Changing the mechanism of transcriptional activation by phage lambda repressor

Structure and molecular mechanism of bacterial transcription activation

Transcription activation is an important checkpoint of regulation of gene expression which occurs in response to different intracellular and extracellular signals. The key elements in this signal transduction process are transcription activators, which determine when and how gene expression is activated. Recent structural studies on a considerable number of new transcription activation complexes (TACs) revealed the remarkable mechanistic diversity of transcription activation mediated by different factors, necessitating a review and re-evaluation of the transcription activation mechanisms. In this review, we present a comprehensive summary of transcription activation mechanisms and propose a new, elaborate, and systematic classification of transcription activation mechanisms, primarily based on the structural features of diverse TAC components.

Quantifying the regulatory role of individual transcription factors in Escherichia coli

Gene regulation often results from the action of multiple transcription factors (TFs) acting at a promoter, obscuring the individual regulatory effect of each TF on RNA polymerase (RNAP). Here we measure the fundamental regulatory interactions of TFs in E. coli by designing synthetic target genes that isolate individual TFs' regulatory effects. Using a thermodynamic model, each TF's regulatory interactions are decoupled from TF occupancy and interpreted as acting through (de)stabilization of RNAP and (de)acceleration of transcription initiation. We find that the contribution of each mechanism depends on TF identity and binding location; regulation immediately downstream of the promoter is insensitive to TF identity, but the same TFs regulate by distinct mechanisms upstream of the promoter. These two mechanisms are uncoupled and can act coherently, to reinforce the observed regulatory role (activation/repression), or incoherently, wherein the TF regulates two distinct steps with opposing effects.

Aspects of protein-DNA interactions: a review of quantitative thermodynamic theory for modelling synthetic circuits utilising LacI and CI repressors, IPTG and the reporter gene lacZ

Protein-DNA interactions are central to the control of gene expression across all forms of life. The development of approaches to rigorously model such interactions has often been hindered both by a lack of quantitative binding data and by the difficulty in accounting for parameters relevant to the intracellular situation, such as DNA looping and thermodynamic non-ideality. Here, we review these considerations by developing a thermodynamically based mathematical model that attempts to simulate the functioning of an Escherichia coli expression system incorporating two of the best characterised prokaryotic DNA binding proteins, Lac repressor and lambda CI repressor. The key aim was to reproduce experimentally observed reporter gene activities arising from the expression of either wild-type CI repressor or one of three positive-control CI mutants. The model considers the role of several potentially important, but sometimes neglected, biochemical features, including DNA looping, macromolecular crowding and non-specific binding, and allowed us to obtain association constants for the binding of CI and its variants to a specific operator sequence.

New Insights into the Phage Genetic Switch: Effects of Bacteriophage Lambda Operator Mutations on DNA Looping and Regulation of PR, PL, and PRM

One of the best understood systems in genetic regulatory biology is the so-called "genetic switch" that determines the choice the phage-encoded CI repressor binds cooperatively to tripartite operators, O_L and O_R, in a defined pattern, thus blocking the transcription at two lytic promoters, P_L and P_R, and auto-regulating the promoter, P_RM, which directs CI synthesis by the prophage. Fine-tuning of the maintenance of lysogeny is facilitated by interactions between CI dimers bound to O_R and O_L through the formation of a loop by the intervening DNA segment. By using a purified in vitro transcription system, we have genetically dissected the roles of individual operator sites in the formation of the DNA loop and thus have gained several new and unexpected insights into the system. First, although both O_R and O_L are tripartite, the presence of only a single active CI binding site in one of the two operators is sufficient for DNA loop formation. Second, in P_L, unlike in P_R, the promoter distal operator site, O_L3, is sufficient to directly repress P_L. Third, DNA looping mediated by the formation of CI octamers arising through the interaction of pairs of dimers bound to adjacent operator sites in O_R and O_L does not require O_R and O_L to be aligned "in register", that is, CI bound to "out-of-register" sub-operators, for example, O_L1~O_l2 and O_R2~O_R3, can also mediate loop formation. Finally, based on an examination of the mechanism of activation of P_RM when only O_R1 or O_R2 are wild type, we hypothesize that RNA polymerase bound at P_R interferes with DNA loop formation. Thus, the formation of DNA loops involves potential interactions between proteins bound at numerous cis-acting sites, which therefore very subtly contribute to the regulation of the "switch".

ACCURATE CHEMICAL MASTER EQUATION SOLUTION USING MULTI-FINITE BUFFERS

The discrete chemical master equation (dCME) provides a fundamental framework for studying stochasticity in mesoscopic networks. Because of the multi-scale nature of many networks where reaction rates have large disparity, directly solving dCMEs is intractable due to the exploding size of the state space. It is important to truncate the state space effectively with quantified errors, so accurate solutions can be computed. It is also important to know if all major probabilistic peaks have been computed. Here we introduce the Accurate CME (ACME) algorithm for obtaining direct solutions to dCMEs. With multi-finite buffers for reducing the state space by O(n!), exact steady-state and time-evolving network probability landscapes can be computed. We further describe a theoretical framework of aggregating microstates into a smaller number of macrostates by decomposing a network into independent aggregated birth and death processes, and give an a priori method for rapidly determining steady-state truncation errors. The maximal sizes of the finite buffers for a given error tolerance can also be pre-computed without costly trial solutions of dCMEs. We show exactly computed probability landscapes of three multi-scale networks, namely, a 6-node toggle switch, 11-node phage-lambda epigenetic circuit, and 16-node MAPK cascade network, the latter two with no known solutions. We also show how probabilities of rare events can be computed from first-passage times, another class of unsolved problems challenging for simulation-based techniques due to large separations in time scales. Overall, the ACME method enables accurate and efficient solutions of the dCME for a large class of networks.

