Effects of Memory Testing in Rats on GSK-3B Expression in Hippocampus and Striatum

A Thesis Submitted in Partial Fulfillment of the

Requirements of the Renée Crown University Honors Program at

Syracuse University

Morgan Lelis Temple

Candidate for Bachelor of Science and Renée Crown University Honors

Spring 2020

Honors Thesis in Biology

Thesis Advisor: ____________________________

Dr. Paul E. Gold, Professor of Biology

Thesis Reader: ____________________________________

Dr. Robin Jones, Associate Professor of

Neuroscience [ILM]

Honors Director: ___________________________________

Dr. Danielle Smith, Director

© 2020 Morgan Lelis TempleAbstract

Modern research has demonstrated that the adult brain retains a very high degree of structural and functional plasticity across the lifespan, continuously reorganizing in response to learning, memory, and experience. As we encounter new experiences and learn new information along the way, an experience can profoundly influence the important details of our brain circuitry and prime future experiences. Our “Use it and Boost” theory suggests that cognitive priming via stimulating or enriching experiences enhance neural functioning and provide us with the molecular machinery needed to support future learning and memory. Previous experiments found that brain derived neurotrophic factor (BDNF) serves as an important regulatory mechanism underlying the beneficial effects of cognitive priming on learning and memory. To further identify the mechanisms supporting cognitive activity-induced learning enhancements, the current research examines the inhibition of glycogen synthase kinase 3 beta (GSK3β), a downstream target of BDNF-TrkB signaling, following a spatial working memory task. To determine if GSK3β inhibition plays a role in activity-induced learning and memory enhancements, young male Sprague Dawley rats were cognitively primed with a spontaneous alternation task, then euthanized immediately, 1 hr, 4 hrs, or 24 hrs following testing to analyze GSK3β inhibition states in the hippocampus and striatum via western blotting. The results indicate that SA priming failed to modulate the phosphorylation/inhibition of GSK3β in any consistent manner. Thus, BDNF-TrkB signaling induced by cognitive priming likely enhances subsequent behaviors via GSK3β independent mechanisms.

Executive Summary

Neuroplasticity, also known as brain or neural plasticity, is a term that refers to the brain's remarkable ability to change and adapt in response to environmental demands, experience, and/or damage. Neuroplasticity is closely tied to changes in neural excitability and can be observed at multiple scales, from microscopic changes in individual neurons to larger-scale changes such as in cortical remapping. Through contemporary literature, it has become increasingly evident that experience exerts a powerful influence on the structure and function of neuronal circuits across the lifespan. As an individual engages in new experiences, the neuronal activity generated by what we think or do sculpts the connections between our neurons, allowing the brain to constantly create neural communication routes and rewire existing ones. Likewise, under our “Use it and Boost it” model, stimulating and enriching experiences not only change neural circuits but can enhance neural functioning and produce robust enhancements in learning and memory.

Like an extraordinary machine, the brain records its experiences in its wiring and thus an experience has the ability to prime future experiences, a phenomenon known as cognitive priming. Cognitive priming can be understood as a mechanism of metaplasticity, in which an activity-dependent change in the structure or function of neurons and synapses alters their ability to generate future synaptic plasticity. A great body of literature has demonstrated that cognitive priming, via exercise or enriching experience, can induce a variety of neuroplastic adaptations that provide us with the molecular machinery to support future learning and memory.

Previous experiments from the Korol-Gold labs found that priming with spontaneous alternation, a working memory task, or voluntary exercise enhanced new learning of subsequent hippocampus-sensitive place tasks or striatum-sensitive response tasks via increased BDNF-TrkB signaling. Brain derived neurotrophic factor (BDNF) is an activity-dependent protein that serves as an important molecular mechanism mediating activity-induced learning and memory enhancements. BDNF synthesis and signaling increase in response to cellular excitation and activate downstream signaling cascades via its high-affinity receptor, tyrosine kinase receptor B (TrkB). While BDNF-TrkB signaling aids in enhancing subsequent behaviors, on the opposite side of the spectrum, a dysregulation in BDNF-TrkB signaling has been implicated in several age-related cognitive declines and the development of neurodegenerative diseases, such as Alzheimer’s disease. Beyond this, the inhibition or activation of downstream targets of BDNF-TrkB signaling, such as glycogen synthase kinase 3β (GSK3β), likely also contributes to the activity-induced learning enhancements following priming.

In a previous experiment examining the effect of cognitive priming on the downstream inhibition of GSK3β, it was found that the inhibition of GSK3β increased in the hippocampus and striatum of cognitively primed rats following place and response training, but not after the spontaneous alternation priming task. GSK3β is an incredibly busy and multifunctional serine/threonine protein kinase that, unlike many other kinases, is constitutively active under basal conditions. Like BDNF-TrkB signaling, GSK3β inhibition is activity-dependent and occurs in response to upstream signals via phosphorylation at its serine 9 (Ser9) residue. Furthermore, while the activity-dependent inhibition of GSK3β has been seen to enhance cognition and reduce some age-related cognitive deficits, hyperactive GSK3β signaling has been implicated in promoting some neurodegenerative processes and linked to learning and memory deficits. These findings thus suggest that a balance of GSK3β activation and inhibition is essential for normal learning and memory in healthy animals.

