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1.  Evolution of the Ferric Reductase Domain (FRD) Superfamily: Modularity, Functional Diversification, and Signature Motifs 
PLoS ONE  2013;8(3):e58126.
A heme-containing transmembrane ferric reductase domain (FRD) is found in bacterial and eukaryotic protein families, including ferric reductases (FRE), and NADPH oxidases (NOX). The aim of this study was to understand the phylogeny of the FRD superfamily. Bacteria contain FRD proteins consisting only of the ferric reductase domain, such as YedZ and short bFRE proteins. Full length FRE and NOX enzymes are mostly found in eukaryotic cells and all possess a dehydrogenase domain, allowing them to catalyze electron transfer from cytosolic NADPH to extracellular metal ions (FRE) or oxygen (NOX). Metazoa possess YedZ-related STEAP proteins, possibly derived from bacteria through horizontal gene transfer. Phylogenetic analyses suggests that FRE enzymes appeared early in evolution, followed by a transition towards EF-hand containing NOX enzymes (NOX5- and DUOX-like). An ancestral gene of the NOX(1-4) family probably lost the EF-hands and new regulatory mechanisms of increasing complexity evolved in this clade. Two signature motifs were identified: NOX enzymes are distinguished from FRE enzymes through a four amino acid motif spanning from transmembrane domain 3 (TM3) to TM4, and YedZ/STEAP proteins are identified by the replacement of the first canonical heme-spanning histidine by a highly conserved arginine. The FRD superfamily most likely originated in bacteria.
doi:10.1371/journal.pone.0058126
PMCID: PMC3591440  PMID: 23505460
2.  Toward community standards in the quest for orthologs 
Bioinformatics  2012;28(6):900-904.
The identification of orthologs—genes pairs descended from a common ancestor through speciation, rather than duplication—has emerged as an essential component of many bioinformatics applications, ranging from the annotation of new genomes to experimental target prioritization. Yet, the development and application of orthology inference methods is hampered by the lack of consensus on source proteomes, file formats and benchmarks. The second ‘Quest for Orthologs’ meeting brought together stakeholders from various communities to address these challenges. We report on achievements and outcomes of this meeting, focusing on topics of particular relevance to the research community at large. The Quest for Orthologs consortium is an open community that welcomes contributions from all researchers interested in orthology research and applications.
Contact: dessimoz@ebi.ac.uk
doi:10.1093/bioinformatics/bts050
PMCID: PMC3307119  PMID: 22332236
3.  Conceptual framework and pilot study to benchmark phylogenomic databases based on reference gene trees 
Briefings in Bioinformatics  2011;12(5):423-435.
Phylogenomic databases provide orthology predictions for species with fully sequenced genomes. Although the goal seems well-defined, the content of these databases differs greatly. Seven ortholog databases (Ensembl Compara, eggNOG, HOGENOM, InParanoid, OMA, OrthoDB, Panther) were compared on the basis of reference trees. For three well-conserved protein families, we observed a generally high specificity of orthology assignments for these databases. We show that differences in the completeness of predicted gene relationships and in the phylogenetic information are, for the great majority, not due to the methods used, but to differences in the underlying database concepts. According to our metrics, none of the databases provides a fully correct and comprehensive protein classification. Our results provide a framework for meaningful and systematic comparisons of phylogenomic databases. In the future, a sustainable set of ‘Gold standard’ phylogenetic trees could provide a robust method for phylogenomic databases to assess their current quality status, measure changes following new database releases and diagnose improvements subsequent to an upgrade of the analysis procedure.
doi:10.1093/bib/bbr034
PMCID: PMC3178055  PMID: 21737420
conceptual comparison; phylogenomic databases; quality assessment; reference gene trees
4.  Detecting non-orthology in the COGs database and other approaches grouping orthologs using genome-specific best hits 
Nucleic Acids Research  2006;34(11):3309-3316.
