Exercise with low glycogen increases PGC-1α gene expression in human skeletal muscle
- First Online:
- Cite this article as:
- Psilander, N., Frank, P., Flockhart, M. et al. Eur J Appl Physiol (2013) 113: 951. doi:10.1007/s00421-012-2504-8
- 1.4k Views
Recent studies suggest that carbohydrate restriction can improve the training-induced adaptation of muscle oxidative capacity. However, the importance of low muscle glycogen on the molecular signaling of mitochondrial biogenesis remains unclear. Here, we compare the effects of exercise with low (LG) and normal (NG) glycogen on different molecular factors involved in the regulation of mitochondrial biogenesis. Ten highly trained cyclists (VO2max 65 ± 1 ml/kg/min, Wmax 387 ± 8 W) exercised for 60 min at approximately 64 % VO2max with either low [166 ± 21 mmol/kg dry weight (dw)] or normal (478 ± 33 mmol/kg dw) muscle glycogen levels achieved by prior exercise/diet intervention. Muscle biopsies were taken before, and 3 h after, exercise. The mRNA of peroxisome proliferator-activated receptor-γ coactivator-1 was enhanced to a greater extent when exercise was performed with low compared with normal glycogen levels (8.1-fold vs. 2.5-fold increase). Cytochrome c oxidase subunit I and pyruvate dehydrogenase kinase isozyme 4 mRNA were increased after LG (1.3- and 114-fold increase, respectively), but not after NG. Phosphorylation of AMP-activated protein kinase, p38 mitogen-activated protein kinases and acetyl-CoA carboxylase was not changed 3 h post-exercise. Mitochondrial reactive oxygen species production and glutathione oxidative status tended to be reduced 3 h post-exercise. We conclude that exercise with low glycogen levels amplifies the expression of the major genetic marker for mitochondrial biogenesis in highly trained cyclists. The results suggest that low glycogen exercise may be beneficial for improving muscle oxidative capacity.
KeywordsTrain lowCarbohydrate restrictionGene expressionPGC-1αOxidative stress
Muscle glycogen is an essential fuel during intensive exercise, and muscle fatigue is closely related to depleted glycogen stores (Bergstrom et al. 1967). In contrast, recent studies suggest that restricted carbohydrate (CHO) availability may enhance the adaptative response to endurance training (Baar and McGee 2008; Burke et al. 2011; Hansen et al. 2005; Hulston et al. 2010) giving rise to the expression “train low–compete high”. However, it remains unclear whether the mechanism for the enhanced training response is related to exercise with low muscle glycogen or to other metabolic or exercise-related factors.
The initial study within this area used an experimental model where subjects trained every day with one leg and twice every second day with the other leg. Muscle glycogen was reduced during the second bout of exercise in the leg training twice every second day and after 10 weeks of training this leg had both greater citrate synthase (CS) activity and endurance performance (one leg knee extension exercise, 20 vs. 12 min) compared with the leg that trained once daily (Hansen et al. 2005). Following studies, that used a whole body training approach, confirmed that mitochondrial markers, such as CS (Yeo et al. 2008) and succinate dehydrogenase (Morton et al. 2009) are induced to a greater extent when training twice every second day. The difference in glycogen between the once-per-day and twice-every-second day groups were, however, relatively small (Morton et al. 2009; Yeo et al. 2008) and it remains unclear if the observed increase in mitochondrial biogenesis is related to exercise with low muscle glycogen or to other factors related to the timing of exercise sessions.
Understanding of the molecular signaling involved in the muscle adaptive response has increased considerably during the last decade. Peroxisome proliferator-activated receptor-γ coactivator-1 (PGC-1α) is considered to be the master regulator of mitochondrial gene expression (Lin et al. 2005). PGC-1α is a transcriptional coactivator that activates numerous mitochondrial transcription factors such as the nuclear respiratory factors (NRF-1 and -2) and the mitochondrial transcription factor A (Tfam) (Gleyzer et al. 2005; Jager et al. 2007). PGC-1α is also involved in the regulation of fuel selection and can enhance fat metabolism by inducing the expression of pyruvate dehydrogenase kinase, isozyme 4 (PDK4) (Olesen et al. 2010). Other potential genes involved in the regulation of mitochondrial biogenesis are PGC-1-related coactivator (PRC), peroxisome proliferator-activated receptor δ (PPARδ) and the cytochrome c oxidase subunits (COX I–IV). AMP-activated protein kinase (AMPK) and p38 mitogen-activated protein kinases (MAPK) are up-stream proteins that have been identified as major regulators of PGC-1α and mitochondrial biogenesis. Recent studies have also associated reactive oxygen species (ROS) with mitochondrial biogenesis and increased PGC-1α expression (Kang et al. 2009; Powers et al. 2011), possibly mediated by AMPK activation (Irrcher et al. 2009; Katz 2007).
Several studies have shown that restricted CHO supply affects the acute molecular response to exercise. In one study restricted CHO intake post-exercise prolonged the expression of PGC-1α and other genes regulating mitochondrial biogenesis (Pilegaard et al. 2005) and in another study, where exercise was performed with reduced muscle glycogen content, there was an increased expression of genes related to lipid metabolism (Pilegaard et al. 2002). Restricted CHO availability during or after exercise has also been shown to augment phosphorylation of (i.e. activate) MAPK (Cochran et al. 2010) and AMPK (Yeo et al. 2010). Although these studies suggest that the signaling response to exercise is affected by CHO supply, it remains unclear whether exercise in a glycogen-depleted state can enhance the adaptive signaling response for mitochondrial biogenesis.
The purpose of the present investigation was twofold: (1) to determine if exercise in a glycogen-depleted state enhances expression of PGC-1α and other genes related to mitochondrial biogenesis and CHO metabolism, and (2) to investigate the role of oxidative stress and/or other potential signaling pathways. We hypothesized that low glycogen exercise would enhance the expression of genes regulating mitochondrial biogenesis and that this effect is mediated in part by increased ROS production.
Materials and methods
Ten highly trained male cyclists volunteered to participate in the study. They were all competing at the national level or had been competing at the national elite level during the preceding years in road or mountain biking. Average [mean ± standard error (SE)] age, body weight, height, and VO2max were 27.8 ± 1.6 years, 74.7 ± 2.0 kg, 183 ± 2 cm, and 4.9 ± 0.1 l/min or 65.4 ± 0.9 ml/kg/min. Subjects were informed about the possible risks and discomforts involved in the experiment prior to giving their written consent to participate in the study. The study design was approved by the Regional Ethics Committee of Stockholm, Sweden.
Preliminary testing was performed at least 1 week before the first trial with a Monark 839E ergometer (Monark Exercise, Varberg, Sweden). The seat and handlebar height were adjusted to fit each subject and were maintained during all the following experimental sessions. VO2max was determined with a standardized two stage incremental exercise protocol (Wang et al. 2009). The first part (4 min exercise at 5 submaximal intensities) was used to establish the relation between VO2 and work rate (W) and to get a rough estimate of the work rate corresponding to VO2max. After 4 min active rest, the work rate was increased rapidly until voluntary exhaustion with a protocol designed to elicit VO2max after 7–8 min. VO2max was defined as the highest recorded oxygen uptake during 60 consecutive seconds.