To further investigate the mechanism supporting cognitive activity-induced learning enhancements, we examined the effect of spontaneous alternation priming on GSK3β inhibition in the hippocampus and striatum of young male rats. Spontaneous alternation is a spatial working memory task that takes advantage of a rat's natural tendency to explore novelty. Three-month-old Sprague Dawley rats were tested on a 20-minute 4-arm spontaneous alternation task and scored for alternation behavior to examine their working memory capacity. An alternation occurred when a rat entered all four arms of the maze within five consecutive entries. Rats were next euthanized immediately, 1 hour, 4 hours, or 24 hours after testing, and the hippocampus and striatum were rapidly dissected from each side of the brain. To analyze the inhibition state of GSK3β, the ratio of phosphorylated GSK3β at Ser9 to total GSK3β (pGSK3β:GSK3β) in the hippocampus and striatum were quantified via western blot to determine the levels of GSK3β inhibition following the priming task. We found that in the hippocampus and striatum, priming with spontaneous alternation failed to modulate the phosphorylation/inhibition of GSK3β in any consistent manner, and thus we were unable demonstrate a link between spontaneous alternation priming and increased GSK3β inhibition.

While a body of literature suggests that GSK3β inhibition contributes to various learning and memory processes in transgenic animals and pathological models, our results indicate that GSK3β inhibition may not be necessary or important for the effects of priming with spontaneous alternation. Further scientific inquiry into the mechanisms and processes modulated by BDNF-TrkB signaling and its downstream targets may contribute to a better understanding of how cognitive activity induces learning enhancements and facilitate the development of novel therapeutic methods that could help to prevent or counteract the effects of aging on the human brain.

Table of Contents

Abstract ………………………………………….……………….…………… 3

Executive Summary …………………………….……………….…………… 4

Acknowledgements…………………………………………………………. . . 8

Introduction …………………………………………………………………. . 9

Methods ………………………………………………………………………. 18

Results ………………………………………………………………………… 24

Discussion ……………………………………………………………………. . 26

Figures………………………………………………………………………… 29

References.……………………………………………………………………. 34

Acknowledgments

I would like to express my deepest gratitude and appreciation to all the members of the Korol-Gold labs. Specifically, I would like to thank and acknowledge my advisors, Dr. Paul Gold and Dr. Donna Korol, for their constant support, expertise, and the amazing opportunity to perform research in their lab space. Next, I would like to thank my post-doc and mentor, Dr. Bob Gardner, for providing me with a broad knowledge of many scientific techniques and the confidence to become a great scientist. I would additionally like to express my great appreciation to Dr. Gardner for assisting in the final stages of data acquisition and for always answering my unending questions. I would like to thank my reader, Dr. Robin Jones, for being an amazing and supporting professor whose classes helped to spark my interests in neuroscience. Finally, I offer a special thanks to Dr. Alesia Prakapenka and Stephen Ajayi for constantly keeping my company during late night experiment and for always providing great conversation, entertainment, and advice in Café Disco.

Introduction

“The mind, in short, works on the data it receives very much as a sculptor works on his block of stone.” – William James

In the late nineteenth and early twentieth century, conventional wisdom in neuroscience held that the circuits of the brain were hardwired once the brain had matured to adulthood. Researchers were convinced that the adult nervous system could not generate new neurons and that once development ended the “founts of growth and regeneration of the axons and dendrites dried up irrevocably. In the adult centers the nerve paths are something fixed, ended and immutable” (Ramon y Cajal, 1928). Contrary to the early dogma, contemporary neuroscience has demonstrated that the brain is exceptionally dynamic, has the capacity to birth new neurons, and retains a very high degree of structural and functional plasticity across the lifespan (Altman, 1962; Erickson et al., 1998; Gould, 1999; Lledo et al.,2005). As we encounter new experiences and learn new information along the way, the neuronal activity generated by what we think or do has the ability to sculpt the connections between our neurons, thereby changing the structure and function of these circuits. The Korol-Gold labs’ “Use it and Boost it” (Korol et al., 2013) theory suggests that stimulating experiences can enhance neural functioning; thus, experience primes future experience, but how, at a cellular level?

Previous experiments performed by Claire Scavuzzo and other members of the Korol-Gold labs have implicated heightened brain-derived neurotrophic factor (BDNF) protein and BDNF-TrkB signaling as the molecular mechanism underlying our “Use it and Boost it” motto (Korol et al. 2013). In these experiments, priming with spontaneous alternation (SA), a working memory task, or voluntary physical exercise, in running wheels, enhanced new learning of hippocampus-sensitive place, or striatum-sensitive response tasks via an increased reliance on BDNF-TrkB signaling. Furthermore, in cognitively primed rats, inhibition of glycogen synthase kinase 3β (GSK3β), a downstream target of BDNF-TrkB signaling, increased in the hippocampus and striatum following place and response training, but not after the SA priming task (Scavuzzo, 2014). To further identify the mechanisms supporting cognitive activity-induced learning enhancements, the current research examines the effect of SA priming on GSK3β inhibition in the hippocampus and striatum of young male rats.

