To test whether the activity related to the hypothetical outcomes from a particular target changed with the animal’s choice (Figure S5), the following model was applied separately for each combination of chosen and unchosen targets Fulvestrant cell line in loss and tie trials for experiment I. M8i:y=bo+bhHwinFor experiment II, another regressor was included to factor out the effect of actual outcome from the chosen target. M8ii:y=bo+blossOloss+bhHwinThen, the correlation coefficient between the standardized regression coefficients (bh) estimated for two different choices was calculated for the same unchosen winning target. As a control analysis, we also calculated

the correlation coefficient between the regression coefficients associated with BKM120 the same chosen target but two different unchosen winning targets. The angular difference in the retinal positions of the unchosen targets during the feedback period was matched for these two analyses (Figure S5). Therefore, if the activity related to hypothetical outcome merely reflected the properties of visual receptive

fields, these two correlation coefficients would be similar. To test whether the neurons significantly modulating their activity according to a particular factor (e.g., AOC or HO) are anatomically segregated from the remaining neurons, MANOVA was applied to their anatomical locations with the statistical significance as the factor (Figure 3; Figure S3). For this analysis, neurons recorded in all the animals were combined separately for the DLPFC and OFC. We thank MRIP Irina Bobeica, Mark Hammond, and Patrice Kurnath for their technical assistance. This work was supported by Kavli Institute for Neuroscience at Yale University and US

National Institute of Health grants (DA029330 and EY000785). “
“Synapse formation and elimination are fundamental elements in both the initial construction of neural circuits and the experience-dependent modification of the mature nervous system (Sanes and Lichtman, 1999 and Trachtenberg et al., 2002). During development, refinement of neural connectivity after axon guidance and dendrite morphogenesis are characterized by dynamic, regulated synaptogenesis and synapse elimination (Cline, 2001 and Hua and Smith, 2004). Even in mature animals, a certain amount of “synapse turnover” is maintained, suggesting that a balanced synapse formation and elimination are likely required for the maintenance of circuit functions. It is generally believed that neuronal activity drives the modification of neural circuits through strengthening and weakening connectivity between neurons (Balice-Gordon and Lichtman, 1994 and Goda and Davis, 2003). Although a large body of work has focused on the molecular mechanisms of synapse formation, less is known about the process of synapse elimination. Very few studies have focused on the mechanisms that coordinate synaptogenesis and synapse elimination.

5 mM Sr2+ and increasing Mg2+ to 3.3 mM. To minimize voltage-clamp errors, we recorded CF-PC EPSCs either between −65 mV and −70 mV in the presence of 600–800 nM NBQX or at depolarized potentials (−15 to −10 mV). Drugs were applied in the bath or via a flow pipe (ValveLink 8.2, Automate Scientific, Berkeley, CA). KYN and NBQX were purchased from Ascent Scientific (Princeton, NJ), TBOA, cyclothiazide (CTZ), and (2S,1′S,2′S)-2-(carboxycyclopropyl) glycine (L-CCG-I) were purchased

from C646 Tocris Bioscience (Ellisville, MO). Picrotoxin was purchased from Sigma (St. Louis, MO). Whole-cell recordings were made from visually identified PCs with a gradient contrast system by using a 60 × water-immersion objective on an upright microscope selleck products (Olympus BX51WI). Pipettes were pulled from either PG10165 glass (WPI,

