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PubMed2005

From cyclohydrolase to oxidoreductase: discovery of nitrile reductase activity in a common fold.

The enzyme YkvM from Bacillus subtilis was identified previously along with three other enzymes (YkvJKL) in a bioinformatics search for enzymes involved in the biosynthesis of queuosine, a 7-deazaguanine modified nucleoside found in tRNA(GUN) of Bacteria and Eukarya. Genetic analysis of ykvJKLM mutants in Acinetobacter confirmed that each was essential for queuosine biosynthesis, and the genes were renamed queCDEF. QueF exhibits significant homology to the type I GTP cyclohydrolases characterized by FolE. Given that GTP is the precursor to queuosine and that a cyclohydrolase-like reaction was postulated as the initial step in queuosine biosynthesis, QueF was proposed to be the putative cyclohydrolase-like enzyme responsible for this reaction. We have cloned the queF genes from B. subtilis and Escherichia coli and characterized the recombinant enzymes. Contrary to the predictions based on sequence analysis, we discovered that the enzymes, in fact, catalyze a mechanistically unrelated reaction, the NADPH-dependent reduction of 7-cyano-7-deazaguanineto7-aminomethyl-7-deazaguanine, a late step in the biosynthesis of queuosine. We report here in vitro and in vivo studies that demonstrate this catalytic activity, as well as preliminary biochemical and bioinformatics analysis that provide insight into the structure of this family of enzymes.

Acinetobacter↗

PubMed2005

Unsupervised learning of natural languages.

We address the problem, fundamental to linguistics, bioinformatics, and certain other disciplines, of using corpora of raw symbolic sequential data to infer underlying rules that govern their production. Given a corpus of strings (such as text, transcribed speech, chromosome or protein sequence data, sheet music, etc.), our unsupervised algorithm recursively distills from it hierarchically structured patterns. The adios (automatic distillation of structure) algorithm relies on a statistical method for pattern extraction and on structured generalization, two processes that have been implicated in language acquisition. It has been evaluated on artificial context-free grammars with thousands of rules, on natural languages as diverse as English and Chinese, and on protein data correlating sequence with function. This unsupervised algorithm is capable of learning complex syntax, generating grammatical novel sentences, and proving useful in other fields that call for structure discovery from raw data, such as bioinformatics.

Algorithms↗

PubMed2003

A distal enhancer in the interferon-gamma (IFN-gamma) locus revealed by genome sequence comparison.

Large-scale cross-species DNA sequence comparison has become a powerful tool to identify conserved cis-regulatory modules of genes. However, bioinformatic analysis alone cannot reveal how an evolutionarily conserved region regulates gene expression: whether it functions as an enhancer, silencer, or insulator; whether its function is cell-type restricted; and whether biologically relevant transcription factors bind to the element. Here we combine bioinformatics with wet-lab techniques to illustrate a general and systematic method of identifying functional conserved regulatory regions of genes. We applied this approach to the interferon-gamma (IFN-gamma) gene. Comparison of human and mouse IFN-gamma reveals a highly conserved non-coding sequence located approximately 5 kb 5' of the transcription start site. This region coincides with constitutive and inducible DNase I hypersensitivity sites present in IFN-gamma-producing Th1 cells but not in Th2 cells that do not produce IFN-gamma. Histone methylation at the 5' conserved non-coding sequences indicates a more accessible chromatin structure in Th1 cells compared with Th2 cells. This element binds two transcription factors known to be essential for IFN-gamma expression: nuclear factor of activated T cells, an inducible transcription factor, and T-box protein expressed in T cells, a cell lineage-restricted transcription factor. Together, these findings identify a highly conserved distal enhancer in the IFN-gamma cytokine locus and validate our approach as a successful method to detect cis-regulatory elements.

Animals↗

PubMed2004

Solution structure of a ubiquitin-like domain from tubulin-binding cofactor B.

