Anti-fatigue potential of glycoprotein from Periplaneta americana: improving oxidative stress and regulating the gut microbiota

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Glycoproteins from Periplaneta americana (PA), a medicinal insect resource, exhibit pharmacological activities (e.g., regulating the gut microbiota (GM), antioxidation and enhancing immunity) consistent with the core therapeutic targets for anti-fatigue. This study aimed to investigate the efficacy and mechanisms of PA glycoprotein (PAG) in anti-fatigue. The antioxidant capacity of PAG was evaluated by detecting antioxidant-related indexes in simulated gastrointestinal environment. The effectiveness of PAG in anti-fatigue was verified through swimming time measurement, histological staining and biochemical index monitoring. 16S rRNA sequencing, targeted metabolomics and Spearman correlation analysis were integrated to dissect the underlying mechanism of its anti-fatigue effect. PAG has excellent antioxidant activity. Secondly, PAG exerts anti-fatigue effects through multiple mechanisms: prolonged swimming time, improved liver injury, increased glutathione peroxidase and superoxide dismutase activities, decreased malondialdehyde level, promoted glycogen storage, simultaneously inhibited lactate dehydrogenase and creatine kinase activities, and reduced blood urea nitrogen and lactate accumulation in fatigued mice, altered the composition and structure of GM, and increased short-chain fatty acids (SCFAs) content. In conclusion, these findings suggest that PAG is promising candidates for anti-fatigue, and it warrants further systematic investigation for clinical translation. Biological sciences/Biochemistry Health sciences/Diseases Biological sciences/Microbiology Biological sciences/Physiology Gut microbiota anti-fatigue Periplaneta americana glycoprotein antioxidant Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Fatigue refers to the inability of an organism to maintain its physiological functions at a certain level, or to sustain appropriate exercise intensity, and is characterized by sustained lack of energy, decreased physical strength, and a sense of exhaustion throughout the body. It not only hinders daily activities, but also significantly reduces people's overall health and quality of life. Prolonged fatigue without effective relief can lead to the development of a variety of serious diseases, including neurodegenerative diseases like Alzheimer's disease, and metabolic disorders like obesity. In addition, fatigue is strongly associated with mental health problems, such as anxiety and depression 1,2 . However, the types of drugs currently used to relieve fatigue symptoms are limited and have obvious side effects 3-5 . With the development of society and fast-paced life, various enormous pressures have made fatigue-related syndromes a serious global health problem. Therefore, the exploration of novel bioactive substances with fatigue relieving properties has received extensive attention. The causes of fatigue are diverse and complex, and its pathophysiology and etiology have been fully unelucidated. At present, a large number of researchers have confirmed the mechanisms of relieving fatigue mainly include reducing oxidative stress damage 6 , regulating gut microbiota (GM) 7 , enhancing energy reserve 8 , and reducing metabolite levels 9 , etc. In particular, oxidative stress and imbalance of GM are regarded as factors closely related to fatigue. Sufficient evidence indicates that excessive exercise usually disrupts the balance of the body's oxidation/antioxidant system, so regulating the oxidation balance by eliminating acquired 1,1-diphenyl-2-picrylhydrazyl (DPPH), hydroxyl, and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radical is a way to alleviate fatigue 6 . Studies have demonstrated that short-chain fatty acids (SCFAs), the metabolites of GM, are energy sources for skeletal muscle and play a regulatory role in maintaining redox homeostasis in vivo. Modulating the balance of GM has been shown to extend exercise duration, enhance antioxidant enzyme activity, decrease metabolic byproduct accumulation, and promote glycogen storage in mice experiencing exercise-induced fatigue (EIF) 10 . Probiotics, such as Lactobacillus, Akkermansia , and Bifidobacterium , not only maintain intestinal balance but also promote the production of SCFAs to further exert anti-fatigue effects 11-13 . The above results clearly indicate that improving oxidative stress and regulating GM balance are effective means to alleviate fatigue. Significantly, due to the good biological activity of macromolecular substances like glycoproteins, they have attracted the attention of many researchers. Glycoproteins are a class of bioactive macromolecules formed by connecting sugar chains with proteins or peptides, widely existing in nature, which possess various pharmacological activities including anti-fatigue, antioxidation, regulating GM, anti-aging, immune regulation, and antitumor 14 . According to reports, glycoprotein can play an anti-fatigue role by scavenging excessive free radicals, improving antioxidant enzyme activity, increasing glycogen reserves, and reducing metabolites accumulation 15,16 . Trichiurus lepturus glycoprotein has been confirmed to have obvious antioxidant activity in vitro and relieve fatigue in exercise mice 16,17 . The glycoprotein of breast milk and edible bird's nest have various biological activities like antioxidant and regulating GM 18,19 . Therefore, glycoproteins have broad application prospects in the development of anti-fatigue functional products. Periplaneta american a (PA), commonly known as “cockroach”, was first recorded in the ancient book " Divine Farmer's Materia Medica " 20 . It is a famous traditional medicinal insect with a medicinal history of more than 2,000 years and has been widely raised and used commercially in China 21 . In ethnic minority areas of China, there has been a custom of eating insects since ancient times. PA is an insect with drug and food homology. In recent years, its medicinal and nutritional functions have attracted extensive attention and research. The adult powder of PA has been certified as a health supplement 22 . Modern studies have shown PA, which rich contain of bioactive substances such as amino acids, peptides, polysaccharides and nucleosides, exhibits a variety of pharmacological activities including antioxidation, regulating GM, wound repair, and immunomodulation 23-25 . Lu et al. confirmed PA Oligosaccharides played a preventive role in streptozotocin-induced diabetes in mice by reducing inflammation and oxidative stress, improving pancreatic function, enhancing immunity and regulating GM 26 . In recent years, numerous research pieces of evidence have revealed the excellent biological activity of macromolecular substances. Researchers firmly believe macromolecular substances are one of the key substances in PA that exert biological activity 20 . Based on this, our previous study isolated and purified PA glycoprotein (PAG) from PA, and characterized its structural composition, revealing that the total sugar and protein content of PAG are about 20.60% and 66.00%, respectively. PAG is mainly composed of 7 kinds of monosaccharides and 10 kinds of amino acids. The molecular weight of PAG was divided into 4 segments, among which the molecular weight of 66-14.5 kDa accounts for about 79.05% 27 . In previous research, we found that PAG can effectively eliminate DPPH, hydroxyl and ABTS free radicals to exert antioxidant activity 28 , and also promote the proliferation of Lactobacillus plantarum and Bifidobacterium adolesc entis and the generation of SCFAs 29 . Therefore, we scientifically speculate PAG can play a role in relieving fatigue through antioxidant, regulating GM, and increasing SCFAs content. For this reason, we first investigated