Subjects recorded their food intake during the 24-h period preceding the first experiment and were instructed to duplicate this prior to the second experiment. During and after the glycogen depletion exercise on day 1 and the following test exercise on day 2, subjects either consumed a high CHO (NG) or low CHO (LG) diet as shown in Fig. 1. The NG diet included two high CHO meals [dinner (pasta with meat sauce and lemonade): 1.83 g CHO, 0.53 g protein and 0.14 g fat/kg body weight (bw); breakfast (oat meal and orange juice): 1.54 g CHO, 0.31 g protein and 0.12 g fat/kg bw] and eight high CHO beverages [50/50 % maltodextrin-dextrose powder (Carbo 136, Dalblads, Sweden) dissolved in water: 1.0 g CHO/kg bw]. A banana was served together with beverage nr. 3, 5, 7 and 8 adding an additional of 0.31 g CHO, 0.01 g protein and 0.01 g fat/kg bw. The NG diet provided a total of 12.6 g CHO, 0.9 g protein and 0.3 g fat/kg bw (approximately 57 kcal/kg bw ~4,275 kcal). The LG diet included two low CHO meals [dinner and breakfast (egg and bacon): <0.02 g CHO, 0.6 g protein and 0.8 g fat/kg bw] and provided a total of <0.04 g CHO, 1.2 g protein and 1.6 g fat/kg bw (approximately 19 kcal/kg bw ~1,425 kcal). The energy content of the two meals was similar in NG and LG. NG provided 88 % of total energy intake from CHO, 6 % from protein and 6 % from fat while LG provided less than 1 % of total energy intake from CHO, 22 % from protein, and 77 % from fat. Water was consumed ad libitum during the exercise sessions in the first trial and the same volume was consumed during the second trial.
Analysis of blood samples
Blood (4 ml) was sampled from an antecubital vein and centrifuged at 1,500 g at 4 °C for 10 min. Plasma was stored at −20 °C for later analysis of free fatty acids (FFA) and glucose. A commercially available colorimetric enzymatic procedure (NEFA C test kit; Wako Chemicals GmbH, Neuss, Germany) was used for determining plasma FFA concentration. Blood samples were analyzed for lactate and glucose concentration with an automated analyzer (Biosen 5140, EKF Diagnostics, Barleben, Germany).
Muscle samples were obtained from the middle portion of the vastus lateralis muscle through an incision made through the skin and fascia at one-third the distance between the patella and anterior superior iliac spine, using the percutaneous needle biopsy technique with suction (Bergstrom 1975). Muscle samples were separated into two: one part for mitochondrial respiration analysis and the other rapidly frozen in liquid nitrogen and stored at −80 °C. Muscle biopsy samples contain a variable amount of non-muscle constituents (connective tissue, blood and fat), which would add variability in the reference base used for glycogen (muscle weight). Presence of blood and fat may also interfere with the biochemical analysis e.g. glutathione status. The frozen samples were therefore freeze-dried, powdered, dissected free of blood, fat and connective tissue, and stored at −80 °C for later determination of glycogen and mRNA content, as well as protein phosphorylation levels and glutathione status.
Glycogen and mRNA analysis
Details of primers used for RT-qPCR
General description of protein
Transcriptional coactivator involved in mitochondrial biogenesis
Transcriptional coactivator involved in mitochondrial biogenesis
Transcription factor involved in metabolism
Promotes lipid oxidation by inhibiting pyruvate dehydrogenase
Subunit of a transmembrane protein in the electron transport chain
Transcription factor involved in mitochondrial biogenesis
Transcription factor involved in mitochondrial biogenesis
NAD-dependent deacetylase that promotes the activation of transcription factors such as PGC-1α
Promotes the formation of citrate from acetyl coenzyme A and oxaloacetat in the citric acid cycle
Promotes the formation of 1,3-bisphosphoglycerate from glyceraldehyde 3-phosphate in the glycolysis pathway
Mitochondrial respiration and ROS generation
Mitochondrial respiration and ROS emission were measured in permeabilized muscle fiber bundles. Permeabilization was achieved by adding the muscle sample (10–25 mg wet weight) into ice-cold permeabilization solution (in mM): CaK2EGTA (2.8), K2EGTA (7.2), Na2ATP (5.8), MgCl2 (6.6), taurine (20), Na2phosphocreatine (15), imidazole (20), dithiothreitol (0.5) and MES (50). The pH was adjusted to 7.1. The specimen was split into 2–5 mg fiber bundles and each bundle was mechanically separated using surgical needles into a network formation to expose fiber membranes to the surrounding medium. The bundles were incubated with saponin (50 μg/ml), washed twice, and put in storage medium (in mM): EGTA (0.5), MgCl2 (3), K-lactobionate (60), taurine (20), KH2PO4 (10), HEPES (20), sucrose (110) and bovine serum albumin (BSA 1 g/l), adjusted to pH 7.1. Mitochondrial respiration was measured with a Clark-type electrode (Hansatech instruments, Kings Lynn, England) in a water-jacketed glass chamber at 25 °C. Permeabilized muscle fiber bundles (n = 8) were added to the storage medium supplemented with benzyltoluene sulfonamide (45 μM) to prevent fiber contraction. The oxygen consumption was measured after sequential additions of: octanoyl-carnitine (1.5 mM), ADP (5 mM), pyruvate (20 mM), glutamate (5 mM), succinate (5 mM), and cytochrome c (10 μM). The rate of mitochondrial H2O2 production was measured with Amplex red (Invitrogen, Eugene, OR, USA), which, in the presence of peroxidase enzyme, reacts with H2O2 and produces the red fluorescent compound Resorufin. Permeabilized fiber bundles (n = 8) were added to the measuring medium (in mM): mannitol (225), sucrose (75), Tris-base (10), K2HPO4 (10), EDTA (0.1), MgCl2 (0.08), BSA (2 g/l), horseradish peroxidase (13.5 U/ml), benzyltoluene sulfonamide (45 μM) and superoxide dismutase (SOD; 45 U/ml) adjusted to pH 7.1 and kept at 30 °C. The change in fluorescence was recorded on a Hitachi f-2500 fluorescence spectrophotometer equipped with a magnetic stirrer (Tokyo, Japan) after subsequent additions of: octanoyl-carnitine (1.5 mM), pyruvate (5 mM), succinate (5 mM) and rotenone (0.5 μM). Due to limited material in some muscle samples, mitochondrial respiration and H2O2 production analysis was only performed in eight of the ten subjects.
Western immunoblot analysis
Western blot analysis was performed in freeze-dried muscle tissue. The samples were homogenized using glass homogenizers in ice-cold buffer (80 μl/mg tissue; in mM): HEPES (2), EDTA (1), EGTA (5), MgCl2 (10), β-glycerophosphate (50), Triton X-100 (1 %), Na3VO4 (1), dithiothreitol (2), leupeptin (20 μg/ml), aprotinin (50 μg/ml), phosphatase inhibitor cocktail (1 %; Sigma, St Louis, MO, USA), PMSF (40 μg/μl). The homogenate was centrifuged at 10,000 g for 10 min to pellet the insoluble debris and the supernatant was stored at −80 °C. The protein concentration of the supernatant was determined with the bicinchoninic acid assay (Pierce Biotechnology, Rockford, IL, USA) by measuring the absorbance at 560 nm with a Tecan infinite F200 pro plate reader (Männedorf, Switzerland). The samples were diluted with Laemmli sample buffer (Bio-Rad, Richmond, CA, USA) and homogenizing buffer (1:1) to 1.5 μg/μl final protein concentration and heated to 95 °C for 5 min to denature proteins. The diluted samples were stored at −20 °C. The proteins in the diluted samples were separated by SDS-PAGE (Criterion cell gradient gels, Bio-Rad) for 2 h at 200 V on ice and then transferred to polyvinylidene fluoride membranes (Bio-Rad) for 3 h at 300 mA on ice. The amount of protein loaded to the membranes (30 μg) was kept constant for all samples and was verified by staining with MemCode Reversible Protein Stain Kit (ThermoScientific, Rockford, IL, USA). After blocking for 1 h at room temperature in 5 % non-fat milk, the membranes were incubated overnight with primary antibodies: Malondialdehyde (MDA; 1:500; Nordic BioSite, Täby, Sweden), p-AMPKThr172 (1:1,000), p-acetyl-CoA carboxylase (ACCS79; 1:1,000) p-pMAPKTT180/Y182 (1:1000), and β-tubulin (1:1000, Cell Signalling, Beverly, MA, USA). This was followed by 1 h incubation with anti-rabbit HRP (1:10,000) as secondary antibody. The antibodies were visualized by chemiluminescent detection on a Molecular Imager ChemiDoc XRS system and the bands were analyzed using Quantity One version 4.6.3 software (Bio-Rad). Evidence of the specificity of the primary antibodies used in this study has been provided by the producer (Cell Signalling, Beverly, MA, USA).
