All cells use circuits of interacting genes and proteins to respond to stimuli, communicate with one another, and control their differentiation. Even when the components and regulatory interactions that compose these circuits are known, the design principles that govern circuit architecture usually remain mysterious. Why has one circuit design been selected over another? What minimal circuit designs are sufficient to implement key cellular behaviors? How can a particular circuit be rewired or perturbed to predictably alter its behavior in cells or tissues? More generally, how do genetic circuits contend with, and even utilize, stochastic fluctuations, or "noise," in their components?
To address these questions, we combine three synergistic approaches. First, we apply time-lapse movies and quantitative image analysis to follow the dynamics of genetic circuits in individual cells. Single-cell approaches are critical because many gene circuit behaviors are obscured by traditional biological techniques that average over populations of cells. Second, we develop synthetic biology approaches in which we design and construct new genetic circuits that can implement specific functions in cells, or we rewire natural circuits to test the capabilities of alternate circuit architectures. Finally, we use mathematical models to explore the dynamics of actual and potential genetic circuit architectures. We work in bacteria, yeast, and mammalian cells, model systems that enable precise genetic manipulation and measurement of the dynamics of cellular gene circuits.
The Functional Role of Noise in Cells
Cells can be strikingly heterogeneous, even when they are genetically identical and living in a homogeneous environment. We introduced methods to detect and measure stochastic fluctuations, or noise, in the expression of genes and showed that noise can be the dominant source of gene expression variation in cells. Even more dramatically, we found that noise is not just a nuisance: cells utilize noise to carry out functions that would be difficult or impossible without it.
One key role of noise is to enable probabilistic differentiation. Bacterial cells spontaneously switch among distinct physiological states with different capabilities, different sensitivities to antibiotics, and other properties. This switching occurs in an apparently stochastic fashion. For example, in Bacillus subtilis, a small fraction of cells spontaneously differentiate into the alternative cell fate of genetic competence, in which they can take up extracellular DNA from other cells. After some time, cells revert to their original vegetative state. Using movies and extensive rewiring of the underlying genetic circuitry, we showed that the key design principle underlying this system is excitability: stochastic fluctuations in cells can initiate a pulse of activation of a master transcription factor, causing a transient episode of differentiation in an inherently probabilistic fashion. The competence control circuit consists of a fast autoregulatory positive-feedback loop and a slower post-translational negative-feedback loop. This architecture enables a stochastic fluctuation in protein expression to generate a stereotyped pulse of differentiation. These pulses of differentiation are mathematically similar to the mechanism generating action potentials in neurons, despite totally different components and vastly different timescales. Excitability also allows cells to independently regulate the frequency and duration of differentiation events.
Stochastic differentiation also works at the evolutionary level. Recently, we showed how noise can enable partially penetrant developmental phenotypes, in which a mutation causes only a fraction of cells to show a new morphology. We also showed that these partially penetrant phenotypes in turn facilitate evolutionary transitions. We focused on the process of bacterial sporulation. Some bacterial species form one spore per cell, while others form two or more, a behavior that may be advantageous in some environments. Changing from one form of sporulation to the other requires simultaneous changes in multiple genes, and corresponding processes, including DNA replication, septation, and intercompartmental signaling. In B. subtilis, we discovered a stochastic cell fate determination system exposed in some mutants can lead to multiple distinct developmental fates, including ones with two spores, rather than one, per cell. This noise-dependent, partially penetrant differentiation system enables a more continuous evolutionary pathway between discrete fates.
Pulsatility in Signaling Systems
Recently, we discovered that many cells—including bacteria and eukaryotes—activate genes in a sustained series of stochastic, coherent pulses, in which most copies of a transcription factor become active simultaneously for a brief period, and then deactivate. Increasing the activation of these systems leads to an increased frequency of pulses, with little or no change in their duration or amplitude. In other words, cells use frequency-modulated (FM) pulsing to regulate genes. What functional capabilities does FM pulsing provide, and how do cells implement such systems?
In yeast, we found FM pulsing in the calcium signaling system, mediated by the Crz1 transcription factor. Calcium regulates target genes by controlling the frequency of stochastic pulses of Crz1 nuclear localization. Because of FM pulsing, cells can control the fraction of time that all target genes are turned on (this system resembles "bang-bang" control strategies in engineering). In yeast, FM pulsing enables a transcription factor to coregulate those target genes in fixed proportions, without fine-tuning of target promoters.
FM pulsing does not require a nucleus. In bacteria, we discovered that the alternative sigma factor σB is similarly controlled by frequency modulation of stochastic pulses of activation, in response to some stresses. The mechanism enabling FM pulsing in bacteria involves a phosphoswitch that amplifies noise to initiate pulses, and a feedback module that shapes the pulses. Through this simple circuit architecture, cells can implement a "DC-to-AC" converter with just a few genes.
Synthetic Biology and Intercellular Signaling Systems
Genetic circuits often appear extremely complex, making it difficult to address basic questions, such as what parts of a circuit are sufficient to implement a given behavior, and how they could be rewired to alter their functionality. To address this problem, we introduced synthetic biology approaches, in which one constructs new genetic circuits and analyzes their behavior in living cells. For example, in 2000 we developed the repressilator, a synthetic clock-like circuit composed of three repressor genes, each of which turns off one of the others, in a rock-scissors-paper configuration. This circuit is sufficient to generate self-sustaining oscillations in individual cells.
In mammalian systems, we have brought synthetic biology and single-cell techniques to the Notch signaling pathway, which enables direct cell-cell communication and is dysregulated in many diseases. We reconstituted a "diverted" Notch signaling pathway in mammalian cells and studied its dynamics at the level of individual cells. This work revealed that Notch can function as a kind of walkie-talkie, allowing individual cells to send or receive signals but not to send and receive at the same time. Moreover, this walkie-talkie-like behavior can facilitate precisely the kinds of developmental processes that Notch participates in, where neighboring cells take on distinct fates. We are now working to understand better how Notch signaling works in the presence of a more complete set of modulators, and to reconstitute more complex signaling behaviors.
These examples show some of the ways in which circuit architecture and noise together determine the behavior of individual cells. While we are expanding the use of these approaches in microbial systems, we are also using embryonic stem cells as a model system in a new effort to address conceptually related problems in mammalian differentiation and development.
This work is supported by the National Institutes of Health, the National Science Foundation, the Human Frontier Science Program, and the David and Lucile Packard Foundation.
As of November 30, 2012