European Journal of Applied Physiology

, Volume 113, Issue 4, pp 951–963

Exercise with low glycogen increases PGC-1α gene expression in human skeletal muscle

Authors

    • The Åstrand Laboratory of Work PhysiologyGIH, The Swedish School of Sport and Health Sciences
    • Department of Physiology and PharmacologyKarolinska Institutet
  • Per Frank
    • The Åstrand Laboratory of Work PhysiologyGIH, The Swedish School of Sport and Health Sciences
    • Department of Physiology and PharmacologyKarolinska Institutet
  • Mikael Flockhart
    • The Åstrand Laboratory of Work PhysiologyGIH, The Swedish School of Sport and Health Sciences
  • Kent Sahlin
    • The Åstrand Laboratory of Work PhysiologyGIH, The Swedish School of Sport and Health Sciences
    • Department of Physiology and PharmacologyKarolinska Institutet
Original Article

DOI: 10.1007/s00421-012-2504-8

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

Abstract

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.

Keywords

Train lowCarbohydrate restrictionGene expressionPGC-1αOxidative stress

Introduction

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

Subjects

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

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.

Experimental protocol

Subjects participated in two experimental sessions separated by at least 1 week in a crossover design with randomized order (Fig. 1). In one of the sessions, subjects had a high CHO (NG) diet and in the other a low CHO (LG) diet (see below for details). Both sessions included two exercise tests separated by about 14 h. The purpose of the first exercise was to deplete muscle glycogen (depletion exercise) and the second exercise to test the influence of low muscle glycogen on the signaling response (test exercise). Subjects were instructed to refrain from exhaustive exercise and alcohol during the 2 days prior to the experiment. Subjects arrived to the laboratory in the afternoon (approximately 15:00) and a blood sample was taken from an arm vein and a muscle biopsy sample was obtained from the middle portion of the vastus lateralis muscle of one leg. The depletion exercise started with 45 min cycling at 75 % VO2max followed by eight intervals at 88 % VO2max (duty cycle 4 min exercise and 4 min active rest at 100 W), and ended with an additional 45 min at 70 % VO2max. The test exercise was performed the following morning, about 14 h after the depletion exercise, and included six intervals of 10 min cycling with 4 min active rest (100 W) between intervals. The first interval was at 72.5 % VO2max after which the work rate was reduced 2.5 % during each interval (last interval 60 % VO2max). Capillary blood samples were collected from fingertips before test exercise and during the last seconds of intervals 2, 4, and 6 and were analyzed for lactate and glucose. Venous blood samples and muscle biopsies were obtained approximately 15 min before and 3 h after the test exercise.
https://static-content.springer.com/image/art%3A10.1007%2Fs00421-012-2504-8/MediaObjects/421_2012_2504_Fig1_HTML.gif
Fig. 1

Schematic illustration of the experimental design. B beverages containing CHO (NG normal glycogen) or only water (LG low glycogen). Meals contained either high (NG) or low CHO (LG). Beverages and meals post-exercise were separated by ~1 h intervals and the beverages served during exercise were consumed ad libitum. Muscle biopsies and venous blood samples were obtained approximately 15 min before the depletion (S1) and test exercise (S2) as well as 3 h after the test exercise (S3). See “Materials and methods” for more details

Dietary intervention

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 biopsies

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

Glycogen was analyzed in 1–2 mg freeze-dried muscle according to the method previously described by Harris et al. (1974), which includes enzymatic hydrolysis of glycogen followed by enzymatic analysis of glucose. For mRNA analysis, total RNA was extracted from 2–5 mg freeze-dried muscle tissue using a Polytron PT 1600 E homogenizer (Kinematica, Lucerne, Switzerland) and a PureZOL RNA isolation kit according to the manufacturer’s instructions (Bio-Rad Laboratories AB, Sundbyberg, Sweden). The yield and quality of extracted RNA were estimated by spectrometry and micro-gel electrophoresis (Experion, Bio-Rad). The 260/280 absorbance ratios were within 1.9–2.1 (in Tris–EDTA buffer, pH 8.0) and the RNA quality indicator values (RQI) were greater than 0.7. RNA (1 μg) was reverse transcribed to cDNA (20 μl) using the iScript cDNA synthesis kit (Bio-Rad). Real-time RT-PCR was performed with an iCycler (Bio-Rad) in a mixture containing 12.5 μl 2× SYBR Green Supermix (Bio-Rad), 0.5 μl of both the forward and reverse primers (final concentrations 10 μM), and 11.5 μl template cDNA. All reactions were performed in triplicate with GAPDH as reference gene (Livak and Schmittgen 2001). The nucleotide sequences of the primers are presented in Table 1. The melting curves of the PCR product showed only one peak, demonstrating specificity of the primers and absence of contamination. The cDNA concentration, annealing temperature and thermocycling conditions were optimized for each primer pair, and assay sensitivity was high for all PCR products (RSq >0.99, and efficiency >90 %). The comparative critical threshold (CT) method could therefore be used to calculate changes in mRNA levels.
Table 1