Glutathione in reduced (GSH) and oxidized (GSSG) form were determined with the Bioxytech GSH/GSSG-412 assay (Oxis Research, Foster City, CA, USA). The freeze-dried muscle tissue was divided into two aliquots and homogenized using glass homogenizers in ice-cold buffer (80 μl/mg) containing (in mM): Tris buffer (10), EDTA (1), EGTA (1), Na-orthovanadate (2), Na-pyrophosphate (2), NaF (5) and protease inhibitor cocktail, with or without 1-methyl-2-vinylpyridinium trifluoromethanesulfonate (M2VP), a scavenger of reduced GSH. Following 5 min incubation with 1 % Triton X-100 (room temperature for M2VP aliquot and ice cold for the M2VP free aliquot), 5 % metaphosphoric acid was added and the aliquots were centrifuged at 13,000 g for 10 min. The supernatant (5 μl) was diluted 1:20 with homogenization buffer and 100 μl chromogen, glutathione reductase and NADPH was added, followed by spectrophotometric measurement of the change in absorbance at 412 nm over 3 min. Reduced GSH was calculated from the measurements of total GSH (without M2VP in homogenate) and GSSG (with M2VP in homogenate). Due to lack of muscle material, GSSG and GSH analyses were performed in only five of the ten subjects. GSSG values are expressed in GSH units, i.e. 1 GSSG = 2 GSH.
All data are expressed as the mean ± SE and analyzed by two-way repeated measures ANOVA (time and dietary intervention). When a significant primary effect or interaction was observed, post hoc analyses (Fisher LSD) were performed to locate the differences. Statistical significance was accepted at a P level less than 0.05.
Physiological and metabolic responses to exercise
To deplete muscle glycogen stores, subjects performed an exercise session 14 h prior to the test exercise. The average power output of the depletion exercise was 273 ± 23 W (74.3 ± 3.1 % VO2max) and the duration was 122 min. Corresponding values of test exercise were 226 ± 20 W (63.6 ± 4.3 % VO2max) and 60 min. Power output was adjusted during the second session to match the power and duration of the first session. However, two subjects with NG in the first session were not able to repeat test exercise in the second session with LG, and the work rate was therefore reduced.
Effect of exercise and diet on muscle glycogen, plasma FFA, glucose and insulin
623 ± 57
166 ± 21**,##
130 ± 17**,##
645 ± 42
478 ± 33**
477 ± 31**
0.31 ± 0.07
0.66 ± 0.05**,##
1.21 ± 0.18**,##,††
0.23 ± 0.04
0.10 ± 0.02
0.03 ± 0.01
6.0 ± 0.4
5.0 ± 0.1**
4.3 ± 0.2**
5.8 ± 0.3
5.1 ± 0.1
5.0 ± 0.3*
13.4 ± 3.3
5.3 ± 0.7*,#
1.4 ± 0.5**,##
11.3 ± 2.3
13.0 ± 2.1
18.2 ± 3.8*
Gene expression and protein phosphorylation
Expression of genes related to mitochondrial biogenesis
2.80 ± 0.29
3.09 ± 0.28
3.24 ± 0.35
2.69 ± 0.39
3.39 ± 0.33
2.95 ± 0.30
0.93 ± 0.24
0.88 ± 0.24
1.00 ± 0.24
0.88 ± 0.21
0.80 ± 0.19
1.02 ± 0.22
1.86 ± 0.35
2.27 ± 0.49
1.75 ± 0.27
1.78 ± 0.28
1.96 ± 0.33
1.93 ± 0.36
1.47 ± 0.43
1.13 ± 0.24
1.03 ± 0.20
1.07 ± 0.30
1.06 ± 0.26
1.26 ± 0.26
Phosphorylation of proteins involved in upstream signaling for mitochondrial biogenesis
0.81 ± 0.11
0.82 ± 0.16
0.70 ± 0.17
1.22 ± 0.17#
1.06 ± 0.17
0.99 ± 0.19
1.04 ± 0.25
1.33 ± 0.26
0.91 ± 0.07
1.02 ± 0.07
1.12 ± 0.07
1.36 ± 0.10
Mitochondrial respiration and markers for oxidative stress
By combining exercise with dietary intervention, we produced two conditions with substantial differences in muscle glycogen prior to a standardized test exercise. The major new finding in this study was that exercise with low muscle glycogen enhanced the expression of genetic markers of mitochondrial biogenesis (PGC-1α and COX I). Only one previous study used an experimental design similar to the present study to investigate the effects of CHO restriction on the acute regulation of mitochondrial biogenesis (Cochran et al. 2010). However, reduced CHO availability had no effect on PGC-1α or COX IV expression in that study. This discrepancy can be explained by differences in the experimental protocols. In contrast to the present study where muscle glycogen was threefold higher for NG than for LG, muscle glycogen was similar between conditions in the study by Cochran et al. (2010), most likely due to the short recovery period (3 vs. 14 h in the present study). Secondly, muscle biopsies were taken immediately after the test exercise (Cochran et al. 2010) whereas muscle biopsies in the present study were taken 3 h after the test exercise. It is well established that the exercise-induced increase of PGC-1α mRNA occurs with a delay of several hours, and differences in expression are therefore not expected to occur that early in the recovery period.
Previous studies have shown that the exercise-induced increase in PGC-1α mRNA is not affected by CHO restriction during the first 2–5 h of recovery (Cluberton et al. 2005; Cochran et al. 2010; Mathai et al. 2008; Pilegaard et al. 2005). The augmented PGC-1α expression observed 3 h after the test exercise in LG (Fig. 2) can therefore not be explained by CHO restriction during the recovery period, but most likely by exercise with low glycogen. Muscle glycogen was reduced prior to test exercise both during LG (from 623 to 166 mmol/kg dw) and NG (from 645 to 478 mmol/kg dw), but the increase in PGC-1α mRNA after test exercise was more than fourfold higher in LG than after NG. This supports the idea that the activation of metabolic genes by exercise might be sensitive to a critically low “threshold” level of glycogen (Pilegaard et al. 2002) and that this threshold is somewhere between 478 and 133 mmol/kg dw. Further evidence for this idea is found in the study by Mathai et al. (2008) where a large glycogen reduction during exercise was associated with a large increase in PGC-1α protein abundance. An interesting finding in the present study was that muscle glycogen did not decrease further during the test exercise, probably due to the low exercise intensity (64 % of VO2max) and the high aerobic training status of the subjects. The stimulus for augmented PGC-1α expression in LG is thus not exercise leading to glycogen depletion but rather exercise with low muscle glycogen stores. Furthermore, the finding that PGC-1α mRNA was not elevated 14 h after depletion exercise despite markedly reduced muscle glycogen demonstrates that low muscle glycogen per se is not sufficient to enhance the signaling pathway.
