Negative autoregulation linearizes the dose-response and suppresses the heterogeneity of gene expression.
ABSTRACT: Although several recent studies have focused on gene autoregulation, the effects of negative feedback (NF) on gene expression are not fully understood. Our purpose here was to determine how the strength of NF regulation affects the characteristics of gene expression in yeast cells harboring chromosomally integrated transcriptional cascades that consist of the yEGFP reporter controlled by (i) the constitutively expressed tetracycline repressor TetR or (ii) TetR repressing its own expression. Reporter gene expression in the cascade without feedback showed a steep (sigmoidal) dose-response and a wide, nearly bimodal yEGFP distribution, giving rise to a noise peak at intermediate levels of induction. We developed computational models that reproduced the steep dose-response and the noise peak and predicted that negative autoregulation changes reporter expression from bimodal to unimodal and transforms the dose-response from sigmoidal to linear. Prompted by these predictions, we constructed a "linearizer" circuit by adding TetR autoregulation to our original cascade and observed a massive (7-fold) reduction of noise at intermediate induction and linearization of dose-response before saturation. A simple mathematical argument explained these findings and indicated that linearization is highly robust to parameter variations. These findings have important implications for gene expression control in eukaryotic cells, including the design of synthetic expression systems.
Project description:Some microbiology experiments and biotechnology applications can be improved if it is possible to tune the expression of two different genes at the same time with cell-to-cell variation at or below the level of genes constitutively expressed from the chromosome (the "extrinsic noise limit"). This was recently achieved for a single gene by exploiting negative autoregulation by the tetracycline repressor (TetR) and bicistronic gene expression to reduce gene expression noise. We report new plasmids that use the same principles to achieve simultaneous, low-noise expression for two genes in Escherichia coli The TetR system was moved to a compatible plasmid backbone, and a system based on the lac repressor (LacI) was found to also exhibit gene expression noise below the extrinsic noise limit. We characterized gene expression mean and noise across the range of induction levels for these plasmids, applied the LacI system to tune expression for single-molecule mRNA detection under two different growth conditions, and showed that two plasmids can be cotransformed to independently tune expression of two different genes.IMPORTANCE Microbiologists often express foreign proteins in bacteria in order study them or to use bacteria as a microbial factory. Usually, this requires controlling the number of foreign proteins expressed in each cell, but for many common protein expression systems, it is difficult to "tune" protein expression without large cell-to-cell variation in expression levels (called "noise" in protein expression). This work describes two protein expression systems that can be combined in the same cell, with tunable expression levels and very low protein expression noise. One new system was used to detect single mRNA molecules by fluorescence microscopy, and the two systems were shown to be independent of each other. These protein expression systems may be useful in any experiment or biotechnology application that can be improved with low protein expression noise.
Project description:Experiments in synthetic biology and microbiology can benefit from protein expression systems with low cell-to-cell variability (noise) and expression levels precisely tunable across a useful dynamic range. Despite advances in understanding the molecular biology of microbial gene regulation, many experiments employ protein-expression systems exhibiting high noise and nearly all-or-none responses to induction. I present an expression system that incorporates elements known to reduce gene expression noise: negative autoregulation and bicistronic transcription. I show by stochastic simulation that while negative autoregulation can produce a more gradual response to induction, bicistronic expression of a repressor and gene of interest can be necessary to reduce noise below the extrinsic limit. I synthesized a plasmid-based system incorporating these principles and studied its properties in Escherichia coli cells, using flow cytometry and fluorescence microscopy to characterize induction dose-response, induction/repression kinetics and gene expression noise. By varying ribosome binding site strengths, expression levels from 55-10,740 molecules/cell were achieved with noise below the extrinsic limit. Individual strains are inducible across a dynamic range greater than 20-fold. Experimental comparison of different regulatory networks confirmed that bicistronic autoregulation reduces noise, and revealed unexpectedly high noise for a conventional expression system with a constitutively expressed transcriptional repressor. I suggest a hybrid, low-noise expression system to increase the dynamic range.
Project description:Tandem repeats of DNA that contain transcription factor (TF) binding sites could serve as decoys, competitively binding to TFs and affecting target gene expression. Using a synthetic system in budding yeast, we demonstrate that repeated decoy sites inhibit gene expression by sequestering a transcriptional activator and converting the graded dose-response of target promoters to a sharper, sigmoidal-like response. On the basis of both modeling and chromatin immunoprecipitation measurements, we attribute the altered response to TF binding decoy sites more tightly than promoter binding sites. Tight TF binding to arrays of contiguous repeated decoy sites only occurs when the arrays are mostly unoccupied. Finally, we show that the altered sigmoidal-like response can convert the graded response of a transcriptional positive-feedback loop to a bimodal response. Together, these results show how changing numbers of repeated TF binding sites lead to qualitative changes in behavior and raise new questions about the stability of TF/promoter binding.
