Bulletin of the American Physical Society
2006 APS March Meeting
Monday–Friday, March 13–17, 2006; Baltimore, MD
Session P7: Focus Session: Physics of Transcriptional Regulatory Networks |
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Sponsoring Units: GSNP DBP Chair: Joshua Socolar, Duke University Room: Baltimore Convention Center 307 |
Wednesday, March 15, 2006 11:15AM - 11:51AM |
P7.00001: Programming bacterial dynamics by synthetic killer circuits Invited Speaker: In addition to offering insight into biological ``design'' principles, de novo engineering of synthetic gene circuits may impact broad areas including computation, engineering, and medicine. However, it remains challenging to realize predictable and robust circuit performance due to noise in gene expression and cell-to-cell variation in phenotype. We address these issues by using cell-cell communication to regulate cell killing to enable precise programming of bacterial dynamics. To establish cell-cell communication, we take advantage of quorum sensing systems that many bacteria use to detect and respond to changes in the cell density. As a prototype example, we have built and characterized a population control circuit in bacterium Escherichia coli. This circuit autonomously controls cell density by regulating the death rate using a quorum sensing module. Upon activation, the circuit will lead to a stable steady state or sustained oscillations in cell density, as predicted by a simple mathematical model. Further exploiting this design strategy, we have constructed a synthetic predator-prey ecosystem, where two E. coli populations regulate each other's growth and death by engineered two-way communication. Systems such as this will enable us to explore complex ecological dynamics in a well-defined experimental framework. [Preview Abstract] |
Wednesday, March 15, 2006 11:51AM - 12:27PM |
P7.00002: Molecules, nonlinearity, and function in regulatory networks. Invited Speaker: Biological regulatory networks are capable of sophisticated functions, such as integrating chemical signals, storing memories of previous molecular events, and keeping time. These networks often contain feedback loops, which can promote bistability and oscillation. However, feedback alone is not enough. Strong nonlinearities in the network dynamic are also needed. It is known that many regulatory proteins form higher-order complexes and multimers. I will discuss two important sources of nonlinearity in multimerization. First, ample experimental evidence suggests that protein subunits \textit{in vivo} can degrade less rapidly when associated in complexes. For homodimers, this effect leads to a concentration dependence in the protein degradation rate. Theoretical analysis of two model gene circuits in bacteria, i.e. switch and oscillator, demonstrates that this effect can substantially enhance the function of these circuits. Second, active proteins can often be sequestered into inactive complexes. This molecular titration can lead to sharp nonlinearities, and suggests a scenario for the rapid evolution of bistable or oscillatory circuits in nature. [Preview Abstract] |
Wednesday, March 15, 2006 12:27PM - 1:03PM |
P7.00003: Combinatorial Regulation in Yeast Transcription Networks Invited Speaker: Yeast has evolved a complex network to regulate its transcriptional program in response to changes in environment. It is quite common that in response to an external stimulus, several transcription factors will be activated and they work in combinations to control different subsets of genes in the genome. We are interested in how the promoters of genes are designed to integrate signals from multiple transcription factors and what are the functional and evolutionary constraints. To answer how, we have developed a number of computational algorithms to systematically map the binding sites and target genes of transcription factors using sequence and gene expression data. To analyze the functional constraints, we have employed mechanistic models to study the dynamic behavior of genes regulated by multiple factors. We have also developed methods to trace the evolution of transcriptional networks via comparative analysis of multiple species. [Preview Abstract] |
Wednesday, March 15, 2006 1:03PM - 1:39PM |
P7.00004: Gene expression dynamics during cell differentiation: Cell fates as attractors and cell fate decisions as bifurcations Invited Speaker: During development of multicellular organisms, multipotent stem and progenitor cells undergo a series of hierarchically organized ``somatic speciation'' processes consisting of binary branching events to achieve the diversity of discretely distinct differentiated cell types in the body. Current paradigms of genetic regulation of development do not explain this discreteness, nor the time-irreversibility of differentiation. Each cell contains the same genome with the same $N (\sim $ 25,000) genes and each cell type $k$ is characterized by a distinct stable gene activation pattern, expressed as the cell state vector $S_{k}(t)$ = {\{}$x_{k1}(t) $,.. $x_{ki}(t)$,.. $x_{kN}(t)${\}}, where $x_{ki}$ is the activation state of gene $i$ in cell type $k$. Because genes are engaged in a network of mutual regulatory interactions, the movement of $S_{k}(t)$ in the $N$-dimensional state space is highly constrained and the organism can only realize a tiny fraction of all possible configurations $S_{k}$. Then, the trajectories of $S_ {k}$ reflect the diversifying developmental paths and the mature cell types are high-dimensional attractor states. Experimental results based on gene expression profile measurements during blood cell differentiation using DNA microarrays are presented that support the old idea that cell types are attractors. This basic notion is extended to treat binary fate decisions as bifurcations in the dynamics of networks circuits. Specifically, during cell fate decision, the metastable progenitor attractor is destabilized, poising the cell on a `watershed state' so that it can stochastically or in response to deterministic perturbations enter either one of two alternative fates. Overall, the model and supporting experimental data provide an overarching conceptual framework that helps explain how the specifics of gene network architecture produces discreteness and robustness of cell types, allows for both stochastic and deterministic cell fate decision and ensures directionality of organismal development. [Preview Abstract] |
Wednesday, March 15, 2006 1:39PM - 2:15PM |
P7.00005: Network theory and prediction of regulatory switches Invited Speaker: While the influence of the high intracellular concentration of macromolecules on cell physiology is increasingly appreciated, its impact on the function of intracellular molecular interaction networks remains poorly understood. To test the effect of molecular crowding on the function of metabolic networks, we introduce a modified form of flux balance analysis that takes into account the constraint imposed by the limit on the attainable concentration of enzymes in the crowded cytoplasm. We demonstrate and experimentally confirm that the method can successfully predict the existence of regulatory points that allow switching from high to low biomass yield pathways when changing cellular growth rate. These results demonstrate that molecular crowding represents a bound on the achievable functional states of metabolic networks, and provide a systematic approach to uncover potential regulatory points in cellular metabolism. [Preview Abstract] |
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