Interestingly, evidence for ion-flux independent LTD can be observed in data from older literature. Over 20 years ago, data were published indicating that MK-801, which blocks NMDAR channels, blocked LTP but failed to block LTD (Mayford et al., 1995). A similar effect was obtained by a different group (Scanziani et al., 1996). Surprisingly, these observations were not discussed in either study. The ion-flux dependence of LTD was recently examined more closely (Nabavi et al., 2013). Low-frequency stimulation (LFS) produced LTD in the presence of either MK-801 or 7-chloro-kynurenate (7CK, a competitive GluN1 antagonist; see **Figure 1A**) but not APV (a competitive GluN2 antagonist); all three antagonists effectively blocked ion-flux through the NMDAR. Moreover, LTD was observed in experiments in which intracellular Ca2+ was clamped to basal levels, suggesting that a rise in intracellular Ca2+ is not required for LTD. It was thus proposed that glutamate binding to the NMDAR could induce a conformational change in the cytoplasmic domain of the NMDAR that triggers downstream signaling resulting in LTD.

To test if ligand binding could drive movement of the NMDAR intracellular domain, FRET-FLIM [Forster resonance energy transfer measured by fluorescence lifetime imaging of the FRET donor, see **Toolbox** and (Wallrabe and Periasamy, 2005; Yasuda, 2006)] was employed (Dore et al., 2015). Recombinant GluN1 subunits of the NMDAR were tagged with GFP or mCherry at their carboxyl(c)-terminus and co-expressed in neurons. As the magnitude of FRET is very sensitive to the distance and orientation of the interacting fluorophores, nanometer-scale changes in distance can be reliably detected. Bath application or uncaging of glutamate in the presence of MK-801 or 7CK, but not APV, produced a transient change in FRET consistent with conformational movement of the NMDAR cytoplasmic domain (**Figure 1B**). Infusing neurons with a GluN1 c-terminus antibody through a patch pipette blocked the ligand-driven FRET change as well as LTD, suggesting that this conformational change is required for LTD induction.

Downstream signaling events were also examined using FRET-FLIM (Aow et al., 2015). Protein-phosphatase 1 (PP1) is one of the first molecules whose activity was shown to be required for LTD (Mulkey et al., 1993) and it co-immunoprecipitates with the NMDAR complex (Husi et al., 2000). FRET between GluN1-GFP and PP1-mCherry, observed in baseline conditions, was transiently reduced during chemical LTD induction. This ligand-driven decrease in FRET required NMDAR conformational movement but not PP1 activity (Aow et al., 2015). It is possible that the transient movement of PP1 relative to the NMDAR cytoplasmic domain exposes the catalytic active site of PP1 to a target unavailable under basal conditions. One potential target is calcium-calmodulin dependent protein kinase II (CaMKII; Strack et al., 1997), which is recruited to the NMDAR complex during LTP stimuli (Otmakhov et al., 2004) and whose activity is required for both LTP (Malenka et al., 1989; Malinow et al., 1989; Silva et al., 1992) and LTD (Coultrap et al., 2014). By monitoring FRET between fluorescently-tagged GluN1 and CaMKII, a delayed decrease in the NMDAR-CaMKII interaction was observed during ionflux independent LTD (Aow et al., 2015). This effect depended on PP1 activity and was not seen with a CaMKII mutant that cannot be dephosphorylated at Thr-286 (CaMKII-Thr-286-Asp), suggesting that dephosphorylation of Thr-286 is necessary to modify the NMDAR-CaMKII interaction (Aow et al., 2015). Co-immunoprecipitation experiments additionally revealed that the amount of total CaMKII bound to the NMDAR was unaffected by ion-flow independent LTD, whereas levels of phosphorylated Thr-286 were reduced both during and after LTD induction (Aow et al., 2015). These results are consistent with a model for ion-flux independent LTD in which glutamate binding to the NMDAR induces a conformational change in the NMDAR intracellular domain that facilitates PP1 access to and dephosphorylation of CaMKII at Thr-286, thereby repositioning the CaMKII holoenzyme within the NMDAR complex. The relocated CaMKII could in turn potentially act on a novel site of the GluA1 subunit (Ser-567) that undergoes phosphorylation during LTD (Coultrap et al., 2014). Consistent with this model, CaMKII phosphorylation of GluA1-Ser-567 does not require Ca2+ or calmodulin (Coultrap et al., 2014). Ultimately, this process could increase AMPAR endocytosis (Lüscher et al., 1999; Lin et al., 2000; Kim et al., 2001; Shi et al., 2001) and lead to depressed synaptic transmission.

Ion-flow independent NMDAR activation of downstream signaling pathways has also been linked to shrinkage of dendritic spines (Stein et al., 2015). Stein et al. used 2 photon laser scanning microscopy (TPLSM) to monitor structural changes in the dendritic spines of GFPexpressing hippocampal neurons. Low-frequency uncaging of glutamate produced a ∼20% decrease in spine size that was independent of ion-flow through the NMDAR (**Figure 1C**). While high-frequency glutamate uncaging produced an increase in spine volume, the same stimulus in the presence of either 7CK or MK-801 led to spine shrinkage. This result is consistent with the finding that HFS (delivered electrically) in the presence of MK-801 produces LTD instead of LTP (Nabavi et al., 2013). Spine shrinkage was also abolished when p38 MAPK activity was blocked (Stein et al., 2015), which is again consistent with the observation that levels of phosphorylated p38 (which is the active form) were increased during ion-flow independent LTD (Nabavi et al., 2013). In the future, it will be important to elucidate how the initial movement in the NMDAR cytoplasmic domain subsequently affects signaling molecules, such as cofilin, calcineurin and p38, implicated in LTD.

An ion-flux-independent mechanism for NMDARdependent LTD has been challenged by some recent studies (Babiec et al., 2014; Volianskis et al., 2015; Sanderson et al., 2016) but confirmed by others (Kim et al., 2015; Stein et al., 2015; Carter and Jahr, 2016). It is notable that the experimental conditions used in these recent studies that failed to detect ion-flux-independent LTD were not identical to those supporting this form of LTD. For instance, NMDAR antagonists were typically acutely washed in and then out of the preparation during LTD induction (Volianskis et al., 2015), instead of being present throughout the experimental duration. Furthermore, control pathways, which monitor transmission onto the same neurons but do not receive the conditioning stimulus, were generally not included (Babiec et al., 2014; Volianskis et al., 2015; Sanderson et al., 2016). These differences in methodology are significant and can make an impact in the outcome and interpretation of results (Nabavi et al., 2014). Therefore, it will be important to compare carefully the experimental conditions employed by different studies. Nevertheless, it remains possible that two different, independent

#### TOOLBOX | FRET measurements using fluorescence lifetime imaging microscopy.

FRET is a non-radiative energy transfer mechanism between two fluorescent molecules. There are two main requirements for successful FRET. First the fluorescence emission of the FRET donor must overlap with the FRET acceptor absorption spectrum; and second, these fluorescent molecules must be no more than ∼10 nm apart from each other (Lakowicz, 2006). This spatial requirement of FRET is very sensitive; it can thus be used as a "molecular ruler" to assess protein structure (Gustiananda et al., 2004) or to monitor subtle conformational changes (Dore et al., 2015).

FRET can be measured by acquiring a series of images in different combinations of excitation and emission channels or by photobleaching of the FRET acceptor. However, these methods are prone to errors and are generally not well suited for measurements in living cells expressing fluorescent proteins (Selvin, 2000; Yasuda, 2006; Piston and Kremers, 2007). Fluorescence lifetime is defined as the average time a molecule stays in its excited state before emitting a photon (A). Because lifetime is an intrinsic property of fluorophores, it is independent of experimental conditions such as concentration, excitation intensity and photobleaching (Lakowicz, 2006; Yasuda, 2006). Importantly, by adding an additional route for the donor fluorophore to return to ground state, the degree of FRET makes the fluorescence lifetime of the donor proportionally shorter (A,B). To measure fluorescence lifetimes, the most common approach is time correlated single photon counting (TCSPC; Becker et al., 2004) which calculates the time delay between the detection of fluorescence photons and laser excitation pulses (B). When TCSPC is combined with laser scanning microscopy, it is possible to obtain fluorescence lifetimes, and hence detect changes in donor-acceptor distances, at every pixel of an image (B,C).

FRET-FLIM. (A) Jablonski diagram of FRET donor and acceptor energy levels. After excitation by a 1-photon (blue arrow) or 2-photon (brown arrows) laser, the FRET donor can return to ground state by emitting a photon (green arrow) or by transferring its energy to a nearby acceptor (dashed green arrows). (B) The fluorescence lifetime of the FRET donor, which becomes shorter with increased proximity of the FRET acceptor, is calculated with the fluorescence decay curve. (C) Time-correlated single photon counting (TCSPC) records fluorescence decay curves for each pixel of an image. By fitting these curves, the fluorescence lifetime of the FRET donor can be assessed. The FLIM image is then color coded according to the FRET donor lifetime at each pixel.

ion-flux through the NMDAR is not required for spine shrinkage. Modified from Stein et al. (2015).

forms of NMDAR-dependent LTD exist: one that requires ion-flow through NMDARs and one that does not. Different experimental conditions could selectively recruit either of these two forms.

### TRAFFICKING OF NMDAR IS REGULATED BY SYNAPTIC ACTIVITY BUT NOT ION-FLUX

In addition to its more recently described role in LTD, a few older studies have indicated that ligand binding to the NMDAR, in the absence of ion-flux, could control NMDAR trafficking (Vissel et al., 2001; Barria and Malinow, 2002; Nong et al., 2003). The Westbrook lab showed that even with its pore blocked, ligand binding to the NMDAR drove tyrosine dephosphorylation of GluN2A subunits, resulting in NMDAR endocytosis and decreased NMDA currents. Another group separately observed that an initial application of glycine was sufficient to prime NMDARs for subsequent use-dependent endocytosis, again leading to a decline in NMDA currents (Nong et al., 2003). Moreover, synaptic replacement of GluN2B- with GluN2A-containing NMDARs, an important developmentally controlled process (Hestrin, 1992; Monyer et al., 1994; Sheng et al., 1994; Stocca and Vicini, 1998; Tovar and Westbrook, 1999), required ligand binding without ion flux (Barria and Malinow, 2002). Interestingly, the replacement of synaptic GluN2B-containing NMDARs by newly synthetized GluN2B-containing NMDARs did not require ligand binding. It is important to note that these effects on NMDAR trafficking required both agonist and co-agonist binding to NMDARs as they were blocked by antagonists to the glutamate binding site on GluN2 subunits or to the glycine binding site on GluN1 subunits (Vissel et al., 2001; Barria and Malinow, 2002; Nong et al., 2003); in contrast, LTD only requires ligand binding to GluN2 subunits (Nabavi et al., 2013).

(AMPAR) currents of such a recording (top right). Bottom, results from paired-recordings performed in ACSF containing no drug (N = 41), Ro 25-6981 (N = 37) or MK-801 (N = 25); ∗∗indicates p < 0.001. Modified from Kessels et al. (2013). (B) Spine density is reduced in a transgenic mouse model of Alzheimer's disease (AD), APV blocks the effect but not memantine. Scale bar, 5 µm. Modified from Birnbaum et al. (2015). (C) Sustained NMDA application causes excito-toxic insults to CA1 neurons in the form of blebbing of dendrites (left panels). This effect is blocked by APV and CGP-78608 (middle panels) but not MK-801 (right panels). Scale bar, 25 µm. Modified from Weilinger et al. (2016).

### METABOTROPIC NMDAR ACTIVITY CAN INDUCE SYNAPTIC DYSFUNCTION

Recent results have suggested a role for metabotropic NMDAR activity in amyloid-beta mediated synaptic dysfunction, which may contribute to hippocampal deficits in Alzheimer's disease (AD) and precede neurological symptoms by a decade or more (Terry et al., 1991; Reiman et al., 1996). A number of studies using electrophysiology and imaging have reported that amyloid-beta impairs LTP, depresses synaptic transmission and induces synapse loss in various hippocampal preparations (Chapman et al., 1999; Larson et al., 1999; Walsh et al., 2002; Wang et al., 2002; Kamenetz et al., 2003; Snyder et al., 2005; Hsieh et al., 2006; Shankar et al., 2007; Wei et al., 2010; Birnbaum et al., 2015). The effect of intracellularly delivered amyloid-beta is not clear, as one report indicated synaptic depression (Ripoli et al., 2014) while another indicated synaptic potentiation (Whitcomb et al., 2015). In many of these studies the electrophysiological results could be corroborated using imaging. For instance, Wei et al. (2010) used TPLSM to show that GFP-filled dendritic spines close to axons or dendrites overexpressing amyloid-beta displayed a smaller increase in spine volume following a chemically-induced LTP protocol as compared to more distant spines, suggesting that secreted amyloid-beta impaired LTP. Hsieh et al. (2006) used TPLSM of AMPARs tagged with the pH-sensitive GFP-variant SEP (Super-Ecliptic-Phluorin) to measure surface AMPARs and found that amyloid-beta reduced surface GluA1 and GluA2. Likewise, immunostaining and imaging primary cultures treated with amyloid-beta revealed a reduction in surface NMDARs (Snyder et al., 2005) and AMPARs (Almeida et al., 2005; Alfonso et al., 2014). The decrease in synaptic AMPAR and NMDAR currents correlates, therefore, with a decrease in surface receptors as determined with optical techniques. Finally, several groups have shown using TPLSM or confocal microscopy that endogenously expressed or exogenously applied amyloid-beta reduces spine density in GFP-expressing neurons (Hsieh et al., 2006; Shrestha et al., 2006; Calabrese et al., 2007; Shankar et al., 2007; Wei et al., 2010; Zempel et al., 2010), which may explain the electrophysiologically observed decreased frequency of miniature excitatory postsynaptic currents (Kamenetz et al., 2003; Hsieh et al., 2006). Therefore, amyloid-beta induces synaptic insults that can be directly observed through imaging.

