Bulletin of the American Physical Society
APS March Meeting 2015
Volume 60, Number 1
Monday–Friday, March 2–6, 2015; San Antonio, Texas
Session T48: Focus Session: Physics of Evolutionary and Population Dynamics II |
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Sponsoring Units: DBIO Chair: Uwe Tauber, Virginia Tech University Room: 217C |
Thursday, March 5, 2015 11:15AM - 11:27AM |
T48.00001: Noise-Induced Homochirality in Spatially Extended Chemical and Biological Systems Farshid Jafarpour, Tommaso Biancalani, Nigel Goldenfeld Autocatalysis has long been assumed to be the primary mechanism for homochirality in chemical and biological systems. The connection between autocatalysis and homochirality was originally established in a model by F. C. Frank [1], which included nonlinearity through an annihilation reaction. This extra reaction, which is not of the autocatalytic form, introduces fixed points in the dynamics at mean field level, which are identified as homochiral states. Here we remove this extra reaction, so that at the mean field level the only fixed point is the racemic state. Nevertheless, solving the full stochastic theory in zero dimensions, we show that homochiral states can arise due to intrinsic noise. Finally we explore whether these homochiral states are stable in spatially-extended systems.\\[4pt] [1] F. Frank, Biochimica et biophysica acta 11, 459 (1953). [Preview Abstract] |
Thursday, March 5, 2015 11:27AM - 11:39AM |
T48.00002: Moment Closure Analysis of SIRS Disease Model on Heterogeneous Networks Daniel T. Citron, Christopher R. Myers We perform a moment closure analysis of the stochastic susceptible-infected-recovered-susceptible (SIRS) model of infectious disease dynamics on heterogeneous networks. The SIRS model, which returns previously infected individuals to a susceptible state, supports a nontrivial steady state representing persistent endemic disease. In the context of networks, the heterogeneous mean field (HMF) method can be used to predict how network structure affects the SIRS model by dividing the network into classes with degree-dependent mean field coupling strengths. To verify the accuracy of the HMF, we simulate the SIRS model on heterogeneous networks. In our simulations we find, in disagreement with the HMF, the survival probability of the steady state depends on system size. This discrepancy stems from the fluctuations present in the stochastic model that are ignored by the HMF. We extend the HMF results by applying moment closure to each degree class. Our moment closure analysis provides a probabilistic description of the steady state for each degree class, which can be used to show how stochastic fluctuations and extinction depend on the size of the full network. We suggest that this technique may be used to analyze other stochastic models of dynamical processes. [Preview Abstract] |
Thursday, March 5, 2015 11:39AM - 11:51AM |
T48.00003: Scaling laws describe memories of host-pathogen riposte in the HIV population John Barton, Mehran Kardar, Arup Chakraborty The enormous genetic diversity and mutability of the human immunodeficiency virus (HIV) has prevented effective control of this virus by natural immune responses or vaccination. Evolution of the circulating HIV population has thus occurred in response to diverse, ultimately ineffective, immune selection pressures that randomly change from host to host. We show that the interplay between the diversity of human immune responses and the ways that HIV mutates to evade them results in distinct sets of sequences defined by similar collectively coupled mutations. Scaling laws that relate these sets of sequences resemble those observed in linguistics and other branches of inquiry, and dynamics reminiscent of neural networks are observed. Like neural networks that store memories of past stimulation, the circulating HIV population stores memories of host-pathogen combat won by the virus. We describe an exactly solvable model that captures the main features of the sets of sequences, and a simple mechanistic model for the origin of the observed scaling laws. Our results define collective mutational pathways used by HIV to evade human immune responses, which could guide vaccine design. [Preview Abstract] |
Thursday, March 5, 2015 11:51AM - 12:03PM |
T48.00004: Environmental spatial structure and competition determine the relative fitness of a multicellular aggregate in a young bacterial biofilm Jaime Hutchison, Kasper Kragh, Gavin Melaugh, Christopher Rodesney, Yasuhiko Irie, Aled Roberts, Steve Diggle, Rosalind Allen, Vernita Gordon, Thomas Bjarnsholt The canonical description of biofilm development begins with free-swimming, single bacterial cells which land on and adhere to a surface, mature into three-dimensional structures, and eventually disperse to form new biofilms. However, the interplay between single cells and larger, three-dimensional structures in early biofilm development has not been studied. We use timelapse confocal microscopy and quantitative measurements of biomass, combined with numerical, individual-based simulations to determine the relative fitness of single cells and preformed, multicellular aggregates. We find that the relative fitness of multicellular aggregates depends markedly on the density of surrounding single cells. We attribute this competition-dependent growth advantage to an interplay between a spatially-structured nutrient environment and the spatial distribution of cells in the aggregate. Our findings suggest that when competition for resources is high and there is spatial structure in the distribution of resources, aggregates of cells can outperform single cells and may be a preferred way to seed new biofilms. [Preview Abstract] |
