Mechanism of transcriptional repression at a bacterial promoter by analysis of single molecules

Regulatory properties of transcription factors with diverse mechanistic function

Transcription factors (TFs) regulate the process of transcription through the modulation of different kinetic steps. Although models can often describe the observed transcriptional output of a measured gene, predicting a TFs role on a given promoter requires an understanding of how the TF alters each step of the transcription process. In this work, we use a simple model of transcription to assess the role of promoter identity, and the degree to which TFs alter binding of RNAP (stabilization) and initiation of transcription (acceleration) on three primary characteristics: the range of steady-state regulation, cell-to-cell variability in expression, and the dynamic response time of a regulated gene. We find that steady state regulation and the response time of a gene behave uniquely for TFs that regulate incoherently, i.e that speed up one step but slow the other. We also find that incoherent TFs have dynamic implications, with one type of incoherent mode configuring the promoter to respond more slowly at intermediate TF concentrations. We also demonstrate that the noise of gene expression for these TFs is sensitive to promoter strength, with a distinct non-monotonic profile that is apparent under stronger promoters. Taken together, our work uncovers the coupling between promoters and TF regulatory modes with implications for understanding natural promoters and engineering synthetic gene circuits with desired expression properties.

Transcription factor competition facilitates self-sustained oscillations in single gene genetic circuits

Genetic feedback loops can be used by cells to regulate internal processes or to keep track of time. It is often thought that, for a genetic circuit to display self-sustained oscillations, a degree of cooperativity is needed in the binding and unbinding of actor species. This cooperativity is usually modeled using a Hill function, regardless of the actual promoter architecture. Furthermore, genetic circuits do not operate in isolation and often transcription factors are shared between different promoters. In this work we show how mathematical modelling of genetic feedback loops can be facilitated with a mechanistic fold-change function that takes into account the titration effect caused by competing binding sites for transcription factors. The model shows how the titration effect facilitates self-sustained oscillations in a minimal genetic feedback loop: a gene that produces its own repressor directly without cooperative transcription factor binding. The use of delay-differential equations leads to a stability contour that predicts whether a genetic feedback loop will show self-sustained oscillations, even when taking the bursty nature of transcription into account.

Engineering eukaryote-like regulatory circuits to expand artificial control mechanisms for metabolic engineering in Saccharomyces cerevisiae

Temporal control of heterologous pathway expression is critical to achieve optimal efficiency in microbial metabolic engineering. The broadly-used GAL promoter system for engineered yeast (Saccharomyces cerevisiae) suffers from several drawbacks; specifically, unintended induction during laboratory development, and unintended repression in industrial production applications, which decreases overall production capacity. Eukaryotic synthetic circuits have not been well examined to address these problems. Here, we explore a modularised engineering method to deploy new genetic circuits applicable for expanding the control of GAL promoter-driven heterologous pathways in S. cerevisiae. Trans- and cis- modules, including eukaryotic trans-activating-and-repressing mechanisms, were characterised to provide new and better tools for circuit design. A eukaryote-like tetracycline-mediated circuit that delivers stringent repression was engineered to minimise metabolic burden during strain development and maintenance. This was combined with a novel 37 °C induction circuit to relief glucose-mediated repression on the GAL promoter during the bioprocess. This delivered a 44% increase in production of the terpenoid nerolidol, to 2.54 g L^-1 in flask cultivation. These negative/positive transcriptional regulatory circuits expand global strategies of metabolic control to facilitate laboratory maintenance and for industry applications.

Modelling and measuring intracellular competition for finite resources during gene expression

Dissecting the competition between genes for shared expressional resources is of fundamental importance for understanding the interplay between cellular components. Owing to the relationship between gene expression and cellular fitness, genomes are shaped by evolution to improve resource allocation. Whereas experimental approaches to investigate intracellular competition require technical resources and human expertise, computational models and in silico simulations allow vast numbers of experiments to be carried out and controlled easily, and with significantly reduced costs. Thus, modelling competition has a pivotal role in understanding the effects of competition on the biophysics of the cell. In this article, we review various computational models proposed to describe the different types of competition during gene expression. We also present relevant synthetic biology experiments and their biotechnological implications, and discuss the open questions in the field.

Deciphering the Rules Underlying Xenogeneic Silencing and Counter-Silencing of Lsr2-like Proteins Using CgpS of Corynebacterium glutamicum as a Model

Lsr2-like nucleoid-associated proteins play an important role as xenogeneic silencers (XS) of horizontally acquired genomic regions in actinobacteria. In this study, we systematically analyzed the in vivo constraints underlying silencing and counter-silencing of the Lsr2-like protein CgpS in Corynebacterium glutamicum Genome-wide analysis revealed binding of CgpS to regions featuring a distinct drop in GC profile close to the transcription start site (TSS) but also identified an overrepresented motif with multiple A/T steps at the nucleation site of the nucleoprotein complex. Binding of specific transcription factors (TFs) may oppose XS activity, leading to counter-silencing. Following a synthetic counter-silencing approach, target gene activation was realized by inserting operator sites of an effector-responsive TF within various CgpS target promoters, resulting in increased promoter activity upon TF binding. Analysis of reporter constructs revealed maximal counter-silencing when the TF operator site was inserted at the position of maximal CgpS coverage. This principle was implemented in a synthetic toggle switch, which features a robust and reversible response to effector availability, highlighting the potential for biotechnological applications. Together, our results provide comprehensive insights into how Lsr2 silencing and counter-silencing shape evolutionary network expansion in this medically and biotechnologically relevant bacterial phylum.IMPORTANCE In actinobacteria, Lsr2-like nucleoid-associated proteins function as xenogeneic silencers (XS) of horizontally acquired genomic regions, including viral elements, virulence gene clusters in Mycobacterium tuberculosis, and genes involved in cryptic specialized metabolism in Streptomyces species. Consequently, a detailed mechanistic understanding of Lsr2 binding in vivo is relevant as a potential drug target and for the identification of novel bioactive compounds. Here, we followed an in vivo approach to investigate the rules underlying xenogeneic silencing and counter-silencing of the Lsr2-like XS CgpS from Corynebacterium glutamicum Our results demonstrated that CgpS distinguishes between self and foreign by recognizing a distinct drop in GC profile in combination with a short, sequence-specific motif at the nucleation site. Following a synthetic counter-silencer approach, we studied the potential and constraints of transcription factors to counteract CgpS silencing, thereby facilitating the integration of new genetic traits into host regulatory networks.

Conformational heterogeneity and bubble dynamics in single bacterial transcription initiation complexes

Transcription initiation is a major step in gene regulation for all organisms. In bacteria, the promoter DNA is first recognized by RNA polymerase (RNAP) to yield an initial closed complex. This complex subsequently undergoes conformational changes resulting in DNA strand separation to form a transcription bubble and an RNAP-promoter open complex; however, the series and sequence of conformational changes, and the factors that influence them are unclear. To address the conformational landscape and transitions in transcription initiation, we applied single-molecule Förster resonance energy transfer (smFRET) on immobilized Escherichia coli transcription open complexes. Our results revealed the existence of two stable states within RNAP–DNA complexes in which the promoter DNA appears to adopt closed and partially open conformations, and we observed large-scale transitions in which the transcription bubble fluctuated between open and closed states; these transitions, which occur roughly on the 0.1 s timescale, are distinct from the millisecond-timescale dynamics previously observed within diffusing open complexes. Mutational studies indicated that the σ⁷⁰ region 3.2 of the RNAP significantly affected the bubble dynamics. Our results have implications for many steps of transcription initiation, and support a bend-load-open model for the sequence of transitions leading to bubble opening during open complex formation.

Phenotypic Nonspecificity as the Result of Limited Specificity of Transcription Factor Function

Drosophila transcription factor (TF) function is phenotypically nonspecific. Phenotypic nonspecificity is defined as one phenotype being induced or rescued by multiple TFs. To explain this unexpected result, a hypothetical world of limited specificity is explored where all TFs have unique random distributions along the genome due to low information content of DNA sequence recognition and somewhat promiscuous cooperative interactions with other TFs. Transcription is an emergent property of these two conditions. From this model, explicit predictions are made. First, many more cases of TF nonspecificity are expected when examined. Second, the genetic analysis of regulatory sequences should uncover cis-element bypass and, third, genetic analysis of TF function should generally uncover differential pleiotropy. In addition, limited specificity provides evolutionary opportunity and explains the inefficiency of expression analysis in identifying genes required for biological processes.

