Bioinformatics: computers or clinicians for complex disease risk assessment?
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Adult↗
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Results for “Bioinformatics”
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Bioinformatics in a post-genomics world--the need for an inclusive approach.
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Computational Biology↗
Bioinformatic analysis of the nucleolus.
The nucleolus is a plurifunctional, nuclear organelle, which is responsible for ribosome biogenesis and many other functions in eukaryotes, including RNA processing, viral replication and tumour suppression. Our knowledge of the human nucleolar proteome has been expanded dramatically by the two recent MS studies on isolated nucleoli from HeLa cells [Andersen, Lyon, Fox, Leung, Lam, Steen, Mann and Lamond (2002) Curr. Biol. 12, 1-11; Scherl, Coute, Deon, Calle, Kindbeiter, Sanchez, Greco, Hochstrasser and Diaz (2002) Mol. Biol. Cell 13, 4100-4109]. Nearly 400 proteins were identified within the nucleolar proteome so far in humans. Approx. 12% of the identified proteins were previously shown to be nucleolar in human cells and, as expected, nearly all of the known housekeeping proteins required for ribosome biogenesis were identified in these analyses. Surprisingly, approx. 30% represented either novel or uncharacterized proteins. This review focuses on how to apply the derived knowledge of this newly recognized nucleolar proteome, such as their amino acid/peptide composition and their homologies across species, to explore the function and dynamics of the nucleolus, and suggests ways to identify, in silico, possible functions of the novel/uncharacterized proteins and potential interaction networks within the human nucleolus, or between the nucleolus and other nuclear organelles, by drawing resources from the public domain.
Amino Acid Motifs↗
Mapping of catalytically important residues in the rat L-histidine decarboxylase enzyme using bioinformatic and site-directed mutagenesis approaches.
HDC (L-histidine decarboxylase), the enzyme responsible for the catalytic production of histamine from L-histidine, belongs to an evolutionarily conserved family of vitamin B6-dependent enzymes known as the group II decarboxylases. Yet despite the obvious importance of histamine, mammalian HDC enzymes remain poorly characterized at both the biochemical and structural levels. By comparison with the recently described crystal structure of the homologous enzyme L-DOPA decarboxylase, we have been able to identify a number of conserved domains and motifs that are important also for HDC catalysis. This includes residues that were proposed to mediate events within the active site, and HDC proteins carrying mutations in these residues were inactive when expressed in reticulocyte cell lysates reactions. Our studies also suggest that a significant change in quartenary structure occurs during catalysis. This involves a protease sensitive loop, and incubating recombinant HDC with an L-histidine substrate analogue altered enzyme structure so that the loop was no longer exposed for tryptic proteolysis. In total, 27 mutant proteins were used to test the proposed importance of 34 different amino acid residues. This is the most extensive mutagenesis study yet to identify catalytically important residues in a mammalian HDC protein sequence and it provides a number of novel insights into the mechanism of histamine biosynthesis.
Amino Acid Sequence↗
Modelling and bioinformatics studies of the human Kappa-class glutathione transferase predict a novel third glutathione transferase family with similarity to prokaryotic 2-hydroxychromene-2-carboxylate isomerases.
