Lev S. Tsimring

A synchronized quorum of genetic clocks

The engineering of genetic circuits with predictive functionality in living cells represents a defining focus of the expanding field of synthetic biology. This focus was elegantly set in motion a decade ago with the design and construction of a genetic toggle switch and an oscillator, with subsequent highlights that have included circuits capable of pattern generation, noise shaping, edge detection and event counting. Here we describe an engineered gene network with global intercellular coupling that is capable of generating synchronized oscillations in a growing population of cells. Using microfluidic devices tailored for cellular populations at differing length scales, we investigate the collective synchronization properties along with spatiotemporal waves occurring at millimetre scales. We use computational modelling to describe quantitatively the observed dependence of the period and amplitude of the bulk oscillations on the flow rate. The synchronized genetic clock sets the stage for the use of microbes in the creation of a macroscopic biosensor with an oscillatory output. Furthermore, it provides a specific model system for the generation of a mechanistic description of emergent coordinated behaviour at the colony level.

Patterns and collective behavior in granular media: Theoretical concepts

Granular materials are ubiquitous in our daily lives. While they have been a subject of intensive engineering research for centuries, in the last decade granular matter attracted significant attention of physicists. Yet despite a major efforts by many groups, the theoretical description of granular systems remains largely a plethora of different, often contradicting concepts and approaches. Authors give an overview of various theoretical models emerged in the physics of granular matter, with the focus on the onset of collective behavior and pattern formation. Their aim is two-fold: to identify general principles common for granular systems and other complex non-equilibrium systems, and to elucidate important distinctions between collective behavior in granular and continuum pattern-forming systems.

Metabolic gene regulation in a dynamically changing environment

Natural selection dictates that cells constantly adapt to dynamically changing environments in a context-dependent manner. Gene-regulatory networks often mediate the cellular response to perturbation, and an understanding of cellular adaptation will require experimental approaches aimed at subjecting cells to a dynamic environment that mimics their natural habitat. Here we monitor the response of Saccharomyces cerevisiae metabolic gene regulation to periodic changes in the external carbon source by using a microfluidic platform that allows precise, dynamic control over environmental conditions. We show that the metabolic system acts as a low-pass filter that reliably responds to a slowly changing environment, while effectively ignoring fast fluctuations. The sensitive low-frequency response was significantly faster than in predictions arising from our computational modelling, and this discrepancy was resolved by the discovery that two key galactose transcripts possess half-lives that depend on the carbon source. Finally, to explore how induction characteristics affect frequency response, we compare two S. cerevisiae strains and show that they have the same frequency response despite having markedly different induction properties. This suggests that although certain characteristics of the complex networks may differ when probed in a static environment, the system has been optimized for a robust response to a dynamically changing environment.

Performance analysis of correlation-based communication schemes utilizing chaos

Using chaotic signals in spread-spectrum communications has a few clear advantages over traditional approaches. Chaotic signals are nonperiodic, wideband, and more difficult to predict, reconstruct, and characterize than periodic carriers. These properties of chaotic signals make it more difficult to intercept and decode the information modulated upon them. However, many suggested chaos-based communication schemes do not provide processing gain, a feature highly desirable in spread-spectrum communication schemes. In this paper, we suggest two communication schemes that provide a processing gain. The performance of these and of the earlier proposed differential chaos shift keying is studied analytically and numerically for discrete time implementations. It is shown that, when performance is characterized by the dependence of bit error rate on E/sub b//N/sub 0/, the increase of the spreading sequence length beyond a certain point degrades the performance. For a given E/sub b//N/sub 0/, there is a length of the spreading sequence that minimizes the bit error rate.

A sensing array of radically coupled genetic /`biopixels/'

Although there has been considerable progress in the development of engineering principles for synthetic biology, a substantial challenge is the construction of robust circuits in a noisy cellular environment. Such an environment leads to considerable intercellular variability in circuit behaviour, which can hinder functionality at the colony level. Here we engineer the synchronization of thousands of oscillating colony ‘biopixels’ over centimetre-length scales through the use of synergistic intercellular coupling involving quorum sensing within a colony and gas-phase redox signalling between colonies. We use this platform to construct a liquid crystal display (LCD)-like macroscopic clock that can be used to sense arsenic via modulation of the oscillatory period. Given the repertoire of sensing capabilities of bacteria such as Escherichia coli, the ability to coordinate their behaviour over large length scales sets the stage for the construction of low cost genetic biosensors that are capable of detecting heavy metals and pathogens in the field.