Details of primers used for RT-qPCR

Gene

General description of protein

Forward

Reverse

Genebank

PGC-1α

Transcriptional coactivator involved in mitochondrial biogenesis

CAAGCCAAACCAACAACTTTATCTCT

CACACTTAAGGTGCGTTCAATAGTC

NM_013261

PRC

Transcriptional coactivator involved in mitochondrial biogenesis

GCTGAAACAGAGGTTCTCCG

AAAGTCTTCCCGGTTGGAGT

AF325193

PPARδ

Transcription factor involved in metabolism

ATGGAGCAGCCACAGGAGGAAGCC

GCATGAGGCCCCGTCACAGC

NM_006238

PDK4

Promotes lipid oxidation by inhibiting pyruvate dehydrogenase

TCCACTGCACCAACGCCT

TGGCAAGCCGTAACCAAAA

NM_002612

COX I

Subunit of a transmembrane protein in the electron transport chain

CTATACCTATTATTCGGCGCATGA

CAGCTCGGCTCGAATAAGGA

NC_012920

Tfam

Transcription factor involved in mitochondrial biogenesis

AGATTCCAAGAAGCTAAGGGTGATT

TTTCAGAGTCAGACAGATTTTTCCA

NM_003201

NRF2

Transcription factor involved in mitochondrial biogenesis

AAATTGAGATTGATGGAACAGAGAA

TATGGCCTGGCTTACACATTCA

EU159453

Sirt1

NAD-dependent deacetylase that promotes the activation of transcription factors such as PGC-1α

TACGACGAAGACGACGACGA

AAGGTTATCTCGGTACCCAATCG

NM_012238

CS

Promotes the formation of citrate from acetyl coenzyme A and oxaloacetat in the citric acid cycle

GACTACATCTGGAACACACTCAACTCA

CGCGGATCAGTCTTCCTTAGTAC

NM_004077

GAPDH

Promotes the formation of 1,3-bisphosphoglycerate from glyceraldehyde 3-phosphate in the glycolysis pathway

AACCTGCCAAATATGATGAC

TCATACCAGGAAATGAGCTT

NM_002046

PGC-1α peroxisome proliferative-activated receptor-γ coactivator 1α, PRC PGC-1-related coactivator, PPARδ peroxisome proliferator-activated receptors δ, PDK4 pyruvate dehydrogenase kinase isozyme 4, COX I cytochrome c oxidase subunit I, Tfam mitochondrial transcription factor A, NRF2 nuclear respiratory factor 2, Sirt1 silent mating-type information regulator 2 homolog 1, CS citrate synthase, GAPDH glyceraldehyde 3-phosphate dehydrogenase

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 analysis

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.

Statistical analysis

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.

Results

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.

Muscle glycogen content was reduced 14 h after the depletion exercise to 27 % (LG) and 74 % (NG) of the initial level, respectively (P < 0.01, LG vs. NG), but was not further reduced by the subsequent test exercise (Table 2). FFA, measured in blood samples obtained ~15 min before the muscle biopsies, were unchanged in NG but increased in LG (P < 0.01 LG vs. NG, Table 2). In the same samples, blood glucose was slightly reduced in both NG and LG, with no difference between conditions, and insulin was reduced in LG and slightly elevated in NG (P < 0.01 LG vs. NG, Table 2). Lactate, measured in capillary blood samples before, during and immediately after test exercise, remained at a low level during both NG (<2.7 mmol/l) and LG (<1.4 mmol/l). Glucose, measured in the same samples, decreased immediately after test exercise in both NG (from 5.0 ± 0.2 to 4.3 ± 0.2 mmol/l) and LG (from 4.1 ± 0.1 to 2.5 ± 0.2 mmol/l) and was significantly higher in NG vs. LG at all time points (P < 0.01).
Table 2

