MAPU 2.0: high-accuracy proteomes mapped to genomes

Abstract

The MAPU 2.0 database contains proteomes of organelles, tissues and cell types measured by mass spectrometry (MS)-based proteomics. In contrast to other databases it is meant to contain a limited number of experiments and only those with very high-resolution and -accuracy data. MAPU 2.0 displays the proteomes of organelles, tissues and body fluids or conversely displays the occurrence of proteins of interest in all these proteomes. The new release addresses MS-specific problems including ambiguous peptide-to-protein assignments and it provides insight into general functional features on the protein level ranging from gene ontology classification to comprehensive SwissProt annotation. Moreover, the derived proteomic data are used to annotate the genomes using Distributed Annotation Service (DAS) via EnsEMBL services. MAPU 2.0 is a model for a database specifically designed for high-accuracy proteomics and a member of the ProteomExchange Consortium. It is available on line at http://www.mapuproteome.com.

Figure 1.

To retrieve proteomic data for a protein of interest, one can search organism specifically via accession number, gene symbol, protein description, protein name or peptide sequence (left panel). If there are several hits for a query, all potential proteins of interest are listed (middle panel). Proteins that have been identified in any of the projects in MAPU 2.0 are shown in red. The final result page provides a total overview of cell types and tissues that contain the protein of interest (right panel).

Figure 2.

For each project, all measured peptides are listed along with validation scores such as the Mascot protein identification score.

Figure 3.

For each protein that has a SwissProt accession number, general features such as active sites, domains and motifs are displayed and mapped to the entry of the database that was used for identification.

Figure 4.

The genome annotation section of MAPU 2.0 provides insight into the number of identified gene transcripts. It links each detected transcript to the EnsEMBL database, which illustrates gene features derived from proteomic approaches via the MAPU 2.0 and PHOSIDA DAS sources.