The non-inducible nature of super-repressors of the gal operon in Escherichia coli

Molecular insights into effector binding by DgoR, a GntR/FadR family transcriptional repressor of D-galactonate metabolism in Escherichia coli

Several GntR/FadR transcriptional regulators govern sugar acid metabolism in bacteria. Although effectors have been identified for a few sugar acid regulators, the mode of effector binding is unknown. Even in the overall FadR subfamily, there are limited details on effector-regulator interactions. Here, we identified the effector-binding cavity in Escherichia coli DgoR, a FadR subfamily transcriptional repressor of D-galactonate metabolism that employs D-galactonate as its effector. Using a genetic screen, we isolated several dgoR superrepressor alleles. Blind docking suggested eight amino acids corresponding to these alleles to form a part of the effector-binding cavity. In vivo and in vitro assays showed that these mutations compromise the inducibility of DgoR without affecting its oligomeric status or affinity for target DNA. Taking Bacillus subtilis GntR as a representative, we demonstrated that the effector-binding cavity is similar among FadR subfamily sugar acid regulators. Finally, a comparison of sugar acid regulators with other FadR members suggested conserved features of effector-regulator recognition within the FadR subfamily. Sugar acid metabolism is widely implicated in bacterial colonization and virulence. The present study sets the basis to investigate the influence of natural genetic variations in FadR subfamily regulators on their sensitivity to sugar acids and ultimately on host-bacterial interactions.

Data on publications, structural analyses, and queries used to build and utilize the AlloRep database

The AlloRep database (www.AlloRep.org) (Sousa et al., 2016) [1] compiles extensive sequence, mutagenesis, and structural information for the LacI/GalR family of transcription regulators. Sequence alignments are presented for >3000 proteins in 45 paralog subfamilies and as a subsampled alignment of the whole family. Phenotypic and biochemical data on almost 6000 mutants have been compiled from an exhaustive search of the literature; citations for these data are included herein. These data include information about oligomerization state, stability, DNA binding and allosteric regulation. Protein structural data for 65 proteins are presented as easily-accessible, residue-contact networks. Finally, this article includes example queries to enable the use of the AlloRep database. See the related article, “AlloRep: a repository of sequence, structural and mutagenesis data for the LacI/GalR transcription regulators” (Sousa et al., 2016) [1].

The transcriptional regulator GalR self-assembles to form highly regular tubular structures

The Gal repressor regulates transport and metabolism of D-galactose in Escherichia coli and can mediate DNA loop formation by forming a bridge between adjacent or distant sites. GalR forms insoluble aggregates at lower salt concentrations in vitro, which can be solubilized at higher salt concentrations. Here, we investigate the assembly and disassembly of GalR aggregates. We find that a sharp transition from aggregates to soluble species occurs between 200 and 400 mM NaCl, incompatible with a simple salting-in effect. The aggregates are highly ordered rod-like structures, highlighting a remarkable ability for organized self-assembly. Mutant studies reveal that aggregation is dependent on two separate interfaces of GalR. The highly ordered structures dissociate to smaller aggregates in the presence of D-galactose. We propose that these self-assembled structures may constitute galactose-tolerant polymers for chromosome compaction in stationary phase cells, in effect linking self-assembly with regulatory function.

Mutations in transcriptional regulators allow selective engineering of signal integration logic

Bacterial cells monitor their environment by sensing a set of signals. Typically, these environmental signals affect promoter activities by altering the activity of transcription regulatory proteins. Promoters are often regulated by more than one regulatory protein, and in these cases the relevant signals are integrated by certain logic. In this work, we study how single amino acid substitutions in a regulatory protein (GalR) affect transcriptional regulation and signal integration logic at a set of engineered promoters. Our results suggest that point mutations in regulatory genes allow independent evolution of regulatory logic at different promoters.

