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Prediction of co-regulated genes in
Background Identification of co-regulated genes is essential for elucidating transcriptional regulatory networks and the function of uncharacterized genes. Although co-regulated genes should have at least one common sequence element, it is generally difficult to identify these genes from the presence of this element because it is very easily obscured by noise. To overcome this problem, we used conserved information from three closely related species: Bacillus subtilis, B. halodurans and B. stearothermophilus. Results Even though such species have a limited number of clearly orthologous genes, we obtained 1,884 phylogenetically conserved elements from the upstream intergenic regions of 1,568 B. subtilis genes. Similarity between these elements was used to cluster these genes. No other a priori knowledge on genes and elements was used. We could identify some genes known or suggested to be regulated by a common transcription factor as well as genes regulated by a common attenuation effector. Conclusions We confirmed that our method generates relatively few false positives in clusters with higher scores and that general elements such as -35/-10 boxes and Shine-Dalgarno sequence are not major obstacles. Moreover, we identified some plausible additional members of groups of known co-regulated genes. Thus, our approach is promising for exploring potentially co-regulated genes.
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Evidence for large domains of similarly expressed genes in the
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Background Transcriptional regulation in eukaryotes generally operates at the level of individual genes. Regulation of sets of adjacent genes by mechanisms operating at the level of chromosomal domains has been demonstrated in a number of cases, but the fraction of genes in the genome subject to regulation at this level is unknown. Results Drosophila gene-expression profiles that were determined from over 80 experimental conditions using high-density oligonucleotide microarrays were searched for groups of adjacent genes that show similar expression profiles. We found about 200 groups of adjacent and similarly expressed genes, each having between 10 and 30 members; together these groups account for over 20% of assayed genes. Each group covers between 20 and 200 kilobase pairs of genomic sequence, with a mean group size of about 100 kilobase pairs. Groups do not appear to show any correlation with polytene banding patterns or other known chromosomal structures, nor were genes within groups functionally related to one another. Conclusions Groups of adjacent and co-regulated genes that are not otherwise functionally related in any obvious way can be identified by expression profiling in Drosophila. The mechanism underlying this phenomenon is not yet known.
Evaluation of thresholds for the detection of binding sites for regulatory proteins in
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Background Sites in DNA that bind regulatory proteins can be detected computationally in various ways. Pattern discovery methods analyze collections of genes suspected to be co-regulated on the evidence, for example, of clustering of transcriptome data. Pattern searching methods use sequences with known binding sites to find other genes regulated by a given protein. Such computational methods are important strategies in the discovery and elaboration of regulatory networks and can provide the experimental biologist with a precise prediction of a binding site or identify a gene as a member of a set of co-regulated genes (a regulon). As more variations on such methods are published, however, thorough evaluation is necessary, as performance may differ depending on the conditions of use. Detailed evaluation also helps to improve and understand the behavior of the different methods and computational strategies. Results We used a collection of 86 regulons from Escherichia coli as datasets to evaluate two methods for pattern discovery and pattern searching: dyad analysis/dyad sweeping using the program Dyad-analysis, and multiple alignment using the programs Consensus/Patser. Clearly defined statistical parameters are used to evaluate the two methods in different situations. We placed particular emphasis on minimizing the rate of false positives. Conclusions As a general rule, sensors obtained from experimentally reported binding sites in DNA frequently locate true sites as the highest-scoring sequences within a given upstream region, especially using Consensus/Patser. Pattern discovery is still an unsolved problem, although in the cases where Dyad-analysis finds significant dyads (around 50%), these frequently correspond to true binding sites. With more robust methods, regulatory predictions could help identify the function of unknown genes.
Computational prediction of membrane-tethered transcription factors
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Background Sequestration of transcription factors in the membrane is emerging as an important mechanism for the regulation of gene expression. A handful of membrane-spanning transcription factors has been previously identified whose access to the nucleus is regulated by proteolytic cleavage from the membrane. To investigate the existence of other transmembrane transcription factors, we analyzed computationally all proteins in SWISS-PROT/TrEMBL for the combined presence of a DNA-binding domain and a transmembrane segment. Results Using Pfam hidden Markov models and four transmembrane-prediction programs, we identified with high confidence 76 membrane-spanning transcription factors in SWISS-PROT/TrEMBL. Analysis of the distribution of two proteins predicted by our method, MTJ1 and DMRT2, confirmed their localization to intracellular membrane compartments. Furthermore, elimination of the predicted transmembrane segment led to nuclear localization for each of these proteins. Conclusions Our analysis uncovered a wealth of predicted membrane-spanning transcription factors that are structurally and taxonomically diverse, 56 of which lack experimental annotation. Seventy-five of the proteins are modular in structure, suggesting that a single proteolysis may be sufficient to liberate a DNA-binding domain from the membrane. This study provides grounds for investigations into the stimuli and mechanisms that release this intriguing class of transcription factors from membranes.
