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Alex Bateman

Publications and source records attributed to Alex Bateman.

At least 19 recordsLinked to original sources
PubMed2007

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.

Databases, Protein↗
PubMed2006

miRBase: microRNA sequences, targets and gene nomenclature.

The miRBase database aims to provide integrated interfaces to comprehensive microRNA sequence data, annotation and predicted gene targets. miRBase takes over functionality from the microRNA Registry and fulfils three main roles: the miRBase Registry acts as an independent arbiter of microRNA gene nomenclature, assigning names prior to publication of novel miRNA sequences. miRBase Sequences is the primary online repository for miRNA sequence data and annotation. miRBase Targets is a comprehensive new database of predicted miRNA target genes. miRBase is available at http://microrna.sanger.ac.uk/.

Animals↗
PubMed2006

Pfam: clans, web tools and services.

Pfam is a database of protein families that currently contains 7973 entries (release 18.0). A recent development in Pfam has enabled the grouping of related families into clans. Pfam clans are described in detail, together with the new associated web pages. Improvements to the range of Pfam web tools and the first set of Pfam web services that allow programmatic access to the database and associated tools are also presented. Pfam is available on the web in the UK (http://www.sanger.ac.uk/Software/Pfam/), the USA (http://pfam.wustl.edu/), France (http://pfam.jouy.inra.fr/) and Sweden (http://pfam.cgb.ki.se/).

Computer Graphics↗
PubMed2006

Metazoan Scc4 homologs link sister chromatid cohesion to cell and axon migration guidance.

Saccharomyces cerevisiae Scc2 binds Scc4 to form an essential complex that loads cohesin onto chromosomes. The prevalence of Scc2 orthologs in eukaryotes emphasizes a conserved role in regulating sister chromatid cohesion, but homologs of Scc4 have not hitherto been identified outside certain fungi. Some metazoan orthologs of Scc2 were initially identified as developmental gene regulators, such as Drosophila Nipped-B, a regulator of cut and Ultrabithorax, and delangin, a protein mutant in Cornelia de Lange syndrome. We show that delangin and Nipped-B bind previously unstudied human and fly orthologs of Caenorhabditis elegans MAU-2, a non-axis-specific guidance factor for migrating cells and axons. PSI-BLAST shows that Scc4 is evolutionarily related to metazoan MAU-2 sequences, with the greatest homology evident in a short N-terminal domain, and protein-protein interaction studies map the site of interaction between delangin and human MAU-2 to the N-terminal regions of both proteins. Short interfering RNA knockdown of human MAU-2 in HeLa cells resulted in precocious sister chromatid separation and in impaired loading of cohesin onto chromatin, indicating that it is functionally related to Scc4, and RNAi analyses show that MAU-2 regulates chromosome segregation in C. elegans embryos. Using antisense morpholino oligonucleotides to knock down Xenopus tropicalis delangin or MAU-2 in early embryos produced similar patterns of retarded growth and developmental defects. Our data show that sister chromatid cohesion in metazoans involves the formation of a complex similar to the Scc2-Scc4 interaction in the budding yeast. The very high degree of sequence conservation between Scc4 homologs in complex metazoans is consistent with increased selection pressure to conserve additional essential functions, such as regulation of cell and axon migration during development.

Animals↗
PubMed2005

Visualizing profile-profile alignment: pairwise HMM logos.

UNLABELLED: The availability of advanced profile-profile comparison tools, such as PRC or HHsearch demands sophisticated visualization tools not presently available. We introduce an approach built upon the concept of HMM logos. The method illustrates the similarities of pairs of protein family profiles in an intuitive way. Two HMM logos, one for each profile, are drawn one upon the other. The aligned states are then highlighted and connected. AVAILABILITY: A web interface offering online creation of pairwise HMM logos is available at http://www.sanger.ac.uk/Software/analysis/logomat-p. Furthermore, software developers may download a Perl package that includes methods for creation of pairwise HMM logos locally. CONTACT: bsb@sanger.ac.uk.

