Bulletin of the American Physical Society
APS March Meeting 2010
Volume 55, Number 2
Monday–Friday, March 15–19, 2010; Portland, Oregon
Session P10: Focus Session: Physics of Behavior |
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Sponsoring Units: DBP Chair: Will Ryu, University of Toronto Room: A106 |
Wednesday, March 17, 2010 8:00AM - 8:12AM |
P10.00001: Collective decisions among bacterial viruses Richard Joh, Yuriy Mileyko, Eberhard Voit, Joshua Weitz For many temperate bacteriophages, the decision of whether to kill hosts or enter a latent state depends on the multiplicity of infection. In this talk, I present a quantitative model of gene regulatory dynamics to describe how phages make collective decisions within host cells. Unlike most previous studies, the copy number of viral genomes is treated as a variable. In the absence of feedback loops, viral mRNA transcription is expected to be proportional to the viral copy number. However, when there are nonlinear feedback loops in viral gene regulation, our model shows that gene expression patterns are sensitive to changes in viral copy number and there can be a domain of copy number where the system becomes bistable. Hence, the viral copy number is a key control parameter determining host cell fates. This suggests that bacterial viruses can respond adaptively to changes in population dynamics, and can make alternative decisions as a bet-hedging strategy. Finally, I present a stochastic version of viral gene regulation and discuss speed-accuracy trade-offs in the context of cell fate determination by viruses. [Preview Abstract] |
Wednesday, March 17, 2010 8:12AM - 8:24AM |
P10.00002: Reconstructing the behavior of walking fruit flies Gordon Berman, William Bialek, Joshua Shaevitz Over the past century, the fruit fly \emph{Drosophila melanogaster} has arisen as almost a lingua franca in the study of animal behavior, having been utilized to study questions in fields as diverse as sleep deprivation, aging, and drug abuse, amongst many others. Accordingly, much is known about what can be done to manipulate these organisms genetically, behaviorally, and physiologically. Most of the behavioral work on this system to this point has been experiments where the flies in question have been given a choice between some discrete set of pre-defined behaviors. Our aim, however, is simply to spend some time with a cadre of flies, using techniques from nonlinear dynamics, statistical physics, and machine learning in an attempt to reconstruct and gain understanding into their behavior. More specifically, we use a multi-camera set-up combined with a motion tracking stage in order to obtain long time-series of walking fruit flies moving about a glass plate. This experimental system serves as a test-bed for analytical, statistical, and computational techniques for studying animal behavior. In particular, we attempt to reconstruct the natural modes of behavior for a fruit fly through a data-driven approach in a manner inspired by recent work in C. elegans and cockroaches. [Preview Abstract] |
Wednesday, March 17, 2010 8:24AM - 8:36AM |
P10.00003: Interactive Learning Susanne Still We present an approach to behavioral learning that is based solely on simple information processing principles. Colloquially stated, we require that a learner's action policy should result in observations that enable the learner to construct a model with high predictive power at small cost. This requirement is formalized by an optimization problem, using information theoretic quantities. Our approach integrates model- and decision-making into one theoretical framework, including feedback from the learner. We derive and study classes of optimal models and policies. The models are distinguished in that they optimally trade bits for prediction accuracy by adjusting their fuzziness. We have shown elsewhere how these models are related to an established approach that was developed in the context of nonlinear dynamical systems, and we discuss here how our theory extends that approach. The optimal policies contain a natural balance between exploration and control. In contrast, in computer science the view is often that exploration is achieved by policy randomness. We have shown elsewhere that our theoretical approach can be used to remedy this misconception and to provide a unified view of curiosity-driven learning. [Preview Abstract] |
Wednesday, March 17, 2010 8:36AM - 9:12AM |
P10.00004: Thermal impulse response and the temperature preference of \textit{Escherichia coli} Invited Speaker: From a broad perspective, exposure to environmental temperature changes is a universal condition of living organisms. Escherichia coli is a powerful model system to study how a biochemical network measures and processes thermal information to produce adaptive changes in behavior. E. coli performs thermotaxis, directing its movements to a preferred temperature in spatial thermal gradients. How does the system perform thermotaxis? Where biologically is this analog value of thermal preference stored? Previous studies using populations of cells have shown that \textit{E.coli} accumulate in spatial thermal gradients, but these experiments did not cleanly separate thermal responses from chemotactic responses. Here we have isolated the thermal behavior by studying the thermal impulse response of single, tethered cells. The motor output of cells was measured in response to small, impulsive increases in temperature, delivered by an infrared laser, over a range of ambient temperature (23 to 43 degrees C). The thermal impulse response at temperatures $<$ 31 degrees C is similar to the chemotactic impulse response: both follow a similar time course, share the same directionality, and show biphasic characteristics. At temperatures $>$ 31 degrees C, some cells show an inverted response, switching from warm- to cold-seeking behavior. The fraction of inverted responses increases nonlinearly with temperature, switching steeply at the preferred temperature of 37 degrees C. [Preview Abstract] |
