Abstract

Expressed throughout the central nervous system, the myocardin-related, megakaryoblastic acute leukemia 1 and 2 (Mkl1/2) are transcriptional cofactors that can be found tethered in the cytoplasm to monomeric actin but on synaptic activation translocate to the nucleus and associate with transcription factors such as serum response factor (SRF) to regulate expression of structural genes. This implies a potential role for Mkls in linking synaptic activity, through gene-expression control, to neuronal structural plasticity. Here, we present evidence that Mkls, particularly Mkl2, are powerful regulators of neuronal structure in vitro. Moreover, using the passive avoidance–conditioning paradigm, we identify learning-associated alterations of neuronal Mkl expression that appear to contribute to 2 phases of gene regulation during memory consolidation in the hippocampus. Gene regulation immediately after learning includes Egr2 and may be facilitated by downregulation of Mkls likely releasing ternary complex factor–regulated SRF activity. The second transcriptional phase occurs later at the 3-h postavoidance time point when Mkl accumulates in the nucleus of hippocampal neurons and there is enhanced transcription of Mkl-dependent structural genes that may contribute to the elaboration of new, memory-associated synapses known to appear over the subsequent 3-h period.

Introduction

Serum response factor (SRF) is a highly conserved transcription factor that regulates the expression of a host of stimulus-dependent genes. Within the central nervous system (CNS), the specific repertoire of genes induced by a particular stimulus is largely dictated by the interaction of SRF with 1 of 2 families of cofactors that compete for an overlapping binding site on SRF (Gineitis and Treisman 2001; Zaromytidou et al. 2006). The first of these, the relatively well-studied ternary complex factor (TCF) family, has been shown to mediate the expression of many immediate early genes (IEGs) (Sgambato et al. 1998; Cesari et al. 2004). The second family is the myocardin-related cofactors, of which megakaryoblastic acute leukemia 1 (Mkl1; also known as MAL1 and MRTF-A) and Mkl2 are expressed throughout the CNS (Wang et al. 2002; Miralles et al. 2003; Shiota et al. 2006). In vitro studies have shown that Mkl proteins bind to monomeric actin in the cytoplasm via 3 RPEL motifs (RPXXXEL; Guettler et al. 2008). Increased Rho-activated actin polymerization causes Mkl proteins to accumulate in the nucleus (Vartiainen et al. 2007), where they bind to SRF and mediate the expression of a large number of genes with functions related to actin dynamics (Posern and Treisman 2006; Miano et al. 2007).

To date, studies investigating the function of Mkl proteins within the CNS have focused on Mkl1. Mkl1 has been found to translocate to the nucleus of cultured cortical neurons following Rho-A signaling, synaptic activation, and membrane depolarization implying a potential role for this transcriptional cofactor in linking synaptic activity, through gene expression control, to neuronal structural plasticity (Tabuchi et al. 2005; Kalita et al. 2006). However, there exists some discrepancy in the literature as to the subcellular localization of Mkl1 within neurons: Some groups report that it is largely cytoplasmic and others constitutively nuclear (Kalita et al. 2006; Shiota et al. 2006; Stern et al. 2009). It is unclear if this represents differences in cell populations or differences between the antibodies used in these immunohistochemical studies. Moreover, in vitro work has shown that there is functional redundancy between Mkl1 and Mkl2, with complete blockade of serum response element–dependent reporter gene activity requiring inhibition of both Mkl1 and Mkl2 (Cen et al. 2003; Li et al. 2006). Despite this, to our knowledge, the role of Mkl2 within neurons has not been investigated.

Tightly regulated synaptic plasticity and physical reorganization of neuronal connections, particularly within the hippocampus, is critical to consolidation of long-term memory (LTM) (O'Malley et al. 1998, 2000; Eyre et al. 2003; Morris et al. 2003; Lamprecht and LeDoux 2004). Although there has been much debate as to the nature of the plasticity, it is now clear that both functional (synapse strength) and morphological (synapse size and position) plasticity occur (Bliss and Collingridge 1993; Malenka and Nicoll 1999; Geinisman 2000). At the cellular level, LTM is dependent on de novo gene and protein expression and is sensitive to inhibitors of transcription and translation (Davis and Squire 1984; Quevedo et al. 1999; Igaz et al. 2002). Such regulation of gene expression occurs in coordinated waves during memory consolidation, controlled by transcription factor activity, providing the raw materials for the long-term neuronal changes needed for information storage (Igaz et al. 2002). Moreover, SRF is known to be one of the transcription factors involved in regulating hippocampal plasticity (Dash et al. 2005; Ramanan et al. 2005; Miano et al. 2007).

To investigate the function of Mkl1/2 proteins in hippocampal neurons, we carried out individual and combined knockdown of expression using small interfering RNAs (siRNAs). We found that dysregulation of Mkl1/2 expression inhibits Mkl SRF–dependent gene expression and disrupts neurite growth and branching. In addition, we explored the role of endogenous Mkl1/2-dependent gene regulation in discrete subregions of the adult hippocampus following passive avoidance training. These results lead us to suggest that Mkl1/2 competes for SRF binding in hippocampal neurons to regulate neuronal structural plasticity during memory formation.

Materials and Methods

Animal Maintenance and Training

Postnatal day 80 male Wistar rats (330–350 g) were individually housed on a 12:12 light/dark cycle, with ad libitum access to food and water. Animals were assessed for 3 days prior to passive avoidance training by observing their open field behavior. The 1-trial, step-through, light–dark version of the passive avoidance paradigm was employed as we have described previously (Fox et al. 1995). The smaller illuminated compartment was separated from the larger dark compartment by a shutter that contained a small entrance. The floor of the training apparatus consisted of a grid of stainless steel bars that would deliver a scrambled shock (0·75 mA every 0·5 ms) for 5 s when the animal entered the dark chamber. Passive controls were exposed to the avoidance apparatus for a time matched to trained counterparts but never received a foot shock. Animals were killed by cervical dislocation at 0 and 3 h following training (4 animals per group, 16 animals in total). For immunohistochemical analysis, brains were quickly dissected out, covered in optimal cutting temperature compound and snap frozen in CO2-cooled n-hexane. For real-time polymerase chain reaction (PCR), the dentate gyrus (DG) was rapidly dissected, snap frozen in liquid nitrogen, and stored at −80 °C until required. All experimental procedures were approved by the Animal Research Ethics Committee, University College Dublin and were carried out by individuals who held the appropriate license issued by the Irish Minister for Health and Children.

