title: Bioinformatic identification of novel regulatory DNA sequence motifs in Streptomyces coelicolor.
abstract: BACKGROUND
  Streptomyces 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.
  
  
  RESULTS
  The 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.
  
  
  CONCLUSIONS
  We 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.
authors.affiliation: Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK. ds2@sanger.ac.uk
authors.forename: David J
authors.initials: DJ
authors.lastname: Studholme
authors.forename: Stephen D
authors.initials: SD
authors.lastname: Bentley
authors.forename: Jan
authors.initials: J
authors.lastname: Kormanec
mesh_terms: D001483:Base Sequence; D050260:Carbohydrate Metabolism; D019295:Computational Biology / Q000379:methods*; D017124:Conserved Sequence; D004260:DNA Repair / Q000235:genetics; D004261:DNA Replication / Q000235:genetics; D004269:DNA, Bacterial / Q000032:analysis / Q000737:chemistry*; D016680:Genome, Bacterial; D008969:Molecular Sequence Data; D009690:Nucleic Acid Conformation; D011134:Polysaccharides / Q000378:metabolism; D017422:Sequence Analysis, DNA; D013302:Streptomyces / Q000235:genetics / Q000302:isolation & purification*
chemical_list: D004269:DNA, Bacterial; D011134:Polysaccharides