Attila Becskei

Engineering stability in gene networks by autoregulation

The genetic and biochemical networks which underlie such things as homeostasis in metabolism and the developmental programs of living cells, must withstand considerable variations and random perturbations of biochemical parameters. These occur as transient changes in, for example, transcription, translation, and RNA and protein degradation. The intensity and duration of these perturbations differ between cells in a population. The unique state of cells, and thus the diversity in a population, is owing to the different environmental stimuli the individual cells experience and the inherent stochastic nature of biochemical processes (for example, refs 5 and 6). It has been proposed, but not demonstrated, that autoregulatory, negative feedback loops in gene circuits provide stability, thereby limiting the range over which the concentrations of network components fluctuate. Here we have designed and constructed simple gene circuits consisting of a regulator and transcriptional repressor modules in Escherichia coli and we show the gain of stability produced by negative feedback.

Positive feedback in eukaryotic gene networks: cell differentiation by graded to binary response conversion

Feedback is a ubiquitous control mechanism of gene networks. Here, we have used positive feedback to construct a synthetic eukaryotic gene switch in Saccharomyces cerevisiae. Within this system, a continuous gradient of constitutively expressed transcriptional activator is translated into a cell phenotype switch when the activator is expressed autocatalytically. This finding is consistent with a mathematical model whose analysis shows that continuous input parameters are converted into a bimodal probability distribution by positive feedback, and that this resembles analog–digital conversion. The autocatalytic switch is a robust property in eukaryotic gene expression. Although the behavior of individual cells within a population is random, the proportion of the cell population displaying either low or high expression states can be regulated. These results have implications for understanding the graded and probabilistic mechanisms of enhancer action and cell differentiation.

Enhancement of cellular memory by reducing stochastic transitions.

On induction of cell differentiation, distinct cell phenotypes are encoded by complex genetic networks. These networks can prevent the reversion of established phenotypes even in the presence of significant fluctuations. Here we explore the key parameters that determine the stability of cellular memory by using the yeast galactose-signalling network as a model system. This network contains multiple nested feedback loops. Of the two positive feedback loops, only the loop mediated by the cytoplasmic signal transducer Gal3p is able to generate two stable expression states with a persistent memory of previous galactose consumption states. The parallel loop mediated by the galactose transporter Gal2p only increases the expression difference between the two states. A negative feedback through the inhibitor Gal80p reduces the strength of the core positive feedback. Despite this, a constitutive increase in the Gal80p concentration tunes the system from having destabilized memory to having persistent memory. A model reveals that fluctuations are trapped more efficiently at higher Gal80p concentrations. Indeed, the rate at which single cells randomly switch back and forth between expression states was reduced. These observations provide a quantitative understanding of the stability and reversibility of cellular differentiation states.

Contributions of low molecule number and chromosomal positioning to stochastic gene expression

The presence of low-copy-number regulators and switch-like signal propagation in regulatory networks are expected to increase noise in cellular processes. We developed a noise amplifier that detects fluctuations in the level of low-abundance mRNAs in yeast. The observed fluctuations are not due to the low number of molecules expressed from a gene per se but originate in the random, rare events of gene activation. The frequency of these events and the correlation between stochastic expressions of genes in a single cell depend on the positioning of the genes along the chromosomes. Transcriptional regulators produced by such random expression propagate noise to their target genes.

Binary and Graded Responses in Gene Networks

Although gene expression can be regulated in a graded or a binary fashion, the majority of eukaryotic genes are either fully activated or not expressed at all in individual cells. This binary response might be an inherent property of many eukaryotic promoters. Analysis of transcription under the control of yeast GAL1 promoter suggests, however, that graded and binary modes of transcription are not mutually exclusive, but that both can occur at the same promoter when the activity of different signaling pathways is varied. In view of that, it can be expected that forthcoming experimental studies on the combinatorial effects of signaling and transcriptional mechanisms will reveal new strategies for generating graded or binary responses.

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.

The strategy for coupling the RanGTP gradient to nuclear protein export

The Ran GTPase plays critical roles in both providing energy for and determining the directionality of nucleocytoplasmic transport. The mechanism that couples the RanGTP gradient to nuclear protein export will determine the rate of and limits to accumulation of export cargoes in the cytoplasm, but is presently unknown. We reasoned that plausible coupling mechanisms could be distinguished by comparing the rates of reverse motion of export cargoes through the nuclear pore complex (NPC) with the predictions of a mathematical model. Measurement of reverse export rates in Xenopus oocytes revealed that nuclear export signals can facilitate RanGTP-dependent cargo movement into the nucleus against the RanGTP gradient at rates comparable to export rates. Although export cargoes with high affinity for their receptor are exported faster than those with low affinity, their reverse transport is also greater. The ratio of the rates of reverse and forward export of a cargo is proportional to its rate of diffusion through the NPC, i.e., to the ability of the cargo to penetrate the NPC permeability barrier. The data substantiate a diffusional mechanism of coupling and suggest the existence of a high concentration of RanGTP-receptor complexes within the NPC that decreases sharply at the cytoplasmic boundary of the NPC permeability barrier.

Spatial Epigenetic Control of Mono- and Bistable Gene Expression

Changes in the spatial distribution of regulatory protein binding elements relative to gene coding sequences is sufficient to change gene expression patterns from graded to switch-like.

Contribution of IL‐12R mediated feedback loop to Th1 cell differentiation

T helper 1 (Th1) cell fate is induced by overlapping signaling pathways, whose kinetic principles and regulatory motifs are largely unknown. We identified a simple positive feedback loop in the STAT4 signaling pathway, whereby activation by IL‐12 leads to the increased expression in IL‐12 receptor. A computational analysis shows that this feedback loop synergizes with the one mediated by the IFN‐γ secreted by differentiating cells, when the induction of Th1 cell fate is weak. Positive feedback loops are often utilized to enhance phenotypic differentiation. This effect was confirmed by experiments showing that stochastic fluctuations in the expression of IL‐12 receptor gene were amplified, leading to two discrete levels of expression in a cell population.

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.