ExtraTrain: a database of Extragenic regions and Transcriptional information in prokaryotic organisms

Pareja, Eduardo; Pareja-Tobes, Pablo; Manrique, Marina; Pareja-Tobes, Eduardo; Bonal, Javier; Tobes, Raquel

doi:10.1186/1471-2180-6-29

Cited by 50 publications

(19 citation statements)

References 18 publications

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“…One means of coupling chemical stimuli to appropriate transcriptional responses is to take advantage of ‘one-component systems’ (reviewed in [1]). T etR f amily transcriptional r egulators (TFRs) are widely distributed in bacteria and archea (reviewed in [2]) and they constitute one of the largest groups of one-component transcription factors [3]. TFRs are easily identified through the high sequence conservation in their N-terminal DNA-binding domains [2]; however, their C-terminal domains – which in many of the characterized TFRs interact with small-molecule ligands – are highly variable, suggesting that this family can respond to a diverse range of stimuli.…”

Section: Introductionmentioning

confidence: 99%

Genome Context as a Predictive Tool for Identifying Regulatory Targets of the TetR Family Transcriptional Regulators

2012

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TetR family transcriptional regulators (TFRs) are found in most bacteria and archea. Most of the family members that have been investigated to date are repressors of their target genes, and the majority of these, like the well-characterized protein TetR, regulate genes that encode transmembrane efflux pumps. In many cases repression by TFR proteins is reversed through the direct binding of a small-molecule ligand. The number of TFRs in the public database has grown rapidly as a result of genome sequencing and there are now thousands of family members; however virtually nothing is known about the biology and biochemistry they regulate. Generally applicable methods for predicting their regulatory targets would assist efforts to characterize the family. Here, we investigate chromosomal context of 372 TFRs from three Streptomyces species. We find that the majority (250 TFRs) are transcribed divergently from one neighboring gene, as is the case for TetR and its target tetA. We explore predicted target gene product identity and intergenic separation to see which either correlates with a direct regulatory relationship. While intergenic separation is a critical factor in regulatory prediction the identity of the putative target gene product is not. Our data suggest that those TFRs that are <200 bp from their divergently oriented neighbors are most likely to regulate them. These target genes include membrane proteins (26% of which 22% are probable membrane-associated pumps), enzymes (60%), other proteins such as transcriptional regulators (1%), and proteins having no predictive sequence motifs (13%). In addition to establishing a solid foundation for identifying targets for TFRs of unknown function, our analysis demonstrates a much greater diversity of TFR-regulated biochemical functions.

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Section: Introductionmentioning

confidence: 99%

Genome Context as a Predictive Tool for Identifying Regulatory Targets of the TetR Family Transcriptional Regulators

2012

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“…TFs from NtrC family are typically involved in the regulation of stress response under harsh environmental conditions promoting transcription via σ54‐mediated recruitment of RNA polymerase . The LysR family of transcriptional regulators constitutes the most abundant family of TFs found in bacteria …”

Section: Tf‐based Screening Systems For Strain Evolutionmentioning

confidence: 99%

Transcription Factor‐Based Biosensors in High‐Throughput Screening: Advances and Applications

Cheng

Tang

Kardashliev

2018

Biotechnology Journal

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The molecular mechanisms that cells use to sense changes in the intra- and extracellular environment are increasingly utilized in synthetic biology to build genetic reporter constructs for various applications. Although in nature sensing can be RNA-mediated, most existing genetically-encoded biosensors are based on transcription factors (TF) and cognate DNA sequences. Here, the recent advances in the integration of TF-based biosensors in metabolic and protein engineering screens whereas distinction is made between production-driven and competitive screening systems for enzyme evolution under physiological conditions are discussed. Furthermore, the advantages and disadvantages of existing TF-based biosensors are examined with respects to dynamic range, sensitivity, and robustness, and compared to other screening approaches. The application examples discussed in this review demonstrate the promising potential TF-based biosensors hold as screening tools in laboratory evolution of proteins and metabolic pathways, alike.

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“…Two databases collect regulatory sites: DPInteract (4), which is not longer supported, includes E.coli data, and PRODORIC (5,6) that contains data on a number of bacteria. BacTregulators (7) and ExtraTrain (8) collect computationally derived information about distribution of transcription factors in bacterial genomes. Finally, PredictRegulon (9) and TRACTOR (10) are servers for the identification of candidate sites similar to user-supplied ones (PredictRegulon) or sites from RegulonDB (TRACTOR).…”

Section: Introductionmentioning

confidence: 99%

RegTransBase--a database of regulatory sequences and interactions in a wide range of prokaryotic genomes

Kazakov

Cipriano

Novichkov

et al. 2007

Nucleic Acids Research

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RegTransBase is a manually curated database of regulatory interactions in prokaryotes that captures the knowledge in public scientific literature using a controlled vocabulary. Although several databases describing interactions between regulatory proteins and their binding sites are already being maintained, they either focus mostly on the model organisms Escherichia coli and Bacillus subtilis or are entirely computationally derived. RegTransBase describes a large number of regulatory interactions reported in many organisms and contains the following types of experimental data: the activation or repression of transcription by an identified direct regulator, determining the transcriptional regulatory function of a protein (or RNA) directly binding to DNA (RNA), mapping or prediction of a binding site for a regulatory protein and characterization of regulatory mutations. Currently, RegTransBase content is derived from about 3000 relevant articles describing over 7000 experiments in relation to 128 microbes. It contains data on the regulation of about 7500 genes and evidence for 6500 interactions with 650 regulators. RegTransBase also contains manually created position weight matrices (PWM) that can be used to identify candidate regulatory sites in over 60 species. RegTransBase is available at .

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ExtraTrain: a database of Extragenic regions and Transcriptional information in prokaryotic organisms

Cited by 50 publications

References 18 publications

Genome Context as a Predictive Tool for Identifying Regulatory Targets of the TetR Family Transcriptional Regulators

Genome Context as a Predictive Tool for Identifying Regulatory Targets of the TetR Family Transcriptional Regulators

Transcription Factor‐Based Biosensors in High‐Throughput Screening: Advances and Applications

RegTransBase--a database of regulatory sequences and interactions in a wide range of prokaryotic genomes

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