Primary Neuronal Culture

Rats at embryonic day 17 were used to prepare low-density primary hippocampal neuronal cultures. After complete removal of meninges, hippocampi were dissected in Hank's balanced salt solution (HBSS). The tissue was triturated in HBSS with 0.05% trypsin and dissociated by repeated pipetting. Cells were plated in cortical plating medium (neurobasal medium (NB), 2% B27 + supplement, 0.5-mM L-glutamine, penicillin, and streptomycin) on poly-D-lysine coated coverslips in 12-well plates at a density of 1.5 × 104 cells per well (low density) or 1.5 × 105 cells per well (high density). Plated neurons were maintained in an incubator with 5% CO2 at 37 °C. Staining with the neuron-specific marker NeuN indicates that plating at a low density produces very pure neuronal cultures (Fig. 1E), whereas plating at the higher density results in a more heterogenous mix of neuronal and nonneuronal cells (Fig. 3A).

Figure 1.

siRNA knockdown of Mkl1 and Mkl2 in neuronal cultures. (AD) siRNA treatment reduces Mkl1 and Mkl2 mRNA expression levels 48 and 96 h following treatment. Results are expressed as the mean ± standard error of the mean (SEM) percent change from control (10 ≤ n ≤ 20), and values significantly different from control are indicated by an asterisk (P < 0.01, 1-way ANOVA and Dunnett's post-hoc test). (E,F) siRNA treatment decreases Mkl1/2 protein levels 96 h following treatment. Panel E shows representative immunohistochemical images of primary hippocampal cell cultures double labeled for Mkl1/2 (red) and the neuronal marker NeuN (green) and counterstained with the nuclear marker Hoechst (blue). Panel F presents a quantification of the Mkl1/2 immunohistochemistry study, and results are expressed as the mean ± SEM pixel intensity for each cell (relative fluorescence units, 2009 ≤ n ≤ 2226). Values significantly different from control are indicated by an asterisk (P < 0.01, one-way ANOVA and Dunnett's post-hoc test). Scale bar = 50 μm. (G) Mkl1/2 protein levels assessed by western blot. C = untransfected control, NTC = 100 nM NTC siRNA, Mkl1 = 100 nM Mkl1 siRNA, Mkl2 = 100 nM Mkl2 siRNA, and mix = 50 nM each Mkl1 and Mkl2 siRNA.

Figure 1.

siRNA knockdown of Mkl1 and Mkl2 in neuronal cultures. (AD) siRNA treatment reduces Mkl1 and Mkl2 mRNA expression levels 48 and 96 h following treatment. Results are expressed as the mean ± standard error of the mean (SEM) percent change from control (10 ≤ n ≤ 20), and values significantly different from control are indicated by an asterisk (P < 0.01, 1-way ANOVA and Dunnett's post-hoc test). (E,F) siRNA treatment decreases Mkl1/2 protein levels 96 h following treatment. Panel E shows representative immunohistochemical images of primary hippocampal cell cultures double labeled for Mkl1/2 (red) and the neuronal marker NeuN (green) and counterstained with the nuclear marker Hoechst (blue). Panel F presents a quantification of the Mkl1/2 immunohistochemistry study, and results are expressed as the mean ± SEM pixel intensity for each cell (relative fluorescence units, 2009 ≤ n ≤ 2226). Values significantly different from control are indicated by an asterisk (P < 0.01, one-way ANOVA and Dunnett's post-hoc test). Scale bar = 50 μm. (G) Mkl1/2 protein levels assessed by western blot. C = untransfected control, NTC = 100 nM NTC siRNA, Mkl1 = 100 nM Mkl1 siRNA, Mkl2 = 100 nM Mkl2 siRNA, and mix = 50 nM each Mkl1 and Mkl2 siRNA.

siRNA Knockdown

Synthetic siRNAs targeting rat Mkl1 (L-081405-00) and Mkl2 (L-103684-01), as well as a nontargeting control (NTC; D-001810-10), were obtained from Dharmacon Inc. (Thermo Scientific, Northumberland, United Kingdom). Twenty-four hours after hippocampal neurons were plated on coverslips, as described above, the medium was replaced with antibiotic-free maintenance medium (NB, 2% B27 minus supplement, 0.5 mM L-glutamine) containing 100 nM siRNA: 100 nM of NTC, Mkl1 siRNA, Mkl2 siRNA, or 50 nM each Mkl1 and Mkl2 siRNA for double knockdown. Transfection was achieved using DharmaFECT 3 reagent following the manufacturer's instructions. All experiments were performed in triplicate and repeated with at least 3 different platings.

Real-Time PCR

Total RNA was purified from individual wells or DG in TRIzol reagent (Invitrogen, United Kingdom) according to the manufacturer's instructions. cDNA was produced using SuperScript II RNase H Reverse Transcriptase Kit (Invitrogen, United Kingdom) using 50–250 ng of random primers. Real-time PCR was carried out using TaqMan technology on an ABI Prism 7900HT sequence detection system (PE Applied Biosystems, United Kingdom). The mRNA expression for Mkl1, Snai2, tropomyosin 3 (Tpm3), alpha smooth muscle actin (α-SMA), and Egr2 was determined using TaqMan Gene Expression Assay primers and probes (Applied BiosystemsAssay ID Rn01458644_m1, Rn00709370_m1, Rn00589483_m1, Rn01759928_g1, and Rn0058622_m1, respectively. Assayed primers and probes were not available for Mkl2 so were designed as follows: forward-GACCTCATTGAACGCGTGAAA, reverse-ATACTGCCAGTGGCAAGGTTATTAC, and probe-CCTACCAGGAAGTGACC. The mRNA expression was quantified by constructing a standard curve for the primer and probe set with pooled DNA from all samples. A ribosomal RNA control primer and probe set served as an internal control (Applied Biosystems).

Immunoblotting

Protein lysates from high-density plates treated for 4 days with siRNA were separated on polyacrylamide minigels and electrophoretically transferred to nitrocellulose membranes (Bio-rad). Equal protein loading was confirmed by ponceau S staining of the membrane (not shown). The nitrocellulose was blocked in 5% nonfat milk in 10 mM Tris–HCl, 150 nM NaCl, and 0.05% (vol/vol) Tween-20 (Tris-buffered saline tween-20 [TBS-T]) for 1 h at room temperature. Rabbit anti-Mkl1/2 (Sc-32909; Santa Cruz, CA) was diluted in 5% milk and incubated overnight at 4 °C. After incubation with antirabbit horseradish peroxidise (A6154, Sigma) and SuperSignal Chemiluminescent Substrate (Pierce), bands were visualized by exposure to X-ray film (Kodak).

Structural Analysis

Cells were grown in siRNA-treated medium for 4 days, which allowed for growth of neurites while remaining distinct from surrounding neurons. Coverslips were blinded before the cells were fixed in 70% ethanol for 30 min and images captured by phase contrast microscopy. Neuronal morphology was analyzed using Sholl analysis, which measures the density of neurites as a function of distance from the cell body (Sholl 1953). In this study, concentric digitally generated rings 4.9 μm apart were centered on the cell soma, and the neurites intersecting each ring were counted. Total length of neurites was determined by automated analysis, whereas branch point numbers were manually counted.

