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PubMed2004

Estimation of the number of authentic orphan genes in bacterial genomes.

Genome annotation produces a considerable number of putative proteins lacking sequence similarity to known proteins. These are referred to as "orphans." The proportion of orphan genes varies among genomes, and is independent of genome size. In the present study, we show that the proportion of orphan genes roughly correlates with the isolation index of organisms (IIO), an indicator introduced in the present study, which represents the degree of isolation of a given genome as measured by sequence similarity. However, there are outlier genomes with respect to the linear correlation, consisting of those genomes that may contain excess amounts of orphan genes. Comparisons of genome sequences among closely related strains revealed that some of the annotated genes are not conserved, suggesting that they are ORFs occurring by chance. Exclusion of these non-conserved ORFs within closely related genomes improved the correlation between the proportion of orphan genes and the IIO values. Assuming that the correlation holds in general, this relationship was used to estimate the number of "authentic" orphan genes in a genome. Using this definition of authentic orphan genes, the anomalies arising from over-assignments, e.g., the percentages of structural annotations, were corrected for 16 genomes, including those of five archaea.

Amino Acid Sequence↗
PubMed2006

An integrated approach to the prediction of domain-domain interactions.

BACKGROUND: The development of high-throughput technologies has produced several large scale protein interaction data sets for multiple species, and significant efforts have been made to analyze the data sets in order to understand protein activities. Considering that the basic units of protein interactions are domain interactions, it is crucial to understand protein interactions at the level of the domains. The availability of many diverse biological data sets provides an opportunity to discover the underlying domain interactions within protein interactions through an integration of these biological data sets. RESULTS: We combine protein interaction data sets from multiple species, molecular sequences, and gene ontology to construct a set of high-confidence domain-domain interactions. First, we propose a new measure, the expected number of interactions for each pair of domains, to score domain interactions based on protein interaction data in one species and show that it has similar performance as the E-value defined by Riley et al. Our new measure is applied to the protein interaction data sets from yeast, worm, fruitfly and humans. Second, information on pairs of domains that coexist in known proteins and on pairs of domains with the same gene ontology function annotations are incorporated to construct a high-confidence set of domain-domain interactions using a Bayesian approach. Finally, we evaluate the set of domain-domain interactions by comparing predicted domain interactions with those defined in iPfam database that were derived based on protein structures. The accuracy of predicted domain interactions are also confirmed by comparing with experimentally obtained domain interactions from H. pylori. As a result, a total of 2,391 high-confidence domain interactions are obtained and these domain interactions are used to unravel detailed protein and domain interactions in several protein complexes. CONCLUSION: Our study shows that integration of multiple biological data sets based on the Bayesian approach provides a reliable framework to predict domain interactions. By integrating multiple data sources, the coverage and accuracy of predicted domain interactions can be significantly increased.

Algorithms↗
PubMed2006

Similarity networks of protein binding sites.

An increasing attention has been dedicated to the characterization of complex networks within the protein world. This work is reporting how we uncovered networked structures that reflected the structural similarities among protein binding sites. First, a 211 binding sites dataset has been compiled by removing the redundant proteins in the Protein Ligand Database (PLD) (http://www-mitchell.ch.cam.ac.uk/pld/). Using a clique detection algorithm we have performed all-against-all binding site comparisons among the 211 available ones. Within the set of nodes representing each binding site an edge was added whenever a pair of binding sites had a similarity higher than a threshold value. The generated similarity networks revealed that many nodes had few links and only few were highly connected, but due to the limited data available it was not possible to definitively prove a scale-free architecture. Within the same dataset, the binding site similarity networks were compared with the networks of sequence and fold similarity networks. In the protein world, indications were found that structure is better conserved than sequence, but on its own, sequence was better conserved than the subset of functional residues forming the binding site. Because a binding site is strongly linked with protein function, the identification of protein binding site similarity networks could accelerate the functional annotation of newly identified genes. In view of this we have discussed several potential applications of binding site similarity networks, such as the construction of novel binding site classification databases, as well as the implications for protein molecular design in general and computational chemogenomics in particular.

