Bulletin of the American Physical Society
2009 APS March Meeting
Volume 54, Number 1
Monday–Friday, March 16–20, 2009; Pittsburgh, Pennsylvania
Session V39: Biological Networks and Systems Biology |
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Sponsoring Units: DBP Chair: Ilya Nemenman, Los Alamos National Laboratory Room: 411 |
Thursday, March 19, 2009 8:00AM - 8:12AM |
V39.00001: Boolean modeling of collective effects in complex networks Johannes Norrell, Joshua Socolar Complex systems are often modeled as Boolean networks in attempts to capture their logical structure and reveal its dynamical consequences. Approximating the dynamics of continuous variables by discrete values and Boolean logic gates may, however, introduce dynamical possibilities that are not accessible to the original system. We show that large random networks of variables coupled through continuous transfer functions often fail to exhibit the complex dynamics of corresponding Boolean models in the disordered (chaotic) regime, even when each individual function appears to be a good candidate for Boolean idealization. A simple criterion identifies continuous systems that exhibit the full dynamical range of their Boolean counterparts. Transfer functions inferred from the literature on transcriptional regulation of genes do not satisfy the criterion. [Preview Abstract] |
Thursday, March 19, 2009 8:12AM - 8:24AM |
V39.00002: A Network Model For Sea Urchin Development Xinwei Gong, Xianrui Cheng, Joshua Socolar The sea urchin embryo developmental gene regulatory network has been a subject of experimental study for decades. While current knowledge of the network is incomplete, boolean network models with autonomous updating can reveal dynamical features of the known network. Our analysis of such a model based on the network provided by Davidson et al [http://sugp.caltech.edu/endomes/index.html] shows that, with the suggested initial inputs and certain sets of logic functions that are consistent with the known regulatory relations, a 3-cell system settles into an attractor that corresponds to the 3 different cell fates expected for the organism. The attractor is not sensitive to modest variations in the time delay parameters. [Preview Abstract] |
Thursday, March 19, 2009 8:24AM - 8:36AM |
V39.00003: Achieving optimal growth: lessons from simple metabolic modules Sidhartha Goyal, Thomas Chen, Ned Wingreen Metabolism is a universal property of living organisms. While the metabolic network itself has been well characterized, the logic of its regulation remains largely mysterious. Recent work has shown that growth rates of microorganisms, including the bacterium \textit{Escherichia coli}, correlate well with optimal growth rates predicted by flux-balance analysis (FBA), a constraint-based computational method. How difficult is it for cells to achieve optimal growth? Our analysis of representative metabolic modules drawn from real metabolism shows that, in all cases, simple feedback inhibition allows nearly optimal growth. Indeed, product-feedback inhibition is found in every biosynthetic pathway and constitutes about 80{\%} of metabolic regulation. However, we find that product-feedback systems designed to approach optimal growth necessarily produce large pool sizes of metabolites, with potentially detrimental effects on cells via toxicity and osmotic imbalance. Interestingly, the sizes of metabolite pools can be strongly restricted if the feedback inhibition is ultrasensitive ($i.e.$ with high Hill coefficient). The need for ultrasensitive mechanisms to limit pool sizes may therefore explain some of the ubiquitous, puzzling complexity found in metabolic feedback regulation at both the transcriptional and post-transcriptional levels. [Preview Abstract] |
Thursday, March 19, 2009 8:36AM - 8:48AM |
V39.00004: Bifurcation in stochastic differential equations with delayed feedback Gaudreault Mathieu, Jorge Vinals The bifurcation diagram of a model nonlinear Langevin equation with delayed feedback is obtained numerically. This model relates to a common motif in genetic regulatory networks, and we study the effect of fluctuating parameters on the bifurcation diagram of the network. We observe both direct and oscillatory bifurcations in different ranges of model parameters. Below threshold, the stationary distribution function $p(x)$ is a delta function at the trivial state $x=0$. Above threshold, $p(x) \sim x^{\alpha}$ at small $x$, with $\alpha = -1$ at threshold, and monotonously increasing with the value of the control parameter above threshold. Unlike the case without delayed feedback, the bifurcation threshold is shifted by fluctuations by an amount that scales linearly with the noise intensity. With numerical information about time delayed correlations, we derive an analytic expression for $p(x) $ which is in good agreement with the numerical results. [Preview Abstract] |
Thursday, March 19, 2009 8:48AM - 9:00AM |
