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See detailThe FurA regulon in Anabaena sp. PCC 7120: in silico prediction and experimental validation of novel target genes.
Gonzalez, Andres; Espinosa Angarica, Vladimir UL; Sancho, Javier et al

in Nucleic acids research (2014), 42(8), 4833-46

In the filamentous cyanobacterium Anabaena sp. PCC 7120, the ferric uptake regulator FurA functions as a global transcriptional regulator. Despite several analyses have focused on elucidating the FurA ... [more ▼]

In the filamentous cyanobacterium Anabaena sp. PCC 7120, the ferric uptake regulator FurA functions as a global transcriptional regulator. Despite several analyses have focused on elucidating the FurA-regulatory network, the number of target genes described for this essential transcription factor is limited to a handful of examples. In this article, we combine an in silico genome-wide predictive approach with experimental determinations to better define the FurA regulon. Predicted FurA-binding sites were identified upstream of 215 genes belonging to diverse functional categories including iron homeostasis, photosynthesis and respiration, heterocyst differentiation, oxidative stress defence and light-dependent signal transduction mechanisms, among others. The probabilistic model proved to be effective at discerning FurA boxes from non-cognate sequences, while subsequent electrophoretic mobility shift assay experiments confirmed the in vitro specific binding of FurA to at least 20 selected predicted targets. Gene-expression analyses further supported the dual role of FurA as transcriptional modulator that can act both as repressor and as activator. In either role, the in vitro affinity of the protein to its target sequences is strongly dependent on metal co-regulator and reducing conditions, suggesting that FurA couples in vivo iron homeostasis and the response to oxidative stress to major physiological processes in cyanobacteria. [less ▲]

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See detailNAR Molecular Biology Database Collection entry number 0953
Choi, C.; Münch, R.; Klein, J. et al

in Nucleic Acids Research (2014)

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See detailDirect elicitation of template concentration from quantification cycle (Cq) distributions in digital PCR
Mojtahedi, Mitra; Fouquier d'Hérouël, Aymeric UL; Huang, Sui

in Nucleic Acids Research (2014), 42(16), 126

Digital PCR (dPCR) exploits limiting dilution of a template into an array of PCR reactions. From this array the number of reactions that contain at least one (as opposed to zero) initial template is ... [more ▼]

Digital PCR (dPCR) exploits limiting dilution of a template into an array of PCR reactions. From this array the number of reactions that contain at least one (as opposed to zero) initial template is determined, allowing inferring the original template concentration. Here we present a novel protocol to efficiently infer the concentration of a sample and its optimal dilution for dPCR from few targeted qPCR assays. By taking advantage of the real-time amplification feature of qPCR as opposed to relying on endpoint PCR assessment as in standard dPCR prior knowledge of template concentration is not necessary. This eliminates the need for serial dilutions in a separate titration and reduces the number of necessary reactions. We describe the theory underlying our approach and discuss experimental moments that contribute to uncertainty. We present data from a controlled experiment where the initial template concentration is known as proof of principle and apply our method on directly monitoring transcript level change during cell differentiation as well as gauging amplicon numbers in cDNA samples after pre-amplification. [less ▲]

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See detailIntegrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network
Galhardo, Mafalda Sofia UL; Sinkkonen, Lasse UL; Berninger, Philippe et al

in Nucleic Acids Research (2013)

Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied ... [more ▼]

Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied through experimental and computational analysis. Integrating gene regulation data with a human metabolic network prompted the establishment of an open-sourced web portal, IDARE (Integrated Data Nodes of Regulation), for visualizing various gene-related data in context of metabolic pathways. Motivated by increasing availability of deep sequencing studies, we obtained ChIP-seq data from widely studied human umbilical vein endothelial cells. Interestingly, we found that association of metabolic genes with multiple transcription factors (TFs) enriched disease-associated genes. To demonstrate further extensions enabled by examining these networks together, constraintbased modeling was applied to data from human preadipocyte differentiation. In parallel, data on gene expression, genome-wide ChIP-seq profiles for peroxisome proliferator-activated receptor (PPAR) c, CCAAT/enhancer binding protein (CEBP) a, liver X receptor (LXR) and H3K4me3 and microRNA target identification for miR-27a, miR-29a and miR-222 were collected. Disease-relevant key nodes, including mitochondrial glycerol-phosphateacyltransferase (GPAM), were exposed from metabolic pathways predicted to change activity by focusing on association with multiple regulators. In both cell types, our analysis reveals the convergence of microRNAs and TFs within the branched chain amino acid (BCAA) metabolic pathway, possibly providing an explanation for its downregulation in obese and diabetic conditions. [less ▲]

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See detailInterplay of microRNAs, transcription factors and target genes: Linking dynamic expression changes to function
Nazarov, P. V. A; Reinsbach, Susanne UL; Muller, A. A et al

in Nucleic Acids Research (2013), 41(5), 2817-2831

MicroRNAs (miRNAs) are ubiquitously expressed small non-coding RNAs that, in most cases, negatively regulate gene expression at the posttranscriptional level. miRNAs are involved in fine-tuning ... [more ▼]

MicroRNAs (miRNAs) are ubiquitously expressed small non-coding RNAs that, in most cases, negatively regulate gene expression at the posttranscriptional level. miRNAs are involved in fine-tuning fundamental cellular processes such as proliferation, cell death and cell cycle control and are believed to confer robustness to biological responses. Here, we investigated simultaneously the transcriptional changes of miRNA and mRNA expression levels over time after activation of the Janus kinase/Signal transducer and activator of transcription (Jak/STAT) pathway by interferon-c stimulation of melanoma cells. To examine global miRNA and mRNA expression patterns, time-series microarray data were analysed. We observed delayed responses of miRNAs (after 24-48 h) with respect to mRNAs (12-24 h) and identified biological functions involved at each step of the cellular response. Inference of the upstream regulators allowed for identification of transcriptional regulators involved in cellular reactions to interferon-c stimulation. Linking expression profiles of transcriptional regulators and miRNAs with their annotated functions, we demonstrate the dynamic interplay of miRNAs and upstream regulators with biological functions. Finally, our data revealed network motifs in the form of feed-forward loops involving transcriptional regulators, mRNAs and miRNAs. Additional information obtained from integrating time-series mRNA and miRNA data may represent an important step towards understanding the regulatory principles of gene expression. © The Author(s) 2013. [less ▲]

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See detailPredicting missing expression values in gene regulatory networks using a discrete logic modeling optimization guided by network stable states
Crespo, Isaac UL; Krishna, Abhimanyu UL; Le Béchec, Antony UL et al

in Nucleic Acids Research (2013), 41(1), 8

The development of new high-throughput technologies enables us to measure genome-wide transcription levels, protein abundance, metabolite concentration, etc. Nevertheless, these experimental data are ... [more ▼]

The development of new high-throughput technologies enables us to measure genome-wide transcription levels, protein abundance, metabolite concentration, etc. Nevertheless, these experimental data are often noisy and incomplete, which hinders data analysis, modeling and prediction. Here, we propose a method to predict expression values of genes involved in stable cellular phenotypes from the expression values of the remaining genes in a literature-based gene regulatory network. The consistency between predicted and known stable states from experimental data is used to guide an iterative network pruning that contextualizes the network to the biological conditions under which the expression data were obtained. Using the contextualized network and the property of network stability we predict gene expression values missing from experimental data. The prediction method assumes a Boolean model to compute steady states of networks and an evolutionary algorithm to iteratively prune the networks. The evolutionary algorithm samples the probability distribution of positive feedback loops or positive circuits and individual interactions within the subpopulation of the best-pruned networks at each iteration. The resulting expression inference is based not only on previous knowledge about local connectivity but also on a global network property (stability), providing robustness in the predictions. [less ▲]