Experience and the Brain

Brains are incredibly malleable and continuously undergo structural and functional reorganization in response to neural activity and/or experience. Active engagement in physical, motor, or cognitive activity benefits brain health and can induce changes in structural and functional plasticity via neurogenesis, the development of new neurons, via angiogenesis, the sprouting of new blood vessels in the brain, and via synaptogenesis, the strengthening of existing connections and formation of new synapses between neurons (Black et al., 1990; Anderson et al., 1994; van Praag et al., 1999, 2005; Ding et al., 2006). Recent literature has indicated that enriching experiences including cognitive (Wilson et al., 2002; Hall et al., 2009; Korol et al., 2013; Anguera et al., 2013) and physical activity (Colcombe and Kramer, 2003; Chen et al., 2005, Anderson et al., 2010; Intlekofer and Cotman, 2013) can produce robust changes in learning and memory, protect against non-pathological age-related deficits, and reduce the risk of Alzheimer’s disease (AD) or Parkinson’s disease (PD) (Fillit et al., 2002).

Under the scope of this experiment, cognitive priming can be understood as a mechanism of metaplasticity (Abraham, 2008). Metaplasticity refers to an activity-dependent and persistent change in the structure and function of neurons and synapses which then alters their ability to generate synaptic plasticity (Abraham, 2008; Ireland et al., 2009). A key feature of metaplasticity is that this change outlasts the triggering or priming event and persists until a second bout of activity and thus it is essentially the plasticity of plasticity. In previous experiments from our lab, SA was used as a behavioral primer in rats prior to their training on a hippocampus-sensitive place task or a striatum-sensitive response task. SA takes advantage of a rat's natural tendency to explore novelty and alternate arm choices in a maze in order to measure spatial working memory. While SA was previously thought to be a hippocampus sensitive task (Stevens and Cowey, 1973; Lalonde, 2002), it is now considered to be a mixed task as SA testing increases extracellular levels of acetylcholine and lactate in both the hippocampus and striatum, suggesting activation of both structures (Pych et al., 2005; Newman et al., 2011; Gold et al., 2013). Beyond this, it should be noted that the cognitive load of a priming task also plays a role in determining which experiences will enhance subsequent behaviors. Interestingly, the cognitive load of a SA task has been found to be a function of the number of maze arms available for exploration (McNay et al., 2000). For example, a previous study examining the cognitive load of a 2-arm straight alley maze vs. a 4-arm plus-shaped maze established that only priming with a 4-arm maze was sufficient to enhance later learning on the place or response task (Scavuzzo, 2014).

The impact of cognitive experiences on future learning and memory has received relatively less attention than the physical components of these experiences. Much of what is known about the neurochemical mechanisms underlying enhancements in cognition following enriching or priming experiences have been derived from exercise studies. A great body of literature has demonstrated that functions most vulnerable to decline with age and health status can be favorably influenced by physical activity (Smith and Zigmond, 2003; Dishman et al., 2006). As we age, physically active humans and rodents excel across a variety of learning and memory tasks in comparison to their sedentary controls (Colcombe and Kramer, 2003; Vaynman et al., 2004; Erickson et al., 2011; Korol et al., 2013; Scavuzzo, 2014). Much like physical activity, engaging in regular cognitive activity or training early in life supports future enhancements of learning and memory across the lifespan (Studenski et al., 2006; Buschkuehl et al., 2008; Light et al., 2010; Schmeidek et al., 2010; Korol et al., 2013).

While engaging in cognitive and physical activity supports the future functioning of neural systems, it is likely that the most robust enhancements of future behaviors are seen on tasks that rely on and tap into those previously practiced memory systems (Moser et al., 1994; Vaynman et al, 2004; Kleinknecht et al., 2012). For example, older adults cognitively trained for memory, reasoning, or speed of processing exhibited substantial enhancements in cognitive tasks specific to the previously trained domains of cognition for 2 years following training (Ball et al., 2002). Alternatively, multiple studies have established that cognitive training, via working memory testing, produce adaptations that are beneficial for a variety of tasks that tap multiple domains of cognition (Chien and Morrison, 2010; Jaeggi et al., 2008; Light et al., 2010; Korol et al. 2013).

Neural Mechanisms of Priming

Under the “use it and boost it” model, engaging in enriching experiences induces neuroplastic adaptations and provides us with the molecular machinery to support future learning and memory. As discussed above, much of the brain’s neuroplasticity is derived from the actions of neurogenesis, angiogenesis, and synaptogenesis. One molecule that appears to play a crucial mediating role in these actions is brain-derived neurotrophic factor (BDNF), a protein belonging to a family of neurotrophins. Neurotrophins, or neurotrophic factors, are a group of regulatory growth factors that mediate neuronal development, survival, and synaptic plasticity (Huang and Reichardt, 2001).

