Michael B. Elowitz

A synthetic oscillatory network of transcriptional regulators

Networks of interacting biomolecules carry out many essential functions in living cells, but the ‘design principles’ underlying the functioning of such intracellular networks remain poorly understood, despite intensive efforts including quantitative analysis of relatively simple systems. Here we present a complementary approach to this problem: the design and construction of a synthetic network to implement a particular function. We used three transcriptional repressor systems that are not part of any natural biological clock to build an oscillating network, termed the repressilator, in Escherichia coli. The network periodically induces the synthesis of green fluorescent protein as a readout of its state in individual cells. The resulting oscillations, with typical periods of hours, are slower than the cell-division cycle, so the state of the oscillator has to be transmitted from generation to generation. This artificial clock displays noisy behaviour, possibly because of stochastic fluctuations of its components. Such ‘rational network design’ may lead both to the engineering of new cellular behaviours and to an improved understanding of naturally occurring networks.

Intrinsic and extrinsic contributions to stochasticity in gene expression

Gene expression is a stochastic, or “noisy,” process. This noise comes about in two ways. The inherent stochasticity of biochemical processes such as transcription and translation generates “intrinsic” noise. In addition, fluctuations in the amounts or states of other cellular components lead indirectly to variation in the expression of a particular gene and thus represent “extrinsic” noise. Here, we show how the total variation in the level of expression of a given gene can be decomposed into its intrinsic and extrinsic components. We demonstrate theoretically that simultaneous measurement of two identical genes per cell enables discrimination of these two types of noise. Analytic expressions for intrinsic noise are given for a model that involves all the major steps in transcription and translation. These expressions give the sensitivity to various parameters, quantify the deviation from Poisson statistics, and provide a way of fitting experiment. Transcription dominates the intrinsic noise when the average number of proteins made per mRNA transcript is greater than ≃2. Below this number, translational effects also become important. Gene replication and cell division, included in the model, cause protein numbers to tend to a limit cycle. We calculate a general form for the extrinsic noise and illustrate it with the particular case of a single fluctuating extrinsic variable—a repressor protein, which acts on the gene of interest. All results are confirmed by stochastic simulation using plausible parameters for Escherichia coli.

Functional roles for noise in genetic circuits

The genetic circuits that regulate cellular functions are subject to stochastic fluctuations, or ‘noise’, in the levels of their components. Noise, far from just a nuisance, has begun to be appreciated for its essential role in key cellular activities. Noise functions in both microbial and eukaryotic cells, in multicellular development, and in evolution. It enables coordination of gene expression across large regulons, as well as probabilistic differentiation strategies that function across cell populations. At the longest timescales, noise may facilitate evolutionary transitions. Here we review examples and emerging principles that connect noise, the architecture of the gene circuits in which it is present, and the biological functions it enables. We further indicate some of the important challenges and opportunities going forward.

An excitable gene regulatory circuit induces transient cellular differentiation.

Certain types of cellular differentiation are probabilistic and transient. In such systems individual cells can switch to an alternative state and, after some time, switch back again. In Bacillus subtilis, competence is an example of such a transiently differentiated state associated with the capability for DNA uptake from the environment. Individual genes and proteins underlying differentiation into the competent state have been identified, but it has been unclear how these genes interact dynamically in individual cells to control both spontaneous entry into competence and return to vegetative growth. Here we show that this behaviour can be understood in terms of excitability in the underlying genetic circuit. Using quantitative fluorescence time-lapse microscopy, we directly observed the activities of multiple circuit components simultaneously in individual cells, and analysed the resulting data in terms of a mathematical model. We find that an excitable core module containing positive and negative feedback loops can explain both entry into, and exit from, the competent state. We further tested this model by analysing initiation in sister cells, and by re-engineering the gene circuit to specifically block exit. Excitable dynamics driven by noise naturally generate stochastic and transient responses, thereby providing an ideal mechanism for competence regulation.

Negative Autoregulation Speeds the Response Times of Transcription Networks

Cells regulate gene expression using networks of transcription interactions; it is of interest to discover the principles that govern the dynamical behavior of such networks. An important characteristic of these systems is the rise-time: the delay from the initiation of production until half maximal product concentration is reached. Here we employ synthetic gene circuits in Escherichia coli to measure the rise-times of non-self-regulated and of negatively autoregulated transcription units. Non-self-regulated units have a rise-time of one cell-cycle. We demonstrate experimentally that negative autoregulation feedback (also termed autogenous control) reduces the rise-time to about one fifth of a cell-cycle. This agrees with an analytical solution of a mathematical model for negative autoregulation. This may help in understanding the function of negative autoregulation, which appears in over 40% of known transcription factors in E.coli.