Computer Graphics↗
PubMed2005

Rfam: annotating non-coding RNAs in complete genomes.

Rfam is a comprehensive collection of non-coding RNA (ncRNA) families, represented by multiple sequence alignments and profile stochastic context-free grammars. Rfam aims to facilitate the identification and classification of new members of known sequence families, and distributes annotation of ncRNAs in over 200 complete genome sequences. The data provide the first glimpses of conservation of multiple ncRNA families across a wide taxonomic range. A small number of large families are essential in all three kingdoms of life, with large numbers of smaller families specific to certain taxa. Recent improvements in the database are discussed, together with challenges for the future. Rfam is available on the Web at http://www.sanger.ac.uk/Software/Rfam/ and http://rfam.wustl.edu/.

Animals↗
PubMed2005

InterPro, progress and status in 2005.

InterPro, an integrated documentation resource of protein families, domains and functional sites, was created to integrate the major protein signature databases. Currently, it includes PROSITE, Pfam, PRINTS, ProDom, SMART, TIGRFAMs, PIRSF and SUPERFAMILY. Signatures are manually integrated into InterPro entries that are curated to provide biological and functional information. Annotation is provided in an abstract, Gene Ontology mapping and links to specialized databases. New features of InterPro include extended protein match views, taxonomic range information and protein 3D structure data. One of the new match views is the InterPro Domain Architecture view, which shows the domain composition of protein matches. Two new entry types were introduced to better describe InterPro entries: these are active site and binding site. PIRSF and the structure-based SUPERFAMILY are the latest member databases to join InterPro, and CATH and PANTHER are soon to be integrated. InterPro release 8.0 contains 11 007 entries, representing 2573 domains, 8166 families, 201 repeats, 26 active sites, 21 binding sites and 20 post-translational modification sites. InterPro covers over 78% of all proteins in the Swiss-Prot and TrEMBL components of UniProt. 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).

Databases, Protein↗
PubMed2004

The G5 domain: a potential N-acetylglucosamine recognition domain involved in biofilm formation.

SUMMARY: Biofilms are complex microbial communities found at surfaces that are often associated with extracellular polysaccharides. Biofilm formation is a complex process that is being understood at the molecular level only recently. We have identified a novel domain that we call the G5 domain (named after its conserved glycine residues), which is found in a variety of enzymes such as Streptococcal IgA peptidases and various glycosyl hydrolases in bacteria. The G5 domain is found in the Accumulation Associated Protein (AAP), which is an important component in biofilm formation in Staphylococcus aureus. A common feature of the proteins containing G5 domains is N-acetylglucosamine binding, and we attribute this function to the G5 domain. CONTACT: agb@sanger.ac.uk.

Acetylglucosamine↗
PubMed2004

iPfam: visualization of protein-protein interactions in PDB at domain and amino acid resolutions.

SUMMARY: There are many resources that contain information about binary interactions between proteins. However, protein interactions are defined by only a subset of residues in any protein. We have implemented a web resource that allows the investigation of protein interactions in the Protein Data Bank structures at the level of Pfam domains and amino acid residues. This detailed knowledge relies on the fact that there are a large number of multidomain proteins and protein complexes being deposited in the structure databases. The resource called iPfam is hosted within the Pfam UK website. Most resources focus on the interactions between proteins; iPfam includes these as well as interactions between domains in a single protein. AVAILABILITY: iPfam is available on the Web for browsing at http://www.sanger.ac.uk/Software/Pfam/iPfam/; the source-data for iPfam is freely available in relational tables via the ftp site ftp://ftp.sanger.ac.uk/pub/databases/Pfam/database_files/.

Amino Acids↗
PubMed2004

The Hotdog fold: wrapping up a superfamily of thioesterases and dehydratases.