BDNF serves as an important regulatory mechanism underlying the beneficial effects of cognitive priming and physical activity on learning and memory (Cunha et al., 2010; Vaynman et al., 2003, 2004; Erickson et al., 2013; Korol et al., 2013). As an activity-dependent protein, BDNF synthesis and signaling increase in response to cellular excitation (Zafra et al., 1990; Patterson et al., 1992 Hartmann et al., 2001; Lu, 2003). Like other neurotrophins, BDNF is first synthesized as a precursor molecule, proBDNF, and upon sufficient activation, proBDNF is cleaved into its mature and active form, mBDNF (Nagappan, et al., 2009). For example, following cognitive and physical training, a surge in neural activity induces rapid and durable increases in both mBDNF protein and BDNF mRNA content in the hippocampus and striatum (Neeper et al., 1996; Kesslak et al., 1998 Hall et al., 2000; Korol et al., 2013). On the other hand, a dysregulation in BDNF signaling and reduced BDNF mRNA and protein has been implicated in age-related cognitive declines, the development of psychiatric disorders, and the development neurodegenerative diseases (Phillips et al., 1991; Martinowich et al., 2007; Zuccato and Cattaneo 2009).

BDNF signaling occurs via a high-affinity receptor, tyrosine kinase receptor B (TrkB),

and modulates many cellular activities in both neurons and glia (Middlemas et al., 1991; Frisen et al., 1993, Armanini et al., 1995). TrkB receptors, found on neurons and astrocytes, respond to BDNF to induce similar intracellular cascades, but they do so via different mechanisms. In neurons, full-length TrkB receptors are predominantly expressed, allowing signaling to occur via mBDNF binding to the TrkB receptor. Following mBDNF binding, dimerization and autophosphorylation of the ligand-receptor complexes occur to initiate downstream signaling cascades (Hubbard et al. 1998; Kaplan and Miller, 2000; Chao, 2003). On the other hand, astrocytes express truncated TrkB receptors which lack phosphorylation sites, and thus no dimerization and autophosphorylation occur (Klein et al., 1990; Frisen et al., 1993; Biffo et al., 1995). Instead, mBDNF binding induces a conformational change in the truncated TrkB receptor, which activates a G protein (Gq) that acts on PLCɣ to increase intracellular calcium concentrations ([Ca2+]) (Rose et al., 2003). While BDNF-TrkB signaling in astrocytes initiates many of the same cascades present in neurons, previous work from the lab implies that increased BDNF signaling following priming acts through the neuronal TrkB receptor subtype, as infusions of K252a, a selective TrkB inhibitor, attenuated cognitive and physical activity-induced enhancements in place and response learning (Kafitz et al., 1999; Scavuzzo, 2014).

As aforementioned, engaging in physical activity and enriching experiences produce robust changes in the molecular machinery that support future behaviors, such as learning and memory. Given that mBDNF content and release increase following priming with mental or physical activity, the cognitive benefits of this priming are likely a consequence of heightened BDNF signaling at the time of priming and an increased reliance on BDNF-TrkB signaling (Kesslak et al., 1998; Vaynman at al., 2003, 2004; Korol et al., 2013; Scavuazzo, 2014). Beyond this, inhibition or activation of signaling cascades downstream of BDNF-TrkB signaling, such as glycogen synthase kinase 3β (GSK3β), likely contribute to the activity-induced learning enhancements following priming. While the downstream targets of BDNF-TrkB signaling that mediate activity-induced learning enhancements have received relatively less attention, the inhibition of GSK3β may be an intermediary step involved in the regulation of learning and memory via BDNF mechanisms.

GSK3, originally identified as a regulator of glycogen synthesis (Embi et al, 1980), has been implicated in various signal transduction pathways, learning and memory, psychiatric disorders, and neurodegenerative diseases (Sutherland, 2011). Unlike many other kinases, GSK3 is constitutively active under basal conditions and is inhibited via serine phosphorylation (Beurel et at., 2015). While GSK3 exists as two structurally similar isoforms, GSK3α and GSK3β, only the actions of GSK3β will be examined. GSK3β, is an incredibly busy and multifunctional serine/threonine protein kinase that acts on nearly 100 substrates including tau, a protein implicated in Alzheimer’s disease (AD)-related brain changes (Sutherland, 2011). Like BDNF-TrkB signaling, GSK3β inhibition is activity-dependent and occurs in response to upstream signals. BDNF-TrkB signaling triggers the activation of downstream phosphatidylinositol 3-kinase (PI3K)/Akt, which leads to GSK3β inhibition through phosphorylation at the serine 9 (Ser9) residue (Cross et al., 1995; Mai et al, 2002).

As previously mentioned, a dysregulation in BDNF-TrkB signaling has been implicated in several age-related cognitive declines and the development of neurodegenerative diseases, such as AD. Similarly, GSK3β hyperactivity has also been implicated in the above-mentioned processes as functional BDNF-TrkB signaling is required to phosphorylate and inactivate GSK3β (Hooper et al., 2007, 2008).