the antioxidant activity of PAG under simulated gastrointestinal digestion environment. On this basis, we first established a fatigue mouse models by swimming tests, and detected fatigue-related indexes such as swimming time, antioxidant indexes and glycogen content. Subsequently, the diversity of GM in intestinal contents and the content of SCFAs in feces were analyzed. Finally, Spearman correlation analysis was used to analyze the correlation among GM, SCFAs and fatigue-related indexes to clarify the role and potential mechanism of PAG in preventing and alleviating fatigue. In summary, this study is intended to provide scientific evidence for PAG as a potential raw material for anti-fatigue drugs/nutritional supplements. Results In Vitro Antioxidant Activity of PAG Physical fatigue often results from the excessive accumulation of free radicals 30 . Therefore, we evaluated the antioxidant activity of PAG in a simulated gastrointestinal environment using several markers, such as total reducing capacity and ABTS, DPPH, and hydroxyl free radicals clearance ability, to supply data to support further research on the antioxidant and anti-fatigue effects of PAG in vivo. As shown in Fig. 1 , when assessed in the simulated gastric environment, no significant differences were observed in the total reducing capacity, DPPH, or hydroxyl free radicals scavenging capacity between the pepsin and gastric acid groups and the gastric blank group ( p > 0.05). With increasing PAG concentration, the ABTS free radical scavenging rate increased gradually. At the same PAG concentration, the ABTS free radical scavenging rate of the pepsin group was significantly greater than those of the gastric acid and gastric blank groups ( p < 0.01). After trypsin digestion, the total reduction capacity, ABTS and hydroxyl free radicals clearance rate of PAG increased with increasing concentration, as shown in Fig. 2 . The scavenging rate of the trypsin group was higher than that of the intestinal blank group, but there was no statistically significant difference in the rate of DPPH free radical clearance between the two sets of data ( p > 0.05). EIF Effect of PAG Effects of PAG on the Body Weight Change and Organ Index Body weight change and organ index reflect the effects of PAG and American ginseng capsules (AGC) administration on the health of mice. During the experimental period, the weight of mice in the 5 experimental groups continued to increase (Fig. 3 A). However, there was no significant difference in the weight change of the treatment groups compared with the control group ( p > 0.05), indicating that PAG and AGC didn't affect growth and development of mice. Moreover, the weight increase depended on food intake. We noted that intervention with PAG and AGC significantly reduced the liver weight of mice with EIF ( p < 0.01), suggesting that continuous high-intensity exercise might cause mild liver edema, resulting in an increased liver weight (Fig. 3 B). PAG appeared to alleviate oxidative stress in the liver, playing a protective role to a certain degree. The indexes of the other organs were not significantly different from those of the control group (Fig. 3 C-E) ( p > 0.05). Effect of PAG on Exhaustive Swimming Time The exhaustive swimming time of mice is one of the main indexes to study the anti-fatigue effect. The duration of weight-loaded swimming directly reflects the level of EIF mice. The longer the swimming time, the more effective the sample is at mitigating fatigue. Establishing a weight-loaded swimming model provides a reliable way to objectively evaluate the fatigue tolerance of mice and the anti-fatigue effects of samples 11 . As the PAG dosage was raised, the exhaustive swimming time of the mice increased compared to the control group (Fig. 3 F). The PAG-M (43 min) and PAG-H (43 min) groups swam for 27 min longer than the control group (16 min, p < 0.05), and also surpassed the positive group (32 min). This study confirmed that PAG prolonged exercise time in mice, improved their fatigue tolerance, and had a good anti-fatigue effect. Morphological Analysis of Liver Tissue According to the available literature 31 , EIF mice are closely related to liver metabolism, which includes oxidative stress leading to liver tissue damage during exercise. This is reflected in the microscopic observation results of the hematoxylin & eosin (H&E) staining paraffin sections of liver tissue, presented in Fig. 3 G. After free swimming for 30 min, the hepatocytes of mice in the control group had large intercellular spaces, loose cells, irregular nuclei arrangement, and different nuclei sizes. Conversely, in the PAG groups, the intercellular space gradually decreased with increasing PAG dosage, and the cellular structure tended to be normal. H&E staining confirmed that the hepatocytes of EIF mice were irregularly arranged, indicating that oxidative stress damage occurred in the liver tissue. After the administration of PAG, the arrangement of hepatocytes returned to normal, and oxidative stress injury of the liver tissue was alleviated to a certain extent. These findings suggest that PAG mitigated oxidative stress damage to hepatocytes in mice with EIF and played a protective role in liver function. Effect of PAG on Liver Speroxide Dismutase (SOD), Glutathione Peroxidase (GSH-Px) and Malondialdehyde (MDA) Critical antioxidant enzymes, such as SOD and GSH-Px, play a pivotal role in the body's defense against oxidative damage, while MDA is an important final product of lipid peroxidation triggered by a large amount of free radicals. Therefore, the SOD, GSH-Px, and MDA levels were measured to assess the anti-fatigue effects of PAG. Comparing the PAG and positive groups to the control group, we observed significant increases in the activities of SOD and GSH-Px in the liver of mice and a substantial decrease in MDA levels ( p < 0.01) (Fig. 4 A-C). These results suggest that PAG reversed the decline in antioxidant enzyme activity and the rise in MDA levels in the livers of exercise-fatigued mice, indicating favorable antioxidant activity in vivo. Moreover, the activities of SOD and GSH-Px and the content of MDA in the mice liver changed in a dose-dependent manner with the increase of PAG concentration. Effect of PAG on Blood Urea Nitrogen (BUN) and Lactic Acid (LA) During intense exercise, the body's metabolism generates harmful products BUN and LA, and the higher the accumulation, the greater the impact on exercise endurance. Therefore, they are regarded as factors leading to fatigue. In the control group, the expression of BUN in the serum and LA in the muscle increased, whereas PAG significantly reduced the levels of BUN and LA ( p < 0.05). Moreover, their levels decreased with increasing PAG dosage (Fig. 4 D, E). This suggests that PAG effectively eliminated the accumulation of the exercise metabolites LA and BUN, reduced exercise injury, and improved exercise tolerance in a dose-dependent manner. Effect of PAG on Lactate Dehydrogenase (LDH) and Creatine Kinase (CK) The levels of LDH and CK in serum are considered as biomarkers of muscle fatigue, so we detected their activity. As illustrated in Fig. 4 F, G, the LDH and CK activities in the PAG and positive groups were considerably lower than those in the control group ( p < 0.05). In the PAG-L, PAG-M, and PAG-H groups, the LDH activity were decreased by 13.18%, 25.10%, and 33.90%, and CK activity were reduced by 12.34%, 41.97%, and 55.61%, respectively. Our results indicate that PAG effectively inhibit the activities of LDH and CK in the serum of fatigued mice, thereby alleviating muscle injury caused by strenuous exercise. Effect of PAG on Muscle Glycogen (MG) and Liver Glycogen (LG) Glycogen storage reflects the body's tolerance to fatigue ang is an important index for fatigue evaluation. Therefore, we examined glycogen content in mice. As demonstrated