7,299 research outputs found

    PromBase: a web resource for various genomic features and predicted promoters in prokaryotic genomes

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    <p>Abstract</p> <p>Background</p> <p>As more and more genomes are being sequenced, an overview of their genomic features and annotation of their functional elements, which control the expression of each gene or transcription unit of the genome, is a fundamental challenge in genomics and bioinformatics.</p> <p>Findings</p> <p>Relative stability of DNA sequence has been used to predict promoter regions in 913 microbial genomic sequences with GC-content ranging from 16.6% to 74.9%. Irrespective of the genome GC-content the relative stability based promoter prediction method has already been proven to be robust in terms of recall and precision. The predicted promoter regions for the 913 microbial genomes have been accumulated in a database called PromBase. Promoter search can be carried out in PromBase either by specifying the gene name or the genomic position. Each predicted promoter region has been assigned to a reliability class (low, medium, high, very high and highest) based on the difference between its average free energy and the downstream region. The recall and precision values for each class are shown graphically in PromBase. In addition, PromBase provides detailed information about base composition, CDS and CG/TA skews for each genome and various DNA sequence dependent structural properties (average free energy, curvature and bendability) in the vicinity of all annotated translation start sites (TLS).</p> <p>Conclusion</p> <p>PromBase is a database, which contains predicted promoter regions and detailed analysis of various genomic features for 913 microbial genomes. PromBase can serve as a valuable resource for comparative genomics study and help the experimentalist to rapidly access detailed information on various genomic features and putative promoter regions in any given genome. This database is freely accessible for academic and non- academic users via the worldwide web <url>http://nucleix.mbu.iisc.ernet.in/prombase/</url>.</p

    Promoter prediction and annotation of microbial genomes based on DNA sequence and structural responses to superhelical stress

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    BACKGROUND: In our previous studies, we found that the sites in prokaryotic genomes which are most susceptible to duplex destabilization under the negative superhelical stresses that occur in vivo are statistically highly significantly associated with intergenic regions that are known or inferred to contain promoters. In this report we investigate how this structural property, either alone or together with other structural and sequence attributes, may be used to search prokaryotic genomes for promoters. RESULTS: We show that the propensity for stress-induced DNA duplex destabilization (SIDD) is closely associated with specific promoter regions. The extent of destabilization in promoter-containing regions is found to be bimodally distributed. When compared with DNA curvature, deformability, thermostability or sequence motif scores within the -10 region, SIDD is found to be the most informative DNA property regarding promoter locations in the E. coli K12 genome. SIDD properties alone perform better at detecting promoter regions than other programs trained on this genome. Because this approach has a very low false positive rate, it can be used to predict with high confidence the subset of promoters that are strongly destabilized. When SIDD properties are combined with -10 motif scores in a linear classification function, they predict promoter regions with better than 80% accuracy. When these methods were tested with promoter and non-promoter sequences from Bacillus subtilis, they achieved similar or higher accuracies. We also present a strictly SIDD-based predictor for annotating promoter sequences in complete microbial genomes. CONCLUSION: In this report we show that the propensity to undergo stress-induced duplex destabilization (SIDD) is a distinctive structural attribute of many prokaryotic promoter sequences. We have developed methods to identify promoter sequences in prokaryotic genomes that use SIDD either as a sole predictor or in combination with other DNA structural and sequence properties. Although these methods cannot predict all the promoter-containing regions in a genome, they do find large sets of potential regions that have high probabilities of being true positives. This approach could be especially valuable for annotating those genomes about which there is limited experimental data

    Integrative omics analysis of Pseudomonas aeruginosa virus PA5oct highlights the molecular complexity of jumbo phages

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    Pseudomonas virus vB_PaeM_PA5oct is proposed as a model jumbo bacteriophage to investigate phage-bacteria interactions and is a candidate for phage therapy applications. Combining hybrid sequencing, RNA-Seq and mass spectrometry allowed us to accurately annotate its 286,783 bp genome with 461 coding regions including four non-coding RNAs (ncRNAs) and 93 virion-associated proteins. PA5oct relies on the host RNA polymerase for the infection cycle and RNA-Seq revealed a gradual take-over of the total cell transcriptome from 21% in early infection to 93% in late infection. PA5oct is not organized into strictly contiguous regions of temporal transcription, but some genomic regions transcribed in early, middle and late phases of infection can be discriminated. Interestingly, we observe regions showing limited transcription activity throughout the infection cycle. We show that PA5oct upregulates specific bacterial operons during infection including operons pncA-pncB1-nadE involved in NAD biosynthesis, psl for exopolysaccharide biosynthesis and nap for periplasmic nitrate reductase production. We also observe a downregulation of T4P gene products suggesting mechanisms of superinfection exclusion. We used the proteome of PA5oct to position our isolate amongst other phages using a gene-sharing network. This integrative omics study illustrates the molecular diversity of jumbo viruses and raises new questions towards cellular regulation and phage-encoded hijacking mechanisms