Wednesday, March 17, 2010 9:12AM - 9:24AM |
P10.00005: Cell fate determination dynamics in bacteria Anna Kuchina, Lorena Espinar, Tolga Cagatay, Jordi Garcia-Ojalvo, Gurol Suel The fitness of an organism depends on many processes that serve the purpose to adapt to changing environment in a robust and coordinated fashion. One example of such process is cellular fate determination. In the presence of a variety of alternative responses each cell adopting a particular fate represents a ``choice'' that must be tightly regulated to ensure the best survival strategy for the population taking into account the broad range of possible environmental challenges. We investigated this problem in the model organism B.Subtilis which under stress conditions differentiates terminally into highly resistant spores or initiates an alternative transient state of competence. The dynamics underlying cell fate choice remains largely unknown. We utilize quantitative fluorescent microscopy to track the activities of genes involved in these responses on a single-cell level. We explored the importance of temporal interactions between competing cell fates by re- engineering the differentiation programs. I will discuss how the precise dynamics of cellular ``decision-making'' governed by the corresponding biological circuits may enable cells to adjust to diverse environments and determine survival. [Preview Abstract] |
Wednesday, March 17, 2010 9:24AM - 9:36AM |
P10.00006: Temperature control of molecular circuit switch responsible for virulent phenotype expression in uropathogenic \textit{Escherichia coli} Michael Samoilov The behavior and fate of biological organisms are to a large extent dictated by their environment, which can be often viewed as a collection of features and constraints governed by physics laws. Since biological systems comprise networks of molecular interactions, one such key physical property is temperature, whose variations directly affect the rates of biochemical reactions involved. For instance, temperature is known to control many gene regulatory circuits responsible for pathogenicity in bacteria. One such example is type 1 fimbriae (T1F) -- the foremost virulence factor in uropathogenic \textit{E. coli} (UPEC), which accounts for 80-90{\%} of all community-acquired urinary tract infections (UTIs). The expression of T1F is randomly `phase variable', i.e. individual cells switch between virulent/fimbriate and avirulent/afimbriate phenotypes, with rates regulated by temperature. Our computational investigation of this process, which is based on FimB/FimE recombinase-mediated inversion of\textit{ fimS} DNA element, offers new insights into its discrete-stochastic kinetics. In particular, it elucidates the logic of T1F control optimization to the host temperature and contributes further understanding toward the development of novel therapeutic approaches to UPEC-caused UTIs. [Preview Abstract] |
Wednesday, March 17, 2010 9:36AM - 9:48AM |
P10.00007: The emergence of stereotyped behaviors in {\em C. elegans} Greg Stephens, William Ryu, William Bialek Many organisms, including humans, engage in stereotyped behaviors and these are often attributed to a deterministic command process within the nervous system. Here we use the locomotor dynamics of the nematode {\em C. elegans} to suggest an alternative explanation in which stereotyped behavior emerges due to noise within a non-linear dynamical system. In previous work ({\em PLoS Comp Bio} {\bf 4,} e1000028 (2008)) we found that the body shapes of freely-crawling {\em C. elegans} are well-captured by four `eigenworms', two of which encode the phase of a locomotory wave that generates forward and backward motion. We also used this representation to infer a non-linear dynamical model for the phase in which forward and backward crawling emerge as attractors of the deterministic dynamics. Here we show that noise induces reversals between forward and backward crawling and that the predicted reversal rate is in good agreement with experiment, with no adjustable parameters. In this model, reversals follow a stereotyped trajectory for the same reason that Brownian escape over a barrier is dominated by a narrowly defined class of trajectories. Stereotypy becomes even clearer in the dynamics with lower noise levels; the real {\em C. elegans} is just outside the regime where the reversal rate follows an Arrhenius dependence on the noise level. We discus the implications of our results for {\em C. elegans} and other organisms. [Preview Abstract] |
Wednesday, March 17, 2010 9:48AM - 10:00AM |
P10.00008: ABSTRACT WITHDRAWN |
Wednesday, March 17, 2010 10:00AM - 10:12AM |