Although the magnitude of exercise-induced transcription seems to be independent of dietary CHO supply, there is evidence that CHO restriction can prolong mRNA expression of specific genes. For example, PGC-1α mRNA levels are elevated for at least 8 h post-exercise when CHO intake is restricted but reversed to basal levels during conditions with CHO intake (Pilegaard et al. 2005). The low level of PGC-1α mRNA 14 h after depletion exercise (Fig. 2) suggests that the effect of exercise on PGC-1α expression is reversed somewhere between 8 and 14 h post-exercise, even during conditions of CHO restriction. PDK4 is also affected by CHO availability but somewhat different than PGC-1α. It has been shown that PDK4 expression is blunted by exogenous CHO supply already 4 h post-exercise (Cluberton et al. 2005). We confirmed this finding by showing that PDK4 expression remained unchanged in NG 3 h post-test exercise. We also showed that the increased PDK4 mRNA in LG was independent of exercise, which indicates that the gene is controlled by substrate availability rather than exercise per se.
To the best of our knowledge, this is the first study to measure Tfam and PRC expression after exercise with reduced muscle glycogen. Tfam mRNA was elevated 14 h after the depletion exercise and 3 h after the test exercise, while PRC mRNA was only elevated after the test exercise. The present study confirms previous findings that both Tfam and PRC expression are up-regulated by exercise (Pilegaard et al. 2003; Psilander et al. 2010). However, there was no difference in Tfam and PRC expression between LG and NG. Tfam is regulated by PGC-1α, and its expression might peak at a later time point than PGC-1α. Therefore, it is possible that a difference in Tfam expression between LG and NG occurs more than 3 h after the test exercise. PRC, on the other hand, belongs to the same family of transcription factors as PGC-1α and, therefore, should have a similar expression pattern. The data therefore suggests that PRC expression is independent of glycogen status.
Most genes activated downstream of PGC-1α were not affected by exercise in the present study (Table 3). The mRNA expression curves for these genes are not well examined but studies indicate that they peak later than 3 h after exercise (Leick et al. 2010; Norrbom et al. 2004; Pilegaard et al. 2003).
The mechanisms by which exercise with low muscle glycogen stimulates markers of mitochondrial biogenesis may relate to increased energetic stress, with reduced levels of high energy phosphates and elevated AMP (as indicated by the increased rate of AMP deamination) (Broberg and Sahlin 1989). Increased AMP/ATP, as well as reduced creatine phosphate content, activates AMPK, which has several metabolic functions including activation of PGC-1α (Jager et al. 2007). The phosphorylation of AMPK and its downstream target ACC was not altered 3 h post-exercise (Table 4), but it seems likely that any potential effect of exercise was reversed at this time. Studies in humans have shown that exercise with low initial muscle glycogen results in greater activation (i.e. phosphorylation) of AMPK compared with exercise with normal or elevated initial glycogen (Wojtaszewski et al. 2003; Yeo et al. 2010) but that AMPK activity is back to basal levels 2–3 h post-exercise (Wang et al. 2011; Wojtaszewski et al. 2003). Previous studies have also shown that ACC activity returns to baseline within 3 h after exercise (Wang et al. 2011). Phosphorylation of MAPK was not changed in this study, but, again, the timing of the muscle biopsies was not optimal to detect possible changes for this protein.
The total caloric intake was lower in LG (1,425 kcal) than in NG (4,275 kcal) and might be a confounding factor. Some (Civitarese et al. 2007; Finley et al. 2012) but not all (Hancock et al. 2011) studies have shown that mitochondrial biogenesis and PGC-1α gene expression are elevated after long-term calorie restriction but there is no evidence that short-term calorie restriction (<24 h) affects PGC-1α expression (Tsintzas et al. 2006). The subjects in the present study were only partially calorie restricted and the duration was less than 21 h and it therefore seems unlikely that differences in caloric intake would have influenced the observed results.
