Stress-dependent and -independent expression of the myogenic regulatory factors and the MARP genes after eccentric contractions in
1 Departments of Orthopaedic Surgery and Bioengineering, and the Biomedical Sciences Graduate Group, University of California and Veterans Administration Medical Centers, San Diego, CA, USA
2 Department of Hand Surgery, Sahlgrenska University Hospital, Gteborg, Sweden
Abstract
The relationship between muscle mechanical conditions and gene expression was investigated by varying both stress and contraction mode imposed upon rat dorsiflexors (n= 25), activating them at high or low frequencies (150 Hz or 40 Hz) either eccentrically or isometrically. Muscle physiological, immunohistochemical and gene expression changes were then measured 24 h after the exercise bout. Peak stress was the best predictor of muscle injury, independent of contraction mode (i.e. eccentric or isometric). When peak stresses were matched, no physiological or immunohistochemical differences were detected between isometric and eccentric contractions. The expression of certain myogenic regulatory and muscle ankyrin repeat protein (MARP) genes (myoD, myogenin, MLP and CARP) depended both on peak muscle stress achieved during contraction and contraction mode. In contrast, Arpp/Ankrd2 was dramatically upregulated only by eccentric contractions, but not by isometric contractions, even though the stress level of the eccentric contractions varied over a three-fold range and overlapped with that of the isometric group. The role that Arpp/Ankrd2 upregulation plays in the biological response to eccentric contraction remains to be determined, as does the control mechanism whereby the expression of certain genes (such as myoD, myogenin, MLP and CARP) is sensitive to muscle stress while another (Arpp/Ankrd2) is sensitive only to contraction mode.
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Skeletal muscle tissue is highly plastic (Pette, 1990). A plethora of reports describe consistent and systematic changes in muscles subjected to altered use patterns such as immobilization (Booth, 1982), endurance exercise (Saltin & Gollnick, 1983), eccentric exercise (Morgan & Allen, 1999), weightlessness (Edgerton & Roy, 2000), tenotomy (Jamali et al. 2000) and chronic electrical stimulation (Salmons & Henriksson, 1981). Muscles may change their fibre size, fibre type, microcirculation, calcium regulation, mitochondrial density and calcium transport, in order to adapt to their new functional requirements. Such alterations result from orchestrated gene expression patterns both within and around the muscle cell. While numerous descriptive studies describe genes that are sensitive to muscle's general mechanical environment, there are almost no data available that attempt to define the fundamental mechanical variables (i.e. stress, strain, energy absorbed) transduced by skeletal muscles. Strain-based mechanisms might implicate such cellular components as strain-activated ion channels (Guharay & Sachs, 1984; Komuro et al. 1991), while stress-based mechanisms may implicate the involvement of cytoskeletal elements, membrane-associated G-proteins or integrins (Frangos et al. 1985; Ingber, 1990; Banes, 1993; Petrof et al. 1993). In any case, defining both the mechanism of tissue mechanical transduction and the genes affected by specific mechanical factors is of tremendous importance.
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Certain genes and gene families have been demonstrated as being highly mechanically sensitive in striated muscle and are excellent candidates for involvement in the adaptive response to mechanical perturbation. The recently discovered MARP family, or muscle ankryin repeat proteins, (cardiac ankyrin repeat protein (CARP), Arpp/Ankrd2, and diabetes-associated ankyrin repeat protein (DARP), respectively), have been shown in vivo and in vitro to be highly responsive to muscle mechanical status (Kemp et al. 2000; Miller et al. 2003). In an in vivo model, both CARP and Arpp/Ankrd2 rapidly reached peak expression levels of 10 times contralateral values 12–24 h after the eccentric contraction (EC) bout and returned to baseline levels within 72 h (Barash et al. 2004). A second protein, muscle LIM protein (MLP), is a Z-disk protein that was recently identified as also being dramatically upregulated in response to EC-induced muscle injury (Chen et al. 2002; Barash et al. 2004). MLP has been found in the nucleus during early development (Arber et al. 1994), where it is a potent activator of the myogenic regulatory factor myoD (Kong et al. 1997). This nuclear activity suggests that MLP may have transcriptional activity in addition to its structural role, leading to the intriguing possibility that MLP is a striated muscle stress sensor (Knll et al. 2002). Unfortunately, there have been no studies in which expression of these novel gene products have been measured under controlled mechanical conditions.
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Skeletal muscle tissue, being contractile in nature, affords the unique opportunity to vary tissue stress systematically, simply by altering activation frequency and exploiting the well-defined relationship between force and frequency (Close, 1972). Further, because the force response of skeletal muscle is highly asymmetrical when comparing active shortening to active lengthening (Katz, 1939), muscle contraction mode (i.e. active lengthening, active shortening or isometric contraction) can also be exploited to alter tissue stress experimentally. With the development of minimally invasive animal exercise models (McCully & Faulkner, 1985; Ashton-Miller et al. 1992; Caiozzo et al. 1992; Lieber et al. 1994; Peters et al. 2003; Barash et al. 2004), it is now possible to modulate muscle stress and activation mode precisely in an in vivo model. Thus, the purpose of this study was to impose controlled stresses and contraction modes upon muscles in vivo, in order to understand the relationship between mechanical factors, the resulting injury and the subsequent gene expression pattern. A brief version of this study has appeared in abstract form (Hentzen et al. 2004).
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Methods
Animal care
Laboratory animals used in this study were untrained, adult male Sprague-Dawley rats (Harlan, Indianapolis, IN, USA), with an average size of 443 ± 24 g (mean ±S.D., n= 29). Rats were housed two per cage at 20–23°C with a 12 h dark–light cycle. All procedures were approved by the University of California and VA Medical Center Committees on the Use of Animal Subjects in Research. After terminal experiments, animals were killed with an intracardiac injection of pentobarbitol sodium (0.5 ml of 390 mg ml–1 solution).
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Experimental protocol
Animals were anaesthetized using 0.3 ml subcutaneous injection of a ketamine–rompum–acepromazine mixture (25, 2.5, and 0.5 mg ml–1, respectively), and maintained on isoflurane anaesthesia (2%, 1.5 l min–1) throughout the experiment. Respiratory rate was monitored visually, and anaesthetic concentration was adjusted as needed. Ankle isometric dorsiflexion torque was measured prior to eccentric activation or isometric activation as well as 24 h later. The exercise bouts consisted of 30 contractions (either eccentric or isometric), with 2 min between each contraction to eliminate the effects of fatigue, as previously described in detail (Peters et al. 2003).
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A small lateral incision was made near the fibular head, and the peroneal nerve was isolated as previously described (Peters et al. 2003). This method permitted measurement of isometric dorsiflexion torque with a coefficient of variation of repeated measures between two different measuring days of 7.3%± 3.5% (pilot study of eight animals). Rats (n= 4) were stimulated at frequencies ranging from 5 to 150 Hz to determine the torque–frequency relationship either isometrically (, Fig. 1A) or eccentrically (, Fig. 1A). This was performed to determine stimulation frequencies and modes that result in identical stimulation stresses (see sample records in Fig. 1B). (The small decrease in peak torque for the eccentric contractions in Fig. 1A at high frequency probably represents a slight degree of injury that occurs with repeat torque–frequency testing in the eccentric mode).
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A, torque–frequency relationship for muscles stimulated either isometrically () or eccentrically () across a range of frequencies. Data represent the average ±S.E.M. of n= 4 animal subjects. The crosses illustrate the points chosen to match stress between isometric and eccentric contractions (EC40 and ISO150). B, sample contractile records of muscles stimulated under the four different conditions described in Methods. Note that nearly identical peak torque is obtained when stimulating eccentrically at 40 Hz (EC40) and isometrically at 150 Hz (ISO150).
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After treatment, animals recovered for 24 h, at which time isometric dorsiflexion torque measurement was repeated. Animals were sacrificed and the tibialis anterior (TA) and extensor digitorum longus (EDL) muscles were excised, immediately frozen in liquid nitrogen-cooled isopentane (–159°C) and stored at –80°C for subsequent analysis. This time period was chosen based on previous studies that documented near-peak expression of both the myogenic regulatory factors (Peters et al. 2003) and MARP proteins (Barash et al. 2004) at this time point. While other gene expression profiles were increased 2–5 days after the stimulation bout (Peters et al. 2003), we were interested in the early events that presumably would be most closely related to the cellular transduction of the mechanical events.
