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Originally published In Press as doi:10.1074/jbc.M408364200 on September 10, 2004

J. Biol. Chem., Vol. 279, Issue 47, 48976-48982, November 19, 2004
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Lateral Diffusion of Inositol 1,4,5-Trisphosphate Receptor Type 1 Is Regulated by Actin Filaments and 4.1N in Neuronal Dendrites*

Kazumi Fukatsu{ddagger}, Hiroko Bannai{ddagger}§, Songbai Zhang¶, Hideki Nakamura{ddagger}||, Takafumi Inoue{ddagger}**, and Katsuhiko Mikoshiba{ddagger}§{ddagger}{ddagger}

From the {ddagger}Division of Molecular Neurobiology and {ddagger}{ddagger}Division of Neural Signal Information Nippon Telegraph and Telephone Company-The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan, the §Laboratory for Developmental Neurobiology, Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan, the Calcium Oscillation Project, ICORP, Japan Science and Technology Corporation, 3-4-4 Shirokanedai, Minato-ku, Tokyo 108-0071, Japan, and the ||Department of Physics, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan

Received for publication, July 23, 2004 , and in revised form, September 9, 2004.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 EXPERIMENTAL PROCEDURES
 RESULTS
 DISCUSSION
 REFERENCES
 
Inositol 1,4,5-trisphosphate receptor type1 (IP3R1) plays an important role in neuronal functions; however, the lateral diffusion of IP3R1 on the endoplasmic reticulum membrane and its regulation in the living neurons remain unknown. We expressed green fluorescent protein-tagged IP3R1 in cultured rat hippocampal neurons and observed the lateral diffusion by the fluorescence recovery after photobleaching technique. IP3R1 showed lateral diffusion with an effective diffusion constant of ~0.3 µm2/s. Depletion of actin filaments increased the diffusion constant of IP3R1, suggesting that the diffusion of IP3R1 is regulated negatively through actin filaments. We also found that protein 4.1N, which binds to IP3R1 and contains an actin-spectrin-binding region, was responsible for this actin regulation of the IP3R1 diffusion constant. Overexpression of dominant-negative 4.1N and blockade of 4.1N binding to IP3R1 increased the IP3R1 diffusion constant. The diffusion of IP3R type 3 (IP3R3), one of the isoforms of IP3Rs lacking the binding ability to 4.1N, was not dependent on actin filaments but became dependent on actin filaments after the addition of a 4.1N-binding sequence. These data suggest that 4.1N serves as a linker protein between IP3R1 and actin filaments. This actin filament-dependent regulation of IP3R1 diffusion may be important for the spatiotemporal regulation of intracellular Ca2+ signaling.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
EXPERIMENTAL PROCEDURES
 RESULTS
 DISCUSSION
 REFERENCES
 
Inositol 1,4,5-trisphosphate (IP3)1 receptors (IP3Rs) are intracellular Ca2+ channels that are responsible for Ca2+ release from intracellular stores (1) and located on the membrane of the endoplasmic reticulum (ER). IP3, which is generated in response to various extracellular stimuli, binds to IP3Rs and induces Ca2+ release (IP3-induced Ca2+ release; IICR) (1, 2). IICR plays crucial roles in various neuronal activities. For example, mouse strains mutated in the IP3R type 1 (IP3R1) gene display severe ataxia and epileptic seizures (3, 4). The control of nerve growth in chick dorsal root ganglia neurons is dependent on IP3R1 (5). IICR is also known to be involved in long term potentiation and long term depression in the hippocampal CA1 area (6, 7) and in long term depression in cerebellar Purkinje cells (8). Interestingly, IICR in neurons is highly restricted spatially (9, 10), although the ER is spread throughout the cell, and the induction of synaptic plasticity (11) and regulation of nerve growth (5) require spatially restricted IICR. Some ER Ca2+-handling proteins including IP3Rs show uneven distribution patterns (12), and this heterogeneity is postulated to be responsible for the spatially and temporally heterogeneous Ca2+ signaling patterns. Thus, targeting of IP3Rs to specific regions in the cell may be one of the important factors in the spatial regulation of IICR; however, the molecular mechanisms underlying the spatial regulation of IICR remain to be elucidated.

The dynamics of the {alpha}-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) type glutamate receptor (AMPAR) have been intensively studied. In addition to an elaborate mechanism for insertion and removal from the plasma membrane (13), the lateral diffusion of AMPAR on the plasma membrane is regulated actively, especially by local Ca2+ signals (14, 15). All of the dynamics of AMPAR have been implied to play important roles in the regulation of synaptic transmission and plasticity. Thus, the distribution pattern of IP3Rs and their dynamics in dendrites is also considered to be important for the fine tuning of Ca2+-dependent events, such as synaptic plasticity, that are little understood to date.