State Space Truncation with Quantified Errors for Accurate Solutions to Discrete Chemical Master Equation

The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEGs), we truncate the state space by limiting the total molecular copy numbers in each MEG. We further describe a theoretical framework for analysis of the truncation error in the steady-state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of (1) the birth and death model, (2) the single gene expression model, (3) the genetic toggle switch model, and (4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady-state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate our theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks.

CarD uses a minor groove wedge mechanism to stabilize the RNA polymerase open promoter complex

A key point to regulate gene expression is at transcription initiation, and activators play a major role. CarD, an essential activator in Mycobacterium tuberculosis, is found in many bacteria, including Thermus species, but absent in Escherichia coli. To delineate the molecular mechanism of CarD, we determined crystal structures of Thermus transcription initiation complexes containing CarD. The structures show CarD interacts with the unique DNA topology presented by the upstream double-stranded/single-stranded DNA junction of the transcription bubble. We confirm that our structures correspond to functional activation complexes, and extend our understanding of the role of a conserved CarD Trp residue that serves as a minor groove wedge, preventing collapse of the transcription bubble to stabilize the transcription initiation complex. Unlike E. coli RNAP, many bacterial RNAPs form unstable promoter complexes, explaining the need for CarD.

DOI:http://dx.doi.org/10.7554/eLife.08505.001

Inside cells, molecules of double-stranded DNA encode the instructions needed to make proteins. To make a protein, the two strands of DNA that make up a gene are separated and one strand acts as a template to make molecules of messenger ribonucleic acid (or mRNA for short). This process is called transcription. The mRNA is then used as a template to assemble the protein. An enzyme called RNA polymerase carries out transcription and is found in all cells ranging from bacteria to humans and other animals.

Bacteria have the simplest form of RNA polymerase and provide an excellent system to study how it controls transcription. It is made up of several proteins that work together to make RNA using DNA as a template. However, it requires the help of another protein called sigma factor to direct it to regions of DNA called promoters, which are just before the start of the gene. When RNA polymerase and the sigma factor interact the resulting group of proteins is known as the RNA polymerase ‘holoenzyme’.

Transcription takes place in several stages. To start with, the RNA polymerase holoenzyme locates and binds to promoter DNA. Next, it separates the two strands of DNA and exposes a portion of the template strand. At this point, the DNA and the holoenzyme are said to be in an ‘open promoter complex’ and the section of promoter DNA that is within it is known as a ‘transcription bubble’. Another protein called CarD helps to speed up transcription but it is not clear how this stage of the process works.

Bae et al. have now used X-ray crystallography to reveal the structure of CarD bound to the RNA polymerase holoenyzme and a DNA promoter. The structures show that one part of CarD interacts with the DNA at the start of the transcription bubble, and another part binds to the RNA polymerase. CarD fits between the two strands of DNA in the promoter, like a wedge, to keep the strands apart. Therefore, CarD stabilizes the open promoter complex and prevents the transcription bubble from collapsing.

These findings reveal a previously unseen mechanism involved in activating transcription and will guide further experiments probing the role of CarD in living cells. Another study by Bae, Feklistov et al.—which involves some of the same researchers as this study—reveals that the sigma factor also binds to DNA at the start of the transcription bubble. The general principles outlined by these studies may help to identify other proteins that regulate transcription.

DOI:http://dx.doi.org/10.7554/eLife.08505.002

Different Modes of Transactivation of Bacteriophage Mu Late Promoters by Transcription Factor C

Transactivator protein C is required for the expression of bacteriophage Mu late genes from lys, I, P and mom promoters during lytic life cycle of the phage. The mechanism of transcription activation of mom gene by C protein is well understood. C activates transcription at Pmom by initial unwinding of the promoter DNA, thereby facilitating RNA polymerase (RNAP) recruitment. Subsequently, C interacts with the ß' subunit of RNAP to enhance promoter clearance. The mechanism by which C activates other late genes of the phage is not known. We carried out promoter-polymerase interaction studies with all the late gene promoters to determine the individual step of C mediated activation. Unlike at Pmom, at the other three promoters, RNAP recruitment and closed complex formation are not C dependent. Instead, the action of C at Plys, PI, and PP is during the isomerization from closed complex to open complex with no apparent effect at other steps of initiation pathway. The mechanism of transcription activation of mom and other late promoters by their common activator is different. This distinction in the mode of activation (promoter recruitment and escape versus isomerization) by the same activator at different promoters appears to be important for optimized expression of each of the late genes.

Bacterial nucleoid-associated protein uncouples transcription levels from transcription timing

The histone-like nucleoid-structuring (H-NS) protein binds to horizontally acquired genes in the bacterium Salmonella enterica serovar Typhimurium, silencing their expression. We now report that overcoming the silencing effects of H-NS imposes a delay in the expression of genes activated by the transcriptional regulator PhoP. We determine that PhoP-activated genes ancestral to Salmonella are expressed before those acquired horizontally. This expression timing reflects the in vivo occupancy of the corresponding promoters by the PhoP protein. These results are surprising because some of these horizontally acquired genes reached higher mRNA levels than ancestral genes expressed earlier and were transcribed from promoters harboring PhoP-binding sites with higher in vitro affinity for the PhoP protein. Our findings challenge the often-made assumption that for genes coregulated by a given transcription factor, early genes are transcribed to higher mRNA levels than those transcribed at later times. Moreover, they provide a singular example of how gene ancestry can impact expression timing.