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Experimental design
To determine whether muscle stress acts as an independent variable or whether treatment mode (eccentric versus isometric) was a significant factor in the muscle's response, an experimental design was created that varied both the treatment mode and muscle stress. A high-stress, eccentric mode was created by treating animal subjects with eccentric contractions while stimulating the peroneal nerve at 150 Hz (EC150, n= 5). Two groups, matched for peak stress (crosses on lines in Fig. 1A) but ‘exercised’ in different modes were created by treating with either eccentric contractions at 40 Hz (EC40, n= 7) or isometric contractions at 150 Hz (ISO150, n= 6). As a control for stimulation frequency, and to balance the experimental design, a group of subjects treated isometrically at 40 Hz was also generated (ISO40, n= 7). Ideally, the experimental design would have also included a group subjected to shortening contractions at the same stresses. However, based on the dramatic muscle force drop that occurs during shortening, this experimental group was impossible to create at any stimulation frequency or shortening velocity. Thus, in this report, ‘contraction mode’ refers to either eccentric or isometric contraction. For immunohistochemistry and transcript assays, control TA muscles were obtained from rats that had not undergone either eccentric or isometric treatment protocols
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Contractile properties were measured as previously described (Peters et al. 2003). Briefly, isometric dorsiflexion torque was measured by activating the peroneal nerve maximally using a 15 V stimulus, with a train duration of 650 ms. Muscles were stimulated at 2 min intervals at frequencies of 5, 15, 25, 40, and 100 Hz, to determine the torque–frequency relationship. Maximum isometric torque was defined as dorsiflexion torque at 100 Hz stimulation frequency, which was always the greatest value achieved. Eccentric contractions were induced by imposing a 38 deg ankle plantarflexion over a 400 ms duration during maximal dorsiflexor activation. All activations were repeated at 2 min intervals for 60 min, yielding 30 contractions in the prescribed mode and at the prescribed frequency.
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Immunohistochemistry
Muscle cross-sections (10 μm thick) were taken from the midbelly of the TA only, since the EDL did not previously show any abnormalities (Peters et al. 2003). A portion of the muscle cross-section, free from sectioning artifacts, excessive connective tissue or large blood vessels, was labelled with monoclonal antibodies to desmin (DER11, 1 : 1000, Novocastra Laboratories, Newcastle, UK), fibronectin (EDA domain, 1 : 50, Sigma), vimentin (VIM-V9, 1 : 5000, Novocastra), embryonic myosin heavy chain (clone 1.652, 1 : 10, courtesy of Helen Blau, Stanford University), or laminin (clone II (2E8), 1 : 1000, Gibco, Carlsbad, CA, USA) using an indirect immunoperoxidase technique (Vectastain Elite ABC Kit, Vector laboratories, Burlingame, CA, USA). Muscle sections were treated with bovine serum albumin (Sigma, St Louis, MO, USA) as a blocking agent, and incubated with the primary antibodies overnight. The secondary antibody was biotinylated, rat-adsorbed, horse antimouse (1 : 20,000, Vector), and labelling was visualized using diaminobenzidine (Sigma).
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Cross-sections were viewed at 25x magnification, to enable viewing the entire muscle cross-section, and affected fibres were counted directly by an observer blinded to tissue experimental group. Each affected fibre of every section was counted to quantify immunohistochemical appearance, and the criteria for ‘abnormal’ fibres were exactly as previously described (Peters et al. 2003) and illustrated in Fig. 1 of that reference.
Skeletal muscle transcript levels
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Total RNA was isolated from frozen muscle tissues using TRIZOL extraction (Gibco BRL, Grand Island, NY, USA). RNA concentration was measured by absorption at 260 nm, and separation of RNA from contaminant genomic DNA and protein was checked based on a 260 nm/280 nm absorption ratio of 2.0. One microgram of RNA per reaction was reverse transcribed (Superscript, Invitrogen, Carlsbad, CA, USA) into cDNA using Oligo dT as the primer and the manufacturer's protocol, and thus all transcript levels are expressed per microgram of extracted RNA. Primers were designed to amplify myostatin, MyoD, myogenin, MLP (also referred to as CRP3), CARP and Arpp/Ankrd2 in the translated region, while for embryonicMHC the sense primer was designed in the translated region and the antisense primer in the 3'-untranslated region, where the sequence is more specific for this MHC isoform (Periasamy et al. 1985; Weiss et al. 1999). Primers for myostatin, MyoD, myogenin and embryonicMHC were as previously described (Peters et al. 2003) while primers, accession numbers and expected product lengths for MLP, CARP and Arpp/Ankrd2 are provided in Table 1.
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Quantification of transcript levels was performed using the Cepheid SmartCycler (Sunnyvale, CA) on cDNA, as previously described in detail for myostatin,MyoD, myogenin and embryonic MHC (Peters et al. 2003). For MLP, CARP and Arpp/Ankrd2, 1 μl of 1 : 10 diluted cDNA was analysed using platinum taq DNA polymerase (Invitrogen) and SYBR Green dye. All samples were analysed in triplicate along with the gel-purified PCR product standard. The PCR reaction vessel (25 μl) contained: 2.5 μl 10x PCR buffer (1x), 2 mM MgCl2, 0.2 μM sense and antisense primers, 0.2 mM dNTP, 0.2x SYBR Green and 1 U platinum taq polymerase. Two-step amplification was performed as follows: An initial hold at 95°C for 3 min (myogenin) or 5 min (for MLP, CARP, Arpp/Ankrd2, myostatin,MyoD and embryonic MHC) was followed by 40 cycles of denaturing at 95°C for 15 s, and annealing/extension at 68°C for 30 s (CARP), 66°C for 30 s (Arpp/Ankrd2), 62°C for 40 s (myostatin), 67°C for 40 s (MyoD), 68°C for 30 s (myogenin) or 69°C for 40 s (MLP and embryonic MHC). Success of each reaction was deduced based on observing a single reaction product on an agarose gel and a single peak on the DNA melting temperature curve determined at the end of the reaction.
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Analysis of experimental data
Mean values among treatment groups were compared by one-way analysis of variance (ANOVA). Post hoc multiple comparisons between each time period and, in some cases, control groups were made using Fischer's least squared differences (LSD) test. Correlations between and among variables were calculated using simple linear regression and multiple linear regression. Stepwise regression and factor analysis were the multivariate methods used to understand independent relationships among the variables measured.
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Two separate indicators of tissue stress were obtained from the real-time torque measurements: torque-time integral and peak torque. The total torque-time integral for each subject was calculated according to the formula:
where i(t) represents dorsiflexion torque at time t (in ms) during a contraction, the subscript i is contraction number (from 1 to 30), the total stimulation time per contraction was 650 ms, and the time interval between data points was 0.25 ms (i.e. data acquisition rate of 4000 Hz). (Torque–time integral was used for this study instead of the traditional value of energy absorbed (Fung, 1981; Sam et al. 2000) since, for the isometric contractions, no external work was performed and thus energy absorbed for isometric contraction would be zero.) Peak torque during treatment was defined as the peak torque measured for any of the 30 contractions, regardless of the contraction number. In practice, peak torque was observed within the first five contractions for the eccentric bouts, but ranged from the first to last contraction for either isometric treatment.
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Statistical significance level () was set to 0.05 and statistical power (1 –) exceeded 80% in all cases where results were not significantly different, demonstrating an adequate sample size. All analyses were performed with the StatView program (v.5.1, Abacus Concepts, Berkeley, CA, USA). Data are presented in the text as mean ±S.E.M. unless otherwise stated.
Results
Mechanics of treatment
Dorsiflexion torque was recorded in real-time for each contraction of each bout as described in Methods. The torque–time integral varied significantly among groups (P < 0.0001) with the highest value observed for the EC150 group (1.32 ± 0.04 N m s) and the lowest for the ISO40 group (0.67 ± 0.07 N m s). While the goal of the experimental design was to match peak torque of the EC40 and ISO150 groups, the ISO150 group (1.17 ± 0.07 N m s) had a significantly greater torque–time integral compared to the EC40 group (0.99 ± 0.04 N m s; P < 0.05). As expected, dorsiflexion torque was initially highest for the EC150 group, lowest for the ISO40 group and intermediate for the EC40 and ISO150 groups (Fig. 2). Interestingly, while torque was nearly identical for the first 10 contractions of the EC40 and ISO150 groups, it then dropped significantly for the EC40 group. This formed the basis for the significant difference in torque–time integrals between the EC40 and ISO150 groups.
