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At least 1,639 records · Page 91Linked to original sources
PubMed2005

Inferring hypotheses on functional relationships of genes: Analysis of the Arabidopsis thaliana subtilase gene family.

The gene family of subtilisin-like serine proteases (subtilases) in Arabidopsis thaliana comprises 56 members, divided into six distinct subfamilies. Whereas the members of five subfamilies are similar to pyrolysins, two genes share stronger similarity to animal kexins. Mutant screens confirmed 144 T-DNA insertion lines with knockouts for 55 out of the 56 subtilases. Apart from SDD1, none of the confirmed homozygous mutants revealed any obvious visible phenotypic alteration during growth under standard conditions. Apart from this specific case, forward genetics gave us no hints about the function of the individual 54 non-characterized subtilase genes. Therefore, the main objective of our work was to overcome the shortcomings of the forward genetic approach and to infer alternative experimental approaches by using an integrative bioinformatics and biological approach. Computational analyses based on transcriptional co-expression and co-response pattern revealed at least two expression networks, suggesting that functional redundancy may exist among subtilases with limited similarity. Furthermore, two hubs were identified, which may be involved in signalling or may represent higher-order regulatory factors involved in responses to environmental cues. A particular enrichment of co-regulated genes with metabolic functions was observed for four subtilases possibly representing late responsive elements of environmental stress. The kexin homologs show stronger associations with genes of transcriptional regulation context. Based on the analyses presented here and in accordance with previously characterized subtilases, we propose three main functions of subtilases: involvement in (i) control of development, (ii) protein turnover, and (iii) action as downstream components of signalling cascades. Supplemental material is available in the Plant Subtilase Database (PSDB) (http://csbdb.mpimp-golm.mpg.de/psdb.html), as well as from the CSB.DB (http://csbdb.mpimp-golm.mpg.de).

Animals↗
PubMed2003

Comparing the base usage frequency between bacteria DNA double strand.

During the Evolution, effected by select pressure or nature mutation, the compositions of bacteria genomes is various. And many experiences prove that the genes between leading strand and lagging strand is distinctly in copy, transcription and repair. Some scholars presume that the bases distribution is difference between the two strand, to verify the guess, we using the technology of bioinformatics, compare the base usage between the DNA double strand in 17 species bacteria. The result show: 1. there is same bases usage frequency in coding sequence between leading strand and lagging strand 2. There also same bases usage frequency in first codon, second codon and third codon. It suggest that there is a equilibrium between the two strand by the effect of select pressure and nature mutation.

Bacteria↗
PubMed2005

Automatic drawing of biological networks using cross cost and subcomponent data.

Automatic graph drawing function for biopathways is indispensable for biopathway databases and softwares. This paper proposes a new grid-based algorithm for biopathway layout that considers (a) edge-edge crossing, (b) node-edge crossing, (c) distance measures between nodes, as its costs, and (d) subcellular localization information from Gene Ontology, as its constraints. For this algorithm, we newly define cost functions, devise an efficient method for computing the costs (a)-(c) by employing a matrix representing the difference between two layouts, and take a steepest descent method for searching locally optimal solutions and multi-step layout method for finding better solutions. We implemented this algorithm on Cell Illustrator which is a biopathway modeling and simulation software. The algorithm is applied to a signal transduction pathway of apoptosis induced by fas ligand. We compare our layout with that of the grid-based algorithm by Li and Kurata (Bioinformatics 21 (9):2036-2042, 2005). The result shows that our algorithm reduces edge-edge crossings and node-edge crossings, and solves the ''isolated island problem'', that is, despite the intension, some groups of nodes are apart from other nodes in the layout. As a result, the biological understandability of the layout is fairly improved.

Algorithms↗
PubMed2005

Validation of in silico prediction by in vitro immunoserological results of fine epitope mapping on citrate synthase specific autoantibodies.