We have shown the existence of vesicular ERs that are transported along dendrites bi-directionally with a fast velocity (0.2–0.3 µm/s) (16), in addition to the ER in reticular structure. In this study, we focused on the dynamics of ER membrane proteins in the reticular ER in dendrites of cultured hippocampal neurons and observed their diffusive movements using the fluorescence recovery after photobleaching (FRAP) technique. To our surprise, the diffusive movement of IP3R1 was regulated through actin filaments, and this regulation was not seen for other ER membrane proteins such as sarcoplasmic/endoplasmic reticulum calcium-ATPase (SERCA) and IP3R type 3 (IP3R3). Furthermore, we found that the actin-spectrin-binding protein 4.1N, which binds to the C terminus of IP3R1 (17), may play crucial roles in the actin-dependent regulation of IP3R1 diffusion.


   EXPERIMENTAL PROCEDURES
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL PROCEDURES
RESULTS
 DISCUSSION
 REFERENCES
 
DNA Constructions—All of the plasmids were propagated in the Escherichia coli strain HB101. All PCR products were verified by nucleotide sequencing using an ABI PRISM 377 automated sequencer (Applied Biosystems, Foster City, CA). The constructions of GFP-tagged sarcoplasmic/endoplasmic reticulum calcium-ATPase 2a (GFP-SERCA2a) (18), GFP-tagged IP3R1 (GFP-IP3R1), GFP-IP3R1-{Delta}CTT14aa, and HA-4.1N-FL (17) were described previously. GFP-tagged IP3R3 (GFP-IP3R3)2 was generated using cDNA clones of mouse IP3R3 and a cDNA fragment coding enhanced green fluorescent protein. GFP-H2Ldin (19) was kindly provided by Dr. Edidin (The Johns Hopkins University, Baltimore, MD). DsRed2–4.1N-FL and DsRed2–4.1N-CTD were generated by replacing a Venus fragment, a variant of yellow fluorescent protein (20), in pcDNA3-Venus-4.1N-FL and pcDNA3-Venus-4.1N-CTD (17) with DsRed2 (BD Biosciences, San Jose, CA), a gene encoding a red fluorescent protein.

A monomeric red fluorescent protein (mRFP) expression plasmid (pcDNA3.1/Zeo+-mRFP) was generated by inserting a fragment encoding mRFP (21), which was kindly provided by Dr. Tsien (University of California, San Diego, CA), into the EcoRI-BamHI site of pcDNA3.1/Zeo+ (Invitrogen). mRFP-CTT14aa, namely mRFP-fused with the C-terminal 14 residues of IP3R1, was generated by inserting a synthesized DNA fragment corresponding to amino acids 2736–2749 of mouse IP3R1 into the EcoRI-XhoI site of pcDNA3.1/Zeo+-mRFP.

To construct a chimeric cDNA GFP-IP3R3-CTT14aa, we synthesized primers 1 (5'-CATGAGCCGGGGACATCCTCCTCAC-3'), 2 (5'-CAACAACGCACAGAATCTAGC-3'), 3 (5'-GACAAGATGGACTGTGTCTC-3'), 4 (5'-GAGGATGTCCCCGGTCATGCAGTTC-3'), and 5 (5'-TGCTTCATCTCTGGCCTGGAG-3'). First, cDNA sequences encoding amino acids 2735–2740 of IP3R1 and amino acids 2666–2670 of IP3R3 were amplified by PCR with primer set 1 and 2 and primer set 3 and 4, and pBlueBac4.5-C12 and pcDNA3.1/Zeo+-EC3 as templates, respectively. The PCR products were mixed, denatured, annealed, and reamplified using primer set 2 and 5 to create a chimeric sequence. The chimeric product and the original pcDNA3.1/Zeo+-EC3 were both digested with SacII and XbaI and ligated together to obtain the full-length chimera GFP-IP3R3-CTT14aa in pcDNA3.1/Zeo+.

Primary Culture and Transfection of Hippocampal Neurons—Primary cultures of hippocampal neurons were prepared from the hippocampi of 1-day-old Wistar rats, as described previously (16). Briefly, dissociated cells were plated on poly-L-lysine (Nacalai Tesque, Kyoto, Japan)-coated coverslips at a density of 3.2 x 104 cells/cm2 and cultured in Neurobasal Medium (Invitrogen) supplemented with 2.5 mM L-glutamine (Nacalai Tesque), 2.5% (v/v) B-27 (Invitrogen), and antibiotics (250 units/ml penicillin and 250 µg/ml streptomycin).

The cultures were transfected with 10 µg of the DNAs, usually on days 4–5 in vitro, using a standard calcium phosphate method (22). The transfected cells were used for cytochemistry or imaging experiments 2–3 days after the transfection.

