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Calcium concentration in activated dendritic spines?

Calcium concentration in activated dendritic spines?


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What are the typical calcium levels reached in single postsynaptic spines following activation of NMDA receptors by an EPSP or backpropagating spike? Everyone seems to refer to that one Neuron paper (Sabatini et al. 2002) which reports experimental estimates of around 1 uM following single synaptic stimulation in CA1 neuron spines. However, most computational papers on LTP (even biophysically detailed models) work with much lower values for Ca2+ transients that do not seem to have concrete experimental support. I am trying to put together a realistic model for hippocampal spine calcium signaling, and would really appreciate it if anyone can point out other relevant experimental papers that provide estimates for spine calcium transients.


An earlier source for an estimate of ${[Ca]_{i}}^{+2}$ in spines comes from hippocampal slices of P13-P19 rats (Majewska et al. 2000). The resting ${[Ca]_{i}}^{+2}$ in this paper was ~80 nM and a back-propagating action potential (AP) elicited a response up to ~250 nM (change of ~170 nM). They included $F_{min}$ and $F_{max}$, the minimum and maximum fluorescence signal from a single AP, as parameters in the equation they used to estimate ${[Ca]_{i}}^{+2}$. This paper may be where the models you mention got their numbers from.

The resting ${[Ca]_{i}}^{+2}$ estimated in Sabatini et al. (2002), where they also used rat hippocampal slices from P14-P20, matches that found in Majewska et al. as it was ~70 nM. For the estimation of the evoked change in ${[Ca]_{i}}^{+2}$ after a single AP they used the maximum fluorescence increase from trains of action potentials at 62.5 Hz and 83.3 Hz as a parameter in their estimator equation, assuming that the calcium indicator was fully saturated at those stimulation frequencies. Their estimate for the change in ${[Ca]_{i}}^{+2}$ per AP was about 530 nM. They then reasoned that the buffering properties of the calcium indicator itself could reduce the change in ${[Ca]_{i}}^{+2}$. Thus they loaded several different calcium indicators with different affinities and at different concentrations, in order to manipulate the $kappa_b$, the buffer capacity, of the calcium indicator. They observed a very strong linear relationship between $kappa _b$ and the change in ${[Ca]_{i}}^{+2}$. By extrapolating from a linear fit on these data, they concluded that in the case where there was no calcium indicator in the cell -i.e. when $kappa _b = 0$- the change in ${[Ca]_{i}}^{+2}$ per AP would be approximately 1 $mu$M.

So the difference between these studies is that in Majewska et al. they used the maximum observed fluorescence of the calcium indicator in their data after single APs, whereas in Sabatini et al. they attempted to saturate the calcium indicator with high-frequency trains of APs. Furthermore, in Sabatini et al. they attempted to account for the buffering capacity of the calcium indicator itself, thus arriving at a more unbiased estimate.

Reassuringly, later work from the Yuste lab (the same lab as in the Majewska et al. study) could replicate the results of Sabatini et al. when they used similar methodology (Cornelisse et al. 2007). Their estimate for $Delta{[Ca]_{i}}^{+2}$ for a single AP was also ~1 $mu$M.


The Role of Dendritic Spine Density in Neuropsychiatric and Learning Disorders

Photo originally by MethoxyRoxy on Wikimedia Commons. No changes. CC License BY-SA 2.5.

By Neha Madugala, Cognitive Science, ‘21

Author’s Note: Last quarter I took Neurobiology (NPB100) with Karen Zito, a professor at UC Davis. I was interested in her research in dendritic spines and its correlation to my personal area of interest in research regarding the language and cognitive deficiencies present in different populations such as individuals with schizophrenia. There seems to be a correlational link between the generation and quantity of dendritic spines and the presence of different neurological disorders. Given the dynamic nature of dendritic spines, current research is studying their exact role and the potential to manipulate these spines in order to impact learning and memory.

Dendritic spines are small bulbous protrusions that line the sides of dendrites on a neuron [12]. Dendritic spines serve as a major site of synapses for excitatory neurons, which continue signal propagation in the brain. Relatively little is known about the exact purpose and role of dendritic spines, but as of now, there seems to be a correlation between the concentration of dendritic spines and the presence of different disorders, such as autism spectrum disorders (ASD), schizophrenia, and Alzheimer’s disease. Scientists hypothesize that dendritic spines are a key player in the pathogenesis of various neuropsychiatric disorders [8]. It should be noted that other morphological changes are also observed when comparing individuals with the mentioned neuropsychiatric disorders are compared to neurotypical individuals. However, all these disorders share the common thread of abnormal dendritic spine density.

The main disorders studied in relation to dendritic spine density are autism spectrum disorder (ASD), schizophrenia, and Alzheimer’s disease. Current studies suggest that these disorders result in the number of dendritic spines straying from what is observed in a neurotypical individual. It should be noted that there is a general decline in dendritic spines as an individual ages. However intellectual disabilities and neuropsychiatric disorders seem to alter this density at a more extreme rate. The graph demonstrates the general trend of dendritic spine density for various disorders however, these trends may slightly vary across individuals with the same disorder.

I. Role of Dendritic Spines

Dendritic spines are protrusions found on certain types of neurons throughout the brain, such as in the cerebellum and cerebral cortex. They were first identified by Ramon y Cajal, who classified them as “thorns or short spines” located nonuniformly along the dendrite [6].

The entire human cerebral cortex consists of 10 14 dendritic spines. A single dendrite can contain several hundred spines [12]. There is an overall greater density of dendritic spines on peripheral dendrites versus proximal dendrites and the cell body [3]. Their main role is to assist in synapse formation on dendrites.

Dendritic Spines fall into two categories: persistent and transient spines. Persistent spines are considered ‘memory’ spines, while transient spines are considered ‘learning’ spines. Transient spines are categorized as spines that exist for four days or less and persistent spines as spines that exist for eight days or longer [5].

The dense concentration of spines on dendrites is crucial to the fundamental nature of dendrites. At an excitatory synaptic cleft, the release of the neurotransmitter at excitatory receptors on the postsynaptic cell results in an excitatory postsynaptic potential (EPSP), which causes the cell to fire an action potential. An action potential is where a signal is transmitted from one neuron to another neuron. In order for a neuron to propagate an action potential, there must be an accumulation of positive charge at the synapses, reaching a certain threshold ( Figure 2 ). The cell must reach a certain level of depolarization – a difference in charge across the neuron’s membrane making the inside more positive. A single EPSP may not result in enough depolarization to reach this action potential threshold. As a result, the presence of multiple dendritic spines on the dendrite allows for multiple synapses to be formed and multiple EPSPs to be summated. With the summation of various EPSPs on the dendrites of the neurons, the cell can reach the action potential threshold. The greater density of dendritic spines along the postsynaptic cell allows for more synaptic connections to be formed, increasing the chance of an action potential to occur.

Figure 2. Firing of Action Potential (EPSP)

  1. Neurotransmitter is released by the presynaptic cell into the synaptic cleft.
  2. For an EPSP, an excitatory neurotransmitter will be released, which will bind to receptors on the postsynaptic cell.
  3. The binding of these excitatory neurotransmitters will result in sodium channels opening, allowing sodium to go down its electrical and chemical gradient – depolarizing the cell.
  4. The EPSPs will be summated at the axon hillock and trigger an action potential.
  5. This actional potential will cause the firing cell to release a neurotransmitter at its axon terminal, further conveying the electrical signal to other neurons.

Dendrites initially are formed without spines. As development progresses, the plasma membrane of the dendrite forms protrusions called filopodia. These filopodia then form synapses with axons, and eventually transition from filopodia to dendritic spines [6].

The reason behind the creation of dendritic spines is currently unknown. There are a few potential hypotheses. The first hypothesis suggests that the presence of dendritic spines can increase the packing density of synapses, allowing for more potential synapses to be formed. The second hypothesis suggests that their presence can help prevent excitotoxicity, overexcitation of the excitatory receptors (NMDA and AMPA receptors) present on the dendrites. These receptors usually bind with glutamate, a typically excitatory neurotransmitter, released from the presynaptic cell. This can result in damage to the neuron or if more severe, neuronal death. Since dendritic spines compartmentalize charge [3], this feature helps prevent the dendrite from being over-excited beyond the threshold potential for an action potential. Lastly, another hypothesis suggests that the large variation in dendritic spine morphology suggests that these different shapes play a role in modulating how postsynaptic potentials can be processed by the dendrite based on the function of the signal.

The creation of these dendritic spines is rapid during early development, slowly tapering off as the individual gets older. This process is mostly replaced with the pruning of synapses formed with dendritic spines when the individual is older. Pruning helps improve the signal-to-noise ratio of signals sent within neuronal circuits [3]. The signal-to-noise ratio outlines the ratio of signals sent by neurons and signals actually received by postsynaptic cells. It determines the efficiency of signal transmission. Experimentation has shown that the presence of glutamate and excitatory receptors (such as NMDA and AMPA) can result in the formation of dendritic spines within seconds [3]. The introduction of NMDA and AMPA results in cleavage of intracellular adhesion molecule-5 (ICAM5) from hippocampal neurons. ICAM5 is a “neuronal adhesion molecule that regulates dendritic elongation and spine maturation. [11]” Furthermore, through a combination of fluorescent dye and confocal or two-photon laser scanning microscopy, scientists were able to use imaging technology to witness that spines can undergo minor changes within seconds and more drastic conformational changes, even disappearing over minutes to hours [12].

The spine head’s morphology, a large bulbous head connected to a very thin neck that attaches to the dendrite, assists in its role as a postsynaptic cell. This shape allows one synapse at a dendritic spine to be activated and strengthened without influencing neighboring synapses [12].

Dendritic spine shape is extremely dynamic, allowing one spine to slightly alter its morphology throughout its lifetime [5]. However, dendritic spine morphology seems to take on a predominant form that is determined by the brain region of its location. For instance, presynaptic neurons from the thalamus take on the mushroom shape, whereas the lateral nucleus of the amygdala have thin spines on their dendrites [2]. The type of neuron and brain region the spine originates from seem to be correlated to the observed morphology.