Thursday, March 5, 2015 12:03PM - 12:15PM |
T48.00005: Population Dynamics of Metastable Growth Rates Lindsay Moore, Elad Stolovicki, Erez Braun Neo-Darwinian evolution provides a paradigm for population dynamics built on random mutations and selection with a clear separation of time-scales between single-cell mutation rates and the rate of reproduction. By studying the adaptation dynamics of genetically rewired yeast cells adapting to a severe regulatory challenge, we have uncovered a novel type of population dynamics in which intracellular processes seem to play a role in shaping the population structure. Under constant environmental conditions, we measure a wide distribution of growth rates that coexist in the population for very long durations (\textgreater 100 generations). Remarkably, the fastest growing cells do not take over the population on the time-scale dictated by the width of the growth-rate distributions and simple selection. In fact, the population-average growth rate plateaus and even decreases over the course of the adaptation, on intermediate time-scales of tens of generations. Our data show that the phenotypic state of the cells in a constant environment is metastable and varies on time-scales that reflect the importance of long-term intracellular processes in shaping the population structure. Moore LS, Stolovicki E, Braun E (2013) Population Dynamics of Metastable Growth-Rate Phenotypes. PLoS ONE 8(12):e81671. [Preview Abstract] |
Thursday, March 5, 2015 12:15PM - 12:27PM |
T48.00006: Steering antibody evolution to combat rapidly mutating pathogens Shenshen Wang, Jordi Mata-Fink, Dennis Burton, Dane Wittrup, Mehran Kardar, Arup Chakraborty The adaptive immune system houses amazingly efficient evolutionary processes coordinated across multiple length and time scales to protect higher organisms from diverse infectious pathogens. The optimization problem to be solved is often intricately constrained and highly dynamical. Failure of solving the problem timely leads to loss of protection. One such devastating situation is posed by rapidly mutating viruses (e.g. HIV which infects the immune system itself). One major challenge of designing an effective vaccine is to contain a diversifying mixture of antigen variants from evading recognition by antibodies. To confront this challenge, we develop a multi-scale computational model to simulate the stochastic evolutionary process of antibody affinity maturation against time varying antigen. By introducing dynamics into the design principle, we identify the optimal vaccination strategy which has been shown in mouse experiment to be very effective in focusing antibody response to the vulnerable part of the virus. [Preview Abstract] |
Thursday, March 5, 2015 12:27PM - 12:39PM |
T48.00007: Balancing the evolution advantages and drawbacks of CRISPR. Pu Han, Michael Deem CRISPR/Cas (Cluster Regularly Interspaced Short Palindromic Repeats/CRISPR associated proteins) is an adaptive immune system of prokaryotes. It can protect bacteria against invading genetic material. Besides providing immunity against lytic phages, the CRISRP/Cas system can block the acquisition of beneficial mobile genes, such as plasmids carrying antibody resistant genes. We discuss how bacteria balance the advantages and the drawbacks of CRISPR in an environment that has both lytic phages and beneficial mobile genes. We show that in the absence of lytic phages, bacteria lose CRISPR/Cas rapidly to acquire the beneficial mobile genes. We also discuss how CRISPR/Cas establishes in the bacterial population in the presence of both lytic phages and beneficial mobile genes. [Preview Abstract] |
Thursday, March 5, 2015 12:39PM - 12:51PM |
T48.00008: A Stochastic Cooperative Agent Model of Band-Pass Antibiotic Resistance Louis Nemzer, Robert Smith The recently described phenomenon of band-pass antibiotic resistance occurs when bacteria exposed to a periodic environment of oscillating antibiotic concentration grow fastest at intermediate period lengths. Previously, it has been shown that such behavior can arise from a non-linearity in individual fitness as a function of the initial colony density, called the ``Allee effect,'' as well as a fixed-point catastrophe that depends very strongly on the antibiotic concentration. Here, we present a new agent-based, \textit{in silico} stochastic model of cooperative antibiotic resistance. This model attempts to capture the behavior of ``cooperative'' bacteria that, for example, expend resources to produce enzymes that break down $\beta $-lactam antibiotic molecules, but are subject to the problem of freeloading by non-secretors that benefit but do not contribute. Colony survival can be threatened when exposed to a periodic antibiotic challenge. By creating a simulation in which the bacteria are modeled as stochastic agents, the effect of antibiotic concentration, period of antibiotic oscillation, and degree of cooperativity can be evaluated. [Preview Abstract] |
Thursday, March 5, 2015 12:51PM - 1:03PM |
