Weakness and fatigability are typical features of Duchenne muscular dystrophy patients and are aggravated in dystrophic mdx mice by chronic treadmill exercise. Mechanical activity modulates gene expression and muscle plasticity. Here, we investigated the outcome of 4 (T4, 8 weeks of age) and 12 (T12, 16 weeks of age) weeks of either exercise or cage-based activity on a large set of genes in the gastrocnemius muscle of mdx and wild-type (WT) mice using quantitative real-time PCR. Basal expression of the exercise-sensitive genes peroxisome-proliferator receptor γ coactivator 1α (Pgc-1α) and Sirtuin1 (Sirt1) was higher in mdx versus WT mice at both ages. Exercise increased Pgc-1α expression in WT mice; Pgc-1α was downregulated by T12 exercise in mdx muscles, along with Sirt1, Pparγ and the autophagy marker Bnip3. Sixteen weeks old mdx mice showed a basal overexpression of the slow Mhc1 isoform and Serca2; T12 exercise fully contrasted this basal adaptation as well as the high expression of follistatin and myogenin. Conversely, T12 exercise was ineffective in WT mice. Damage-related genes such as gp91-phox (NADPH-oxidase2), Tgfβ, Tnfα and c-Src tyrosine kinase were overexpressed in mdx muscles and not affected by exercise. Likewise, the anti-inflammatory adiponectin was lower in T12-exercised mdx muscles. Chronic exercise with minor adaptive effects in WT muscles leads to maladaptation in mdx muscles with a disequilibrium between protective and damaging signals. Increased understanding of the pathways involved in the altered mechanical–metabolic coupling may help guide appropriate physical therapies while better addressing pharmacological interventions in translational research.

INTRODUCTION

Exercise regulates function, morphology and metabolism in skeletal muscle via the modulation of various signalling pathways in relation to its intensity, pattern and duration. Proper muscle activity maintains a healthy state and prevents chronic inflammation and diseases, such as obesity and cardiovascular disorders. However, intense or unaccustomed exercise typically leads to metabolic perturbations and muscle damage in healthy subjects (1,2). The delicate equilibrium between positive and harmful effects of exercise is far less clear in progressively degenerating myopathies, such as Duchenne muscular dystrophy (DMD), with important implications for setting appropriate physical therapies (3,4). DMD is a severe muscle-wasting disease affecting ∼1 in 3500 boys and is caused by mutations of the dystrophin gene on the X chromosome (5). Dystrophin is a subsarcolemmal protein that is part of the dystrophin–glycoprotein complex (DGC) and works to link the cytoskeleton to the extracellular matrix (6). The absence of dystrophin leads to a disorganization of DGC and triggers a complex cascade that finally results in myofiber death and fibrosis in dystrophin-deficient muscles. Several key harmful events have been clarified by studies in animal models, such as widely used mdx mice. These events include the mechanical fragility of sarcolemma, aberrant calcium homeostasis, mitochondrial distress, unbalanced oxidative stress and chronic inflammation (6,7).

A unique upstream phenomenon for this complex cascade might be an aberrant transduction of mechanical signals resulting from the absence of dystrophin and DGC. The use of different exercise regimens in mdx mice suggests in fact a lower threshold for contraction-induced injury. While voluntary wheel running may lead to beneficial effects via proper adaptive mechanisms, enforced mild chronic exercise or more exhaustive downhill running have detrimental effects, exacerbating disease-related alterations in the otherwise benign murine phenotype (814). In our laboratory, the damaging effect of a standard protocol of forced exercise running on a horizontal treadmill has long since been used for pre-clinical drug tests (12,14,15). At least 4 weeks of such exercise regimen worsens in vivo weakness and fatigue in mdx mice but not in WT mice, enabling a non-invasive longitudinal evaluation of drug outcome; ex vivo indices of muscle damage are also observed (12,13,16,17). However, the molecular mechanisms underlying the chronic exercise-induced damage and how these mechanisms reproduce those occurring in DMD patients are still unclear.

Our hypothesis is that dystrophic myofibers have a different threshold for adaptation to exercise compared with WT muscles and that their maladaptation to exercise is defined by inappropriate signalling, which leads to cumulative damage. In skeletal muscles, metabolic pathways are physiological responders to mechanical signals via key molecular sensors. One such molecule is Pgc-1α, which adapts muscle metabolism and mitochondrial function to enhanced workload (2,18).

Overexpression of Pgc-1α gene or its stimulation has been described to ameliorate mdx phenotype with a fast-to-slow myofiber transition and consequent metabolic remodeling, enhancement of endogenous anti-oxidant molecules and upregulation of the dystrophin surrogate utrophin (Utrn) (1921). Similar results have been observed with pharmacological stimulation of upstream or downstream signaling molecules, such as AMP kinase, the nicotinamide adenine dinucleotide (NAD)-dependent deacetylase sirtuin 1 (Sirt1) and peroxisome proliferator-activated receptor (Ppar) β/δ. Exogenous reinforcement of metabolic remodelling is a promising therapeutic strategy in association with mild voluntary exercise (2225). Contradictory aspects are related to the evidence that the basal expression of Pgc-1α and related molecules such as Sirt1 is higher in dystrophic versus normal muscles, which is suggestive of compensatory remodelling spontaneously occurring in the benign murine phenotype (22). In fact, the dystrophic signature in samples of more severely affected DMD patients is generally characterized by an induction of genes involved in the inflammatory response and fibrosis while those of oxidative energy metabolism are downregulated (2630).

The outcome of chronic forced exercise on these pathways has never before been evaluated, although aberrant mechanical signaling could be a feasible mechanism for chronic exercise-induced damage in the dystrophic condition. A validation of this hypothesis would further justify the need for pharmacological reinforcement in patients, other than leading to identification of better drug targets. Considering that exercise is the main regulator of gene profiles, we focused on the gene expression of various key molecules involved in mechanical–metabolic coupling, starting from Pgc-1α. We also studied molecules involved in muscle damage and regeneration, in the hindlimb muscles of mdx and WT mice of different ages and undergoing either 4 or 12 weeks of exercise. Our analyses focused on the gastrocnemius (GC) muscle employed in treadmill exercise. The mechanism of long-term adaptation has been validated by assessing the outcome of an acute single exercise session on the expression of the most sensitive genes.

RESULTS

Effect of exercise on in vivo performance

WT and mdx mice were monitored for body mass and in vivo performance, both at the beginning and at the end of the two exercise durations. Basal values of the mice of the various groups are shown in Supplementary Material, Table S1. A one-way ANOVA test, followed by the Bonferroni post hoc analysis, was used for assessing statistical differences in relation to genotype and exercise. No significant differences were observed in body mass gain in the two genotypes in response to exercise (data not shown). Genotype and exercise-related changes in the absolute and normalized values of forelimb strength at T4 and T12 are shown in Figure 1A and B. In agreement with previous studies (12,13,17), a reduction in both absolute and normalized strength was observed in T4 exercised mdx animals which was maintained up to T12. Importantly, no significant effect of exercise was found on absolute and normalized forelimb strength of WT mice.

Figure 1.

Effect of exercise on in vivo performance. Genotype (WT, mdx) and exercise-related changes (WT exe, mdx exe) are shown in absolute (Fmax) (A) and normalized values (FN) (B) of forelimb strength and in the total distance (E test) run in the treadmill exhaustion test (C). Each bar is the mean ± SEM of the percent reduction in absolute forelimb strength with respect to the WT group (arbitrarily taken as 100%) at either time 4 (T4) or time 12 (T12). Values are mean ± SEM from 6 to 18 animals. A statistical difference was found by the one-way ANOVA test for Fmax at T4 (F > 40; P < 8.2 × 10−14) and at T12 (F > 35; P < 7.4 × 10−10), FN at T4 (F > 30; P < 1.64 × 10−11) and T12 (F > 23.3; P < 5.57 × 10−8), E test at T4 (F > 13; P < 4.4 × 10−6) and at T12 (F > 8.7; P < 0.001). The post hoc Bonferroni correction is as follows: *Significantly different with respect to WT mice with 5.5 × 10−11 < P < 0.003. #Significantly different with respect to exe WT mice with 6.9 × 10−14 < P < 0.004. °Significantly different with respect to mdx mice with 2 × 10−7 < P < 0.0005.

Figure 1.

