The ISME Journal · 2021 · 28 citations · 61 references
Life SciencesBiologyEntomologyHost-pathogen InteractionsInsect EcologyPlant-microbe InteractionsCoevolution Of MicrobesFungal SymbiosisHost-microbe CoevolutionSymbiosisHost Genotype Effects On MicrobiomesHost Genotype InteractionsInsect MicrobiomesInsect-microbe SymbiosisMicrobial Species InteractionsMicrobial SymbiosisPhenotypic Trait VariationPlant-microbe Symbiosis
Microbial symbionts often alter the phenotype of their host. Benefits and costs to hosts depend on many factors, including host genotype, symbiont species and genotype, and environmental conditions. Here, we present a study demonstrating genotype-by-genotype (G×G) interactions between multiple species of endosymbionts harboured by an insect, and the first to quantify the relative importance of G×G interactions compared with species interactions in such systems. In the most extensive study to date, we microinjected all possible combinations of five Hamiltonella defensa and five Fukatsuia symbiotica (X-type; PAXS) isolates into the pea aphid, Acyrthosiphon pisum. We applied several ecological challenges: a parasitoid wasp, a fungal pathogen, heat shock, and performance on different host plants. Surprisingly, genetic identity and genotype × genotype interactions explained far more of the phenotypic variation (on average 22% and 31% respectively) than species identity or species interactions (on average 12% and 0.4%, respectively). We determined the costs and benefits associated with co-infection, and how these compared to corresponding single infections. All phenotypes were highly reliant on individual isolates or interactions between isolates of the co-infecting partners. Our findings highlight the importance of exploring the eco-evolutionary consequences of these highly specific interactions in communities of co-inherited species.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Fitting Linear Mixed-Effects Models Using <b>lme4</b>
Douglas M. Bates, Martin Mächler, Benjamin M. Bolker et al. · Journal of Statistical Software · 2015 · 85.6K citations · Full text
Strains, functions and dynamics in the expanded Human Microbiome Project
Jason Lloyd‐Price, Anup Mahurkar, Jonathan Crabtree et al. · Nature · 2017 · 1.4K citations · Full text
Life Sciences, Biology, Microbiology +17