Animals↗
PubMed2005

The autoimmune contrivance: genetics in the mouse model.

Autoimmunity and inheritance of complex characters behold an explosive interest in biology over the last 15 years. Research in the genetics of autoimmunity has been impelled by the isolation of genetic markers allowing tracing of heredity. The annotation and sequencing of the human and mouse genomes provide with the potential for further advancements, through the development of new technologies. This review aims to summarize advances made in the autoimmunity field, centered in type 1 diabetes in the NOD mouse model. It also aims to demonstrate that animal models, albeit some phenotypic and genetic dissimilarities with the human diseases, still remain the best way to move towards an understanding of the molecular mechanisms involved in autoimmunity. Assessing the current state of research in this field together with the increasing potential of novel biotechnology advancements, new insights to disease pathogenesis and discovery of molecular targets for intervention strategies are anticipated in the coming years.

Animals↗
PubMed2000

Human BAC ends.

The Human BAC Ends database includes all non-redundant human BAC end sequences (BESs) generated by The Institute for Genomic Research (TIGR), the University of Washington (UW) and California Institute of Technology (CalTech). It incorporates the available BAC mapping data from different genome centers and the annotation results of each end sequence for the contents of repeats, ESTs and STS markers. For each BAC end the database integrates the sequence, the phred quality scores, the map and the annotation, and provides links to sites of the library information, the reports of GenBank, dbGSS and GDB, and other relevant data. The database is freely accessible via the web and supports sequence or clone searches and anonymous FTP. The relevant sites and resources are described at http://www.tigr.org/ tdb/humgen/bac_end_search/bac_end_intro.html

Chromosome Mapping↗
PubMed2002

Genome-wide analysis of the odorant-binding protein gene family in Drosophila melanogaster.

Olfaction is of considerable importance to many insects in behaviors critical for survival and reproduction, including location of food sources, selection of mates, recognition of colony con-specifics, and determination of oviposition sites. An ubiquitous, but poorly understood, component of the insect's olfactory system is a group of odorant-binding proteins (OBPs) that are present at high concentrations in the aqueous lymph surrounding the dendrites of olfactory receptor neurons. OBPs are believed to shuttle odorants from the environment to the underlying odorant receptors, for which they could potentially serve as odorant presenters. Here we show that the Drosophila genome carries 51 potential OBP genes, a number comparable to that of its odorant-receptor genes. We find that the majority (73%) of these OBP-like genes occur in clusters of as many as nine genes, in contrast to what has been observed for the Drosophila odorant-receptor genes. Two of the presumptive OBP gene clusters each carries an odorant-receptor gene. We also report an intriguing subfamily of 12 putative OBPs that share a unique C-terminal structure with three conserved cysteines and a conserved proline. Members of this subfamily have not previously been described for any insect. We have performed phylogenetic analyses of the OBP-related proteins in Drosophila as well as other insects, and we discuss the duplication and divergence of the genes for this large family. [The sequence data from this study have been submitted to FlyBase. Annotations for these sequences are available as supplementary material at http://www.genome.org.]

Amino Acid Sequence↗
PubMed2005

Genome organization of more than 300 defensin-like genes in Arabidopsis.