P10.00009: A remote control for the \textit{C. elegans} nervous system Andrew M. Leifer, Christopher Fang-Yen, Aravinthan D. T. Samuel We demonstrate a closed-loop optogenetic illumination system to stimulate or inhibit arbitrary patterns of neurons and muscle in a freely roaming worm. Transgenic worms that express light-sensitive ion channels in neurons or muscle are used. A microscope with a video camera records the worm's posture and motion. As the worm moves unrestrained, custom real-time image processing software analyzes the worm's position and estimates the location of targeted muscle and neuron cells. For each frame captured by the camera, the software generates an illumination pattern and directs a digital mirror device to shine laser light onto the targeted cells. The system can illuminate an arbitrary spatial and temporal pattern and thus can selectively inhibit or stimulate different sets of cells during the course of a single experiment. The image processing software is very fast and analyzes a 1024 by 768 pixel image containing a worm in less than 10ms. The system has been tested using worms expressing Channelrhodopsin and Halorhodopsin in both neurons and muscle. Preliminary results from an investigation of the \textit{C. elegans} motor circuit are shown. [Preview Abstract] |
Wednesday, March 17, 2010 10:12AM - 10:24AM |
P10.00010: High-resolution, long-term characterization of bacterial motility using optical tweezers Patrick J. Mears, Taejin L. Min, Lon M. Chubiz, Christopher V. Rao, Ido Golding, Yann R. Chemla We present a single-cell motility assay, which allows the quantification of bacterial swimming in a well-controlled environment, for durations of up to an hour and with a temporal resolution greater than the flagellar rotation rates of approximately 100 Hz. The assay is based on an instrument combing optical tweezers, light and fluorescence microscopy, and a microfluidic chamber. Using this device we characterized the long-term statistics of the run-tumble time series in individual \textit{Escherichia coli} cells. We also quantified higher-order features of bacterial swimming, such as changes in velocity and reversals of swimming direction. Additionally, we investigated the effects of flagella number on swimming parameters including speed and tumble frequency. [Preview Abstract] |
Wednesday, March 17, 2010 10:24AM - 10:36AM |
P10.00011: Mechanisms of adaptation to stimulus statistics in neuronal systems Michael Famulare, Barry Wark, Rebecca Mease, Adrienne Fairhall In transforming sensory data into voltage signals, the strategies employed by neurons and neural systems have been shown to be adaptive: as the statistical properties of the environment change, the mapping from input to output also changes, often in such a way as to maximize information transmission. In large part, neuronal dynamics arise from voltage-dependent configuration changes in ion-selective conducting channel proteins, and so neurons are inherently nonlinear when viewed as electrical devices. By expressing different mixes of channels, isolated neurons can express a large variety of particular input/output relations. We show how the mechanisms by which neurons implement adaptive coding arise from the intrinsic neuronal nonlinearities, and we study the conditions under which the adaptation is optimal. We focus specifically on the timescales over which adaptation occurs and the functional changes to the input/output relationships that result. The timescale for adaptation to changes in stimulus statistics is limited by statistical considerations. We show that treating adaptation to changing stimulus statistics as an estimation problem predicts experimentally observed properties of adaptation timescales. [Preview Abstract] |
Wednesday, March 17, 2010 10:36AM - 10:48AM |
P10.00012: Automated Probing and Inference of Analytical Models for Metabolic Network Dynamics John Wikswo, Michael Schmidt, Jerry Jenkins, Jonathan Hood, Hod Lipson We introduce a method to automatically construct mathematical models of a biological system, and apply this technique to infer a seven-dimensional nonlinear model of glycolytic oscillations in yeast -- based only on noisy observational data obtained from \textit{in silico} experiments. Graph-based symbolic encoding, fitness prediction, and estimation-exploration can for the first time provide the level of symbolic regression required for biological applications. With no \textit{a priori} knowledge of the system, the Cornell algorithm in several hours of computation correctly identified all seven ordinary nonlinear differential equations, the most complicated of which was $\frac{dA_3 }{dt}=-1.12\cdot A_3 -\frac{\mbox{192.24}\cdot A_3 S_1 }{1+\mbox{12.50}\cdot A_3 ^4}+124.92\cdot S_3 +31.69\cdot A_3 S_3 $, where A$_{3}$ = [ATP], S$_{1}$= [glucose], and S$_{3}$ = [cytosolic pyruvate and acetaldehyde pool]. Errors on the 26 parameters ranged from 0 to 14.5{\%}. The algorithm also automatically identified new and potentially useful chemical constants of the motion, $e.g. \quad -k_1 N_2 +K_2 v_1 +k_2 S_1 A_3 -(k_4 -k_5 v_1 )A_3 ^4+k_6 \approx 0$. This approach may enable automated design, control and analysis of wet-lab experiments for model identification/refinement. [Preview Abstract] |
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