Synergy of repression and silencing gradients along the chromosome

Engineering Epigenetic Regulation Using Synthetic Read-Write Modules

Chemical modifications to DNA and histone proteins are involved in epigenetic programs underlying cellular differentiation and development. Regulatory networks involving molecular writers and readers of chromatin marks are thought to control these programs. Guided by this common principle, we established an orthogonal epigenetic regulatory system in mammalian cells using N6-methyladenine (m6A), a DNA modification not commonly found in metazoan epigenomes. Our system utilizes synthetic factors that write and read m6A and consequently recruit transcriptional regulators to control reporter loci. Inspired by models of chromatin spreading and epigenetic inheritance, we used our system and mathematical models to construct regulatory circuits that induce m6A-dependent transcriptional states, promote their spatial propagation, and maintain epigenetic memory of the states. These minimal circuits were able to program epigenetic functions de novo, conceptually validating "read-write" architectures. This work provides a toolkit for investigating models of epigenetic regulation and encoding additional layers of epigenetic information in cells.

Impact of Methods on the Measurement of mRNA Turnover

The turnover of the RNA molecules is determined by the rates of transcription and RNA degradation. Several methods have been developed to study RNA turnover since the beginnings of molecular biology. Here we summarize the main methods to measure RNA half-life: transcription inhibition, gene control, and metabolic labelling. These methods were used to detect the cellular activity of the mRNAs degradation machinery, including the exo-ribonuclease Xrn1 and the exosome. On the other hand, the study of the differential stability of mature RNAs has been hampered by the fact that different methods have often yielded inconsistent results. Recent advances in the systematic comparison of different method variants in yeast have permitted the identification of the least invasive methodologies that reflect half-lives the most faithfully, which is expected to open the way for a consistent quantitative analysis of the determinants of mRNA stability.

Multiplexed gene control reveals rapid mRNA turnover

The rates of mRNA synthesis and decay determine the mRNA expression level. The two processes are under coordinated control, which makes the measurements of these rates challenging, as evidenced by the low correlation among the methods of measurement of RNA half-lives. We developed a minimally invasive method, multiplexed gene control, to shut off expression of genes with controllable synthetic promoters. The method was validated by measuring the ratios of the nascent to mature mRNA molecules and by measuring the half-life with endogenous promoters that can be controlled naturally or through inserting short sequences that impart repressibility. The measured mRNA half-lives correlated highly with those obtained with the metabolic pulse-labeling method in yeast. However, mRNA degradation was considerably faster in comparison to previous estimates, with a median half-life of around 2 min. The half-life permits the estimation of promoter-dependent and promoter-independent transcription rates. The dynamical range of the promoter-independent transcription rates was larger than that of the mRNA half-lives. The rapid mRNA turnover and the broad adjustability of promoter-independent transcription rates are expected to have a major impact on stochastic gene expression and gene network behavior.

The epigenome: the next substrate for engineering

We are entering an era of epigenome engineering. The precision manipulation of chromatin and epigenetic modifications provides new ways to interrogate their influence on genome and cell function and to harness these changes for applications. We review the design and state of epigenome editing tools, highlighting the unique regulatory properties afforded by these systems.

Stochastic signalling rewires the interaction map of a multiple feedback network during yeast evolution

During evolution, genetic networks are rewired through strengthening or weakening their interactions to develop new regulatory schemes. In the galactose network, the GAL1/GAL3 paralogues and the GAL2 gene enhance their own expression mediated by the Gal4p transcriptional activator. The wiring strength in these feedback loops is set by the number of Gal4p binding sites. Here we show using synthetic circuits that multiplying the binding sites increases the expression of a gene under the direct control of an activator, but this enhancement is not fed back in the circuit. The feedback loops are rather activated by genes that have frequent stochastic bursts and fast RNA decay rates. In this way, rapid adaptation to galactose can be triggered even by weakly expressed genes. Our results indicate that nonlinear stochastic transcriptional responses enable feedback loops to function autonomously, or contrary to what is dictated by the strength of interactions enclosing the circuit.

Modeling of chromosomal epigenetic silencing processes

Silenced genes in eukaryotes are packaged into heterochromatin. In addition to establishing a passive storage site for inactive genes in differentiated cells, silencing can play an active role in promoting cellular differentiation. Here, we describe quantitative modeling of silencing processes.