Proper folding and assembly of tubulin alphabeta-heterodimers involves a stepwise progression mediated by a group of protein cofactors A through E. Upon release of the tubulin monomers from the chaperonin CCT, they are acted upon by each cofactor in the folding pathway through a unique combination of protein interaction domains. Three-dimensional structures have previously been reported for cofactor A and the C-terminal CAP-Gly domain of cofactor B (CoB). Here we report the NMR structure of the N-terminal domain of Caenorhabditis elegans CoB and show that it closely resembles ubiquitin as was recently postulated on the basis of bioinformatic analysis (Grynberg, M., Jaroszewski, L., and Godzik, A. (2003) BMC Bioinformatics 4, 46). CoB binds partially folded alpha-tubulin monomers, and a putative tubulin-binding motif within the N-terminal domain is identified from sequence and structure comparisons. Based on modeling of the homologous cofactor E ubiquitin-like domain, we hypothesize that cofactors B and E may associate via their beta-grasp domains in a manner analogous to the PB1 and caspase-activated deoxyribonuclease superfamily of protein interaction domains.

Amino Acid Sequence↗

PubMed2005

A mathematical model for the branched chain amino acid biosynthetic pathways of Escherichia coli K12.

As a first step toward the elucidation of the systems biology of the model organism Escherichia coli, it was our goal to mathematically model a metabolic system of intermediate complexity, namely the well studied end product-regulated pathways for the biosynthesis of the branched chain amino acids L-isoleucine, L-valine, and L-leucine. This has been accomplished with the use of kMech (Yang, C.-R., Shapiro, B. E., Mjolsness, E. D., and Hatfield, G. W. (2005) Bioinformatics 21, in press), a Cellerator (Shapiro, B. E., Levchenko, A., Meyerowitz, E. M., Wold, B. J., and Mjolsness, E. D. (2003) Bioinformatics 19, 677-678) language extension that describes a suite of enzyme reaction mechanisms. Each enzyme mechanism is parsed by kMech into a set of fundamental association-dissociation reactions that are translated by Cellerator into ordinary differential equations. These ordinary differential equations are numerically solved by Mathematica. Any metabolic pathway can be simulated by stringing together appropriate kMech models and providing the physical and kinetic parameters for each enzyme in the pathway. Writing differential equations is not required. The mathematical model of branched chain amino acid biosynthesis in E. coli K12 presented here incorporates all of the forward and reverse enzyme reactions and regulatory circuits of the branched chain amino acid biosynthetic pathways, including single and multiple substrate (Ping Pong and Bi Bi) enzyme kinetic reactions, feedback inhibition (allosteric, competitive, and non-competitive) mechanisms, the channeling of metabolic flow through isozymes, the channeling of metabolic flow via transamination reactions, and active transport mechanisms. This model simulates the results of experimental measurements.

Acetolactate Synthase↗

PubMed2005

hCLCA1 and mCLCA3 are secreted non-integral membrane proteins and therefore are not ion channels.

Proteins of the CLCA gene family have been proposed to mediate calcium-activated chloride currents. In this study, we used detailed bioinformatics analysis and found that no transmembrane domains are predicted in hCLCA1 or mCLCA3 (Gob-5). Further analysis suggested that they are globular proteins containing domains that are likely to be involved in protein-protein interactions. In support of the bioinformatics analysis, biochemical studies showed that hCLCA1 and mCLCA3, when expressed in HEK293 cells, could be removed from the cell surface and could be detected in the extracellular medium, even after short incubation times. The accumulation in the medium was shown to be brefeldin A-sensitive, demonstrating that hCLCA1 is constitutively secreted. The N-terminal cleavage products of hCLCA1 and mCLCA3 could be detected in bronchoalveolar lavage fluid taken from asthmatic subjects and ovalbumin-challenged mice, demonstrating release from cells in a physiological setting. We conclude that hCLCA1 and mCLCA3 are non-integral membrane proteins and therefore cannot be chloride channels in their own right.

