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MatrisomeDB: the ECM-protein knowledge database
The extracellular matrix (ECM) is a complex and dynamic meshwork of cross-linked proteins that supports cell polarization and functions and tissue organization and homeostasis. Over the past few decades, mass-spectrometry-based proteomics has emerged as the method of choice to characterize the compo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6943062/ https://www.ncbi.nlm.nih.gov/pubmed/31586405 http://dx.doi.org/10.1093/nar/gkz849 |
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author | Shao, Xinhao Taha, Isra N Clauser, Karl R Gao, Yu (Tom) Naba, Alexandra |
author_facet | Shao, Xinhao Taha, Isra N Clauser, Karl R Gao, Yu (Tom) Naba, Alexandra |
author_sort | Shao, Xinhao |
collection | PubMed |
description | The extracellular matrix (ECM) is a complex and dynamic meshwork of cross-linked proteins that supports cell polarization and functions and tissue organization and homeostasis. Over the past few decades, mass-spectrometry-based proteomics has emerged as the method of choice to characterize the composition of the ECM of normal and diseased tissues. Here, we present a new release of MatrisomeDB, a searchable collection of curated proteomic data from 17 studies on the ECM of 15 different normal tissue types, six cancer types (different grades of breast cancers, colorectal cancer, melanoma, and insulinoma) and other diseases including vascular defects and lung and liver fibroses. MatrisomeDB (http://www.pepchem.org/matrisomedb) was built by retrieving raw mass spectrometry data files and reprocessing them using the same search parameters and criteria to allow for a more direct comparison between the different studies. The present release of MatrisomeDB includes 847 human and 791 mouse ECM proteoforms and over 350 000 human and 600 000 mouse ECM-derived peptide-to-spectrum matches. For each query, a hierarchically-clustered tissue distribution map, a peptide coverage map, and a list of post-translational modifications identified, are generated. MatrisomeDB is the most complete collection of ECM proteomic data to date and allows the building of a comprehensive ECM atlas. |
format | Online Article Text |
id | pubmed-6943062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-69430622020-01-08 MatrisomeDB: the ECM-protein knowledge database Shao, Xinhao Taha, Isra N Clauser, Karl R Gao, Yu (Tom) Naba, Alexandra Nucleic Acids Res Database Issue The extracellular matrix (ECM) is a complex and dynamic meshwork of cross-linked proteins that supports cell polarization and functions and tissue organization and homeostasis. Over the past few decades, mass-spectrometry-based proteomics has emerged as the method of choice to characterize the composition of the ECM of normal and diseased tissues. Here, we present a new release of MatrisomeDB, a searchable collection of curated proteomic data from 17 studies on the ECM of 15 different normal tissue types, six cancer types (different grades of breast cancers, colorectal cancer, melanoma, and insulinoma) and other diseases including vascular defects and lung and liver fibroses. MatrisomeDB (http://www.pepchem.org/matrisomedb) was built by retrieving raw mass spectrometry data files and reprocessing them using the same search parameters and criteria to allow for a more direct comparison between the different studies. The present release of MatrisomeDB includes 847 human and 791 mouse ECM proteoforms and over 350 000 human and 600 000 mouse ECM-derived peptide-to-spectrum matches. For each query, a hierarchically-clustered tissue distribution map, a peptide coverage map, and a list of post-translational modifications identified, are generated. MatrisomeDB is the most complete collection of ECM proteomic data to date and allows the building of a comprehensive ECM atlas. Oxford University Press 2020-01-08 2019-10-05 /pmc/articles/PMC6943062/ /pubmed/31586405 http://dx.doi.org/10.1093/nar/gkz849 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Database Issue Shao, Xinhao Taha, Isra N Clauser, Karl R Gao, Yu (Tom) Naba, Alexandra MatrisomeDB: the ECM-protein knowledge database |
title | MatrisomeDB: the ECM-protein knowledge database |
title_full | MatrisomeDB: the ECM-protein knowledge database |
title_fullStr | MatrisomeDB: the ECM-protein knowledge database |
title_full_unstemmed | MatrisomeDB: the ECM-protein knowledge database |
title_short | MatrisomeDB: the ECM-protein knowledge database |
title_sort | matrisomedb: the ecm-protein knowledge database |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6943062/ https://www.ncbi.nlm.nih.gov/pubmed/31586405 http://dx.doi.org/10.1093/nar/gkz849 |
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