Accurate quantification of the microbiome in the sinus and the bloodstream

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Accurate quantification of the microbiome in the sinus and the bloodstream
Hyun, Hwi
Kwon, Taejoon
Microbiome, Taxonomy assignment, Sepsis, Rhinosinusitis
Issue Date
Ulsan National Institute of Science and Technology
Since the microbiome exists across the body, it has been a long time to try to understand the microbiome’s relation between the host’s health and disease. Represented by Human Microbiome Project (HMP) that shows the variety of microbiome exists in human, previous studies are proved there is a myriad of interactions encompassed the host body which includes an immune response, cell differentiation, nerve system, and other fields1–5. However, most studies are focused on the gut microbiome compared to other organs6 which confines understanding of host-microbiome relation. Indeed, a less focused microbiome with various sites also has an important role in host health. For example, the blood microbiome is associated with bloodstream infection (BSI) that extensive danger to human health7. Also, the sinus microbiome is related to rhinosinusitis caused by inflammation of the sinus that prompts asthma and intracranial complications8,9. Additionally, to investigate the host-related microbiome, various kinds of reference files and alignment tools are suggested. However, verification of its product and revision for performance is often neglected. _x000D_ One of the difficult points is extracting the DNA and RNA from the bacterial cell with handling the low microbial load samples. Additionally, the absence of a validated method for microbiome analysis hinders precise comprehension of its nature. Therefore, in this dissertation, I suggest improved methods to overcome the presented problems that exist across the blood and sinus that are related to sampling the low number of the microbiome. Also, by analyzing the bacterial population, I try to reveal the changes in the microbiome that are related to the alteration of the environment that the host provides._x000D_ Here, I devised the method for a precise taxonomy assignment that is confirmed with the ground truth, a mock community. With a naive Bayesian classifier, I point out how to choose the confidence score base on the clustering and refining of the current reference file. Commonly, reference files nomenclate the organisms based on the whole 16S rRNA gene sequence10. However, it is not fit with the ordinary sequencing method. As the general sequencing target is the V34 region of the 16S rRNA gene that only covers two variable regions of the nine, it can lead to unintended output that interrupts correct understanding. Therefore, I performed an accurate result of the taxonomy assignment with a refined reference file and applied it to further studies.
Department of Biomedical Engineering
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