The Kappa class of GSTs (glutathione transferases) comprises soluble enzymes originally isolated from the mitochondrial matrix of rats. We have characterized a Kappa class cDNA from human breast. The cDNA is derived from a single gene comprising eight exons and seven introns located on chromosome 7q34-35. Recombinant hGSTK1-1 was expressed in Escherichia coli as a homodimer (subunit molecular mass approximately 25.5 kDa). Significant glutathione-conjugating activity was found only with the model substrate CDNB (1-chloro-2,4-ditnitrobenzene). Hyperbolic kinetics were obtained for GSH (parameters: K(m)app, 3.3+/-0.95 mM; V(max)app, 21.4+/-1.8 micromol/min per mg of enzyme), while sigmoidal kinetics were obtained for CDNB (parameters: S0.5app, 1.5+/-1.0 mM; V(max)app, 40.3+/-0.3 micromol/min per mg of enzyme; Hill coefficient, 1.3), reflecting low affinities for both substrates. Sequence analyses, homology modelling and secondary structure predictions show that hGSTK1 has (a) most similarity to bacterial HCCA (2-hydroxychromene-2-carboxylate) isomerases and (b) a predicted C-terminal domain structure that is almost identical to that of bacterial disulphide-bond-forming DsbA oxidoreductase (root mean square deviation 0.5-0.6 A). The structures of hGSTK1 and HCCA isomerase are predicted to possess a thioredoxin fold with a polyhelical domain (alpha(x)) embedded between the beta-strands (betaalphabetaalpha(x)betabetaalpha, where the underlined elements represent the N and C motifs of the thioredoxin fold), as occurs in the bacterial disulphide-bond-forming oxidoreductases. This is in contrast with the cytosolic GSTs, where the helical domain occurs exclusively at the C-terminus (betaalphabetaalphabetabetaalphaalpha(x)). Although hGSTK1-1 catalyses some typical GST reactions, we propose that it is structurally distinct from other classes of cytosolic GSTs. The present study suggests that the Kappa class may have arisen in prokaryotes well before the divergence of the cytosolic GSTs.
Amino Acid Sequence↗
Bioinformatics and type II G-protein-coupled receptors.
The best known family B, or Type II, G-protein-coupled receptors (GPCRs) recognize peptides as ligands. The receptors for corticotrophin-releasing factor, parathyroid hormone and secretin typify this group. However, there are only 15 such GPCRs. Many other receptors share sequence homology and have been assigned to this family. The ten 'Frizzled' and one 'Smoothened' receptors show the lowest sequence homology and are not necessarily G-protein coupled. Drosophila genetics have enabled our understanding of their biology. In contrast, relatively little is known about the largest group with family B, the 33 'large amino termini' or large N-terminal family B seven-transmembrane (LNB 7TM) receptors. This review highlights the similarities found between family B receptors and provides a classification of LNB 7TM receptors.
Animals↗
A new insight into the pathogenesis of Reiter's syndrome using bioinformatics tools.
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Arthritis, Reactive↗
A combined bioinformatic approach oriented to the analysis and design of peptides with high affinity to MHC class I molecules.
We report on a new method to compute the antigenic degree of peptides from available experimental data on peptide binding affinity to class I MHC molecules. The methodology is a combination of two strategies at different levels of information. The first, at the primary structure level, consists in expressing the peptides binding activity as a profile of amino acid contributions, amino acid similarity being accounted for by their characteristic physicochemical properties and their position within the sequence. The higher level of the strategy is based on a meticulous analysis of the contact interface of the peptides with the cleft constituting the receptor region of a particular class I MHC molecule. Interaction interfaces are inferred by docking the peptide onto the receptor groove of the MHC molecule; evaluation of the affinity of the peptide to the receptor is then performed by analysis of the electrostatic and hydrophobic energies on points of the interaction interface. The result is a robust system for analysis of peptide affinity to class I MHC molecules since while the first analysis dictates the composition of active sequences at the amino acid level, the second translates this information to the atomic level, where the molecular interaction can be analyzed in terms of the intrinsic interatomic forces and energies. Evaluation results for the methodology are encouraging since high affinity peptides are reflected by high scores at both levels of information, and are proportionally lower for peptides of medium and lower affinity for which interaction surfaces show relatively lower electrostatic complementarity and hydrophobic correlation than for the former.
Algorithms↗
A tumor progression model for hepatocellular carcinoma: bioinformatic analysis of genomic data.
