Analysis of mechanisms of activation and repression at bacterial promoters

Promoter Architecture Differences among Alphaproteobacteria and Other Bacterial Taxa

Much of our knowledge of bacterial transcription initiation has been derived from studying the promoters of Escherichia coli and Bacillus subtilis. Given the expansive diversity across the bacterial phylogeny, it is unclear how much of this knowledge can be applied to other organisms. Here, we report on bioinformatic analyses of promoter sequences of the primary σ factor (σ70) by leveraging publicly available transcription start site (TSS) sequencing data sets for nine bacterial species spanning five phyla. This analysis identifies previously unreported differences in the -35 and -10 elements of σ70-dependent promoters in several groups of bacteria. We found that Actinobacteria and Betaproteobacteria σ70-dependent promoters lack the TTG triad in their -35 element, which is predicted to be conserved across the bacterial phyla. In addition, the majority of the Alphaproteobacteria σ70-dependent promoters analyzed lacked the thymine at position -7 that is highly conserved in other phyla. Bioinformatic examination of the Alphaproteobacteria σ70-dependent promoters identifies a significant overrepresentation of essential genes and ones encoding proteins with common cellular functions downstream of promoters containing an A, C, or G at position -7. We propose that transcription of many σ70-dependent promoters in Alphaproteobacteria depends on the transcription factor CarD, which is an essential protein in several members of this phylum. Our analysis expands the knowledge of promoter architecture across the bacterial phylogeny and provides new information that can be used to engineer bacteria for use in medical, environmental, agricultural, and biotechnological processes. IMPORTANCE Transcription of DNA to RNA by RNA polymerase is essential for cells to grow, develop, and respond to stress. Understanding the process and control of transcription is important for health, disease, the environment, and biotechnology. Decades of research on a few bacteria have identified promoter DNA sequences that are recognized by the σ subunit of RNA polymerase. We used bioinformatic analyses to reveal previously unreported differences in promoter DNA sequences across the bacterial phylogeny. We found that many Actinobacteria and Betaproteobacteria promoters lack a sequence in their -35 DNA recognition element that was previously assumed to be conserved and that Alphaproteobacteria lack a thymine residue at position -7, also previously assumed to be conserved. Our work reports important new information about bacterial transcription, illustrates the benefits of studying bacteria across the phylogenetic tree, and proposes new lines of future investigation.

Mapping DNA sequence to transcription factor binding energy in vivo

Despite the central importance of transcriptional regulation in biology, it has proven difficult to determine the regulatory mechanisms of individual genes, let alone entire gene networks. It is particularly difficult to decipher the biophysical mechanisms of transcriptional regulation in living cells and determine the energetic properties of binding sites for transcription factors and RNA polymerase. In this work, we present a strategy for dissecting transcriptional regulatory sequences using in vivo methods (massively parallel reporter assays) to formulate quantitative models that map a transcription factor binding site’s DNA sequence to transcription factor-DNA binding energy. We use these models to predict the binding energies of transcription factor binding sites to within 1 k_BT of their measured values. We further explore how such a sequence-energy mapping relates to the mechanisms of trancriptional regulation in various promoter contexts. Specifically, we show that our models can be used to design specific induction responses, analyze the effects of amino acid mutations on DNA sequence preference, and determine how regulatory context affects a transcription factor’s sequence specificity.

It has been said that we live in the “genomic era,” a time where we can readily sequence full genomes at will. However, it remains difficult to interpret much of the information within a genome. This is especially true of non-coding sequences such as promoters, which contain a number of features such as transcription factor binding sites that determine how genes are regulated. There is no straightforward regulatory “code” that tells us how transcription factor binding sites are organized within a promoter. In this work we examine how DNA sequence determines one of the most important features of a promoter, the strength with which a transcription factor binds to its DNA binding site. We discuss an approach to modeling DNA sequence-specific transcription factor binding energies in vivo using a massively parellel reporter assay. We develop models that allow us to predict the binding energy between a transcription factor and a mutated version of its binding site. We then show that this modeling technique can be used to address a number of scientific and design questions, such as engineering the behavior of genetic circuit elements or examining how transcription factors and their binding sites co-evolve.

Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655

Transcriptional regulation enables cells to respond to environmental changes. Of the estimated 304 candidate transcription factors (TFs) in Escherichia coli K-12 MG1655, 185 have been experimentally identified, but ChIP methods have been used to fully characterize only a few dozen. Identifying these remaining TFs is key to improving our knowledge of the E. coli transcriptional regulatory network (TRN). Here, we developed an integrated workflow for the computational prediction and comprehensive experimental validation of TFs using a suite of genome-wide experiments. We applied this workflow to (i) identify 16 candidate TFs from over a hundred uncharacterized genes; (ii) capture a total of 255 DNA binding peaks for ten candidate TFs resulting in six high-confidence binding motifs; (iii) reconstruct the regulons of these ten TFs by determining gene expression changes upon deletion of each TF and (iv) identify the regulatory roles of three TFs (YiaJ, YdcI, and YeiE) as regulators of l-ascorbate utilization, proton transfer and acetate metabolism, and iron homeostasis under iron-limited conditions, respectively. Together, these results demonstrate how this workflow can be used to discover, characterize, and elucidate regulatory functions of uncharacterized TFs in parallel.

Systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria

Organisms must constantly make regulatory decisions in response to a change in cellular state or environment. However, while the catalog of genomes expands rapidly, we remain ignorant about how the genes in these genomes are regulated. Here, we show how a massively parallel reporter assay, Sort-Seq, and information-theoretic modeling can be used to identify regulatory sequences. We then use chromatography and mass spectrometry to identify the regulatory proteins that bind these sequences. The approach results in quantitative base pair-resolution models of promoter mechanism and was shown in both well-characterized and unannotated promoters in Escherichia coli. Given the generality of the approach, it opens up the possibility of quantitatively dissecting the mechanisms of promoter function in a wide range of bacteria.

Gene regulation is one of the most ubiquitous processes in biology. However, while the catalog of bacterial genomes continues to expand rapidly, we remain ignorant about how almost all of the genes in these genomes are regulated. At present, characterizing the molecular mechanisms by which individual regulatory sequences operate requires focused efforts using low-throughput methods. Here, we take a first step toward multipromoter dissection and show how a combination of massively parallel reporter assays, mass spectrometry, and information-theoretic modeling can be used to dissect multiple bacterial promoters in a systematic way. We show this approach on both well-studied and previously uncharacterized promoters in the enteric bacterium Escherichia coli. In all cases, we recover nucleotide-resolution models of promoter mechanism. For some promoters, including previously unannotated ones, the approach allowed us to further extract quantitative biophysical models describing input–output relationships. Given the generality of the approach presented here, it opens up the possibility of quantitatively dissecting the mechanisms of promoter function in E. coli and a wide range of other bacteria.

Two Agrobacterium tumefaciens CheW Proteins Are Incorporated into One Chemosensory Pathway with Different Efficiencies

Agrobacterium tumefaciens is the agent that causes crown gall tumor disease on more than 140 species of dicotyledonous plants. Chemotaxis of A. tumefaciens toward the wound sites of the host plant is the first step to recognize the host. CheW is a coupling protein that bridges the histidine kinase CheA and the chemoreceptors to form the chemotaxis core signaling complex and plays a crucial role in the assembly and function of the large chemosensory array. Unlike all previously reported chemotaxis systems, A. tumefaciens has only one major che operon but two cheW homologs (atu2075 as cheW₁ and atu2617 as cheW₂) on unlinked loci. The in-frame deletion of either cheW gene significantly affects A. tumefaciens chemotaxis but does not abolish the chemotaxis, unless both cheW genes were deleted. The effect of cheW₂ deletion on the chemotaxis is more severe than that of cheW₁ deletion. Either CheW can interact with CheA and couple it to the cell poles. The promoter activity of cheW₂ is always higher than that of cheW₁ under all of the tested conditions. When two cheW genes were adjusted to the same expression level by using the identical promoter, the difference between the effects of two CheW proteins on the chemotaxis still existed. Therefore, we envision that both the different molecular ratio of two CheW proteins in cell and the different affinities of two CheW proteins with CheA and chemoreceptors result in the efficiency difference of two CheW proteins in functioning in the large chemosensory array.