Rate-limiting steps in transcription dictate sensitivity to variability in cellular components

Cell-to-cell variability in cellular components generates cell-to-cell diversity in RNA and protein production dynamics. As these components are inherited, this should also cause lineage-to-lineage variability in these dynamics. We conjectured that these effects on transcription are promoter initiation kinetics dependent. To test this, first we used stochastic models to predict that variability in the numbers of molecules involved in upstream processes, such as the intake of inducers from the environment, acts only as a transient source of variability in RNA production numbers, while variability in the numbers of a molecular species controlling transcription of an active promoter acts as a constant source. Next, from single-cell, single-RNA level time-lapse microscopy of independent lineages of Escherichia coli cells, we demonstrate the existence of lineage-to-lineage variability in gene activation times and mean RNA production rates, and that these variabilities differ between promoters and inducers used. Finally, we provide evidence that this can be explained by differences in the kinetics of the rate-limiting steps in transcription between promoters and induction schemes. We conclude that cell-to-cell and consequent lineage-to-lineage variability in RNA and protein numbers are both promoter sequence-dependent and subject to regulation.

One ligand, two regulators and three binding sites: How KDPG controls primary carbon metabolism in Pseudomonas

Effective regulation of primary carbon metabolism is critically important for bacteria to successfully adapt to different environments. We have identified an uncharacterised transcriptional regulator; RccR, that controls this process in response to carbon source availability. Disruption of rccR in the plant-associated microbe Pseudomonas fluorescens inhibits growth in defined media, and compromises its ability to colonise the wheat rhizosphere. Structurally, RccR is almost identical to the Entner-Doudoroff (ED) pathway regulator HexR, and both proteins are controlled by the same ED-intermediate; 2-keto-3-deoxy-6-phosphogluconate (KDPG). Despite these similarities, HexR and RccR control entirely different aspects of primary metabolism, with RccR regulating pyruvate metabolism (aceEF), the glyoxylate shunt (aceA, glcB, pntAA) and gluconeogenesis (pckA, gap). RccR displays complex and unusual regulatory behaviour; switching repression between the pyruvate metabolism and glyoxylate shunt/gluconeogenesis loci depending on the available carbon source. This regulatory complexity is enabled by two distinct pseudo-palindromic binding sites, differing only in the length of their linker regions, with KDPG binding increasing affinity for the 28 bp aceA binding site but decreasing affinity for the 15 bp aceE site. Thus, RccR is able to simultaneously suppress and activate gene expression in response to carbon source availability. Together, the RccR and HexR regulators enable the rapid coordination of multiple aspects of primary carbon metabolism, in response to levels of a single key intermediate.

Here we show how Pseudomonas controls multiple different primary carbon metabolism pathways by sensing levels of KDPG, an Entner Doudoroff (ED) pathway intermediate. KDPG binds to two highly similar transcription factors; the ED regulator HexR and the previously uncharacterised protein RccR. RccR inversely controls the glyoxylate shunt, gluconeogenesis and pyruvate metabolism, suppressing the first two pathways as pyruvate metabolism genes are expressed, and vice versa. This complex regulation is enabled by two distinct RccR-binding consensus sequences in the RccR regulon promoters. KDPG binding simultaneously increases RccR affinity for the glyoxylate shunt and gluconeogenesis promoters, and releases repression of pyruvate metabolism. This elegant two-regulator circuit allows Pseudomonas to rapidly respond to carbon source availability by sensing a single key intermediate, KDPG.