In silico antibody-antigen binding predictions are generally employed in research to rationalize epitope development. These techniques are widely spread despite their technical limitations. To validate the results of these bioinformatic calculations evidence based comparative in vitro studies are necessary. We have used a well-conserved mitochondrial inner membrane antigen-citrate synthase to develop a model for comparative analysis of the predicted and the immunoserologically verified epitopes of circulating autoantibodies. Epitopes were predicted using accepted tools: the GCG Wisconsin package and TEPITOPE 2000. An overlapping multipin ELISA assay--covering 49% of the citrate synthase molecule--was developed to map autoantibody epitopes of individuals (healthy, systemic autoimmune, and heart transplanted) in different immunopathological conditions. From the 40 synthesized decapeptides 34 were predicted in silico and 27 were validated in vitro. Thirty-two percent of epitopes were recognized by majority of sera 47% by at least one sera. False positive predictions were 21%. There was major difference in the recognized epitope pattern under different immunopathological conditions. Our results suggest that special databases are needed for training and weighing prediction methods by clinically well-characterized samples, due to the differences in the immune response under different health status. The development of these special algorithms needs a new approach. A high number of samples under these special immunological conditions are to be mapped and then used for the "fine tuning" of different prediction algorithms.

Amino Acid Sequence↗
PubMed2004

Structure, circadian regulation and bioinformatic analysis of the unique sigma factor gene in Chlamydomonas reinhardtii.

In higher plants, the transcription of plastid genes is mediated by at least two types of RNA polymerase (RNAP); a plastid-encoded bacterial RNAP in which promoter specificity is conferred by nuclear-encoded sigma factors, and a nuclear-encoded phage-like RNAP. Green algae, however, appear to possess only the bacterial enzyme. Since transcription of much, if not most, of the chloroplast genome in Chlamydomonas reinhardtii is regulated by the circadian clock and the nucleus, we sought to identify sigma factor genes that might be responsible for this regulation. We describe a nuclear gene (RPOD) that is predicted to encode an 80 kDa protein that, in addition to a predicted chloroplast transit peptide at the N-terminus, has the conserved motifs (2.1- 4.2) diagnostic of bacterial sigma-70 factors. We also identified two motifs not previously recognized for sigma factors, adjacent PEST sequences and a leucine zipper, both suggested to be involved in protein-protein interactions. PEST sequences were also found in approximately 40% of sigma factors examined, indicating they may be of general significance. Southern blot hybridization and BLAST searches of the genome and EST databases suggest that RPODmay be the only sigma factor gene in C. reinhardtii. The levels of RPODmRNA increased 2- 3-fold in the mid-to-late dark period of light-dark cycling cells, just prior to, or coincident with, the peak in chloroplast transcription. Also, the dark-period peak in RPOD mRNA persisted in cells shifted to continuous light or continuous dark for at least one cycle, indicating that RPODis under circadian clock control. These results suggest that regulation of RPODexpression contributes to the circadian clock's control of chloroplast transcription.

Journal Article↗
PubMed2006

A general pipeline for the development of anchor markers for comparative genomics in plants.

BACKGROUND: Complete or near-complete genomic sequence information is presently only available for a few plant species representing a large phylogenetic diversity among plants. In order to effectively transfer this information to species lacking sequence information, comparative genomic tools need to be developed. Molecular markers permitting cross-species mapping along co-linear genomic regions are central to comparative genomics. These "anchor" markers, defining unique loci in genetic linkage maps of multiple species, are gene-based and possess a number of features that make them relatively sparse. To identify potential anchor marker sequences more efficiently, we have established an automated bioinformatic pipeline that combines multi-species Expressed Sequence Tags (EST) and genome sequence data. RESULTS: Taking advantage of sequence data from related species, the pipeline identifies evolutionarily conserved sequences that are likely to define unique orthologous loci in most species of the same phylogenetic clade. The key features are the identification of evolutionarily conserved sequences followed by automated design of intron-flanking Polymerase Chain Reaction (PCR) primer pairs. Polymorphisms can subsequently be identified by size- or sequence variation of PCR products, amplified from mapping parents or populations. We illustrate our procedure in legumes and grasses and exemplify its application in legumes, where model plant studies and the genome- and EST-sequence data available have a potential impact on the breeding of crop species and on our understanding of the evolution of this large and diverse family. CONCLUSION: We provide a database of 459 candidate anchor loci which have the potential to serve as map anchors in more than 18,000 legume species, a number of which are of agricultural importance. For grasses, the database contains 1335 candidate anchor loci. Based on this database, we have evaluated 76 candidate anchor loci with respect to marker development in legume species with no sequence information available, demonstrating the validity of this approach.

Arachis↗
PubMed2025

Logical Exploration of Cinnamoyl-Containing Nonribosomal Peptides via Metabologenomic Targeting and Regulator Overexpression.

