Patterns and potential mechanisms of thermal preference in E. muscae-infected Drosophila melanogaster

Animals use various strategies to defend against pathogens. Behavioral fever, or fighting infection by moving to warm locations, is seen in many ectotherms. The behavior-manipulating fungal pathogen Entomophthora muscae infects numerous dipterans, including fruit flies and house flies, Musca domestica. House flies have been shown to exhibit robust behavioral fever early after exposure to E. muscae, then switch to prefer cool temperatures in the later stages of infection. Interestingly, no evidence of behavioral fever in response to any investigated pathogen has been found in the fruit fly, Drosophila melanogaster. However, they have been found to prefer cool temperatures during infections. To determine if fruit flies utilize behavioral fever, cold-seeking, or both during E. muscae infection, we used a two-choice behavioral assay to measure individual temperature preferences of E. muscae-exposed and unexposed flies at early (24-72 hour) and late (72-120 hour) infection time points. In contrast with our expectation from house flies, fruit flies did not exhibit behavioral fever. However, we found significant cold temperature-seeking in flies that died from infection on the day of the assay. To investigate whether this cold-seeking behavior was being caused by the fly or the fungus, we tested the effects of temperature on the fitness of the host, D. melanogaster, and the pathogen, E. muscae, during infection. We found that flies held at low and high temperatures for 24 hours before death from infection laid no eggs at the lower temperature. This could suggest that the fly is not causing the cold-seeking behavior because there is no apparent fitness benefit at low temperatures. Conversely, cadavers sporulating at the low temperature tended to cause more flies to eventually die from infection, indicating that E. muscae infects flies more effectively at lower temperatures. Preliminarily, our results support fungal control of temperature preference before death, though further testing is needed. The idea that E. muscae benefits from colder temperatures, and therefore drives cold-seeking behavior in D. melanogaster at the end of the host’s life, expands our current knowledge about host behavior manipulation by E. muscae and provides a fascinating avenue for investigating the mechanisms by which this fungus manipulates complex behaviors in its animal host

Variability in thermal and phototactic preferences in Drosophila may reflect an adaptive bet‐hedging strategy

Organisms use various strategies to cope with fluctuating environmental conditions. In diversified bet‐hedging, a single genotype exhibits phenotypic heterogeneity with the expectation that some individuals will survive transient selective pressures. To date, empirical evidence for bet‐hedging is scarce. Here, we observe that individual Drosophila melanogaster flies exhibit striking variation in light‐ and temperature‐preference behaviors. With a modeling approach that combines real world weather and climate data to simulate temperature preference‐dependent survival and reproduction, we find that a bet‐hedging strategy may underlie the observed interindividual behavioral diversity. Specifically, bet‐hedging outcompetes strategies in which individual thermal preferences are heritable. Animals employing bet‐hedging refrain from adapting to the coolness of spring with increased warm‐seeking that inevitably becomes counterproductive in the hot summer. This strategy is particularly valuable when mean seasonal temperatures are typical, or when there is considerable fluctuation in temperature within the season. The model predicts, and we experimentally verify, that the behaviors of individual flies are not heritable. Finally, we model the effects of historical weather data, climate change, and geographic seasonal variation on the optimal strategies underlying behavioral variation between individuals, characterizing the regimes in which bet‐hedging is advantageous

Wild flies hedge their thermal preference bets in response to seasonal fluctuations

Fluctuating environmental pressures can challenge organisms by repeatedly shifting the optimum phenotype. Two contrasting evolutionary strategies to cope with these fluctuations are 1) evolution of the mean phenotype to follow the optimum (adaptive tracking) or 2) diversifying phenotypes so that at least some individuals have high fitness in the current fluctuation (bet-hedging). Bet-hedging could underlie stable differences in the behavior of individuals that are present even when genotype and environment are held constant. Instead of being simply ‘noise,’ behavioral variation across individuals may reflect an evolutionary strategy of phenotype diversification. Using geographically diverse wild-derived fly strains and high-throughput assays of individual preference, we tested whether thermal preference variation in Drosophila melanogaster could reflect a bet-hedging strategy. We also looked for evidence that populations from different regions differentially adopt bet-hedging or adaptive-tracking strategies. Computational modeling predicted regional differences in the relative advantage of bet-hedging, and we found patterns consistent with that in regional variation in thermal preference heritability. In addition, we found that temporal patterns in mean preference support bet-hedging predictions and that there is a genetic basis for thermal preference variability. Our empirical results point to bet-hedging in thermal preference as a potentially important evolutionary strategy in wild populations