in Fig. 4 H, the leg muscle MG content in the PAG and positive groups was significantly higher than that in the control group. Similarly, the amount of LG in the livers of mice in the PAG and positive groups was upregulated compared to that in the control group (Fig. 4 I) ( p < 0.01). Both the MG and LG contents gradually increased with increasing PAG dosage. The research indicated that PAG increased glycogen reserves in mice, serving as an energy source to supplement exercise consumption, and enhanced exercise tolerance in mice through energy consumption. Effects of PAG on GM Alpha Diversity Analysis of GM To investigate the effect of PAG on GM of fatigued mice, we performed 16S rRNA sequencing on colonic contents. Alpha Diversity analysis was used to analyze the community diversity of GM in mice (Fig. 5 A-D). The Chao1 and Ace indexes reflect the flora richness, and are positively correlated with community richness. The Shannon and Simpson indexes reflect the flora diversity, and the Shannon is positively correlated with the diversity of microbiota, whereas the Simpson is negatively correlated with it 13 . The Chao1, Ace, and Shannon values of the positive and PAG-L groups all increased and the Simpson value decreased compared to the control group, while the PAG-M and PAG-H groups showed the opposite phenomenon to the positive group. However, no significant variations ( p > 0.05) existed between the groups. The findings show that, following PAG intervention, there were no appreciable changes in the general composition and richness of the GM population of EIF mice. Beta Diversity Analysis of GM Beta diversity analysis is used to measure the differences in species diversity among different flora, revealing differences in microbiota structure among samples by comparing species composition between communities. To visually demonstrate these differences, we used principal coordinate analysis (PCoA) to reflect the differences among microbiota. In PCoA plot, the distance between samples reflects the similarity of microbial community composition and abundance. Specifically, the smaller the distance between samples, the more similar the microbial community composition and species abundance 13 . In Fig. 5 E, the dispersion degree of the microbiota in the positive, PAG-L, PAG-M groups compared to the control group was greater than the degree of overlap, indicating that there is a certain difference in microbial diversity of the mice GM. However, the GM of the PAG-H group was clearly separated from that of the control group, and had a certain intersection with the other treatment groups, indicating that a certain concentration of PAG effectively regulated the composition and diversity of the GM in fatigued mice, and formed a new community structure. Impact of PAG on the Phylum-level Structure and Composition of the GM To clarify the effects of PAG on the GM of exercise-fatigued mice, community structures among the different groups were compared at the phylum level (Fig. 5 F). The relative abundance of Firmicutes accounted for 82.79%, which was the major bacterial groups in the intestinal content of the control group mice. In addition, there were six phyla with relative abundances above 0.02%, namely Desulfobacterota (6.74%), Patescibacteria (4.95%), Actinobacteria (4.21%), Bacteroidetes (0.79%), Verrucomicrobiota (0.02%), and Bacteria_unclassified (0.24%). The effect of PAG on the GM at the phylum level was mainly concentrated in the Firmicutes, Actinobacteria, Verrucomicrobiota, Desulfobacterota, and Patescibacteria. Firmicutes dominated the GM of the PAG-treated mice, but there were differences in the relative abundance between the groups. Compared with the control group, the abundance of Firmicutes was upregulated by 6.49%, 4.31%, and 4.15% in the PAG-L, PAG-M, and PAG-H groups, respectively. In addition, the abundance of Desulfobacterota and Patescibacteria in the PAG group decreased to varying degrees compared to that in the control group, whereas Verrucomicrobiota and Actinobacteria increased to varying degrees. Impact of PAG on the Genus-level Structure and Composition of the GM Moving from the phylum level to the genus level, we examined the community structure of the gut bacteria in mice. The distribution of genera is shown in Fig. 5 G. The dominant bacteria in the mice intestines were Lactobacillus, Ligilactobacillus, Lactobacillaceae_ unclassified, Limosilactobacillus, Akkermansia, Bifidobacterium , and Desulfovibrio . Compared to the control group, the bacterial genera that showed increases in relative abundance in the intestinal contents after the different PAG concentrations were administered included Ligilactobacillus , Lactobacillaceae _unclassified, and Akkermansia . Meanwhile, the abundance of Limosilactobacillus , and Desulfovibrio , decreased. In addition, the relative abundance of Bifidobacterium and Faecalibaculum increased in the PAG-H group. Impact of PAG on GM Structure To further explore the biomarkers of GM in different groups of mice, we applied LDA effect size (LEfSe) differential analysis (Linear discriminant analysis (LDA) > 2) 32 . Figure 6 A represents an evolutionary branching diagram of LEfSe analysis, showing the taxonomic rank relationships from phylum to genus major groups of sample community. The predominant GM in the control group were Firmicutes and Desulfobacterota. The dominant microbial communities in PAG-L and PAG-H comprised Dubosiella and Bifidobacteria , respectively. Figure 6 B express the histogram of LDA value distribution from LEfSe analysis. This histogram shows the LDA threshold of each marker species, with higher values indicating more obvious differences in the species. In the control group intestinal contents, four phyla and 21 genera were identified. Those with LDA values greater than 4 included Limosilactobacillus, Desulfovibrionales , and Desulfobacterota, and the other groups followed in descending order. The abundance of Desulfovibrio significantly exceeded those of the other groups. In the positive group, a total of 12 genera were identified across three phyla (Firmicutes, Desulfobacterota, and Bacteroidetes), which were significantly different from the bacteria in the other groups. The abundance of bacteria in the PAG-H group was significantly higher than those in the other groups, with 13 genera across three phyla (Actinobacteria, Firmicutes, and Bacteria_unclassified), including five unclassified bacterial genera. In contrast, the PAG-M and PAG-L groups had only one identified for genera, all of which belonged to the Firmicutes, a prominent phylum of gut microorganisms that play a crucial role in maintaining GM balance. Effect of PAG on SCFAs Content Dysbiosis of GM profoundly affects the production of its metabolites, especially SCFAs, which play a crucial role in relieving fatigue. The effects of PAG on the SCFAs content in mice feces are shown in Fig. 6 C-F. When EIF mice were administered PAG, their feces had significantly higher levels of acetic acid, propionic acid, butyric acid, and valeric acid than the control group ( p < 0.05). Additionally, the amount of SCFAs increased as the PAG concentration rose. This indicated that PAG enhanced the secretion of SCFAs by the GM, thereby promoting intestinal health in mice and ultimately exerting an anti-fatigue effect. Spearman Correlation Analysis of GM, SCFAs, and EIF Evaluation Indexes To shed light on the “GM–SCFAs–anti-fatigue indexes” relationship, and ultimately clarify the potential pathways of PAG in alleviates fatigue. We conducted Spearman correlation analysis on GM, SCFAs, and fatigue resistance related indexes, including LDH, CK, BUN, LA, MG, LG, MDA, GSH-Px, SOD, and swimming duration, As shown in Fig. 7 A, the increase in SCFAs content after PAG administration was positively correlated with MG, LG, SOD content, and swimming duration to varying degrees, while