Effect of exercise on in vivo performance. Genotype (WT, mdx) and exercise-related changes (WT exe, mdx exe) are shown in absolute (Fmax) (A) and normalized values (FN) (B) of forelimb strength and in the total distance (E test) run in the treadmill exhaustion test (C). Each bar is the mean ± SEM of the percent reduction in absolute forelimb strength with respect to the WT group (arbitrarily taken as 100%) at either time 4 (T4) or time 12 (T12). Values are mean ± SEM from 6 to 18 animals. A statistical difference was found by the one-way ANOVA test for Fmax at T4 (F > 40; P < 8.2 × 10−14) and at T12 (F > 35; P < 7.4 × 10−10), FN at T4 (F > 30; P < 1.64 × 10−11) and T12 (F > 23.3; P < 5.57 × 10−8), E test at T4 (F > 13; P < 4.4 × 10−6) and at T12 (F > 8.7; P < 0.001). The post hoc Bonferroni correction is as follows: *Significantly different with respect to WT mice with 5.5 × 10−11 < P < 0.003. #Significantly different with respect to exe WT mice with 6.9 × 10−14 < P < 0.004. °Significantly different with respect to mdx mice with 2 × 10−7 < P < 0.0005.

An acute test of resistance to treadmill exercise was performed in all groups measuring the total distance run by each mouse during a single exercise session until exhaustion. Fatigue was detectable in mdx mice at all time points; these mice ran a 30–40% shorter distance than age-matched WT mice (Supplementary Material, Table S1 and Fig. 1C). Fatigue was enhanced in T4 exercised mdx mice and this functional impairment was maintained up to T12 (Fig. 1C). On the contrary, the exercised WT mice showed a slight minor fatigability with respect to their sedentary counterparts.

Gene expression in the GC muscle of mdx and WT mice of different ages and after 4 and 12 weeks of exercise

We now turn to describing the changes in the expression of the various genes assessed, organized in subclasses, in relation to genotype and physical activity. A general overview of the results is given in Tables 1 and 2.

Table 1.

Qualitative changes in gene expression in relation to genotype and exercise

 8 weeks of age
 
16 weeks of age
 
Genes Genotype (mdx versus WT) Exercise T4 (exe versus cage-based) Genotype (mdx versus WT) Exercise T12 (exe versus cage-based) 
WT
 
mdx WT
 
mdx 
Fold change
 
Fold change
 
Fold change
 
Fold change
 
Fold change
 
Fold change
 
Exercise 
Pgc-1α ↑? 1.4 ↑↑ n.c. – ↑↑ 1.7 ↑? 1.2 ↓↓ −1.8 
Sirt1 ↑↑ n.c. – n.c. – ↑↑ n.c. – ↓↓ −1.5 
Pparδ n.c. – n.c. – n.c. – ↑↑? 1.6 n.c. – n.c. – 
Pparγ ↑? 1.5 n.c. – n.c. – ↑? n.c. – ↓↓ −2 
Pgc-1α targets 
Cox4 n.c. – n.c. – n.c. – ↑? n.c. – ↓? −1.3 
Cs n.c. – n.c. – n.c. – ↑? n.c. – n.c. – 
Utrn ↑↑ n.c. – n.c. – ↑↑ 2.4 n.c. – n.c. – 
Vegfa n.c. – n.c. – n.c. – ↑↑ n.c. – n.c. – 
Vegfb n.c. – n.c. – n.c. – ↓↓? −1.7 n.c. – n.c. – 
Myofiber phenotype 
Mhc1 ↑? 1.2 n.c. – ↓? −1.5 ↑↑↑ 12 n.c. – ↓? −1 
Mhc2a n.c. – n.c. – n.c. – ↑? 1.4 n.c. – ↓? −1 
Mhc2b ↓? −1.5 ↑? 1.3 ↑? 1.6 ↓↓ −2 n.c. – ↑↑ 
Mhc2x n.c. – n.c. – n.c. – n.c. – n.c. – n.c. – 
Serca1 ↓? −1.4 n.c. – n.c. – ↓? −1 n.c. – n.c. – 
Serca2 ↑↑ n.c. – ↓? −1.2 ↑↑ n.c. – ↓↓ −2 
Cn n.c. – ↑↑? ↑? 1.4 ↓↓? −1.8 n.c. – ↑? 
Mef2d n.c. – n.c. – n.c. – n.c. – n.c. – n.c. – 
Mef2c n.c. – ↑↑? 1.6 n.c. – ↓? −1.4 n.c. – ↑↑? 1.7 
Hdac5 ↑↑ 1.6 n.c. – ↓↓ −2 n.c. – n.c. – ↓? −1 
Regeneration 
Fst ↑? 1.3 n.c. – n.c. – ↑↑↑ n.c. – ↓↓↓ −9 
Myog ↑↑ n.c. – n.c. – ↑↑↑ n.c. – ↓↓↓ −6 
Igf-1 ↑↑ n.c. – n.c. – ↓↓? −2.5 n.c. – n.c. – 
Svil ↑? 1.4 n.c. – ↓? −1.4 ↓? −2 ↑? 1.2 n.c. – 
Fibrosis and atrophy 
Mstn ↓? −1.3 n.c. – n.c. – ↓↓ −2 n.c. – n.c. – 
Atrogin1 n.c. – n.c. – n.c. – n.c. – n.c. – n.c. – 
Tgfβ ↑↑↑ n.c. – n.c. – ↑↑ n.c. – n.c. – 
Inflammation/oxidative stress 
Nox2 ↑↑↑ n.c. – n.c. – ↑↑ n.c. – n.c. – 
Tubα-1b ↑↑↑ n.c. – n.c. – ↑↑ n.c. – ↓? −1.4 
c-Src       ↑↑ n.c. – n.c. – 
Tnfα       ↑↑? ↑? 1.3 n.c. – 
Adipoq       n.c. – ↑? ↓? −1 
Adipor1       n.c. – n.c. – n.c. – 
Autophagy 
Bnip3 ↓↓? −2 n.c. – ↓? −1 n.c. – ↑? ↓↓ −1.6 
Lc3 n.c. – n.c. – ↓? −1.5 n.c. – n.c. – n.c. – 
 8 weeks of age
 
16 weeks of age
 
Genes Genotype (mdx versus WT) Exercise T4 (exe versus cage-based) Genotype (mdx versus WT) Exercise T12 (exe versus cage-based) 
WT
 
mdx WT
 
mdx 
Fold change
 
Fold change
 
Fold change
 
Fold change
 
Fold change
 
Fold change
 
Exercise 
Pgc-1α ↑? 1.4 ↑↑ n.c. – ↑↑ 1.7 ↑? 1.2 ↓↓ −1.8 
Sirt1 ↑↑ n.c. – n.c. – ↑↑ n.c. – ↓↓ −1.5 
Pparδ n.c. – n.c. – n.c. – ↑↑? 1.6 n.c. – n.c. – 
Pparγ ↑? 1.5 n.c. – n.c. – ↑? n.c. – ↓↓ −2 
Pgc-1α targets 
Cox4 n.c. – n.c. – n.c. – ↑? n.c. – ↓? −1.3 
Cs n.c. – n.c. – n.c. – ↑? n.c. – n.c. – 
Utrn ↑↑ n.c. – n.c. – ↑↑ 2.4 n.c. – n.c. – 
Vegfa n.c. – n.c. – n.c. – ↑↑ n.c. – n.c. – 
Vegfb n.c. – n.c. – n.c. – ↓↓? −1.7 n.c. – n.c. – 
Myofiber phenotype 
Mhc1 ↑? 1.2 n.c. – ↓? −1.5 ↑↑↑ 12 n.c. – ↓? −1 
Mhc2a n.c. – n.c. – n.c. – ↑? 1.4 n.c. – ↓? −1 
Mhc2b ↓? −1.5 ↑? 1.3 ↑? 1.6 ↓↓ −2 n.c. – ↑↑ 
Mhc2x n.c. – n.c. – n.c. – n.c. – n.c. – n.c. – 
Serca1 ↓? −1.4 n.c. – n.c. – ↓? −1 n.c. – n.c. – 
Serca2 ↑↑ n.c. – ↓? −1.2 ↑↑ n.c. – ↓↓ −2 
Cn n.c. – ↑↑? ↑? 1.4 ↓↓? −1.8 n.c. – ↑? 
Mef2d n.c. – n.c. – n.c. – n.c. – n.c. – n.c. – 
Mef2c n.c. – ↑↑? 1.6 n.c. – ↓? −1.4 n.c. – ↑↑? 1.7 
Hdac5 ↑↑ 1.6 n.c. – ↓↓ −2 n.c. – n.c. – ↓? −1 
Regeneration 
Fst ↑? 1.3 n.c. – n.c. – ↑↑↑ n.c. – ↓↓↓ −9 
Myog ↑↑ n.c. – n.c. – ↑↑↑ n.c. – ↓↓↓ −6 
Igf-1 ↑↑ n.c. – n.c. – ↓↓? −2.5 n.c. – n.c. – 
Svil ↑? 1.4 n.c. – ↓? −1.4 ↓? −2 ↑? 1.2 n.c. – 
Fibrosis and atrophy 
Mstn ↓? −1.3 n.c. – n.c. – ↓↓ −2 n.c. – n.c. – 
Atrogin1 n.c. – n.c. – n.c. – n.c. – n.c. – n.c. – 
Tgfβ ↑↑↑ n.c. – n.c. – ↑↑ n.c. – n.c. – 
Inflammation/oxidative stress 
Nox2 ↑↑↑ n.c. – n.c. – ↑↑ n.c. – n.c. – 
Tubα-1b ↑↑↑ n.c. – n.c. – ↑↑ n.c. – ↓? −1.4 
c-Src       ↑↑ n.c. – n.c. – 
Tnfα       ↑↑? ↑? 1.3 n.c. – 
Adipoq       n.c. – ↑? ↓? −1 
Adipor1       n.c. – n.c. – n.c. – 
Autophagy 
Bnip3 ↓↓? −2 n.c. – ↓? −1 n.c. – ↑? ↓↓ −1.6 
Lc3 n.c. – n.c. – ↓? −1.5 n.c. – n.c. – n.c. – 