Time Lapse Imaging and Photobleaching Experiments—For the time lapse imaging experiments, the culture medium was supplemented with 20 mM HEPES (pH 7.3). Fluorescence images of the cells were taken under a confocal scanning microscope (FV-300; Olympus, Tokyo, Japan) attached to an inverted microscope (IX70; Olympus) with a 60x objective (NA 1.4 or 1.45, oil immersion, UplanApo; Olympus). The temperature was maintained at 37 °C using a heating chamber that surrounded the microscope stage. The GFP signal was excited at 488 nm, and emission was detected through a 510–550-nm bandpass filter. The FRAP technique was carried out as follows. An image was taken before the photobleaching (Before) with a low laser power (6% of full power) and a scanning area (66 x 88 µm), and the center area of the field of view was bleached out with continuous high power (100%) laser scanning with a scanning area (20 x 27 µm) for 40 s. The laser power and scanning area were then returned to the initial settings, and the fluorescence recovery into the photobleached area was monitored every 5 s for 5 min. The images were stored at a resolution of 600 x 800 pixels. The images shown in Figs. 1 (A and B) and 3A were processed after digital smoothing to reduce the noise level. The smoothing filter is implemented using 3 x 3 spatial convolutions, where the value of each pixel in the selection is replaced with the weighted average of its 3 x 3 neighborhood. Center pixels are weighted 4-fold more than surrounding pixels.



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  		FIG. 1.
FRAP studies in dendrites of cultured hippocampal neurons expressing GFP-IP3R1 and GFP-SERCA2a. A, fluorescence images of neurons transfected with GFP-IP3R1 and GFP-SERCA2a before FRAP. Scale bar, 5 µm. B, time lapse fluorescence images during FRAP. Before, higher magnification of the same images in A. The areas indicated by white boxes were photobleached and recovering fluorescence was recorded every 5 s. The images shown are picked out from the time lapse image stack. The amount of time after the termination of the photobleach is indicated. C, line-compressed images of fluorescence recovery were constructed from the time lapse image stacks (see "Experimental Procedures").

 



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  		FIG. 3.
The Deff of GFP-IP3R1 is dependent on actin filaments, whereas that of GFP-SERCA2a is not. A, effects of latrunculin A and jasplakinolide treatment on actin cytoskeleton. Fluorescence images of the dendrite of neurons stained with Alexa 594-conjugated phalloidin. Scale bar, 5 µm. B and C, the Deff of GFP-IP3R1 (B) and GFP-SERCA2a (C) without or with latrunculin A, jasplakinolide, and nocodazole treatments. Note that the Deff of GFP-IP3R1 is altered in the presence of the drugs that affect the actin filaments (latrunculin A and jasplakinolide), whereas that of GFP-SERCA2a is not. Treatment with nocodazole, which destabilizes microtubules, decreases the Deff of GFP-IP3R1 and GFP-SERCA2a. The data represent the means ± S.D. *, p < 0.05; **, p < 0.01. The numbers in parentheses indicate the numbers of neurons examined. The Deff of GFP-IP3R1 and GFP-SERCA2a for No treat are the same data shown in Fig. 2.

 
Estimation of the Effective Diffusion Constant (Deff)—In a previous study (18), we quantified the movement of ER proteins as the apparent velocity of the fluorescence recovery after photobleaching, which was effective for comparing the speed of protein diffusion under the same experimental conditions, but we could not compare them to the diffusion constants of other proteins reported in the literature. To solve this issue, we adopted a different approach that enabled direct estimation of the effective diffusion constants (Deff) of ER proteins from the FRAP results. We adopted a theory described by Siggia et al. (23) in which the movement of proteins on the ER membrane is simulated by diffusion in random media.

Throughout this study, we considered the ER networks in neuronal dendrites to be one-dimensional along dendrites, because the thicknesses of the target dendrites were much thinner than the photobleached length. We thus simulated the axial movement of the fluorescent signals as one-dimensional diffusion using the model proposed by Siggia et al. (23). To convert the basic data set, which consisted of a prebleach image and a series of postbleach images of 12-bit precision, to a series of one-dimensional data sets, the following arrangements were carried out. During the experiments, the cells were placed so that the dendrites lay horizontally in the image frame. During the analysis, the image was rotated if necessary to ensure that the target dendrite was horizontal (parallel to the x axis; Fig. 1A). A sufficiently large rectangular strip was then selected, including the bleached region of the dendrite, with its long axis in the x direction, and further analysis was performed within this rectangle (Fig. 1B). The fluorescence intensity data in the rectangle was compressed in the y direction by averaging to create one-dimensional data sets ("line compress"), which were stacked to create a two-dimensional data set (the second axis represents time; Fig. 1C). To reduce noise, four contiguous pixels along the x axis were further averaged to make a "binned" pixel strip of N pixels (Fx(t)).