A mechanism proposed to account for synaptic impairment by amyloid-beta is enhanced ionotropic glutamate receptor endocytosis. Indeed, there is evidence that inhibiting endocytic signaling pathways or overexpressing mutant endocytic-resistant receptors can ameliorate the reduction in AMPAR and/or NMDAR currents (Snyder et al., 2005; Hsieh et al., 2006; Knafo et al., 2016). Notably, Kessels et al. (2013) reported that despite block of ion flux, not all NMDAR antagonists prevented amyloidbeta-induced depression of AMPAR-mediated transmission. The GluN2 antagonists (R)-CPP, Ro25-6981, and ifenprodil afforded a complete block; whereas the GluN1 antagonist 7CK and the NMDAR pore blocker MK-801 had no effect (**Figure 2A**; Kessels et al., 2013). Thus, the block of depression correlated with actions on different NMDAR subunits rather than block of ion-flux. In another model, amyloid-beta oligomers exogenously applied to organotypic hippocampal slices acutely depressed AMPAR-mediated transmission in a manner that was dependent on synaptic stimulation and NMDAR activation but not NMDAR ion-flux (Tamburri et al., 2013). Both studies therefore suggest that amyloidbeta activates a metabotropic NMDAR signaling pathway that depresses synaptic transmission. The evidence that this pathway could then be involved in eventual spine loss comes from three other studies using imaging techniques. Two studies (Shankar et al., 2007, 2008) showed using TPLSM that (R)-CPP

prevented amyloid-beta-induced spine loss in GFP-expressing organotypic slice neurons. Birnbaum et al. (2015) subsequently demonstrated that the competitive GluN2 antagonist APV also blocked spine loss in transgenic AD mice (as well as in hippocampal slices incubated in amyloid-beta oligomers), whilst MK-801, memantine, another NMDAR pore blocker, and buffering postsynaptic calcium ions with BAPTA had no effect (**Figure 2B**). That study (Birnbaum et al., 2015) also showed an amyloid-beta-induced reduction in PSD-95 and synaptophysin levels that was blocked by APV but not by MK-801 or memantine. Moreover, they demonstrated that p38 MAPK phosphorylation was increased by amyloidbeta in a NMDAR ion-flux independent manner and that spine loss depended on p38 MAPK activity (Birnbaum et al., 2015), supporting a link, previously examined (Hsieh et al., 2006), between LTD and amyloid-beta-induced depression. Taken together, these imaging results are in agreement with electrophysiological experiments and support the hypothesis that amyloid-beta toxicity depresses synaptic transmission via metabotropic NMDAR signaling that results in eventual spine loss.

The role of NMDARs in mediating excitotoxicity has been extensively described (reviewed in Choi, 1992), and it has been widely suggested that excessive Ca2+ influx through the receptor is responsible for inducing cell death (Choi, 1995; Tu et al., 2010). Interestingly, recent findings suggest that a metabotropic NMDAR ''signalsome''—involving the NMDAR, the pannexin-1 channel (Panx1) and src kinase—is capable of inducing cellular dysfunction in response to excessive NMDAR stimulation (Weilinger et al., 2016). TPLSM was used to image fluorescently labeled CA1 neurons in acute rat hippocampal slices treated with a high dose of NMDA. This protocol induced blebbing in the dendrites of CA1 neurons as well as mitochondrial dysfunction, an effect that was blocked by co-application of the GluN1 antagonist CGP-78608 and APV, but not by MK-801, indicating that ligand binding to the NMDAR was capable of damaging neuronal morphology independently of ion flux through the receptor (**Figure 2C**). Interestingly, Panx1 channels appear to be located almost exclusively at the PSD (Zoidl et al., 2007), which suggests that this metabotropic NMDAR ''signalsome'' is synaptic. Additional experiments demonstrated that ligand binding, but not NMDAR ion flux, was necessary for downstream activation of Panx1 (Thompson et al., 2006, 2008; Weilinger et al., 2012). Metabotropic NMDAR activity did not change the degree of interaction between GluN1 and Panx1, but it did increase Src kinase binding to GluN1, Src activation, as well as Src-dependent phosphorylation

presence, spine elimination will occur.

of Panx1. Peptides that either disrupted the GluN1-Src interaction (Src48) or interfered with Panx1 phosphorylation (Tat-Panx308) were neuroprotective in vitro, and injection of Tat-Panx308 reduced brain lesion volume in an in vivo model of stroke. Indeed, as ischemia in the brain is believed to drive subsequent excitotoxicity, these results suggest that targeting Src or Panx1 in a clinical setting could be therapeutically effective.

### CONCLUDING REMARKS

A number of studies have provided evidence that physiological and pathological processes can be triggered by ligand binding to the NMDAR, without requiring flow of ions through its pore. It will be important to determine conditions that control whether an ionotropic or metabotropic NMDAR

## REFERENCES

mechanism is engaged during LTD. Ion-flux independent LTD appears to be mediated by a movement in the NMDAR cytoplasmic domain that affects its interactions with at least two signaling proteins, PP1 and CaMKII. Subsequent signaling, with increased p38 MAPK phosphorylation likely, leads to AMPAR removal, shrinkage of dendritic spines and depressed synaptic transmission (**Figure 3**). Interestingly, it seems that if the stimulus recruiting metabotropic NMDAR function is sustained, as in the contexts of amyloid-beta overproduction or excitotoxic conditions following ischemia, metabotropic NMDAR activity can also lead to synaptic and neuronal dysfunction.

### AUTHOR CONTRIBUTIONS

KD, JA and RM wrote the manuscript. KD designed figures.

**Conflict of Interest Statement**: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Dore, Aow and Malinow. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Correlative Light Electron Microscopy: Connecting Synaptic Structure and Function

Isabell Begemann1,2 and Milos Galic1,2 \*

1 DFG Cluster of Excellence 'Cells in Motion', (EXC 1003), University of Muenster, Muenster, Germany, 2 Institute of Medical Physics and Biophysics, University Hospital Münster, University of Muenster, Muenster, Germany

Many core paradigms of contemporary neuroscience are based on information obtained by electron or light microscopy. Intriguingly, these two imaging techniques are often viewed as complementary, yet separate entities. Recent technological advancements in microscopy techniques, labeling tools, and fixation or preparation procedures have fueled the development of a series of hybrid approaches that allow correlating functional fluorescence microscopy data and ultrastructural information from electron micrographs from a singular biological event. As correlative light electron microscopy (CLEM) approaches become increasingly accessible, long-standing neurobiological questions regarding structure-function relation are being revisited. In this review, we will survey what developments in electron and light microscopy have spurred the advent of correlative approaches, highlight the most relevant CLEM techniques that are currently available, and discuss its potential and limitations with respect to neuronal and synapse-specific applications.

### Edited by:

Marc Fivaz, Duke NUS Graduate Medical School, Singapore

#### Reviewed by:

Jeff Lichtman, Harvard University, USA Christian Wilms, Scientifica Ltd., UK

### \*Correspondence:

Milos Galic<EMAIL_ADDRESS>
Received: 23 March 2016 Accepted: 12 August 2016 Published: 23 August 2016

#### Citation:

Begemann I and Galic M (2016) Correlative Light Electron Microscopy: Connecting Synaptic Structure and Function. Front. Synaptic Neurosci. 8:28. doi: 10.3389/fnsyn.2016.00028 Keywords: correlative light electron microscopy, CLEM, synapse, neuron, fluorescence microscopy, electron microscopy, TEM, SEM

### INTRODUCTION

Neurons transmit the majority of trans-cellular signals via synaptic contacts. To correctly and reliably respond to various stimuli (e.g., different input frequencies), each synapse hosts an elaborate machinery to regulate signal transmission in a context-dependent manner. On the molecular level, synaptic transmission in its most simple form relies on fusion of ∼40 nm large vesicles at the presynaptic site, diffusion of released neuro-transmitters across the 30 nm wide synaptic cleft, and subsequent ligand-specific activation of receptors at the postsynaptic site. Considering the small size of this signaling unit, it is not surprising that major advancements in understanding synaptic function have been closely correlated with progress in imaging technology. For instance, the notion that communication across synaptic clefts relies on chemical signals would not have been possible without detailed information from electron micrographs on synapse ultrastructure (Derobertis and Bennett, 1955; Pappas and Bennett, 1966) and vesicle dynamics (Heuser and Reese, 1973). Likewise, our understanding about the function of individual synaptic proteins has substantially advanced with the introduction of ion and protein markers (Shimomura et al., 1962; Tsien, 1981; Heim et al., 1994) for fluorescence light microscopy. Intriguingly, and despite the fact that today's neuroscience is building up on information obtained with electron and light microscopy, strategies to combine these two approaches only recently have started gaining traction.

The emergence of such dual approaches, termed correlative light electron microscopy (CLEM), from a sparsely known branch of imaging to center stage can be linked to a series of landmark papers from the nineties (Deerinck et al., 1994; Svitkina et al., 1995). Since then, fueled by advances in imaging and labeling techniques, publications using CLEM approaches have steadily been rising. In this review, we will revisit what developments have incited the advent of correlative imaging approaches, and highlight the most relevant dual microscopy techniques that are currently available. We begin by giving an overview of electron and light-based imaging methods that can be used for CLEM, followed by a section describing how individual approaches can be successfully combined to create correlative approaches. Next, we will reflect on technical concerns that need to be taken care of when designing dual imaging experiments, before closing with a discussion on current limitations and future challenges associated with CLEM.

### ELECTRON AND LIGHT-BASED TECHNIQUES USED FOR CLEM

CLEM describes a continuously growing number of procedures that allow merging electron and light-based images from the same object. Thus, at least in theory, each existing electron and light microscopy technique where ultrastructure remains intact could be paired to generate a CLEM image. To illustrate this combinatorial potential, and to expound existing limitations, we begin this section by discussing electron and light microscopy techniques suitable for correlative approaches, before proceeding to examples where CLEM was successful applied to study neuronal and synaptic function.

### Electron Microscopy–Visualizing the Ultrastructure

Electron micrographs in CLEM rely to a large extent on transmission electron microscopy (TEM) and scanning electron microscopy (SEM). TEM, which enables visualization of 50– 100 nm thick cross-sections of samples with a resolution of down to a few Angstrom (Pierce and Buseck, 1974; Ruska, 1987; Erni et al., 2009), was critically involved in the detailed characterization of synaptic structures (Gray, 1959; Pappas and Bennett, 1966; Fifkova and Delay, 1982; Landis and Reese, 1983; Watanabe et al., 2013, 2014), and has helped to advance our understanding on age and disease-dependent changes in synaptic properties (DeKosky and Scheff, 1990; Navlakha et al., 2013).

Contrary to TEM, where electron shadows are used to create the image, SEM-based strategies utilizes the interaction of electrons with molecules in the sample to recreate the image. One commonly applied SEM strategy, where secondary electrons are used to determine the surface topography of objects with a precision of ∼1 nm (Vernon-Parry, 2000), was central for investigating surface features such as the morphology of neuromuscular junctions (Desaki and Uehara, 1981) as well as structural reorganization during exploratory dendritic filopodia formation in hippocampal neurons (Galic et al., 2014). In addition, back-scattered electrons created by interaction with heavy elements (i.e., high atomic number) in the uncoated sample can also be used to render images comparable to transmission electron micrographs of ultrathin sections, an approach that is of particular relevance for embedded sections on an electronopaque surface or samples that are investigated 'en block' (Briggman et al., 2011).

A single cross-section, or the surface of the sample, is lacking information on the three-dimensional organization within the biological specimen. Here, cryo-fracture, where frozen samples are broken to expose cell structures along the fracture line (Castejon and Caraballo, 1980; Castejon, 1996), or unroofing, where intracellular structures are uncovered by brief bursts of ultrasound (Lang, 2003), can be used together with deep-etching (Heuser and Salpeter, 1979) to gain insights into subcellular organization. While useful, these strategies lack the capability for systematic three-dimensional sample reconstruction that can be achieved with serial sectioning, where successive ultrathin slices are imaged. Early attempts of serial sectioning reach back to the late 60s (De Rosier and Klug, 1968), and have since then continuously been used to investigate neuronal networks (White et al., 1986) and synaptic connection (Mishchenko et al., 2010). In modern serial section TEM (ssTEM), sections of 60 ± 20 nm are cut with an ultra-microtome and placed manually on a metal support grid (Harris et al., 2006).  Here, sections of 30 nm are cut by an ultra-microtome and collected from the water bath using a conveyor-belt like support tape. As the support tape is electron-opaque, a finely focused SEM beam is applied to raster the surface of the sample and backscattered electrons are used to reconstruct the image. Thus, compared to ssTEM, ATUM-based strategies not only allow thinner sectioning and rapid imaging of larger areas but also substantially reduce errors associated with manual sample handling (Hayworth et al., 2014). Alternatively, an embedded tissue block can also be sectioned directly within the SEM vacuum chamber, either using a diamond knife (serial block-face SEM, SBEM; Leighton, 1981; Denk and Horstmann, 2004) or by milling with a focused ion-beam (FIB-SEM; Watkins et al., 1986; Knott et al., 2008). In the latter, a scanning electron microscope is used to image the surface of the embedded sample, while a high current focused ion beam continuously slices off sections perpendicular to the SEM axis, thus allowing 3D reconstruction of the sample. Compared to diamond-based sectioning, FIB-SEM is thus not only faster but also permits sectioning samples with a step size in the single nm range (Knott et al., 2008; Merchan-Perez et al., 2009; Lehmann et al., 2014).

Another strategy for detailed three-dimensional reconstructions relies on electron tomography (ET). In this approach, a tilt series (usually ranging from −60◦ to +60◦ ) of two-dimensional images is generated to reconstruct the three-dimensional shape of an object within the single slice (Crowther et al., 1970; Hoppe et al., 1974; Penczek, 2010; Ercius et al., 2015). ET was successfully used to resolve ultrastructural features of the presynapse (Perkins et al., 2015) and synaptic vesicle populations in saccular hair cells (Lenzi et al., 1999). Yet,

while ET is suitable for atomic-resolution, radiation damage, and limitations in interpretability for thicker sections need to be considered when preparing the sample (Tocheva et al., 2010).