Cryosectioning

Whole brains were cryosectioned horizontally at −7.1 mm with respect to Bregma to reveal the ventral hippocampus. Twelve-micrometer sections were adhered to glass slides coated with poly-L-lysine. One section from each rat brain was used for analysis, and each trained section was prepared, stained, and imaged along with their relevant passive control.

Immunocytochemistry and Confocal Microscopy

Coverslips or sections were fixed in 70% ethanol, permeablized using a solution of 0.2% Triton X in phosphate buffered saline (PBS), and incubated overnight (18 h) with primary antibody. We used rabbit anti-Mkl1/2 (Sc-32909, Santa Cruz), mouse anti-NeuN (MAB377, Chemicon), and mouse anti-glial fibrillary acidic protein (GFAP; Ab10062, Abcam). After washing with PBS, cells or sections were incubated with the appropriate Cy3− or fluorescein (FITC)-conjugated fluorescent antibodies. The secondary antibody was then washed off, and samples were incubated with either propidium iodide (PI) or Hoechst, in order to stain all nuclei. If not imaged immediately, sections were mounted with Citifluor (glycerol in PBS) and stored in darkness at 4 °C.

All confocal images (1024 × 1024 pixels, 0.22-μm × 0.22-μm pixel size, and 3.6-μm optical slice) used for analysis were captured using identical settings. Images taken from hippocampal sections were captured at 4 distinct regions of the hippocampus, that is, CA1, CA2, CA3, and the apex of the DG. These specific areas of the hippocampal neuronal circuit were kept consistent between sections (Fig. 4A).

Image Analysis

Image analysis was conducted using the Bioconductor EBImage plugin for R (Sklyar et al. 2009), which has an implementation of the watershed segmentation algorithm, as this approach to image analysis allows the automated and accurate separation and fluorescence intensity measurement in individual cells that are very close together or touching. Using watershed segmentation, the nucleus of each cell was defined from a binary threshold image derived from the red channel of each image, corresponding to the PI iodide staining. Threshold levels, distance between objects, and minimum object radii were set for each region independently to select only nuclei. After nuclear identification, green channel intensity, which corresponds to Mkl1/2 expression, was quantified for each nuclear region. To assess expression in a cytoplasmic region around each nucleus, the nuclear threshold image was “dilated” using morphological kernel expansion, and image segmentation repeated, beginning at the identified nuclei. This resulted in a “whole-cell” object being defined corresponding to each nucleus, in which green channel fluorescence was quantified. Cytoplasmic fluorescence levels were calculated by subtracting nuclear from whole-cell values, and nuclear:cytoplasmic ratios were then calculated according to the equation [(FnFc)/Fc], where Fn = average nuclear fluorescence and Fc = average cytoplasmic fluorescence.

For siRNA experiments, protein levels were assessed on a cell-by-cell basis by immunocytochemistry and analyzed using the same image segmentation and intensity measurement approach. In this case, mean intensity across the whole cell, as opposed to nuclear/cytoplasmic intensity ratio, was used as an index of protein levels in each cell.

Statistical Analysis

Statistical significance was calculated using 1 way analysis of variance (ANOVA) and Dunnett's post-hoc tests (P < 0.01), 2way ANOVA, and Bonferonni post-hoc tests (P < 0.01), or by Student's t-test analysis (P < 0.05), as appropriate.

Statistical significance of Mkl1/2 localization changes was determined using a Kolmogorov–Smirnov (KS) test, performed on the data using R (P < 0.01). Normal parametric statistical tests, such as Student's t-test, can only detect changes in a population mean and is therefore most useful in detecting more homogeneous changes in a population. However, the automated process of gathering data in this study resulted in the measurement of nuclear:cytoplasmic ratios in ∼125–250 cells in each hippocampal subregion in each sample (4 samples in each trained/passive group; total cell count for each subregion available in table S1). This relatively large sample size allows the use of a nonparametric statistical test that can detect any changes in a population. In contrast to Student's t-test, the KS test has the advantage of making no assumption about the distribution of data and so can detect differences between populations even if there is marked heterogeneity in the response of the cell population to a learning event. The D statistic, the maximum deviation between the populations, was also generated.

Results

Knockdown of Mkl1 in Hippocampal Neurons Can Result in a Concomitant Upregulation of Mkl2 Expression

We knocked down expression of Mkl genes in hippocampal neurons by transfecting 100 nM siRNAs for Mkl1 and Mkl2. Following treatment with Mkl1 siRNA for 48 and 96 h, we see effective reduction of Mkl1 mRNA from controls (50 ± 7% and 56 ± 7% of control, respectively, 1-way ANOVA and Dunnett's post-hoc test, P < 0.01; Fig. 1A,C). However, Mkl1 siRNA treatment also produced an increase in Mkl2 mRNA from controls (159 ± 11% and 148 ± 20% from control for 48 and 96 h, respectively, P < 0.01 at 48 h P > 0.05 at 96 h; Fig. 1B,D). Forty eight– and 96-hour treatment with Mkl2 siRNA results in reduced Mkl2 mRNA levels (44 ± 5% and 49 ± 15% of control, respectively, P < 0.01 at 48 h and P < 0.05 at 96 h; Fig. 1B,D) with no change in Mkl1 expression observed. Finally, we simultaneously knocked down Mkl1 and Mkl2, using 50 nM of each siRNA, which resulted in decreased expression of Mkl1 and Mkl2 at 48 h (43 ± 5% and 41 ± 6% of control, respectively, P < 0.01; Fig. 1A,B) although this was less robust as it was not maintained at 96 h (80 ± 7% and 84 ± 15% of control, respectively, P > 0.05; Fig. 1C,D). One-hundred nanomoles of NTC siRNA showed no significant change from untransfected control levels in any parameter investigated.

We immunostained siRNA-treated neurons with an antibody purporting to be reactive to Mkl1 (Sc-32909; Santa Cruz). We did not see any change in protein intensity 48 h following treatment (data not shown). However, 96 h posttreatment we found decreased antibody staining in cells treated with Mkl1 siRNA, Mkl2 siRNA, and the double knockdown (80 ± 2%, 87 ± 2%, and 84 ± 2% of control respectively, P < 0.01; Fig. 1E,F). This provides evidence that this antibody binds both Mkl1 and Mkl2. Moreover, immunoblotting of protein lysate from neurons 96 h following siRNA treatment reveals a decrease in a ∼98-kDa band, the expected molecular weight of rat Mkl1 (Fig. 1G).

