MitoMiner v3.1, an update on the mitochondrial proteomics database.

Area of Science:

• Biochemistry
• Molecular Biology
• Genetics

Background:

• Mitochondrial proteins are crucial in various diseases, including metabolic disorders, cancer, and neurodegenerative conditions.
• Accurate and comprehensive definition of the mitochondrial proteome is essential but remains challenging.
• Existing research highlights the need for integrated resources to study mitochondrial proteins.

Purpose of the Study:

• To present significant updates to MitoMiner, a freely accessible database for mitochondrial proteomics.
• To enhance the resource with new data types and expand species coverage.
• To provide a comprehensive platform for investigating mitochondrial proteins and disease genes.

Main Methods:

• Integration of subcellular immunofluorescent staining data from the Human Protein Atlas.
• Inclusion of computational predictions for mitochondrial targeting sequences.
• Addition of large-scale mass-spectrometry and GFP tagging datasets.
• Homology mapping to share evidence across 12 species, including Schizosaccharomyces pombe.
• Development of multiple querying functionalities: text, predefined, and custom (QueryBuilder).
• Provision of APIs for remote programmatic access.

Main Results:

• MitoMiner now incorporates diverse evidence, including experimental and computational data, for mitochondrial protein localization.
• The database supports research across 12 species through homology mapping.
• Flexible querying options and programmatic access facilitate data exploration.
• The updated MitoMiner serves as a valuable resource for mitochondrial research.

Conclusions:

• MitoMiner provides a unique and comprehensive platform for studying mitochondrial proteins.
• The database aids in prioritizing candidate genes for mitochondrial diseases.
• These updates significantly enhance the utility of MitoMiner for the research community.