Bulletin of the American Physical Society
2008 APS March Meeting
Volume 53, Number 2
Monday–Friday, March 10–14, 2008; New Orleans, Louisiana
Session D16: Biological Networks |
Hide Abstracts |
Sponsoring Units: DBP Chair: Eivind Almaas Room: Morial Convention Center 208 |
Monday, March 10, 2008 2:30PM - 2:42PM |
D16.00001: Cooperation of multiple copies of noisy genes Aleksandra Walczak, Peter Wolynes The regulation of gene expression is influenced by the small numbers of protein and gene copies present in the cell. Noise properties arising from single copies of the gene are well known. In this talk we consider the case when a few copies of the same gene are present and actively transcribed in the cell. We use mathematical models which treat both the DNA and protein degrees of freedom stochastically. We study how the switching of one gene influences the switching behaviour of another gene, to which it is coupled by a mutual protein environment. We show that the genes loose properties defined by their individual parameters and take on the characteristics of a group to reach a new steady state. We show that system with multiple gene copies can be used to reduce noise or to modify the cooperativity of the regulatory characteristics of the circuit. These results can be useful for interpreting and designing bioengineering experiments in which there can be multiple copies of a gene. [Preview Abstract] |
Monday, March 10, 2008 2:42PM - 2:54PM |
D16.00002: Chaotic Gene Regulatory Networks Can Be Robust Against Mutations and Noise Volkan Sevim, Per Arne Rikvold Robustness to mutations and noise has been shown to evolve through stabilizing selection for optimal phenotypes in model gene regulatory networks. The ability to evolve robust mutants is known to depend on the network architecture. How do the state-space structures of networks with high and low robustness differ? Here we present large-scale computer simulations of a Random Threshold Network model of gene regulatory networks undergoing biological evolution. We show using damage propagation analysis and an extensive statistical analysis of state spaces of these model gene networks that the change in their dynamical properties due to stabilizing selection is very small. Therefore, conventional measures of stability do not provide much information about robustness in model gene regulatory networks. Interestingly, the networks that are most robust to both mutations and noise are highly chaotic. Chaotic networks are able to produce large attractor basins, which can be useful for maintaining a stable gene-expression pattern.\\ {[1] V.~Sevim and P.~A. Rikvold (2007), e-print arXiv:0708.2244.}\\ {[2] V.~Sevim and P.~A. Rikvold (2007), e-print arXiv:0711.1522.} [Preview Abstract] |
Monday, March 10, 2008 2:54PM - 3:06PM |
D16.00003: A quantitative model of DNA replication in \textit{Xenopus} embryos: reliable replication despite stochasticity Scott Cheng-Hsin Yang, John Bechhoefer DNA synthesis in \textit{Xenopus} frog embryos initiates stochastically in time at many sites (origins) along the chromosome. Stochastic initiation implies fluctuations in the replication time and may lead to cell death if replication takes longer than the cell cycle time ($\sim $ 25 min.). Surprisingly, although the typical replication time is about 20 min., \textit{in vivo} experiments show that replication fails to complete only about 1 in 250 times. How is replication timing accurately controlled despite the stochasticity? Biologists have proposed two mechanisms: the first uses a regular spatial distribution of origins, while the second uses randomly located origins but increases their probability of initiation as the cell cycle proceeds. Here, we show that both mechanisms yield similar end-time distributions, implying that regular origin spacing is not needed for control of replication time. Moreover, we show that the experimentally inferred time-dependent initiation rate satisfies the observed low failure probability and nearly optimizes the use of replicative proteins. [Preview Abstract] |
Monday, March 10, 2008 3:06PM - 3:18PM |
D16.00004: Exponential sensitivity of noise-driven switching in genetic networks Pankaj Mehta, Ranjan Mukhopadhyay, Ned Wingreen Cells are known to utilize biochemical noise to probabilistically switch between distinct gene expression states. We demonstrate that such noise-driven switching is dominated by tails of probability distributions and is therefore exponentially sensitive to changes in physiological parameters such as transcription and translation rates. However, provided mRNA lifetimes are short, switching can still be accurately simulated using protein-only models of gene expression. Exponential sensitivity limits the robustness of noise-driven switching, suggesting cells may use other mechanisms in order to switch reliably. [Preview Abstract] |
Monday, March 10, 2008 3:18PM - 3:30PM |
D16.00005: Effects of coarse-graining on fluctuations in gene expression Juan Pedraza, Johan Paulsson Many cellular components are present in such low numbers per cell that random births and deaths of individual molecules can cause significant `noise' in concentrations. But biochemical events do not necessarily occur in steps of individual molecules. Some processes are greatly randomized when synthesis or degradation occurs in large bursts of many molecules in a short time interval. Conversely, each birth or death of a macromolecule could involve several small steps, creating a memory between individual events. Here we present generalized theory for stochastic gene expression, formulating the variance in protein abundance in terms of the randomness of the individual events, and discuss the effective coarse-graining of the molecular hardware. We show that common molecular mechanisms produce gestation and senescence periods that can reduce noise without changing average abundances, lifetimes, or any concentration-dependent control loops. We also show that single-cell experimental methods that are now commonplace in cell biology do not discriminate between qualitatively different stochastic principles, but that this in turn makes them better suited for identifying which components introduce fluctuations. [Preview Abstract] |