We report that gene ancestry dictates the expression behavior of genes under the direct control of the Salmonella transcriptional regulator PhoP. That is, ancestral genes are transcribed before horizontally acquired genes. This reflects both the need to overcome silencing by the H-NS protein of the latter genes and the architecture of the corresponding promoters. Unexpectedly, transcription levels do not reflect transcription timing. Our results illustrate how a bacterium can exhibit an elaborate temporal expression behavior among genes coregulated by a transcription factor even though the products encoded by the target genes do not participate in a morphological or developmental pathway.

Role of cis-acting sites in stimulation of the phage λ P(RM) promoter by CI-mediated looping

The lysogenic state of phage λ is maintained by the CI repressor. CI binds to three operators each in the right operator (O(R)) and left operator (O(L)) regions, which lie 2.4 kb apart. At moderate CI levels, the predominant binding pattern is two dimers of CI bound cooperatively at each regulatory region. The resulting tetramers can then interact, forming an octamer and a loop of the intervening DNA. CI is expressed from the P(RM) promoter, which lies in the O(R) region and is subjected to multiple regulatory controls. Of these, the most recently discovered is stimulation by loop formation. In this work, we have investigated the mechanism by which looping stimulates P(RM). We find that two cis-acting sites lying in the O(L) region are involved. One site, an UP element, is required for stimulation. Based on the behavior of other promoters with UP elements located upstream of the -35 region, we suggest that a subunit of RNA polymerase (RNAP) bound at P(RM) binds to the UP element located in the O(L) region. In addition, adjacent to the UP element lies a binding site for integration host factor (IHF); this site plays a less critical role but is required for stimulation of the weak prm240 allele. A loop with CI at the O(L)2 and O(L)3 operators does not stimulate P(RM), while one with CI only at O(L)2 provides some stimulation. We discuss possible mechanisms for stimulation.

Activating transcription in bacteria

Bacteria use a variety of mechanisms to direct RNA polymerase to specific promoters in order to activate transcription in response to growth signals or environmental cues. Activation can be due to factors that interact at specific promoters, thereby increasing transcription directed by these promoters. We examine the range of architectures found at activator-dependent promoters and outline the mechanisms by which input from different factors is integrated. Alternatively, activation can be due to factors that interact with RNA polymerase and change its preferences for target promoters. We summarize the different mechanistic options for activation that are focused directly on RNA polymerase.

The promoter architectural landscape of the Salmonella PhoP regulon

The DNA-binding protein PhoP controls virulence and Mg²⁺ homeostasis in the Gram-negative pathogen Salmonella enterica serovar Typhimurium. PhoP regulates expression of a large number of genes that differ both in their ancestry and in the biochemical functions and physiological roles of the encoded products. This suggests that PhoP-regulated genes are differentially expressed. To understand how a bacterial activator might generate varied gene expression behaviour, we investigated the cis-acting promoter features (i.e. the number of PhoP binding sites, as well as their orientation and location with respect to the sites bound by RNA polymerase and the sequences that constitute the PhoP binding sites) in 23 PhoP-activated promoters. Our results show that natural PhoP-activated promoters utilize only a limited number of combinations of cis-acting features – or promoter architectures. We determine that PhoP activates transcription by different mechanisms, and that ancestral and horizontally acquired PhoP-activated genes have distinct promoter architectures.

Predicting gene-regulation functions: lessons from temperate bacteriophages

Gene-regulation functions (GRF) provide a unique characteristic of a cis-regulatory module (CRM), relating the concentrations of transcription factors (input) to the promoter activities (output). The challenge is to predict GRFs from the sequence. Here we systematically consider the lysogeny-lysis CRMs of different temperate bacteriophages such as the Lactobacillus casei phage A2, Escherichia coli phages lambda, and 186 and Lactococcal phage TP901-1. This study allowed explaining a recent experimental puzzle on the role of Cro protein in the lambda switch. Several general conclusions have been drawn: 1), long-range interactions, multilayer assembly and DNA looping may lead to complex GRFs that cannot be described by linear functions of binding site occupancies; 2), in general, GRFs cannot be described by the Boolean logic, whereas a three-state non-Boolean logic suffices for the studied examples; 3), studied CRMs of the intact phages seemed to have a similar GRF topology (the number of plateaus and peaks corresponding to different expression regimes); we hypothesize that functionally equivalent CRMs might have topologically equivalent GRFs for a larger class of genetic systems; and 4) within a given GRF class, a set of mechanistic-to-mathematical transformations has been identified, which allows shaping the GRF before carrying out a system-level analysis.

Stochastic probability landscape model for switching efficiency, robustness, and differential threshold for induction of genetic circuit in phage lambda

The genetic switch of phage lambda provides a paradigm for studying developmental biology and cell fate. Although there have been numerous experimental and theoretical studies, the mechanisms for switching efficiency, stability and robustness, maintenance of lysogenic state, and the induction lytic state are not fully understood. In this paper, a new method is adopted to account for the full stochasticity typical in small copy events and the exact steady state probability landscape of the genetic circuit of the switch network is computed. The stability and sensitivity of phage lambda switch and its robustness against perturbations derived from our model for wild type and mutants are consistent with experimental data. Our study has revealed likely mechanism of the phage switch network that was previously unknown.