Finally, we would like to note that further electron-based imaging strategies exist (e.g., STEM (Crewe et al., 1970; Engel, 1978), tSEM (Kuwajima et al., 2013)). While not commonly used in CLEM studies, it is plausible to envision that some of these additional types of electron microscopy may be beneficial for a particular question. For readers interested in learning more on electron microscopy techniques, we recommend reading one of the many excellent reviews available on this exciting topic (Briggman and Bock, 2012; Knott and Genoud, 2013; Miranda et al., 2015; Perkins et al., 2015).

### Light Microscopy–Monitoring and Manipulating Cell Function

While the electron microscopy techniques described above are well suited to investigate ultrastructural features with high axial resolution, they lack spatio-temporal information available with light microscopy. To increase penetration depth and reduce background compared to whole field illumination (Epi), CLEM studies frequently rely on confocal microscopy, where a pinhole is used to reduce out-of-focus light (Minsky, 1988), light sheet microscopy, where a light beam perpendicular to the objective illuminates only the focal plane (Engelbrecht and Stelzer, 2006; Keller et al., 2008), or two-photon microscopy, where simultaneous absorption of two photons is used for spatially controlled illumination (Denk et al., 1990). Resolution in light and electron microscopy is based on numerical aperture and wavelength. However, unlike in electron microscopy, where resolution is limited by the spot size (SEM) or the grain of the detector (TEM), the limiting factors in light microscopy is the wavelength (Rayleigh, 1879; Abbe, 1883). To reach beyond the diffraction limit, several approaches have been introduced over the last decade. Among the most prominent super-resolution microscopy techniques used in CLEM studies are stimulated emission depletion microscopy (STED), where a depletion laser limits the width of the emitting light source (Hell and Wichmann, 1994; Klar et al., 2001), and stochastic techniques, such as fluorescent photo-activation localization microscopy (PALM; Betzig and Chichester, 1993; Betzig et al., 2006) or stochastic optical reconstruction microscopy (STORM; Rust et al., 2006), where light emitted from sequentially activated fluorophores is fitted to determine its precise localization. As before, we would like to note that additional light-based approaches [e.g., total internal reflection fluorescence microscopy (Axelrod, 1981) or structured illumination microscopy (Neil et al., 1997)] can be used in CLEM approaches. Readers interested to learn more about fluorescence microscopy techniques, we refer to one of the many excellent reviews focused on these topics (Lichtman and Conchello, 2005; Combs, 2010; Huang et al., 2010).

Fluorescence light microscopy not only allows to visualize cells within neuronal circuits (Livet et al., 2007), but a continuously growing number of molecular probes and genetically encoded markers also provide tools to study a variety of neuronal and synaptic properties. Parameters that can be analyzed include among others subcellular protein localization (Chalfie et al., 1994; Heim et al., 1994; Kilgore et al., 2013), protein activity (Adams et al., 1991), ion dynamics (Tsien, 1980, 1981; Tsien et al., 1982; Minta and Tsien, 1989; Nakai et al., 2001), pH (Tanasugarn et al., 1984; Miesenbock et al., 1998), membrane potential or voltage (Davila et al., 1973; Siegel and Isacoff, 1997; Zochowski et al., 2000), or lipid species (Stauffer et al., 1998). Intriguingly, light is also suitable to actively manipulate the biological sample in a precise spatio-temporal manner. One commonly used approach relies on light-activation of caged substrates. Relevant for neurobiology, strategies for uncaging calcium (Ellisdavies and Kaplan, 1994), IP3 (Wang and Augustine, 1995), and various neurotransmitters (Ellis-Davies, 2011) have been realized. More recently, light has also been used to regulate protein function (Cao et al., 2008; Tischer and Weiner, 2014). This approach, coined optogenetics, has provided among others tools for controlling neuronal and synaptic activity with unprecedented spatio-temporal precision (Boyden et al., 2005; Fenno et al., 2011; Rost et al., 2015). Finally, it is worth mentioning that even physical cell parameters, such as shape or membrane tension, can be altered by light in living samples, using for instance optical tweezers (Ashkin, 1970; Zhang and Liu, 2008). In summary, when combined with electron microscopy, these light-based approaches allow precisely altering a specific parameter while monitoring the cellular responses followed by analysis of the corresponding ultrastructural features.

## Correlative Light and Electron Microscopy in Neuroscience

Although the potential of combining ultrastructural information with functional studies was early noticed, first attempts to combine these microscopy techniques were limited to depicting separately prepared and imaged biological samples (Porter et al., 1945). Experiments where fluorescence and EM images of subcellular structures from the same cell were aligned started appearing in the 1970s (Hollander, 1970; Nakai and Iwashita, 1976), and have since then been applied to investigate a variety of neurobiological questions.

To fully understand neuronal or synaptic function, the cellular context needs to be considered. It is thus not surprising, that large efforts have been put into elucidating ultrastructural information within the intact tissue. In situ CLEM, where data from lifecell fluorescence imaging is combined with EM micrographs, has advanced our understanding of neuronal circuits (Bock et al., 2011; Briggman et al., 2011; Lee et al., 2016), and has also shed light on subcellular behaviors such as axosome shedding (**Figure 1A**) (Bishop et al., 2004). An alternative strategy, frequently applied to gain information of individual neurons in situ, relies on array tomography (AT), where plasticembedded tissue samples are sliced with an ultra-microtome, bonded array-wise onto a glass coverslip, stained, and finally imaged by fluorescence and electron microscopy (**Figure 1B**) (Micheva and Smith, 2007; Rah et al., 2013; Collman et al., 2015). By combining super-resolution techniques and serial sectioning, it was even possible to detect presynaptic dense projection proteins at a lateral resolution of 35–65 nm (Watanabe

et al., 2011). While serial sectioning-based CLEM approaches allow studying biological samples with high axial and lateral resolution, sample preparation, and 3D image alignment can be challenging (Micheva and Smith, 2007; Collman et al., 2015). Here, SBEM and FIB-SEM based approaches, where en-block EM imaging and fluorescence approaches are merged to obtain CLEM images, have helped to streamline in situ studies focused on the complexity of the nervous system (Briggman et al., 2011; Blazquez-Llorca et al., 2015), or to reconstruct whole cortical neurons (Maco et al., 2013) and single synapses (Bosch et al., 2015).

Orthogonal to in situ approaches described above, CLEM can also be applied to neurons isolated from brain tissues and cultured in vitro (Banker and Cowan, 1977). As such, cultured neurons are compatible with each CLEM technique described above (**Figure 1C**) (Al Jord et al., 2014; Paez-Segala et al., 2015; Fares et al., 2016). Although these cells lack the physiological context usually encountered by neurons within a tissue, cultured neurons may still yield advantages compared to in situ samples depending on the biological question. One such example, and complementing the section-based CLEM assays described so far, is the analysis of processes at the cellular surface, such as curvature-dependent protein recruitment to deforming plasma membranes (**Figure 1D**) (Galic et al., 2014).

### TECHNICAL CONSIDERATIONS

In this section, we will focus on technical possibilities and limitations that need to be taken into consideration when designing a CLEM experiment. We start by discussing challenges arising from sample preparation. Next, we will survey what markers are suitable for which technique, and discuss strategies for alignment of corresponding fluorescence images and electron micrographs with respect to their potential and drawbacks.

### Sample Preparation for CLEM Images

The quality of correlative image alignment critically relies on the ability to maintain the native organization of the cell during fixation and subsequent sample preparation. Thus, CLEM techniques not only need to be optimized for signal strength, but also for shape preservation. Formaldehyde, glutaraldehyde, and osmium tetroxide (OsO4), have been the standard fixatives for decades, including for brain tissues that are due to their softness easily damaged during fixation and subsequent processing. Classical fixation protocols include whole animal perfusion via the vascular system for larger specimens (e.g., whole brain) as well as immersion of tissue slice and cultured cells. Once the biological sample is fixed, the actual preparation for the respective EM technique is rendered. For slice-based assays, two different approaches exist: the pre-embedding method and the post-embedding method. For both methods, correlative approaches have been reported (Watanabe et al., 2011; Kopek et al., 2012). In the pre-embedding method, the antigen–antibody reaction is performed before (i.e., pre) plastic embedding and subsequent ultrathin sectioning. While better for preserving ultra-structures, this approach is often hindered by poor penetration of the antibody. In the post-embedding method, the antigen–antibody reaction is performed after (i.e., post) plastic embedding. As labeling takes place on thin tissue slices, antigens are more easily accessible. However, OsO4, which is often used as fixative and stain for membrane structures, can quench the fluorescence signal, and epoxy-based resins used due to its good preservation and ultra-sectioning properties partially inhibit photo-switching of fluorophores (Kim et al., 2015). Here, a number of modifications, such as using acrylic resins as embedding material or replacing OsO4 with uranyl acetate, tannic acid or p-phenylenediamine, have helped to enhance compatibility and immunoreactivity (Phend et al., 1995; Osamura et al., 2000; Akagi et al., 2006; Kim et al., 2015). Complementing these slice-based assays, cells can also be prepared for analysis of surface features. As before, samples are fixed. However, rather than embedding the sample, a platinum replica of the surface is generated (Heuser et al., 1976), or the sample is subjected to critical point drying and surface staining, prior to image acquisition via SEM. Finally, one last concern is that chemical fixation is not instantaneous (Szczesny et al., 1996). To circumvent this issue, quick-freezing, where samples are 'slammed' on a super-cold block of metal sprayed with liquid helium (Heuser et al., 1976) or high-pressure freezing, where samples are frozen in milli seconds while pressure is increased to avoid water crystallization (Hunziker et al., 1984; Dahl and Staehelin, 1989), have improved preservation quality.

### Picking the Right Markers for CLEM

Unfortunately, not all markers are equally well suited for individual CLEM approaches. To account for these limitations, a series of labeling techniques has emerged. Considering its widespread availability, the most commonly used markers for CLEM are genetically encoded fluorescence tags, such as GFP, that can be detected in electron micrographs via immunogold labeling (**Figure 2A**) (Kukulski et al., 2011; Galic et al., 2012). In order to distinguish several proteins in the same sample, immuno-gold particles of variable sizes directed against different fluorescence tags can be used. However, since sample fixation may interfere with genetically encoded fluorescence markers (Muller-Reichert and Verkade, 2014) and gold particles may quench the fluorophore in parallel fluorescence/electron imaging (Kandela and Albrecht, 2007), additional markers are desirable. One such alternative relies on quantum dots (QDs; **Figure 2B**), which were shown to have a 10 times higher labeling efficiency than immuno-gold (Giepmans et al., 2005; Kuipers et al., 2015). These semiconductor nanocrystals consist of a cadmium selenide core surrounded by a zinc sulfide shell coated with affinity ligands (e.g., antibodies) for targeting the desired biomolecules (Alivisatos, 1996). Intriguingly, as the fluorescence wavelength of these photo-stable nanocrystals depends on their core size, it is possible to label samples with fluorescently different QDs, and then to distinguish individual QDs in electron micrographs by size (Giepmans et al., 2005; Kuipers et al., 2015). A minor disadvantage of QDs, however, lies in the difficulty to precisely measure sizes of small QDs due to its low contrast in EM (Brown and Verkade, 2010). While widely used, both

scanning electron microscopy (SEM) images of 70 nm section from the mouse cerebral cortex. From left to right: immunostaining of ultrathin sections for tubulin, GABA, SNAP-25, β-actin, and SEM image. Below, the boxed region is shown at a higher magnification. (C) In vitro CLEM of confocal and TEM images of hippocampal neurons. Ultrastructure of hα-Syn inclusions in cultured neurons from SNCA+/− mice shown in TEM (top), confocal image (middle), and as merged CLEM image (bottom). For illustration, the nucleus is rendered in blue, the cytosol in purple, and inclusions in yellow. To the right, high-resolution images of inclusions (red boxes 1–3), with arrowheads indicating filamentous structures, are shown. (D) In vitro CLEM of confocal and SEM images of cultured hippocampal neurons. Alignment of SEM and fluorescence signal for actin in cultured hippocampal neurons (top) and magnified sections of actin-rich convoluted nodes that form along dendritic arbors (bottom) are shown. Scale bars: (A) 25 µm at the top left, 1 µm at the top right, 0.25 µm at the bottom; (B) 10 µm at the top and 2 µm at the bottom; (C) 5 µm; (D) 2 µm. Pictures reprinted with permission from: (A) (Bishop et al., 2004); (B) (Micheva and Smith, 2007); (C) (Fares et al., 2016); (D) (Galic et al., 2014).

FIGURE 2 | Examples of markers commonly used for CLEM. (A) To the left, cartoon depicting immune-gold labeling of genetically encoded fluorescent protein. Note difference between the relative position of signal in fluorescence (yellow) and electron microscope (blue) images caused by antibodies. To the right, an example showing fluorescence and electron micrographs of HIV particle labeled with MA-EGFP on MDCK cells expressing RFP-tagged Histone 2B. (B) To the left, cartoon depicting protein and signal from QD in fluorescence (yellow) and electron microscope (blue) images. Note difference between protein epitope recognized by antibody and QD signal position. To the right, example depicting RFL6 fibroblasts fixed and stained with primary antibodies followed by secondary antibodies linked to QDs. QDs identify Cx43 at gap junctions and trafficking intermediates (green) and α-tubulin in microtubules (red). (C) To the left, cartoon depicting genetically encoded MiniSOG, as well as the relative position and signal shape for fluorescence (yellow) and electron microscope (blue) images. To the right, an example showing fluorescence and electron micrographs of HeLa cells expressing miniSOG labeled α-actinin. (D) To the left, cartoon depicting HaloTag labeling of protein as well as position and signal shape for fluorescence (yellow) and electron microscope (blue) images. To the right, an example showing fluorescence and electron micrographs of Hela cell transfected with Palmitoyl-HaloTag-meGFP. (E) Dendrites of medium-size spiny neurons in the rat neostriatum labeled with membrane-targeted GFP and immunolabeled with Cy5 against vesicular glutamate transporter2 (VGluT2; top). After detection by fluorescence microscopy, GFP and VGluT2 immunoreactivities were further developed for focused ion-beam SEM (FIB-SEM) via immunogold/silver enhancement and immunoperoxidase/DAB methods, respectively (bottom). Scale bars: (A) 5 µm to the left and 100 nm to the right; (B) 5 µm; (C) 2 µm to the left and 1 µm to the right; (D) 1 µm to the left and 500 nm to the right; (E) 3 µm. Pictures reprinted with permission from: (A) (Kukulski et al., 2011); (B) (Giepmans et al., 2005); (C) (Shu et al., 2011); (D) (Liss et al., 2015); (E) (Sonomura et al., 2013).

methods are hampered by a localization error due to spatial separation between the protein epitope and the electro-dense particle that is visualized in light and electron micrographs (Kandela et al., 2007; van Donselaar et al., 2007). To bypass this imprecision, Aptamers directed against the fluorescence tag (Shui et al., 2012) linked to gold (Javier et al., 2008; Chang et al., 2013), or nano-bodies directed against fluorescent proteins that can be conjugated to gold nanoparticles (Van de Broek et al., 2011; Ries et al., 2012) may provide promising alternatives.

