# Spirulina liquid extract regulates gene expression related to glucose and lipid metabolisms of soleus muscle during exercise training in young male Wistar rats fed a high-fat diet

Jordi Vignaud, Céline Loiseau, Martine Côme, Josiane Hérault, Claire Mayer, Olivier Lépine, Lionel Ulmann

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Jordi Vignaud, Céline Loiseau, Martine Côme, Josiane Hérault, Claire Mayer, et al. Spirulina liquid extract regulates gene expression related to glucose and lipid metabolisms of soleus muscle during exercise training in young male Wistar rats fed a high-fat diet. Nutrition Research, 2025, 10.1016/j.nutres.2025.09.006. hal-05266390

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Original Research

# Spirulina liquid extract regulates gene expression related to glucose and lipid metabolisms of soleus muscle during exercise training in young male Wistar rats fed a high-fat diet ☆

<figure><img src="image_3.png" /></figure>

Jordi Vignaud<sup>a</sup>, Céline Loiseau<sup>a</sup>, Martine Côme<sup>a</sup>, Josiane Hérault<sup>a</sup>, Claire Mayer<sup>a</sup>, Olivier Lépine<sup>b</sup>, Lionel Ulmann<sup>a,*</sup>

## ARTICLE INFO

Article history:

Received 13 March 2025

Revised 10 September 2025

Accepted 10 September 2025

Keywords:

Spirulina liquid extract

Obesity

Soleus muscle

Glucose metabolism

Fatty acid metabolism

## ABSTRACT

Metabolic disorders induced by high-fat diets (HFD) contribute to obesity, diabetes, and cardiovascular diseases. While *Spirulina* liquid extract (SLE) has shown promise in improving lipid accumulation and insulin resistance, in vivo evidence remains limited, particularly in combination with exercise. Muscle activity is a key regulator of metabolism, but the potential combined effect of SLE and physical training under HFD conditions has not been established. In this study, young male rats were fed an HFD (60% energy from lipids) and assigned to four groups: HFD with 10% fructose (HF<sub>f</sub>), HF<sub>f</sub> with SLE (HF<sub>f</sub>SP), HF<sub>f</sub> with exercise (HF<sub>f</sub>T), and HF<sub>f</sub> with both interventions (HF<sub>f</sub>SPT). Bodyweight, lipid profiles, glycemia regulation, and gene expression in soleus muscle (SOL) of lipid and glucose metabolism were assessed. SLE reduced fasting glycemia compared to the HF<sub>f</sub> group (1.19-fold) and upregulated Gys1 (1.78-fold) and CPT1A expression (4.13-fold) in SOL. Training improved glucose tolerance, as reflected by reduced area under the curve (P = .01), and upregulated PGC1α and CPT1A expression. The combined intervention (HF<sub>f</sub>SPT) decreased bodyweight, increased high-density lipoprotein-cholesterol (1.62-fold), reduced the atherogenic index of plasma (1.39-fold). During training conditions, PGC1α expression was downregulated by SLE (3.03-fold), suggesting a possible interference with exercise-induced muscle adaptation. p38

<footnote><sup>a</sup>Department of Biological Engineering, BiOSSE Laboratory, Biology of Organisms, Stress, Health, Environment, IUT, Le Mans University, Laval, France</footnote>

<footnote><sup>b</sup>Société Algosource, Guérande, France</footnote>

<footnote>* *Abbreviations:* AIP, atherogenic index of plasma; AUC, area under the curve; BW, bodyweight; CD36, cluster of differentiation 36; CPT1A, carnitine palmitoyltransferase 1A; CVD, cardiovascular disease; Fabp4, fatty acid-binding protein 4; GLUT4, glucose transporter type 4; GTT, glucose tolerance test; Gys1, glycogen synthase 1; HDL-chol, high-density lipoprotein cholesterol; HFD, high-fat diet; IRS1, insulin receptor substrate 1; MAS, maximal aerobic speed; Non-HDL-chol, nonhigh-density lipoprotein cholesterol; p38 MAPK, p38 mitogen-activated protein kinase; PC, phycocyanin; PGC1α, peroxisome proliferator-activated receptor gamma coactivator 1-alpha; SLE, *Spirulina* liquid extract; TG, triglycerides</footnote>

<footnote>\* *Corresponding author* at: Département Génie Biologique, Laboratoire BiOSSE, Biologie des Organismes, Stress, Santé, Environnement, IUT, Le Mans Université, 52 rue des Drs Calmette et Guérin, 53020 Cedex 9 Laval, France. Tel.: + 33 (0)244 02 24 73.</footnote>

<footnote>E-mail address: lionel.ulmann@univ-lemans.fr (L. Ulmann).</footnote>
MAPK, elevated by HFD, was downregulated by SLE, exercise, and their combination (3.20-, 5.14-, and 2.72-fold, respectively). Overall, these findings support the potential of SLE as a complementary strategy to exercise in attenuating HFD-induced metabolic dysfunctions, while also raising concerns about possible interference with training adaptations.

© 2025 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

# 1. Introduction

According to a 2021 report by the World Health Organization, over 1.9 billion adults worldwide were classified as overweight in 2016, with more than 650 million falling into the obese category, with a prevalence that increased from 1975 to 2016 [1]. A significant contributor to the development of obesity is the rise in sedentary behavior, compounded by excessive consumption of foods rich in saturated fatty acids and refined carbohydrates [2,3].

Glucose and fatty acids are two major substrates utilized by mitochondria, specifically in skeletal muscle, playing a key role in the regulation of glycemia and lipid storage [4]. The glucose transporter type 4 (GLUT4), a major glucose transporter in muscle cells, is regulated under physiological conditions by insulin. Indeed, insulin binds to its receptor, where insulin receptor substrate 1 (IRS1) encodes a protein that triggers uni-directional pathways, activating the membrane translocation of GLUT4 and facilitating glucose entry into muscle cells [5]. Then, glucose can be transformed into glycogen by the glycogen synthase enzyme, which is regulated by the glycogen synthase 1 (Gys1) gene. The glycogen is stored in this form in skeletal muscle [6]. However, when fatty acids accumulate in the muscle cell cytosol, they can inhibit the activity of muscle GLUT4. As a consequence, pancreatic insulin secretion is increased to compensate for the inactivity of GLUT4, which leads to insulin resistance [4]. Without any physical activity, accumulated fatty acids are less oxidized and can induce lipotoxicity, which results in altered oxidation of fatty acids and glucose during mitochondrial dysfunction, leading to apoptosis and inflammation [7].

To counterbalance these alterations, physical training, particularly aerobic exercise, is recommended [8,9]. It has already been reported that aerobic physical exercise regulates body energy expenditure and helps to decrease body fat [10], increases fatty acid oxidation [11], improves the profile and metabolism of lipids and glucose [12,13], and regulates mechanisms involved in chronic inflammation [14]. Moderate aerobic exercise improves mitochondrial dynamics (fusion, fission) and biogenesis, as demonstrated in obese mice induced by high-fat diet (HFD) [15]. The regulation factor of mitochondrial dynamics is peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α), which has been shown to increase during aerobic training and decrease during HFD [16]. It is recognized that supplemented diets with specific carbohydrates, fatty acids, fibers, vitamins, probiotics, or natural bioactive ingredients from plants are effective in promoting weight loss and improving insulin sensitivity or glycemic control [17,18].