The spine contains a postsynaptic density, which consists of neurotransmitter receptors, ion channels, scaffolding proteins, and signaling molecules [12]. In addition to this, the spine has smooth endoplasmic reticulum, which forms stacks called spine apparatus. It further has polyribosomes, hypothesized to be the site of local protein synthesis in these spines, and an actin-based cytoskeleton for structure [12]. The actin-based cytoskeleton makes up for the lack of microtubules and intermediate filaments, which play a crucial role in the structure and transport of most of our animal cells. Furthermore, these spines are capable of compartmentalizing calcium, the ion used at neural synapses that signal the presynaptic cell to release its neurotransmitter into the synaptic cleft [12]. Calcium plays a crucial role in second messenger cascades, influencing neural plasticity [6]. It also plays a role in actin polymerization, which allows for the motile nature of spine morphology [6].

There are many various shapes for dendritic spines. The common types are ‘stubby’ (short and thick spines with no neck), ‘thin’ (small head and thin neck), ‘mushroom’ (large head with a constricted neck), and ‘branched’ (two heads branching from the same neck) [12].

IV. Learning and Memory

Dendritic spines play a crucial role in memory and learning through occurrence of long-term potentiation (LTP), which is thought to be the cellular level of learning and memory. LTP is thought to induce spine formation, which hints at the common correlation that learning is associated with the formation of dendritic spines. Furthermore, LTP is thought to be capable of altering the immature and mature hippocampus, commonly associated with memory [2]. To contrast LTP, long-term depression (LTD) essentially works opposite to LTP – decreasing the dendritic spine density and size [2].

The correlation between dendritic spines and learning is relatively unknown. There seems to be a general trend suggesting that the creation of these spines is associated with learning. However, it is unclear whether learning results in the formation of these spines or if the formation of these spines results in learning. The general idea behind this hypothesis is that dendritic spines aid in the formation of synapses, allowing the brain to form more connections. As a result, a decline in these dendritic spines in neuropsychiatric disorders, such as schizophrenia, can inhibit an individual’s ability to learn. This is observed in various cognitive and linguistic deficiencies observed in individuals with schizophrenia.

Memory is associated with the strengthening and weakening of connections due to LTP and LTD, respectively. The alteration of these spines through LTP and LTD is called activity-dependent plasticity [6]. The main morphological shapes associated with memory are the mushroom spine, a large head with a constricted neck, and the stubby spine, a short and thick spine with no neck [6]. Both of these spines are relatively large, resulting in more stable and enduring connections. These bigger and heavier spines associated with learning are a result of LTP. By contrast, transient spines (live four days or shorter) are usually smaller and more immature in morphology and function, resulting in more temporary and less stable connections.

LTP and LTD play a crucial role in modifying dendritic spine morphology. Neuropsychiatric disorders can alter these mechanisms resulting in abnormal density and size of these spines.

I. What is Schizophrenia?

Schizophrenia is a mental disorder that results in disordered thinking and behaviors, hallucinations, and delusions [9]. The exact mechanics of schizophrenia are still being studied as researchers are trying to determine the underlying biological reasons behind this disorder and a way to help these individuals. Current treatment is focused on reducing and in some cases treating symptoms of this disorder, but more research and understanding is required to fully treat this mental disorder.

The exact source of schizophrenia seems to lie somewhere between the presence of certain genes and environmental effects. There seems to be a correlation between traumatic or stressful life events during an individual’s adolescence to an increased susceptibility to developing schizophrenia [1]. While research is still underway, certain studies point to cannabis having a role in increasing susceptibility to schizophrenia or worsening symptoms if an individual already has schizophrenia [1]. There seems to be some form of a genetic correlation, given an increased likelihood of developing schizophrenia if present in a family member. This factor seems to result from a combination of genes however, no genes have been identified yet. There also seems to be a chemical component, given the variation of chemical composition and density of neurotypical individuals and individuals with schizophrenia. Specifically, researchers have observed an elevated amount of dopamine found in individuals with schizophrenia [1].

III. Relationship between Dendritic Spines and Schizophrenia

A common thread among most schizophrenia patients is an impairment of pyramidal neuron (prominent cell form found in the cerebral cortex) dendritic morphology, occurring in various regions of the cerebral cortex [7]. Observed in postmortem brain tissue studies, there seems to be a reduced density of dendritic spines in the brains of individuals with schizophrenia. These findings are consistent with various regions of the brain that have been studied, such as the frontal and temporal neocortex, the primary visual cortex, and the subiculum within the hippocampal formation [7]. Out of seven studies observing this finding, the median reported decrease in spine density was 23%, with the overall range of these various studies being a decline of 6.5% to 66% [7].

It should be noted that studies were done to see if the decline in spine density was due to the usage of antipsychotic drugs. However animal and human trials showed no significant difference in the dendritic spine density of tested individuals.

This decline in dendritic spine density is hypothesized to be the result of the failure of the brain of schizophrenic individuals to produce sufficient dendritic spines at birth or if there is a more rapid decline of these spines during adolescence, where the onset of schizophrenia is typically observed [7]. The source of this decline is unclear, but seems to be attributed to deficits in pruning, maintenance, or simply the mechanisms of the underlying formation of these dendritic spines [7].

However, there are conflicting results. For instance, Thompson et al. conducted a study that seemed to suggest that a decline in spine density resulted in a progressive decline of gray matter, typically observed in schizophrenic individuals. Thompson et al. conducted an in vivo study of this phenomena. The study used MRI scans for twelve schizophrenic individuals and twelve neurotypical individuals, finding a progressive decline in gray matter – starting in the parietal lobe and expanding out to motor, temporal, and prefrontal areas [10]. The study suggests that the main attribution for this is a decline in dendritic spine density with the progression of the disorder. This study coincides with the previously mentioned hypothesis of a decline of spines during adolescence.

It is also possible that there is a combination of both of these factors occurring. Most studies have only been able to observe postmortem brain tissue, creating the confusion of whether there is a decline in spines or if the spines are simply not produced in the first place. The lack of in vivo studies makes it difficult to find a concrete trend within data.

While research is still ongoing, current evidence seems to suggest that dendritic spines are a crucial aspect in learning and memory. Their role in these crucial functions has been reflected by their absence in various neuropsychiatric disorders – such as schizophrenia, certain learning deficits present in some individuals with ASD, and memory deficits present in Alzheimer’s disease. These deficits seem to occur during the early creation of neural networks in the brain at synapses. Further research understanding the development of these spines and the creation of different morphological forms can be crucial in determining how to potentially cure or treat these deficiencies present in neuropsychiatric and learning disorders.


From form to function: calcium compartmentalization in dendritic spines

Dendritic spines compartmentalize calcium, and this could be their main function. We review experimental work on spine calcium dynamics. Calcium influx into spines is mediated by calcium channels and by NMDA and AMPA receptors and is followed by fast diffusional equilibration within the spine head. Calcium decay kinetics are controlled by slower diffusion through the spine neck and by spine calcium pumps. Calcium release occurs in spines, although its role is controversial. Finally, the endogenous calcium buffers in spines remain unknown. Thus, spines are calcium compartments because of their morphologies and local influx and extrusion mechanisms. These studies highlight the richness and heterogeneity of pathways that regulate calcium accumulations in spines and the close relationship between the morphology and function of the spine.


Control of Dendritic Spine Morphological and Functional Plasticity by Small GTPases

Structural plasticity of excitatory synapses is a vital component of neuronal development, synaptic plasticity, and behaviour. Abnormal development or regulation of excitatory synapses has also been strongly implicated in many neurodevelopmental, psychiatric, and neurodegenerative disorders. In the mammalian forebrain, the majority of excitatory synapses are located on dendritic spines, specialized dendritic protrusions that are enriched in actin. Research over recent years has begun to unravel the complexities involved in the regulation of dendritic spine structure. The small GTPase family of proteins have emerged as key regulators of structural plasticity, linking extracellular signals with the modulation of dendritic spines, which potentially underlies their ability to influence cognition. Here we review a number of studies that examine how small GTPases are activated and regulated in neurons and furthermore how they can impact actin dynamics, and thus dendritic spine morphology. Elucidating this signalling process is critical for furthering our understanding of the basic mechanisms by which information is encoded in neural circuits but may also provide insight into novel targets for the development of effective therapies to treat cognitive dysfunction seen in a range of neurological disorders.

1. Introduction

Brain function is an emergent property of the connections between neurons. Proper wiring of the brain during development is critical for cognition and memory [1–3], while, conversely, abnormal wiring due to neurological disorder, disease, or brain injury results in dysfunction [4–6]. Understanding how neural circuitry underlies information storage and processing is a fundamental challenge facing modern neuroscience [1, 3]. Though modest inroads into deciphering brain wiring have been made, very little is known about how this wiring contributes to its function. A primary obstacle to progress is the staggering complexity of neural circuits in mammalian brains, trillions of synapses impinge on billions of neurons. One approach to managing this complexity is to limit focus to synapses of a single neurotransmitter type. Glutamatergic synapses are highly plastic, play essential roles in learning, memory, as well as cognition, and comprise the majority of the connections between pyramidal neurons in the forebrain [7–9]. A defining characteristic of these synapses is that they occur at specialized postsynaptic compartments known as dendritic spines (Figures 1(a)–1(c)). These micron-scale, actin-rich structures garnish the dendritic arbour and typically consist of a spine neck and a spine head [10, 11]. It is within the spine head that the protein-rich postsynaptic density (PSD) is found (Figure 1(c)). Embedded in the PSD are

-Methyl-D-aspartic acid (NMDA) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) type glutamate receptors which mediate excitatory synaptic transmission (Figure 1(c)) [10, 12]. Dendritic spines exhibit both transient and enduring lifetimes, persisting from minutes to years in vivo [7, 13]. A myriad of dendritic spine morphologies are observed in the brain and the notion that spine structure is highly correlated with important synaptic properties has become a recurrent theme over the last decade [14, 15]. For example, large dendritic spines are likely to feature large PSDs and make strong connections, while small dendritic spines are indicative of weak connections and may be highly plastic [16]. Accordingly, larger spines tend to persist for long periods of time, whereas smaller, thinner spines are more transient [15, 17]. However, recent data suggests that these phenomena may be different between the cortex and hippocampus, with spines on CA1 hippocampal neurons demonstrating a more rapid turnover as compared to those found in cortical regions [18]. Nevertheless, many reports demonstrate that dendritic spines are not static structures and can rapidly reorganize in response to diverse stimuli including experience-dependent learning [19–21], as well as neuromodulatory and even hormonal signals [22–25]. One key sequela of this structural dynamism is the ability to sample the surrounding neuropil for incident axons [19, 26, 27].