Monday, March 10, 2008 3:30PM - 3:42PM |
D16.00006: ABSTRACT WITHDRAWN |
Monday, March 10, 2008 3:42PM - 3:54PM |
D16.00007: Regulatory control and the costs and benefits of biochemical noise Sorin Tanase-Nicola, Pieter Rein ten Wolde Experiments in recent years have vividly demonstrated that gene expression can be highly stochastic. We present a mathematical model that makes it possible to quantify the effect of protein concentration fluctuations on the growth rate of a population of genetically identical cells. The model predicts that the population's growth rate depends on how the growth rate of a single cell varies with protein concentration, the variance of the protein concentration fluctuations, and the correlation time of these fluctuations. The model shows that when the average concentration of a protein is close to the value that maximizes the growth rate, fluctuations in its concentration always reduce the growth rate. However, when the average protein concentration deviates sufficiently from the optimal level, fluctuations can enhance the growth rate of the population, even when the growth rate of a cell depends linearly on the protein concentration. We also apply our model to perform a cost-benefit analysis of gene regulatory control. Our analysis predicts that the optimal expression level of a gene regulatory protein is determined by the trade-off between the cost of synthesizing the regulatory protein and the benefit of minimizing the fluctuations in the expression of its target gene. [Preview Abstract] |
Monday, March 10, 2008 3:54PM - 4:06PM |
D16.00008: Effects of time-delayed negative feedback loops on noise-induced oscillations on the NF-KappaB signaling network Jaewook Joo, Jean-Loup Faulon NF-kappaB is a stimulus-responsive pleiotropic regulator of gene control. Our work was motivated by Nelson et al. [Science 306:704 (2004)], which showed noisy quasi-periodic oscillations of NF-kappaB translocation between cytoplasm and nucleus in single cells. Using both stochastic simulations and analytical approaches, we investigated the dynamic patterns of NF-kappaB translocation with a stochastic two-compartmental model, especially taking into account the interplay between intrinsic noise and delayed negative feedback loops of the NF-kappaB signaling system. We will present noise-induced oscillations of the NF-kappaB shuttling and the effects of time-delayed negative feedback loops on them. [Preview Abstract] |
Monday, March 10, 2008 4:06PM - 4:18PM |
D16.00009: How is the fitness landscaped upon which life evolves selected? Michael Deem We investigate the selective forces that promote the emergence of modularity in nature. We demonstrate the spontaneous emergence of modularity in a population of individuals that evolve in a changing environment. We show that the level of modularity correlates with the rapidity and severity of environmental change. The modularity arises as a synergistic response to the noise in the environment in the presence of horizontal gene transfer. We suggest that the hierarchical structure observed in the natural world may be a broken symmetry state, which generically results from evolution in a changing environment. The existence of such structure, therefore, need not necessarily rest on intelligent design or the anthropic principle. 1) J. Sun and M. W. Deem, Phys. Rev. Lett., to appear., arXiv:0710.3436 [Preview Abstract] |
Monday, March 10, 2008 4:18PM - 4:30PM |
D16.00010: Early life was a generalist: protein modularity increase as evolution proceeds Jiankui He, Jun Sun, Michael Deem We study the evolution of modularity in protein-protein interaction network and protein domain-domain interaction networks. By introducing compositional age, we construct the interaction networks at different points in evolutionary time. We use the average-linkage hierarchical clustering method to reorganize the network matrix to identify the modules. With several different definitions of modularity, we compare the observed modularity at different evolutionary times in both E. coli and S.cerevisiae. We conclude that the modularity of protein-protein interaction network and domain-domain interaction network grows in evolution, validating recent theoretical predictions of spontaneous modularity in evolution [1]. \newline \newline [1] J. Sun and M. W. Deem, Phys. Rev. Lett, to appear, arXiv:0710.3436. [Preview Abstract] |
Monday, March 10, 2008 4:30PM - 4:42PM |
D16.00011: Genetic recombination models in molecular evolution Enrique Munoz, Jeong-Man Park, Michael Deem We introduce generalizations of two classical models of molecular evolution: the parallel or Crow-Kimura model, and the Eigen model. These generalizations include, in addition to point mutations and selection as driving forces for biological evolution, the presence of different forms of horizontal gene transfer and genetic recombination events between individuals in the population. We will present analytical solutions for these models, and compare our results with numerical solutions of the corresponding system of differential equations. We will also present stochastic simulation results for the single peak fitness case. [Preview Abstract] |