Cis -interactions between Notch and Delta generate mutually exclusive signalling states

The Notch–Delta signalling pathway allows communication between neighbouring cells during development. It has a critical role in the formation of ‘fine-grained’ patterns, generating distinct cell fates among groups of initially equivalent neighbouring cells and sharply delineating neighbouring regions in developing tissues. The Delta ligand has been shown to have two activities: it transactivates Notch in neighbouring cells and cis-inhibits Notch in its own cell. However, it remains unclear how Notch integrates these two activities and how the resulting system facilitates pattern formation. Here we report the development of a quantitative time-lapse microscopy platform for analysing Notch–Delta signalling dynamics in individual mammalian cells, with the aim of addressing these issues. By controlling both cis- and trans-Delta concentrations, and monitoring the dynamics of a Notch reporter, we measured the combined cis–trans input–output relationship in the Notch–Delta system. The data revealed a striking difference between the responses of Notch to trans- and cis-Delta: whereas the response to trans-Delta is graded, the response to cis-Delta is sharp and occurs at a fixed threshold, independent of trans-Delta. We developed a simple mathematical model that shows how these behaviours emerge from the mutual inactivation of Notch and Delta proteins in the same cell. This interaction generates an ultrasensitive switch between mutually exclusive sending (high Delta/low Notch) and receiving (high Notch/low Delta) signalling states. At the multicellular level, this switch can amplify small differences between neighbouring cells even without transcription-mediated feedback. This Notch–Delta signalling switch facilitates the formation of sharp boundaries and lateral-inhibition patterns in models of development, and provides insight into previously unexplained mutant behaviours.

Tunability and Noise Dependence in Differentiation Dynamics

The dynamic process of differentiation depends on the architecture, quantitative parameters, and noise of underlying genetic circuits. However, it remains unclear how these elements combine to control cellular behavior. We analyzed the probabilistic and transient differentiation of Bacillus subtilis cells into the state of competence. A few key parameters independently tuned the frequency of initiation and the duration of competence episodes and allowed the circuit to access different dynamic regimes, including oscillation. Altering circuit architecture showed that the duration of competence events can be made more precise. We used an experimental method to reduce global cellular noise and showed that noise levels are correlated with frequency of differentiation events. Together, the data reveal a noise-dependent circuit that is remarkably resilient and tunable in terms of its dynamic behavior.

Frequency-modulated nuclear localization bursts coordinate gene regulation

In yeast, the transcription factor Crz1 is dephosphorylated and translocates into the nucleus in response to extracellular calcium. Here we show, using time-lapse microscopy, that Crz1 exhibits short bursts of nuclear localization (typically lasting 2 min) that occur stochastically in individual cells and propagate to the expression of downstream genes. Strikingly, calcium concentration controls the frequency, but not the duration, of localization bursts. Using an analytic model, we also show that this frequency modulation of bursts ensures proportional expression of multiple target genes across a wide dynamic range of expression levels, independent of promoter characteristics. We experimentally confirm this theory with natural and synthetic Crz1 target promoters. Another stress-response transcription factor, Msn2, exhibits similar, but largely uncorrelated, localization bursts under calcium stress suggesting that frequency-modulation regulation of localization bursts may be a general control strategy used by the cell to coordinate multi-gene responses to external signals.

Reconstruction of genetic circuits

The complex genetic circuits found in cells are ordinarily studied by analysis of genetic and biochemical perturbations. The inherent modularity of biological components like genes and proteins enables a complementary approach: one can construct and analyse synthetic genetic circuits based on their natural counterparts. Such synthetic circuits can be used as simple in vivo models to explore the relation between the structure and function of a genetic circuit. Here we describe recent progress in this area of synthetic biology, highlighting newly developed genetic components and biological lessons learned from this approach.

Programming gene expression with combinatorial promoters.

Promoters control the expression of genes in response to one or more transcription factors (TFs). The architecture of a promoter is the arrangement and type of binding sites within it. To understand natural genetic circuits and to design promoters for synthetic biology, it is essential to understand the relationship between promoter function and architecture. We constructed a combinatorial library of random promoter architectures. We characterized 288 promoters in Escherichia coli, each containing up to three inputs from four different TFs. The library design allowed for multiple −10 and −35 boxes, and we observed varied promoter strength over five decades. To further analyze the functional repertoire, we defined a representation of promoter function in terms of regulatory range, logic type, and symmetry. Using these results, we identified heuristic rules for programming gene expression with combinatorial promoters.