Among food supplements, microalgae are known to provide bioactive molecules such as proteins, carbohydrates, omega-3 polyunsaturated fatty acids, minerals, vitamins, or antioxidants [19]. Among these sources, the cyanobacterium *Spirulina platensis* has been particularly studied due to its high nutritional content: 50% to 70% protein, 15% to 25% carbohydrates, 6% to 13% lipids, 4% to 6% nucleic acids, and 2% to 5% minerals and vitamins [20,21]. It has been reported that *Spirulina platensis* can reduce bodyweight (BW), total cholesterol, and triglycerides (TG), while increasing high-density lipoprotein (HDL) cholesterol in humans [22]. In rats fed an HFD (60% of total energy intake), supplementation with *Spirulina* reduced glucose and insulin concentrations, thereby improving insulin resistance. These results suggest that *Spirulina* may have a beneficial effect on managing obesity-related insulin resistance [23]. One potential bioactive compound responsible for these antioxidant properties is phycocyanin (PC), which is found in high amounts in *Spirulina*. PC has demonstrated antidiabetic effects, including improved insulin sensitivity, regulation of lipid metabolism, and glycemic control [24]. Additionally, PC prevents weight gain during HFD consumption, modulates leptin and resistin concentration, and reduces proinflammatory conditions [25]. Recent studies have reported that a *Spirulina* liquid extract (SLE) rich in PC was able to protect against hyperglycemia, lipid accumulation, inflammation, and insulin resistance in mice and hamster models after hypercaloric diet consumption [26,27]. Moreover, in young rats fed a normocaloric diet, it has been reported that SLE increased physical performance and improved glucose and lipid metabolisms through a modified expression of genes such as GLUT4, Gys1, cluster of differentiation 36 (CD36), and carnitine palmitoyltransferase 1A (CPT1A) in the soleus muscle, a skeletal muscle essentially composed of type I fibers [28]. However, while the individual benefits of SLE and aerobic exercise are well documented, their combined effects on skeletal muscle metabolism under HFD conditions, particularly during growth, remain poorly understood. To our knowledge, no study has yet explored the synergistic potential of combining SLE supplementation with aerobic training in the context of early-life exposure to an HFD.

Thus, this study aimed to evaluate the effects of SLE as a food supplement in combination with physical training on HFD rats. Given that human adolescents are increasingly affected by metabolism alteration related to obesity during their growth, 2-week-old rats were submitted to HFD for 8 weeks, corresponding to an equivalent age of young adults. This experimental design allows us to address a key knowledge gap regarding the impact of early nutritional and lifestyle interventions on muscle-specific metabolic and energetic gene adaptations. In this study, plasma and soleus muscle samples
were analyzed. It has been hypothesized that supplementation with SLE, associated with aerobic exercise, may mitigate the negative effects of HFD on glucose and lipid metabolism in growing rats. Both interventions are expected to improve plasma parameters, with SLE modulating key metabolic genes such as GLUT4, Gys1, CD36, and CPT1A, reducing inflammation and insulin resistance through the antioxidant and anti-inflammatory properties of PC, while aerobic exercise enhances mitochondrial dynamics and biogenesis in skeletal muscle, promotes fatty acid oxidation, reduces lipotoxicity, and increases insulin sensitivity through the regulation of factors such as PGC1α. Moreover, the combination of SLE supplementation in combination with aerobic exercise may act to more effectively counteract HFD-induced metabolic alterations, improving glycemic control, glycogen storage, lipid metabolism, and muscle performance compared to each intervention alone.

# 2. Methods and materials

## 2.1. Animals

Thirty-two male Wistar rats, weighing 120 ± 10 g, were obtained from Janvier Labs (Le Genest-Saint-Isle, France). They were housed four per cage under controlled conditions of temperature, hygrometry, and with a 12 hours light/dark cycle. The rats with homogeneous weights were randomly distributed into the following groups: an HFD group (HF<sub>f</sub>), an HF<sub>f</sub> group supplemented with SLE (HF<sub>f</sub>SP), an exercise training group with an HF<sub>f</sub> diet (HF<sub>f</sub>T), and an HF<sub>f</sub>T group supplemented with SLE (HF<sub>f</sub>SPT). To improve the effect of the HF<sub>f</sub> diet, 10% fructose was added to the drinking water [29]. Indeed, fructose is recognized to stimulate TG synthesis and consequently increases fat storage, thereby promoting obesity [30–32]. Thus, the addition of 10% fructose aimed to mimic the combined effects of an HFD and sugar-sweetened beverages commonly observed in human consumption, thereby enhancing the metabolic disturbances induced by the diet. Moreover, fructose, like sucrose, can act as a stabilizing agent for PC contained in SLE by preventing its degradation. This property helps to preserve PC bioactivity and ensures that any observed physiological effects are due to the compound itself, thereby minimizing potential confounding effects related to its instability [33–35]. The experimental procedures, including the rationale for using the animal model and the specifics regarding the 3R rule (housing and husbandry, well-being, animal care and monitoring) have received approval from the Ethical Committee 006 Pays de la Loire and by the French Ministère de l'Éducation Nationale, de l'Enseignement Supérieur et de la Recherche (APAFIS #40394-202301111324826 v6, 23 February 2023).

## 2.2. Diets, supplementation, and BW monitoring

During a week of acclimatization, all animals were fed ad libitum with A04 diet (SAFE, Augy, France) and had free access to tap water. Then, the rats were fed the HF260 HFD, HFD (SAFE, Augy, France) for 8 weeks. According to the manufacturer's information, the ingredient composition of the HFD is reported

<table><caption>Table 1 – Manufacturer's formula of ingredients incorporated into high-fat diet for feeding the male Wistar rats [100].</caption><thead><tr><td>Ingredients</td><td>High-fat diet (HF260) (g/kg)</td></tr></thead><tbody><tr><td>Anhydrous butter</td><td>333</td></tr><tr><td>Acid casein</td><td>228</td></tr><tr><td>Maltodextrin</td><td>170</td></tr><tr><td>Sucrose</td><td>166</td></tr><tr><td>Soybean oil</td><td>25</td></tr><tr><td>Premix minerals AIN93M_G</td><td>45.5</td></tr><tr><td>Premix vitamins AIN93M_G</td><td>13</td></tr><tr><td>Sodium bicarbonate</td><td>10.5</td></tr><tr><td>Potassium citrate</td><td>4</td></tr><tr><td>Choline bitartrate</td><td>2</td></tr><tr><td>DL-methionine</td><td>2</td></tr><tr><td>Butylhydroxytoluene</td><td>0.02</td></tr></tbody></table>

in Table 1. Additionally, the drinking water for HFD groups was supplemented with 10% (w/w) fructose. The HF260 diet consists of 27% carbohydrates, 14% proteins, and 59% lipids, with a total energy of 5.52 kcal/g. The fructose-supplemented drinking water provides 0.4 kcal/mL. The SLE (commercialized as Spirulysat) was added to drinking water at a dose of 1.1 mg/100 g of BW and changed every day according to the previous study on hamsters [26]. The chosen dose of 1.1 mg of PC per 100 g of BW corresponds to a dose of 11 mg/kg of PC. PC typically represents between 15 and 20% of the dry biomass of *Spirulina*, depending on the strain, cultivation conditions, and drying methods [36]. Assuming an average content of 15%, one would need to consume 73.3 mg of *Spirulina* per kg of BW to reach this target dose (11/0.15 = 73.3). Thus, for a 70 kg adult, this corresponds to approximately 5 g of *Spirulina* per day. This estimate aligns with doses used in clinical and preclinical literature, which generally range from 13 to 100 mg/kg/d in humans and 10 to 1500 mg/kg/d in animals [37]. Concerning the PC dose, for a 70 kg adult human, a consumption of 1.1 mg/100 g of BW corresponded to 124.74 mg of PC per day [38], which is commonly used as a food supplement. Concerning safety analyses, a toxicological study using PC in animals employed a dose of 2000 mg/kg [39]. However, in this study, the methodology did not indicate whether this referred to a daily dose or a cumulative dose over 30 days. If administered daily, the dose would be several times higher than the one used in our study. Conversely, if the cumulated dose was over 30 days, then our cumulative dose over 56 days (616 mg/kg) remained considerably lower. In either case, no signs of toxicity were observed at our administered dose of 1.1 mg per 100 g of BW, justified by a previous study and ANSES report in 2017 [39,40]. The SLE was kindly supplied by Algosource (Guérande, France). Its composition is as follows [26]: PC (mg/L) 883; carbohydrates (g/100 g) 0.4; amino acids (g/100 g): threonine 0.009, aspartate 0.0187, alanine 0.0168, arginine 0.0138, leucine 0.0164, glutamate 0.022; ions (mg/kg): Fe<sup>2+</sup>, 1.05; Mg<sup>2+</sup>, 18; Ca<sup>2+</sup>, 330; K<sup>+</sup>, 55; Cu<sup>2+</sup>, 0.2. According to its composition (the calorie value was 1.67 kcal/100 g dry matter) and the daily provided dose, the SLE caloric supplement was considered negligible. Daily food and water consumption were monitored every day for 8 weeks.
The BW gain of the rats was monitored three times a week, and before training.