Growing evidence indicates that the hyperactivation of GSK3β promotes some neurodegenerative processes while inhibition of GSK3β reduces some cognitive deficits. Numerous studies have linked hyperactive GSK3β signaling to learning and memory deficits and the development of AD based on the GSK3β-mediated hyperphosphorylation of tau (Wagner et al., 1996; Lucas et al., 2001; Hernandez et al., 2002; Liu et al., 2003). This abnormal phosphorylation of tau is associated with neurofibrillary tangles, one of the hallmark features of AD (Lucas et al., 2001; Hooper et al., 2008). Furthermore, the hyperactivation of GSK3β also accounts for the cognitive impairments, increased amyloid-beta production, and neuroinflammation seen in AD (Hooper et al., 2008). On the other hand, the inactivation of GSK3β is beneficial for learning and memory processes and stimulates both neuroprotective and neuroplastic mechanisms in neurons (Chin et al., 2005; Hooper et al, 2007). For instance, in rodent models of AD, the inhibition of GSK3β activity ameliorated the learning and memory deficits caused by hyperactive or overexpressed GSK3β (Engel et al., 2006), while in healthy animals, drugs that chronically inhibit GSK3β activity impair memory processing (Kimura et al., 2008). These findings suggest that some level of GSK3β activity must be maintained for normal learning and memory and thus a balance of GSK3β activity and inhibition seems to be essential for learning and memory in healthy animals.

Project Outline

The purpose of this experiment is to further investigate the relationship between cognitive activity-induced learning enhancements and the phosphorylation status of GSK3β in healthy young male rats. As previously mentioned, in cognitively primed rats, inhibition of GSK3β, a downstream target of BDNF-TrkB signaling, increased in the hippocampus and striatum following place and response training, but not after the SA priming task (Scavuzzo, 2014). In this experiment rats were euthanized either 1 hr after SA testing or immediately after place and response training and thus the differences seen in GSK3β inhibition states could be a consequence of the increased cognitive load associated with place and response training, or a function of time as place and response training takes significantly longer than SA. Given that GSK3β inhibition was not seen 1 hour after SA, the current study examines GSK3β inhibition at 4 different timepoints following the SA priming task to determine if activity-induced GSK3β inhibition occurs several hours after testing or at all.

In this experiment young adult male rats were tested on a 4-arm SA task for 20 minutes then euthanized immediately, 1 hour, 4 hours, or 24 hours after testing. Next, the hippocampus and striatum were rapidly dissected from each side of the brain and analyzed for GSK activation. The ratio of phosphorylated GSK3β at Ser9 to total GSK3β (pGSK3β:GSK3β) in the hippocampus and striatum were quantified via Western blot to determine the levels of GSK3β inhibition. We hypothesized that a significant increase in GSK3β inhibition, or pGSK3β/totalGSK3β ratios, would be seen at 4 and 24 hours after SA testing but not immediately or 1 hour after testing. If significant inhibition is seen at the later time points, this would imply that BDNF-TrkB signaling, induced by cognitive priming, modulates subsequent learning enhancements via GSK3β-related mechanisms.

Methods

Subjects and Experimental Design

This experiment was conducted using 3-month-old male Sprague-Dawley rats supplied by Envigo. All procedures performed were approved by the Syracuse University Animal Care and Use Committee (IACUC), accredited by the Association for Assessment and Accreditation of Animal Care (AAALAC). Upon arrival, the rats were individually housed and maintained on a 12:12-hr light:dark cycle with ad libitum access to food and water until food-restriction procedures were initiated. Rats were allowed one week to acclimate to the vivarium before starting food restriction procedures. All rats were food-restricted to 80-85% of their free-feeding weight during the ten days prior to spontaneous alternation. The experimental groups include rats euthanized immediately (N=6), 1 hr (N=6), 4 hrs (N=7), and 24 hrs (N=6) after the spontaneous alternation task and a naïve control group (N=7).

Testing Apparatus & Procedure

To examine spontaneous alternation behavior, rats were tested on a 4-arm, plus-shaped maze made out of black Plexiglas®. The 4-arm maze was located in the center on the testing room and was surrounded by several 2- and 3-dimensional extramaze cues (Figure 1). Furthermore, each arm of the maze was designated either A, B, C, or D.

Prior to spontaneous alternation testing, rats were transferred to a new cage and given at least 15 minutes to acclimate to the testing room. At the start of testing the rat was placed in start arm A or C then was allowed to explore the maze freely for 20 minutes. To examine the rats working memory capacity, the number and sequence of arm entries were recorded then a moving window of five arm entries was analyzed and scored for possible alternations. An alternation occurred when a rat entered all four arms within five consecutive entries. For example, entering arms ABDAC in five consecutive choices would be considered an alternation while entering arms ABACB in five consecutive choices would not be an alternation. Immediately, 1 hr, 4 hrs, or 24 hrs following testing rats were overdosed using a 1ml intraperitoneal injection of sodium pentobarbital and decapitated for brain tissue collection. The hippocampi and striata were dissected from the brain, flash-frozen on dry ice, and stored at -80ºC.

Tissue Preparation

The brain samples were first crushed by hand using a mortar and pestle, then mechanically homogenized on ice in a homogenization buffer composed of 1mM EGTA, 1 mM EDTA, 20 mM Tris (pH 7.4), 1 mM sodium pyrophosphate tetrabasic decahydrate, 4 mM 4-nitrophenyl phosphate disodium hexahydrate (Phosphatase Substrate), and a dissolved protease cocktail inhibitor tablet (Complete Mini tablets, Roche Diagnostic Corporation). After homogenizing, the samples were transferred to a microfuge tube and centrifuged at 4°C for 5 minutes at 6,700 x g. The supernatant was collected and stored at 20°C for further use.

Protein Assay

The protein concentrations of the supernatants were determined using a Pierce Micro-BCA assay kit. Each tissue sample was diluted 1:20 with homogenization buffer (10 µl sample + 190 µl buffer) and diluted Albumin (BSA) Standards raging from 0 μg/ml to 2000 μg/ml were prepared. Next, the diluted standards (25 μl) and samples (25 μl) were added in triplicate to a 96-well microtiter plate. A working reagent (100 μl) was added to each well and incubated in a warm room at 37ºC for 30 min. Following the incubation period, the plate was cooled to room temperature (25ºC) then the optical density was measured at an absorbance of 562 nm using a ThermoMax microplate reader with SoftMax Pro software.

Western Blot Sample Preparation

Following the BCA assay, the protein concentrations of the samples were calculated and diluted for loading. The brain supernatants were added to a calculated amount of fresh homogenization buffer and 4X protein loading buffer (LI-COR Biosciences) with 10% β-mercaptoethanol. The loading buffer was added to the samples in a 1:3 dilution (50 μl buffer + 150 μl sample). The samples were boiled in a dry bath heater at 95°C for 10 mins, centrifuged at

11,300 x g for 5 min, and stored at -20°C until loading on a gel. The hippocampal samples had a final protein concentration of 3 μg/μl, while the striatal samples had a final protein concentration of 2 μg/μl.

Western Blots

To analyze the inactivation states of GSK3β in the hippocampus and striatum, western blotting was performed. To make 10% acrylamide gels, a separating gel solution (10%) was added to a 1.0 mm thick gel casting mold and immediately topped with ethanol (EtOH) to ensure an even interface between the two layers. Once the separating gel polymerized, the EtOH was poured off and a stacking gel solution (5%) was added to the glass mold along with a 15-well gel comb. Once the gel had completely polymerized, the glass molds were removed from the casting stand, snapped into the gel holders, and placed in the running box.

Prior to protein loading, 1x running buffer (0.025 M Tris base, 0.192 M glycine, and 0.1% SDS) was used to overflow the space in-between the gels and the gel combs were removed. To allow for comparisons across gels, standard curves were generated from pooled hippocampal or striatal homogenates and loaded onto each gel in three different protein concentrations: 10 μg, 20 μg, and 30 μg total protein. The standard curve samples, prepared experimental samples (20 μg), and All Blue precision plus protein ladder (2 μl; BioRad Laboratories) were loaded onto each 10% acrylamide gel and were resolved on ice via electrophoresis for 75 min at 200 V. As the gel ran, 2 black filter pads per gel were boiled for ~10 min to remove excess salts and Immobilon-FL PVDF transfer membranes (0.45 µm pore size, MilliporeSigma) were cut to approximately 9 x 6.5 cm and labeled in the top left corner. Prior to transfer, the PVDF membranes were activated in methanol (MeOH) for ~30 secs, rinsed in ultrapure water (ddH2O) for ~1 min, and placed in 1x transfer buffer (0.025 M Tris base, 0.192 M glycine, and 20% MeOH) to equilibrate.

Following electrophoresis, each gel was removed from the glass casting and the stacking gel and gel foot were cut off using a spatula. The top left corner of the gels was also cut off, allowing for easy identification of the gel orientation in subsequent steps, then the gels were allowed to equilibrate in chilled transfer buffer for 15 min prior to assembling the transfer sandwich. The transfer was set up as follows: cathode (-) → black cassette face → filter pad → buffer-soaked filter paper → gel → PVDF membrane → filter paper → filter pad → clear cassette face → anode (+). After assembling the transfer, the gel holder cassettes were placed in a blotting tank filled with transfer buffer and a stir bar. The transfer was run at 100 V for 2 hrs in an ice bath on top of a stir plate.

Following protein transfer, membranes were removed from the sandwich and added to 5 ml of Ponceau stain. Of note, all subsequent steps occurred while rocking on a VMR platform shaker set to 5-6 speed. After 1 min, membranes were rinsed in ddH2O then 1x Tris-buffered saline (TBS) until all stain was gone. The membranes were blocked in Odyssey blocking buffer (TBS; LI-COR Biosciences) for 1 hr at room temperature (25ºC) before being added to the primary antibody solution. The membranes were then incubated at 4ºC overnight in GSK3β (3D10) mouse monoclonal antibody (1:1500; #9832S, Cell Signaling Technology), phospho-GSK3β (Ser9) (5B3) rabbit monoclonal antibody (1:1000; #9323S, Cell Signaling Technology), and β-Tubulin (D3U1W) mouse monoclonal antibody (1:30,000; #86298T, Cell Signaling Technology) in Odyssey blocking buffer (TBS) plus 0.1% Tween 20 (Sigma-Aldrich). Following primary antibody incubation, the membranes were washed 4 times for 10 min each in 1x TBS plus 0.1% Tween 20 at room temperature. Next, the membranes were incubated for 1 hr at room temperature with IRDye 680RD goat anti-mouse secondary antibody (1:10,000; LI-COR Biosciences) and IRDye 800CW goat anti-rabbit secondary antibody (1:10,000; LI-COR Biosciences) in Odyssey blocking buffer (TBS) plus 0.1% Tween 20. Finally, the membranes were washed 4 more times in 1x TBS plus 0.1% Tween 20, rinsed for 2 min in ddH2O, and scanned, both wet and dry, on the Odyssey CLx Imaging System (LI-COR Biosciences) to quantify the protein bands.