The Impact of Gene Silencing on Horizontal Gene Transfer and Bacterial Evolution

The H-NS family of DNA-binding proteins is the subject of intense study due to its important roles in the regulation of horizontally acquired genes critical for virulence, antibiotic resistance, and metabolism. Xenogeneic silencing proteins, typified by the H-NS protein of Escherichia coli, specifically target and downregulate expression from AT-rich genes by selectively recognizing specific structural features unique to the AT-rich minor groove. In doing so, these proteins facilitate bacterial evolution; enabling these cells to engage in horizontal gene transfer while buffering potential any detrimental fitness consequences that may result from it. Xenogeneic silencing and counter-silencing explain how bacterial cells can evolve effective gene regulatory strategies in the face of rampant gene gain and loss and it has extended our understanding of bacterial gene regulation beyond the classic operon model. Here we review the structures and mechanisms of xenogeneic silencers as well as their impact on bacterial evolution. Several H-NS-like proteins appear to play a role in facilitating gene transfer by other mechanisms including by regulating transposition, conjugation, and participating in the activation of virulence loci like the locus of enterocyte effacement pathogenicity island of pathogenic strains of E. coli. Evidence suggests that the critical determinants that dictate whether an H-NS-like protein will be a silencer or will perform a different function do not lie in the DNA-binding domain but, rather, in the domains that control oligomerization. This suggests that H-NS-like proteins are transcription factors that both recognize and alter the shape of DNA to exert specific effects that include but are not limited to gene silencing.

Comparative genomics and evolution of transcriptional regulons in Proteobacteria

Comparative genomics approaches are broadly used for analysis of transcriptional regulation in bacterial genomes. In this work, we identified binding sites and reconstructed regulons for 33 orthologous groups of transcription factors (TFs) in 196 reference genomes from 21 taxonomic groups of Proteobacteria. Overall, we predict over 10 600 TF binding sites and identified more than 15 600 target genes for 1896 TFs constituting the studied orthologous groups of regulators. These include a set of orthologues for 21 metabolism-associated TFs from Escherichia coli and/or Shewanella that are conserved in five or more taxonomic groups and several additional TFs that represent non-orthologous substitutions of the metabolic regulators in some lineages of Proteobacteria. By comparing gene contents of the reconstructed regulons, we identified the core, taxonomy-specific and genome-specific TF regulon members and classified them by their metabolic functions. Detailed analysis of ArgR, TyrR, TrpR, HutC, HypR and other amino-acid-specific regulons demonstrated remarkable differences in regulatory strategies used by various lineages of Proteobacteria. The obtained genomic collection of in silico reconstructed TF regulons contains a large number of new regulatory interactions that await future experimental validation. The collection provides a framework for future evolutionary studies of transcriptional regulatory networks in Bacteria. It can be also used for functional annotation of putative metabolic transporters and enzymes that are abundant in the reconstructed regulons.

A Bayesian inference method for the analysis of transcriptional regulatory networks in metagenomic data

Background

Metagenomics enables the analysis of bacterial population composition and the study of emergent population features, such as shared metabolic pathways. Recently, we have shown that metagenomics datasets can be leveraged to characterize population-wide transcriptional regulatory networks, or meta-regulons, providing insights into how bacterial populations respond collectively to specific triggers. Here we formalize a Bayesian inference framework to analyze the composition of transcriptional regulatory networks in metagenomes by determining the probability of regulation of orthologous gene sequences. We assess the performance of this approach on synthetic datasets and we validate it by analyzing the copper-homeostasis network of Firmicutes species in the human gut microbiome.

