4.7 Article

Genomic reconstruction of transcriptional regulatory networks in lactic acid bacteria

Journal

BMC GENOMICS
Volume 14, Issue -, Pages -

Publisher

BMC
DOI: 10.1186/1471-2164-14-94

Keywords

Transcriptional regulatory network; Comparative genomics; Carbohydrate metabolism; Lactobacillaceae; Streptococcaceae; Lactic acid bacteria; Regulon; Transcription factor

Funding

  1. Office of Science, Office of Biological and Environmental Research, of the U.S. Department of Energy [DE-SC0004999]
  2. SBMRI
  3. LBNL
  4. Russian Foundation for Basic Research [12-04-33003, 12-04-31939]
  5. State [8135, 2012-1.2.2-12-000-1013-079]
  6. National Science Foundation [DBI-0850546]
  7. Div Of Biological Infrastructure
  8. Direct For Biological Sciences [0850546] Funding Source: National Science Foundation

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Background: Genome scale annotation of regulatory interactions and reconstruction of regulatory networks are the crucial problems in bacterial genomics. The Lactobacillales order of bacteria collates various microorganisms having a large economic impact, including both human and animal pathogens and strains used in the food industry. Nonetheless, no systematic genome-wide analysis of transcriptional regulation has been previously made for this taxonomic group. Results: A comparative genomics approach was used for reconstruction of transcriptional regulatory networks in 30 selected genomes of lactic acid bacteria. The inferred networks comprise regulons for 102 orthologous transcription factors (TFs), including 47 novel regulons for previously uncharacterized TFs. Numerous differences between regulatory networks of the Streptococcaceae and Lactobacillaceae groups were described on several levels. The two groups are characterized by substantially different sets of TFs encoded in their genomes. Content of the inferred regulons and structure of their cognate TF binding motifs differ for many orthologous TFs between the two groups. Multiple cases of non-orthologous displacements of TFs that control specific metabolic pathways were reported. Conclusions: The reconstructed regulatory networks substantially expand the existing knowledge of transcriptional regulation in lactic acid bacteria. In each of 30 studied genomes the obtained regulatory network contains on average 36 TFs and 250 target genes that are mostly involved in carbohydrate metabolism, stress response, metal homeostasis and amino acids biosynthesis. The inferred networks can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. All reconstructed regulons are captured within the Streptococcaceae and Lactobacillaceae collections in the RegPrecise database (http://regprecise.lbl.gov).

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