Construction of cis-regulatory input functions of yeast promoters

Promoters contain a large number of binding sites for transcriptional factors transmitting signals from a variety of cellular pathways. The promoter processes these input signals and sets the level of gene expression, the output of the gene. Here, we describe how to design genetic constructs and measure gene expression to deliver data suitable for quantitative analysis. Synthetic genetic constructs are well suited to precisely control and measure gene expression to construct cis-regulatory input functions. These functions can be used to predict gene expression based on signal intensities transmitted to activators and repressors in the gene regulatory region. Simple models of gene expression are presented for competitive and noncompetitive repressions. Complex phenomena, exemplified by synergistic silencing, are modeled by reaction-diffusion equations.

Combinatorial gene regulation using auto-regulation

As many as 59% of the transcription factors in Escherichia coli regulate the transcription rate of their own genes. This suggests that auto-regulation has one or more important functions. Here, one possible function is studied. Often the transcription rate of an auto-regulator is also controlled by additional transcription factors. In these cases, the way the expression of the auto-regulator responds to changes in the concentrations of the “input” regulators (the response function) is obviously affected by the auto-regulation. We suggest that, conversely, auto-regulation may be used to optimize this response function. To test this hypothesis, we use an evolutionary algorithm and a chemical–physical model of transcription regulation to design model cis-regulatory constructs with predefined response functions. In these simulations, auto-regulation can evolve if this provides a functional benefit. When selecting for a series of elementary response functions—Boolean logic gates and linear responses—the cis-regulatory regions resulting from the simulations indeed often exploit auto-regulation. Surprisingly, the resulting constructs use auto-activation rather than auto-repression. Several design principles show up repeatedly in the simulation results. They demonstrate how auto-activation can be used to generate sharp, switch-like activation and repression circuits and how linearly decreasing response functions can be obtained. Auto-repression, on the other hand, resulted only when a high response speed or a suppression of intrinsic noise was also selected for. The results suggest that, while auto-repression may primarily be valuable to improve the dynamical properties of regulatory circuits, auto-activation is likely to evolve even when selection acts on the shape of response function only.

Bacteria adjust which proteins they make, and how many copies of each kind, depending on their environment. The production rate of each regulated protein is controlled by a special class of proteins called transcription factors. The rate at which a certain protein is produced usually depends on the cellular concentrations of a few such transcription factors. When circumstances change, the concentrations of these transcription factors alter too and consequently the production rates of all proteins regulated by them are adjusted. Interestingly, many transcription factors also regulate their own synthesis rate. This suggests that this self-regulation must have one or more important functions. In this article we study one possible function. In order for cells to function properly each protein concentration has to respond in a particular way to changes in transcription factor concentrations. We have studied how bacteria can optimize and fine-tune these responses. To this end, we formulated a physical model of the regulation by transcription factors and performed computer simulations. These simulations show that self-regulation—and in particular self-activation—is often a useful tool to achieve the prescribed response. Therefore we conclude that natural selection on the regulation of protein levels could naturally lead to self-regulation.

Spatial epigenetic control of mono- and bistable gene expression

Bistability in signaling networks is frequently employed to promote stochastic switch-like transitions between cellular differentiation states. Differentiation can also be triggered by antagonism of activators and repressors mediated by epigenetic processes that constitute regulatory circuits anchored to the chromosome. Their regulatory logic has remained unclear. A reaction-diffusion model reveals that the same reaction mechanism can support both graded monostable and switch-like bistable gene expression, depending on whether recruited repressor proteins generate a single silencing gradient or two interacting gradients that flank a gene. Our experiments confirm that chromosomal recruitment of activator and repressor proteins permits a plastic form of control; the stability of gene expression is determined by the spatial distribution of silencing nucleation sites along the chromosome. The unveiled regulatory principles will help to understand the mechanisms of variegated gene expression, to design synthetic genetic networks that combine transcriptional regulatory motifs with chromatin-based epigenetic effects, and to control cellular differentiation.

Control and signal processing by transcriptional interference

A transcriptional activator can suppress gene expression by interfering with transcription initiated by another activator. Transcriptional interference has been increasingly recognized as a regulatory mechanism of gene expression. The signals received by the two antagonistically acting activators are combined by the polymerase trafficking along the DNA. We have designed a dual-control genetic system in yeast to explore this antagonism systematically. Antagonism by an upstream activator bears the hallmarks of competitive inhibition, whereas a downstream activator inhibits gene expression non-competitively. When gene expression is induced weakly, the antagonistic activator can have a positive effect and can even trigger paradoxical activation. Equilibrium and non-equilibrium models of transcription shed light on the mechanism by which interference converts signals, and reveals that self-antagonism of activators imitates the behavior of feed-forward loops. Indeed, a synthetic circuit generates a bell-shaped response, so that the induction of expression is limited to a narrow range of the input signal. The identification of conserved regulatory principles of interference will help to predict the transcriptional response of genes in their genomic context.