CiteULike: alexg's library [264 articles]

Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli

Robert Schuetz — 2007-07-11T18:26:55-00:00

Mol Syst Biol, Vol. 3 (10 July 2007), 119.

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

CR Yang — 2007-10-01T05:02:36-00:00

J Biol Chem, Vol. 280, No. 12. (25 March 2005), pp. 11224-11232.

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.

Feedback inhibition of dihydrodipicolinate synthase enzymes by L-lysine.

S Blickling — 2007-10-01T05:00:47-00:00

Biol Chem, Vol. 378, No. 3-4. (r 1997), pp. 207-210.

Dihydrodipicolinate synthase (DHDPS) is the first enzyme unique to the lysine biosynthetic pathway and is feedback regulated by L-lysine in plants and some bacteria. The allosteric binding site has been localized by X-ray crystallography and is in agreement with reported mutations of plant DHDPS enzymes, which confer insensitivity to feedback inhibition. Three possible elements of the mechanism of lysine inhibition are discussed.

The aromatic amino acid hydroxylases.

PF Fitzpatrick — 2007-10-01T04:58:48-00:00

Adv Enzymol Relat Areas Mol Biol, Vol. 74 (2000), pp. 235-294.

The enzymes phenylalanine hydroxylase, tyrosine hydroxylase, and tryptophan hydroxylase constitute the family of pterin-dependent aromatic amino acid hydroxylases. Each enzyme catalyzes the hydroxylation of the aromatic side chain of its respective amino acid substrate using molecular oxygen and a tetrahydropterin as substrates. Recent advances have provided insights into the structures, mechanisms, and regulation of these enzymes. The eukaryotic enzymes are homotetramers comprised of homologous catalytic domains and discrete regulatory domains. The ligands to the active site iron atom as well as residues involved in substrate binding have been identified from a combination of structural studies and site-directed mutagenesis. Mechanistic studies with nonphysiological and isotopically substituted substrates have provided details of the mechanism of hydroxylation. While the complex regulatory properties of phenylalanine and tyrosine hydroxylase are still not fully understood, effects of regulation on key kinetic parameters have been identified. Phenylalanine hydroxylase is regulated by an interaction between phosphorylation and allosteric regulation by substrates. Tyrosine hydroxylase is regulated by phosphorylation and feedback inhibition by catecholamines.

The molecular pathway for the allosteric regulation of tryptophan synthase.

S Raboni — 2007-10-01T04:55:26-00:00

Biochim Biophys Acta, Vol. 1647, No. 1-2. (11 April 2003), pp. 157-160.

The pyridoxal 5'-phosphate (PLP)-dependent tryptophan synthase is a alpha(2)beta(2) complex. The alpha-beta subunit interaction plays a critical role both in the reciprocal activation of the individual subunits and in the allosteric regulation. We have investigated whether mutations of alpha loop6 Gly(181) and beta helix6 Ser(178) affect intersubunit communication. The loss of the hydrogen bond between these residues, achieved by proline substitution, does not significantly influence the intersubunit catalytic activation, but completely abolishes ligand-induced intersubunit signaling. The comparison of the crystal structure of the wild type and beta Ser(178)Pro mutant, in the absence and presence of alpha-subunit ligands, indicates that the removal of the interaction between beta Ser(178) and alpha Gly(181) strongly affects the equilibrium between active (closed) and inactive (open) conformations of the alpha-active site, the latter being stabilized in both mutants.

Complexity in regulation of tryptophan biosynthesis in Bacillus subtilis.

P Gollnick — 2007-10-01T04:54:44-00:00

Annu Rev Genet, Vol. 39 (2005), pp. 47-68.

Bacillus subtilis uses novel regulatory mechanisms in controlling expression of its genes of tryptophan synthesis and transport. These mechanisms respond to changes in the intracellular concentrations of free tryptophan and uncharged tRNA(Trp). The major B. subtilis protein that regulates tryptophan biosynthesis is the tryptophan-activated RNA-binding attenuation protein, TRAP. TRAP is a ring-shaped molecule composed of 11 identical subunits. Active TRAP binds to unique RNA segments containing multiple trinucleotide (NAG) repeats. Binding regulates both transcription termination and translation in the trp operon, and translation of other coding regions relevant to tryptophan metabolism. When there is a deficiency of charged tRNA(Trp), B. subtilis forms an anti-TRAP protein, AT. AT antagonizes TRAP function, thereby increasing expression of all the genes regulated by TRAP. Thus B. subtilis and Escherichia coli respond to identical regulatory signals, tryptophan and uncharged tRNA(Trp), yet they employ different mechanisms in regulating trp gene expression.

Gut hormones and appetite control.

AM Wren — 2007-10-01T04:51:15-00:00

Gastroenterology, Vol. 132, No. 6. (May 2007), pp. 2116-2130.

Many peptides are synthesized and released from the gastrointestinal tract. Although their roles in the regulation of gastrointestinal function have been known for some time, it is now evident that they also physiologically influence eating behavior. Our understanding of how neurohormonal gut-brain signaling regulates energy homeostasis has advanced significantly in recent years. Ghrelin is an orexigenic peptide produced by the stomach, which appears to act as a meal initiator. Satiety signals derived from the intestine and pancreas include peptide YY, pancreatic polypeptide, glucagon-like peptide 1, oxyntomodulin, and cholecystokinin. Recent research suggests that gut hormones can be manipulated to regulate energy balance in humans, and that obese subjects retain sensitivity to the actions of gut hormones. Gut hormone-based therapies may thus provide an effective and well-tolerated treatment for obesity.

Regulation of blood glucose homeostasis during prolonged exercise.

