Tyramine and its Amtyr1 receptor modulate attention in honey bees (Apis mellifera)

Sublethal glyphosate exposure reduces honey bee foraging and alters the balance of biogenic amines in the brain

Glyphosate is a broad-spectrum herbicide that inhibits the shikimate pathway, which honey bees (Apis mellifera), a non-target beneficial pollinator, do not endogenously express. Nonetheless, sublethal glyphosate exposure in honey bees has been correlated to impairments in gustation, learning, memory and navigation. While these impacted physiologies underpin honey bee foraging and recruitment, the effects of sublethal glyphosate exposure on these important behaviors remain unclear, and any proximate mechanism of action in the honey bee is poorly understood. We trained cohorts of honey bees from the same hives to forage at one of two artificial feeders offering 1 mol l-1 sucrose solution, either unaltered (N=40) or containing glyphosate at 5 mg acid equivalent (a.e.) l-1 (N=46). We then compared key foraging behaviors and, on a smaller subset of bees, recruitment behaviors. Next, we quantified protein levels of octopamine, tyramine and dopamine, and levels of the amino acid precursor tyrosine in the brains of experimental bees collected 3 days after the exposure. We found that glyphosate treatment bees reduced their foraging by 13.4% (P=0.022), and the brain content of tyramine was modulated by a crossover interaction between glyphosate treatment and the number of feeder visits (P=0.004). Levels of octopamine were significantly correlated with its precursors tyramine (P=0.011) and tyrosine (P=0.018) in glyphosate treatment bees, but not in control bees. Our findings emphasize the critical need to investigate impacts of the world's most-applied herbicide and to elucidate its non-target mechanism of action in insects to create better-informed pollinator protection strategies.

Cognition from genes to ecology: individual differences incognition and its potential role in a social network

There have now been many reports of intra-colony differences in how individuals learn on a variety of conditioning tasks in both honey bees and bumble bees. Yet the fundamental mechanistic and adaptive bases for this variation have yet to be fully described. This review summarizes a long series of investigations with the honey bee (Apis mellifera) that had the objective of describing the factors that contribute to this variation. Selection on haploid drones for extremes in learning performance revealed that genotype accounted for much of the variance. Neither age nor behavioral caste consistently accounted for observed variation on different conditioning protocols until genotype was controlled. Two subsequent Quantitative Trait Locus mapping studies identified a locus in the honey bee genome with a significant effect on the learning phenotype. Pharmacological and reverse genetic approaches, combined with neurophysiological analyses, confirmed that a biogenic amine receptor for tyramine affects expression of the trait. This work allowed for development of a hypothetical model of how that receptor functions in the brain to produce broad pleiotropic effects on behavior. Subsequent work used genotype as a treatment condition for evaluation of the variation under quasi-natural conditions, which revealed that individual variation reflects how foragers weigh known and novel resources in decision making. This work, together with other studies of individual differences, suggests a unifying framework for understanding how and why individuals differ in cognitive abilities.

Plasticity in inhibitory networks improves pattern separation in early olfactory processing

Distinguishing between nectar and non-nectar odors is challenging for animals due to shared compounds and varying ratios in complex mixtures. Changes in nectar production throughout the day and over the animal's lifetime add to the complexity. The honeybee olfactory system, containing fewer than 1000 principal neurons in the early olfactory relay, the antennal lobe (AL), must learn to associate diverse volatile blends with rewards. Previous studies identified plasticity in the AL circuits, but its role in odor learning remains poorly understood. Using a biophysical computational model, tuned by in vivo electrophysiological data, and live imaging of the honeybee's AL, we explored the neural mechanisms of plasticity in the AL. Our findings revealed that when trained with a set of rewarded and unrewarded odors, the AL inhibitory network suppresses responses to shared chemical compounds while enhancing responses to distinct compounds. This results in improved pattern separation and a more concise neural code. Our calcium imaging data support these predictions. Analysis of a graph convolutional neural network performing an odor categorization task revealed a similar mechanism for contrast enhancement. Our study provides insights into how inhibitory plasticity in the early olfactory network reshapes the coding for efficient learning of complex odors.