exhibiting a negative correlation with LDH, BUN, and MDA content. Furthermore, butyric acid showed a negative correlation with CK and LA levels and a positive correlation with GSH-Px content. Further Spearman analysis between SCFAs and fatigue indexes underscored the close connection between SCFAs secretion and body fatigue. Figure 7 B, C depict the phylum level analyses. Firmicutes and Verrucomicrobiota displayed positive correlations with MG, LG, GSH-Px, SOD, SCFAs, and swimming duration to varying degrees. Actinobacteria were positively correlated to varying degrees with MG, LG, GSH-Px, and SOD content, but negatively correlated with LDH, CK, BUN, LA, MDA, and SCFAs. Desulfobacterota and Patescibacteria were positively associated with LDH, CK, BUN, LA, and MDA content and negatively associated with MG, LG, GSH-Px, and SOD content and swimming duration. Based on the above results, we speculated that PAG promoted the expression of SCFAs by upregulating the abundance of Firmicutes and Verrucomicrobiota in the intestinal contents. It also upregulated the abundance of Actinobacteriota and downregulated Desulfobacterota and Patescibacteria, which together inhibited the leakage of LDH and the accumulation of BUN, LA, and MDA, and promoted glycogen storage and oxidase activity, thereby increasing the fatigue tolerance of mice. Analyses at the genus level are shown in Fig. 7 D, E. The genera that were positively correlated with MG and LG content, GSH-Px and SOD activity, and swimming duration to varying degrees included Ligilactobacillus, Lactobacillaceae _unclassified, Akkermansia, Bifidobacterium, Faecalibaculum , and Lachnospiraceae _NK4A136_group, which were also negatively correlated with LDH, CK, BUN, LA, and MDA content. For example, Lactobacillus, Limosilactobacillus, Desulfovibrio, Candidatus_Saccharimonas , Lachnospireaceae_ UCG-006, Lachnospireaceae _unclassified, Turicibacter , and Oscillospiraceae _unclassified were positively correlated with LDH, CK, BUN, LA, and MDA to varying degrees but negatively correlated with other indexes. Moreover, Lactobacillus , Lactobacillaceae _unclassified, Akkermansia , and Dubosiella were positively correlated with SCFAs content to varying degrees. In summary, we inferred that PAG play an anti-fatigue role by regulating the richness of GM to promote the secretion of SCFAs, alleviating oxidative stress damage, reducing metabolite accumulation, and increasing energy storage. Discussion Fatigue is a complex physiological phenomenon involving a variety of mechanisms, including oxidative stress damage, energy metabolism disorders, and GM disorders. No studies have reported on the anti-fatigue effect and potential mechanism of PA, although a large number of research has shown that PA has a variety of pharmacological effects. In this study, we aim to elucidate the anti-fatigue effects and the potential mechanisms of PAG. Firstly, the antioxidant activity and activity stability of PAG in vitro were confirmed by simulating the gastrointestinal environment. Then, a fatigue mouse model was established to investigate the effects of PAG on fatigue-related indexes, GM, and SCFAs. Finally, the possible potential anti-fatigue mechanism of PAG was elucidated using spearman correlation analysis. The antioxidant activity of glycoproteins has been reported to be related not only to the intrinsic molecular structure but also to the direct antioxidant activity of some amino acids 31 . PAG is one of the key active ingredients of PA. The glycopeptide bonds in PAG are O-glycopeptide bonds, which remain stable under acidic conditions and easily dissociate into unsaturated amino acids under weakly alkaline conditions 20 . Therefore, PAG may maintain its original molecular structure in a simulated gastric digestion environment (pH = 2). PAG did not show significant changes in total reducing capacity or DPPH and hydroxyl free radicals clearance ability in the simulated gastric environment. However, the increased ABTS free radical scavenging rate may be the result of the increased exposure of antioxidant amino acid residues in some peptides of PAG without structural dissociation, which neutralizes the specific charge of ABTS radical, as reported by Ma 33 . In addition, trypsin can hydrolyze certain peptides into smaller peptides and amino acids 34 . The increased radicals scavenging rate of PAG in the intestinal environment was attributed to the decomposition of PAG by trypsin into smaller molecules. This resulted in an increased content of hydrophilic peptides and amino acids, leading to stronger binding with Fe 2+ , ABTS and hydroxyl radicals. However, this hydrolysis had no influence on lipophilic DPPH free radical. Our results demonstrate that PAG still has vigorous antioxidant activity during simulated gastric and intestinal digestion, indicating that PAG has good activity stability in the gastrointestinal environment. This study provides experimental evidence for subsequent research on the antioxidation and anti-fatigue effects of PAG in vivo. Intense exercise significantly elevates the body's levels of ROS causing an imbalance between the oxidative and antioxidant systems and a decrease in the body's overall antioxidant capacity. However, antioxidant enzymes play a crucial role in the body's defense against oxidative damage. As SOD and GSH-Px, SOD converts ROS into H 2 O 2 and O 2 , while GSH-Px and catalase break down H 2 O 2 into H 2 O and O 2 , effectively terminating the chain reaction of ROS, mitigating damage to the body, and delaying EIF 30 . MDA is an effective biomarker for oxidative stress triggered by excessive oxygen free radicals attacking membrane lipids, and its content is an index for evaluating the degree of fatigue 11 . Based on this, the activities of SOD, GSH-Px and the level of MDA were measured. The results showed that after PAG intervention, SOD and GSH-Px activities were increased in the liver of mice, while MDA level was decreased, indicating that PAG eliminated excessive free radicals, prevented lipid peroxidation, and protected the body from oxidative stress injury, which likely a pathway of its anti-fatigue effects. The antioxidant effect of PAG is consistent with our previous results 28 . Therefore, the good antioxidant activity of PAG was validated by both the in vitro and in vivo data. During anaerobic exercise, BUN is a byproduct of metabolic protein production after muscle glycogen depletion and serves as an index associated with fatigue 2 , 11 . The levels of BUN in serum gradually increase with continuous high-intensity exercise, and this increase is inversely correlated with exercise tolerance. In simpler terms, the higher the concentration of BUN, the poorer the body's adaptation to exercise 35 , 36 . LA is a common anaerobic metabolic byproduct of high-intensity exercise. Intense exercise accelerates oxygen expenditure and glycolysis, resulting in a large accumulation of LA in the body, which lowers the pH value of tissues and blood and causes a decrease in physical exercise endurance and fatigue 37 . As a result, LA is frequently employed as a crucial index to gauge levels of weariness. LDH can reduce the accumulation of LA produced in muscles during exercise and promote the conversion of LA to pyruvate 38 . As a critical enzyme involved in energy metabolism and ATP synthesis, CK activity surges as ATP is heavily depleted during exercise. The activity of CK in the serum has been confirmed as an index of post-exercise muscle damage 39 . Notably, our study revealed a dose-dependent manner decrease in LDH and CK activity in mice treated with PAG (The reduction values of the PAG-L, PAG-M and PAG-H groups were: LDH: 13.18%, 25.10% and 33.90%, CK: 12.34%, 41.97% and 55.61%), and effectively reduced BUN and LA stockpile, indicating that PAG can reduce fatigue-related metabolites pile up, lower body's damage caused by