Shifted levels of sleep and activity under darkness as mechanisms underlying ectoparasite resistance.

Parasites harm host fitness and are pervasive agents of natural selection to evolve host defense strategies Host defensive traits in natural populations typically show genetic variation, which may be maintained when parasite resistance imposes fitness costs on the host in the absence of parasites. Previously we demonstrated significant evolutionary responses to artificial selection for increasing behavioral immunity to Gamasodes queenslandicus mites in replicate lines of Drosophila melanogaster. Here, we report transcriptional shifts in metabolic processes between selected and control fly lines based on RNA-seq analyses.

Heritability and preadult survivorship costs of ectoparasite resistance in the naturally occurring Drosophila-Gamasodes mite system.

Our understanding of the evolutionary significance of ectoparasites in natural communities is limited by a paucity of information concerning the mechanisms and heritability of resistance to this ubiquitous group of organisms. Here, we report the results of artificial selection for increasing ectoparasite resistance in replicate lines of Drosophila melanogaster derived from a field-fresh population. Resistance, as ability to avoid infestation by naturally co-occurring Gamasodes queenslandicus mites, increased significantly in response to selection and realized heritability (SE) was estimated to be 0.

Interactions with ectoparasitic mites induce host metabolic and immune responses in flies at the expense of reproduction-associated factors.

Parasites cause harm to their hosts and represent pervasive causal agents of natural selection. Understanding host proximate responses during interactions with parasites can help predict which genes and molecular pathways are targets of this selection. In the current study, we examined transcriptional changes arising from interactions between Drosophila melanogaster and their naturally occurring ectoparasitic mite, Gamasodes queenslandicus.

Experimental evolution with a multicellular host causes diversification within and between microbial parasite populations-Differences in emerging phenotypes of two different parasite strains.

Host-parasite coevolution is predicted to have complex evolutionary consequences, potentially leading to the emergence of genetic and phenotypic diversity for both antagonists. However, little is known about variation in phenotypic responses to coevolution between different parasite strains exposed to the same experimental conditions. We infected Caenorhabditis elegans with one of two strains of Bacillus thuringiensis and either allowed the host and the parasite to experimentally coevolve (coevolution treatment) or allowed only the parasite to adapt to the host (one-sided parasite adaptation).

Evolution of increased larval competitive ability in Drosophila melanogaster without increased larval feeding rate.

Multiple experimental evolution studies on Drosophila melanogaster in the 1980s and 1990s indicated that enhanced competitive ability evolved primarily through increased larval tolerance to nitrogenous wastes and increased larval feeding and foraging rate, at the cost of efficiency of food conversion to biomass, and this became the widely accepted view of how adaptation to larval crowding evolves in fruitflies.We recently showed that populations of D. ananassae and D.

Multiple-genotype infections and their complex effect on virulence.

Multiple infections are common. Although in recent years our understanding of multiple infections has increased significantly, it has also become clear that a diversity of aspects has to be considered to understand the interplay between co-infecting parasite genotypes of the same species and its implications for virulence and epidemiology, resulting in high complexity. Here, we review different interaction mechanisms described for multiple infections ranging from competition to cooperation.

Adaptation to larval crowding in Drosophila ananassae and Drosophila nasuta nasuta: increased larval competitive ability without increased larval feeding rate.

The standard view of adaptation to larval crowding in fruitflies, built on results from 25 years of multiple experimental evolution studies on Drosophila melanogaster, was that enhanced competitive ability evolves primarily through increased larval feeding and foraging rate, and increased larval tolerance to nitrogenous wastes, at the cost of efficiency of food conversion to biomass. These results were at odds from the predictions of classical K-selection theory, notably the expectation that selection at high density should result in the increase of efficiency of conversion of food to biomass, and were better interpreted through the lens of α-selection. We show here that populations of D.

Testing GxG interactions between coinfecting microbial parasite genotypes within hosts.

Host-parasite interactions represent one of the strongest selection pressures in nature. They are often governed by genotype-specific (GxG) interactions resulting in host genotypes that differ in resistance and parasite genotypes that differ in virulence depending on the antagonist's genotype. Another type of GxG interactions, which is often neglected but which certainly influences host-parasite interactions, are those between coinfecting parasite genotypes.

Adaptation to larval crowding in Drosophila ananassae leads to the evolution of population stability.

Density-dependent selection is expected to lead to population stability, especially if r and K tradeoff. Yet, there is no empirical evidence of adaptation to crowding leading to the evolution of stability. We show that populations of Drosophila ananassae selected for adaptation to larval crowding have higher K and lower r, and evolve greater stability than controls.

Sparse distributed memory using rank-order neural codes.

A variant of a sparse distributed memory (SDM) is shown to have the capability of storing and recalling patterns containing rank-order information. These are patterns where information is encoded not only in the subset of neuron outputs that fire, but also in the order in which that subset fires. This is an interesting companion to several recent works in the neuroscience literature, showing that human memories may be stored in terms of neural spike timings.