Altered Mkl1/2 Expression in Hippocampal Neurons Modulates Neuritic Growth and Branching

We observed that treatment with Mkl1 and Mkl2 siRNAs resulted in significant changes to neuronal structure (Fig. 2A). This effect was not immediate (no structural changes seen at 48 posttreatment, data not shown) but was visible 96 h posttreatment, coincident with the alteration in Mkl1/2 protein level. Specifically, neurons treated with Mkl1 siRNA, which have decreased Mkl1 and increased Mkl2 expression, have significantly more neurite complexity (assessed by Sholl distribution) compared with controls (2-way ANOVA and Bonferonni post-hoc tests, P < 0.01; Fig. 2B and Fig. S1A). In addition, these neurons had increased neurite branching (24 ± 1 compared with 18 ± 1 branch points for controls, P < 0.01; Fig. 2C), total neuritic length (1348 ± 58μm compared with 826 ± 27 μm for controls, P < 0.01; Fig. 2D), and longer maximal neurite distance from soma (210 ± 12 μm compared with 124 ± 5 μm for controls, P < 0.01; Fig. S1B). In contrast, neurons treated with Mkl2 siRNA, which have decreased Mkl2 but normal Mkl1 expression, and the double knockdown, which have decreased Mkl1 and Mkl2 expression, have significantly less Sholl neurite complexity compared with controls (P < 0.01; Fig. 2B and Fig. S1A). These neurons also have decreased branching (10 ± 1 and 8 ± 1, respectively, P < 0.01; Fig. 2C), total neuritic length (508 ± 23 and 443±26 μm, respectively, P < 0.01; Fig. 2D), and longer maximal neurite distance from soma (87 ± 4 and 77 ± 4 μm, respectively, P < 0.01; Fig. S1B) compared with controls.

Figure 2.

Modulations in Mkl1 and Mkl2 regulate neurite outgrowth and expression of downstream Mkl–SRF genes in hippocampal neurons. (A) Representative line tracings of hippocampal neurons from control and siRNA-treated cultures. Scale bar = 50 μm. (B) Sholl analysis of neuritic density following 96 h of treatment. Sholl analysis calculates the number of neurites crossing a series of concentric circles centered on the soma of each cell as illustrated in insert (B‘). Data are expressed as mean ± SEM (55 ≤ n ≤ 103) number of crossings for each treatment group. Statistical difference from the control was determined by 2-way ANOVA and Bonferonni post-hoc tests (*P < 0.001). (C,D) Number of branch points and total length of neurites following 96 h of treatment. Data are expressed as mean ± SEM (55 ≤ n ≤ 103), and values significantly different from control are indicated by an asterisk (P < 0.01; 1-way ANOVA and Dunnett's post-hoc test). (E,F,G) Effect of siRNA treatments on mRNA expression levels of α-SMA, Tpm3, and Snai2 as determined using real-time PCR. Results are expressed as the mean ± SEM (5 ≤ n ≤ 10) percent control, and values significantly different from control are indicated by an asterisk (P < 0.01; 1-way ANOVA and Dunnett's post-hoc test).

Figure 2.

Modulations in Mkl1 and Mkl2 regulate neurite outgrowth and expression of downstream Mkl–SRF genes in hippocampal neurons. (A) Representative line tracings of hippocampal neurons from control and siRNA-treated cultures. Scale bar = 50 μm. (B) Sholl analysis of neuritic density following 96 h of treatment. Sholl analysis calculates the number of neurites crossing a series of concentric circles centered on the soma of each cell as illustrated in insert (B‘). Data are expressed as mean ± SEM (55 ≤ n ≤ 103) number of crossings for each treatment group. Statistical difference from the control was determined by 2-way ANOVA and Bonferonni post-hoc tests (*P < 0.001). (C,D) Number of branch points and total length of neurites following 96 h of treatment. Data are expressed as mean ± SEM (55 ≤ n ≤ 103), and values significantly different from control are indicated by an asterisk (P < 0.01; 1-way ANOVA and Dunnett's post-hoc test). (E,F,G) Effect of siRNA treatments on mRNA expression levels of α-SMA, Tpm3, and Snai2 as determined using real-time PCR. Results are expressed as the mean ± SEM (5 ≤ n ≤ 10) percent control, and values significantly different from control are indicated by an asterisk (P < 0.01; 1-way ANOVA and Dunnett's post-hoc test).

We next explored if these structural changes were associated with altered expression of Mkl1/2 target genes as a result of the siRNA treatment. Coincident with the change in protein level and altered neuritic structure at 96 h posttraining we found decreased expression of the SRF Mkl–regulated genes αSMA and Tpm3. Specifically, αSMA expression was decreased in Mkl2 siRNA and double knockdown–treated cells (27 ± 4% and 47 ± 9% of control, respectively, P < 0.01; Fig. 2E). Tpm3 expression was significantly decreased in Mkl1 siRNA and double knockdown–treated cells (76 ± 4% and 74 ± 7% of control, respectively, P < 0.05) and decreased in Mkl2 siRNA–treated cells, though this did not reach significance (78 ± 4% of control, P > 0.05; Fig. 2F). In contrast, expression of the Mkl–SMAD3 regulated snail family transcription factor member Snai2 was not altered by the siRNA treatments (Fig. 2G).

Mkl1/2 Is Expressed in Hippocampal Neurons and Astrocytes In Vitro and In Vivo

There has been debate in the literature as to the cellular localization of Mkl1/2 protein in CNS tissue. As this point is fundamental to an understanding of the role of Mkl1/2 in neuronal function, we next established where Mkl1/2 was expressed across the major subtypes of hippocampal cells. In primary hippocampal cultures, colocalization of Mkl1/2 with both the neuronal marker NeuN and the actrocytic marker GFAP indicated that Mkl1/2 was expressed in both neurons and astrocytes (Fig. 3A and Fig. S2). In addition, Mkl1/2 was clearly expressed in both the nucleus and cytoplasm of neuronal cells (Fig. 3A and enlarged in Fig. S2A, arrowheads).

Figure 3.

Mkl1/2 expression is evident in both the cytoplasm and nucleus of cells in hippocampal cultures and in the adult hippocampus. Mkl1/2 colocalizes with NeuN and GFAP staining in cultured high-density hippocampal cells (A) and within the adult hippocampus (B; arrows). Within both cell types, Mkl1/2 protein is detected within the nuclear and cytoplasic compartments (arrow head). Images were captured on an LSM Pascal confocal microscope (Zeiss). Mkl1/2 is labeled red using Cy3-conjugated secondary antibody; NeuN or GFAP is labeled green using FITC-conjugated secondary antibodies, and nuclei are stained blue with Hoechst. Scale bar = 50 μm.

Figure 3.

Mkl1/2 expression is evident in both the cytoplasm and nucleus of cells in hippocampal cultures and in the adult hippocampus. Mkl1/2 colocalizes with NeuN and GFAP staining in cultured high-density hippocampal cells (A) and within the adult hippocampus (B; arrows). Within both cell types, Mkl1/2 protein is detected within the nuclear and cytoplasic compartments (arrow head). Images were captured on an LSM Pascal confocal microscope (Zeiss). Mkl1/2 is labeled red using Cy3-conjugated secondary antibody; NeuN or GFAP is labeled green using FITC-conjugated secondary antibodies, and nuclei are stained blue with Hoechst. Scale bar = 50 μm.

