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

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Summary
This summary is machine-generated.

MatrisomeDB now offers expanded extracellular matrix (ECM) proteomic data for 24 new tissues, enhancing matrisome research. New visualizations and tools improve data accessibility and analysis for scientists.

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Area of Science:

  • Biochemistry
  • Proteomics
  • Bioinformatics

Background:

  • The extracellular matrix (ECM) provides structural organization for cells, tissues, and organs.
  • Mass-spectrometry-based proteomics is crucial for profiling the ECM, known as the matrisome.
  • MatrisomeDB was initially released in 2020 to aid non-specialists in reusing ECM proteomic datasets.

Purpose of the Study:

  • To expand MatrisomeDB with new curated ECM proteomic studies.
  • To improve data visualization and accessibility for ECM research.
  • To provide tools for enhanced analysis of matrisome data.

Main Methods:

  • Curated and integrated data from 25 new studies on the ECM of 24 new tissues.
  • Enhanced data visualization with peptide and post-translational modification mapping onto protein structures.
  • Developed an abstract-mining tool for protein enrichment analysis.

Main Results:

  • MatrisomeDB size has more than doubled, achieving near-complete coverage of the in-silico predicted matrisome.
  • New visualizations map detected peptides and post-translational modifications onto protein domains and 3D structures.
  • The abstract-mining tool identifies protein enrichment in specific studies.

Conclusions:

  • The expanded MatrisomeDB significantly enhances the accessibility and utility of ECM proteomic data.
  • Advanced visualization and analysis tools facilitate deeper insights into matrisome composition and function.
  • MatrisomeDB serves as a comprehensive resource for researchers studying the extracellular matrix.