The background fluorescence, which included the offset of the analog/digital conversion added in reading the photomultiplier output of the confocal scanner, was obtained by averaging the pixel intensities over a region of the image that did not contain any cell structures. The time constant of the photobleaching during the acquisition of the postbleach images was estimated by fitting the fluorescence intensity decay of the entire cell area to an exponential function.

We calculated the theoretical time course using Equations 1 and 2, which are derived from Equations 11 and 12, respectively, of Siggia et al. (23) by slight modifications to introduce the photobleach correction,

(Eq. 1)

(Eq. 2)
where T is the time lapse interval, {tau} is the photobleach time constant, jx(t) is the current of the fluorescence, and {rho}x(t) is the fluorescence density to which the raw data Fx(t) was fitted. corresponds to the initial fluorescence distribution calculated from the prebleach image. The actual pixel values obtained in experiments were used as a boundary condition (F0(t) and FN–1(t)) for every time step, which effectively canceled the fluorescent decrease of the surrounding nonbleached areas during the photobleaching. We calculated {rho}x(t) recursively with different values of the Deff and determined the value that best fitted the real data Fx(t). All of the analyses were performed using custom-made software (TI Workbench) running on a Macintosh computer. We have reported the existence of vesicular ERs, which are transported along dendrites, in addition to the reticular ER structure in hippocampal neurons (16). However, the total fluorescence signal of reticular ER was about 700-fold larger than that of vesicular ERs in dendrites (data not shown); we assumed that the effect of signal arising from the vesicular ER was negligible in this study. The data were expressed as the means ± S.D. Statistical analysis was performed using StatView (Abacus Concepts, Berkeley, CA). A comparison between the two groups was performed by an unpaired t test. Differences with p values less than 0.05 were considered to be statistically significant.

Drug Preparation and Immunocytochemistry—Stock solutions of latrunculin A (1 mg/ml; Invitrogen), jasplakinolide (1 mM; Invitrogen), and nocodazole (10 mg/ml; Sigma-Aldrich) were prepared in dimethyl sulfoxide and stored at –20 °C. The final concentrations of latrunculin A, jasplakinolide, and nocodazole in the culture medium were 1 µg/ml, 10 µM, and 30 µg/ml, respectively. To apply the drugs to the cells, a certain quantity of medium containing twice the final concentrations of the drugs was added to an equal volume of the culture medium. Cultured neurons were incubated with latrunculin A and nocodazole for 1 h each or with jasplakinolide for 3 h at 37 °C in 5% CO2.

To confirm that the cytoskeleton was disrupted or polymerized, fixed cells were stained with Alexa 594-conjugated phalloidin (Invitrogen) or an anti-tubulin antibody (Lab Vision, Fremont, CA). The cells were fixed with 4% formaldehyde in phosphate-buffered saline for 10 min. After permeabilization with 0.1% Triton X-100 in phosphate-buffered saline for 10 min and blocking with 5% skim milk in phosphate-buffered saline, the cells were incubated with the anti-tubulin antibody (1:500 dilution) or Alexa 594-conjugated phalloidin (1:40 dilution). Alexa 488-conjugated IgGs (Invitrogen) were used as the secondary antibody for the anti-tubulin antibody.

Co-immunoprecipitation and Immunoblotting—COS-7 cells were maintained in Dulbecco's modified Eagle's medium (Nacalai Tesque) supplemented with 10% heat-inactivated fetal bovine serum. Five µg DNA/10-cm diameter culture dish was transfected using TransIT transfection regents (Mirus, Madison, WI) according to the manufacturer's protocol. Transfected COS-7 cells were harvested 1 day after transfection, and the lysates were prepared as previously described (24). The cell lysates were centrifuged at 10,000 x g for 30 min at 4 °C, and the supernatants were used for immunoprecipitation. The lysates were preincubated with 5–10 µg of an anti-HA mouse monoclonal antibody (clone 12CA5; Roche Applied Science) or an anti-mouse IgG antibody (Sigma) for 1 h at 4 °C and then incubated with 30 µl of protein G-Sepharose (Amersham Biosciences) for 2–3 h at 4 °C. The complexes were then centrifuged and washed with buffer three times. The proteins were eluted by boiling in 1x SDS-PAGE sample buffer for 3 min and separated by SDS-PAGE. The proteins were transferred to polyvinylidene difluoride membranes (Millipore), and the membranes were probed with an anti-enhanced green fluorescent protein antibody (Santa Cruz, Santa Cruz, CA) and an anti-HA antibody (Zymed Laboratories Inc., South San Francisco, CA).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL PROCEDURES
 RESULTS
DISCUSSION
 REFERENCES
 
Movement of GFP-tagged ER Membrane Proteins in Dendrites—Cultured rat hippocampal neurons were transfected with GFP-tagged IP3R1 (GFP-IP3R1) or GFP-tagged SERCA2a (GFP-SERCA2a) to observe the dynamics of ER membrane proteins in dendrites (Fig. 1A). A segment of each dendrite was photobleached, and the recovery of fluorescence into the bleached area was measured. As shown in Fig. 1B, both GFP-IP3R1 and GFP-SERCA2a gradually migrated into the photobleached area from both ends. The movements of these proteins were also visualized by constructing "compressed images" from time lapse image stacks (Fig. 1C; refer to Experimental Procedures). This apparent diffusive nature allowed us to measure the effective diffusion constant (Deff) by fitting to a diffusion model, which was specialized for modeling diffusion in a straight tubular structure, such as a dendrite (see "Experimental Procedures"). To examine the validity of this model in neuronal dendrites, we measured the Deff of a smaller ER protein, GFP-tagged mouse major histocompatibility complex class I H2Ld (GFP-H2Ldin) (19) in dendrites and compared this Deff with that reported for the same protein in non-neuronal cells. The diffusion coefficient of GFP-H2Ldin has been reported to be ~0.40 µm2/s in the absence of interaction with the transporter associated with antigen processing 1 complex in L or EE2H cell lines (19). In dendrites of hippocampal neurons, in which no mRNA for transporter associated with antigen processing 1 is detected (26), the Deff of GFP-H2Ldin was 0.46 ± 0.13 µm2/s (n = 25). The similarity between the Deff values shows that our model adequately calculates the diffusion constants in dendrites. Interestingly, the Deff of GFP-IP3R1 (0.26 ± 0.10 µm2/s, n = 18) was significantly smaller than those of GFP-SERCA2a (0.47 ± 0.13 µm2/s, n = 11) and GFP-H2Ldin (0.46 ± 0.13 µm2/s, n = 25) (Fig. 2).



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  		FIG. 2.
The Deff of GFP-IP3R1 is smaller than those of GFP-SERCA2a and GFP-H2Ldin. Average effective diffusion constants (Deff) of GFP-IP3R1, GFP-SERCA2a and GFP-H2Ldin in dendrites. Note that the Deff of GFP-IP3R1 is 1.8-fold smaller than those of GFP-SERCA2a and GFP-H2Ldin. The data represent the means ± S.D. **, p < 0.01. The numbers in parentheses indicate the numbers of neurons examined.

 
GFP-IP3R1 Diffusion Is Sensitive to Actin Filament-destabilizing or -stabilizing Drugs—The diffusion of plasma membrane proteins is regulated by the cytoskeleton, especially actin filaments (27, 28). We hypothesized that the slow diffusion of IP3R1 was caused by an interaction with the cytoskeleton and tested this possibility by disturbing microtubules and actin filaments pharmacologically. Nocodazole (30 µg/ml) was used to disrupt microtubules, and latrunculin A (1 µg/ml) and jasplakinolide (10 µM) were used to disrupt and stabilize actin filaments, respectively. The effectiveness of the treatments with these compounds was confirmed by cytochemistry in cultured rat hippocampal neurons. After treatment with nocodazole, anti-tubulin antibody staining in neurons was reduced (data not shown). Latrunculin A reduced the density of actin filaments, whereas jasplakinolide turned individual bundles of actin filaments thick and dense (Fig. 3A). Treatment with nocodazole decreased the Deff of GFP-IP3R1 and GFP-SERCA2a to 0.16 ± 0.06 µm2/s (n = 10) and 0.33 ± 0.08 µm2/s (n = 9), respectively (Fig. 3, B and C), indicating that the integrity of microtubules is an important determinant for the diffusion rate of ER proteins. To our surprise, manipulation of actin filaments only affected the diffusion rate of IP3R1. The Deff of GFP-IP3R1 was increased by latrunculin A treatment and decreased by jasplakinolide treatment to 0.40 ± 0.13 µm2/s (n = 9) and 0.18 ± 0.07 µm2/s (n = 15), respectively (Fig. 3B). However, the Deff of GFP-SERCA2a remained unchanged after treatments with latrunculin A and jasplakinolide at 0.43 ± 0.16 µm2/s (n = 9) and 0.45 ± 0.13 µm2/s (n = 17), respectively (Fig. 3C). These data suggest that the movement of GFP-IP3R1 is negatively regulated through actin filaments, whereas that of GFP-SERCA2a is not. We decided to concentrate on investigating the actin-mediated molecular mechanisms that specifically regulate the diffusion of IP3R1.