The table shows relative fold changes (as simple ratio) of various genes in relation to mouse age, genotype and duration of exercise. Up arrows show increased expression with relative fold changes; down arrows show decreased expression with relative negative fold changes; n.c.: no change with respect to the gene expression of relative control case, based on the statistical analysis with the one-way ANOVA test and Bonferroni post hoc correction for multiple comparisons described in Table 2. One arrow indicates a fold change < 1.5; two arrows indicate a fold change ≥ 1.5; three arrows indicate a fold change ≥ 6; ? indicates an observed change in gene expression that did not reach statistical significance (Table 2) likely in relation to high inter-individual variability.

Table 2.

Gene sampled and results of one-way ANOVA analysis of data.

Gene
 
ANOVA
 
P-value of Bonferroni post hoc correction for multiple comparison 
F-value P-value WT sed versus WT exe WT sed versus mdx sed WT sed versus mdx exe mdx sed versus WT exe mdx exe versus WT exe mdx sed versus mdx exe 
Exercise 
Pgc-1α T4 4.57 0.016 0.0152 ns ns ns ns ns 
T12 4.083 0.0131 ns 0.0327 ns ns ns 0.0298 
Sirt1 T4 7.269 0.0019 ns 0.0241 ns 0.0036 0.0444 ns 
T12 5.535 0.0072 ns 0.01 ns 0.0132 ns 0.0488 
Pparδ T4 1.695 0.2037       
T12 2.785 0.0724       
Pparγ T4 7.657 0.0017 ns ns 0.0174 0.0262 0.0094 ns 
T12 5.135 0.0044 ns ns ns 0.0387 ns 0.0039 
Pgc-1α targets 
Cox4 T4 0.9914 0.4192       
T12 1.762 0.1885       
Cs T4 0.97 0.4298       
T12 2.42 0.0978 ns ns ns ns ns ns 
Utrn T4 11.24 0.0002 ns 0.0036 0.0036 0.0044 0.0044 ns 
T12 11.52 0.0001 ns 0.0083 0.0043 0.0022 0.0012 ns 
Vegfa T4 0.656 0.5896       
T12 8.087 0.0011 ns 0.0252 0.0471 0.0057 0.0101 ns 
Vegfb T4 1.169 0.349       
T12 2.29 0.1093       
Myofiber phenotype 
Mhc1 T4 1.698 0.2052       
T12 4.989 0.0125 ns 0.0213 ns 0.0354 ns ns 
Mhc2a T4 0.0218 0.9955       
T12 1.773 0.1864       
Mhc2b T4 1.879 0.1673       
T12 6.909 0.003 ns 0.0022 ns ns ns 0.0436 
Mhc2x T4 1.488 0.2516       
T12 1.237 0.3255       
Cn T4 2.414 0.1001       
T12 1.608 0.2191       
Serca1 T4 2.15 0.1275       
T12 2.786 0.0705       
Serca2 T4 4.781 0.0127 ns 0.042 ns 0.0269 ns ns 
T12 6.568 0.0034 ns 0.0068 ns 0.0065 ns 0.0417 
Mef2c T4 1.179 0.3439       
T12 2.069 0.135       
Mef2d T4 0.210 0.882       
T12 0.405 0.7506       
Hdac5 T4 4.858 0.0113 ns 0.0487 ns 0.0402 ns 0.025 
T12 2.195 0.122       
Regeneration 
Fst T4 5.194 0.0099 ns ns ns 0.0371 0.0167 ns 
T12 13.8 <0.0001 ns 0.0004 ns 0.0001 ns 0.0004 
Myog T4 13.11 0.0001 ns 0.0183 0.0018 0.006 0.0005 ns 
T12 25.84 <0.0001 ns <0.0001 ns <0.0001 ns <0.0001 
Igf-1 T4 9.251 0.0006 ns 0.0478 0.0058 0.0242 0.0025 ns 
T12 2.602 0.0837       
Svil T4 1.053 0.392       
T12 3.911 0.0271 ns ns ns 0.0254 ns ns 
Fibrosis and atrophy 
Mstn T4 4.256 0.0194 ns ns ns 0.0425 0.0396 ns 
T12 13.52 <0.0001 ns 0.0105 0.004 0.0008 0.0003 ns 
Tgfβ T4 17.68 <0.0001 ns 0.0002 0.0014 0.0001 0.001 ns 
T12 10.32 0.0003 ns 0.0177 0.0063 0.0055 0.0019 ns 
Atrogin1 T4 0.086 0.9665       
T12 0.532 0.6662       
Inflammation/ oxidative stress 
Nox2 T4 10.91 0.0005 ns 0.0111 0.0471 0.0013 0.0101 ns 
T12 6.041 0.0039 ns 0.0371 ns 0.0233 0.0443 ns 
Tubα-1b T4 11.39 0.0002 ns 0.0028 0.0069 0.0021 0.0052 ns 
T12 20.03 <0.0001 ns <0.0001 0.0049 <0.0001 0.0019 ns 
c-Src T12 9.256 0.0005 ns 0.0437 0.0058 0.0151 0.002 ns 
Tnfα T12 2.697 0.0733       
Adipoq T12 1.283 0.3141       
Adipor1 T12 3.085 0.0506       
Autophagy 
Bnip3 T4 6.015 0.0055 ns ns 0.0158 ns 0.0356 ns 
T12 8.329 0.0009 ns ns 0.0109 ns 0.0006 0.0494 
Lc3 T4 2.034 0.1451       
T12 1.155 0.3516       
Gene
 