A tandem repeats database for bacterial genomes: application to the genotyping of
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Background Some pathogenic bacteria are genetically very homogeneous, making strain discrimination difficult. In the last few years, tandem repeats have been increasingly recognized as markers of choice for genotyping a number of pathogens. The rapid evolution of these structures appears to contribute to the phenotypic flexibility of pathogens. The availability of whole-genome sequences has opened the way to the systematic evaluation of tandem repeats diversity and application to epidemiological studies. Results This report presents a database () of tandem repeats from publicly available bacterial genomes which facilitates the identification and selection of tandem repeats. We illustrate the use of this database by the characterization of minisatellites from two important human pathogens, Yersinia pestis and Bacillus anthracis. In order to avoid simple sequence contingency loci which may be of limited value as epidemiological markers, and to provide genotyping tools amenable to ordinary agarose gel electrophoresis, only tandem repeats with repeat units at least 9 bp long were evaluated. Yersinia pestis contains 64 such minisatellites in which the unit is repeated at least 7 times. An additional collection of 12 loci with at least 6 units, and a high internal conservation were also evaluated. Forty-nine are polymorphic among five Yersinia strains (twenty-five among three Y. pestis strains). Bacillus anthracis contains 30 comparable structures in which the unit is repeated at least 10 times. Half of these tandem repeats show polymorphism among the strains tested. Conclusions Analysis of the currently available bacterial genome sequences classifies Bacillus anthracis and Yersinia pestis as having an average (approximately 30 per Mb) density of tandem repeat arrays longer than 100 bp when compared to the other bacterial genomes analysed to date. In both cases, testing a fraction of these sequences for polymorphism was sufficient to quickly develop a set of more than fifteen informative markers, some of which show a very high degree of polymorphism. In one instance, the polymorphism information content index reaches 0.82 with allele length covering a wide size range (600-1950 bp), and nine alleles resolved in the small number of independent Bacillus anthracis strains typed here.
Genome-wide Transcription Factor DNA Binding Sites and Gene Regulatory Networks in Clostridium thermocellum
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Clostridium thermocellum is a thermophilic bacterium recognized for its natural ability to effectively deconstruct cellulosic biomass. While there is a large body of studies on the genetic engineering of this bacterium and its physiology to-date, there is limited knowledge in the transcriptional regulation in this organism and thermophilic bacteria in general. The study herein is the first report of a high-throughput application of DNA-affinity purification sequencing (DAP-seq) to transcription factors (TFs) from a thermophile. We applied DAP-seq to >90 TFs in C. thermocellum and detected genome-wide binding sites for 11 of them. We then compiled and aligned DNA binding sequences from these TFs to deduce the primary DNA-binding sequence motifs for each TF. These binding motifs are further validated with electrophoretic mobility shift assay (EMSA) and are used to identify individual TFs’ regulatory targets in C. thermocellum. Our results led to the discovery of novel, uncharacterized TFs as well as homologues of previously studied TFs including RexA-, LexA- and LacI-type TFs. We then used these data to reconstruct gene regulatory networks for the 11 TFs individually, which resulted in a global network encompassing the TFs with some interconnections. As gene regulation governs and constrains how bacteria behave, our findings shed light on the roles of TFs delineated by their regulons, and potentially provides a means to enable rational, advanced genetic engineering of C. thermocellum and other organisms alike towards a desired phenotype.
ISS Bacillus Genomes
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SRA of spore forming Bacillus strains isolated from various areas of the ISS during Microbial tracking investigation
DNA loops and semicatenated DNA junctions
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Background Alternative DNA conformations are of particular interest as potential signals to mark important sites on the genome. The structural variability of CA microsatellites is particularly pronounced; these are repetitive poly(CA) · poly(TG) DNA sequences spread in all eukaryotic genomes as tracts of up to 60 base pairs long. Many in vitro studies have shown that the structure of poly(CA) · poly(TG) can vary markedly from the classical right handed DNA double helix and adopt diverse alternative conformations. Here we have studied the mechanism of formation and the structure of an alternative DNA structure, named Form X, which was observed previously by polyacrylamide gel electrophoresis of DNA fragments containing a tract of the CA microsatellite poly(CA) · poly(TG) but had not yet been characterized. Results Formation of Form X was found to occur upon reassociation of the strands of a DNA fragment containing a tract of poly(CA) · poly(TG), in a process strongly stimulated by the nuclear proteins HMG1 and HMG2. By inserting Form X into DNA minicircles, we show that the DNA strands do not run fully side by side but instead form a DNA knot. When present in a closed DNA molecule, Form X becomes resistant to heating to 100°C and to alkaline pH. Conclusions Our data strongly support a model of Form X consisting in a DNA loop at the base of which the two DNA duplexes cross, with one of the strands of one duplex passing between the strands of the other duplex, and reciprocally, to form a semicatenated DNA junction also called a DNA hemicatenane.