Sarasota, FL) with resistances of 0.8–1.5 MΩ or BF150-110 borosilicate glass (Sutter Instrument Co., Novato, CA) with resistances of 1–1.5 MΩ. The series resistance (Rs), measured by the instantaneous current response to a 1–2 mV step with only the pipette capacitance cancelled, was <5 MΩ (usually <3 MΩ) and routinely compensated >80%. CFs were stimulated (2–10 V, 20–200 μs) with a theta glass electrode (BT-150 glass, Sutter Instrument Co., Novato, CA) filled with extracellular solution placed in the granule cell layer. The paired-pulse ratio (50 ms interstimulus interval) was determined after the stimulation train. Responses were recorded with a MultiClamp 700B amplifier (Molecular Devices, Sunnyvale, CA), filtered at 4–10 kHz, and digitized (Digidata 1440A, Molecular Devices) at 50–100 kHz by using Clampex 10 acquisition software (Molecular Devices). Pipette solutions PD184352 (CI-1040) for EPSC recordings contained 35 mM CsF, 100 mM CsCl, 10 mM EGTA, 10 mM HEPES,

and 5 mM QX314, adjusted to pH 7.2 with CsOH or 9 mM KCl, 10 mM KOH, 120 mM K gluconate, 3.48 mM MgCl2, 10 mM HEPES, 4 mM NaCl, 4 mM Na2ATP, 0.4 mM Na3GTP, and 17.5 mM sucrose (pH 7.25 with KOH) for current-clamp recordings. In current-clamp recordings, PCs were injected with a negative current (<500 pA) to maintain a membrane potential between −65 and −70 mV during synaptic stimulation (−66.9 ± 0.8 mV at 0.05 Hz and −68.4 ± 0.8 mV at 2 Hz; n = 26; p > 0.05). The frequency of synaptic stimulation did not alter the CpS plateau potential from which spikelets were generated (−41.0 ± 0.9 mV at 0.05 Hz and −44.0 ± 1.1 mV at 2 Hz; n = 26; p > 0.05). For experiments described in Figure 7, the membrane potential was also kept at approximately −70 mV. The peak amplitude of the injected current used to evoke complex-like spikes varied across cells (5–18 nA, corresponding to peak conductances of 70–250 nS). The maximal rate of spikelet rise was measured from differentiating the CpS waveform. Spikelets and their height were determined from trough to peak by setting the peak detection threshold to within 2%–10% of the maximum peak with a separating valley of adjacent peaks of <90%.

Commands from the behavioral control computer synchronized the robotic movements of the objective stage with voluntary head restraint to move the objective into imaging position with each insertion. Using this approach, the objective could be held at a safe position (typically 1 mm) above the imaging position, selleck chemicals llc then lowered to the imaging position during restraint, and finally retracted to the safe position prior to release of the kinematic clamp. A necessary

criterion for successful in vivo imaging is that brain motion artifacts are small enough so that they are addressable through software (Dombeck et al., 2007). To quantify the performance of this aspect of the combined microscope and head-restraint apparatus, we measured across-trial

registration and within-trial brain motion during voluntary head restraint in eight Selleck Verteporfin trained rats by imaging GCaMP-labeled neurons in AGm (six rats) or V1 (four rats) through an implanted optical window (Figure 4C, see Experimental Procedures). Prior to implantation of the window, the dura was removed and AAV-GCaMP3 (AGm and V1) or AAV-GCaMP6s (V1) was injected into layer II/III of the exposed cortical region. One to four weeks after implantation of the optical window, GCaMP fluorescence was observed in the perinuclear somata and processes of neurons (Figure 4D). For analysis of brain motion, images of GCaMP-labeled neurons were acquired at a rate of 10 Hz over a 6–8 s head restraint period (Figure 5). Motion correlated with the activation of the kinematic clamp limited visibility during the first few hundred milliseconds of the behavioral trial, delaying the start of the effective imaging period until approximately 600 ms after the initiation of head restraint (Figure 5A).

In addition, when an immersion fluid objective was employed, optical distortions caused by the removal of immersion fluid prevented image acquisition in the last 500 ms of the head-restraint trial. In vivo trial-to-trial displacement (4.7 μm in x, 8.4 μm in y, 3.5 μm in z; Figures 5B, 5C, and S3) was slightly larger than that measured by manual insertion of an isolated headplate. In most cases these registration errors could be corrected by offline image registration Liothyronine Sodium algorithms (see Experimental Procedures). However, on a subset of trials in which the immersion objective was used (10.0% ± 11.5%, n = 13/130 trials), no visible image was produced. This problem was caused by loss of imaging fluid, by the formation of bubbles in the imaging fluid, or by movements of the rat’s head after it had triggered a behavioral trial but before the kinematic clamp was fully engaged. Nevertheless, because of the large number of trials performed per day, the loss of 10% of imaging did not significantly impact the utility of the immersion objective.

