Discovery of DNA operators for TetR and MarR family transcription factors from Burkholderia xenovorans (original) (raw)
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DNA binding site analysis of Burkholderia thailandensis response regulators
Journal of Microbiological Methods, 2012
Promoter binding site Burkholderia Two component systems Gene regulation 25 Bacterial response regulator (RR) that functions as a transcription factor in two-component signaling path-26 ways is crucial for ensuring tight regulation and coordinated expression of the genome. Currently, consensus 27 DNA binding sites in the promoter for very few bacterial RRs have been identified. A systematic method to 28 characterize these DNA binding sites for RRs would enable prediction of specific gene expression patterns 29 in response to extracellular stimuli. To identify RR DNA binding sites, we functionally activated RRs using ber-30 yllofluoride and applied them to protein-binding microarray (PBM) to discover DNA binding motifs for RRs 31 expressed in Burkholderia, a Gram-negative bacterial genus. We identified DNA binding motifs for conserved 32 RRs in Burkholderia thailandensis, including KdpE, RisA, and NarL, as well as for a previously uncharacterized 33 RR at locus BTH_II2335 and its ortholog in the human pathogen Q6 Burkholderia pseudomallei at locus BPSS2315. 34 We further demonstrate RR binding of predicted genomic targets for the two orthologs using gel shift assays 35 and reveal a pattern of RR regulation of expression of self and other two component systems. Our studies il-36 lustrate the use of PBMs to identify DNA binding specificities for bacterial RRs and enable prediction of gene 37 regulatory networks in response to two component signaling. 38 Published by Elsevier B.V. 39 40 65 tem that scavenges K + to maintain ionic homeostasis in the cell 66 (Gasell and Altendorf, 2001). 67 The rapid sequencing of bacterial genomes in the last several years 68 has revealed a diversity of RRs with undefined regulatory functions. 69 From 1123 distinct bacterial genomes,~39,000 two-component pro-70 teins adjacent in the genome have been identified (Ulrich and 71 Zhulin, 2010). The majority of RRs with DNA binding capability fall 72 into three major families based on the structural similarity of their ef-73 fector domains, (1) OmpR/PhoB family, winged helix-turn-helix motif 74 (Kenney, 2002), (2) NarL family, helix-turn-helix motif (Baikalov et 75 al., 1996), and (3) NtrC family, ATPase domain (Yang et al., 2004). Al-76 though the target genes of some RRs can be predicted based on geno-77 mic organization, such as KdpE control of kdpFABC, RRs can regulate 78 multiple target genes scattered throughout a bacterial genome. The 79 completion of sequenced bacterial genomes has enabled bioinformat-80 ics searches using consensus sequence motifs to predict DNA binding 81 sites for specific RRs. Thus far, experimental confirmation of DNA 82 binding sites for RRs has been limited. Aside from KdpE, DNA binding 83 sites have been determined for the Q7 Escherichia coli RRs OmpR (Pratt 84
Microbiology and Molecular Biology Reviews
SUMMARY Species within the genus Burkholderia exhibit remarkable phenotypic diversity. Genomic plasticity, including genome reduction and horizontal gene transfer, has been correlated with virulence traits in several species. However, the conservation of virulence genes in species otherwise considered to have limited potential for infection suggests that phenotypic diversity may not be explained solely on the basis of genetic diversity. Instead, differential organization and control of gene regulatory networks may underlie many phenotypic differences. In this review, we evaluate how regulation of gene expression by members of the multiple antibiotic resistance regulator (MarR) family of transcription factors may contribute to shaping the physiological diversity of Burkholderia species, with a focus on the clinically relevant human pathogens. All Burkholderia species encode a relatively large number of MarR proteins, a feature common to bacteria that must respond to environmental cha...
The Condition-Dependent Transcriptional Landscape of Burkholderia pseudomallei
PLoS Genetics, 2013
Burkholderia pseudomallei (Bp), the causative agent of the often-deadly infectious disease melioidosis, contains one of the largest prokaryotic genomes sequenced to date, at 7.2 Mb with two large circular chromosomes (1 and 2). To comprehensively delineate the Bp transcriptome, we integrated whole-genome tiling array expression data of Bp exposed to .80 diverse physical, chemical, and biological conditions. Our results provide direct experimental support for the strandspecific expression of 5,467 Sanger protein-coding genes, 1,041 operons, and 766 non-coding RNAs. A large proportion of these transcripts displayed condition-dependent expression, consistent with them playing functional roles. The two Bp chromosomes exhibited dramatically different transcriptional landscapes-Chr 1 genes were highly and constitutively expressed, while Chr 2 genes exhibited mosaic expression where distinct subsets were expressed in a strongly conditiondependent manner. We identified dozens of cis-regulatory motifs associated with specific condition-dependent expression programs, and used the condition compendium to elucidate key biological processes associated with two complex pathogen phenotypes-quorum sensing and in vivo infection. Our results demonstrate the utility of a Bp conditioncompendium as a community resource for biological discovery. Moreover, the observation that significant portions of the Bp virulence machinery can be activated by specific in vitro cues provides insights into Bp's capacity as an ''accidental pathogen'', where genetic pathways used by the bacterium to survive in environmental niches may have also facilitated its ability to colonize human hosts.