DNA looping provides stability and robustness to the bacteriophage lambda switch

The bistable gene regulatory switch controlling the transition from lysogeny to lysis in bacteriophage lambda presents a unique challenge to quantitative modeling. Despite extensive characterization of this regulatory network, the origin of the extreme stability of the lysogenic state remains unclear. We have constructed a stochastic model for this switch. Using Forward Flux Sampling simulations, we show that this model predicts an extremely low rate of spontaneous prophage induction in a recA mutant, in agreement with experimental observations. In our model, the DNA loop formed by octamerization of CI bound to the O(L) and O(R) operator regions is crucial for stability, allowing the lysogenic state to remain stable even when a large fraction of the total CI is depleted by nonspecific binding to genomic DNA. DNA looping also ensures that the switch is robust to mutations in the order of the O(R) binding sites. Our results suggest that DNA looping can provide a mechanism to maintain a stable lysogenic state in the face of a range of challenges including noisy gene expression, nonspecific DNA binding, and operator site mutations.

When activators repress and repressors activate: a qualitative analysis of the Shea-Ackers model

The concept of activation in transcriptional regulation is based on the assumption that product mRNA increases monotonically as a function of regulator concentration. We analyze the Shea-Ackers model of transcription and find this assumption to be correct only for the simplest of promoters. We define a new regulatory constant that is a nonlinear combination of association and transcription initiation constants characterizing activation and repression for more complicated promoters. Our results can guide the synthesis of new promoters and lead to a deeper understanding of the constraints guiding the natural promoters evolution.

Binding cooperativity in phage lambda is not sufficient to produce an effective switch

In the wild-type phage lambda, binding of CI to O(R)2 helps polymerase bound to P(RM) transition from a closed to open complex. Activators on other promoters increase the polymerase-DNA binding energy, or affect both the binding energy and the closed-open transition probability. Using a validated mathematical model, we show that these two modes of upregulation have very different effects on the promoter function. We predict that if CI(2) bound to O(R)2 produced equal increase in RNAP-DNA binding constant (compared to wild-type increase in the closed-open transition probability), the lysogen would be significantly less stable.

Optimal enumeration of state space of finitely buffered stochastic molecular networks and exact computation of steady state landscape probability

BACKGROUND

Stochasticity plays important roles in many molecular networks when molecular concentrations are in the range of 0.1 muM to 10nM (about 100 to 10 copies in a cell). The chemical master equation provides a fundamental framework for studying these networks, and the time-varying landscape probability distribution over the full microstates, i.e., the combination of copy numbers of molecular species, provide a full characterization of the network dynamics. A complete characterization of the space of the microstates is a prerequisite for obtaining the full landscape probability distribution of a network. However, there are neither closed-form solutions nor algorithms fully describing all microstates for a given molecular network.

RESULTS

We have developed an algorithm that can exhaustively enumerate the microstates of a molecular network of small copy numbers under the condition that the net gain in newly synthesized molecules is smaller than a predefined limit. We also describe a simple method for computing the exact mean or steady state landscape probability distribution over microstates. We show how the full landscape probability for the gene networks of the self-regulating gene and the toggle-switch in the steady state can be fully characterized. We also give an example using the MAPK cascade network. Data and server will be available at URL: http://scsb.sjtu.edu.cn/statespace.

CONCLUSION

Our algorithm works for networks of small copy numbers buffered with a finite copy number of net molecules that can be synthesized, regardless of the reaction stoichiometry, and is optimal in both storage and time complexity. The algorithm can also be used to calculate the rates of all transitions between microstates from given reactions and reaction rates. The buffer size is limited by the available memory or disk storage. Our algorithm is applicable to a class of biological networks when the copy numbers of molecules are small and the network is closed, or the network is open but the net gain in newly synthesized molecules does not exceed a predefined buffer capacity. For these networks, our method allows full stochastic characterization of the mean landscape probability distribution, and the steady state when it exists.

Promoter activation by repositioning of RNA polymerase

Spo0A, a classical two-component-type response regulator in Bacillus subtilis, binds to a specific DNA sequence found in many promoters to repress or activate the transcription of over 100 genes. On the spoIIG promoter, one of the Spo0A binding sites, centered at position -40, overlaps a consensus -35 element that may also interact with region 4 of the sigma A (sigma(A)) subunit of RNA polymerase. Molecular modeling corroborated by genetic evidence led us to propose that the binding of Spo0A to this site repositions sigma(A) region 4 on the promoter. Therefore, we used a chemical nuclease, p-bromoacetamidobenzyl-EDTA-Fe, that was covalently tethered to a single cysteine in region 4 of sigma(A) to map the position of sigma(A) on the promoter. The results indicated that in the absence of Spo0A, sigma(A) region 4 of the RNA polymerase was located near the -35 element sequence centered at position -40. However, in the presence of Spo0A, sigma(A) region 4 was displaced downstream from the -35 element by 4 bp. These and other results support the model in which the binding of Spo0A to the spoIIG promoter stimulates promoter utilization by repositioning prebound RNA polymerase and stabilizing the repositioned RNA polymerase-promoter complex at a new position that aligns sigma(A) region 2 with the -10 region sequences of the promoter, thus facilitating open complex formation.