Fluorescent Labeling of Proteins in Whole Cell Extracts for Single-Molecule Imaging

Cellular machines such as the spliceosome and ribosome can be composed of dozens of individual proteins and nucleic acids. Given this complexity, it is not surprising that many cellular activities have not yet been biochemically reconstituted. Such processes are often studied in vitro in whole cell or fractionated lysates. This presents a challenge for obtaining detailed biochemical information when the components being investigated may be only a minor component of the extract and unrelated processes may interfere with the assay. Single-molecule fluorescence microscopy methods allow particular biomolecules to be analyzed even in the complex milieu of a cell extract. This is due to the use of bright fluorophores that emit light at wavelengths at which few cellular components fluoresce, and the development of chemical biology tools for attaching these fluorophores to specific cellular proteins. Here, we describe a protocol for fluorescent labeling of endogenous, SNAP-tagged yeast proteins in whole cell extract. This method allows biochemical reactions to be followed in cell lysates in real time using colocalization single-molecule fluorescence microscopy. Labeled complexes can also be isolated from extract and characterized by SNAP tag single-molecule pull-down (SNAP-SiMPull). These approaches have proven useful for studying complex biological machines such as the spliceosome that cannot yet be reconstituted from purified components.

Multi-wavelength single-molecule fluorescence analysis of transcription mechanisms

Multi-wavelength single molecule fluorescence microscopy is a valuable tool for clarifying transcription mechanisms, which involve multiple components and intermediates. Here we describe methods for the analysis and interpretation of such single molecule data. The methods described include those for image alignment, drift correction, spot discrimination, as well as robust methods for analyzing single-molecule binding and dissociation kinetics that account for non-specific binding and photobleaching. Finally, we give an example of the use of the resulting data to extract the kinetic mechanism of promoter binding by a bacterial RNA polymerase holoenzyme.

RNA polymerase molecular beacon as tool for studies of RNA polymerase-promoter interactions

The molecular details of formation of transcription initiation complex upon the interaction of bacterial RNA polymerase (RNAP) with promoters are not completely understood. One way to address this problem is to understand how RNAP interacts with different parts of promoter DNA. A recently developed fluorometric RNAP molecular beacon assay allows one to monitor the RNAP interactions with various unlabeled DNA probes and quantitatively characterize partial RNAP-promoter interactions. This paper focuses on methodological aspects of application of this powerful assay to study the mechanism of transcription initiation complex formation by Escherichia coli RNA polymerase σ(70) holoenzyme and its regulation by bacterial and phage encoded factors.

A framework for modelling gene regulation which accommodates non-equilibrium mechanisms

BACKGROUND

Gene regulation has, for the most part, been quantitatively analysed by assuming that regulatory mechanisms operate at thermodynamic equilibrium. This formalism was originally developed to analyse the binding and unbinding of transcription factors from naked DNA in eubacteria. Although widely used, it has made it difficult to understand the role of energy-dissipating, epigenetic mechanisms, such as DNA methylation, nucleosome remodelling and post-translational modification of histones and co-regulators, which act together with transcription factors to regulate gene expression in eukaryotes.

RESULTS

Here, we introduce a graph-based framework that can accommodate non-equilibrium mechanisms. A gene-regulatory system is described as a graph, which specifies the DNA microstates (vertices), the transitions between microstates (edges) and the transition rates (edge labels). The graph yields a stochastic master equation for how microstate probabilities change over time. We show that this framework has broad scope by providing new insights into three very different ad hoc models, of steroid-hormone responsive genes, of inherently bounded chromatin domains and of the yeast PHO5 gene. We find, moreover, surprising complexity in the regulation of PHO5, which has not yet been experimentally explored, and we show that this complexity is an inherent feature of being away from equilibrium. At equilibrium, microstate probabilities do not depend on how a microstate is reached but, away from equilibrium, each path to a microstate can contribute to its steady-state probability. Systems that are far from equilibrium thereby become dependent on history and the resulting complexity is a fundamental challenge. To begin addressing this, we introduce a graph-based concept of independence, which can be applied to sub-systems that are far from equilibrium, and prove that history-dependent complexity can be circumvented when sub-systems operate independently.

CONCLUSIONS

As epigenomic data become increasingly available, we anticipate that gene function will come to be represented by graphs, as gene structure has been represented by sequences, and that the methods introduced here will provide a broader foundation for understanding how genes work.