, 1997). Progesterone and its metabolites FG-4592 supplier are produced in the brain and participate in stress responses (Wirth, 2011), and thus progesterone and glucocorticoid receptors could contribute to interactions between nicotine and ethanol. Our demonstration that nicotine enhances ethanol-induced VTA GABA transmission through a stress hormone signal is consistent with evidence that GABAergic

neuroactive hormones contribute to ethanol self-administration (Biggio et al., 2007, Helms et al., 2012 and Morrow et al., 2009). These results complement previous studies showing a critical role for glucocorticoids in alcohol reward and in the transition to compulsive alcohol drinking (Rotter et al., 2012 and Vendruscolo et al., 2012). We found no evidence of long-term changes in nAChR function after one nicotine exposure. However, activation of nAChRs in the brain stem may contribute to the initial response of the HPA axis to nicotine (Armario, 2010), which our results suggest involves high-affinity β2∗ nAChRs (Figure 2A). Blocking the initial stress hormone response

locally in the VTA prevented the long-term alterations in ethanol-induced DA release (Figure 5B) and thus identified the VTA as a locus for mechanistic interactions between nicotine and ethanol. Interestingly, local VTA infusion of RU486 to antagonize stress receptors did not completely reverse the effects of nicotine pretreatment on ethanol-induced DA release compared to the saline control. This incomplete effect Navitoclax clinical trial could arise from a partial diffusion of RU486 in the VTA, but it is also feasible that nicotine pretreatment acted outside of the VTA to induce neuroadaptations that regulate DA signals. In summary, we provide evidence that nicotine pretreatment decreases ethanol-induced DA transmission owing to increased GABAergic inhibition onto DA neurons. These responses to nicotine pretreatment, including increased ethanol intake, required an initial stress hormone signal. These results support the hypothesis that the actions of drugs of abuse recruit neuroendocrine pathways (Kenna

et al., 2012, Koob, 2008 and Richards et al., Histone demethylase 2011). Our data suggest a neurophysiological basis for the observation that nicotine use can increase the reinforcing properties of alcohol. Long-Evans rats (Harlan Sprague) weighing between 300–500 g were used. The rats were handled and weighed for at least 3 days and commonly more than a week prior to surgery and testing, and the rats were housed in a humidity-and temperature-controlled (22°C) environment under a 12 hr light/dark cycle. The rats had food and water available ad libitum in the home cage. All procedures complied with guidelines specified by the Institutional Animal Care and Use Committee at Baylor College of Medicine. For the microdialysis experiments, each animal was implanted with an intravenous catheter through the jugular vein and a stainless steel guide cannula (21G) (Plastics One). The surgery occurred under isoflurane anesthesia (1.5%–2.

Additionally, by alternating blocks in which the animals needed to detect orientation and spatial frequency changes they could compare responses find more when one or the other feature was attended and isolate the effects of feature-based attention ( McAdams and Maunsell, 2000). The authors found that populations of V4 neurons could independently show both types of attentional modulation. For example, a neuron could be modulated by spatial attention but not by feature-based attention and vice-versa. One main difference between the effects of spatial and feature-based attention was that the former enhanced responses of neurons within the hemisphere

contralateral to the attended stimulus, while the buy Compound Library latter enhanced neuronal responses in both hemispheres, irrespective of the attended stimulus location. The feature-based attentional modulation was dependent on the relationship between the attended stimulus feature and the cell’s preferred feature (FSG, see Figure 2 of Cohen and Maunsell [2011]). For example, the response of a neuron when animals attended to a particular orientation was enhanced if the unit preferred that orientation but was suppressed if the attended orientation was antipreferred. FSG, as opposed to FM, produces enhanced or suppressed responses in neurons

with receptive fields containing stimuli with the target features, depending Metalloexopeptidase on the units’ feature selectivity

(Treue and Martínez Trujillo, 1999). Moreover, recording from 96 electrodes at a time (48 in each hemisphere) allowed the authors to examine the impact of spatial and feature-based attention on spike count correlations, a variable that has been shown to be influenced by the allocation of attention (Cohen and Maunsell, 2009 and Mitchell et al., 2009). V4 units showing increases in response by both spatial- and feature-based attention show decreases in correlation, while V4 units showing response decreases by either type of attention showed increases in correlation. This suggests that response modulation and correlated firing are two sides of the same coin. Any variable that increases or decreases the firing rate of visual neurons to sensory stimuli (e.g., changes in contrast or adaptation) will likely produce decreases or increases in correlated firing, respectively, and therefore will influence the ability of neuronal populations to encode visual information. Supporting this hypothesis, spike count correlations between pairs of MT neurons decrease when increasing stimulus contrast (Huang and Lisberger, 2009). The exact mechanisms of these effects need to be elucidated.

In confirmation, we also found increased levels of phosphorylated p130-CAS, a downstream substrate of FAK, in mutants ( Figure S3C). To establish a system in which we could manipulate neurons pharmacologically and genetically, we cultured dissociated neurons from Pcdh-γdel/del and control cortex. To label the morphology of individual neurons at random, we lipofected cultures (∼1%–5% efficiency) with a construct encoding YFP and measured dendrite

arborization by Sholl analysis at 2, 8, and 14 days in vitro (DIV). Y-27632 chemical structure Consistent with in vivo analyses, we found that dendrite complexity was significantly reduced in mutant neurons ( Figures 4A, 4B, and 4I; Figures S4A–S4F). As expected for homophilic adhesion molecules, loss of the γ-Pcdhs affected dendrite arborization in a cell-autonomous manner, as

shown by Cre transfection of individual Pcdh-γfcon3/fcon3 neurons ( Figures S4G and S4H). Next, we cultured check details cortical neurons in the presence of three pharmacological inhibitors. We broadly inhibited PKC isoforms with Gö6983 (Gschwendt et al., 1996), which significantly rescued dendrite arborization in mutant neurons toward control levels (Figures 4E and 4I), as did the addition of U73122, a potent inhibitor of PLC activity (Bleasdale et al., 1989) (Figures 4G and 4I). A recently characterized inhibitor of FAK, PF-573228 (referred to as PF-228; Slack-Davis et al., 2007), completely rescued the phenotype, increasing arborization in mutant neurons such that they were indistinguishable from controls (Figures 4A, 4C, 4F, and 4I). MARCKS associates with the plasma membrane in part through a basic effector domain (ED). PKC phosphorylation

of four serines in the ED causes MARCKS to lose its associations with actin and the membrane (Swierczynski and Blackshear, 1995 and Hartwig et al., 1992). In hippocampal neurons, transfection of MARCKS or a nonphosphorylatable version with all four ED serines mutated to asparagines (N/S-MARCKS), but not a pseudophosphorylated mutant with these serines replaced by aspartates (D/S-MARCKS) (Spizz and Blackshear, 2001), led to significant increases in dendrite arborization (Li et al., 2008). We tested these constructs for their ability to rescue arborization in Pcdh-γ mutant neurons. Cultures were Electron transport chain transfected at 1 DIV and fixed for Sholl analysis at 8 DIV; all MARCKS constructs were efficiently expressed in transfected neurons ( Figures S4I–S4K). Compared to controls, both MARCKS-GFP and N/S-MARCKS-GFP (but not D/S-MARCKS-GFP) greatly increased arborization in mutant neurons to levels even above those of untransfected control neurons ( Figures 4D, 4H, and 4I). Although these experiments alone cannot exclude the possibility that γ-Pcdhs affect dendrite branching through a distinct pathway parallel to the PKC pathway, this is unlikely.