Immunohistochemical analysis of hippocampal slices from adult rat brain revealed widespread colocalization of Mkl1/2 staining with NeuN across the hippocampus (Fig. 3B and Fig. S3). There was also some evidence for Mkl1/2 colocalization with GFAP staining in the intact adult hippocampus (Fig. 3B and Fig. S4, arrow), though only a small proportion of GFAP-positive cells exhibited appreciable Mkl1/2 expression.

Mkl1/2 Undergoes Learning-Specific Nuclear Accumulation in Hippocampal Neurons 3 h Following Passive Avoidance Training

As the studies presented above indicate that Mkl1/2 can be detected and quantified in the primary excitatory neurons in the subregions of the adult hippocampus, we wanted to determine whether it undergoes nuclear translocation following a learning event. Equivalent horizontal sections of the ventral hippocampus (−7.1 mm w.r.t. Bregma) were taken from animals 0 and 3 h following passive avoidance training and from corresponding passive controls. High-magnification confocal images were taken of Mkl1/2 staining in the granule cells of the DG and the pyramidal cells of the CA regions of the ventral hippocampus (CA1-3; Fig. 4A). Double labeling using Mkl1/2 and the nuclear marker PI demonstrates that Mkl1/2 protein can be detected in the nucleus and somatic cytoplasm of cells in all 4 hippocampal subregions (Fig. 4B). Using a cell-by-cell analysis approach, the relative amount of Mkl1/2 present in different cellular compartments, that is, nucleus and somatic cytoplasm, within each distinct cell population of the hippocampus was quantified. Interestingly, though detectable in both compartments, the levels of Mkl1/2 expression are consistently greater in the nucleus than in the cytoplasm (Figs. S5 and S6). Finally, the nuclear:cytoplasmic ratio for each cell was calculated. Within each subregion, these ratios were pooled and used for comparison between trained and passive samples at both posttraining time points.

Figure 4.

Subcellular Mkl1/2 localization in hippocampal regions 0 and 3 h following passive avoidance training. (A) Horizontal section through the rat ventral hippocampus (ca. −7.1 mm w.r.t. Bregma) immunofluorescently labeled for Mkl1/2. Images were captured on an LSM Pascal confocal microscope (Zeiss). Nuclei are stained using PI (red) and Mkl1/2 is labeled using an FITC-conjugated secondary antibody (green). The white boxes represent the 4 regions of the hippocampal neuronal network that were analyzed throughout this study, that is, DG, CA3, CA2, and CA1. Scale bar = 500 μm. (B) High-magnification images of the hippocampal regions. Scale bar = 10 μm. (C) Data shown as cumulative frequency distributions of the nuclear:cytoplasmic ratio values of trained (black line) and passive control (dotted line) samples. Values were gathered from 4 animals per group, with 883 ≤ n ≤ 975, 628 ≤ n ≤ 749, 543 ≤ n ≤ 585, and 672 ≤ n ≤ 729 cells analyzed for the DG, CA3, CA2, and CA1 regions, respectively. Training significantly increased the nuclear:cytoplasmic ratio of Mkl1/2 in all hippocampal regions at the 3-h time (P < 0.01, K–S test; specific P values indicated in the lower right-hand corner of the plots).

Figure 4.

Subcellular Mkl1/2 localization in hippocampal regions 0 and 3 h following passive avoidance training. (A) Horizontal section through the rat ventral hippocampus (ca. −7.1 mm w.r.t. Bregma) immunofluorescently labeled for Mkl1/2. Images were captured on an LSM Pascal confocal microscope (Zeiss). Nuclei are stained using PI (red) and Mkl1/2 is labeled using an FITC-conjugated secondary antibody (green). The white boxes represent the 4 regions of the hippocampal neuronal network that were analyzed throughout this study, that is, DG, CA3, CA2, and CA1. Scale bar = 500 μm. (B) High-magnification images of the hippocampal regions. Scale bar = 10 μm. (C) Data shown as cumulative frequency distributions of the nuclear:cytoplasmic ratio values of trained (black line) and passive control (dotted line) samples. Values were gathered from 4 animals per group, with 883 ≤ n ≤ 975, 628 ≤ n ≤ 749, 543 ≤ n ≤ 585, and 672 ≤ n ≤ 729 cells analyzed for the DG, CA3, CA2, and CA1 regions, respectively. Training significantly increased the nuclear:cytoplasmic ratio of Mkl1/2 in all hippocampal regions at the 3-h time (P < 0.01, K–S test; specific P values indicated in the lower right-hand corner of the plots).

Given that there is no compelling a priori reason to believe that every cell in a given hippocampal region would respond in the same way to a learning stimulus, it is important to select an analytical approach that allows the detection of heterogenous changes after learning. Indeed, we observed that Mkl1/2 levels are not uniform across the hippocampus, being highest in the CA3 region and lowest in the DG (Figs. S5 and S6). When the nuclear:cytoplasmic ratios from the hippocampal regions were analyzed by t-tests, differences were only detected in the CA2 region 3 h posttraining (Fig. S7). However, parametric statistics based on a normal distribution are particularly insensitive to differences in skew or kurtosis of 2 distributions, which is an important source of variation if a population responds to a stimulus in a heterogeneous manner. As such, the trained and passive control values in each subregion were compared using the KS test and the differences between populations illustrated graphically using cumulative frequency distributions. In these frequency distributions, a rightward shift of a distribution indicated a relatively higher nuclear expression, and, conversely, a leftward shift indicated relatively less accumulation within the nucleus in that part of the distribution.

No change in Mkl1/2 cellular distribution was detected immediately following training, in any of the hippocampus cell populations studied (Fig. 4C; D = 0.0.3, P = 0.76 for DG; D = 0.08, P = 0.014 for CA3; D = 0.07, P = 0.1 for CA2; and D = 0.05, P = 0.35 for CA1). In contrast, we found that the nuclear:cytoplasmic ratio of Mkl1/2 was consistently higher in trained animals relative to passive controls for all hippocampal regions studied 3 h following training (Fig. 4C; D = 0.15, P = 2.4 × 10−10 for DG, D = 0.12, P = 1.2 × 10−4 for CA3, D = 0.15, P = 5.8 × 10−6 for CA2, and D = 0.09, P = 6.8 × 10−3 for CA1). These findings indicated that nuclear accumulation of Mkl1/2 occurs across the hippocampal subregions at this time following avoidance conditioning.

Upregulation of Mkl1/2-Induced Genes Snai2, Tpm3, and α-SMA in the Hippocampal DG Coincident with Increased Mkl1/2 Nuclear Localization

Having shown that Mkl1/2 accumulated within the nucleus of hippocampal neurons 3 h postlearning, we wanted to investigate if this contributes to memory-associated gene regulation. The expression readout of 3 genes whose transcription is known to be regulated by Mkl1/2 was used to see if transcription of Mkl1/2 target genes increased coincident with the observed nuclear translocation. The DG, a region established to undergo synaptic reorganization during consolidation (O'Malley et al. 1998, 2000), was dissected from trained and passive control animals 0 and 3 h following training. mRNA was isolated from these samples and real-time PCR analysis carried out. We detected significantly increased expression of the Mkl–SRF activated genes Tpm3 and α-SMA 3h, but not 0 h, following passive avoidance training (150 ± 16% and 160 ± 15% of control respectively, P < 0.05; Fig. 5). We also found significantly increased expression of the Mkl–SMAD3 activated gene Snai2 3h and not 0 h posttraining (204 ± 29% of control, P <0.05; Fig. 5).