4.1N Binding Regulates the Diffusion Rate of GFP-IP3R1—We recently found that protein 4.1N, an actin-spectrin-binding protein, binds to the C-terminal cytoplasmic tail of IP3R1 via its C-terminal domain, and regulates IP3R1 localization in the Madin-Darby canine kidney cell line (17). Because 4.1N is expressed in central nervous system neurons, including those in the hippocampus, and its expression has also been shown in cultured hippocampal neurons (29), we therefore considered 4.1N to be a good candidate for the actin-mediated control of IP3R1 diffusion. To test this possibility, we investigated the effects of DsRed2 (a red fluorescent protein)-tagged 4.1N fusion proteins on the Deff of GFP-IP3R1. Overexpression of DsRed2-tagged full-length 4.1N (DsRed2–4.1N-FL) or DsRed2 alone had little effect on the Deff of GFP-IP3R1 (0.25 ± 0.09 µm2/s, n = 21) and (0.24 ± 0.13 µm2/s, n = 11), respectively (Fig. 4). Next, we analyzed the effect of overexpression of a dominant-negative form of 4.1N, namely a C-terminal domain of 4.1N (4.1N-CTD) that lacks the actin-spectrin-binding domain (17), on the Deff of GFP-IP3R1. Interestingly, overexpression of the dominant-negative 4.1N increased the Deff of GFP-IP3R1 to 0.41 ± 0.15 µm2/s (n = 11), which was similar to the Deff after latrunculin A treatment (Fig. 4). On the other hand, the Deff of GFP-SERCA2a remained unchanged, showing no apparent side effects of the overexpression of DsRed2–4.1N-CTD (Table I). These results suggest that DsRed2–4.1N-CTD disrupted the interaction of GFP-IP3R1 with endogenous 4.1N and support our idea that actin filaments affect the diffusion rate of GFP-IP3R1 through 4.1N.



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  		FIG. 4.
The 4.1N-CTD fragment increases the Deff of GFP-IP3R1. The Deff of GFP-IP3R1 under co-expression with DsRed2, DsRed2–4.1N-FL, or DsRed2–4.1N-CTD. The Deff of GFP-IP3R1 coexpressed with DsRed2–4.1N-FL is not significantly different from that with DsRed2, whereas that after co-expression with DsRed2–4.1N-CTD increases. The data represent the means ± S.D. *, p < 0.05. The numbers in parentheses indicate the numbers of neurons examined.

 


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  		TABLE I
Effective diffusion constants (Deff) of various proteins

The values shown are the means ± S.D.

 
GFP-IP3R1 Diffusion Is Regulated by the CTT14aa Site— The 4.1N-binding region of IP3R1 was identified as the C-terminal 14 amino acids of the cytoplasmic tail: CTT14aa (17). To confirm whether the 4.1N interaction with CTT14aa was responsible for the negative regulation of GFP-IP3R1 diffusion, we observed the diffusion of GFP-tagged IP3R3 (GFP-IP3R3), one of the isoforms of IP3Rs that lacks a segment corresponding to CTT14aa (Fig. 5A). We confirmed that GFP-IP3R3 did not bind to 4.1N by immunoprecipitation (Fig. 5B). The Deff of GFP-IP3R3 (0.45 ± 0.13 µm2/s, n = 20) was significantly larger than that of GFP-IP3R1 (Fig. 6A). On the other hand, the diffusion of GFP-IP3R3-CTT14aa, GFP-IP3R3 fused with CTT14aa at its C-terminal (Fig. 5A), showed properties similar to IP3R1 rather than to IP3R3. We confirmed the binding of GFP-IP3R3-CTT14aa to 4.1N by immunoprecipitation (Fig. 5B). The Deff of GFP-IP3R3-CTT14aa in dendrites (0.29 ± 0.13 µm2/s, n = 15) was close to that of GFP-IP3R1 (Fig. 6A) and significantly smaller than that of GFP-IP3R3 (Fig. 6A). Latrunculin A treatment increased the Deff of GFP-IP3R3-CTT14aa to 0.41 ± 0.12 µm2/s (n = 21), which was close to that of GFP-IP3R3 (Fig. 6A). This result suggests that CTT14aa serves as a linker for the actin-mediated diffusion control of IP3R1.



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  		FIG. 5.
Association between IP3R3-CTT14aa and 4.1N in vitro. A, schematic representation of the structures of GFP-IP3R1, GFP-IP3R1-{Delta}CTT14aa, GFP-IP3R3, and GFP-IP3R3-CTT14aa.B, HA-4.1N-FL was transiently transfected to COS-7 cells with GFP-IP R1, GFP-IP3R3-CTT14aa, or GFP-IP3R3, and the cell lysates were immunoprecipitated (IP) with an anti-HA antibody or control IgG. The input and immunoprecipitated proteins were subjected to SDS-PAGE followed by Western blotting with anti-GFP and anti-HA antibodies. GFP-IP3R1 and GFP-IP3R3-CTT14aa bound to HA-4.1N-FL.