It is widely recognized that dendritic spines are an integral component in circuit formation, but the precise nature of their contribution is still a topic of inquiry and debate. Dendritic spines exhibit a wide spectrum of structural reorganization, from formation and elimination, to more subtle changes in size and shape. These structures are estimated to contain over 1000 different proteins [28], including scaffolds, receptors, adhesion proteins, signalling proteins, F-actin, and cytoskeletal proteins (Figures 2(a) and 2(b)). Current theories postulate that dendritic spines provide a chemical and electrical signalling domain that is partially discrete from their parent dendrite, thus enhancing the computational capacity of the neuron [3], and that they are sufficiently enriched with the molecular components necessary for structural and function modifications [29]. Critically, the development, refinement, and maintenance of telencephalic neural circuits are essential for sensory perception, motor control, cognition, and memory [1, 8, 30, 31]. Importantly, a better understanding of circuit dynamics can provide a bridge between plasticity phenomena observed at the synapse and animal behaviour [8, 9, 18, 19]. Thus it is essential to examine mechanisms that rewire the brain and the current review is dedicated to this purpose. In the past decade, enormous progress has been made in dissecting the molecular mechanisms that contribute to the structural plasticity of dendritic spines [10, 12, 32, 33]. A key molecular determinant of dendritic spine plasticity is the actin cytoskeleton and its regulators. Here we review recent work that has begun to unravel the complex manner in which the family of small GTPases proteins, their regulators, and effectors modulate the actin cytoskeleton to control dendritic spine morphology in support of synaptic function.

2. Actin: A Key Determinant of Dendritic Spine Morphology

The morphological malleability of dendrite spines has been shown to be due to a dynamic actin cytoskeleton [34, 35]. Spines are rich repositories of filamentous and monomeric actin and achieve both stability and dynamism through a turnover process known as treadmilling, where monomers are simultaneously added to the barbed end (at the spine periphery) and removed from the pointed end of the filament (near the spine’s core) [36, 37]. A variety of proteins exhibit control over the actin cytoskeleton and many of these proteins are potent spine morphogens and synaptic modulators [23, 38–42].

Tight control of the actin cytoskeleton is crucial to proper synaptic function. Indeed, actin treadmilling controls the distribution of proteins in the postsynaptic density, including AMPA receptors, as revealed by work employing fluorescence recovery after photobleaching [43]. Thus, understanding the complex signalling pathways impinging on actin filaments is critical for revealing mechanisms underlying normal and pathological synaptic transmission. To this end, much research effort has focused on identifying and characterizing actin regulatory proteins. By considering the positioning of these proteins in signalling cascades relative to the extracellular space and the actin cytoskeleton, they can be organized into hierarchical functional groups including actin binding proteins, small GTPases, and small GTPase regulators and effectors (Figure 2(b)) [32, 44].

3. Small GTPases: Morphological Signalling Hubs in Dendritic Spines

The super family of small GTPases is classified into 5 subfamilies: the Ras, Rho, Rab, Sar1/ARF, and Ran families. Members of this superfamily regulate diverse cellular functions and are often referred to as molecular switches as they exist in binary “on” and “off” states when bound to GTP and GDP, respectively [45, 46]. The present review will be limited to members of Rho and Ras families as these proteins have been most directly linked with actin remodelling. Further, Rho- and Ras-mediated signalling pathways exhibit substantial cross talk that has important implications for spine morphological and functional plasticity. While our understanding of small GTPase control of the actin cytoskeleton has been greatly enhanced by work in nonneuronal cells, the dendritic spine represents a unique microdomain, with distinct functional requirements. As such, we will focus on studies conducted in dendritic spines unless otherwise noted.

Extensive literature links the Rho subfamily to regulation of synaptic actin structure and dynamics [47]. Perhaps best studied among these family members are Rac1 and RhoA, which have potent and opposite effects on the structure of dendritic spines [48]. Overexpression of dominant negative Rac1 leads to reduced spine density in hippocampal slices and dissociated cultures [49, 50], while overexpression of a constitutively active form or RhoA leads to spine loss [51]. It is generally accepted that Rac1 activation stimulates F-actin polymerization and stabilizes dendritic spines through the activation of downstream effectors p21-activated kinase (PAK), LIM-kinase-I (LIMK-I), and the actin binding protein cofilin [52, 53]. Conversely, RhoA activation stimulates F-actin polymerization through its downstream protein kinase ROCK, which in turn directly regulates LIMK-1 phosphorylation in nonneuronal and neuronal cells [54, 55]. Rho GTPases are rapidly and locally activated in spine heads following potentiating stimuli as revealed by two-photon fluorescence lifetime imaging of FRET-based probes [55]. Interestingly, Cdc42, a Rac-related Rho GTPase, and RhoA exhibited differential spatial activity, reflecting their unique contributions to spine morphology regulation blockade of the RhoA signalling cascade inhibited initial spine growth while Cdc42 pathway inhibition prevented sustained spine enlargement. Reinforcing the importance of Rho GTPases in forebrain plasticity is a recent study demonstrating active Rac1-induced spine proliferation in cortical pyramidal neurons as well as enhanced plasticity of visual circuits in monocularly deprived animals [56, 57]. In concordance with this idea, disruption of signalling through Rho/Rac pathways is frequently associated with intellectual disability (ID), a condition characterized by abnormalities in dendritic spine morphology [58–60].

Though most investigations of neuronal structure have focused on the Rho GTPase subfamily, other GTPases have been shown to regulate dendritic spine morphology. Members of the Ras subfamily of small GTPases have also been found to regulate dendritic spine structure and dynamics [61]. One of the first studies to link Ras with structural remodelling of dendritic spines was from a mouse model where a constitutive active form of H-Ras was overexpressed [62]. These mice displayed increased neuronal complexity, which was mirrored in subsequent studies which also revealed abnormal spine formation and connectivity [63, 64]. Consistent with a role in mediating dendritic spine plasticity, it has also been shown that Ras is activated concurrently with spine enlargement induced by uncaging of glutamate in hippocampal neurons [65]. Interestingly, the spatiotemporal dynamics of Ras activation was again different to that of the Rho GTPases, RhoA, and Cdc42, reinforcing the idea that both the temporal activation and the localization of these molecules are critical in determining their impact on cellular function [55, 65, 66]. Prior work in nonneuronal cells has also linked Rap, a member of the Ras subfamily, to cytoskeletal dynamics [67]. In neurons, activation of Rap1 by NMDA receptors in cultured cortical neurons results in a decrease in spine size [41]. Another powerful regulator of small GTPase activity in neuronal cell is the estrogen hormone, 17β-estradiol [68–70]. Interestingly, when mature cortical neurons are acutely exposed to 17β-estradiol, a rapid increase in active Rap1 is seen concurrent with an increase in spine density [25]. Critically, overexpression of RapGAP, a protein that inhibits Rap activation, blocked the effect of 17β-estradiol on spine density [25]. In contrast, overexpression of constitutively active Rap2 causes a loss of dendritic spine density and an increase in the number of filopodia-like protrusions in culture hippocampal neurons [71]. Consistent with these observations in vitro, mice that express a constitutively active Rap2 display fewer dendritic spines and impaired learning [72]. Collectively, these data demonstrate that Rho and Ras family GTPases have potent regulatory effects on dendritic spines which can impact cognitive function.

4. Small GTPase Regulators

GTPases are themselves tightly regulated by two classes of proteins: guanine nucleotide exchange factors (GEFs) which facilitate the binding of GTP by the GTPase and GTPase activating proteins (GAPs) which catalyze the hydrolysis of GTP to GDP. These proteins convey diverse signals from the extracellular space to GTPases and differ in their cellular expression patterns and intracellular distributions. Each GTPase can be regulated by a variety of different GEFs and GAPs, allowing for both signalling diversity and spatial specificity. Through catalyzing the exchange of the GTPase bound GDP to GTP, GEFs serve to activate GTPases. By responding to extracellular signals including neuromodulators and neuronal activity, GEFs can achieve bidirectional control over spine morphology and synaptic strength by acting through their target GTPases.

As RhoA is associated with spine shrinkage and destabilization, GEFs that activate this GTPase have similar effects on dendritic spine morphology. For example, GEF-H1 has been shown to colocalize with the AMPA receptor complex and negatively regulate spine density and length through a RhoA signalling cascade [73]. Similarly, activation of the Eph receptor A4 (EphA4) results in the retraction of dendritic spines, an effect that is dependent on activation of RhoA via its GEF, ephexin1 [74]. Another GEF involved in the destabilization and shrinkage of spines is Epac2. This multidomain Rap1 GEF is activated by cAMP and leads to reduced spine AMPA receptor content, depressed excitatory transmission, and spine destabilization as demonstrated by live imaging studies. Conversely, inhibition of Epac2 leads to spine enlargement and stabilization [23]. Interestingly, rare de novo mutations of the Epac2 gene have been found to be associated with individuals with autism spectrum disorders (ASDs) [75]. The resulting mutant Epac2 proteins displayed altered abilities to activate Rap and when expressed in primary cortical neurons, they resulted in a range of abnormal dendritic spine morphologies [23]. Analysis of Epac2 knockout mice has further revealed deficits in social and communicative behaviours, whereas memory and leaning behaviours are seemingly unaffected [76]. Interestingly, these mice also display reduced dendritic spine turnover in vivo, consistent with what has been shown previously in vitro [23, 76]. However, it is not clear how alterations in dendritic spine plasticity are linked with altered social and communicative behaviours. More recently, using in utero electroporation to express an RNAi construct against Epac2 in a subset of layer 2/3 cortical neurons, a role for Epac2 in maintenance of basal, but not apical, dendrites has been revealed [77]. Interestingly, regulation of basal dendrite formation by Epac2 requires Ras signalling, as a ASD-associated mutant Epac2 protein, which has a reduced ability to bind active Ras, also induces deficits in basal dendrite maintenance [77]. This demonstrates that there can be a level of cross talk between small GTPase systems. Consistent with this, it has recently been shown that the polo-like kinase 2 (Plk2) regulates both Ras and Rap activity through directly influencing the activity regulatory proteins of each small GTPase in response to homeostatic plasticity [78]. These studies demonstrate that the synchronized regulation of both Ras and Rap small GTPases via their GEFs and GAPs plays an important role in homeostatic plasticity and in the maintenance of neuronal morphology [77, 78].