SH Suh — 2007-10-01T04:49:45-00:00

Mol Cells, Vol. 23, No. 3. (30 June 2007), pp. 272-279.

The maintenance of normal blood glucose levels at rest and during exercise is critical. The maintenance of blood glucose homeostasis depends on the coordination and integration of several physiological systems, including the sympathetic nervous system and the endocrine system. During prolonged exercise increased demand for glucose by contracting muscle causes to increase glucose uptake to working skeletal muscle. Increase in glucose uptake by working skeletal muscle during prolonged exercise is due to an increase in the translocation of insulin and contraction sensitive glucose transporter-4 (GLUT4) proteins to the plasma membrane. However, normal blood glucose level can be maintained by the augmentation of glucose production and release through the stimulation of liver glycogen breakdown, and the stimulation of the synthesis of glucose from other substances, and by the mobilization of other fuels that may serve as alternatives. Both feedback and feedforward mechanisms allow glycemia to be controlled during exercise. This review focuses on factors that control blood glucose homeostasis during prolonged exercise.

Synthesis and function of membrane phosphoinositides in budding yeast, Saccharomyces cerevisiae.

T Strahl — 2007-10-01T04:48:11-00:00

Biochim Biophys Acta, Vol. 1771, No. 3. (March 2007), pp. 353-404.

It is now well appreciated that derivatives of phosphatidylinositol (PtdIns) are key regulators of many cellular processes in eukaryotes. Of particular interest are phosphoinositides (mono- and polyphosphorylated adducts to the inositol ring in PtdIns), which are located at the cytoplasmic face of cellular membranes. Phosphoinositides serve both a structural and a signaling role via their recruitment of proteins that contain phosphoinositide-binding domains. Phosphoinositides also have a role as precursors of several types of second messengers for certain intracellular signaling pathways. Realization of the importance of phosphoinositides has brought increased attention to characterization of the enzymes that regulate their synthesis, interconversion, and turnover. Here we review the current state of our knowledge about the properties and regulation of the ATP-dependent lipid kinases responsible for synthesis of phosphoinositides and also the additional temporal and spatial controls exerted by the phosphatases and a phospholipase that act on phosphoinositides in yeast.

Global reconstruction of the human metabolic network based on genomic and bibliomic data.

Natalie Duarte — 2007-02-06T08:41:35-00:00

Proc Natl Acad Sci U S A, Vol. 104, No. 6. (31 January 2007), pp. 1777-1782.

Metabolism is a vital cellular process, and its malfunction is a major contributor to human disease. Metabolic networks are complex and highly interconnected, and thus systems-level computational approaches are required to elucidate and understand metabolic genotype-phenotype relationships. We have manually reconstructed the global human metabolic network based on Build 35 of the genome annotation and a comprehensive evaluation of >50 years of legacy data (i.e., bibliomic data). Herein we describe the reconstruction process and demonstrate how the resulting genome-scale (or global) network can be used (i) for the discovery of missing information, (ii) for the formulation of an in silico model, and (iii) as a structured context for analyzing high-throughput biological data sets. Our comprehensive evaluation of the literature revealed many gaps in the current understanding of human metabolism that require future experimental investigation. Mathematical analysis of network structure elucidated the implications of intracellular compartmentalization and the potential use of correlated reaction sets for alternative drug target identification. Integrated analysis of high-throughput data sets within the context of the reconstruction enabled a global assessment of functional metabolic states. These results highlight some of the applications enabled by the reconstructed human metabolic network. The establishment of this network represents an important step toward genome-scale human systems biology.

Investigating the metabolic capabilities of Mycobacterium tuberculosis H37Rv using the in silico strain iNJ661 and proposing alternative drug targets

Neema Jamshidi — 2007-10-01T04:32:36-00:00

BMC Systems Biology, Vol. 1, No. 1. (2007), 26.

BACKGROUND::Mycobacterium tuberculosis continues to be a major pathogen in the third world, killing almost 2 million people a year by the most recent estimates. Even in industrialized countries, the emergence of multi-drug resistant (MDR) strains of tuberculosis hails the need to develop additional medications for treatment. Many of the drugs used for treatment of tuberculosis target metabolic enzymes. Genome-scale models can be used for analysis, discovery, and as hypothesis generating tools, which will hopefully assist the rational drug development process. These models need to be able to assimilate data from large datasets and analyze them.RESULTS::We completed a bottom up reconstruction of the metabolic network of Mycobacterium tuberculosis H37Rv. This functional in silico bacterium, iNJ661, contains 661 genes and 939 reactions and can produce many of the complex compounds characteristic to tuberculosis, such as mycolic acids and mycocerosates. We grew this bacterium in silico on various media, analyzed the model in the context of multiple high-throughput data sets, and finally we analyzed the network in an 'unbiased' manner by calculating the Hard Coupled Reaction (HCR) sets, groups of reactions that are forced to operate in unison due to mass conservation and connectivity constraints.CONCLUSION::Although we observed growth rates comparable to experimental observations (doubling times ranging from about 12 to 24 hours) in different media, comparisons of gene essentiality with experimental data were less encouraging (generally about 55%). The reasons for the often conflicting results were multi-fold, including gene expression variability under different conditions and lack of complete biological knowledge. Some of the inconsistencies between in vitro and in silico or in vivo and in silico results highlight specific loci that are worth further experimental investigations. Finally, by considering the HCR sets in the context of known drug targets for tuberculosis treatment we proposed new alternative, but equivalent drug targets.

Genome-scale Reconstruction of Metabolic Network in Bacillus subtilis Based on High-throughput Phenotyping and Gene Essentiality Data.

YK Oh — 2007-10-01T04:32:20-00:00

J Biol Chem, Vol. 282, No. 39. (28 September 2007), pp. 28791-28799.