ANOVA
 
P-value of Bonferroni post hoc correction for multiple comparison 
F-value P-value WT sed versus WT exe WT sed versus mdx sed WT sed versus mdx exe mdx sed versus WT exe mdx exe versus WT exe mdx sed versus mdx exe 
Exercise 
Pgc-1α T4 4.57 0.016 0.0152 ns ns ns ns ns 
T12 4.083 0.0131 ns 0.0327 ns ns ns 0.0298 
Sirt1 T4 7.269 0.0019 ns 0.0241 ns 0.0036 0.0444 ns 
T12 5.535 0.0072 ns 0.01 ns 0.0132 ns 0.0488 
Pparδ T4 1.695 0.2037       
T12 2.785 0.0724       
Pparγ T4 7.657 0.0017 ns ns 0.0174 0.0262 0.0094 ns 
T12 5.135 0.0044 ns ns ns 0.0387 ns 0.0039 
Pgc-1α targets 
Cox4 T4 0.9914 0.4192       
T12 1.762 0.1885       
Cs T4 0.97 0.4298       
T12 2.42 0.0978 ns ns ns ns ns ns 
Utrn T4 11.24 0.0002 ns 0.0036 0.0036 0.0044 0.0044 ns 
T12 11.52 0.0001 ns 0.0083 0.0043 0.0022 0.0012 ns 
Vegfa T4 0.656 0.5896       
T12 8.087 0.0011 ns 0.0252 0.0471 0.0057 0.0101 ns 
Vegfb T4 1.169 0.349       
T12 2.29 0.1093       
Myofiber phenotype 
Mhc1 T4 1.698 0.2052       
T12 4.989 0.0125 ns 0.0213 ns 0.0354 ns ns 
Mhc2a T4 0.0218 0.9955       
T12 1.773 0.1864       
Mhc2b T4 1.879 0.1673       
T12 6.909 0.003 ns 0.0022 ns ns ns 0.0436 
Mhc2x T4 1.488 0.2516       
T12 1.237 0.3255       
Cn T4 2.414 0.1001       
T12 1.608 0.2191       
Serca1 T4 2.15 0.1275       
T12 2.786 0.0705       
Serca2 T4 4.781 0.0127 ns 0.042 ns 0.0269 ns ns 
T12 6.568 0.0034 ns 0.0068 ns 0.0065 ns 0.0417 
Mef2c T4 1.179 0.3439       
T12 2.069 0.135       
Mef2d T4 0.210 0.882       
T12 0.405 0.7506       
Hdac5 T4 4.858 0.0113 ns 0.0487 ns 0.0402 ns 0.025 
T12 2.195 0.122       
Regeneration 
Fst T4 5.194 0.0099 ns ns ns 0.0371 0.0167 ns 
T12 13.8 <0.0001 ns 0.0004 ns 0.0001 ns 0.0004 
Myog T4 13.11 0.0001 ns 0.0183 0.0018 0.006 0.0005 ns 
T12 25.84 <0.0001 ns <0.0001 ns <0.0001 ns <0.0001 
Igf-1 T4 9.251 0.0006 ns 0.0478 0.0058 0.0242 0.0025 ns 
T12 2.602 0.0837       
Svil T4 1.053 0.392       
T12 3.911 0.0271 ns ns ns 0.0254 ns ns 
Fibrosis and atrophy 
Mstn T4 4.256 0.0194 ns ns ns 0.0425 0.0396 ns 
T12 13.52 <0.0001 ns 0.0105 0.004 0.0008 0.0003 ns 
Tgfβ T4 17.68 <0.0001 ns 0.0002 0.0014 0.0001 0.001 ns 
T12 10.32 0.0003 ns 0.0177 0.0063 0.0055 0.0019 ns 
Atrogin1 T4 0.086 0.9665       
T12 0.532 0.6662       
Inflammation/ oxidative stress 
Nox2 T4 10.91 0.0005 ns 0.0111 0.0471 0.0013 0.0101 ns 
T12 6.041 0.0039 ns 0.0371 ns 0.0233 0.0443 ns 
Tubα-1b T4 11.39 0.0002 ns 0.0028 0.0069 0.0021 0.0052 ns 
T12 20.03 <0.0001 ns <0.0001 0.0049 <0.0001 0.0019 ns 
c-Src T12 9.256 0.0005 ns 0.0437 0.0058 0.0151 0.002 ns 
Tnfα T12 2.697 0.0733       
Adipoq T12 1.283 0.3141       
Adipor1 T12 3.085 0.0506       
Autophagy 
Bnip3 T4 6.015 0.0055 ns ns 0.0158 ns 0.0356 ns 
T12 8.329 0.0009 ns ns 0.0109 ns 0.0006 0.0494 
Lc3 T4 2.034 0.1451       
T12 1.155 0.3516       

F-values were considered statistical significant when P < 0.05. Bonferroni post hoc correction was performed only in the presence of a statistical significant F-value. ns = not statistical significant by Bonferroni post hoc correction.

Exercise-related genes

In agreement with previous studies (31), the T4 exercise significantly increased the expression of the Pgc-1α gene in WT mice. GC muscles from non-exercised mdx mice showed a basal upregulation of Pgc-1α with respect to WT mice at both ages. Contrary to what was observed in WT mice, T4 exercise did not change Pgc-1α gene expression in mdx mice. In fact, it was significantly reduced after T12 exercise with respect to age-matched sedentary mdx mice (Fig. 2).

Figure 2.

Effect of T4 or T12 exercise on the expression of genes target of exercise or of Pgc-1α and genes related to myofiber phenotype. Histograms show quantification of transcript levels with qPCR for Pgc-1α and Sirt1 (exercise-sensitive), Pparγ and Utrn (Pgc-1α targets), Mhc1, Mhc2b and Serca2 (myofiber phenotype) genes, normalized by the Gapdh gene, in GC muscle in relation to genotype (mdx and WT) and physical activity (sed or exe). Mice exercised for either 4 weeks (T4) or 12 weeks (T12) were compared with animals of the same age; i.e. 8 weeks and 16 weeks, respectively. In each graph, the bars are the means ± SEM from the n animals indicated in brackets. For graphical reasons, the values at T12 were scaled down for Sirt1 (by 4), Pparγ (by 2), Utrn (by 3), Mhc1 (by 8) and Serca2 (by 2), while the value of Mhc2b at T4 was scaled up by a factor of 1.5. Significant differences between groups were evaluated using the one-way ANOVA test and Bonferroni post-hoc correction for multiple comparisons. Significant differences found with P < 0.05 are expressed with respect to *WT sed, °mdx sed and #WT exe (see Table 2 for details).

Figure 2.

Effect of T4 or T12 exercise on the expression of genes target of exercise or of Pgc-1α and genes related to myofiber phenotype. Histograms show quantification of transcript levels with qPCR for Pgc-1α and Sirt1 (exercise-sensitive), Pparγ and Utrn (Pgc-1α targets), Mhc1, Mhc2b and Serca2 (myofiber phenotype) genes, normalized by the Gapdh gene, in GC muscle in relation to genotype (mdx and WT) and physical activity (sed or exe). Mice exercised for either 4 weeks (T4) or 12 weeks (T12) were compared with animals of the same age; i.e. 8 weeks and 16 weeks, respectively. In each graph, the bars are the means ± SEM from the n animals indicated in brackets. For graphical reasons, the values at T12 were scaled down for Sirt1 (by 4), Pparγ (by 2), Utrn (by 3), Mhc1 (by 8) and Serca2 (by 2), while the value of Mhc2b at T4 was scaled up by a factor of 1.5. Significant differences between groups were evaluated using the one-way ANOVA test and Bonferroni post-hoc correction for multiple comparisons. Significant differences found with P < 0.05 are expressed with respect to *WT sed, °mdx sed and #WT exe (see Table 2 for details).

We then analyzed the expression of Sirt1, one of the exercise-sensitive upstream modulators of Pgc-1α, and of Ppars that are involved in the co-regulation of gene expression by Pgc-1α. The mRNA of Sirt1 did not change in T4 and T12 exercised WT mice. Sirt1 was significantly upregulated in sedentary mdx mice versus WT, at both ages; T4 exercise did not change its gene expression. On the contrary, T12 exercise led to a significant downregulation (Fig. 2). No effect of either T4 or T12 exercise was found on the expression of Pparδ, a main co-modulator with Pgc-1α of exercise-induced adaptation (31), in WT mice. At 8 weeks of age, no differences were found in Pparδ between WT and mdx mice; this effect was independent of T4 exercise. However, the Pparδ mRNA was upregulated in both T12 sedentary and exercised mdx mice versus WT sedentary mice (Supplementary Material, Fig. S2). The lack of statistical significance could be related to the high inter-individual variability in the expression of this gene. The expression of Pparγ was not modified by exercise in WT mice at the two times analyzed. However, Pparγ mRNA expression was significantly upregulated in muscles of T4 sedentary and exercised mdx mice versus age-matched WT mice (Fig. 2). A similar expression change has been observed in T12 sedentary animals. In agreement with results obtained for Pgc-1α and Sirt1, however, T12 exercise led to a significant downregulation of Pparγ with respect to age-matched, non-exercised mdx mice.

Pgc-1α target genes

To better understand the involvement of Pgc-1α /Sirt1 in the possible maladaptation of dystrophic muscles to exercise, we assessed the expression of selected genes that are known targets of this pathway. These genes included some oxidative energy metabolism genes (also treated as indices of mitochondrial biogenesis), such as Cytochrome oxidase IV subunit isoform 1 (Cox4) and Citrate synthase (Cs) and genes that can be involved in the impact of exercise on pathology such as Utrn and vascular endothelium growth factors (Vegfa and b).

No significant differences were found in Cox4 and Cs in relation to both genotype and exercise at T4. Older mdx animals showed a not-significant upregulation of both genes in mdx with respect to WT (data not significant), with minor if any change by T12 exercise (Supplementary Material, Fig. S2).

As expected, the mdx mice showed a significant upregulation of Utrn with respect to WT mice at both ages in basal conditions and no changes were observed after T4 and T12 exercise (Fig. 2). The Vegfa and Vegfb gene expression was comparable at T4 in all conditions. The 16-week-old mdx mice, either exercised or not, showed a significant upregulation of Vegfa mRNA and a downregulation of Vegfb with respect to the WT groups (Supplementary Material, Fig. S2).

Myofiber phenotype genes

To evaluate whether the alteration of the Pgc-1α pathway was related to a different myofiber type program, we analyzed the expression of myosin heavy chain (Mhc) isoforms and other phenotype-specific proteins, such as sarco/endoplasmic reticulum Ca2+-ATPase (Sercas).

Both T4 and T12 exercise did not significantly change the expression of Mhcs genes in WT mice (Fig. 2 and Supplementary Material, Fig. S3). The mdx mice at T4, either exercised or not, did not show significant changes in Mhc isoforms. However, a 50% increase in Mhc1 and a reduction of Mhc2b were observed in the sedentary group. These changes became statistically significant for both Mhc1 and Mhc2b in 16-week-old mdx mice, in agreement with the greater expression of Pgc-1α, Sirt1 and Pparδ. Interestingly, these differences were markedly attenuated with T12 exercise. In particular, the Mhc1 mRNA decreased, while Mhc2b mRNA was significantly upregulated versus sedentary counterparts (Fig. 2).

The Mhc2a and the Mhc2x gene expression did not change significantly in the various conditions (Supplementary Material, Fig. S3).

In agreement with the changes in Mhcs discussed above, Serca2 was upregulated in sedentary mdx mice versus WT mice at both ages (Fig. 2), while Serca1 was downregulated Supplementary Material, Fig. S3). Exercise did not significantly modify the expression of Sercas in WT mice. In mdx mice, both T4 and T12 exercise did not change the expression of Serca1 (Supplementary Material, Fig. S3); similarly, no marked changes were observed in Serca2 expression in T4 exercised mdx mice, while Serca2 was significantly downregulated at T12 (Fig. 2).

The gene expression of calcineurin (Cn), the calcium-sensitive phosphatase involved in slow-fiber type determination, was similar in the two genotypes at 8 weeks of age. Cn was upregulated by T4 exercise in WT mice, but not in mdx mice. In contrast, at 16 weeks of age, the expression of Cn was downregulated in sedentary mdx mice versus age-matched WT, with a contrasting effect of T12 exercise (Supplementary Material, Fig. S3).

We then analyzed the gene expression of transcription factors that are involved in exercise-mediated shift toward the slow-oxidative myofiber phenotype, such as some isoforms of myocyte enhancer factor 2 (Mef2), as well as class II histone deacetylase (Hdac), taken as the paradigm of skeletal muscle Mef2 modulators (32). Minor changes were observed in Mef2c expression in relation to genotype and/or exercise and these were in line with those of Cn. In fact, T4 exercise increased expression of Mef2c in WT muscles, but not in mdx muscles. The 16-week-old mdx mice showed a downregulation of Mef2c with respect to age-matched WT mice. T12 exercise induced an upregulation, although not significant of Mef2c in mdx mice versus the non-exercised counterparts (Supplementary Material, Fig. S3).

At both ages, the expression of Mef2d did not change in relation to either genotype or exercise (data not shown).

The mRNA of Hdac5 was unaffected by either T4 or T12 exercise in WT mice. Basal expression of Hdac5 was significantly higher at 8 weeks of age in mdx mice versus WT mice; this difference was not observed in the 16-week-old group. However, both T4 and T12 exercise downregulated Hdac5 in mdx mice (Supplementary Material, Fig. S3).

Regeneration-related genes

We analyzed the expression of genes involved in muscle mass and regeneration in the attempt to correlate the changes in metabolism-related genes with muscle repair mechanisms and performance after damage (33). T4 and T12 exercise did not modify the expression of follistatin (Fst) and myogenin (Myog) genes in WT mice. As expected, the basal expression of Myog and Fst was significantly higher in sedentary mdx mice than WT mice at both ages. While T4 exercise was ineffective, T12 exercise led to a significant downregulation of both genes (Fig. 3). In agreement with our previous radioimmunoassay findings, insulin-like growth factors 1 (Igf-1) mRNA was upregulated in the muscles of 8-week-old mdx mice versus age-matched WT mice, independent of physical activity (34). No significant change was observed in Igf-1 expression at T12 (Supplementary Material, Fig. S2). The gene expression of Supervillin (Svil), a cytoskeletal co-activator of androgen receptor possibly involved in myogenesis and myofiber structure (35), did not show significant differences at T4, irrespective of genotype and exercise. T12 exercise led to a slight increase in Svil expression in WT mice (Supplementary Material, Fig. S2). On the other hand, the mRNA of Svil was downregulated in both sedentary and exercised mdx mice when compared with age-matched, exercised WT mice (Supplementary Material, Fig. S2).

Figure 3.

Effect of T4 or T12 exercise on the expression of genes related to muscle regeneration, damage/fibrosis and autophagy. Histograms show quantification of transcript levels with qPCR for Fst and Myog (muscle regeneration), Mstn, Tgfβ, Nox2 and Tubα-1b (damage/fibrosis) and Bnip3 (autophagy) genes, normalized by the Gapdh gene, in GC muscle in relation to genotype (mdx and WT) and physical activity (sed or exe). Mice exercised for either 4 weeks (T4) or 12 weeks (T12) were compared with animals of the same age; i.e. 8 weeks and 16 weeks, respectively. In each graph, the bars are the means ± SEM from the n animals indicated in brackets. For graphical reasons, the values were scaled down at T12 for Fst (by 7.5), Myog (by 2.5), Mstn (by 2) and Tgfβ (by 2) and at T4 for Nox2 (by 10) and Tubα-1b (by 3); the values of Bnip3 were scaled up by 10 at T12. Significant differences between groups were evaluated using the one-way ANOVA test and Bonferroni post-hoc correction for multiple comparisons. Significant differences found with P < 0.05 are expressed with respect to *WT sed, °mdx sed and #WT exe (see Table 2 for details).

Figure 3.

Effect of T4 or T12 exercise on the expression of genes related to muscle regeneration, damage/fibrosis and autophagy. Histograms show quantification of transcript levels with qPCR for Fst and Myog (muscle regeneration), Mstn, Tgfβ, Nox2 and Tubα-1b (damage/fibrosis) and Bnip3 (autophagy) genes, normalized by the Gapdh gene, in GC muscle in relation to genotype (mdx and WT) and physical activity (sed or exe). Mice exercised for either 4 weeks (T4) or 12 weeks (T12) were compared with animals of the same age; i.e. 8 weeks and 16 weeks, respectively. In each graph, the bars are the means ± SEM from the n animals indicated in brackets. For graphical reasons, the values were scaled down at T12 for Fst (by 7.5), Myog (by 2.5), Mstn (by 2) and Tgfβ (by 2) and at T4 for Nox2 (by 10) and Tubα-1b (by 3); the values of Bnip3 were scaled up by 10 at T12. Significant differences between groups were evaluated using the one-way ANOVA test and Bonferroni post-hoc correction for multiple comparisons. Significant differences found with P < 0.05 are expressed with respect to *WT sed, °mdx sed and #WT exe (see Table 2 for details).

Muscle damage-related genes

The downregulation of Pgc-1α, Sirt1, Pparγ, Fst and Myog in mdx muscles exercised for 12 weeks, other than being interpreted as a harmful faulty metabolic-mechanical coupling, may also be suggestive of a generalized reduction in damaging signaling upon prolonged physical activity. It is therefore important to better assess the impact of exercise on the gene expression of proteins that are classically involved in dystrophic muscle damage.

Myostatin (Mstn) is a negative regulator of muscle mass. Contrary to what is expected, but in agreement with previous observation (36) and with the high expression of its natural antagonist Fst described above, Mstn was downregulated in mdx muscles at both ages and exercise did not induce any further changes (Fig. 3). In parallel, no changes in mRNA of Atrogin1 were observed in any experimental condition (data not shown).

On the other hand, the mRNA of transforming growth factor β1 (Tgfβ) was significantly higher in mdx mice than WT mice, independent of age and exercise (Fig. 3).

This finding is indicative of the high pro-fibrotic profile, which is involved in the impaired regeneration efficiency, replacement of muscular tissue and the establishment of reinforcing loops with pro-inflammatory and pro-oxidative signals. We accordingly evaluated the impact of genotype and exercise on the expression of gp91-phox for NADPH oxidase2 (Nox2) and its regulator, the tubulinα-1b chain (Tubα-1b). The gene expression of both genes was never influenced by exercise in WT mice. In agreement with other findings (37), the basal expression of Nox2 and Tubα-1b was significantly greater in mdx mice than WT mice, at both ages. T4 and T12 exercise did not change the expression of Nox2; similarly, Tubα-1b gene expression always remained always significantly higher in mdx mice than in WT mice (Fig. 3).

In order to better evaluate the outcome of exercise on expression of oxidative stress-sensitive pathways, we assessed the expression of c-Src tyrosine kinase (c-Src), a redox-sensitive protein, in the T12 groups. Again, an overexpression was observed in the mdx mice, independent of exercise (Supplementary Material, Fig. S4). The expression of Tnfα, a well-known reactive oxygen species producing pro-inflammatory cytokine involved in dystrophic muscle necrosis, was upregulated in mdx muscles at 16 weeks of age. In parallel, a decreased expression in the gene of adiponectin (Adipoq), a natural Pparγ-related hormone with anti-inflammatory and metabolic actions in skeletal muscles (38), was observed in T12 exercised mdx muscles, while an opposite change was observed in T12 exercised WT animals. However for both Tnfα and Adipoq, the high inter-individual variability did not allow to appreciate statistical significance. The expression of adiponectin receptor 1 (Adipor1) tended to be lower, although not significantly, in mdx mice than WT mice in both conditions (Supplementary Material, Fig. S4).

Autophagy genes

Exercise, along with fasting, is a typical inducer of autophagy; defects of autophagy may contribute to dystrophic progression (39). We then analyzed the gene expression of BCL2/adenovirus E1B 19 kDa protein-interacting protein 3 (Bnip3) and microtubule-associated protein 1 light chain 3 alpha (Lc3), two proteins involved in autophagy. No significant differences were observed in WT mice in response to either T4 or T12 exercise in terms of the expression of Bnip3 and Lc3, suggesting that the protocol used was not intense enough to have an impact on autophagy. In basal conditions, a lower expression of Bnip3 at 8 weeks was evident in mdx muscles. Interestingly, both T4 and T12 exercise further reduced the expression of Bnip3 in mdx mice to values significantly lower than those of WT mice and, at 16 weeks of age, lower than the value of age-matched sedentary mdx mice (Fig. 3). Lc3 mRNA underwent only minor changes in relation to genotype and exercise at either T4 orT12 exercise (Supplementary Material, Fig. S3).

Analysis of selected gene expression in fast-twitch extensor digitorum longus (EDL) and slow-twitch soleus muscles

Due to the mixed myofiber composition of GC muscle and the possible different outcomes of exercise on different myofiber types, we assessed the expression of a few selected genes in pure fast-twitch extensor digitorum longus (EDL) and in slow-twitch soleus muscles at T12 in order to check for the classical paradigm of exercise-related, fast-to-slow transition. As shown in Figure 4, under basal conditions, both mdx muscles differed from WT muscles in terms of greater expression of Sirt1, Mhc1 and Fst, in agreement with a metabolic shift toward the more fatigue-resistant slow fiber phenotype and greater muscle regeneration potential in both phenotypes. The chronic exercise protocol led to minor effects in WT muscles with slight changes observed in the expression of Mhc1 and Pgc-1α for EDL and soleus, respectively. In contrast, the exercise protocol led to a significant downregulation of Pgc-1α, Sirt1 and Fst and to a reduction in Mhc1 in EDL mdx muscles. Hence, a behavior similar to that observed in GC muscles was seen. Similar although minor changes were found in soleus muscle, supporting the view that even in the dystrophic genotype the pure slow-type muscle is more resistant to the mechanical challenge (Fig. 4).

Figure 4.

Effect of T12 exercise on gene expression in EDL and soleus muscles. Results obtained from fast-twitch EDL (A) and slow-twitch soleus (B) muscles of WT and mdx mice of 16 weeks of age, whether exercised for 12 weeks or not. Transcript levels were determined by qPCR for Pgc-1α, Sirt1, Mhc1 and Fst, normalized for the Gapdh gene. The graphs show the effect of genotype (mdx sed versus WT sed) calculated as (mdx sed-WT sed)/mdx sed, and the effect of T12 exercise in WT and mdx mice, calculated as (sed – exe)/sed, from 3–6 animals. *Significant differences between groups by unpaired Student's t-test (P < 0.05).

Figure 4.

Effect of T12 exercise on gene expression in EDL and soleus muscles. Results obtained from fast-twitch EDL (A) and slow-twitch soleus (B) muscles of WT and mdx mice of 16 weeks of age, whether exercised for 12 weeks or not. Transcript levels were determined by qPCR for Pgc-1α, Sirt1, Mhc1 and Fst, normalized for the Gapdh gene. The graphs show the effect of genotype (mdx sed versus WT sed) calculated as (mdx sed-WT sed)/mdx sed, and the effect of T12 exercise in WT and mdx mice, calculated as (sed – exe)/sed, from 3–6 animals. *Significant differences between groups by unpaired Student's t-test (P < 0.05).

Analysis of gene expression in the GC muscles of mdx and WT mice 24 h after a single exercise session

To confirm that the alteration of gene expression observed was an effect of chronic exercise and then to possible maladaptation, we analyzed the expression of a few selected genes in GC muscles 24 h after a single session of exercise in both WT and mdx mice 16 weeks old. The acute exercise did not influence the expression of any of the analyzed genes (Pgc-1α, Sirt1, Mhc1, Pparγ, Fst, Cn and Serca2) in both WT and mdx mice, with the exception of a slight but not significant increase of Cn in exercised WT mice (Supplementary Material, Fig. S5).

DISCUSSION

A chronic protocol of exercise on a treadmill applied early on postnatally is used in our laboratory as a strategy to worsen the phenotype of mdx mice and increase its suitability for testing new therapeutics for DMD (12; http://www.treat-nmd.eu/resources/research-resources/dmd-sops/).

The exercised mdx mice exhibit typical dystrophic features, including more severe weakness and fatigability, along with muscle necrosis and fibrosis, high plasma levels of muscular enzymes, deregulated calcium homeostasis and markers of oxidative stress (12,16,17,40). However, the molecular mechanisms responsible for the intolerance to such a protocol and for additional damage are not yet fully clear.

Considering that exercise is a main modulator of gene expression in plastic skeletal muscle tissue, we presently focused on the impact of either 4 or 12 weeks of our protocol on the expression of key molecules involved in adaptation/plasticity, regeneration and/or damage. An overview of the results is summarized in Table 1.

We chose the GC muscle since it is used extensively by treadmill exercise (17). Also it is composed of both fast and slow myofibers, resembling the typical composition of human skeletal muscle. A standard and constant protocol was equally applied to all animals, irrespective of age and genotype. We thereby ensured the same amount of physical activity for both WT and mdx mice. This approach allows us to compare the outcome of a similar challenge in the two genotypes, minimizing variability occurring with voluntary wheel running, while enhancing differences related to pathology.

We presently confirmed the impairment of in vivo performance upon chronic treadmill exercise selectively occurring in mdx versus WT animals (12,13,17). Also, no overt signs of adaptation over time were observed in either genotype as far as fore limb force and fatigability were concerned.

Our gene expression study started from Pgc-1α because of its key role in exercise-induced adaptation, via stimulation of the fast-to-slow transition, mitochondrial biogenesis, endogenous anti-oxidant response and Utrn upregulation (2,22).

Interestingly, building on the previous findings of Ljubicic et al. (22), Pgc-1α and its upstream regulator Sirt1 were upregulated in mdx versus age-matched WT muscles in basal condition and in an age-dependent manner. Accordingly, an overexpression of related signaling molecules genes (i.e. Pparδ or γ), Utrn and slow-phenotype genes such as Mhc1 and Serca2 was evident, particularly at 16 weeks of age. Our results corroborate that a gene fingerprint toward the slow phenotype characterizes the mdx muscles at the time the pathology attains a stable level after the intense degeneration/regeneration cycles occurring at earlier ages (14). This process can be part of a main compensatory adaptation that accounts for the mild mdx phenotype. The spontaneous overexpression of these pathways may also be indicative of a basal hypersensitivity of mdx mice to drugs acting as phenotypic modifiers that should be taken into account in translational research (2125,41).

Our exercise protocol led to different effects in the two genotypes, based on the duration of the exercise. The pathway Cn/Pgc-1α/Mef2c was activated early by the exercise protocol in WT animals according to classical paradigms and possibly involving reinforcing positive loops, as Mef2 stimulates the promoter of Pgc-1α (42). However, the activation of this pathway, likely related to an adaptation of calcium homeostasis, was not sufficient to trigger a slow-phenotype gene fingerprint, in agreement with our previous results (16,43). This finding is supported by the lack of an effect of exercise on Mhc, Cox4 and Cs expression. We confirmed that our protocol is too mild to be able to trigger a metabolic adaptation in healthy conditions. In contrast, the effects observed in mdx muscles were profound. Contrary to the physiological increase observed in Pgc-1α expression in WT muscles, a significant and marked reduction in Pgc-1α expression was observed in chronically exercised mdx mice. Such a decrease was particularly appreciable at T12 and was accompanied by a marked downregulation of Sirt1 and Pparγ and a reduction of Mhc1 and Serca2.

Interestingly, failures in mitochondrial oxidative metabolism pathways that worsen or do not adapt have been observed in both DMD patients and mdx muscles in response to exercise or experimentally induced mechanical overloading (36,44,45). In addition, a reduction in the Pgc-1α protein level has been found in a recent proteomic study of dogs suffering from severe golden retriever muscular dystrophy (46). Importantly, a failing Pgc-1α pathway is consistent with a more severe phenotype due to a defective metabolic adaptation; in fact, muscle-specific knockout mice for Pgc-1α show intolerance to exercise and overt myopathic signs (47). Then, the impairment to Pgc-1α expression discussed above, as a consequence of maladaptation, could contribute to the intolerance to our exercise protocol observed in mdx mice. This may also be reinforced by the reduced Mstn expression, based on recent findings about the link between reduced Mstn signaling and impaired metabolic muscle response (36,48). Mainly, the results corroborate that the exercised mdx mouse model develops changes more similar to those of more severe pathology conditions, which supports the model's usefulness for pre-clinical drug studies.

The maladaptation to exercise in mdx mice is also supported by the controversial expression profile of other genes involved in the slow phenotype reprogramming that may be explained as attempts to compensate for a failing Pgc-1α pathway. These effects include the minor changes observed in Pparδ and its target genes Utrn and Vegfa, as well as in Cox4 and Cs as markers of mitochondrial biogenesis (6,4951). Similarly, compensatory changes may account for the exercise-induced decrease in Hdac5 expression, considering that class IIa Hdacs play a fundamental role in muscle phenotype by repressing a program of oxidative genes, including Mef2c and Pgc-1α (52). Accordingly, an overexpression of Hdac5 in mouse skeletal muscles has been shown to impair the increase in type I oxidative fibers following chronic wheel exercise (32,53).

Importantly, the expression of genes related to muscle regeneration follows more closely the changes of Pgc-1α; in fact, the high expression of Fst and Myog was markedly contrasted by exercise in mdx muscles, with effects more visible at T12 than at T4.

In addition, it was important to determine that most of the genes involved in damaging signals and markedly upregulated in basal conditions were only minimally sensitive, if at all, to the exercise protocol. These genes include those encoding for Nox2 and Tubα-1b, biomarkers of oxidative stress, Tgfβ, the classical pro-fibrotic cytokine involved in muscular dystrophy, the pro-inflammatory cytokine Tnfα and Src-tyrosine kinase, a redox-sensitive enzyme involved in inflammation as well as in phosphorylation and degradation of dystroglycan in the absence of dystrophin (54).

The data show, for the first time, that genes primarily involved in harmful signaling in dystrophic skeletal muscles are kept deregulated in exercised mdx mice, while the expression of genes involved in protective programs and upregulated in basal conditions is markedly impaired. Autophagy is another protective mechanism modulated by exercise that is defective in muscles of dystrophic subjects. Restoring autophagy by a low-protein diet or by pharmacological stimulation of AMPK by AICAR has been found to ameliorate the mdx phenotype, although a defective adaptation has also been described (25,39,55). Interestingly, we found that exercise, mostly after 12 weeks, contributed to further reduce the expression of the autophagy gene Bnip3.

All of this evidence and the lack of changes observed after a single exercise session support the working hypothesis that dystrophic muscles have a defect in mechano-transduction signaling. This defect is more important in fast-twitch muscles than in slow-twitch muscles and leads to progressive maladaptations in response to a mild protocol of physical activity, finally resulting in cumulative damage. In particular, these concomitant events may be leading mechanisms for self-sustaining a chronic inflammation and in turn for the impairment of regenerative potential.

According to this viewpoint, it is important to highlight the significant downregulation in the expression of Pparγ in T12 exercised mdx mice. In fact, Pparγ exerts anti-inflammatory actions in various tissues, including skeletal muscles. Such an action is mediated by both adiponectin (another inducer of Pgc-1α) and direct inhibition of NF-κB (56). Importantly, adiponectin expression was likely to be reduced in T12 exercised mdx muscles. In addition, increasing evidence supports the link between insufficient metabolic adaptation and inflammation in various tissues, including skeletal muscles (57). Pgc-1α has been shown to be physically inhibited by the p65 subunit of activated NF-κB (58).

A summary scheme of the proposed exercise-induced damage in mdx muscle is shown in Figure 5.

Figure 5.

Summary scheme of exercise-induced damage in mdx muscles. The absence of dystrophin, with the consequent disassembling of DGC, impacts the mechano-transduction of mdx myofibers. Obvious indices of damage can be observed in the enhanced expression of pro-fibrotic (Tgfβ), pro-inflammation (Tnfα) and pro-oxidative pathways, with formation of reactive oxygen species (ROS). However, as shown in (A), the normal cage activity is already “sensed” as a mild exercise and metabolic pathways are activated, leading to an increase in Sirt1/Pgc-1α expression and a consequent enhancement of protective slow-type gene fingerprint (Mhc1 and Serca2). This response, in turn, allows an efficient regeneration program (via follistatin and myogenin), as well as the activation of a gene program for proper control of inflammation (via Pparγ), finally resulting in a milder phenotype. When a forced chronic treadmill protocol (without adaptive effects in WT muscle) is applied, as in (B), the damaging pathways are maintained. The low threshold for mechano-transduction described above actually leads to maladaptation, with a marked decrease in the expression of protective pathways (including a further impairment of autophagy, i.e. Bnip3) involved in mechanical-metabolic coupling. This process finally results in an impaired regeneration and failure in endogenous anti-inflammatory signals, potentially reinforcing the establishment of a chronic and unbalanced inflammation and leading to a more severe phenotype.

Figure 5.

Summary scheme of exercise-induced damage in mdx muscles. The absence of dystrophin, with the consequent disassembling of DGC, impacts the mechano-transduction of mdx myofibers. Obvious indices of damage can be observed in the enhanced expression of pro-fibrotic (Tgfβ), pro-inflammation (Tnfα) and pro-oxidative pathways, with formation of reactive oxygen species (ROS). However, as shown in (A), the normal cage activity is already “sensed” as a mild exercise and metabolic pathways are activated, leading to an increase in Sirt1/Pgc-1α expression and a consequent enhancement of protective slow-type gene fingerprint (Mhc1 and Serca2). This response, in turn, allows an efficient regeneration program (via follistatin and myogenin), as well as the activation of a gene program for proper control of inflammation (via Pparγ), finally resulting in a milder phenotype. When a forced chronic treadmill protocol (without adaptive effects in WT muscle) is applied, as in (B), the damaging pathways are maintained. The low threshold for mechano-transduction described above actually leads to maladaptation, with a marked decrease in the expression of protective pathways (including a further impairment of autophagy, i.e. Bnip3) involved in mechanical-metabolic coupling. This process finally results in an impaired regeneration and failure in endogenous anti-inflammatory signals, potentially reinforcing the establishment of a chronic and unbalanced inflammation and leading to a more severe phenotype.

The results pave the way for focused experiments to assess the post-transcriptional activity of the impaired pathways and to better understand the temporal sequences of events. Also, in light of the present findings, it is predictable that a more intense training protocol able to trigger a myofiber adaptation in WT muscles may lead to a further maladaptation and more significant damage in mdx muscles, an hypothesis that needs to be verified in focused experimental settings. The inhibition of the deregulated downstream pathways is expected to ameliorate the dystrophic condition and possibly counter the maladaptation to physical activity, according to drug mechanism of action. However, a better understanding of the upstream mechanisms responsible for the aberrant mechanical–metabolic uncoupling will lead to the identification of novel drug targets for a broader protecting effect and better evaluation of the clinical interest of phenotypic modifiers based on results obtained in the mdx mouse model.

MATERIALS AND METHODS

In vivo experiments

Male WT (WT, C57BL/10ScSnJ) and mdx mice 4–5 weeks of age were used for this study (Charles River, Italy for Jackson Laboratories, USA). For in vivo and ex vivo experiments, a total of 37 WT and 41 mdx mice were used. The WT and mdx mice were divided into different experimental groups: a sedentary group (sed or cage-based) and an exercised group (exe) with different total durations of exercise.

The exercise consisted of 30 min running on a horizontal treadmill (Columbus Instruments, USA) at 12 m/min, twice a week with a consistent 48 or 72 h break between each exercise session (12). The exercise was performed for a mean duration of 4 weeks (6 WT and 6 mdx mice) or 12 weeks (11 WT and 12 mdx mice). Age-matched, non-exercised (sedentary) mice comprised 5 WT and 6 mdx mice for the first group and 10 WT and 12 mdx mice for the second group (Supplementary Material, Fig. S1).

Mice were weekly monitored for body mass and forelimb strength, where the latter parameter was measured by a grip strength meter (Columbus Instruments), according to standard procedures (12; http://www.treat-nmd.eu/resources/research-resources/dmd-sops/). Specific time points were used for analysis: the beginning (T0) and after 4 (T4) and 12 (T12) weeks of either exercise or cage-based activity. An acute exhaustion test was used to assess resistance to treadmill running by measuring the maximal distance run by the different experimental groups at the same time points (17). At the end of the scheduled exercise, the ex vivo experiments were started. A 2-week time window was considered for mouse sacrifice, when the age range of the two primary groups was 8–10 weeks and 16–18 weeks. The exercised mice underwent the exercise protocol until sacrifice, which was performed 48–72 h after the last exercise session. Considering this timing and the aim of having all animals experience the same amount of exercise, the actual number of additional running sessions for both genotypes never exceeded two for the eight sessions of T4 and the 32 sessions of T12.

Some animals were exclusively used for testing the effect of an acute protocol of exercise on the expression of selected genes. The acute test consisted of 30 min of running on a horizontal treadmill at 12 m/min, 24 h prior to sacrifice. The animals for the acute protocol (5 WT mice and 5 mdx mice) were compared with sedentary animals of the same age (16 weeks).

Isolation of total RNA, reverse transcription and real-time PCR

GC, Soleus and EDL muscles were snap frozen in liquid nitrogen soon after removal and stored at –80°C until use. For each muscle sample, the total RNA was isolated by an RNeasy Fibrous Tissue Mini Kit (Qiagen C.N. 74704, Valencia) and quantified using a spectrophotometer (ND-1000 NanoDrop, Thermo Scientific, USA). To perform reverse transcription, 400 ng of total RNA was added to 1 µl dNTP mix 10 mm (Roche N.C. 11277049001, Switzerland) and 1 µl Random Hexamers 50 µm (Life Technologies C.N. n808-0127, USA) and incubated at 65°C for 5 min. Afterward, 4 µl 5X First Standard Buffer (Life Technologies C.N. Y02321), 2 µl 0.1 m DTT (Life Technologies C.N. Y00147) and 1 µl Recombinant RNasin Ribonuclease Inhibitor 40 U/µl (Promega, C.N. N2511, USA) were added and incubated at 42°C for 2 min. One microliter of Super Script II Reverse Trascriptase 200 U/µl (Life Technologies C.N. 18064-014) was added to each solution and incubated at 25°C for 10 min, at 42°C for 50 min and at 70°C for 15 min. Real-time PCR was performed in triplicate using the Applied Biosystems Real-time PCR 7500 Fast system (USA), MicroAmp Fast Optical 96-Well Reaction Plate 0.1 ml (Life Technologies C.N. 4346906) and MicroAmp Optical Adhesive Film (Life Technologies C.N. 4311971). Each reaction was carried in triplicate on a single plex reaction. The setup of reactions consisted of 8 ng cDNA, 0.5 µl of TaqMan Gene Expression Assays (Life Technologies), 5 µl of TaqMan Universal PCR master mix No AmpErase UNG (2x) (Life Technologies C.N. 4324018) and Nuclease-Free Water not Diethylpyrocarbonate (DEPC-Treated) (Life Technologies C.N. AM9930) for a final volume of 10 µl. The following RT-TaqMan-PCR conditions were as follows: step 1: 95°C for 20 s, step 2: 95°C for 3 s and step 3: 60°C for 30 s; steps 2 and 3 were repeated 40 times. The results were compared with a relative standard curve obtained by five points of 1:4 serial dilutions. The mRNA expression of the genes was normalized to the best housekeeping genes glyceraldehyde-3-phosphate dehydrogenase (Gapdh) selected from beta-actin (Actinβ) and beta-2 microglobulin (B2m) and Gapdh. TaqMan Hydrolysis primer and probe gene expression assays were ordered with the assay IDs reported in Supplementary Material, Table S2, by Life Technologies except for Lc3, where the assay was made with the following sequences: forward primer: 5′-ATCCCAGTGATTATAGAGCGATACAA-3′, reverse primer: 5′-TCAGGCACCAGGAACTTGGT-3′ and Probe: 6-FAM-AGA AGC AGC TGC CCG-MGB to amplify mRNA with the following NCBI Reference Sequence number: NM_026160.4.

For genes that are little expressed, such as Adipoq and Tnfα, a pre-amplification by TaqMan PreAmp Master Mix (Life Technologies C.N. 4391128) was made before the real-time experiments. The set up of pre-amplification consisted by 250 ng of reverse-transcribed (in 12.5 µl volume), 25 µl of TaqMan PreAmp Master Mix (2x) and 12.5 µl of Pool Assay 0.2 x (containing Adipoq, Tnfα and Gapdh). The solution was incubated at 50°C for 2 min, 95°C for 10 min and for 40 cycles of 95°C for 15 s and 60°C for 1 min.

In order to enable a better description of the results, the name or abbreviations of proteins, rather than the names of genes, are primarily used throughout the text. Names and abbreviations of genes are reported in Supplementary Material, Table S2.

Statistics

All experimental data were expressed as mean ± standard error (SEM). Statistical analysis was performed for each data set belonging to the same age group, using a one-way ANOVA test followed by post hoc Bonferroni correction for multiple comparisons when the null hypothesis was rejected (P < 0.05) (13,17,40). Single comparison between individual means was performed by the unpaired Student's t-test to specifically analyze differences due to genotype (mdx mice versus WT mice) or to exercise (exercised mice versus sedentary mice of the same genotype), when necessary, as indicated in the text. The statistical analysis was performed by GraphPad Prism version 6. For graphical considerations and to facilitate reading of the figures, some of the values were scaled down or up, as indicated in the figure legends.

SUPPLEMENTARY MATERIAL

Supplementary Material is available at HMG online.

FUNDING

This work was mainly supported by grants to A.D.L.: the Duchenne Parent Project Netherland (DPP/NL) research grant to the project entitled “Role of PGC-1 alpha in exercise intolerance of dystrophic mdx mouse: identification and validation of novel drug targets for DMD by means pre-clinical pharmacological tests” and partly by the Italian MIUR-PRIN project (20108YB5W3_004).

Conflict of Interest statement. None declared.

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