T48.00009: Flow-driven waves during pattern formation of Dictyostelium discoideum Azam Gholami, Oliver Steinbock, Vladimir Zykov, Eberhard Bodenschatz The slime mold Dictyostelium discoideum (D.d.) is a well known model system for the study of biological pattern formation. In the natural environment, aggregating populations of starving Dictyostelium cells may experience fluid flows that can profoundly change the underlying wave generation process. Recently we conducted experiments to study the effect of a differential flow in quasi one-dimensional colonies of the signaling D.d. cells. The external flow advects the signaling molecule cAMP downstream, while the chemotactic cells attached to the solid substrate and are not transported with flow. This transport anisotropy in the extracellular medium induced macroscopic wave trains that developed spontaneously, propagated with the velocity proportinoal to the imposed flow velocity with a unique period. In this work, we investigate the mechanism of flow-induced waves using the well-established Martiel-Goldbeter model. In the linear regime, our analytical calculations show that a convective transport of extracellular cAMP in a uniform field of signal-relaying cells leads to a flow-induced instability of the traveling-wave type. In the nonlinear regime, numerical simulations show a convective instability with propagating waves, in agreement with the predictions of linear analysis. [Preview Abstract] |
Thursday, March 5, 2015 1:03PM - 1:39PM |
T48.00010: Diffusion limited mutualism Invited Speaker: Kirill Korolev Microbes trade diffusible molecules to survive and maintain complex ecological functions. Physicists have substantially advanced our understanding of microbial populations, primarily relying on the evolutionary game theory. Game theory however was developed for higher organisms and cannot easily describe microbial cooperation, which involves the exchange of small, highly diffusible molecules. We formulated and solved a model that accurately represents the physics of diffusion in microbial colonies. In particular, we discovered a general approach that eliminates metabolite diffusion and recasts population dynamics in the traditional game theory framework, but with renormalized parameters. We applied this approach to the problem of two-way cross-feeding, a common interaction motif in the microbial world that is the subject of several experimental studies. Naively one would assume that nutrient diffusion should facilitate mutualistic interactions in microbial colonies. Indeed, because microbes are not completely mixed inside a colony, different species tend to form small domains, and diffusion should facilitate the exchange of the nutrients between the two cross-feeding species. We, however, find that nutrient diffusion reduces the strength of mutualism and leads to a phase transition that makes mutualism impossible. We analytically compute the critical diffusivity at which mutualism is lost and find the universality class of the phase transition. The distance to this phase transition controls the size of the domains formed by the species, a quantity of prime interest in empirical studies. Finally, we show that the differences in public good diffusivities affect mutualism only in the presence of nonlinearities in the public good dynamics. In particular, fitness nonlinearities suppress mutualism and favor the species producing nutrients that diffuse more slowly. [Preview Abstract] |
Thursday, March 5, 2015 1:39PM - 1:51PM |
T48.00011: Coalescent theory analysis of phylogenetic trees in a model of evolutionary dynamics Dawn King, Sonya Bahar Phylogenetic trees and the hierarchal, biological levels of organization that exist within them are of great importance to evolutionary theory. With a neutral, agent-based model of evolutionary dynamics, we have investigated the conditions under which organisms form clusters, analogous to species. Previous work has shown phase transition behavior as a function of the maximum mutation size ($\mu )$ on a rugged landscape with assortative mating (Dees and Bahar, 2010), and, with the addition of bacterial fission, on a completely neutral landscape (Scott \textit{et al.}, 2013). The bacterial version was then classified as belonging to the directed percolation universality class (Scott, 2014). Here, we further investigate the emergent property of speciation by analyzing the genealogical tree structures created by the forward-in-time reaction-diffusion dynamics of the three mating types -- assortative, bacterial, and random -- as a function of the random death percentage. Specifically, we will use Kingman's $n$-coalescent to investigate the distributions of the times to most recent common ancestor (TMRCA) and determine whether universal ratios exist. [Preview Abstract] |
Thursday, March 5, 2015 1:51PM - 2:03PM |
T48.00012: Influenza Evolution and Vaccine Effectiveness in 2014/2015 Michael Deem I discuss evolution of the influenza virus, in the context of the 2014/2015 season. Typically a quasispecies of related influenza strains is responsible for the majority of virus in the human population. The virus evolves, however, and this is the reason for the yearly updates to the influenza vaccine. The selection pressure on the virus to evolve arises from immune history in the population due to prior infection or vaccination, which provide protection against closely related strains. This immune protection is well described by the $p_{\rm epitope}$ theory of vaccine efficacy for both H3N2 and H1N1 influenza. The 2014 flu season provides an interesting example of the emergence of new flu strains, which are not protected against by the vaccine. I will discuss how the emergence of these new strains can be detected and predicted, making use of theory of the immune system. I discuss the significantly different strain of the virus that is likely to dominant in the 2015/2016 flu season. [Preview Abstract] |
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