Animals↗

PubMed2006

Subclassification of the RBCC/TRIM superfamily reveals a novel motif necessary for microtubule binding.

The biological significance of RBCC (N-terminal RING finger/B-box/coiled coil) proteins is increasingly being appreciated following demonstrated roles in disease pathogenesis, tumorigenesis, and retroviral protective activity. Found in all multicellular eukaryotes, RBCC proteins are involved in a vast array of intracellular functions; but as a general rule, they appear to function as part of large protein complexes and possess ubiquitin-protein isopeptide ligase activity. Those members characterized to date have diverse C-terminal domain compositions and equally diverse subcellular localizations and functions. Using a bioinformatics approach, we have identified some new RBCC proteins that help define a subfamily that shares an identical domain arrangement (MID1, MID2, TRIM9, TNL, TRIM36, and TRIFIC). Significantly, we show that all analyzed members of this subfamily associate with the microtubule cytoskeleton, suggesting that subcellular compartmentalization is determined by the unique domain architecture, which may in turn reflect basic functional similarities. We also report a new motif called the COS box, which is found within these proteins, the MURF family, and a distantly related non-RBCC microtubule-binding protein. Notably, we demonstrate that mutations in the COS box abolish microtubule binding ability, whereas its incorporation into a nonmicrotubule-binding RBCC protein redirects it to microtubule structures. Further bioinformatics investigation permitted subclassification of the entire human RBCC complement into nine subfamilies based on their varied C-terminal domain compositions. This classification schema may aid the understanding of the molecular function of members of each subgroup and their potential involvement in both basic cellular processes and human disease.

Adaptor Proteins, Signal Transducing↗

PubMed2006

Coordinated regulation of the Neisseria gonorrhoeae-truncated denitrification pathway by the nitric oxide-sensitive repressor, NsrR, and nitrite-insensitive NarQ-NarP.

Neisseria gonorrhoeae survives anaerobically by reducing nitrite to nitrous oxide catalyzed by the nitrite and nitric oxide reductases, AniA and NorB. P(aniA) is activated by FNR (regulator of fumarate and nitrate reduction), the two-component regulatory system NarQ-NarP, and induced by nitrite; P(norB) is induced by NO independently of FNR by an uncharacterized mechanism. We report the results of microarray analysis, bioinformatic analysis, and chromatin immunoprecipitation, which revealed that only five genes with readily identified NarP-binding sites are differentially expressed in narP(+) and narP strains. These include three genes implicated in the truncated gonococcal denitrification pathway: aniA, norB, and narQ. We also report that (i) nitrite induces aniA transcription in a narP mutant; (ii) nitrite induction involves indirect inactivation by nitric oxide of a gonococcal repressor, NsrR, identified from a multigenome bioinformatic study; (iii) in an nsrR mutant, aniA, norB, and dnrN (encoding a putative reactive nitrogen species response protein) were expressed constitutively in the absence of nitrite, suggesting that NsrR is the only NO-sensing transcription factor in N. gonorrhoeae; and (iv) NO rather than nitrite is the ligand to which NsrR responds. When expressed in Escherichia coli, gonococcal NarQ and chimaeras of E. coli and gonococcal NarQ are ligand-insensitive and constitutively active: a "locked-on" phenotype. We conclude that genes involved in the truncated denitrification pathway of N. gonorrhoeae are key components of the small NarQP regulon, that NarP indirectly regulates P(norB) by stimulating NO production by AniA, and that NsrR plays a critical role in enabling gonococci to evade NO generated as a host defense mechanism.

Antigens, Bacterial↗

PubMed2002

A new method to estimate ligand-receptor energetics.

