Bulletin of the American Physical Society
APS March Meeting 2014
Volume 59, Number 1
Monday–Friday, March 3–7, 2014; Denver, Colorado
Session D10: Focus Session: Evolutionary Dynamics and Population Genetics |
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Sponsoring Units: DBIO GSNP Chair: Xiang Qiang Chu, Wayne State University Room: 201 |
Monday, March 3, 2014 2:30PM - 3:06PM |
D10.00001: Fitness seascapes and adaptive evolution of the influenza virus Invited Speaker: Michael Lassig The seasonal human influenza A virus undergoes rapid genome evolution. This process is triggered by interactions with the host immune system and produces significant year-to-year sequence turnover in the population of circulating viral strains. We develop a dynamical fitness model that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a viral strain: adaptive changes, which are under positive selection, and deleterious mutations, which affect conserved viral functions such as protein stability. Combined with the influenza strain tree, this fitness model maps the adaptive history of influenza A. We discuss the implications of our results for the statistical theory of adaptive evolution in asexual populations. Based on this and related systems, we touch upon the fundamental question of when evolution can be predicted. [Preview Abstract] |
Monday, March 3, 2014 3:06PM - 3:18PM |
D10.00002: Biophysical Fitness Landscapes and Evolutionary Dynamics of Proteins Michael Manhart, Alexandre Morozov The molecular biophysics of proteins fundamentally shapes their fitness landscapes and evolutionary dynamics. For example, the evolution of new function in a protein is constrained by the need to maintain folding stability. We investigate the role of molecular biophysics in protein evolution by developing a class of fitness landscapes based on protein folding and binding energetics. We characterize the properties of these landscapes, such as their epistasis, accessibility, and number of local maxima. We also use a recently-developed path-based approach to random walks on networks to analyze the dynamics of populations evolving on these landscapes, focusing especially on the distribution and diversity of adaptive trajectories. These models make qualitative predictions relevant to both natural evolution as well as directed evolution experiments. [Preview Abstract] |
Monday, March 3, 2014 3:18PM - 3:30PM |
D10.00003: Inferring the Mode of Selection from the Transient Response to Demographic Perturbations Daniel Balick, Ron Do, David Reich, Shamil Sunyaev Despite substantial recent progress in theoretical population genetics, most models work under the assumption of a constant population size. Deviations from fixed population sizes are ubiquitous in natural populations, many of which experience population bottlenecks and re-expansions. The non-equilibrium dynamics introduced by a large perturbation in population size are generally viewed as a confounding factor. In the present work, we take advantage of the transient response to a population bottleneck to infer features of the mode of selection and the distribution of selective effects. We develop an analytic framework and a corresponding statistical test that qualitatively differentiates between alleles under additive and those under recessive or more general epistatic selection. This statistic can be used to bound the joint distribution of selective effects and dominance effects in any diploid sexual organism. We apply this technique to human population genetic data, and severely restrict the space of allowed selective coefficients in humans. Additionally, one can test a set of functionally or medically relevant alleles for the primary mode of selection, or determine the local regional variation in dominance coefficients along the genome. [Preview Abstract] |
Monday, March 3, 2014 3:30PM - 3:42PM |
D10.00004: Hidden Complexity in Bacterial Evolution Robert Austin, Julia Bos, Grigory Tarnopolskiy, John Bestoso, James Sturm, Hyunsung Kim, Nader Pourmand, Robert Austin We compare the local fitness maxima a Growth Advantage in Stationary Phase (GASP) \cite{roberto} bacterial strain evolves in comparison to the local maxima of the parental wild-type strain. The rapid evolution of antibiotic resistance in GASP to an identical stressor, starting from a different initial phenotype and genotype, diverges from a parental wild-type strain on the fitness landscape. That is, while the GASP strain evolves a (Serine$^{83}$ $\rightarrow$ Leucine missense mutation in $gyrA$) which is the target of the antibiotic, only 2 amino acids removed from the WT strain resistant mutant, it does not evolve the other 3 SNPS the WT strain did. Rather, it excises the prophage e14 sequence \cite{e14}. We show that this e14 excision profoundly changes the ability of the GASP strain to form a biofilm, revealing the hidden complexity of {\it E. coli} evolution to antibiotics in complex environments. We show that these profound changes in resistance to cipro do not come at a substantial fitness cost on the landscape and discuss why this makes the mutations basically irreversible. [Preview Abstract] |
