MatrisomeDB: the ECM-protein knowledge database

Author:

Shao Xinhao1,Taha Isra N2,Clauser Karl R3,Gao Yu (Tom)14,Naba Alexandra24ORCID

Affiliation:

1. College of Pharmacy, University of Illinois at Chicago, Chicago, IL 60612, USA

2. Department of Physiology and Biophysics, University of Illinois at Chicago, Chicago, IL 60612, USA

3. Broad Institute, Cambridge, MA 02139, USA

4. University of Illinois at Chicago Cancer Center, Chicago, IL 60612, USA

Abstract

Abstract 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.

Funder

Department of Physiology and Biophysics at the University of Illinois at Chicago

College of Pharmacy

University of Illinois at Chicago

Publisher

Oxford University Press (OUP)

Subject

Genetics

Reference59 articles.

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