A targeted method for discovering cinnamoyl-containing nonribosomal peptides (CCNPs), a unique class of bioactive compounds, was devised by using cinnamoyl isomerase, a key enzyme in the biosynthesis of the cinnamoyl moiety, as a genome mining probe. A total of 39 hit strains were obtained, including 35 from polymerase chain reaction-based screening of the in-house bacterial library (2.5% of 1400 strains) targeting the cinnamoyl isomerase-encoding gene and 4 from the genome mining of online databases. Sequence similarity networking and phylogenetic analyses of the isomerase amplicons (∼530 bp) classified the CCNPs into three major substructure-based groups (Z-, E-, and M-type CCNPs) and revealed distinct clade-structure relationships (13 clades). To overcome the challenge of silent biosynthetic gene clusters, we activated these clusters by overexpressing conserved cluster-situated LuxR regulators combined with extensive culture optimization. CCNP production was metabolomically detected in the bacterial extracts by using the characteristic UV absorption and MS/MS fragments of cinnamoyl moieties. CCNP production was observed in 20 of the 39 hit strains, resulting in the isolation of 6 new CCNPs, including oxy-skyllamycin B (2), gwanacinnamycin (3), and luxocinnamycins A-D (4-7), with high structural novelty. Their structures were elucidated using comprehensive spectroscopic analyses and multiple-step chemical derivatizations, and the putative biosynthetic pathways were bioinformatically proposed. Gwanacinnamycin (3) exhibited significant antimycobacterial activity, whereas luxocinnamycin A (4) displayed moderate antiproliferative activity against stomach cancer cells. Our findings highlight a targeted metabologenomic approach combined with transcriptional regulator overexpression as a logical and efficient platform for the discovery of bioactive compounds from nature.

Peptides↗
PubMed2001

Functional assignment of the 20 S proteasome from Trypanosoma brucei using mass spectrometry and new bioinformatics approaches.

As experimental technologies for characterization of proteomes emerge, bioinformatic analysis of the data becomes essential. Separation and identification technologies currently based on two-dimensional gels/mass spectrometry provide the inherent analytical power required. This strategy involves protein spot digestion and accurate mass mapping together with computational interrogation of available data bases for protein functional identification. When either no exact match is found or when the possible matches only partially account for molecular weights actually observed, peptide sequencing by tandem mass spectrometry has emerged as the methodology of choice to provide the basic additional information required. To evaluate the capabilities of bioinformatics methods employed for identifying homologs of a protein of interest, we attempted to identify the major proteins from the 20 S proteasome of Trypanosoma brucei using sequence information determined using mass spectrometry. The results suggest that neither the traditional query engines, BLAST and FASTA, nor specialized software developed for analysis of sequence information obtained by mass spectrometry are able to identify even closely related sequences at statistically significant scores. To address this deficit, new bioinformatics approaches were developed for concomitant use of the multiple fragments of short sequence typically available from methods of tandem mass spectrometry. These approaches rely on the occurrence of congruence across searches of multiple fragments from a single protein. This method resulted in sharply better statistical significance values for correct hits in the data base output relative to that achieved for independent searches using single sequence fragments.

Algorithms↗
PubMed2003

myGrid: personalised bioinformatics on the information grid.

MOTIVATION: The (my)Grid project aims to exploit Grid technology, with an emphasis on the Information Grid, and provide middleware layers that make it appropriate for the needs of bioinformatics. (my)Grid is building high level services for data and application integration such as resource discovery, workflow enactment and distributed query processing. Additional services are provided to support the scientific method and best practice found at the bench but often neglected at the workstation, notably provenance management, change notification and personalisation. RESULTS: We give an overview of these services and their metadata. In particular, semantically rich metadata expressed using ontologies necessary to discover, select and compose services into dynamic workflows.

Computational Biology↗
PubMed2005

SOAP-based services provided by the European Bioinformatics Institute.

SOAP (Simple Object Access Protocol) (http://www.w3.org/TR/soap) based Web Services technology (http://www.w3.org/ws) has gained much attention as an open standard enabling interoperability among applications across heterogeneous architectures and different networks. The European Bioinformatics Institute (EBI) is using this technology to provide robust data retrieval and data analysis mechanisms to the scientific community and to enhance utilization of the biological resources it already provides [N. Harte, V. Silventoinen, E. Quevillon, S. Robinson, K. Kallio, X. Fustero, P. Patel, P. Jokinen and R. Lopez (2004) Nucleic Acids Res., 32, 3-9]. These services are available free to all users from http://www.ebi.ac.uk/Tools/webservices.