In the discovery of new drugs, lead identification and optimization have assumed critical importance given the number of drug targets generated from genetic, genomics, and proteomic technologies. High-throughput experimental screening assays have been complemented recently by "virtual screening" approaches to identify and filter potential ligands when the characteristics of a target receptor structure of interest are known. Virtual screening mandates a reliable procedure for automatic ranking of structurally distinct ligands in compound library databases. Computing a rank score requires the accurate prediction of binding affinities between these ligands and the target. Many current scoring strategies require information about the target three-dimensional structure. In this study, a new method to estimate the free binding energy between a ligand and receptor is proposed. We extend a central idea previously reported (Bock, J. R., and Gough, D. A. (2001) Predicting protein-protein interactions from primary structure. Bioinformatics 17, 455-460; Bock, J. R., and Gough, D. A. (2002) Whole-proteome interaction mining. Bioinformatics, in press) that uses simple descriptors to represent biomolecules as input examples to train a support vector machine (Smola, A. J., and Schölkopf, B. (1998) A Tutorial on Support Vector Regression, Neuro-COLT Technical Report NC-TR-98-030, Royal Holloway College, University of London, UK) and the application of the trained system to previously unseen pairs, estimating their propensity for interaction. Here we seek to learn the function that maps features of a receptor-ligand pair onto their equilibrium free binding energy. These features do not comprise any direct information about the three-dimensional structures of ligand or target. In cross-validation experiments, it is demonstrated that objective measurements of prediction error rate and rank-ordering statistics are competitive with those of several other investigations, most of which depend on three-dimensional structural data. The size of the sample (n = 2,671) indicates that this approach is robust and may have widespread applicability beyond restricted families of receptor types. It is concluded that newly sequenced proteins, or those for which three-dimensional crystal structures are not easily obtained, can be rapidly analyzed for their binding potential against a library of ligands using this methodology.

Drug Design↗

PubMed2004

Microarray transfection analysis of transcriptional regulation by cAMP-dependent protein kinase.

A wide variety of bioinformatic tools have been described to characterize potential transcriptional regulatory mechanisms based on genomic sequence analysis and microarray hybridization studies. However, these regulatory mechanisms are still experimentally verified using transient transfection methods. Current transfection methods are limited both by their large scale and by the low level of efficiency for certain cell types. Our goals were to develop a microarray-based transfection method that could be optimized for different cell types and that would be useful in reporter assays of transcriptional regulation. Here we describe a novel transfection method, termed STEP (surface transfection and expression protocol), which employs microarray-based DNA transfection of adherent cells in the functional analysis of transcriptional regulation. In STEP, recombinant proteins with biological activities designed to enhance transfection are complexed with expression vector DNAs prior to spotting on microscope slides. The recombinant proteins used in STEP complexes can be varied to increase the efficiency for different cell types. We demonstrate that STEP efficiently transfects both supercoiled plasmids and PCR-generated linear expression cassettes. A co-transfection assay using effector expression vectors encoding the cAMP-dependent protein kinase (PKA), as well as reporter vectors containing PKA-regulated promoters, showed that STEP transfection allows detection and quantitation of transcriptional regulation by this protein kinase. Because bioinformatic studies often result in the identification of many putative regulatory elements and signaling pathways, this approach should be of utility in high-throughput functional genomic studies of transcriptional regulation.

Animals↗

PubMed2006

Reconstructing the regulatory kinase pathways of myogenesis from phosphopeptide data.

Multiple kinase activities are required for skeletal muscle differentiation. However, the mechanisms by which these kinase pathways converge to coordinate the myogenic process are unknown. Using multiple phosphoprotein and phosphopeptide enrichment techniques we obtained phosphopeptides from growing and differentiating C2C12 muscle cells and determined specific peptide sequences using LC-MS/MS. To place these phosphopeptides into a rational context, a bioinformatics approach was used. Phosphorylation sites were matched to known site-specific and to site non-specific kinase-substrate interactions, and then other substrates and upstream regulators of the implicated kinases were incorporated into a model network of protein-protein interactions. The model network implicated several kinases of known relevance to myogenesis including AKT, GSK3, CDK5, p38, DYRK, and MAPKAPK2 kinases. This combination of proteomics and bioinformatics technologies should offer great utility as the volume of protein-protein and kinase-substrate information continues to increase.

