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Computational analysis of LexA regulons in Cyanobacteria
Shan Li, Minli Xu, Zhengchang Su
BMC Genomics , 2010, DOI: 10.1186/1471-2164-11-527
Abstract: Our analysis indicates that six of 33 sequenced cyanobacterial genomes do not harbor a lexA gene although they all encode the key SOS response genes, suggesting that LexA is not an indispensable transcription factor in these cyanobacteria, and that their SOS responses might be regulated by different mechanisms. Our phylogenetic analysis suggests that lexA was lost during the course of evolution in these six cyanobacterial genomes. For the 26 cyanobacterial genomes that encode a lexA gene, we have predicted their LexA-binding sites and regulons using an efficient binding site/regulon prediction algorithm that we developed previously. Our results show that LexA in most of these 26 genomes might still function as the transcriptional regulator of the SOS response genes as seen in E. coli and other organisms. Interestingly, putative LexA-binding sites were also found in some genomes for some key genes involved in a variety of other biological processes including photosynthesis, drug resistance, etc., suggesting that there is crosstalk between the SOS response and these biological processes. In particular, LexA in both Synechocystis sp. PCC6803 and Gloeobacter violaceus PCC7421 has largely diverged from those in other cyanobacteria in the sequence level. It is likely that LexA is no longer a regulator of the SOS response in Synechocystis sp. PCC6803.In most cyanobacterial genomes that we analyzed, LexA appears to function as the transcriptional regulator of the key SOS response genes. There are possible couplings between the SOS response and other biological processes. In some cyanobacteria, LexA has adapted distinct functions, and might no longer be a regulator of the SOS response system. In some other cyanobacteria, lexA appears to have been lost during the course of evolution. The loss of lexA in these genomes might lead to the degradation of its binding sites.The LexA protein was first characterized as the transcriptional regulator of the SOS response in Escherichia c
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.
Computational prediction of cAMP receptor protein (CRP) binding sites in cyanobacterial genomes
Minli Xu, Zhengchang Su
BMC Genomics , 2009, DOI: 10.1186/1471-2164-10-23
Abstract: We have predicted and analyzed the CRP binding sites and regulons in 12 sequenced cyanobacterial genomes using a highly effective cis-regulatory binding site scanning algorithm. Our results show that cyanobacterial CRP binding sites are very similar to those in E. coli; however, the regulons are very different from that of E. coli. Furthermore, CRP regulons in different cyanobacterial species/ecotypes are also highly diversified, ranging from photosynthesis, carbon fixation and nitrogen assimilation, to chemotaxis and signal transduction. In addition, our prediction indicates that crp genes in modern cyanobacteria are likely inherited from a common ancestral gene in their last common ancestor, and have adapted various cellular functions in different environments, while some cyanobacteria lost their crp genes as well as CRP binding sites during the course of evolution.The CRP regulons in cyanobacteria are highly diversified, probably as a result of divergent evolution to adapt to various ecological niches. Cyanobacterial CRPs may function as lineage-specific regulators participating in various cellular processes, and are important in some lineages. However, they are dispensable in some other lineages. The loss of CRPs in these species leads to the rapid loss of their binding sites in the genomes.Cyclic AMP receptor protein (CRP), also known as catabolite gene activator protein (CAP), is an important transcriptional regulator widely distributed in a variety of bacterial groups [1,2]. The biological processes under the regulation of CRP are highly diverse, including energy metabolism [3,4], cell division and development [5], toxin production [1], competence development [6], quorum sensing [7] and cellular motility [8,9]. CRP belongs to the CRP/FNR transcription factor (TF) superfamily [10], which are generally believed to function as global regulators throughout the eubacteria [11]. Each member of the CRP/FNR superfamily contains an N-terminal effector binding domain a
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
Computational biology and protein modeling of cyanobacteria using bioinformatics tools and techniques
Padhi S.B.,Behera S.,Swain P.,Behura S.
International Journal of Bioinformatics Research , 2010,
Abstract: Computational biology is a term coined from analogy to the role of physical sciences, is nowcoming into its own as a major element of contemporary biological and biomedical research. In the sharp inthis pattern, over past few years, experiments in life sciences in the academic institutions have begun torecognize the value of bioinformatics and computational biology in the field of algology. Cyanobacteria (alsoknown as blue–green algae) are a group of extraordinarily diverse Gram-negative prokaryotes thatoriginated 3.5 billion years ago. After the advent of bioinformatics in the field of algology, complete genomesequences of Cyanobacteria have been reported in more than 30 species and strains including unicellular.The filamentous cyanobacterium Anabaena sp. PCC 7120 (further referred to as Anabaena sp.) is a modelsystem to study nitrogen fixation, cell differentiation, cell pattern formation and evolution of plastids. It is amulticellular photosynthetic microorganism consisting of two cell types, vegetative cells and nitrogen fixingheterocysts. The nucleotide sequence of the entire genome of a filamentous Cyanobacterium, Anabaena sp.Strain PCC 7120, was determined. This study focuses on the function and dynamics of the proteome of theGram-negative outer membrane in Anabaena sp.
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.