Figure 5.

Upregulation of Mkl1/2-induced genes coincident with Mkl1/2 nuclear translocation following passive avoidance training. Trained (black bars) and passive control (open bars) mRNA expression levels of Tpm3, α-SMA, Snai2, Egr2, Mkl1, and Mkl2 were determined using real-time PCR. Results are expressed as the mean ± SEM percent change from passive control (n = 4), and values significantly different from naïve and corresponding passive control are indicated by an asterisk (P < 0.05, Student's t-test).

Figure 5.

Upregulation of Mkl1/2-induced genes coincident with Mkl1/2 nuclear translocation following passive avoidance training. Trained (black bars) and passive control (open bars) mRNA expression levels of Tpm3, α-SMA, Snai2, Egr2, Mkl1, and Mkl2 were determined using real-time PCR. Results are expressed as the mean ± SEM percent change from passive control (n = 4), and values significantly different from naïve and corresponding passive control are indicated by an asterisk (P < 0.05, Student's t-test).

In contrast, the TCF–SRF activated gene Egr2, whose expression has been shown to be independent of Mkl1/2 signaling (Selvaraj and Prywes 2004), did not increase at the 3 h time point. In keeping with what is known about the regulation of IEGs following learning, however, we observed increased Egr2 expression 0 h posttraining (140 ± 18% of control, P < 0.05; Fig. 5). In addition, we found that the expression levels of Mkl1 and Mkl2 were not themselves increased at the 3 h time point but, interestingly, were decreased at the 0 h time (75 ± 9% and 55 ± 10% of control, respectively, P < 0.05; Fig. 5).

Discussion

Regulation of Hippocampal Neurite Structure —a Dominant Role for Mkl2

Previous studies have suggested a role for Mkl1 in neuronal structural control. For example, transfection with Mkl1 siRNA–expressing plasmids in high-density cortical cultures results in reduced neuritic growth, whereas neurite outgrowth in cortical and dorsal root ganglia cells is disrupted in dominant negative (DN) mutants of Mkl1 (Shiota et al. 2006; Wickramasinghe et al. 2008). One of the key findings of the present study is the dominate effect that Mkl2 expression has on control of neuritic growth in hippocampal neurons. We found that increased Mkl2 was associated with enhanced neurite outgrowth and branching, whereas decreased Mkl2 significantly inhibits neuritic growth. Interestingly, the previous studies on Mkl1 function did not investigate the effect of the siRNA plasmid or DN mutation on Mkl2 expression, and so we cannot eliminate the possibility that Mkl2 expression was also affected and contributed to the structural deficits observed in those studies. In support of this suggestion, DN Mkl2 mutants have been shown to block activation of both Mkl1 and Mkl2 (Selvaraj and Prywes 2003) raising the possibility that a similar effect occurs for the Mkl1 DN.

Subcellular Localization of Mkl1/2 in Hippocampal Neurons

As mentioned previously, no consensus has been reached as to the subcellular localization of Mkl1/2 (Kalita et al. 2006; Shiota et al. 2006; Stern et al. 2009). Importantly, the Mkl1 antibody used in the present study clearly detects both Mkl1 and Mkl2 proteins. As such, studies using this antibody should refer to Mkl1/2 and not Mkl1 alone. Using this antibody, we report that Mkl1/2 is endogenously expressed in both the cytoplasm and the nucleus of hippocampal neurons in culture and in adult brain. It is noteworthy that our analysis reveals nuclear expression to be more substantial than cytoplasmic in hippocampal neurons (Figs. S6 and S7) and that the Mkl1/2 outside of the nucleus is largely detected in the somatic cytoplasm. Clearly, other antibodies used previously may simply be more specific for Mlk1 and correctly identify this protein to be restricted to the nucleus. This would imply that the cytoplasmic expression seen with our antibody is attributable to Mkl2.

Hippocampal Nuclear Regulation of Mkl1/2 Following Passive Avoidance Learning

Mkl1/2 shuttles between the nucleus and the cytoplasm, even in unstimulated cells (Vartiainen et al. 2007) and has been found to translocate to the nucleus of cortical cells in response to activation of Rho-A signaling (Tabuchi et al. 2005). Here, we provide evidence for dynamic movements of Mkl1/2 between cytoplasmic and nuclear compartments following a learning event. Specifically, Mkl1/2 translocates to, and accumulates within, the nucleus of granule and pyramidal neurons 3 h following passive avoidance training. The functional relevance to learning of such Mkl1/2 nuclear accumulation likely relates to the coincident increased expression of the Mkl1/2-dependent genes, Tpm3, αSMA, and Snai2 in the hippocampal DG. Expression levels of Tpm3 and αSMA are regulated by Mkl1/2-SRF, with αSMA expression in Mkl1 knockout mice attributed specifically to Mkl2 (Li et al. 2006). Our current findings support a direct regulatory role as knockdown of Mkl1 and Mkl2 inhibits transcription of these genes with a particularly profound reduction in αSMA seen following treatment with Mkl2 siRNA. Snai2, a negative regulator of E-cadherin expression, is instead controlled by the Mkl–SMAD3 transcription complex (Schmidt et al. 2005; Morita et al. 2007). Snai2 levels were also increased in the DG 3 h posttraining, but were not affected by dysregulation of Mkl1 or Mkl2 expression in vitro suggesting that basal expression of this gene is Mkl independent, whereas learning-associated activation may still be driven by these transcription cofactors.

Altogether, Mkl targets comprise an impressive list of genes with functions related to actin-dynamics (Miano et al. 2007). The bidirectionality of the relationship between actin dynamics and Mkl signaling can be seen with actin mutations that inhibit actin polymerization, reducing neurite length and downregulating levels of the reported full-length Mkl1/2 protein (Stern et al. 2009). These properties of Mkl signaling, coupled with the postlearning time of regulation preceding the appearance of new synapses (O'Malley et al. 1998, 2000; Eyre et al. 2003), identify Mkl as an ideal candidate to drive transcriptional events underpinning memory-associated synaptic reorganization.

