Thesis (Ph. D., Biology)--University of Idaho, 2009. / Major professor: Larry J. Forney. Includes bibliographical references. Also available online (PDF file) by subscription or by purchasing the individual file.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 119-139).

Thesis (Ph. D.)--University of Queensland, 2002. / Includes bibliographical references.

Thesis (doctoral)--Swedish University of Agricultural Sciences, 2007. / Includes bibliographical references. Also available on the Internet.

In the past, the response of microbial populations to anthropogenic disturbances was studied using conventional methods based on cultivation of microorganisms and on measurement of their metabolic activities (Fantroussi et al., 1999). However, these culturing methods often account for a small proportion of the total microbial community (Ibekwe and Kennedy, 1998; Hill et al., 2000). To overcome this, molecular techniques were developed and these allowed for the analyses of microorganisms in their natural habitats. Analysis of the 16S rRNA molecule and its corresponding gene (16S rDNA) has been the most widely used approach in the last decade (Amman et al., 1995). Although molecular techniques based on PCR have been used to eliminate the bias of culturing methods, they also have their drawbacks (Wintzingerode et al., 1997; Kirk et al., 2004). As another alternative, Garland and Mills (1991) developed a rapid community-level physiological approach to study microbial communities. The use of the community-level approach to microorganisms provided an accurate and meaningful measure of the heterotrophic microbial community by measuring the community’s metabolic abilities (Garland and Mills, 1991). Zak et al. (1994) used the method to study the functional diversity of microbial communities. The approach has been used to study the soil functional diversities in polluted or disturbed environments. Over the years, the application of gypsum in agriculture has received much attention. The gypsum has been used to ameliorate both acidic and alkali soils with elevated amounts of salinity (Suhayda et al., 1997; Sun et al., 2000). In these studies, the application of gypsum lead to changes in the soil chemical properties by causing a drastic increase in the amount of exchangeable calcium and sulphate and reduced the levels of exchangeable aluminium. It has been noted that high levels of aluminium and/or reduced amounts of calcium restrict root elongation and thus hindered the plants ability to access adequate water (Sun et al., 2000). Also, the replacement of sodium ions with calcium ions resulted in the flocculation of soil particles and improved the porous structure and water permeability of the soil (Suhayda et al., 1997). This study revealed that the application of the gypsiferous mine water did not have any negative impact on the bacterial communities. In fact, on average, the bacterial diversities were found to be higher in the gypsum-irrigated soils. This was most evident in pivot Major and Tweefontein, where the gypsum-irrigated soils were more diverse than the control soils. DGGE results from pivot Major and Tweefontein revealed a high level of bacterial diversity in gypsum-irrigated soils, as estimated by the number of dominant bands. Also, the number of heterotrophic bacteria in the gypsum-irrigated soils was one to two orders of magnitude higher than in the control soils. Principal component analysis performed on BIOLOG data showed that in both pivot Major and Tweefontein, the gypsum-irrigated soils were able to utilise a wider range of carbon sources as compared to their control counterparts. The bacterial communities in pivot Four appeared to be steady in both the gypsum-irrigated soils and the control soils. The number of visible DGGE bands was consistent between the gypsum-irrigated and the control soils. The heterotrophic bacterial counts in the gypsum-irrigated soils had an average of 273x106 cfu g-1 soil and those present in the control soils were slightly higher at 380x106 cfu g-1 soil. Principal component analysis revealed no differences in terms of substrate utilisation capabilities among the gypsum-irrigated soils and the control soils. All three techniques revealed no significant difference in community structures between soil profiles at 0-10 cm and 40-60 cm. The lack of difference could be attributed to the crops planted in all three pivots during sampling. The root system of Zea Maysplants enhanced microbial growth by exuding nutrients such as amino acids and sugars. In conclusion, the application of polyphasic approach proved successful in studying the response of soil bacterial communities to gypsiferous mine water. The use of both culture-dependent and culture-independent methods is recommended as the methods compensate each other’s limitations and therefore provide a more detailed description of the community. In this study, the application of gypsiferous mine water did not have an adverse effect on the soil bacterial communities. In fact, the addition of gypsiferous mine water seemed to ameliorate the soil bacterial communities. However, further comprehensive study is needed to determine the response of bacterial communities to gypsiferous mine water over longer periods of time. 16S rDNA sequencing and analysis of DGGE bands should also be done to identify the bacterial species present in the gypsum-irrigated samples. / Dissertation (MSc)--University of Pretoria, 2010. / Microbiology and Plant Pathology / unrestricted