Orthogonal to these approaches, several strategies have emerged that take advantage of singlet oxygen generators. Genetically encoded singlet oxygen generators are of particular relevance for samples that are investigated 'en block' (i.e., SBEM and FIB-SEM) and thus preclude post-staining of individual sections. One such example is the genetically encoded miniSOG (**Figure 2C**), which not only fluoresces when illuminated by blue light, but also yields an osmophilic reaction product by catalyzing the polymerization of 3,30 - Diaminobenzidine (DAB) into electron-dense polymers that are detectable in electron micrographs (Shu et al., 2011). The same strategy is also applicable using the Halo-Tag system, where a modified haloalkene dehalogenase (Los et al., 2008) is used to covalently bind to specific ligands such as tetramethylrhodamine (TMR; **Figure 2D**). Like miniSOG, TMR fluoresces upon illumination and is visible in EM due to DAB oxidation (Liss et al., 2015). Other self-labeling systems are provided by SNAP/CLIP-tags, in which the enzyme domain is bound to the protein of interest and labeled with a cell–permeable fluorescent ligand (Liss et al., 2015). Finally, cells can also be transfected with APEX, a non-fluorescent peroxidase that withstands strong fixation to yield light-independently EM contrast (Martell et al., 2012). However, considering that the reaction product can diffuse, these approaches may yield best results when staining enclosed structures. Notably, multiple procedures can be combined within a sample for visualization (**Figure 2E**).

### Strategies of Aligning Fluorescence Image and Electron Micrograph in CLEM

Correlation of fluorescence images and electron micrographs can be challenging for a number of reasons. For one, the region of interest can cover less than 0.0004% of the total sample area (Begemann et al., 2015), thus offering only on a limited number of reference points for navigation. And even after the region of interest acquired at the light microscope is found again on the electron microscope, rotation, magnification, and tilting angle still need to be adjusted for image alignment. This is of particular relevance in pre-embedding approaches, where, unlike to post-embedding strategies, the angle of the respective acquisition planes may differ. To tackle these obstacles, several strategies for navigation and image alignment have emerged for in situ and in vitro approaches.

For in situ CLEM, various fiduciary markers have been described that are equally suitable for pre-embedding and post-embedding strategies. In both approaches, the region of interest in the embedded sample is identified using a previously determined set of reference points. Here both, biological (e.g., blood vessels and dirt) and artificial (e.g., silica beads and gold markers) landmarks have proven to be useful for navigation. Once identified, individual EM sections are made and, if desired, 3D reconstruction of individual slices can be prepared by manual or automatic alignment using fiduciary landmarks present in adjacent sections (Bishop et al., 2004; Bock et al., 2011; Lee et al., 2016). Finally, electron micrographs (2D or 3D) are merged with the corresponding fluorescence images either manually or automatically using large features visible in both images (e.g., blood vessels and silica beads) for coarse alignment. For subsequent fine-adjustment, subcellular structures (e.g., gold fiduciary markers, nucleus, and filopodia) can be used. To estimate how accurate the alignment is, crosscorrelation analysis between light and electron micrographs can be performed.

In vitro CLEM approaches permit the generation of additional reference systems for image alignment on the plating substrate (i.e., glass and plastic). For example, a unique reference point can be created at the position where the fluorescence image is acquired, using for instance laser etching (Colombelli et al., 2008; Bishop et al., 2011; Urwyler et al., 2015) or a scratching device such as diamond objective markers (Sochacki et al., 2014). Upon processing, this reference point can then be used for navigation on the electron microscope and for subsequent image alignment. Another popular reference system relies on pre-formed structured (Svitkina, 2009; Benedetti et al., 2014) and stochastic (Begemann et al., 2015) micro-patterns or fiducial landmarks (Kukulski et al., 2011) for re-finding the region of interest on the EM as well as subsequent image alignment. Intriguingly, such reference points are not only suitable for manual alignment, but also for software-assisted solutions (Begemann et al., 2015), rendering these approaches an attractive entry point compared to more sophisticated CLEM strategies.

Finally, simultaneous fluorescence and electron imaging may provide an alternative strategy. Here, a number of custom-made (Liv et al., 2013; Nishiyama et al., 2014; Peddie et al., 2014; de Boer et al., 2015) and commercial (e.g., from Fei and Zeiss) instruments have been presented. These instruments, which are equally suitable for in situ and in vitro samples, integrate lightand electron imaging in one apparatus (iCLEM), thus ensuring dual imaging of the region of interest without need of later image alignment. However, as sample preparation for iCLEM is restricted to techniques suitable for parallel LM and EM (Agronskaia et al., 2008), and due to the limited availability of such instruments, iCLEM has not yet reached the optional users.

### CLEM–POTENTIAL AND LIMITATIONS

In this review, we have discussed possible combinations for correlating optical and electron microscopy approaches. We mentioned how improvements in imaging techniques, sample preparation, markers, and image alignment have facilitated

development of novel CLEM approaches, and showed examples where these strategies were successfully used for structurefunction analysis in neurons and synapses. In order to visualize the combinatorial potential, we provide a chart summarizing published CLEM pairings (**Figure 3**).

While correlative approaches have revealed aspects of neuronal and synaptic function that would not have been possible without it, challenges still remain due to the limited temporal and spatial resolution of CLEM. From this perspective, recent work on liquid cell electron microscopy (Ross, 2015), where electron-permeable membranes are used to host aqueous solutions under atmospheric pressure conditions for TEM and SEM imaging (Danilatos et al., 2011; Ominami et al., 2015), cryo-ET to study the supramolecular architecture of cellular structures (Medalia et al., 2002; Beck et al., 2007), and the continuous increase in sophistication and computational power used for image analysis have captured the imagination of people. While it remains elusive whether these and other emerging techniques will merge or replace CLEM-based studies, they are exemplary for an ongoing push toward visualization and comprehensive analysis of biological function on the structural level.

Taken together, the possibilities of applying correlative approaches to study neuronal and synapse function are growing thanks to the continuous progress in techniques, tools and protocols for combining these two types of microscopy. Alas, while correlative approaches in neurobiology have substantially increased in quality and availability, truly artifactfree preparation techniques for precise molecule-localization are yet to be achieved.

### AUTHOR CONTRIBUTIONS

fnsyn-08-00028 August 20, 2016 Time: 14:30 # 9

IB and MG conceived the idea, prepared illustrations for publication and wrote the manuscript.

### FUNDING

The authors acknowledge funding from the Cluster of Excellence 'Cells in Motion' (DFG, EXC-1003) to IB (PP-2014-04) and MG (FF-2016-03).

### REFERENCES

### ACKNOWLEDGMENT

The authors thank members of the Galic and Matis labs for critical reading of the manuscript.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fnsyn. 2016.00028

for measuring membrane potential. Nat. New Biol. 241, 159–160. doi: 10.1038/newbio241159a0

visualized by cryoelectron tomography. Science 298, 1209–1213. doi: 10.1126/science.1076184

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Begemann and Galic. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

## Advanced Fluorescence Protein-Based Synapse-Detectors

Hojin Lee1,2† , Won Chan Oh1† , Jihye Seong2,3\* and Jinhyun Kim1,2 \*

1 Center for Functional Connectomics, Korea Institute of Science and Technology, Seoul, South Korea, 2 Neuroscience Program, Korea University of Science and Technology, Daejeon, South Korea, 3 Center for Diagnosis Treatment Care of Dementia, Korea Institute of Science and Technology, Seoul, South Korea

The complex information-processing capabilities of the central nervous system emerge from intricate patterns of synaptic input-output relationships among various neuronal circuit components. Understanding these capabilities thus requires a precise description of the individual synapses that comprise neural networks. Recent advances in fluorescent protein engineering, along with developments in light-favoring tissue clearing and optical imaging techniques, have rendered light microscopy (LM) a potent candidate for large-scale analyses of synapses, their properties, and their connectivity. Optically imaging newly engineered fluorescent proteins (FPs) tagged to synaptic proteins or microstructures enables the efficient, fine-resolution illumination of synaptic anatomy and function in large neural circuits. Here we review the latest progress in fluorescent protein-based molecular tools for imaging individual synapses and synaptic connectivity. We also identify associated technologies in gene delivery, tissue processing, and computational image analysis that will play a crucial role in bridging the gap between synapse- and system-level neuroscience.

#### Edited by:

George Augustine, National Technical University, Singapore

#### Reviewed by:

Lucas Pozzo-Miller, The University of Alabama at Birmingham, USA Maurizio Giustetto, University of Torino, Italy

### \*Correspondence:

Jihye Seong<EMAIL_ADDRESS>Jinhyun Kim<EMAIL_ADDRESS>
†Co-first author.

Received: 09 May 2016 Accepted: 13 June 2016 Published: 30 June 2016

#### Citation:

Lee H, Oh WC, Seong J and Kim J (2016) Advanced Fluorescence Protein-Based Synapse-Detectors. Front. Synaptic Neurosci. 8:16. doi: 10.3389/fnsyn.2016.00016 Keywords: fluorescent protein sensors, synaptic connectivity, synapses, gene delivery, mapping and localization, light microscopy

### INTRODUCTION

The synapse is the primary site for neurons to make functional contacts for exchanging information. The term ''synapse'', meaning conjunction in Greek (synapsis = together + to fasten), was coined in 1897 by the eminent physiologist Charles Scott Sherrington (Nobel Laureate 1932). But the idea that synapses play critical roles as dynamically polarized, communication contacts was proposed

**Abbreviations:** 3 0UTR, 30 untranslated region; AMPAR, α-amino-hydroxy-5-methyl-4-isoxazolepropionic acid receptor; CA3, Cornu Ammonis 3; CALI, chromophore-assisted light inactivation; CaMKII, calcium/calmodulindependent kinase II; CFP, Cyanfluorescent protein; CD4, cluster of differentiation 4; ChR, Channelrhodopsin; CRISPR, clustered regularly-interspaced short palindromic repeats; ENABLED, endogenous labeling via exon duplication; EM, electron microscopy; FMN, flavin mononucleotide; FP, fluorescent protein; fSPIM, fluorescent selective plane illumination microscopy; GFP, green fluorescent protein; HA, hemagglutinin; HSV-1, Herpes simplex virus-1; iDISCO, immunolabeling-enabled three-dimensional imaging of solvent-cleared organs; ID-PRIME, Interaction-Dependent Probe Incorporation Mediated by Enzymes; InSynC, Inhibition of Synaptic Release with CALI; KI, knock-in; LAP, lipoic acid acceptor peptide; LM, light microscopy; LOV2, light, oxygen, and voltage 2; LpIA, lipoic acid ligase; mGluR, metabotropicglutamate receptors;mGRASP,MammalianGFPReconstitutionAcrossSynapticPartners;miniSOG,mini small singlet oxygen generator; NCBI, National Center for Biotechnology Information; NS3, Nonstructural protein 3; OFP, Orangefluorescent protein; PDZ, PSD-95, Drosophila disc large tumor suppressor (Dlg1), and zonula occludens-1 protein (zo-1); PSD-95, postsynaptic density protein-95; rAAV, recombinant adeno-associated virus; SM protein, Sec1/Munc18-like protein; SNARE, SNAP (Soluble N-ethylmaleimide-sensitive factor attachment protein) Receptor; syb, synaptobrevin; spGFP, split-GFP; sypHTomato, Synaptophysin-fused pHTomato; TimeSTAMP, Time-Specific Tagging for the Age Measurement of Proteins; VAMP2, vesicle-associated membrane protein 2; VenusNT, Venus N-terminal; VenusCT, Venus C-terminal; VGluT, vesicular glutamate transporter; YFP, Yellow fluorescent protein.

by Santiago Ramon y Cajal (Nobel Laureate 1906). Since then, the synapse as a structural and functional communication unit has been in the spotlight of neuroscientific inquiry (Cowan et al., 2001). In fact, many studies have demonstrated that synaptic events, such as changes in molecular composition, structure, efficacy, and potentiation, play important roles in brain functions including memory formation, perception, and other complex behaviors (Tsien et al., 1996; Markram et al., 1997; Malinow and Malenka, 2002; Russo et al., 2010; Caroni et al., 2014). An important focus has been to visualize the synapse and to measure its activity. In 1954, DeRobertis and Palay first observed synapses independently by electron microscopy (EM) and George Gray suggested there may be different types of synapses, i.e., excitatory and inhibitory (De Robertis and Bennett, 1955; Palay and Palade, 1955; Palay, 1956; Gray, 1959). EM provides enough resolution for nanometer-scale imaging of the synaptic ultrastructure, something that cannot be achieved by light microscopy (LM) because of its diffraction limit. However, despite recent advances that have reduced the time needed for image acquisition and reconstruction, EM remains inherently time-consuming, laborintensive, and volume-limited for large neural circuits.