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See detailA systemic transcriptome analysis reveals the regulation of neural stem cell maintenance by an E2F1-miRNA feedback loop.
Palm, Thomas; Hemmer, Kathrin; Winter, Julia et al

in Nucleic Acids Research (2013), 41(6), 3699-712

Stem cell fate decisions are controlled by a molecular network in which transcription factors and miRNAs are of key importance. To systemically investigate their impact on neural stem cell (NSC ... [more ▼]

Stem cell fate decisions are controlled by a molecular network in which transcription factors and miRNAs are of key importance. To systemically investigate their impact on neural stem cell (NSC) maintenance and neuronal commitment, we performed a high-throughput mRNA and miRNA profiling and isolated functional interaction networks of involved mechanisms. Thereby, we identified an E2F1-miRNA feedback loop as important regulator of NSC fate decisions. Although E2F1 supports NSC proliferation and represses transcription of miRNAs from the miR-17 approximately 92 and miR-106a approximately 363 clusters, these miRNAs are transiently up-regulated at early stages of neuronal differentiation. In these early committed cells, increased miRNAs expression levels directly repress E2F1 mRNA levels and inhibit cellular proliferation. In mice, we demonstrated that these miRNAs are expressed in the neurogenic areas and that E2F1 inhibition represses NSC proliferation. The here presented data suggest a novel interaction mechanism between E2F1 and miR-17 approximately 92 / miR-106a approximately 363 miRNAs in controlling NSC proliferation and neuronal differentiation. [less ▲]

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See detailDataset integration identifies transcriptional regulation of microRNA genes by PPARgamma in differentiating mouse 3T3-L1 adipocytes
John, Elisabeth UL; Wienecke-Baldacchino, Anke UL; Liivrand, Maria UL et al

in Nucleic Acids Research (2012), 40(10), 4446-4460

Peroxisome proliferator-activated receptor gamma (PPARgamma) is a key transcription factor in mammalian adipogenesis. Genome-wide approaches have identified thousands of PPARgamma binding sites in mouse ... [more ▼]

Peroxisome proliferator-activated receptor gamma (PPARgamma) is a key transcription factor in mammalian adipogenesis. Genome-wide approaches have identified thousands of PPARgamma binding sites in mouse adipocytes and PPARgamma upregulates hundreds of protein-coding genes during adipogenesis. However, no microRNA (miRNA) genes have been identified as primary PPARgamma-targets. By integration of four separate datasets of genome-wide PPARgamma binding sites in 3T3-L1 adipocytes we identified 98 miRNA clusters with PPARgamma binding within 50 kb from miRNA transcription start sites. Nineteen mature miRNAs were upregulated >/=2-fold during adipogenesis and for six of these miRNA loci the PPARgamma binding sites were confirmed by at least three datasets. The upregulation of five miRNA genes miR-103-1 (host gene Pank3), miR-148b (Copz1), miR-182/96/183, miR-205 and miR-378 (Ppargc1b) followed that of Pparg. The PPARgamma-dependence of four of these miRNA loci was demonstrated by PPARgamma knock-down and the loci of miR-103-1 (Pank3), miR-205 and miR-378 (Ppargc1b) were also responsive to the PPARgamma ligand rosiglitazone. Finally, chromatin immunoprecipitation analysis validated in silico predicted PPARgamma binding sites at all three loci and H3K27 acetylation was analyzed to confirm the activity of these enhancers. In conclusion, we identified 22 putative PPARgamma target miRNA genes, showed the PPARgamma dependence of four of these genes and demonstrated three as direct PPARgamma target genes in mouse adipogenesis. [less ▲]

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See detailRNASEQR—a streamlined and accurate RNA-seq sequence analysis program
Chen, Leslie Y.; Wei, Kuo-Chen; Huang, Abner C.-Y. et al

in Nucleic Acids Research (2012), 40(6), 42-

Next-generation sequencing (NGS) technologiesbased transcriptomic profiling method often called RNA-seq has been widely used to study global gene expression, alternative exon usage, new exon discovery ... [more ▼]