Taken together, the studies presented herein indicate that the rate at which vitamin D therapy is administered can have a significant impact on treatment outcomes. Further, they support continued investigation of MR calcifediol as a treatment of SHPT

in patients with CKD and vitamin D insufficiency. Support for these studies was provided by OPKO Health, Renal Division. We thank Drs. Christian Helvig and Dominic Cuerrier for technical suggestions. M.P. is supported by funding from the Canadian Institutes of Health Research. “
“Most animals have to cope with important environmental changes caused by the day/night selleck chemical cycle. Their physiology and behavior are therefore temporally controlled and optimized with their ever-changing environment. Twenty-four hour (circadian) rhythms are generated by intracellular pacemakers called circadian clocks, which consist of interlocked transcriptional feedback loops that control the rhythmic expression check details of clock-controlled genes. In Drosophila, the PERIOD (PER) feedback loop generates transcriptional rhythms that peak in the early night, while the PAR Domain Protein1/VRILLE (PDP1/VRI) feedback loop generates rhythms with a peak

in the early day ( Hardin, 2006). These two interlocked feedback loops are connected by the dimeric transcription factor CLOCK/CYCLE (CLK/CYC), which transactivates both per and timeless (tim) in one loop, and pdp1 and vri in the other. PDP1 and VRI feed back positively and negatively on the Clk promoter, respectively. PER and TIM form a dimer that acts as a CLK/CYC transcriptional repressor to negatively regulate their own genes’ transcription. The fly brain contains a mosaic of ∼150 circadian neurons, which express various neuropeptides and classic neurotransmitters and have different patterns of neuronal projections (Johard et al., 2009; Nitabach and Taghert,

2008). Studies in the past 10 years have begun to shed light on the function of such complex neural organization. Specific neurons have specific roles in the control of circadian behavior. For example, the Pigment Dispersing Factor (PDF)-positive small ventral lateral neurons (sLNvs) predominantly generate morning activity in a light:dark (LD) cycle, while the dorsal lateral neurons (LNds) and the PDF-negative sLNv are important for evening activity (Grima Phosphoprotein phosphatase et al., 2004; Stoleru et al., 2004). Some neurons are more sensitive to temperature cycles (lateral posterior neurons [LPNs], Dorsal Neurons [DN] 1 and 2) and can influence circadian behavior specifically when such environmental cycles are present (Busza et al., 2007; Miyasako et al., 2007; Picot et al., 2009; Yoshii et al., 2009a). Others (large LNvs, LNds, DN1s) appear to be particularly important for light responses (Murad et al., 2007; Picot et al., 2007; Shang et al., 2008; Stoleru et al., 2007; Tang et al., 2010). Finally, a subset of DNs (DN1s) integrates light and temperature inputs to influence circadian behavior (Zhang et al., 2010).

We also thank A. Scimemi for precious help and suggestions on STC recordings. This work was supported by grants from the Swiss National Foundation (3100A0-100850, 3100A0-120398, and NCCR Transcure) to A.V. and from the University of Lausanne, grant FBM 2006, and Novartis Foundation (26077772) to P.B. M.S. is recipient of a University of Lausanne FBM PhD fellowship. “
“A substantial part of the knowledge that we acquire in real life is a consequence of a one-time exposure to an event, yet the brain mechanisms that

underlie this type of rapid learning are largely unknown. While the prevalent example of single-event knowledge acquisition is episodic memory (Roediger et al., 2007 and Tulving, 1983), another type of real-life single-event learning is insight: the sudden realization BIBF-1120 of a solution to a problem (Hebb, 1949 and Köhler, 1925). Although insight is most often discussed in the context of cognitive tasks such as problem solving (Kaplan and Simon, 1990 and Sternberg and Davidson, 1995), abrupt improvements in performance, as well as the subjective “Aha!” experience characteristic of insight, can also be observed in perception (Porter, 1954, Rubin et al., selleck chemical 1997 and Rubin et al., 2002). The sudden realization of the solution may happen spontaneously, but it can also be induced by an external cue, both in cognitive problem solving (Maier, 1931) and in