Results

Assessment on synthetic datasets shows that our method provides a robust and interpretable metric for assessing putative regulation by a transcription factor on sets of promoter sequences mapping to an orthologous gene cluster. The inference framework integrates the regulatory contribution of secondary sites and can discern false positives arising from multiple instances of a clonal sequence. Posterior probabilities for orthologous gene clusters decline sharply when less than 20 % of mapped promoters have binding sites, but we introduce a sensitivity adjustment procedure to speed up computation that enhances regulation assessment in heterogeneous ortholog clusters. Analysis of the copper-homeostasis regulon governed by CsoR in the human gut microbiome Firmicutes reveals that CsoR controls itself and copper-translocating P-type ATPases, but not CopZ-type copper chaperones. Our analysis also indicates that CsoR frequently targets promoters with dual CsoR-binding sites, suggesting that it exploits higher-order binding conformations to fine-tune its activity.

Conclusions

We introduce and validate a method for the analysis of transcriptional regulatory networks from metagenomic data that enables inference of meta-regulons in a systematic and interpretable way. Validation of this method on the CsoR meta-regulon of gut microbiome Firmicutes illustrates the usefulness of the approach, revealing novel properties of the copper-homeostasis network in poorly characterized bacterial species and putting forward evidence of new mechanisms of DNA binding for this transcriptional regulator. Our approach will enable the comparative analysis of regulatory networks across metagenomes, yielding novel insights into the evolution of transcriptional regulatory networks.

Electronic supplementary material

The online version of this article (doi:10.1186/s13015-016-0082-8) contains supplementary material, which is available to authorized users.

Transcriptional analysis of the MrpJ network: modulation of diverse virulence-associated genes and direct regulation of mrp fimbrial and flhDC flagellar operons in Proteus mirabilis

The enteric bacterium Proteus mirabilis is associated with a significant number of catheter-associated urinary tract infections (UTIs). Strict regulation of the antagonistic processes of adhesion and motility, mediated by fimbriae and flagella, respectively, is essential for disease progression. Previously, the transcriptional regulator MrpJ, which is encoded by the mrp fimbrial operon, has been shown to repress both swimming and swarming motility. Here we show that MrpJ affects an array of cellular processes beyond adherence and motility. Microarray analysis found that expression of mrpJ mimicking levels observed during UTIs leads to differential expression of 217 genes related to, among other functions, bacterial virulence, type VI secretion, and metabolism. We probed the molecular mechanism of transcriptional regulation by MrpJ using transcriptional reporters and chromatin immunoprecipitation (ChIP). Binding of MrpJ to two virulence-associated target gene promoters, the promoters of the flagellar master regulator flhDC and mrp itself, appears to be affected by the condensation state of the native chromosome, although both targets share a direct MrpJ binding site proximal to the transcriptional start. Furthermore, an mrpJ deletion mutant colonized the bladders of mice at significantly lower levels in a transurethral model of infection. Additionally, we observed that mrpJ is widely conserved in a collection of recent clinical isolates. Altogether, these findings support a role of MrpJ as a global regulator of P. mirabilis virulence.

Informational requirements for transcriptional regulation

Transcription factors (TFs) regulate transcription by binding to specific sites in promoter regions. Information theory provides a useful mathematical framework to analyze the binding motifs associated with TFs but imposes several assumptions that limit their applicability to specific regulatory scenarios. Explicit simulations of the co-evolution of TFs and their binding motifs allow the study of the evolution of regulatory networks with a high degree of realism. In this work we analyze the impact of differential regulatory demands on the information content of TF-binding motifs by means of evolutionary simulations. We generalize a predictive index based on information theory, and we validate its applicability to regulatory scenarios in which the TF binds significantly to the genomic background. Our results show a logarithmic dependence of the evolved information content on the occupancy of target sites and indicate that TFs may actively exploit pseudo-sites to modulate their occupancy of target sites. In regulatory networks with differentially regulated targets, we observe that information content in TF-binding motifs is dictated primarily by the fraction of total probability mass that the TF assigns to its target sites, and we provide a predictive index to estimate the amount of information associated with arbitrarily complex regulatory systems. We observe that complex regulatory patterns can exert additional demands on evolved information content, but, given a total occupancy for target sites, we do not find conclusive evidence that this effect is because of the range of required binding affinities.