Synaptic activity, via the MAPK/ERK kinase pathway, activates TCF–SRF mediated transcription of IEG expression (Xia et al. 1996; Gokce et al. 2009). This pathway is crucial for the initiation of a cascade of downstream genes required to mediate long-term synaptic plasticity. Here, we confirm the upregulation of the IEG Egr2 0 h posttraining. Strikingly, Egr2 expression is controlled by TCF-SRF activity independent of Mkl1/2 (Selvaraj and Prywes 2004). Also, at 0 h, gene expression and corresponding protein levels of Mkl1/2 are significantly decreased, and there is no active shuttling of Mkl1/2 between subcellular compartments. Given that Mkl1/2 and TCF compete for an overlapping binding site on SRF (Zaromytidou et al. 2006), it is tempting to suggest that decreased Mkl1/2 expression immediately following training in the hippocampus may facilitate TCF SRF–mediated IEG expression necessary at this time (Fig. 6). This theory is supported by studies showing that the TCF Elk-1 can dissociate Mkl1/2 from SRF and that expression levels of Mkl–SRF and TCF–SRF genes are inversely correlated (Yoshida et al. 2007; Descot et al. 2009).

Figure 6.

Diagram illustrating the proposed competition for SRF binding and gene-expression control between the cofactors TCF and Mkl1/2 at different times following a learning event. (A) Immediately following learning, reduced expression of Mkl1/2 facilitates the SRF-TCF interaction, which mediates expression of genes including the IEGs. (B) By 3 h posttraining, during a period of synaptic growth and remodeling, increased nuclear accumulation of Mkl1/2 allows these cofactors to dominate at the SRF-binding site resulting in increased expression of downstream structural genes.

Figure 6.

Diagram illustrating the proposed competition for SRF binding and gene-expression control between the cofactors TCF and Mkl1/2 at different times following a learning event. (A) Immediately following learning, reduced expression of Mkl1/2 facilitates the SRF-TCF interaction, which mediates expression of genes including the IEGs. (B) By 3 h posttraining, during a period of synaptic growth and remodeling, increased nuclear accumulation of Mkl1/2 allows these cofactors to dominate at the SRF-binding site resulting in increased expression of downstream structural genes.

Conclusion

These studies have characterized a role for Mkl transcription cofactors, particularly Mkl2, in regulation of neuronal structure both in vitro and in vivo. These findings support a model where regulation of Mkl1/2 nuclear accumulation contributes to 2 waves of gene regulation during memory consolidation (Fig. 6). The first, immediate gene regulation relates to IEGs may be facilitated by downregulation of Mkls releasing TCF-SRF activity. The second transcriptional wave occurs later at the 3 h postavoidance time point when Mkl accumulates in the nucleus of hippocampal neurons enhancing transcription of Mkl-dependent structural genes that may contribute to the elaboration of new, memory-associated synapses that appear over the subsequent 3-h period.

Supplementary Material

Supplementary material can be found at: http://www.cercor.oxfordjournals.org.

Conflict of Interest: None declared.

References

Bliss
TV
Collingridge
GL
A synaptic model of memory: long-term potentiation in the hippocampus
Nature
 , 
1993
, vol. 
361
 (pg. 
31
-
39
)
Cen
B
Selvaraj
A
Burgess
RC
Hitzler
JK
Ma
Z
Morris
SW
Prywes
R
Megakaryoblastic leukemia 1, a potent transcriptional coactivator for serum response factor (SRF), is required for serum induction of SRF target genes
Mol Cell Biol
 , 
2003
, vol. 
23
 (pg. 
6597
-
6608
)
Cesari
F
Brecht
S
Vintersten
K
Vuong
LG
Hofmann
M
Klingel
K
Schnorr
JJ
Arsenian
S
Schild
H
Herdegen
T
, et al.  . 
Mice deficient for the ets transcription factor elk-1 show normal immune responses and mildly impaired neuronal gene activation
Mol Cell Biol
 , 
2004
, vol. 
24
 (pg. 
294
-
305
)
Dash
PK
Orsi
SA
Moore
AN
Sequestration of serum response factor in the hippocampus impairs long-term spatial memory
J Neurochem
 , 
2005
, vol. 
93
 (pg. 
269
-
278
)
Davis
HP
Squire
LR
Protein synthesis and memory: a review
Psychol Bull
 , 
1984
, vol. 
96
 (pg. 
518
-
559
)
Descot
A
Hoffmann
R
Shaposhnikov
D
Reschke
M
Ullrich
A
Posern
G
Negative regulation of the EGFR-MAPK cascade by actin-MAL-mediated Mig6/Errfi-1 induction
Mol Cell
 , 
2009
, vol. 
35
 (pg. 
291
-
304
)
Eyre
MD
Richter-Levin
G
Avital
A
Stewart
MG
Morphological changes in hippocampal dentate gyrus synapses following spatial learning in rats are transient
Eur J Neurosci
 , 
2003
, vol. 
17
 (pg. 
1973
-
1980
)
Fox
GB
O'Connell
AW
Murphy
KJ
Regan
CM
Memory consolidation induces a transient and time-dependent increase in the frequency of neural cell adhesion molecule polysialylated cells in the adult rat hippocampus
J Neurochem
 , 
1995
, vol. 
65
 (pg. 
2796
-
2799
)
Geinisman
Y
Structural synaptic modifications associated with hippocampal LTP and behavioral learning
Cereb Cortex
 , 
2000
, vol. 
10
 (pg. 
952
-
962
)
Gineitis
D
Treisman
R
Differential usage of signal transduction pathways defines two types of serum response factor target gene
J Biol Chem
 , 
2001
, vol. 
276
 (pg. 
24531
-
24539
)
Gokce
O
Runne
H
Kuhn
A
Luthi-Carter
R
Short-term striatal gene expression responses to brain-derived neurotrophic factor are dependent on MEK and ERK activation
PLoS One
 , 
2009
, vol. 
4
 pg. 
e5292
 
