Dataset Information

Genome-wide inference of regulatory networks in Streptomyces coelicolor.

ABSTRACT: BACKGROUND: The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intricacies of the regulatory cascades and develop biologically meaningful hypotheses. RESULTS: In this study, more than 500 samples of genome-wide temporal transcriptome data, comprising wild-type and more than 25 regulatory gene mutants of Streptomyces coelicolor probed across multiple stress and medium conditions, were investigated. Information based on transcript and functional similarity was used to update a previously-predicted whole-genome operon map and further applied to predict transcriptional networks constituting modules enriched in diverse functions such as secondary metabolism, and sigma factor. The predicted network displays a scale-free architecture with a small-world property observed in many biological networks. The networks were further investigated to identify functionally-relevant modules that exhibit functional coherence and a consensus motif in the promoter elements indicative of DNA-binding elements. CONCLUSIONS: Despite the enormous experimental as well as computational challenges, a systems approach for integrating diverse genome-scale datasets to elucidate complex regulatory networks is beginning to emerge. We present an integrated analysis of transcriptome data and genomic features to refine a whole-genome operon map and to construct regulatory networks at the cistron level in Streptomyces coelicolor. The functionally-relevant modules identified in this study pose as potential targets for further studies and verification.

SUBMITTER: Castro-Melchor M

PROVIDER: S-EPMC3224704 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Genome-wide inference of regulatory networks in Streptomyces coelicolor.

Castro-Melchor Marlene M Charaniya Salim S Karypis George G Takano Eriko E Hu Wei-Shou WS

BMC genomics 20101018

<h4>Background</h4>The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intr ...[more]

PMID: 20955611

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Project description:BackgroundThe learning of global genetic regulatory networks from expression data is a severely under-constrained problem that is aided by reducing the dimensionality of the search space by means of clustering genes into putatively co-regulated groups, as opposed to those that are simply co-expressed. Be cause genes may be co-regulated only across a subset of all observed experimental conditions, biclustering (clustering of genes and conditions) is more appropriate than standard clustering. Co-regulated genes are also often functionally (physically, spatially, genetically, and/or evolutionarily) associated, and such a priori known or pre-computed associations can provide support for appropriately grouping genes. One important association is the presence of one or more common cis-regulatory motifs. In organisms where these motifs are not known, their de novo detection, integrated into the clustering algorithm, can help to guide the process towards more biologically parsimonious solutions.ResultsWe have developed an algorithm, cMonkey, that detects putative co-regulated gene groupings by integrating the biclustering of gene expression data and various functional associations with the de novo detection of sequence motifs.ConclusionWe have applied this procedure to the archaeon Halobacterium NRC-1, as part of our efforts to decipher its regulatory network. In addition, we used cMonkey on public data for three organisms in the other two domains of life: Helicobacter pylori, Saccharomyces cerevisiae, and Escherichia coli. The biclusters detected by cMonkey both recapitulated known biology and enabled novel predictions (some for Halobacterium were subsequently confirmed in the laboratory). For example, it identified the bacteriorhodopsin regulon, assigned additional genes to this regulon with apparently unrelated function, and detected its known promoter motif. We have performed a thorough comparison of cMonkey results against other clustering methods, and find that cMonkey biclusters are more parsimonious with all available evidence for co-regulation.

Project description:BackgroundThe present study represents a genome-wide transcriptomic analysis of the response of the model streptomycete Streptomyces coelicolor A3(2) M145 to fermentor culture in Modified Evans Media limited, respectively, for nitrogen, phosphate and carbon undertaken as part of the ActinoGEN consortium to provide a publicly available reference microarray dataset.FindingsA microarray dataset using samples from two replicate cultures for each nutrient limitation was generated. In this report our analysis has focused on the genes which are significantly differentially expressed, as determined by Rank Products Analysis, between samples from matched time points correlated by growth phase for the three pairs of differently limited culture datasets. With a few exceptions, genes are only significantly differentially expressed between the N6/N7 time points and their corresponding time points in the C and P-limited cultures, with the vast majority of the differentially expressed genes being more highly expressed in the N-limited cultures. Our analysis of these genes indicated expression of several members of the GlnR regulon are induced upon nitrogen limitation, as assayed for by [NH4+] measurements, and we are able to identify several additional genes not present in the GlnR regulon whose expression is induced in response to nitrogen limitation. We also note SCO3327 which encodes a small protein (32 amino acid residues) unusually rich in the basic amino acids lysine (31.25%) and arginine (25%) is significantly differentially expressed in the nitrogen limited cultures. Additionally, we investigate the expression of known members of the GlnR regulon and the relationship between gene organization and expression for the SCO2486-SCO2487 and SCO5583-SCO5585 operons.ConclusionsWe provide a list of genes whose expression is differentially expressed in low nitrogen culture conditions, including a putative nitrogen storage protein encoded by SCO3327. Our list includes several genes whose expression patterns are similar to up-regulated members of the GlnR regulon and are induced in response to nitrogen limitation. These genes represent likely targets for future studies into the nitrogen starvation response in Streptomyces coelicolor.

Project description:BackgroundStreptomyces coelicolor is a bacterium with a vast repertoire of metabolic functions and complex systems of cellular development. Its genome sequence is rich in genes that encode regulatory proteins to control these processes in response to its changing environment. We wished to apply a recently published bioinformatic method for identifying novel regulatory sequence signals to gain new insights into regulation in S. coelicolor.ResultsThe method involved production of position-specific weight matrices from alignments of over-represented words of DNA sequence. We generated 2497 weight matrices, each representing a candidate regulatory DNA sequence motif. We scanned the genome sequence of S. coelicolor against each of these matrices. A DNA sequence motif represented by one of the matrices was found preferentially in non-coding sequences immediately upstream of genes involved in polysaccharide degradation, including several that encode chitinases. This motif (TGGTCTAGACCA) was also found upstream of genes encoding components of the phosphoenolpyruvate phosphotransfer system (PTS). We hypothesise that this DNA sequence motif represents a regulatory element that is responsive to availability of carbon-sources. Other motifs of potential biological significance were found upstream of genes implicated in secondary metabolism (TTAGGTtAGgCTaACCTAA), sigma factors (TGACN19TGAC), DNA replication and repair (ttgtCAGTGN13TGGA), nucleotide conversions (CTACgcNCGTAG), and ArsR (TCAGN12TCAG). A motif found upstream of genes involved in chromosome replication (TGTCagtgcN7Tagg) was similar to a previously described motif found in UV-responsive promoters.ConclusionsWe successfully applied a recently published in silico method to identify conserved sequence motifs in S. coelicolor that may be biologically significant as regulatory elements. Our data are broadly consistent with and further extend data from previously published studies. We invite experimental testing of our hypotheses in vitro and in vivo.

Dataset Information

Genome-wide inference of regulatory networks in Streptomyces coelicolor.

Publications

Genome-wide inference of regulatory networks in Streptomyces coelicolor.

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