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Title: Assessing the accuracy of metagenomic analysis of microorganisms involved in human diseases using control materials
Author: Temisak, Sasithon
ISNI:       0000 0004 6061 0118
Awarding Body: St George's, University of London
Current Institution: St George's, University of London
Date of Award: 2015
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Metagenomics is the study of the collective genomes of the members of a microbial community. In contrast to conventional culture methods, sequence-based metagenomics exclusively relies on sequence analysis without culturing microorganisms. This approach has revolutionised our understanding of the complexity of microbiomes. As such, microbial profiling, particularly of microbiomes in humans that appear to play key roles in numerous disease phenotype, may provide information to help define associated underlying aetiological mechanisms. However, a number of available metagenomic approaches have different biases in the identification and quantification of the microbial composition, resulting in misinterpretation of the accrued data which subsequently affect conclusions. Therefore, the aim of this study was to interrogate sources of error in various methodologies in sequence-based metagenomic analysis. In this study, genomic DNA of common bacterial pathogens representative of both Gram-positive and Gram-negative organisms mixed at defined quantitative proportions were used as a standardised metagenomics control material (MCM) in order to assess the comparative accuracy of different approaches, i.e. 16S ribosomal RNA (rRNA) profiling and metagenomic shot~un-sequencing. Sources of bias in 16S rRNA including primer-template mismatches, primer design, and bioinformatics analytical tools were identified. Whole genome sequencing generated a high precision of microbial profiling. Bias was also observed due to DNA extraction protocol when the whole cell material (WCM) containing a bacteriologically quantitated range of bacteria was used. This study also suggested that the MCM provided the opportunity to develop species specific assays to detect multiple bacterial pathogens collected from the clinical samples by using high-throughput quantitative PCR (ht-qPCR). In conclusion, the methodology applied to microbial profiling analysis must consider sources of error and methods of standardisation such as those described here. Moreover, ht-qPCR demonstrated the value of a high-throughput bacterial detection technique for clinical diagnostic applications. This thesis has thus applied the principles of metrology to generate, characterise and evaluate whole organism and DNA based quantitative control materials as an essential pre-requisite for the precise and accurate biological interpretation of both 16S profiling and metagenomic analysis of human diseases.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available