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PePPER: a webserver for prediction of prokaryote promoter elements and regulons
Anne de Jong, Hilco Pietersma, Martijn Cordes, Oscar P Kuipers, Jan Kok
BMC Genomics , 2012, DOI: 10.1186/1471-2164-13-299
Abstract: We here extend the current databases of TFs, TFBSs and regulons with our knowledge on Lactococcus lactis and developed a webserver for prediction, mining and visualization of prokaryote promoter elements and regulons via a novel concept. This new approach includes an all-in-one method of data mining for TFs, TFBSs, promoters, and regulons for any bacterial genome via a user-friendly webserver. We demonstrate the power of this method by mining WalRK regulons in Lactococci and Streptococci and, vice versa, use L. lactis regulon data (CodY) to mine closely related species.The PePPER webserver offers, besides the all-in-one analysis method, a toolbox for mining for regulons, promoters and TFBSs and accommodates a new L. lactis regulon database in addition to already existing regulon data. Identification of putative regulons and full annotation of intergenic regions in any bacterial genome on the basis of existing knowledge on a related organism can now be performed by biologists and it can be done for a wide range of regulons. On the basis of the PePPER output, biologist can design experiments to further verify the existence and extent of the proposed regulons. The PePPER webserver is freely accessible at http://pepper.molgenrug.nl webcite.
Genomic Arrangement of Regulons in Bacterial Genomes  [PDF]
Han Zhang, Yanbin Yin, Victor Olman, Ying Xu
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0029496
Abstract: Regulons, as groups of transcriptionally co-regulated operons, are the basic units of cellular response systems in bacterial cells. While the concept has been long and widely used in bacterial studies since it was first proposed in 1964, very little is known about how its component operons are arranged in a bacterial genome. We present a computational study to elucidate of the organizational principles of regulons in a bacterial genome, based on the experimentally validated regulons of E. coli and B. subtilis. Our results indicate that (1) genomic locations of transcriptional factors (TFs) are under stronger evolutionary constraints than those of the operons they regulate so changing a TF's genomic location will have larger impact to the bacterium than changing the genomic position of any of its target operons; (2) operons of regulons are generally not uniformly distributed in the genome but tend to form a few closely located clusters, which generally consist of genes working in the same metabolic pathways; and (3) the global arrangement of the component operons of all the regulons in a genome tends to minimize a simple scoring function, indicating that the global arrangement of regulons follows simple organizational principles.
Probabilistic Clustering of Sequences: Inferring new bacterial regulons by comparative genomics  [PDF]
Erik van Nimwegen,Mihaela Zavolan,Nikolaus Rajewsky,Eric D. Siggia
Physics , 2002, DOI: 10.1073/pnas.112690399
Abstract: Genome wide comparisons between enteric bacteria yield large sets of conserved putative regulatory sites on a gene by gene basis that need to be clustered into regulons. Using the assumption that regulatory sites can be represented as samples from weight matrices we derive a unique probability distribution for assignments of sites into clusters. Our algorithm, 'PROCSE' (probabilistic clustering of sequences), uses Monte-Carlo sampling of this distribution to partition and align thousands of short DNA sequences into clusters. The algorithm internally determines the number of clusters from the data, and assigns significance to the resulting clusters. We place theoretical limits on the ability of any algorithm to correctly cluster sequences drawn from weight matrices (WMs) when these WMs are unknown. Our analysis suggests that the set of all putative sites for a single genome (e.g. E. coli) is largely inadequate for clustering. When sites from different genomes are combined and all the homologous sites from the various species are used as a block, clustering becomes feasible. We predict 50-100 new regulons as well as many new members of existing regulons, potentially doubling the number of known regulatory sites in E. coli.
Bacterial promoter recognition and application
细菌启动子识别及应用研究进展

Youqiang Xu,Cuiqing M,Fei Tao,Ping Xu,
徐友强
,马翠卿,陶飞,许平

生物工程学报 , 2010,
Abstract: Bacterial promoter is a kind of regulators which are needed in bacterial gene expression and decide the strength and opportunity of gene expression. By insertion or deletion of promoters, we can change bacterial gene expression in order to study the growth and metabolic regulation. Promoters are also used to construct many kinds of vectors, so as to express heterologous genes. The study of promoter recognition and application is of great importance to realize the regulation of genes, gain products effectively and promote biological catalysis and metabolic engineering. This paper reviews bacterial promoters, and the methods for recognition of bacterial promoters as well as the study and application of bacterial promoters.