In this report, a genome-scale reconstruction of Bacillus subtilis metabolism and its iterative development based on the combination of genomic, biochemical, and physiological information and high-throughput phenotyping experiments is presented. The initial reconstruction was converted into an in silico model and expanded in a four-step iterative fashion. First, network gap analysis was used to identify 48 missing reactions that are needed for growth but were not found in the genome annotation. Second, the computed growth rates under aerobic conditions were compared with high-throughput phenotypic screen data, and the initial in silico model could predict the outcomes qualitatively in 140 of 271 cases considered. Detailed analysis of the incorrect predictions resulted in the addition of 75 reactions to the initial reconstruction, and 200 of 271 cases were correctly computed. Third, in silico computations of the growth phenotypes of knock-out strains were found to be consistent with experimental observations in 720 of 766 cases evaluated. Fourth, the integrated analysis of the large-scale substrate utilization and gene essentiality data with the genome-scale metabolic model revealed the requirement of 80 specific enzymes (transport, 53; intracellular reactions, 27) that were not in the genome annotation. Subsequent sequence analysis resulted in the identification of genes that could be putatively assigned to 13 intracellular enzymes. The final reconstruction accounted for 844 open reading frames and consisted of 1020 metabolic reactions and 988 metabolites. Hence, the in silico model can be used to obtain experimentally verifiable hypothesis on the metabolic functions of various genes.

Control theory of regulatory cascades.

D Kahn — 2007-09-14T02:20:13-00:00

J Theor Biol, Vol. 153, No. 2. (21 November 1991), pp. 255-285.

We have extended Metabolic Control Theory to include cascades consisting of several modules controlling each other solely via regulatory effects. We derive several theorems that determine how the control properties of a cascade derive from (1) the control properties of each module, taken in isolation and (2) the regulatory interactions between the modules. Two cases are treated explicitly. The first concerns cascades in the absence of feed-back: in this case the internal control behaviour of each module is unaffected by external regulatory interactions. The second includes one feed-back loop and gives a quantitative expression of how feed-back modifies control properties: the internal control matrix within one module can be calculated as if the elasticity matrix of this module was the sum of its intrinsic elasticity matrix and a cyclic regulation matrix. More complex cascades can be analysed recursively by subdividing them into simpler modules, which can be treated individually. The theoretical framework developed here should facilitate quantitative experimental analysis of the control of cell physiology where the latter involves regulatory cascades.

Systems biology. Tracing life's circuitry.

E Pennisi — 2007-04-01T09:23:41-00:00

Science, Vol. 302, No. 5651. (5 December 2003), pp. 1646-1649.

Bow ties, metabolism and disease

Marie Csete — 2006-03-07T11:05:08-00:00

Trends in Biotechnology, Vol. 22, No. 9. (September 2004), pp. 446-450.

Highly organized, universal structures underlying biological and technological networks mediate effective trade-offs among efficiency, robustness and evolvability, with predictable fragilities that can be used to understand disease pathogenesis. The aims of this article are to describe the features of one common organizational architecture in biology, the bow tie. Large-scale organizational frameworks such as the bow tie are necessary starting points for higher-resolution modeling of complex biologic processes

An excitable gene regulatory circuit induces transient cellular differentiation

Gã¼rol Sã¼el — 2006-03-23T02:32:55-00:00

Nature, Vol. 440, No. 7083., pp. 545-550.

A synthetic gene–metabolic oscillator

Eileen Fung — 2005-05-05T02:38:45-00:00

Nature, Vol. 435, No. 7038., pp. 118-122.

Modular approaches to expanding the functions of living matter

Jason Chin — 2007-08-23T06:09:24-00:00

Nat Chem Biol, Vol. 2, No. 6. (June 2006), pp. 304-311.

Integration of metabolome data with metabolic networks reveals reporter reactions.

T Cakir — 2007-08-15T08:07:53-00:00

Mol Syst Biol, Vol. 2 (2006)

Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from Saccharomyces cerevisiae. The algorithm includes preprocessing of a genome-scale yeast model such that the fraction of measured metabolites within the model is enhanced, and thus it is possible to map significant alterations associated with a perturbation even though a small fraction of the complete metabolome is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through combination of metabolome and transcriptome data.

Uncovering transcriptional regulation of metabolism by using metabolic network topology.

KR Patil — 2007-03-22T12:52:20-00:00

Proc Natl Acad Sci U S A, Vol. 102, No. 8. (22 February 2005), pp. 2685-2689.

Cellular response to genetic and environmental perturbations is often reflected and/or mediated through changes in the metabolism, because the latter plays a key role in providing Gibbs free energy and precursors for biosynthesis. Such metabolic changes are often exerted through transcriptional changes induced by complex regulatory mechanisms coordinating the activity of different metabolic pathways. It is difficult to map such global transcriptional responses by using traditional methods, because many genes in the metabolic network have relatively small changes at their transcription level. We therefore developed an algorithm that is based on hypothesis-driven data analysis to uncover the transcriptional regulatory architecture of metabolic networks. By using information on the metabolic network topology from genome-scale metabolic reconstruction, we show that it is possible to reveal patterns in the metabolic network that follow a common transcriptional response. Thus, the algorithm enables identification of so-called reporter metabolites (metabolites around which the most significant transcriptional changes occur) and a set of connected genes with significant and coordinated response to genetic or environmental perturbations. We find that cells respond to perturbations by changing the expression pattern of several genes involved in the specific part(s) of the metabolism in which a perturbation is introduced. These changes then are propagated through the metabolic network because of the highly connected nature of metabolism.

Global metabolic changes following loss of a feedback loop reveal dynamic steady states of the yeast metabolome.