Next-generation sequencing (NGS) technologiesbased transcriptomic profiling method often called RNA-seq has been widely used to study global gene expression, alternative exon usage, new exon discovery, novel transcriptional isoforms and genomic sequence variations. However, this technique also poses many biological and informatics challenges to extracting meaningful biological information. The RNA-seq data analysis is built on the foundation of high quality initial genome localization and alignment information for RNA-seq sequences. Toward this goal, we have developed RNASEQR to accurately and effectively map millions of RNA-seq sequences. We have systematically compared RNASEQR with four of the most widely used tools using a simulated data set created from the Consensus CDS project and two experimental RNA-seq data sets generated from a human glioblastoma patient. Our results showed that RNASEQR yields more accurate estimates for gene expression, complete gene structures and new transcript isoforms, as well as more accurate detection of single nucleotide variants (SNVs). RNASEQR analyzes raw data from RNA-seq experiments effectively and outputs results in a manner that is compatible with a wide variety of specialized downstream analyses on desktop computers. [less ▲]

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See detailThe non-autonomous retrotransposon SVA is trans-mobilized by the human LINE-1 protein machinery
Raiz, J.; Damert, A.; Chira, S. et al

in Nucleic Acids Research (2012), 40(4), 1666-1683

SINE-VNTR-Alu (SVA) elements are non-autonomous, hominid-specific non-LTR retrotransposons and distinguished by their organization as composite mobile elements. They represent the evolutionarily youngest ... [more ▼]

SINE-VNTR-Alu (SVA) elements are non-autonomous, hominid-specific non-LTR retrotransposons and distinguished by their organization as composite mobile elements. They represent the evolutionarily youngest, currently active family of human non-LTR retrotransposons, and sporadically generate disease-causing insertions. Since preexisting, genomic SVA sequences are characterized by structural hallmarks of Long Interspersed Elements 1 (LINE-1, L1)-mediated retrotransposition, it has been hypothesized for several years that SVA elements are mobilized by the L1 protein machinery in trans. To test this hypothesis, we developed an SVA retrotransposition reporter assay in cell culture using three different human-specific SVA reporter elements. We demonstrate that SVA elements are mobilized in HeLa cells only in the presence of both L1-encoded proteins, ORF1p and ORF2p. SVA trans-mobilization rates exceeded pseudogene formation frequencies by 12-to 300-fold in HeLa-HA cells, indicating that SVA elements represent a preferred substrate for L1 proteins. Acquisition of an AluSp element increased the trans-mobilization frequency of the SVA reporter element by ∼25-fold. Deletion of (CCCTCT)n repeats and Alu-like region of a canonical SVA reporter element caused significant attenuation of the SVA trans-mobilization rate. SVA de novo insertions were predominantly full-length, occurred preferentially in G+C-rich regions, and displayed all features of L1-mediated retrotransposition which are also observed in preexisting genomic SVA insertions. © 2012 The Author(s). [less ▲]

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See detailGenie: literature-based gene prioritization at multi genomic scale.
Fontaine, Jean-Fred; Priller, Florian; Barbosa Da Silva, Adriano UL et al

in Nucleic acids research (2011), 39(Web Server issue), 455-61

Biomedical literature is traditionally used as a way to inform scientists of the relevance of genes in relation to a research topic. However many genes, especially from poorly studied organisms, are not ... [more ▼]

Biomedical literature is traditionally used as a way to inform scientists of the relevance of genes in relation to a research topic. However many genes, especially from poorly studied organisms, are not discussed in the literature. Moreover, a manual and comprehensive summarization of the literature attached to the genes of an organism is in general impossible due to the high number of genes and abstracts involved. We introduce the novel Genie algorithm that overcomes these problems by evaluating the literature attached to all genes in a genome and to their orthologs according to a selected topic. Genie showed high precision (up to 100%) and the best performance in comparison to other algorithms in most of the benchmarks, especially when high sensitivity was required. Moreover, the prioritization of zebrafish genes involved in heart development, using human and mouse orthologs, showed high enrichment in differentially expressed genes from microarray experiments. The Genie web server supports hundreds of species, millions of genes and offers novel functionalities. Common run times below a minute, even when analyzing the human genome with hundreds of thousands of literature records, allows the use of Genie in routine lab work. Availability: http://cbdm.mdc-berlin.de/tools/genie/. [less ▲]