The C-terminal domain of the Escherichia coli RNA polymerase alpha subunit plays a role in the CI-dependent activation of the bacteriophage lambda pM promoter

The bacteriophage lambda p(M) promoter is required for maintenance of the lambda prophage in Escherichia coli, as it facilitates transcription of the cI gene, encoding the lambda repressor (CI). CI levels are maintained through a transcriptional feedback mechanism whereby CI can serve as an activator or a repressor of p(M). CI activates p(M) through cooperative binding to the O(R)1 and O(R)2 sites within the O(R) operator, with the O(R)2-bound CI dimer making contact with domain 4 of the RNA polymerase sigma subunit (sigma(4)). Here we demonstrate that the 261 and 287 determinants of the C-terminal domain of the RNA polymerase alpha subunit (alphaCTD), as well as the DNA-binding determinant, are important for CI-dependent activation of p(M). We also show that the location of alphaCTD at the p(M) promoter changes in the presence of CI. Thus, in the absence of CI, one alphaCTD is located on the DNA at position -44 relative to the transcription start site, whereas in the presence of CI, alphaCTD is located at position -54, between the CI-binding sites at O(R)1 and O(R)2. These results suggest that contacts between CI and both alphaCTD and sigma are required for efficient CI-dependent activation of p(M).

Transcriptional activation mechanisms of the PRM promoter of λ phage

We investigate the transcriptional activity associated with the P(RM) promoter of lambda phage. The probability for formation of a transcriptionally active (open) RNA polymerase-DNA complex is calculated by means of an equilibrium statistical-mechanical model. In particular, we study two different models of the transcriptional activation mechanism when the O(R)2 site is occupied by a CI dimer (typical for a lysogen) compared to the situation when O(R)2 is vacant: (1) transcription rate increases (wild-type mechanism) or (2) RNA polymerase becomes stronger (or weaker) bound to DNA (mutant mechanism). By applying experimental determined protein-DNA binding energies we show that these two mechanisms exhibit different characteristics when we study the activity versus CI concentration. We also show that our model may be fitted to in vivo activity data satisfactorily despite that the activated transcription rate is significantly reduced compared to the wild-type value. The model is consistent with experimental determined activities based upon mutations of CI and RNA polymerase.

Nature of the promoter activated by C.PvuII, an unusual regulatory protein conserved among restriction-modification systems

A widely distributed family of small regulators, called C proteins, controls a subset of restriction-modification systems. The C proteins studied to date activate transcription of their own genes and that of downstream endonuclease genes; this arrangement appears to delay endonuclease expression relative to that of the protective methyltransferase when the genes enter a new cell. C proteins bind to conserved sequences called C boxes. In the PvuII system, the C boxes have been reported to extend from -23 to +3 relative to the transcription start for the gene for the C protein, an unexpected starting position relative to a bound activator. This study suggests that transcript initiation within the C boxes represents initial, C-independent transcription of pvuIICR. The major C protein-dependent transcript appears to be a leaderless mRNA starting farther downstream, at the initiation codon for the pvuIIC gene. This conclusion is based on nuclease S1 transcript mapping and the effects of a series of nested deletions in the promoter region. Furthermore, replacing the region upstream of the pvuIIC initiation codon with a library of random oligonucleotides, followed by selection for C-dependent transcription, yielded clones having sequences that resemble -10 promoter hexamers. The -35 hexamer of this promoter would lie within the C boxes. However, the spacing between C boxes/-35 and the apparent -10 hexamer can be varied by +/-4 bp with little effect. This suggests that, like some other activator-dependent promoters, PpvuIICR may not require a -35 hexamer. Features of this transcription activation system suggest explanations for its broad host range.

The effects of upstream DNA on open complex formation by Escherichia coli RNA polymerase

Binding of activators to upstream DNA sequences regulates transcription initiation by affecting the stability of the initial RNA polymerase (RNAP)-promoter complex and/or the rate of subsequent conformational changes required to form the open complex (RP(O)). Here we observe that the presence of nonspecific upstream DNA profoundly affects an early step in formation of the transcription bubble. Kinetic studies with the lambdaP(R) promoter and Escherichia coli RNAP reveal that the presence of DNA upstream of base pair -47 greatly increases the rate of forming RP(O), without significantly affecting its rate of dissociation. We find that this increase is largely due to an acceleration of the rate-limiting step (isomerization) in RP(O) formation, a step that occurs after polymerase binds. Footprinting experiments reveal striking structural differences downstream of the transcription start site (+1) in the first kinetically significant intermediate when upstream DNA is present. On the template strand, the DNase I downstream boundary of this early intermediate is +20 when upstream DNA is present but is shortened by approximately two helical turns when upstream DNA beyond -47 is removed. KMnO(4) footprinting reveals an identical initiation bubble (-11 to +2), but unusual reactivity of template strand upstream cytosines (-12, -14, and -15) on the truncated promoter. Based on this work, we propose that early wrapping interactions between upstream DNA and the polymerase exterior strongly affect the events that control entry and subsequent unwinding of the DNA start site in the jaws of polymerase.

Structure of a ternary transcription activation complex

The cI protein of bacteriophage lambda (lambdacI) activates transcription by binding a DNA operator just upstream of the promoter and interacting with the RNA polymerase sigma subunit domain 4 (sigma(4)). We determined the crystal structure of the lambdacI/sigma(4)/DNA ternary complex at 2.3 A resolution. There are no conformational changes in either protein, which interact through an extremely small interface involving at most 6 amino acid residues. The interactions of the two proteins stabilize the binding of each protein to the DNA. The results provide insight into how activators can operate through a simple cooperative binding mechanism but affect different steps of the transcription initiation process.