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Each point represents the mean value for the group. S.E.M. bars are shown only for the final contraction for all groups for clarity. No change in data variability were seen as a function of contraction number. () EC150 () EC40 () ISO150 () ISO40.
Peak torque during treatment varied significantly among the four experimental groups (Fig. 3, P < 0.0001). Not surprisingly, the EC150 group experienced the highest peak torque (0.086 ± 0.002 N m) and the ISO40 group the lowest (0.036 ± 0.001 N m), while no significant difference was observed between the EC40 (0.061 ± 0.002 N m) and ISO150 groups (0.056 ± 0.003 N m, P > 0.3). Thus, in spite of differences in torque–time integrals, our effort to match peak stress between the EC40 and ISO150 groups was successful.
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The largest torque change 24 h after eccentric contraction was observed for the EC150 group (–32 ± 2%) while the ISO40 demonstrated almost no change (+3.4 ± 4.4%). Importantly, no significant difference was observed between the ISO150 (9.7 ± 6.1%) and EC40 (–14.4 ± 5.8%). Symbols at the top of the figure indicate significant differences between leftmost group (with arrowhead) and another group when connected with a vertical bar (P < 0.05). Error bars are S.E.M.
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Two-way ANOVA revealed a significant torque decrease after treatment (P < 0.01), and a significant time–treatment interaction (P < 0.01). When expressed as a percentage change relative to initial torque level, the largest torque change was observed for the EC150 group (–32 ± 2%), while the ISO40 demonstrated no change (+3.4 ± 4.4%). Importantly, no significant difference was observed between the ISO150 (–9.7 ± 6.1%) and EC40 (–14.4 ± 5.8%) groups, suggesting similar degrees of physiological injury in response to these treatments (P > 0.4), even though the EC40 group demonstrated a torque drop during the EC bout while the ISO150 group did not (Fig. 2).
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When analysing correlations among physiological variables, the strongest predictor of the percentage change in torque 24 h after treatment was peak torque achieved during treatment (r2= 0.58, P < 0.0001), while no significant correlation was observed between the torque–time integral and percentage change in torque 24 h after treatment (r2= 0.04, P > 0.6). These data suggest that the peak torque imposed upon the muscle during treatment, regardless of mode, was the best predictor of the magnitude of physiological ‘injury’ observed. In addition, the torque–time integral is not an indicator of the magnitude of injury experienced by the muscle. Factor analysis performed on all physiological variables (peak torque during treatment, torque before treatment, torque immediately after treatment (absolute and percentage), torque 24 h after treatment (absolute and percentage), and torque–time integral) supported this concept because only three factors emerged (P < 0.0001, 2= 570, d.f. = 90). In this ‘physiological’ analysis, the EC40 and ISO150 groups were indistinguishable based on any mechanical variable measured.
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Immunohistochemical changes after treatment
Based on the physiological changes observed above, the results of the immunohistochemical analysis were not surprising (Table 2). Several proteins that are commonly used as markers of muscle injury were probed. The most severe indications of injury were observed for the EC150 group, and least severe indications were observed for the ISO40 group. No significant difference was observed between the EC40 and ISO150 group for any immunostaining pattern quantified (Table 2). A high correlation between peak torque during treatment and all immunohistochemical indicators of ‘injury’ was observed (r2 values ranging from 0.61 to 0.84). Again, factor analysis performed on all immunohistochemical indicators of injury revealed only three distinct factors (P < 0.0001, 2= 622, d.f. = 90) indicating, as above, that the EC40 and ISO150 groups were indistinguishable based on any immunohistochemical assay used.
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Gene expression after treatment
The current experimental design was intended to investigate the early changes after treatment, especially with regard to gene expression. The earliest changes observed previously were those associated with the myogenic regulatory factors (Peters et al. 2003) and, in an analogous mouse model, the MARP and MLP genes (Barash et al. 2004). To determine the similarity between the models, the time-course of MARP and MLP mRNA expression was measured on the muscles previously injured by a single eccentric bout at 100 Hz (Peters et al. 2003) with similar results to those previously reported for the mouse. Thus the two models are physiologically and biologically comparable (See Fig. 2A–D of Barash et al. 2004).
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Gene expression patterns, unexpectedly, revealed sensitivity to both treatment mode and treatment stress, in spite of the fact that physiological and immunohistochemical responses were consistent across treatment groups and uniformly showed equivalent effects of EC40 and ISO150 treatments (the two groups treated at similar stresses). For example, myoD expression was significantly elevated in all treatment groups relative to controls (Fig. 4A) but expression in the EC150 group was significantly elevated above all other groups (P < 0.001), none of which were significantly different from one another (P > 0.6). In fact, the myoD expression level measured in the EC150 group was the highest level (17.9 ± 5.0 pg (μg RNA)–1) that we have measured in any experiment of this type (Peters et al. 2003). The other myogenic regulatory factor, myogenin, showed a graded response whereby eccentric groups were significantly different from isometric groups (P < 0.005), and the EC150 and EC40 groups were significantly different from one another (P < 0.01, Fig. 4B). The most interesting comparison was between the EC40 and ISO150 groups, which, in spite of being subjected to similar peak stresses and demonstrating similar physiological and immunohistochemical responses (see above) yielded significantly different levels of the myogenin transcript (P < 0.05; Fig. 4B).
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A, MyoD gene expression levels. B, myogenin gene expression levels. Control myogenin levels were finite and easily measurable (0.057 ± 004 fg. (μg RNA)–1) but not visible on this graph's scale. Symbols at the top of the figure. indicate significant differences between leftmost group (with arrowhead) and another group when connected with a vertical bar (P < 0.05). Error bars are S.E.M.
Two of the members of the MARP family (Miller et al. 2003) showed distinct gene expression patterns in response to the various treatments. CARP was significantly elevated in all eccentric groups (Fig. 5A) compared to isometric groups with the EC40 group having a significantly lower expression level compared to EC150 group (Fig. 5A, P < 0.05). CARP levels in both the ISO150 and ISO40 groups were slightly above levels measured in contralateral control or true experimental control muscles (Fig. 5A). Surprisingly, Arpp/Ankrd2 expression showed a distinct and repeatable association only with the mode of treatment, and no apparent dependence on tissue stress (Fig. 5B). Eccentric groups expressed Arpp/Ankrd2 at twice the level of both isometric groups, with no significant difference observed within either eccentric or isometric groups (P > 0.8).
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A, CARP expression levels, B, Arpp/Ankrd2 expression levels, C, MLP expression levels. Symbols at the top of the figure. indicate significant differences between leftmost group (with arrowhead) and another group when connected with a vertical bar (P < 0.05). Error bars are S.E.M.
The MLP expression pattern roughly paralleled the CARP expression pattern (Fig. 5C), with the EC150 group expressing MLP at a significantly higher level compared to the EC40 group (P < 0.001) which expressed MLP at significantly higher levels than either the ISO150 or ISO40 groups (P < 0.001). No significant difference among experimental groups was observed for myostatin (P > 0.7) or embryonic MHC (P > 0.2) expression. This was probably based on the fact that the 24 h time period was too late to detect myostatin expression changes, and too early to detect embryonic MHC expression (Peters et al. 2003).
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Multivariate analysis
In an attempt to determine unique relationships among variables investigated in this study, stepwise regression was applied to the data set. Stepwise regression was used to predict the percentage torque drop 24 h after treatment. Surprisingly, of the 13 independent variables that could enter the regression equation, three physiological parameters, four immunohistochemical variables, and six gene expression levels), only one variable did – peak torque during the exercise bout (F-to-enter = 36.6 F-to-enter represents the discriminating ability of a variable with higher F-values representing greater discriminating ability). While 11 of the independent variables initially had an F-to-enter that exceeded the threshold of 4.000 (all but myoD and embryonicMHC mRNA levels), these values all dropped to less than 3.000 after entry of the peak torque variable into the model. Such a uniform drop in F-to-enter indicates that percentage torque drop 24 h after treatment was highly correlated with all other variables measured but most highly correlated with peak torque.