The regulation of Rac by its GEFs has also been well studied. One such GEF is kalirin-7, which is especially unique due to the fact that it is the only known Rac1 GEF expressed in the cortex of adult mice [32]. Overexpression of this kalirin-7 in cortical cultures leads to an increase in spine head area and density. Concomitantly, knockdown of kalirin-7 through an RNAi approach reduces the spine area and density [42]. Interestingly, mice in which the kalirin gene has been deleted exhibit many phenotypes reminiscent of schizophrenia including deficits in working memory as well as reduced dendritic spine density in the cortex [79]. In the hippocampus, the role of kalirin-7 is obscured due to the presence of two other Rac1 GTPases, Tiam1 and β-PIX [32, 52, 80]. Tiam1 is regulated by NMDA receptor activation and has also been implicated in EphB receptor-dependent dendritic spine development [80, 81]. Likewise, the Rac1 GEF β-PIX, a downstream target of NMDA receptors, has been shown to be regulated by CaM kinase kinase and CaM kinase I [52].

Select GAPs have received research attention due to their putative roles in ID. Loss of the Rho-GAP oligophrenin-1, a gene implicated in ID, disrupts activity-dependent synapse and spine maturation [82]. Another such gene is the Ras-GAP SYNGAP1, which can regulate spine morphology through its target Ras as well as downstream signalling to Rac and cofilin [83]. This study illustrates that small GTPase signalling is often complex and nonlinear and may feature cross talk between pathways. Mutations in SYNGAP1 have also been associated with both ID and ASD [84]. Interestingly, an animal model of human SYNGAP1 haploinsufficiency displayed accelerated dendritic spine maturation resulting in disrupted excitatory/inhibitory balance in neural networks [85]. Moreover, these mice also developed persistent behavioural abnormalities. Critically, these effects were most prominent when SYNGAP1 was disrupted during early development and minimal when disrupted in adulthood [85]. More recently, SYNGAP1 has been shown to be phosphorylated by CaMKII, resulting in the trafficking of this protein away from synapses in response to LTP stimulation. Importantly, removal of this GAP protein from synapses is thought to be required for LTP-dependent Ras activation and subsequent AMPA receptor insertion and spine enlargement [86].

A number of extracellular signals are known to exert profound influences over dendritic spine morphology, through the activation of small GTPase pathways. The predominant receptor in regulating dendritic spine plasticity in response to synaptic activity is the NMDA receptor. Following activation of NMDA receptors, dendritic spines undergo a transient increase in calcium concentration [87, 88]. This rise in calcium activates the calcium-sensing calmodulin (CaM): calcium-bound CaM subsequently activates the CaMK family of serine/threonine kinases including CaMKI, CaMKII, and CaMKIV [89]. These kinases go on to phosphorylate a variety of targets involved in spine structural plasticity, including the Rac-GEF kalirin-7, as well as other signalling and scaffolding proteins involved in plasticity [42, 90]. Aside from glutamate, other neurotransmitters have been shown to modulate dendritic spine plasticity. Activation of 5-HT2A receptors in pyramidal neurons increased spine size through a kalirin-7-Rac1-PAK-dependent mechanism [22]. This study is of particular importance as it provides a direct link between serotonergic signalling and dendritic spine morphogenesis, both implicated in schizophrenia. Another important neurotransmitter implicated in the modulation of dendritic spines and small GTPase function is dopamine [91]. For example, treatment of rats with 6-hydroxydopamine, a neurotoxin that selectively ablates dopaminergic and noradrenergic neurons, resulted in a decrease in dendritic spine density in the prelimbic cortex 3 weeks after toxin administration [92]. Intriguingly, cognitive deficits in schizophrenia have been linked with dopamine dysfunction [93, 94] and reduced dendritic spine density has been observed in postmortem tissue taken from schizophrenic patients [95–97]. Results from Solis et al. suggest that there may indeed be a pathological link between dopamine dysfunction and loss of dendritic spine density. A finding consistent with this idea is that treatment with the atypical antipsychotic olanzapine, but not the typical antipsychotic haloperidol, was able to rescue 6-hydroxydopamine-induced spine loss in the rat prefrontal cortex [98]. At the molecular level, activation of the D1/D5 receptors with the selective agonist SKF-38393 leads to spine shrinkage through activation of the Rap GEF Epac2 [23].

Less conventional neuromodulators have also been implicated in the regulation of dendritic spines. Classically defined as a hormone, estrogens have recently come into the spotlight as an important modulator of dendritic spine plasticity [99]. Treatment of primary cortical cultures with 17β-estradiol increased spine density while decreasing the AMPA receptor content of spines. These “silent synapses” were potentiated by activation of NMDA receptors, reminiscent of activity-dependent maturation of silent synapses during development [25]. These effects were mediated by the Rap/AF-6(afadin)/ERK1/2 signalling pathways, as inhibiting or interfering with the actions of these proteins was sufficient to block 17β-estradiol’s effects on spines [25]. Additionally, recent studies have demonstrated that acute treatment of rat cortical cultures with 17β-estradiol leads to phosphorylation of WAVE1 and its subsequent targeting to spines, resulting in the polymerization of actin. This is thought to be required for the formation of immature dendritic protrusions in young cortical neurons [100]. Similar findings have been reported in hippocampal cultured neurons. Here, chronic treatment of hippocampal cultures with 17β-estradiol resulted in an increased number of synapses and increased localization of kalirin-7 to dendritic spines [101]. However, these actions of 17β-estradiol seem to be mediated through the estrogen receptor beta (ERβ) as activation of ERβ but not ERα agonists is able to recapitulate these effects [101–104].

5. Small GTPase Effectors and Actin Binding Proteins

Downstream of small GTPases is a series of effector proteins which convey signals to direct regulators of the actin cytoskeleton. A particularly well-described family of effectors of the Rho GTPases Rac1 and Cdc42 are the p21-activated kinases (PAKs) [105] and the Rho kinases (ROCK) [106]. The PAKs are critical for spine morphogenesis and synaptic structure, particularly in the cortex [107]. More recently, a series of studies has explored the consequences of PAK and ROCK knockout in the forebrain. Deletion of PAK1 or ROCK-2 results in the loss of F-actin from spines [108, 109]. Further, both knockout animals demonstrated deficits in hippocampal LTP, highlighting the importance of these Rho kinases for synaptic plasticity. Intriguingly, codeletion of PAK1 and PAK3 resulted in a more severe structural and functional phenotype the PAK1/3 knockouts showed impaired bidirectional plasticity in the hippocampus, deficits in learning and memory, and gross structural abnormalities in the forebrain [110]. Shared features of these Rho kinase knockout animals include disruption of the kinase cascade downstream of the Rho GTPases, a release of cofilin from inhibition, and a subsequent loss of F-actin from dendritic spines.

More insight into the effects of PAK and ROCK family members on the actin cytoskeleton is provided by work examining LIM-kinase (LIMK). Active Pak1 can phosphorylate LIMK-1 which in turn inhibits cofilin activity [111]. As a result, genetic ablation of LIMK-1 results in elevated cofilin activity, aberrant spine morphology, and enhanced LTP [53]. Intriguingly, recent work has identified a new mechanism of regulation for LIMK-1 via lipid modification [24]. N-terminal palmitoylation of LIMK-1 targets the kinase to dendritic spines and is necessary for activity-dependent spine growth. Palmitoylation is emerging as a critical modulator of spiny synapse function [112] small GTPases themselves are targeted to various microdomains through dynamic palmitoylation [113–115], though the implications of this signalling have yet to be explored thoroughly in neurons.

As their name suggests, actin binding proteins directly influence actin dynamics through nucleating, stabilizing, or severing actin filaments. Members of the Wiskott-Aldrich syndrome protein (WASP) family bind both monomeric and filamentous actin [116] and are relieved from autoinhibition by Rho GTPases [117]. N-WASP, a brain enriched WASP, appears to be critical for spine and excitatory synapse formation [40]. Small GTPases also exert control over a similar WASP-family verprolin-homologous protein (WAVE) family. These proteins play a role in spine maintenance [118] and formation [119] deficient WAVE1 expression is accompanied by spatial memory deficits in mice [120].

The Arp2/Arp3 complex is a well-studied actin nucleator and facilitator of actin branching [121]. The Arp2/Arp3 complex is downstream of Rho family GTPases, WASP, and WAVE proteins [122] and is likely to be instrumental in dendritic spine remodelling during spine growth [123]. Inhibition of the Arp2/Arp3 complex by protein kinase C binding protein (PICK1) is necessary for spine shrinkage during LTD [124]. More recently, PICK1 has been shown to signal downstream of AMPARs to inactivate Cdc42 [125]. As mentioned above, cofilin is another critical determinant of actin skeletal dynamics and competes with the Arp2/Arp3 complex by severing and debranching actin filaments [126]. Though prolonged cofilin activation promotes a reduction in spine size [127], it appears that a transient burst of cofilin activity is required for spine growth during chemically induced LTP [128]. A recent review of small GTPase control of the actin cytoskeleton covers these pathways in greater detail [44].

Among the list of Rap effectors are a number of actin cytoskeleton regulators. Rap1 binds directly to afadin, also known as AF-6 [129] which is a multidomain scaffolding protein instrumental in cell-cell adhesion [130]. Indeed, active Rap was responsible for the subcellular targeting of afadin in neurons under basal and after NMDA receptor activation [41, 131]. Intriguingly, following activation of NMDA receptors, afadin translocates to both synapses and the nucleus in a time-dependent manner. At synapses, afadin is required for activity-dependent and Rap-dependent spine modifications [41], whereas in the nucleus, afadin is required for the time-dependent phosphorylation of H3 histones, suggesting a potential role in regulating activity-dependent gene transcription [131]. Afadin also directly interacts with the actin-polymerizing protein profilin [129] and with the adhesion protein, N-cadherin [132], and the AMPA receptor subunit, GluA2 [133]. Consistent with these interactions, afadin is required for linking N-cadherin with the kalirin-7, therefore allowing regulation of Rac activation and linking N-cadherin with the dynamic modulation of dendritic spine morphology [132]. Moreover, knockdown of afadin using an RNAi approach results in a loss of dendritic architecture, dendritic spine density, and AMPA receptor mediated transmission [133]. Rap has also been shown to interact with and activate the Rac-GEFs Vav2 and Tiam1 [134], providing another example of small GTPase pathway cross talk.