BACKGROUND: The Hotdog fold was initially identified in the structure of Escherichia coli FabA and subsequently in 4-hydroxybenzoyl-CoA thioesterase from Pseudomonas sp. strain CBS. Since that time structural determinations have shown a number of other apparently unrelated proteins also share the Hotdog fold. RESULTS: Using sequence analysis we unify a large superfamily of HotDog domains. Membership includes numerous prokaryotic, archaeal and eukaryotic proteins involved in several related, but distinct, catalytic activities, from metabolic roles such as thioester hydrolysis in fatty acid metabolism, to degradation of phenylacetic acid and the environmental pollutant 4-chlorobenzoate. The superfamily also includes FapR, a non-catalytic bacterial homologue that is involved in transcriptional regulation of fatty acid biosynthesis. We have defined 17 subfamilies, with some characterisation. Operon analysis has revealed numerous HotDog domain-containing proteins to be fusion proteins, where two genes, once separate but adjacent open-reading frames, have been fused into one open-reading frame to give a protein with two functional domains. Finally we have generated a Hidden Markov Model library from our analysis, which can be used as a tool for predicting the occurrence of HotDog domains in any protein sequence. CONCLUSIONS: The HotDog domain is both an ancient and ubiquitous motif, with members found in the three branches of life.

Amino Acid Motifs↗
PubMed2004

Novel protein domains and motifs in the marine planctomycete Rhodopirellula baltica.

The planctomycetes are a phylum of bacteria that have a unique cell compartmentalisation and yeast-like budding cell division and peptidoglycan-less proteinaceous cell walls. We wished to further our understanding of these unique organisms at the molecular level by searching for conserved amino acid sequence motifs and domains in the proteins encoded by Rhodopirellula baltica. Using BLAST and single-linkage clustering, we have discovered several new protein domains and sequence motifs in this planctomycete. R. baltica has multiple members of the newly discovered GEFGR protein family and the ASPIC C-terminal domain family, whilst most other organisms for which whole genome sequence is available have no more than one. Many of the domains and motifs appear to be restricted to the planctomycetes. It is possible that these protein domains and motifs may have been lost or replaced in other phyla, or they may have undergone multiple duplication events in the planctomycete lineage. One of the novel motifs probably represents a novel N-terminal export signal peptide. With their unique cell biology, it may be that the planctomycete cell compartmentalisation plan in particular needs special membrane transport mechanisms. The discovery of these new domains and motifs, many of which are associated with secretion and cell-surface functions, will help to stimulate experimental work and thus enhance further understanding of this fascinating group of organisms.

Amino Acid Motifs↗
PubMed2004

Enhanced protein domain discovery using taxonomy.

BACKGROUND: It is well known that different species have different protein domain repertoires, and indeed that some protein domains are kingdom specific. This information has not yet been incorporated into statistical methods for finding domains in sequences of amino acids. RESULTS: We show that by incorporating our understanding of the taxonomic distribution of specific protein domains, we can enhance domain recognition in protein sequences. We identify 4447 new instances of Pfam domains in the SP-TREMBL database using this technique, equivalent to the coverage increase given by the last 8.3% of Pfam families and to a 0.7% increase in the number of domain predictions. We use PSI-BLAST to cross-validate our new predictions. We also benchmark our approach using a SCOP test set of proteins of known structure, and demonstrate improvements relative to standard Hidden Markov model techniques. CONCLUSIONS: Explicitly including knowledge about the taxonomic distribution of protein domains can enhance protein domain recognition. Our method can also incorporate other context-specific domain distributions - such as domain co-occurrence and protein localisation.

Computational Biology↗
PubMed2004

The Pfam protein families database.