Monday, March 3, 2014 3:42PM - 3:54PM |
D10.00005: Population subdivision with migration can facilitate evolution on rugged fitness landscapes Anne-Florence Bitbol, David Schwab Natural selection drives organisms towards higher fitness, but crossing fitness valleys or plateaus may be necessary to progress up a rugged fitness landscape. In a subdivided population, quasi-independent explorations of the fitness landscape can be run in parallel, and furthermore, stochastic effects have an increased importance due to the smaller size of subpopulations. Thus, valley or plateau crossing may be facilitated locally, and migration can then spread beneficial mutations. We show that population subdivision with migration significantly accelerates the crossing of fitness valleys and plateaus over a wide parameter range, both with respect to a non-subdivided population and to a single subpopulation. Our generic and minimal model does not require environmental heterogeneity or specific geographic structure, and includes only subdivision with migration. Using Markov chain theory, we obtain analytical expressions of the conditions under which valley or plateau crossing by the subdivided population is as fast as that of its fastest subpopulation. We verify this prediction through stochastic simulations. Our results, obtained for fitness valleys and plateaus, also hold for weakly beneficial intermediate mutations. [Preview Abstract] |
Monday, March 3, 2014 3:54PM - 4:06PM |
D10.00006: Guiding the evolution to catch the virus: An in silico study of affinity maturation against rapidly mutating antigen Shenshen Wang, Dennis Burton, Mehran Kardar, Arup Chakraborty The immune system comprises an intricate and evolving collection of cells and molecules that enables a defense against pathogenic agents. Its workings present a rich source of physical problems that impact human health. One intriguing example is the process of affinity maturation (AM) through which an antibody (Ab)---a component of the host immune system---evolves to more efficiently bind an antigen (Ag)---a unique part of a foreign pathogen such as a virus. Sufficiently strong binding to the Ag enables recognition and neutralization. A major challenge is to contain a diversifying mixture of Ag variants, that arise in natural infection, from evading Ab neutralization. This entails a thorough understanding of AM against multiple Ag species and mutating Ag. During AM, Ab-encoding cells undergo cycles of mutation and selection, a process reminiscent of Darwinian evolution yet occurring in real time. We first cast affinity-dependent selection into an extreme value problem and show how the binding characteristics scale with Ag diversity. We then develop an agent-based residue-resolved computational model of AM which allows us to track the evolutionary trajectories of individual cells. This dynamic model not only reveals significant stochastic effects associated with the relatively small and highly dynamic population size, it also uncovers the markedly distinct maturation outcomes if designed Ag variants are presented in different temporal procedures. Insights thus obtained would guide rational design of vaccination protocols. [Preview Abstract] |
Monday, March 3, 2014 4:06PM - 4:18PM |
D10.00007: ABSTRACT WITHDRAWN |
Monday, March 3, 2014 4:18PM - 4:30PM |
D10.00008: Functional trade-offs and phenotypic diversity in cellular migration Thierry Emonet, Nicholas Frankel, Yann Dufour I will discuss our recent efforts to uncover the functional role of phenotypic heterogeneity in cellular migration and understand how biological systems may resolve functional trade-offs. We addressed this question using bacterial chemotaxis as model system. We find (1) that, while robust network design maintains the average behavior of the population in a functional range, harnessing inherent cell-to-cell variability around the average allows populations to adaptively diversify network functions, resolving trade-offs; and (2) that the molecular mechanism for directing this diversity is mutations in common gene regulatory elements. Our main theoretical conclusion is that the distribution of network parameters in itself is as likely to be under selection as network design. [Preview Abstract] |
Monday, March 3, 2014 4:30PM - 4:42PM |