 



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  		FIG. 6.
CTT14aa is involved in the regulation of GFP-IP3R1 diffusion. A, the Deff of GFP-IP3R3 and GFP-IP3R3-CTT14aa and the Deff of GFP-IP3R3-CTT14aa treated with latrunculin A. Note that the Deff of GFP-IP3R3-CTT14aa is smaller than that of GFP-IP R3 and that it is increased by latrunculin A treatment. B, the Deff of GFP-IP3R1-{Delta}CTT14aa and GFP-IP3R1 under co-expression with mRFP-CTT14aa, both of which are larger than that of GFP-IP3R1. The data represent the means ± S.D. **, p < 0.01. The numbers in parentheses indicate the numbers of neurons examined. The Deff of GFP-IP3R1 in A and B are the same data shown in Fig. 2.

 
To further investigate whether CTT14aa was involved in the regulation of GFP-IP3R1 diffusion through interaction with 4.1N, GFP-IP3R1-{Delta}CTT14aa (GFP-tagged IP3R1 lacking the last 14 amino acids, i.e. CTT14aa; Fig. 5A), which does not bind to 4.1N (17), was expressed in neurons. The Deff of GFP-IP3R1-{Delta}CTT14aa (0.44 ± 0.11 µm2/s, n = 23) was significantly larger than that of GFP-IP3R1 and close to those of GFP-IP3R3 and GFP-SERCA2a (Fig. 6B). We then overexpressed a CTT14aa peptide, which is expected to compete with the GFP-IP3R1 for the binding site in the endogenous 4.1N. mRFP-tagged CTT14aa significantly increased the diffusion constant of GFP-IP3R1 (0.39 ± 0.12 µm2/s, n = 13) while leaving the diffusion constant of GFP-SERCA2a unchanged (Fig. 6B and Table I). Overexpression of mRFP did not affect the Deff of GFP-IP3R1 (Table I). Taking all of the results together, we conclude that the last 14-amino acid segment of IP3R1, CTT14aa, is involved in the actin-dependent regulation of the GFP-IP3R1 diffusion rate by interaction with 4.1N (Fig. 7).



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  		FIG. 7.
Schematic model of regulatory mechanism for IP3R1 diffusion. A, protein 4.1N binds spectrin-actin filaments and CTT14aa of IP3R1. Therefore IP3R1 does not diffuse freely. B, IP3R3 does not bind to 4.1N. Therefore it is able to diffuse freely.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL PROCEDURES
 RESULTS
 DISCUSSION
REFERENCES
 
Nature of the IP3R1 Diffusion—In the present study, we showed that ER membrane proteins IP3R1, SERCA2a, and H2Ldin diffused on the reticular ER membrane in neuronal dendrites (Figs. 1 and 2). This is the first report describing the diffusion of ER membrane proteins and calculating their Deff in neuronal dendrites. The Deff of GFP-IP3R1 (0.26 µm2/s) was 1.8-fold smaller than those of GFP-SERCA2a and GFP-H2Ldin (0.47 and 0.46 µm2/s, respectively; Fig. 2). This result shows heterogeneity in the diffusion rates of ER proteins. It has been proposed that the diffusion of proteins on biological membranes is dependent on the size of the transmembrane region of each protein (30), although this does not appear to be consistent with our results. The Deff of GFP-IP3R3, GFP-SERCA2a, and GFP-H2Ldin, which are expected to have transmembrane regions of different sizes, were quite similar (0.45–0.47 µm2/s) (Figs. 2 and 6A). Moreover, the Deff of GFP-IP3R1 was smaller than that of GFP-IP3R3 (Fig. 6A), despite the similarity in size of their transmembrane regions as well as of the whole molecules. Thus, we consider that the small Deff of GFP-IP3R1 compared with those of other ER proteins is not due to the difference in molecular size but rather to a negative regulatory mechanism specific for IP3R1 diffusion.

We previously reported that the movement velocity of the GFP-tagged C-terminal half of IP3R1, containing the transmembrane region, was similar to that of GFP-SERCA2a in the axons of chick dorsal root ganglion neurons (18). The discrepancy between this study and the previous one may arise from the difference in the cellular region studied (dendrites versus axons), the cell type, or the structure of the IP3R1 used (full-length versus truncated form).

Regulatory Mechanism of the GFP-IP3R1 Diffusion—The diffusion of plasma membrane proteins is regulated by the cytoskeleton, especially actin filaments (reviewed in Refs. 27 and 28). Actin filaments are also involved in the regulation of phospholipids diffusion in the plasma membrane (31). In this study, we have demonstrated an example of actin-mediated regulation of ER protein diffusion for the first time. It has been reported that the integrity of actin filaments affects IICR properties (32). The specific regulation of IP3R1 diffusion by actin filaments found in the present study could be underlying such functional regulations of Ca2+ release by actin cytoskeleton in neurons.