strenuous exercise, and exert an anti-fatigue effect, which is consistent with previous research results 2 . Glucose, mainly in the form of glycogen, is stored in the liver and skeletal muscles. When the body experiences hypoglycemia, LG is converted into glucose, and MG directly supplies energy to the muscle tissue through anaerobic glycolysis to replenish the energy consumed during exercise 37 . Therefore, glycogen content is often used to evaluate the anti-fatigue efficacy of tested drugs 37 . Our results confirmed that PAG significantly increased LG and MG content in fatigued mice, revealing the role of PAG in relieving fatigue by increasing energy storage. In recent years, a large number of studies have confirmed that maintaining the diversity of GM is very important for the body to keep normal physiological functions, and the key role of GM in relieving fatigue has also attracted the attention of many researchers 2 , 10 , 13 . In this study, PAG altered diversity and species abundance of GM in fatigued mice. Moreover, beta diversity analysis also indicated that PAG significantly adjusting the structure and composition of the GM in fatigued mice, which is consistent with previous study report 13 . Our research shows that, the effects of PAG on the GM at the phylum level was mainly concentrated in the Firmicutes, Actinobacteriota, Verrucomicrobiota, Desulfobacterota, and Patescibacteria. Firmicutes include a variety of butyric acid-producing bacteria. As the main energy source for colonic mucosal epithelial cells, butyric acid provides energy to the intestine, inhibits the growth of harmful bacteria, maintains electrolyte balance, and promotes repair of the intestinal mucosa 40 , 41 . Firmicutes play a role in synthesizing an enzyme responsible for carbohydrate degradation, indirectly influencing the body's anti-fatigue function 42 . Bacteroidota are also one of the main components of the human GM and are essential for preserving its equilibrium 43 . Actinobacteria are the dominant bacteria in the intestinal tract of mammals, and some Actinomycetes help to regulate certain bodily functions, including the immune system, intestinal homeostasis, and metabolism, by producing active metabolites 44 , 45 . PAG increased the abundance of Firmicutes, Verrucomicrobiota, and Actinobacteriota, and decreased Desulfobacterota and Patescibacteria. The changes in the structural composition of these microbiota suggest that, in the intestinal content of exercise-fatigued mice, the right amount of PAG increases the number of beneficial bacteria while preventing the phylum-level development of detrimental bacteria. This helps maintain intestinal environmental balance and, in turn, indirectly contributes to anti-fatigue effects. At the genus level, our analysis found that the predominant bacteria of the mice GM include Lactobacillus, Ligilactobacillus, Lactobacillaceae_ unclassified, Limosilactobacillus, Akkermansia, Bifidobacterium, Faecalibaculum , Lachnospiraceae -NK4A136-group, Turicibacter , and Desulfovibrio . Lactobacillus , Akkermansia , and Bifidobacterium are common members of the GM 44 . Lactobacillus and Bifidobacterium are important for intestinal homeostasis because they modulate intestinal tight junction protein expression, improve intestinal permeability, enhance intestinal barrier function, and inhibit the proliferation of harmful intestinal bacteria. Furthermore, through the inhibition of pro-inflammatory cytokines, they exhibit anti-inflammatory properties 44 , 46 . Lactobacillus also reduces the antioxidant activities of SOD and glutathione reductase in the liver, and alleviates liver oxidative stress injury 47 . Akkermansia , accounting for 3–5% of the microbial composition of the gastrointestinal tract in healthy humans, affects host functions, such as metabolism, inflammatory response, and immune regulation, and plays an important role in host health by ameliorating glucose and insulin levels to eliminate the risk of metabolic disorders 48 . Ligilactobacillus and Akkermansia maintain homeostasis in the intestinal microenvironment by maintaining the integrity of the intestinal mucosa 49 , 50 . Faecalibaculum has been reported to regulate duodenal epithelial homeostasis by remodeling the retinoic acid–eosinophil–interferon-γ-dependent circuit 51 . Butyrate-producing bacteria in the Lachnospiraceae _NK4A136_group preserve the integrity of the intestinal barrier in rats and have a negative correlation with intestinal permeability 52 . Limosilactobacillus can regulate the abundance of GM, promote intestinal homeostasis, and improve the inflammatory response of the host organism, thereby promoting human health through various channels 53 . Turicibacter is involved in the regulation of host bile acid metabolism and plays a part in the treatment of bile acid metabolism disorders caused by colitis 54 . It has also been reported that some Turicibacter s species are pathogenic and are often associated with inflammation in the host 55 . The sulfate-reducing bacteria Desulfovibrio can "breathe" sulfate and produce hydrogen sulfide, which is toxic to the intestinal epithelium and leads to gastrointestinal diseases 56 . Our results indicate that PAG alters the structure and abundance of the GM in exercise fatigue mice at the genus level, promotes the proliferation of some probiotics, and maintains the balance of the GM. Using the LEfSe differential analysis method, we identified significant differences in key species among the GM of mice in each group 32 . Analysis reveals that, PAG downregulated the abundance of Desulfobacterota in the intestinal contents of mice with exercise fatigue, while upregulating the relative abundance of probiotics, such as Bifidobacterium and Dubosiella . Dubosiella reduces MDA and increases SOD activity in aged mice, with various effects, such as decreasing oxidative stress and improving vascular endothelial function 57 . We reconfirm that the various PAG concentrations encouraged the growth of helpful bacteria while suppressing the growth of harmful bacteria, thus regulating the healthy balance of the GM. Interestingly, these findings are consistent with our previous studies 29 . SCFAs can promote the proliferation of intestinal epithelial cells, maintain the integrity of the intestinal barrier, prevent LA from entering the blood, and eliminate excessive LA buildup in the muscles, thus alleviating EIF 58 , 59 . Acetic acid, a major metabolite, serves as an essential energy source for the GM 60 . Propionic acid functions as an anti-inflammatory agent, is involved in immune regulation, and helps reverse fatigue-induced muscle damage 61 . EIF leads to intestinal damage and mucosal dysfunction 62 , whereas Butyric acid, the primary energy source for colonic epithelial cells, exhibits the highest utilization rate among SCFAs, maintains intestinal wall integrity, and simultaneously enables the self-apoptosis of cells with abnormal oxidative damage, thus preventing the occurrence of disease 63 , 64 . Therefore, we measured the content of SCFAs in mice feces using Gas Chromatography-Mass Spectrometer (GC-MS) targeted metabolomics, and found a significant increase in SCFAs content, which was dose-dependent on the dosage of PAG, suggesting that the PAG play a relieving fatigue a role by promoting the generation of SCFAs. Spearman analysis revealed that, within a certain range of PAG concentrations, as the content of SCFAs increased, the levels of MG, LG, and SOD increased, and the swimming duration prolonged, while the levels of LDH, BUN, and MDA decreased. In addition, butyric acid also enhanced the activity of GSH-Px and decreased the levels of CK and LA. Considering this, we speculated that PAG promotes the secretion of SCFAs in the intestinal, providing the energy substances needed by colon cells, and combines with SCFAs to resist oxidative stress damage in