Genomic reconstruction of the transcriptional regulatory network in Bacillus subtilis

The adaptation of microorganisms to their environment is controlled by complex transcriptional regulatory networks (TRNs), which are still only partially understood even for model species. Genome scale annotation of regulatory features of genes and TRN reconstruction are challenging tasks of microbial genomics. We used the knowledge-driven comparative-genomics approach implemented in the RegPredict Web server to infer TRN in the model Gram-positive bacterium Bacillus subtilis and 10 related Bacillales species. For transcription factor (TF) regulons, we combined the available information from the DBTBS database and the literature with bioinformatics tools, allowing inference of TF binding sites (TFBSs), comparative analysis of the genomic context of predicted TFBSs, functional assignment of target genes, and effector prediction. For RNA regulons, we used known RNA regulatory motifs collected in the Rfam database to scan genomes and analyze the genomic context of new RNA sites. The inferred TRN in B. subtilis comprises regulons for 129 TFs and 24 regulatory RNA families. First, we analyzed 66 TF regulons with previously known TFBSs in B. subtilis and projected them to other Bacillales genomes, resulting in refinement of TFBS motifs and identification of novel regulon members. Second, we inferred motifs and described regulons for 28 experimentally studied TFs with previously unknown TFBSs. Third, we discovered novel motifs and reconstructed regulons for 36 previously uncharacterized TFs. The inferred collection of regulons is available in the RegPrecise database (http://regprecise.lbl.gov/) and can be used in genetic experiments, metabolic modeling, and evolutionary analysis.

Inference of self-regulated transcriptional networks by comparative genomics

The assumption of basic properties, like self-regulation, in simple transcriptional regulatory networks can be exploited to infer regulatory motifs from the growing amounts of genomic and meta-genomic data. These motifs can in principle be used to elucidate the nature and scope of transcriptional networks through comparative genomics. Here we assess the feasibility of this approach using the SOS regulatory network of Gram-positive bacteria as a test case. Using experimentally validated data, we show that the known regulatory motif can be inferred through the assumption of self-regulation. Furthermore, the inferred motif provides a more robust search pattern for comparative genomics than the experimental motifs defined in reference organisms. We take advantage of this robustness to generate a functional map of the SOS response in Gram-positive bacteria. Our results reveal definite differences in the composition of the LexA regulon between Firmicutes and Actinobacteria, and confirm that regulation of cell-division inhibition is a widespread characteristic of this network among Gram-positive bacteria.

Transcription activation by the siderophore sensor Btr is mediated by ligand-dependent stimulation of promoter clearance

Bacterial transcription factors often function as DNA-binding proteins that selectively activate or repress promoters, although the biochemical mechanisms vary. In most well-understood examples, activators function by either increasing the affinity of RNA polymerase (RNAP) for the target promoter, or by increasing the isomerization of the initial closed complex to the open complex. We report that Bacillus subtilis Btr, a member of the AraC family of activators, functions principally as a ligand-dependent activator of promoter clearance. In the presence of its co-activator, the siderophore bacillibactin (BB), the Btr:BB complex enhances productive transcription, while having only modest effects on either RNAP promoter association or the production of abortive transcripts. Btr binds to two direct repeat sequences adjacent to the −35 region; recognition of the downstream motif is most important for establishing a productive interaction between the Btr:BB complex and RNAP. The resulting Btr:BB dependent increase in transcription enables the production of the ferric-BB importer to be activated by the presence of its cognate substrate.

Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

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.