Physical constraints determine the logic of bacterial promoter architectures  [PDF]
Daphne Ezer,Nicolae Radu Zabet,Boris Adryan
Quantitative Biology , 2013, DOI: 10.1093/nar/gku078
Abstract: Site-specific transcription factors (TFs) bind to their target sites on the DNA, where they regulate the rate at which genes are transcribed. Bacterial TFs undergo facilitated diffusion (a combination of 3D diffusion around and 1D random walk on the DNA) when searching for their target sites. Using computer simulations of this search process, we show that the organisation of the binding sites, in conjunction with TF copy number and binding site affinity, plays an important role in determining not only the steady state of promoter occupancy, but also the order at which TFs bind. These effects can be captured by facilitated diffusion-based models, but not by standard thermodynamics. We show that the spacing of binding sites encodes complex logic, which can be derived from combinations of three basic building blocks: switches, barriers and clusters, whose response alone and in higher orders of organisation we characterise in detail. Effective promoter organizations are commonly found in the E. coli genome and are highly conserved between strains. This will allow studies of gene regulation at a previously unprecedented level of detail, where our framework can create testable hypothesis of promoter logic.
Triad pattern algorithm for predicting strong promoter candidates in bacterial genomes
Michael Dekhtyar, Amelie Morin, Vehary Sakanyan
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-233
Abstract: We describe a new triad pattern algorithm that predicts strong promoter candidates in annotated bacterial genomes by matching specific patterns for the group I σ70 factors of Escherichia coli RNA polymerase. It detects promoter-specific motifs by consecutively matching three patterns, consisting of an UP-element, required for interaction with the α subunit, and then optimally-separated patterns of -35 and -10 boxes, required for interaction with the σ70 subunit of RNA polymerase. Analysis of 43 bacterial genomes revealed that the frequency of candidate sequences depends on the A+T content of the DNA under examination. The accuracy of in silico prediction was experimentally validated for the genome of a hyperthermophilic bacterium, Thermotoga maritima, by applying a cell-free expression assay using the predicted strong promoters. In this organism, the strong promoters govern genes for translation, energy metabolism, transport, cell movement, and other as-yet unidentified functions.The triad pattern algorithm developed for predicting strong bacterial promoters is well suited for analyzing bacterial genomes with an A+T content of less than 62%. This computational tool opens new prospects for investigating global gene expression, and individual strong promoters in bacteria of medical and/or economic significance.Efficient promoter recognition is crucial in the synthesis of the gene-encoded products required by bacteria to allow them to grow rapidly and to adapt to different environmental conditions. The general architecture and protein-DNA interaction interfaces appear to be conserved in RNA polymerases of different bacteria, to judge by a comparison of the resolved structures of the multi-subunit protein or its subunits [1]. This structural information suggests that the principles of DNA recognition by RNA polymerases are universal, and this constitutes a basis for in silico prediction of promoters that are recognized by families of sigma factors. Research in bioinform
FITBAR: a web tool for the robust prediction of prokaryotic regulons
Jacques Oberto
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-554
Abstract: FITBAR (Fast Investigation Tool for Bacterial and Archaeal Regulons) is a web service designed to identify new protein binding sites on fully sequenced prokaryotic genomes. This tool consists in a workbench where the significance of the predictions can be compared using different statistical methods, a feature not found in existing resources. The Local Markov Model and the Compound Importance Sampling algorithms have been implemented to compute the P-value of newly discovered binding sites. In addition, FITBAR provides two optimized genomic scanning algorithms using either log-odds or entropy-weighted position-specific scoring matrices. Other significant features include the production of a detailed genomic context map for each detected binding site and the export of the search results in spreadsheet and portable document formats. FITBAR discovery of a high affinity Escherichia coli NagC binding site was validated experimentally in vitro as well as in vivo and published.FITBAR was developed in order to allow fast, accurate and statistically robust predictions of prokaryotic regulons. This feature constitutes the main advantage of this web tool over other matrix search programs and does not impair its performance. The web service is available at http://archaea.u-psud.fr/fitbar webcite.In every living organism, the binding of regulatory proteins to their specific DNA targets accounts for the accurate transcription modulation and expression of the neighboring genes. The prediction, in silico, of new transcription factor binding sites (TFBSs) is a key aspect of the deeper understanding of gene regulation. The discovery of regulons, sets of functionally related and co-regulated genes scattered throughout the genome, is of great importance for the geneticist. However, the exponentially growing number of fully sequenced genomes, especially prokaryotic, has turned the prediction of regulons into a daunting task. Several reviews compare the algorithms that have been develope
Variability of Leptin gene promoter in cattle  [cached]
C. Lisa,S. Sartore,L. Di Stasio
Italian Journal of Animal Science , 2010, DOI: 10.4081/ijas.2007.1s.150
Abstract: A preliminary analysis on the variability of Leptin gene promoter in seven cattle breeds was carried out, focusing the attention on the SNP at nt 1759, which has been suggested to affect some quantitative traits in cattle. In addition, the linkage disequilibrium with the C305T mutation in exon 2 of Leptin gene was tested. The results indicate that the Leptin gene promoter is polymorphic in all the analysed breeds, with significant betweenbreed differences. Pairwise comparison of genotypes at the two considered SNPs revealed a significant linkage disequilibrium, with the presence of the haplotypes 1759C - 305T and 1759G - 305C.