## 2.3. Training protocols

During the acclimatization week, all groups were familiarized with a treadmill (BIOSEB, Vitrolles, France) by gradually increasing the speed from 11 to 21 cm/s. Following this adaptation period, the rats distributed in the HF~f~T and HF~f~SPT groups participated in the exercise training protocol. On the final day of the adaptation week, maximal aerobic speed (MAS) was assessed for these groups to adjust the treadmill speed for the upcoming training week (data not reported). MAS was considered an index of exercise intensity, and endurance training was developed at 60%, 70%, and 80% of MAS [41]. Training sessions were conducted on the treadmill 5 days a week for 8 weeks. The MAS protocol started with a running speed of 15 cm/s, which increased by 3 cm/s each minute, followed by increments of 2 cm/s in the subsequent minute. The speed alternates between 3 and 2 cm/s and increases until exhaustion (adapted form of refs. [42,43]). MAS was assessed before each training block to adjust the training speed for the next session. The first training block was structured as follows: week 1 at 60% of MAS, week 2 at 70% of MAS, and week 3 at 80% of MAS. The next two blocks followed the same intensity progression based on MAS, with one additional rule: sprints were incorporated each week at an intensity 10% higher than the MAS prescribed for that respective week. These sprints were intended to improve MAS and further stimulate mitochondrial adaptations [44]. Additionally, each MAS test or daily training session began with a 6-minute warm-up, gradually increasing speed from 15 to 30 cm/s [45].

## 2.4. Glucose tolerance test

A glucose tolerance test (GTT) was conducted in the 7th week of the experimental protocol. The exercise protocol was halted 2 days before the test to eliminate any potential effects from recent training, and the rats were fasted the day before the test. Briefly, each rat received an intraperitoneal injection of glucose (1 g/kg BW), and glycemia was measured using a glucometer (Freestyle Papillon Vision) from tail vein samples. Glucose concentrations were recorded at baseline (0 minutes, before the glucose challenge) and then at 15, 30, 60, 90, and 120 minutes postinjection.

## 2.5. Blood and tissue sampling

After the final training day, a 3-day rest period was implemented to prevent any acute effects from exercise. The animals were then anesthetized with an intraperitoneal injection (0.1 mL/100 g of BW) of a mixture containing diazepam (5 mg/mL) and ketamine (100 mg/mL) in a 4:3 ratio (v/v). Blood samples were collected via the abdominal aorta using an ACD (acid-citrate-dextrose) anticoagulant solution, composed of 130 mM citric acid, 170 mM trisodium citrate, and 4% dextrose. The blood was subsequently centrifuged at 1000 × g for 10 minutes, and the supernatant was collected. The soleus muscle was harvested for biochemical and molecular analyses. All samples were aliquoted and stored at -80°C before analyses.

## 2.6. Plasma parameter analysis

Plasma concentrations of TG (CAK-1086, Clinisciences), total cholesterol (KA3709, Clinisciences), HDL cholesterol (HDL-chol, 90406, Biolabo), and insulin (17475383, Fisher) were measured following the manufacturer's instructions. The concentration of non-HDL-chol was calculated by subtracting HDL-chol from total cholesterol [46]. The atherogenic index of plasma (AIP) was calculated using the formula: $AIP = \log10(TG/HDL-chol)$ [47].

## 2.7. Muscle RNA extraction and gene expression

Thirty milligrams of soleus muscle were used for total RNA extraction, utilizing the RNeasy Fibrous Tissue Mini Kit (Abcam). RNA quantity was quantified by measuring absorbance at 260 nm using a Nanodrop OneC (Thermo Fisher Scientific).

Reverse transcription of RNA samples was performed using M-MLV Reverse Transcriptase (Promega) in a GeneAmp PCR System 9700 (Applied Biosystems). In the first step, 1 µg of RNA from each sample, 500 ng of oligo (dT)15 primers, and 500 ng of random hexamer primers were incubated in 15 µL at 70°C for 5 minutes to allow annealing. In the second step, 10 µL of a mix containing dNTPs (0.5 mM), M-MLV RT (200 U), RNase inhibitor (25 U), and M-MLV 1X buffer was added. The tubes were then incubated at 42°C for 1 hour, followed by incubation at 70°C for 5 minutes to inactivate the enzyme.

The resulting cDNA was diluted 4 times prior to use. Quantitative PCR was conducted using a QuantStudio 3 qPCR system (Applied Biosystems) with a standard program: an initial denaturation step at 95°C for 2 minutes, followed by 40 cycles of denaturation at 95°C for 15 seconds and annealing/elongation at 60°C for 1 minute. A total of 5 µL of cDNA was added to a 15 µL reaction mix containing 10 µL of GoTaq qPCR Master Mix 2X (Promega), 1 µL of each forward and reverse primer (10 µM), and 3 µL of nuclease-free water.

Primers were designed using Primer3 software. In a view to investigate the expression of genes associated with glucose, lipid, and mitochondrial metabolism, a list of primers has been designed (Table 2). Relative expressions were calculated using the 2(-ΔΔCt) method and normalized to tubulin α as the housekeeping gene [48].

## 2.8. Statistical analyses

Statistical power analysis was conducted using G*Power (version 3.1). Since the study involved independent groups without repeated measures, the “F test” family was selected, specifically the “ANOVA: fixed effects, omnibus, one-way” option. A post hoc power analysis was performed, setting the significance at 5% ($\alpha$ = 0.05) and the total sample size according to the variables. The effect size was calculated based on group means and the mean standard deviations of the groups. From these effect sizes and statistical power was computed and is reported in Table 3. Based on established guidelines for preclinical studies using one-way ANOVA [49], a minimum of 4 and a maximum of 6 animals per group is generally sufficient to maintain appropriate degrees of freedom for statistical analysis. In this study, 8 rats per group were used, exceeding the recommended minimum, to ensure adequate sta-
<table><caption>Table 2 – Primer sequences for the real-time PCR reaction.</caption><thead><tr><th>Genes</th><th>Abbreviations</th><th>Forward primers</th><th>Reverse primers</th></tr></thead><tbody><tr><td>p38 mitogen-activated protein kinases</td><td>p38 MAPK</td><td>TGCCAGGAATGGAGCCACAT</td><td>CATGGAGAAAACTGCCGCC</td></tr><tr><td>Carnitine palmitoyltransferase 1A</td><td>CPT1A</td><td>AGCTGGATCTGGGAAACGGG</td><td>TCGATCAATGTGGGAGGCC</td></tr><tr><td>Fatty acid binding protein 4</td><td>Fabp4</td><td>GCTGTACTGTCTGGGCCTCA</td><td>ATGAGAGGGTGGAGGTGCAG</td></tr><tr><td>Cluster of differentiation 36</td><td>CD36</td><td>ACTAAGCTGTTTGTGTGCCCC</td><td>ATCATCGAGTGGTGCTACTGGT</td></tr><tr><td>Glucose transporter 4</td><td>GLUT4</td><td>TTGACCAGATCTCGGCCACC</td><td>AGTGCTGCGAGGAAAGGAGG</td></tr><tr><td>Glycogen synthase 1</td><td>Gys1</td><td>ACCCATTCCCTGCCTGTTC</td><td>GCGATCCAAGAAAGGCACGG</td></tr><tr><td>Insulin receptor substrate 1</td><td>IRS1</td><td>GCACCTCTCATTCAGCCCT</td><td>CATGCAGCGTTTGTGGACCA</td></tr><tr><td>PPARG coactivator 1 alpha</td><td>PGC1α</td><td>TTCCAGAAGCTCCAGTGCCC</td><td>CCTGCTCAGCCATGCCTACT</td></tr><tr><td>Tubulin alpha 1</td><td>Tubα</td><td>CCACTTCCCTCTGGCCACTT</td><td>GGGACCACATCACCACGGTA</td></tr></tbody></table>