BACKGROUND & AIMS: It is widely recognized that genomic abnormalities underpin the development of human cancers. Aberrant patterns of chromosomal changes may represent useful information that can be used in classifying the complex traits of liver cancer cases for the genetic events involved in tumor carcinogenesis, tumor progression, and prognosis. METHODS: Genome-wide chromosomal aberrations of 158 hepatitis B virus-associated hepatocellular carcinoma (HCC) were studied by comparative genomic hybridization (CGH). By application of a self-organizing tree algorithm, statistically significant CGH events were used to construct an evolutionary tree that could infer patient subgroups with different degrees of tumor progression. The key CGH events in the subgroups were identified. The clinical significance of the groupings and the key CGH events were examined. RESULTS: Based on the patterns of significant chromosomal aberrations derived, 3 HCC subgroups organized in an evolutionary tree were identified. The groupings possessed information reflecting the degrees of tumor progression, including numbers of chromosomal aberrations, tumor stages, tumor sizes, and disease outcome. Gains of 1q21-23 and 8q22-24 were identified as genomic events associated with the early development of HCC. Gain of 3q22-24, however, was identified as 1 of the late genomic events found to be associated with tumor recurrence and poor overall patient survival. CONCLUSIONS: A tumor progression model for HCC was constructed and revealed chromosomal imbalances that were significantly associated with clinical pathologic characteristics of the disease. This model explains a significant part of the variations in clinical outcome among HCC patients.
Adult↗
A bioinformatical approach suggests the function of the autoimmune hepatitis target antigen soluble liver antigen/liver pancreas.
Antibodies to a soluble liver antigen/liver pancreas (SLA/LP) appear to be highly specific for the diagnosis of autoimmune hepatitis. The SLA/LP target antigen was recently identified as a hitherto unknown gene encoding 474 amino acid residues. The function of this antigen remains unclear, because it does not share sequence homology with proteins of known function stored in any of the publicly accessible databases. Therefore we used a new theoretical method called fold recognition and could show that the SLA/LP sequence is compatible with the architecture of the superfamily of pyridoxal phosphate (PLP; vitamin B6)-dependent transferases. Its function is likely to be that of a serine hydroxymethyltransferase and may be an important enzyme in the thus far poorly understood selenocysteine pathway.
Amino Acid Sequence↗
Building a human kinase gene repository: bioinformatics, molecular cloning, and functional validation.
Kinases catalyze the phosphorylation of proteins, lipids, sugars, nucleosides, and other important cellular metabolites and play key regulatory roles in all aspects of eukaryotic cell physiology. Here, we describe the mining of public databases to collect the sequence information of all identified human kinase genes and the cloning of the corresponding ORFs. We identified 663 genes, 511 encoding protein kinases, and 152 encoding nonprotein kinases. We describe the successful cloning and sequence verification of 270 of these genes. Subcloning of this gene set in mammalian expression vectors and their use in high-throughput cell-based screens allowed the validation of the clones at the level of expression and the identification of previously uncharacterized modulators of the survivin promoter. Moreover, expressions of the kinase genes in bacteria, followed by autophosphorylation assays, identified 21 protein kinases that showed autocatalytic activity. The work described here will facilitate the functional assaying of this important gene family in phenotypic screens and their use in biochemical and structural studies.
Animals↗
Bioinformatic analyses implicate the collaborating meiotic crossover/chiasma proteins Zip2, Zip3, and Spo22/Zip4 in ubiquitin labeling.
Zip2 and Zip3 are meiosis-specific proteins that, in collaboration with several partners, act at the sites of crossover-designated, axis-associated recombinational interactions to mediate crossover/chiasma formation. Here, Spo22 (also called Zip4) is identified as a probable functional collaborator of Zip2/3. The molecular roles of Zip2, Zip3, and Spo22/Zip4 are unknown. All three proteins are part of a small evolutionary cohort comprising similar homologs in four related yeasts. Zip3 is shown to contain a RING finger whose structural features most closely match those of known ubiquitin E3s. Further, Zip3 exhibits major domainal homologies to Rad18, a known DNA-binding ubiquitin E3. Also described is an approach to the identification and mapping of repeated protein sequence motifs, Alignment Based Repeat Annotation (ABRA), that we have developed. When ABRA is applied to Zip2 and Spo22/Zip4, they emerge as a 14-blade WD40-like repeat protein and a 22-unit tetratricopeptide repeat protein, respectively. WD40 repeats of Cdc20, Cdh1, and Cdc16 and tetratricopeptide repeats of Cdc16, Cdc23, and Cdc27, all components of the anaphase-promoting complex, are also analyzed. These and other findings suggest that Zip2, Zip3, and Zip4 act together to mediate a process that involves Zip3-mediated ubiquitin labeling, potentially as a unique type of ubiquitin-conjugating complex.
