Biology Letters · 2019 · 76 citations · 22 references
Life SciencesBiologyEntomologyInsect BehaviorInsect EcologyInsect PhysiologyForaging EcologyMicrobial Chemical SignalingOlfactory PhysiologyOlfactory SystemsPlant-insect Chemical InteractionsPollinator BehaviorFeeding Preference AssaysGustatory Cue UseGustatory PerceptionNectar ForagingOlfactory Cue ResponseOlfactory Cue UseOlfactory SignalingPollinator Attraction
Animals such as bumblebees use chemosensory cues to both locate and evaluate essential resources. Increasingly, it is recognized that microbes can alter the quality of foraged resources and produce metabolites that may act as foraging cues. The distinct nature of these chemosensory cues however and their use in animal foraging remain poorly understood. Here, we test the hypothesis that species of nectar-inhabiting microbes differentially influence pollinator attraction and feeding via microbial metabolites produced in nectar. We first examined the electrophysiological potential for bumblebee (Bombus impatiens) antennal olfactory neurons to respond to microbial volatile organic compounds (mVOCs), followed by an olfactory preference test. We also assessed gustatory preferences for microbial-altered nectar through both no-choice and choice feeding assays. Antennal olfactory neurons responded to some mVOCs, and bees preferred nectar solutions inoculated with the bacterium Asaia astilbes over the yeast Metschnikowia reukaufii based on volatiles alone. However, B. impatiens foragers consumed significantly more Metschnikowia-inoculated nectar, suggesting distinct roles for mVOCs and non-volatile metabolites in mediating both attraction and feeding decisions. Collectively, our results suggest that microbial metabolites have significant potential to shape interspecific, plant-pollinator signalling, with consequences for forager learning, economics and floral host reproduction.
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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
Diversity and evolutionary patterns of bacterial gut associates of corbiculate bees
Hauke Koch, Dharam P. Abrol, Jilian Li et al. · Molecular Ecology · 2013 · 267 citations
Life Sciences, Biology, Microbiology +17