Correct orthology assignment is a critical prerequisite of numerous comparative genomics procedures, such as function prediction, construction of phylogenetic species trees and genome rearrangement analysis. We present an algorithm for the detection of non-orthologs that arise by mistake in current orthology classification methods based on genome-specific best hits, such as the COGs database. The algorithm works with pairwise distance estimates, rather than computationally expensive and error-prone tree-building methods. The accuracy of the algorithm is evaluated through verification of the distribution of predicted cases, case-by-case phylogenetic analysis and comparisons with predictions from other projects using independent methods. Our results show that a very significant fraction of the COG groups include non-orthologs: using conservative parameters, the algorithm detects non-orthology in a third of all COG groups. Consequently, sequence analysis sensitive to correct orthology assignments will greatly benefit from these findings.
doi:10.1093/nar/gkl433
PMCID: PMC1500873  PMID: 16835308
5.  The Universal Protein Resource (UniProt): an expanding universe of protein information 
Nucleic Acids Research  2005;34(Database issue):D187-D191.
The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at or downloaded at .
doi:10.1093/nar/gkj161
PMCID: PMC1347523  PMID: 16381842
6.  UniProt: the Universal Protein knowledgebase 
Nucleic Acids Research  2004;32(Database issue):D115-D119.
To provide the scientific community with a single, centralized, authoritative resource for protein sequences and functional information, the Swiss-Prot, TrEMBL and PIR protein database activities have united to form the Universal Protein Knowledgebase (UniProt) consortium. Our mission is to provide a comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and query interfaces. The central database will have two sections, corresponding to the familiar Swiss-Prot (fully manually curated entries) and TrEMBL (enriched with automated classification, annotation and extensive cross-references). For convenient sequence searches, UniProt also provides several non-redundant sequence databases. The UniProt NREF (UniRef) databases provide representative subsets of the knowledgebase suitable for efficient searching. The comprehensive UniProt Archive (UniParc) is updated daily from many public source databases. The UniProt databases can be accessed online (http://www.uniprot.org) or downloaded in several formats (ftp://ftp.uniprot.org/pub). The scientific community is encouraged to submit data for inclusion in UniProt.
doi:10.1093/nar/gkh131
PMCID: PMC308865  PMID: 14681372
7.  The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003 
Nucleic Acids Research  2003;31(1):365-370.
The SWISS-PROT protein knowledgebase (http://www.expasy.org/sprot/ and http://www.ebi.ac.uk/swissprot/) connects amino acid sequences with the current knowledge in the Life Sciences. Each protein entry provides an interdisciplinary overview of relevant information by bringing together experimental results, computed features and sometimes even contradictory conclusions. Detailed expertise that goes beyond the scope of SWISS-PROT is made available via direct links to specialised databases. SWISS-PROT provides annotated entries for all species, but concentrates on the annotation of entries from human (the HPI project) and other model organisms to ensure the presence of high quality annotation for representative members of all protein families. Part of the annotation can be transferred to other family members, as is already done for microbes by the High-quality Automated and Manual Annotation of microbial Proteomes (HAMAP) project. Protein families and groups of proteins are regularly reviewed to keep up with current scientific findings. Complementarily, TrEMBL strives to comprise all protein sequences that are not yet represented in SWISS-PROT, by incorporating a perpetually increasing level of mostly automated annotation. Researchers are welcome to contribute their knowledge to the scientific community by submitting relevant findings to SWISS-PROT at swiss-prot@expasy.org.
PMCID: PMC165542  PMID: 12520024
8.  The SWISS-PROT protein sequence data bank 
Nucleic Acids Research  1992;20(Suppl):2019-2022.
PMCID: PMC333979  PMID: 1598233
9.  The SWISS-PROT protein sequence data bank 
Nucleic Acids Research  1991;19(Suppl):2247-2249.
PMCID: PMC331359  PMID: 2041811

Results 1-9 (9)