Guettler
S
Vartiainen
MK
Miralles
F
Larijani
B
Treisman
R
RPEL motifs link the serum response factor cofactor MAL but not myocardin to Rho signaling via actin binding
Mol Cell Biol
 , 
2008
, vol. 
28
 (pg. 
732
-
742
)
Igaz
LM
Vianna
MR
Medina
JH
Izquierdo
I
Two time periods of hippocampal mRNA synthesis are required for memory consolidation of fear-motivated learning
J Neurosci
 , 
2002
, vol. 
22
 (pg. 
6781
-
6789
)
Kalita
K
Kharebava
G
Zheng
JJ
Hetman
M
Role of megakaryoblastic acute leukemia-1 in ERK1/2-dependent stimulation of serum response factor-driven transcription by BDNF or increased synaptic activity
J Neurosci
 , 
2006
, vol. 
26
 (pg. 
10020
-
10032
)
Lamprecht
R
LeDoux
J
Structural plasticity and memory
Nat Rev Neurosci
 , 
2004
, vol. 
5
 (pg. 
45
-
54
)
Li
S
Chang
S
Qi
X
Richardson
JA
Olson
EN
Requirement of a myocardin-related transcription factor for development of mammary myoepithelial cells
Mol Cell Biol
 , 
2006
, vol. 
26
 (pg. 
5797
-
5808
)
Malenka
RC
Nicoll
RA
Long-term potentiation–a decade of progress?
Science
 , 
1999
, vol. 
285
 (pg. 
1870
-
1874
)
Miano
JM
Long
X
Fujiwara
K
Serum response factor: master regulator of the actin cytoskeleton and contractile apparatus
Am J Physiol Cell Physiol
 , 
2007
, vol. 
292
 (pg. 
C70
-
C81
)
Miralles
F
Posern
G
Zaromytidou
AI
Treisman
R
Actin dynamics control SRF activity by regulation of its coactivator MAL
Cell
 , 
2003
, vol. 
113
 (pg. 
329
-
342
)
Morita
T
Mayanagi
T
Sobue
K
Dual roles of myocardin-related transcription factors in epithelial mesenchymal transition via slug induction and actin remodeling
J Cell Biol
 , 
2007
, vol. 
179
 (pg. 
1027
-
1042
)
Morris
RG
Moser
EI
Riedel
G
Martin
SJ
Sandin
J
Day
M
O'Carroll
C
Elements of a neurobiological theory of the hippocampus: the role of activity-dependent synaptic plasticity in memory
Philos Trans R Soc Lond B Biol Sci
 , 
2003
, vol. 
358
 (pg. 
773
-
786
)
O'Malley
A
O'Connell
C
Murphy
KJ
Regan
CM
Transient spine density increases in the mid-molecular layer of hippocampal dentate gyrus accompany consolidation of a spatial learning task in the rodent
Neuroscience
 , 
2000
, vol. 
99
 (pg. 
229
-
232
)
O'Malley
A
O'Connell
C
Regan
CM
Ultrastructural analysis reveals avoidance conditioning to induce a transient increase in hippocampal dentate spine density in the 6 hour post-training period of consolidation
Neuroscience
 , 
1998
, vol. 
87
 (pg. 
607
-
613
)
Posern
G
Treisman
R
Actin’ together: serum response factor, its cofactors and the link to signal transduction
Trends Cell Biol
 , 
2006
, vol. 
16
 (pg. 
588
-
596
)
Quevedo
J
Vianna
MR
Roesler
R
de-Paris
F
Izquierdo
I
Rose
SP
Two time windows of anisomycin-induced amnesia for inhibitory avoidance training in rats: protection from amnesia by pretraining but not pre-exposure to the task apparatus
Learn Mem
 , 
1999
, vol. 
6
 (pg. 
600
-
607
)
Ramanan
N
Shen
Y
Sarsfield
S
Lemberger
T
Schutz
G
Linden
DJ
Ginty
DD
SRF mediates activity-induced gene expression and synaptic plasticity but not neuronal viability
Nat Neurosci
 , 
2005
, vol. 
8
 (pg. 
759
-
767
)
Schmidt
CR
Gi
YJ
Patel
TA
Coffey
RJ
Beauchamp
RD
Pearson
AS
E-cadherin is regulated by the transcriptional repressor SLUG during Ras-mediated transformation of intestinal epithelial cells
Surgery
 , 
2005
, vol. 
138
 (pg. 
306
-
312
)
Selvaraj
A
Prywes
R
Megakaryoblastic leukemia-1/2, a transcriptional co-activator of serum response factor, is required for skeletal myogenic differentiation
J Biol Chem
 , 
2003
, vol. 
278
 (pg. 
41977
-
41987
)
Selvaraj
A
Prywes
R
Expression profiling of serum inducible genes identifies a subset of SRF target genes that are MKL dependent
BMC Mol Biol
 , 
2004
, vol. 
5
 pg. 
13
 
Sgambato
V
Pages
C
Rogard
M
Besson
MJ
Caboche
J
Extracellular signal-regulated kinase (ERK) controls immediate early gene induction on corticostriatal stimulation
J Neurosci
 , 
1998
, vol. 
18
 (pg. 
8814
-
8825
)
Shiota
J
Ishikawa
M
Sakagami
H
Tsuda
M
Baraban
JM
Tabuchi
A
Developmental expression of the SRF co-activator MAL in brain: role in regulating dendritic morphology
J Neurochem
 , 
2006
, vol. 
98
 (pg. 
1778
-
1788
)
Sholl
DA
Dendritic organization in the neurons of the visual and motor cortices of the cat
J Anat
 , 
1953
, vol. 
87
 (pg. 
387
-
406
)
Sklyar
O
Pau
G
Smith
M
Huber
W
EBImage: image processing and image analysis toolkit for R
 , 
2009
 
Stern
S
Debre
E
Stritt
C
Berger
J
Posern
G
Knoll
B
A nuclear actin function regulates neuronal motility by serum response factor-dependent gene transcription
J Neurosci
 , 
2009
, vol. 
29
 (pg. 
4512
-
4518
)
Tabuchi
A
Estevez
M
Henderson
JA
Marx
R
Shiota
J
Nakano
H
Baraban
JM
Nuclear translocation of the SRF co-activator MAL in cortical neurons: role of RhoA signalling
J Neurochem
 , 
2005
, vol. 
94
 (pg. 
169
-
180
)
Vartiainen
MK
Guettler
S
Larijani
B
Treisman
R
Nuclear actin regulates dynamic subcellular localization and activity of the SRF cofactor MAL
Science
 , 
2007
, vol. 
316
 (pg. 
1749
-
1752
)
Wang
DZ
Li
S
Hockemeyer
D
Sutherland
L
Wang
Z
Schratt
G
Richardson
JA
Nordheim
A
Olson
EN
Potentiation of serum response factor activity by a family of myocardin-related transcription factors
Proc Natl Acad Sci U S A
 , 
2002
, vol. 
99
 (pg. 
14855
-
14860
)
Wickramasinghe
SR
Alvania
RS
Ramanan
N
Wood
JN
Mandai
K
Ginty
DD
Serum response factor mediates NGF-dependent target innervation by embryonic DRG sensory neurons
Neuron
 , 
2008
, vol. 
58
 (pg. 
532
-
545
)
Xia
Z
Dudek
H
Miranti
CK
Greenberg
ME
Calcium influx via the NMDA receptor induces immediate early gene transcription by a MAP kinase/ERK-dependent mechanism
J Neurosci
 , 
1996
, vol. 
16
 (pg. 
5425
-
5436
)
Yoshida
T
Gan
Q
Shang
Y
Owens
GK
Platelet-derived growth factor-BB represses smooth muscle cell marker genes via changes in binding of MKL factors and histone deacetylases to their promoters
Am J Physiol Cell Physiol
 , 
2007
, vol. 
292
 (pg. 
C886
-
C895
)
Zaromytidou
AI
Miralles
F
Treisman
R
MAL and ternary complex factor use different mechanisms to contact a common surface on the serum response factor DNA-binding domain
Mol Cell Biol
 , 
2006
, vol. 
26
 (pg. 
4134
-
4148
)

Author notes

2
Current address: Department of Genetics, University of Cambridge, Downing Street, Cambridge CB2 3EK, UK