Noise and information transmission in promoters with multiple internal States

Based on the measurements of noise in gene expression performed during the past decade, it has become customary to think of gene regulation in terms of a two-state model, where the promoter of a gene can stochastically switch between an ON and an OFF state. As experiments are becoming increasingly precise and the deviations from the two-state model start to be observable, we ask about the experimental signatures of complex multistate promoters, as well as the functional consequences of this additional complexity. In detail, we i), extend the calculations for noise in gene expression to promoters described by state transition diagrams with multiple states, ii), systematically compute the experimentally accessible noise characteristics for these complex promoters, and iii), use information theory to evaluate the channel capacities of complex promoter architectures and compare them with the baseline provided by the two-state model. We find that adding internal states to the promoter generically decreases channel capacity, except in certain cases, three of which (cooperativity, dual-role regulation, promoter cycling) we analyze in detail.

Direct measurement of transcription factor dissociation excludes a simple operator occupancy model for gene regulation

Transcription factors mediate gene regulation by site-specific binding to chromosomal operators. It is commonly assumed that the level of repression is determined solely by the equilibrium binding of a repressor to its operator. However, this assumption has not been possible to test in living cells. Here we have developed a single-molecule chase assay to measure how long an individual transcription factor molecule remains bound at a specific chromosomal operator site. We find that the lac repressor dimer stays bound on average 5 min at the native lac operator in Escherichia coli and that a stronger operator results in a slower dissociation rate but a similar association rate. Our findings do not support the simple equilibrium model. The discrepancy with this model can, for example, be accounted for by considering that transcription initiation drives the system out of equilibrium. Such effects need to be considered when predicting gene activity from transcription factor binding strengths.

The transcription factor titration effect dictates level of gene expression

Models of transcription are often built around a picture of RNA polymerase and transcription factors (TFs) acting on a single copy of a promoter. However, most TFs are shared between multiple genes with varying binding affinities. Beyond that, genes often exist at high copy number-in multiple identical copies on the chromosome or on plasmids or viral vectors with copy numbers in the hundreds. Using a thermodynamic model, we characterize the interplay between TF copy number and the demand for that TF. We demonstrate the parameter-free predictive power of this model as a function of the copy number of the TF and the number and affinities of the available specific binding sites; such predictive control is important for the understanding of transcription and the desire to quantitatively design the output of genetic circuits. Finally, we use these experiments to dynamically measure plasmid copy number through the cell cycle.

Quantitation of the DNA tethering effect in long-range DNA looping in vivo and in vitro using the Lac and λ repressors

Efficient and specific interactions between proteins bound to the same DNA molecule can be dependent on the length of the DNA tether that connects them. Measurement of the strength of this DNA tethering effect has been largely confined to short separations between sites, and it is not clear how it contributes to long-range DNA looping interactions, such as occur over separations of tens to hundreds of kilobase pairs in vivo. Here, gene regulation experiments using the LacI and λ CI repressors, combined with mathematical modeling, were used to quantitate DNA tethering inside Escherichia coli cells over the 250- to 10,000-bp range. Although LacI and CI loop DNA in distinct ways, measurements of the tethering effect were very similar for both proteins. Tethering strength decreased with increasing separation, but even at 5- to 10-kb distances, was able to increase contact probability 10- to 20-fold and drive efficient looping. Tethering in vitro with the Lac repressor was measured for the same 600-to 3,200-bp DNAs using tethered particle motion, a single molecule technique, and was 5- to 45-fold weaker than in vivo over this range. Thus, the enhancement of looping seen previously in vivo at separations below 500 bp extends to large separations, underlining the need to understand how in vivo factors aid DNA looping. Our analysis also suggests how efficient and specific looping could be achieved over very long DNA separations, such as what occurs between enhancers and promoters in eukaryotic cells.

