Dynamical analysis on gene activity in the presence of repressors and an interfering promoter

A symmetric toggle switch explains the onset of random X inactivation in different mammals

Gene-regulatory networks control establishment and maintenance of alternative gene expression states during development. A particular challenge is the acquisition of opposing states by two copies of the same gene, as it is the case in mammals for Xist at the onset of random X-chromosome inactivation (XCI). The regulatory principles that lead to stable mono-allelic expression of Xist remain unknown. Here, we uncovered the minimal Xist regulatory network, by combining mathematical modeling and experimental validation of central model predictions. We identified a symmetric toggle switch as the basis for random mono-allelic Xist up-regulation, which reproduces data from several mutant, aneuploid and polyploid murine cell lines with various Xist expression patterns. Moreover, this toggle switch explains the diversity of strategies employed by different species at the onset of XCI. In addition to providing a unifying conceptual framework to explore X-chromosome inactivation across mammals, our study sets the stage for identifying the molecular mechanisms required to initiate random XCI.

Models of life: epigenetics, diversity and cycles

This review emphasizes aspects of biology that can be understood through repeated applications of simple causal rules. The selected topics include perspectives on gene regulation, phage lambda development, epigenetics, microbial ecology, as well as model approaches to diversity and to punctuated equilibrium in evolution. Two outstanding features are repeatedly described. One is the minimal number of rules to sustain specific states of complex systems for a long time. The other is the collapse of such states and the subsequent dynamical cycle of situations that restitute the system to a potentially new metastable state.

Directing traffic on DNA-How transcription factors relieve or induce transcriptional interference

Transcriptional interference (TI) is increasingly recognized as a widespread mechanism of gene control, particularly given the pervasive nature of transcription, both sense and antisense, across all kingdoms of life. Here, we discuss how transcription factor binding kinetics strongly influence the ability of a transcription factor to relieve or induce TI.

The role of repressor kinetics in relief of transcriptional interference between convergent promoters

Transcriptional interference (TI), where transcription from a promoter is inhibited by the activity of other promoters in its vicinity on the same DNA, enables transcription factors to regulate a target promoter indirectly, inducing or relieving TI by controlling the interfering promoter. For convergent promoters, stochastic simulations indicate that relief of TI can be inhibited if the repressor at the interfering promoter has slow binding kinetics, making it either sensitive to frequent dislodgement by elongating RNA polymerases (RNAPs) from the target promoter, or able to be a strong roadblock to these RNAPs. In vivo measurements of relief of TI by CI or Cro repressors in the bacteriophage λ PR-PRE system show strong relief of TI and a lack of dislodgement and roadblocking effects, indicative of rapid CI and Cro binding kinetics. However, repression of the same λ promoter by a catalytically dead CRISPR Cas9 protein gave either compromised or no relief of TI depending on the orientation at which it binds DNA, consistent with dCas9 being a slow kinetics repressor. This analysis shows how the intrinsic properties of a repressor can be evolutionarily tuned to set the magnitude of relief of TI.

Dynamic competition between transcription initiation and repression: Role of nonequilibrium steps in cell-to-cell heterogeneity

Transcriptional repression may cause transcriptional noise by a competition between repressor and RNA polymerase binding. Although promoter activity is often governed by a single limiting step, we argue here that the size of the noise strongly depends on whether this step is the initial equilibrium binding or one of the subsequent unidirectional steps. Overall, we show that nonequilibrium steps of transcription initiation systematically increase the cell-to-cell heterogeneity in bacterial populations. In particular, this allows also weak promoters to give substantial transcriptional noise.

Specific contacts of the -35 region of the galP1 promoter by RNA polymerase inhibit GalR-mediated DNA looping repression

The P1 promoter of the galactose operon in Escherichia coli is one of the best studied examples of ‘extended −10’ promoters. Recognition of the P1 promoter does not require specific contacts between RNA polymerase and its poor −35 element. To investigate whether specific recognition of the −35 element would affect the regulation of P1 by GalR, we mutagenized the −35 element of P1, isolated variants of the −35 element and studied the regulation of the mutant promoters by in vitro transcription assays and by mathematical modeling. The results show that the GalR-mediated DNA loop is less efficient in repressing P1 transcription when RNA polymerase binds to the −10 and −35 elements concomitantly. Our results suggest that promoters that lack specific −35 element recognition allow decoupling of local chromosome structure from transcription initiation.