Peng Lu — 2006-11-09T10:23:57-00:00

Metab Eng, Vol. 9, No. 1. (30 June 2006), pp. 8-20.

Metabolic enzymes control cellular metabolite concentrations dynamically in response to changing environmental and intracellular conditions. Such real-time feedback regulation suggests the global metabolome may sample distinct dynamic steady states, forming "basins of stability" in the energy landscape of possible metabolite concentrations and enzymatic activities. Using metabolite, protein and transcriptional profiling, we characterize three dynamic steady states of the yeast metabolome that form by perturbing synthesis of the universal methyl donor S-adenosylmethionine (AdoMet). Conversion between these states is driven by replacement of serine with glycine+formate in the media, loss of feedback inhibition control by the metabolic enzyme Met13, or both. The latter causes hyperaccumulation of methionine and AdoMet, and dramatic global compensatory changes in the metabolome, including differences in amino acid and sugar metabolism, and possibly in the global nitrogen balance, ultimately leading to a G1/S phase cell cycle delay. Global metabolic changes are not necessarily accompanied by global transcriptional changes, and metabolite-controlled post-transcriptional regulation of metabolic enzymes is clearly evident.

Systems biology, metabolic modelling and metabolomics in drug discovery and development

Douglas Kell — 2006-12-02T19:55:16-00:00

Drug Discovery Today, Vol. 11, No. 23-24. (December 2006), pp. 1085-1092.

Unlike signalling pathways, metabolic networks are subject to strict stoichiometric constraints. Metabolomics amplifies changes in the proteome, and represents more closely the phenotype of an organism. Recent advances enable the production (and computer-readable encoding as SBML) of metabolic network models reconstructed from genome sequences, as well as experimental measurements of much of the metabolome. There is increasing convergence between the number of human metabolites estimated via genomics (~3000) and the number measured experimentally. It is thus both timely, and now possible, to bring these two approaches together as an integrated (if distributed) whole to help understand the genesis of metabolic biomarkers, the progress of disease, and the modes of action, efficacy, off-target effects and toxicity of pharmaceutical drugs.

Current Progress in computational metabolomics.

David S Wishart — 2007-07-15T13:16:44-00:00

Brief Bioinform (11 July 2007)

Being a relatively new addition to the 'omics' field, metabolomics is still evolving its own computational infrastructure and assessing its own computational needs. Due to its strong emphasis on chemical information and because of the importance of linking that chemical data to biological consequences, metabolomics must combine elements of traditional bioinformatics with traditional cheminformatics. This is a significant challenge as these two fields have evolved quite separately and require very different computational tools and skill sets. This review is intended to familiarize readers with the field of metabolomics and to outline the needs, the challenges and the recent progress being made in four areas of computational metabolomics: (i) metabolomics databases; (ii) metabolomics LIMS; (iii) spectral analysis tools for metabolomics and (iv) metabolic modeling.

Underground metabolism

Richard D'Ari — 2007-08-06T05:19:51-00:00

BioEssays, Vol. 20, No. 2. (1998), pp. 181-186.

All enzymes are able to use alternative substrates. When these are naturally occurring metabolites, an ?underground reaction? takes place. Examples are presented in which underground metabolism of this sort produces an observable phenotype. Although biological processes can be remakably accurate, evolution has selected error rates far from perfect. It is suggested here that a certain level of metabolic inaccuracy, in addition to saving energy, may also confer an evolutionary advantage, for example by providing metabolic plasticity. Since underground reactions are unpredictable from DNA sequence data, caution is in order when interpreting correlations between genetic disorders and pathological syndromes. BioEssays 20:181-186, 1998. © 1998 John Wiley & Sons, Inc.

A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information

Adam Feist — 2007-07-31T06:08:30-00:00

Mol Syst Biol, Vol. 3 (26 June 2007), 121.

Intergenic transcription is required to repress the Saccharomyces cerevisiae SER3 gene.

JA Martens — 2007-07-30T08:12:46-00:00

Nature, Vol. 429, No. 6991. (3 June 2004), pp. 571-574.

Transcription by RNA polymerase II in Saccharomyces cerevisiae and in humans is widespread, even in genomic regions that do not encode proteins. The purpose of such intergenic transcription is largely unknown, although it can be regulatory. We have discovered a role for one case of intergenic transcription by studying the S. cerevisiae SER3 gene. Our previous results demonstrated that transcription of SER3 is tightly repressed during growth in rich medium. We now show that the regulatory region of this gene is highly transcribed under these conditions and produces a non-protein-coding RNA (SRG1). Expression of the SRG1 RNA is required for repression of SER3. Additional experiments have demonstrated that repression occurs by a transcription-interference mechanism in which SRG1 transcription across the SER3 promoter interferes with the binding of activators. This work identifies a previously unknown class of transcriptional regulatory genes.

Life and reference.

J Hoffmeyer — 2007-07-30T07:58:27-00:00

Biosystems, Vol. 60, No. 1-3. (y 2001), pp. 123-130.

The paper recommends a broadening of Howard Pattee's seminal distinction between a dynamic and a linguistic mode of living systems. It is observed that even the dynamic mode is always a semiotic mode although indexical and analogically coded rather than symbolic and digitally coded. The analogically coded messages corresponds to a kind of tacit knowledge hidden in macromolecular structure and shape (e.g. molecular complementarity) and in organismic architecture and communication, i.e. in the semiotic interactions of the body. It is claimed that the origin of referential processes is tied to the flow of historical singularities. The function of analog and digital codes in evolutionary systems is discussed.

Differential metabolic networks unravel the effects of silent plant phenotypes.

