The InterPro protein families database: the classification resource after 15 years.

The InterPro database (http://www.ebi.ac.uk/interpro/) is a freely available resource that can be used to classify sequences into protein families and to predict the presence of important domains and sites. Central to the InterPro database are predictive models, known as signatures, from a range of different protein family databases that have different biological focuses and use different methodological approaches to classify protein families and domains. InterPro integrates these signatures, capitalizing on the respective strengths of the individual databases, to produce a powerful protein classification resource. Here, we report on the status of InterPro as it enters its 15th year of operation, and give an overview of new developments with the database and its associated Web interfaces and software. In particular, the new domain architecture search tool is described and the process of mapping of Gene Ontology terms to InterPro is outlined. We also discuss the challenges faced by the resource given the explosive growth in sequence data in recent years. InterPro (version 48.0) contains 36,766 member database signatures integrated into 26,238 InterPro entries, an increase of over 3993 entries (5081 signatures), since 2012.

InterProScan 5: genome-scale protein function classification.

MOTIVATION: Robust large-scale sequence analysis is a major challenge in modern genomic science, where biologists are frequently trying to characterize many millions of sequences. Here, we describe a new Java-based architecture for the widely used protein function prediction software package InterProScan. Developments include improvements and additions to the outputs of the software and the complete reimplementation of the software framework, resulting in a flexible and stable system that is able to use both multiprocessor machines and/or conventional clusters to achieve scalable distributed data analysis. InterProScan is freely available for download from the EMBl-EBI FTP site and the open source code is hosted at Google Code.

EBI metagenomics--a new resource for the analysis and archiving of metagenomic data.

Metagenomics is a relatively recently established but rapidly expanding field that uses high-throughput next-generation sequencing technologies to characterize the microbial communities inhabiting different ecosystems (including oceans, lakes, soil, tundra, plants and body sites). Metagenomics brings with it a number of challenges, including the management, analysis, storage and sharing of data. In response to these challenges, we have developed a new metagenomics resource (http://www.ebi.ac.uk/metagenomics/) that allows users to easily submit raw nucleotide reads for functional and taxonomic analysis by a state-of-the-art pipeline, and have them automatically stored (together with descriptive, standards-compliant metadata) in the European Nucleotide Archive.

Metagenomic analysis: the challenge of the data bonanza.

Several thousand metagenomes have already been sequenced, and this number is set to grow rapidly in the forthcoming years as the uptake of high-throughput sequencing technologies continues. Hand-in-hand with this data bonanza comes the computationally overwhelming task of analysis. Herein, we describe some of the bioinformatic approaches currently used by metagenomics researchers to analyze their data, the issues they face and the steps that could be taken to help overcome these challenges.

Protein complex prediction based on maximum matching with domain-domain interaction.

With the development of high-throughput methods for identifying protein-protein interactions, large scale interaction networks are available. Computational methods to analyze the networks to detect functional modules as protein complexes are becoming more important. However, most of the existing methods only make use of the protein-protein interaction networks without considering the structural limitations of proteins to bind together. In this paper, we design a new protein complex prediction method by extending the idea of using domain-domain interaction information. Here we formulate the problem into a maximum matching problem (which can be solved in polynomial time) instead of the binary integer linear programming approach (which can be NP-hard in the worst case). We also add a step to predict domain-domain interactions which first searches the database Pfam using the hidden Markov model and then predicts the domain-domain interactions based on the database DOMINE and InterDom which contain confirmed DDIs. By adding the domain-domain interaction prediction step, we have more edges in the DDI graph and the recall value is increased significantly (at least doubled) comparing with the method of Ozawa et al. (2010) [1] while the average precision value is slightly better. We also combine our method with three other existing methods, such as COACH, MCL and MCODE. Experiments show that the precision of the combined method is improved. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction.

Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation.