perception. Readers may be able to experience induced perceptual insight for themselves by viewing Figure 1, which was generated by degrading a real-world picture, taking a few moments to try to identify

the underlying scene, and then turning to Figure 2 (next page), which shows the original image. Upon re-exposure to the degraded 4-Aminobutyrate aminotransferase image, or “camouflage” (Figure 1), many observers report perceiving a compelling depiction of the underlying scene—just moments after the very same image appeared as a meaningless collection of ink blots. In daily life, information that results from moments of insight is, almost by definition, incorporated into long-term memory: once we have realized a new way to solve a problem, or to perform a task better and faster, we are not likely to forget that insight easily. But what is the neural basis of this long-lasting nature of insight? Other forms of learning typically require long training periods and many repeated trials, as has been observed in sensory and perceptual learning (e.g., Gauthier and Tarr, 1997, Karni and Sagi, 1991 and Seitz and Watanabe, 2009), motor learning (e.g., Newell and Rosenbloom, 1981), and rote-learning in animals (e.g., Stevens and Savin, 1962). These timescales accord well with the long-held idea that incorporation of new knowledge into long-term memory involves synaptic modifications that require gradual processes, sometimes over weeks or months (Dudai, 2004, Hebb, 1949, Martin et al., 2000 and Squire and Kandel, 1999).

, 2011), which involves aberrant mossy fiber sprouting (Sutula et al., 1989). Of note, increased occurrence of epileptic seizures Fulvestrant cost is often associated with DS (Musumeci et al., 1999; Stafstrom, 1993) as well as fragile X syndrome (FXS) (Musumeci et al., 1999; Stafstrom, 1993), which is caused by loss of FMRP function (Verkerk et al., 1991). Our study suggests that elevated Dscam levels may contribute to the pathogenesis of these disorders by causing excessive presynaptic arbor growth. It also establishes a functional

link between Dscam and FMRP, raising the intriguing possibility that Dscam might be a mechanistic link between DS and FXS, the two most prevalent genetic causes of mental retardation. Recent studies have shown that axon injury activates the DLK pathway, which is essential for subsequent axon regeneration (Hammarlund et al., 2009; Shin et al., 2012; Watkins et al., 2013; Xiong et al., 2010; Yan et al., 2009). In light of the present study, it will be interesting to determine whether the DLK pathway requires Dscam to instruct axon regeneration. In summary, this study demonstrates

that Dscam expression levels, regulated by the DLK pathway and FMRP, determine presynaptic arbor size. It further shows the functional significance of dysregulated Dscam expression in neuronal development and provides a model for studying the pathogenesis of neurological disorders with dysregulated Dscam expression. hiwΔN, UAS-Hiw::GFP ( Wu et al., 2005); wnd1, wnd3, and UAS-Wnd ( BMN 673 mw Collins et al., 2006); DscamP1 ( Schmucker et al., 2000); Dscam18 ( Wang et al., 2002); UAS-Dscam[TM2]::GFP (3.36.25), UAS-Dscam[TM1]::GFP (3.36.25), and DscamP-Dscam[TM2]::GFP (3.36.25)( Wang et al., 2004); UAS-Dscam[TM2] (11.31.25) ( Zhan et al., 2004); Dscam10.27.25, Dscam3.31.8 and DscamFRT ( Hattori et al., 2007); dFMRP50M, UAS-dFMRP ( Zhang et al., 2001); ppk-Gal4 ( Kuo