W Weckwerth — 2007-07-30T07:09:08-00:00

Proc Natl Acad Sci U S A, Vol. 101, No. 20. (18 May 2004), pp. 7809-7814.

Current efforts aim to functionally characterize each gene in model plants. Frequently, however, no morphological or biochemical phenotype can be ascribed for antisense or knock-out plant genotypes. This is especially the case when gene suppression or knockout is targeted to isoenzymes or gene families. Consequently, pleiotropic effects and gene redundancy are responsible for phenotype resistance. Here, techniques are presented to detect unexpected pleiotropic changes in such instances despite very subtle changes in overall metabolism. The method consists of the relative quantitation of >1,000 compounds by GC/time-of-flight MS, followed by classical statistics and multivariate clustering. Complementary to these tools, metabolic networks are constructed from pair-wise analysis of linear metabolic correlations. The topology of such networks reflects the underlying regulatory pathway structure. A differential analysis of network connectivity was applied for a silent potato plant line suppressed in expression of sucrose synthase isoform II. Metabolic alterations could be assigned to carbohydrate and amino acid metabolism even if no difference in average metabolite levels was found.

High-throughput metabolic state analysis: the missing link in integrated functional genomics of yeasts.

SG Villas-Bôas — 2007-07-30T07:07:36-00:00

Biochem J, Vol. 388, No. Pt 2. (1 June 2005), pp. 669-677.

The lack of comparable metabolic state assays severely limits understanding the metabolic changes caused by genetic or environmental perturbations. The present study reports the application of a novel derivatization method for metabolome analysis of yeast, coupled to data-mining software that achieve comparable throughput, effort and cost compared with DNA arrays. Our sample workup method enables simultaneous metabolite measurements throughout central carbon metabolism and amino acid biosynthesis, using a standard GC-MS platform that was optimized for this purpose. As an implementation proof-of-concept, we assayed metabolite levels in two yeast strains and two different environmental conditions in the context of metabolic pathway reconstruction. We demonstrate that these differential metabolite level data distinguish among sample types, such as typical metabolic fingerprinting or footprinting. More importantly, we demonstrate that this differential metabolite level data provides insight into specific metabolic pathways and lays the groundwork for integrated transcription-metabolism studies of yeasts.

Protein interactions from complexes: a structural perspective.

L Hakes — 2007-07-30T06:32:44-00:00

Comp Funct Genomics (2007)

By combining crystallographic information with protein-interaction data obtained through traditional experimental means, this paper determines the most appropriate method for generating protein-interaction networks that incorporate data derived from protein complexes. We propose that a combined method should be considered; in which complexes composed of five chains or less are decomposed using the matrix model, whereas the spoke model is used to derive pairwise interactions for those with six chains or more. The results presented here should improve the accuracy and relevance of studies investigating the topology of protein-interaction networks.

Repression of the human dihydrofolate reductase gene by a non-coding interfering transcript

Igor Martianov — 2007-01-22T15:44:55-00:00

Nature (21 January 2007)

From genomes to in silico cells via metabolic networks.

I Borodina — 2007-07-30T05:47:23-00:00

Curr Opin Biotechnol, Vol. 16, No. 3. (June 2005), pp. 350-355.

Genome-scale metabolic models are the focal point of systems biology as they allow the collection of various data types in a form suitable for mathematical analysis. High-quality metabolic networks and metabolic networks with incorporated regulation have been successfully used for the analysis of phenotypes from phenotypic arrays and in gene-deletion studies. They have also been used for gene expression analysis guided by metabolic network structure, leading to the identification of commonly regulated genes. Thus, genome-scale metabolic modeling currently stands out as one of the most promising approaches to obtain an in silico prediction of cellular function based on the interaction of all of the cellular components.

A high-resolution map of transcription in the yeast genome

Lior David — 2006-06-14T09:34:50-00:00

PNAS, Vol. 103, No. 14. (4 April 2006), pp. 5320-5325.

There is abundant transcription from eukaryotic genomes unaccounted for by protein coding genes. A high-resolution genome-wide survey of transcription in a well annotated genome will help relate transcriptional complexity to function. By quantifying RNA expression on both strands of the complete genome of Saccharomyces cerevisiae using a high-density oligonucleotide tiling array, this study identifies the boundary, structure, and level of coding and noncoding transcripts. A total of 85% of the genome is expressed in rich media. Apart from expected transcripts, we found operon-like transcripts, transcripts from neighboring genes not separated by intergenic regions, and genes with complex transcriptional architecture where different parts of the same gene are expressed at different levels. We mapped the positions of 3' and 5' UTRs of coding genes and identified hundreds of RNA transcripts distinct from annotated genes. These nonannotated transcripts, on average, have lower sequence conservation and lower rates of deletion phenotype than protein coding genes. Many other transcripts overlap known genes in antisense orientation, and for these pairs global correlations were discovered: UTR lengths correlated with gene function, localization, and requirements for regulation; antisense transcripts overlapped 3' UTRs more than 5' UTRs; UTRs with overlapping antisense tended to be longer; and the presence of antisense associated with gene function. These findings may suggest a regulatory role of antisense transcription in S. cerevisiae. Moreover, the data show that even this well studied genome has transcriptional complexity far beyond current annotation. 10.1073/pnas.0601091103

Global identification of noncoding RNAs in Saccharomyces cerevisiae by modulating an essential RNA processing pathway.

MP Samanta — 2006-12-28T20:05:00-00:00

Proc Natl Acad Sci U S A, Vol. 103, No. 11. (14 March 2006), pp. 4192-4197.