the body, which may be one of the pathways PAG's anti fatigue effects. Spearman analysis also found Limosilactobacillus , Turicibacter and other bacteria genera were positively correlated with the expression of metabolites key enzymes (LDH, CK) and metabolic wastes (BUN, LA and MDA). Additionally, the LEfSe analysis revealed that the intestinal contents of the control group contained considerably higher relative abundances of Limosilactobacillus and Turicibacter than those of the positive and PAG groups. Therefore, we inferred that the upregulation of these bacterial abundances accelerated exercise-fatigue in the mice, while PAG reduced the accumulation of metabolic waste by reducing the bacterial abundance, providing an anti-fatigue effect. In the LEfSe analysis, it was also found that the abundance of Bifidobacterium, Faecalibaculum , and other bacterial genera in the intestinal contents of swimming-induced fatigue mice intervened with PAG was upregulated compared to that in the control group. These bacteria were positively correlated with the expression of MG, LG, GSH-Px, and SOD, as well as swimming duration. Accordingly, we inferred speculated that PAG effectively enhanced the fatigue tolerance in mice by increasing the population of these microorganisms, MG and LG accumulation, and GSH-PX and SOD activity. The results of Spearman analysis of the GM at the genus level further showed that PAG had a regulatory effect on the GM of swimming-induced fatigued mice, and different GM had different regulatory effects on SCFAs and anti-fatigue indexes. In this study, it was first demonstrated that PAG has good antioxidant activity under simulated gastric and intestinal environmental conditions. Further, animal experiments have proved that PAG significantly prolong exhaustive swimming time, improve liver injury, rise the activities of SOD and GSH-Px and reduce the level of MDA in the liver, decrease the accumulation of BUN and LA and the activities of LDH and CK in the serum, augment the storage of LG and MG, optimize the structure of mice GM, increase the abundance of some beneficial bacteria, and promote the secretion of SCFAs, thereby prolonging the swimming time of fatigue mice. Finally, Spearman correlation analysis was used to demonstrate varying degrees of correlation among GM, SCFAs, and fatigue related indexes. In summary, this study elucidates the potential of PAG to exert anti-fatigue effects by reducing oxidative stress damage, decreasing metabolite accumulation, increasing glycogen storage, and regulating GM. This study provides a scientific basis for PAG as an anti-fatigue drugs/nutritional supplements and for its development and utilization. Future studies are needed to further clarify its exact target of action and validate its clinical impact on EIF and the effective dose range for the human body, thereby facilitating translational application. Materials and Methods Materials and R eagents PA was purchased from the GAP breeding base of Yunnan Jingxin Biotechnology Co., Ltd (Yunnan, China). PAG was isolated from PA via water extraction and alcohol precipitation. AGC were obtained from Xiamen Yongfuxing Health Products Co., Ltd. (Xiamen, China). Pepsin (porcine, activity: 1:10000), trypsin (from the porcine pancreas, activity: 1:250), and ABTS were obtained from Beijing Solarbio Science & Technology Co., Ltd. (Beijing, China). We acquired DPPH from Tokyo Kasei Kogyo Co., Ltd. (Tokyo, Japan). Appropriate kits for the determination of LG, MG, BUN, LA, LDH, CK, SOD, GSH-Px, MDA, and total protein were acquired from the Nanjing Jiancheng Biotechnology Institute (Nanjing, China). Acetic, propionic, butyric, and valeric acid standards were purchased from Sigma-Aldrich Co. (St. Louis, MO, USA). PAG Extraction from PA According to our previous research, the dried PA was processed through crushing (24 mesh sieve) and three extractions using ultrapure water (1/5, g/v) with heating reflux extraction. The resulting filtrate, concentrated to one-quarter of the total volume, was defatted thrice with petroleum ether (1/3, w/v) at 30 °C and precipitated using 95% ethanol (1/5, v/v), followed by 12 h at 4 °C. The precipitate was collected via centrifugation (4000 rpm, 10 min) and dissolved in an appropriate amount of water. Then, the free proteins were removed by employing a 3-fold volume of Sevag reagent (chloroform/n-butanol = 4/1, v/v), and the supernatant was concentrated and freeze-dried to obtain PAG. Formulation of PAG Solution for Simulating Gastrointestinal Digestion The method described in the literature was used to guide the preparation of simulated gastrointestinal fluid 65 , with slight modifications. To obtain the simulated gastric fluid, hydrochloric acid (4.2 mL) and pepsin (2.5 g) were added to deionized water, and the volume was fixed at 250 mL. The simulated intestinal fluid was prepared by mixing potassium dihydrogen phosphate (1.7 g), sodium hydroxide (adjusted to pH 6.8), deionized water (500 mL), and trypsin (10 g) and diluting it to 1000 mL with water. Simulated gastrointestinal digestion was performed as described by Sun et al . 66 , with slight modifications. A certain amount of PAG was weighed and dissolved in 0.9% normal saline to prepare PAG solutions with different concentrations for antioxidant experiments in simulated gastrointestinal environments. The PAG concentrations used to determine the total reducing capacities were 0.1, 0.2, 0.4, 0.8, and 1.6 mg/mL. The PAG concentrations used for the DPPH and hydroxyl free radicals scavenging experiments were 0.025, 0.050, 0.100, 0.200, and 0.400 mg/mL. The concentration of PAG for the ABTS free radical scavenging experiment were as follows: 0.01, 0.02, 0.04, 0.08, and 0.16 mg/mL. To obtain the pepsin, gastric acid, and gastric blank groups, 15 mL of simulated gastric juice, 0.01 mol/L hydrochloric acid, and 0.9% saline, respectively, was added to different concentrations (injection nitrogen) of the sample solutions. After digestion for 0 and 2 h, the samples were removed and centrifuged at 6000 rpm for 15 min. The supernatant was removed to obtain the simulated gastric digestion sample solution and stored at –80 °C. The 2 h pepsin group, which had varying concentrations of sample solutions and injected nitrogen, was mixed with simulated intestinal solution and phosphate buffer solution (pH ≈ 6.8) to generate sample solutions for the intestinal digestion and blank intestinal groups. After digestion for 0, 3, or 6 h, the sample solutions were removed, and the remaining steps were the same as those used for the simulated gastric digestion sample solution. Assessment of PAG Antioxidant Capacity in Simulated Gastrointestinal Digestion Total Reducing Capacity Assay The total reduction capacity of PAG was measured using the method described by Vasylie et al. 67 , with slight modifications. The phosphate buffer solution (0.025 mol/L, 1 mL) was transferred into a centrifuge tube with different concentrations of simulated gastric digestion sample solutions (0 and 2 h, 1 mL) and K 3 Fe(CN) 6 (1%, 1 mL), then centrifuged for 10 min at 4000 rpm. We mixed the supernatant with distilled water and FeCl 3 solution (0.1%, 0.5 mL), let it sit for 10 min, and measured absorbances A 1 and A 2 at 700 nm. The simulated intestinal digestion sample solutions (0, 3, and 6 h) were analyzed using the same method. Total reducing power was calculated using equation (1): Total reducing capacity = A 2 - A 1 , (1) where A 1 is the absorbance value of the sample and A 2 is the absorbance value of the control (containing an equal volume of distilled water instead of FeCl 3 solution). DPPH Free Radical Clearance Assay The scavenging rate of PAG on DPPH free radical activity was determined according to the method described by Lu et al. with slight modifications 68 . Various concentrations of simulated gastric digestion sample solutions (0 and 2 h, 1 mL) were mixed with DPPH (1 mL) and centrifuged at 4000 rpm for 10 min. The supernatant was then removed for the detection of absorbances A 0 and A 1 at 517 nm. The simulated intestinal digestion sample solutions (0, 3, and 6 h) were analyzed using the same method. The activity of DPPH free radical scavenging was calculated by employing equation (2): DPPH free radical scavenging activity (%) = ( A 0 - A 1 ) / A 0 × 100 , (2) where A 0 is the absorbance of the control (saline instead of the sample solution) and A 1 is the absorbance of the sample. Hydroxyl Free Radical Clearance Assay The method described by Xiao et al . 