V39.00005: Constraints imposed by nonfunctional protein-protein interactions on gene expression and proteome size Jingshan Zhang, Sergei Maslov, Eugene Shakhnovich Crowded intracellular environments present a challenge for proteins to form functional specific complexes while reducing nonfunctional interactions with promiscuous nonfunctional partners. Here we show how nonfunctional interactions limit the proteome diversity and the average concentration of co-expressed and co-localized proteins. We use yeast compartments to verify our hypothesis that the yeast proteome has evolved to operate closely to the upper limit of its size, while keeping individual protein concentrations sufficiently low to reduce nonfunctional interactions. These findings have implication for conceptual understanding of intracellular compartmentalization, multicellularity, and differentiation. [Preview Abstract] |
Thursday, March 19, 2009 9:00AM - 9:12AM |
V39.00006: Effect of TNF autocrine signaling on dosage-dependent NF-kappaB response to lipopolysaccharide stimulation Jaewook Joo, Bryan Carson, Cathy Branda, Jens Poschet We will present the dosage-dependent characteristics of NF-kappaB translocation patterns from single macrophages stimulated by E. Coli lipopolysacchride. The NF-kappaB translocation patterns in single cells are found to be quite heterogeneous: The patterns are more heterogeneous with low dosage stimulation than with high dosage stimulation. For low dosage stimulation, most of cells take a rising pattern and we demonstrate that it is due to the TNFalpha autocrine signaling effect. The above results are predicted and explained by a computational model, and corroborated and verified by a single cell fluorescence imaging technique. [Preview Abstract] |
Thursday, March 19, 2009 9:12AM - 9:24AM |
V39.00007: Gain control in molecular signaling without feedback Ilya Nemenman Statistical properties of environments experienced by biological systems in the real world change, and this requires adaptation to achieve a high fidelity information transmission in cellular networks. One form of such adaptive response is gain control. When the mean response of a signaling system is matched to the mean value of its signal, rescaling the gain allows to respond to signals with different variances without saturation and by utilizing the entire available dynamic range of the response. Here we argue that a certain simple mechanism of gain control, understood well in the context of systems neuroscience, translates to molecular signaling systems as well. The mechanism allows to transmit more than one bit (on or off) of information about the signal independently of the signal variance. The mechanism does not require additional molecular circuitry beyond that already present in many molecular systems, and, in particular, it does not depend on existence of feedback loops. This analysis provides a plausible explanation for certain structural aspects of cellular networks. [Preview Abstract] |
Thursday, March 19, 2009 9:24AM - 9:36AM |
V39.00008: Noise in Random Boolean Networks Tiago Peixoto, Barbara Drossel We investigate the effect of noise on Random Boolean Networks. Noise is implemented as a probability $p$ that a node does not obey its deterministic update rule. We define two order parameters, the long-time average of the Hamming distance between a network with and without noise, and the average frozenness, which is a measure of the extent to which a node prefers one of the two Boolean states. We evaluate both order parameters as function of the noise strength, finding a smooth transition from deterministic ($p=0$) to fully stochastic ($p=1/2$) dynamics for networks with $K\le2$, and a first order transition at $p=0$ for $K>2$. Most of the results obtained by computer simulation are also derived analytically. The average Hamming distance can be evaluated using the annealed approximation. In order to obtain the distribution of frozenness as function of the noise strength, more sophisticated self-consistent calculations had to be performed. This distribution is a collection of delta peaks for $K=1$, and it has a fractal sructure for $K>1$, approaching a continuous distribution in the limit $K\gg1$. [Preview Abstract] |
Thursday, March 19, 2009 9:36AM - 9:48AM |
V39.00009: The effect of negative autoregulation on eukaryotic gene expression Dmitry Nevozhay, Rhys Adams, Kevin Murphy, Kresimir Josic, G\'abor Bal\'azsi Negative autoregulation is a frequent motif in gene regulatory networks, which has been studied extensively in prokaryotes. Nevertheless, some effects of negative feedback on gene expression in eukaryotic transcriptional networks remain unknown. We studied how the strength of negative feedback regulation affects the characteristics of gene expression in yeast cells carrying synthetic transcriptional cascades. We observed a drastic reduction of gene expression noise and a change in the shape of the dose-response curve. We explained these experimentally observed effects by stochastic simulations and a simple set of algebraic equations. [Preview Abstract] |
Thursday, March 19, 2009 9:48AM - 10:00AM |
