Use of waggle dance information in honey bees is linked to gene expression in the antennae, but not in the brain

Early life exposure to queen mandibular pheromone mediates persistent transcriptional changes in the brain of honey bee foragers

Behavioural regulation in insect societies remains a fundamental question in sociobiology. In hymenopteran societies, the queen plays a crucial role in regulating group behaviour by affecting individual behaviour and physiology through modulation of worker gene expression. Honey bee (Apis mellifera) queens signal their presence via queen mandibular pheromone (QMP). While QMP has been shown to influence behaviour and gene expression of young workers, we know little about how these changes translate in older workers. The effects of the queen pheromone could have prolonged molecular impacts on workers that depend on an early sensitive period. We demonstrate that removal of QMP impacts long-term gene expression in the brain and antennae in foragers that were treated early in life (1 day post emergence), but not when treated later in life. Genes important for division of labour, learning, chemosensory perception and ageing were among those differentially expressed in the antennae and brain tissues, suggesting that QMP influences diverse physiological and behavioural processes in workers. Surprisingly, removal of QMP did not have an impact on foraging behaviour. Overall, our study suggests a sensitive period early in the life of workers, where the presence or absence of a queen has potentially life-long effects on transcriptional activity.

Dynamic antennal positioning allows honeybee followers to decode the dance

The honeybee waggle dance has been widely studied as a communication system, yet we know little about how nestmates assimilate the information needed to navigate toward the signaled resource. They are required to detect the dancer's orientation relative to gravity and duration of the waggle phase and translate this into a flight vector with a direction relative to the sun1 and distance from the hive.2,3 Moreover, they appear capable of doing so from varied, dynamically changing positions around the dancer. Using high-speed, high-resolution video, we have uncovered a previously unremarked correlation between antennal position and the relative body axes of dancer and follower bees. Combined with new information about antennal inputs4,5 and spatial encoding in the insect central complex,6,7 we show how a neural circuit first proposed to underlie path integration could be adapted to decoding the dance and acquiring the signaled information as a flight vector that can be followed to the resource. This provides the first plausible account of how the bee brain could support the interpretation of its dance language.

Transcriptomic responses to location learning by honeybee dancers are partly mirrored in the brains of dance-followers

The waggle dances of honeybees are a strikingly complex form of animal communication that underlie the collective foraging behaviour of colonies. The mechanisms by which bees assess the locations of forage sites that they have visited for representation on the dancefloor are now well-understood, but few studies have considered the remarkable backward translation of such information into flight vectors by dance-followers. Here, we explore whether the gene expression patterns that are induced through individual learning about foraging locations are mirrored when bees learn about those same locations from their nest-mates. We first confirmed that the mushroom bodies of honeybee dancers show a specific transcriptomic response to learning about distance, and then showed that approximately 5% of those genes were also differentially expressed by bees that follow dances for the same foraging sites, but had never visited them. A subset of these genes were also differentially expressed when we manipulated distance perception through an optic flow paradigm, and responses to learning about target direction were also in part mirrored in the brains of dance followers. Our findings show a molecular footprint of the transfer of learnt information from one animal to another through this extraordinary communication system, highlighting the dynamic role of the genome in mediating even very short-term behavioural changes.

Task-specific odorant receptor expression in worker antennae indicates that sensory filters regulate division of labor in ants

Division of labor (DOL) is a characteristic trait of insect societies, where tasks are generally performed by specialized individuals. Inside workers focus on brood or nest care, while others take risks by foraging outside. Theory proposes that workers have different thresholds to perform certain tasks when confronted with task-related stimuli, leading to specialization and consequently DOL. Workers are presumed to vary in their response to task-related cues rather than in how they perceive such information. Here, we test the hypothesis that DOL instead stems from workers varying in their efficiency to detect stimuli of specific tasks. We use transcriptomics to measure mRNA expression levels in the antennae and brain of nurses and foragers of the ant Temnothorax longispinosus. We find seven times as many genes to be differentially expressed between behavioral phenotypes in the antennae compared to the brain. Moreover, half of all odorant receptors are differentially expressed, with an overrepresentation of the 9-exon gene family upregulated in the antennae of nurses. Nurses and foragers thus apparently differ in the perception of their olfactory environment and task-related signals. Our study supports the hypothesis that antennal sensory filters predispose workers to specialize in specific tasks.

Brain and antennal transcriptomes of host ants reveal potential links between behaviour and the functioning of socially parasitic colonies

Insect social parasites are characterized by exploiting the hosts' social behaviour. Why exactly hosts direct their caring behaviour towards these parasites and their offspring remains largely unstudied. One hypothesis is that hosts do not perceive their social environment as altered and accept the parasitic colony as their own. We used the ant Leptothorax acervorum, host of the dulotic, obligate social parasite Harpagoxenus sublaevis, to shed light on molecular mechanisms underlying behavioural exploitation by contrasting tissue-specific transcriptomes in young host workers. Host pupae were experimentally (re-)introduced into fragments of their original, another conspecific, heterospecific or parasitic colony. Brain and antennal mRNA was extracted and sequenced from adult ants after they had lived in the experimental colony for at least 50 days after eclosion. The resulting transcriptomes of L. acervorum revealed that ants were indeed affected by their social environment. Host brain transcriptomes were altered by the presence of social parasites, suggesting that the parasitic environment influences brain activity, which may be linked to behavioural changes. Transcriptional activity in the antennae changed most with the presence of unrelated individuals, regardless of whether they were conspecifics or parasites. This suggests early priming of odour perception, which was further supported by sensory perception of odour as an enriched function of differentially expressed genes. Furthermore, gene expression in the antennae, but not in the brain corresponded to ant worker behaviour before sampling. Our study demonstrated that the exploitation of social behaviours by brood parasites correlates with transcriptomic alterations in the central and peripheral nervous systems.

