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Profiling and annotation of human kidney glomerulus proteome

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 un...

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Autores principales: Cui, Zenyui, Yoshida, Yutaka, Xu, Bo, Zhang, Ying, Nameta, Masaaki, Magdeldin, Sameh, Makiguchi, Tomoo, Ikoma, Toshikazu, Fujinaka, Hidehiko, Yaoita, Eishin, Yamamoto, Tadashi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3639854/
https://www.ncbi.nlm.nih.gov/pubmed/23566277
http://dx.doi.org/10.1186/1477-5956-11-13
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author Cui, Zenyui
Yoshida, Yutaka
Xu, Bo
Zhang, Ying
Nameta, Masaaki
Magdeldin, Sameh
Makiguchi, Tomoo
Ikoma, Toshikazu
Fujinaka, Hidehiko
Yaoita, Eishin
Yamamoto, Tadashi
author_facet Cui, Zenyui
Yoshida, Yutaka
Xu, Bo
Zhang, Ying
Nameta, Masaaki
Magdeldin, Sameh
Makiguchi, Tomoo
Ikoma, Toshikazu
Fujinaka, Hidehiko
Yaoita, Eishin
Yamamoto, Tadashi
author_sort Cui, Zenyui
collection PubMed
description 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.
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spelling pubmed-36398542013-05-01 Profiling and annotation of human kidney glomerulus proteome Cui, Zenyui Yoshida, Yutaka Xu, Bo Zhang, Ying Nameta, Masaaki Magdeldin, Sameh Makiguchi, Tomoo Ikoma, Toshikazu Fujinaka, Hidehiko Yaoita, Eishin Yamamoto, Tadashi Proteome Sci Research 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. BioMed Central 2013-04-08 /pmc/articles/PMC3639854/ /pubmed/23566277 http://dx.doi.org/10.1186/1477-5956-11-13 Text en Copyright © 2013 Cui et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Cui, Zenyui
Yoshida, Yutaka
Xu, Bo
Zhang, Ying
Nameta, Masaaki
Magdeldin, Sameh
Makiguchi, Tomoo
Ikoma, Toshikazu
Fujinaka, Hidehiko
Yaoita, Eishin
Yamamoto, Tadashi
Profiling and annotation of human kidney glomerulus proteome
title Profiling and annotation of human kidney glomerulus proteome
title_full Profiling and annotation of human kidney glomerulus proteome
title_fullStr Profiling and annotation of human kidney glomerulus proteome
title_full_unstemmed Profiling and annotation of human kidney glomerulus proteome
title_short Profiling and annotation of human kidney glomerulus proteome
title_sort profiling and annotation of human kidney glomerulus proteome
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3639854/
https://www.ncbi.nlm.nih.gov/pubmed/23566277
http://dx.doi.org/10.1186/1477-5956-11-13
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