Biology subjects

Monteith, K.

Publications and source records attributed to Monteith, K..

4 recordsLinked to original sources

bioRxiv2024

Genetic variation in trophic avoidance shows fruit flies are generally attracted to bacterial pathogens

Pathogen avoidance behaviours are often assumed to be an adaptive host defence from infection. However, there is limited experimental data on the prerequisite for this assumption: heritable, intrapopulation phenotypic variation for avoidance. We investigated trophic pathogen avoidance in 122 inbred Drosophila melanogaster lines, and in a derived outbred population. Using the FlyPAD system, we tracked the feeding choice that flies made between substrates that were either clean or contained a bacterial pathogen. We uncovered significant, but weakly heritable variation in the preference index among fly lines. However, instead of avoidance, most lines demonstrated a preference for several bacterial pathogens, showing avoidance only for extremely high bacterial concentrations. Bacterial preference was not associated with susceptibility to infection and was retained in flies with disrupted immune signalling. Phenotype-genotype association analysis indicated several novel genes (CG2321, CG2006, ptp99A) associated with increased preference for the bacterial substrate, while the amino-acid transporter sobremesa was associated with greater aversion. Together with previous work showing fitness benefits of consuming high-protein diets, our results suggest that bacterial attraction may instead reflect a dietary preference for protein over carbohydrate. More work quantifying intrapopulation variation in avoidance behaviours is needed to fully assess its importance in host-pathogen evolutionary ecology.

ecology↗

bioRxiv2024

Mitochondrial genome variation affects humoral and cell-mediated innate immune responses and infection outcomes

The role of mitochondria in both adaptive and innate immune responses is increasingly recognized, but the role of mitochondrial DNA (mtDNA) variation as an immunomodulatory factor has received less attention. One reason for this is the difficulty of separating the effect of mtDNA from that of the nuclear genome. By utilizing the fruit fly Drosophila melanogaster, a powerful model system, we created cytoplasmic hybrids, aka. cybrid lines, where unique mtDNAs (mitotypes) were introgressed into a controlled isogenic nuclear background. We harnessed a panel of cybrid lines to study the effect of mtDNA variation on humoral and cell-mediated innate immune responses. Mitotypes exhibited heterogeneity in infection outcomes upon bacterial, viral and parasitoid infections. One mitotype of note (mtKSA2) was more immunocompetent when compared to other mitotypes. We performed transcriptomic profiling of uninfected and infected flies to find the mechanistic basis of the immunocompetence of the mtKSA2 line. We found that in uninfected flies mtKSA2 caused an upregulation of oxidative phosphorylation (OXPHOS) and tricarboxylic acid cycle (TCA) related genes and a downregulation of a set of antimicrobial peptides (AMPs). Upon infection, mtKSA2 flies produced transcriptomic changes that were infection type and duration specific. When we examined immune cells (hemocytes) in mtKSA2 larvae, we noted an increase in hemocyte numbers. These hemocytes were activated in the absence of infection, increased their production of ROS, and showed evidence of increased encapsulation efficiency upon parasitoid wasp infection. Overall, our results show that mtDNA variation acts as an immunomodulatory factor in both humoral and cell-mediated innate immunity and that specific mitotypes can provide enhanced protection against various infections.

immunology↗

bioRxiv2021

Solving the Sample Size Problem for Resource Selection Analysis

O_LISample size sufficiency is a critical consideration for conducting Resource-Selection Analyses (RSAs) from GPS-based animal telemetry. Cited thresholds for sufficiency include a number of captured animals M [≥] 30 and as many relocations per animal N as possible. These thresholds render many RSA-based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations. C_LIO_LIWe provide the first comprehensive solution for RSA sample size by deriving closed-form mathematical expressions for the number of animals M and the number of relocations per animal N required for model outputs to a given degree of precision. The sample sizes needed depend on just 2 biologically meaningful quantities: habitat selection strength and a novel measure of landscape complexity, which we define rigorously. The mathematical expressions are calculable for any environmental dataset at any spatial scale and are applicable to any study involving resource selection (including sessile organisms). We validate our analytical solutions using globally relevant empirical data including 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores, and herbivores living in boreal, temperate, and tropical forests, montane woodlands, swamps, and arctic tundra). C_LIO_LIOur analytic expressions show that the required M and N must decline with increasing selection strength and increasing landscape complexity, and this decline is insensitive to the definition of availability used in the analysis. Our results contradict conventional wisdom by demonstrating that the most biologically relevant effects on the utilization distribution (i.e. those landscape conditions with the greatest absolute magnitude of resource selection) can often be estimated with far fewer data than is commonly assumed. C_LIO_LIWe identify several critical steps in implementing these equations, including (i) a priori selection of expected model coefficients, and (ii) sampling intensity for background (absence/pseudo-absence) data within a given definition of availability. We show that random sampling of background data violates the underlying mathematics of RSA, leading to incorrect values for necessary M and N and potentially incorrect RSA model outputs. We argue that these equations should be a mandatory component for all future RSA studies. C_LI

ecology↗

bioRxiv2020

Testing evolutionary explanations for the lifespan benefit of dietary restriction in Drosophila melanogaster

Dietary restriction (DR), limiting calories or specific nutrients, extends lifespan across diverse taxa. This lifespan extension has been explained as diet-mediated changes in the trade-off between lifespan and reproduction, with survival favoured with scarce resources. Another evolutionary hypothesis suggests the selective benefit of the response is the maintenance of reproduction. This hypothesis predicts that lifespan extension is a side effect of benign laboratory conditions, where DR individuals are frailer and unable to deal with additional stressors, and thus lifespan extension should disappear under more stressful conditions. We tested this by rearing outbred female Drosophila melanogaster on 10 different protein:carbohydrate diets. Flies were either infected with a bacterial pathogen (Pseudomonas entomophila), injured or unstressed. We monitored lifespan, fecundity and ageing measures. DR extended lifespan and reduced reproduction irrespective of injury and infection. These results do not support lifespan extension under DR being a side effect of benign laboratory conditions.

evolutionary biology↗