Thus, a stereotyped spine-morphogenic signalling cascade begins with an extracellular signal that is conveyed to GEFs or GAPs that control small GTPase activity, which in turn influences actin binding proteins through small GTPase effectors. It is now emerging that, in addition to activity-dependent signalling via NMDA receptors, other extracellular signals, including neuromodulators [22, 23] and neurosteroids, may act via similar pathways.

6. Conclusions

Understanding how neurons encode information is a fundamental challenge in determining how we store and retrieve information about our surrounds, allowing us to adapt at a behavioural level. Growing evidence indicates that a key cellular correlate of information encoding is the regulation of dendritic spines and thus excitatory synaptic connections [1, 3]. In this review, we have presented recent evidence that places small GTPase proteins as an important intermediate between extracellular signals and the actin cytoskeleton, allowing for the regulation of synapse structure and function. Important advances have been made in our understanding of the molecules that exert a tight regulation of small GTPase function in neurons [32, 61], and it is also emerging that these molecules have unique spatiotemporal dynamics that are critical to their cellular functions [55, 65, 66]. Our current understanding suggests that small GTPases can act independently, via their effectors, directly regulating the actin cytoskeleton, to exert effects of dendritic spine structure and numbers, as well as on synaptic function. However, several studies have now demonstrated that multiple small GTPases can act in cooperation to bring about changes in dendritic spine, or on the maintenance of overall neuronal morphology [77, 78]. Moreover, it is also emerging that a wide range of extracellular signals also signal via small GTPases to exert morphogenic actions [22, 25, 42, 47, 50, 65, 74, 80, 81]. Many of these extracellular signals can activate the same small GTPases, suggesting that within a single neuron multiple factors can modulate the activity of a single subfamily of small GTPase. Elucidating how neurons integrate multiple signals and how they in turn summate impacting the function of the cell and ultimately affect cognition is fast emerging as another challenge. It is likely that gaining a greater understanding of the spatiotemporal dynamics of small GTPase signalling will provide an insight into how neurons handle this amount of information. In addition, further determining the complex manner in which regulators of small GTPase signalling interact and determining the nonlinear manner in which multiple pathways are activated by the same signals will provide a more comprehensive understanding of how multiple factors regulate spine plasticity.

It is also of note that multiple neurodevelopmental, psychiatric, and neurodegenerative disorders have been strongly associated with disruptions of neural circuits [6, 135]. Indeed, numerous neuropathological postmortem studies have strongly linked abnormal spine morphology with the pathogenesis of a number of neuropsychiatric, neurodevelopmental, and neurodegenerative disorders [135, 136], such as ID [137], fragile-X [138], Down’s syndrome [139], autism spectrum disorders (ASDs) [140–142], schizophrenia [96, 143], depression [144], and Alzheimer’s disease [145, 146]. It is currently posited that dendritic spine dysmorphogenesis can lead to defective or excessive synapse function and connectivity, resulting in disruptions in neural circuitry. This topic has recently been reviewed in depth [2, 6, 135]. Dysregulation of the complex mechanisms that control dendritic spine structure and function may contribute to these synaptic irregularities. Understanding the cellular mechanisms by which dendritic spine morphogenesis occurs will expand not only our knowledge of normal brain function, but that of abnormal brain function as well. Though a greater understanding of the cellular mechanisms that underpin cortical plasticity will be required, harnessing structural plasticity may offer a powerful future therapeutic avenue for neuropathologies.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

Research described in the text has been funded by grants from the Medical Research Council (MRC), UK, Royal Society, UK, Brain and Behaviour Foundation (formally NARSAD), Psychiatric Research Trust to Deepak P. Srivastava, and American Heart Association (AHA) to Deepak P. Srivastava and Kevin M. Woolfrey.

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Copyright

Copyright © 2016 Kevin M. Woolfrey and Deepak P. Srivastava. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


2. The Model

A compartmental model based on a reconstructed adult rat CA1 pyramidal cell is developed as an extension to the model of Migliore (Migliore, Ferrante, & Ascoli, 2005: cell number 5038804 see Figure 1a). Full model details are given in the appendix. The morphology is divided into 337 electrical compartments (not counting spines). Spatially distributed ion channels consist of the following families: fast sodium (Na), delayed rectifier potassium (K), A-type K, h-current, HVA (putatively R-type) calcium (Ca), and Ca-activated, mAHP K. Na and KDR are distributed throughout the cell, but Na has a higher density in the axon and a lower density in the dendrites it also has slower recovery from inactivation in the dendrites. KA and h channels both increase in density with distance from the soma, with a saturating density beyond 350 m. Voltage-gated calcium channels (VGCCs: HVA R-type Ca) are distributed throughout the dendrites and spines with a fixed density. Ion channel model details are given in the appendix.

This is a restricted set of all the ion channels identified in CA1 PC membrane, but it is sufficient to capture key features of the electrical excitability of the cell. Two distinct features are the ease of spread of signals throughout the dendrites (the electrical compactness) and the ability to generate nonlinear, threshold-gated signals, namely, sodium and calcium spikes in the dendrites. Both features can be under the control of inhibition and neuromodulation in a single neuron so that different cell excitability may be obtained in different behavioral conditions. Different cell configurations, in terms of membrane excitability, are considered. These are obtained by altering either passive membrane properties or active channel densities. Specific configurations are detailed in section 3. The base configuration (from which individual parameters may be altered) includes the passive properties: Rm=28 K ⁠ .cm 2 , Ra=150 ⁠ .cm, Cm=1 F/cm 2 . Base active properties are listed in the appendix.

Particularly powerful controllers of voltage spread in the dendrites are the A-type K channels and anomalous rectifier h channels. Both channel types increase in density away from the soma and may strongly attenuate the electrical excitability of the membrane (see Figure 1b), restricting propagation of backpropagating action potentials (bAPs) and the generation and propagation of dendritic spikes. Lowering the KA density gives a much more electrically compact cell in which bAPs propagate with little attenuation (see Figure 1c). The h-current also is known to have a controlling role in calcium spike generation in distal dendrites (Tsay, Dudman, & Siegelbaum, 2007).

Calcium concentration is modeled in all compartments. Calcium entry is via VGCCs and, in spine heads, via NMDA channels. Calcium decay is modeled as an instantaneous buffer, which limits the peak free calcium obtained, and an exponential decay to baseline due to slower buffering and extrusion across the membrane by calcium pumps. The magnitude and time course of typical spine head calcium transients are based on the data of Sabatini, Oertner, and Svoboda (2002). According to those data, extrusion of calcium is quite fast, so that calcium transients approximately follow the driving currents through NMDA channels and VGCCs.

Excitatory synapses are made onto two-compartment (neck + head) spines that are added to dendritic branches at random locations. To minimize computation times, only the maximum number of activated spines for a simulation is added in a layer, which is taken to be 500 in each of stratum radiatum (SR), stratum oriens (SO), and stratum lacunosum-moleculare (SLM). An example random distribution of spines (and associated synapses) in each layer is shown in Figure 1a.

Excitation is mediated through colocalized AMPA and NMDA currents in the spine head. The AMPA conductance is modeled as a dual exponential waveform, with a rise time of 0.5 ms and a fall time of 3 ms. Peak AMPA conductance is set to give isolated spine head EPSPs of the order of 10 mV (Palmer & Stuart, 2009). The NMDA conductance is also modeled as a dual exponential waveform, with a rise time of 3 ms and a fall time of 100 ms. Peak NMDA conductance is voltage sensitive due to magnesium block. A percentage (10%) of the NMDA current is carried by calcium ions (Bloodgood & Sabatini, 2007). The reversal potential for both AMPA and NMDA currents is 0 mV. The ratio of NMDA to AMPA peak conductance is set slightly larger in SLM to reflect the known greater contribution of NMDA currents there (Otmakhova & Lisman, 1998).

The model was simulated using the NEURON software environment (Carnevale & Hines, 2006) and the source code is available on ModelDB (senselab.med.yale.edu/senselab/modeldb, accession number 154732).


Discussion

The experiments presented here provide the first observations of SK channel activation in spines and dendrites of cortical pyramidal neurons during bAPs. We find that during bAP SK channels regulate calcium influx into spines and dendrites in a distance-dependent manner, with a greater impact at distal dendritic locations. Furthermore, we show that R-type VDCCs exhibit tight and specific control of SK channel activation in spines during bAPs. In contrast, coupling of SK channels at the soma to VDCCs is much less specific, with all known VDCCs, except R-type channels, playing a role in SK activation during the mAHP.

SK channel activation in dendrites and spines during action potentials

The observed increase in bAP-evoked calcium influx during SK channel block is presumably due to enhanced activation of VDCCs in spines and dendrites following an increase in amplitude or broadening of bAPs. Consistent with this idea, it has recently been observed that SK channels can control bAP amplitude in cerebellar Purkinje neurons (Ohtsuki et al., 2012). The observation that dendritic SK channels can influence bAPs is surprising given that apamin had no impact on the somatic AP waveform, but may be due to the tighter coupling of SK channels in spines and dendrites to their calcium source, speeding their activation compared with SK channels at the soma. Previous studies indicate that SK channels can activate within a millisecond during rapid changes in intracellular calcium at room temperature (Xia et al., 1998), and would be expected to activate even faster at physiological temperatures. In addition, one might expect SK channels to have a greater impact on bAPs due to their increased duration compared with somatic APs (Stuart et al., 1997). Consistent with this idea, the impact of SK channels on bAP-evoked calcium transients was greatest at distal basal dendritic locations where bAP duration is longest (Kampa and Stuart, 2006 but see Antic, 2003). The distance-dependent impact of apamin on bAP-evoked calcium transients could also be due to differences in the expression of SK or R-type calcium channels. Finally, we observed that blocking SK channels caused a greater increase in bAP-evoked calcium influx in spines compared with dendrites. While this effect may also be due to differences in the expression of SK or R-type calcium channels, the larger surface-to-volume ratio of spines compared with dendrites is also likely to contribute (Sabatini et al., 2002).