RNA polymerase approaches its promoter without long-range sliding along DNA

Sequence-specific DNA binding proteins must quickly bind target sequences, despite the enormously larger amount of nontarget DNA present in cells. RNA polymerases (or associated general transcription factors) are hypothesized to reach promoter sequences by facilitated diffusion (FD). In FD, a protein first binds to nontarget DNA and then reaches the target by a 1D sliding search. We tested whether Escherichia coli σ(54)RNA polymerase reaches a promoter by FD using the colocalization single-molecule spectroscopy (CoSMoS) multiwavelength fluorescence microscopy technique. Experiments directly compared the rates of initial polymerase binding to and dissociation from promoter and nonpromoter DNAs measured in the same sample under identical conditions. Binding to a nonpromoter DNA was much slower than binding to a promoter-containing DNA of the same length, indicating that the detected nonspecific binding events are not on the pathway to promoter binding. Truncating one of the DNA segments flanking the promoter to a length as short as 7 bp or lengthening it to ~3,000 bp did not alter the promoter-specific binding rate. These results exclude FD over distances corresponding to the length of the promoter or longer from playing any significant role in accelerating promoter search. Instead, the data support a direct binding mechanism, in which σ(54)RNA polymerase reaches the local vicinity of promoters by 3D diffusion through solution, and suggest that binding may be accelerated by atypical structural or dynamic features of promoter DNA. Direct binding explains how polymerase can quickly reach a promoter, despite occupancy of promoter-flanking DNA by bound proteins that would impede FD.

Stochastic models of transcription: from single molecules to single cells

Genes in prokaryotic and eukaryotic cells are typically regulated by complex promoters containing multiple binding sites for a variety of transcription factors leading to a specific functional dependence between regulatory inputs and transcriptional outputs. With increasing regularity, the transcriptional outputs from different promoters are being measured in quantitative detail in single-cell experiments thus providing the impetus for the development of quantitative models of transcription. We describe recent progress in developing models of transcriptional regulation that incorporate, to different degrees, the complexity of multi-state promoter dynamics, and its effect on the transcriptional outputs of single cells. The goal of these models is to predict the statistical properties of transcriptional outputs and characterize their variability in time and across a population of cells, as a function of the input concentrations of transcription factors. The interplay between mathematical models of different regulatory mechanisms and quantitative biophysical experiments holds the promise of elucidating the molecular-scale mechanisms of transcriptional regulation in cells, from bacteria to higher eukaryotes.

Regulation of noise in gene expression

The biochemical processes leading to the synthesis of new proteins are random, as they typically involve a small number of diffusing molecules. They lead to fluctuations in the number of proteins in a single cell as a function of time and to cell-to-cell variability of protein abundances. These in turn can lead to phenotypic heterogeneity in a population of genetically identical cells. Phenotypic heterogeneity may have important consequences for the development of multicellular organisms and the fitness of bacterial colonies, raising the question of how it is regulated. Here we review the experimental evidence that transcriptional regulation affects noise in gene expression, and discuss how the noise strength is encoded in the architecture of the promoter region. We discuss how models based on specific molecular mechanisms of gene regulation can make experimentally testable predictions for how changes to the promoter architecture are reflected in gene expression noise.

Kinetic approaches to lactose operon induction and bimodality

The quasi-equilibrium approximation is acceptable when molecular interactions are fast enough compared to circuit dynamics, but is no longer allowed when cellular activities are governed by rare events. A typical example is the lactose operon (lac), one of the most famous paradigms of transcription regulation, for which several theories still coexist to describe its behaviors. The lac system is generally analyzed by using equilibrium constants, contradicting single-event hypotheses long suggested by Novick and Weiner (1957). Enzyme induction as an all-or-none phenomenon. Proc. Natl. Acad. Sci. USA 43, 553-566) and recently refined in the study of (Choi et al., 2008. A stochastic single-molecule event triggers phenotype switching of a bacterial cell. Science 322, 442-446). In the present report, a lac repressor (LacI)-mediated DNA immunoprecipitation experiment reveals that the natural LacI-lac DNA complex built in vivo is extremely tight and long-lived compared to the time scale of lac expression dynamics, which could functionally disconnect the abortive expression bursts and forbid using the standard modes of lac bistability. As alternatives, purely kinetic mechanisms are examined for their capacity to restrict induction through: (i) widely scattered derepression related to the arrival time variance of a predominantly backward asymmetric random walk and (ii) an induction threshold arising in a single window of derepression without recourse to nonlinear multimeric binding and Hill functions. Considering the complete disengagement of the lac repressor from the lac promoter as the probabilistic consequence of a transient stepwise mechanism, is sufficient to explain the sigmoidal lac responses as functions of time and of inducer concentration. This sigmoidal shape can be misleadingly interpreted as a phenomenon of equilibrium cooperativity classically used to explain bistability, but which has been reported to be weak in this system.

