Effects of aversive conditioning on expression of physiological stress in honey bees (Apis mellifera)

Abstract

Stress is defined as any deviation from an organism’s baseline physiological levels. Therefore, introduction of new stimuli and information, such as in learning, can be defined as a stressor. A large body of research exists examining the role that stress plays in learning, but virtually none addresses whether or not learning itself is a measurable cause of stress. The current study used a wide variety of learning centric stress responses. Researchers examined changes in expression of ten stress and learning related genes in various physiological systems in domesticated honey bees (Apis mellifera) as a result of exposure to an aversive conditioning task. Gene expression was examined using quantitative real-time polymerase chain reaction following the learning task. Results indicate that learning affects expression of some stress related genes.

Introduction

The purpose of this experiment is to examine the effects of aversive conditioning on the expression of a number of neural proteins in the honey bee brain. This study seeks to understand the effects of physiological stress in association with the acquisition of new behaviors in an invertebrate model. Currently, there is little research indicating the effect learning plays on the expression of physiological stress markers in vertebrates, and no literature examining these effects in invertebrate brains. Aversive conditioning was selected for this study as a method of tiered experimental control to observe differences between gross physiological stress, and stress in the context of learning.

Stress is defined as any deviation from an organism’s baseline physiological levels (Selye, 1950). Along with these deviations, organisms possess a suite of adaptations in order to combat stressors, and return physiological systems to their baseline levels in the general adaptation syndrome (Selye, 1950). This syndrome includes a wide variety of adaptations including cellular changes (Kültz, 2005), proteomic shifts (Hranitz et al., 2010, Kültz, 2005), neural adaptations (Niewalda et al., 2015), and hormonal alterations (Kapan et al., 2012, Sapolsky and Meaney, 1986). These varied physiological responses to stress are necessary due to the wide range of stressors potentially altering an organism’s homeostatic balance. For example, a startling stimuli may not pose a threat to cellular structure, but must evoke a rapid shift in an organism’s hormonal profile in order to maintain survival (Sapolsky, 1990). Conversely, a virus attempting to invade a cell elicits a cellular stress response, while potentially not causing organismal stress responses (Kültz, 2005). Due to this, it is important to select the appropriate physiological measure when examining stress responses.

Considering stress as any deviation from baseline levels, behavioral and neurological processes that result in physiological changes may also be classified as such. In particular, learning has been linked to the generation of a number of neurological changes, including development of new neural connections, new cellular projections, and increased synaptic activity (Houweling et al., 2008, Kami et al., 1995, Kelly and Garavan, 2005, Lisberger, 1988). As such, learning is known to exert a physiological toll on the cells involved in the creation or modification of the neural pathways involved. Similar physiological occurrences, such as changes in neurohormonal sensitivity and alterations in neuronal protein structures have been observed as a result of stress exposure (Kapan et al., 2012, Niewalda et al., 2015, Sapolsky and Meaney, 1986). This suggests that the link between stress and learning may be more dynamic than previously thought.

For example, Lisberger (1988) noted distinct changes in the firing rates of neurons controlling eye movements in non-human primates trained to an eye movement task after learning of the task was complete. This result suggests that the cells involved can make a physiological change to respond more efficiently to a given stimulus. Likewise, this suggests an increased rate of cellular metabolism, as more energy must be expended in order to maintain a higher rate of neuronal activity. This in turn, opens the cells up to a higher rate of oxidative stress as a result of the increased metabolism.

Additional studies have corroborated this effect using magnetic resonance imaging (MRI) and electroencephalograph (EEG) readings (Houweling et al., 2008, Kami et al., 1995, Kelly and Garavan, 2005) in regards to neural pathways corresponding to repeated motor skills in humans. As a result, we can argue that neural systems are extremely plastic, and subject to conformational and chemoreceptive changes as a result of learning.

In the psychological literature, there exist a number of studies suggesting that the expression of physiological stress may alter an individual’s ability to learn. The nature of the stress has been shown to both increase and decrease recall depending on the task, the timing of the stressor in relation to the task, and the organism engaged in learning (Joëls et al., 2006, Kim and Diamond, 2002, Smeets et al., 2009).

A consistent finding regarding the role of stress in learning performance is that of dose dependency. Studies conducted in both rodents and humans show that moderate levels of stress are likely to improve learning performance, while both high and low levels are likely to have an impairing effect (Joëls et al., 2006, Kim and Diamond, 2002).

Using a Morris water maze, Sandi, Loscertales, and Guaza (1997) conducted a study in rats to examine the effect of cortisol in conjunction with performance. Results indicated that animals which had received a dosage of cortisol displayed higher learning acquisition and better recall over time than control animals. In addition, when examining the effects of environment, the researchers noted that animals subjected to cooler water temperatures expressed better performance, and higher levels of cortisol post-trial. These results suggest that the glucocorticoid system in vertebrates, and its homologous system in invertebrates, may promote increased learning performance when subjects are placed under moderate stress.