Effect of exercise and diet on muscle glycogen, plasma FFA, glucose and insulin

 

Pre-depletion exercise

Pre-test exercise

Post-test exercise

Gly

 LG

623 ± 57

166 ± 21**,##

130 ± 17**,##

 NG

645 ± 42

478 ± 33**

477 ± 31**

FFA

 LG

0.31 ± 0.07

0.66 ± 0.05**,##

1.21 ± 0.18**,##,††

 NG

0.23 ± 0.04

0.10 ± 0.02

0.03 ± 0.01

Glu

 LG

6.0 ± 0.4

5.0 ± 0.1**

4.3 ± 0.2**

 NG

5.8 ± 0.3

5.1 ± 0.1

5.0 ± 0.3*

Ins

 LG

13.4 ± 3.3

5.3 ± 0.7*,#

1.4 ± 0.5**,##

 NG

11.3 ± 2.3

13.0 ± 2.1

18.2 ± 3.8*

Muscle and blood samples were obtained before the depletion exercise on day 1 (pre-depletion exercise), before the test exercise on day 2 (pre-test exercise) and 3 h after the test exercise on day 2 (post-test exercise)

Gly muscle glycogen (mmol/kg dw), FFA venous plasma free fatty acids (mmol/l), Glu venous plasma glucose (mmol/l), Ins venues plasma insulin (mU/l), LG low glycogen, NG normal glycogen

Values are reported as mean ± SE from 10 subjects

* P < 0.05 and ** P < 0.01 versus pre-depletion exercise; †† P < 0.01 versus pre-test exercise; P < 0.05 and ## P < 0.01 LG versus NG

Gene expression and protein phosphorylation

The mRNA content of the master regulator of mitochondrial biogenesis (PGC-1α) was not changed 14 h after depletion exercise (pre-test exercise) but was significantly increased 3 h after the test exercise in both conditions (Fig. 2). The increase was, however, much more pronounced in LG than in NG (8.1-fold vs. 2.5-fold, P < 0.01). The mRNA content of two other regulators of mitochondrial biogenesis (PRC and Tfam) also increased significantly but with no difference between conditions (time-dependent effect, P < 0.01; Fig. 2). The mRNA content of genes for oxidative metabolism enzymes (PDK4 and COX I) only increased after LG with a significant difference between the two conditions (P < 0.01; Fig. 3). The mRNA content of CS, Sirt1, NRF1 and PPARδ did not change under any conditions (Table 3). In addition, phosphorylation of proteins involved in the upstream signaling pathways of mitochondrial biogenesis (p-AMPKThr172, p-p38MAPKT180/Y182) and the downstream target of AMPK (ACCS79) did not change significantly 3 h after test exercise in any of the conditions (Table 4; Fig. 4).
https://static-content.springer.com/image/art%3A10.1007%2Fs00421-012-2504-8/MediaObjects/421_2012_2504_Fig2_HTML.gif
Fig. 2

Effect of exercise on markers of mitochondrial biogenesis. Muscle samples were obtained before the depletion exercise on day 1 (pre-depletion exercise), before the test exercise on day 2 (pre-test exercise) and 3 h after the test exercise on day 2 (post-test exercise). Values are expressed in arbitrary units (AU) related to the reference gene GAPDH, and are reported as the mean ± SE, n = 10. For abbreviations of genes see Table 1 legend. LG low glycogen, NG normal glycogen. *P < 0.05 and **P < 0.01 vs. pre-depletion exercise; ##P < 0.01 LG versus NG; §§P < 0.01 versus pre-depletion exercise (time-dependent effect)

https://static-content.springer.com/image/art%3A10.1007%2Fs00421-012-2504-8/MediaObjects/421_2012_2504_Fig3_HTML.gif
Fig. 3

Effect of exercise on PDK4 and COX I mRNA levels. Muscle samples were obtained before the depletion exercise on day 1 (pre-depletion exercise), before the test exercise on day 2 (pre-test exercise) and 3 h after the test exercise on day 2 (post-test exercise). Values are expressed in arbitrary units (AU) related to the reference gene GAPDH, and are reported as the mean ± SE, n = 10. For abbreviations of genes see Table 1 legend. LG low glycogen, NG normal glycogen. *P < 0.05 and **P < 0.01 versus Pre-depletion exercise; ##P < 0.01 LG versus NG

Table 3

Expression of genes related to mitochondrial biogenesis

 

Pre-depletion exercise

Pre-test exercise

Post-test exercise

CS

 LG

2.80 ± 0.29

3.09 ± 0.28

3.24 ± 0.35

 NG

2.69 ± 0.39

3.39 ± 0.33

2.95 ± 0.30

Sirt1

 LG

0.93 ± 0.24

0.88 ± 0.24

1.00 ± 0.24

 NG

0.88 ± 0.21

0.80 ± 0.19

1.02 ± 0.22

NRF2

 LG

1.86 ± 0.35

2.27 ± 0.49

1.75 ± 0.27

 NG

1.78 ± 0.28

1.96 ± 0.33

1.93 ± 0.36

PPARδ

 LG

1.47 ± 0.43

1.13 ± 0.24

1.03 ± 0.20

 NG

1.07 ± 0.30

1.06 ± 0.26

1.26 ± 0.26

Values of mRNA are expressed in arbitrary units with GAPDH as the reference gene

Muscle samples were obtained before the depletion exercise on day 1 (pre-depletion exercise), before the test exercise on day 2 (pre-test exercise) and 3 h after the test exercise on day 2 (post-test exercise)

Values are reported as the mean ± SE, n = 10

For gene abbreviations see Table 1 legend

Table 4

Phosphorylation of proteins involved in upstream signaling for mitochondrial biogenesis

 

Pre-depletion exercise

Post-test exercise

p-AMPKThr 172

 LG

0.81 ± 0.11

0.82 ± 0.16

 NG

0.70 ± 0.17

1.22 ± 0.17#

p-ACCS79

 LG

1.06 ± 0.17

0.99 ± 0.19

 NG

1.04 ± 0.25

1.33 ± 0.26

p-p38 MAPKT180/Y182

 LG

0.91 ± 0.07

1.02 ± 0.07

 NG

1.12 ± 0.07

1.36 ± 0.10

Muscle samples were obtained before the depletion exercise on day 1 (pre-depletion exercise) and 3 h after the test exercise on day 2 (post-test exercise)

Values are expressed in arbitrary units relative to β-tubulin and are reported as mean ± SE (n = 10)

LG low glycogen, NG normal glycogen

#P = 0.058 LG versus NG

Mitochondrial respiration and markers for oxidative stress

Mitochondrial respiration, measured after sequential additions of ADP and substrates, was similar before and after exercise, without any difference between LG and NG (data not shown). Mitochondrial H2O2 production, measured with a cocktail of substrates (octanoyl-carnitine, pyruvate and succinate), tended to be reduced (P = 0.053), 3 h after the test exercise (Fig. 5). Glutathione status after test exercise also indicated reduced oxidative stress, as the GSSG/GSH ratio tended to be lower (P = 0.076; Fig. 5). There were no differences in mitochondrial H2O2 production and glutathione status between LG and NG. MDA, a marker for lipid peroxidation (expressed as arbitrary units relative to β-tubulin), was in the pre-depletion exercise: 0.17 ± 0.03 (LG) and 0.17 ± 0.02 (NG) and in the post-test exercise: 0.19 ± 0.03 (LG) and 0.18 ± 0.02 (NG). There were no differences between time points or conditions.
https://static-content.springer.com/image/art%3A10.1007%2Fs00421-012-2504-8/MediaObjects/421_2012_2504_Fig5_HTML.gif
Fig. 4

Representative western blots of proteins involved in upstream signaling for mitochondrial biogenesis

https://static-content.springer.com/image/art%3A10.1007%2Fs00421-012-2504-8/MediaObjects/421_2012_2504_Fig4_HTML.gif
Fig. 5

Effect of exercise on muscle parameters related to oxidative stress. Muscle samples were obtained before the depletion exercise on day 1 (pre-depletion exercise) and 3 h after the test exercise on day 2 (post-test exercise). Values are reported as the mean ± SE from 8 (mitochondrial H2O2 production) and 5 (GSSG/GSH ratio) subjects. LG low glycogen, NG normal glycogen. §Non-significant trend versus pre-depletion exercise (time-dependent effect); P = 0.053 (mitochondrial H2O2 production) and P = 0.076 (GSSG/GSH ratio)

Discussion

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.

Acknowledgments

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.

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© Springer-Verlag Berlin Heidelberg 2012