<table><caption>Table 3 – Mean standard deviation, effect sizes (f), and post hoc statistical power for each variable.</caption><thead><tr><th>Variable</th><th>Effect size f</th><th>Power</th></tr></thead><tbody><tr><td>Bodyweight</td><td>0.80</td><td>0.96</td></tr><tr><td>Area under curve (GTT)</td><td>0.78</td><td>0.94</td></tr><tr><td>Plasma triglycerides</td><td>0.83</td><td>0.97</td></tr><tr><td>Plasma cholesterol</td><td>0.40</td><td>0.40</td></tr><tr><td>Plasma HDL</td><td>0.95</td><td>0.99</td></tr><tr><td>Non-HDL cholesterol</td><td>0.82</td><td>0.93</td></tr><tr><td>AIP</td><td>0.72</td><td>0.85</td></tr><tr><td>Glycemia</td><td>0.80</td><td>0.96</td></tr><tr><td>Insulin</td><td>0.29</td><td>0.15</td></tr><tr><td>p38 MAPK</td><td>1.60</td><td>1.00</td></tr><tr><td>PGC1α</td><td>1.20</td><td>0.99</td></tr><tr><td>IRS1</td><td>0.60</td><td>0.70</td></tr><tr><td>GLUT4</td><td>0.40</td><td>0.50</td></tr><tr><td>Gys1</td><td>0.82</td><td>0.93</td></tr><tr><td>CD36</td><td>0.44</td><td>0.41</td></tr><tr><td>Fabp4</td><td>1.52</td><td>0.99</td></tr><tr><td>CPT1A</td><td>1.14</td><td>0.99</td></tr></tbody></table>

Abbreviations: AIP, atherogenic index of plasma; CD36, cluster of differentiation 36; CPT1A, carnitine palmitoyltransferase 1A; Fabp4, fatty acid binding protein 4; GLUT4, glucose transporter type 4; GTT, glucose tolerance test; Gys1, glycogen synthase 1; IRS1, insulin receptor substrate 1; p38 MAPK, p38 mitogen-activated protein kinase; PGC1α, peroxisome proliferator-activated receptor gamma coactivator 1-alpha.

This table represents the statistical power calculated from the effect size itself, determined from the mean standard deviation, number of values in experimental groups, and mean value of each variable in the study. When the statistical power is between 0.8 and 1, the statistical test used is considered robust and supports the identified differences.

Statistical power and account for potential variability, thereby strengthening the reliability of the experimental findings. Although flexibility in sample sizes (n = 5-8 per group) was allowed to account for potential exclusions due to aberrant values or technical issues during measurements. Outlier exclusion was justified using the ROUT method (Q = 1%) and further supported when the value differed by at least twofold from the mean of the remaining data points. All data are presented as mean ± standard error of the mean except for rat characteristics and plasma parameters (Table 4), where data are mean ± standard deviation. Normality was assessed using

the Shapiro-Wilk test. A significance of P < .05 was considered statistically significant. Differences between groups were evaluated using one-way ANOVA. The homogeneity of the variances was verified with parametric tests (Brown-Forsythe test and Bartlett's test). If the homogeneity was rejected, a Welch ANOVA was performed. On the other hand, if the normality was not followed, a nonparametric test (Kruskal-Wallis test) was performed. Post hoc comparisons were performed using Tukey's test following parametric ANOVA, Dunn's test following Kruskal-Wallis nonparametric ANOVA, and Dunnett T3's test following Welch's ANOVA when comparing each experimental group to the control group. For all tests, p-values were adjusted for multiple comparisons using GraphPad Prism (GraphPad Software Inc., San Diego, CA, USA).

## 3. Results

### 3.1. Effect of SLE and exercise training on BW

When comparing the $HF_f$ group to the $HF_f$SP group, no significant effect on BW (Table 4) was observed. However, training ($HF_f$T) led to a significant decrease in BW ($P = .04$) (Table 4) compared to the $HF_f$ group. Moreover, SLE supplementation did not interfere with this effect; training combined with SLE ($HF_f$SPT) resulted in a significant decrease compared to SLE alone ($HF_f$SP) ($P = .03$).

### 3.2. GTT improves with exercise training but remained unchanged with SLE

When HFD was supplemented with SLE ($HF_f$SP group), glycemia tended to decrease at T15 ($P = .1$) and T60 ($P = .1$), although the reduction was not statistically significant (Fig. 1A). In the trained groups, the area under the curve (AUC) was significantly reduced in $HF_f$T ($P = .01$) and $HF_f$SPT group ($P = .002$) compared to the $HF_f$ group (Fig. 1B), indicating that the effect would be attributable to exercise training. Moreover, at T15, the glycemia peak in the $HF_f$SPT group was significantly lower ($P = .0006$) than the $HF_f$T group one, demonstrating a cumulative effect of training and SLE supplementation (Fig. 1A).

In conclusion, SLE supplementation exhibited an effect in combination with exercise 15 minutes after glucose injection but not at other time points or on the AUC result.
<table><caption>Table 4 – Rat bodyweight, plasma lipid profile, glucose, and insulin concentrations.</caption><thead><tr><th>Parameters</th><th>HF<sub>f</sub></th><th>HF<sub>f</sub>SP</th><th>HF<sub>f</sub>T</th><th>HF<sub>f</sub>SPT</th><th>n</th></tr></thead><tbody><tr><td>Bodyweight (g)</td><td>495 ± 20<sup>ab</sup></td><td>527 ± 20<sup>a</sup></td><td>415 ± 26<sup>c</sup></td><td>444 ± 11<sup>bc</sup></td><td>7-8</td></tr><tr><td>TG (mmol/L)</td><td>2.2 ± 0.2<sup>b</sup></td><td>4.2 ± 0.7<sup>a</sup></td><td>2.6 ± 0.4<sup>ab</sup></td><td>2.2 ± 0.2<sup>b</sup></td><td>7-8</td></tr><tr><td>T-Chol (mmol/L)</td><td>1.2 ± 0.1<sup>a</sup></td><td>1.5 ± 0.1<sup>a</sup></td><td>1.3 ± 0.05<sup>a</sup></td><td>1.4 ± 0.2<sup>a</sup></td><td>8</td></tr><tr><td>HDL-Chol (mmol/L)</td><td>0.34 ± 0.03<sup>bc</sup></td><td>0.47 ± 0.06<sup>ab</sup></td><td>0.25 ± 0.03<sup>c</sup></td><td>0.55 ± 0.03<sup>a</sup></td><td>7-8</td></tr><tr><td>Non-HDL-Chol (mmol/L)</td><td>0.87 ± 0.06<sup>ab</sup></td><td>1.06 ± 0.07<sup>a</sup></td><td>1.08 ± 0.06<sup>a</sup></td><td>0.66 ± 0.07<sup>b</sup></td><td>7-8</td></tr><tr><td>AIP</td><td>0.82 ± 0.04<sup>ab</sup></td><td>0.93 ± 0.08<sup>a</sup></td><td>1.15 ± 0.10<sup>a</sup></td><td>0.59 ± 0.04<sup>b</sup></td><td>6-8</td></tr><tr><td>Glycemia (mg/dL)</td><td>65.2 ± 2.5<sup>a</sup></td><td>54.7 ± 2.3<sup>b</sup></td><td>53.0 ± 1.8<sup>b</sup></td><td>51.5 ± 2.2<sup>b</sup></td><td>6-8</td></tr><tr><td>Insulin (µIU/mL)</td><td>57.1 ± 3.0<sup>a</sup></td><td>67.9 ± 8.4<sup>a</sup></td><td>65.7 ± 7.7<sup>a</sup></td><td>74.7 ± 15.0<sup>a</sup></td><td>5-8</td></tr></tbody></table>

Abbreviations: AIP, atherogenic index of plasma; ANOVA, analysis of variance; HDL-chol, high-density lipoprotein cholesterol; HF<sub>f</sub>, high-fat diet group; HF<sub>f</sub>SP, HF<sub>f</sub> with *Spirulina* liquid extract supplementation; HF<sub>f</sub>SPT, HF<sub>f</sub>T with *Spirulina* liquid extract; HF<sub>f</sub>T, HF<sub>f</sub> with exercise training; IU, international units; non-HDL-chol, non-HDL-cholesterol; SD, standard deviation; TG, triglycerides.

The table represents the final bodyweight of experimental protocol, plasma concentrations of triglycerides, total cholesterol, high-density lipoprotein cholesterol, non-HDL-cholesterol, glucose, and insulin. The atherogenic index of plasma has been determined with the triglyceride and HDL-cholesterol values. The groups include high-fat diet group, with *Spirulina* liquid extract supplementation, with exercise training, or in combination with *Spirulina* liquid extract and exercise training. All experimental groups were fed a high-fat diet, with 10% fructose in the drinking water. The data are expressed as mean ± SD, n = 5 to 8 per group. Different letters a > b > c indicate statistically significant differences between groups (P < .05); a Kruskal–Wallis test was used for insulin and total cholesterol, while a one-way ANOVA was applied for the other parameters.

<figure><img src="image_4.png" /><figcaption>Fig. 1 – Evaluation of the effects of *Spirulina* liquid extract on glucose tolerance in experimental rats submitted an 8-week high-fat diet and exercise training. The combination of *Spirulina* liquid extract and exercise shows a faster reduction in the glycemic peak at 15 minutes after glucose injection compared to exercise alone, making the glycemia regulation more efficient than exercise alone. (A) Glycemic response (mg/dL) over a 120-minute period following glucose administration, glycemia were measured at 0, 15, 30, 60, and 120 minutes postglucose administration. The data are expressed as mean ± SEM with n = 6 to 8 rats per group. The following symbols indicate a statistically different (P < .05): & vs HF<sub>f</sub>, # vs HF<sub>f</sub>SP, and $ vs HF<sub>f</sub>T. (B) The area under the curve of the glycemic response curves is expressed in arbitrary units; data are expressed as mean ± SEM with n = 6 to 8 rats per group. Different letters a > b > c indicate statistically significant differences between groups (P < .05). A one-way ANOVA was performed for both A and B. All experimental groups were fed an HFD, with 10% fructose in the drinking water. ANOVA, analysis of variance; AU, arbitrary units; AUC, area under the curve; HFD, high-fat diet; HF<sub>f</sub>, high-fat diet group; HF<sub>f</sub>SP, HF<sub>f</sub> with *Spirulina* liquid extract supplementation; HF<sub>f</sub>SPT, HF<sub>f</sub>T with *Spirulina* liquid extract; HF<sub>f</sub>T, HF<sub>f</sub> with exercise training; SEM, standard error of the mean.</figcaption></figure>

### 3.3. Combination of SLE supplementation with exercise training improves plasma atherogenic index and HDL-chol concentration

SLE supplementation (HF<sub>f</sub>SP group) showed a significant increase in TG concentration (P = .009) and a decrease in fasting glycemia (P = .01) compared to the HF<sub>f</sub> group (Table 4). When SLE was combined with exercise training (HF<sub>f</sub>SPT group), TG concentration remained unchanged compared to the HF<sub>f</sub> group (Table 4). Moreover, the HDL-chol concentration increased significantly (P = .01) and fasting glycemia decreased (P = .0007) in HF<sub>f</sub>SPT compared to the HF<sub>f</sub> group, as ob-

served in the HF<sub>f</sub>SP one (Table 4). Notably, HDL-chol did not increase in the HF<sub>f</sub>T group, indicating a combined effect of both SLE supplementation and exercise training. Similarly, the AIP index and non-HDL-chol concentration were significantly lower (P = .001 and P = .002, respectively) in the HF<sub>f</sub>SPT group compared to the HF<sub>f</sub>T group (Table 4). Concerning the insulin and total cholesterol concentrations, no significant difference has been measured between experimental groups (Table 4).

In conclusion, while SLE increased triglyceridemia, this effect was not observed when combined with exercise training. Moreover, the combination of SLE and exercise led to an in-
crease in HDL-chol, as well as a decrease in the non-HDL-chol and AIP index.

### 3.4. SLE and training do not have the same effect on the mRNA expression of p38 MAPK and PGC1α in the soleus muscle

A significant downregulation of p38 MAPK gene expression was measured in the $HF_f$SP ($P < .01$), $HF_f$T ($P < .006$), and $HF_f$SPT ($P < .02$) groups compared to the $HF_f$ one (Fig. 2A). The combination of SLE with training did not induce any additional changes in p38 MAPK gene expression. During exercise training, the PGC1α gene expression was overexpressed ($P = .02$) ($HF_f$T compared to $HF_f$ group). However, when SLE supplementation was added ($HF_f$SPT group), the PGC1α gene expression was significantly downregulated ($P = .001$) in comparison to the $HF_f$ group (Fig. 2B). Moreover, a trend toward downregulation was observed between $HF_f$ and $HF_f$SP groups ($P = .1$).

To conclude, SLE alone decreased p38 MAPK gene expression, while no combined effect was observed with exercise training. Interestingly, PGC1α mRNA expression tended to decrease with SLE alone, but when combined with exercise training, its expression decreased significantly in the $HF_f$SPT group compared to the $HF_f$T one.

### 3.5. mRNA expression of glucose metabolism pathways are improved by SLE, demonstrating a similar effect to exercise training in soleus muscle

IRS1 gene expression was significantly downregulated in $HF_f$SP ($P = .01$) and $HF_f$T ($P = .04$) groups but not ($P = .1$) in the $HF_f$SPT compared to HF group (Fig. 3A). Then, GLUT4 gene expression was downregulated during exercise training condition ($P = .05$) ($HF_f$T group) and with SLE ($P = .05$) ($HF_f$SPT group) compared to the $HF_f$ group (Fig. 3B). In the other hand, Gys1 gene expression was significantly upregulated in all three conditions: $HF_f$SP, $HF_f$T and $HF_f$SPT ($P = .04$, $P = .04$ and $P = .05$, respectively) compared to the $HF_f$ group.

To conclude, regarding the IRS1 and Gys1 gene expression, SLE supplementation produced changes similar to exercise training, but without any added effect when combined with exercise training. The GLUT4 mRNA expression was downregulated with exercise training alone or with SLE supplementation.

### 3.6. Combination of SLE supplementation with exercise training regulates genes lipid metabolism with the upregulation of CPT1A and the downregulation of Fabp4 gene expression in soleus muscle

No significant effect of endurance training or SLE supplementation on CD36 gene expression was observed between groups (Fig. 4A). The Fabp4 gene expression tended to decrease with SLE supplementation alone ($HF_f$SP vs $HF_f$, $P = .1$) (Fig. 4B). In presence of exercise training and SLE supplementation ($HF_f$SPT group) or not ($HF_f$T), a significant downregulation of Fabp4 mRNA expression was observed ($P = .0003$ and $P < .0001$, respectively) compared to the $HF_f$ group (Fig. 4B). In the other hand, the supplementation with SLE ($HF_f$SP group)

<figure><img src="image_5.png" /></figure>

Fig. 2 – Effect of Spirulina liquid extract on gene oxidative pathways in the soleus muscle of rats fed a high-fat diet and submitted an exercise training for 8 weeks. Evaluation of the mRNA expression of p38 MAPK (A) and PGC1α (B). The Spirulina liquid extract, the exercise, and their combination both decrease the gene expression of p38 MAPK, an oxidative-sensitive protein. The PGC1α gene expression is upregulated with exercise, whereas with Spirulina liquid extract, a downregulation is measured. The data are expressed as mean ± SEM. Different letters correspond to significant comparisons a > b > c ($P < .05$), a one-way ANOVA has been realized for p38 MAPK, and a Welch ANOVA for PGC1α. All experimental groups were fed an HFD, with 10% fructose in the drinking water. ANOVA, analysis of variance; HFD, high-fat diet; $HF_f$, high-fat diet group; $HF_f$SP, $HF_f$ with Spirulina liquid extract supplementation; $HF_f$SPT, $HF_f$T with Spirulina liquid extract; $HF_f$T, $HF_f$ with exercise training; p38 MAPK, p38 mitogen-activated protein kinase; PGC1α, peroxisome proliferator-activated receptor gamma coactivator 1-alpha; SEM, standard error of the mean.

significantly upregulated CPT1A gene expression ($P = .003$) and this improvement was also observed in the presence of exercise training ($HF_f$SPT group) ($P = .05$) compared to the $HF_f$ group (Fig. 4C).

To conclude, SLE supplementation upregulates CPT1A expression, and this effect is maintained with exercise training.
<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

Fig. 3 – Effect of *Spirulina* liquid extract on glucose gene metabolism and pathways in the soleus muscle of rats fed a high-fat diet and submitted an exercise training for 8 weeks. Evaluation of the mRNA expression of IRS1 (A), GLUT4 (B), and Gys1 (C). SLE downregulated genes related to the insulin receptor, similar to exercise. Moreover, glucose-to-glycogen gene transformation are upregulated in skeletal muscle with *Spirulina* liquid extract that could lead to better glucose homeostasis and tolerance. The data are expressed as mean ± SEM. Different letters a > b > c indicate statistically significant differences between groups (P < .05); a one-way ANOVA has been performed for all genes. All experimental groups were fed an HFD, with 10% fructose in the drinking water. ANOVA, analysis of variance; GLUT4, glucose transporter type 4; Gys1, glycogen synthase; HF<sub>f</sub>, high-fat diet group; HF<sub>f</sub>SP, HF<sub>f</sub> with *Spirulina* liquid extract supplementation; HF<sub>f</sub>SPT, HF<sub>f</sub>T with *Spirulina* liquid extract; HF<sub>f</sub>T, HF<sub>f</sub> with exercise training; IRS1, insulin receptor substrate 1; SEM, standard error of the mean.

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

Fig. 4 – Effect of *Spirulina* liquid extract on fatty acid gene metabolism and pathways in the soleus muscle of rats fed a high-fat diet and submitted an exercise training for 8 weeks. Evaluation of the mRNA expression of CD36 (A), Fabp4 (B), and CPT1A (C). The fatty acid transport genes are not modified. However, the CPT1A gene expression, which is involved in fatty acid oxidation and transport into mitochondria, increases with the SLE. This could lead to a protective mechanism against lipotoxicity induced by a high-fat diet. The data are expressed as mean ± SEM. Different letters a > b > c indicate statistically significant differences between groups (P < .05), a one-way ANOVA has been performed for CD36 or Fabp4 genes, and a Kruskal–Wallis test for CPT1A gene. All experimental groups were fed an HFD, with 10% fructose in the drinking water. ANOVA, analysis of variance; CD36, cluster of differentiation; CPT1A, carnitine palmitoyltransferase 1A; Fabp4, fatty acid binding protein 4; HF<sub>f</sub>, high-fat diet group; HF<sub>f</sub>SP, HF<sub>f</sub> with *Spirulina* liquid extract supplementation; HF<sub>f</sub>SPT, HF<sub>f</sub>T with *Spirulina* liquid extract; HF<sub>f</sub>T, HF<sub>f</sub> with exercise training; SEM, standard error of the mean.
## 4. Discussion

The hypothesis that SLE supplementation combined with aerobic exercise mitigates the negative effects of HFD and 10% fructose on glucose and lipid metabolism was partially supported by the plasma results. In this study, the $HF_f$ group was considered a control group, while experimental ones were, in addition to HF diet, they were submitted to SLE supplementation ($HF_f$SP), exercise ($HF_f$T), or both ($HF_f$SPT). Thus, a limitation of this study could be the absence of control groups fed with a nonhyperlipidemic diet that would be considered a control diet, which would prevent isolation of SLE's effects from HF diet-induced pathology. It is the reason why in this section, the results were therefore only discussed in a limited way on the basis of an HF diet context. Exercise alone showed benefits in glycemic regulation, particularly by improving glucose tolerance. SLE supplementation had similar effects to exercise on fasting glycemia regulation, but no effect was observed on glycemia regulation measured by GTT. However, when SLE and exercise were combined, a decrease in glycemia at T15 was observed, suggesting a potential additive protective effect. Then, when SLE and exercise were combined, the lipid profile improved, with an increase in HDL-chol compared to the $HF_f$ group. When the combined group ($HF_f$SPT) was compared to the exercise group ($HF_f$T), a decrease in non-HDL-chol was observed. The absence of individual effects from SLE and exercise suggests that their combination produced a positive effect on lipid metabolism. Furthermore, the AIP index also decreased with both exercise and SLE compared to the exercise group ($HF_f$T). These findings indicate that the combination of exercise and SLE can improve both lipid and glucose metabolism regulation in plasma. Regarding muscle gene expressions, the hypothesis is also partially supported. Exercise training led to beneficial changes in genes such as PGC1α and p38 MAPK, which are involved in oxidative stress management and muscle adaptation. SLE supplementation alone appeared to increase glucose storage in the soleus muscle, as indicated by the upregulation of the Gys1 gene. Furthermore, when combined with exercise, SLE supplementation showed an upregulation of both Gys1 and CPT1A genes, suggesting potential benefits for muscle metabolism.

During this work, the effects of SLE supplementation with or without exercise training were investigated in rats fed an HFD with 10% fructose. Nutritional and plasma parameters have been studied, and gene expression in the soleus muscle has been analyzed after 8 weeks. Thus, in this section, the effects of SLE and exercise training, combined or not, will be discussed.

In the present conditions, it has been previously demonstrated that HFD increased BW, as already reported using the same experimental design [50]. However, SLE supplementation did not alter this parameter. In combination with exercise, a decrease in BW was observed. The PC in SLE has not been shown to have any effect on BW, regardless of the administered concentration in rats [51]. Thus, our results could be attributed to exercise rather than to the food supplement.

In a view to investigate the glucose absorption and the mechanisms associated with glycemia regulation, a GTT was performed. It is well-known that an HFD composed with satu-

rated fatty acids induces dysregulation in glucose homeostasis following glucose injection [29]. In this study, it was found that exercise training improved glycemic control and AUC, demonstrating its beneficial effect on glucose tolerance. This improvement could primarily be attributed to enhanced insulin sensitivity and increased lipid mobilization [52]. Interestingly, SLE supplementation alone induced a slight trend toward decreased glycemia. Although not significant, this trend could be explained by the PC content of SLE. Indeed, PC has previously been shown to improve glucose regulation. In KK-Ay mice, PC significantly reduced blood glucose concentrations during GTT [24]. Moreover, previous studies on hamsters supplemented with SLE under HFD conditions have similarly demonstrated reductions in fasting glycemia [26]. By these results, the present study showed that fasting glycemia was significantly lower in the $HF_f$SP group compared to the $HF_f$ group, and a similar effect was observed with exercise training. In contrast, plasma insulin concentrations remained unchanged whatever the experimental conditions. Whereas, it has been reported that PC can enhance pancreatic beta-cell function by activating the phosphatidylinositol 3-kinase/protein kinase B pathway, thereby offering protection against methylglyoxal, a glycation agent implicated in cellular damage during diabetes [53,54]. Therefore, our results do not agree with previous data. Further study would be needed to investigate this discrepancy and determine the specific conditions under which SLE supplementation may influence insulin concentrations.

In the HFD group supplemented with SLE, it has been observed a significant increase in triglyceridemia. However, the total cholesterol, HDL-chol, and non-HDL-chol remained unchanged compared to the HFD group ($HF_f$ vs $HF_f$SP). It has been reported that in hamsters supplemented with 0.2% cholesterol, the plasma TG concentrations decreased with PC [55]. Another study, conducted on a hyperlipidemia and altered lipid metabolism model using apolipoprotein E-deficient mice supplemented with the same SLE extract, reported an increased triglyceridemia ($P = .06$) in male mice [56]. Moreover, PC has been shown to increase the length of intestinal villi, thereby improving the gut's ability to absorb dietary fats, as demonstrated in mice [57]. Thus, as the plasma compartment can reflect food absorption, it could be proposed that SLE increased TG absorption in relation to HFD. Further studies should be necessary to dissociate the effects of SLE and PC, which appear to act differently. On the other hand, in the $HF_f$SPT group, this increase was not observed. Indeed, the review by Muscella et al. demonstrated that training reduces plasma TG concentrations through several mechanisms. First, lipoprotein lipase activity is increased, leading to the degradation of TG-rich lipoproteins. Second, there is a reduction in hepatic TG and very low-density lipoprotein production, which is associated with exercise-induced hypoinsulinemia. Finally, exercise promotes lipid oxidation and reduces circulating free fatty acid concentrations. In addition, TGs can be stored within intramuscular cells and more readily taken up by muscles during endurance training conditions [58]. These mechanisms related to exercise training could explain that no modification in triglyceridemia was observed in the $HF_f$SPT group. Moreover, exercise training is also able to increase intestinal barrier permeability [59]. Thus, the effects of exercise and PC on the intestinal barrier could affect permeabil-
ity and nutrient absorption. In order to better understand these effects on the intestinal barrier, other studies should be conducted to confirm the hypotheses proposed here. Interestingly, the HDL-chol in the $HF_f$SPT group increased significantly compared to the $HF_f$ and $HF_f$T groups. As HDL-chol is able to reverse cholesterol transport from peripheral tissues, it is considered protective against cardiovascular disease (CVD) [60,61]. It has already been reported that with or without an HFD, SLE or PC did not alter HDL-chol concentration in the serum of hamsters [26] or rats [51]. As expected, no modification in the HDL-chol concentration has been obtained using SLE ($HF_f$SP). Even if no effect has not been observed during training ($HF_f$T), it can be considered that a cumulative effect of these two parameters is obtained, related to the increase in plasma HDL-chol concentration (Table 4). Moreover, the non-HDL-cholesterolemia in the $HF_f$SPT group decreased significantly compared to the $HF_f$T and $HF_f$SP groups. The present study reported that total cholesterol was not modified whatever the conditions (Table 4). However, the HDL-chol increased and non-HDL-chol decreased when SLE and exercise training were combined, leading to a beneficial effect against lipid consumption, which is known to induce CVD [62]. Moreover, the AIP confirmed the evolution of both previous makers, with a decrease observed only in the $HF_f$SPT group. The AIP is considered a CVD marker and is calculated taking into account the TG and HDL-chol concentrations. A study has reported that it is able to reflect the lipid profile and atherogenic lipoproteins, highlighting its relevance [63]. Thus, our results support the preventive effect of SLE combined with exercise training on CVD risks.

Regarding relative gene expression, p38 MAPK responds positively to elevated pro-oxidant molecules in skeletal muscle and plays a role in glucose uptake independently of insulin [64]. The role of the stress-activated serine/threonine kinase p38 MAPK has been demonstrated in response to $H_2O_2$ exposure in L6 myocytes [65] and isolated rat skeletal muscle [66]. In the present study, SLE supplementation, exercise alone, and their combination downregulate the expression of p38 MAPK. According to the study by Vichaiwong et al. [64], exercise training can counteract the effects of an HFD and insulin resistance. This can explain the improvement observed during the GTT in the exercise groups ($HF_f$T and $HF_f$SPT). Moreover, HFD is known to induce oxidative stress in skeletal muscle composed of type 1 fibers [67]. Thus, interestingly, supplementation with SLE, exercise, or their combination led to a downregulation of p38 MAPK. This result is probably due to PC content, which has demonstrated anti-inflammatory and antioxidant effects [68]. Although based only on p38 MAPK gene expression, it is not possible to conclude an antioxidant effect; it would be necessary to perform additional biochemical measurements related to oxidative stress to verify the antioxidant capacity of SLE in muscle. $PGC1\alpha$ mRNA, known in skeletal muscle for regulating glucose metabolism, fatty acid oxidation, and mitochondrial turnover and dynamics [69], is typically downregulated by obesogenic diets [70,71]. In contrast, $PGC1\alpha$ expression significantly increased in the exercise training group ($HF_f$T), corresponding to mitochondrial biogenesis and muscle adaptation due to training [72,73]. However, in the $HF_f$SP group, the $PGC1\alpha$ gene expression tends to downregulate compared to the $HF_f$ group, while this downregulation

was significant, particularly in the $HF_f$SPT group compared to the $HF_f$T group. These measures are in line with the fact that PC possesses antioxidant properties capable of neutralizing reactive oxygen species such as hydrogen peroxide ($H_2O_2$), which plays a key signaling role in the activation of transcription pathways, as $PGC1\alpha$ gene [74,75]. The absence of upregulation in the $HF_f$SPT group, as in the $HF_f$T group, is considered incoherence; this effect could reflect an altered effect of SLE on exercise-induced adaptive signaling, through a mechanism of inhibition. A recent study has shown that PC exerts antioxidant effects comparable to those of vitamin C [76]. This is particularly relevant, as vitamin C is known to attenuate some of the beneficial adaptations to high-intensity exercise by interfering with reactive oxygen species-mediated signaling pathways that are essential for muscle adaptation [77]. However, this interpretation remains hypothetical and should be further investigated through complementary studies, particularly by directly measuring the antioxidant activity of SLE in muscle tissue and its effects on reactive oxygen species.

Interestingly, Gys1 expression was upregulated in the $HF_f$SP group compared to $HF_f$ group. It has been reported that in soleus muscle of Gys1 knockdown mice, glycogen concentrations decreased by around 70% compared to controls, and this was associated with glucose intolerance and peripheral insulin resistance [6]. Moreover, other studies have proposed that GLUT4 regulates glucose flux in skeletal muscle cells, which is also regulated by glycogen production [78]. GLUT4 membrane translocation is regulated by insulin pathways, notably IRS1 [79,80]. Based on this knowledge, in the $HF_f$SP group, an increase in Gys1 expression was observed compared to the $HF_f$ group, which is not consistent with the measure of GLUT4 expression. Moreover, in the $HF_f$SP group, IRS1 expression is downregulated compared to $HF_f$ group without negatively affecting GLUT4. However, the statistical power for GLUT4 (50%) is low, and it is possible that the effect size was too small to detect a significant difference. In another biological model, a previous study had reported that PC was able to stimulate the Ras-related C3 botulinum toxin substrate (Rac1) signaling pathway [81]. Or, in skeletal muscle cells, Rac1 is an independent insulin regulator of GLUT4 gene expression [82]. Due to its content in PC, it could be hypothesized that SLE induced an independent insulin mechanism leading to glycogen synthase activation in skeletal muscle, by activation of Rac1 signaling pathway. This suggests that SLE may exert a protective effect against insulin resistance, as demonstrated with exercise [83] or PC [84]. Interestingly, in the SLE group ($HF_f$SP), these effects are similar to those observed in the exercise training group ($HF_f$T) concerning the Gys1 and IRS1 gene expressions. Moreover, when SLE and exercise were combined, no significant difference was observed compared to the $HF_f$ group. However, a trend was noted, and the relatively low statistical power (70%) may have prevented the detection of a significant difference. Then, independently of IRS1 downregulation in the $HF_f$T group, it is known that GLUT4 is regularly modulated by exercise stress, thus increasing its turnover rate related to muscle adaptation [85]. Moreover, it has been reported that GLUT4 gene expression increased immediately after the last exercise but then decreased rapidly [86]. In our present experimental protocol, all measurements were per-
formed 3 days before the last running session, after which
adaptation had been completed, explaining the downregula-
tion of the GLUT4 gene expression in the HF<sub>f</sub>T and HF<sub>f</sub>SPT
group. The results obtained in the HF<sub>f</sub>SPT group to the HF<sub>f</sub> one
a no significant decrease has been reported for the IRS1, but
measured for GLUT4 gene expression, while a significant in-
crease in the GYS1 gene expression was observed. However, as
no significative difference is observed when compared to the
HF<sub>f</sub>SP and HF<sub>f</sub>T groups, it can be concluded that there is no
cumulative effect of SLE and exercise training on the expres-
sion of the studied genes. The results obtained for IRS1 and
GLUT4 showed low statistical power, and this should be taken
into account when interpreting the potential effects of SLE.
These findings on glucose metabolism genes demonstrated
a correlation; however, they do not support a causal infer-
ence. Further research is therefore needed to validate these
results.

Regarding genes implicated in lipid metabolism, only the
expressions of the Fabp4 and CPT1A genes were modified
during SLE supplementation or exercise training. The Fabp4
gene encodes a protein recognized as a marker of mature
adipocytes in muscle and is involved in intramuscular adipose
tissue development, leading to muscle atrophy and strength
loss [87,88]. Moreover, saturated long-chain fatty acids are
known to be captured by the CD36 transporter and trans-
ported by Fabp4 in the skeletal muscle cell cytosol; this path-
way is enhanced during HFD consumption [89]. Thus, with
SLE supplementation, a tendency toward decreased expres-
sion of the Fabp4 gene was observed. However, in physical
training condition, Fabp4 expression was significantly reduced
with or without SLE (HF<sub>f</sub>T and HF<sub>f</sub>SPT groups) compared to
the HF<sub>f</sub> group. These results suggest that it could be possible
that SLE play a protective role against intramuscular adipose
tissue, but not as effectively as exercise training. Moreover,
regardless of the condition, CD36 gene expression remained
unchanged, although Fabp4 did. This suggests that exercise
and SLE may act directly on fatty acid intracellular trans-
port mechanisms. Interestingly, SLE supplementation upreg-
ulated CPT1A expression. It has been reported that CPT1A is
an important mitochondrial transporter of long-chain acyl-
carnitine from the cytosol to β-oxidation [90], and its expres-
sion could be protective against an increased muscle lipid
uptake during HFD [91]. Other studies have proposed that
CPT1A could induce mitochondrial uncoupling. Indeed, when
the proton gradient generated by the electron transport chain
is dissipated as heat rather than being used for ATP synthe-
sis, it creates a futile cycle of glucose and fatty acid oxidation
[92–94], serving as a protective mechanism against metabolic
pathologies associated with HFD, such as metabolic syndrome
[95,96]. Moreover, Qiu et al. [97] reported for the first time
that CPT1A played an important role in maintaining muscle
stem cell homeostasis during muscle proliferation and regen-
eration. Based on these findings, although no effect of SLE
has been reported on CD36 gene expression, the statistical
power for this variable being low (41%). It is therefore possi-
ble that a significant effect could have been detected if the
effect size had been larger. The increased CPT1A expression
could be linked to an increase in fatty acid oxidation via β-
oxidation and may lead to mitochondrial uncoupling or play a
role in muscle rebuilding related to CPT1A and stem cell inter-

actions. In combination with exercise training (HF<sub>f</sub>SPT) com-
pared to the HF<sub>f</sub> group, an increase in the CPT1A gene expres-
sion is observed without any difference compared to the HF<sub>f</sub>T
group. These findings on lipid metabolism genes do not sup-
port a causal inference and require additional measurements,
such as β-oxidation rates or mitochondrial respiration as-
sessed through biochemical assays, to confirm these hypothe-
ses. It is known that exercise training can increase CPT1A
expression as an adaptive response in muscle metabolism
[98,99]. However, in our study, the HF<sub>f</sub>T group without SLE
did not show an increase in CPT1A expression. This suggests
that SLE might have a direct effect on CPT1A expression,
warranting further research to understand the underlying
mechanisms.

The results reported in this present study were obtained
using a concentration of PC at 1.1 mg/100 g of BW, which repre-
sents a relatively low dose for animals. However, when scaled
to humans, and taking into account the conversion factor km
(0.162) to convert a rat dose to a human one, it appears that
our administered dose corresponds to 124.74 mg for an adult
of 70kg [38]. Thus, it can be considered that our dose is com-
patible with doses that can be applied to humans. Moreover,
according to toxicological analyses, 1.1 mg/100 g BW does not
induce any sign of toxicity [39,40].

**5. Conclusion**

In conclusion, our study demonstrates that SLE supplemen-
tation, particularly when combined with physical exercise,
has beneficial effects on gene expression of glucose and lipid
metabolism in young rats exposed to an HFD. SLE supple-
mentation alone reduced fasting glycemia, upregulated Gys1
and downregulated IRS1 expression, indicating improved in-
sulin sensitivity and enhanced glucose-to-glycogen conver-
sion. Furthermore, exercise training independently improved
glycemic control, as evidenced by reduced glycemia and im-
proved glucose tolerance (AUC). Regarding lipid metabolism,
SLE supplementation increased TG concentrations, poten-
tially due to enhanced fat absorption. However, when com-
bined with exercise, it improved the lipid profile by increasing
HDL-chol, reducing non-HDL-chol, and lowering the AIP, key
indicators of cardiovascular health. Gene expression analysis
revealed an upregulation of CPT1A with SLE, suggesting en-
hanced fatty acid oxidation and a downregulation of Fabp4
with exercise, reflecting a protective effect against intramus-
cular adipose tissue accumulation. These findings suggest
that SLE supplementation, particularly when combined with
physical exercise, may serve as a promising strategy to coun-
teract the metabolic disturbances induced by HFD consump-
tion, including improving insulin resistance and reducing car-
diovascular risk factors. However, all results are based on
gene measurements and require biochemical and mechanis-
tic validation to confirm these measurements. Thus, further
studies are required to validate these results, better under-
stand the underlying mechanisms, and explore the long-term
effects of SLE supplementation and exercise on metabolic
health.
CRediT authorship contribution statement

**Jordi Vignaud:** Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Conceptualization. **Céline Loiseau:** Writing – review & editing, Writing – original draft, Validation, Supervision, Methodology, Conceptualization. **Martine Côme:** Methodology, Investigation. **Josiane Hérault:** Writing – review & editing, Methodology, Investigation. **Claire Mayer:** Writing – review & editing, Investigation. **Olivier Lépine:** Writing – review & editing, Supervision. **Lionel Ulmann:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Project administration, Conceptualization.

Acknowledgment

The authors acknowledge Frédérique Guéno and Isabelle Martin for their technical assistance during animal monitoring and tissue sampling.

Sources of support

The work was supported by the Collectivités Locales Mayen-
naises.

Author declarations

The authors declare that the research was conducted in the
absence of any commercial or financial relationships that
could be construed as a potential conflict of interest.

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