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See detailComparative genomics and evolution of regulons of the LacI-family transcription factors
Ravcheev, Dmitry UL; Khoroshkin, Matvei S.; Laikova, Olga N. et al

in Frontiers in Microbiology (2014), 5

DNA-binding transcription factors (TFs) are essential components of transcriptional regulatory networks in bacteria. LacI-family TFs (LacI-TFs) are broadly distributed among certain lineages of bacteria ... [more ▼]

DNA-binding transcription factors (TFs) are essential components of transcriptional regulatory networks in bacteria. LacI-family TFs (LacI-TFs) are broadly distributed among certain lineages of bacteria. The majority of characterized LacI-TFs sense sugar effectors and regulate carbohydrate utilization genes. The comparative genomics approaches enable in silico identification of TF-binding sites and regulon reconstruction. To study the function and evolution of LacI-TFs, we performed genomics-based reconstruction and comparative analysis of their regulons. For over 1300 LacI-TFs from over 270 bacterial genomes, we predicted their cognate DNA-binding motifs and identified target genes. Using the genome context and metabolic subsystem analyses of reconstructed regulons, we tentatively assigned functional roles and predicted candidate effectors for 78 and 67% of the analyzed LacI-TFs, respectively. Nearly 90% of the studied LacI-TFs are local regulators of sugar utilization pathways, whereas the remaining 125 global regulators control large and diverse sets of metabolic genes. The global LacI-TFs include the previously known regulators CcpA in Firmicutes, FruR in Enterobacteria, and PurR in Gammaproteobacteria, as well as the three novel regulators—GluR, GapR, and PckR—that are predicted to control the central carbohydrate metabolism in three lineages of Alphaproteobacteria. Phylogenetic analysis of regulators combined with the reconstructed regulons provides a model of evolutionary diversification of the LacI protein family. The obtained genomic collection of in silico reconstructed LacI-TF regulons in bacteria is available in the RegPrecise database (http://regprecise.lbl.gov). It provides a framework for future structural and functional classification of the LacI protein family and identification of molecular determinants of the DNA and ligand specificity. The inferred regulons can be also used for functional gene annotation and reconstruction of sugar catabolic networks in diverse bacterial lineages. [less ▲]

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See detailGenomic reconstruction of transcriptional regulatory networks in lactic acid bacteria
Ravcheev, Dmitry UL; Best, Aaron A.; Sernova, Natalia V. et al

in BMC Genomics (2013), 14(94), 1-14

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 ... [more ▼]

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). [less ▲]

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See detailRegPrecise 3.0 - a resource for genome-scale exploration of transcriptional regulation in Bacteria
Novichkov, Pavel S.; Kazakov, Alexey E.; Ravcheev, Dmitry UL et al

in BMC Genomics (2013), 14(745), 1-12

Background: Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different ... [more ▼]

Background: Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). Description: RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. Conclusions: RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in bacterial genomes. Analytical capabilities include exploration of: regulon content, structure and function; TF binding site motifs; conservation and variations in genome-wide regulatory networks across all taxonomic groups of Bacteria. RegPrecise 3.0 was selected as a core resource on transcriptional regulation of the Department of Energy Systems Biology Knowledgebase, an emerging software and data environment designed to enable researchers to collaboratively generate, test and share new hypotheses about gene and protein functions, perform large-scale analyses, and model interactions in microbes, plants, and their communities. [less ▲]

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See detailTranscriptional regulation of central carbon and energy metabolism in bacteria by redox responsive repressor Rex
Ravcheev, Dmitry UL; Li, Xiaoqing; Latif, Haythem et al

in Journal of Bacteriology (2012), 194(5), 1145-1157

Redox-sensing repressor Rex was previously implicated in the control of anaerobic respiration in response to the cellular NADH/NAD(+) levels in gram-positive bacteria. We utilized the comparative genomics ... [more ▼]

Redox-sensing repressor Rex was previously implicated in the control of anaerobic respiration in response to the cellular NADH/NAD(+) levels in gram-positive bacteria. We utilized the comparative genomics approach to infer candidate Rex-binding DNA motifs and assess the Rex regulon content in 119 genomes from 11 taxonomic groups. Both DNA-binding and NAD-sensing domains are broadly conserved in Rex orthologs identified in the phyla Firmicutes, Thermotogales, Actinobacteria, Chloroflexi, Deinococcus-Thermus, and Proteobacteria. The identified DNA-binding motifs showed significant conservation in these species, with the only exception detected in Clostridia, where the Rex motif deviates in two positions from the generalized consensus, TTGTGAANNNNTTCACAA. Comparative analysis of candidate Rex sites revealed remarkable variations in functional repertoires of candidate Rex-regulated genes in various microorganisms. Most of the reconstructed regulatory interactions are lineage specific, suggesting frequent events of gain and loss of regulator binding sites in the evolution of Rex regulons. We identified more than 50 novel Rex-regulated operons encoding functions that are essential for resumption of the NADH:NAD(+) balance. The novel functional role of Rex in the control of the central carbon metabolism and hydrogen production genes was validated by in vitro DNA binding assays using the TM0169 protein in the hydrogen-producing bacterium Thermotoga maritima. [less ▲]

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See detailInference of the Transcriptional Regulatory Network in Staphylococcus aureus by Integration of Experimental and Genomics-Based Evidence
Ravcheev, Dmitry UL; Best, Aaron A.; Tintle, Nathan et al

in Journal of Bacteriology (2011), 193(12), 3228-3240

Transcriptional regulatory networks are fine-tuned systems that help microorganisms respond to changes in the environment and cell physiological state. We applied the comparative genomics approach ... [more ▼]

Transcriptional regulatory networks are fine-tuned systems that help microorganisms respond to changes in the environment and cell physiological state. We applied the comparative genomics approach implemented in the RegPredict Web server combined with SEED subsystem analysis and available information on known regulatory interactions for regulatory network reconstruction for the human pathogen Staphylococcus aureus and six related species from the family Staphylococcaceae. The resulting reference set of 46 transcription factor regulons contains more than 1,900 binding sites and 2,800 target genes involved in the central metabolism of carbohydrates, amino acids, and fatty acids; respiration; the stress response; metal homeostasis; drug and metal resistance; and virulence. The inferred regulatory network in S. aureus includes ∼320 regulatory interactions between 46 transcription factors and ∼550 candidate target genes comprising 20% of its genome. We predicted ∼170 novel interactions and 24 novel regulons for the control of the central metabolic pathways in S. aureus. The reconstructed regulons are largely variable in the Staphylococcaceae: only 20% of S. aureus regulatory interactions are conserved across all studied genomes. We used a large-scale gene expression data set for S. aureus to assess relationships between the inferred regulons and gene expression patterns. The predicted reference set of regulons is captured within the Staphylococcus collection in the RegPrecise database (http://regprecise.lbl.gov). [less ▲]

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See detailComparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus
Rodionov, Dmitry A.; Novichkov, Pavel S.; Stavrovskaya, Elena D. et al

in BMC Genomics (2011), 12 (Suppl 1)(S3), 1-17

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 ... [more ▼]

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. [less ▲]

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