Insulin levels were higher in NG compared with LG (Table 2) and studies on insulin resistant subjects indicate that there might be a link between insulin and PGC-1α expression (Lira et al. 2010). However, differences in insulin levels does not influence PGC-1α expression 2–5 h after exercise (Cluberton et al. 2005; Pilegaard et al. 2005) and a direct link for how insulin can regulate PGC-1α expression and mitochondrial biogenesis has to our knowledge not been established.
FFA levels were elevated during LG (Table 2) and it has been suggested that FFA are involved in the regulation of mitochondrial biogenesis (Holloszy 2008). FFA regulates the activity of the peroxisome proliferator activator receptor (PPAR) family of transcription factors. Raising FFA levels enhances mitochondrial biogenesis in mouse muscle by activating PPARβ/δ (Garcia-Roves et al. 2007). PPARδ interacts with AMPK in a transcriptional complex, and this complex enhances the stimulating effect of AMPK on PGC-1α expression (Narkar et al. 2008). However, human studies do not support these observations. In fact, in humans, elevated FFA levels are not associated with the acute activation of genes regulating mitochondrial biogenesis (Russell et al. 2005; Watt et al. 2004), and one study even showed that FFA suppressed PPAR and PGC-1α expression (Hoeks et al. 2006). PPARδ expression did not change in this study, and it is unlikely that the increased plasma FFA during LG can trigger the increased PGC-1α transcription.
We hypothesized that low glycogen exercise should increase ROS generation and elicit increased PGC-1α expression. In contrast, both mitochondrial ROS formation and the ratio of oxidized to reduced glutathione (GSSG/GSH) decreased 3 h post-exercise, with no significant difference between groups. The observed trend towards reduced oxidative stress is consistent with the findings of decreased mitochondrial ROS production in rats 48 h following an acute downhill running exercise (Molnar et al. 2006) and the findings of attenuated ROS generation during the later stage of exercise correlating with increased UCP3 protein levels (Jiang et al. 2009). Considering the high reactivity of ROS and the instability of redox balance, the redox status observed 3 h post-exercise in this study is not necessarily representative of the conditions during or immediately following exercise. Increased free radical formation during exercise can trigger the induction of endogenous antioxidant systems like SOD, catalase, glutathione reductase and glutathione peroxidase (Ji 1993), which can scavenge H2O2 and thus reduce GSSG. Although the present findings of reduced oxidative stress 3 h post-exercise do not exclude increased ROS generation during exercise, the lack of a significant difference between LG and NG suggests that the increased PGC-1α expression after glycogen-depleted exercise is not caused by ROS. The lack of changes in muscle levels of MDA, a marker for lipid oxidation, reinforces this conclusion.
Physiological and practical implications
High intensity exercise is a strong stimulator of mitochondrial biogenesis (Little et al. 2010; Psilander et al. 2010) and intensity seems to be more important than duration for the acute up-regulation of mitochondrial markers (Egan et al. 2010; Nordsborg et al. 2010). Exercise with low muscle glycogen content is not possible to perform at high intensity and might therefore limit the use of such an exercise protocol. However, despite the fact that subjects in this study cycled at a moderate intensity during the test exercise (approximately 64 % VO2max), LG induced a more pronounced increase in PGC-1α expression (eightfold) than studies using high intensity protocols (two- to sevenfold) (Gibala et al. 2009; Nordsborg et al. 2010; Psilander et al. 2010). The present study show that very low glycogen levels are needed to obtain a strong PGC-1α response and exercising with profoundly reduced glycogen levels might therefore be a beneficial training strategy for well-trained cyclists to promote muscle oxidative potential. Longitudinal studies examining protein levels and performance are required to confirm this conclusion.
The study was supported by grants from the Swedish National Centre for Research in Sports, the Swedish Research Council and the Swedish School of Sport and Health Sciences, Stockholm, Sweden. We thank all the participants for their time and effort. We also gratefully acknowledge Marjan Pontén for her excellent technical assistance. No conflicts of interest, financial or otherwise, are declared by the authors.