With the recent engineering of fluorescent proteins (FPs) and new developments in light-favoring tissue clearing and advanced optical methods, LM is rising as a potent alternative tool for investigating individual synapses in the context of neural networks (Gray, 1959; Keller et al., 2008; Kim et al., 2012; Tomer et al., 2012; Chung et al., 2013; Richardson and Lichtman, 2015). Imaging the synapse with LM by using newly engineered FPs tagged to synaptic proteins or targeted to synaptic structures enables fine-resolution illumination of synaptic anatomy and function in large neural circuits, possibly in real-time. In this review, we describe recent FP-based molecular tools for imaging individual synapses and synaptic connectivity in the contexts of single- and dual component synaptic detection. We also identify crucial technologies: gene delivery of molecular synapse detector; tissue clearing for whole-brain imaging; and computational analysis, whose parallel development has potential to bridge synaptic sensor engineering and systems neuroscience. We end by proposing a scheme of technological integration for synaptic neuroscience at the systems level.

### SINGLE COMPONENT SYNAPTIC DETECTION

The discovery of green fluorescent protein (GFP) and its derivatives revolutionized the visualization of biological phenomena, including the individual synapse and its functions. GFP and other FPs are relatively inert and small (27 kDa) and can be used to tag synaptic proteins while minimally interfering with their normal functions. In fact, the distribution, trafficking, and physiological changes of synaptic proteins caused by neural activity became evident in the last two decades, largely through observations of synaptic proteins, such as synaptophysin (Li and Murthy, 2001) vesicle-associated membrane protein 2 (VAMP2; Ahmari et al., 2000), postsynaptic density protein-95 (PSD-95; Nelson et al., 2013) calcium/calmodulin-dependent kinase II (CaMKII; Shen et al., 2000), α-amino-hydroxy-5 methyl-4-isoxazolepropionic acid receptor (AMPAR; Zamanillo et al., 1999) and so forth, that had been tagged with FPs. Recently, sophisticated molecular engineering has allowed even more precise and detailed visualization of synaptic structure, composition, and physiology (Chen et al., 2014; Fortin et al., 2014; **Figure 1**, **Table 1**).

### pH-Sensitive FPs for Visualizing Vesicle Release: pHluorin, pHTomato, and pHuji

Although previous, straightforward, FP-based detection of synaptic distribution revealed many important details of synaptic physiology, synaptic vesicle release/recycling and neural activitydriven changes in membrane-bound synaptic proteins are difficult to be detected by regular FP-tagging. Special sensors of vesicle secretion and neurotransmission have been developed by linking vesicle membrane proteins with pH-sensitive mutants of GFP called pHlourin (Miesenböck et al., 1998). The fluorescence intensity of pHluorin largely depends on the pH of its biochemical environment: in acidic environments with pH below 6.5, pHluorin is mostly nonfluorescent in 480 nm of light illumination, but becomes highly fluorescent in neutral environments with pH around 7.4. This special feature of pHluorin was achieved by several mutations on residues important for the proton-relay of tyrosine 66 in the chromophore (S147D, N149Q, T161I, S202F, and Q204T). These amino acid substitutions, which set the pKa of pHluorin to around 7.0, can facilitate the pH-dependent switching of the electrostatic environment of the chromophore, allowing the pHdependent changes in fluorescent intensity (Sankaranarayanan and Ryan, 2000). When pHluorin is fused to presynaptic vesicle proteins such as VAMP2 (Miesenböck et al., 1998), synaptophysin (Zhu et al., 2009), and vesicular glutamate transporter (vGluT; Voglmaier et al., 2006), the release and recycle of synaptic vesicles can be monitored as the pH inside the synaptic vesicles (∼5.5) transitions to the pH of the extracellular environment (∼7.4). Thus, by tracking changes in pHluorin fluorescence intensity, one can detect real-time presynaptic exocytosis in living, active neurons. Similarly, postsynaptic endo-/exo-cytosis and related receptor dynamics can be visualized by pHluorin-fused mGluRs, for instance (Pelkey et al., 2007).

More recently, red pH-sensitive FPs such as pHTomato (Li and Tsien, 2012) and pHuji (Shen et al., 2014) have been developed, allowing for the simultaneous monitoring of multiple synaptic activities when combined with the green GFP-based sensors (e.g., GCaMP). pHTomato (pKa ∼ 7.8) was derived from mStrawberry by introducing six mutations (F41T, F83L, S182K, I194K, V195T, and G196D). Synaptophysin-fused pHTomato (sypHTomato) has been shown to be suitable for simultaneously monitoring the fusion of synaptic vesicles and, when paired with GCaMP3, postsynaptic Ca2+ changes in living neurons. In addition, multiple synaptic events have been successfully measured by using sophisticated combinations of these pHsensitive FP-fused synaptic proteins and spectrally distinct variants of optogentic stimulators (ChR2-T2A-vGluT-pHlourin

FIGURE 1 | Scheme of single component synapse detectors. (A) Graphical depiction of the conventional green fluorescent protein (GFP) tagging scheme and summary of the expressed carrier-sensor construct. GFP (green circle) and other fluorescent proteins (FPs) are directly tagged to synaptic proteins in the presynaptic terminal or postsynaptic spines. Major targets for tagging include presynaptic vesicle proteins (e.g., vesicle-associated membrane protein 2 (VAMP2) and synaptophysin), postsynaptic receptors (e.g., α-amino-hydroxy-5-methyl-4-isoxazolepropionic acid receptor, AMPAR) and postsynaptic density protein-95 (PSD-95). (B) pH-sensitive FP mutants are fused to synaptic vesicle membrane proteins, such as VAMP2, to visualize vesicle secretion/recycling and neurotransmission. A pH-sensitive GFP variant, pHluorin does not fluoresce (gray circle) when inside the acidic chemical environment of the synaptic vesicle, but becomes highly fluorescent (green circle) when the vesicle is released and exposed to the neutral extracellular environment. (C) Inhibition of Synaptic Release with CALI (InSynC): attached to target SNARE proteins, molecular actuators such as mini small singlet oxygen generator (miniSOG; light blue filled-in circle) selectively inactivate specific synaptic proteins that regulate vesicle release and other synaptic events. When illuminated with blue light, miniSOG stimulates generation of reactive oxygen species (small, dark blue filled-in circles), which then oxidizes susceptible amino acid residues in target vesicle proteins and deactivates protein functions. (D) TimeSTAMP effectively tracks spatiotemporally controlled protein synthesis and trafficking in living neurons. In the presence of a membrane-permeable protease inhibitor, NS3 protease (gray oval) activity is inhibited, and Venus C-terminus (Venus CT) and Venus N-terminus (Venus NT) reconstitute as fluorescent Venus (yellow circle). Reconstituted Venus accumulates in the postsynaptic spine, the trafficking destination of the fused PSD-95. When the protease inhibitor is present, however, NS3 protease cleaves the protease target sites (gray circles flanking NS3), preventing Venus reconstitution.

and VChR1-T2A-synpHTomato). However, the pH-sensitivity of pHTomato is relatively low (3-fold change in pH 5.5–7.5). Thus, a new red pH-sensitive FP, named pHuji, has been more recently derived from mApple (Shaner et al., 2008) by including a K163Y mutation, resulting in high pH sensitivity (20-fold change in pH 5.5–7.5). The use of different colored pH-sensitive FPs together with a Ca2+ indicator and/or a spectrally distinct optogenetic modulator offers a new promising readout system for complex, coordinated synaptic events.

## Inhibition of Synaptic Release with CALI (InSynC)

Beyond merely visualizing the distributions and endo-/exocytosis of synaptic proteins by tagging them with FPs and their pHsensitive variants, genetically encoded chromophore-assisted light inactivation (CALI) has been developed to selectively inactivate specific synaptic protein functions that regulate synaptic events such as synaptic release (Lin et al., 2013). CALI is based on light-induced generation of reactive oxygen and the consequent inactivation of nearby attached synaptic proteins. Its original agents were synthetic chromophores for example malachite green (Jay, 1988), fluorescein (Beck et al., 2002), FlAsH (Marek and Davis, 2002), ReAsH (Tour et al., 2003), and eosin (Takemoto et al., 2011) and FPs such as KillerRed (Bulina et al., 2006). To precisely inhibit synaptic release with improved target specificity and inactivation efficiency compared to these CALI agents, inhibition of synaptic release with CALI (InSynC) has been recently developed using a newly engineered flavoprotein called mini small singlet oxygen generator (miniSOG), fused with the SNARE proteins VAMP2 and synaptophysin (Lin et al., 2013). miniSOG was originally derived from the light, oxygen, and voltage 2 (LOV2) domain of phototropin, a blue light photoreceptor (Shu et al., 2011). Under blue light illumination, this photoreceptor binds to and excites flavin mononucleotide (FMN), which then functions as an oxygen generator in cells. miniSOG contains the single amino acid substitution of FMN-binding residue Cys426 to Gly on the LOV2 domain, allowing for more efficient energy transfer to FMN, and contains further mutations for enhanced brightness. When illuminated by blue light, synaptic proteins can be selectively inactivated by miniSOG-mediated oxidization of susceptible residues such as tryptophan, tyrosine, histidine, cysteine, and methionine. InSynC by miniSOG can selectively inhibit vesicle release at individual synapses in vitro and in vivo thanks to the high efficiency of its light-induced oxygen generation, independence of exogenous cofactors, and small size (106 residues, 14 kDa; Lin et al., 2013). However, further engineering is required for investigating the functional dynamics of synaptic circuits with physiologically relevant temporal resolutions, as inactivation by InSynC persists relatively long (∼1 h) after light stimulation.

### Time-Specific Tagging for the Age Measurement of Proteins (TimeSTAMP)

Another new strategy beyond merely visualizing synaptic proteins by tagging with FPs is time-specific tagging for the age measurement of proteins (TimeSTAMP; Lin et al., 2008). As spatiotemporally controlled protein synthesis and trafficking are critical for synaptogenesis, synaptic connectivity, and long-lasting changes in synapses, TimeSTAMP is beneficial for tracking important, newly synthesized synaptic proteins such as PSD-95 and CaMKII in living neurons. TimeSTAMP is a drug-controllable, time-specific tagging strategy based on the hepatitis C virus NS3 protease and its cell-permeable inhibitor BILN-2061. PSD-95-GFP, for example, was fused to NS3 protease flanked by NS4A/B target sites and the C-terminal HA tag (PSD-95-GFP-TS-HA). In the absence of the specific inhibitor BILN-2061, NS3 protease cleaves the NS4A/B target sites allowing the C-terminal HA-tag to be cleaved from PSD-95-GFP and degraded; but drug application will allow the HA-tag to be accumulated. This allows distinguishing between newly and previously synthesized PSD-95 by measuring HA/GFP signals at a time defined by the drug application. For the TimeSTAMP strategy, the NS3 protease domain was chosen because it is small (19 kDa) and monomeric, specific to its substrate, and not cytotoxic, and most of all, NS3 shows high selectivity and efficiency of its cell-permeable inhibitor.

Although the first version of TimeSTAMP has worked successfully in primary hippocampal neurons to track PSD-95 accumulation during synaptic growth, and in Drosophila for whole-brain mapping of newly synthesized CaMKII, it required post hoc immunostaining against epitope tags, limiting the benefits of pulse-chase labeling through time. Thus, TimeSTAMP2 has been introduced, replacing HAtag with split-fluorescence proteins (e.g., Yellow fluorescent protein, YFP; Orange fluorescent protein, OFP). In fluorescent TimeSTAMP2, for instance, Venus yellow fluorescent protein is separated by an NS3 domain flanked by NS4A/B target sites into VenusNT (1-158 aa) and VenusCT (159-238 aa) for drug-dependent fluorescence. In the absence of BILN-2061, VenusCT is cleaved and degraded by the active NS domain resulting in no yellow fluorescence, while VenusNT and CT are reconstituted as fluorescent forms after drug application. This allows optical pulse labeling of synaptic proteins such as PSD-95 and Neuroligin with a drug-defined temporal resolution. Additionally, photo-oxidizing TimeSTAMP using miniSOG inserted into TS:YFP can be used to visualize new proteins at an EM-based ultrastructural level (Butko et al., 2012).

### DUAL COMPONENT SYNAPTIC DETECTION

Thus far, we have described methods for detecting synapses by labeling single components, either pre- or post-synaptic. Although these single-component tools allow for detecting, measuring, and manipulating synaptic structures and activities, they do not address the critical fact that synapses are bilateral microstructures involving both presynaptic terminal and postsynaptic density. For reliable synapse detection, therefore, several recent studies introduced new methods for labeling synaptic interactions between pre- and post-synaptic components, such as using split-FPs or enzymes to label neurexin-neuroligin interactions. Here we review dual-component methods using handshaking-like transmembrane molecular interaction across the synaptic cleft, with particular attention to GFP Reconstitution Across Synaptic Partners (GRASP; **Figure 2**, **Table 1**).

### Mammalian GFP Reconstitution Across Synaptic Partners (mGRASP)

To detect particular synaptic connections with LM, the Mammalian GFP Reconstitution Across Synaptic Partners (mGRASP) technique takes advantage of the complementarity of two non-fluorescent split-GFP fragments, each of which is tethered specifically to the pre- and postsynaptic membrane, respectively (Kim et al., 2012). When two neurons, each expressing one of the fragments, are closely opposed across a

synaptic cleft, the split fragments are reconstituted as fluorescent GFP in that location. This dual component synapse detection bypasses the Abbe's diffraction limit and allows relatively rapid and accurate synapse mapping with LM. This method takes advantage of the fast folding kinetics and stability after maturation of superfolder GFP (Pédelacq et al., 2006), split into two fragments, namely spGFP1-10 (first 214 residues comprising ten β barrels) and spGFP11 (16 residues, 11th βbarrel strand). The GRASP technique was initially implemented in C. elegans (Feinberg et al., 2008; Park et al., 2011) and later in Drosophila (Gordon and Scott, 2009; Fan et al., 2013; Gorostiza et al., 2014). In the original GRASP constructs, membrane carriers (human CD4) for split-GFP fragments were not synapse-specific—fluorescence could arise wherever any membranes expressing fragment pairs were closely apposed. This became a critical issue for mammalian synapse detection because the mammalian nervous system contains much more compactly intermingled neurites than the invertebrate nervous system.