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See detailHierarchical regulation of the NikR-mediated nickel response in Helicobacter pylori.
Muller, Cecile; Bahlawane, Christelle UL; Aubert, Sylvie et al

in Nucleic acids research (2011), 39(17), 7564-75

Nickel is an essential metal for Helicobacter pylori, as it is the co-factor of two enzymes crucial for colonization, urease and hydrogenase. Nickel is taken up by specific transporters and its ... [more ▼]

Nickel is an essential metal for Helicobacter pylori, as it is the co-factor of two enzymes crucial for colonization, urease and hydrogenase. Nickel is taken up by specific transporters and its intracellular homeostasis depends on nickel-binding proteins to avoid toxicity. Nickel trafficking is controlled by the Ni(II)-dependent transcriptional regulator NikR. In contrast to other NikR proteins, NikR from H. pylori is a pleiotropic regulator that depending on the target gene acts as an activator or a repressor. We systematically quantified the in vivo Ni(2+)-NikR response of 11 direct NikR targets that encode functions related to nickel metabolism, four activated and seven repressed genes. Among these, four targets were characterized for the first time (hpn, hpn-like, hydA and hspA) and NikR binding to their promoter regions was demonstrated by electrophoretic mobility shift assays. We found that NikR-dependent repression was generally set up at higher nickel concentrations than activation. Kinetics of the regulation revealed a gradual and temporal NikR-mediated response to nickel where activation of nickel-protection mechanisms takes place before repression of nickel uptake. Our in vivo study demonstrates, for the first time, a chronological hierarchy in the NikR-dependent transcriptional response to nickel that is coherent with the control of nickel homeostasis in H. pylori. [less ▲]

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See detailSequence-structure relationships in RNA loops: establishing the basis for loop homology modeling.
Schudoma, Christian; May, Patrick UL; Nikiforova, Viktoria et al

in Nucleic Acids Research (2010), 38(3), 970-80

The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three ... [more ▼]

The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three-dimensional structures of RNA molecules. A comprehensive loop-structure data set was created and organized into distinct clusters based on structural and sequence similarity. We detected clear evidence of the hallmark of homology present in the sequence-structure relationships in loops. Loops differing by <25% in sequence identity fold into very similar structures. Thus, our results support the application of homology modeling for RNA loop model building. We established a threshold that may guide the sequence divergence-based selection of template structures for RNA loop homology modeling. Of all possible sequences that are, under the assumption of isosteric relationships, theoretically compatible with actual sequences observed in RNA structures, only a small fraction is contained in the Rfam database of RNA sequences and classes implying that the actual RNA loop space may consist of a limited number of unique loop structures and conserved sequences. The loop-structure data sets are made available via an online database, RLooM. RLooM also offers functionalities for the modeling of RNA loop structures in support of RNA engineering and design efforts. [less ▲]

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See detailA series of PDB related databases for everyday needs
Joosten, R.; Beek, T.; Krieger, E. et al

in Nucleic Acids Research (2010), 39(1), 411-419

The Protein Data Bank (PDB) is the world-wide repository of macromolecular structure information. We present a series of databases that run parallel to the PDB. Each database holds one entry, if possible ... [more ▼]

The Protein Data Bank (PDB) is the world-wide repository of macromolecular structure information. We present a series of databases that run parallel to the PDB. Each database holds one entry, if possible, for each PDB entry. DSSP holds the secondary structure of the proteins. PDBREPORT holds reports on the structure quality and lists errors. HSSP holds a multiple sequence alignment for all proteins. The PDBFINDER holds easy to parse summaries of the PDB file content, augmented with essentials from the other systems. PDB_REDO holds re-refined, and often improved, copies of all structures solved by X-ray. WHY_NOT summarizes why certain files could not be produced. All these systems are updated weekly. The data sets can be used for the analysis of properties of protein structures in areas ranging from structural genomics, to cancer biology and protein design. [less ▲]