et al., 2005); ppk-CD4::tdTomato ( Han et al., 2011); and UAS-Syt::eGFP ( Zhang et al., 2002) were used in this study. cDNA constructs of EGFP expression reporters and dFMRP were subcloned MRIP into the pUAST vector. Dscam cDNA containing variable exons 4.3-6.36-9.25-17.2 ( Wang et al., 2004) were used to generate Dscam[TM2]::GFP constructs with or without the 5′ and/or 3′ UTR of Dscam mRNA in the pUASTattB vector. Using standard methods ( Bateman et al., 2006), UAS-Dscam[TM2]::GFP (3.36.25) transgenic lines were generated using PhiC31 integrase-mediated site-specific insertion at the attP40 landing site. As such, there is no position effect on the transcription of these transgenes. The UAS-EGFP construct containing the Dscam 3′ UTR was used to generate serial deletion constructs of the Dscam 3′ UTR for mapping the required sequence for Wnd regulation. The genomic Dscam transgene used for rescue experiments and the wnd cDNA construct were, respectively, generous gifts from Dr. Tzumin Lee (Howard Hughes Medical Institute) and Dr.

NLG1 knockout (KO) or transgenic mice showed synaptic dysfunctions and ASD-like behaviors (Varoqueaux et al., 2006; Chubykin et al., 2007; Blundell et al., 2010; Dahlhaus et al., 2010). Thus, the levels of NLGs within the synaptic membranes are presumed to directly modulate the synaptic functions in vivo. Although several reports indicated that the surface see more levels of NLG1 are regulated by synaptic activities through membrane trafficking (Schapitz et al., 2010; Thyagarajan and Ting, 2010), the regulatory mechanisms to control protein levels of NLG remains unclear. Here, we show that NLG1 is sequentially cleaved by ADAM10 and γ-secretase to release its extra- and intracellular domain fragments,

respectively. Proteolytic processing of NLG1 resulted in the elimination of NLG1 on the cell surface, thereby causing a decrease in the synaptogenic activity of NLG1. We further show that ADAM10-mediated shedding is regulated in an activity-dependent manner through NMDA receptor (NMDAR) activation or by binding to secreted forms of NRXs. Our present results suggest that neuronal activity and interaction with NRXs regulate the levels of NLG1 via proteolytic processing to modulate the adhesion

system as well as the functions of synapses. NLGs are synaptogenic type 1 transmembrane proteins that harbor INCB024360 concentration large extracellular domains (Ichtchenko et al., 1995). While the levels of NLGs are presumed to be correlated with their physiological and pathological functions (Varoqueaux et al., 2006; Chubykin et al., 2007; Glessner et al., Resminostat 2009; Blundell et al., 2010; Dahlhaus et al., 2010), little information is available on the proteolytic mechanism of NLGs. Several lines of evidence have indicated that a subset of type 1 transmembrane proteins are processed by

sequential cleavages by ectodomain shedding and intramembrane cleavage, the latter being executed by γ-secretase (Beel and Sanders, 2008; Bai and Pfaff, 2011). To test whether the levels of NLGs are regulated by proteolytic processing, we analyzed endogenous NLG polypeptides in adult rat brains (Figure 1A). Immunoblot analysis using antibodies that specifically recognize the cytoplasmic region of NLG1 and NLG2 (see Figure S1 available online) revealed immunopositive bands at ∼20–25 kDa, in addition to full-length (FL) protein that migrated at ∼120 kDa. Because the predicted sizes of the cytoplasmic domain of NLGs were within the range of 120–165 amino acid (aa) lengths (NLG1, 125 aa; NLG2, 137 aa), we reasoned that the ∼20–25 kDa polypeptides represent the membrane-tethered C-terminal fragment (CTF) of endogenous NLGs. Multiple bands corresponding to CTFs may represent different posttranslational modifications (e.g., glycosylation, see below). To examine whether these CTFs are processed by the γ-secretase activity, we incubated the membrane fractions of rat brains at 37°C and detected the appearance of additional bands that migrate faster than the CTFs with each NLG.