Amino Acid Sequence↗
Diversity and complexity of HIV-1 drug resistance: a bioinformatics approach to predicting phenotype from genotype.
Drug resistance testing has been shown to be beneficial for clinical management of HIV type 1 infected patients. Whereas phenotypic assays directly measure drug resistance, the commonly used genotypic assays provide only indirect evidence of drug resistance, the major challenge being the interpretation of the sequence information. We analyzed the significance of sequence variations in the protease and reverse transcriptase genes for drug resistance and derived models that predict phenotypic resistance from genotypes. For 14 antiretroviral drugs, both genotypic and phenotypic resistance data from 471 clinical isolates were analyzed with a machine learning approach. Information profiles were obtained that quantify the statistical significance of each sequence position for drug resistance. For the different drugs, patterns of varying complexity were observed, including between one and nine sequence positions with substantial information content. Based on these information profiles, decision tree classifiers were generated to identify genotypic patterns characteristic of resistance or susceptibility to the different drugs. We obtained concise and easily interpretable models to predict drug resistance from sequence information. The prediction quality of the models was assessed in leave-one-out experiments in terms of the prediction error. We found prediction errors of 9.6-15.5% for all drugs except for zalcitabine, didanosine, and stavudine, with prediction errors between 25.4% and 32.0%. A prediction service is freely available at http://cartan.gmd.de/geno2pheno.html.
Computational Biology↗
Analyses of p53 target genes in the human genome by bioinformatic and microarray approaches.
The completion of the human genome sequence (International Human Genome Sequence Consortium (2001) Nature 409, 860-921; Venter, J. C., et al. (2001) Science 291, 1304-1351) allows for new ways to analyze global cellular regulatory mechanisms. Here we present a strategy to identify genes regulated by specific transcription factors in the human genome, and apply it to p53. We first collected promoters or introns of all genes available using two methods: GenBank(TM) annotation and a computationally derived transcript map. 4,852 genes analyzed in this way contained at least one p53 consensus binding sequence. Of 13 genes randomly selected for mRNA analysis, 11 were shown to respond to p53 expression. Five promoters were analyzed by chromatin immunoprecipitation, which revealed that all were bound by p53 in vivo. We then analyzed 33,615 unique human genes on cDNA microarrays, identifying 1,501 genes that respond to p53 expression. A parameter was derived that demonstrates that in silico prediction greatly enriches for genes that are activated and repressed by p53 and assists us to suggest other signaling pathways that may be connected to p53. The methods shown here illustrate a novel approach to analysis of global gene regulatory network through the integration of human genomic sequence information and genome-wide gene expression analysis.
Computational Biology↗
Specificity changes in the evolution of type II restriction endonucleases: a biochemical and bioinformatic analysis of restriction enzymes that recognize unrelated sequences.