Why the lysogenic state of phage lambda is so stable: a mathematical modeling approach

We develop a mathematical model of the phage lambda lysis/lysogeny switch, taking into account recent experimental evidence demonstrating enhanced cooperativity between the left and right operator regions. Model parameters are estimated from available experimental data. The model is shown to have a single stable steady state for these estimated parameter values, and this steady state corresponds to the lysogenic state. When the CI degradation rate (gammacI) is slightly increased from its normal value (gammacI approximately 0.0 min(-1)), two additional steady states appear (through a saddle-node bifurcation) in addition to the lysogenic state. One of these new steady states is stable and corresponds to the lytic state. The other steady state is an (unstable) saddle node. The coexistence these two globally stable steady states (the lytic and lysogenic states) is maintained with further increases of gammacI until gammacI approximately 0.35 min(-1), when the lysogenic steady state and the saddle node collide and vanish (through a reverse saddle node bifurcation) leaving only the lytic state surviving. These results allow us to understand the high degree of stability of the lysogenic state because, normally, it is the only steady state. Further implications of these results for the stability of the phage lambda switch are discussed, as well as possible experimental tests of the model.

Thermoirreversible and thermoreversible promoter opening by two Escherichia coli RNA polymerase holoenzymes

Promoter opening, in which the complementary DNA strands separate around the transcriptional start site, is generally thermoreversible. An exceptional case of thermoirreversible opening of the T4 late promoter has been analyzed by KMnO4 footprinting and transcription. T4 late promoters, which consist of an 8-base pair (bp) TATA box "-10" element, are recognized by the small, phage-encoded, highly diverged sigma-family initiation subunit gp55. The T4 late promoter only opens above 15-20 degrees C, but once it has been formed remains open and transcriptionally active for days at -0.5 degrees C. The low temperature-trapped open complex and its isothermally formed state are shown to be structurally distinctive. Two "extended -10" sigma 70 promoters, which, like the T4 late promoter, lack "-35" sites, have been subjected to a comparative analysis: the T4 middle promoter PrIIB2 opens and closes thermoreversibly under conditions of basal and MotA- and AsiA-activated transcription. The open galP1 promoter complex, whose transcription bubble is very AT-rich, also closes reversibly upon shift to -0.5 degrees C, but more slowly than does the rIIB2 promoter. Formation of a trapped-open low temperature state of the promoter complex appears to be a singular property of gp55-RNA polymerase holoenzyme.

MalR-mediated regulation of the Streptococcus pneumoniae malMP operon at promoter PM. Influence of a proximal divergent promoter region and competition between MalR and RNA polymerase proteins

The Streptococcus pneumoniae mal regulon contains two operons, malXCD and malMP involved in the uptake and utilization of maltosaccharides. Both operons are transcribed from two divergent promoters, P(X) and P(M), and are negatively regulated by the MalR transcriptional repressor. Purified MalR protein binds to two DNA regions that encompasses both promoters, thus occupying its two operators, O(M) and O(X). However, the levels of occupation and repression were different, being higher when MalR was bound to O(M) than when it was anchored to O(X). Competition experiments between MalR and the Escherichia coli RNA polymerase on promoters P(M) and P(X) showed that the affinity of either protein for the promoter/operator DNA sequences was important to determine the frequency of transcription initiation. In addition to the control exerted by MalR, expression from promoter P(M) was affected by upstream sequences located within or close to P(X) promoter.

Mechanism for a transcriptional activator that works at the isomerization step

Transcriptional activators in prokaryotes have been shown to stimulate different steps in the initiation process including the initial binding of RNA polymerase (RNAP) to the promoter and a postbinding step known as the isomerization step. Evidence suggests that activators that affect initial binding can work by a cooperative binding mechanism by making energetically favorable contacts with RNAP, but the mechanism by which activators affect the isomerization step is unclear. A well-studied example of an activator that normally exerts its effect exclusively on the isomerization step is the bacteriophage lambda cI protein (lambdacI), which has been shown genetically to interact with the C-terminal region of the final sigma(70) subunit of RNAP. We show here that the interaction between lambdacI and final sigma can stimulate transcription even when the relevant portion of final sigma is transplanted to another subunit of RNAP. This activation depends on the ability of lambdacI to stabilize the binding of the transplanted final sigma moiety to an ectopic -35 element. Based on these and previous findings, we discuss a simple model that explains how an activator's ability to stabilize the binding of an RNAP subdomain to the DNA can account for its effect on either the initial binding of RNAP to a promoter or the isomerization step.

Transcription activation by the Escherichia coli cyclic AMP receptor protein: determinants within activating region 3

At Class II CRP-dependent promoters, the Escherichia coli cyclic AMP receptor protein (CRP) activates transcription by making multiple interactions with RNA polymerase (RNAP). Two discrete surfaces of CRP, known as Activating Region 1 (AR1) and Activating Region 2 (AR2), interact with the C-terminal and N-terminal domains, respectively, of the alpha subunit of RNAP. Activating Region 3 (AR3) is a third separate surface of CRP, which is thought to interact with a target in the C-terminal region of the RNAP sigma(70) subunit. We have used a CRP mutant that functions primarily via AR3, CRP HL159 KE101 KN52, as a tool to identify residues within AR3 that are important for activation. This was achieved by screening a random mutant library of the gene encoding CRP HL159 KE101 KN52 for positive control mutants at Class II CRP-dependent promoters, and also by performing alanine scanning mutagenesis. Using both in vivo reporter assays and in vitro transcription assays, we measured the effects of key substitutions within AR3 on transcription activation in both CRP HL159 KE101 KN52 and wild-type CRP. We show that a cluster of negatively charged surface-exposed residues at positions 53, 54, 55 and 58 is required for optimal activation at a Class II, but not at a Class I, CRP-dependent promoter. We conclude that these residues in AR3 of CRP form an activatory determinant for Class II transcription activation. Abortive initiation assays were used to show that this activatory determinant accelerates the rate of isomerisation from the closed to open complex at a Class II CRP-dependent promoter. AR3 of CRP also contains an inhibitory determinant: the lysine residue at position 52 of CRP is inhibitory to maximal levels of transcription activation from Class II promoters. We show that the negative effects of K52 are not simply due to "masking" of the negatively charged residues at positions 53, 54, 55 and 58. Our results suggest that, during activation by wild-type CRP, the activatory and inhibitory determinants of AR3 balance each other. Thus, activation is predominantly determined by AR1 and AR2.

