Genetic circuits, composed of interacting genes and proteins, enable individual cells to respond to signals and environmental conditions, make decisions, and communicate with one another. What are the key design principles of genetic circuits? And, how do these circuits function dynamically in individual cells and multicellular systems? To address these questions, we develop and use several experimental approaches. We build our own synthetic genetic circuits and study their functions in bacteria, yeast, and mammalian cells. These synthetic circuits are simpler counterparts to the complex circuits one finds in nature. This approach is often called "synthetic biology."

  • We make time-lapse movies to quantitatively observe dynamics of natural and synthetic genetic circuits in individual cells.  These experiments take advantage of multiple fluorescent proteins to observe several parts of a circuit simultaneously in the same cell.
  • We study variability within cell populations, to understand how genetic circuits generate variability, through stochastic fluctuations, or "noise," how they use this variability (for differentiation and evolution), and how they operate reliably in spite of variability. 

Projects in the lab make use of mathematical models of genetic circuits.

Examples of recent projects:

  • Cell signaling at the single-cell level: Mammalian cells have a diverse, but conserved repertoire of intercellular signaling pathways that enable physiological and developmental functions. We have an increasingly detailed understanding of the components and molecular interactions in these pathways. But it is often unclear exactly what functionality these interactions provide. To address these issues we have begun studying signaling pathways quantitatively at the level of individual cells.

    • The Notch signaling pathway can act as a "walkie-talkie." The Notch signaling pathway enables neighboring cells to directly Send Receive communicate with one another. Recently, we began analyzing Notch signaling quantitatively at the level of individual cells. These studies (Sprinzak et al, Nature 2010) suggest that inhibitory same-cell interactions between the Notch receptor and its ligand, Delta, have significant consequences for the possible modes of intercellular signaling. In particular, these interactions prevent individual cells from efficiently sending and receiving signals at the same time. This "walkie-talkie"-like effect can facilitate developmental patterning processes (Sprinzak et al, PLoS Comp. Bio. 2011).

  • Send ReceiveCells use pulsing as a key mode of regulation: Cells must respond to external signals and other environmental conditions. Recently, we have discovered that both bacteria and eukaryotic cells respond to constant conditions with a sustained series of stochastic pulses of activation of key regulators.

    • Bacteria convert constant stress inputs into frequency-modulated pulsatile outputs with a noise-dependent "DC-to-AC" converter. DC_to_AC In the bacteria B. subtilis, we found that the general stress response pathway is activated in a sustained series of pulses. A core circuit modulates pulse frequency in response to levels of stress. This circuit uses a two-stage system: The first stage initiates pulses using an ultrasensitive phospho-switch. The second stage amplifies and terminates pulses using feedback loops. This simple module, composed only of a few genes, thereby provideds a kind of "DC-to-AC" conversion capability for the cell (Locke et al, Science 2011). See MOVIE.

    • Bacteria pulse to procrastinate. B. subtilis cells can turn into dormant spores. Under some conditions, they postpone bacteria sporulate this dramatic response for multiple cell cycles and, moreover, do so in a cell autonomous fashion (i.e. each cell has its own internal "timer"). How can cells implement a timer that works on a timescale of many cell divisions? Our recent work shows that this timer capability depends on a core pulsed positive feedback loop, and suggests ways that cells might use pulsing to enable new kinds of regulatory mechanisms that would be difficult to achieve with continuous regulatory systems(Levine et al, PLoS Biology, 2012).

    • FM pulsing coordinates gene expression in yeast: In yeast, calcium signaling modulates the frequency of stochastic pulses of nuclear translocation of the Czr1 transcription factor. This mode of reglulation enables cells to coordinate the expression of a large regulon of target genes, so that many genes can be expressed in fixed proportions across a broad range of activation levels (Cai et al, Nature 2008).

  • Noise, partial penetrance, and evolution: A classic problem in evolution is to understand how an organism can evolve from one discrete phenotype to another if multiple mutations are required. In development, some mutations cause discrete qualitative changes in phenotype but do so only in a fraction of individuals. Such mutations are said to be "partially penetrant." We recently found that in B. subtilis sporulation, partially penetrant mutations enable a range of specific alternative developmental phenotypes that are not seen in wild-type cells. In particular, mutants will occasionally make spores two at a time in a manner similar to that seen in some species, but not in B. subtilis. This "twin" phenotype emerges rarely, but its penetrance can be increased through specific mutations affecting DNA replication, cell septation, and intercompartmental signaling. By enabling a smooth evolutionary trajectory from making single spores to making twin spores, partial penetrance facilitates discrete evolutionary transitions in bacterial development (Eldar et al, Nature 2009).

