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Physiol. Genomics 32: 207-218, 2008. First published November 13, 2007; doi:10.1152/physiolgenomics.00017.2007
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Received 16 January 2007; accepted in final form 12 November 2007.
Physiological Genomics 32:207-218 (2008)
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Gene profiling of skeletal muscle in an amyotrophic lateral sclerosis mouse model

Jose-Luis Gonzalez de Aguilar 1,2, Christa Niederhauser-Wiederkehr 3, Benoît Halter 1,2, Marc De Tapia 1,2, Franck Di Scala 1,2, Philippe Demougin 3, Luc Dupuis 1,2, Michael Primig 3, Vincent Meininger 4 and Jean-Philippe Loeffler 1,2

1 Institut National de la Santé et de la Recherche Médicale, U692, Laboratoire de Signalisations Moléculaires et Neurodégénérescence, Strasbourg
2 Université Louis Pasteur, Faculté de Médecine, Unité Mixte de Recherche en Santé-692, Strasbourg, France
3 Biozentrum and Swiss Institute of Bioinformatics, Basel, Switzerland
4 Hôpital de la Pitié-Salpêtrière, Fédération des Maladies du Système Nerveux, Centre Référent Maladie Rare Sclérose Latérale Amyotrophique, Paris, France


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Muscle atrophy is a major hallmark of amyotrophic lateral sclerosis (ALS), the most frequent adult-onset motor neuron disease. To define the full set of alterations in gene expression in skeletal muscle during the course of the disease, we used the G86R superoxide dismutase-1 transgenic mouse model of ALS and performed high-density oligonucleotide microarrays. We compared these data to those obtained by axotomy-induced denervation. A major set of gene regulations in G86R muscles resembled those of surgically denervated muscles, but many others appeared specific to the ALS condition. The first significant transcriptional changes appeared in a subpopulation of mice before the onset of overt clinical symptoms and motor neuron death. These early changes affected genes involved in detoxification (e.g., ALDH3, metallothionein-2, and thioredoxin-1) and regeneration (e.g., BTG1, RB1, and RUNX1) but also tissue degradation (e.g., C/EBP{delta} and DDIT4) and cell death (e.g., ankyrin repeat domain-1, CDKN1A, GADD45{alpha}, and PEG3). Of particular interest, metallothionein-1 and -2, ATF3, cathepsin-Z, and galectin-3 genes appeared, among others, commonly regulated in both skeletal muscle (our present data) and spinal motor neurons (as previously reported) of paralyzed ALS mice. The importance of these findings is twofold. First, they designate the distal part of the motor unit as a primary site of disease. Second, they identify specific gene regulations to be explored in the search for therapeutic strategies that could alleviate disease before motor neuron death manifests clinically.

atrophy; axotomy; denervation; neuromuscular disease


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
AMYOTROPHIC LATERAL SCLEROSIS (ALS) is a fatal adult-onset neuromuscular disease characterized by the selective degeneration of upper and lower motor neurons, progressive muscle wasting, and paralysis. Most cases occur sporadically, but some patients exhibit an autosomal dominant pattern of inheritance. A small subset of these cases results from mutations in the gene encoding Cu/Zn-superoxide dismutase (SOD1), a free radical-scavenging enzyme protecting cells against oxidative stress (66). When ubiquitously expressed in mice, SOD1 mutations trigger ALS as observed in humans (27, 65, 81). However, mutant SOD1 (mSOD1) expression exclusively in motor neurons does not cause ALS, which suggests that these cells may not be the only site where the mutant enzyme acts primarily to trigger disease (44, 62). Astrocytes and microglial cells seem to play an important role in the degenerative process (5, 14). Beyond motor neuron loss, mSOD1 expression also induces unexpectedly high levels of energy expenditure and muscular metabolic rate and a reduction in adipose tissue stores. Counteracting this hypermetabolic trait with a highly energetic diet offers neuroprotection and extends survival (22). Altogether, these findings strongly suggest that other pathological events distinct from motor neuron death do contribute to ALS.

Neuromuscular junction pathology occurs in ALS before the onset of overt clinical symptoms and motor neuron death (2, 24, 25, 26). In mSOD1 muscles, increased total dismutase activity (41), high expression of uncoupling protein-3 (20) and other anabolic (22) and anti-oxidant enzymes (34, 50), mSOD1 aggregates (73), and muscle fiber atrophy (35) also precede significant motor neuron loss. Interestingly, expressing a locally acting IGF-I isoform in mSOD1 muscles maintains neuromuscular junction integrity, delays motor neuron death, and extends lifespan (18). It is therefore reasonable to suggest that ALS proceeds in a distal-to-proximal dying back pattern and that certain alterations of muscular origin could contribute to enhance axon vulnerability.

Important progress has been made to decipher the global pattern of transcriptional modifications underlying muscle atrophy under experimental and disease conditions. In turn, although a few studies examined large-scale gene expression changes in ALS spinal cord motor neurons (23, 33, 46, 60), the alterations of the muscle transcriptome in this disease have never been investigated. We hypothesized that analysis of gene expression in skeletal muscle may provide new insight to better understand the early neuromuscular abnormalities that precede motor neuron death in ALS. To this end, we performed high-density oligonucleotide microarray analysis of gene expression in hindlimb skeletal muscles of SOD1(G86R) mice, one of the existing transgenic models that recapitulate many of the characteristics of ALS (65). To monitor denervation-dependent gene expression, we also determined the effects of sciatic nerve axotomy on the muscle transcriptome. The pathophysiological implications of the observed expressional changes are discussed in relation to ALS neurodegeneration.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Animals.
Transgenic FVB/N males expressing the murine G86R SOD1 mutation were obtained in our animal facility and genotyped as described (65). Transgenic male mice with the human G93A SOD1 mutation were obtained from The Jackson Laboratory (Bar Harbor, ME). The altered transgenes contained the entire coding sequence of either mouse or human SOD1 and their corresponding flanking regulatory regions (27, 65). mSOD1 mRNA and protein were detected in G86R and G93A muscles, as reported elsewhere (1, 35, 65). Mice were maintained at 23°C with a 12:12-h light-dark cycle and were provided water and regular rodent chow ad libitum. We had previously determined the progression of disease symptoms in G86R mice according to a clinical rating scale going from score 4 to 0 (67). Score 4 is attributed to asymptomatic G86R mice, relative to their wild-type littermates. Score 3 corresponds to an alteration in hindlimb extension when the animal is hung by the tail. Score 2 is attributed when any slight alteration in the locomotion is observed. Score 1 represents an asymmetric or symmetric paralysis of the limbs. Score 0 corresponds to the stage at which animals are unable to roll over within 10 s after being pushed on their back. For this study, hindlimb skeletal muscles, including soleus and gastrocnemius, were dissected from G86R mice at 75 days of age (score 4 or asymptomatic); at 90 days of age, when ~40% of the animals present with altered hindlimb extension reflexes (score 3 or preparalyzed); and at the onset of hindlimb paralysis at 105–107 days of age (score 1). Nontransgenic male littermates served as controls. Denervated muscles were obtained from wild-type mice at 90 days of age after 7 days of sciatic nerve axotomy as previously described (21). Ipsilateral and contralateral hindlimbs from axotomized and sham-operated animals were used. Mice were killed by decapitation, and muscles were carefully dissected, frozen in liquid nitrogen, and stored at –80°C until use. Three to four animals were pooled per experimental condition, and each condition was done in duplicate (Table 1). Animal manipulation followed present European Union regulations and was carried out under the supervision of authorized investigators.


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  		Table 1. Experimental groups

 
Data analysis.
Microarray data files were uploaded to the European Bioinformatics Institute ArrayExpress repository at http://www.ebi.ac.uk/arrayexpress/ (accession no. E-TABM-195). CEL data files were computed using the statistical algorithm implemented in Microarray Suite 5.0. Data were further analyzed using programs developed in R 1.8.0 (Ref. 30 and http://www.r-project.org). The Robust Multichip Average method as implemented in the BioConductor package "affy" (Refs. 6, 31 and http://www.bioconductor.org) or GeneSpring 7.2 (Silicon Genetics, Redwood City, CA) was employed for data normalization, background correction, and summarization. Gene expression signal calculation was based on the Perfect Match values from each probe set as previously reported (31). To remove transcripts with unreliable measurements (i.e., very close to background levels), we used the "Filter on Expression Level" tool in GeneSpring 7.2 and kept transcripts whose raw intensities were higher than 50 in at least 2 of the 20 microarrays. To isolate highly regulated genes, an unsupervised selection of transcripts was performed based on the calculation of the standard deviation (SD) of every single probe set (or transcript) across all microarrays (Fig. 1). Those probe sets with SD >0.8 were retained. This cutoff was arbitrarily fixed to obtain a handleable, small subset of genes (i.e., <100) displaying highly differential expression in at least one of the experimental conditions. To learn about previously unknown relationships among the experimental conditions we tested, the 20 samples were ordered according to the expression patterns of the selected transcripts using Ward's hierarchical clustering method. Although there is no definite rule as to which type of clustering to use, we preferred the Ward's method because it is particularly adapted to large-scale studies and produces an ordering of objects, which may be informative for data display. Since Ward's method always tries to minimize within-groups variance, it tends to generate small clusters, which may be helpful for discovery (77). To identify typical transcriptional patterns among those transcripts, they were subgrouped into smaller categories (or clusters) according to their overall transcription patterns but not signal intensities using partitioning around medoids (PAM) (37). After several rounds of analysis with increasing numbers of clusters, the best significance was obtained with six clusters, as assessed by comparing the degree of similarity of a given pattern to those within its own cluster and to those in all other clusters (determined by the silhouette plots method; data not shown). To evaluate the implication of different functional categories of genes as represented in the preselected group of transcripts, the whole database was screened for differentially expressed genes between the pathological or denervation condition and their corresponding controls (Fig. 1). Only genes whose expression was changed at least twofold were kept. The twofold cutoff was selected because it is the most stringent one suggested by the GeneChip manufacturer to reduce false positives (47). Functional categorization was performed using the Affymetrix Gene Ontology Data Mining Tool, and additional information was obtained from the National Center for Biotechnology Information database and the basic local alignment search tool BLAST-N. The most significant changes in G86R muscles at the onset of paralysis and axotomy-induced denervated muscles were highlighted by applying the Welch t-test using error model variances in combination with the Benjamini and Hochberg false discovery rate for multiple testing corrections, as implemented in GeneSpring 7.2.


Figure 1
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  		Fig. 1. Flowchart of data mining. SD, standard deviation; PAM, partitioning around medoids.

 
Protocols for RNA extraction, cRNA target synthesis, GeneChip hybridization, real-time RT-PCR, and Western blot and assessment of oxidative stress are given in the Supplemental Methods (supplemental materials are available at the online version of this article). For the real-time RT-PCR experiments, statistical analysis was accomplished using ANOVA followed by Tukey's multiple comparisons test.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
Methodological considerations.
Because RNA degradation causes data to be less reproducible and makes it more difficult to detect low-abundance transcripts, all total RNA and cRNA target molecule preparations made from each muscle sample were analyzed for their concentration and overall length. Supplemental Fig. S1 shows that reproducibility between samples is of very high quality. Another critical aspect introducing unwanted gene expression variability is the heterogeneous origin of the samples. Although the use of animal models of disease greatly minimizes this variability, the course of ALS in the mSOD1 mice is not exempt from a certain degree of heterogeneity. To reduce interindividual differences in disease progression, we used two replicates per experimental condition, each containing three to four pooled samples (Table 1). Finally, we applied an innovative approach that only uses the Perfect Match values and does not take into account the Mismatch values to calculate gene expression levels. This method increases the sensitivity of the measures because the Mismatch oligonucleotide signal is thought not only to reflect nonspecific hybridization events but also to contain true expression information that is lost when the default statistical algorithm for data analysis provided by the manufacturer is applied (6, 31).

We used in this study two hindlimb muscles: the soleus, which is composed of 60% slow-twitch fibers and 40% fast-twitch fatigue-resistant fibers, and the gastrocnemius, which is ~10 times bigger than the soleus and contains 55% fast-twitch fatigable fibers, 30% fast-twitch fatigue-resistant fibers, and 10% slow-twitch fibers (8, 12). Fast-twitch fibers are more vulnerable and weaken at earlier stages of ALS than slow-twitch fibers (1, 17). In addition, fast muscles of mSOD1 mice become slower and fatigue resistant, and show an age-dependent increase in their oxidative capacity as a consequence of the disease progression (69). Because the contractile features and phenotype of individual fibers in a muscle are constantly changing during the course of the disease, we assumed that there is no simple correlation between gene expression changes in isolated fibers and the overall genetic signature characterizing the atrophic process of the whole limb, and therefore analyzed the transcriptional alterations expressed by both soleus and gastrocnemius all together.

Finally, we studied here the transcriptome of ALS and acutely denervated muscles. Increased expression of acetylcholine receptor {alpha}- and β-subunits is very noticeable after 7 days of sciatic nerve axotomy (80), and, in our hands, such modifications were found to be very similar to those observed in paralyzed G86R mice (Supplemental Fig. S2), which makes the two denervation conditions comparable.

The transcriptome of ALS muscle is altered at preparalysis stages.
The scatterplot matrix of the totality of the probe sets in the MG-U74Av2 GeneChips indicated that samples from G86R mice at the onset of paralysis and those suffering from axotomy resembled each other but differed importantly from the others (Supplemental Fig. S3). In addition, one of the sample replicates of 90-day-old G86R mice presented significant differences with respect to the other 90-day-old sample. To further assess these observations, we performed unsupervised hierarchical clustering of the 20 samples and 83 transcripts whose expression signals displayed an SD >0.8 across the 20 data sets (Fig. 2). Although this approach yields a very conservative estimate of the number of differentially expressed genes, the two 90-day-old sample replicates appeared clearly separated: one sample looked more like the wild-type and control samples and represented an early preparalysis phase of the disease, whereas the other one more closely resembled the samples from paralyzed and axotomized mice and represented a late preparalysis phase (Fig. 2, dendrogram at top). We then applied the PAM algorithm to identify typical transcriptional patterns among the 83 preselected transcripts. Using centered and scaled data to minimize the impact of expression levels, we defined six typical transcriptional patterns (or medoids) that gave rise to six different groups (or clusters) of genes (Fig. 3). Clusters 1 and 2 contained 18 and 34 transcripts, respectively, that were upregulated in samples from G86R mice during the late preparalysis phase and at the onset of paralysis as well as in those suffering from axotomy. The three transcripts contained in cluster 3 presented very variable expression levels, even among the several control conditions, and were not considered. Clusters 4 and 6 contained nine and seven transcripts, respectively, that were downregulated mostly in samples from paralyzed G86R and axotomized mice. Finally, cluster 5 contained 11 transcripts that appeared mostly upregulated in ALS but not after experimental denervation.


Figure 2
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  		Fig. 2. Hierarchical clustering of 20 samples and 83 probe sets. A heat map of 83 transcripts and 2 dendograms that group genes (left) and samples (top) together are shown. Each line is a gene, and each column is a sample. Expression signal intensities are shown in red and blue, indicating high and low expression, respectively. Names of the 83 genes are indicated at right.

 

Figure 3
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  		Fig. 3. PAM clustering of 83 probe sets. Log scale graphic display of the expression patterns of the 83 genes separated into 6 clusters. Medoids representing each cluster are indicated by bold line.

 
To gain further insight into the gene expression changes in a subset of mice at 90 days of age, we searched for differentially regulated genes in the entire database that presented at least a twofold change between the pathological or denervation condition and their corresponding controls (Supplemental Table S1). We did not find any significant alterations in steady-state mRNA abundance in G86R mice at 75 days of age or in the subset of 90-day-old mice at the early preparalysis phase. In contrast, 66 transcripts were regulated during the late preparalysis phase at 90 days of age, and this list expanded, with 360 transcripts at the onset of paralysis. Sciatic nerve axotomy induced transcriptional changes in 318 transcripts. On the basis of the applied cutoff, 42.8% of transcripts (204 of 477) were commonly regulated in ALS mice and after axotomy. In contrast, 33.1% of transcripts (158 transcripts) were regulated only in the ALS condition, whereas 24.1% (115 transcripts) appeared exclusively axotomy dependent. Considering genes with known function (Table 2), those involved in cell cycle, growth and differentiation [e.g., B cell translocation gene-1 (BTG1), growth differentiation factor-5, myogenic factor-6 (MYF6), retinoblastoma susceptibility gene-1 (RB1), cyclin-dependent kinase inhibitor-1A (CDKN1A), and growth arrest- and DNA damage-inducible gene-45{alpha} (GADD45{alpha})], and cytoskeleton organization [e.g., high mobility group nucleosomal binding domain-1 (MYL4), myosin binding protein-H (MYBPH), myosin light chain-regulatory-B (MYLC2B), shroom, tektin-1, and tubulin-β6] constituted the most represented functional categories regulated at 90 days of age. These changes gained intensity in paralyzed G86R mice and after axotomy, as deduced from the increased number of genes involved. One-third of the transcriptional changes in paralyzed and axotomized animals affected genes implicated in metabolic processes. In the ALS condition, one-half of these genes were involved in muscle protein breakdown [e.g., cathepsins, proteasome subunits, serine (or cysteine) proteinase inhibitors, transformed mouse 3T3 cell double minute-2, and ubiquitin carboxy-terminal hydrolase-L1 (UCHL1)]. Finally, genes acting on carbohydrate and lipid metabolism were mostly downregulated in paralyzed G86R and axotomized animals (Supplemental Table S1).


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  		Table 2. Classification of genes with known function differentially regulated at least twofold in G86R and axotomized mice

 
Expression of regulated genes is validated by real-time RT-PCR.
To validate the microarray expression signals, we chose several genes in the preselected group of 83 transcripts and performed real-time RT-PCR assays. We observed a good correlation between both techniques (Fig. 4). In addition, many genes previously reported to respond to muscle denervation (3, 49) also appeared regulated in this study. Specifically, the expression of runt-related transcription factor-1 (RUNX1) and Ras-related associated with diabetes (RRAD), from cluster 1, was highly increased in preparalyzed, paralyzed G86R, and axotomized muscles (Fig. 4, A and B). In the case of RRAD, the increase in mRNA levels was correlated with an increase in protein abundance (Supplemental Fig. S4). These measurements were obtained from a set of animals distinct from that used for the microarray experiments, which further reinforces the reliability of our data. On the other hand, the expression of CCAAT/enhancer binding protein-{delta} (C/EBP{delta}) and neuroepithelial cell transforming gene-1 (NET1), from cluster 5, was upregulated in G86R but not axotomized mice (Fig. 4, C and D). To confirm that changes in these cluster 5 genes were not due to expressional artifacts linked to the SOD1 transgene insertion, we also analyzed C/EBP{delta} and NET1 expression in muscles of G93A mice, another typical ALS model (27), and obtained similar results (Fig. 4, E and F).


Figure 4
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  		Fig. 4. Validation of the expression of selected transcripts. A–D: relative RNA concentrations of runt-related transcription factor-1 (RUNX1), Ras-related associated with diabetes (RRAD), CCAAT/enhancer binding protein-{delta} (C/EBP{delta}), and neuroepithelial cell transforming gene-1 (NET1) as determined by microarray expression signals (top) and real-time RT-PCR (bottom) in hindlimb skeletal muscle of G86R mice. E and F: relative concentrations of C/EBP{delta} and NET1 were also determined in hindlimb skeletal muscle of G93A mice by real-time RT-PCR. Affymetrix codes are indicated in parentheses. The experimental groups are as in Table 1 for G86R and axotomized (Axo) mice. Muscle samples were obtained from G93A mice at 100 and 120 days (d) of age and at the onset of hindlimb paralysis at ~140 days of age. Real-time RT-PCR data are presented as means ± SE of 3–10 individual muscle samples. I, ipsilateral; M, mutant; Sham, sham operated; Wt, wild type; ME, early preparalysis; ML, late preparalysis; OS, onset of paralysis; C, control. *P < 0.05 vs. corresponding control condition (ANOVA followed by Tukey's multiple comparisons test).

 
Genes involved in stress mechanisms.
One early transcriptional change in preparalyzed G86R mice was the upregulation of lysyl oxidase (LOX), an extracellular enzyme catalyzing the first step of the cross-linking of collagen and elastin to obtain mature insoluble fibers and assumed to generate high amounts of H2O2 as a by-product of its catalytic reaction (43). On the other hand, we observed increased expression of a series of antioxidant genes, including heat shock 27-kDa protein-8 (HSPB8), heat shock protein-4, metallothionein-I (MT1) and -II (MT2), thioredoxin-1, sestrin-1, which participates in reestablishing the antioxidant firewall that must be transiently disabled to allow physiological H2O2-dependent signaling (7), and aldehyde dehydrogenase-3 (ALDH3), which is believed to detoxify aldehydes from lipid peroxidation (64). The expression of other antioxidant genes such as microsomal glutathione S-transferase-3 and selenoprotein-X1 was, however, downregulated in paralyzed G86R and axotomized mice (Supplemental Table S1). Of note, the whole of these transcriptional regulations was correlated in vivo with an increase in reactive oxygen species in muscles from preparalyzed and paralyzed G86R mice and after axotomy, compared with muscles of wild-type animals (Supplemental Fig. S5), which strongly suggests that an important number of genes with antioxidant properties appeared regulated in response to that oxidative insult.

Genes involved in alternative pathways of ATP production.
Our previous work demonstrated a constant decrease in the production of muscle ATP starting in G86R mice as early as 75 days of age (20). This metabolic shutdown seems to underlie some transcriptional adaptations, because the expression of DNA damage-inducible transcript-4 (DDIT4, also known as REDD1), which is involved in the response to hypoxia and energy depletion, was upregulated in preparalyzed mice. Energy stress-induced REDD1 expression leads to suppression of cell growth by dephosphorylation of key mTOR substrates, including eukaryotic translation initiation factor-4E binding protein-1 (EIF4EBP1) and ribosomal protein-S6 kinase-1 (70). We found that the expression of EIF4EBP1 and mTOR (identified herein as FK506 binding protein-12 rapamycin-associated protein-1) was upregulated in paralyzed G86R mice (but not after axotomy) (Supplemental Table S1). It is therefore tempting to suggest that the early stimulation triggered by ATP loss of inhibitors of the mTOR pathway, such as REDD1, could play a significant role in ALS muscle pathology.

In paralyzed G86R and axotomized mice, gene expression involved in carbohydrate and lipid metabolism was in general downregulated, further aggravating the metabolic stress at this stage of the disease. The concerted action of adenylate kinase, which catalyzes the conversion of two molecules of ADP to ATP and AMP, and AMP deaminase, responsible for deamination of AMP to IMP and ammonia, constitutes an additional pathway to produce ATP in stressed cells (29). We detected increased expression of AMP deaminase-3 (AMPD3) as early as 90 days of age in G86R mice as well as in denervated muscles. In paralyzed and axotomized mice, however, adenylate kinase-1 expression was decreased (Supplemental Table S1). It is also known that the purine salvage pathway stimulates the conversion of hypoxanthine to IMP, which can in turn be reaminated via the purine nucleotide cycle and eventually result in ATP resynthesis (48). We found in G86R and axotomized mice increased expression of hypoxanthine phosphoribosyltransferase-1 (HPRT1), which catalyzes the conversion of hypoxanthine to IMP, although the expression of adenylosuccinate synthetase-like-1, involved in generating AMP (71), appeared downregulated (Supplemental Table S1).

Genes involved in protein degradation.
Several transcription factors involved in muscle proteolysis, such as C/EBP{delta} and -β and forkhead box-O3a, were upregulated in G86R mice. Along with this, we also observed, particularly in paralyzed G86R mice, increased expression of many proteasome subunits and, as early as 90 days of age, increased expression of UCHL1, involved in recycling ubiquitin from substrates that have been committed to degradation by the proteasome (79). Proteolysis by intralysosomal cathepsins is another type of protein degradation. mRNA levels of cathepsin-L and -Z were increased in muscles of paralyzed G86R mice as well as those of cathepsin-L and -S in surgically denervated muscles. In contrast, the expression of skeletal muscle-specific calpain-3, involved in selective calcium-dependent proteolysis (15), appeared downregulated (Supplemental Table S1).

Genes involved in cell cycle, growth, differentiation, and cell death.
The expression of key regulators of myogenesis, such as BTG1, appeared early to be upregulated in G86R mice. BTG1 induces myoblast differentiation by stimulating the transcriptional activity of triiodothyronine and all-trans retinoic acid receptors, c-JUN, and myogenic factors including myogenic differentiation antigen-1 (MYOD1), myogenic factor-5, and myogenin (9). In turn, MYOD1 induces cell cycle arrest by stimulating the expression of CDKN1A and RB1, which is also a downstream target of CDKN1A (28, 52). Although MYOD1 expression was unchanged in G86R mice (but upregulated in denervated muscle), CDKN1A and RB1 mRNAs appeared upregulated in preparalyzed animals (Supplemental Table S1).

The transcription factor RUNX1 has been shown to sustain muscle by preventing denervated myofibers from undergoing autophagy and wasting. The protective action of RUNX1 seems to depend on a set of targets among which the small GTPase RRAD has been identified (76). We detected an important upregulation of both RUNX1 and RRAD in our experimental conditions, which could indicate their contribution to the regenerative efforts to oppose muscle atrophy (Supplemental Table S1 and Supplemental Fig. S4).

Other transcriptional regulations seemed, however, to promote cell death pathways. For instance, the increasing upregulation of CDKN1A and GADD45{alpha} could mediate apoptosis of myonuclei and hence trigger muscle atrophy (10). Similarly, cytokeratins, the largest subgroup of intermediate filament proteins, have also been involved in apoptosis (38). The increase in cytokeratin-endoB expression observed in our experimental conditions could therefore be associated with muscle atrophy. Polyamines, including putrescine, spermidine and spermine, are small aliphatic cations that promote cell proliferation, growth, and differentiation but also induce apoptosis when they occur in abnormally elevated levels. Ornithine decarboxylase (ODC) and S-adenosylmethionine decarboxylase (AMD) are the key enzymes responsible for polyamine synthesis (32). In our hands, ODC expression stayed unchanged, but we observed in both G86R and axotomized mice a dramatic decrease in the levels of different AMD isoenzyme mRNAs (Supplemental Table S1), which could lead to the aberrant toxic accumulation of putrescine. We also observed a high increase in the expression of ankyrin repeat domain-containing protein-1 (ANKRD1) and, to a lesser extent, ANKRD2 only in paralyzed G86R mice. These findings corroborate previous observations of altered protein contents of ANKRD1 in atrophic myofibers in cases of ALS (57). These ankyrin repeat proteins are typically regulated following muscle stress (53). For example, ANKRD2 has been shown to bind p53 and enhance p53-induced CDKN1A upregulation (40). Interestingly, we also found increased mRNA levels of paternally expressed gene-3 (PEG3) (Supplemental Table S1), a transcription factor that functions downstream of p53 to regulate Bax redistribution into the cell and promote apoptosis (16). Of note, this is consistent with other studies that showed Bax immunoreactivity as a fine granular precipitate at the sarcolemma and within the sarcosol of atrophic myofibers in samples of sporadic ALS (68).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
Muscle gene regulations precede the onset of paralysis in mSOD1 mice.
The goal of this study was to determine gene expression changes occurring in skeletal muscle of G86R mice during the course of ALS. At 75 days of age, we did not detect significant transcriptional changes, which may contrast with our own previous studies showing muscle gene expression alterations at early presymptomatic stages (22). These transcriptional changes could not pass the several filtering steps employed in this study because we used the stringent twofold criteria to eliminate uncertain regulations and uncover the most significant changes relevant to the disease. By this means, the first expressional modifications characterizing muscle pathology appeared in a subset of 90-day-old G86R mice, coincident at the histological level with the onset of the reduction in myofiber size (35) but not motor neuron loss. Indeed, no reduction in the number of lumbar motor neurons is observed in animals at 80–90 days of age, whereas a significant decrease starts at ~105 days of age, when mice display motor deficits in at least one limb (19, 54, 65). By comparing the transcriptomes from G86R and surgically denervated muscles, we showed that most transcriptional changes appearing at 90 days of age in G86R mice were common to those observed following 7 days of sciatic nerve axotomy. These findings establish a parallel between the rupture of neuromuscular transmission originated by cutting the nerve in axotomized mice and the existence of denervation in preparalyzed G86R mice. Because axotomy-induced motor neuron death, if it occurs, takes more than a week in the adult mouse (39), one can infer that the first signs of denervation and atrophy in G86R muscle are not caused by degeneration of the motor neuron cell bodies but are rather the result of axonal dysfunction. Consistent with this notion, accumulation of light chain neurofilament subunits (55) and altered expression of the fast axonal transport regulator KIF3-associated protein-3 (19) occur early in G86R motor neurons, thus providing evidence of premature axonal impairment. Several previous studies had pointed to axonal dysfunction as primarily causing a progressive deterioration of the neuromuscular function that would eventually lead to muscle atrophy and motor neuron death (2, 24, 25). Recent research has further demonstrated that clinical symptoms in mSOD1 mice result specifically from damage to the distal motor axon and not from activation of death pathways in the cell soma (26, 67). Our present findings now provide a set of genes differentially regulated in preparalyzed G86R mice that characterizes the initiatory mechanisms underlying muscle pathology in ALS. The increased expression of genes implicated in detoxification (e.g., ALDH3, MT2, and thioredoxin-1), energy balance (e.g., AMPD3, DDIT4, and HPRT1), and injury response (e.g., ANKRD1 and HSPB8) is consistent with previous studies showing increased amounts of malondialdehyde and protein carbonyls, as well as high levels of manganese SOD and catalase activity in G93A muscles (50). We also show here the in vivo accumulation of muscle reactive oxygen species starting before overt paralysis, which further highlights the importance of mechanisms involved in facing oxidative and energy stress. The induction of genes implicated in myogenesis (e.g., BTG1, MYF6, RB1, RUNX1, and RRAD) and cytoskeleton organization (e.g., MYL4, MYBPH, MYLC2B, and shroom) can play an important role in stimulating the regenerative capacity of muscle during the first steps of atrophy. In contrast, the upregulation of others underlying cell death (e.g., CDKN1A, GADD45{alpha}, and PEG3) and cell degradation (e.g., MAP1LC3{alpha} and UCHL1) can promote apoptotic and proteolytic pathways that characterize the fatal end of the atrophic process.

Common gene regulations occur in muscles and motor neurons of paralyzed mSOD1 mice.
Although there are some differences among the existing mSOD1 mouse lines (4), they all present with almost the same pathological hallmarks and clinical progression. We looked for similar gene expression changes operating in muscle and motor neurons at the time of paralysis by comparing our present data with those obtained using laser-captured microdissected motor neurons (23, 46, 60) (Table 3). Notably, upregulation of MT1 and MT2, involved in metal homeostasis/detoxification and free radical scavenging, appears as a general transcriptional event, occurring not only in muscle and isolated motor neurons but also in whole spinal cord (59) and motor cortex of sporadic ALS patients (42). Reduced expression of metallothioneins by genetic means aggravated disease in mSOD1 mice (56, 63), which strongly suggests that their upregulation may be regarded as a key protective mechanism. Also of interest is the increased expression of LOX and thioredoxin-1 in muscle and human ALS spinal cord (51), which points to common pathways of oxidative damage in the whole motor unit.


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  		Table 3. Genes with common or opposed transcriptional regulation between muscle and spinal cord of paralyzed mSOD1 mice

 
The upregulation of cathepsins, intralysosomal proteolytic enzymes important for normal protein turnover and involved in a number of pathological conditions (72), appears as a general transcriptional event in ALS. In particular, increased expression of cathepsin-Z (also named cathepsin-X) was detected in muscles and isolated motor neurons (Table 3). Consistently, increases in cathepsin-Z protein content and enzymatic activity were also observed in mSOD1 mouse spinal cord (78), although its exact role in the pathological process is presently unknown. Interestingly, several serpins, serine (or cysteine) proteinase inhibitors, were commonly upregulated in muscles (our present data), isolated spinal motor neurons (23, 60), and motor cortex of sporadic ALS patients (42). These transcriptional regulations can be relevant to the disease because certain serpins can inhibit cathepsin activity and have been involved in preventing cell death in response to oxidative stress (45). Moreover, several serpins were found in the neurofilamentous lesions characteristic of ALS motor neurons (13) and were suggested to participate locally in neuromuscular junction remodeling (74).

Another noticeable finding is the upregulation of the stress-inducible gene-activating transcription factor-3 (ATF3) in muscles and motor neurons (Table 3). Interestingly, high levels of ATF3 mRNA and protein were found to precede death of ALS motor neurons (75). Although it is not clear whether ATF3 upregulation can promote or prevent cell death in ALS, transgenic mice expressing ATF3 in cardiomyocytes showed conduction and contractile abnormalities (58). If expression of ATF3 correlates with cellular injury, deciphering the molecular targets and pathways dependent on this immediate early gene could help with the identification of potential therapeutic interventions.

Also of interest is the increased expression of lectin galactoside binding soluble-3 (or galectin-3) in muscles and motor neurons, together with that of galectin-1 in muscles (Table 3). Galectin-1 was found to accumulate in the neurofilamentous lesions of the spinal cord of sporadic and familial ALS subjects (36), and its administration as an oxidized molecule to mSOD1 mice ameliorated impairment of motor function and extended survival (11). In contrast to these findings, the reduced form of galectin-1 has been shown to participate in the degeneration of presynaptic nerve terminals after axonal lesion in vivo (61). The aberrant muscle expression of such lectins in the ALS condition could therefore contribute to the degenerative process.

Muscle atrophy is the major cause of motor disability and suffering in ALS patients. To determine efficient therapeutic strategies that could alleviate muscle pathology, it is imperative to identify the specific molecular effectors that alter muscle function during the course of the disease. The set of transcriptional regulations we describe herein, appearing early at preparalysis stages and, in some cases, in common with those occurring in spinal cord motor neurons, can channelize our efforts to palliate neuromuscular dysfunction before the irrevocable loss of motor neuron cell bodies.


   GRANTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
REFERENCES
 
The Institut National de la Santé et de la Recherche Médicale-U692 laboratory is supported by Alsace Biovalley, Association Française contre les Myopathies, Association pour la Recherche sur la Sclérose Latérale Amyotrophique, and Fondation pour la Recherche sur le Cerveau. B. Halter is supported by Région Alsace and Association pour la Recherche et le Développement de Moyens de Lutte contre les Maladies Neurodégénératives.


   ACKNOWLEDGMENTS
 
We thank A. Picchinenna and M. J. Ruivo for excellent technical assistance. We also thank Dr. C. R. Kahn (Joslin Diabetes Center, Boston, MA) for providing anti-RRAD antiserum.


   FOOTNOTES
 
Address for reprint requests and other correspondence: J.-L. Gonzalez de Aguilar, INSERM, U692, Université Louis Pasteur, Faculté de Médecine, 11 rue Humann, F-67085 Strasbourg, France (e-mail: gonzalez{at}neurochem.u-strasbg.fr).

Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).


   REFERENCES
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