How restriction enzymes with their different specificities and mode of cleavage evolved has been a long standing question in evolutionary biology. We have recently shown that several Type II restriction endonucleases, namely SsoII (downward arrow CCNGG), PspGI (downward arrow CCWGG), Eco-RII (downward arrow CCWGG), NgoMIV (G downward arrow CCGGC), and Cfr10I (R downward arrow CCGGY), which recognize similar DNA sequences (as indicated, where the downward arrows denote cleavage position), share limited sequence similarity over an interrupted stretch of approximately 70 amino acid residues with MboI, a Type II restriction endonuclease from Moraxella bovis (Pingoud, V., Conzelmann, C., Kinzebach, S., Sudina, A., Metelev, V., Kubareva, E., Bujnicki, J. M., Lurz, R., Luder, G., Xu, S. Y., and Pingoud, A. (2003) J. Mol. Biol. 329, 913-929). Nevertheless, MboI has a dissimilar DNA specificity (downward arrow GATC) compared with these enzymes. In this study, we characterize MboI in detail to determine whether it utilizes a mechanism of DNA recognition similar to SsoII, PspGI, EcoRII, NgoMIV, and Cfr10I. Mutational analyses and photocross-linking experiments demonstrate that MboI exploits the stretch of approximately 70 amino acids for DNA recognition and cleavage. It is therefore likely that MboI shares a common evolutionary origin with SsoII, PspGI, EcoRII, NgoMIV, and Cfr10I. This is the first example of a relatively close evolutionary link between Type II restriction enzymes of widely different specificities.
Amino Acid Sequence↗
The endonuclease domain of bacteriophage terminases belongs to the resolvase/integrase/ribonuclease H superfamily: a bioinformatics analysis validated by a functional study on bacteriophage T5.
Bacteriophage terminases are essential molecular motors involved in the encapsidation of viral DNA. They are hetero-multimers whose large subunit encodes both ATPase and endonuclease activities. Although the ATPase domain is well characterized from sequence and functional analysis, the C-terminal region remains poorly defined. We describe sequence-structure comparisons of the endonuclease region of various bacteriophages that revealed new sequence similarities shared by this region and the Holliday junction resolvase RuvC and to a lesser extent the HIV integrase and the ribonuclease H. Extensive sequence comparison and motif refinement led to a common signature of terminases and resolvases with three conserved acidic residues engaged in catalytic activity. Sequence analyses were validated by in vivo and in vitro functional assays showing that the nuclease activity of the endonuclease domain of bacteriophage T5 terminase was abolished by mutation of any of the three predicted catalytic aspartates. Overall, these data suggest that the endonuclease domains of terminases operate autonomously and that they adopt a fold similar to that of resolvases and share the same divalent cation-dependent enzymatic mechanism.
Amino Acid Sequence↗
PROTEOME-3D: an interactive bioinformatics tool for large-scale data exploration and knowledge discovery.
Comprehensive understanding of biological systems requires efficient and systematic assimilation of high-throughput datasets in the context of the existing knowledge base. A major limitation in the field of proteomics is the lack of an appropriate software platform that can synthesize a large number of experimental datasets in the context of the existing knowledge base. Here, we describe a software platform, termed PROTEOME-3D, that utilizes three essential features for systematic analysis of proteomics data: creation of a scalable, queryable, customized database for identified proteins from published literature; graphical tools for displaying proteome landscapes and trends from multiple large-scale experiments; and interactive data analysis that facilitates identification of crucial networks and pathways. Thus, PROTEOME-3D offers a standardized platform to analyze high-throughput experimental datasets for the identification of crucial players in co-regulated pathways and cellular processes.
Computational Biology↗
InterRett--The application of bioinformatics to International Rett syndrome research.
InterRett, International Rett Syndrome Association (IRSA) Rett Phenotype Database, is a unique international project funded by the IRSA, which brings together child neurologists, geneticists, paediatricians, epidemiologists, researchers and families of affected children. The principal aim of InterRett is to increase the clinical understanding of Rett syndrome throughout the world and with the statistical power of large case numbers, determine any correlations between genotype and the phenotypic characteristics. Since establishment of the database in January 2003, InterRett has registered 286 cases from 24 countries, with family questionnaire data submitted on 242 cases and clinician data on 116 cases. Collated de-identified data gathered from families and clinicians have been incorporated into a searchable online database allowing simple and complex interrogation of the clinical phenotype information. InterRett will also serve as a clearing house for data to encourage inter-country collaboration between researchers and negotiations are in place with several countries for data contributions in excess of 1000 cases. The resulting online database will be an invaluable resource for understanding the nature and management of Rett syndrome, as well as providing a model for other rare childhood disorders.
Child↗