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Of the various transcript levels measured, myogenin expression varied most significantly among groups (Fig. 4B), and was thus another interesting candidate for stepwise regression analysis. In this case, several variables entered the model and it is instructive to observe the process by which model entry occurred. In the first step of this analysis (Table 3), 9 of the 13 variables exceeded the F-to-enter, but the highest value was observed for the number of desmin-negative fibres (F-to-enter = 46.7) following closely by the number of cells that included fibronectin (F-to-enter = 44.2). The ‘desmin-negative’ variable alone accounted for 73% of the experimental variability (i.e. r2= 0.862). In the second step, after accounting for covariation with the number of desmin-negative fibres (Table 4), Arpp/Ankrd2 transcript level was one of only two variables of the remaining 12 with an F-value that would permit it to enter the regression equation (F-to-enter = 34.1) and it was actually a better discriminator after accounting for covariation with the number of desmin-negative fibres (F-to-enter = 18.8 in Step no. 1 of Table 3). With both number of desmin-negative fibres and Arpp/Ankrd2 expression levels, 91% of the experimental variability was explained. Interestingly, after accounting for correlation with number of desmin-negative fibres and Arpp/Ankrd2 expression levels, myoD expression level then became a significant covariate with an F-to-enter of 5.3, resulting in a slightly higher value of r2 of 0.94 (Table 5). Thus, myogenin expression level was multifactorial and related to protein and transcript level alterations within the tissue. The crux of this multivariate analysis is that loss of desmin immunostaining was the best predictor of myogenin expression and was highly correlated with a number of other variables measured. Arpp/Ankrd2 and myoD gene expression represented independent factors that uniquely affected myogenin gene expression to a lesser extent.
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Discussion
The purpose of this study was to define the effects of mechanical factors on gene expression in skeletal muscle. We tested the hypothesis that eccentric contractions and isometric contractions (i.e. contraction mode), when performed at the same stress, yield unique results in muscle tissue. We found no unique effects of contraction mode when measuring either physiological or immunohistochemical parameters (Fig. 3, Table 2). However, gene expression levels were uniquely responsive to both contraction mode and treatment stress. Specifically, the Arpp/Akrd2 gene was sensitive only to contraction mode, independent of stress, while other genes measured responded to both stress and contraction mode.
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Because we measured mechanical variables and gene expression in the same animal subjects, it was possible to define such interrelationships. The most interesting expression patterns was observed for Arpp/Ankrd2 (Fig. 5B). This gene showed a clear dichotomous pattern – high expression levels for eccentric contractions, and low expression levels for isometric contractions. For the eccentric groups, peak dorsiflexion torque varied over the range 0.05–0.09 N m while for the isometric groups, peak torque varied over the range 0.03–0.06 N m. In spite of this wide variation, eccentric groups expressed Arpp/Ankrd2 at a level almost three times that of each of the isometric groups (Fig. 5B). The eccentric contraction data obtained here are nearly identical to Arpp/Ankrd2 expression levels (2.97 ± 0.25 fg (μg RNA)–1), n= 5) measured in a similar animal model 24 h after being stimulated at 100 Hz with the same eccentric contraction protocol (Peters et al. 2003). Importantly, the Arpp/Ankrd2 gene has been implicated in mechanical signalling within muscle. For example, it is highly expressed in skeletal muscle and its expression is increased with denervation (Tsukamoto et al. 2002), chronic immobilization in a stretched position (Kemp et al. 2000), and strain in culture (Miller et al. 2003). Its intracellular distribution reveals a specific location in both the nucleus and the I-band (Tsukamoto et al. 2002) where it binds the amino terminus of the nebulin-anchoring protein myopalladin (Bang et al. 2001) and possibly the N2A region of titin (Miller et al. 2003), and is thus strategically located to sense muscle cell strain. In a recent study of EC in a mouse model, we showed that Arpp/Ankrd2 was rapidly upregulated within 12 h and returned to control levels within 48 h (Barash et al. 2004). Thus, at least three conditions have now been identified in which Arpp/Ankrd2 expression is altered by changes in mechanical stress: strain in culture, chronic immobilization and eccentric exercise in vivo. However, this is the first demonstration that Arpp/Ankrd2 expression might also be sensitive to the mode of contraction imposed upon the muscle. This field is in its infancy, only describing conditions under which Arpp/Ankrd2 expression levels change. Subsequent mechanistic studies are under way to provide more detailed explanations for these observations. In order for Arpp/Ankrd2 to be sensitive to active strain, it would have to be uniquely situated within the sarcomere to sense strain independent of stress. This might suggest a parallel connection to the titin molecule independent of the serial stress within the protein itself, perhaps mediated through Arpp/Ankrd2's binding of myopalladin (Bang et al. 2001) or titin N2A (Miller et al. 2003), although the specific binding domains that could result in this configuration remain unknown. Another possible structural basis for the observed result would be a unique association between Arpp/Ankrd2 and strain-activated ion channels, although there is as yet no evidence suggesting this.
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In contrast to Arpp/Ankrd2 expression, myogenin, CARP and MLP expression levels were highly correlated with peak torque and mode of muscle contraction. Correlations between the expression levels of these genes and peak torque varied from 0.73 to 0.78. The fact that not all of these genes entered the multiple regression model suggests that they might be coregulated since they were all highly correlated with one another (paired r2 values ranging from 0.81 to 0.89). Taken together, our interpretation of these data is that myogenin, CARP and MLP are sensitive to both muscle tissue stress and contraction mode, while Arpp/Ankrd2 expression is sensitive only to contraction mode. A physical location that might enable proteins to sense stress would be the Z-disk, a structure that has long been thought to be involved in force transduction within skeletal muscle (Fridén et al. 1983). The recent study examining the numerous important Z-disk-associated proteins (Bang et al. 2001; Knll et al. 2002) underscores its importance in transducing muscle signals. Of course one caveat to this discussion is that we have made the implicit assumption that the gene expression patterns measured reflect muscle cell expression rather than that of satellite cells, fibroblasts or blood cells. While this is the most likely interpretation, the use of immunohistochemistry and in situ hybridization are needed to confirm this assumption.
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It should be noted that while this discussion is presented in terms of tissue stress, only dorsiflexion torque was directly measured. In this study we believe that it is reasonable to use dorsiflexion torque as a surrogate indicator of muscle stress. This is because no size differences were observed between animals, and therefore moment arms and physiological cross-sectional areas (PCSAs) were presumably identical so that torque would scale linearly with muscle stress. Based on the moment arms and PCSAs previously reported for this model (Peters et al. 2003), peak muscle stresses would be in the range of 200–350 kPa. These values would be at the high end of the physiological stress range, but certainly within the reported capability of rat skeletal muscle (Close, 1969).
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We used peak torque measured 24 h after treatment as the main indicator of ‘physiological injury.’ This is due, in part, to the observation that some of these models showed partial recovery 24 h after treatment, suggesting that some of the initial torque decrease immediately after the exercise bout probably represented some type of neuromuscular fatigue. Peak torque was clearly the best predictor of physiological injury (P < 0.0001, r2= 0.68) as revealed by the multivariate analysis. This is consistent with a previous study of the rat soleus in which peak muscle force and injury were highly correlated (Warren et al. 1993). No indicator of any mode-specific cause of injury was seen, and there was no significant correlation between torque–time integral and torque measured 24 h after treatment. The fact that all immunohistochemical indicators of injury were significantly correlated with the peak torque and drop in torque implies that all of these parameters are indicators, albeit indirect, of muscle injury. It must be emphasized that, because the relationship between dorsiflexion torque and these parameters is completely asynchronous (Peters et al. 2003), this indicates that they are not causally related.
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In conclusion, by varying the peak stress and the contraction mode imposed upon rat dorsiflexors, we demonstrated that peak muscle stress is the best predictor of muscle injury in vivo. When peak stresses were matched, no physiological or immunohistochemical differences were detected between isometric and eccentric contractions. This was contrasted greatly by the unique patterns of mRNA expression levels, which, in the case of Arpp/Ankrd2, was upregulated only with eccentric contractions but not by isometric contractions. The role that Arpp/Ankrd2 upregulation plays in the biological response to eccentric contraction remains to be determined. Similarly, further study is required to understand the control mechanisms governing its expression as modulated by contraction mode, in contrast to certain other genes (such as myoD, myogenin, MLP, and CARP) which demonstrate sensitivity to tissue stress.