BMC genomics, 2014
The clustering of genes in a pathway and the co-location of functionally related genes is widely recognized in prokaryotes. We used these characteristics to predict the metabolic involvement for a Transcriptional Regulator (TR) of unknown function, identified and confirmed its biological activity. A software tool that identifies the genes encoded within a defined genomic neighborhood for the subject TR and its homologs was developed. The output lists of genes in the genetic neighborhoods, their annotated functions, the reactants/products, and identifies the metabolic pathway in which the encoded-proteins function. When a set of TRs of known function was analyzed, we observed that their homologs frequently had conserved genomic neighborhoods that co-located the metabolically related genes regulated by the subject TR. We postulate that TR effectors are metabolites in the identified pathways; indeed the known effectors were present. We analyzed Bxe_B3018 from Burkholderia xenovorans, a...
Applied Microbiology and Biotechnology, 2009
TfdT is a LysR-type transcriptional regulator that activates the transcription of the 2 chlorocatechol degradative gene operon tfdCDEF of the chlorobenzoate-degrading bacterium 3 Burkholderia sp. NK8. To identify the amino acids involved in the effector recognition by TfdT, a 4 polymerase-chain-reaction-based random mutagenesis protocol was applied to introduce mutations 5 into the tfdT gene. Nine types of TfdT mutant bearing a single-amino-acid substitution at positions, 6
Bioinformatics, 2010
Motivation: Computational techniques for microbial genomic sequence analysis are becoming increasingly important. With nextgeneration sequencing technology and the human microbiome project underway, current sequencing capacity is significantly greater than the speed at which organisms of interest can be studied experimentally. Most related computational work has been focused on sequence assembly, gene annotation and metabolic network reconstruction. We have developed a method that will primarily use available sequence data in order to determine prokaryotic transcription factor (TF) binding specificities. Results: Specificity determining residues (critical residues) were identified from crystal structures of DNA-protein complexes and TFs with the same critical residues were grouped into specificity classes. The putative binding regions for each class were defined as the set of promoters for each TF itself (autoregulatory) and the immediately upstream and downstream operons. MEME was used to find putative motifs within each separate class. Tests on the LacI and TetR TF families, using RegulonDB annotated sites, showed the sensitivity of prediction 86% and 80%, respectively.
PLOS ONE, 2020
DNA-binding Transcription Factors (TFs) play a central role in regulation of gene expression in prokaryotic organisms, and similarities at the sequence level have been reported. These proteins are predicted with different abundances as a consequence of genome size, where small organisms contain a low proportion of TFs and large genomes contain a high proportion of TFs. In this work, we analyzed a collection of 668 experimentally validated TFs across 30 different species from diverse taxonomical classes, including Escherichia coli K-12, Bacillus subtilis 168, Corynebacterium glutamicum, and Streptomyces coelicolor, among others. This collection of TFs, together with 111 hidden Markov model profiles associated with DNA-binding TFs collected from diverse databases such as PFAM and DBD, was used to identify the repertoire of proteins putatively devoted to gene regulation in 1321 representative genomes of Archaea and Bacteria. The predicted regulatory proteins were posteriorly analyzed in terms of their genomic context, allowing the prediction of functions for TFs and their neighbor genes, such as genes involved in virulence, enzymatic functions, phosphorylation mechanisms, and antibiotic resistance. The functional analysis associated with PFAM groups showed diverse functional categories were significantly enriched in the collection of TFs and the proteins encoded by the neighbor genes, in particular, small-molecule binding and amino acid transmembrane transporter activities associated with the LysR family and proteins devoted to cellular aromatic compound metabolic processes or responses to drugs, stress, or abiotic stimuli in the MarR family. We consider that with the increasing data derived from new technologies, novel TFs can be identified and help improve the predictions for this class of proteins in complete genomes. The complete collection of experimentally characterized and predicted TFs is available at http://web.pcyt.unam.mx/EntrafDB/.
Plant Journal, 2011
Transcriptional regulation depends on the specificity of transcription factors (TFs) recognizing cis regulatory sequences in the promoters of target genes. Current knowledge about DNA-binding specificities of TFs is based mostly on low-to medium-throughput methodologies, revealing DNA motifs bound by a TF with high affinity. These strategies are time-consuming and often fail to identify DNA motifs recognized by a TF with lower affinity but retaining biological relevance. Here we report on the development of a protein-binding microarray (PBM11) containing all possible double-stranded 11-mers for the determination of DNA-binding specificities of TFs. The large number of sequences in the PBM11 allows accurate and high-throughput quantification of TF-binding sites, outperforming previous methods. We applied this tool to determine binding site specificities of two Arabidopsis TFs, MYC2 and ERF1, rendering the G-box and the GCC-box, respectively, as their highest-affinity binding sites. In addition, we identified variants of the G-box recognized by MYC2 with high and medium affinity, whereas ERF1 only recognized GCC variants with low affinity, indicating that ERF1 binding to DNA has stricter base requirements than MYC2. Analysis of transcriptomic data revealed that high-and medium-affinity binding sites have biological significance, probably representing relevant cis-acting elements in vivo. Comparison of promoter sequences with putative orthologs from closely related species demonstrated a high degree of conservation of all the identified DNA elements. The combination of PBM11, transcriptomic data and phylogenomic footprinting provides a straightforward method for the prediction of biologically active cis-elements, and thus for identification of in vivo DNA targets of TFs.