Biotechnology↗
PubMed2006

A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB.

BACKGROUND: Sharing of microarray data within the research community has been greatly facilitated by the development of the disclosure and communication standards MIAME and MAGE-ML by the MGED Society. However, the complexity of the MAGE-ML format has made its use impractical for laboratories lacking dedicated bioinformatics support. RESULTS: We propose a simple tab-delimited, spreadsheet-based format, MAGE-TAB, which will become a part of the MAGE microarray data standard and can be used for annotating and communicating microarray data in a MIAME compliant fashion. CONCLUSION: MAGE-TAB will enable laboratories without bioinformatics experience or support to manage, exchange and submit well-annotated microarray data in a standard format using a spreadsheet. The MAGE-TAB format is self-contained, and does not require an understanding of MAGE-ML or XML.

Computational Biology↗
PubMed2002

Prediction of food protein allergenicity: a bioinformatic learning systems approach.

Food hypersensitivity is constantly increasing in Western societies with a prevalence of about 1-2% in Europe and in the USA. Among children, the incidence is even higher. Because of the introduction of foods derived from genetically modified crops on the marketplace, the scientific community, regulatory bodies and international associations have intensified discussions on risk assessment procedures to identify potential food allergenicity of the newly introduced proteins. In this work, we present a novel biocomputational methodology for the classification of amino acid sequences with regard to food allergenicity and non-allergenicity. This method relies on a computerised learning system trained using selected excerpts of amino acid sequences. One example of such a successful learning system is presented which consists of feature extraction from sequence alignments performed with the FASTA3 algorithm (employing the BLOSUM50 substitution matrix) combined with the k-Nearest-Neighbour (kNN) classification algorithm. Briefly, the two features extracted are the alignment score and the alignment length and the kNN algorithm assigns the pair of extracted features from an unknown sequence to the prevalent class among its k nearest neighbours in the training (prototype) set available. 91 food allergens from several specialised public repositories of food allergy and the SWALL database were identified, pre-processed, and stored, yielding one of the most extensively characterised repositories of allergenic sequences known today. All allergenic sequences were classified using a standard one-leave-out cross validation procedure yielding about 81% correctly classified allergens and the classification of 367 non-allergens in an independent test set resulted in about 98% correct classifications. The biocomputational approach presented should be regarded as a significant extension and refinement of earlier attempts suggested for in silico food safety assessment. Our results show that the framework described here is powerful enough to become useful as part of a multiple-procedure test scheme that also depicts other evaluation approaches such as solid phase immunoassay and tests for stability to digestions.

Algorithms↗
PubMed2005

NdPASA: a novel pairwise protein sequence alignment algorithm that incorporates neighbor-dependent amino acid propensities.

Sequence alignment has become one of the essential bioinformatics tools in biomedical research. Existing sequence alignment methods can produce reliable alignments for homologous proteins sharing a high percentage of sequence identity. The performance of these methods deteriorates sharply for the sequence pairs sharing less than 25% sequence identity. We report here a new method, NdPASA, for pairwise sequence alignment. This method employs neighbor-dependent propensities of amino acids as a unique parameter for alignment. The values of neighbor-dependent propensity measure the preference of an amino acid pair adopting a particular secondary structure conformation. NdPASA optimizes alignment by evaluating the likelihood of a residue pair in the query sequence matching against a corresponding residue pair adopting a particular secondary structure in the template sequence. Using superpositions of homologous proteins derived from the PSI-BLAST analysis and the Structural Classification of Proteins (SCOP) classification of a nonredundant Protein Data Bank (PDB) database as a gold standard, we show that NdPASA has improved pairwise alignment. Statistical analyses of the performance of NdPASA indicate that the introduction of sequence patterns of secondary structure derived from neighbor-dependent sequence analysis clearly improves alignment performance for sequence pairs sharing less than 20% sequence identity. For sequence pairs sharing 13-21% sequence identity, NdPASA improves the accuracy of alignment over the conventional global alignment (GA) algorithm using the BLOSUM62 by an average of 8.6%. NdPASA is most effective for aligning query sequences with template sequences whose structure is known. NdPASA can be accessed online at http://astro.temple.edu/feng/Servers/BioinformaticServers.htm.

Algorithms↗
PubMed2006

Bioinformatics for comprehensive finding and analysis of glycosyltransferases.