Bacterial promoter architecture: subsite structure of UP elements and interactions with the carboxy-terminal domain of the RNA polymerase alpha subunit

We demonstrate here that the previously described bacterial promoter upstream element (UP element) consists of two distinct subsites, each of which, by itself, can bind the RNA polymerase holoenzyme alpha subunit carboxy-terminal domain (RNAP alphaCTD) and stimulate transcription. Using binding-site-selection experiments, we identify the consensus sequence for each subsite. The selected proximal subsites (positions -46 to -38; consensus 5'-AAAAAARNR-3') stimulate transcription up to 170-fold, and the selected distal subsites (positions -57 to -47; consensus 5'-AWWWWWTTTTT-3') stimulate transcription up to 16-fold. RNAP has subunit composition alpha(2)betabeta'sigma and thus contains two copies of alphaCTD. Experiments with RNAP derivatives containing only one copy of alphaCTD indicate, in contrast to a previous report, that the two alphaCTDs function interchangeably with respect to UP element recognition. Furthermore, function of the consensus proximal subsite requires only one copy of alphaCTD, whereas function of the consensus distal subsite requires both copies of alphaCTD. We propose that each subsite constitutes a binding site for a copy of alphaCTD, and that binding of an alphaCTD to the proximal subsite region (through specific interactions with a consensus proximal subsite or through nonspecific interactions with a nonconsensus proximal subsite) is a prerequisite for binding of the other alphaCTD to the distal subsite.

GalR-mediated repression and activation of hybrid lacUV5 promoter: differential contacts with RNA polymerase

The GalR repressor regulates expression of genes of the gal regulon in Escherichia coli. We studied the regulatory effect of GalR in vitro on a heterologous promoter, lacUV5, by placing the GalR-binding site, OE, at different locations upstream of this promoter. Despite the fact that the lacUV5 promoter is transcribed efficiently by RNA polymerase (RNP) alone, GalR modulated transcription from many of the PlacUV5 variants. Depending on the location of OE and the neighboring DNA sequence, GalR repressed, activated or had no effect on the promoter. Both repression and activation involved formation of GalR-RNP-DNA ternary complexes and required an intact c-domain of the alpha subunit of the holoenzyme. These results support the differential contact model of a regulator action, in which a regulator differentially binds to, and lowers the energy of, intermediates of transcription initiation either to hinder or to facilitate a step of initiation. The nature of the contacts depends upon the context, i.e. the geometry of the ternary complex. The observed repression and activation effect of GalR on a heterologous promoter also underscores the point that a regulator is not a dedicated protein for repression or for activation.

The differential effects of guanosine tetraphosphate on open complex formation at the Escherichia coli ribosomal protein promoters rplJ and rpsA P1

The effects of guanosine tetraphosphate (ppGpp) on inhibition of single-round in vitro transcription and on the kinetics of open complex formation were investigated at the Escherichia coli ribosomal protein promoters rplJ and rpsA P1. The two promoters differ in their saturation characteristics and sensitivities to ppGpp. With a 10:1 molar ratio of RNA polymerase (RNAP) to DNA, saturation of transcription activity and weak inhibition (approximately 30%) are observed at rplJ, in contrast to the weak activity and strong inhibition (approximately 80%) at rpsA P1. In the absence of ppGpp, the two promoters show a threefold difference in the overall rate constants of association (ka) (6.5 x 10(7) M-1 s-1 at rplJ and 2.0 x 10(7) M-1 s-1 at rpsA P1), while the dissociation rate constants (kd) are similar (approximately 4.8 x 10(-5) s-1). The addition of ppGpp causes a twofold reduction in k2 (isomerisation constant) rplJ and a threefold decrease in KB (equilibrium constant of RNAP binding) at rpsA P1. There is a significant twofold increase in kd at rplJ, compared with smaller changes at rpsA P1 and at the non-stringent lacUV5 promoter. These results indicate that ppGpp affects the formation and stability of the open complex at the rplJ promoter, in contrast to the inhibition of RNAP binding to the rpsA P1 promoter.

Characterization of the closed complex intermediate formed during transcription initiation by Escherichia coli RNA polymerase

We have carried out detailed DNase I footprinting studies of the closed complex formed on the phage lambda prmup-1 Delta265 promoter under reaction conditions such that the contribution of the open complex to the footprint was negligible. Detailed quantification shows that the closed complex detected has the same binding constant as that determined in kinetic studies. The footprinting pattern of the closed complex shows major differences from that of the open complex. Not only is it about 20 base pairs shorter, there are also many fewer positions being protected around and upstream of the -35 region. We have derived potential contact regions in the closed and open complexes based on the DNase I footprinting patterns, and confirmed the contact region for the open complex by hydroxyl radical footprinting. One important finding is that most of the essential contacts with the phosphate groups in the -35 region are formed during the isomerization step, a conclusion consistent with our kinetic data showing that this step is salt dependent on this promoter. In addition, we found that the derived contact regions for the closed and open complexes are offset by about three base pairs in the -35 region, which suggests a shift of the contact during isomerization. Finally, we found that the footprinting pattern of the complex formed at 4 degreesC has some similarities to as well as differences from the closed complex formed under standard transcription conditions.