What possible function might SK channels in spines and dendrites serve when activated by bAPs? The capacity of SK channels in spines and dendrites to constrain the amplitude and/or width of bAPs would be expected to influence NMDA receptor activation during EPSP—AP pairing. This effect would be greatest at distal dendritic locations, where NMDA receptor activation during synaptic events is most pronounced (Branco and Häusser, 2011). Given that changes in synaptic strength during spike timing-dependent plasticity (STDP) are dependent on NMDA receptor activation (Markram et al., 1997), the impact of SK channels on bAP time course may play a role in setting the STDP time window (Froemke et al., 2005 Letzkus et al., 2006), possibly increasing the fidelity of coincidence detection during STDP, particularly at distal dendritic locations.

As SK channels play an important role in regulating dendritic calcium dynamics, modulation of these channels would be expected to modify neuronal excitability and synaptic plasticity. Consistent with this idea, downregulation of SK channels following activation of M1 muscarinic or β-adrenoceptor receptors in CA1 pyramidal (Buchanan et al., 2010 Giessel and Sabatini, 2010) and lateral amygdala neurons (Faber et al., 2008), respectively, increases synaptic strength. Conversely, changes in synaptic strength during synaptic plasticity have been shown to be associated with changes in SK channel function (Lin et al., 2008 Ohtsuki et al., 2012). Given the specific coupling of R-type VDCCs to SK channels in spines as shown here and previously (Bloodgood and Sabatini, 2007), modulation of R-type VDCCs following activation of D2 dopamine receptors (Higley and Sabatini, 2010) could provide another mechanism in which SK channel activation in spines may be regulated. Recent evidence indicates that the inhibition of individual dendritic spines can modulate spine calcium influx during bAPs in a selective manner (Chiu et al., 2013). These data suggest that SK channel modulation in individual spines could selectively influence calcium influx into only those spines during bAPs, although this effect may be dominated by the progressive recruitment of SK channels distributed along the entire length of a dendritic branch. Consistent with this idea, the impact of SK channel activation on bAP calcium influx increased with distance from the soma (Fig. 1E,F).

Calcium sources for SK channel activation in dendritic spines

While there is evidence that R-type VDCCs control SK channel activation in spines during EPSP-like events evoked by glutamate uncaging (Bloodgood and Sabatini, 2007), other studies have suggested that calcium influx through NMDA receptors contributes to SK channel activation during EPSPs (Faber et al., 2005 Ngo-Anh et al., 2005 Faber, 2010). Consistent with this latter idea, NMDA receptors and SK channels are colocalized within the postsynaptic density in CA1 pyramidal neurons (Lin et al., 2008). Because SK channels in spines modulate NMDA receptor activation (Faber et al., 2005 Ngo-Anh et al., 2005 Faber, 2010), which provides the main calcium source during synaptic activation (Kovalchuk et al., 2000 Sabatini et al., 2002), identifying the calcium source driving SK channel activation in spines during EPSPs is complicated. This complication does not exist in our experiments as NMDA receptor activation during bAPs is negligible (Koester and Sakmann, 2000 Sabatini and Svoboda, 2000 Bloodgood and Sabatini, 2007). During bAPs, we find that the inhibition of solely R-type VDCCs is sufficient to block SK channel activation. Moreover, the inhibition of N- and P/Q-type VDCCs, which are expressed in spines along with R-type VDCCs and led to similar calcium influx during bAPs, did not influence SK channel activation. This indicates tight and specific coupling between R-type VDCCs and SK channels within the spine head. This conclusion is similar to that made previously during EPSP-like events evoked by glutamate uncaging in spines from CA1 pyramidal neurons (Bloodgood and Sabatini, 2007). These data suggest that R-type VDCCs and SK channels in the spine head are coupled in “nanodomains,” consistent with previous observations showing that only high concentrations of the fast, high-affinity calcium buffer BAPTA are able to interfere with SK channel activation in spines during EPSPs (Ngo-Anh et al., 2005).

Calcium sources for SK channel activation during the mAHP

SK channels contribute to the mAHP in many neuronal cell types, including L5 pyramidal neurons (Schwindt et al., 1988 Sah and McLachlan, 1991 Faber and Sah, 2002 Womack and Khodakhah, 2003), although this is controversial in CA1 pyramidal neurons (Stocker et al., 1999 Gu et al., 2008). The ability of low concentrations of both fast (OGB-1) and slow (EGTA) calcium buffers to inhibit the mAHP in L5 cortical pyramidal neurons suggests that the calcium influx driving activation of somatic SK channels is working within a microdomain rather than a nanodomain (Neher, 1998 Augustine et al., 2003 Eggermann et al., 2012), with a coupling distance greater than ∼150 nm. Consistent with this idea, we show that the SK channel-dependent component of the mAHP in L5 neurons is controlled by all known VDCC subtypes except R-type VDCCs, which are not expressed at the soma. The coupling between somatic SK channels and their calcium source in L5 neurons differs from that in other cell types, where the calcium source for SK channel activation during the mAHP has been linked to specific VDCC subtypes. For example, in midbrain dopaminergic neuron activation of SK channels during the mAHP is solely dependent on T-type VDCCs (Wolfart and Roeper, 2002), whereas only L-type channels are coupled to somatic SK channels in hippocampal pyramidal neurons (Marrion and Tavalin, 1998). The reasons for this difference between neuronal cell types, and why it is that SK channels are weakly coupled to multiple calcium sources in L5 neurons is unclear. Finally, it is worth noting that our observation that low concentrations of the calcium indicator OGB-1 blocks the mAHP, increasing firing rate and promoting burst firing, raises the concern that the use of high-affinity calcium indicators to investigate network activity (Garaschuk et al., 2006) may inadvertently influence neuronal excitability and thereby network dynamics.

In conclusion, we show that SK channels in spines and dendrites are activated by bAPs and act to constrain dendritic and spine calcium influx in a distance-dependent manner. This effect of SK channels would be expected to influence STDP, particularly at distal dendritic locations. Furthermore, we provide evidence that SK channels in spines and dendrites are strongly coupled to their calcium source, forming nanodomains with R-type VDCCs. In contrast, SK channels at the soma of L5 cortical pyramidal neurons are weakly coupled to multiple calcium sources, forming microdomains with all known VDCCs except R-type channels. These findings provide evidence for heterogeneous and location-dependent coupling of SK channels to VDCCs within the same neuronal cell type. Such exquisite compartmentalization exemplifies the contrasting role calcium plays in regulating neuronal excitability at different cellular locations even within the same neuron.


Conclusions

In summary, we created a series of models incorporating biochemistry and electrophysiology that unify observations in various SCAs. These models employ several novel concepts and approaches and provide a framework for the study not only of IP3R1-associated ataxias, but of various SCAs involving mutations of other molecules in the model, such as potassium channels [65, 79, 101, 102] and calcium channels [29, 76, 77, 103].

Model results indicate that, in mouse models of various ataxias associated with activity of the calcium channel IP3R1, ICpeptides may be used to stabilize intracellular calcium concentration. Further, restoration of normal calcium release in the model does not alter fine-tuning of coincidence detection suggested by Brown et al. [42]. The hypothesis of IP3R1 supersensitivity in SCA1 is supported by simulation results. Even more, IP3R1 downregulation experimentally observed in SCA1 mice may partially compensate for the receptor’s supersensitivity. Homer and MyoVa downregulation are further compensatory. However, downregulation of calcium buffer proteins accelerates pathology. The model demonstrates that IP3-mediated calcium release in the Purkinje neuron could activate voltage-gated KCa channels, namely BK and IK, and provides insight into the interplay between IP3R1 sensitivity and abundance in the function and dysfunction of the Purkinje cell. Results help to explain experimental findings in mice, and can be used to make predictions for further experiments, which may ultimately be translated to ataxic individuals with reduced IP3R1 protein levels or increased sensitivity. IP3R1 abundance and sensitivity are components involved in calcium signaling, but by no means the only factors involved in the signaling systems of these SCAs.


Geometry of Dendritic Spines Affects Calcium Dynamics in Hippocampal Neurons: Theory and Experiments

The role of dendritic spine morphology in the regulation of the spatiotemporal distribution of free intracellular calcium concentration ([Ca 2+ ]i) was examined in a unique axial-symmetrical model that focuses on spine–dendrite interactions, and the simulations of the model were compared with the behavior of real dendritic spines in cultured hippocampal neurons. A set of nonlinear differential equations describes the behavior of a spherical dendritic spine head, linked to a dendrite via a cylindrical spine neck. Mechanisms for handling of calcium (including internal stores, buffers, and efflux pathways) are placed in both the dendrites and spines. In response to a calcium surge, the magnitude and time course of the response in both the spine and the parent dendrite vary as a function of the length of the spine neck such that a short neck increases the magnitude of the response in the dendrite and speeds up the recovery in the spine head. The generality of the model, originally constructed for a case of release of calcium from stores, was tested in simulations of fast calcium influx through membrane channels and verified the impact of spine neck on calcium dynamics. Spatiotemporal distributions of [Ca 2+ ]i, measured in individual dendritic spines of cultured hippocampal neurons injected with Calcium Green-1, were monitored with a confocal laser scanning microscope. Line scans of spines and dendrites at a <1-ms time resolution reveal simultaneous transient rises in [Ca 2+ ]i in spines and their parent dendrites after application of caffeine or during spontaneous calcium transients associated with synaptic or action potential discharges. The magnitude of responses in the individual compartments, spine–dendrite disparity, and the temporal distribution of [Ca 2+ ]i were different for spines with short and long necks, with the latter being more independent of the dendrite, in agreement with prediction of the model.