Defensins represent an ancient and diverse set of small, cysteine-rich, antimicrobial peptides in mammals, insects, and plants. According to published accounts, most species' genomes contain 15 to 50 defensins. Starting with a set of largely nodule-specific defensin-like sequences (DEFLs) from the model legume Medicago truncatula, we built motif models to search the near-complete Arabidopsis (Arabidopsis thaliana) genome. We identified 317 DEFLs, yet 80% were unannotated at The Arabidopsis Information Resource and had no prior evidence of expression. We demonstrate that many of these DEFL genes are clustered in the Arabidopsis genome and that individual clusters have evolved from successive rounds of gene duplication and divergent or purifying selection. Sequencing reverse transcription-PCR products from five DEFL clusters confirmed our gene predictions and verified expression. For four of the largest clusters of DEFLs, we present the first evidence of expression, most frequently in floral tissues. To determine the abundance of DEFLs in other plant families, we used our motif models to search The Institute for Genomic Research's gene indices and identified approximately 1,100 DEFLs. These expressed DEFLs were found mostly in reproductive tissues, consistent with our reverse transcription-PCR results. Sequence-based clustering of all identified DEFLs revealed separate tissue- or taxon-specific subgroups. Previously, we and others showed that more than 300 DEFL genes were expressed in M. truncatula nodules, organs not present in most plants. We have used this information to annotate the Arabidopsis genome and now provide evidence of a large DEFL superfamily present in expressed tissues of all sequenced plants.

Amino Acid Sequence↗
PubMed2005

Armadillo: domain boundary prediction by amino acid composition.

The identification and annotation of protein domains provides a critical step in the accurate determination of molecular function. Both computational and experimental methods of protein structure determination may be deterred by large multi-domain proteins or flexible linker regions. Knowledge of domains and their boundaries may reduce the experimental cost of protein structure determination by allowing researchers to work on a set of smaller and possibly more successful alternatives. Current domain prediction methods often rely on sequence similarity to conserved domains and as such are poorly suited to detect domain structure in poorly conserved or orphan proteins. We present here a simple computational method to identify protein domain linkers and their boundaries from sequence information alone. Our domain predictor, Armadillo (http://armadillo.blueprint.org), uses any amino acid index to convert a protein sequence to a smoothed numeric profile from which domains and domain boundaries may be predicted. We derived an amino acid index called the domain linker propensity index (DLI) from the amino acid composition of domain linkers using a non-redundant structure dataset. The index indicates that Pro and Gly show a propensity for linker residues while small hydrophobic residues do not. Armadillo predicts domain linker boundaries from Z-score distributions and obtains 35% sensitivity with DLI in a two-domain, single-linker dataset (within +/-20 residues from linker). The combination of DLI and an entropy-based amino acid index increases the overall Armadillo sensitivity to 56% for two domain proteins. Moreover, Armadillo achieves 37% sensitivity for multi-domain proteins, surpassing most other prediction methods. Armadillo provides a simple, but effective method by which prediction of domain boundaries can be obtained with reasonable sensitivity. Armadillo should prove to be a valuable tool for rapidly delineating protein domains in poorly conserved proteins or those with no sequence neighbors. As a first-line predictor, domain meta-predictors could yield improved results with Armadillo predictions.

Amino Acid Sequence↗
PubMed2005

The Biomolecular Interaction Network Database and related tools 2005 update.

The Biomolecular Interaction Network Database (BIND) (http://bind.ca) archives biomolecular interaction, reaction, complex and pathway information. Our aim is to curate the details about molecular interactions that arise from published experimental research and to provide this information, as well as tools to enable data analysis, freely to researchers worldwide. BIND data are curated into a comprehensive machine-readable archive of computable information and provides users with methods to discover interactions and molecular mechanisms. BIND has worked to develop new methods for visualization that amplify the underlying annotation of genes and proteins to facilitate the study of molecular interaction networks. BIND has maintained an open database policy since its inception in 1999. Data growth has proceeded at a tremendous rate, approaching over 100 000 records. New services provided include a new BIND Query and Submission interface, a Standard Object Access Protocol service and the Small Molecule Interaction Database (http://smid.blueprint.org) that allows users to determine probable small molecule binding sites of new sequences and examine conserved binding residues.

Animals↗
PubMed2005

The EMBL Nucleotide Sequence Database.