Project description:RNAs play major roles in the regulation of gene expression. Hence, designer RNA molecules are increasingly explored as regulatory switches in synthetic biology. Among these, the TetR-binding RNA aptamer was selected by its ability to compete with operator DNA for binding to the bacterial repressor TetR. A fortuitous finding was that induction of TetR by tetracycline abolishes both RNA aptamer and operator DNA binding in TetR. This enabled numerous applications exploiting both the specificity of the RNA aptamer and the efficient gene repressor properties of TetR. Here, we present the crystal structure of the TetR-RNA aptamer complex at 2.7 Å resolution together with a comprehensive characterization of the TetR-RNA aptamer versus TetR-operator DNA interaction using site-directed mutagenesis, size exclusion chromatography, electrophoretic mobility shift assays and isothermal titration calorimetry. The fold of the RNA aptamer bears no resemblance to regular B-DNA, and neither does the thermodynamic characterization of the complex formation reaction. Nevertheless, the functional aptamer-binding epitope of TetR is fully contained within its DNA-binding epitope. In the RNA aptamer complex, TetR adopts the well-characterized DNA-binding-competent conformation of TetR, thus revealing how the synthetic TetR-binding aptamer strikes the chords of the bimodal allosteric behaviour of TetR to function as a synthetic regulator.
Project description:Negative feedback is known to enable biological and man-made systems to perform reliably in the face of uncertainties and disturbances. To date, synthetic biological feedback circuits have primarily relied upon protein-based, transcriptional regulation to control circuit output. Small RNAs (sRNAs) are non-coding RNA molecules that can inhibit translation of target messenger RNAs (mRNAs). In this work, we modelled, built and validated two synthetic negative feedback circuits that use rationally-designed sRNAs for the first time. The first circuit builds upon the well characterised tet-based autorepressor, incorporating an externally-inducible sRNA to tune the effective feedback strength. This allows more precise fine-tuning of the circuit output in contrast to the sigmoidal, steep input-output response of the autorepressor alone. In the second circuit, the output is a transcription factor that induces expression of an sRNA, which inhibits translation of the mRNA encoding the output, creating direct, closed-loop, negative feedback. Analysis of the noise profiles of both circuits showed that the use of sRNAs did not result in large increases in noise. Stochastic and deterministic modelling of both circuits agreed well with experimental data. Finally, simulations using fitted parameters allowed dynamic attributes of each circuit such as response time and disturbance rejection to be investigated.
Project description:Regulatory networks have evolved to allow gene expression to rapidly track changes in the environment as well as to buffer perturbations and maintain cellular homeostasis in the absence of change. Theoretical work and empirical investigation in Escherichia coli have shown that negative autoregulation confers both rapid response times and reduced intrinsic noise, which is reflected in the fact that almost half of Escherichia coli transcription factors are negatively autoregulated. However, negative autoregulation is rare amongst the transcription factors of Saccharomyces cerevisiae. This difference is surprising because E. coli and S. cerevisiae otherwise have similar profiles of network motifs. In this study we investigate regulatory interactions amongst the transcription factors of Drosophila melanogaster and humans, and show that they have a similar dearth of negative autoregulation to that seen in S. cerevisiae. We then present a model demonstrating that this striking difference in the noise reduction strategies used amongst species can be explained by constraints on the evolution of negative autoregulation in diploids. We show that regulatory interactions between pairs of homologous genes within the same cell can lead to under-dominance--mutations which result in stronger autoregulation, and decrease noise in homozygotes, paradoxically can cause increased noise in heterozygotes. This severely limits a diploid's ability to evolve negative autoregulation as a noise reduction mechanism. Our work offers a simple and general explanation for a previously unexplained difference between the regulatory architectures of E. coli and yeast, Drosophila and humans. It also demonstrates that the effects of diploidy in gene networks can have counter-intuitive consequences that may profoundly influence the course of evolution.