Animals↗

PubMed2006

Lectin capture strategies combined with mass spectrometry for the discovery of serum glycoprotein biomarkers.

The application of mass spectrometry to identify disease biomarkers in clinical fluids like serum using high throughput protein expression profiling continues to evolve as technology development, clinical study design, and bioinformatics improve. Previous protein expression profiling studies have offered needed insight into issues of technical reproducibility, instrument calibration, sample preparation, study design, and supervised bioinformatic data analysis. In this overview, new strategies to increase the utility of protein expression profiling for clinical biomarker assay development are discussed with an emphasis on utilizing differential lectin-based glycoprotein capture and targeted immunoassays. The carbohydrate binding specificities of different lectins offer a biological affinity approach that complements existing mass spectrometer capabilities and retains automated throughput options. Specific examples using serum samples from prostate cancer and hepatocellular carcinoma subjects are provided along with suggested experimental strategies for integration of lectin-based methods into clinical fluid expression profiling strategies. Our example workflow incorporates the necessity of early validation in biomarker discovery using an immunoaffinity-based targeted analytical approach that integrates well with upstream discovery technologies.

Amino Acid Sequence↗

PubMed2006

DivergentSet, a tool for picking non-redundant sequences from large sequence collections.

DivergentSet addresses the important but so far neglected bioinformatics task of choosing a representative set of sequences from a larger collection. We found that using a phylogenetic tree to guide the construction of divergent sets of sequences can be up to 2 orders of magnitude faster than the naive method of using a full distance matrix. By providing a user-friendly interface (available online) that integrates the tasks of finding additional sequences, building and refining the divergent set, producing random divergent sets from the same sequences, and exporting identifiers, this software facilitates a wide range of bioinformatics analyses including finding significant motifs and covariations. As an example application of DivergentSet, we demonstrate that the motifs identified by the motif-finding package MEME (Motif Elicitation by Maximum Entropy) are highly unstable with respect to the specific choice of sequences. This instability suggests that the types of sensitivity analysis enabled by DivergentSet may be widely useful for identifying the motifs of biological significance.

Amino Acid Sequence↗

PubMed2001

Are grammatical representations useful for learning from biological sequence data?--a case study.

This paper investigates whether Chomsky-like grammar representations are useful for learning cost-effective, comprehensible predictors of members of biological sequence families. The Inductive Logic Programming (ILP) Bayesian approach to learning from positive examples is used to generate a grammar for recognising a class of proteins known as human neuropeptide precursors (NPPs). Collectively, five of the co-authors of this paper, have extensive expertise on NPPs and general bioinformatics methods. Their motivation for generating a NPP grammar was that none of the existing bioinformatics methods could provide sufficient cost-savings during the search for new NPPs. Prior to this project experienced specialists at SmithKline Beecham had tried for many months to hand-code such a grammar but without success. Our best predictor makes the search for novel NPPs more than 100 times more efficient than randomly selecting proteins for synthesis and testing them for biological activity. As far as these authors are aware, this is both the first biological grammar learnt using ILP and the first real-world scientific application of the ILP Bayesian approach to learning from positive examples. A group of features is derived from this grammar. Other groups of features of NPPs are derived using other learning strategies. Amalgams of these groups are formed. A recognition model is generated for each amalgam using C4.5 and C4.5rules and its performance is measured using both predictive accuracy and a new cost function, Relative Advantage (RA). The highest RA was achieved by a model which includes grammar-derived features. This RA is significantly higher than the best RA achieved without the use of the grammar-derived features. Predictive accuracy is not a good measure of performance for this domain because it does not discriminate well between NPP recognition models: despite covering varying numbers of (the rare) positives, all the models are awarded a similar (high) score by predictive accuracy because they all exclude most of the abundant negatives.