    Genome sequence of the button mushroom Agaricus bisporus reveals mechanisms governing adaptation to a humic-rich ecological niche

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    Agaricus bisporus is the model fungus for the adaptation, persistence, and growth in the humic-rich leaf-litter environment. Aside from its ecological role, A. bisporus has been an important component of the human diet for over 200 y and worldwide cultivation of the "button mushroom" forms a multibillion dollar industry. We present two A. bisporus genomes, their gene repertoires and transcript profiles on compost andduringmushroomformation.The genomes encode a full repertoire of polysaccharide-degrading enzymes similar to that of wood-decayers. Comparative transcriptomics of mycelium grown on defined medium, casing-soil, and compost revealed genes encoding enzymes involved in xylan, cellulose, pectin, and protein degradation aremore highly expressed in compost. The striking expansion of heme-thiolate peroxidases and ÎČ-etherases is distinctive from Agaricomycotina wood-decayers and suggests a broad attack on decaying lignin and related metabolites found in humic acid-rich environment. Similarly, up-regulation of these genes together with a lignolytic manganese peroxidase, multiple copper radical oxidases, and cytochrome P450s is consistent with challenges posed by complex humic-rich substrates. The gene repertoire and expression of hydrolytic enzymes in A. bisporus is substantially different from the taxonomically related ectomycorrhizal symbiont Laccaria bicolor. A common promoter motif was also identified in genes very highly expressed in humic-rich substrates. These observations reveal genetic and enzymatic mechanisms governing adaptation to the humic-rich ecological niche formed during plant degradation, further defining the critical role such fungi contribute to soil structure and carbon sequestration in terrestrial ecosystems. Genome sequence will expedite mushroom breeding for improved agronomic characteristics

    Promoter prediction in E. coli based on SIDD profiles and Artificial Neural Networks

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    <p>Abstract</p> <p>Background</p> <p>One of the major challenges in biology is the correct identification of promoter regions. Computational methods based on motif searching have been the traditional approach taken. Recent studies have shown that DNA structural properties, such as curvature, stacking energy, and stress-induced duplex destabilization (SIDD) are useful in promoter prediction, as well. In this paper, the currently used SIDD energy threshold method is compared to the proposed artificial neural network (ANN) approach for finding promoters based on SIDD profile data.</p> <p>Results</p> <p>When compared to the SIDD threshold prediction method, artificial neural networks showed noticeable improvements for precision, recall, and <it>F</it>-score over a range of values. The maximal <it>F</it>-score for the ANN classifier was 62.3 and 56.8 for the threshold-based classifier.</p> <p>Conclusions</p> <p>Artificial neural networks were used to predict promoters based on SIDD profile data. Results using this technique were an improvement over the previous SIDD threshold approach. Over a wide range of precision-recall values, artificial neural networks were more capable of identifying distinctive characteristics of promoter regions than threshold based methods.</p

    Impact of Environmental Factors on Bacteriocin Promoter Activity in Gut-Derived Lactobacillus salivarius

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    peer-reviewedBacteriocin production is regarded as a desirable probiotic trait that aids in colonization and persistence in the gastrointestinal tract (GIT). Strains of Lactobacillus salivarius, a species associated with the GIT, are regarded as promising probiotic candidates and have a number of associated bacteriocins documented to date. These include multiple class IIb bacteriocins (salivaricin T, salivaricin P, and ABP-118) and the class IId bacteriocin bactofencin A, which show activity against medically important pathogens. However, the production of a bacteriocin in laboratory media does not ensure production under stressful environmental conditions, such as those encountered within the GIT. To allow this issue to be addressed, the promoter regions located upstream of the structural genes encoding the L. salivarius bacteriocins mentioned above were fused to a number of reporter proteins (green fluorescent protein [GFP], red fluorescent protein [RFP], and luciferase [Lux]). Of these, only transcriptional fusions to GFP generated signals of sufficient strength to enable the study of promoter activity in L. salivarius. While analysis of the class IIb bacteriocin promoter regions indicated relatively weak GFP expression, assessment of the promoter of the antistaphylococcal bacteriocin bactofencin A revealed a strong promoter that is most active in the absence of the antimicrobial peptide and is positively induced in the presence of mild environmental stresses, including simulated gastric fluid. Taken together, these data provide information on factors that influence bacteriocin production, which will assist in the development of strategies to optimize in vivo and in vitro production of these antimicrobials.This work was funded by a SFI PI award “Obesibiotics” (11/PI/1137) to PD
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