D10.00009: Emergence of Rapid Evolution from Demographic Stochasticity Hong-Yan Shih, Nigel Goldenfeld The phenomenon of ``rapid evolution'' arises when genetic variation occurs fast enough to significantly change ecodynamics. Data from experiments with algae-rotifer system and bacteria-phage system show unusual dynamics when there are subpopulations of preys with different trait values, including predator-prey phase shifts near $\pi$ (and distinct from the canonical value of $\pi/2$) and so-called cryptic cycles, in which populations of preys remain constant while the predator population oscillates. Such phenomena have been modeled with deterministic differential equations containing empirical Michaelis-Menten kinetic terms and the unusual dynamics that is attributed to postulate complicated trade-off between sub-populations. Here we present a generic individual-level stochastic model of interacting populations that includes a subpopulation resistant to the predator but with metabolic cost. We solve this model by using a master equation approach, and by performing system size expansion, we find that antiphase and cryptic quasi-cycles can emerge from the combination of intrinsic demographic fluctuations and clonal mutations alone. These analytic results are then compared with Gillespie simulations, and the typical phase diagram of the system is calculated. [Preview Abstract] |
Monday, March 3, 2014 4:42PM - 4:54PM |
D10.00010: Selection, adaptation, and predictive information in changing environments Quentin Feltgen, Ilya Nemenman Adaptation by means of natural selection is a key concept in evolutionary biology. Individuals better matched to the surrounding environment outcompete the others. This increases the fraction of the better adapted individuals in the population, and hence increases its collective fitness. Adaptation is also prominent on the physiological scale in neuroscience and cell biology. There each individual infers properties of the environment and changes to become individually better, improving the overall population as well. Traditionally, these two notions of adaption have been considered distinct. Here we argue that both types of adaptation result in the same population growth in a broad class of analytically tractable population dynamics models in temporally changing environments. In particular, both types of adaptation lead to subextensive corrections to the population growth rates. These corrections are nearly universal and are equal to the predictive information in the environment time series, which is also the characterization of the time series complexity. [Preview Abstract] |
Monday, March 3, 2014 4:54PM - 5:06PM |
D10.00011: Cluster-Level Dynamics in a Neutral Phenotype Evolution Model Adam Scott, Dawn King, Sonya Bahar In agent-based models of nonequilibrium phase transitions, the agent dynamics can be described by reaction-diffusion processes such as branching-coalescing random walks. We have recently shown that a phase transition in a neutral phenotype evolution model comprised of many branching-coalescing random walkers belongs to the directed percolation (DP) universality class. However, while the organism processes are described by A-\textgreater 2A, 2A-\textgreater A, {\&} A-\textgreater 0, the cluster processes are B-\textgreater nB, mB-\textgreater B, {\&} B-\textgreater 0 (where n and m are positive integers). Therefore, despite the DP behavior of the transition at the organism level, we do not expect the clusters to exhibit the same universality class. Here, we will investigate cluster branching behavior by measuring reaction rates and show that the cluster density exponent suggests a different universality class at the cluster level. These results may have significant implications for multilevel selection in evolutionary biology. [Preview Abstract] |
Monday, March 3, 2014 5:06PM - 5:18PM |
D10.00012: Phase Transition Behavior in a Neutral Evolution Model Dawn King, Adam Scott, Nevena Maric, Sonya Bahar The complexity of interactions among individuals and between individuals and the environment make agent based modeling ideal for studying emergent speciation. This is a dynamically complex problem that can be characterized via the critical behavior of a continuous phase transition. Concomitant with the main tenets of natural selection, we allow organisms to reproduce, mutate, and die within a neutral phenotype space. Previous work has shown phase transition behavior in an assortative mating model with variable fitness landscapes as the maximum mutation size ($\mu )$ was varied (Dees and Bahar, 2010). Similarly, this behavior was recently presented in the work of Scott et al. (2013), even on a completely neutral landscape, for bacterial-like fission as well as for assortative mating. Here we present another neutral model to investigate the `critical' phase transition behavior of three mating types -- assortative, bacterial, and random -- in a phenotype space as a function of the percentage of random death. Results show two types of phase transitions occurring for the parameters of the population size and the number of clusters (an analogue of species), indicating different evolutionary dynamics for system survival and clustering. [Preview Abstract] |
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