A region in Bacillus subtilis sigmaH required for Spo0A-dependent promoter activity

Spo0A activates transcription in Bacillus subtilis from promoters that are used by two types of RNA polymerase, RNA polymerase containing the primary sigma factor, sigmaA, and RNA polymerase containing a secondary sigma factor, known as sigmaH. The region of sigmaA near positions 356 to 359 is required for Spo0A-dependent promoter activation, possibly because Spo0A interacts with this region of sigmaA at these promoters. To determine if the amino acids in the corresponding region of sigmaH are also important in Spo0A-dependent promoter activation, we examined the effects of single alanine substitutions at 10 positions in sigmaH (201 to 210). Two alanine substitutions in sigmaH, at glutamine 201 (Q201A) and at arginine 205 (R205A), significantly decreased activity from the Spo0A-dependent, sigmaH-dependent promoter spoIIA but did not affect expression from the sigmaH-dependent, Spo0A-independent promoters citGp2 and spoVG. Therefore, promoter activation by Spo0A requires homologous regions in sigmaA and sigmaH. A mutant form of Spo0A, S231F, that suppresses the sporulation defect caused by several amino acid substitutions in sigmaA did not suppress the sporulation defects caused by the Q201A and R205A substitutions in sigmaH. This result and others indicate that different surfaces of Spo0A probably interact with sigmaA and sigmaH RNA polymerases.

A region in the Bacillus subtilis transcription factor Spo0A that is important for spoIIG promoter activation

Spo0A is a DNA binding protein in Bacillus subtilis required for the activation of spoIIG and other promoters at the onset of endospore formation. Activation of some of these promoters may involve interaction of Spo0A and the sigmaA subunit of RNA polymerase. Previous studies identified two single-amino-acid substitutions in sigmaA, K356E and H359R, that specifically impaired Spo0A-dependent transcription in vivo. Here we report the identification of an amino acid substitution in Spo0A (S231F) that suppressed the sporulation deficiency due to the H359R substitution in sigmaA. We also found that the S231F substitution partially restored use of the spoIIG promoter by the sigmaA H359R RNA polymerase in vitro. Alanine substitutions in the 231 region of Spo0A revealed an additional amino acid residue important for spoIIG promoter activation, I229. This amino acid substitution in Spo0A did not affect repression of abrB transcription, indicating that the alanine-substituted Spo0A was not defective in DNA binding. Moreover, the alanine-substituted Spo0A protein activated the spoIIA promoter; therefore, this region of Spo0A is probably not required for Spo0A-dependent, sigmaH-directed transcription. These and other results suggest that the region of Spo0A near position 229 is involved in sigmaA-dependent promoter activation.

DNA strand separation during activation of a developmental promoter by the Bacillus subtilis response regulator Spo0A

Spo0A is the central regulator of commitment to sporulation in Bacillus subtilis. Spo0A is a member of the response regulator family of proteins and both represses and stimulates transcription from promoters when activated. In vivo Spo0A activation takes place by phosphorylation and in vitro activation can be accomplished by phosphorylation or removal of the N-terminal domain of the protein. We have examined the mechanism of Spo0A stimulation of transcription from the promoter of the spoIIG operon. This operon encodes one of the first compartment specific sigma factors whose appearance regulates sporulation development. When activated Spo0A was incubated with RNA polymerase and a DNA fragment containing the spoIIG promoter, bases between -13 and -3, relative to the start site of transcription, were denatured. Addition of activated Spo0A or RNA polymerase alone did not induce denaturation. Heteroduplex templates that contained the nontemplate sequence of the wild-type promoter on both strands between positions -3 and -13 were efficiently transcribed without activated Spo0A. These data suggest that DNA strand separation is a two-step process and that the activation of Spo0A creates a form that interacts with the polymerase to induce the first of the two steps.

Positive activation of gene expression

Most bacterial transcription activators function by making direct contact with RNA polymerase at target promoters. Some activators contact the carboxy-terminal domain of the RNA polymerase alpha subunit, some contact region 4 of the sigma70 subunit, whilst others interact with other contact sites. A number of activators are ambidextrous and can, apparently simultaneously, contact more than one target site on RNA polymerase. Expression from many promoters is co-dependent on two or more activators. There are several different mechanisms for coupling promoter activity to more than one activator: in one such mechanism, the different activators make independent contacts with different target sites on RNA polymerase.

Activation of the Bacillus subtilis spoIIG promoter requires interaction of Spo0A and the sigma subunit of RNA polymerase

Bacillus subtilis Spo0A activates transcription from both sigmaA- and sigmaH-dependent promoters. Baldus et al. (2) identified two amino acid substitutions in the carboxyl terminus of sigmaA, K356E and H359R, that specifically impaired Spo0A-activated transcription in vivo. To test the model in which the K356E and H359R substitutions in sigmaA interfere with the interaction of Spo0A and sigmaA, we examined the effects of alanine substitutions at these positions in sigmaA on sigmaA's ability to direct transcription in vivo and in vitro. We found that alanine substitutions at these positions specifically reduced expression from the sigmaA-dependent, Spo0A-dependent promoters, spoIIG and spoIIE, in vivo. Furthermore, we found that stimulation of spoIIG promoter activity by Spo0A in vitro was reduced by the single substitutions H359A and H359R in sigmaA.