The EMBL Nucleotide Sequence Database (http://www.ebi.ac.uk/embl), maintained at the European Bioinformatics Institute (EBI) near Cambridge, UK, is a comprehensive collection of nucleotide sequences and annotation from available public sources. The database is part of an international collaboration with DDBJ (Japan) and GenBank (USA). Data are exchanged daily between the collaborating institutes to achieve swift synchrony. Webin is the preferred tool for individual submissions of nucleotide sequences, including Third Party Annotation (TPA) and alignments. Automated procedures are provided for submissions from large-scale sequencing projects and data from the European Patent Office. New and updated data records are distributed daily and the whole EMBL Nucleotide Sequence Database is released four times a year. Access to the sequence data is provided via ftp and several WWW interfaces. With the web-based Sequence Retrieval System (SRS) it is also possible to link nucleotide data to other specialist molecular biology databases maintained at the EBI. Other tools are available for sequence similarity searching (e.g. FASTA and BLAST). Changes over the past year include the removal of the sequence length limit, the launch of the EMBLCDSs dataset, extension of the Sequence Version Archive functionality and the revision of quality rules for TPA data.

Base Sequence↗
PubMed2006

Plant metabolomics: from holistic hope, to hype, to hot topic.

In a short time, plant metabolomics has gone from being just an ambitious concept to being a rapidly growing, valuable technology applied in the stride to gain a more global picture of the molecular organization of multicellular organisms. The combination of improved analytical capabilities with newly designed, dedicated statistical, bioinformatics and data mining strategies, is beginning to broaden the horizons of our understanding of how plants are organized and how metabolism is both controlled but highly flexible. Metabolomics is predicted to play a significant, if not indispensable role in bridging the phenotype-genotype gap and thus in assisting us in our desire for full genome sequence annotation as part of the quest to link gene to function. Plants are a fabulously rich source of diverse functional biochemicals and metabolomics is also already proving valuable in an applied context. By creating unique opportunities for us to interrogate plant systems and characterize their biochemical composition, metabolomics will greatly assist in identifying and defining much of the still unexploited biodiversity available today.

Biotechnology↗
PubMed2006

The molecular structure of Rv1873, a conserved hypothetical protein from Mycobacterium tuberculosis, at 1.38 A resolution.

The X-ray crystal structure of the gene product encoded by open reading frame Rv1873 of Mycobacterium tuberculosis has been determined by single isomorphous replacement with anomalous scattering (SIRAS) phasing techniques at 1.38 A resolution from monoclinic crystals with unit-cell parameters a = 33.44, b = 31.63, c = 53.19 A, beta = 90.8 degrees. The 16.2 kDa Rv1873 is a monomer that adopts a primarily alpha-helical fold with limited structural similarity to previously determined tertiary structures. It has been annotated as a conserved hypothetical protein of unknown function and is classified by the Clusters of Orthologous Groups (COG) database as belonging to COG5579. The three-dimensional structure of the Rv1873 gene product reveals limited similarity to a repeated motif that is found in a variety of other proteins. While not a novel fold, it serves as a model for orthologues predicted to be related by sequence and it is hoped that knowledge of the structure of Rv1873 will aid in determining a possible function for this protein.

Amino Acid Sequence↗
PubMedDate not supplied

Functional inferences from blind ab initio protein structure predictions.

Ab initio protein structure prediction methods have improved dramatically in the past several years. Because these methods require only the sequence of the protein of interest, they are potentially applicable to the open reading frames in the many organisms whose sequences have been and will be determined. Ab initio methods cannot currently produce models of high enough resolution for use in rational drug design, but there is an exciting potential for using the methods for functional annotation of protein sequences on a genomic scale. Here we illustrate how functional insights can be obtained from low-resolution predicted structures using examples from blind ab initio structure predictions from the third and fourth critical assessment of structure prediction (CASP3, CASP4) experiments.

Computational Biology↗
PubMed2006

LC-MS/MS based proteomic analysis and functional inference of hypothetical proteins in Desulfovibrio vulgaris.

