Database Commons

a catalog of worldwide biological databases

Increasing numbers of diseases are associated with mitochondrial dysfunction. This is unsurprising given mitochondria have major roles in bioenergy generation, signalling, detoxification, apoptosis and biosynthesis. However, fundamental questions of mitochondrial biology remain, including: which nuclear genes encode mitochondrial proteins; how their expression varies with tissue; and which are associated with disease. But experiments to catalogue the mitochondrial proteome are incomplete and sometimes contradictory. This arises because the mitochondrial proteome has tissue- and stage-specific variability, plus differences among experimental techniques and localization evidence types used. This leads to limitations in each technique's coverage and inevitably conflicting results. To support identification of mitochondrial proteins, we developed MitoMiner (http://mitominer.mrc-mbu.cam.ac.uk/), a database combining evidence of mitochondrial localization with information from public resources. Here we report upgrades to MitoMiner, including its re-engineering to be gene-centric to enable easier sharing of evidence among orthologues and support next generation sequencing, plus new data sources, including expression in different tissues, information on phenotypes and diseases of genetic mutations and a new mitochondrial proteome catalogue. MitoMiner is a powerful platform to investigate mitochondrial localization by providing a unique combination of experimental sub-cellular localization datasets, tissue expression, predictions of mitochondrial targeting sequences, gene annotation and links to phenotype and disease.

Mitochondrial proteins remain the subject of intense research interest due to their implication in an increasing number of different conditions including mitochondrial and metabolic disease, cancer, and neuromuscular degenerative and age-related disorders. However, the mitochondrial proteome has yet to be accurately and comprehensively defined, despite many studies. To support mitochondrial research, we developed MitoMiner (http://mitominer.mrc-mbu.cam.ac.uk), a freely accessible mitochondrial proteomics database. MitoMiner integrates different types of subcellular localisation evidence with protein information from public resources, and so provides a comprehensive central resource for data on mitochondrial protein localisation. Here we report important updates to the database including the addition of subcellular immunofluorescent staining results from the Human Protein Atlas, computational predictions of mitochondrial targeting sequences, and additional large-scale mass-spectrometry and GFP tagging data sets. This evidence is shared across the 12 species in MitoMiner (now including Schizosaccharomyces pombe) by homology mapping. MitoMiner provides multiple ways of querying the data including simple text searches, predefined queries and custom queries created using the interactive QueryBuilder. For remote programmatic access, API's are available for several programming languages. This combination of data and flexible querying makes MitoMiner a unique platform to investigate mitochondrial proteins, with application in mitochondrial research and prioritising candidate mitochondrial disease genes. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

MitoMiner (http://mitominer.mrc-mbu.cam.ac.uk/) is a data warehouse for the storage and analysis of mitochondrial proteomics data gathered from publications of mass spectrometry and green fluorescent protein tagging studies. In MitoMiner, these data are integrated with data from UniProt, Gene Ontology, Online Mendelian Inheritance in Man, HomoloGene, Kyoto Encyclopaedia of Genes and Genomes and PubMed. The latest release of MitoMiner stores proteomics data sets from 46 studies covering 11 different species from eumetazoa, viridiplantae, fungi and protista. MitoMiner is implemented by using the open source InterMine data warehouse system, which provides a user interface allowing users to upload data for analysis, personal accounts to store queries and results and enables queries of any data in the data model. MitoMiner also provides lists of proteins for use in analyses, including the new MitoMiner mitochondrial proteome reference sets that specify proteins with substantial experimental evidence for mitochondrial localization. As further mitochondrial proteomics data sets from normal and diseased tissue are published, MitoMiner can be used to characterize the variability of the mitochondrial proteome between tissues and investigate how changes in the proteome may contribute to mitochondrial dysfunction and mitochondrial-associated diseases such as cancer, neurodegenerative diseases, obesity, diabetes, heart failure and the ageing process.

Mitochondria are a vital component of eukaryotic cells with functions that extend beyond energy production to include metabolism, signaling, cell growth, and apoptosis. Their dysfunction is implicated in a large number of metabolic, degenerative, and age-related human diseases. Therefore, it is important to characterize and understand the mitochondrion. Many experiments have attempted to define the mitochondrial proteome, resulting in large and complex data sets that are difficult to analyze. To address this, we developed a new public resource for the storage and investigation of this mitochondrial proteomics data, called MitoMiner, that uses a model to describe the proteomics data and associated biological information. The proteomics data of 33 publications from both mass spectrometry and green fluorescent protein tagging experiments were imported and integrated with protein annotation from UniProt and genome projects, metabolic pathway data from Kyoto Encyclopedia of Genes and Genomes, homology relationships from HomoloGene, and disease information from Online Mendelian Inheritance in Man. We demonstrate the strengths of MitoMiner by investigating these data sets and show that the number of different mitochondrial proteins that have been reported is about 3700, although the number of proteins common to both animals and yeast is about 1400, and membrane proteins appear to be underrepresented. Furthermore analysis indicated that enzymes of some cytosolic metabolic pathways are regularly detected in mitochondrial proteomics experiments, suggesting that they are associated with the outside of the outer mitochondrial membrane. The data and advanced capabilities of MitoMiner provide a framework for further mitochondrial analysis and future systems level modeling of mitochondrial physiology.