Despite this wealth of literature proposing stress impairs or enhances learning, fairly little research has been conducted examining the relationship in the reverse. The current study proposes to fill this gap by examining the effects of a learning protocol on a suite of physiological stress markers, while controlling for levels of stress across subjects.

Honey bees (Apis mellifera) offer a unique opportunity to explore the junction of stress and learning, as they are a model system for many learning paradigms within the study of insect behavior. Behaviors such as foraging choice (Amaya-Márquez et al., 2014, Hill et al., 1997, Menzel and Erber, 1978, Menzel, 1999), avoidance (Agarwal et al., 2011, Dinges et al., 2017), appetitive and aversive conditioning (Abramson, 1986, Abramson et al., 2008, Dinges et al., 2013) can all be readily observed within honey bees and their various subspecies.

In free flight experiments, honey bees rapidly display associations between a number of stimuli and a potential reward. Bees have been shown to not only use color and odor to predict the strength of reward, but to alter their foraging behavior when the pattern of reward is no longer as pronounced, or a greater reward is available (Giray et al., 2015, Hill et al., 1997, Sanderson et al., 2006). This consistent pattern of behavior in response to the potential changes in environmental cues suggests that bees possess a remarkable neural plasticity and an ability to rapidly acquire learned associations.

Of particular interest to the present study, are the results of the learned helplessness paradigm designed by Dinges et al. (2013). This aversive conditioning paradigm pairs “master” and “yoked” bees together for the duration of a learning session. The master bee is trained to avoid a colored portion of a chamber through exposure to shock upon entering the assigned portion. The yoked bee then is subjected to shock at any point the master bee is, regardless of position. This paradigm allows researchers to examine learning in conjunction with existing physiological stress, as well as the effects of a similar stressor (e.g. shock) without the presence of learning.

In addition to their wealth of behavioral advantages, honey bees possess an extensively mapped genome. Much of their genome is shared with another highly researched organism, Drosophila melanogaster. A survey of the genomes of both animals by Walldorf, Fleig, and Gehring (1989) suggested that honey bees possess a genome with 90% similarity of homeobox regions to that of D. melanogaster. This result has been corroborated by recent honey bee genomic sequencing efforts (Honeybee Genome Sequencing Consortium, 2006). As such, where genetic information is missing from models such as the honey bee stress response (Even, Devaud, & Barron, 2012), researchers may look to D. melanogaster to provide an educated launching point for exploration of genetic material.

Due to the nature of stress as a varied physiological process and the broad spectrum scope of this experiment, it is necessary to examine a suite of genetic markers in order to fully assess the extent to which learning affects physiological stress. As such, 10 genes associated with varying phases of the stress response were selected for examination (See Table 1). Heat Shock Protein 70 (HSP70), a chaperone protein and measure of oxidative stress (Hranitz et al., 2010), Protein Kinase A (PKA; Horiuchi et al., 2008, Li et al., 1996, Yamazaki et al., 2010) and the calcium/calmodulin-dependent protein kinase II (CaMKII; Santalla et al., 2014, Kadas et al., 2012), both g-protein coupled receptors, Diuretic Hormone 44 (DH44; Cannell et al., 2016, Kapan et al., 2012), a vasodilator and invertebrate homologue of corticosteroids, the Diuretic Hormone 44 receptor protein (DH44R; Dus et al., 2015, King et al., 2017), Dopamine receptor 2 (DOP2), a receptor for an insect dopamine (Humphries et al., 2003, Mustard et al., 2010), the insect serotonin receptor (5HT2A; Nichols, 2007), the discs large homologue, a cytoskeletal scaffolding protein, (DLG1; Mauri et al., 2014, Noseda et al., 2016), pumilio, a neural ion channel protein (PUM; Burow et al., 2015, Schweers et al., 2002, Stern et al., 1995), and bruchpilot, a presynaptic anchor protein (BRP; Gehring et al., 2017, Honeybee Genome Sequencing Consortium, 2006).

The current experiment examines the effects of an aversive learning paradigm on the expression of genetic products associated with a suite of physiological stress related genes. Due to the varied nature of these genes, the study possesses two hypotheses. H₁: honey bees that undergo a learning task should express higher levels of HSP70, PKA, II, DH44, DH44R, and DOP2 and lower levels of BPR, PUM, 5HT2A, and DLG1 when compared to bees who have not undergone a learning task. H₂: bees that are not exposed to shock will express the lowest levels of HSP70, PKA, II, DH44, DH44R, and DOP2 and the highest levels of BPR, PUM, 5HT2A, and DLG1.