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Updated: Jun 25, 2026
09:04
Two-Step Tag-Free Isolation of Mitochondria for Improved Protein Discovery and Quantification
Published on: June 2, 2023
MitoMiner, an integrated database for the storage and analysis of mitochondrial proteomics data
Anthony C Smith1, Alan J Robinson
1MRC Mitochondrial Biology Unit, Hills Road, Cambridge CB20XY, United Kingdom.
Molecular & Cellular Proteomics : MCP
|February 12, 2009
Summary
MitoMiner is a new public resource that integrates mitochondrial proteomics data, aiding the analysis of mitochondrial proteins and their roles in human diseases. It helps researchers understand mitochondrial function and dysfunction.
Area of Science:
- Cell Biology
- Biochemistry
- Bioinformatics
Background:
- Mitochondria are crucial for cellular functions beyond energy production, including metabolism, signaling, cell growth, and apoptosis.
- Mitochondrial dysfunction is linked to numerous metabolic, degenerative, and age-related human diseases.
- Characterizing the mitochondrial proteome is essential but challenging due to large, complex datasets.
Purpose of the Study:
- To develop a public resource, MitoMiner, for storing and investigating mitochondrial proteomics data.
- To integrate diverse biological information with proteomics data for enhanced analysis.
- To provide a framework for further mitochondrial research and systems-level modeling.
Main Methods:
- Developed MitoMiner, a public resource for mitochondrial proteomics data.
- Integrated data from 33 publications (mass spectrometry, GFP tagging) with UniProt, KEGG, HomoloGene, and OMIM.
- Utilized a data model to describe proteomics data and associated biological information.
Main Results:
- Identified approximately 3700 unique mitochondrial proteins.
- Found about 1400 proteins common to both animals and yeast.
- Observed underrepresentation of mitochondrial membrane proteins and detection of cytosolic metabolic enzymes on the outer mitochondrial membrane.
Conclusions:
- MitoMiner facilitates the analysis of complex mitochondrial proteomics data.
- The resource aids in understanding mitochondrial protein composition and potential mislocalizations.
- Provides a foundation for advanced mitochondrial research and systems biology approaches.
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