Research Article: Genome Biology
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Background Computational predictions are critical for directing the experimental study of protein functions. Therefore it is paradoxical when an apparently erroneous computational prediction seems to be supported by experiment. Results We analyzed six cases where application of novel or conventional computational methods for protein sequence and structure analysis led to non-trivial predictions that were subsequently supported by direct experiments. We show that, on all six occasions, the original prediction was unjustified, and in at least three cases, an alternative, well-supported computational prediction, incompatible with the original one, could be derived. The most unusual cases involved the identification of an archaeal cysteinyl-tRNA synthetase, a dihydropteroate synthase and a thymidylate synthase, for which experimental verifications of apparently erroneous computational predictions were reported. Using sequence-profile analysis, multiple alignment and secondary-structure prediction, we have identified the unique archaeal 'cysteinyl-tRNA synthetase' as a homolog of extracellular polygalactosaminidases, and the 'dihydropteroate synthase' as a member of the β-lactamase-like superfamily of metal-dependent hydrolases. Conclusions In each of the analyzed cases, the original computational predictions could be refuted and, in some instances, alternative strongly supported predictions were obtained. The nature of the experimental evidence that appears to support these predictions remains an open question. Some of these experiments might signify discovery of extremely unusual forms of the respective enzymes, whereas the results of others could be due to artifacts.
Screening for sequence-specific RNA-BPs by comprehensive UV crosslinking
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Background Specific cis-elements and the associated trans-acting factors have been implicated in the post-transcriptional regulation of gene expression. In the era of genome wide analyses identifying novel trans-acting factors and cis-regulatory elements is a step towards understanding coordinated gene expression. UV-crosslink analysis is a standard method used to identify RNA-binding proteins. Uridine is traditionally used to radiolabel substrate RNAs, however, proteins binding to cis-elments particularly uridine poor will be weakly or not detected. We evaluate here the possibility of using UV-crosslinking with RNA substrates radiolabeled with each of the four ribonucleotides as an approach for screening for novel sequence specific RNA-binding proteins. Results The radiolabeled RNA substrates were derived from the 3'UTRs of the cloned Eg and c-mos Xenopus laevis maternal mRNAs. Specific, but not identical, uv-crosslinking signals were obtained, some of which corresponded to already identified proteins. A signal for a novel 90 kDa protein was observed with the c-mos 3'UTR radiolabeled with both CTP and GTP but not with UTP. The binding site of the 90 kDa RNA-binding protein was localised to a 59-nucleotide portion of the c-mos 3'UTR. Conclusion That the 90 kDa signal was detected with RNAs radiolabeled with CTP or GTP but not UTP illustrates the advantage of radiolabeling all four nucleotides in a UV-crosslink based screen. This method can be used for both long and short RNAs and does not require knowledge of the cis-acting sequence. It should be amenable to high throughput screening for RNA binding proteins.
Metabolic flux balance analysis and the
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Background Genome sequencing and bioinformatics are producing detailed lists of the molecular components contained in many prokaryotic organisms. From this 'parts catalogue' of a microbial cell, in silico representations of integrated metabolic functions can be constructed and analyzed using flux balance analysis (FBA). FBA is particularly well-suited to study metabolic networks based on genomic, biochemical, and strain specific information. Results Herein, we have utilized FBA to interpret and analyze the metabolic capabilities of Escherichia coli. We have computationally mapped the metabolic capabilities of E. coli using FBA and examined the optimal utilization of the E. coli metabolic pathways as a function of environmental variables. We have used an in silico analysis to identify seven gene products of central metabolism (glycolysis, pentose phosphate pathway, TCA cycle, electron transport system) essential for aerobic growth of E. coli on glucose minimal media, and 15 gene products essential for anaerobic growth on glucose minimal media. The in silico tpi-, zwf, and pta- mutant strains were examined in more detail by mapping the capabilities of these in silico isogenic strains. Conclusions We found that computational models of E. coli metabolism based on physicochemical constraints can be used to interpret mutant behavior. These in silica results lead to a further understanding of the complex genotype-phenotype relation. Supplementary information: