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Human Molecular Genetics Advance Access originally published online on June 13, 2007
Human Molecular Genetics 2007 16(15):1884-1895; doi:10.1093/hmg/ddm137
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Activation of MAPK in hearts of EMD null mice: similarities between mouse models of X-linked and autosomal dominant Emery–Dreifuss muscular dystrophy

Antoine Muchir1,2, Paul Pavlidis3,{dagger}, Gisèle Bonne4,5,6, Yukiko K. Hayashi7 and Howard J. Worman1,2,*

1 Department of Medicine and 2 Department of Anatomy and Cell Biology and 3 Department of Biomedical Informatics, College of Physicians and Surgeons, Columbia University, New York, USA and 4 Institut National de la Santé et de la Recherche Médicale, U582, Institut de Myologie, Paris, France and 5 Université Pierre et Marie Curie-Paris 6, Faculté de médecine, Paris, France and 6 AP-HP, Groupe hospitalier Pitié-Salpêtrière, U.F. Myogénétique et Cardiogénétique, service de Biochimie Métabolique, Paris, France and 7 Department of Neuromuscular Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan

* To whom correspondence should be addressed at: Department of Medicine, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, 10 Floor, Room 508, New York, NY 10032, USA. Tel: +1 2123058156; Fax: + 2123056443; Email: hjw14{at}columbia.edu

Received April 25, 2007; Accepted May 18, 2007


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Emery–Dreifuss muscular dystrophy (EDMD) is an inherited disorder characterized by slowly progressive skeletal muscle weakness in a humero-peroneal distribution, early contractures and prominent cardiomyopathy with conduction block. Mutations in EMD, encoding emerin, and LMNA, encoding A-type lamins, respectively, cause X-linked and autosomal dominant EDMD. Emerin and A-type lamins are proteins of the inner membrane of the nuclear envelope. Whereas the genetic cause of EDMD has been described and the proteins well characterized, little is known on how abnormalities in nuclear envelope proteins cause striated muscle disease. In this study, we analyzed genome-wide expression profiles in hearts from Emd knockout mice, a model of X-linked EDMD, using Affymetrix GeneChips. This analysis showed a molecular signature similar to that we previously described in hearts from Lmna H222P knock-in mice, a model of autosomal dominant EDMD. There was a common activation of the ERK1/2 branch of the mitogen-activated protein kinase (MAPK) pathway in both murine models, as well as activation of downstream targets implicated in the pathogenesis of cardiomyopathy. Activation of MAPK signaling appears to be a cornerstone in the development of heart disease in both X-linked and autosomal dominant EDMD.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Emery–Dreifuss muscular dystrophy (EDMD) is an inherited disorder characterized by contractures of the elbows, Achilles’ tendons and spine, slowly progressive wasting and weakness of skeletal muscles in a humero-peroneal distribution (1). Individuals with EDMD also suffer from cardiomyopathy with conduction defects that increases the risk of sudden death. Initially described as an X-linked inherited disorder, autosomal dominant and recessive forms of EDMD are also recognized, with the dominant form being most prevalent.

X-linked EDMD arises as a consequence of mutations in EMD on chromosome Xq28 (2). EMD encodes emerin, a ubiquitously expressed integral protein of the inner nuclear membrane (3,4). Emerin is composed of 254 amino acids in humans and has a 220 amino acid nucleoplasmic amino-terminal domain, a single transmembrane segment and a short luminal tail (5). Emerin binds to several nuclear proteins and these interactions may underlie various functions attributed to emerin, including regulation of gene expression, nuclear assembly during mitosis, cell cycle control and providing structural support to the nuclear envelope (6). More recently, emerin has also been shown to bind ß-catenin and restrict its accumulation in the nucleus (7).

Autosomal EDMD arises from mutations in LMNA (8). LMNA encodes A-type nuclear lamins, of which lamin A and lamin C are the predominant somatic cell isoforms (9). Nuclear lamins are intermediate filament proteins that polymerize to form a meshwork of 10 nm diameter filaments on the inner aspect of the inner nuclear membrane called the nuclear lamina (10–13). Lamins function in maintaining nuclear architecture and organizing chromatin (14–17). Lamins may also have complex roles in linking the nucleus to the cytoskeleton (18) and in DNA synthesis and transcription regulation (19–21). Lamins interact with integral proteins in the inner nuclear membrane, including emerin, and provide anchorage sites for chromatin and structural support to the nuclear envelope (6,22–27).

Genetically engineered mouse models have been created to study the role of emerin and A-type lamins in the development of EDMD. Lmna knockout mice provided the first animal model of the disease (27). The null mice develop cardiomyopathy and regional skeletal muscle wasting reminiscent of human EDMD (27). Subsequently, knock-in mice that express A-type lamins with the H222P (28) and N195K (29) amino acid substitutions were created. Similar to Lmna knockout mice, homozygous knock-in animals develop features of human EDMD, including cardiomyopathy; however, heterozygous mice are apparently normal. In transgenic mice, cardiac overexpression of human lamin A M371K leads to heart damage, whereas similar overexpression of wild type human lamin A does not cause significant abnormalities (30). Melcon et al. (31) have generated Emd null mice, reporting that Emd–/y males are normal at birth and that their subsequent postnatal growth and locomotion are indistinguishable from wild type siblings. These investigators did not report cardiac pathology in Emd–/y mice. Hayashi and colleagues (32) also generated and characterized Emd knockout mice and reported that they have a normal growth rate and life span without marked muscle weakness or joint abnormalities but have subtle motor coordination abnormalities. These investigators demonstrated small vacuoles in cardiomyocytes of emerin-deficient mice and detected a slight prolongation of atrioventricular conduction time in Emd–/y mice greater than 40 weeks of age.

Despite the fact that the human genetics have been well described and that relevant animal models have been generated, little is known about how mutations in the genes encoding emerin and A-type lamins lead to striated muscle abnormalities. One strategy that could allow for the identification of molecular abnormalities underlying muscle pathology in animal models of EDMD is comprehensive expression analysis at the transcriptome level using microarrays. Using such methods, Melcon et al. (31) have shown that regenerating skeletal muscle from emerin-deficient mice have abnormalities in cell cycle parameters and delayed myogenic differentiation, which is associated with perturbations to transcriptional pathways regulated by the retinoblastoma and MyoD genes. Hence, abnormalities in satellite cell proliferation or differentiation may be responsible for aspects of the pathophysiology of skeletal muscle disease in EDMD by impairing the replacement of fibers. However, this molecular mechanism cannot readily explain cardiac muscle abnormalities, as replacement of cardiomyocytes and regeneration of cardiac tissue is not significant. We recently identified activation of mitogen-activated protein kinase (MAPK) signaling pathway in hearts from mice with the Lmna H222P mutation (33). This molecular pathway has been previously implicated in the development of cardiomyopathy and conduction defects (34,35). We now report the results of a genome-wide expression analysis in hearts from Emd knockout mice, in which we have identified common molecular alterations found in Lmna H222P knock-in mouse hearts, including activation of a MAPK pathway.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Gene expression profiling analysis in hearts from Emd knockout mice
We performed a comparative genome-wide RNA expression analysis in hearts from Emd–/y mice. These mice have mild motor dysfunction, slight prolongation of atrioventricular conduction time and structural fragility of myonuclei (32). We studied mice at 10 weeks of age, before any signs of cardiac dysfunction, to focus on genes with expressions primarily altered as a result of emerin-deficiency and not secondary to possible cardiac damage. At 10 weeks of age, histological analysis of cardiac muscle from Emd–/y mice does not reveal notable pathological changes compared to hearts from control mice (data not shown).

To analyze transcriptomes, we used Affymetrix Mouse Genome 430 2.0 Arrays, which contain 45 101 probes sets for known and predicted genes. We first examined similarities in transcription profiles between hearts from control (n = 8) and Emd–/y (n = 6) mice by hierarchical cluster analysis. The individual patterns of mRNA signal intensities fell into two distinct groups on a heat map corresponding to the sample genotype, wild type and Emd–/y, with similarity between members within each group higher than between the groups (Fig. 1A). This demonstrated that the differences in the distribution of mRNA expression intensities between heart tissue samples from wild type controls and Emd–/y mice were due to changes in the individual gene expression between groups rather than non-specific variations between samples. We then used a supervised learning method to distinguish probe sets representing genes with significant differences in expression between hearts from control and Emd–/y mice. Genes were selected using sufficiently high absolute changes measured by a corrected t-test (q < 0.05) combined with a one log2-fold change cut-off. This analysis identified 27 probe sets in hearts from Emd–/y mice, which correspond to 18 upregulated genes and 9 down-regulated genes (Fig. 1B).


Figure 1
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  		Figure 1. Affymetrix GeneChip expression profiling in hearts of Emd–/y mice. (A) Hierarchical clustering analysis of differentially expressed genes in hearts from control and Emd–/y mice. Rows indicate the expression of individual genes and vertical lines indicate each sample. For each gene, the ratio of transcript abundance in the samples to its abundance in the control is represented by color intensities (yellow indicates higher expression and blue indicates lower expression). (B) Volcano plots of absolute expression values (log2[q-value]) determined by robust multichip analysis. For each probe set, expression in hearts from Emd–/y mice is plotted. A two-fold threshold and q < 0.05 was used to determine the genes significantly altered in the analysis (yellow line squares).

 
The 27 genes with significant differences in expression in hearts of Emd–/y mice compared to control mice are listed in Table 1. Expression of Emd encoding emerin was significantly downregulated (1.8 log2-fold). Several muscle-specific genes were abnormally expressed in hearts from Emd–/y mice. Genes encoding myosin light chains (Myl7, 3.3 log2-fold; Myl4, 2.6 log2-fold) and myosin heavy chains (Myh7, 2.2 log2-fold) were upregulated. Similarly, there was upregulation of expression of genes encoding sarcolipin (Sln, 2.5 log2-fold), calcium channel L-type (Cacna1C, 1.2 log2-fold) and phospholamban (Pln, 1.1 log2-fold), proteins involved in cardiac contractility. The top-ranked genes identified in this analysis (Myl4, Myl7, Myh7, Sln) are common with those previously identified in hearts from LmnaH222P/H222P and LmnaH222P/+ mice of the same age (33). Hence, upregulation of several identical gene signatures appears in hearts from animal models of both X-linked and autosomal dominant EDMD before any overt clinical or cardiac pathology.


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  		Table 1. Genes with altered expression as defined by q < 0.05 and ≥ 1 or ≤ – 1 log2-fold change in hearts from Emd–/y mice

 
To independently validate the expression of selected transcripts identified in the microarray analysis, we performed real-time quantitative RT–PCR using RNA extracted from hearts of mice different from those used for the microarrays. Primers corresponding to genes encoding myosin proteins (Myl4, Myl7, Myh7), polyadenylate binding protein-interacting protein 1 (Paip1), sarcolipin (Sln), peptidylglycine alpha-amidating monooxygenase (Pam), transferrin receptor (Trfc) and emerin (Emd) were selected as representative. Primers for Emd were chosen in the 3’ region following the portion of the gene containing the inserted neor cassette. For these genes, there was a strong correlation between real-time quantitative RT–PCR results and altered expression detected in the microarray analysis of hearts from Emd–/y mice (Fig. 2).


Figure 2
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  		Figure 2. Validation of differential expression in hearts of Emd–/y mice of selected genes identified by GeneChips using real-time quantitative RT–PCR. (A) Matrices visualizing Affymetrix GeneChip data of corresponding probe sets of RNAs are shown at left of bar graph. In these matrices, each probe set is visualized as a row of colored squares with one square for each sample. (B) Bars indicate the fold overexpression of the indicated mRNA in hearts measured by real time quantitative RT–PCR as calculated by the {Delta}{Delta}CT method. White bars are values corresponding to the control mice and black bars are values corresponding to the Emd–/y mice. Values are means ± standard deviations for n = 4 samples per group. The real-time quantitative RT–PCR was performed in triplicate with the different RNA samples.

 
Functional class scoring analysis and ranked gene ontology classes
To obtain a global picture of the affected processes in hearts of Emd–/y mice, we used gene-class testing based on gene ontology (GO) terms. GO terms are functional categories that give information on the known biological processes associated with each gene. Because gene expression might be altered in related groups defined by pathways or functions rather than individually, genes showing coordinated but weak changes may be missed. We therefore used a semi-supervised method called functional class scoring, which examines the statistical distribution of individual gene expression scores among all genes in an ontology class. We can then identify GO terms with significant expression changes for which individual genes involved may not be identified as significant in single gene-profile analysis. Our functional class scoring analysis uses as input the 45 101 q-values from all the probes sets from the Affymetrix Mouse Genome 430 2.0 Arrays without an initial gene selection step. We used two different software packages, ermineJ and Ingenuity Pathway Analysis, which use different statistical approaches (see Materials and Methods).

Using ermineJ, we identified differential expression of GO classes involved in muscle contraction, transcription and translation, metabolism and angiogenesis in hearts from Emd–/y mice (Table 2). GO classes corresponding to signaling pathways were also affected in hearts of Emd–/y mice. These signaling pathways included JNK, MAPK, Wnt, I-kappaB kinase/NF-kappaB and TGF-ß (Table 2). Most of the GO classes with altered expression in hearts of Emd–/y mice were previously identified in hearts of LmnaH222P/H222P (33). This suggested common molecular alterations downstream of Lmna and Emd mutations. Using Ingenuity Pathways Analysis, we identified the same pathways as with ermineJ in the Emd–/y mice. When Ingenuity Pathways Analysis was similarly used to analyze gene expression data from hearts of LmnaH222P/H222P mice (33), it identified genes of several similar pathways affected in hearts of Emd–/y mice (Fig. 3).


Figure 3
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  		Figure 3. GO analysis of functional groups of genes differentially expressed in hearts of Emd–/y and LmnaH222P/H222P mice. The most significantly changed GO terms/pathways were identified by canonical pathways analysis using the Ingenuity Pathways Knowledge base. The ratio represents the number of genes from the data set that map to the pathway divided by the number of all known genes ascribed to the pathway.

 


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  		Table 2. Top-scoring GO terms listed with corresponding P-value and GO identification numbers in hearts from Emd–/y mice. The corresponding significant GO classes from LmnaH222P/H222P mice are reported

 
MAPK is activated in hearts of Emd knockout mice
Our analysis of functional classes of genes revealed significant differences in expression of the groups of genes encoding proteins of the MAPK pathway in hearts of Emd–/y mice. Because we previously identified activation of MAPK cascade in the Lmna H222P knock-in mouse model of autosomal dominant EDMD, we determined if it was similarly activated in hearts of the Emd–/y mouse model of X-linked EDMD. We evaluated the activation of two MAPKs, ERK1/2 and JNK, in hearts from control and Emd–/y mice. These kinases are activated by phosphorylation. Immunoblotting with antibody that recognized phosphorylated ERK1/2 demonstrated an increase in activated ERK1/2 in hearts from Emd–/y mice (Fig. 4A). However, using an antibody that recognized phosphorylated JNK, we did not detect an increase in activated JNK in hearts from Emd–/y mice (Fig. 4A). Phosphorylated ERK1/2 activates a series of downstream target genes, including those encoding elk-1 and atf-2. Immunoblotting with antibodies against elk-1 and atf-2 demonstrated increased expression of atf-2 but not elk-1 in hearts from Emd–/y mice compared to control mice (Fig. 4B). These data indicate an activation of ERK1/2 signaling in hearts from Emd–/y mice.


Figure 4
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  		Figure 4. MAPK signaling is activated in hearts from Emd–/y mice. (A) Detection of phosphorylated ERK1/2 (pERK1/2), total ERK1/2, phosphorylated JNK (pJNK) and total ERK1/2 by immunoblotting of proteins extracted from hearts of control and Emd–/y mice. Data in bar graphs are means ± standard deviations for four samples per group (* P < 0.05). (B) Detection of elk-1, atf2 and emerin by immunoblotting of proteins extracted from hearts of control and Emd–/y mice. ß-actin is used as an internal loading control.

 
To compare the degree of ERK1/2 activation in hearts from Emd–/y and LmnaH222P/H222P mice, we measured the activated phosphorylated ERK1/2 by immunoblot. Phosphorylated ERK1/2 was activated 2-fold in hearts from Emd–/y mice and 3-fold in hearts from LmnaH222P/H222P mice compared to hearts from control mice (Fig. 5). This showed a greater activation of ERK1/2 in hearts from LmnaH222P/H222P mice than in hearts from Emd–/y mice.


Figure 5
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  		Figure 5. ERK1/2 activation in hearts from both Emd–/y and LmnaH222P/H222P mice. Detection of phosphorylated ERK1/2 (pERK1/2) and total ERK1/2 by immunoblotting of proteins extracted from hearts of control, Emd–/y and LmnaH222P/H222P mice. Data in bar graphs are means ± standard deviations (* P < 0.05).

 
We analyzed the expression of additional genes normally activated downstream in the MAPK cascade using real-time quantitative RT–PCR. While these individual genes were not found to be significantly differentially expressed in our single gene-profile analysis, the fact that they are in MAPK GO classes suggested they may be activated. Expression of c-jun was statistically significantly increased in hearts from Emd–/y mice but expression of Elk1 and Elk4 was not (Fig. 6A). We further detected increases in expression of Atf2, Atf4, Nfat2 and Nfat4 in hearts from Emd–/y mice (Fig. 6A). To compare this model of X-linked EDMD to a model of autosomal dominant EDMD, we examined the expression of these same genes in hearts from LmnaH222P/H222P mice at 10 weeks of age. In hearts from these mice, there was significantly increased expression of all of these downstream factors in the MAPK cascade (Fig. 6B). These results showed an activation of MAPK pathway in mouse models of X-linked and autosomal dominant EDMD; however, more downstream genes in MAPK pathway were activated in hearts from LmnaH222P/H222P mice.


Figure 6
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  		Figure 6. Expression of downstream genes in MAPK pathway in hearts from mouse models of EDMD. (A) Summary of real-time RT–PCR results in hearts from Emd–/y mice is shown. Bars indicate the fold overexpression of the indicated mRNA normalized to Gapdh as calculated by the {Delta}{Delta}CT method. Values are means ± standard deviations for n = 4 samples per group (*P < 0.05). (B) Summary of real-time quantitative RT–PCR results in hearts from LmnaH222P/H222P mice is shown. Bars indicate the fold overexpression of the indicated mRNA normalized to Gapdh as calculated by the {Delta}{Delta}CT method. Values are means ± standard deviations for n = 4 samples per group (*P < 0.05, **P < 0.005).

 
To analyze in vivo activation of ERK1/2 in cardiac cells, we used an antibody that recognized phosphorylated ERK1/2 in sections of heart tissue. Histological examination of hearts revealed neither fibrosis nor inflammation or a significant number of cells other than cardiomyocytes (data not shown). Immunofluorescence microscopic labeling of heart sections from control mice with these antibodies revealed a rather diffuse fluorescence pattern, whereas fluorescence in hearts from Emd–/y mice was more intense and predominantly nuclear (Fig. 7A). Quantitative analysis of individual cardiomyocytes in the sections confirmed that the anti-phosphorylated ERK antibody labeled both cytoplasm and nucleus in hearts from control mice but essentially only the nucleus in hearts from Emd–/y mice (Fig. 7B). While fluorescence intensity of nuclear labeling was significantly higher in cardiomyocytes from Emd–/y mice compared to control mice, it was less than that in cardiomyocytes of LmnaH222P/H222P mice (Fig. 7C). These results suggested a gradient of activation and nuclear translocation of ERK1/2 in hearts from Emd–/y and LmnaH222P/H222P mice compared to control mice.


Figure 7
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  		Figure 7. Immunofluorescence microscopic analysis of phopshorylated ERK1/2 (pERK) in heart sections from mouse models of EDMD. (A) Sections of frozen heart from control, Emd–/y and LmnaH222P/H222P mice were analyzed by immunofluorescence microscopy using anti-pERK1/2 antibody (red). Sections were counterstained with 4',6-diamidino-2-phenylindole (blue). Bars: 50 µm. (B) Quantification of pERK1/2 labeling in cardiomyocytes from control, Emd–/y and LmnaH222P/H222P mice. Cardiomyocytes are delineated by dotted line and intensity of emitted fluorescence is measured along the yellow arrow (a to b). Intensity of the signal varies from 255 (absence of fluorescence) to 0 as reported on the scale; maximal intensity show on y-axis varies between panels. Position of the nucleus and intensity of fluorescence using mouse anti-pERK1/2 antibody is shown in the diagram of a single cardiomyocyte. (C) Quantification of pERK1/2 labeling in cardiomyocytes. Bars indicate intensity of pERK1/2 fluorescence in the nucleus of the indicated hearts. Values are means ± standard deviations for the intensity of nuclear fluorescence from n = 80 cardiomyocytes from two different hearts per group (*P < 0.05, **P < 0.005).

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 REFERENCES
 
Although the causative genetic mutations have been identified and the descriptive pathology well documented, cellular mechanisms linking the genetic mutations to cardiac dysfunction in EDMD are unknown. We recently showed that in the Lmna H222P knock-in mouse model of autosomal dominant EDMD, there was activation of MAPK cascade and downstream targets in heart prior to the development of clinical or histological pathology (33). Genes encoding myosins and other sarcomeric proteins were also abnormally activated in these mice at an age when their hearts were histologically normal (33). In addition to being present in LmnaH222P/H222P, which develop cardiomyopathy at approximately 8 weeks of age and have shortened life spans, similar early changes in gene expression were present in LmnaH222P/+ mice, which do not develop significant cardiomyopathy and have normal life spans. In this study, we examined gene expression changes in the hearts of Emd–/y mice, a genetic model of X-linked EDMD. Similar to LmnaH222P/+ mice, these mice apparently have normal life spans and do not develop clinically significant cardiomyopathy; however, they have small vacuoles mostly bordering nuclei in cardiomyocytes and develop mild first-degree heart block at 40 weeks of age (32). The Emd–/y mice had gene expression alterations in hearts similar to those in hearts of LmnaH222P/+ and LmnaH222P/H222P mice, including activation of the ERK branch of the MAPK pathway.

It has been hypothesized that dilated cardiomyopathy-causing mutations affect force transmission from the sarcomere to the extra-sarcomeric cytoskeleton (36). In the present study, in which we performed genome-wide expression analysis in hearts from Emd–/y mice before any clinical cardiac abnormalities, we showed that genes encoding proteins involved in cardiac contraction are abnormally upregulated. The identified genes encoded either proteins of the sarcomere, such as ß-myosin heavy chain and myosin light chain, or proteins involved in the Ca2+ homeostasis such as sarcolipin, calcium channel voltage-dependent L type and phospholamban. A concomitant deregulation of these two functional categories acting in muscle excitation-contraction is a common observation in cardiomyopathies (36,37).

We detected an abnormal activation of genes in the MAPK cascade in hearts of Emd–/y mice. For some of these genes, we found increased expression only by using real-time RT–PCR. Others and we have previously reported similar differences between microarrays and real-time RT–PCR for transcripts with a low absolute expression or when the difference of expression between the experimental and control are small (33,38,39). The fact that we also showed an increase in phosphorylation and nuclear translocation of ERK1/2 in cardiomyocytes strongly supports an activation of this branch of the MAPK cascade in hearts of Emd–/y mice. Although altered expression of the GO group defined as JNK cascade appeared significant in our statistical analysis using ermineJ and Ingenuity Systems, we did not detect activation of JNK in hearts of Emd–/y mice. This could be explained by the redundancy of functional classes in GO analysis. JNK and ERK1/2 are two branches of the MAPK pathway and have been described as activated by similar stimuli through the same G-protein-coupled receptors (40). Both kinases also activate the same downstream nuclear substrates (41). The dichotomy between the two branches is not entirely clear and is reflected by 55 probes sets corresponding to 22 genes in both the JNK and ERK1/2 GO functional classes.

Our results further showed that activation of MAPK cascade in hearts of Emd–/y mice was less significant than in hearts of LmnaH222P/H222P mice. We previously demonstrated that both ERK1/2 and JNK were activated in heart from LmnaH222P/H222P mice and to a lesser extent in hearts from LmnaH222P/+ mice (33). In this study, we detected only an activation of ERK1/2 in hearts from Emd–/y mouse. We further showed that more downstream targets of MAPK were activated in hearts from LmnaH222P/H222P mice than in hearts from Emd–/y mice. The Emd–/y mice have slight cardiac dysfunction characterized by a mild prolongation of atrioventricular conduction time and vacuolization in cardiomyocytes (32). In contrast, male LmnaH222P/H222P mice develop cardiac chamber dilation associated with decreased left ventricle fractional shortening starting at 8 weeks of age (33). At 12 weeks of age, male LmnaH222P/H222P mice have pronounced conduction system abnormalities characterized by an increased atrioventricular conduction time. Male LmnaH222P/H222P mice die between 4 to 9 months of age. Two hypotheses can be raised to explain these differences between male LmnaH222P/H222P mice and Emd–/y mice. First, activation of the ERK branch of MAPK cascade may ultimately lead only to conduction defects in heart and not to pump failure. This hypothesis remains to be tested. Second, a relationship may exist between the degree of MAPK cascade activation and the severity of the heart disease. Our results suggest that this is more likely to be the case.

Several previous studies have implicated MAPK signaling in the development of cardiomyopathy. Overexpression of members of the ERK branch of MAPK cascade in mice causes cardiomyopathy (41–44). Activation of the MAPK cascade has also been reported in caveolin-3 (45), caveolin-1 (46) and p85 subunit of class I(A) PI3K (47) knockout mice, all of which develop cardiomyopathy. Activating mutations in MEK1 and MEK2 encoding kinases that activate ERK1 and ERK2 cause a cardio-facial-cutaneous syndrome (48). In addition, we previously demonstrated that the MAPK cascade is abnormally activated in hearts from Lmna H222P knock-in mice (33). The JNK branch of the MAPK cascade is also activated in dilated human hearts (49,50).

The results of this study and our previous work (33) suggest that activation of MAPK results directly from mutations in Emd and Lmna and that the MAPK activation leads to heart dysfunction. The mechanism of how mutations in genes encoding nuclear envelope proteins activate MAPK remains to be elucidated; however, ERK and JNK appear to be directly activated by the expression of A-type lamins with amino acid substitutions encoded by LMNA mutations that cause autsomal dominant EDMD (33). It remains to be determined if loss of emerin from cells similarly leads directly to MAPK cascade activation. Activation of MAPK leads to the further activation of several downstream target genes and we found several of these, including c-Jun, Atf2, Atf4, Nfat2 and Nfat4, to be abnormally activated in hearts from Emd–/y and Lmna H222P mice. Transcription factors encoded by these genes can in turn regulate the expression of additional genes, including those encoding proteins involved in sarcomere structure, cardiomyofiber organization and other aspects of heart function (51,52). Abnormal expression of these proteins can lead to cardiomyopathy. Activation of the MAPK cascade has also been previously shown to regulate the calcium induced calcium-released mechanism, producing a negative inotropic effect (53,54). Hence, MAPK activation induced by abnormalities in emerin and A-type lamins can initiate a chain of events that leads to cardiomyopathy.

In summary, our data provide insights into the initial stages of cardiac pathology induced by defects in emerin and A-type lamins. Mutations in the genes encoding these proteins that cause EDMD lead to activation of MAPK signaling in hearts and changes in the expression of downstream genes implicated in the development of cardiomyopathy. These results have important practical implications because small molecule drugs can potentially be used to inhibit the different branches of the MAPK pathway (55,56).


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
REFERENCES
 
Mice
Emd–/y mice (32) and LmnaH222P/H222P mice (28) were generated and genotyped as described.

RNA isolation
Total RNA was extracted from mouse hearts using the Rneasy isolation kit (Qiagen) according to the manufacturer's instructions. Adequacy and integrity of extracted RNA were determined by gel electrophoresis and concentrations measured by ultraviolet absorbance spectroscopy.

Microarray processing
We used Mouse Genome 430 2.0 GeneChip Arrays (Affymetrix). cDNA synthesis, cRNA synthesis and labeling were performed as described previously (33). Hybridization, washing, staining and scanning of arrays were performed at the Gene Chip Core Facility of the Columbia University Genome Center.

Microarray data analysis
Image files were obtained through Affymetrix GeneChip software and analyzed by robust multichip analysis using Affymetrix microarray ‘.cel’ image file and GeneTraffic (Iobion Informatics) software. Robust multichip analysis is composed of three steps: background correction, quantile normalization and robust probe set summary. Genes were identified as differentially expressed if they met a false discovery rate threshold of 0.05 in a two-sample t-test (q-value) and showed at least a log2-fold difference in expression independent of absolute signal intensity. Our gene expression data are available in the National center for Biotechnology Information's Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/), accessible through GEO Series accession number GSE6399.

Analysis of functional groups of genes
Gene expression changes related to functional groups were analyzed using the class score method in ermineJ (http://www.bioinformatics.ubc.ca/ermineJ/) (57) and the functional annotation method in Ingenuity Systems software (http://www.ingenuity.com). In ermineJ, the algorithm takes as input the log-transformed t-test P-values of genes that are members of a single GO class and estimates the probability that the set of q-values would occur by chance. Significant GO terms were identified using a false discovery rate of 0.05. In ingenuity systems, the identified canonical pathways were evaluated employing the right-tailed Fisher's exact test to calculate levels of significance. The P-value for each pathway was calculated by comparing the number of user-specified genes of interest that participated in a given function or pathway, relative to the total number of occurrences of these genes in all functional/pathway annotations stored in the ingenuity pathways knowledge base. Only annotations that have more Functions/Canonical Pathways Analysis genes than expected by chance (‘right-tailed’ annotations) were used.