Novel plasmid-based genetic tools for the study of promoters and terminators in Streptococcus pneumoniae and Enterococcus faecalis

Promoter-probe and terminator-probe plasmid vectors make possible to rapidly examine whether particular sequences function as promoter or terminator signals in various genetic backgrounds and under diverse environmental stimuli. At present, such plasmid-based genetic tools are very scarce in the Gram-positive pathogenic bacteria Streptococcus pneumoniae and Enterococcus faecalis. Hence, we developed novel promoter-probe and terminator-probe vectors based on the Streptococcus agalactiae pMV158 plasmid, which replicates autonomously in numerous Gram-positive bacteria. As reporter gene, a gfp allele encoding a variant of the green fluorescent protein was used. These genetic tools were shown to be suitable to assess the activity of promoters and terminators (both homologous and heterologous) in S. pneumoniae and E. faecalis. In addition, the promoter-probe vector was shown to be a valuable tool for the analysis of regulated promoters in vivo, such as the promoter of the pneumococcal fuculose kinase gene. These new plasmid vectors will be very useful for the experimental verification of predicted promoter and terminator sequences, as well as for the construction of new inducible-expression vectors. Given the promiscuity exhibited by the pMV158 replicon, these vectors could be used in a variety of Gram-positive bacteria.

Protein-protein interactions between sigma(70) region 4 of RNA polymerase and Escherichia coli SoxS, a transcription activator that functions by the prerecruitment mechanism: evidence for "off-DNA" and "on-DNA" interactions

According to the prerecruitment hypothesis, Escherichia coli SoxS activates the transcription of the genes of the SoxRS regulon by forming binary complexes with RNA polymerase (RNAP) that scan the chromosome for class I and class II SoxS-dependent promoters. We showed previously that the alpha subunit's C-terminal domain plays a role in activating both classes of promoter by making protein-protein contacts with SoxS; some of these contacts are made in solution in the absence of promoter DNA, a critical prediction of the prerecruitment hypothesis. Here, we identified seven single-alanine substitutions of the region 4 of sigma(70) (sigma(70) R4) of RNAP that reduce SoxS activation of class II promoters. With genetic epistasis tests between these sigma(70) R4 mutants and positive control mutants of SoxS, we identified 10 pairs of amino acids that interact with each other in E. coli. Using the yeast two-hybrid system and affinity immobilization assays, we showed that SoxS and sigma(70) R4 can interact in solution (i.e., "off-DNA"). The interaction requires amino acids of the class I/II (but not the class II) positive control surface of SoxS, and five amino acids of sigma(70) R4 that reduce activation in E. coli also reduce the SoxS-sigma(70) R4 interaction in yeast. One of the epistatic interactions that occur in E. coli also occurs in the yeast two-hybrid system (i.e., off-DNA). Importantly, we infer that the five epistatic interactions occurring in E. coli that require an amino acid of the class II surface occur "on-DNA" at class II promoters. Finding that SoxS contacts sigma(70) R4 both off-DNA and on-DNA is consistent with the prerecruitment hypothesis. Moreover, SoxS is now the first example of an E. coli transcriptional activator that uses a single positive control surface to make specific protein-protein contacts with two different subunits of RNAP.

How transcription factors can adjust the gene expression floodgates

The rate of transcription initiation is the main level of quantitative control of gene expression, primarily responsible for the accumulation of mRNAs in the cell. Many, if not all, molecular actors involved in transcription initiation are known but the mechanisms underlying the frequency of initiations, remain elusive. To make the connection between transcription factors and the frequency of transcription initiation, intricated aspects of this complex activity are classified i) depending on whether or not the DNA-bound transcription factors directly activate the commitment to transcription and ii) on the destructive or non-destructive effect of transcription initiation on the stability of promoter complexes. Two possible sources of synergy allowing the combinatorial specificity of transcription factors action are compared, for binding to DNA and for recruiting transcription machineries. Tentative formulations are proposed to discriminate the different micro-reversible modes of DNA binding cooperativity modulating the specificity and dosage of transcription initiation.

DNA sampling: a method for probing protein binding at specific loci on bacterial chromosomes

We describe a protocol, DNA sampling, for the rapid isolation of specific segments of DNA, together with bound proteins, from Escherichia coli K-12. The DNA to be sampled is generated as a discrete fragment within cells by the yeast I-SceI meganuclease, and is purified using FLAG-tagged LacI repressor and beads carrying anti-FLAG antibody. We illustrate the method by investigating the proteins bound to the colicin K gene regulatory region, either before or after induction of the colicin K gene promoter.