Date of Award

8-2018

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Biological Sciences

Committee Member

Dr. Vincent Richards, Committee Chair

Committee Member

Dr. Christina Wells

Committee Member

Dr. J. Antonio Baeza

Abstract

According to the National Institutes of Health, dental caries is the leading chronic disease of children in the United States. Dental caries is biofilm-mediated, multifactorial and dynamic. Research using culturing techniques and high throughput 16S rRNA amplicon sequencing unraveled the taxonomic complexity of mixed microbial communities (microbiome) in dental biofilms (plaque) and their abundance differences. However, 16S rRNA sequencing fails to resolve taxonomic assignment beyond genus level for certain taxa, which is problematic in identifying potential antagonistic species within the same genus. The presented work addressed current shortcomings in dental microbiome research. First, dental plaque samples used in this study were collected from either caries-free (PF) teeth or caries-active teeth with lesions in the enamel layer (PE). This site-specific collection method provides a better understanding of the role of specific organisms and biological processes as teeth transition from health to disease. Second, deep sequencing was used to produce whole genome metagenomic data, i.e. complete or semi complete genomes drafted from mixed bacterial communities, potentially enhancing bacterial species detection, identifying rare species, and providing the gene content of the samples and their metabolic potential. Overall, the objective of this study was to provide species level taxonomic classification and metabolic potential of mixed microbial communities in plaque collected from site-specific dentition. Two different approaches to analyze whole genome metagenomic data were used and compared. (i) Read based taxonomic classification and supervised assembly where short reads are taxonomically classified prior to genome assembly. (ii) Contig based taxonomic classification and unsupervised assembly where an assembler is used to assemble reads into contigs directly. The contigs produced are then classified taxonomically. The read based taxonomic classification and supervised assembly approach outperformed the latter in an assessment of taxonomic assignment accuracy using a mock metagenomic data set. The taxonomic profiles for PF and PE reported by both approaches were virtually identical however their distributions showed variation. The taxonomic inter-sample similarities were reflected in the gene content information as both approaches reported minor metabolic potential differences between PF and PE. Noticeably, both approaches reported significantly enriched biological processes involved in sugar transport and metabolism in PE.

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