InterPro amalgamates predictive protein signatures from a number of well-known partner databases into a single resource. To aid with interpretation of results, InterPro entries are manually annotated with terms from the Gene Ontology (GO). The InterPro2GO mappings are comprised of the cross-references between these two resources and are the largest source of GO annotation predictions for proteins. Here, we describe the protocol by which InterPro curators integrate GO terms into the InterPro database. We discuss the unique challenges involved in integrating specific GO terms with entries that may describe a diverse set of proteins, and we illustrate, with examples, how InterPro hierarchies reflect GO terms of increasing specificity. We describe a revised protocol for GO mapping that enables us to assign GO terms to domains based on the function of the individual domain, rather than the function of the families in which the domain is found. We also discuss how taxonomic constraints are dealt with and those cases where we are unable to add any appropriate GO terms. Expert manual annotation of InterPro entries with GO terms enables users to infer function, process or subcellular information for uncharacterized sequences based on sequence matches to predictive models. Database URL: http://www.ebi.ac.uk/interpro. The complete InterPro2GO mappings are available at: ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/external2go/interpro2go.

InterPro in 2011: new developments in the family and domain prediction database.

InterPro (http://www.ebi.ac.uk/interpro/) is a database that integrates diverse information about protein families, domains and functional sites, and makes it freely available to the public via Web-based interfaces and services. Central to the database are diagnostic models, known as signatures, against which protein sequences can be searched to determine their potential function. InterPro has utility in the large-scale analysis of whole genomes and meta-genomes, as well as in characterizing individual protein sequences. Herein we give an overview of new developments in the database and its associated software since 2009, including updates to database content, curation processes and Web and programmatic interfaces.

Co-ordination of quorum-sensing regulation in Rhizobium leguminosarum by induction of an anti-repressor.

Analysis of quorum-sensing (QS) regulation in Rhizobium leguminosarum revealed an unusual type of gene regulation that relies on the population density-dependent accumulation of an anti-repressor. The cinS gene, which is co-transcribed with the N-acyl-homoserine-lactone synthase gene cinI, is required to fully induce rhiR and raiR, whose products, together with their partner AHL synthases, regulate other genes in a QS-regulated hierarchy. Purified CinS bound to the R. leguminosarum transcriptional regulator PraR, which repressed rhiR and raiR expression. PraR bound to the rhiR and raiR promoters and CinS displaced PraR from these promoters, thereby inducing their expression. Although induction of cinS required CinI-made AHL, it appears CinS does not require the AHL for its anti-repressor function. The LuxR-type regulator ExpR was also required for normal induction of rhiR and raiR and it appears that this occurs by ExpR repressing the transcription of praR. Therefore ExpR and CinS act independently to attenuate PraR action, ExpR by repressing its transcription and CinS by attenuating its repressive activity. Thus, as CinS accumulates in a population density-dependent manner it induces the QS hierarchy by relieving PraR-mediated repression of rhiR and raiR.

The InterPro BioMart: federated query and web service access to the InterPro Resource.

The InterPro BioMart provides users with query-optimized access to predictions of family classification, protein domains and functional sites, based on a broad spectrum of integrated computational models ('signatures') that are generated by the InterPro member databases: Gene3D, HAMAP, PANTHER, Pfam, PIRSF, PRINTS, ProDom, PROSITE, SMART, SUPERFAMILY and TIGRFAMs. These predictions are provided for all protein sequences from both the UniProt Knowledge Base and the UniParc protein sequence archive. The InterPro BioMart is supplementary to the primary InterPro web interface (http://www.ebi.ac.uk/interpro), providing a web service and the ability to build complex, custom queries that can efficiently return thousands of rows of data in a variety of formats. This article describes the information available from the InterPro BioMart and illustrates its utility with examples of how to build queries that return useful biological information. Database URL: http://www.ebi.ac.uk/interpro/biomart/martview.

InterPro: the integrative protein signature database.

The InterPro database (http://www.ebi.ac.uk/interpro/) integrates together predictive models or 'signatures' representing protein domains, families and functional sites from multiple, diverse source databases: Gene3D, PANTHER, Pfam, PIRSF, PRINTS, ProDom, PROSITE, SMART, SUPERFAMILY and TIGRFAMs. Integration is performed manually and approximately half of the total approximately 58,000 signatures available in the source databases belong to an InterPro entry. Recently, we have started to also display the remaining un-integrated signatures via our web interface. Other developments include the provision of non-signature data, such as structural data, in new XML files on our FTP site, as well as the inclusion of matchless UniProtKB proteins in the existing match XML files. The web interface has been extended and now links out to the ADAN predicted protein-protein interaction database and the SPICE and Dasty viewers. The latest public release (v18.0) covers 79.8% of UniProtKB (v14.1) and consists of 16 549 entries. InterPro data may be accessed either via the web address above, via web services, by downloading files by anonymous FTP or by using the InterProScan search software (http://www.ebi.ac.uk/Tools/InterProScan/).