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2 Department of Hand Surgery, Sahlgrenska University Hospital, Gteborg, Sweden
Abstract
The relationship between muscle mechanical conditions and gene expression was investigated by varying both stress and contraction mode imposed upon rat dorsiflexors (n= 25), activating them at high or low frequencies (150 Hz or 40 Hz) either eccentrically or isometrically. Muscle physiological, immunohistochemical and gene expression changes were then measured 24 h after the exercise bout. Peak stress was the best predictor of muscle injury, independent of contraction mode (i.e. eccentric or isometric). When peak stresses were matched, no physiological or immunohistochemical differences were detected between isometric and eccentric contractions. The expression of certain myogenic regulatory and muscle ankyrin repeat protein (MARP) genes (myoD, myogenin, MLP and CARP) depended both on peak muscle stress achieved during contraction and contraction mode. In contrast, Arpp/Ankrd2 was dramatically upregulated only by eccentric contractions, but not by isometric contractions, even though the stress level of the eccentric contractions varied over a three-fold range and overlapped with that of the isometric group. The role that Arpp/Ankrd2 upregulation plays in the biological response to eccentric contraction remains to be determined, as does the control mechanism whereby the expression of certain genes (such as myoD, myogenin, MLP and CARP) is sensitive to muscle stress while another (Arpp/Ankrd2) is sensitive only to contraction mode.
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Skeletal muscle tissue is highly plastic (Pette, 1990). A plethora of reports describe consistent and systematic changes in muscles subjected to altered use patterns such as immobilization (Booth, 1982), endurance exercise (Saltin & Gollnick, 1983), eccentric exercise (Morgan & Allen, 1999), weightlessness (Edgerton & Roy, 2000), tenotomy (Jamali et al. 2000) and chronic electrical stimulation (Salmons & Henriksson, 1981). Muscles may change their fibre size, fibre type, microcirculation, calcium regulation, mitochondrial density and calcium transport, in order to adapt to their new functional requirements. Such alterations result from orchestrated gene expression patterns both within and around the muscle cell. While numerous descriptive studies describe genes that are sensitive to muscle's general mechanical environment, there are almost no data available that attempt to define the fundamental mechanical variables (i.e. stress, strain, energy absorbed) transduced by skeletal muscles. Strain-based mechanisms might implicate such cellular components as strain-activated ion channels (Guharay & Sachs, 1984; Komuro et al. 1991), while stress-based mechanisms may implicate the involvement of cytoskeletal elements, membrane-associated G-proteins or integrins (Frangos et al. 1985; Ingber, 1990; Banes, 1993; Petrof et al. 1993). In any case, defining both the mechanism of tissue mechanical transduction and the genes affected by specific mechanical factors is of tremendous importance.
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Certain genes and gene families have been demonstrated as being highly mechanically sensitive in striated muscle and are excellent candidates for involvement in the adaptive response to mechanical perturbation. The recently discovered MARP family, or muscle ankryin repeat proteins, (cardiac ankyrin repeat protein (CARP), Arpp/Ankrd2, and diabetes-associated ankyrin repeat protein (DARP), respectively), have been shown in vivo and in vitro to be highly responsive to muscle mechanical status (Kemp et al. 2000; Miller et al. 2003). In an in vivo model, both CARP and Arpp/Ankrd2 rapidly reached peak expression levels of 10 times contralateral values 12–24 h after the eccentric contraction (EC) bout and returned to baseline levels within 72 h (Barash et al. 2004). A second protein, muscle LIM protein (MLP), is a Z-disk protein that was recently identified as also being dramatically upregulated in response to EC-induced muscle injury (Chen et al. 2002; Barash et al. 2004). MLP has been found in the nucleus during early development (Arber et al. 1994), where it is a potent activator of the myogenic regulatory factor myoD (Kong et al. 1997). This nuclear activity suggests that MLP may have transcriptional activity in addition to its structural role, leading to the intriguing possibility that MLP is a striated muscle stress sensor (Knll et al. 2002). Unfortunately, there have been no studies in which expression of these novel gene products have been measured under controlled mechanical conditions.
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Skeletal muscle tissue, being contractile in nature, affords the unique opportunity to vary tissue stress systematically, simply by altering activation frequency and exploiting the well-defined relationship between force and frequency (Close, 1972). Further, because the force response of skeletal muscle is highly asymmetrical when comparing active shortening to active lengthening (Katz, 1939), muscle contraction mode (i.e. active lengthening, active shortening or isometric contraction) can also be exploited to alter tissue stress experimentally. With the development of minimally invasive animal exercise models (McCully & Faulkner, 1985; Ashton-Miller et al. 1992; Caiozzo et al. 1992; Lieber et al. 1994; Peters et al. 2003; Barash et al. 2004), it is now possible to modulate muscle stress and activation mode precisely in an in vivo model. Thus, the purpose of this study was to impose controlled stresses and contraction modes upon muscles in vivo, in order to understand the relationship between mechanical factors, the resulting injury and the subsequent gene expression pattern. A brief version of this study has appeared in abstract form (Hentzen et al. 2004).
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Methods
Animal care
Laboratory animals used in this study were untrained, adult male Sprague-Dawley rats (Harlan, Indianapolis, IN, USA), with an average size of 443 ± 24 g (mean ±S.D., n= 29). Rats were housed two per cage at 20–23°C with a 12 h dark–light cycle. All procedures were approved by the University of California and VA Medical Center Committees on the Use of Animal Subjects in Research. After terminal experiments, animals were killed with an intracardiac injection of pentobarbitol sodium (0.5 ml of 390 mg ml–1 solution).
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Experimental protocol
Animals were anaesthetized using 0.3 ml subcutaneous injection of a ketamine–rompum–acepromazine mixture (25, 2.5, and 0.5 mg ml–1, respectively), and maintained on isoflurane anaesthesia (2%, 1.5 l min–1) throughout the experiment. Respiratory rate was monitored visually, and anaesthetic concentration was adjusted as needed. Ankle isometric dorsiflexion torque was measured prior to eccentric activation or isometric activation as well as 24 h later. The exercise bouts consisted of 30 contractions (either eccentric or isometric), with 2 min between each contraction to eliminate the effects of fatigue, as previously described in detail (Peters et al. 2003).
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A small lateral incision was made near the fibular head, and the peroneal nerve was isolated as previously described (Peters et al. 2003). This method permitted measurement of isometric dorsiflexion torque with a coefficient of variation of repeated measures between two different measuring days of 7.3%± 3.5% (pilot study of eight animals). Rats (n= 4) were stimulated at frequencies ranging from 5 to 150 Hz to determine the torque–frequency relationship either isometrically (, Fig. 1A) or eccentrically (, Fig. 1A). This was performed to determine stimulation frequencies and modes that result in identical stimulation stresses (see sample records in Fig. 1B). (The small decrease in peak torque for the eccentric contractions in Fig. 1A at high frequency probably represents a slight degree of injury that occurs with repeat torque–frequency testing in the eccentric mode).
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A, torque–frequency relationship for muscles stimulated either isometrically () or eccentrically () across a range of frequencies. Data represent the average ±S.E.M. of n= 4 animal subjects. The crosses illustrate the points chosen to match stress between isometric and eccentric contractions (EC40 and ISO150). B, sample contractile records of muscles stimulated under the four different conditions described in Methods. Note that nearly identical peak torque is obtained when stimulating eccentrically at 40 Hz (EC40) and isometrically at 150 Hz (ISO150).
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After treatment, animals recovered for 24 h, at which time isometric dorsiflexion torque measurement was repeated. Animals were sacrificed and the tibialis anterior (TA) and extensor digitorum longus (EDL) muscles were excised, immediately frozen in liquid nitrogen-cooled isopentane (–159°C) and stored at –80°C for subsequent analysis. This time period was chosen based on previous studies that documented near-peak expression of both the myogenic regulatory factors (Peters et al. 2003) and MARP proteins (Barash et al. 2004) at this time point. While other gene expression profiles were increased 2–5 days after the stimulation bout (Peters et al. 2003), we were interested in the early events that presumably would be most closely related to the cellular transduction of the mechanical events.
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Experimental design
To determine whether muscle stress acts as an independent variable or whether treatment mode (eccentric versus isometric) was a significant factor in the muscle's response, an experimental design was created that varied both the treatment mode and muscle stress. A high-stress, eccentric mode was created by treating animal subjects with eccentric contractions while stimulating the peroneal nerve at 150 Hz (EC150, n= 5). Two groups, matched for peak stress (crosses on lines in Fig. 1A) but ‘exercised’ in different modes were created by treating with either eccentric contractions at 40 Hz (EC40, n= 7) or isometric contractions at 150 Hz (ISO150, n= 6). As a control for stimulation frequency, and to balance the experimental design, a group of subjects treated isometrically at 40 Hz was also generated (ISO40, n= 7). Ideally, the experimental design would have also included a group subjected to shortening contractions at the same stresses. However, based on the dramatic muscle force drop that occurs during shortening, this experimental group was impossible to create at any stimulation frequency or shortening velocity. Thus, in this report, ‘contraction mode’ refers to either eccentric or isometric contraction. For immunohistochemistry and transcript assays, control TA muscles were obtained from rats that had not undergone either eccentric or isometric treatment protocols
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Contractile properties were measured as previously described (Peters et al. 2003). Briefly, isometric dorsiflexion torque was measured by activating the peroneal nerve maximally using a 15 V stimulus, with a train duration of 650 ms. Muscles were stimulated at 2 min intervals at frequencies of 5, 15, 25, 40, and 100 Hz, to determine the torque–frequency relationship. Maximum isometric torque was defined as dorsiflexion torque at 100 Hz stimulation frequency, which was always the greatest value achieved. Eccentric contractions were induced by imposing a 38 deg ankle plantarflexion over a 400 ms duration during maximal dorsiflexor activation. All activations were repeated at 2 min intervals for 60 min, yielding 30 contractions in the prescribed mode and at the prescribed frequency.
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Immunohistochemistry
Muscle cross-sections (10 μm thick) were taken from the midbelly of the TA only, since the EDL did not previously show any abnormalities (Peters et al. 2003). A portion of the muscle cross-section, free from sectioning artifacts, excessive connective tissue or large blood vessels, was labelled with monoclonal antibodies to desmin (DER11, 1 : 1000, Novocastra Laboratories, Newcastle, UK), fibronectin (EDA domain, 1 : 50, Sigma), vimentin (VIM-V9, 1 : 5000, Novocastra), embryonic myosin heavy chain (clone 1.652, 1 : 10, courtesy of Helen Blau, Stanford University), or laminin (clone II (2E8), 1 : 1000, Gibco, Carlsbad, CA, USA) using an indirect immunoperoxidase technique (Vectastain Elite ABC Kit, Vector laboratories, Burlingame, CA, USA). Muscle sections were treated with bovine serum albumin (Sigma, St Louis, MO, USA) as a blocking agent, and incubated with the primary antibodies overnight. The secondary antibody was biotinylated, rat-adsorbed, horse antimouse (1 : 20,000, Vector), and labelling was visualized using diaminobenzidine (Sigma).
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Cross-sections were viewed at 25x magnification, to enable viewing the entire muscle cross-section, and affected fibres were counted directly by an observer blinded to tissue experimental group. Each affected fibre of every section was counted to quantify immunohistochemical appearance, and the criteria for ‘abnormal’ fibres were exactly as previously described (Peters et al. 2003) and illustrated in Fig. 1 of that reference.
Skeletal muscle transcript levels
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Total RNA was isolated from frozen muscle tissues using TRIZOL extraction (Gibco BRL, Grand Island, NY, USA). RNA concentration was measured by absorption at 260 nm, and separation of RNA from contaminant genomic DNA and protein was checked based on a 260 nm/280 nm absorption ratio of 2.0. One microgram of RNA per reaction was reverse transcribed (Superscript, Invitrogen, Carlsbad, CA, USA) into cDNA using Oligo dT as the primer and the manufacturer's protocol, and thus all transcript levels are expressed per microgram of extracted RNA. Primers were designed to amplify myostatin, MyoD, myogenin, MLP (also referred to as CRP3), CARP and Arpp/Ankrd2 in the translated region, while for embryonicMHC the sense primer was designed in the translated region and the antisense primer in the 3'-untranslated region, where the sequence is more specific for this MHC isoform (Periasamy et al. 1985; Weiss et al. 1999). Primers for myostatin, MyoD, myogenin and embryonicMHC were as previously described (Peters et al. 2003) while primers, accession numbers and expected product lengths for MLP, CARP and Arpp/Ankrd2 are provided in Table 1.
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Quantification of transcript levels was performed using the Cepheid SmartCycler (Sunnyvale, CA) on cDNA, as previously described in detail for myostatin,MyoD, myogenin and embryonic MHC (Peters et al. 2003). For MLP, CARP and Arpp/Ankrd2, 1 μl of 1 : 10 diluted cDNA was analysed using platinum taq DNA polymerase (Invitrogen) and SYBR Green dye. All samples were analysed in triplicate along with the gel-purified PCR product standard. The PCR reaction vessel (25 μl) contained: 2.5 μl 10x PCR buffer (1x), 2 mM MgCl2, 0.2 μM sense and antisense primers, 0.2 mM dNTP, 0.2x SYBR Green and 1 U platinum taq polymerase. Two-step amplification was performed as follows: An initial hold at 95°C for 3 min (myogenin) or 5 min (for MLP, CARP, Arpp/Ankrd2, myostatin,MyoD and embryonic MHC) was followed by 40 cycles of denaturing at 95°C for 15 s, and annealing/extension at 68°C for 30 s (CARP), 66°C for 30 s (Arpp/Ankrd2), 62°C for 40 s (myostatin), 67°C for 40 s (MyoD), 68°C for 30 s (myogenin) or 69°C for 40 s (MLP and embryonic MHC). Success of each reaction was deduced based on observing a single reaction product on an agarose gel and a single peak on the DNA melting temperature curve determined at the end of the reaction.
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Analysis of experimental data
Mean values among treatment groups were compared by one-way analysis of variance (ANOVA). Post hoc multiple comparisons between each time period and, in some cases, control groups were made using Fischer's least squared differences (LSD) test. Correlations between and among variables were calculated using simple linear regression and multiple linear regression. Stepwise regression and factor analysis were the multivariate methods used to understand independent relationships among the variables measured.
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Two separate indicators of tissue stress were obtained from the real-time torque measurements: torque-time integral and peak torque. The total torque-time integral for each subject was calculated according to the formula:
where i(t) represents dorsiflexion torque at time t (in ms) during a contraction, the subscript i is contraction number (from 1 to 30), the total stimulation time per contraction was 650 ms, and the time interval between data points was 0.25 ms (i.e. data acquisition rate of 4000 Hz). (Torque–time integral was used for this study instead of the traditional value of energy absorbed (Fung, 1981; Sam et al. 2000) since, for the isometric contractions, no external work was performed and thus energy absorbed for isometric contraction would be zero.) Peak torque during treatment was defined as the peak torque measured for any of the 30 contractions, regardless of the contraction number. In practice, peak torque was observed within the first five contractions for the eccentric bouts, but ranged from the first to last contraction for either isometric treatment.
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Statistical significance level () was set to 0.05 and statistical power (1 –) exceeded 80% in all cases where results were not significantly different, demonstrating an adequate sample size. All analyses were performed with the StatView program (v.5.1, Abacus Concepts, Berkeley, CA, USA). Data are presented in the text as mean ±S.E.M. unless otherwise stated.
Results
Mechanics of treatment
Dorsiflexion torque was recorded in real-time for each contraction of each bout as described in Methods. The torque–time integral varied significantly among groups (P < 0.0001) with the highest value observed for the EC150 group (1.32 ± 0.04 N m s) and the lowest for the ISO40 group (0.67 ± 0.07 N m s). While the goal of the experimental design was to match peak torque of the EC40 and ISO150 groups, the ISO150 group (1.17 ± 0.07 N m s) had a significantly greater torque–time integral compared to the EC40 group (0.99 ± 0.04 N m s; P < 0.05). As expected, dorsiflexion torque was initially highest for the EC150 group, lowest for the ISO40 group and intermediate for the EC40 and ISO150 groups (Fig. 2). Interestingly, while torque was nearly identical for the first 10 contractions of the EC40 and ISO150 groups, it then dropped significantly for the EC40 group. This formed the basis for the significant difference in torque–time integrals between the EC40 and ISO150 groups.
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Each point represents the mean value for the group. S.E.M. bars are shown only for the final contraction for all groups for clarity. No change in data variability were seen as a function of contraction number. () EC150 () EC40 () ISO150 () ISO40.
Peak torque during treatment varied significantly among the four experimental groups (Fig. 3, P < 0.0001). Not surprisingly, the EC150 group experienced the highest peak torque (0.086 ± 0.002 N m) and the ISO40 group the lowest (0.036 ± 0.001 N m), while no significant difference was observed between the EC40 (0.061 ± 0.002 N m) and ISO150 groups (0.056 ± 0.003 N m, P > 0.3). Thus, in spite of differences in torque–time integrals, our effort to match peak stress between the EC40 and ISO150 groups was successful.
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The largest torque change 24 h after eccentric contraction was observed for the EC150 group (–32 ± 2%) while the ISO40 demonstrated almost no change (+3.4 ± 4.4%). Importantly, no significant difference was observed between the ISO150 (9.7 ± 6.1%) and EC40 (–14.4 ± 5.8%). Symbols at the top of the figure indicate significant differences between leftmost group (with arrowhead) and another group when connected with a vertical bar (P < 0.05). Error bars are S.E.M.
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Two-way ANOVA revealed a significant torque decrease after treatment (P < 0.01), and a significant time–treatment interaction (P < 0.01). When expressed as a percentage change relative to initial torque level, the largest torque change was observed for the EC150 group (–32 ± 2%), while the ISO40 demonstrated no change (+3.4 ± 4.4%). Importantly, no significant difference was observed between the ISO150 (–9.7 ± 6.1%) and EC40 (–14.4 ± 5.8%) groups, suggesting similar degrees of physiological injury in response to these treatments (P > 0.4), even though the EC40 group demonstrated a torque drop during the EC bout while the ISO150 group did not (Fig. 2).
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When analysing correlations among physiological variables, the strongest predictor of the percentage change in torque 24 h after treatment was peak torque achieved during treatment (r2= 0.58, P < 0.0001), while no significant correlation was observed between the torque–time integral and percentage change in torque 24 h after treatment (r2= 0.04, P > 0.6). These data suggest that the peak torque imposed upon the muscle during treatment, regardless of mode, was the best predictor of the magnitude of physiological ‘injury’ observed. In addition, the torque–time integral is not an indicator of the magnitude of injury experienced by the muscle. Factor analysis performed on all physiological variables (peak torque during treatment, torque before treatment, torque immediately after treatment (absolute and percentage), torque 24 h after treatment (absolute and percentage), and torque–time integral) supported this concept because only three factors emerged (P < 0.0001, 2= 570, d.f. = 90). In this ‘physiological’ analysis, the EC40 and ISO150 groups were indistinguishable based on any mechanical variable measured.
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Immunohistochemical changes after treatment
Based on the physiological changes observed above, the results of the immunohistochemical analysis were not surprising (Table 2). Several proteins that are commonly used as markers of muscle injury were probed. The most severe indications of injury were observed for the EC150 group, and least severe indications were observed for the ISO40 group. No significant difference was observed between the EC40 and ISO150 group for any immunostaining pattern quantified (Table 2). A high correlation between peak torque during treatment and all immunohistochemical indicators of ‘injury’ was observed (r2 values ranging from 0.61 to 0.84). Again, factor analysis performed on all immunohistochemical indicators of injury revealed only three distinct factors (P < 0.0001, 2= 622, d.f. = 90) indicating, as above, that the EC40 and ISO150 groups were indistinguishable based on any immunohistochemical assay used.
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Gene expression after treatment
The current experimental design was intended to investigate the early changes after treatment, especially with regard to gene expression. The earliest changes observed previously were those associated with the myogenic regulatory factors (Peters et al. 2003) and, in an analogous mouse model, the MARP and MLP genes (Barash et al. 2004). To determine the similarity between the models, the time-course of MARP and MLP mRNA expression was measured on the muscles previously injured by a single eccentric bout at 100 Hz (Peters et al. 2003) with similar results to those previously reported for the mouse. Thus the two models are physiologically and biologically comparable (See Fig. 2A–D of Barash et al. 2004).
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Gene expression patterns, unexpectedly, revealed sensitivity to both treatment mode and treatment stress, in spite of the fact that physiological and immunohistochemical responses were consistent across treatment groups and uniformly showed equivalent effects of EC40 and ISO150 treatments (the two groups treated at similar stresses). For example, myoD expression was significantly elevated in all treatment groups relative to controls (Fig. 4A) but expression in the EC150 group was significantly elevated above all other groups (P < 0.001), none of which were significantly different from one another (P > 0.6). In fact, the myoD expression level measured in the EC150 group was the highest level (17.9 ± 5.0 pg (μg RNA)–1) that we have measured in any experiment of this type (Peters et al. 2003). The other myogenic regulatory factor, myogenin, showed a graded response whereby eccentric groups were significantly different from isometric groups (P < 0.005), and the EC150 and EC40 groups were significantly different from one another (P < 0.01, Fig. 4B). The most interesting comparison was between the EC40 and ISO150 groups, which, in spite of being subjected to similar peak stresses and demonstrating similar physiological and immunohistochemical responses (see above) yielded significantly different levels of the myogenin transcript (P < 0.05; Fig. 4B).
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A, MyoD gene expression levels. B, myogenin gene expression levels. Control myogenin levels were finite and easily measurable (0.057 ± 004 fg. (μg RNA)–1) but not visible on this graph's scale. Symbols at the top of the figure. indicate significant differences between leftmost group (with arrowhead) and another group when connected with a vertical bar (P < 0.05). Error bars are S.E.M.
Two of the members of the MARP family (Miller et al. 2003) showed distinct gene expression patterns in response to the various treatments. CARP was significantly elevated in all eccentric groups (Fig. 5A) compared to isometric groups with the EC40 group having a significantly lower expression level compared to EC150 group (Fig. 5A, P < 0.05). CARP levels in both the ISO150 and ISO40 groups were slightly above levels measured in contralateral control or true experimental control muscles (Fig. 5A). Surprisingly, Arpp/Ankrd2 expression showed a distinct and repeatable association only with the mode of treatment, and no apparent dependence on tissue stress (Fig. 5B). Eccentric groups expressed Arpp/Ankrd2 at twice the level of both isometric groups, with no significant difference observed within either eccentric or isometric groups (P > 0.8).
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A, CARP expression levels, B, Arpp/Ankrd2 expression levels, C, MLP expression levels. Symbols at the top of the figure. indicate significant differences between leftmost group (with arrowhead) and another group when connected with a vertical bar (P < 0.05). Error bars are S.E.M.
The MLP expression pattern roughly paralleled the CARP expression pattern (Fig. 5C), with the EC150 group expressing MLP at a significantly higher level compared to the EC40 group (P < 0.001) which expressed MLP at significantly higher levels than either the ISO150 or ISO40 groups (P < 0.001). No significant difference among experimental groups was observed for myostatin (P > 0.7) or embryonic MHC (P > 0.2) expression. This was probably based on the fact that the 24 h time period was too late to detect myostatin expression changes, and too early to detect embryonic MHC expression (Peters et al. 2003).
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Multivariate analysis
In an attempt to determine unique relationships among variables investigated in this study, stepwise regression was applied to the data set. Stepwise regression was used to predict the percentage torque drop 24 h after treatment. Surprisingly, of the 13 independent variables that could enter the regression equation, three physiological parameters, four immunohistochemical variables, and six gene expression levels), only one variable did – peak torque during the exercise bout (F-to-enter = 36.6 F-to-enter represents the discriminating ability of a variable with higher F-values representing greater discriminating ability). While 11 of the independent variables initially had an F-to-enter that exceeded the threshold of 4.000 (all but myoD and embryonicMHC mRNA levels), these values all dropped to less than 3.000 after entry of the peak torque variable into the model. Such a uniform drop in F-to-enter indicates that percentage torque drop 24 h after treatment was highly correlated with all other variables measured but most highly correlated with peak torque.
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Of the various transcript levels measured, myogenin expression varied most significantly among groups (Fig. 4B), and was thus another interesting candidate for stepwise regression analysis. In this case, several variables entered the model and it is instructive to observe the process by which model entry occurred. In the first step of this analysis (Table 3), 9 of the 13 variables exceeded the F-to-enter, but the highest value was observed for the number of desmin-negative fibres (F-to-enter = 46.7) following closely by the number of cells that included fibronectin (F-to-enter = 44.2). The ‘desmin-negative’ variable alone accounted for 73% of the experimental variability (i.e. r2= 0.862). In the second step, after accounting for covariation with the number of desmin-negative fibres (Table 4), Arpp/Ankrd2 transcript level was one of only two variables of the remaining 12 with an F-value that would permit it to enter the regression equation (F-to-enter = 34.1) and it was actually a better discriminator after accounting for covariation with the number of desmin-negative fibres (F-to-enter = 18.8 in Step no. 1 of Table 3). With both number of desmin-negative fibres and Arpp/Ankrd2 expression levels, 91% of the experimental variability was explained. Interestingly, after accounting for correlation with number of desmin-negative fibres and Arpp/Ankrd2 expression levels, myoD expression level then became a significant covariate with an F-to-enter of 5.3, resulting in a slightly higher value of r2 of 0.94 (Table 5). Thus, myogenin expression level was multifactorial and related to protein and transcript level alterations within the tissue. The crux of this multivariate analysis is that loss of desmin immunostaining was the best predictor of myogenin expression and was highly correlated with a number of other variables measured. Arpp/Ankrd2 and myoD gene expression represented independent factors that uniquely affected myogenin gene expression to a lesser extent.
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Discussion
The purpose of this study was to define the effects of mechanical factors on gene expression in skeletal muscle. We tested the hypothesis that eccentric contractions and isometric contractions (i.e. contraction mode), when performed at the same stress, yield unique results in muscle tissue. We found no unique effects of contraction mode when measuring either physiological or immunohistochemical parameters (Fig. 3, Table 2). However, gene expression levels were uniquely responsive to both contraction mode and treatment stress. Specifically, the Arpp/Akrd2 gene was sensitive only to contraction mode, independent of stress, while other genes measured responded to both stress and contraction mode.
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Because we measured mechanical variables and gene expression in the same animal subjects, it was possible to define such interrelationships. The most interesting expression patterns was observed for Arpp/Ankrd2 (Fig. 5B). This gene showed a clear dichotomous pattern – high expression levels for eccentric contractions, and low expression levels for isometric contractions. For the eccentric groups, peak dorsiflexion torque varied over the range 0.05–0.09 N m while for the isometric groups, peak torque varied over the range 0.03–0.06 N m. In spite of this wide variation, eccentric groups expressed Arpp/Ankrd2 at a level almost three times that of each of the isometric groups (Fig. 5B). The eccentric contraction data obtained here are nearly identical to Arpp/Ankrd2 expression levels (2.97 ± 0.25 fg (μg RNA)–1), n= 5) measured in a similar animal model 24 h after being stimulated at 100 Hz with the same eccentric contraction protocol (Peters et al. 2003). Importantly, the Arpp/Ankrd2 gene has been implicated in mechanical signalling within muscle. For example, it is highly expressed in skeletal muscle and its expression is increased with denervation (Tsukamoto et al. 2002), chronic immobilization in a stretched position (Kemp et al. 2000), and strain in culture (Miller et al. 2003). Its intracellular distribution reveals a specific location in both the nucleus and the I-band (Tsukamoto et al. 2002) where it binds the amino terminus of the nebulin-anchoring protein myopalladin (Bang et al. 2001) and possibly the N2A region of titin (Miller et al. 2003), and is thus strategically located to sense muscle cell strain. In a recent study of EC in a mouse model, we showed that Arpp/Ankrd2 was rapidly upregulated within 12 h and returned to control levels within 48 h (Barash et al. 2004). Thus, at least three conditions have now been identified in which Arpp/Ankrd2 expression is altered by changes in mechanical stress: strain in culture, chronic immobilization and eccentric exercise in vivo. However, this is the first demonstration that Arpp/Ankrd2 expression might also be sensitive to the mode of contraction imposed upon the muscle. This field is in its infancy, only describing conditions under which Arpp/Ankrd2 expression levels change. Subsequent mechanistic studies are under way to provide more detailed explanations for these observations. In order for Arpp/Ankrd2 to be sensitive to active strain, it would have to be uniquely situated within the sarcomere to sense strain independent of stress. This might suggest a parallel connection to the titin molecule independent of the serial stress within the protein itself, perhaps mediated through Arpp/Ankrd2's binding of myopalladin (Bang et al. 2001) or titin N2A (Miller et al. 2003), although the specific binding domains that could result in this configuration remain unknown. Another possible structural basis for the observed result would be a unique association between Arpp/Ankrd2 and strain-activated ion channels, although there is as yet no evidence suggesting this.
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In contrast to Arpp/Ankrd2 expression, myogenin, CARP and MLP expression levels were highly correlated with peak torque and mode of muscle contraction. Correlations between the expression levels of these genes and peak torque varied from 0.73 to 0.78. The fact that not all of these genes entered the multiple regression model suggests that they might be coregulated since they were all highly correlated with one another (paired r2 values ranging from 0.81 to 0.89). Taken together, our interpretation of these data is that myogenin, CARP and MLP are sensitive to both muscle tissue stress and contraction mode, while Arpp/Ankrd2 expression is sensitive only to contraction mode. A physical location that might enable proteins to sense stress would be the Z-disk, a structure that has long been thought to be involved in force transduction within skeletal muscle (Fridén et al. 1983). The recent study examining the numerous important Z-disk-associated proteins (Bang et al. 2001; Knll et al. 2002) underscores its importance in transducing muscle signals. Of course one caveat to this discussion is that we have made the implicit assumption that the gene expression patterns measured reflect muscle cell expression rather than that of satellite cells, fibroblasts or blood cells. While this is the most likely interpretation, the use of immunohistochemistry and in situ hybridization are needed to confirm this assumption.
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It should be noted that while this discussion is presented in terms of tissue stress, only dorsiflexion torque was directly measured. In this study we believe that it is reasonable to use dorsiflexion torque as a surrogate indicator of muscle stress. This is because no size differences were observed between animals, and therefore moment arms and physiological cross-sectional areas (PCSAs) were presumably identical so that torque would scale linearly with muscle stress. Based on the moment arms and PCSAs previously reported for this model (Peters et al. 2003), peak muscle stresses would be in the range of 200–350 kPa. These values would be at the high end of the physiological stress range, but certainly within the reported capability of rat skeletal muscle (Close, 1969).
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We used peak torque measured 24 h after treatment as the main indicator of ‘physiological injury.’ This is due, in part, to the observation that some of these models showed partial recovery 24 h after treatment, suggesting that some of the initial torque decrease immediately after the exercise bout probably represented some type of neuromuscular fatigue. Peak torque was clearly the best predictor of physiological injury (P < 0.0001, r2= 0.68) as revealed by the multivariate analysis. This is consistent with a previous study of the rat soleus in which peak muscle force and injury were highly correlated (Warren et al. 1993). No indicator of any mode-specific cause of injury was seen, and there was no significant correlation between torque–time integral and torque measured 24 h after treatment. The fact that all immunohistochemical indicators of injury were significantly correlated with the peak torque and drop in torque implies that all of these parameters are indicators, albeit indirect, of muscle injury. It must be emphasized that, because the relationship between dorsiflexion torque and these parameters is completely asynchronous (Peters et al. 2003), this indicates that they are not causally related.
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In conclusion, by varying the peak stress and the contraction mode imposed upon rat dorsiflexors, we demonstrated that peak muscle stress is the best predictor of muscle injury in vivo. When peak stresses were matched, no physiological or immunohistochemical differences were detected between isometric and eccentric contractions. This was contrasted greatly by the unique patterns of mRNA expression levels, which, in the case of Arpp/Ankrd2, was upregulated only with eccentric contractions but not by isometric contractions. The role that Arpp/Ankrd2 upregulation plays in the biological response to eccentric contraction remains to be determined. Similarly, further study is required to understand the control mechanisms governing its expression as modulated by contraction mode, in contrast to certain other genes (such as myoD, myogenin, MLP, and CARP) which demonstrate sensitivity to tissue stress.
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