Article Title: Similar mitochondrial signaling responses to a single bout of continuous or small-

sided-games-based exercise in sedentary men.

Authors: Mendham, Amy E 1,3., Duffield, Rob 2., Coutts, Aaron J 2., Marino, Frank 3., Boyko,

Andriy 2., McAinch, Andrew J 4,5., Bishop, David J 5

Affiliation: 1 Division of Exercise Science and Sports Medicine, Department of Human Biology,

University of Cape Town, Cape Town, South Africa.

2 Sport and Exercise Discipline Group, UTS: Health, University of Technology

Sydney (UTS), Moore Park, NSW, Australia.

3 School of Exercise Science, Sport and health, Charles Sturt University, Bathurst,

NSW, Australia.

4 Centre for Chronic Diseases, College of Health and Biomedicine, Victoria

University, Melbourne, VIC, Australia.

5 Institute of Sport, Exercise and Active Living (ISEAL), Victoria University,

Melbourne, VIC, Australia.

Running title: Mitochondrial signaling in response to exercise.

Author contributions: Conception and design of research: Mendham, Duffield, Marino, Coutts; Performed

Experiments: Mendham, Duffield, Bishop, McAinch, Coutts, Boyko; Interpreted results of experiments:

Mendham, Duffield, Bishop, McAinch; Prepared figures: Mendham; Drafted and revised manuscript:

Mendham, Duffield, Bishop, McAinch, Coutts, Marino, Boyko; Approved final version of manuscript:

Mendham, Duffield, Bishop, McAinch, Coutts. Marino, Boyko.

Correspondence: Amy Mendham

Division of Exercise Science and Sports Medicine

Department of Human Biology, University of Cape Town

Boundary Road, Newlands, 7700,

Cape Town, South Africa

amy.mendham@uct.ac.za (Email)

+27 723 879 889 (Telephone)

1

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

ABSTRACT

Purpose: This study assessed the mitochondrial related signaling responses to a single bout of non-contact,

modified football (touch rugby), played as small-sided games (SSG), or cycling (CYC) exercise in sedentary,

obese, middle-aged men.

Method: In a randomized, cross-over design, nine middle-aged, sedentary, obese men completed two, 40-min

exercise conditions (CYC and SSG) separated by a 21-d recovery period. Heart rate (HR) and Ratings of

Perceived Exertion (RPE) were collected during each bout. Needle biopsy samples from the m. vastus lateralis

were collected at rest, 30 and 240min post-exercise for analysis of protein content and phosphorylation (PGC-

1α, SIRT1, p53, p53Ser15, AMPK, AMPKThr172, CAMKII, CAMKIIThr286, p38MAPK and p38MAPKThr180/Tyr182) and

mRNA expression (PGC-1α, p53, NRF1, NRF2, Tfam and cytochrome-c).

Results: A main effect of time effect for both conditions was evident for HR, RPE and blood lactate (P<0.05),

with no condition by time interaction (P>0.05). Both conditions increased PGC1-α protein and mRNA

expression at 240min (P<0.05). AMPKThr172 increased 30min post CYC (P<0.05), with no change in SSG

(P>0.05). CYC increased p53 protein content at 240min to a greater extent than SSG (P<0.05). mRNA

expression of NRF2 decreased in both conditions (P<0.05)No condition x time interactions were evident for

mRNA expression of Tfam, NRF1, cytochrome-c and p53.Conclusions: The similar PGC-1α response between

intensity-matched conditions suggests both conditions are of similar benefit for stimulating mitochondrial

biogenesis. Differences between conditions regarding fluctuation in exercise intensity and type of muscle

contraction may explain the increase of p53 and AMPK within CYC and not SSG (non-contact, modified

football).

New and Noteworthy: 75 words

Small-sided games is an effective alternative to traditional continuous exercise modes at stimulating intracellular

signalling pathways associated with mitochondrial biogenesis in obese, sedentary, middle-aged men. The similar

responses between conditions suggests the average exercise intensity, rather than the type of exercise, may be

more important for stimulating mitochondrial biogenesis in this population.

Key Words: Rugby, cycling, PGC-1α, AMPK

INTRODUCTION

2

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

Mitochondria are key components of skeletal muscles and provide the energy required for most cellular

activities. Mitochondria also appear important for health, with mitochondrial dysfunction being implicated in the

aetiology of sarcopenia and many age-related degenerative metabolic diseases in sedentary populations (32, 36).

Accordingly, exercise interventions that most appropriately target signaling pathways associated with

mitochondrial biogenesis may represent viable therapeutic interventions to counter abnormalities developed in

inactive and ageing muscle (5, 22)(Safdar, Hamadeh, Kaczor, Raha, & Tarnopolsky, 2010).

Research investigating exercise-induced mitochondrial biogenesis has traditionally employed continuous

aerobic exercise as the experimental model, and typically in young trained populations (41). This research has

demonstrated that contractile activity disrupts homeostasis, leading to cellular changes such as increases in the

AMP:ATP ratio, increases in intracellular calcium (Ca2+), generation of reactive oxygen species (ROS), and

increased nicotinamide adenine dinucleotide (NAD+) (1, 43, 45, 53). These cellular changes can alter the

phosphorylation and/or abundance of AMPK (53), CAMKII (45), p38MAPK (1), and SIRT1 (43), which, in

turn, initiates the phosphorylation or deacetylation of PGC-1α in the nucleus to help regulate the transcription of

many nuclear genes encoding mitochondrial proteins (31). In addition to PGC-1α, the tumor suppressor protein

p53 has emerged as a potential regulator of mitochondrial content, and subsequent oxidative capacity (39).

More recently, research has demonstrated that some of these molecular signaling pathways are activated in an

intensity-dependent manner (2, 43). As a consequence, increased focus has been directed toward low-volume,

high-intensity, exercise in an attempt to establish whether exercise intensity plays an important role in exercise-

induced mitochondrial biogenesis (17, 18). However, these laboratory-based exercise models have been

criticized for being poorly motivating (51) or excessively exhausting (11) for the general population. An

alternative to these more traditional training modes is intermittent running in the form of football-based small-

sided games (SSG). Similar exercise modes have been reported to improve health in clinical populations, and to

provide a group-exercise approach that assists with adherence and compliance for long-term lifestyle changes

(26, 35). A single bout of SSG can produce changes in muscle and blood metabolites (27); however, the effect

of SSG on mitochondrial signaling in human skeletal muscle is unknown, particularly in comparison to

traditional, non-weight bearing continuous exercise such as cycling (CYC).

3

61

62

63

64

65

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

81

82

83

84

85

86

87

88

89

This study, therefore aimed to assess changes in molecular signaling cascades associated with mitochondrial

biogenesis in response to a single bout of either SSG or CYC. Given that prior training history can alter acute

signaling and gene expression responses to subsequent bouts (8), and most previous research has been

conducted with young, active men, we sought to investigate these changes in a sedentary, middle-aged,

population. It was hypothesized that if total exercise intensity (duration and internal load) is matched between

conditions, SSG will be as effective as continuous CYC to stimulate signaling pathways associated with

mitochondrial biogenesis in obese sedentary middle-aged men.

MATERIALS AND METHODS

Participant recruitment

The participants consisted of nine sedentary, obese, middle-aged men (characteristics are shown in Table 1) who

were not on any medications and were not clinically diagnosed with any pre-existing immunological

irregularities, or cardiovascular/metabolic disorder. Participants also needed to be free from acute and chronic

musculoskeletal injuries/conditions. The sedentary criteria ensured participants had completed no more than one

regular exercise session per week (>20 min) during the preceding six months. Participants did not need any

sports-specific skills prior to involvement in the study. Prior to participant recruitment the study was approved

by the Research in Human Ethics Committee of Charles Sturt University (Protocol Number: 2011/007) and

conformed to the research standards outlined in the fifth revision of the Declaration of Helsinki. All participants

provided verbal and written consent prior to the commencement of testing procedures. Prior to testing all

participants also completed a Physical Activity Readiness-Questionnaire (PAR-Q).

INSERT TABLE 1 ABOUT HERE

Overview

Following an initial baseline testing session, and ensuing 7-d recovery period, participants completed the CYC

and SSG condition in a randomized, cross-over design. Each respective condition was separated by a 21-d

sedentary period where participants were instructed to continue normal physical activity (no more than one

regular exercise session per week of >20 min) and dietary patterns to allow adequate recovery from each

unaccustomed exercise session. Adequate recovery between conditions was determined based on expected time

4

90

91

92

93

94

95

96

97

98

99

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

for muscle damage, soreness and swelling to peak between 24 h to 10 d after and unaccustomed bout of

eccentric exercise (7). However, consideration must be taken regarding a repeated bout effect especially within

participants who completed the SSG session first. Testing procedures commenced between standardized times

(0600-0800 h), following an overnight fast (10-12 h), and were conducted by the same research team in either a

laboratory (20-22°C, 35-45% relative humidity) or an outdoor football field (14-20°C, 35-45% relative

humidity).

Physical activity and diet were controlled for each participant prior to and during each respective exercise

condition. Participants refrained from physical activity for 72 h prior to each testing session and diet was

standardized 24 h prior to all sessions. Participants recorded physical activity 72 h prior and food/fluid ingestion

24 h prior to their first condition. Participants then replicated and recorded this diet and activity profile in

preparation for the remaining condition. Diaries were used to assist the recording of activity and nutritional

patterns and were inspected by the research team to ensure compliance with the dietary and physical activity

requirements. During each condition, and until a post-exercise muscle sample was obtained 240 min after each

condition, participants remained fasted and consumed water ab libitum (~500 mL).

Baseline testing and familiarization

Baseline measures obtained from all participants included anthropometry (height, mass, waist and hip girths), a

supine whole-body, dual-energy x-ray absorptiometry (DXA; XR800, Norland, Cooper Surgical Company,

USA) scan and a graded exercise test (GXT). All anthropometric measures were obtained using standard

techniques (38). Scans were conducted with a scanning resolution of 6.5 x 13.0 mm, with the speed set at 130

mm.s-1, and analyzed (Illuminatus DXA, ver.4.2.0, USA) for total body fat-mass (TB-FM) (25). Finally, aerobic

power was estimated from oxygen consumption (VO2) during a sub-maximal GXT (52). Pulmonary gas

exchange was measured by determining O2 and CO2 concentrations and ventilation to calculate VO2 using a

metabolic gas analysis system (Parvo Medics, True2400, East Sandy, UT, USA). The system was calibrated

according to the manufacturer’s instructions. The GXT was performed on an electronically-braked cycle

ergometer (LODE Excalibur Sport, LODE BV, Groningen, Netherlands); the test started at 25 W and increased

by 25 W every minute. Heart rate (HR; Vantage NV, Polar, Finland) was recorded each minute throughout the

GXT, and participants exercised until attainment of 80% of age-predicted (220-age) maximum heart rate

5

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

(%HRmax). This baseline testing also served to familiarize participants with all exercise trial and testing

procedures.

Exercise conditions

Upon arrival, a resting venous blood sample was collected and the lateral portion of the right thigh was sterilised

(4% Chlorhexidine) and locally anaesthetized (2% plain Lignocaine) for needle biopsy samples from the m.

vastus lateralis. Using a 5-mm Bergstrom needle biopsy an ~100 mg sample was obtained, blotted on filter

paper, removed of fat and connective tissue, frozen in liquid nitrogen and stored at -80°C for later analysis. For

both exercise conditions, venous blood was collected at rest and immediately post-exercise. Due to the invasive

nature of the study design muscle samples were collected at rest (on one occasion and randomized between

conditions). Previous research has shown that one vastus lateralis muscle sample per subject is sufficient to

establish a reliable baseline for comparing the changes in gene expression of selected pathways within the same

individual (4). Remaining post-exercise muscle samples were collected at 30 and 240 min following both

exercise conditions. These post-exercise time-points were chosen based on the transient nature of signalling

proteins and mRNA expression, with support from previous studies (15, 16, 45). All muscle samples were

collected through different incision sites (~1 cm apart) on the right thigh.

Small-sided games condition

The SSG condition involved modified football (non-contact- touch rugby), as this is the most popular football code

in the recruited participants’ local geographical region (24). Participants completed 40 min of a six-a-side game on a

reduced-size pitch (width: 40 m; length: 60 m) to induce a mean target HR zone ~8085% HRmax. The session was

comprised of 4 x 10-min bouts, interspersed by 2 min of passive recovery. Speed was recorded every second using a

1 Hz Global Positioning Satellite (GPS) device (SPIelite, GPSports, Canberra, Australia). The GPS unit was

worn in a customized harness between the scapulae to quantify distance and mean speed (m .min-1) of movement

patterns during the session (9). At the end of each 10-min period, and also 30 min post-exercise, HR and Rating

of Perceived Exertion (RPE; Borg’s 6-20 scale) were recorded (21). To ensure participant randomization

between conditions, testing was conducted over 2 separate games (n=4 in game 1 and n=5 in game 2) with

additional and standardized research assistants forming the remaining player numbers in each game. To ensure

a consistent physiological strain between participants, the field size, player number, opponents and rules

remained the same for all participants, including no coach encouragement (42).

6

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

Cycling condition

The CYC condition was non-weight bearing and conducted on a stationary cycle ergometer (Monark 828E,

Varburg, Sweden). The session comprised of 4 x 10 min of continuous, steady-state bouts, interspersed by 2 min

of passive recovery. At the end of each 10-min period, and also 30 min post-exercise, HR and RPE were recorded.

The internal load and duration of CYC was designed to match SSG, with a target HR zone of 8085% HRmax.

During the session, cadence was maintained at 60-65 rpm and individual resistance adjusted to maintain the target

HR range. It is recognized that there are limitations when matching exercise intensity between the two respective

modes. As such, the respective exercise bouts were matched for duration and designed to elicit similar internal

training loads (i.e. HR and RPE) (13, 24, 28).

Venous blood sampling and analyses

At the first exercise testing session, a resting venous blood sample was collected for the analysis of glycosylated

haemoglobin (HbA1c; Liquid Chromatography: Bio-Rad Variant, Australia). For both exercise conditions, 2 mL

of venous blood was collected at rest and immediately post-exercise for the analysis of lactate (ABL825

Radiometer, Denmark). Samples were centrifuged at 3,500 rpm for 15 min at 4°C in fluoride oxalate tubes.

Fluoride oxalate tubes were analysed immediately for lactate and whole blood was collected in EDTA tubes and

refrigerated (4°C) for a maximum of 6 h until analysis for HbA1c. Intra-assay coefficients of variation were 4.0

and 7.4% for HbA1c and lactate, respectively.

Western blotting analysis

Approximately 20 mg of frozen muscle was homogenized in 400 µL of ice-cold lysis buffer (50 mM Tris-HCI

(pH 7.4), 1% Triton X-100, 0.1% SDS, 1µg.mL-1 Aprotinin and Leupeptin, 1 mM Benzamidine, 1 mM NaF, 150

mM NaCI, 1mM EDTA, 5 mM Na-pyrophosphate, 1 mM DTT, 1 mM PMSF and 1 mM Na3 VO4), followed by

end-over-end rotation for 60 min at 4°C. Homogenates were centrifuged at 15, 000 g for 10 min at 4°C and

supernatant was collected. The protein content of the supernatant was determined with a Bradford assay using a

protein assay dye reagent and bovine serum albumin (BSA) as the standard. Each sample was diluted with equal

volume 2X Laemmli buffer (125 mM Tris-HCI (pH 6.8; 4% SDS, 20% glycerol, 0.015% Bromophenol Blue)

and β-mercaptoethanol (10%). For each blot, an internal standard was loaded along with 10-25 µg of protein for

each sample and separated in Tris-glycine running buffer using self-cast stacking 4% and 8-12% resolving gels.

7

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

In transfer buffer, gels were transferred wet onto PVDF membranes for 90 min at 100 V. Membranes were

blocked at room temperature (RT) by incubating for 1 h in 5% fat-free milk and Tris buffered saline 0.1%

Tween-20 (TBS-T). Membranes were washed for 3 x 5 min in TBST, incubated with primary antibodies

(dilutions based on the manufacturer’s instructions) in 3% fat-free milk or fatty acid-free BSA overnight (16 h)

at 4°C. α-tubulin was used as a loading control.

Following incubation, membranes were washed for a further 3 x 5 min in TBST and incubated with anti-species

horseradish peroxidise-conjugated secondary antibody (1:10,000 dilutions) in 1% fat-free milk for 90 min at

room temperature (RT). After a further 3 x 5-min wash in TBST membranes were exposed to a

chemiluminescence liquid (2.5 mM Luminol, 400 µM p-coumaric acid, 100 µM Tris (pH 8.5), 5.4 mM H2O2)

for 5 min. Membranes were visualized using a Versa Doc 4000 MP imaging system and band densities were

determined using Quality One image-analysis software (Bio-Rad laboratories, Hercules, CA). All samples

across all time-points and conditions from each participant were run on the same gel. Raw density values were

corrected to and normalized to the internal standard. These data were used for statistical analysis to compare

within and between participant responses to the respective conditions. For graphical purposes, fold change

relative to pre-training values are reported.

Samples were analyzed for phosphorylated and/or total protein content of PGC-1α (Calbiochem, Darmstadt,

Germany; ST1202), SIRT 1 (Cell Signaling, Beverly, MA, United States; 8469), p53 (Cell Signaling, Beverly,

MA, United States; 2527), p53Ser15 (Cell Signaling, Beverly, MA, United States; 9286), p38 (Cell Signaling,

Beverly, MA, United States; 9212), p38Thr180 (Cell signaling, Beverly, MA, United States; 9211), CAMKIIα

(Cell Signaling, Beverly, MA, United States; 3362), CAMKIIThr286 (Cell Signaling, Beverly, MA, United States;

3361), AMPKα (Cell Signaling, Beverly, MA, United States; 2532), AMPKThr172 (Cell Signaling, Beverly, MA,

United States; 2531) and α-tubulin (Cell Signaling, Beverly, MA, United States; 2125).

Real-Time PCR

Tissues (~20 mg) were lysed for 5 min at room temperature in 800 µL of TRIzol (Invitrogen, Carlsbad, CA) and

transferred to 1.5 mL tubes. Samples were homogenized and centrifuged at 13,000 rpm for 15 min (4°C) to

pellet tissue debris. Upper homogenate was removed and added to 250 µL chloroform (Sigma Aldrich, St Louis,

MO), and centrifuged at 13,000 rpm for 15 min at 4°C. The clear upper layer was removed and added to 1.5 mL

8

208

209

210

211

212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

tubes containing ~400 µL of 2-isopropanol (Sigma Aldrich, St Louis, MO) and 10µL of 5M NaCl. Samples

were precipitated for 12 h at -20°C. Samples were then centrifuged at 13,000 for 20 min at 4°C forming a small

white RNA pellet. The supernatant was removed and the RNA pellet was washed with 500 µL of 75% (vol/vol)

ethanol made with DEPC water (Invitrogen Life Sciences). Samples were centrifuged at 9,000 rpm for 8 min at

4 °C. Ethanol was aspirated off and the RNA pellet was dried for ~15 min at room temperature. The pellet was

dissolved in 10 µL of DEPC water. Samples were stored at - 80 ̊C until further analysis.

Samples were measured for total RNA using nanodrop spectrometry (NanoDrop 2000, Thermo Fisher

Scientific, Wilmington, DE) at 260 nm. Total RNA (1.0 µg) was reverse transcribed into cDNA using iScript™

cDNA Synthesis Kit (Bio-Rad, Melbourne, Australia). ‘Real-time’ PCR was conducted using MyiQ™ single

colour ‘real-time’ PCR detection system (Bio-Rad Laboratories, Hercules, CA) with iQ™ SYBR Green

Supermix (Bio-Rad Laboratories, Hercules, CA) as a fluorescent agent. Forward and reverse oligonucleotide

primers for the gene were designed using OligoPerfect™ Suite (Invitrogen, Melbourne, Australia) with

sequences obtained from GenBank. Selective gene homologies were confirmed with BLAST (Basic Local

Alignment Search Tool, National Centre for Biotechnology Information, Bethesda, MD). To compensate for

variations in RNA input amounts and reverse transcriptase efficiency, mRNA abundance of the housekeeping

gene glyceraldehydes-3-phosphate dehydrogenase (GAPDH) and cyclophilin were quantified and the expression

of the genes of interest was normalized to this (Forward and reverse oligonucleotide primers are shown in Table

2). ‘Real time’-PCR reactions (total volume 20 µL) were primed with 2.5 ng of cDNA and were run for 50

cycles of 95°C for 15 s and 60°C for 60 s (MyCycler™ Thermo Cycler; Bio-rad Laboratories, Hurcules, CA).

Relative changes in mRNA abundance were quantified using the 2 -∆∆CT method as previously detailed (30), and

reported in arbitrary units.

INSERT TABLE 1 ABOUT HERE

Statistical Analysis

All data are reported as mean ±SEM. Raw data were used to assess condition by time interactions and main

effects of time using two-way repeated measures ANOVA. When significant interactions or main effects were

observed, simple main effects and post hoc analyses using Tukey’s pairwise comparisons were used where

9

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

appropriate to locate the source of significance, with alpha set at p<0.05. All statistical analyses were performed

using PASW™ for MS-Windows v20.0 (Statistical Package for the Social Sciences, Chicago, IL, USA).

RESULTS

Small-sided games and cycling demands

Total distance covered during the SSG was 3173 ±104 m, at a mean speed of 79 ±3 m .min-1 or 4.8 ±0.2 km.h-1,

which included 146 ±91 m of high-speed running (designated as above 14 km.h-1). The percentages of time spent

at very low (<0.7 km.h-1), low (0.8-7 km.h-1), moderate (7-14.4 km.h-1), high (14.5-19.9 km.h-1) and very high

(20-23 km.h-1) speed aerobic zones were 6.3 ±2.5%, 75.3 ±5.0%, 17.1 ±2.1%, 1.2 ±0.7% and 0.1 ±0.1%,

respectively. Mean resistance for the CYC condition was 1.9 ±0.2 kp. No significant condition x time

interactions were evident for HR (SSG, 85.9 ±1.8% HRmax,144 ±6 b.min-1; CYC, 83.8 ±1.2% HRmax,141 ±5

b.min-1; p=0.22) or session-RPE (SSG, 13.2 ±0.4 AU; CYC, 13.6 ±0.4 AU; p=0.40). Blood lactate showed no

significant condition x time interaction (p=0.638) but there was a significant main effect of time (p=0.001).

Lactate increased immediately post-exercise in both conditions (2.3 ±0.4 and 2.1 ±0.5 mmol .L-1 for CYC and

SSG (p<0.05), respectively)..

Total protein content and phosphorylation

Change in phosphorylation and representative blots for AMPKThr172/total, CAMKIIThr286/total,

p38MAPKThr180/total, and total SIRT1 are shown in Figure 1. Phosphorylation of AMPKThr172/total showed no

condition x time interaction (p=0.219). A significant main effect of time (p=0.050) was evident at 30 min post-

exercise, with a 2.4-fold increase above rest in CYC (p=0.034), with no change observed in SSG (1.3 fold

increase; p=0.418). No significant condition x time interaction or main effect of time were evident for total

protein content of AMPK, p38MAPK, CAMKII, SIRT1, p38MAPKThr180/Tyr182/total and CAMKIIThr286/total

(p>0.05). Total protein content of PGC-1α showed no significant condition x time interaction (p=0.471) and a

significant main effect of time (p=0.001), which indicated an increase at 30 min post in CYC only (p=0.033)

and a 2.3-fold increase above rest in CYC (p=0.006) and a 1.9-fold increase in SSG (p=0.007) at 240 min post–

exercise (Figure 2A). Total protein content of p53 showed a significant condition x time interaction (Figure 2C;

p=0.018) with differences between conditions occurring at 240 min post exercise (p=0.004). A main effect of

time (p=0.028) with post hoc analyses revealing a 2.3-fold increase above rest at 240 min post exercise in CYC

(p=0.008) and no change in SSG (p=0.857). Phosphorylation of p53Ser15/total (Figure 2B) showed no condition x

10

267

268

269

270

271

272

273

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

296

time interaction (p=0.089) or main time effect (p=0.335). The loading control α-tubulin showed no significant

condition x time interaction or main effect of time for all respective western blot variables (P>0.05).

INSERT FIGURE 1 ABOUT HERE

INSERT FIGURE 2 ABOUT HERE

mRNA expression

Gene expression of PGC-1α and p53 are shown in Figure 3. Gene expression of NRF1, NRF2, Tfam and

cytochrome-c are shown in Figure 4. There was no condition x time interaction for PGC-1α mRNA expression

(p=0.079).There was a main effect of time for PGC-1α mRNA expression (p=0.001) with an increase of 12.9-

fold in CYC (p=0.001) and 7.8-fold in SSG (p=0.008) at 240 min post-exercise. NRF2 mRNA expression

showed no condition x time interaction (p=0.409), but showed a main effect of time (p=0.015), which indicated

a decrease below rest at 240 min post exercise in both CYC (p=0.012) and SSG (p=0.036). There was no

condition x time interaction for Tfam (p=0.353). There was a significant main effect of time for Tfam

(p=0.007), with a significant decrease below rest at 30 min post exercise in the SSG condition (p=0.008), and no

significant change from rest within CYC (p>0.05). However, CYC showed a significant increase from 30 min to

240 min post-exercise (p=0.033). No condition x time interactions or main effect of time were evident for

mRNA expression of NRF1, cytochrome-c and p53 (p>0.05). Housekeeping genes GAPDH and cyclophilin

showed no condition x time interactions (p=0.147) or main effects of time (p=0.471; data not shown).

INSERT FIGURE 3 ABOUT HERE

INSERT FIGURE 4 ABOUT HERE

DISCUSSION

The present study examined changes in molecular signaling cascades, which have been associated with

mitochondrial biogenesis, in response to a single bout of either SSG or CYC. The main finding was that when

11

297

298

299

300

301

302

303

304

305

306

307

308

309

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

CYC and SSG conditions are matched for duration and intensity (HR, RPE and lactate) there were few

differences in gene and protein expression between protocols. In particular, there was a significant increase in

both PGC-1α mRNA and protein content in response to both exercise protocols. Differences between conditions

regarding fluctuation in exercise intensity and type of muscle contraction may explain the acute increase of p53

and AMPK within CYC and not SSG. Regardless, small-sided games are an effective alternative to traditional

continuous exercise modes at stimulating intracellular signalling pathways associated with mitochondrial

biogenesis in obese, sedentary, middle-aged men. The similar responses between conditions suggests that

average exercise intensity, when duration is matched, rather than the type of exercise, may be more important

for stimulating mitochondrial biogenesis in this population.

Skeletal muscle readily responds to changes in contractile activity, with rapid alterations in the regulation of

signaling pathways associated with mitochondrial biogenesis (5, 22, 31)(Safdar, Hamadeh, Kaczor, Raha, &

Tarnopolsky, 2010). Previous research has reported increases in PGC-1α mRNA in response to a single bout of

either high-intensity interval running or moderate intensity continuous running (3, 10). However, this is the first

study to report that continuous exercise and high-intensity intermittent exercise performed as SSG’s are

associated with similar changes in both PGC-1α gene and protein content in obese, sedentary, middle-aged men.

When interpreting the PGC-1α response between conditions, it must be acknowledged that although condition x

time interaction failed to reach significance (p=0.079), there was a trend for a greater increase in PGC-1α

mRNA post CYC. This is consistent with a greater activation of AMPK signalling (15, 33). Regardless, the low

statistical power of the present study (n=9), means it is not possible to conclude there were post-exercise

differences between conditions for PGC-1α mRNA content.

Exercise-induced changes in PGC-1α gene and protein content have been reported to be influenced by both

exercise intensity (14) and the participants’ training status (8). Despite the intermittent high-intensity activity

during the SSG protocol, similar post-exercise responses were evident between conditions, which may indicate

the average intensity of the entire exercise bout is the more important variable. In addition, it may also be that

untrained participants are more responsive to exercise per se (8), and the type of exercise performed is less

consequential. The PGC-1α responses observed in the present study may be a combination of intensity-matched

conditions and the untrained nature of the participants. Given the importance of PGC-1α in regulating

12

325

326

327

328

329

330

331

332

333

334

335

336

337

338

339

340

341

342

343

344

345

346

347

348

349

350

351

352

353

mitochondrial content and function, the similar response between conditions suggest that both modes may be of

similar benefit to induce mitochondrial adaptations within an obese, middle-aged sedentary population.

The exercise-induced increase in PGC-1α protein and mRNA content is thought to be related to the

phosphorylation of upstream protein kinases, namely p38MAPK and AMPK (29). Despite the similar post-

exercise PGC-1α response between conditions, CYC was the only protocol to stimulate an increase (2.4-fold) in

AMPK phosphorylation 30 min post-exercise. This response is similar to that previously reported by

Sriwijitkamol (49), who reported a peak in AMPKThr172 at 30 min and a residual increase above baseline at 150

min post moderate-intensity cycling. Nonetheless, it is possible that the 30-min post-exercise biopsy may have

missed the peak response in each condition, hence limiting the ability to compare conditions. Despite similar

average exercise intensities between conditions, the observed differences in AMPK phosphorylation may be a

result of differences in fuel utilization between conditions. . For example, the high-intensity intermittent nature

of SSG’s meant that ~82% of the time was spent in a low-intensity aerobic zone (<7 km.h-1), and 18% of the

time in moderate- to high-intensity aerobic exercise (>7 km.h-1). In comparison to continuous cycling at 80-85%

HRmax (~70%VO2max), the intermittent nature of SSG suggests difference in the utilization of fuel sources

between conditions. (2, 13, 44). The phosphorylation of AMPK is increased in glycogen-depleted states and

amplified during glycogen utilization (12), which may also have contributed to the greater phosphorylation at 30

min following CYC and not SSG.

Like AMPK, SIRT1 responds to change in energy expenditure with the regulation of SIRT1 being attributed to

changes in NAD+ abundance and the NAD/NADH ratio (6, 47). Furthermore, SIRT1 activity increases cellular

NAD+ concentrations, resulting in the deacetylation and modulation of the activity of downstream targets that

include PGC-1α and p53 (20). In an animal model, acute aerobic exercise has been reported to increase post-

exercise SIRT1 protein content (50); however, in the present study no acute change in SIRT1 total protein

content was evident in either condition. Previous evidence of the acute exercise responses of SIRT1 in human

tissue is minimal, though Morales-Alamo et al. (37) reported a decrease in SIRT1 protein content in response to

hypoxic (10.4% O2 in N2) conditions after a 30-s Wingate test (despite no observed changes when exercise was

performed in normoxic conditions). Moreover, SIRT1 protein content 120 min after a 30-s Wingate test was

lower than when the same test was performed after glucose ingestion (19). These results suggest that within a

young trained population, either nutritional and/or hypoxic interventions may be required to stimulate a post-

exercise change in total protein content of SIRT1. Regardless, this is the first study to document the SIRT1

13

354

355

356

357

358

359

360

361

362

363

364

365

366

367

368

369

370

371

372

373

374

375

376

377

378

379

380

381

382

383

protein response to a single bout of exercise in obese sedentary, middle-aged men, and to report that neither

CYC nor SSG increases SIRT1 protein content in this population.

In addition to being the only exercise mode to increase phosphorylation of AMPK, CYC was the only protocol

to increase p53 total protein content. A recent study by Bartlett et al. (3) found a time-course association

between phosphorylation of AMPK and p53 in response to both high-intensity intermittent and continuous

running within young healthy men, although p53 total protein content was not reported. Furthermore, Jones (23)

reports that p53 is dependent on the activation of AMPK, which may promote the conservation of available

glucose to support cellular survival physiologic function. Accordingly, differences between conditions regarding

exercise intensity and the type of muscle contraction (eccentric and concentric) are all components of exercise

that dictate glucose availability, which may have collectively contributed to a post-exercise increase in p53

protein content in CYC and not SSG. There were no differences in p53 Ser15 between protocols, despite the

differences in AMPK phosphorylation. Metabolic stress triggers an adaptive p53 response, that is emerging as

an important regulator of metabolic homeostasis through its stimulatory effects on mitochondrial biogenesis

(33). Thus, the amplified p53 response in CYC when compared to SSG may suggest different stimulatory

effects on mitochondrial biogenesis between conditions. As this is the first study to our knowledge to report

exercise-induced changes in p53 content, further research is warranted. While CYC increased p53 content,

neither protocol increased p53 mRNA content. However, it may be that our final biopsy (3 h post-exercise) was

too early to detect the increase in p53 mRNA content as studies in cells indicate an increase in p53 mRNA takes

place only after 6-12 h (40). Finally, it has been suggested that the p53 response to cellular stress is mostly

related to post-translational stabilization of the p53 protein, with only a minor role for an increase in p53 gene

transcription (34).

Although we observed an increase in the phosphorylation of AMPK following CYC, there was no change in

protein content of total or phosphorylated p38MAPK and CAMKII in sedentary, middle-aged men. Similar

observations were noted by Serpiello et al. (48), who demonstrated that in healthy. young men both p38MAPK

and CAMKII total protein abundance and phosphorylation were not changed immediately following continuous

running and futsal. Increases in cytosolic Ca2+ as a result of muscle contraction lead to the activation of

CAMKII, which has been shown to be an upstream activator of p38MAPK (45, 54). Previous research has

reported that exercise-induced increases in Ca2+ rapidly return to baseline when exercise is complete and

14

384

385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

411

412

413

corresponds with short-term CAMKII phosphorylation that also reduces to baseline immediately after the

cessation of intermittent or continuous exercise (17, 46, 48). Accordingly, these results suggest that the timing

of muscle biopsy collection at 30 min post-exercise may have been too late to detect phosphorylation

ofCAMKIIThr286 and it’s down steam target of p38MAPK Thr180/Tyr182.

Given the small differences in protein content between protocols, especially for PGC-1α, it is perhaps not

surprising we observed few differences in mRNA content between protocols. There was however, a post-

exercise reduction in Tfam mRNA content within only the SSG protocol and reduced NRF2 mRNA content in

both conditions. Although a decrease in mRNA content was unexpected, Bori et al. (5) have also reported an

exercise-induced decrease in the content of fusion-associated genes (i.e. NRF1, Fis1 and Mfn1 mRNA) in old

sedentary participants. This reported decrease in key genes responsible for the transcription and expression of

the mitochondrial genome warrants further investigation as the mechanisms for this are unclear. Although there

was no significant decrease in Tfam at 30 min post-exercise, the CYC condition showed an increase from 30

min to 240 min. These results may suggest that the low participant numbers in the present study and subsequent

effect on statistical power may have limited our ability to detect small differences within and between

conditions.

Several limitations within the present study should be considered when interpreting the data. Firstly, although

the number of participants is typical for muscle biopsy studies, it could be conceived as relatively low, and the

subsequent effect on statistical power may have affected our ability to detect small differences within and

between conditions. The use of age-predicted (220 bpm – age) HRmax is not always representative of a true

individual HRmax, which may create differences in relative intensity between participants and have contributed to

the individual variability observed for some responses. Additionally, the 30-min biopsy was modelled from

previous research (10); however, the invasive nature of the present study means it is difficult to capture the peak

expression for all proteins within the respective signaling cascades and we acknowledge that biopsy time points

may not have been ideal for all genes and proteins reported. It is also possible that the time course for changes in

gene and protein content is different for different exercise protocols, and this may have contributed to some of

the observed differences between protocols. Furthermore, due to the invasive nature of this study design, muscle

samples were collected at rest on one occasion and randomized between conditions. Physical activity and diet

were recorded and standardized between session at 72 and 24 hours prior to testing, respectively. This was to

15

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

429

430

431

432

433

434

435

436

437

438

439

440

441

442

443

ensure all protein expression, protein phosphorylation or gene expression was specific to the exercise session.

Previous research has shown that one vastus lateralis muscle sample per subject is sufficient to establish a

reliable baseline for comparing gene expression representing selected pathways overtime within the same

individual (4). However, due to the exercise conditions being performed 21 days apart this must be recognized

as a potential limitation. Finally, to reduce risk of adverse responses to the exercise in middle-aged, obese

populations it is recommended that exercise, especially of a high-intensity nature (i.e. SSG) be prescribed in

coordination with a full health check and approval from a medical doctor.

Conclusions

In conclusion, this study shows that when exercise intensity is matched, CYC and non-contact SSG are

associated with a similar increase in both PGC-1α gene and protein content. The similar response between

conditions suggest that both modes may be of similar benefit to induce mitochondrial adaptations within a

middle-aged sedentary population. However, differences were evident between protocols regarding AMPK

phosphorylation and p53 protein content, which may be a result of fluctuations of exercise intensity and muscle

contraction type between the respective intermittent (SSG) and continuous (CYC) protocols. These data

suggests that both conditions are of an acute benefit to participants, however, when prescribing exercise to a

middle-aged, obese population cardio-vascular complications, muscle soreness and risk of injury must be

considered, especially when prescribing SSG. Further research is required to determine if the exercise-induced

changes in gene and protein content observed in this study translate to training-induced changes in

mitochondrial content and function in this population.

ACKNOWLEDGEMENTS: We thank all the participants for their time and dedication to the study. We also

thank Tegan Kastelein, Kerry Mann, Danielle Girard, Karen Hill, Cesare Granata and Rodrigo S.F Oliveira for

their research and analytical assistance.

GRANTS: Charles Sturt University, Faculty of Education, Small Grant

DISCLOSURES: No conflicts of interest, financial or otherwise, are declared by the author(s).

Figure Captions

Figure 1.

16

444

445

446

447

448

449

450

451

452

453

454

455

456

457

458

459

460

461

462

463

464

465

466

467

468

469

470

471

472

473

Phosphorylation of AMPKThr172/total (A), CAMKThr286/total (B), p38MAPKThr180/total (C), and total protein

content of SIRT1 (D), corrected to α-tubulin (Representative blots; D). Values expressed in arbitrary units

relative to rest. a Significant difference from rest within the cycling (CYC) condition P<0.05. Resting values

represent pooled data. Data reported as Mean ± SEM.

Figure 2.

Total protein content of PGC-1α (A), phosphorylated p53Ser15 (B), and Total p53 (C), corrected α-tubulin

(Representative blots; C). Values expressed in arbitrary units relative to rest. a Significant difference from rest

within the cycling (CYC) condition P<0.05; b Significant difference from rest within the small-sided games

(SSG) condition P<0.05; c Significant time-point difference between conditions P<0.05. Resting values

represent pooled data. Data reported as Mean ± SEM.

Figure 3.

Gene expression (AU) of PGC-1α (A), and p53 (B) corrected to GAPDH and cyclophilin (Data not shown).

Values expressed in arbitrary units relative to rest. a Significant difference from rest within the cycling (CYC)

condition P<0.05; b Significant difference from rest within the small-sided games (SSG) condition P<0.05.

Resting values represent pooled data. Data reported as Mean ± SEM.

Figure 4.

Gene expression of NRF1 (A), NRF2 (B) and Tfam (C), and Cytochrome-C (D) corrected to GAPDH and

cyclophilin (Data not shown). Values expressed in arbitrary units relative to rest. a Significant difference from

rest within the cycling (CYC) condition P<0.05; b Significant difference from rest within the small-sided games

(SSG) condition P<0.05. c Significant difference from 30 min post within the CYC condition P<0.05. Resting

values represent pooled data. Data reported as Mean ± SEM.

17

474

475

476

477

478

479

480

481

482

483

484

485

486

487

488

489

490

491

492

493

494

495

496

497

498

499

500

References

1. Akimoto T, Pohnert SC, Li P, Zhang M, Gumbs C, Rosenberg PB, Williams RS, and Yan Z.

Exercise stimulates pgc-1α transcription in skeletal muscle through activation of the p38 mapk

pathway. J Biol Chem (280) 20: 19587-19593, 2005.

2. Baar K, Wende AR, Jones TE, Marison M, Nolte LA, Chen MAY, Kelly DP, and Holloszy JO.

Adaptations of skeletal muscle to exercise: Rapid increase in the transcriptional coactivator pgc-1. The

FASEB Journal (16) 14: 1879-1886, 2002.

3. Bartlett JD, Joo CH, Jeong TS, Louhelainen J, Cochran AJ, Gibala MJ, Gregson W, Close GL,

Drust B, and Morton JP. Matched work high-intensity interval and continuous running induce similar

increases in pgc-1α mrna, ampk, p38, and p53 phosphorylation in human skeletal muscle. J Appl

Physiol (112) 7: 1135-1143, 2012.

4. Boman N, Burén J, Antti H, and Svensson MB. Gene expression and fiber type variations in

repeated vastus lateralis biopsies. Muscle Nerve 2015.

5. Bori Z, Zhao Z, Koltai E, Fatouros IG, Jamurtas AZ, Douroudos II, Terzis G, Chatzinikolaou A,

Sovatzidis A, and Draganidis D. The effects of aging, physical training, and a single bout of exercise

on mitochondrial protein expression in human skeletal muscle. Exp Gerontol (47) 6: 417-424, 2012.

6. Cantó C, Gerhart-Hines Z, Feige JN, Lagouge M, Noriega L, Milne JC, Elliott PJ, Puigserver P,

and Auwerx J. Ampk regulates energy expenditure by modulating nad+ metabolism and sirt1 activity.

Nature (458) 7241: 1056-1060, 2009.

7. Clarkson PM and Hubal MJ. Exercise-induced muscle damage in humans. Am J Phys Med Rehabil

(81) 11: S52-S69, 2002.

8. Coffey VG, Shield A, Canny BJ, Carey KA, Cameron-Smith D, and Hawley JA. Interaction of

contractile activity and training history on mrna abundance in skeletal muscle from trained athletes.

American Journal of Physiology-Endocrinology and Metabolism (290) 5: E849-E855, 2006.

9. Coutts AJ and Duffield R. Validity and reliability of gps devices for measuring movement demands

of team sports. J Sci Med Sport (13) 1: 133-135, 2010.

10. De Filippis E, Alvarez G, Berria R, Cusi K, Everman S, Meyer C, and Mandarino LJ. Insulin-

resistant muscle is exercise resistant: Evidence for reduced response of nuclear-encoded mitochondrial

genes to exercise. American Journal of Physiology-Endocrinology and Metabolism (294) 3: E607-

E614, 2008.

18

501

502

503

504

505

506

507

508

509

510

511

512

513

514

515

516

517

518

519

520

521

522

523

524

525

526

527

528

529

530

11. Doherty M, Smith P, Hughes M, and Davison R. Caffeine lowers perceptual response and increases

power output during high-intensity cycling. J Sports Sci (22) 7: 637-643, 2004.

12. Drust B, Reilly T, and Cable NT. Physiological responses to laboratory-based soccer-specific

intermittent and continuous exercise. J Sports Sci (18) 11: 885-892, 2000.

13. Duffield R, Allen NG, and Mendham AE. The health benefits of rugby-specific small-sided games

for sedentary populations. World Congress on Science in Football (In press ) 2016.

14. Edgett BA, Foster WS, Hankinson PB, Simpson CA, Little JP, Graham RB, and Gurd BJ.

Dissociation of increases in pgc-1α and its regulators from exercise intensity and muscle activation

following acute exercise. PLoS One (8) 8: e71623, 2013.

15. Egan B and Zierath JR. Exercise metabolism and the molecular regulation of skeletal muscle

adaptation. Cell Metabolism (17) 2: 162-184, 2013.

16. Franchi MV, Atherton PJ, Reeves ND, Flück M, Williams J, Mitchell WK, Selby A, Beltran Valls

RM, and Narici MV. Architectural, functional and molecular responses to concentric and eccentric

loading in human skeletal muscle. Acta Physiologica (210) 3: 642-654, 2014.

17. Gibala MJ, McGee SL, Garnham AP, Howlett KF, Snow RJ, and Hargreaves M. Brief intense

interval exercise activates ampk and p38 mapk signaling and increases the expression of pgc-1alpha in

human skeletal muscle. J Appl Physiol (106) 3: 929-934, 2009.

18. Granata C, Oliveira RSF, Little JP, Renner K, and Bishop DJ. Training intensity modulates

changes in pgc-1α and p53 protein content and mitochondrial respiration, but not markers of

mitochondrial content in human skeletal muscle. The FASEB Journal (30) 2: 959-970, 2015.

19. Guerra B, Guadalupe-Grau A, Fuentes T, Ponce-González JG, Morales-Alamo D, Olmedillas H,

Guillén-Salgado J, Santana A, and Calbet JAL. Sirt1, amp-activated protein kinase phosphorylation

and downstream kinases in response to a single bout of sprint exercise: Influence of glucose ingestion.

Eur J Appl Physiol (109) 4: 731-743, 2010.

20. Hardie DG. Amp-activated/snf1 protein kinases: Conserved guardians of cellular energy. Nature

Reviews Molecular Cell Biology (8) 10: 774-785, 2007.

21. Herman L, Foster C, Maher MA, Mikat RP, and Porcari JP. Validity and reliability of the session

rpe method for monitoring exercise training intensity. South African Journal of Sports Medicine (18) 1:

14-17, 2006.

19

531

532

533

534

535

536

537

538

539

540

541

542

543

544

545

546

547

548

549

550

551

552

553

554

555

556

557

558

559

22. Irving BA, Lanza IR, Henderson GC, Rao RM, Spiegelman BM, and Sreekumaran Nair K.

Combined training enhances skeletal muscle mitochondrial oxidative capacity independent of age. The

Journal of Clinical Endocrinology and Metabolism 2015.

23. Jones RG, Plas DR, Kubek S, Buzzai M, Mu J, Xu Y, Birnbaum MJ, and Thompson CB. Amp-

activated protein kinase induces a p53-dependent metabolic checkpoint. Mol Cell (18) 3: 283-293,

2005.

24. Kennett DC, Kempton T, and Coutts AJ. Factors affecting exercise intensity in rugby-specific small-

sided games. J Strength Cond Res (26) 8: 2037-2042, 2012.

25. Kim J, Wang ZM, Heymsfield SB, Baumgartner RN, and Gallagher D. Total-body skeletal muscle

mass: Estimation by a new dual-energy x-ray absorptiometry method. Am J Clin Nutr (76) 2: 378-383,

2002.

26. Krustrup P, Aagaard P, Nybo L, Petersen J, Mohr M, and Bangsbo J. Recreational football as a

health promoting activity: A topical review. Scand J Med Sci Sports (20) s1: 1-13, 2010.

27. Krustrup P, Mohr M, Steensberg A, Bencke J, Kjær M, and Bangsbo J. Muscle and blood

metabolites during a soccer game: Implications for sprint performance. Med Sci Sports Exerc (38) 6:

1165-1174, 2006.

28. Krustrup P, Nielsen JJ, Krustrup BR, Christensen JF, Pedersen H, Randers MB, Aagaard P,

Petersen AM, Nybo L, and Bangsbo J. Recreational soccer is an effective health-promoting activity

for untrained men. Br J Sports Med (43) 11: 825-831, 2009.

29. Lanza IR and Sreekumaran Nair K. Regulation of skeletal muscle mitochondrial function: Genes to

proteins. Acta Physiologica (199) 4: 529-547, 2010.

30. Livak KJ and Schmittgen TD. Analysis of relative gene expression data using real-time quantitative

pcr and the 2−δδct method. Methods (25) 4: 402-408, 2001.

31. Ljubicic V, Joseph AM, Saleem A, Uguccioni G, Collu-Marchese M, Lai RYJ, Nguyen LMD, and

Hood DA. Transcriptional and post-transcriptional regulation of mitochondrial biogenesis in skeletal

muscle: Effects of exercise and aging. Biochim Biophys Acta (1800) 3: 223-234, 2010.

32. Lowell BB and Shulman GI. Mitochondrial dysfunction and type 2 diabetes. Science (307) 5708:

384-387, 2005.

33. Maddocks ODK and Vousden KH. Metabolic regulation by p53. J Mol Med (89) 3: 237-245, 2011.

20

560

561

562

563

564

565

566

567

568

569

570

571

572

573

574

575

576

577

578

579

580

581

582

583

584

585

586

587

588

34. Marchenko ND, Hanel W, Li D, Becker K, Reich N, and Moll UM. Stress-mediated nuclear

stabilization of p53 is regulated by ubiquitination and importin-α3 binding. Cell Death Differ (17) 2:

255-267, 2010.

35. Mendham AE, Duffield R, Coutts A, Marino F, Boyko A, and Bishop D. Rugby-specific small-

sided games training is an effective alternative to stationary cycling at reducing clinical risk factors

associated with the development of type 2 diabetes: A randomized, controlled trial. PLoS One (10) 6:

e0127548, 2015.

36. Mogensen M, Sahlin K, Fernstrom M, Glintborg D, Vind BF, Beck-Nielsen H, and Hojlund K.

Mitochondrial respiration is decreased in skeletal muscle of patients with type 2 diabetes. Diabetes (56)

6: 1592-1599, 2007.

37. Morales-Alamo D, Ponce-González JG, Guadalupe-Grau A, Rodríguez-García L, Santana A,

Cusso MR, Guerrero M, Guerra B, Dorado C, and Calbet JAL. Increased oxidative stress and

anaerobic energy release, but blunted thr172-ampkα phosphorylation, in response to sprint exercise in

severe acute hypoxia in humans. J Appl Physiol (113) 6: 917-928, 2012.

38. Norton K and Olds T, Anthropometrica: A textbook of body measurement for sports and health

courses. 1996: University of New South Wales Press. 1-422.

39. Park JY, Wang P, Matsumoto T, Sung HJ, Ma W, Choi JW, Anderson SA, Leary SC, Balaban

RS, and Kang JG. P53 improves aerobic exercise capacity and augments skeletal muscle

mitochondrial DNA content. Circ Res (105) 7: 705-712, 2009.

40. Park S, Kim D, Dan HC, Chen H, Testa JR, and Cheng JQ. Identification of akt interaction protein

phf20/tzp that transcriptionally regulates p53. J Biol Chem (287) 14: 11151-11163, 2012.

41. Pilegaard H, Osada T, Andersen LT, Helge JW, Saltin B, and Neufer PD. Substrate availability

and transcriptional regulation of metabolic genes in human skeletal muscle during recovery from

exercise. Metabolism (54) 8: 1048-1055, 2005.

42. Rampinini E, Impellizzeri FM, and Castagna C. Factors influencing physiological responses to

small-sided soccer games. J Sports Sci (25) 6: 659-666, 2007.

43. Rodgers JT, Lerin C, Gerhart-Hines Z, and Puigserver P. Metabolic adaptations through the pgc-

1α and sirt1 pathways. FEBS Lett (582) 1: 46-53, 2008.

21

589

590

591

592

593

594

595

596

597

598

599

600

601

602

603

604

605

606

607

608

609

610

611

612

613

614

615

616

44. Romijn JA, Coyle EF, Sidossis LS, Gastaldelli A, Horowitz JF, Endert E, and Wolfe RR.

Regulation of endogenous fat and carbohydrate metabolism in relation to exercise intensity and

duration. American Journal of Physiology-Endocrinology and Metabolism (265) 3: E380-E391, 1993.

45. Rose AJ and Hargreaves M. Exercise increases ca2+– calmodulin‐dependent protein kinase ii activity

in human skeletal muscle. The Journal of Physiology (553) 1: 303-309, 2003.

46. Rose AJ, Kiens B, and Richter EA. Ca2+–calmodulin-dependent protein kinase expression and

signalling in skeletal muscle during exercise. The Journal of Physiology (574) 3: 889-903, 2006.

47. Ruderman NB, Xu XJ, Nelson L, Cacicedo JM, Saha AK, Lan F, and Ido Y. Ampk and sirt1: A

long-standing partnership? American Journal of Physiology-Endocrinology and Metabolism (298) 4:

E751-E760, 2010.

48. Serpiello FR, McKenna MJ, Coratella G, Markworth JF, Tarperi C, Bishop D, Stepto NK,

Cameron-Smith D, and Schena F. Futsal and continuous exercise induce similar changes in specific

skeletal muscle signalling proteins. Int J Sports Med (35) 10: 863-870, 2014.

49. Sriwijitkamol A, Coletta DK, Wajcberg E, Balbontin GB, Reyna SM, Barrientes J, Eagan PA,

Jenkinson CP, Cersosimo E, and DeFronzo RA. Effect of acute exercise on ampk signaling in

skeletal muscle of subjects with type 2 diabetes a time-course and dose-response study. Diabetes (56)

3: 836-848, 2007.

50. Suwa M, Nakano H, Radak Z, and Kumagai S. Endurance exercise increases the sirt1 and

peroxisome proliferator-activated receptor-γ coactivator-1α protein expressions in rat skeletal muscle.

Metabolism (57) 7: 986-998, 2008.

51. Tjønna AE, Lee SJ, Rognmo Ø, Stølen TO, Bye A, Haram PM, Loennechen JP, Al-Share QY,

Skogvoll E, Slørdahl SA, Kemi OJ, Najjar SM, and Wisløff U. Aerobic interval training versus

continuous moderate exercise as a treatment for the metabolic syndrome: A pilot study. Circulation

(118) 4: 346-354, 2008.

52. Wallman KE and Campbell L. Test–retest reliability of the aerobic power index submaximal exercise

test in an obese population. J Sci Med Sport (10) 3: 141-146, 2007.

53. Winder WW, Holmes BF, Rubink DS, Jensen EB, Chen M, and Holloszy JO. Activation of amp-

activated protein kinase increases mitochondrial enzymes in skeletal muscle. J Appl Physiol (88) 6:

2219-2226, 2000.

22

617

618

619

620

621

622

623

624

625

626

627

628

629

630

631

632

633

634

635

636

637

638

639

640

641

642

643

644

645

54. Wright DC, Han DH, Garcia-Roves PM, Geiger PC, Jones TE, and Holloszy JO. Exercise-induced

mitochondrial biogenesis begins before the increase in muscle pgc-1alpha expression. The Journal of

Biological Chemistry (282) 194-199, 2007.

23

646

647

648

649