Quorum-sensing-regulated transcriptional initiation of plasmid transfer and replication genes in Rhizobium leguminosarum biovar viciae.

Transfer of the Rhizobium leguminosarum biovar viciae symbiosis plasmid pRL1JI is regulated by a cascade of gene induction involving three LuxR-type quorum-sensing regulators, TraR, BisR and CinR. TraR induces the plasmid transfer traI-trb operon in a population-density-dependent manner in response to N-acylhomoserine lactones (AHLs) made by TraI. Expression of the traR gene is primarily induced by BisR in response to AHLs made by CinI, and expression of cinI is induced by CinR and repressed by BisR. Analysis of transcription initiation of cinI, traR and traI identified potential regulatory domains recognized by the CinR, BisR and TraR regulators. Deletion and mutation of the cinI promoter identified potential recognition motifs for activation by CinR and repression by BisR. Analysis of the DNA sequence upstream of traI and expression of transcriptional gene fusions revealed a predicted TraR-binding (tra-box) domain. Two transcript initiation sites were identified upstream of the plasmid replication gene repA, which is divergently transcribed from traI; one of these repA transcripts requires the quorum-sensing cascade mediated via BisR and TraR, showing that the pRL1JI plasmid replication genes are co-regulated with the plasmid transfer genes.

New developments in the InterPro database.

InterPro is an integrated resource for protein families, domains and functional sites, which integrates the following protein signature databases: PROSITE, PRINTS, ProDom, Pfam, SMART, TIGRFAMs, PIRSF, SUPERFAMILY, Gene3D and PANTHER. The latter two new member databases have been integrated since the last publication in this journal. There have been several new developments in InterPro, including an additional reading field, new database links, extensions to the web interface and additional match XML files. InterPro has always provided matches to UniProtKB proteins on the website and in the match XML file on the FTP site. Additional matches to proteins in UniParc (UniProt archive) are now available for download in the new match XML files only. The latest InterPro release (13.0) contains more than 13 000 entries, covering over 78% of all proteins in UniProtKB. The database is available for text- and sequence-based searches via a webserver (http://www.ebi.ac.uk/interpro), and for download by anonymous FTP (ftp://ftp.ebi.ac.uk/pub/databases/interpro). The InterProScan search tool is now also available via a web service at http://www.ebi.ac.uk/Tools/webservices/WSInterProScan.html.

Chloromethane-induced genes define a third C1 utilization pathway in Methylobacterium chloromethanicum CM4.

Methylobacterium chloromethanicum CM4 is an aerobic alpha-proteobacterium capable of growth with chloromethane as the sole carbon and energy source. Two proteins, CmuA and CmuB, were previously purified and shown to catalyze the dehalogenation of chloromethane and the vitamin B12-mediated transfer of the methyl group of chloromethane to tetrahydrofolate. Three genes located near cmuA and cmuB, designated metF, folD and purU and encoding homologs of methylene tetrahydrofolate (methylene-H4folate) reductase, methylene-H4folate dehydrogenase-methenyl-H4folate cyclohydrolase and formyl-H4folate hydrolase, respectively, suggested the existence of a chloromethane-specific oxidation pathway from methyl-tetrahydrofolate to formate in strain CM4. Hybridization and PCR analysis indicated that these genes were absent in Methylobacterium extorquens AM1, which is unable to grow with chloromethane. Studies with transcriptional xylE fusions demonstrated the chloromethane-dependent expression of these genes. Transcriptional start sites were mapped by primer extension and allowed to define three transcriptional units, each likely comprising several genes, that were specifically expressed during growth of strain CM4 with chloromethane. The DNA sequences of the deduced promoters display a high degree of sequence conservation but differ from the Methylobacterium promoters described thus far. As shown previously for purU, inactivation of the metF gene resulted in a CM4 mutant unable to grow with chloromethane. Methylene-H4folate reductase activity was detected in a cell extract of strain CM4 only in the presence of chloromethane but not in the metF mutant. Taken together, these data provide evidence that M. chloromethanicum CM4 requires a specific set of tetrahydrofolate-dependent enzymes for growth with chloromethane.