In a previous study, we engineered and successfully applied mGRASP for mapping fine-scale synaptic connectivity in the mouse brain (Kim et al., 2012). The primary features of mGRASP include targeting specific synapses, and matching the approximately 20 nm-wide synaptic cleft without gross changes in endogenous synaptic organization and physiology. Based on published sequences from NCBI, we generated synapsespecific chimeric carriers. Both the pre- and postsynaptic mGRASP components share a common six-subcomponent framework: (1) a signal peptide; (2) a split-GFP fragment; (3) an extracellular domain; (4) a transmembrane domain; (5) an intracellular domain; and (6) a fluorescent protein for neurite and soma visualization. The presynaptic mGRASP component consists of the signal peptide of nematode βintegrin (PAT-3, residues 1–29), GFP β-strand 11 (spGFP11, 16 residues), two flexible GGGGS linkers, the extracellular and transmembrane domains of human CD4-2 (residues 25–242). Rat neurexin-1β (residues 414–468) containing the PDZ-binding motif constitutes the intracellular domain for maintenance of correct localization at the presynaptic site. mCerulean is fused to the intracellular end of the presynaptic mGRASP to visualize axonal expression. The postsynaptic mGRASP component is based primarily on mouse neuroligin-1, which interacts with presynaptic adhesion proteins including β-neurexins, and mediates the formation and maintenance of synapses between neurons. To prevent nonspecific synaptogenesis through interactions with its

endogenous partner, neurexin, the extracellular esterase domain of neuroligin is deleted in the main skeleton of the postsynaptic mGRASP. Similar to presynaptic mGRASP, post-mGRASP is composed a signal peptide from the esterase-truncated neuroligin-1 (residues 1–49), GFP βstrand 1-10 (spGFP1-10, 648 residues), the extracellular, transmembrane, and intracellular regions of neuroligin (71, 19, and 127 residues, respectively), followed by the selfcleavable 2A peptide-fused dTomato for visualizing postsynaptic neuronal morphology. This optimized mGRASP enabled the comprehensive synaptic connectivity mapping of hippocampal CA3-CA1 and identified spatially structured patterns of synaptic connectivity (Druckmann et al., 2014). It is important to note that brain-wide synapse detection for comprehensive fine-scale mapping becomes achievable not only by advanced molecular engineering to label the synapse such as mGRASP, but also by appropriately engineered computational analysis (Feng et al., 2012, 2015).

Current GRASP technology has proved to be a tool suitable for rapid and accurate mapping of synaptic connectivity in nematode (Feinberg et al., 2008), fruit fly (Gordon and Scott, 2009), and mouse (Kim et al., 2012; Druckmann et al., 2014). Yet, further improvements to GRASP such as multi-colored FPs for analyzing convergent synaptic inputs, various carriers for neural activities, and tailored computational analyses will provide a clear overview of complex synaptic connectivity and its operation. We next discuss recent efforts in these directions.

### Engineering FPs for Multi-Color GRASP

A neuron oftentimes receives multiple inputs from different presynaptic neurons of distinct cell types and/or various brain areas. For comprehensive mapping of complex synaptic circuits, multiple synaptic detection is beneficial, as described earlier in the section describing pH-sensitive FPs. The current version of GRASP restricts convergent synaptic mapping because it relies on only a single pair of spGFP fragments such that spectral overlap of its signals hinders simultaneous imaging with previously well-established GFPbased tools such as GCaMP. Therefore, the multi-color GRASP (XRASP) components have been developed recently (Macpherson et al., 2015; Li et al., 2016). Given that Cyan fluorescent protein (CFP), GFP, and YFP have identical structures except for several residues in the chromophore located in beta barrels of 1-10, C-RASP and Y-RASP were generated by color-shifting mutations in spGFP1-10 (Y66W, S72A, F145A∗ , N146I, and H148D for C-RASP, ∗ additional mutation in Li et al., 2016, T65G, V68L, S72A and T203Y for Y-RASP) paired with the unaltered spGFP11 (Li et al., 2016). Multi-color GRASP (XRASP) was tested in vivo in several circuits, including the Kenyon cells of the mushroom body, and projection neurons of the thermosensory and olfactory systems in the fruit fly. Reconstructed CFP and YFP signals showed minimal spectral overlap with the GRASP emission and excitation spectra. Extended choices of multicolor GRASP (XRASP) will allow simultaneous imaging of multiple, convergent connectivity and functional activity. However, more red-shifted XRASP is required for in vivo 2-photon imaging together with Ca2+ indicators and for fine-scale synapse labeling from multiple inputs within the single neuron, because it has proved difficult to separate CFP/GFP/YFP signals in the complex mammalian nerve system.

### Engineering Carriers for Activity-Dependent GRASP

To understand functional organizations underlying complex brain functions that go beyond structural connectivity patterns, it will be essential to identify active synaptic connectivity at defined times and conditions. For the activity-dependent GRASP system, synaptobrevin (syb), a key constituent of synaptic vesicle membrane, was used as a synaptic carrier instead of constantly membrane-targeted carriers in the previous GRASP systems. The straightforward fusion of syb and spGFP1-10 (syb:spGFP1-10) with the original CD4:spGFP11 can together form activity-dependent GRASP, called the syb:GRASP system. Given activity-dependent interactions of syb with SNARE-SM protein complex triggering synaptic vesicle release, syb:GRASP showed preferential labeling of active synapses as a boost of GRASP fluorescence signals in well-studied thermosensory and olfactory circuits in the fruit fly (Macpherson et al., 2015). This new strategy for mapping active synaptic connectivity might expedite the mapping of functional connectivity at the synapse level in a way previously achieved only by difficult combinations of Ca2+ imaging and exhaustive EM reconstruction (Bock et al., 2011; Briggman et al., 2011). Yet, these new techniques raise basic concerns about possible side effects caused by the overexpression of key synaptic vesicle proteins, and need further optimization before they can be applied to mammalian networks.

### FP- and Enzyme-Based Visualization of Neuroligin-Neurexin Interaction

An alternative way to detect synapses has been suggested by imaging neurexin-neuroligin interactions. Presynaptic neurexin and postsynaptic neurolign are transmembrane adhesion proteins and their interaction at the synaptic cleft has been believed to be a key process for synaptic formation, maintenance, and connectivity (Li and Sheng, 2003; Graf et al., 2004; Chen et al., 2010; Krueger et al., 2012). Therefore, it is thought that identifying sites of neurexin-neuroligin interactions could provide selective visualization of synapses. Similar to the GRASP approaches, this method, based on neuroligin-neurexin interactions using splitGFP, is called SynView. It is composed of spGFP1- 10-inserted neurexin-1β between residues N275-D276 or A200-G201 for the presynaptic component, and the split-GFP11-inserted neuroligin-1 in the C-terminal end of the extracellular esterase (between Q641-Y642) for the postsynaptic component (Tsetsenis et al., 2014). Another method for visualizing neuroligin-neurexin interactions is based on mutated bacterial lipoic acid ligase (LpIA) and lipoic acid acceptor peptide (LAP) tags (Uttamapinant et al., 2010, 2012), and is called Interaction-Dependent Probe Incorporation Mediated by Enzymes (ID-PRIME; Liu et al., 2013). Using the same principle of SynView, ID-PRIME was designed to detect trans-synaptic contacts of neurexin and neuroligin enzymatically using lipoic acid. These two methods successfully imaged the direct interactions of neurexin-neuroligin synaptic adhesive molecules. However, these methods seem restricted to particular investigations of the dynamics of neurexinneuroligin, rather general synaptic mapping. In addition, it is known that overexpressing these synaptic adhesion molecules causes substantial structural and physiological perturbations of normal synaptic compartments and cleft structures.

### BRIDGING TOOLS BETWEEN MOLECULAR SYNAPSE DETECTORS AND BRAIN-WIDE SYNAPSE MAPPING

Thus far, we have described methods for detecting synapses focusing on molecular engineering. To exert these genetically encoded synapse detectors to brain-wide synaptic mapping at the system level, there need to be critically partnered technologies such as gene delivery, advanced imaging, and digital representation platform that are appropriate for neural system (**Figure 3**).

### Gene Delivery System for Synapse Detectors in the Mouse Brain

Improving the targeting specificity for types of cells and scaling up the scope of synaptic sensor delivery are among the crucial initial steps needed to expand single-synapse level analysis to systems level neuroscience. Gene delivery technologies, particularly for the nervous system, have developed at a breathtaking pace over the past decades, establishing methodologies that can be classified into two main categories: germ line manipulation and viral injection.

### Genetic Manipulation-Based Gene Delivery

To avoid side effects that can sometimes be caused by the overexpression of FP-tagged synaptic proteins, and to mimic expression patterns of endogenous proteins, gene knockin (KI) technology has been used to substitute wild-type genes with FP-tagged copies. For synaptic detectors based on universal synaptic proteins such as PSD-95, however, this standard KI method leads to expression of FP-tagged synapse detectors globally, throughout the brain, which makes it difficult to acquire high resolution images of a particular cell type. Therefore, a recent study introduced a conditional KI strategy called endogenous labeling via exon duplication (ENABLED; Fortin et al., 2014). In the ENABLED strategy, a knocked-in gene cassette is composed of the floxed last exon and 3'UTR of PSD-95 followed by its mVenus-tagged duplicated last exon and 3'UTR. The FP-tagged duplicated gene will be selectively expressed only in Cre-expressing neurons because its translation is designed to be blocked by translation stop signals in the endogenous copy in the absence of Cre recombinase. When this PSD-95-ENABLED mouse line is crossed with a dopaminergic cell-type specific DAT-Cre line, for instance, PSD-95mVenus is expressed specifically in dopaminergic neurons. PSD-95-ENABLED was shown to functionally replace wild-type PSD-95 and to sparsely label a particular cell-type, allowing insights into the detailed distribution and dynamics of synapses. In applying this strategy to a wide variety of synaptic proteins, one concern with using the ENABLED strategy is that it is limited to synaptic proteins that are compatible with C-terminal FPtagging.

Thanks to incredibly fast developments and improvements in genetic manipulation technologies such as clustered regularlyinterspaced short palindromic repeats (CRISPR) and effector nucleases Cas system (Cong et al., 2013; Wang et al., 2013; Fujii et al., 2014; Aida et al., 2015), the generation of synapse detector KI mouse lines is becoming time- and cost-efficient, and is dramatically facilitating synapse mapping.

### Viral System-Based Gene Delivery

Spatially targeted gene delivery into the mature brain can be achieved through stereotactic microinjection of viral vectors expressing FP-tagged proteins. Diverse virus families have been recruited into this effort: Retroviridae (e.g., lentivirus), Parvoviridae (e.g., rAAV), Adenoviridae (e.g., canine adenovirus), and Alphaviridae (e.g., sindbis virus), including some that cross the synapse, such as Rhabdoviridae (e.g., rabies virus) and Herpesviridae (e.g., HSV-1 and pseudorabies virus; Nassi et al., 2015). Because of their low cytotoxicity and stable expression, lentiviruses and rAAVs are the most widely used viral vectors in neuroanatomical tracing studies and human clinical trials testing gene therapy. In fact, spatially restricted injection of Cre-(in)dependent rAAV vectors have been used for mGRASP-assisted synaptic mapping.

In parallel, ongoing efforts include searching for and engineering new types of virus to allow transduction efficiency/ specificity and retrograde infection. Canine adenovirus has drawn attention because of its strong retrograde transport capability and relatively large payload size (∼30 kb); further, several successful applications of Canine adenovirus in the mouse brain suggest a powerful complement to the lentivirus and rAAV (Bru et al., 2010; Ekstrand et al., 2014; Junyent and Kremer, 2015; Schwarz et al., 2015). Additionally, systemic delivery of viral vectors in animal models has proved to be effective and safe for various serotypes of AAV (Foust et al., 2009; Bevan et al., 2011; Gray et al., 2011; Yang et al., 2014; Deverman et al., 2016).

### Advanced Brain-Wide Imaging and Digital Representation of Synaptic Detectors

Once FP-based synaptic detectors are introduced into the brain as described above, appropriate brain-wide imaging and digital representation technologies are necessary to map synaptic connectivity. Happily, there has been remarkable progress in tissue clearing methodology such as BABB (Dodt et al.,

GRASP (mGRASP) constructs and newly engineered serotypes that have more selective tropism and transduction efficiency (e.g., AAV-PHP.B). Local tissue or systemic injection of such viral systems can lead to flexible, versatile gene delivery in mature organisms. (B) Combination of light-favoring brain clearing, whole-brain imaging, and computational techniques for three-dimensional synapse mapping enables single-synapse level analysis of synaptic profiles across the whole brain. Further improvements in lipid extraction, refractive index matching, advanced light-sheet microscopy, and large-scale data processing and 3D reference space generation will accelerate systems neuroscience at the synaptic scale.

2007), CUBIC (Susaki et al., 2014) 3DISCO (Ertürk et al., 2012), immunolabeling-enabled three-dimensional imaging of solvent-cleared organs (iDISCO; Renier et al., 2014), SeeDB (Ke et al., 2013) and CLARITY (Chung et al., 2013; Tomer et al., 2014) that are needed to prepare the intact brain for imaging while avoiding distortions caused by physical sectioning. These new clearing techniques, together with advanced optical methods such as fluorescent selective plane illumination microscopy (fSPIM; Huisken et al., 2004), will allow high-throughput whole brain imaging. Also, once images are acquired, digital representation programs are necessary to reliably extract synaptic wiring information from the images, and to bring data from different sections and animals into register with one another (Johnson et al., 2010; Oh et al., 2014). Improvements in this software will be greatly beneficial.

In our view, new clearing methods, optics, and tailored computational analysis platforms together with advanced synaptic detectors such as mGRASP are very promising developments for the complete mapping of mammalian synaptic connectivity.

### CONCLUSION AND PERSPECTIVE

Here we reviewed new FP-based synapse detection techniques, which are useful for rapidly imaging individual synapses and synaptic connectivity in the whole brain with LM. Recent technical developments have allowed a focus of neuroscience to move from individual synapses to ensemble interactions among neurons of various cell types through multiple synaptic pathways. Comprehensively mapping individual synapses in the whole

### REFERENCES

brain will provide firm grounds for further anatomical and functional studies and such mapping is essential for analyzing large-scale information processing phenomena. We believe that rapid, scalable synaptic cartography with the triad of singlesynapse resolution, brain-wide scope, and cell-type-specific connectivity requires a synergistic combination of advanced technologies, and that FP-based neurosensors are the key to this grand integrative project.