MATERIALS AND METHODS

PBMC isolation and DC generation

After written consent from platelet donors, leukoreduction chambers of apheresis, performed in the Blood Bank from Hospital Oswaldo Cruz (São Paulo, SP, Brazil), were collected. The Institutional Ethics Committee of the Institute of Biomedical Sciences approved the protocol. PBMCs from those chambers were separated by centrifugation over Ficoll-Paque (GE Healthcare, Uppsala, Sweden). PBMCs were resuspended in AIM V medium (Gibco, Grand Island, NY, USA), seeded in 75 cm 2 cell-culture flasks, and incubated overnight at 37°C and 5% CO2. After overnight incubation, nonadherent cells were removed, the medium was replaced, and GM-CSF (50 ng/ml PeproTech, Rocky Hill, NJ, USA) and IL-4 (50 ng/ml PeproTech) were added. After 5 days, the cells received a maturation stimulus with TNF-α (50 ng/ml PeproTech). mDCs were obtained 48 h after activation. For phenotypic characterization of the cells during the culture, Mo were harvested after nonadherent cell removal at Day 0, and iDCs were harvest before the maturation stimulus, at Day 5.

Determination of the membrane phenotype of DCs

Membrane phenotype of the cells during differentiation and maturation of DCs was determined by flow cytometry. For each condition, 2 × 10 5 cells were labeled with fluorescence-labeled antibodies specific for the different membrane molecules (HLA-DR, CD14, CD83, CD80, CD86, CD11c BD Biosciences, San Jose, CA, USA) and analyzed in a FACSCalibur cytometer (BD Biosciences) using the FlowJo software (Version 7.2.4 Tree Star, Ashland, OR, USA). Dead cells were excluded from the analysis by using the LIVE/DEAD Fixable Dead Cell Stain Kit (Invitrogen, Carlsbad, CA, USA). The RFI of the surface markers was calculated by dividing the MFI of the labeled group by the MFI of the unlabeled group.

Transfection of iDCs with siRNA

For each group, 5 μl iMAX (Invitrogen) was diluted in 95 μl Opti-MEM media (Invitrogen) and 1.5 μl of a 50-mM siRNA solution was diluted in 98.5 μl Opti-MEM. Then, both solutions were mixed, incubated at room temperature for 30 min, and placed in a six-well plate. iDCs were harvest and resuspended in AIM V medium, supplemented with IL-4 and GM-CSF. For each treatment, 1 × 10 6 cells (which were resuspended in 1.3 mL medium) were seeded in a six-well plate, pretreated with 200 μl siRNA complex. Cells were activated with TNF-α, 4 h after transfection and analyzed after 48 h.

CD83 blocking

To block membrane CD83 in mDCs, 100 ng CD83 mAb (HB15e clone BD Biosciences) were added to 5 × 10 4 cells. After 20 min of incubation at 4°C, DCs were washed twice to remove antibody excess. IgG antibodies were used as control.

MDC staining

mDCs were harvest and resuspended at a concentration of 1 × 10 6 cells/mL in PBS, supplemented with 0.5% of BSA and 5 mM CellTracker Red CMPTX (Invitrogen). The cells were incubated at 37°C for 15 min, washed twice, and resuspended in the calcium assay buffer (composed of 1 mM CaCl2, 130 mM NaCl, 4.6 mM KCl, 5 mM glucose, and 20 mM HEPES) or a KEGTA solution (composed of 10 mM NaCl, 130 mM KCl, 20 mM HEPES, 10 mM EGTA, and 10 mM Na2CO3 Sigma, St. Louis, MO, USA).

Fluo-4-AM loading

T cells were isolated from nonadherent PBMCs by negative selection with magnetic beads from the Pan T Cell Isolation Kit (Miltenyi Biotec, Bergisch Gladbach, Germany), according to the manufacturerˈs instructions. After purification, T cells were resuspended at 1 × 10 7 cells/mL in PBS, supplemented with 0.5% of BSA, incubated with 1μM Fluo-4-AM (Invitrogen) for 30 min at 28°C, washed twice, and resuspended in the calcium assay buffer at 1 × 10 6 cells/mL.

Calcium mobilization assay by flow cytometry

Fluorescence of T cells stained with Fluo-4-AM was acquired by flow cytometry for 60 s without stimulus. Then, allogeneic DCs stained with CellTracker Red CMPTX were added, and the cells were acquired for an additional 240 s. Ionomycin (Invitrogen) was used as a positive control. Using the FlowJo software (Version 7.2.4 Tree Star), changes in the median of Fluo-4-AM fluorescence in the T cells were calculated.

Calcium mobilization assay by fluorescence and confocal microscopy

DCs stained with CellTracker Red CMPTX (Invitrogen) were seeded in a Petri dish, and allogeneic T cells were added while acquiring the video in the fluorescence microscope Nikon Eclipse Ti-S (Nikon, Melville, NY, USA) with NIS-Elements AR software (Nikon) or in the multifoton Zeiss LSM 780 microscope (Zeiss, Oberkochen, Germany) with ZEN confocal software (Zeiss). Images were acquired for at least 10 min.

T cell proliferation assay

Purified T cells were labeled with 5 μM CFSE (Invitrogen) and cultivated in culture in a 96-well U-bottom plate, with allogeneic mDCs at a 10:1 lymphocyte:DC ratio. After 5 days, the cells were harvest, stained with anti-CD3 antibody (BD Biosciences), and analyzed by flow cytometry. T cell proliferation was assessed by CFSE dilution.

Statistical analysis

Statistical analyses were performed using GraphPad Prism (GraphPad Software, La Jolla, CA, USA). The effect of anti-CD83 antibody was analyzed by paired t-test (*P<0.05 **P<0.01). Comparisons among results obtained from the status of DC differentiation and from CD83 knockdown experiments were performed by one-way ANOVA with the Tukey post-test (*P<0.05 **P<0.01). All graphs show mean ± sem .


RESULTS AND DISCUSSION

DCs predominantly express STIM2 not STIM1

Previously, we have demonstrated SOCE through CRAC channels in mature and immature DCs [1]. To determine the molecular components of ICRAC in these cells, we analyzed purified DCs (Fig. 1A and B) for expression of STIM and Orai proteins. Using RT-PCR, we detected transcripts for STIM1, STIM2, and Orai1–3 (data not shown). To confirm protein expression, we used DC lysates to perform Western blot analysis (Figs. 1 and 2). Surprisingly, we found that compared with splenic T cells, DCs express low levels of STIM1 (detected as a single band in DCs and brain and a doublet in T cells at ∼85 kDa Fig. 1C). In contrast, we found robust expression of STIM2 (detected as a single band at ∼100 kDa Fig. 1C) in these cells.

Expression of STIM proteins in murine DCs. (A) Bright-field image of BM-derived DCs with typical dendritic processes (original scale bar, 20 μm). (B) Flow cytometric analysis shows that enriched cultures were >90% positive for the DC marker, CD11c. (C) Western blots showing the expression of STIM1 and (D) STIM2 in DCs. Whole cell lysates (30 μg) were used for each sample. Whole mouse brain and mouse T cells were used as positive controls. (E) The blots were stripped and reprobed with β-actin as a loading control. BMDC, BM-derived DC.

Expression of Orai proteins in DCs. Western blots showing the expression of (A) Orai1, (B) Orai2, and (C) Orai3 in DCs and T cells. Whole cell lysates (30 μg) were used for each sample. Whole mouse brain, T cells, and Jurkat T cells were used as positive controls. The blots were stripped and reprobed with β-actin as a loading control. *Monomer and dimer of Orai proteins.

Similarly, we found differential protein expression of the Orai isoforms (Fig. 2A–C). Notably, DCs express significantly lower levels of Orai1 and Orai3 compared with T cells. For Orai1, a single immunoreactive band was detected at ∼45 kDa (Fig. 2A), which is likely a glycosylated form of the monomeric Orai1 protein, as demonstrated by Gwack and co-workers [18]. To confirm this result, we performed immunoblotting on lysates from myc-Orai-1-expressing HEK293 cells (Supplemental Fig. 1A). This analysis revealed a prominent 45-kDa band. Orai3 was detected as a monomer at ∼30 kDa and a more prominent band at ∼60 kDa, which likely represents a dimer (Fig. 2C). This interpretation is supported by our analysis of Orai3-expressing HEK293 cells (Supplemental Fig. 1C), in which treatment with DTT produced a marked increase in the ∼30-kDa monomeric band.

In contrast to the other Orai proteins, DCs express relatively high levels of Orai2 (Fig. 2B), detected as a monomer at ∼28 kDa and a more prominent band at ∼56 kDa representing a dimer. Analysis of Orai2-expressing HEK293 cells revealed a similar immunoblot pattern (Supplemental Fig. 1C). Further, we saw similar bands with a different commercial anti-Orai2 antibody (Alomone Labs data not shown). We also confirmed expression of Orai2 by immunocytochemistry (Supplemental Fig. 2B). A previous study has identified two splice variants of murine Orai2 associated with functional CRAC channels [22]. Using specific primers, we detected both of these splice variants—Orai2 small and Orai2 large—in BM-derived and splenic DCs (Supplemental Fig. 2A).

As functional support for Orai2 in DCs, we explored sensitivity of SOCE to 2-APB. Recent studies have demonstrated that 2-APB differentially blocks SOCE and ICRAC mediated by the different Orai isoforms 2-APB (50 μM) completely inhibits Orai1 and Orai2 but does not affect Orai3 [23, 24]. Although these studies were performed with heterologously expressed channels, this differential sensitivity to 2-APB, nonetheless, may prove useful in distinguishing the role of Orai isoforms in native tissues. We found that 2-APB (50 μM) produced a near 100% inhibition of SOCE (n=250) and an ∼90% block of ICRAC (–100 mV n=8 Supplemental Fig. 3). Furthermore, in the absence of store depletion, 2-APB produces a weak activation of Orai1 and a robust activation of Orai3 but has no effect on Orai2 [24]. Interestingly, in DCs, 2-APB application failed to produce a Ca 2+ rise (Supplemental Fig. 3C n=30). Moreover, we did not detect any whole cell currents following 2-APB application (Supplemental Fig. 3D n=5). These data are consistent with a primary role for Orai2 in SOCE and ICRAC in DCs.