Wild flies hedge their thermal preference bets in response to seasonal fluctuations

Fluctuating environmental pressures can challenge organisms by repeatedly shifting the optimum phenotype. Two contrasting evolutionary strategies to cope with these fluctuations are 1) evolution of the mean phenotype to follow the optimum (adaptive tracking) or 2) diversifying phenotypes so that at least some individuals have high fitness in the current fluctuation (bet-hedging). Bet-hedging could underlie stable differences in the behavior of individuals that are present even when genotype and environment are held constant. Instead of being simply ‘noise,’ behavioral variation across individuals may reflect an evolutionary strategy of phenotype diversification. Using geographically diverse wild-derived fly strains and high-throughput assays of individual preference, we tested whether thermal preference variation in Drosophila melanogaster could reflect a bet-hedging strategy. We also looked for evidence that populations from different regions differentially adopt bet-hedging or adaptive-tracking strategies. Computational modeling predicted regional differences in the relative advantage of bet-hedging, and we found patterns consistent with that in regional variation in thermal preference heritability. In addition, we found that temporal patterns in mean preference support bet-hedging predictions and that there is a genetic basis for thermal preference variability. Our empirical results point to bet-hedging in thermal preference as a potentially important evolutionary strategy in wild populations

The Genetic Basis of Natural Variation in Drosophila (Diptera: Drosophilidae) Virgin Egg Retention

Drosophila melanogaster is able to thrive in harsh northern climates through adaptations in life-history traits and physiological mechanisms that allow for survival through the winter. We examined the genetic basis of natural variation in one such trait, female virgin egg retention, which was previously shown to vary clinally and seasonally. To further our understanding of the genetic basis and evolution of virgin egg retention, we performed a genome-wide association study (GWAS) using the previously sequenced Drosophila Genetic Reference Panel (DGRP) mapping population. We found 29 single nucleotide polymorphisms (SNPs) associated with virgin egg retention and assayed 6 available mutant lines, each harboring a mutation in a candidate gene, for effects on egg retention time. We found that four out of the six mutant lines had defects in egg retention time as compared with the respective controls: mun, T48, Mes-4, and Klp67A. Surprisingly, none of these genes has a recognized role in ovulation control, but three of the four genes have known effects on fertility or have high expression in the ovaries. We also found that the SNP set associated with egg retention time was enriched for clinal SNPs. The majority of clinal SNPs had alleles associated with longer egg retention present at higher frequencies in higher latitudes. Our results support previous studies that show higher frequency of long retention times at higher latitude, providing evidence for the adaptive value of virgin egg-retention

Precise Quantification of Behavioral Individuality From 80 Million Decisions Across 183,000 Flies

Individual animals behave differently from each other. This variability is a component of personality and arises even when genetics and environment are held constant. Discovering the biological mechanisms underlying behavioral variability depends on efficiently measuring individual behavioral bias, a requirement that is facilitated by automated, high-throughput experiments. We compiled a large data set of individual locomotor behavior measures, acquired from over 183,000 fruit flies walking in Y-shaped mazes. With this data set we first conducted a “computational ethology natural history” study to quantify the distribution of individual behavioral biases with unprecedented precision and examine correlations between behavioral measures with high power. We discovered a slight, but highly significant, left-bias in spontaneous locomotor decision-making. We then used the data to evaluate standing hypotheses about biological mechanisms affecting behavioral variability, specifically: the neuromodulator serotonin and its precursor transporter, heterogametic sex, and temperature. We found a variety of significant effects associated with each of these mechanisms that were behavior-dependent. This indicates that the relationship between biological mechanisms and behavioral variability may be highly context dependent. Going forward, automation of behavioral experiments will likely be essential in teasing out the complex causality of individuality