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Profiling and annotation of human kidney glomerulus proteome
http://hdl.handle.net/10191/24546
http://hdl.handle.net/10191/24546ea94e997-2a6a-465f-95ba-a958d6749818
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本文 (2.1 MB)
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要旨 (203.2 kB)
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| Item type | 学位論文 / Thesis or Dissertation(1) | |||||
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| 公開日 | 2014-05-28 | |||||
| タイトル | ||||||
| タイトル | Profiling and annotation of human kidney glomerulus proteome | |||||
| タイトル | ||||||
| タイトル | Profiling and annotation of human kidney glomerulus proteome | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Human glomerulus proteome | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Human plasma proteome | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Human urine proteome | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Mouse glomerulus proteome | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Cross-reference analysis | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Bioinformatics | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Biomarkers | |||||
| 資源タイプ | ||||||
| 資源 | http://purl.org/coar/resource_type/c_46ec | |||||
| タイプ | thesis | |||||
| その他のタイトル | ||||||
| その他のタイトル | ヒト腎糸球体プロテオームの網羅的解析とその特徴について | |||||
| 著者 |
Cui, Zhenyu
× Cui, Zhenyu |
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| 著者別名 | ||||||
| 識別子Scheme | WEKO | |||||
| 識別子 | 50162 | |||||
| 姓名 | 崔, 珍玉 | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Background: The comprehensive analysis of human kidney glomerulus we previously performed using highly purified glomeruli, provided a dataset of 6,686 unique proteins representing 2,966 distinct genes. This dataset, however, contained considerable redundancy resulting from identification criteria under which all the proteins matched with the same set of peptides and its subset were reported as identified proteins. In this study we reanalyzed the raw data using the Mascot search engine and highly stringent criteria in order to select proteins with the highest scores matching peptides with scores exceeding the “Identity Threshold” and one or more unique peptides. This enabled us to exclude proteins with lower scores which only matched the same set of peptides or its subset. This approach provided a high-confidence, non-redundant dataset of identified proteins for extensive profiling, annotation, and comparison with other proteome datasets that can provide biologically relevant knowledge of glomerulus proteome. Results: Protein identification using the Mascot search engine under highly stringent, computational strategy generated a non-redundant dataset of 1,817 proteins representing 1,478 genes. These proteins were represented by 2-D protein array specifying observed molecular weight and isoelectric point range of identified proteins to demonstrate differences in the observed and calculated physicochemical properties. Characteristics of glomerulus proteome could be illustrated by GO analysis and protein classification. The depth of proteomic analysis was well documented via comparison of the dynamic range of identified proteins with other proteomic analyses of human glomerulus, as well as a high coverage of biologically important pathways. Comparison of glomerulus proteome with human plasma and urine proteomes, provided by comprehensive analysis, suggested the extent and characteristics of proteins contaminated from plasma and excreted into urine, respectively. Among the latter proteins, several were demonstrated to be highly or specifically localized in the glomerulus by cross-reference analysis with the Human Protein Atlas database, and could be biomarker candidates for glomerular injury. Furthermore, comparison of ortholog proteins identified in human and mouse glomeruli suggest some biologically significant differences in glomerulus proteomes between the two species. Conclusions: A high-confidence, non-redundant dataset of proteins created by comprehensive proteomic analysis could provide a more extensive understanding of human glomerulus proteome and could be useful as a resource for the discovery of biomarkers and disease-relevant proteins. | |||||
| 内容記述 | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | 学位の種類: 博士（医学）. 報告番号: 甲第3810号. 学位記番号: 新大院博（医）甲第562号. 学位授与年月日: 平成25年9月20日 | |||||
| 書誌情報 | 発行日 2013-09-20 | |||||
| 出版者 | ||||||
| 出版者 | 新潟大学 | |||||
| DOI | ||||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | info:doi/10.1186/1477-5956-11-13 | |||||
| 権利 | ||||||
| 権利情報 | © 2013 Cui et al.; licensee BioMed Central Ltd. | |||||
| 著者版フラグ | ||||||
| 値 | ETD | |||||
| 学位名 | ||||||
| 学位名 | 博士（医学） | |||||
| 学位授与機関 | ||||||
| 学位授与機関名 | 新潟大学 | |||||
| 学位授与年月日 | ||||||
| 学位授与年月日 | 2013-09-20 | |||||
| 学位授与番号 | ||||||
| 学位授与番号 | 13101A3810 | |||||
| 学位記番号 | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | 新大院博（医）甲第562号 | |||||
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Cite as
Cui, Zhenyu, 2013, Profiling and annotation of human kidney glomerulus proteome: 新潟大学.
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