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See detailEuroPhenome: a repository for high-throughput mouse phenotyping data
Morgan, Hugh; Beck, Tim; Blake, Andrew et al

in Nucleic Acids Research (2010), 38(1), 577-585

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and ... [more ▼]

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated highthroughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress .har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies. [less ▲]

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See detailPTGL: a database for secondary structure-based protein topologies.
May, Patrick UL; Kreuchwig, Annika; Steinke, Thomas et al

in Nucleic Acids Research (2010), 38(Database issue), 326-30

With growing amount of experimental data, the number of known protein structures also increases continuously. Classification of protein structures helps to understand relationships between protein ... [more ▼]

With growing amount of experimental data, the number of known protein structures also increases continuously. Classification of protein structures helps to understand relationships between protein structure and function. The main classification methods based on secondary structures are SCOP, CATH and TOPS, which all classify under different aspects, and therefore can lead to different results. We developed a mathematically unique representation of protein structure topologies at a higher abstraction level providing new aspects of classification and enabling for a fast search through the data. Protein Topology Graph Library (PTGL; http://ptgl.zib.de) aims at providing a database on protein secondary structure topologies, including search facilities, the visualization as intuitive topology diagrams as well as in the 3D structure, and additional information. Secondary structure-based protein topologies are represented uniquely as undirected labeled graphs in four different ways allowing for exploration under different aspects. The linear notations, and the 2D and 3D diagrams of each notation facilitate a deeper understanding of protein topologies. Several search functions for topologies and sub-topologies, BLAST search possibility, and links to SCOP, CATH and PDBsum support individual and large-scale investigation of protein structures. Currently, PTGL comprises topologies of 54,859 protein structures. Main structural patterns for common structural motifs like TIM-barrel or Jelly Roll are pre-implemented, and can easily be searched. [less ▲]

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See detailStructural and mechanistic insights into Helicobacter pylori NikR activation.
Bahlawane, Christelle UL; Dian, C.; Muller, Christian UL et al

in Nucleic acids research (2010), 38(9), 3106-18

NikR is a transcriptional metalloregulator central in the mandatory response to acidity of Helicobacter pylori that controls the expression of numerous genes by binding to specific promoter regions. NikR ... [more ▼]

NikR is a transcriptional metalloregulator central in the mandatory response to acidity of Helicobacter pylori that controls the expression of numerous genes by binding to specific promoter regions. NikR/DNA interactions were proposed to rely on protein activation by Ni(II) binding to high-affinity (HA) and possibly secondary external (X) sites. We describe a biochemical characterization of HpNikR mutants that shows that the HA sites are essential but not sufficient for DNA binding, while the secondary external (X) sites and residues from the HpNikR dimer-dimer interface are important for DNA binding. We show that a second metal is necessary for HpNikR/DNA binding, but only to some promoters. Small-angle X-ray scattering shows that HpNikR adopts a defined conformation in solution, resembling the cis-conformation and suggests that nickel does not trigger large conformational changes in HpNikR. The crystal structures of selected mutants identify the effects of each mutation on HpNikR structure. This study unravels key structural features from which we derive a model for HpNikR activation where: (i) HA sites and an hydrogen bond network are required for DNA binding and (ii) metallation of a unique secondary external site (X) modulates HpNikR DNA binding to low-affinity promoters by disruption of a salt bridge. [less ▲]

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See detailMartini: using literature keywords to compare gene sets.
Soldatos, Theodoros G.; O'Donoghue, Sean I.; Satagopam, Venkata UL et al

in Nucleic acids research (2010), 38(1), 26-38

Life scientists are often interested to compare two gene sets to gain insight into differences between two distinct, but related, phenotypes or conditions. Several tools have been developed for comparing ... [more ▼]