Understanding microbial evolution lies at the heart of microbiology and environmental sciences. Numerous studies have been dedicated to elucidating the underlying mechanisms that create microbial genetic diversity and adaptation. However, due to technical limitations such as the high level of uncultured cells in almost every natural habitat, most of current knowledge is primarily based on axenic cultures grown under laboratory conditions, which typically do not simulate well the natural environment. How well the knowledge from isolates translates to in-situ processes and natural microbial communities remains essentially speculative. The recent development of culture-independent genomic techniques (aka metagenomics) provides possibilities to bypass some of these limitations and provide new insights into microbial evolution in-situ. To date, most of metagenomic studies have been focused on a few reduced-diversity model communities, e.g., acid mine drainage. Highly complex communities such as those of soil and sediment habitats remain comparatively less understood. Furthermore, a great power of metagenomics, which has not been fully capitalized yet, is the ability to follow the evolution of natural microbial communities over time and environmental perturbations, i.e., times-series metagenomics. Although the recent developments in DNA sequencing technologies have enabled (inexpensive) time-series studies, the bioinformatics approaches to analyze the resulting data have clearly fallen behind. Taken together, to scale up metagenomics for complex community studies, three major challenges remain: 1) the difficulty to process and analyze massive short read sequencing data, often at the terabyte level; 2) the difficulty to effectively assemble genomes from complex metagenomes; and 3) the lack of methods for tracking genotypes and mutational events such as horizontal gene transfer (HGT) through time. Therefore, developing efficient bioinformatics approaches to address these challenges represents an important and timely issue. This thesis aimed to develop novel bioinformatics pipelines and algorithms for high performance computing, and, subsequently, apply these tools to natural microbial communities to generate quantitative insights into the relative importance of the molecular mechanisms creating or maintaining microbial diversity. The tools are not specific to a particular habitat or group of organisms and thus, can be broadly used to advance our understanding of microbial evolution in different settings. In particular, the comparative whole-genome analysis of 24 Escherichia isolates form various habitats, including human and non-human associated habitats such as freshwater ecosystems and beaches, showed that organisms with more similar ecologies tend to exchange more genes, which has important implications for the prokaryotic species concept. To more directly test these findings from isolates and quantify the patterns of genetic exchange among co-occurring populations, three years of time-series metagenomics data from planktonic samples from Lake Lanier (Atlanta, GA) were analyzed. For this, it was first important to develop bioinformatics algorithms to robustly assemble population genomes from complex community metagenomes, identify the phylogenetic affiliation of assembled genome and contig sequences, and detect horizontal gene transfer among these sequences. Using these novel algorithms, in situ bacterial lineage evolution was quantitatively assessed, especially with respect to whether or not ecologically distinct lineages evolve according to the recently proposed fragmented speciation model (Retchless and Lawrence, Science 2008). Evidence in support of this model was rarely observed. Instead, it appeared that rampant HGT disseminated ecologically important genes within the population, maintaining intra-population diversity. By expanding the previous approaches to include methods to assess differential gene abundance and selection pressure between samples, it was possible to quantify how soil microbial communities respond to a decade of warming by 2 0C, which simulated the predicted effects of climate change. It was found that the heated communities showed significant shifts in composition and predicted metabolism, reflecting the release of additional soil carbon compared to the unheated (control) communities, and these shifts were community-wide as opposed to being attributable to a few taxa. These findings indicated that the microbial communities of temperate grassland soils play important roles in mediating the feedback responses to climate change. Collectively, the findings presented here advance our understanding of the modes and tempo of microbial community adaptation to environmental perturbations and have important implications for better modeling the microbial diversity on the planet. The bioinformatics algorithms and approaches developed as part of this thesis are expected to facilitate future genomic and metagenomic studies across the fields of microbiology, ecology, evolution and engineering.

Thesis (Ph.D.)--University of Wollongong, 2006. / Typescript. Includes bibliographical references: leaf 173-216.

Thesis (Ph. D.)--Michigan State University. Dept. of Entomology, 2006. / Title from PDF t.p. (viewed on Nov. 20, 2008) Includes bibliographical references. Also issued in print.

Thesis (Ph.D.) - University of Queensland, 2006. / Includes bibliography.

Thesis (Ph. D.)--Georgia State University, 2006. / Title from title screen. George E. Pierce,committee chair; Eric S. Gilbert, Sidney A. Crow, committee members. Electronic text (135 p. : ill. (some col.)) : digital, PDF file. Description based on contents viewed Aug. 20, 2007. Includes bibliographical references (p. 120-124).