The contribution of microtubules was almost the same for the diffusion of GFP-IP3R1 and GFP-SERCA2a (Fig. 3, B and C). Because microtubules are known to be involved in the dynamics of the ER membrane, such as tubule branching, ring closure, and sliding (33, 34), the diffusion of GFP-IP3R1 and GFP-SERCA2a may not be dependent on their direct interaction with microtubules but rather on changes in the dynamics of the ER membrane. Further studies are required to verify this hypothesis, and investigating the contribution of microtubules to the regulation of the dynamics of other ER proteins may be useful for addressing this issue.

In the present study, we focused on an actin filament-dependent regulatory mechanism for the diffusion of GFP-IP3R1 through 4.1N (Figs. 4 and 6). Fig. 7 shows a schematic model of the regulation of IP3R1 diffusion. Protein 4.1N that contains an actin-spectrin-binding domain was identified as a binding protein of the C-terminal 14 amino acids of IP3R1 (17). Because other protein 4.1 homologues play critical roles in the mechanical stability of the plasma membrane, and 4.1N is also postulated to play such a role (29). Recently, 4.1N is also reported to play roles in the translocation or cell surface expression of receptor molecules. In polarized Madin-Darby canine kidney cells, 4.1N is required for IP3R1 translocation to the basolateral membrane domain (17). In neurons, there is growing evidence suggesting that 4.1N is involved in the regulation of the surface expression of receptors and channels in the plasma membrane, such as D2 and D3 dopamine (35) and AMPA (24) receptors. In the latter case, cross-linking of AMPAR to actin filaments through 4.1N is postulated (24). These findings, together with the present results, indicate that 4.1N may regulate proteins on both the plasma membrane and the ER membrane in neurons. However, the present data do not mean that 4.1N is the only regulatory protein for IP3R1 diffusion. Because numerous IP3R1-binding proteins are known (36), including proteins that interact with actin filaments, e.g. ankyrin 2, {beta}-spectrin, and {alpha}-fodrin (37), proteins other than 4.1N may also contribute to the regulation of IP3R1 diffusion through linking to actin filaments. This study is the first step in elucidating the possibly complex regulatory mechanism of IP3R1 diffusion.

Finally, we would like to speculate on the physiological roles for this regulatory mechanism of IP3R1 diffusion. IP3R1 is responsible for various neuronal activities, e.g. synaptic plasticity in postsynapse (6–8) and nerve growth in growth cones (5). Interestingly, actin filaments are enriched in the dendritic spines and growth cones where IICR from IP3R1 is reported to be important for physiological functions (38–40). Heterogeneous distribution of some of the Ca2+-handling ER proteins is considered to be important for generating spatially complex Ca2+ signal (12), and negative regulation of IP3R1 diffusion by actin filaments may be involved in the spatial heterogeneity of IP3R1, namely the spatial regulation of Ca2+ release that influences various neuronal activities such as synaptic plasticity and nerve growth, especially in neurons expressing 4.1N.


   FOOTNOTES
 
* This work was supported by grants from the Ministry of Education, Culture, Sports, Science and Technology of Japan (to T. I. and K. M.), the Ministry of Health, Labour and Welfare of Japan (to T. I.), and the 21st Century COE Program, Center for Integrated Brain Medical Science, from the Ministry of Education, Culture, Sports, Science and Technology of Japan (to K. F. and H. N.). The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Back

** To whom correspondence should be addressed. Tel.: 81-3-5449-5320; Fax: 81-3-5449-5420; E-mail: tinoue{at}ims.u-tokyo.ac.jp.

1 The abbreviations used are: IP3, inositol 1,4,5-trisphosphate; IP3R, inositol 1,4,5-trisphosphate receptor; ER, endoplasmic reticulum; IICR, IP -induced Ca2+ release; IP3R1, inositol 1,4,5-trisphosphate receptor type 1; AMPA, {alpha}-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid; AMPAR, AMPA type glutamate receptor; FRAP, fluorescence recovery after photobleaching; SERCA, sarcoplasmic/endoplasmic reticulum calcium-ATPase; IP3R3, inositol 1,4,5-trisphosphate receptor type 3; GFP, green fluorescent protein; mRFP, monomeric red fluorescent protein; CTD, C-terminal domain; CTT, C-terminal cytoplasmic tail; HA, hemagglutinin. Back

2 M. Iwai, Y. Tateishi, M. Hattori, A. Mizutani, A. Futatsugi, T. Inoue, T. Furuichi, T. Michikawa, and K. Mikoshiba, unpublished data. Back


   ACKNOWLEDGMENTS
 
We are grateful to Dr. R. Tsien for the gift of mRFP and to Dr. M. Edidin for the gift of GFP-H2Ldin. We thank Dr. M. Hattori and Dr. T. Michikawa for valuable discussions and M. Iwai, Y. Tateishi, Dr. A. Mizutani, and N. Ogawa for technical assistance.



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 DISCUSSION
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