A tyramine receptor gene LsTAR2 is involved in reproduction and feeding in the small brown planthopper Laodelphax striatellus

Tyramine (TA) is an important biogenic amine present in the central nervous system of insects, and mediates a variety of physiological and behavioral functions via tyramine receptors (TARs). However, TARs have not yet been characterized in planthoppers, and their physiological functions remain poorly understood in rice pests. Here, we cloned a tyramine receptor gene (LsTAR2) from the small brown planthopper Laodelphax striatellus, one of the most destructive rice pests. LsTAR2 shares high sequence identity with its orthologous receptors, and is closely related to its corresponding receptor groups. LsTAR2 transcript was expressed mostly in the egg stage and brain. RNAi-mediated knockdown of LsTAR2 significantly prolonged the preoviposition period and decreased the fecundity in females. Furthermore, LsTAR2 knockdown reduced the expression levels of vitellogenin (LsVg) in the fat body and ovary of L. striatellus, and changed the expressions of juvenile hormone (JH) and 20-hydroxyecdysone (20E) pathway genes. In addition, LsTAR2 knockdown significantly decreased the honeydew excretion of the adults, and affected the transcript levels of feeding-related neuropeptide signaling genes. These results provide critical information concerning the role of LsTAR2 in reproduction and feeding behavior in L. striatellus, and open the way for further investigations into novel strategies targeting TARs for pest control.

Plasticity in inhibitory networks improves pattern separation in early olfactory processing

Distinguishing between nectar and non-nectar odors is challenging for animals due to shared compounds and varying ratios in complex mixtures. Changes in nectar production throughout the day - and potentially many times within a forager's lifetime - add to the complexity. The honeybee olfactory system, containing fewer than 1,000 principal neurons in the early olfactory relay, the antennal lobe (AL), must learn to associate diverse volatile blends with rewards. Previous studies identified plasticity in the AL circuits, but its role in odor learning remains poorly understood. Using a biophysical computational network model, tuned by in vivo electrophysiological data, and live imaging of the honeybee's AL, we explored the neural mechanisms and functions of plasticity in the early olfactory system. Our findings revealed that when trained with a set of rewarded and unrewarded odors, the AL inhibitory network suppresses shared chemical compounds while enhancing responses to distinct compounds. This results in improved pattern separation and a more concise neural code. Our calcium imaging data support these predictions. Analysis of a graph convolutional neural network performing an odor categorization task revealed a similar mechanism for contrast enhancement. Our study provides insights into how inhibitory plasticity in the early olfactory network reshapes the coding for efficient learning of complex odors.

Reinforcement expectation in the honeybee (Apis mellifera): Can downshifts in reinforcement show conditioned inhibition?

When animals learn the association of a conditioned stimulus (CS) with an unconditioned stimulus (US), later presentation of the CS invokes a representation of the US. When the expected US fails to occur, theoretical accounts predict that conditioned inhibition can accrue to any other stimuli that are associated with this change in the US. Empirical work with mammals has confirmed the existence of conditioned inhibition. But the way it is manifested, the conditions that produce it, and determining whether it is the opposite of excitatory conditioning are important considerations. Invertebrates can make valuable contributions to this literature because of the well-established conditioning protocols and access to the central nervous system (CNS) for studying neural underpinnings of behavior. Nevertheless, although conditioned inhibition has been reported, it has yet to be thoroughly investigated in invertebrates. Here, we evaluate the role of the US in producing conditioned inhibition by using proboscis extension response conditioning of the honeybee (Apis mellifera). Specifically, using variations of a "feature-negative" experimental design, we use downshifts in US intensity relative to US intensity used during initial excitatory conditioning to show that an odorant in an odor-odor mixture can become a conditioned inhibitor. We argue that some alternative interpretations to conditioned inhibition are unlikely. However, we show variation across individuals in how strongly they show conditioned inhibition, with some individuals possibly revealing a different means of learning about changes in reinforcement. We discuss how the resolution of these differences is needed to fully understand whether and how conditioned inhibition is manifested in the honeybee, and whether it can be extended to investigate how it is encoded in the CNS. It is also important for extension to other insect models. In particular, work like this will be important as more is revealed of the complexity of the insect brain from connectome projects.