Bayes Theorem↗

PubMed2003

Mining the biomedical literature in the genomic era: an overview.

The past decade has seen a tremendous growth in the amount of experimental and computational biomedical data, specifically in the areas of genomics and proteomics. This growth is accompanied by an accelerated increase in the number of biomedical publications discussing the findings. In the last few years, there has been a lot of interest within the scientific community in literature-mining tools to help sort through this abundance of literature and find the nuggets of information most relevant and useful for specific analysis tasks. This paper provides a road map to the various literature-mining methods, both in general and within bioinformatics. It surveys the disciplines involved in unstructured-text analysis, categorizes current work in biomedical literature mining with respect to these disciplines, and provides examples of text analysis methods applied towards meeting some of the current challenges in bioinformatics.

Biomedical Research↗

PubMed2003

A life scientist's gateway to distributed data management and computing: the PathPort/ToolBus framework.

The emergent needs of the bioinformatics community challenge current information systems. The pace of biological data generation far outstrips Moore's Law. Therefore, a gap continues to widen between the capabilities to produce biological (molecular and cell) data sets and the capability to manage and analyze these data sets. As a result, Federal investments in large data set generation produces diminishing returns in terms of the community's capabilities of understanding biology and leveraging that understanding to make scientific and technological advances that improve society. We are building an open framework to address various data management issues including data and tool interoperability, nomenclature and data communication standardization, and database integration. PathPort, short for Pathogen Portal, employs a generic, web-services based framework to deal with some of the problems identified by the bioinformatics community. The motivating research goal of a scalable system to provide data management and analysis for key pathosystems, especially relating to molecular data, has resulted in a generic framework using two major components. On the server-side, we employ web-services. On the client-side, a Java application called ToolBus acts as a client-side "bus" for contacting data and tools and viewing results through a single, consistent user interface.

Biological Science Disciplines↗

PubMed2004

Efficient exact p-value computation for small sample, sparse, and surprising categorical data.

A major obstacle in applying various hypothesis testing procedures to datasets in bioinformatics is the computation of ensuing p-values. In this paper, we define a generic branch-and-bound approach to efficient exact p-value computation and enumerate the required conditions for successful application. Explicit procedures are developed for the entire Cressie-Read family of statistics, which includes the widely used Pearson and likelihood ratio statistics in a one-way frequency table goodness-of-fit test. This new formulation constitutes a first practical exact improvement over the exhaustive enumeration performed by existing statistical software. The general techniques we develop to exploit the convexity of many statistics are also shown to carry over to contingency table tests, suggesting that they are readily extendible to other tests and test statistics of interest. Our empirical results demonstrate a speed-up of orders of magnitude over the exhaustive computation, significantly extending the practical range for performing exact tests. We also show that the relative speed-up gain increases as the null hypothesis becomes sparser, that computation precision increases with increase in speed-up, and that computation time is very moderately affected by the magnitude of the computed p-value. These qualities make our algorithm especially appealing in the regimes of small samples, sparse null distributions, and rare events, compared to the alternative asymptotic approximations and Monte Carlo samplers. We discuss several established bioinformatics applications, where small sample size, small expected counts in one or more categories (sparseness), and very small p-values do occur. Our computational framework could be applied in these, and similar cases, to improve performance.

Computational Biology↗

PubMed2006

fjoin: simple and efficient computation of feature overlaps.

Sets of biological features with genome coordinates (e.g., genes and promoters) are a particularly common form of data in bioinformatics today. Accordingly, an increasingly important processing step involves comparing coordinates from large sets of features to find overlapping feature pairs. This paper presents fjoin, an efficient, robust, and simple algorithm for finding these pairs, and a downloadable implementation. For typical bioinformatics feature sets, fjoin requires O(n log(n)) time (O(n) if the inputs are sorted) and uses O(1) space. The reference implementation is a stand-alone Python program; it implements the basic algorithm and a number of useful extensions, which are also discussed in this paper.

Algorithms↗