Monday, March 10, 2008 4:42PM - 4:54PM |
D16.00012: A minimal stochastic model of cell death signaling Subhadip Raychaudhuri Cell death (apoptosis) is mediated by a complex intracellular signaling network that involves a large number of components. We propose a minimal model of signaling network that can sense the strength of any extracellular stimuli such as the concentration of ligands and adapt to a fluctuating environment. Based on stochastic simulations we show that a three step slow, fast, slow pathway is enough to generate large cell to cell fluctuations under the conditions of weak stimulus. Such cell to cell stochastic fluctuations persist even in the presence of large number of molecules and cannot be captured by deterministic differential equation based models. We develop a probability distribution based approach that can characterize the stochastic fluctuations in such inherently stochastic signaling network. Interestingly, our results match with those obtained from kinetic Monte Carlo simulation of the full scale apoptotic network. Hence, our minimal signaling network can serve as a cell type independent general model of apoptosis signaling. We also discuss implications of our probability distribution based approach for diseases such as cancer that can result from disrupted apoptotic balance. [Preview Abstract] |
Monday, March 10, 2008 4:54PM - 5:06PM |
D16.00013: Temperature compensation model for the circadian clock of \textit{Neurospora crassa} Xiaojia Tang, Heinz-Bernd Sch\"uttler, Jonathan Arnold In the lowly bread mould, \textit{Neurospora crassa}, biomolecular reactions involving the \textit{white-collar-1} (\textit{wc-1}), \textit{white-colloar-2} (\textit{wc2}), and \textit{frequency} (\textit{frq}) genes and their products constitute building blocks of the biological clock that would response to temperature as well as light. The period of the biological clock remains stable in response to variation in ambient temperature, which is called a compensation phenomenon. Recent experimental results show evidences that the temperature compensation could be explained by the temperature sensitive translational control of production of two isoforms of the main oscillator protein FRQ: a long form FRQ$^{1-989}$ which is more abundantly produced at higher temperature; and a short from FRQ$^{100-989}$, more abundantly produced at lower temperature. With our recently developed method of genetic network identification, we are now simulating the network's temperature response based on published experimental data. These will serve as the starting point for a simulation-prediction-experiment-simulation workflow cycle. In this cycle, the maximally informative next experiment (MINE) technology will be employed to select the best experimental control parameters specifying the temperature response to be used in the next step of the workflow cycle. [Preview Abstract] |
Monday, March 10, 2008 5:06PM - 5:18PM |
D16.00014: Understanding the Role of Housekeeping and Stress-Related Genes in Transcription-Regulatory Networks Allison Heath, Lydia Kavraki, G\'abor Bal\'azsi Despite the increasing number of completely sequenced genomes, much remains to be learned about how living cells process environmental information and respond to changes in their surroundings. Accumulating evidence indicates that eukaryotic and prokaryotic genes can be classified in two distinct categories that we will call class I and class II. Class I genes are housekeeping genes, often characterized by stable, noise resistant expression levels. In contrast, class II genes are stress-related genes and often have noisy, unstable expression levels. In this work we analyze the large scale transcription-regulatory networks (TRN) of \textit{E. coli} and \textit{S. cerevisiae} and preliminary data on \textit{H. sapien}. We find that stable, housekeeping genes (class I) are preferentially utilized as transcriptional inputs while stress related, unstable genes (class II) are utilized as transcriptional integrators. This might be the result of convergent evolution that placed the appropriate genes in the appropriate locations within transcriptional networks according to some fundamental principles that govern cellular information processing. [Preview Abstract] |
Monday, March 10, 2008 5:18PM - 5:30PM |
D16.00015: The re-design of a theophylline riboswitch for DNT sensing Yaroslav Chushak, Nancy Kelley-Loughnane, Svetlana Harbaugh, Morley Stone Riboswitches are noncoding elements of mRNA that recognize and bind to small molecules and regulate the translation process of downstream genes. As an initial study, we used a theophylline riboswitch that regulates the expression of the Tobacco etch virus (TEV) protease placed downstream of the switch as a controlling element. Upon expression of TEV protease, an optical reporter is cleaved producing change in fluorescence resonance energy transfer (FRET) between BFP and eGFP. We altered the sensing domain of the original construct to create a synthetic riboswitch that responds to the presence of 2,4-dinitrotoluene (DNT) molecules. Computational analysis using Autodock4 and AMBER9 software packages showed that U24A mutant has a significantly higher binding affinity for DNT molecule compared to the original theophylline. Cells expressing the re-designed riboswitch showed a marked optical difference in fluorescence emission in the presence of DNT molecules, leading to the potential of using this construct in biosentinel applications of highly nitrated compounds. [Preview Abstract] |
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