Biocomputational prediction of non-coding RNAs in model cyanobacteria
Bj?rn Vo?, Jens Georg, Verena Sch?n, Susanne Ude, Wolfgang R Hess
BMC Genomics , 2009, DOI: 10.1186/1471-2164-10-123
Abstract: Here we have used comparative genome analysis for the biocomputational prediction of ncRNA genes and other sequence/structure-conserved elements in intergenic regions of the three unicellular model cyanobacteria Synechocystis PCC6803, Synechococcus elongatus PCC6301 and Thermosynechococcus elongatus BP1 plus the toxic Microcystis aeruginosa NIES843. The unfiltered numbers of predicted elements in these strains is 383, 168, 168, and 809, respectively, combined into 443 sequence clusters, whereas the numbers of individual elements with high support are 94, 56, 64, and 406, respectively. Removing also transposon-associated repeats, finally 78, 53, 42 and 168 sequences, respectively, are left belonging to 109 different clusters in the data set. Experimental analysis of selected ncRNA candidates in Synechocystis PCC6803 validated new ncRNAs originating from the fabF-hoxH and apcC-prmA intergenic spacers and three highly expressed ncRNAs belonging to the Yfr2 family of ncRNAs. Yfr2a promoter-luxAB fusions confirmed a very strong activity of this promoter and indicated a stimulation of expression if the cultures were exposed to elevated light intensities.Comparison to entries in Rfam and experimental testing of selected ncRNA candidates in Synechocystis PCC6803 indicate a high reliability of the current prediction, despite some contamination by the high number of repetitive sequences in some of these species. In particular, we identified in the four species altogether 8 new ncRNA homologs belonging to the Yfr2 family of ncRNAs. Modelling of RNA secondary structures indicated two conserved single-stranded sequence motifs that might be involved in RNA-protein interactions or in the recognition of target RNAs. Since our analysis has been restricted to find ncRNA candidates with a reasonable high degree of conservation among these four cyanobacteria, there might be many more, requiring direct experimental approaches for their identification.In bacteria, non-coding RNAs (ncRNAs
Computational Small RNA Prediction in Bacteria
Jayavel Sridhar and Paramasamy Gunasekaran
Bioinformatics and Biology Insights , 2012, DOI: 10.4137/BBI.S11213
Abstract: Bacterial, small RNAs were once regarded as potent regulators of gene expression and are now being considered as essential for their diversified roles. Many small RNAs are now reported to have a wide array of regulatory functions, ranging from environmental sensing to pathogenesis. Traditionally, noncoding transcripts were rarely detected by means of genetic screens. However, the availability of approximately 2200 prokaryotic genome sequences in public databases facilitates the efficient computational search of those molecules, followed by experimental validation. In principle, the following four major computational methods were applied for the prediction of sRNA locations from bacterial genome sequences: (1) comparative genomics, (2) secondary structure and thermodynamic stability, (3) ‘Orphan’ transcriptional signals and (4) ab initio methods regardless of sequence or structure similarity; most of these tools were applied to locate the putative genomic sRNA locations followed by experimental validation of those transcripts. Therefore, computational screening has simplified the sRNA identification process in bacteria. In this review, a plethora of small RNA prediction methods and tools that have been reported in the past decade are discussed comprehensively and assessed based on their attributes, compatibility, and their prediction accuracy. Keywords: comparative genomics, base composition, ncRNA, sRNA prediction, structure stability, transcriptional signal
Computational Prediction of MicroRNAs Encoded in Viral and Other Genomes
Gard O. S. Thomassen, ystein R sok,Torbj rn Rognes
Journal of Biomedicine and Biotechnology , 2006, DOI: 10.1155/jbb/2006/95270
Abstract: We present an overview of selected computational methods for microRNA prediction. It is especially aimed at viral miRNA detection. As the number of microRNAs increases and the range of genomes encoding miRNAs expands, it seems that these small regulators have a more important role than has been previously thought. Most microRNAs have been detected by cloning and Northern blotting, but experimental methods are biased towards abundant microRNAs as well as being time-consuming. Computational detection methods must therefore be refined to serve as a faster, better, and more affordable method for microRNA detection. We also present data from a small study investigating the problems of computational miRNA prediction. Our findings suggest that the prediction of microRNA precursor candidates is fairly easy, while excluding false positives as well as exact prediction of the mature microRNA is hard. Finally, we discuss possible improvements to computational microRNA detection.
Computational approaches for Oral bioavailability prediction: An overview  [PDF]
Rajnish Kumar*,Anju Sharma,Pritish Kumar Varadwaj
Biomirror , 2010,
Abstract: High oral bioavailability is among the most important consideration during drug development process. Oral-bioavailability is usually determined in the pre-clinical stage of drug development process. It was found that 30% of drugs fail during the drug discovery process. Therefore there is a need of a robust and accurate computational model which can predict the oral bioavailability of compounds without carrying out any experiments. There exists a plethora of studies to predict oral bioavailability which indicates that it is incredibly rich area of research. Various attempts in estimating oral bioavailability are reported in literature belonging to different categories. In this article computational oral bioavailability prediction approaches are discussed.
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