69 , with minor modifications, was used to generate hydroxyl free radical. Various concentrations of simulated gastric digestion PAG solutions (0 and 2 h, 1 mL) were mixed with FeSO 4 , a salicylic acid-ethanol solution, and H 2 O 2 (1%, 1 mL) at 37 °C for 30 min. The absorbances A 0 , A 1 , and A 2 were measured at 510 nm, using distilled water as a reference. The measurement method for the simulated intestinal digestion samples (0, 3, and 6 h) was the same as described above. The hydroxyl free radical scavenging activity was calculated using equation (3): Hydroxyl free radical scavenging activity (%) = (A 0 - A 1 + A 2 ) / A 2 × 100 , (3) where A 0 is the absorbance of the control solution (saline instead of the sample solution), A 1 is the absorbance of the sample, and A 2 is the absorbance of the sample with an equal volume of distilled water instead of H 2 O 2 . ABTS Free Radical Clearance Assay The detection of the PAG clearance rate of ABTS was conducted according to a previous method 68 , with minor modifications. An ABTS reserve solution was prepared by mixing equal volumes of ABTS liquid (7.4 mmol/L) and potassium sulfate (2.6 mmol/L), and adjusting its absorbance (A) at 734 nm with phosphate buffer (pH = 7.4) to achieve an A value of 0.70 ± 0.02, thus obtaining the ABTS working solution. The working solution (6 mL) was separately blended with various concentrations of simulated gastric digestion PAG solutions (0 and 2 h, 1 mL) and incubated for 6 min. The A 0 and A 1 absorbances were then detected at 734 nm. The simulated intestinal digestion sample solutions (0, 3, and 6 h) were analyzed using the same method. ABTS free radical scavenging activity was calculated according to equation (4): ABTS free radical scavenging activity (%) = (A 0 - A 1 + A 2 ) / A 2 × 100 , (4) where A 0 is the absorbance of the control (saline instead of the sample solution) and A 1 is the absorbance of the sample. Animals In this experiment, eighty healthy male Kunming species mouse (SPF grade, 6–8 weeks old, weighing 36 ± 3 g) were purchased from Hunan SJA Laboratory Animal Co., Ltd (Hunan, China; No. SCXK (Xiang) 2019–0004). Mice were kept at the Laboratory Animal Center of Dali University (Use License NO.: SYXK(Dian)2024-0001) at a temperature of 23 ± 1 °C, relative humidity of 55 ± 10%, alternating light and dark for 12 hours, and free access to feed and water. The mice were kept in this environment to adapt for one week. All experimental procedure strictly according to ARRIVE guide (https://arriveguidelines.org) and Dali university experimental animal ethics committee guidelines and related regulations, and by Experimental Animal Ethics Committee of Dali University (No. 2021-PZ-071; Approval date: 28 June, 2021). Experimental Design American Ginseng was recognized as an anti-fatigue compound 70 ; therefore, AGC was used as a positive control drug in this study, and its dosage was determined by pre-experiments and dosage conversion between mice and humans 71 . To determine the optimal dose of PAG, this study referred to the dose of the positive control group, and according to the results of the acute toxicity test (no toxicity at a dose of 40g/kg) and the pre-experiment, we designed three experimental groups with varying supplementation levels to systematically evaluate the anti-fatigue and dose-dependent effects. After one week of adaptation, based on a review of an extensive body of anti-fatigue-related literature 43,61,62 and rigorous calculations using PASS software and simple methods, eighty mice were randomly divided into five groups according to their body weight. With sixteen mice in each group, the sample size was sufficient to meet the statistical requirements for both the weight-loaded swimming experiment ( n =8) and the unloaded swimming experiment ( n =8). This design, which minimizes the sample size of experimental animals, is in line with the ethical standards for animal experimentation. The dose settings and assignments were as follows: the control group (saline), the positive group (AGC, 400 mg/kg/d), the PAG-L group (200 mg/kg/d), the PAG-M group (400 mg/kg/d), and the PAG-H group (600 mg/kg/d). The mice were administered once daily for 4 weeks by gavage, and weighed every 2 d for inter group weight comparison. During the study period, the mice were subjected to adaptive free swimming for 15–30 min using an experimental water tank (25 ± 2 °C, water depth 30 cm), twice a week. Determination of Exhaustive Swimming Time At the end of the fourth week, a weight-loaded swimming test was performed on 8 mice from each group to measure exhaustive swimming time. After the final gavage session lasting 30 min, the mice were deprived of food but could drink water for 12 h. Their tails were cleansed of grease, and they were loaded with lead skin weighing 5% of their body weight at the base of the tail. Subsequently, they were placed individually in a water tank, and timing began. The timing concluded when the mice sank to the bottom of the water due to exhaustion and remained submerged for 7 s, marking the point of exhaustion in swimming. The hair of each mouse was dried, and the mice were euthanized with an overdose of anesthetic (Isoflurane). Specifically, mice were sacrificed by the cervical dislocation method after excessive isoflurane anesthesia. Determination of Fatigue-related Biochemical Indexes By the conclusion of the fourth week, the remaining 8 mice in each group were subjected to a 12 h fasting period but allowed to drink water. Following a 30 min gap post-gavage, they engaged in free swimming without bearing additional weight for 30 min. Then, the mice were allowed to rest for 30 min before being anesthetized and blood samples were collected from the eyeball of each mouse. The collected blood was allowed to stand for 2 h at room temperature. It was then centrifuged for 15 min (4000 rpm, 4 °C) to separate the serum. Mice were sacrificed with an overdose of anesthetic (Isoflurane) and dissected immediately. Specifically, mice were sacrificed by the cervical dislocation method after excessive isoflurane anesthesia. The livers, kidneys, spleens, thymuses, and leg muscles were removed and measured mass. The organ index was calculated according to the following formula: Organ index (%) = organ mass (g)/mouse body weight (g) × 100%. The liver levels of SOD, GSH-Px, and MDA were examined to gauge the PAG antioxidant potential. The levels of BUN, LDH, and CK in the serum, as well as LA in the muscle were determined to evaluate the protective effects of PAG on muscle and exercise metabolites in mice. The expression of LG in the liver and MG in the muscle was detected to evaluate the effect of PAG on body energy in mice. The kit instructions were followed in determining the aforementioned indexes. Morphological Observation of Liver Tissue Partial liver samples were fixed for 18–24 h in a 4% paraformaldehyde solution fixative, then dehydrated in ethanol, embedded in paraffin, sectioned, and stained with H&E. To evaluate the protective effect of PAG on the livers of EIF mice, a light microscope outfitted with a Charge-coupled Device camera (BX-53, Olympus, Tokyo, Japan) was used to observe and photograph the gaps and color of hepatocytes. 