Articles: biological-evolution.
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We investigate how the loss of previously evolved diversity in host resistance to disease is dependent on the complexity of the underlying evolutionary trade-off. Working within the adaptive dynamics framework, using graphical tools (pairwise invasion plots, PIPs; trait evolution plots, TEPs) and algebraic analysis we consider polynomial trade-offs of increasing degree. Our focus is on the evolutionary trajectory of the dimorphic population after it has been attracted to an evolutionary branching point. ⋯ In particular, the loss of diversity in this model always occurs in such a way that the remaining strain is not attracted back to the branching point but to an extreme of the trade-off, meaning the diversity is lost forever. We also show similar results for a non-polynomial but complex trade-off, and for a different eco-evolutionary model. Our work further highlights the importance of trade-offs to evolutionary behaviour.
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Q fever is a highly infectious disease with a worldwide distribution. Its causative agent, the intracellular bacterium Coxiella burnetii, infects a variety of vertebrate species, including humans. Its evolutionary origin remains almost entirely unknown and uncertainty persists regarding the identity and lifestyle of its ancestors. ⋯ Using both colony-reared and field-collected gravid females, we further establish the presence of highly efficient maternal transmission of these Coxiella-like organisms in four examined tick species, a pattern coherent with an endosymbiotic lifestyle. Our laboratory culture assays also showed that these Coxiella-like organisms were not amenable to culture in the vertebrate cell environment, suggesting different metabolic requirements compared to C. burnetii. Altogether, this corpus of data demonstrates that C. burnetii recently evolved from an inherited symbiont of ticks which succeeded in infecting vertebrate cells, likely by the acquisition of novel virulence factors.
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Tag-based ethnocentric cooperation is a highly robust behavior which can evolve and prevail under a wide variety of conditions. Recent studies have demonstrated, however, that ethnocentrism can temporarily be suppressed by other competing strategies, especially in its early evolutionary stages. In a series of computational experiments, conducted with an agent-based evolutionary model of tag-mediated cooperation, we addressed the question of whether a stochastically established and once dominant non-ethnocentric strategy such as indiscriminate altruism can stably persist and permanently outweigh ethnocentrism. ⋯ We find that in combination with an implemented memory mechanism and tags, random bias acting in favor of altruists can lead to their long-lasting victory over all other types of strategists. The difference in density between altruistic and ethnocentric cooperators increases with greater rewiring of the underlying network, but decreases with growing population size. These findings suggest that randomness plays an important role in promoting non-ethnocentric cooperation and contributes to our understanding of how other than adaptive mechanisms can initiate the design of novel behavioral phenotypes, thereby shaping surprisingly new evolutionary pathways.
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Simple genetic changes that correlate with drug resistance are used routinely to identify resistant pathogens. These "molecular markers" have usually been defined long after the phenotype of resistance was noted. The molecular changes at the "end game" reflect a long and complex evolution of genetic changes, but once a solidly resistant set of changes assembles under drug selection, that genotype is likely to become fixed, and resistant pathogens will spread widely. ⋯ The full range of modern methods has been applied to define rapidly the genetic changes responsible. Changes associated with artemisinin resistance are complex and seem to be evolving rapidly, especially in Southeast Asia. This is a rare chance to observe the early stages in evolution of resistance, and to develop strategies to reverse or mitigate the trend and to protect these key medicines.
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Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. ⋯ The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network-that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved.