High intensity interval training alters gene expression linked to mitochondrial biogenesis and dynamics in high fat diet fed rats

Abstract

A High-Fat Diet (HFD) leads to disruption of mitochondrial biogenesis and dynamics. Exercise training, especially High-Intensity Interval Training (HIIT) increases mitochondrial biogenesis and dynamics. The present study aimed to investigate the effect of a period of HIIT with and without HFD consumption on the expression of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (Pgc1-α), Mitofusins-2 (Mfn2), Optic atrophy-1 (Opa1), Dynamin-related protein-1 (Drp1) and mitochondrial Fission protein-1 (Fis1) genes as indicators of mitochondrial biogenesis and dynamics function in the soleus muscle of male Wistar rats. Twenty-four healthy male Wistar rats were randomly divided into four groups: (1) Control, (2) Control + HIIT, (3) HFD, and (4) HFD + HIIT. The HIIT training protocol lasted for 10 weeks with a frequency of 3 sessions per week. The Real-Time Quantitative Reverse Transcription PCR method was used to investigate the gene expression. One-way ANOVA and Fisher’s post-hoc analyses were used to examine group differences. HFD consumption caused an increase in weight (P < 0.05), the expression of Drp1 and Fis1 genes (P < 0.001), and a decreased expression of Pgc1-α, Mfn2, and Opa1 genes (P < 0.001). HIIT training increased the expression of PGC1-α (P = 0.009), Mfn2 (P < 0.004), and Opa1 (P < 0.011) genes, while it decreased the expression of Drp1 (P = 0.003) and Fis1 genes (P = 0.027). These findings suggest that HIIT can counteract the negative effects of HFD on mitochondrial function by modulating gene expression related to mitochondrial biogenesis and dynamics.

Introduction

Obesity is a complex multifactorial global disease and its prevalence has rapidly increased worldwide over the past 40 years¹. Obesity has a negative effect on all physiological functions of the body, including mitochondrial health and function, and leads to disruption of mitochondrial biogenesis and dynamics². Mitochondrial health is an essential mediator of cellular function in various tissues. Mitochondria are highly dynamic organelles that constantly undergo a coordinated cycle of biogenesis, fusion, fission, and destruction, forming a complex network to respond to dynamic changes in energy requirements³. Evidence suggests that mitochondrial dysfunction is often modulated by genetic, environmental, and lifestyle factors⁴. For obesity, researchers state many predisposing factors such as geographic region, social conditions, political, economic and genetic factors that have different effects on the prevalence of obesity and overweight. Also, the most common demographic factors are behavioral factors (food habits and lifestyle), genetic factors, and living in developed and industrial areas with high machine facilities⁵. Lifestyle changes in recent decades, including inactivity or reduced physical activity and consumption of high-calorie foods including high-fat diet (HFD), are the most important and common causes of obesity^6,7 and disruption of mitochondrial biogenesis and dynamics^8,9.

Several studies have shown that HFD decreases peroxisome proliferator-activated receptor gamma coactivator 1-alpha (Pgc1-α) levels and ultimately decreases mitochondrial biogenesis in gastrocnemius¹⁰ and cardiac muscles¹¹. On the other hand, some studies have also shown that the consumption of HFD increases the levels of Pgc1-α in the Extensor Digitorum Longus (EDL)¹², quadriceps¹³, and soleus¹⁴ muscles. Mitochondrial dynamics are regulated by fusion and fission processes¹⁵. Fusion is carried out by Mitofusins-1, 2 (Mfn1, Mfn2), and Optic atrophy-1 (Opa1)¹⁵. Dynamin-related protein-1 (Drp1) and mitochondrial Fission protein-1 (Fis1) are responsible for mitochondrial fission¹⁵. Studies have demonstrated that HFD disrupts the balance of mitochondrial dynamics in skeletal muscle^16,17, which may be linked to various disorders and diseases such as obesity, diabetes¹⁸, cardiomyopathy, ischemia, heart infarction, and neurodegenerative conditions like Huntington’s, Parkinson’s, and Alzheimer’s¹⁵.

Exercise training may prevent mitochondrial dysfunction by improving mitochondrial biogenesis^19–21, dynamics²² quality control and metabolism²³. Also, various types of exercise such as resistance^24–26, endurance²⁷ and High-Intensity Interval Training (HIIT)²⁸ have been shown to increase the expression of Pgc1-α in various tissues including the gastrocnemius^25,26, soleus²⁸ and plantaris²⁴ muscles and improve mitochondrial biogenesis. Other research showed that HIIT training improves mitochondrial dynamics^6,29.

Several studies have investigated the effect of exercise training after a period of consuming an HFD on mitochondrial biogenesis and dynamics in different animal tissues, including the liver^6,30, brain (hippocampus)³¹, gastrocnemius muscle^32,33 and EDL muscle¹². One study was done on the soleus muscle²⁹. After 12 weeks of HFD to induce diabetes, Peyravi et al.²⁹ investigated the effect of 8 weeks of HIIT training on the expression of mitochondrial dynamic genes in the soleus muscle of male Sprague Dawley rats. In most of the studies, the rats were first fed with HFD, and after the development of disease conditions such as obesity and diabetes, exercise interventions were applied^6,29,33. In these studies, exercise training has been used as a non-pharmacological treatment method to reduce the consequences of diseases such as obesity and diabetes. According to our knowledge, no study has investigated the simultaneous effects of HIIT training and HFD consumption on the expression of genes related to mitochondrial biogenesis and dynamics in healthy male rats. Hence, we hypothesize that HIIT training as a preventive modality moderates the consequences of HFD consumption. Therefore, the present study aimed to investigate the effect of HIIT training on the expression of genes related to mitochondrial biogenesis and dynamics in the soleus muscle of male Wistar rats that consumed HFD.

The novelty of the study goes beyond the direct comparison of HIIT and HFD on mitochondrial function. While previous research has examined the benefits of HIIT on mitochondrial health and the detrimental effects of HFD on metabolic function, this study offers new perspectives on how these two factors can synergistically impact mitochondrial biogenesis and dynamics, exploring the balance between fission and fusion processes. The study of mitochondrial dynamics is also remarkably noteworthy. This aspect of mitochondrial function is frequently disregarded, but plays a crucial role in maintaining mitochondrial healthy and preventing dysfunction. Additionally, the use of real-time quantitative reverse transcription PCR (RT-qPCR) allows for a precise analysis of gene expression related to mitochondrial biogenesis and dynamics, providing valuable insights into the underlying mechanisms. By examining both mitochondrial biogenesis and dynamics and analyzing gene expression changes, the results of this study may provide valuable insights into the underlying mechanisms and potential clinical implications.

Methods

Animals and experimental design

The present study was experimental and applied. The sample consisted of twenty-four healthy male Wistar rats (age = six weeks, weight = 195 ± 15 g), purchased from Pasteur Institute in Tehran and kept in the Tarbiat Modares University animal house (Tehran, Iran). The determination of the sample size for ANOVA was achieved through the resource equation method³⁴. The animals had free access to standard food and water at an environment temperature of 22 ± 1.4, a humidity of 55 ± 4, and a light-dark cycle of 12:12. After a week of familiarization with the animal house environment, the rats were randomly divided into four groups: (1) control group (Normal Diet (ND) without exercise), (2) Control + HIIT group, (3) HFD group and (4) HFD + HIIT group. Randomization was performed by the laboratory operator blindly using the numbering of rats and a lottery card. Following randomization height, weight, and Lee’s index were measured. Diet and exercise interventions started simultaneously and lasted for ten weeks. After the completion of the intervention, height, weight, and Lee’s index were measured in all groups. Experiments were conducted based on ARRIVE guidelines and the instructions of the ethics committee in research and care of animals of the Institute of Physical Education and Sports Sciences of Iran, and all stages of the study were approved by the ethics committee in research (ethics code: IR.SSRI.REC.1402.083). In addition, all measures were performed in accordance with the relevant guidelines.

Interventions

Exercise training protocol

The HIIT training protocol included eight bouts of intense activity (2.5 min with an intensity of 90% of the maximum running capacity (MRC)) with periods of active rest (2.5 min with an intensity of 50% of the MRC)³⁵; HIIT training was performed for ten weeks with a frequency of 3 sessions per week in the early hours of the day (light period). To familiarize and adapt to the training protocol, after a week of adaptation to the animal house environment, all rats ran on a treadmill for 10 min at a speed of 6 m per minute for one week. The MRC test - performed following group allocation - consisted of running at a speed of 6 m per minute, and gradually every 3 min, the speed increased by 3 m per minute until reaching the fatigue threshold. The inability of the rats to get to the end of the treadmill after five times of mechanical stimulation by a soft brush within 1 min is defined as the fatigue threshold speed (MRC%100), which is considered as the maximum speed and the aerobic performance of the rat. It was calculated according to the distance traveled. The rats not in the exercise training group only underwent a one-week acclimation period and the MRC test. The MRC test was repeated after ten weeks³⁵.

Diet

During the research, rats were fed with ND and HFD prepared by the Razi Serum Institute (Iran). After the period of familiarization with the environment, the HFD and HFD + HIIT groups were fed with HFD (60% of total energy from fat derived from animal oil, 20% carbohydrates, and 20% protein) for ten weeks. Also, the control and control + HIIT groups were fed with ND (10% of total energy from fat, 70% from carbohydrates and 20% from protein) as free access.

Body composition

A digital scale with a sensitivity of 0.01 g was used to measure the weight of the rats. The height (length) of the rats was measured using the caliper (between the tip of the nose and the beginning of the tail). The height of the rats was measured and recorded at the beginning and 48 h after the last session of the training protocol (All groups were measured at the same time of day). The weight was measured and recorded at the beginning and regularly at the end of each week until the end of the period. Lee’s index was used to evaluate the obesity status of rats. Lee’s Index is a measurement used primarily in the context of assessing obesity in rodents, particularly mice and rats. It was developed to evaluate body fatness based on the relationship between an animal’s weight and its body length ([3 square root body weight (g) / nasoanal length (cm)] *1000)³⁶.

Tissue collection

Forty-eight hours after the last training session, the rats in all groups were anesthetized by intraperitoneal injection of xylazine (10 mg/kg) and ketamine (80 mg/kg). After the injection, to confirm complete and deep anesthesia, muscle relaxation, and absence of foot and eye reflexes were checked and confirmed, then euthanasia was performed by cervical dislocation simultaneously on the same day. The soleus muscle tissue was isolated, immediately transferred into coded cryotubes, then frozen using liquid nitrogen, and immediately stored in a freezer at -80 °C. qRT-PCR method was used to investigate the expression of Pgc1-α, Mfn2, Opa1, Drp1, and Fis1 genes in soleus muscle tissue.

Gene expression measurement (real-time PCR)

According to the manufacturer’s instructions, total RNA was extracted from soleus muscle tissues using Trizol Reagent (Kiazist, Iran). Then, the concentration of RNA samples was measured using a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, San Jose, CA, USA). RNA was reverse transcribed using the RevertAid™ First Strand cDNA Synthesis Kit for cDNA synthesis for qPCR using SYBR Green PCR Master Mix in StepOnePlus™ (Applied Biosystems, Carlsbad, CA, USA). PCR reactions were performed under the following conditions: 15 min at 95 °C for initial denaturation, followed by 40 cycles of 15 s at 95 °C for amplification, 15 s at 95 °C and 1 min at 65 °C for the melting curve, and finally, 20 s at 30 °C for cooling. The mRNA expression content of the desired genes was calculated by standard GAPDH expression and then by 2^{− CT∆∆} method¹⁸. The primers used for qRT-PCR are presented in Table 1.

Table 1.

The sequence of the forward-reverse primers of the genes desired for the real-time PCR reaction.

Gene	Forward (5′−3′)	Reverse (5′−3′)
GAPDH	AGGTCGGTGTGAACGGATTTG	TGTAGACCATGTAGTTGAGGTCA
Pgc1-α	CTTCGCTGTCATCAAACAGG	AACAAGCACTTCGGTCATCC
Mfn2	GAATCGGCACAGAGGAGAC	GACGGTGACGATGGAGTTG
Opa1	GATCATCTGCCACGGGTTGTT	GCCTTCACTGAGAGTCACCTT
Drp1	TTCTGAGCTATGTGGTGGT	AAATAAAGCTGGACGGGGG
Fis1	GGTTGCGTGGTAAGGGATG	CACCGCAGCCAGGACATAG

Biochemical analysis

Lipid profile including Total cholesterol (TC), Total triglyceride (TG), Low-Density Lipoprotein-cholesterol (LDL-C), High-Density Lipoprotein-cholesterol (HDL-C), Very Low-Density Lipoprotein-cholesterol (VLDL-C) was measured using Abcam commercial kits (USA) by an autoanalyzer (Hettich mikro-220R, Germany).

Statistical analysis

The Shapiro-Wilk test was used to determine the normal distribution of the data, and the Levene test was used to check the homogeneity of variance between the study groups. One-way ANOVA and Fisher’s or LSD post-hoc test were used to investigate the differences between groups. Also, the dependent T-test was used to examine intra-group changes in body weight and Lee’s index variables between the pre-test and post-test. Significance was accepted at p < 0.05. All data are presented as the mean ± standard deviation (SD). SPSS version 27 was used for statistical data analyses, and Excel was used to draw graphs.

Results

Homogeneity of variance was maintained in all groups (P > 0.05). Also, the distribution of data in all outcomes was normal (P > 0.05). Serum biochemical parameters of animals are presented in Table 2.

Table 2.

The serum characteristics lipid profile of the rats at the end of the ten weeks.

Variables	Control	Control + HIIT	HFD	HFD + HIIT
TC	87.8 ± 3.3	87.7 ± 3.8	177.5 ± 3.7 ‡	31.7 ± 3.9 §
TG	93.5 ± 6.9	96.7 ± 6.2	224 ± 5.1 ‡	212 ± 4
LDL-C	37.5 ± 2.8	38.4 ± 3.2	86.7 ± 3.2 ‡	57.3 ± 1.3 §
HDL-C	6.4 ± 1.1	6.6 ± 0.8	2.2 ± 0.5 ‡	4.6 ± 0.9 §
VLDL-C	17.6 ± 0.7	17.5 ± 0.8	35.5 ± 0.7 ‡	26.3 ± 0.8 §

‡ Significant difference between HFD and Control groups (P ≤ 0.05); § Significant difference between HFD and HFD + HIIT groups (P ≤ 0.05). HIIT: High-Intensity Interval Training; HFD: High-Fat Diet.

Body weight

Figure 1 shows the changes in weight (a and b) and Lee’s index (c and d) through ten weeks of intervention. At the baseline, there was no significant difference between the groups (P ≥ 0.05) (Table 3). After 10 weeks, the weight increased significantly in all groups (P < 0.001). In addition, the Lee’s index increased in all groups (P < 0.05), except for the control + HIIT group (P = 0.33). HFD consumption significantly increased body weight and Lee’s index compared to control and control + HIIT groups (P < 0.001). In addition, HIIT significantly reduced the weight and Lee’s index of the HFD + HIIT group compared to the HFD group (P < 0.001).

Fig. 1.

Weight and Lee’s Index Changes. HIIT training moderates HFD-induced weight gain and Lee’s index. a and b: Intergroup and Intragroup changes in weight. c and d: Intergroup and Intragroup changes of Lee’s index. HIIT: High-Intensity Interval Training; HFD: High-Fat Diet; W: Week. *P < 0.05; **P < 0.001.

Table 3.

Inter- and intra-group changes in body weight and Lee’s index variables.

Variables	Control	Control + HIIT	HFD	HFD + HIIT
Body weight
Pre	181 ± 4.33	205.33 ± 10.23	192.33 ± 9.24	206 ± 10.46
Post	273 ± 10.99 †	270.33 ± 9.43 †	451.5 ± 49.32 †‡	258.5 ± 10.07 †§
Lee’s index
Pre	286.42 ± 2.68	297.37 ± 1.89	293.52 ± 3.95	295.25 ± 2.53
Post	302.85 ± 3 †	299.58 ± 58	310.68 ± 1.66 †‡	302.13 ± 3.25 †§

† Significant difference between Pre and Post (P ≤ 0.001); ‡ Significant difference between HFD and Control groups (P ≤ 0.001); § Significant difference between HFD and HFD + HIIT groups (P ≤ 0.001). HIIT: High-Intensity Interval Training; HFD: High-Fat Diet.

Mitochondrial biogenesis

Pgc1-α gene

There was a statistically significant difference between groups as determined by ANOVA (F(3, 8) = 40.004, P < 0.001, ES = 0.938). HFD consumption significantly decreased Pgc1-α mRNA compared to control and control + HIIT groups (P < 0.001). No significant difference was observed between control + HIIT and control groups (P = 0.6). In addition, HIIT significantly increased the Pgc1-α mRNA expression in the HFD + HIIT group compared to the HFD group (P = 0.009) (Fig. 2a).

Fig. 2.

Effect of HFD consumption and HIIT exercise training on gene expression of Pgc1-α (a), Mfn2 (b), Opa1 (c), Drp1 (d), and FIS1 (e). HIIT: High-Intensity Interval Training; HFD: High-Fat Diet; Pgc-1α: peroxisome proliferator-activated receptor gamma coactivator 1-alpha; Mfn2; Mitofusins-2; Opa1; Optic atrophy-1; Drp1; Dynamin-related protein-1; Fis1: mitochondrial Fission protein-1. *P < 0.05; **P < 0.001.

Mitochondrial dynamics

Mitochondrial fusion genes

Mfn2 and Opa1

The difference between the groups in the mRNA of Mfn2 (F(3, 8) = 35.615, P < 0.001, ES = 0.930) and Opa1 (F(3, 8) = 26.026, P < 0.001, ES = 0.907) was significant. HFD consumption decreased Mfn2 and Opa1 mRNA compared to control and control + HIIT groups (for both P < 0.001). HIIT increased Mfn2 gene expression in the control + HIIT group compared to the control group (P = 0.026). However, it was not significant in the case of Opa1 mRNA (P = 0.38). In addition, HIIT increased Mfn2 (P = 0.004) and Opa1 (P = 0.011) mRNA expression in the HFD + HIIT group compared to the HFD group (Fig. 2b-c).

Mitochondrial fission genes

Drp1 and Fis1

There was a difference in the expression of Drp1 (F(3, 8) = 32.230, P < 0.001, ES = 0.924) and Fis1 (F(3, 8) = 48.992, P < 0.001, ES = 0.948) genes in the groups. HFD consumption increased Drp1 and Fis1 mRNA compared to control and control + HIIT groups (for both P < 0.001). There was no difference between the control + HIIT group and the control group for Drp1 (P = 0.658) and Fis1 (P = 0.384). In addition, HIIT decreased Drp1 (P = 0.003) and Fis1 (P = 0.027) mRNA expression in the HFD + HIIT group compared to the HFD group (Fig. 2d-e).

Discussion

The present study aimed to investigate the effect of HIIT on the expression of Pgc1-α, Mfn2, Opa1, Drp1 and Fis1 genes in the soleus muscle of male Wistar rats consuming HFD. Overall, the results showed that HIIT training moderates the effects of HFD consumption on related genes of mitochondrial biogenesis and dynamics.

The findings of our study indicate that HFD led to a significant increase in TC, TG, LDL-C, and VLDL-C, and a decrease in HDL-C. Furthermore, HIIT moderated this increase but did not restore the lipid profile to the values of the control group. The findings align with previous studies, Arunwan Udomkasemsab et al. (2018) showed that rats fed with HFD for 4 weeks experienced a significant increase in body weight, TC, TG, and LDL-C, while HDL-C levels decreased³⁷.

Studies have shown that HIIT moderates the negative effects of HFD consumption on lipid profile^38,39. Researchers showed that 20 weeks of HFD consumption (30% fat) increased TC and TG levels³⁹. In this study, one week (4 sessions) of HIIT led to a decrease in TC and TG levels³⁹. Another study also showed that 12 weeks of HFD increased the levels of TG, TC, LDL and VLDL and decreased HDL³⁸. Eight weeks of HIIT and moderate-intensity continuous training (MICT) could reverse the results³⁸. In addition, the results of this study showed that there was no significant difference between HIIT and MICT in reducing TG, TC, LDL, and VLDL levels. However, HIIT was significantly more effective in increasing HDL³⁸.

Reduced mitochondrial biosynthesis and disruption of mitochondrial dynamics lead to mitochondrial dysfunction⁴⁰. The Pgc-1 family (includes Pgc1-α and Pgc1-β), and peroxisome proliferator-activated receptor gamma (Ppar-γ), regulates mitochondrial biosynthesis and biogenesis³. Activation of Pgc-1 family consists of transcriptional coactivators under conditions of cellular energy demands, such as cell growth, hypoxia or exercise, promotes mitochondrial remodeling and intracellular energy balance⁴¹.

The effects of HFD on Pgc1-α levels are conflicting in the literature. Some studies have shown that HFD leads to a decrease in Pgc1-α levels, both at the gene expression^6,42, and protein level⁴³. However, other studies have demonstrated an increase in Pgc1-α protein levels^12–14 with HFD consumption, possibly through the Ppar-δ/Ppar-γ/Pgc1-α pathway¹⁴. It seems that the increase in fatty acids from HFD may not always stimulate this pathway, suggesting the need for further research using knockout models to better understand the signaling pathways affected by HFD-induced increase in fatty acids.

In addition, the results showed that ten weeks of HIIT increased the expression of the Pgc1-α gene, which can help mitigate the effects of an HFD. Previous studies have also demonstrated that HIIT can increase the Pgc1-α gene and protein in various tissues, including the liver tissue⁶, and gastrocnemius muscle of diabetic male C57BL/6J mice³³. In contrast, ten weeks of HIIT and endurance training had no significant effect on Pgc1-α protein levels in the quadriceps muscle of HFD-fed male C57BL/6J mice³⁵. The quadriceps muscle is generally composed of type two fibers⁴⁴. The density of mitochondria in type II fibers is lower than in type I. Therefore, it seems likely that Pgc1-α activity and responsiveness are low in fast-twitch muscles. While activity/expression may be low, fast-twitch muscles are actually more prone to an increase in PGC-1α expression upon training compared to slow-twitch muscles, which already have elevated basal expression. Additionally, detecting PGC-1α protein levels is notoriously challenging due to the widespread availability of nonspecific antibodies, complicating the interpretation of such results. Moreover, exercise-induced PGC-1α expression is typically transient, usually observed within 3–8 h post-exercise. This should be considered when addressing chronic elevations (i.e., > 24 h after the last exercise session, as in your study) of PGC-1α expression after a period of exercise training. As shown here, the control + HIIT group did not display increased PGC-1α expression compared to sedentary controls. However, the response of Pgc1-α to exercise training may vary depending on the type of muscle fibers and the intensity of the training. Overall, the findings suggest that HIIT training can positively impact Pgc1-α expression and may have beneficial effects on metabolic health in the context of HFD consumption.

Although the molecular mechanisms involved in the induction of mitochondrial signaling pathways by HIIT are unclear, there is evidence that intermittent effort and repetitive metabolic fluctuations in skeletal muscle may play a role⁴⁵. Following repeated muscle contractions, changes in the concentration of several metabolites in the cytosol, including an increase in the ADP/ATP ratio, calcium flux, an increase in the NAD⁺/NADH ratio, ROS production, and redox status, regulate the expression of genes encoding proteins involved in mitochondrial biogenesis⁴⁶. The metabolic sensors AMP-activated protein kinase (AMPK) and p38 mitogen-activated protein kinase (p38MAPK) phosphorylate Pgc1-α and regulate its transcriptional activity in skeletal muscle cells after high-intensity exercise^47,48. Furthermore, AMPK indirectly increases Pgc1 activity in response to HIIT via SIRT-1^49,50. However, the mechanisms of mitochondrial biosynthesis induced by the combination of exercise with HFD do not overlap⁵¹. Hence, more studies are needed to clarify and separate diet and exercise signaling pathways on mitochondrial biogenesis.

Phosphorylation of Ser616 and dephosphorylation of Ser637 induces Drp1 and leads to increased interaction between Drp1 and Fis1⁵². The result of this signaling pathway increases mitochondrial fission⁵². The results of the present study showed that consuming ten weeks of HFD led to a decrease in the expression of Mfn2 and Opa1 genes and a significant increase in Drp1 and Fis1. Previous studies support these results. Four weeks of HFD consumption has been shown to decrease the expression of Mfn1 and Mfn2 and increase Fis1 and Drp1⁵³. Other studies have shown differences based on the diet type: saturated fat increased Drp1 and FIS1, while unsaturated fat increased Mfn1 and Mfn2, leading to improved mitochondrial function^54,55. Recently, researchers have reported that 24 weeks of HFD consumption leads to a significant decrease in the levels of Mfn2 and Opa1 proteins in various tissues, including the heart, liver, spleen, kidneys, and quadriceps muscle of C57bL6j male mice⁵⁶. The answer to whether changes in gene expression are harmful is not straightforward. However, changes in gene expression can be associated with changes in protein levels^10,11. It seems, that regarding changes and reduction in gene expression related to mitochondrial biogenesis and dynamics, the impact on an organism’s fitness and health depends on various factors, such as the specific genes involved, the type of change, and the organism’s environment. Hence, it seems that HFD may have harmful consequences on muscles and even other body tissues.

Also, Drp1 protein levels following HFD consumption in different tissues showed different results. So that Drp1 decreased in the heart and liver, and increased in the kidney and quadriceps muscles⁵⁶. It seems that the functional nature of the tissues has an important role in their influence from diet. Mitochondrial distribution is strongly associated with high energy demand⁵⁷.

The results of the present study showed that HIIT for ten weeks increased the expression of Mfn2 and Opa1 genes, while decreasing the expression of Drp1 and Fis1 genes. This is consistent with previous studies in the liver⁶ and soleus muscle²⁹ in diabetic mice, where HIIT training was found to improve mitochondrial dynamics by increasing Mfn2 mRNA and decreasing Drp1 gene expression. In another study, the positive effect of exercise training on mitochondrial dynamics in the brain has also been shown. Eight weeks of continuous progressive aerobic training increased the levels of fusion (Mfn1, Mfn2, and Opa1) and decreased fission (Drp1 and Fis1) proteins in the hippocampus of male Sprague-Dawley rats fed an HFD for 16 weeks³¹. These results show that exercise moderates the consequences of HFD consumption on mitochondrial dynamics. On the other hand, various human studies have reported that endurance^58,59, HIIT^58,60, and Sprint Interval Training (SIT)^58–60 induce mitochondrial fusion in healthy subjects by increasing Mfn2 gene expression⁵⁹ and protein levels^58,60. Exercise training induces the phosphorylation of Drp1 at Ser637 through AMPK-mediated activation of A-kinase anchor protein 1 (AKAP1) and inhibits the interaction of Drp1 and Fis1, thereby inhibiting mitochondrial fission⁵². In addition, exercise training affects the glutathione antioxidant (GSH) system by increasing the use of oxygen during exercise and leads to an increase in GSH oxidation. Also, exercise training by increasing the production of oxidized glutathione (GSSG) and increasing the GSSG/GSH ratio leads to disulfide (-S-S-)-mediated Mfn oligomers and then induces mitochondrial fusion⁵².

On the contrary, it has been demonstrated that six weeks of HFD (45%) increased the levels of Mfn2, Drp1, and Fis1 proteins¹², which is contradictory to the results of the previous study^6,33. Because Pgc1-α has been shown to induce the expression of Mfn2¹⁵. It seems that the cause of Mfn2 increase is the induction of Pgc1-α by increasing fatty acids. In addition, the muscle response to low-intensity endurance or HIIT training significantly increases the levels of Mfn1, Mfn2, and Drp1 proteins, while significantly decreasing Fis1 levels in the EDL muscle of male Sprague-Dawley rats¹² and gastrocnemius muscle of C57BL/6J diabetic male mice³³. The type of fat in the HFD (saturated or unsaturated fat), access to food, target tissue (fast twitch or slow twitch muscles, liver, brain, etc.), and exercise protocol are factors that may contribute to the differences in results observed in different studies. Overall, the molecular and cellular responses of tissues to HFD and exercise can vary, suggesting a complex interplay between diet, exercise, and mitochondrial dynamics proteins.