IMPORTANCE

Gene regulatory networks are built from simple building blocks, such as promoters, transcription regulatory proteins, and their binding sites on DNA. Many promoters are regulated by more than one regulatory input. In these cases, the inputs are integrated and allow transcription only in certain combinations of input signals. Gene regulatory networks can be easily rewired, because the function of cis-regulatory elements and promoters can be altered by point mutations. In this work, we tested how point mutations in transcription regulatory proteins can affect signal integration logic. We found that such mutations allow context-dependent engineering of signal integration logic at promoters, further contributing to the plasticity of gene regulatory networks.

Allostery in the LacI/GalR family: variations on a theme

The lactose repressor protein (LacI) was among the very first genetic regulatory proteins discovered, and more than 1000 members of the bacterial LacI/GalR family are now identified. LacI has been the prototype for understanding how transcription is controlled using small metabolites to modulate protein association with specific DNA sites. This understanding has been greatly expanded by the study of other LacI/GalR homologues. A general picture emerges in which the conserved fold provides a scaffold for multiple types of interactions - including oligomerization, small molecule binding, and protein-protein binding - that in turn influence target DNA binding and thereby regulate mRNA production. Although many different functions have evolved from this basic scaffold, each homologue retains functional flexibility: For the same protein, different small molecules can have disparate impact on DNA binding and hence transcriptional outcome. In turn, binding to alternative DNA sequences may impact the degree of allosteric response. Thus, this family exhibits a symphony of variations by which transcriptional control is achieved.

Experimental identification of specificity determinants in the domain linker of a LacI/GalR protein: bioinformatics-based predictions generate true positives and false negatives

In protein families, conserved residues often contribute to a common general function, such as DNA-binding. However, unique attributes for each homolog (e.g. recognition of alternative DNA sequences) must arise from variation in other functionally-important positions. The locations of these "specificity determinant" positions are obscured amongst the background of varied residues that do not make significant contributions to either structure or function. To isolate specificity determinants, a number of bioinformatics algorithms have been developed. When applied to the LacI/GalR family of transcription regulators, several specificity determinants are predicted in the 18 amino acids that link the DNA-binding and regulatory domains. However, results from alternative algorithms are only in partial agreement with each other. Here, we experimentally evaluate these predictions using an engineered repressor comprising the LacI DNA-binding domain, the LacI linker, and the GalR regulatory domain (LLhG). "Wild-type" LLhG has altered DNA specificity and weaker lacO(1) repression compared to LacI or a similar LacI:PurR chimera. Next, predictions of linker specificity determinants were tested, using amino acid substitution and in vivo repression assays to assess functional change. In LLhG, all predicted sites are specificity determinants, as well as three sites not predicted by any algorithm. Strategies are suggested for diminishing the number of false negative predictions. Finally, individual substitutions at LLhG specificity determinants exhibited a broad range of functional changes that are not predicted by bioinformatics algorithms. Results suggest that some variants have altered affinity for DNA, some have altered allosteric response, and some appear to have changed specificity for alternative DNA ligands.

Three-stage Regulation of the Amphibolic gal Operon: From Repressosome to GalR-free DNA

The gal operon of Escherichia coli is negatively regulated by the Gal repressosome, a higher order nucleoprotein complex containing a DNA loop that encompasses two gal promoters. In the repressosome structure, Gal repressor (GalR) dimers are bound to the two operator sites, flanking the promoter region, thus generating a DNA loop. The DNA loop is stabilized by binding of the architectural HU protein to the apex of the loop, and negative supercoiling. The gal promoters are also regulated in opposite directions by GalR without DNA looping. The repressosome-mediated as well as looping-independent transcription regulation of the two promoters is lifted in the presence of the inducer D-galactose. We tested the effect of D-galactose on various DNA-protein and protein-protein interactions of different regulatory complexes and on transcription repression in vitro. We found that the inducer breaks up the repressosome with clear intermediates in a concentration-dependent manner. The sequential disassembly generates different stages of regulation of the gal operon. The D-galactose-dependent switch from one stage of regulation to another satisfies the amphibolic requirement of the gal operon.