Thermodynamics-based models of transcriptional regulation by enhancers: the roles of synergistic activation, cooperative binding and short-range repression

Quantitative models of cis-regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled, or heuristic approximations of the underlying regulatory mechanisms. We have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence, as a function of transcription factor concentrations and their DNA-binding specificities. It uses statistical thermodynamics theory to model not only protein-DNA interaction, but also the effect of DNA-bound activators and repressors on gene expression. In addition, the model incorporates mechanistic features such as synergistic effect of multiple activators, short range repression, and cooperativity in transcription factor-DNA binding, allowing us to systematically evaluate the significance of these features in the context of available expression data. Using this model on segmentation-related enhancers in Drosophila, we find that transcriptional synergy due to simultaneous action of multiple activators helps explain the data beyond what can be explained by cooperative DNA-binding alone. We find clear support for the phenomenon of short-range repression, where repressors do not directly interact with the basal transcriptional machinery. We also find that the binding sites contributing to an enhancer's function may not be conserved during evolution, and a noticeable fraction of these undergo lineage-specific changes. Our implementation of the model, called GEMSTAT, is the first publicly available program for simultaneously modeling the regulatory activities of a given set of sequences.

The development of complex multicellular organisms requires genes to be expressed at specific stages and in specific tissues. Regulatory DNA sequences, often called cis-regulatory modules, drive the desired gene expression patterns by integrating information about the environment in the form of the activities of transcription factors. The rules by which regulatory sequences read this type of information, however, are unclear. In this work, we developed quantitative models based on physicochemical principles that directly map regulatory sequences to the expression profiles they generate. We evaluated these models on the segmentation network of the model organism Drosophila melanogaster. Our models incorporate mechanistic features that attempt to capture how activating and repressing transcription factors work in the segmentation system. By evaluating the importance of these features, we were able to gain insights on the quantitative regulatory rules. We found that two different mechanisms may contribute to cooperative gene activation and that repressors often have a short range of influence in DNA sequences. Combining the quantitative modeling with comparative sequence analysis, we also found that even functional sequences may be lost during evolution.

Simplified models of biological networks

The function of living cells is controlled by complex regulatory networks that are built of a wide diversity of interacting molecular components. The sheer size and intricacy of molecular networks of even the simplest organisms are obstacles toward understanding network functionality. This review discusses the achievements and promise of a bottom-up approach that uses well-characterized subnetworks as model systems for understanding larger networks. It highlights the interplay between the structure, logic, and function of various types of small regulatory circuits. The bottom-up approach advocates understanding regulatory networks as a collection of entangled motifs. We therefore emphasize the potential of negative and positive feedback, as well as their combinations, to generate robust homeostasis, epigenetics, and oscillations.

Modeling of the genetic switch of bacteriophage TP901-1: A heteromer of CI and MOR ensures robust bistability

The lytic-lysogenic switch of the temperate lactococcal phage TP901-1 is fundamentally different from that of phage lambda. In phage TP901-1, the lytic promoter P(L) is repressed by CI, whereas repression of the lysogenic promoter P(R) requires the presence of both of the antagonistic regulator proteins, MOR and CI. We model the central part of the switch and compare the two cases for P(R) repression: the one where the two regulators interact only on the DNA and the other where the two regulators form a heteromer complex in the cytoplasm prior to DNA binding. The models are analyzed for bistability, and the predicted promoter repression folds are compared to experimental data. We conclude that the experimental data are best reproduced the latter case, where a heteromer complex forms in solution. We further find that CI sequestration by the formation of MOR:CI complexes in cytoplasm makes the genetic switch robust.