Limitations and future research directions

In the present study, only gene expression was analyzed. Considering that the increase in gene expression is not necessarily associated with the increase in protein, it has been shown that Pgc1-α protein levels are increased under the influence of HFD through the increase and activation of Pparδ without increasing its gene expression¹⁴. Therefore, it is recommended to investigate gene expression and protein levels involved in the biogenesis up-and-down-regulation of the signaling pathway. Another limitation of this study and previous studies is the lack of measurement of calories consumed. Therefore, it is suggested that future studies in this area measure the amount of calories consumed. Due to the lack of assessment of changes in the functional indicators of mitochondria and morphology, it is suggested that future studies examine the number and size of mitochondria using an electron microscope. It is also recommended to check the variables of mitochondrial respiration.

The results of this study may contribute to our understanding of the complex interaction between exercise, nutrition and mitochondrial health and pave the way for future research in this area. Although this study provides important insights into the short-term effects of HIIT and HFD on mitochondrial function, more research is needed to examine the long-term effects of these exercises. Understanding the long-term effects of HIIT and HFD on mitochondrial health is important in developing disease prevention and treatment strategies. Additionally, the study focused on male Wistar rats. Future research should investigate whether the results can be generalized to other populations, including humans and individuals with different genetic backgrounds or health status. Understanding individual variability in response to HIIT and HFD is important to tailor interventions to specific needs.

Implications

The study’s findings could have important practical implications for individuals looking to enhance their health through physical activity and diet. A better comprehension of how HIIT and HFD interact to affect mitochondrial function can enable healthcare providers to offer more personalized advice on exercise and nutrition. Furthermore, mitochondrial dysfunction is linked to a range of conditions, such as metabolic disorders and neurodegenerative diseases. The results of the study suggest that HIIT could be a promising approach to preventing or alleviating these conditions by preserving mitochondrial health.

Moreover, the results of this study demonstrate the importance of considering both mitochondrial biogenesis and dynamics when examining the effects of exercise and diet on mitochondrial health. Furthermore, the study’s focus on gene expression provides valuable insight into the underlying mechanisms by which HIIT may counteract the detrimental effects of HFD on mitochondrial function. By identifying specific genes involved in mitochondrial biogenesis and dynamics, the results of this study contribute to our understanding of the molecular pathways involved.

This study’s key strength lies in the combined application of HFD regimen and HIIT interventions, which showed promising results in preventing and managing the consequences of HFD. While the findings may not directly translate from animal models to humans, they suggest that individuals consuming an HFD can benefit from HIIT to mitigate its consequences. This study underscores the potential of HIIT as a preventive measure for weight management and obesity, offering valuable insights for healthcare professionals and coaches. Future research should prioritize human subjects to validate and generalize these results.

Conclusion

Based on the results, HFD and HIIT have opposite effects on genes related to mitochondrial biogenesis and dynamics. Thus, HFD consumption reduces the expression of genes related to mitochondrial biogenesis and fusion. HIIT increases the expression of biogenesis and fusion genes. Also, HIIT moderated the increase in the expression of mitochondrial fission genes caused by HFD. As well as, HIIT training as a non-pharmacological treatment can manage weight and obesity status.

Abbreviations

AKAP1

AMPK-mediated activation of A-kinase anchor protein 1

AMPK

AMP-activated protein kinase

DRP1

Dynamin-related protein-1

EDL

Extensor digitorum longus

FIS1

Mitochondrial fission protein-1

HDL-C

High-density lipoprotein-cholesterol

HFD

High-fat diet

HIIT

High-intensity interval training

LDL-C

Low-density lipoprotein-cholesterol

MFN2

Mitofusins-2

MRC

Maximum running capacity

ND

Normal diet

Opa1

Optic atrophy-1

p38MAPK

p38 mitogen-activated protein kinase

PGC-1α

Peroxisome proliferator-activated receptor gamma coactivator-1-alpha

PPAR-γ

Peroxisome proliferator-activated receptor gamma

TC

Total cholesterol

TG

Total triglyceride

VLDL-C

Very low-density lipoprotein-cholesterol

Author contributions

M.J: Performing training protocol, Sampling, Data collection, Statistical analyses, and Manuscript preparation. Sh.Sh: Extensive editing and giving valuable comments for manuscript improvement. R.Gh: Editing and giving valuable comments for manuscript improvement.

Data availability

All data generated or analyzed during this study are included in this published article.

Declarations

Competing interests

The authors declare no competing interests.