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Thesis Format

Integrated Article


Doctor of Philosophy




Gloor, Gregory B.


Advancements in sequencing technologies have revolutionized biological sciences and led to the emergence of a number of fields of research. One such field of research is metagenomics, which is the study of the genomic content of complex communities of bacteria. The goal of this thesis was to contribute computational methodology that can maximize the data generated in these studies and to apply these protocols human and environmental metagenomic samples.

Standard metagenomic analyses include a step for binning of assembled contigs, which has previously been shown to exclude mobile genetic elements, and I demonstrated that this phenomenon extends to all conjugative elements, which are a subset of mobile genetic elements. I proposed two separate methodologies that could detect contigs that are potential conjugative elements: a curated set of profile hidden Markov models that are very efficient to run, or annotation using the full UniRef90 database, a slower but more sensitive method.

I then applied this framework to a large population-based cohort and to a study examining the association of the maternal human gut microbiota and the development of spina bifida. Broadly, the composition and abundances of conjugative elements were discriminatory between the age and geographic cohorts. In the spina bifida cohort, there was an enrichment of Campylobacter hominis and a conjugative element belonging to Campylobacter hominis, which was excluded from the metagenomic bins.

Next, I characterized a novel species belonging to the recently discovered manganese-oxidizing genus Manganitrophus growing on oil refinery carbon filters. I successfully circularized the genomes of three strains and got quality assemblies for the remaining two samples. Furthermore, I identified a previously uncharacterized conjugative plasmid belonging to the species using my framework developed in chapter 2.

Finally, I developed an assembly pipeline to perform a secondary assembly on binned assemblies using long reads. The secondary assemblies yielded a number of additional circularized sequences that would be useful as scaffolds in future metatranscriptomic, variation analysis, and community dynamic studies.

The methodologies and applications in this thesis provide a framework for more complete metagenomic analyses going forward that will aid in our understanding of microbial ecology.

Summary for Lay Audience

Over recent years, the technology to determine the DNA sequence of species' genomes has advanced greatly. These technological advances have allowed for the study of bacterial genomes living in complex communities without the need to isolate them individually, a field referred to as metagenomics. As a rapidly expanding field of research, metagenomic analyses required computational tools that can accurately analyze the massive quantities of data being produced. For my thesis, I sought to develop such tools and apply them to the complex bacterial communities that colonize the human intestinal tract and to communities that grow on carbon filters from the wastewater treatment facility of an oil refinery.

Conjugative elements are pieces of DNA that can be exchanged between bacteria. These mobile genetic elements are of clinical interest because they commonly carry cargo genes that can confer antibiotic resistance to the bacteria. I demonstrate that standard metagenomic analyses systematically exclude these elements, and I proposed a methodology to remedy this issue.

I then applied this methodology for identifying conjugative elements to two separate research questions. First, I showed that conjugative systems are different depending on the age and geographical location of the individual, likely due to antibiotic use and diet differences between populations. Additionally, I showed that harmful bacteria carrying a conjugative element in the guts of expectant mothers may play a role in the development of spina bifida.

Growing on the carbon filters of an oil refinery's wastewater treatment plant, I discovered a novel species of bacteria whose closest known relatives on the tree of life are able to use manganese as a source of energy. I also found a previously uncharacterized conjugative element belonging to this species that is likely able to remove heavy metals from its environment.

Finally, I developed a method for assembling additional complete bacterial genomes from the sequencing of complex environments. Additional complete genomes will enable a better ability to understand the full genetic potential of these bacterial communities from the wastewater treatment plant.

Overall, I improved computational methods for analyzing complex bacterial communities and applied the methods as a proof of principle for their usefulness.

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Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.