Prediction by Promoter Logic in Bacterial Quorum Sensing  [PDF]
Navneet Rai,Rajat Anand,Krishna Ramkumar,Varun Sreenivasan,Sugat Dabholkar,K. V. Venkatesh,Mukund Thattai
PLOS Computational Biology , 2012, DOI: 10.1371/journal.pcbi.1002361
Abstract: Quorum-sensing systems mediate chemical communication between bacterial cells, coordinating cell-density-dependent processes like biofilm formation and virulence-factor expression. In the proteobacterial LuxI/LuxR quorum sensing paradigm, a signaling molecule generated by an enzyme (LuxI) diffuses between cells and allosterically stimulates a transcriptional regulator (LuxR) to activate its cognate promoter (pR). By expressing either LuxI or LuxR in positive feedback from pR, these versatile systems can generate smooth (monostable) or abrupt (bistable) density-dependent responses to suit the ecological context. Here we combine theory and experiment to demonstrate that the promoter logic of pR – its measured activity as a function of LuxI and LuxR levels – contains all the biochemical information required to quantitatively predict the responses of such feedback loops. The interplay of promoter logic with feedback topology underlies the versatility of the LuxI/LuxR paradigm: LuxR and LuxI positive-feedback systems show dramatically different responses, while a dual positive/negative-feedback system displays synchronized oscillations. These results highlight the dual utility of promoter logic: to probe microscopic parameters and predict macroscopic phenotype.
Genome-wide analysis of 3′-untranslated regions supports the existence of post-transcriptional regulons controlling gene expression in trypanosomes
Javier G. De Gaudenzi,Santiago J. Carmona,Fernán Agüero,Alberto C. Frasch
PeerJ , 2013, DOI: 10.7717/peerj.118
Abstract: In eukaryotic cells, a group of messenger ribonucleic acids (mRNAs) encoding functionally interrelated proteins together with the trans-acting factors that coordinately modulate their expression is termed a post-transcriptional regulon, due to their partial analogy to a prokaryotic polycistron. This mRNA clustering is organized by sequence-specific RNA-binding proteins (RBPs) that bind cis-regulatory elements in the noncoding regions of genes, and mediates the synchronized control of their fate. These recognition motifs are often characterized by conserved sequences and/or RNA structures, and it is likely that various classes of cis-elements remain undiscovered. Current evidence suggests that RNA regulons govern gene expression in trypanosomes, unicellular parasites which mainly use post-transcriptional mechanisms to control protein synthesis. In this study, we used motif discovery tools to test whether groups of functionally related trypanosomatid genes contain a common cis-regulatory element. We obtained conserved structured RNA motifs statistically enriched in the noncoding region of 38 out of 53 groups of metabolically related transcripts in comparison with a random control. These motifs have a hairpin loop structure, a preferred sense orientation and are located in close proximity to the open reading frames. We found that 15 out of these 38 groups represent unique motifs in which most 3′-UTR signature elements were group-specific. Two extensively studied Trypanosoma cruzi RBPs, TcUBP1 and TcRBP3 were found associated with a few candidate RNA regulons. Interestingly, 13 motifs showed a strong correlation with clusters of developmentally co-expressed genes and six RNA elements were enriched in gene clusters affected after hyperosmotic stress. Here we report a systematic genome-wide in silico screen to search for novel RNA-binding sites in transcripts, and describe an organized network of several coordinately regulated cohorts of mRNAs in T. cruzi. Moreover, we found that structured RNA elements are also conserved in other human pathogens. These results support a model of regulation of gene expression by multiple post-transcriptional regulons in trypanosomes.
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