University of Illinois at Chicago
Shao et al_NAR_2023.pdf (2.7 MB)

MatrisomeDB 2.0: 2023 updates to the ECM-protein knowledge database

Download (2.7 MB)
journal contribution
posted on 2023-08-22, 21:03 authored by Xinhao Shao, Clarissa D Gomez, Nandini Kapoor, James M Considine, Christopher Grams, Yu Gao, Alexandra NabaAlexandra Naba
The extracellular matrix (ECM) is a complex assembly of proteins that constitutes the scaffold organizing cells, tissues, and organs. Over the past decade, mass-spectrometry-based proteomics has become the method of choice to profile the composition of the ECM, or the matrisome, of tissues. To assist non-specialists with the reuse of ECM proteomic datasets, we released MatrisomeDB ( in 2020. Here, we report the expansion of the database to include 25 new curated studies on the ECM of 24 new tissues in addition to datasets on tissues previously included, more than doubling the size of the original database and achieving near-complete coverage of the in-silico predicted matrisome. We further enhanced data visualization by maps of peptides and post-translational-modifications detected onto domain-based representations and 3D structures of ECM proteins. We also referenced external resources to facilitate the design of targeted mass spectrometry assays. Last, we implemented an abstract-mining tool that generates an enrichment word cloud from abstracts of studies in which a queried protein is found with higher confidence and higher abundance relative to other studies in MatrisomeDB.


Highly sensitive proteomics method to probe cell heterogeneity at single cell resolution | Funder: National Institutes of Health (National Institute of General Medical Sciences) | Grant ID: R35GM133416

Thinking outside the cell: Leveraging HuBMAP data to build the human ECM atlas | Funder: National Institutes of Health (National Human Genome Research Institute) | Grant ID: U01HG012680

Enhanced mass-spectrometry-based approaches for in-depth profiling of the cancer extracellular matrix | Funder: National Institutes of Health (National Cancer Institute) | Grant ID: R21CA261642



Shao, X., Gomez, C. D., Kapoor, N., Considine, J. M., Grams, C., Gao, Y.Naba, A. (2023). MatrisomeDB 2.0: 2023 updates to the ECM-protein knowledge database. Nucleic Acids Research, 51(D1), gkac1009--.


Oxford University Press (OUP)


  • en