In search of behavioral and brain processes involved in honey bee dance communication

Honey bees represent an iconic model animal for studying the underlying mechanisms affecting advanced sensory and cognitive abilities during communication among colony mates. After von Frisch discovered the functional value of the waggle dance, this complex motor pattern led ethologists and neuroscientists to study its neural mechanism, behavioral significance, and implications for a collective organization. Recent studies have revealed some of the mechanisms involved in this symbolic form of communication by using conventional behavioral and pharmacological assays, neurobiological studies, comprehensive molecular and connectome analyses, and computational models. This review summarizes several critical behavioral and brain processes and mechanisms involved in waggle dance communication. We focus on the role of neuromodulators in the dancer and the recruited follower, the interneurons and their related processing in the first mechano-processing, and the computational navigation centers of insect brains.

Genetic mechanisms modulating behaviour through plastic chemosensory responses in insects

The ability to transition between different behavioural stages is a widespread phenomenon across the animal kingdom. Such behavioural adaptations are often linked to changes in the sensitivity of those neurons that sense chemical cues associated with the respective behaviours. To identify the genetic mechanisms that regulate neuronal sensitivity, and by that behaviour, typically *omics approaches, such as RNA- and protein-sequencing, are applied to sensory organs of individuals displaying differences in behaviour. In this review, we discuss these genetic mechanisms and how they impact neuronal sensitivity, summarize the correlative and functional evidence for their role in regulating behaviour and discuss future directions. As such, this review can help interpret *omics data by providing a comprehensive list of already identified genes and mechanisms that impact behaviour through changes in neuronal sensitivity.

Differences in olfactory sensitivity and odor detection correlate with foraging task specialization in honeybees Apis mellifera

Division of labor is central to the ecological success of social insects. Among honeybees foragers, specialization for collecting nectar or pollen correlates with their sensitivity to gustatory stimuli (e.g. sugars). We hypothesize that pollen and nectar foragers also differ in their sensitivity to odors, and therefore in their likelihood to show odor-mediated responses. To assess foragerś sensitivity to natural odors, we quantified the conditioning of the proboscis extension reflex (PER) to increasing concentrations (0.001; 0.01; 0.1; 1 M) of linalool or nonanal. Furthermore, we compared electroantennogram (EAG) recordings to correlate bees' conditioned responses with the electrophysiological responses of their antennae. To further explore differences of the antennal response of foragers in relation to task-related odors, we registered EAG signals for two behaviorally ''meaningful'' odors that mediate pollen collection: fresh pollen odors and the brood pheromone (E)-β-ocimene. Pollen foragers performed better than nectar foragers in PER conditioning trials when linalool and nonanal were presented at low concentrations (0.001, 0.01 M). Consistently, their antennae showed stronger EAG signals (higher amplitudes) to these odors, suggesting that differences in sensitivity can be explained at the periphery of the olfactory system. Pollen and nectar foragers detect pollen odors differently, but not (E)-β-ocimene. Pollen volatiles evoked EAG signals with hyper and depolarization components. In pollen foragers, the contribution of the hyperpolarization component was higher than in nectar foragers. We discuss our findings in terms of adaptive advantages to learn subtle olfactory cues that influence the ability to better identify/discriminate food sources.

Machine Learning models identify gene predictors of waggle dance behaviour in honeybees

The molecular characterisation of complex behaviours is a challenging task as a range of different factors are often involved to produce the observed phenotype. An established approach is to look at the overall levels of expression of brain genes - or 'neurogenomics' - to select the best candidates that associate with patterns of interest. However, traditional neurogenomic analyses have some well-known limitations; above all, the usually limited number of biological replicates compared to the number of genes tested - known as "curse of dimensionality". In this study we implemented a Machine Learning (ML) approach that can be used as a complement to more established methods of transcriptomic analyses. We tested three supervised learning algorithms (Random Forests, Lasso and Elastic net Regularized Generalized Linear Model, and Support Vector Machine) for their performance in the characterization of transcriptomic patterns and identification of genes associated with honeybee waggle dance. We then intersected the results of these analyses with traditional outputs of differential gene expression analyses and identified two promising candidates for the neural regulation of the waggle dance: boss and hnRNP A1. Overall, our study demonstrates the application of Machine Learning to analyse transcriptomics data and identify candidate genes underlying social behaviour. This approach has great potential for application to a wide range of different scenarios in evolutionary ecology, when investigating the genomic basis for complex phenotypic traits and can present some clear advantages compared to the established tools of gene expression analysis, making it a valuable complement for future studies.

Interindividual variation in the use of social information during learning in honeybees

Slow-fast differences in cognition among individuals have been proposed to be an outcome of the speed-accuracy trade-off in decision-making. Based on the different costs associated with acquiring information via individual and social learning, we hypothesized that slow-fast cognitive differences would also be tied to the adoption of these different learning modes. Since foragers in honeybee colonies likely have both these information acquisition modes available to them, we chose to test them for interindividual differences in individual and social learning. By measuring performance on a learning task with and without a social cue and quantifying learning rate and maximum accuracy in these two tasks, our results show the existence of a speed-accuracy trade-off in both the individual and the social learning contexts. However, the trade-off is steeper during individual learning, which was slower than social learning but led to higher accuracy. Most importantly, our results also show that bees that attained high accuracy on the individual learning task had low accuracy on the social learning task and vice versa. We discuss how these two information acquisition strategies tie to slow-fast differences in cognitive phenotypes and how they might contribute to division of labour and social behaviour.