Bulletin of the American Physical Society
APS March Meeting 2018
Volume 63, Number 1
Monday–Friday, March 5–9, 2018; Los Angeles, California
Session X49: Evolutionary Dynamics of Genomes IIFocus
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Sponsoring Units: DBIO GSNP Chair: Benjamin Greenbaum, Mount Sinai Sch of Med Room: LACC 511A |
Friday, March 9, 2018 8:00AM - 8:36AM |
X49.00001: Identification and functional study of nucleosome-depleting factors Invited Speaker: Lu Bai Nucleosomes present a barrier for the binding of most transcription factors (TFs). However, a special group of TFs can invade compact chromosome and deplete nucleosomes near their binding sites. These TFs, known as nucleosome-depleting factors (NDFs), direct the binding of other TFs and enable them to activate transcription. Despite NDFs’ essential functions, we lack an experimental scheme to systematically categorize them and measure their nucleosome-depleting activities on a genome-wide scale. Here, by generating a complex library of synthetic regulatory elements and measuring the nucleosome occupancy on these sequences in vivo, we developed a high-throughput assay to identify NDFs from genome-wide TFs and to systematically evaluate the impact of the location, orientation, copy number, and combination of factor binding sites on the nucleosome-depleting activities. We applied this method to budding yeast and identified both new and established NDFs with variable nucleosome-depleting activities. We found that the activity of strong NDFs show topological relationships with nucleosome structure, and multiple closely-spaced weak NDFs can lead to significant nucleosome depletion, presumably through nucleosome-mediated cooperativity. By comparing the properties of TFs with different nucleosome-depleting activities, we propose that strong NDFs may function by directly competing with histones for the same DNA, while weak NDFs may have developed special structural features in recognizing nucleosomal DNA. Overall, our method presents a new framework to functionally characterize NDFs and further our understanding of the molecular mechanism of nucleosome invasion. |
Friday, March 9, 2018 8:36AM - 8:48AM |
X49.00002: Why does HIV have so few spike proteins on its surface, unlike any other virus? Assaf Amitai, Mehran Kardar, Arup Chakraborty The surface of a virus is covered with spike proteins that are used to penetrate and infect a host cell. Spikes are also targets of the immune system as antibodies can bind to them and neutralize the virus. Most viruses have very high density of spikes of their surface. However, the HIV virus has spike density almost two orders of magnitude smaller than other viruses. This unique feature of HIV has defied explanation since it was first discovered. |
Friday, March 9, 2018 8:48AM - 9:00AM |
X49.00003: Abstract Withdrawn
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Friday, March 9, 2018 9:00AM - 9:12AM |
X49.00004: A model for understanding long-term evolution experiments Yipei Guo, Marija Vucelja, Ariel Amir Laboratory evolution experiments have proven to be a productive way of studying and gaining insights into evolutionary processes. Nevertheless, the dynamics of fitness over long time scales is still not well understood. Data from the Lenski lab’s long-term evolution experiment shows that the relative growth rates of bacteria continue to increase even after almost 30 years (over 65k generations). Despite the rate of fitness increase slowing down dramatically, mutations continue to accumulate at an almost constant rate. This type of adaptation dynamics has often been discussed in the context of fitness landscapes, where growth rates of mutants are assumed to be drawn from some distribution. In such a formalism, the concept of epistasis lies in the idea that the distribution of potential fitness effects varies with the current fitness. However, it is unclear if landscapes are indeed fitness-parametrized, since genotypes with the same fitness could potentially differ in their capacity to gain beneficial mutations that fix in a population, and how any proposed form of epistasis encoded in mutant fitness distributions could arise mechanistically. In this work, we compare various models for adaptation and present an alternative model to explain the observations in Lenski’s experiment. |
Friday, March 9, 2018 9:12AM - 9:24AM |
X49.00005: Forecasting Extinction in Ecosystems with Coevolving Species Vu Nguyen, Dervis Vural Standard ecological models predict how populations change in time, given fixed interspecies interactions. However, as any phenotype, variations in interaction patterns should lead to their evolution. To incorporate ecological evolution into population dynamics, we start with the multi-species Lotka-Volterra equations and occasionally introduce mutants that have slight variations in their interactions with other species. Those favorable interaction patterns will fixate, subsequently causing ecological shifts. We find that the incremental shifts driven by successive fixations gradually accumulate, inevitably leading to a singularity, signaling the extinction of one or more species. Using a simple mean-field approach we obtain analytical upper and lower bounds for the time to soonest extinction. Furthermore, for two kind of mutation models (random, and zero-sum) we determine probability distributions governing the lifetime of species as well as the ecosystem as a whole. |