Image Analysis

Western blot images were analyzed using Odyssey software (LI-COR Biosciences). Each band was manually identified and fitted to measure integrated intensity of the band (band intensity X band area). Standard curves, generated from pooled samples loaded in 10, 20, and 30 micrograms protein per well, were included on each blot and used to determine linearity of the blots and the relative amounts of pGSK3β and GSK3β present in each sample band. For each blot, protein values of our experimental samples were first standardized to the α-tubulin loading control and then were calculated as a percentage of the 20 μg standard for presentation. This approach allowed us to account for differences in loading within a blot (α-tubulin standardization) and for between-blot differences (20 μg-sample standardization). Each sample was run in duplicate on different blots and standardized to its α- tubulin control. The median value from each duplicate set was used to generate the percentage of the 20 μg standard that was used for group calculations. The ratio of pGSK3β to GSK3β was determined to generate a measure of GSK3β inhibition

Statistical Analysis

To assess the differences in percent alternation from chance (44%) a one sample t-test was performed. A Pearson's correlation analysis was performed to determine if there was a correlation between alternation scores and the number of arms entered. To assess differences in SA across groups and arm entries across groups one-way analyses of variance (ANOVAs) were performed. ANOVAs were also performed to assess the differences in total GSK3β, pGSK3β, and pGSK3β:GSK3β signal in the hippocampus and striatum across SA-tested and untested controls.

Results

Behavioral Assessment

All rats tested on the 4-arm spontaneous alternation task had similar alternation scores and number of arm entries (Figure 2). There were no significant differences in spontaneous alternation behavior across groups (F(3,21) = 0.27, p = 0.85), but alternation scores for all groups were significantly above the chance behavior score of 44% (p < 0.05; Figure 2A), indicating that all rats were sufficiently engaged in the task. The number of arm entries was not significantly different across groups (F(3,21) = 1.21, p = 0.33; Figure 2B) and there was no significant correlation between alternation scores and the number of arms entered (r2 =0.07, p > 0.1; Figure 3).

Western Blots

To analyze the effect of spontaneous alternation priming on GSK3β inhibition we examined the ratio of phosphorylated GSK3β (at Ser9) to total GSK3β (pGSK3β:GSK3β). We found that there was no consistent effect of spontaneous alternation testing on pGSK3β:GSK3β levels in the hippocampus (F(4,28) = 1.03, p = 0.4) and striatum (F(4,27) = 0.56, p = 0.69) of primed rats in comparison to the untested controls (Figure 4). In SA-tested rats, there appeared to be an increasing trend of pGSK3β:GSK3β signal in the hippocampus (Figure 4A) and striatum (Figure 4B) as time from testing increased; however, an ANOVA of only SA-tested rats determined that this increasing trend was not statistically significant in the hippocampus (F(3,45) = 1.53, p = 0.22) or striatum (F(3,21) = 1.03, p = 0.4). In the hippocampus (Figure 5A and B), there were no significant differences in pGSK3β (F(4,58) = 1.08, p = 0.38) and total GSK3β (F(4,58) = 0.23, p = 0.92) content normalized to tubulin. Similarly, in the striatum (Figure 5C and D), there were no significant differences in pGSK3β (F(4,27) = 0.61, p = 0.66) and total GSK3β (F(4,27) = 0.77, p = 0.55) content normalized to tubulin.

Discussion

The present findings indicate that SA priming failed to modulate the phosphorylation and inhibition of GSK3β in any consistent manner. While we observed an increasing trend in pGSK3β:GSK3β content in the hippocampus and striatum as time increased from SA testing, the increase of pGSK3β:GSK3β in both brain regions was not statistically significant. This finding suggests that the significant increase in GSK3β inhibition following place and response training was likely a product of the increased cognitive load associated with these tasks. Beyond this, it is possible that differences in task attributes between SA testing and place and response learning could also be responsible for the differences seen in GSK3β inhibition across tasks. For example, SA testing requires fewer cognitive resources as it only lasts for 20 minutes and has no food reward, while place and response training are likely to be more arousing as rats must learn to navigate a maze to find the food reward for 75-100 trials. Given that place and response tasks require more significant resources from the hippocampus and striatum than does SA testing (Gold et al, 2013), it is not surprising that only place and response tasks induced higher levels of GSK3β inhibition (Scavuzzo, 2014).

While past work has indicated that BDNF release is increased in hippocampus and striatum of rats following SA priming (Scavuzzo, 2014), it appears that SA testing alone may not be robust enough cognitive activity to induce significant enough increases in BDNF content to stimulate the downstream inhibition of GSK3β. Given that we did not see an effect of SA testing on GSK3β inhibition in the hippocampus and striatum, it is possible that activity-dependent inhibition of GSK3β requires a certain threshold of activity and/or a more prolonged period of activity. From these data, one might speculate that the cognitive load of the priming task or experience likely plays an important role in determining which experiences will enhance subsequent cognition.