  • Cell fate decision-making: How do cells make random decisions about whether and when to differentiate? And once they do decide, how do they ensure that differentiation proceeds in an orderly fashion? Both questions hinge on the ability of genetic circuits to manage fluctuations, or noise, within their own components. Noise enables genetically identical cells to make different decisions in the same environment, effectively "rolling the dice." Recently, we have begun to use Bacillus subtilis as a model organism to address these questions. In B. subtilis, competence is a transient differentiated state in which cells can take up extracellular DNA. The decision to become competent is probabilistic and occurs in at most 10-20% of cells. Using time-lapse fluorescence microscopy movies, we analyzed the dynamics of the genetic circuit controlling competence at the single-cell level (Süel et al, Nature 2006). Our results suggest that entry into competence and subsequent exit from it are controlled together by a core module of three genes which generate noise-excitable dynamics in a cell-autonomous fashion. (An excitable system, such as a neuron, is one in which a small perturbation can generate a well-defined response, such as an action potential). These results show that cells have evolved a dynamical mechanism which allows them to regulate the probability of competence much as a neural system can control the firing rate of action potentials.
  • Tuning and re-wiring of differentiation circuits: How does the behavior of a genetic circuit depend on its architecture, quantitative parameter values, and noise?  We study this question using the example of competence differentiation in B. subtilis (Süel et al, Science 2007)By re-wiring the circuit, systematically perturbing the basal expression levels of key genes, and reducing global noise levels, we have been able to identify new principles underlying the operation of this cell fate decision system.   For example, we found that the system reliably maintains the ability to transiently differentiate across a wide range of parameter values.  At the same time, it exhibits tunability, by which the probability and duration of differentiation events can be quantitatively and independently adjusted using gene expression levels.  Under other expression levels, cells even exhibit qualitatively different behaviors such as oscillation.  These results show that the system possesses evolutionary plasticity.  The wild-type and potential behaviors can be understood together in the context of a stochastic model of the underlying circuitry. Other techniques like re-wiring of this circuit, showed that the precision of differentiation events can be increased, while in vivo noise reduction provides strong evidence that differentiation actually depends on fluctuations in this system.  Together these results show how a cell fate decision system can be understood quantitatively at the single-cell level, and provide a framework for tackling analogous phenomena at other levels of biological organization.
  • Synthetic biology: One example of this approach is the Repressilator, a synthetic oscillatory network constructed in the bacteria Escherichia coli (Elowitz & Leibler, Nature 2000). The Repressilator is designed to cause oscillations in the level of gene expression over time in individual cells. It consists of a negative feedback loop of three transcriptional repressors. When combined with a green fluorescent reporter gene, the Repressilator causes growing E. coli cells to flash periodically, or twinkle, demonstrating that oscillations can be genetically programmed. Interestingly, these programmed oscillations are far less regular than those of natural cellular clocks, such as the circadian clock that operates in many organisms. We are interested in how natural biological clocks behave so reliably, and conversely, in understanding what, if anything, limits the accuracy of synthetic genetic clocks.  Another example is a recent study of the functions generated by a library of 'random' genetic circuits (Guet et al, Science 2002).
  • Noise and gene regulation: A second example is our recent studies of stochasticity, or "noise," in gene regulation: (Elowitz et al, Science 2002) and (Rosenfeld et al, J Mol Bio. 2005). Because cells are small and contain few copies of certain molecules, stochastic fluctuations in biochemical reactions are expected to be significant, and may in Noisy Bacteria fact be the origin of much cell-cell variability. We developed an experimental technique that enables detection of gene expression noise in vivo, using two differently colored fluorescent protein genes under the control of identical regulatory sequences in the same cell (see figure). In this image, noise causes individual cells to appear reddish or greenish, rather than yellow, which is the color they would be without noise (yellow is equal parts red and green). This approach should contribute to a quantitative understanding of how genetic elements function in the intracellular milieu. In (Rosenfeld et al, Science 2005) we use time-lapse movies to understand the biochemistry of gene regulation at the single cell level. In this study, we found that extrinsic noise can have a very slow correlation time -- that is, a long memory. Fluctuations persist for timescales on the order of the cell cycle time, placing fundamental limits on the accuracy of gene regulation.
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