Noise-Induced Dynamics in Bistable Systems with Delay

Noise-induced dynamics of a prototypical bistable system with delayed feedback is studied theoretically and numerically. For small noise and magnitude of the feedback, the problem is reduced to the analysis of the two-state model with transition rates depending on the earlier state of the system. Analytical solutions for the autocorrelation function and the power spectrum have been found. The power spectrum has a peak at the frequency corresponding to the inverse delay time, whose amplitude has a maximum at a certain noise level, thus demonstrating coherence resonance. The linear response to the external periodic force also has maxima at the frequencies corresponding to the inverse delay time and its harmonics.

Chaotic pulse position modulation: a robust method of communicating with chaos

In this letter we investigate a communication strategy for digital ultra-wide bandwidth impulse radio, where the separation between the adjacent pulses is chaotic arising from a dynamical system with irregular behavior. A pulse position method is used to modulate binary information onto the carrier. The receiver is synchronized to the chaotic pulse train, thus providing the time reference for information extraction. We characterize the performance of this scheme in terms of error probability versus E/sub b//N/sub 0/ by numerically simulating its operation in the presence of noise and filtering.

Accurate information transmission through dynamic biochemical signaling networks

Stochasticity inherent to biochemical reactions (intrinsic noise) and variability in cellular states (extrinsic noise) degrade information transmitted through signaling networks. We analyzed the ability of temporal signal modulation—that is, dynamics—to reduce noise-induced information loss. In the extracellular signal–regulated kinase (ERK), calcium (Ca2+), and nuclear factor kappa-B (NF-κB) pathways, response dynamics resulted in significantly greater information transmission capacities compared to nondynamic responses. Theoretical analysis demonstrated that signaling dynamics has a key role in overcoming extrinsic noise. Experimental measurements of information transmission in the ERK network under varying signal-to-noise levels confirmed our predictions and showed that signaling dynamics mitigate, and can potentially eliminate, extrinsic noise–induced information loss. By curbing the information-degrading effects of cell-to-cell variability, dynamic responses substantially increase the accuracy of biochemical signaling networks. Signaling dynamics increase the information transmission capacity of biochemical signaling pathways. Dynamic signals enhance information transfer Cells need to process information about their external environment reliably to survive. However, variation, or noise, in biochemical reactions, or in the states of individual cells, make it hard for a cell to detect concentration, rather than just the presence or absence of an activating ligand. Selimkhanov et al. show that cellular signaling circuits get around this problem by continually monitoring signals over time. Such dynamic responses in cultured human cells more effectively distinguish signals from noise and thus avoid loss of information transmitted to the cell from external signals. Science, this issue p. 1370

Swarming and Swirling in Self-Propelled Polar Granular Rods

Using experiments with anisotropic vibrated rods and quasi-2D numerical simulations, we show that shape plays an important role in the collective dynamics of self-propelled (SP) particles. We demonstrate that SP rods exhibit local ordering, aggregation at the side walls, and clustering absent in round SP particles. Furthermore, we find that at sufficiently strong excitation SP rods engage in a persistent swirling motion in which the velocity is strongly correlated with particle orientation.

Entrainment of a Population of Synthetic Genetic Oscillators

A positive-feedback loop in a biological oscillator allows effective setting of the clock by external cues. Biological clocks are self-sustained oscillators that adjust their phase to the daily environmental cycles in a process known as entrainment. Molecular dissection and mathematical modeling of biological oscillators have progressed quite far, but quantitative insights on the entrainment of clocks are relatively sparse. We simultaneously tracked the phases of hundreds of synthetic genetic oscillators relative to a common external stimulus to map the entrainment regions predicted by a detailed model of the clock. Synthetic oscillators were frequency-locked in wide intervals of the external period and showed higher-order resonance. Computational simulations indicated that natural oscillators may contain a positive-feedback loop to robustly adapt to environmental cycles.