Tg-induced store depletion promotes oligomerization of STIM2

Recent evidence has shown that aggregation of STIM1 is essential for CRAC channel activation in Jurkat T cells [9]. We therefore tested whether there is an aggregation of STIM1 or alternatively, STIM2 in DCs in response to store depletion. Fig. 3A shows that DCs exhibit diffuse immunostaining for STIM1 (consistent with the low expression of STIM1 in these cells), and this was unaltered by treatment with Tg (2 μM for 10 min). We found that same anti-STIM1 antibody produced marked immunostaining of T cells, confirming the functionality of the antibody (Supplemental Fig. 4A). In contrast to STIM1, Tg produced a punctate pattern of STIM2 immunostaining (Fig. 4B). Thus, STIM2 rather than STIM1 aggregates upon store depletion in DCs.

Tg induces aggregation of STIM2. (A) Immunofluorescence labeling of DCs for (A) STIM1 and (B) STIM2 under control conditions (unstimulated) and after Tg treatment (Stimulated 2 μM Tg for 10 min). Fixed cells were permeabilized and stained with STIM1 and STIM2 antibody followed by a secondary antibody (FITC-conjugated), which alone, produced negligible staining (see Supplemental Fig. 2B).

Stim2 and Orai2 interact upon store depletion

Store depletion is known to produce physical interactions between native and heterologously expressed STIM1 and Orai1 [10–12]. Our results showing STIM2 oligomerization and the predominant expression of Orai2 in DCs led us to examine further the possibility of interactions between STIM2 and Orai2 in response to store depletion. We found that under basal conditions, STIM2 coimmunoprecipitated with Orai2, and this association increased markedly following treatment with Tg (Fig. 4A and B). Surprisingly, we did not detect any STIM1 when we immunoprecipitated with an anti-Orai2 (Fig. 4A) or anti-STIM2 antibody (Fig. 4B). Significantly, STIM2 and Orai2 did not coimmunoprecipitate with STIM1 (using anti-STIM1 antibody Fig. 4C). Although Orai1 was present in the immunoprecipitation complex, its levels were not altered by Tg treatment (Fig. 4C). These findings thus rule out the possibility of STIM1 participating in the robust increase of STIM2 and Orai2 association following store depletion. Furthermore, little Orai1 or Orai3 was found to associate with Orai2 in control and Tg-treated DCs. Taken together, these data support the hypothesis that store depletion in DCs triggers oligomerization of STIM2, which in turn, interacts with Orai2.

Tg induces the association of STIM2 and Orai2 but not STIM1. (A and B) Coimmunoprecipitation showing the enhanced association between STIM2 with Orai2 upon Tg treatment. Although detected in the immunoprecipitation (IP) complex, Orai1 levels are not increased by Tg treatment. (C) STIM2 and Orai2 are not present in the coimmunoprecipitation using a STIM1 antibody. Moreover, Tg treatment does not alter levels of Orai1 in this immunoprecipitation complex.

STIM2 and Orai2 in DCs are recruited to the IS

Antigen presentation, the major function of DCs, occurs at a specialized junction between DCs and T cells–the IS–which facilitates the aggregation of peptide-MHC class II complexes and cognate TCRs, as well as costimulatory molecules, to enhance T cell stimulation [25]. [Ca 2+ ]i signaling, which plays an important role in antigen presentation and T cell activation, may also be facilitated at the IS. Recently, Lioudyno et al. [14] described the movement of Orai1 and STIM1 to the IS in T cells upon stimulation with superantigen (staphylococcal enterotoxin B)-pulsed, autologous DCs. We therefore asked whether STIM2 and Orai2 are similarly recruited to the IS in DCs. Fig. 5 shows that pulsing DCs with ICAM1-coated beads triggered actin polymerization (green phalloidin staining), and aggregation of STIM2 (red, Fig. 5B) and Orai2 (red, Fig. 5C) directed to the site of contact. The coaggregation of F-actin and STIM2/Orai2 appears as intense yellow staining and was evident in the majority of cells studied (n>30). In contrast, actin and STIM2 did not polarize to beads coated with IgG alone (Fig. 5A, n>30), demonstrating the specificity for bone fide synaptic contact. We also observed some weaker Orai-actin costaining distant from the IS (Fig. 5C). The underlying mechanism for this aggregation pattern is unclear, but interestingly, MHC class II in DCs similarly aggregates at the IS and at the opposite pole [26, 27]. For comparison, we explored trafficking of STIM1 in T cells. As reported previously, pulsing T cells with anti-CD3/CD28-coated beads produced marked STIM1 immunostaining and F-actin aggregation at the contact zone (Supplemental Fig. 3B). Taken together, our data show that STIM2 and Orai2 are recruited to the IS of DCs.

Orai2 and STIM2 are localized at the IS. Representative confocal images of STIM2 and ORAI2 immunostaining in DCs stimulated with IgG (A)- or ICAM-1 (B and C)-coated beads. Circles indicate positions of beads clustered with DCs (original scale bars, 15 μm). Cells were colabeled with F-actin [phalloidin (PL), green] to reveal actin polarization toward contact sites. STIM2 (red) and ORAI2 (red) are polarized along with F-actin to the ICAM1-coated bead, as evident by the merged (yellow) staining. Immunostaining was assessed by a blinded scoring of >40 random conjugates from three independent experiments.

Significance of STIM2 and Orai2 signaling in DCs

Ca 2+ signaling is critical for DC maturation and function [2, 3]. Previously, we have shown that Ca 2+ entry in DCs is predominantly mediated by SOCE [1]. Here, we identify the molecular components for SOCE signaling in DCs: STIM2 and Orai2. Significantly, this represents the first report of STIM1-independent SOCE signaling in immune cells. Previous studies using primary T lymphocytes, Jurkat T cells, RBL-2H3 mast cells, and expression systems have reported STIM1 to be necessary and sufficient to signal ER store depletion leading to SOCE [4, 5, 9, 13]. In contrast, we present several lines of evidence arguing against a role for STIM1 in SOCE DCs. Notably, we found that compared with T cells, DCs express high levels of STIM2 and only low levels of STIM1. One could argue that even low levels of STIM1 might be sufficient to trigger SOCE. However, our functional and biochemical data do not support this position. First, we found that depletion of the ER Ca 2+ store triggers the aggregation of STIM2 and not STIM1. Second, we find that store depletion fails to increase physical associations between STIM1 and Orai proteins moreover, STIM1 does not associate with Orai2 under control or stimulated conditions. Instead, we find that store depletion markedly increases the association between STIM2 and Orai2. Thus, our data indicate that SOCE in DCs is likely triggered by STIM2, which in turn, interacts with Orai2.

Recent studies in expression systems [15, 24, 28] indicate that STIM2 possesses the capacity to trigger SOCE. Further, overexpression of STIM2 can restore SOCE in T cells [29] or fibroblasts [13], which are deficient in STIM1. The biological relevance of STIM2-triggered SOCE in immune cells, however, is unclear, as knockdown of STIM2 produces only a minor reduction of SOCE measured in T cells and fibroblasts [13]. In other tissues, STIM2 appears to play a more prominent role in SOCE. For example, STIM2 appears to be the dominant trigger for SOCE in the brain genetic deletion of STIM2 virtually abolishes SOCE in neurons [30]. Further, STIM2 contributes ∼50% of SOCE in human myoblasts and myotubes [31]. These data and our present findings indicate that STIM1 and STIM2 likely function in a tissue-specific manner. Whether these proteins have functionally distinct properties is unclear. Darbellay et al. [31] show that STIM1 and STIM2 are functionally equivalent (at least for SOCE activation) the effects of knockdown of either isoform can be rescued by overexpression of the other. On the other hand, Brandman and colleagues [15] report that STIM2 has an overall reduced affinity for ER Ca 2+ compared with that of STIM1. The implication of this finding is that a smaller decrease in ER Ca 2+ could be sufficient to activate STIM2 and trigger SOCE. In DCs, this could lead to enhanced Ca 2+ entry, even in response to weak, external stimuli, a property that could assist the innate immune function of DCs. In addition to triggering SOCE, STIM1 can bind and activate various TRPC channels [32]. Whether STIM2 shares this property is unknown, although STIM1 and STIM2 contain a polylysine C terminus implicated in electrostatic activation of TRPC channels. Finally, native STIM1, but not STIM2, can insert into the plasma membrane [33, 34], which although not essential for SOCE, may contribute to other cellular functions such as cell adhesion. Thus, the selective expression of STIM2 in DCs may lead to altered cell properties independently of SOCE.

Several studies have shown Orai1 to be the essential subunit of the CRAC channel [6, 10, 17]. In contrast, we show that Orai2 constitutes the major Orai isoform in DCs, and this is based on Orai2 expression, physical interactions with STIM2, and characteristic 2-APB sensitivity. The significance of Orai2-mediated SOCE in DCs is unclear. Although, Orai1–3 possess similar channel properties, including conductance and ion selectivity, they do exhibit different gating properties. Orai1-mediated ICRAC shows a rapid Ca 2+ -induced inactivation [35], not seen in Orai2 [22]. Assuming these properties are reproduced in native tissues, then Orai2-mediated SOCE in DCs may be able to maintain a more sustained increase in [Ca 2+ ]i. Indeed, DCs exhibit prolonged Ca 2+ transients in response to stimulation of GPCRs [1, 36], rather than the oscillatory pattern, which expresses Orai1, commonly observed in T cells. In addition, Orai1 and Orai3 subunits mediate the arachidonate-gated current observed in many nonexcitable cells [37]. The paucity of these proteins in DCs, therefore, suggests a reduced sensitivity to inflammatory arachidonic acid.

Significantly, we show that STIM2 and Orai2 are recruited to the DC immune synapse upon stimulation with ICAM-1. The IS supports clustering of adhesion molecules, peptide-MHC class II, and costimulatory molecules and facilitates productive encounters with T cells [26, 38–40]. The formation of the IS in DCs is accompanied by an increase in [Ca 2+ ]i [41], as well as actin polarization toward the T cell contact site [26, 39]. Ca 2+ is likely important for this cytoskeletal rearrangement. Indeed, surface expression of MHC class II and CD86 in DCs is inhibited by Ca 2+ chelation [3]. Our data, showing that key components of SOCE cluster at the IS, suggest that SOCE may participate in the initiation or maintenance of IS and/or IS signaling. Future studies, will hopefully address these questions.

In conclusion, our data indicate that STIM2 and Orai2 are key molecules underlying SOCE in DCs. Moreover, we show that STIM2 and Orai2 cluster at the IS, suggesting that focal Ca 2+ entry regulates properties of DC synapses.



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