Life scientists are often interested to compare two gene sets to gain insight into differences between two distinct, but related, phenotypes or conditions. Several tools have been developed for comparing gene sets, most of which find Gene Ontology (GO) terms that are significantly over-represented in one gene set. However, such tools often return GO terms that are too generic or too few to be informative. Here, we present Martini, an easy-to-use tool for comparing gene sets. Martini is based, not on GO, but on keywords extracted from Medline abstracts; Martini also supports a much wider range of species than comparable tools. To evaluate Martini we created a benchmark based on the human cell cycle, and we tested several comparable tools (CoPub, FatiGO, Marmite and ProfCom). Martini had the best benchmark performance, delivering a more detailed and accurate description of function. Martini also gave best or equal performance with three other datasets (related to Arabidopsis, melanoma and ovarian cancer), suggesting that Martini represents an advance in the automated comparison of gene sets. In agreement with previous studies, our results further suggest that literature-derived keywords are a richer source of gene-function information than GO annotations. Martini is freely available at http://martini.embl.de. [less ▲]

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See detailJAIL: a structure-based interface library for macromolecules.
Gunther, Stefan; von Eichborn, Joachim; May, Patrick UL et al

in Nucleic Acids Research (2009), 37(Database issue), 338-41

The increasing number of solved macromolecules provides a solid number of 3D interfaces, if all types of molecular contacts are being considered. JAIL annotates three different kinds of macromolecular ... [more ▼]

The increasing number of solved macromolecules provides a solid number of 3D interfaces, if all types of molecular contacts are being considered. JAIL annotates three different kinds of macromolecular interfaces, those between interacting protein domains, interfaces of different protein chains and interfaces between proteins and nucleic acids. This results in a total number of about 184,000 database entries. All the interfaces can easily be identified by a detailed search form or by a hierarchical tree that describes the protein domain architectures classified by the SCOP database. Visual inspection of the interfaces is possible via an interactive protein viewer. Furthermore, large scale analyses are supported by an implemented sequential and by a structural clustering. Similar interfaces as well as non-redundant interfaces can be easily picked out. Additionally, the sequential conservation of binding sites was also included in the database and is retrievable via Jmol. A comprehensive download section allows the composition of representative data sets with user defined parameters. The huge data set in combination with various search options allow a comprehensive view on all interfaces between macromolecules included in the Protein Data Bank (PDB). The download of the data sets supports numerous further investigations in macromolecular recognition. JAIL is publicly available at http://bioinformatics.charite.de/jail. [less ▲]

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See detailIdentification and classification of ncRNA molecules using graph properties.
Childs, Liam; Nikoloski, Zoran; May, Patrick UL et al

in Nucleic Acids Research (2009), 37(9), 66

The study of non-coding RNA genes has received increased attention in recent years fuelled by accumulating evidence that larger portions of genomes than previously acknowledged are transcribed into RNA ... [more ▼]

The study of non-coding RNA genes has received increased attention in recent years fuelled by accumulating evidence that larger portions of genomes than previously acknowledged are transcribed into RNA molecules of mostly unknown function, as well as the discovery of novel non-coding RNA types and functional RNA elements. Here, we demonstrate that specific properties of graphs that represent the predicted RNA secondary structure reflect functional information. We introduce a computational algorithm and an associated web-based tool (GraPPLE) for classifying non-coding RNA molecules as functional and, furthermore, into Rfam families based on their graph properties. Unlike sequence-similarity-based methods and covariance models, GraPPLE is demonstrated to be more robust with regard to increasing sequence divergence, and when combined with existing methods, leads to a significant improvement of prediction accuracy. Furthermore, graph properties identified as most informative are shown to provide an understanding as to what particular structural features render RNA molecules functional. Thus, GraPPLE may offer a valuable computational filtering tool to identify potentially interesting RNA molecules among large candidate datasets. [less ▲]

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