### AUTHOR CONTRIBUTIONS

HL, WCO, JS, and JK wrote this manuscript.

### ACKNOWLEDGMENTS

HL, WCO, JK, and JS are supported by the Korea Institute of Science and Technology (KIST) Institutional Program (2E26190 and 2N41660, respectively) and the Samsung Science and Technology Foundation.

structural plasticity in nucleus accumbens. Trends Neurosci. 33, 267–276. doi: 10.1016/j.tins.2010.02.002

**Conflict of Interest Statement**: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Lee, Oh, Seong and Kim. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Organelle-Specific Sensors for Monitoring Ca2+ Dynamics in Neurons

### Seok-Kyu Kwon, Yusuke Hirabayashi and Franck Polleux\*

Department of Neuroscience, Mortimer B. Zuckerman Mind Brain Behavior Institute, Kavli Institute for Brain Science, Columbia University Medical Center, New York, NY, USA

Calcium (Ca2+) plays innumerable critical functions in neurons ranging from regulation of neurotransmitter release and synaptic plasticity to activity-dependent transcription. Therefore, more than any other cell types, neurons are critically dependent on spatially and temporally controlled Ca2+ dynamics. This is achieved through an exquisite level of compartmentalization of Ca2+ storage and release from various organelles. The function of these organelles in the regulation of Ca2+ dynamics has been studied for decades using electrophysiological and optical methods combined with pharmacological and genetic alterations. Mitochondria and the endoplasmic reticulum (ER) are among the organelles playing the most critical roles in Ca2+ dynamics in neurons. At presynaptic boutons, Ca2+ triggers neurotransmitter release and synaptic plasticity, and postsynaptically, Ca2+ mobilization mediates long-term synaptic plasticity. To explore Ca2+ dynamics in live cells and intact animals, various synthetic and genetically encoded fluorescent Ca2+ sensors were developed, and recently, many groups actively increased the sensitivity and diversity of genetically encoded Ca2+ indicators (GECIs). Following conjugation with various signal peptides, these improved GECIs can be targeted to specific subcellular compartments, allowing monitoring of organelle-specific Ca2+ dynamics. Here, we review recent findings unraveling novel roles for mitochondria- and ER-dependent Ca2+ dynamics in neurons and at synapses.

#### Edited by:

Marc Fivaz, Duke NUS Graduate Medical School, Singapore

Reviewed by:

Lucas Pozzo-Miller, University of Alabama at Birmingham, USA William N. Green, University of Chicago, USA

> \*Correspondence: Franck Polleux<EMAIL_ADDRESS>
Received: 13 June 2016 Accepted: 30 August 2016 Published: 16 September 2016

#### Citation:

Kwon S-K, Hirabayashi Y and Polleux F (2016) Organelle-Specific Sensors for Monitoring Ca2+ Dynamics in Neurons. Front. Synaptic Neurosci. 8:29. doi: 10.3389/fnsyn.2016.00029 Keywords: synapse, mitochondria, endoplasmic reticulum, circuit function, calcium dynamics

### INTRODUCTION

Calcium (Ca2+) ions govern prevalent physiological processes in various cell types (Rizzuto and Pozzan, 2006; Clapham, 2007). This is especially prominent in excitable cells like neurons where Ca2+ influx through the plasma membrane and release of Ca2+ from internal stores transduce the effects of changes in membrane polarization and therefore mediate faithful transfer or storage of information over various timescales (milliseconds to minutes/hours). Therefore, regulation of intracellular Ca2+ homeostasis is central to the proper function of neuronal circuits. The maintenance of baseline levels of intracellular Ca2+ levels is regulated in part through exchangers and pumps such as the plasma membrane Ca2+-ATPase (PMCA pump), the Na+/Ca2+ exchanger (NCX), and the Na+/Ca2+-K+ exchanger (NCKX) which extrude Ca2+ through the plasma membrane into the extracellular space. In addition to these mechanisms, intracellular organelles, such as mitochondria and endoplasmic reticulum (ER), are able to regulate cytoplasmic Ca2+ ([Ca2+]c) through mitochondrial calcium uniporter (MCU) and smooth endoplasmic reticulum Ca2+-ATPase (SERCA), respectively.

In neurons, mitochondria and ER play important physiological roles via [Ca2+]c regulation, thereby diverse synaptic functions including basal synaptic transmission, presynaptic short-term plasticity, and long-term plasticity can be regulated by these organelles (Verkhratsky, 2005; Bardo et al., 2006; Mattson et al., 2008; Vos et al., 2010). In addition, impaired Ca2+ homeostasis in the nervous system has been proposed to play an important function in the physio-pathological mechanisms underlying Alzheimer's disease, Parkinson's disease, and spinocerebellar ataxia (Verkhratsky, 2005; Mattson et al., 2008; Schon and Przedborski, 2011).

To monitor Ca2+ dynamics, various fluorescent Ca2+ dyes and genetically encoded Ca2+ indicators (GECIs) were developed and applied both in vitro and in vivo. Also, GECIs tagged with target peptide sequences have allowed imaging of Ca2+ dynamics in specific organelles (Rizzuto et al., 1992; Palmer et al., 2004; Palmer and Tsien, 2006).

Previously published reviews have already summarized the usefulness and limitations of various Ca2+ sensors and GECIs applied to neuronal and non-neuronal cells (Palmer and Tsien, 2006; Knopfel, 2012; Tian et al., 2012; Rose et al., 2014). In this review, we only describe recently uncovered insights about Ca2+ dynamics and its regulation by mitochondria and ER, and we discuss how these organelle-specific Ca2+ sensors have been used for the exploration of the role of these subcellular compartments in the regulation of Ca2+ homeostasis and synaptic function in neurons.

### UNVEILED SYNAPTIC FUNCTIONS OF MITOCHONDRIA-DEPENDENT Ca2+ HOMEOSTASIS

Mitochondrial Ca2+ uptake has been studied since the 1950s from studies of rat heart muscle and kidney (Slater and Cleland, 1953; Deluca and Engstrom, 1961). In the nervous system, mitochondria were described at presynaptic terminals and dendrites of various neuronal subtypes using the light and electron microscope (EM) several decades ago (Bartelmez and Hoerr, 1933; Palay, 1956; Gray, 1963; Shepherd and Harris, 1998; Rowland et al., 2000). In axons, mitochondria are short and sparsely distributed, and interestingly, several studies showed that half of presynaptic boutons are occupied by mitochondria (Shepherd and Harris, 1998; Kang et al., 2008). In contrast, dendritic mitochondria have tubular shapes and they are rarely observed in postsynaptic spines in the excitatory neurons (Sheng and Hoogenraad, 2007; Kasthuri et al., 2015).

At presynaptic boutons and terminals, synaptic vesicle (SV) fusion with the plasma membrane occurs following increase of [Ca2+]c following opening of voltage-sensitive Ca2+ channels (VSCC) followed by Ca2+ binding to sensors like synaptotagmins (Schneggenburger and Neher, 2005; Neher and Sakaba, 2008; Jahn and Fasshauer, 2012; Südhof, 2012). The ability of mitochondria to import Ca2+ into the mitochondrial matrix ([Ca2+]m) plays a role in regulating presynaptic [Ca2+]c. This has been characterized in various species, neuronal cell types and circuits (**Figure 1A**). At the Drosophila neuromuscular junction (NMJ), the GTPase dMiro mutant lacks presynaptic mitochondria through impaired axonal transport (Guo et al., 2005; Wang and Schwarz, 2009). During prolonged stimulation, these mutants lacking presynaptic mitochondria displayed subtle, but significantly increased presynaptic Ca2+ accumulation and display decrease forms of sustained synaptic transmission or synaptic ''fatigue'' (Guo et al., 2005). Drosophila Drp1 mutants also deplete presynaptic mitochondria at NMJ and exhibit elevated presynaptic Ca2+ levels in resting and evoked states. However, spontaneous release (mini Excitatory junctional potential, mEJP) was not altered, but the evoked synaptic transmission was impaired during high frequency stimulation, and this defect was partially rescued by ATP (Verstreken et al., 2005) suggesting that mitochondria plays a role in synaptic transmission through their ability to generate ATP through oxidative phosphorylation. Although mitochondrial Ca2+ uptake has limited effects on Drosophila NMJ neurons, in mammalian NMJ terminals, acute inhibition of mitochondrial Ca2+ uptake causes rapid depression of the endplate potential (EPP) and increased asynchronous release (David and Barrett, 2003). Furthermore, in synapses of the mammalian central nervous system (CNS), mitochondria-dependent Ca2+ uptake accelerates the recovery from synaptic depression in the calyx of Held (Billups and Forsythe, 2002). Other studies in mammalian hippocampal neurons claimed that impaired mitochondrial anchoring at presynaptic sites increases presynaptic Ca2+ during repetitive stimulation and produces short-term facilitation (STF), and insulin-like growth factor-1 receptor (IGF-1R) signaling regulates resting mitochondrial Ca2+ level and spontaneous transmission (Kang et al., 2008; Gazit et al., 2016). Although most pharmacological studies employed uncoupling agents as mitochondrial Ca2+ influx blocker, which may affect ATP production, these reports support presynaptic control via mitochondrial Ca2+ import (Ly and Verstreken, 2006). A recent study demonstrates that presynaptic boutons associated with mitochondria display lower levels of [Ca2+]c accumulation than presynaptic boutons not associated with mitochondria (Kwon et al., 2016). Furthermore, acute inhibition of mitochondria calcium import increased [Ca2+]c accumulation at presynaptic boutons occupied by mitochondria. In the same study, we demonstrate that this mitochondria-dependent regulation of [Ca2+]c plays an important role in regulating presynaptic release properties including spontaneous release, asynchronous release and short-term synaptic plasticity.

In addition to regulation of [Ca2+]c clearance, Ca2+ release from mitochondria plays important roles at presynaptic sites (**Figure 1A**). Following the sustained high frequency stimulation, an enhancement of synaptic transmission lasting tens of seconds to minutes is observed and which is called post-tetanic potentiation (PTP; Zucker, 1989). Mitochondrial Ca2+ release is suggested as one of the underlying mechanisms for this prolonged enhancement of synaptic transmission. Pharmacological inhibition of mitochondrial Ca2+ uptake and release at the crayfish NMJ impaired PTP (Tang and Zucker, 1997; Zhong et al., 2001). Furthermore,

similar phenotypes were observed at mouse NMJ and hippocampal mossy fiber synapses with blocking the mitochondrial NCX, which mediates mitochondrial Ca2+ release (García-Chacón et al., 2006; Lee et al., 2007).

In contrast to presynaptic boutons and terminals, the postsynaptic function of mitochondrial Ca2+ regulation is less well-documented. In mouse hippocampal pyramidal neurons (Li et al., 2004), a minority (<5%) of dendritic spines contains mitochondria. Also, large branched spines in hippocampal CA3 contain mitochondria (Chicurel and Harris, 1992). However, a physiological role of these postsynaptic mitochondria is largely unknown. In general, mitochondria are distributed primarily in dendrite shaft and therefore localized microns away from the postsynaptic density, but might still be able to buffer [Ca2+]c mobilized through Ca2+-channels and glutamate receptors (Thayer and Miller, 1990; White and Reynolds, 1995; Wang and Thayer, 2002). This mitochondrial calcium import can stimulate tricarboxylic acid (TCA) cycle and might increase ATP production (Kann and Kovács, 2007) and may also regulate other ATP-dependent Ca2+ pumps like PMCA and SERCA. While it is still unclear whether or not mitochondria play significant roles in regulating postsynaptic [Ca2+]c under physiological conditions of neurotransmission, they might play a role in pathophysiological contexts. For example, neurons lacking LRRK2, a protein associated with Parkinson's disease, show impaired dendritic Ca2+ homeostasis through mitochondrial defects and thought to cause defective mitochondrial depolarization and reduction in dendritic complexity (**Figure 1B**; Cherra et al., 2013).

Overall, mitochondria-dependent Ca2+ clearance and release in neurons plays important physiological and developmental roles pre- and post-synaptically but their functional importance seems to depend on the neuronal subtypes and the structure/size of the pre- and postsynaptic compartments.

### MITOCHONDRIAL Ca2+-IMAGING IN NEURONS AND AT SYNAPSES

To investigate organelle-specific Ca2+ dynamics, various Ca2+ sensors are developed (**Table 1**). One of the first method developed to monitor mitochondrial Ca2+ dynamics was established using rhod-2, a cationic chemical Ca2+-binding fluorophore preferentially accumulating in the mitochondrial matrix presumably because of the highly negative membrane potential across the mitochondrial inner membrane (Minta et al., 1989). Then, in the calyx of Held, rhod-2 and rhod-FF (low affinity version) were used to visualize presynaptic mitochondrial Ca2+ transient (Billups and Forsythe, 2002). However, these dyes cannot be precisely targeted to these organelles. Therefore, GECIs have recently become the preferred method to image Ca2+ in specific organelles including mitochondria. For mitochondrial matrix localization, the targeting presequence of subunit VIII of human cytochrome c oxidase (COXVIII) was tagged to GECIs (Rizzuto et al., 1992). Mitochondria-targeted aequorin (mt-AEQ), a luminescent Ca2+ indicator, was first employed to monitor the neuronal mitochondrial Ca2+, and this probe showed NMDA-induced mitochondrial Ca2+ increase in hippocampal neurons (Baron et al., 2003). However, this probe needs a chemical reaction characterized by a modest turnover rate and has very limited dynamic range (Palmer and Tsien, 2006). Other GECIs have been developed and tested in various neuronal subtypes with the same targeting sequence. Mitochondrial-targeted ratiometric pericam (2mtRP) consists of circularly permutated Enhanced yellow fluorescent protein (cpEFYP) conjugated with Ca2+-responsive calmodulin (CaM) and its binding peptide (Nagai et al., 2001; Robert et al., 2001). This probe has a bimodal excitation spectrum and the relative emission intensity is dependent on Ca2+-binding. In hippocampal neurons, the use of 2mtRP described mitochondrial Ca2+ uptake and also determined cytosolic Ca2+ rise upon synaptic activation via dual imaging with cytosolic Ca2+ dye (fura-red AM; Young et al., 2008). Other CaM conjugated cpEGFPs called GCaMPs (mito-GCaMP2, 2mtGCaMP6m, and mito-GCaMP5G) were used to monitor axonal mitochondrial Ca2+ (Gazit et al., 2016; Kwon et al., 2016; Marland et al., 2016). Both sensors displayed action potential (AP)-dependent mitochondrial Ca2+ import. In addition, red fluorescent GECIs by replacing cpEGFP with cpmApple or cpmRuby (mtRCaMP1e and LAR-GECO1.2) revealed mitochondrial Ca2+ import simultaneously with cytosolic Ca2+ (Akerboom et al., 2013; Wu et al., 2014).