Bioinformatics is a very powerful tool in the field of glycoproteomics as well as genomics and proteomics. As a part of the Glycogene Project (GG project), we have developed a novel bioinformatics system for the comprehensive identification and in silico cloning of human glycogenes. Using our system, a total of 105 candidate human glycogenes were identified and then engineered for heterologous expression. Of these candidates, 38 recombinant proteins were successfully identified for their enzyme activity and substrate specificity. We also classified 47 out of 60 carbohydrate-active enzyme glycosyltransferase families into 4 superfamilies using the profile Hidden Markov Model method. On the basis of our classification and the relationship between glycosylation pathways and superfamilies, we propose the evolution of glycosyltransferases.

Algorithms↗
PubMed2006

Using GOstats to test gene lists for GO term association.

MOTIVATION: Functional analyses based on the association of Gene Ontology (GO) terms to genes in a selected gene list are useful bioinformatic tools and the GOstats package has been widely used to perform such computations. In this paper we report significant improvements and extensions such as support for conditional testing. RESULTS: We discuss the capabilities of GOstats, a Bioconductor package written in R, that allows users to test GO terms for over or under-representation using either a classical hypergeometric test or a conditional hypergeometric that uses the relationships among GO terms to decorrelate the results. AVAILABILITY: GOstats is available as an R package from the Bioconductor project: http://bioconductor.org

Algorithms↗
PubMed2003

A structural and primary sequence comparison of the viral RNA-dependent RNA polymerases.

A systematic bioinformatic approach to identifying the evolutionarily conserved regions of proteins has verified the universality of a newly described conserved motif in RNA-dependent RNA polymerases (motif F). In combination with structural comparisons, this approach has defined two regions that may be involved in unwinding double-stranded RNA (dsRNA) for transcription. One of these is the N-terminal portion of motif F and the second is a large insertion in motif F present in the RNA-dependent RNA polymerases of some dsRNA viruses.

Amino Acid Motifs↗
PubMed2002

The Protein Data Bank.

The Protein Data Bank [PDB; Berman, Westbrook et al. (2000), Nucleic Acids Res. 28, 235-242; http://www.pdb.org/] is the single worldwide archive of primary structural data of biological macromolecules. Many secondary sources of information are derived from PDB data. It is the starting point for studies in structural bioinformatics. This article describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource. The reader should come away with an understanding of the scope of the PDB and what is provided by the resource.

Databases, Protein↗
PubMed2003

Structural analysis of the PsbQ protein of photosystem II by Fourier transform infrared and circular dichroic spectroscopy and by bioinformatic methods.

The structure of PsbQ, one of the three main extrinsic proteins associated with the oxygen-evolving complex (OEC) of higher plants and green algae, is examined by Fourier transform infrared (FTIR) and circular dichroic (CD) spectroscopy and by computational structural prediction methods. This protein, together with two other lumenally bound extrinsic proteins, PsbO and PsbP, is essential for the stability and full activity of the OEC in plants. The FTIR spectra obtained in both H(2)O and D(2)O suggest a mainly alpha-helix structure on the basis of the relative areas of the constituents of the amide I and I' bands. The FTIR quantitative analyses indicate that PsbQ contains about 53% alpha-helix, 7% turns, 14% nonordered structure, and 24% beta-strand plus other beta-type extended structures. CD analyses indicate that PsbQ is a mainly alpha-helix protein (about 64%), presenting a small percentage assigned to beta-strand ( approximately 7%) and a larger amount assigned to turns and nonregular structures ( approximately 29%). Independent of the spectroscopic analyses, computational methods for protein structure prediction of PsbQ were utilized. First, a multiple alignment of 12 sequences of PsbQ was obtained after an extensive search in the public databases for protein and EST sequences. Based on this alignment, computational prediction of the secondary structure and the solvent accessibility suggest the presence of two different structural domains in PsbQ: a major C-terminal domain containing four alpha-helices and a minor N-terminal domain with a poorly defined secondary structure enriched in proline and glycine residues. The search for PsbQ analogues by fold recognition methods, not based on the secondary structure, also indicates that PsbQ is a four alpha-helix protein, most probably folding as an up-down bundle. The results obtained by both the spectroscopic and computational methods are in agreement, all indicating that PsbQ is mainly an alpha protein, and show the value of using both methodologies for protein structure investigation.

Amides↗