Noncoding RNAs (ncRNAs) perform essential cellular tasks and play key regulatory roles in all organisms. Although several new ncRNAs in yeast were recently discovered by individual studies, to our knowledge no comprehensive empirical search has been conducted. We demonstrate a powerful and versatile method for global identification of previously undescribed ncRNAs by modulating an essential RNA processing pathway through the depletion of a key ribonucleoprotein enzyme component, and monitoring differential transcriptional activities with genome tiling arrays during the time course of the ribonucleoprotein depletion. The entire Saccharomyces cerevisiae genome was scanned during cell growth decay regulated by promoter-mediated depletion of Rpp1, an essential and functionally conserved protein component of the RNase P enzyme. In addition to most verified genes and ncRNAs, expression was detected in 98 antisense and intergenic regions, 74 that were further confirmed to contain previously undescribed RNAs. A class of ncRNAs, located antisense to coding regions of verified protein-coding genes, is discussed in this article. One member, HRA1, is likely involved in 18S rRNA maturation.

Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change.

Andrew Uzilov — 2006-05-17T18:28:39-00:00

BMC Bioinformatics, Vol. 7, No. 1. (27 March 2006)

ABSTRACT: BACKGROUND: Non-coding RNAs (ncRNAs) have a multitude of roles in the cell, many of which remain to be discovered. However, it is difficult to detect novel ncRNAs in biochemical screens. To advance biological knowledge, computational methods that can accurately detect ncRNAs in sequenced genomes are therefore desirable. The increasing number of genomic sequences provides a rich dataset for computational comparative sequence analysis and detection of novel ncRNAs. RESULTS: Here, Dynalign, a program for predicting secondary structures common to two RNA sequences on the basis of minimizing folding free energy change, is utilized as a computational ncRNA detection tool. The Dynalign-computed optimal total free energy change, which scores the structural alignment and the free energy change of folding into a common structure for two RNA sequences, is shown to be an effective measure for distinguishing ncRNA from randomized sequences. To make the classification as a ncRNA, the total free energy change of an input sequence pair can either be compared with the total free energy changes of a set of control sequence pairs, or be used in combination with sequence length and nucleotide frequencies as input to a classification support vector machine. The latter method is much faster, but slightly less sensitive at a given specificity. Additionally, the classification support vector machine method is shown to be sensitive and specific on genomic ncRNA screens of two different Escherichia coli and Salmonella typhi genome alignments, in which many ncRNAs are known. The Dynalign computational experiments are also compared with two other ncRNA detection programs, RNAz and QRNA. CONCLUSIONS: The Dynalign-based support vector machine method is more sensitive for known ncRNAs in the test genomic screens than RNAz and QRNA. Additionally, both Dynalign-based methods are more sensitive than RNAz and QRNA at low sequence pair identities. Dynalign can be used as a comparable or more accurate tool than RNAz or QRNA in genomic screens, especially for low-identity regions. Dynalign provides a method for discovering ncRNAs in sequenced genomes that other methods may not identify. Significant improvements in Dynalign runtime have also been achieved.

Comparative Analysis of Structured RNAs in S. cerevisiae Indicates a Multitude of Different Functions

Stephan Steigele — 2007-06-20T05:12:27-00:00

BMC Biology, Vol. 5 (18 June 2007), 25.

The expanding universe of noncoding RNAs.

GJ Hannon — 2007-06-24T17:53:40-00:00

Cold Spring Harb Symp Quant Biol, Vol. 71 (2006), pp. 551-564.

The 71st Cold Spring Harbor Symposium on Quantitative Biology celebrated the numerous and expanding roles of regulatory RNAs in systems ranging from bacteria to mammals. It was clearly evident that noncoding RNAs are undergoing a renaissance, with reports of their involvement in nearly every cellular process. Previously known classes of longer noncoding RNAs were shown to function by every possible means-acting catalytically, sensing physiological states through adoption of complex secondary and tertiary structures, or using their primary sequences for recognition of target sites. The many recently discovered classes of small noncoding RNAs, generally less than 35 nucleotides in length, most often exert their effects by guiding regulatory complexes to targets via base-pairing. With the ability to analyze the RNA products of the genome in ever greater depth, it has become clear that the universe of noncoding RNAs may extend far beyond the boundaries we had previously imagined. Thus, as much as the Symposium highlighted exciting progress in the field, it also revealed how much farther we must go to understand fully the biological impact of noncoding RNAs.

RNA Maps Reveal New RNA Classes and a Possible Function for Pervasive Transcription

Philipp Kapranov — 2007-05-27T00:42:53-00:00

Science (17 May 2007), 1138341.

Significant fractions of eukaryotic genomes give rise to RNA, much of which is unannotated and has reduced protein-coding potential. The genomic origins and the relations of human nuclear and cytosolic polyadenylated RNAs longer than 200 nucleotides and whole-cell RNAs less than 200 nt are investigated in this genome-wide study. Subcellular addresses for nucleotides present in detected RNAs were assigned, and their potential processing into short RNAs was investigated. Taken together, these observations suggest a role for some unannotated RNAs as primary transcripts for the production of short RNAs. Three novel potentially functional classes of RNAs have been identified, two of which are syntenically conserved and correlate with the expression state of protein-coding genes. These data support a highly interleaved organization of the human transcriptome. 10.1126/science.1138341

Noncoding RNAs and Gene Silencing

Mikel Zaratiegui — 2007-02-26T14:14:30-00:00

Cell, Vol. 128, No. 4. (23 February 2007), pp. 763-776.

Noncoding RNA has long been proposed to control gene expression via sequence-specific interactions with regulatory regions. Here, we review the role of noncoding RNA in heterochromatic silencing and in the silencing of transposable elements (TEs), unpaired DNA in meiosis, and developmentally excised DNA. The role of cotranscriptional processing by RNA interference and by other mechanisms is discussed, as well as parallels with RNA silencing in imprinting, paramutation, polycomb silencing, and X inactivation. Interactions with regulatory sequences may well occur, but at the RNA rather than at the DNA level.

