quantitative PCR, and sequence analysis were used to analyse and compare the fungal ECC of four wheat cultivars grown under field conditions. A significant organ and cultivar x organ interaction effects on fungal biomass were observed. A chytrid, namely Olpidium brassicae formed a significant component of the fungal endophyte community across all tissues in wheat. This finding highlighted the utility of the culture-independent in revealing cryptic interactions and endophytes, and raised questions about the factors that influence the organisms that reside within field-grown wheat. Systemic fungicides used in wheat production are pathogenic to many plant-inhabiting fungi such as fungal endophytes. The aim of the study was to reveal the effect of tebuconazole on the eukaryotic endophytes of wheat flag leaves using next generation sequencing (NGS). Treated and untreated leaves were surface sterilized prior to metagenomic DNA (mDNA) extraction. NGS was performed on DNA amplified using universal ITS primers. SCATA analysis was used for operational taxonomic unit (OTU) assignment of sequences, which were identified against CBS, UNITE and Genbank databases. A maximum likelihood (ML) tree was developed for taxonomic assignment of key genera. OTU mean read numbers and OTU richness were compared. The treatment effects were analysed using Principal Component Analysis (PCA), permutational multivariate ANOVA (PERMANOVA), distance-based test for homogeneity of multivariate dispersions (PERMDISP) and similarity percentage analysis (SIMPER). With one exception, non-wheat OTUs belonged to the Dikarya. Puccinia read numbers differed significantly (p = 0.01) between treatments and fungicide treatment tended to reduce total OTU read numbers and OTU richness. The variability of most key OTUs correlated positively with unsprayed samples. Treatment influenced OTU composition. Treated samples had the greatest homogeneity in endophyte composition and Puccinia made the greatest contribution to variation, with low contribution from the other OTUs. Dikarya were the dominant wheat flag leaf endophytes, and while the fungicide suppressed Puccinia and reduced fungal endophyte abundance, it did not significantly alter the community assemblage.en_US
dc.language.isoen_ZAen_US
dc.subjectEndophytic fungi.en_US
dc.subjectWheat -- Microbiology.en_US
dc.subjectEndophytes.en_US
dc.subjectTheses -- Microbiology.en_US
dc.subjectUCTDen_US
dc.subject.otherEndophytic fungi.en_US
dc.subject.otherEndophytes.en_US
dc.subject.otherFungal diseases of plants.en_US
dc.titleThe culture-independent analysis of fungal endophytes of wheat grown in KwaZulu-Natal, South Africa.en_US
dc.typeThesisen_US


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