Browsing by Author "Wang, Dong"

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    Effect of Modularity on Evolution in Heterogeneous Environments
    (2017-08-04) Wang, Dong; Deem, Michael W
    Biological systems are modular. It is natural to ask the question: why are biological systems modular? We show that under certain circumstances, being modular is beneficial. For example, when the environment changes, modularity coupled with horizontal gene transfer accelerates the adaptation of individuals. We have proved this result theoretically using a spin glass model of fitness, and we quantify the evolutionary advantage analytically. To establish the generality of this result, we apply other models of the fitness, such as Potts model or generalized NK model, to this problem, finding similar results. Simulations generate results consistent with our analytical calculations. Biological populations migrate at all scales. When individuals in a population migrate, they experience changing environments. What role does modularity play in the migration process? Under what conditions is modularity helpful? We generalize our model in one environment to several correlated environments with migrating individuals. We apply this model to two real world scenarios. First we study the migration of ancient humans in the Americas, and quantify how migration velocity depends on environmental gradient. In addition, we show that a modular knowledge system and frequent knowledge transfer accelerate the migration velocity. Second, we study bacteria in heterogeneous environments, showing that their resistance to antibiotics emerges very quickly in an antibiotic gradient. We show that a modular organization of genes accelerates this emergence of resistance, and we quantify how mutation rate, horizontal gene transfer rate, nutrients, and antibiotic gradient influence this emergence.
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    Modular knowledge systems accelerate human migration in asymmetric random environments
    (The Royal Society, 2016) Wang, Dong; Deem, Michael W.; Center for Theoretical Biological Physics
    Migration is a key mechanism for expansion of communities. In spatially heterogeneous environments, rapidly gaining knowledge about the local environment is key to the evolutionary success of a migrating population. For historical human migration, environmental heterogeneity was naturally asymmetric in the northﾖsouth (NS) and eastﾖwest (EW) directions. We here consider the human migration process in the Americas, modelled as random, asymmetric, modularly correlated environments. Knowledge about the environments determines the fitness of each individual. We present a phase diagram for asymmetry of migration as a function of carrying capacity and fitness threshold. We find that the speed of migration is proportional to the inverse complement of the spatial environmental gradient, and in particular, we find that NS migration rates are lower than EW migration rates when the environmental gradient is higher in the NS direction. Communication of knowledge between individuals can help to spread beneficial knowledge within the population. The speed of migration increases when communication transmits pieces of knowledge that contribute in a modular way to the fitness of individuals. The results for the dependence of migration rate on asymmetry and modularity are consistent with existing archaeological observations. The results for asymmetry of genetic divergence are consistent with patterns of human gene flow.
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    Modularity enhances the rate of evolution in a rugged fitness landscape
    (IOP Publishing Ltd, 2015) Park, Jeong-Man; Chen, Man; Wang, Dong; Deem, Michael W.; Center for Theoretical Biological Physics
    Biological systems are modular, and this modularity affects the evolution of biological systems over time and in different environments. We here develop a theory for the dynamics of evolution in a rugged, modular fitness landscape. We show analytically how horizontal gene transfer couples to the modularity in the system and leads to more rapid rates of evolution at short times. The model, in general, analytically demonstrates a selective pressure for the prevalence of modularity in biology. We use this model to show how the evolution of the influenza virus is affected by the modularity of the proteins that are recognized by the human immune system. Approximately 25% of the observed rate of fitness increase of the virus could be ascribed to a modular viral landscape.