V39.00010: Cell stimulation with optically manipulated microsources. Holger Kress, Jin-Gyu Park, Cecile Mejean, Jason Forster, Jason Park, Spencer Walse, Dianqing Wu, Orion Weiner, Tarek Fahmy, Eric Dufresne Many cells can sense spatial and temporal heterogeneities in concentrations of soluble molecules. The cellular signal transduction which forms the basis of this ability consists of signaling cascades and loops whose length and time scales are largely unknown. The systematic investigation of these networks requires control over the chemical microenvironment of cells. We present a novel technique to create molecular concentration patterns that are chemically, spatially and temporally flexible. Our approach uses optically manipulated colloidal particles which act as microsources of soluble molecules. This technique for flexible cell stimulation is combined with quantitative live cell microscopy measurements of cellular responses. We demonstrate the method by inducing chemotaxis in neutrophils. We quantify the intracellular calcium release, actin distribution, shape and motility of single cells. The possibility for quantitative stimulus-response measurements on single cells makes this method applicable to a wide range of systems biology studies. [Preview Abstract] |
Thursday, March 19, 2009 10:00AM - 10:12AM |
V39.00011: ABSTRACT WITHDRAWN |
Thursday, March 19, 2009 10:12AM - 10:24AM |
V39.00012: Determining Regulatory Networks Governing the Differentiation of Embryonic Stem Cells to Pancreatic Lineage Ipsita Banerjee Knowledge of pathways governing cellular differentiation to specific phenotype will enable generation of desired cell fates by careful alteration of the governing network by adequate manipulation of the cellular environment. With this aim, we have developed a novel method to reconstruct the underlying regulatory architecture of a differentiating cell population from discrete temporal gene expression data. We utilize an inherent feature of biological networks, that of sparsity, in formulating the network reconstruction problem as a bi-level mixed-integer programming problem. The formulation optimizes the network topology at the upper level and the network connectivity strength at the lower level. The method is first validated by in\textit{-silico} data, before applying it to the complex system of embryonic stem (ES) cell differentiation. This formulation enables efficient identification of the underlying network topology which could accurately predict steps necessary for directing differentiation to subsequent stages. Concurrent experimental verification demonstrated excellent agreement with model prediction. [Preview Abstract] |
Thursday, March 19, 2009 10:24AM - 10:36AM |
V39.00013: Stabilizing Motifs in Autonomous Boolean Networks and the Yeast Cell Cycle Oscillator Volkan Sevim, Xinwei Gong, Joshua Socolar Synchronously updated Boolean networks are widely used to model gene regulation. Some properties of these model networks are known to be artifacts of the clocking in the update scheme. Autonomous updating is a less artificial scheme that allows one to introduce small timing perturbations and study stability of the attractors. We argue that the stabilization of a limit cycle in an autonomous Boolean network requires a combination of motifs such as feed-forward loops and auto-repressive links that can correct small fluctuations in the timing of switching events. A recently published model of the transcriptional cell-cycle oscillator in yeast contains the motifs necessary for stability under autonomous updating [1]. \newline \newline [1] D.~A. Orlando, et al. \newblock \emph{Nature (London)}, 453\penalty0 (7197):\penalty0 944--947, 2008. [Preview Abstract] |
Thursday, March 19, 2009 10:36AM - 10:48AM |
V39.00014: The Transition Pathway from Nonspecific to Specific Complex of DNA with a DNA-Bending Protein Serguei Kuznetsov, Paula Vivas, Yogambigai Velmurugu, Anjum Ansari Integration host factor (IHF) from \textit{E. coli} is a DNA-bending protein that recognizes and binds to its specific sites primarily by the indirect read-out mechanism, in which sequence-dependent DNA dynamics and flexibility play an important role. The crystal structure of IHF bound to a 35-bp long cognate site H' indicates that the DNA is kinked at two sites separated by $\sim $9 bp, resulting in a ``U-turn'' bend of the DNA. To probe the DNA bending dynamics, we use a laser T-jump, and time-resolved FRET on end-labeled DNA substrates. Our results show that DNA bending occurs on the same time-scales as thermal disruption of single base-pairs in B-DNA, suggesting that spontaneous kinking may be the rate-limiting step. To test this hypothesis, we modified the DNA at the site of the kinks by introducing (i) a nick in the sugar-phosphate backbone, and (ii) mismatches to create internal loops. For each of these substrates, the 4-20 fold increase in the binding affinity is reflected in a corresponding increase in the bending rates. Furthermore, the DNA bending rates are independent of the salt concentration. These results indicate that in the transition state ensemble the DNA is kinked, but specific protein-DNA interactions involving ion release have not occurred. [Preview Abstract] |
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