title: Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus.
abstract: BACKGROUND
  Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria.
  
  
  RESULTS
  To explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. Multiple variations in regulatory strategies between the Shewanella spp. and E. coli include regulon contraction and expansion (as in the case of PdhR, HexR, FadR), numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. PsrA for fatty acid degradation) and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp).
  
  
  CONCLUSIONS
  We tentatively defined the first reference collection of ~100 transcriptional regulons in 16 Shewanella genomes. The resulting regulatory network contains ~600 regulated genes per genome that are mostly involved in metabolism of carbohydrates, amino acids, fatty acids, vitamins, metals, and stress responses. Several reconstructed regulons including NagR for N-acetylglucosamine catabolism were experimentally validated in S. oneidensis MR-1. Analysis of correlations in gene expression patterns helps to interpret the reconstructed regulatory network. The inferred regulatory interactions will provide an additional regulatory constrains for an integrated model of metabolism and regulation in S. oneidensis MR-1.
authors.affiliation: Sanford-Burnham Medical Research Institute, La Jolla, California, USA. rodionov@burnham.org
authors.forename: Dmitry A
authors.initials: DA
authors.lastname: Rodionov
authors.forename: Pavel S
authors.initials: PS
authors.lastname: Novichkov
authors.forename: Elena D
authors.initials: ED
authors.lastname: Stavrovskaya
authors.forename: Irina A
authors.initials: IA
authors.lastname: Rodionova
authors.forename: Xiaoqing
authors.initials: X
authors.lastname: Li
authors.forename: Marat D
authors.initials: MD
authors.lastname: Kazanov
authors.forename: Dmitry A
authors.initials: DA
authors.lastname: Ravcheev
authors.forename: Anna V
authors.initials: AV
authors.lastname: Gerasimova
authors.forename: Alexey E
authors.initials: AE
authors.lastname: Kazakov
authors.forename: Galina Yu
authors.initials: GY
authors.lastname: Kovaleva
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Permina
authors.forename: Olga N
authors.initials: ON
authors.lastname: Laikova
authors.forename: Ross
authors.initials: R
authors.lastname: Overbeek
authors.forename: Margaret F
authors.initials: MF
authors.lastname: Romine
authors.forename: James K
authors.initials: JK
authors.lastname: Fredrickson
authors.forename: Adam P
authors.initials: AP
authors.lastname: Arkin
authors.forename: Inna
authors.initials: I
authors.lastname: Dubchak
authors.forename: Andrei L
authors.initials: AL
authors.lastname: Osterman
authors.forename: Mikhail S
authors.initials: MS
authors.lastname: Gelfand
mesh_terms: D000117:Acetylglucosamine / Q000378:metabolism; D000596:Amino Acids / Q000378:metabolism; D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism; D001665:Binding Sites; D050260:Carbohydrate Metabolism; D004268:DNA-Binding Proteins / Q000235:genetics; D004926:Escherichia coli / Q000235:genetics; D029968:Escherichia coli Proteins / Q000235:genetics; D005227:Fatty Acids / Q000378:metabolism; D015964:Gene Expression Regulation, Bacterial; D053263:Gene Regulatory Networks; D016680:Genome, Bacterial; D023281:Genomics / Q000379:methods; D005810:Multigene Family; D018085:Regulon; D012097:Repressor Proteins / Q000235:genetics; D058928:Riboswitch; D020592:Shewanella / Q000235:genetics* / Q000378:metabolism*; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism
chemical_list: D000596:Amino Acids; C087018:ArgR protein, Bacteria; D001426:Bacterial Proteins; D004268:DNA-Binding Proteins; D029968:Escherichia coli Proteins; C057119:FadR protein, Bacteria; D005227:Fatty Acids; C084955:PdhR protein, E coli; C430183:PsrA protein, Pseudomonas; D012097:Repressor Proteins; D058928:Riboswitch; D014157:Transcription Factors; C069256:TyrR protein, E coli; D000117:Acetylglucosamine