Monomer and dimer of Chandipura virus unphosphorylated P-protein binds leader RNA differently: implications for viral RNA synthesis

Interaction of the leader RNA with the unphosphorylated P-protein has been proposed to play a key role in the transcription-replication transition of Chandipura virus, a model rhabdovirus. Electrophoretic mobility shift assay with the leader RNA and the unphosphorylated P-protein demonstrated existence of two distinct complexes in vitro. Measurements of stoichiometry indicate the protein monomer/RNA ratio to be 1:1 and 2:1 for faster and slower migrating bands, respectively. We have also observed a concentration-dependent oligomerization of the unphosphorylated P-protein, in sub-micromolar to low micromolar range. Sedimentation velocity, dynamic light scattering and large zone gel filtration experiments suggest a monomer-dimer-tetramer model of association. RNA binding experiments suggest that the two complexes assembled from one molecule of the leader RNA binding to either a protein monomer or a dimer. A truncated RNA consisting of a 3' region of the leader transcript exclusively formed the 1:1 complex, whereas a RNA consisting of only the 5' region forms the 2:1 complex exclusively. RNA binding experiments at different protein concentrations suggest that binding of the RNA comprising the 3' region weakens significantly at higher P(0) concentrations, whereas in contrast the binding of the RNA comprising the 5' region becomes modestly tighter. Implications of two different types of leader RNA-P-protein complexes in viral RNA synthesis are discussed.

Linkage map of Escherichia coli K-12, edition 10: the traditional map

This map is an update of the edition 9 map by Berlyn et al. (M. K. B. Berlyn, K. B. Low, and K. E. Rudd, p. 1715-1902, in F. C. Neidhardt et al., ed., Escherichia coli and Salmonella: cellular and molecular biology, 2nd ed., vol. 2, 1996). It uses coordinates established by the completed sequence, expressed as 100 minutes for the entire circular map, and adds new genes discovered and established since 1996 and eliminates those shown to correspond to other known genes. The latter are included as synonyms. An alphabetical list of genes showing map location, synonyms, the protein or RNA product of the gene, phenotypes of mutants, and reference citations is provided. In addition to genes known to correspond to gene sequences, other genes, often older, that are described by phenotype and older mapping techniques and that have not been correlated with sequences are included.

Interaction of Gal repressor with inducer and operator: induction of gal transcription from repressor-bound DNA

Gal repressor inhibits transcription from the gal promoter (P1) when it binds to the cognate operator (O(E)). The repression is relieved by the presence of the inducer D-galactose. Compared with its interaction with free repressor, D-galactose binds to the repressor-operator complex with 10-fold reduced affinity as determined by fluorescence enhancement measurements. Thermodynamic analysis and fluorescence anisotropy showed that the stability of the repressor-operator complex is reduced by only 7-fold by the presence of the inducer in the complex. The formation of the inducer-repressor-operator ternary complex has been confirmed by CD spectral analysis. Fluorescence spectroscopy and energy transfer experiments suggest that individual allosteric effects of the two ligands, inducer and operator, on Gal repressor are responsible for the slightly weakened stability of the ternary complex compared with the stability of the inducer-repressor and repressor-operator complexes. In vitro transcription results demonstrated full derepression of transcription of the P1 promoter under conditions in which the concentrations of the inducer-repressor binary complex are severalfold higher than the dissociation constant of the inducer-repressor-operator ternary complex into inducer-repressor and free DNA. These results strongly suggest that the inducer binding to the repressor-operator complex does not lead to dissociation of the repressor from the operator during transcription induction. Because Gal repressor inhibits transcription by modulating the alpha subunit of the P1-bound RNA polymerase, we conclude that the inducer binding to the operator-bound repressor only allosterically relieves the inhibitory effect of repressor on RNA polymerase without dissociating the repressor from DNA.