Both BDNF and GSK3β and have been individually implicated in various learning and memory processes (Vaynman et al., 2003, 2004; Chin et al., 2005; Korol et al., 2013; Scavuazzo, 2014); however, through this study, we were unable to demonstrate a link between SA-testing and increased GSK3β inhibition in the hippocampus and striatum as a result of cognitive priming. While literature suggests that GSK3β inhibition contributes to learning and memory in various transgenic animals and pathological models (Liu et al., 2003; Hooper et al, 2007; Kimura et al., 2008), GSK3β inhibition may not be necessary or important for the effects of priming. Given that heightened BDNF-TrkB signaling has previously been implicated as a primary mechanism underlying the effects of priming on cognition (Korol et al., 2013), we should examine other downstream targets and candidate pathways. Upon BDNF binding to TrkB, receptor dimerization and autophosphorylation of specific tyrosine residues in its cytoplasmic kinase domain trigger the activation of downstream signaling cascades (Cunha et al., 2010). Three prominent downstream pathways: extracellular signal-regulated kinases (ERK), phospholipase Cγ (PLCγ), and phosphoinositide 3-kinase (PI3K)/Ark are potential targets to examine as they have been associated with various learning and memory processes, though not with priming in multiple memory systems (Huang and Reichardt, 2001; Bekinschtein et al., 2008; Cunha et al., 2010; Giese and Mizuno, 2013). For instance, a previous study observed learning-associated activation of the TrkB/PI3-K signal transduction pathway in the hippocampus of rats that were trained for a spatial reference/working memory task in a radial arm maze (Mizuno et al., 2003). Furthermore, a separate study has implicated the ERK-signaling pathway in mediating long-term synaptic plasticity and hippocampal-dependent learning (Alonso et al., 2004). Activation of one or more of these downstream signaling cascades could thus promote learning and memory processes via increased glutamate release due to ERK activation and increased intracellular calcium (Almeida et al., 2005) or via increased glucose metabolism brought on by PI3K/Akt activation (Mattson, 2002).

Future studies could examine other rapid signaling actions of BDNF as well as the necessity for long-term trophic actions, as BDNF can exert both rapid, as seen in this study, and long-term actions on synaptic dynamics, (Rose et al., 2003; Korol et al., 2013; Sasi et al., 2017; Kowiański et al., 2018). The rapid actions of BDNF are based on the regulation of neurotransmitter release and the modification of preexisting proteins or synapses (Hall et al., 2000; Tyler and Pozzo-Miller, 2001; Korol et al., 2013). Specifically, increased concentrations of AMPA receptors on the post-synaptic membrane, increased intracellular calcium levels, neurotransmitter release, and dendritic protein translation have been associated with enhanced learning and memory via BDNF mechanisms and thus could be further analyzed in the context of priming (Tyler and Pozzo-Miller, 2001; Du and Poo, 2004; Almeida et al., 2005 Cunha, et al. 2010). On the other hand, the long-term trophic actions of BDNF signaling should be examined as they are related to changes in gene expression, such as increased expression of BDNF itself, synaptogenesis, dendritic and axonal branching, and protein synthesis (Korte et al, 1998; Almeida et al., 2005; Park and Poo, 2013). While BDNF signaling that produce rapid actions are likely to promote faster learning and memory, examining the more durable and trophic actions of BDNF-TrkB signaling may allow us to better understand how BDNF mediates or modulates activity-induced plasticity due to cognitive priming.

Figures

Figure 1. Schematic diagram of spontaneous alternation on a 4-arm plus maze surrounded by extramaze cues. Rats are given 20 minutes to explore all arms of the maze and are tested on their working memory capacity by counting how many times the rat enters all 4 arms within 5 consecutive arm entries.

Chance

A.

B.

Figure 2. Alternation scores and arm entries for SA-tested Sprague Dawley rats. Rats tested on the 4-arm plus maze had similar alternation scores (A) and arem entries (B) across groups. Alternation scores were well above chance behavior at 44% (p < 0.05). N=6 for immed, N=6 for 1 hr, N=7 for 4 hrs, and N=6 for 24 hrs.

Figure 3. Correlation between alternation scores and the number of arms entered. The scatter plot demonstrates a weak negative correlation between (%) alternation and arm entries

(r = –0.265), which is statistically not significant (p = 0.124).

A.

B.

Figure 4. Western blot analysis of pGSK3β:GSK3β levels in the hippocampus and striatum. SA-tested rats exhibit an increasing trend of pGSK3β to GSK3β signal in the hippocampus (A) and striatum (B) as the time from testing/brain collection increased. One-way ANOVAs revealed that pGSK3β:GSK3β levels in SA-tested rats were not statistically different (p > 0.05) from the untested controls in the hippocampus and striatum. N=7 for naïve, N=6 for immed, N=6 for 1 hr, N=7 for 4 hrs, and N=6 for 24 hrs.

A. B.

C. D.

Figure 5. pGSK3β and total GSK3β levels in the hippocampus and striatum of SA-tested rats. In the hippocampus (A and B) and striatum (C and D) of SA-tested rats both total GSK3β and pGSK3β levels we not statistically different compared to the untested controls. N=7 for naïve, N=6 for immed, N=6 for 1 hr, N=7 for 4 hrs, and N=6 for 24 hrs.

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