Regulation of mean and noise of the in vivo kinetics of transcription under the control of the lac/ara-1 promoter

The kinetics of transcription initiation in Escherichia coli depend on the duration of two rate-limiting steps, the closed and the open complex formation. In a lac promoter variant, P(lac/ara-1), the kinetics of these steps is controlled by IPTG and arabinose. From in vivo single-RNA measurements, we find that induction affects the mean and normalized variance of the intervals between consecutive RNA productions. Transcript production is sub-Poissonian in all conditions tested. The kinetics of each step is independently controlled by a different inducer. We conclude that the regulatory mechanism of P(lac/ara-1) allows the stochasticity of gene expression to be environment-dependent.

Novel insights from hybrid LacI/GalR proteins: family-wide functional attributes and biologically significant variation in transcription repression

LacI/GalR transcription regulators have extensive, non-conserved interfaces between their regulatory domains and the 18 amino acids that serve as ‘linkers’ to their DNA-binding domains. These non-conserved interfaces might contribute to functional differences between paralogs. Previously, two chimeras created by domain recombination displayed novel functional properties. Here, we present a synthetic protein family, which was created by joining the LacI DNA-binding domain/linker to seven additional regulatory domains. Despite ‘mismatched’ interfaces, chimeras maintained allosteric response to their cognate effectors. Therefore, allostery in many LacI/GalR proteins does not require interfaces with precisely matched interactions. Nevertheless, the chimeric interfaces were not silent to mutagenesis, and preliminary comparisons suggest that the chimeras provide an ideal context for systematically exploring functional contributions of non-conserved positions. DNA looping experiments revealed higher order (dimer–dimer) oligomerization in several chimeras, which might be possible for the natural paralogs. Finally, the biological significance of repression differences was determined by measuring bacterial growth rates on lactose minimal media. Unexpectedly, moderate and strong repressors showed an apparent induction phase, even though inducers were not provided; therefore, an unknown mechanism might contribute to regulation of the lac operon. Nevertheless, altered growth correlated with altered repression, which indicates that observed functional modifications are significant.

Operator sequence alters gene expression independently of transcription factor occupancy in bacteria

A canonical quantitative view of transcriptional regulation holds that the only role of operator sequence is to set the probability of transcription factor binding, with operator occupancy determining the level of gene expression. In this work, we test this idea by characterizing repression in vivo and the binding of RNA polymerase in vitro in experiments where operators of various sequences were placed either upstream or downstream from the promoter in Escherichia coli. Surprisingly, we find that operators with a weaker binding affinity can yield higher repression levels than stronger operators. Repressor bound to upstream operators modulates promoter escape, and the magnitude of this modulation is not correlated with the repressor-operator binding affinity. This suggests that operator sequences may modulate transcription by altering the nature of the interaction of the bound transcription factor with the transcriptional machinery, implying a new layer of sequence dependence that must be confronted in the quantitative understanding of gene expression.

Dynamics of transcription of closely spaced promoters in Escherichia coli, one event at a time

Many pairs of genes in Escherichia coli are driven by closely spaced promoters. We study the dynamics of expression of such pairs of genes driven by a model at the molecule and nucleotide level with delayed stochastic dynamics as a function of the binding affinity of the RNA polymerase to the promoter region, of the geometry of the promoter, of the distance between transcription start sites (TSSs) and of the repression mechanism. We find that the rate limiting steps of transcription at the TSS, the closed and open complex formations, strongly affect the kinetics of RNA production for all promoter configurations. Beyond a certain rate of transcription initiation events, we find that the interference between polymerases correlates the dynamics of production of the two RNA molecules from the two TSS and affects the distribution of intervals between consecutive productions of RNA molecules. The degree of correlation depends on the geometry, the distance between TSSs and repressors. Small changes in the distance between TSSs can cause abrupt changes in behavior patterns, suggesting that the sequence between adjacent promoters may be subject to strong selective pressure. The results provide better understanding on the sequence level mechanisms of transcription regulation in bacteria and may aid in the genetic engineering of artificial circuits based on closely spaced promoters.