Project description:Gene expression can be highly heterogeneous in isogenic cell populations. An extreme type of heterogeneity is the so-called bistable or bimodal expression, whereby a cell can differentiate into two alternative expression states. Stochastic fluctuations of protein levels, also referred to as noise, provide the necessary source of heterogeneity that must be amplified by specific genetic circuits in order to obtain a bimodal response. A classical model of bimodal differentiation is the activation of genetic competence in Bacillus subtilis. The competence transcription factor ComK activates transcription of its own gene, and an intricate regulatory network controls the switch to competence and ensures its reversibility. However, it is noise in ComK expression that determines which cells activate the ComK autostimulatory loop and become competent for genetic transformation. Despite its important role in bimodal gene expression, noise remains difficult to investigate due to its inherent stochastic nature. We adapted an artificial autostimulatory loop that bypasses all known ComK regulators to screen for possible factors that affect noise. This led to the identification of a novel protein Kre (YkyB) that controls the bimodal regulation of ComK. Interestingly, Kre appears to modulate the induction of ComK by affecting the stability of comK mRNA. The protein influences the expression of many genes, however, Kre is only found in bacteria that contain a ComK homologue and, importantly, kre expression itself is downregulated by ComK. The evolutionary significance of this new feedback loop for the reduction of transcriptional noise in comK expression is discussed. Our findings show the importance of mRNA stability in bimodal regulation, a factor that requires more attention when studying and modelling this non-deterministic developmental mechanism.
Project description:Several studies highlighted the relevance of extrinsic noise in shaping cell decision making and differentiation in molecular networks. Bimodal distributions of gene expression levels provide experimental evidence of phenotypic differentiation, where the modes of the distribution often correspond to different physiological states of the system. We theoretically address the presence of bimodal phenotypes in the context of microRNA (miRNA)-mediated regulation. MiRNAs are small noncoding RNA molecules that downregulate the expression of their target mRNAs. The nature of this interaction is titrative and induces a threshold effect: below a given target transcription rate almost no mRNAs are free and available for translation. We investigate the effect of extrinsic noise on the system by introducing a fluctuating miRNA-transcription rate. We find that the presence of extrinsic noise favours the presence of bimodal target distributions which can be observed for a wider range of parameters compared to the case with intrinsic noise only and for lower miRNA-target interaction strength. Our results suggest that combining threshold-inducing interactions with extrinsic noise provides a simple and robust mechanism for obtaining bimodal populations without requiring fine tuning. Furthermore, we characterise the protein distribution's dependence on protein half-life.
Project description:Gene expression can be highly heterogeneous in clonal cell populations. An extreme type of heterogeneity is the so-called bistable or bimodal expression, whereby a cell can differentiate into two alternative expression states, and consequently a population will be composed of cells that are ‘ON’ and cells that are ‘OFF’. Stochastic fluctuations of protein levels, also referred to as noise, provide the necessary source of heterogeneity that must be amplified by autostimulatory feedback regulation to obtain the bimodal response. A classical model of bistable differentiation is the development of genetic competence in Bacillus subtilis. Noise in expression of the transcription factor ComK ultimately determines the fraction of cells that enter the competent state. Due to its intrinsic random nature, noise is difficult to investigate. We adapted an artificial autostimulatory loop that bypasses all known ComK regulators, to screen for possible factors that affect noise in the bimodal regulation of ComK. This led to the discovery of Kre, a novel factor that controls the bimodal expression of ComK. Kre appears to affect the stability of comK mRNA. Interestingly, ComK itself represses the expression of kre, adding a new double negative feedback loop to the intricate ComK regulation circuit. Our data emphasize that mRNA stability is an important factor in bimodal regulation. Comparing wild type Bacillus subtilis strain 168 (n=2) with Bacillus subtilis PG479 (Δkre, n = 3)
Project description:Gene expression can be highly heterogeneous in clonal cell populations. An extreme type of heterogeneity is the so-called bistable or bimodal expression, whereby a cell can differentiate into two alternative expression states, and consequently a population will be composed of cells that are ‘ON’ and cells that are ‘OFF’. Stochastic fluctuations of protein levels, also referred to as noise, provide the necessary source of heterogeneity that must be amplified by autostimulatory feedback regulation to obtain the bimodal response. A classical model of bistable differentiation is the development of genetic competence in Bacillus subtilis. Noise in expression of the transcription factor ComK ultimately determines the fraction of cells that enter the competent state. Due to its intrinsic random nature, noise is difficult to investigate. We adapted an artificial autostimulatory loop that bypasses all known ComK regulators, to screen for possible factors that affect noise in the bimodal regulation of ComK. This led to the discovery of Kre, a novel factor that controls the bimodal expression of ComK. Kre appears to affect the stability of comK mRNA. Interestingly, ComK itself represses the expression of kre, adding a new double negative feedback loop to the intricate ComK regulation circuit. Our data emphasize that mRNA stability is an important factor in bimodal regulation. Overall design: Comparing wild type Bacillus subtilis strain 168 (n=2) with Bacillus subtilis PG479 (Δkre, n = 3).