Cellular rhythms are generated by complex interactions among genes, proteins and metabolites. They are used to control every aspect of cell physiology, from signalling, motility and development to growth, division and death. We consider specific examples of oscillatory processes and discuss four general requirements for biochemical oscillations: negative feedback, time delay, sufficient 'nonlinearity' of the reaction kinetics and proper balancing of the timescales of opposing chemical reactions. Positive feedback is one mechanism to delay the negative-feedback signal. Biological oscillators can be classified according to the topology of the positive- and negative-feedback loops in the underlying regulatory mechanism.

Synthetic biologists engineer complex artificial biological systems to investigate natural biological phenomena and for a variety of applications. We outline the basic features of synthetic biology as a new engineering discipline, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields. We discuss methods for designing and constructing engineered cells with novel functions in a framework of an abstract hierarchy of biological devices, modules, cells, and multicellular systems. The classical engineering strategies of standardization, decoupling, and abstraction will have to be extended to take into account the inherent characteristics of biological devices and modules. To achieve predictability and reliability, strategies for engineering biology must include the notion of cellular context in the functional definition of devices and modules, use rational redesign and directed evolution for system optimization, and focus on accomplishing tasks using cell populations rather than individual cells. The discussion brings to light issues at the heart of designing complex living systems and provides a trajectory for future development.

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.

Abstract Synthetic biology is a rapidly expanding discipline at the interface between engineering and biology. Much research in this area has focused on gene regulatory networks that function as biological switches and oscillators. Here we review the state of the art in the design and construction of oscillators, comparing the features of each of the main networks published to date, the models used for in silico design and validation and, where available, relevant experimental data. Trends are apparent in the ways that network topology constrains oscillator characteristics and dynamics. Also, noise and time delay within the network can both have constructive and destructive roles in generating oscillations, and stochastic coherence is commonplace. This review can be used to inform future work to design and implement new types of synthetic oscillators or to incorporate existing oscillators into new designs.

Gene networks exhibiting oscillatory dynamics are widespread in biology. The minimal regulatory designs giving rise to oscillations have been implemented synthetically and studied by mathematical modeling. However, most of the available analyses generally neglect the coupling of regulatory circuits with the cellular "chassis" in which the circuits are embedded. For example, the intracellular macromolecular composition of fast-growing bacteria changes with growth rate. As a consequence, important parameters of gene expression, such as ribosome concentration or cell volume, are growth-rate dependent, ultimately coupling the dynamics of genetic circuits with cell physiology. This work addresses the effects of growth rate on the dynamics of a paradigmatic example of genetic oscillator, the repressilator. Making use of empirical growth-rate dependencies of parameters in bacteria, we show that the repressilator dynamics can switch between oscillations and convergence to a fixed point depending on the cellular state of growth, and thus on the nutrients it is fed. The physical support of the circuit (type of plasmid or gene positions on the chromosome) also plays an important role in determining the oscillation stability and the growth-rate dependence of period and amplitude. This analysis has potential application in the field of synthetic biology, and suggests that the coupling between endogenous genetic oscillators and cell physiology can have substantial consequences for their functionality.

Genetic oscillators, such as circadian clocks, are constantly perturbed by molecular noise arising from the small number of molecules involved in gene regulation. One of the strongest sources of stochasticity is the binary noise that arises from the binding of a regulatory protein to a promoter in the chromosomal DNA. In this study, we focus on two minimal oscillators based on activator titration and repressor titration to understand the key parameters that are important for oscillations and for overcoming binary noise. We show that the rate of unbinding from the DNA, despite traditionally being considered a fast parameter, needs to be slow to broaden the space of oscillatory solutions. The addition of multiple, independent DNA binding sites further expands the oscillatory parameter space for the repressor-titration oscillator and lengthens the period of both oscillators. This effect is a combination of increased effective delay of the unbinding kinetics due to multiple binding sites and increased promoter ultrasensitivity that is specific for repression. We then use stochastic simulation to show that multiple binding sites increase the coherence of oscillations by mitigating the binary noise. Slow values of DNA unbinding rate are also effective in alleviating molecular noise due to the increased distance from the bifurcation point. Our work demonstrates how the number of DNA binding sites and slow unbinding kinetics, which are often omitted in biophysical models of gene circuits, can have a significant impact on the temporal and stochastic dynamics of genetic oscillators.