A noncoding RNA in Saccharomyces cerevisiae is an RNase P substrate.

L Yang — 2007-07-26T10:35:21-00:00

RNA, Vol. 13, No. 5. (May 2007), pp. 682-690.

Ribonuclease P (RNase P) is involved in regulation of noncoding RNA (ncRNA) expression in Saccharomyces cerevisiae. A hidden-in-reading-frame antisense-1 (HRA1) RNA in S. cerevisiae, which belongs to a class of ncRNAs located in the antisense strand to verified protein coding regions, was cloned for further use in RNase P assays. Escherichia coli RNase P assays in vitro of HRA1 RNA show two cleavage sites, one major and one minor in terms of rates. The same result was observed with a partially purified S. cerevisiae RNase P activity, both at 30 degrees C and 37 degrees C. These latter cells are normally grown at 30 degrees C. Predictions of the secondary structure of HRA1 RNA in silico show the cleavage sites are canonical RNase P recognition sites. A relatively small amount of endogenous HRA1 RNA was identified by RT-PCR in yeast cells. The endogenous HRA1 RNA is increased in amount in strains that are deficient in RNase P activity. A deletion of 10 nucleotides in the HRA1 gene that does not overlap with the gene coding for a protein (DRS2) in the sense strand shows no defective growth in galactose or glucose. These data indicate that HRA1 RNA is a substrate for RNase P and does not appear as a direct consequence of separate regulatory effects of the enzyme on ncRNAs.

Functionality or transcriptional noise? Evidence for selection within long noncoding RNAs

Jasmina Ponjavic — 2007-05-03T18:31:48-00:00

Genome Res., Vol. 17, No. 5. (1 May 2007), pp. 556-565.

Long transcripts that do not encode protein have only rarely been the subject of experimental scrutiny. Presumably, this is owing to the current lack of evidence of their functionality, thereby leaving an impression that, instead, they represent "transcriptional noise." Here, we describe an analysis of 3122 long and full-length, noncoding RNAs ("macroRNAs") from the mouse, and compare their sequences and their promoters with orthologous sequence from human and from rat. We considered three independent signatures of purifying selection related to substitutions, sequence insertions and deletions, and splicing. We find that the evolution of the set of noncoding RNAs is not consistent with neutralist explanations. Rather, our results indicate that purifying selection has acted on the macroRNAs' promoters, primary sequence, and consensus splice site motifs. Promoters have experienced the greatest elimination of nucleotide substitutions, insertions, and deletions. The proportion of conserved sequence (4.1%-5.5%) in these macroRNAs is comparable to the density of exons within protein-coding transcripts (5.2%). These macroRNAs, taken together, thus possess the imprint of purifying selection, thereby indicating their functionality. Our findings should now provide an incentive for the experimental investigation of these macroRNAs' functions. 10.1101/gr.6036807

Genomics: The amazing complexity of the human transcriptome

Martin Frith — 2005-06-22T12:32:35-00:00

European Journal of Human Genetics, Vol. aop, No. current.

Accelerating, hyperaccelerating, and decelerating networks.

MJ Gagen — 2007-07-30T04:36:20-00:00

Phys Rev E Stat Nonlin Soft Matter Phys, Vol. 72, No. 1 Pt 2. (July 2005)

Many growing networks possess accelerating statistics where the number of links added with each new node is an increasing function of network size so the total number of links increases faster than linearly with network size. In particular, biological networks can display a quadratic growth in regulator number with genome size even while remaining sparsely connected. These features are mutually incompatible in standard treatments of network theory which typically require that every new network node possesses at least one connection. To model sparsely connected networks, we generalize existing approaches and add each new node with a probabilistic number of links to generate either accelerating, hyperaccelerating, or even decelerating network statistics in different regimes. Under preferential attachment for example, slowly accelerating networks display stationary scale-free statistics relatively independent of network size while more rapidly accelerating networks display a transition from scale-free to exponential statistics with network growth. Such transitions explain, for instance, the evolutionary record of single-celled organisms which display strict size and complexity limits.

The Functional Genomics of Noncoding RNA

John Mattick — 2005-10-11T22:00:15-00:00

Science, Vol. 309, No. 5740. (02 September 2005), pp. 1527-1528.

Large numbers of noncoding RNA transcripts (ncRNAs) are being revealed by complementary DNA cloning and genome tiling array studies in animals. The big and as yet largely unanswered question is whether these transcripts are relevant. A paper by Willingham et al. shows the way forward by developing a strategy for large-scale functional screening of ncRNAs, involving small interfering RNA knockdowns in cell-based screens, which identified a previously unidentified ncRNA repressor of the transcription factor NFAT. It appears likely that ncRNAs constitute a critical hidden layer of gene regulation in complex organisms, the understanding of which requires new approaches in functional genomics.

Rapid evolution of noncoding RNAs: lack of conservation does not mean lack of function

Ken Pang — 2006-01-16T17:45:39-00:00

Trends in Genetics, Vol. 22, No. 1. (January 2006), pp. 1-5.

The mammalian transcriptome contains many non-protein-coding RNAs (ncRNAs), but most of these are of unclear significance and lack strong sequence conservation, prompting suggestions that they might be non-functional. However, certain long functional ncRNAs such as Air and Xist are also poorly conserved. In this article, we systematically analyzed the conservation of several groups of functional ncRNAs, including miRNAs, snoRNAs and longer ncRNAs whose function has been either documented or confidently predicted. As expected, miRNAs and snoRNAs were highly conserved. By contrast, the longer functional non-micro, non-sno ncRNAs were much less conserved with many displaying rapid sequence evolution. Our findings suggest that longer ncRNAs are under the influence of different evolutionary constraints and that the lack of conservation displayed by the thousands of candidate ncRNAs does not necessarily signify an absence of function.

Experimental validation of the regulated expression of large numbers of non-coding RNAs from the mouse genome.

T Ravasi — 2006-03-13T07:21:07-00:00

Genome Res, Vol. 16, No. 1. (January 2006), pp. 11-19.

Recent large-scale analyses of mainly full-length cDNA libraries generated from a variety of mouse tissues indicated that almost half of all representative cloned sequences did not contain an apparent protein-coding sequence, and were putatively derived from non-protein-coding RNA (ncRNA) genes. However, many of these clones were singletons and the majority were unspliced, raising the possibility that they may be derived from genomic DNA or unprocessed pre-mRNA contamination during library construction, or alternatively represent nonspecific "transcriptional noise." Here we show, using reverse transcriptase-dependent PCR, microarray, and Northern blot analyses, that many of these clones were derived from genuine transcripts of unknown function whose expression appears to be regulated. The ncRNA transcripts have larger exons and fewer introns than protein-coding transcripts. Analysis of the genomic landscape around these sequences indicates that some cDNA clones were produced not from terminal poly(A) tracts but internal priming sites within longer transcripts, only a minority of which is encompassed by known genes. A significant proportion of these transcripts exhibit tissue-specific expression patterns, as well as dynamic changes in their expression in macrophages following lipopolysaccharide stimulation. Taken together, the data provide strong support for the conclusion that ncRNAs are an important, regulated component of the mammalian transcriptome.

RNA: Networks & Imaging.

M Kenzelmann — 2007-07-30T04:34:01-00:00

Mol Syst Biol, Vol. 2 (2006)

The past few years have brought about a fundamental change in our understanding and definition of the RNA world and its role in the functional and regulatory architecture of the cell. The discovery of small RNAs that regulate many aspects of differentiation and development have joined the already known non-coding RNAs that are involved in chromosome dosage compensation, imprinting, and other functions to become key players in regulating the flow of genetic information. It is also evident that there are tens or even hundreds of thousands of other non-coding RNAs that are transcribed from the mammalian genome, as well as many other yet-to-be-discovered small regulatory RNAs. In the recent symposium RNA: Networks & Imaging held in Heidelberg, the dual roles of RNA as a messenger and a regulator in the flow of genetic information were discussed and new molecular genetic and imaging methods to study RNA presented.

RNAdb 2.0--an expanded database of mammalian non-coding RNAs.

Ken C Pang — 2006-12-06T10:51:31-00:00

Nucleic Acids Res (1 December 2006)

RNAdb is a comprehensive database of mammalian non-protein-coding RNAs (ncRNAs). There is increasing recognition that ncRNAs play important regulatory roles in multicellular organisms, and there is an expanding rate of discovery of novel ncRNAs as well as an increasing allocation of function. In this update to RNAdb, we provide nucleotide sequences and annotations for tens of thousands of non-housekeeping ncRNAs, including a wide range of mammalian microRNAs, small nucleolar RNAs and larger mRNA-like ncRNAs. Some of these have documented functions and/or expression patterns, but the majority remain of unclear significance, and include PIWI-interacting RNAs, ncRNAs identified from the latest rounds of large-scale cDNA sequencing projects, putative antisense transcripts, as well as ncRNAs predicted on the basis of structural features and alignments. Improvements to the database comprise not only new and updated ncRNA datasets, but also provision of microarray-based expression data and closer interface with more specialized ncRNA resources such as miRBase and snoRNA-LBME-db. To access RNAdb, visit http://research.imb.uq.edu.au/RNAdb.

The relationship between non-protein-coding DNA and eukaryotic complexity

Ryan Taft — 2007-02-13T10:47:54-00:00

BioEssays, Vol. 29, No. 3. (2007), pp. 288-299.

There are two intriguing paradoxes in molecular biology - the inconsistent relationship between organismal complexity and (1) cellular DNA content and (2) the number of protein-coding genes - referred to as the C-value and G-value paradoxes, respectively. The C-value paradox may be largely explained by varying ploidy. The G-value paradox is more problematic, as the extent of protein coding sequence remains relatively static over a wide range of developmental complexity. We show by analysis of sequenced genomes that the relative amount of non-protein-coding sequence increases consistently with complexity. We also show that the distribution of introns in complex organisms is non-random. Genes composed of large amounts of intronic sequence are significantly overrepresented amongst genes that are highly expressed in the nervous system, and amongst genes downregulated in embryonic stem cells and cancers. We suggest that the informational paradox in complex organisms may be explained by the expansion of cis-acting regulatory elements and genes specifying trans-acting non-protein-coding RNAs. BioEssays 29: 288-299, 2007. © 2007 Wiley Periodicals, Inc.

A new paradigm for developmental biology.

JS Mattick — 2007-07-30T04:31:30-00:00

J Exp Biol, Vol. 210, No. Pt 9. (May 2007), pp. 1526-1547.

It is usually thought that the development of complex organisms is controlled by protein regulatory factors and morphogenetic signals exchanged between cells and differentiating tissues during ontogeny. However, it is now evident that the majority of all animal genomes is transcribed, apparently in a developmentally regulated manner, suggesting that these genomes largely encode RNA machines and that there may be a vast hidden layer of RNA regulatory transactions in the background. I propose that the epigenetic trajectories of differentiation and development are primarily programmed by feed-forward RNA regulatory networks and that most of the information required for multicellular development is embedded in these networks, with cell-cell signalling required to provide important positional information and to correct stochastic errors in the endogenous RNA-directed program.