Friday, March 9, 2018 9:24AM - 9:36AM |
X49.00006: Controlling social evolution of microbial populations Gurdip Uppal, Dervis Vural Many species of microbes cooperate by producing "public goods" from which they collectively benefit. However, these groups are under the risk of being taken over by cheating mutants that do not contribute to the pool of public goods. Here we present theoretical findings that address how social evolution of microbes can be manipulated by external perturbations, to either prevent or promote the fixation of cheaters. To control group reproduction rate and group size, we determine the effects of fluid dynamical properties such as flow rate or boundary geometry. We also study the social evolutionary consequences of introducing beneficial or harmful chemicals at steady state and in a time dependent fashion. We show that by modulating the flow rate and by applying pulsed chemical signals, we can modulate the spatial structure and dynamics of the groups, in a way that can select for more or less cooperative microbial populations. |
Friday, March 9, 2018 9:36AM - 9:48AM |
X49.00007: High dimensional eco-evolutionary dynamics using consumer-resource models Stephen Martis, Benjamin Good, Oskar Hallatschek Microbes live and adapt in the context of large, complex communities, in the ocean, in human microbiomes and in many other natural settings. Recently, stable coexistence has been shown to evolve spontaneously and reproducibly in clonal evolution experiments, suggesting that diversification and evolution can occur on comparable timescales and may feed back on each other. However, the signatures of this feedback are not well understood in ecosystems with many coexisting species. In order to probe how the timescales of ecological and evolutionary change control the behavior of such systems, we present a minimal model of eco-evolutionary dynamics based on the well-known consumer-resource model, incorporating both resource strategies on a set of substitutable resources and fitness. Using the model, we map how mutation rates in strategy and fitness space impact ecological observables like species-level diversity and evolutionary observables like phylogenetic trees. Inspired by these results, we suggest quantitative measurements to probe the resilience and adaptation of microbial ecosystems to natural selection. |
Friday, March 9, 2018 9:48AM - 10:00AM |
X49.00008: Synergistic Interactions between Host Immunity, Phage and Commensal Bacteria in Controlling Bacterial Pathogens Chung Yin Leung, Joshua Weitz The host immune system is a critical driver of within-host dynamics of pathogens. However, there is limited understanding of the tripartite interactions between host immunity, pathogenic bacteria and antimicrobials. Combining nonlinear dynamic models and animal experiments, we have recently shown how host immunity can clear an acute respiratory infection in synergy with phage (viruses that exclusively infect bacteria) [1, 2]. As a consequence of this synergy, phage and host immunity can eliminate multidrug-resistant bacterial pathogens, even when neither phage nor the immune response can do so alone. Here, we extend our theoretical framework to include potential synergies between host immunity and commensal or probiotic bacteria. By incorporating competition between commensal and pathogenic bacteria, our results suggest that host immunity can act synergistically with commensals to eliminate bacterial pathogens by tipping the balance between beneficial and pathogenic bacterial populations. We will discuss the implications of our results for phage and probiotic therapies. |
Friday, March 9, 2018 10:00AM - 10:12AM |
X49.00009: Green Function of Correlated Genes and the Mechanical Evolution of Protein Sandipan Dutta, Jean-Pierre Eckmann, Albert Libchaber, Tsvi Tlusty Growing evidence suggests that cooperative interactions and motions underpin protein functions. But in spite of vast data, the information-dense, heterogeneous nature of protein has held back the progress in understanding the underlying principles. We outline a general theory of protein that quantitatively links sequence, dynamics and function: The protein is a strongly-coupled amino acid network whose interactions and large-scale motions are captured by the mechanical propagator (the Green function). The propagator relates the gene to the connectivity of the amino acid network and the transmission of forces through the protein. Mutations introduce localized perturbations to the propagator which scatter the force field. The emergence of function is manifested by a topological transition when a band of perturbations divides the protein into subdomains. Epistasis quantifies how much the combined effect of multiple mutations departs from additivity. |
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