RegPrecise: a database of curated genomic inferences of transcriptional regulatory interactions in prokaryotes

Novichkov, Pavel S.; Laikova, Olga N.; Novichkova, Elena S.; Gelfand, Mikhail S.; Arkin, Adam P.; Dubchak, Inna; Rodionov, Dmitry A.

doi:10.1093/nar/gkp894

Cited by 159 publications

(218 citation statements)

References 39 publications

(47 reference statements)

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“…A detailed description of the 46 TF regulons reconstructed by utilizing the three computational workflows is provided below and summarized in Table 1 and in Table S2 in the supplemental material. The reconstructed regulons are also captured in the Staphylococcus collection of regulons in the RegPrecise database (available at http://regprecise.lbl.gov) (29). In Table S3 in the supplemental material, we also provide detailed information on all TFBSs in S. aureus, including both previously described TFBSs and TFBSs first predicted in this work, as well as evidence codes for all TFBSs with references to previous experimental reports where the respective regulatory interactions have been confirmed.…”

Section: Resultsmentioning

confidence: 99%

“…Five other orthologous regulators (FruR, GlvR, ManR, MtlR, and YtrA) in B. subtilis were previously studied, but their TFBSs are still unknown. For these last two groups of orthologous TFs in S. aureus, we report, for the first time, the likely identity of their cognate TFBSs (see the corresponding regulon pages in the RegPrecise database [29]). For the other 21 regulons reconstructed for the Staphylococcaceae, the deduced TFBS motifs were compared to previously known motifs for orthologous regulators in B. subtilis by using the TBTBS database (48) (see Table S4 in the supplemental material).…”

Section: Resultsmentioning

confidence: 99%

“…Initial data about target genes and TF binding sites for several regulons previously described for S. aureus (AgrA, CzrA, GlnR, LacR, MntR, Fur, Zur, and PerR) were extracted from the RegTransBase database (http://regtransbase.lbl.gov/), a database of regulatory interactions based on data in the literature (20). The reconstructed regulons, including TFs, their target genes and operons, and associated TFBSs, were uploaded to the RegPrecise database (http://regprecise.lbl .gov/) (29).…”

Section: Methodsmentioning

confidence: 99%

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Inference of the Transcriptional Regulatory Network in Staphylococcus aureus by Integration of Experimental and Genomics-Based Evidence

et al. 2011

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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 ϳ320 regulatory interactions between 46 transcription factors and ϳ550 candidate target genes comprising 20% of its genome. We predicted ϳ170 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).

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Inference of the Transcriptional Regulatory Network in Staphylococcus aureus by Integration of Experimental and Genomics-Based Evidence

et al. 2011

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“…Regulons controlled by the members of NrtR family, which typically include genes involved in various aspects of NAD metabolism, have been recently described in many diverse bacteria as captured in RegPrecise data base (40). Two representatives of this family from Shewanella oneidensis and Synechocystis sp.…”

Section: Resultsmentioning

confidence: 99%

Genomics-driven Reconstruction of Acinetobacter NAD Metabolism

Sorci

Blaby

Ingeniis

et al. 2010

Journal of Biological Chemistry

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Enzymes involved in the last steps of NAD biogenesis, nicotinate mononucleotide adenylyltransferase (NadD) and NAD synthetase (NadE), are conserved and essential in most bacterial species and are established targets for antibacterial drug development. Our genomics-based reconstruction of NAD metabolism in the emerging pathogen Acinetobacter baumannii revealed unique features suggesting an alternative targeting strategy. Indeed, genomes of all analyzed Acinetobacter species do not encode NadD, which is functionally replaced by its distant homolog NadM. We combined bioinformatics with genetic and biochemical techniques to elucidate this and other important features of Acinetobacter NAD metabolism using a model (nonpathogenic) strain Acinetobacter baylyi sp. ADP1. Thus, a comparative kinetic characterization of PncA, PncB, and NadV enzymes allowed us to suggest distinct physiological roles for the two alternative, deamidating and nondeamidating, routes of nicotinamide salvage/recycling. The role of the NiaP transporter in both nicotinate and nicotinamide salvage was confirmed. The nondeamidating route was shown to be transcriptionally regulated by an ADP-ribose-responsive repressor NrtR. The NadM enzyme was shown to possess dual substrate specificity toward both nicotinate and nicotinamide mononucleotide substrates, which is consistent with its essential role in all three routes of NAD biogenesis, de novo synthesis as well as the two salvage pathways. The experimentally confirmed unconditional essentiality of nadM provided support for the choice of the respective enzyme as a drug target. In contrast, nadE, encoding a glutamine-dependent NAD synthetase, proved to be dispensable when the nondeamidating salvage pathway functioned as the only route of NAD biogenesis.Acinetobacter baumannii is an emerging pathogen that belongs to a relatively underexplored branch of ␥-proteobacteria. It can cause severe pneumonia and infections of the urinary tract, bloodstream, and other parts of the body. Some isolates of A. baumannii display resistance to many known antibiotics (1, 2), emphasizing the importance of pursuing new therapeutic targets for drug development. Biogenesis of nicotinamide adenine nucleotide (NAD), an indispensable cofactor involved in a multitude of biochemical transformations in metabolic networks of all species, was recently established as a target pathway for the development of new antibiotics (3-7). Beyond its main function as a redox cofactor, NAD is consumed as a co-substrate by a number of nonredox enzymes such as bacterial DNA ligase and protein deacetylase of the CobB/Sir2 family (8, 9). A degradative consumption of NAD by these and, likely, other (not fully elucidated) enzymes demands continuous replenishing of the NAD pool, providing further rationale for targeting essential enzymes involved in its biogenesis and recycling. Among these enzymes, nicotinate mononucleotide adenylyltransferase (NaMNAT) 4 of the NadD family and NAD synthetase of the NadE family are widely recognized as the most promising...

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“…Predicted TFBSs with phylogenetic conservation can also be used to extend or to build new PWMs. Huge datasets based on phylogenetic reconstruction were generated in various groups of bacteria (Baumbach et al, 2009;Novichkov et al, 2010;Pérez et al, 2007). Further investigetion of regulon evolution revealed the availability of a core set of genes that is widely conserved across related species and a variable set of target genes reflecting the degree of specialization (Browne et al, 2010;Dufour et al, 2010).…”

Section: Positional Preference Of Tfbssmentioning

confidence: 99%