DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Lee, Sang Yup | - |
dc.contributor.advisor | 이상엽 | - |
dc.contributor.author | Gu, Changdai | - |
dc.date.accessioned | 2019-09-03T02:43:44Z | - |
dc.date.available | 2019-09-03T02:43:44Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=843197&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/266340 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 생명화학공학과, 2019.2,[iv, 47 p. :] | - |
dc.description.abstract | Human gut microbiota is ecological community of commensal microorganisms, which mediates human metabolisms. Recent studies have reported pathologic effects by changes in gut microbiota composition. However, microenvironment of intestinal lumen derived by gut microbiota metabolism have not well elucidated, which is required to develop personal therapeutic strategy for gut microbiota-related diseases. In this study, a platform was developed to collect personal taxon abundance dataset, automatically reconstruct genome-scale metabolic models (GEMs) of personal gut microbiota, and predict metabolic flux distribution of gut microbiota GEMs. For demonstration, 408 taxon abundance data of a colon cancer study were analyzed, and personal GEMs of gut microbiota were reconstructed. As a result, we found 9 taxa enriched in gut microbiota of colon cancer, including Staphylococcus aureus and Peptostreptococcus anaerobius, and altered metabolism by these species in gut microbiota GEMs of colon cancer. Also, using human context-specific GEMs, metabolic flux of colon cancer was analyzed, and we found possible metabolites related to colon cancer development. We ensure that this platform can be used to investigate metabolism of personal microbiota, eventually to find therapeutic strategy such as pre/probiotics. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | gut microbiota▼ametabolic modeling▼ametabolic flux prediction▼acolorectal cancer | - |
dc.subject | 장내 미생물▼a대사 모델링▼a대사 흐름 예측▼a대장암 | - |
dc.title | Automatic metabolic reconstruction of disease-specific human microbiota – colorectal cancer as an example | - |
dc.title.alternative | 자동화 된 질병 관련 인체 장내미생물의 대사 모델 구축 및 대장암에 대한 적용 연구 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :생명화학공학과, | - |
dc.contributor.alternativeauthor | 구창대 | - |
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