Abstract Synthetic biology is highly valued in the recent decade. In a previous study, Elowitz and Leibler ( Nature , vol. 403, pp. 335-338, 2000) have constructed a biological oscillator in consisting of three genes, and found out its mathematical expressions. Designing the optimal transcription rates of mRNA and the decay rates of protein concentration to track desired sinusoidal signal and achieve the best oscillation have been becoming a challenge problem since then. Actually, design of an oscillator can be regarded as a tracking design problem from the control engineer's viewpoint. Genetic algorithm (GA) bears the feature of searching the global optimum for the optimization problem. However, subject to the fixed solution structure, the results may not be the cheap ones. In this paper, we introduce the real structure genetic algorithm (RSGA) to solve the design problem of synthetic biological oscillators. The design approach is shown to be capable of yielding genetic oscillators with a cheaper structure.

Synthetic biology is highly valued in the recent decade. In a previous study, Elowitz and Leibler have made a biological oscillator in consisting of three genes, and found out its mathematical expressions. In which, design of an oscillator is regarded as a tracking design problem. Designing the optimal transcription rates of mRNA and the decaying rate of protein concentration to track desired sinusoidal signal and achieve the best oscillation have becoming a challenge. Genetic algorithm (GA) bears the feature of searching the global optimal for the optimization problem. However, directly applying that kind of algorithms usually leads to premature convergence of the solution and cannot result in solution with the cheapest structure. In this paper, we introduce the real structure genetic algorithm (RSGA) to solve for the design problem of synthetic biological oscillators. The design approach is shown to be capable of yielding genetic oscillators with a cheapest structure.

Abstract Engineering robust and tuneable genetic clocks is a topic of current interest in Systems and Synthetic Biology with wide applications in biotechnology. Synthetic genetic oscillators share a common structure based on a negative feedback loop with a time delay, and generally display only limited tuneability. Recently, the dual-feedback oscillator was demonstrated to be robust and tuneable, to some extent, by the use of chemical inducers. Yet no engineered genetic oscillator currently allows for the independent modulation of amplitude and period. In this work, we demonstrate computationally how recent advances in tuneable synthetic degradation can be used to decouple the frequency and amplitude modulation in synthetic genetic oscillators. We show how the range of tuneability can be increased by connecting additional input dials, e.g. orthogonal transcription factors that respond to chemical, temperature or even light signals. Modelling and numerical simulations predict that our proposed re-designs enable amplitude tuning without period modulation, coupled modulation of both period and amplitude, or period adjustment with near-constant amplitude. We illustrate our work through computational re-designs of both the dual-feedback oscillator and the repressilator, and show that the repressilator is more flexible and can allow for independent amplitude and near-independent period modulation.

fically, we sought to reduce error propagation and information losses, not by adding control loops, but by simply removing existing features. This created highly regular and robust oscillations. Some streamlined circuits kept 14 generation periods over a range of growth conditions and kept phase for hundreds of generations in single cells, allowing cells in flasks and colonies to oscillate synchronously without any coupling between them. Our results show that even the simplest synthetic genetic networks can achieve a precision that rivals natural systems, and emphasize the importance of noise analyses for circuit design in synthetic biology. Many biological systems show remarkably precise and robust dynamics. For example, the circadian clock in cyanobacteria uses a combination of transcriptional and post-translational control mechanisms 2 , 3 to keep phase for weeks without entrainment, while displaying robustness to changes in temperature and growth rate 3 – 5 . Synthetic circuits built from well-characterized parts can also exhibit a wide range of dynamical features – including arithmetic computations 6 , 7 , oscillations 1 , 8 – 13 , logic gates 14 and edge detection 15 – but often with lower accuracy. For example, the repressilator 1 , a now iconic device that helped jump-start the field of synthetic biology 15 years ago, showed clear signs of oscillations using a simple design where three genes inhibit each other’s production in a single loop (A⊣B⊣C⊣A). However, only about 40% of cells were found to support oscillations, and those oscillations were quite irregular. Subsequent synthetic oscillators evaluated different control topologies or repression mechanisms 8 – 13 , but most were again quite irregular in both phase and amplitude despite being mathematically designed to display sustained oscillations in a broad range of parameters. The challenge when designing synthetic circuits to operate reliably in single cells is that biochemical noise can do more than ju