High efficiency capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to examine the proteins extracted from Desulfovibrio vulgaris cells across six treatment conditions. While our previous study provided a proteomic overview of the cellular metabolism based on proteins with known functions [W. Zhang, M.A. Gritsenko, R.J. Moore, D.E. Culley, L. Nie, K. Petritis, E.F. Strittmatter, D.G. Camp II, R.D. Smith, F.J. Brockman, A proteomic view of the metabolism in Desulfovibrio vulgaris determined by liquid chromatography coupled with tandem mass spectrometry, Proteomics 6 (2006) 4286-4299], this study describes the global detection and functional inference for hypothetical D. vulgaris proteins. Using criteria that a given peptide of a protein is identified from at least two out of three independent LC-MS/MS measurements and that for any protein at least two different peptides are identified among the three measurements, 129 open reading frames (ORFs) originally annotated as hypothetical proteins were found to encode expressed proteins. Functional inference for the conserved hypothetical proteins was performed by a combination of several non-homology based methods: genomic context analysis, phylogenomic profiling, and analysis of a combination of experimental information, including peptide detection in cells grown under specific culture conditions and cellular location of the proteins. Using this approach we were able to assign possible functions to 20 conserved hypothetical proteins. This study demonstrated that a combination of proteomics and bioinformatics methodologies can provide verification of the expression of hypothetical proteins and improve genome annotation.

Amino Acid Sequence↗
PubMed2003

Protein family annotation in a multiple alignment viewer.

SUMMARY: The Pfaat protein family alignment annotation tool is a Java-based multiple sequence alignment editor and viewer designed for protein family analysis. The application merges display features such as dendrograms, secondary and tertiary protein structure with SRS retrieval, subgroup comparison, and extensive user-annotation capabilities. AVAILABILITY: The program and source code are freely available from the authors under the GNU General Public License at http://www.pfizerdtc.com

Amino Acid Sequence↗
PubMed2002

Dictionary-driven protein annotation.

Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were released publicly after we built the Bio-Dictionary that is used in our experiments. Finally, we have computed the annotations of more than 70 complete genomes and made them available on the World Wide Web at http://cbcsrv.watson.ibm.com/Annotations/.

Algorithms↗
PubMed2004

Identification and analysis of polyserine linker domains in prokaryotic proteins with emphasis on the marine bacterium Microbulbifer degradans.

Polyserine linkers (PSLs) are interdomain, serine-rich sequences found in modular proteins. Though common among eukaryotes, their presence in prokaryotic enzymes is limited. We identified 46 extracellular proteins involved in complex carbohydrate degradation from Microbulbifer degradans that contain PSLs that separate carbohydrate-binding domains or catalytic domains from other binding domains. In nine M. degradans proteins, PSLs also separated amino-terminal lipoprotein acylation sites from the remainder of the polypeptide. Furthermore, among the 76 PSL proteins identified in sequence repositories, 65 are annotated as proteins involved in complex carbohydrate degradation. We discuss the notion that PSLs are flexible, disordered spacer regions that enhance substrate accessibility.

Alteromonadaceae↗
PubMed2006

Large-scale trends in the evolution of gene structures within 11 animal genomes.

We have used the annotations of six animal genomes (Homo sapiens, Mus musculus, Ciona intestinalis, Drosophila melanogaster, Anopheles gambiae, and Caenorhabditis elegans) together with the sequences of five unannotated Drosophila genomes to survey changes in protein sequence and gene structure over a variety of timescales--from the less than 5 million years since the divergence of D. simulans and D. melanogaster to the more than 500 million years that have elapsed since the Cambrian explosion. To do so, we have developed a new open-source software library called CGL (for "Comparative Genomics Library"). Our results demonstrate that change in intron-exon structure is gradual, clock-like, and largely independent of coding-sequence evolution. This means that genome annotations can be used in new ways to inform, corroborate, and test conclusions drawn from comparative genomics analyses that are based upon protein and nucleotide sequence similarities.

Animals↗