Pfam is a large collection of protein families and domains. Over the past 2 years the number of families in Pfam has doubled and now stands at 6190 (version 10.0). Methodology improvements for searching the Pfam collection locally as well as via the web are described. Other recent innovations include modelling of discontinuous domains allowing Pfam domain definitions to be closer to those found in structure databases. Pfam is available on the web in the UK (http://www.sanger.ac.uk/Software/Pfam/), the USA (http://pfam.wustl.edu/), France (http://pfam.jouy.inra.fr/) and Sweden (http://Pfam.cgb.ki.se/).

Animals↗
PubMed2003

The TROVE module: a common element in Telomerase, Ro and Vault ribonucleoproteins.

BACKGROUND: Ribonucleoproteins carry out a variety of important tasks in the cell. In this study we show that a number of these contain a novel module, that we speculate mediates RNA-binding. RESULTS: The TROVE module--Telomerase, Ro and Vault module--is found in TEP1 and Ro60 the protein components of three ribonucleoprotein particles. This novel module, consisting of one or more domains, may be involved in binding the RNA components of the three RNPs, which are telomerase RNA, Y RNA and vault RNA. A second conserved region in these proteins is shown to be a member of the vWA domain family. The vWA domain in TEP1 is closely related to the previously recognised vWA domain in VPARP a second component of the vault particle. This vWA domain may mediate interactions between these vault components or bind as yet unidentified components of the RNPs. CONCLUSIONS: This work suggests that a number of ribonucleoprotein components use a common RNA-binding module. The TROVE module is also found in bacterial ribonucleoproteins suggesting an ancient origin for these ribonucleoproteins.

Amino Acid Motifs↗
PubMed2003

A comparison of Pfam and MEROPS: two databases, one comprehensive, and one specialised.

BACKGROUND: We wished to compare two databases based on sequence similarity: one that aims to be comprehensive in its coverage of known sequences, and one that specialises in a relatively small subset of known sequences. One of the motivations behind this study was quality control. Pfam is a comprehensive collection of alignments and hidden Markov models representing families of proteins and domains. MEROPS is a catalogue and classification of enzymes with proteolytic activity (peptidases or proteases). These secondary databases are used by researchers worldwide, yet their contents are not peer reviewed. Therefore, we hoped that a systematic comparison of the contents of Pfam and MEROPS would highlight missing members and false-positives leading to improvements in quality of both databases. An additional reason for carrying out this study was to explore the extent of consensus in the definition of a protein family. RESULTS: About half (89 out of 174) of the peptidase families in MEROPS overlapped single Pfam families. A further 32 MEROPS families overlapped multiple Pfam families. Where possible, new Pfam families were built to represent most of the MEROPS families that did not overlap Pfam. When comparing the numbers of sequences found in the overlap between a MEROPS family and its corresponding Pfam family, in most cases the overlap was substantial (52 pairs of MEROPS and Pfam families had an intersection size of greater than 75% of the union) but there were some differences in the sets of sequences included in the MEROPS families versus the overlapping Pfam families. CONCLUSIONS: A number of the discrepancies between MEROPS families and their corresponding Pfam families arose from differences in the aims and philosophies of the two databases. Examination of some of the discrepancies highlighted additional members of families, which have subsequently been added in both Pfam and MEROPS. This has led to improvements in the quality of both databases. Overall there was a great deal of consensus between the databases in definitions of a protein family.

Animals↗
PubMed2003

Enhanced protein domain discovery by using language modeling techniques from speech recognition.

Most modern speech recognition uses probabilistic models to interpret a sequence of sounds. Hidden Markov models, in particular, are used to recognize words. The same techniques have been adapted to find domains in protein sequences of amino acids. To increase word accuracy in speech recognition, language models are used to capture the information that certain word combinations are more likely than others, thus improving detection based on context. However, to date, these context techniques have not been applied to protein domain discovery. Here we show that the application of statistical language modeling methods can significantly enhance domain recognition in protein sequences. As an example, we discover an unannotated Tf_Otx Pfam domain on the cone rod homeobox protein, which suggests a possible mechanism for how the V242M mutation on this protein causes cone-rod dystrophy.

Algorithms↗