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. 2016 Jan 4;44(D1):D1251-7.
doi: 10.1093/nar/gkv1003. Epub 2015 Oct 7.

MitoCarta2.0: an updated inventory of mammalian mitochondrial proteins

Sarah E Calvo  1 , Karl R Clauser  2 , Vamsi K Mootha  3
Affiliations

MitoCarta2.0: an updated inventory of mammalian mitochondrial proteins

Sarah E Calvo et al. Nucleic Acids Res. .

Abstract

Mitochondria are complex organelles that house essential pathways involved in energy metabolism, ion homeostasis, signalling and apoptosis. To understand mitochondrial pathways in health and disease, it is crucial to have an accurate inventory of the organelle's protein components. In 2008, we made substantial progress toward this goal by performing in-depth mass spectrometry of mitochondria from 14 organs, epitope tagging/microscopy and Bayesian integration to assemble MitoCarta (www.broadinstitute.org/pubs/MitoCarta): an inventory of genes encoding mitochondrial-localized proteins and their expression across 14 mouse tissues. Using the same strategy we have now reconstructed this inventory separately for human and for mouse based on (i) improved gene transcript models, (ii) updated literature curation, including results from proteomic analyses of mitochondrial sub-compartments, (iii) improved homology mapping and (iv) updated versions of all seven original data sets. The updated human MitoCarta2.0 consists of 1158 human genes, including 918 genes in the original inventory as well as 240 additional genes. The updated mouse MitoCarta2.0 consists of 1158 genes, including 967 genes in the original inventory plus 191 additional genes. The improved MitoCarta 2.0 inventory provides a molecular framework for system-level analysis of mammalian mitochondria.

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Figures

Figure 1.
Figure 1.
An updated inventory of mitochondrial proteins. MitoCarta2.0 is an inventory of 1158 human genes encoding proteins with strong support of mitochondrial localization. It is built by combining a large training set of 960 mitochondrial genes (based on literature curation, APEX-based mass spectrometry experiments and GFP-tagging/microscopy) with a Bayesian integration of seven genome-scale data sets, updated extensively from the previous MitoCarta1.0 inventory.
Figure 2.
Figure 2.
Naïve Bayes integration improves accuracy over individual data sources. (A) Accuracy of each of seven data sources and the Maestro naïve Bayes integration, calculated from the human Tmito and Tnon_mito genes. (B) LogOdds scores for gene ECHDC1, in MitoCarta2.0 but not MitoCarta1.0, highlights improvements in three data sources (C) LogOdds scores for gene NFXL1, in MitoCarta1.0 but not MitoCarta2.0, highlights improvements to RefSeq gene models—as previous 58aa protein fragment XP_001052092 has been replaced with 918aa full-length protein NP_598682. (D) ROC curve shows accuracy of each data source individually as well as the combined naïve Bayes Integration. Black circle indicates 5% FDR threshold.
Figure 3.
Figure 3.
Overlap between MitoCarta versions
See this image and copyright information in PMC

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