Real-time RT–PCR analysis
Primers were designed correspond to mouse RNA sequences using Primer3 (http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi). RNA was extracted using Rneasy Protect Kit (Qiagen) and subsequently reverse transcribed using SuperScript first-strand synthesis system according to the manufacturer's instructions (Invitrogen). The real-time quantitative RT–PCR reaction contained iQ SYBR green super mix (Bio-Rad), 200 nM of primers and 0.2 µl of template in a 25 µl reaction volume. Amplification was carried out using the MyiQ Single-Color real-time PCR Detection System (Bio-Rad) with incubation times of 2 min at 95°C, followed by 50 cycles of 95°C for 30 s and 62°C for 30 s. Specificity of the amplification was checked by melting-curve analysis. Relative levels of mRNA expression were calculated according to the {Delta}{Delta}CT method, normalized by comparison to Gapdh mRNA expression.

Extraction of proteins from hearts and immunoblotting
Immunoblotting was performed as described previously (33). The following primary antibodies were used at dilutions from 1:200 to 1:1000: mouse monoclonal anti-emerin (Santa-Cruz), rabbit polyclonal anti-ERK1/2 (Santa-Cruz), rabbit polyclonal anti-pERK1/2 (Cell Signaling), rabbit polyclonal anti-JNK (Santa-Cruz), rabbit polyclonal anti-pJNK (Cell Signaling), anti-elk1 (Santa-Cruz), anti-atf-2 (Santa-Cruz) and anti-ß-actin (Santa-Cruz). Secondary antibodies were HRP-conjugated (Amersham). Blots were developed using ECL (GE Healthcare) and exposed to X-OMAT film (Kodak) for appropriate periods of time. Band densities were calculated using Scion Image software (Scion Corporation) and normalized to the appropriate total JNK or ERK1/2 of protein extracts.

Immunofluorescence microscopy
For immunohistochemistry, 8 µm frozen sections of transversal cardiac muscles were fixed in 3.7% formaldehyde in phosphate-buffered saline for 15 min and then blocked in 5% fetal goat serum in phosphate-buffered saline containing 0.5% Triton X-100 for 1 h. Antibodies used were primary mouse anti-pERK1/2 (Cell Signaling) and secondary Texas Red conjugated anti-mouse (Molecular Probes). Sections were counterstained with 0.1 µg/ml 4',6-diamidino-2- phenylindole (Sigma-Aldrich). Specimens were observed using a Microphot SA (Nikon). Images were collected using a Spot RT Slide camera (Diagnostic Instruments) linked to a PC computer running Adobe Photoshop 6.0 (Adobe Systems). Fluorescence intensity in cardiomyocytes was measured using Scion Image software (Scion Corporation). Data are reported as means ± standard deviations and are compared with respective controls using a two-tailed t-test.


   ACKNOWLEDGEMENTS
 
We thank T. Arimura and V. Decostre for assistance with breeding and analyzing Lmna H222P mice, A. Gharavi for assistance with real-time quantitative RT–PCR, V. Miljkovic for assistance with hybridization of Affymetrix GeneChips and J. Ribeiro, C. Derognat and S. Mafray for helpful discussions. A.M. was supported in part by fellowship grants from Association Française contre les Myopathies and Fondation pour la Recherche Médicale. This work was supported primarily by a grant from the National Institutes of Health (AR048997) to H.J.W. It was also supported by grants for Research on Psychiatric and Neurological Diseases and Mental Health from Health and Labor Sciences Research, Scientific Research from the Japan Society for the Promotion of Science and the Nervous and Mental Disorders and from the Japan Ministry of Health, Labor and Welfare to Y.K.H.; from the Human Frontiers Science Program (RGP0057/2001-M) to H.J.W., Y.K.H. and G.B.; and from the European Union Sixth Framework (Euro-laminopathies, Contract No. 018690) and from Association Française contre les Myopathies (No. 11057) to G.B.

Conflict of Interest statement. None declared.


   FOOTNOTES
 
{dagger} Present address: UBC Bioinformatics Centre, University of British Columbia, Vancouver, Canada BC V6T 1Z4. Back


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TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
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