However, these fluorescent proteins have some limitations, for example, they are affected by pH and mitochondrial matrix pH (pHm) can be changed by Ca2+ influx (Abad et al., 2004; Poburko et al., 2011; Chouhan et al., 2012; Marland et al., 2016). In addition to this point, [Ca2+]m can span broad ranges (0.05–300 µM) depending on cell types and stimulation protocol (Arnaudeau et al., 2001; Palmer and Tsien, 2006). Thus, Kd value for Ca2+ of mitochondrial GECI should be considered for experimental purposes because high affinity (low Kd) sensors can be easily saturated by high [Ca2+]m and low affinity (high Kd) sensors may not be sensitive enough to detect small [Ca2+]m changes. Several studies reported low affinity mitochondrial Ca2+ probes for avoiding saturation (Arnaudeau et al., 2001; Suzuki et al., 2014).

In conclusion, these mitochondria-targeted GECIs allow imaging of mitochondria Ca2+ dynamics in neurons and have revealed interesting, synapse-specific properties of mitochondria in the regulation of [Ca2+]c and neurotransmitter release properties.

### REGULATION OF SYNAPTIC Ca2+ DYNAMICS BY THE ENDOPLASMIC RETICULUM

Neurons are among the most polarized cell types in our body and consists of a soma, relatively short dendrites and long axons. ER is found throughout the entire length of neuronal processes, and usually rough ER is prominent in the cell body and proximal dendrites, whereas smooth ER is dominant in distal dendrites, spines and axons (Spacek and Harris, 1997; Verkhratsky, 2005). ER imports and sequesters large amount of Ca2+ ([Ca2+]er ∼500 µM) through SERCA and store-operated Ca2+ entry (SOCE) mechanism (Verkhratsky, 2005; Bardo et al., 2006). Ca2+ release from ER is mediated by two major mechanisms, called Ca2+-induced Ca2+ release (CICR) and IP3-induced Ca2+ release (IICR; Verkhratsky, 2005; Bardo et al., 2006). CICR is caused by the cytosolic Ca2+ increase through N-Methyl-D-Aspartate receptors (NMDAR, GluN receptors) and voltage-gated Ca2+ channels (VGCCs), whereas IICR is triggered by IP3, which is generated via activation of phospholipase C (PLC) depending on metabotropic glutamate receptors (mGluRs) or other receptors like receptor tyrosine kinases (**Figure 1**).

Ryanodine receptors (RyRs) are involved in CICR, and they have three major subtypes; RyR1, RyR2, and RyR3.  Similar to RyRs, IP3 receptor (IP3R), which mediate IICR,

#### TABLE 1 | Organelle-specific Ca2+ sensors in neurobiology.

consist of three isoforms, IP3R1, IP3R2, and IP3R3, but IP3R1 is the dominant form in the brain (Sharp et al., 1993, 1999; Verkhratsky, 2005; Bardo et al., 2006; Baker et al., 2013).

Long-term synaptic plasticity is regulated by Ca2+ dependent signaling mechanisms such as Ca2+/calmodulindependent kinase II (CaMKII), calcineurin (a Ca2+-dependent phosphatase), protein phosphatase 1 (PP1) and protein kinase C (PKC; Malenka and Nicoll, 1999; Yang et al., 1999; Lüscher and Malenka, 2012). Therefore, Ca2+ release from intracellular stores like the ER regulates long-term synaptic plasticity in specific circuits.

In cerebellar Purkinje cell dendrites, mGluR-IP3-dependent Ca2+ increase is observed during parallel fiber (PF) stimulation and this mediates long-term depression (LTD) of PF-Purkinje cell pathway (Finch and Augustine, 1998; Takechi et al., 1998; Miyata et al., 2000; Wang et al., 2000). At synapses made by hippocampal Schaffer collateral (SC) onto CA1 pyramidal neurons, both long-term potentiation (LTP) and LTD are linked to IP3-dependent signaling (Oliet et al., 1997; Nishiyama et al., 2000; Raymond and Redman, 2002; Nagase et al., 2003). In addition, CICR is also observed in CA1 pyramidal neuronal spines, and LTD is abolished in RyR3-deficient mice and following application of RyR inhibitor (ryanodine) although the connection between CICR and LTP is controversial in SC-CA1 pathway (Reyes and Stanton, 1996; Emptage et al., 1999; Futatsugi et al., 1999; Sandler and Barbara, 1999; Kovalchuk et al., 2000; Nishiyama et al., 2000; Raymond and Redman, 2002). Hippocampal mossy fiber pathway (MF, dentate gyrus to CA3) shows IICR- and CICR-dependent LTP and LTD, however, there are conflicting results regarding the underlying mechanisms (**Figure 1B**; Yeckel et al., 1999; Itoh et al., 2001; Kapur et al., 2001; Mellor and Nicoll, 2001; Lauri et al., 2003; Lei et al., 2003).

Presynaptic ER-dependent Ca2+ release is also detected and contributes to changes in neurotransmitter release properties and short-term synaptic plasticity at various inhibitory and excitatory synapses including basket cell to Purkinje cell synapses, hippocampal MF pathway, SC-CA1 and CA3-CA3 pyramidal neuron synapses (**Figure 1A**; Llano et al., 2000; Emptage et al., 2001; Liang et al., 2002; Galante and Marty, 2003; Lauri et al., 2003; Sharma and Vijayaraghavan, 2003; Unni et al., 2004; Mathew and Hablitz, 2008).

In addition to Ca2+ efflux, Ca2+ uptake by ER via SERCA pump affects STF at SC-CA1 presynapses and NMJ (**Figure 1A**; Castonguay and Robitaille, 2001; Scullin and Partridge, 2010; Scullin et al., 2010). Stromal interaction molecules (STIMs) and Orai1, which allow SOCE, are localized to neuronal compartment including dendritic spines, and impaired SOCE alters α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) trafficking, neuronal Ca2+ signaling and LTP in CA1 pyramidal neuron and cerebellar Purkinje neurons (Baba et al., 2003; Hartmann et al., 2014; Korkotian et al., 2014; Garcia-Alvarez et al., 2015; Segal and Korkotian, 2015).

### IMAGING NEURONAL ER Ca2+ DYNAMICS

As mentioned above, ER contains high levels of Ca2+, therefore, in order to monitor Ca2+ dynamics in the ER lumen, low affinity sensors were employed. Mag-Fura-2, a low affinity membranepermeable dye (Kd = 53 µM), has been the first applied for neuronal ER Ca2+ measurement, and after loading this dye in the cytoplasm and organelles, cytosolic dye was removed by perfusion with dye-free pipette solution (Solovyova et al., 2002). This allowed for the first time the visualization of caffeineinduced Ca2+ release and reuptake in the ER of dorsal root ganglia (DRG) neurons (**Table 1**).

However, this method can non-specifically label internal compartments, therefore, genetically targeted sensors have been developed more recently for the visualization of ER-derived Ca2+ dynamics (**Table 1**). The signal sequence of calreticulin, a Ca2+ binding protein in ER, and an ER retention sequence, KDEL, lead GECIs into the ER lumen, and to optimize for measuring a massive amount of [Ca2+]er, various mutations were applied to the CaM domain or EF-hand motif of existing GECIs for reducing their Ca2+ affinity. A fluorescence resonance energy transfer (FRET)-based Ca2+ sensor, D1ER, showed altered ER Ca2+ leak function in hippocampal neurons of presenilin double knockout and Alzheimer's disease model mice (Zhang et al., 2010). Also, bioluminescence-based sensor, GFP-Aequorin protein (GAP), was modified and targeted to ER of DRG and hippocampal neurons, and showed 3- to 4-fold larger ratio change than D1ER (Rodriguez-Garcia et al., 2014). In addition, recently established GCaMP variants for ER Ca2+ detection, calcium-measuring organelle-entrapped protein indicator one in the ER (CEPIA1er) and GCaMPer (10.19), characterized ER Ca2+ uptake and release in cortical neurons and cerebellar Purkinje cells (Suzuki et al., 2014; Henderson et al., 2015). Interestingly, cerebellar Purkinje cells displayed differential ER Ca2+ dynamics in postsynaptic compartment depending on the nature of synaptic inputs (Okubo et al., 2015). These lumenal ER Ca2+ indicators also revealed interesting dynamics in dendritic spines, which suggest that [Ca2+]er and therefore [Ca2+]c can undergo synapse-specific regulation (Suzuki et al., 2014; Henderson et al., 2015).

### FUTURE PERSPECTIVES

Recent studies characterized the roles of presynaptic mitochondria and circuit-specific ER Ca2+ mobility in dendrites directly via live imaging (Okubo et al., 2015; Kwon et al., 2016), however, organelle-specific Ca2+ dynamics at local synapses

### REFERENCES

is only beginning to be explored. Genetically-encoded Ca2+ sensors targeted to intracellular organelle and/or to specific synapses as well as functional indicators (like pHluorin-tagged synaptophysin or GluRs) will lead to the identification of synapse- and circuit-specific roles of mitochondria and ER Ca2+ in neurons.

MCU has been recently shown to be associated with multiple regulatory proteins, which seems to modify or gate its gating properties and can prevent or enhance mitochondrial Ca2+ uptake upon changes in cytosolic Ca2+ dynamics (Perocchi et al., 2010; Mallilankaraman et al., 2012; Csordás et al., 2013; Plovanich et al., 2013; Raffaello et al., 2013; Sancak et al., 2013; De Stefani et al., 2015). In addition, MCU activity can be differentially controlled in different tissues (Fieni et al., 2012). Therefore, future investigations should probe the function of this MCU-regulatory complex in neurons and test if MCU and/or MCU-associated proteins can act as neuronal subtype-specific and/or synapse-specific functional modifiers.

In non-neuronal cells, ER and mitochondria establish focal connections which play a key role in Ca2+ transfer from ER to mitochondria which has been characterized via intra- and inter-organelle Ca2+ imaging (Rizzuto et al., 1993, 2012; Csordás et al., 2010; Kornmann, 2013). This transfer modulates ATP production in mitochondria and may also affect lipid exchange between these two organelles (Voelker, 1990; Cárdenas et al., 2010; Fujimoto and Hayashi, 2011). At present, in neurons, the role of Ca2+ translocation between ER and mitochondria is largely unknown. Although immuno-EM images in vivo and Ca2+ imaging with dyes in respiratory motor neurons suggested ER-mitochondria Ca2+ crosstalk, future work will need to establish the context in which ER-mitochondria interface regulates Ca2+ dynamics and synaptic function (Takei et al., 1992; Shoshan-Barmatz et al., 2004; Mironov and Symonchuk, 2006).

### AUTHOR CONTRIBUTIONS

All three authors co-wrote the manuscript.

### FUNDING

This work was partially funded by support from the NIH-NINDS (R01NS067557, FP), Japan society for the promotion of science fellowship for research abroad and The Uehara Memorial Foundation (YH), and a grant from the Human Frontier Science Program long-term fellowship (S-KK).

Neurosci. Biobehav. Rev. 37, 1211–1239. doi: 10.1016/j.neubiorev.2013. 04.011

**Conflict of Interest Statement**: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Kwon, Hirabayashi and Polleux. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Understanding Synaptogenesis and Functional Connectome in *C. elegans* by Imaging Technology

Jung-Hwa Hong1, 2 and Mikyoung Park 1, 3 \*

*1 Center for Functional Connectomics, Korea Institute of Science and Technology, Seoul, South Korea, 2 Department of Life Sciences, Korea University, Seoul, South Korea, 3 Department of Neuroscience, Korea University of Science and Technology, Daejeon, South Korea*

Formation of functional synapses is a fundamental process for establishing neural circuits and ultimately for expressing complex behavior. Extensive research has interrogated how such functional synapses are formed and how synapse formation contributes to the generation of neural circuitry and behavior. The nervous system of *Caenorhabditis elegans*, due to its relatively simple structure, the transparent body, and tractable genetic system, has been adapted as an excellent model to investigate synapses and the functional connectome. Advances in imaging technology together with the improvement of genetically encoded molecular tools enabled us to visualize synapses and neural circuits of the animal model, which provide insights into our understanding of molecules and their signaling pathways that mediate synapse formation and neuronal network modulation. Here, we review synaptogenesis in active zones and the mapping of local connectome in *C. elegans* nervous system whose understandings have been extended by the advances in imaging technology along with the genetic molecular tools.

#### *Edited by:*

*George Augustine, Nanyang Technological University, Singapore*

#### *Reviewed by:*

*Fabrice Ango, University of Montpellier, France Antonio Malgaroli, Università Vita-Salute San Raffaele, Italy*

#### *\*Correspondence:*

*Mikyoung Park<EMAIL_ADDRESS><EMAIL_ADDRESS>
*Received: 25 April 2016 Accepted: 17 June 2016 Published: 29 June 2016*

#### *Citation:*

*Hong J-H and Park M (2016) Understanding Synaptogenesis and Functional Connectome in C. elegans by Imaging Technology. Front. Synaptic Neurosci. 8:18. doi: 10.3389/fnsyn.2016.00018* Keywords: presynaptic assembly, synaptic specificity, synaptogenesis, functional connectome, neural circuits, imaging, *C. elegans*

### INTRODUCTION