16S rRNA Sequencing and Bioinformatic Analysis Genomic DNA was extracted from intestinal inclusion samples using a genomic DNA extraction kit (Omega Bio-Tek, Norcross, GA, USA), and 1% agarose gel electrophoresis was used to assess the DNA content and purity. Using the V3–V4 region of the 16S rRNA gene as the designated region for high-throughput sequencing, a specific primer with barcodes was synthesized. All samples were amplified through Polymerase Chain Reaction (PCR). Using the AxyPrep DNA Gel Recovery Kit (AXYGEN, San Francisco, CA, USA), the PCR products were recovered, after being detected using 2% agarose gel electrophoresis. The recovered products were quantified using a QuantiFluor™-ST Blue Fluorescence Quantification System (Promega, Madison, USA). To construct sequencing libraries and obtain sequence products, we utilized the Illumina PE250 platform. The high-throughput sequencing of samples was conducted at the Shanghai Yuanxin Biomedical Technology Co. (Shanghai, China). Paired-end reads were obtained from the Illumina PE250 platform and spliced according to the overlap relationship, and the sequence quality was controlled and filtered to obtain the optimized sequence. Using Usearch (v7.01090) for cluster sequences, sequences were classified into the same operational taxonomic units (OTUs) when the similarity was 97% or more. The Ribosomal Database Project Naive Bayes classifier (v2.2, http://sourceforge.net/projects/rdp-classifier/) was used to perform taxonomic analysis on representative OTU sequences, and the community composition of the samples was separately calculated at different taxonomic levels (phylum and genus). Furthermore, alpha and beta diversity index analyses were performed based on the results of the OTU cluster analysis. LEfSe was typically utilized to analyze the variations in microbiota between groups and identify the major microbiota among groups. The relative microbiota abundance of corresponding groups (LDA > 2) was found to be higher than that of other groups, as indicated by an LDA score greater than 2. We employed Spearman’s correlation analysis to examine the relationships between SCFAs, GM, and EIF indexes. This analysis helped us understand how these factors related to one another and their connection to the anti-fatigue properties of PAG. Determination of SCFAs Content Determination of the SCFAs content was based on the method described by Yang et al. 72 , with some modifications. The mouse fecal samples (0.15 g) were precisely weighed, added to methanol (1 mL), vortexed for 3 min, ultrasonicated for 2 min, and thoroughly mixed to prepare a fecal suspension. Following a pH adjustment (pH = 2.0–3.0) with concentrated sulfuric acid, the suspension underwent a 2-min vortex, was centrifuged for 20 min at 5000 rpm, and the supernatant was collected and filtered through a 0.45 μm microporous membrane. Acetic, propionic, butyric, and valeric acid standards were prepared appropriately, and methanol was added to prepare mixed standard solutions at concentrations of 1, 0.75, 0.75, and 0.15 mol/L, respectively. The filtrate was analyzed using a GC-MS (Agilent, Santa Clara, CA, USA) with an Agilent DB-WAXDB-WAX chromatography column (30 m × 250 μm, 0.25 μm). Helium (0.5 mL/min) was used as the carrier gas, with a 1 μL injection volume and 10:1 shunt ratio. The temperature of the column was initially set to 110 °C and kept at that level for 2 min. After that, it was raised to 135 °C at a rate of 5 °C/min and kept at that level for 0 min. Finally, it was raised to 150 °C at a rate of 1 °C/min and kept at that level for 0 min. It was further increased to 160 °C at 5 °C/min, maintained for 0 min, and finally raised to 200 °C at 10 °C/min, with a maintenance period of 0 min. The mass spectrometry conditions were as follows: Agilent 5975C detector at 230 °C, inlet at 230 °C, ion source at 230 °C. Statistical Analysis All the data were expressed as mean ± standard deviation (SD) after processing with SPSS 22.0 software (SPSS Inc, Chicago, IL, USA). Data comparison between groups was performed using one-way analysis of variance. At p < 0.05, statistical significance was established; compared to the control group: * p < 0.05, ** p < 0.01; compared to the positive group: # p < 0.05, ## p < 0.01. Declarations Data availability All the raw sequencing data involved in this study have been deposited in the NCBI SRA database, with the accession number PRJNA1335858. In addition, other raw data have been uploaded to the Mendeley database (https://data.mendeley.com/datasets/5w3skwj28k/1, published on September 18, 2025), DOI: 10.17632/5 w3skwj28k. 1. The name of the dataset is the same as the title of the article. Acknowledgments The authors are grateful for the support of the Analytical and Testing Center of Dali University (Dali University, Dali, China), and Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D (Dali University, Dali, China). Author Contributions Z.C. and X.Y.: Conceptualization, Formal analysis, Methodology, Investigation, Software, Writing—original draft. J.Z.: Software, Validation. K.L.: Visualization. R.H.: Data curation. Y.Y.: Formal analysis. J.W.: Software. Z.H.: Project administration, Funding acquisition, Writing—review and editing. P.X.: Project administration, Resources, Methodology, Supervision, Funding acquisition. All authors have read and agreed to the published version of the manuscript. Funding This study was supported by Basic Research Key Projects of Science and Technology Department of Yunnan Provincial (grant number 202501AS070162); Joint Project of Basic Research of Local Universities in Yunnan Province (grant number 202401BA070001-007); and the Yunnan Expert Workstation (grant number 202405AF140044). The APC was funded by Peiyun Xiao. Competing interests The authors declare no competing interests. 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15:56:31","extension":"xml","order_by":39,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":202810,"visible":true,"origin":"","legend":"","description":"","filename":"4e62c189188a480e9b0189815d7110341structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7515364/v1/46e49e02d41cf24136b54d7a.xml"},{"id":94728443,"identity":"00cd4197-45cc-453f-94f3-a3ca1f35997f","added_by":"auto","created_at":"2025-10-30 07:03:49","extension":"html","order_by":40,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":226487,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7515364/v1/2055f868a57be20bde2007d5.html"},{"id":94688393,"identity":"cfe3ddba-d613-4eb6-a5ec-9c421454bd90","added_by":"auto","created_at":"2025-10-29 15:56:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1403291,"visible":true,"origin":"","legend":"\u003cp\u003eAntioxidant activity of PAG in simulated gastric environments (\u003cem\u003en\u003c/em\u003e= 3). Changes in total reducing capacity and ABTS, DPPH, and hydroxyl free radicals scavenging rate: 0 h: \u003cstrong\u003eA-D\u003c/strong\u003e; 2 h: \u003cstrong\u003eE-H\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7515364/v1/212b08179ea475dad38fc457.png"},{"id":94728740,"identity":"c8916ce2-76c6-4abc-9b3e-0f0b72ddf920","added_by":"auto","created_at":"2025-10-30 07:04:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2539450,"visible":true,"origin":"","legend":"\u003cp\u003eAntioxidant activity of PAG in simulated intestinal environments (\u003cem\u003en \u003c/em\u003e= 3). Changes in total reducing capacity and ABTS, DPPH, and hydroxyl free radicals scavenging rate: 0 h: \u003cstrong\u003eA-D\u003c/strong\u003e; 3 h: \u003cstrong\u003eE-H\u003c/strong\u003e; 6 h: \u003cstrong\u003eI-L\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7515364/v1/b5a95786294b72d87cbadd9a.png"},{"id":94728870,"identity":"49b08ff6-2c36-48e9-80ef-d79d7c35bbc1","added_by":"auto","created_at":"2025-10-30 07:04:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":21341475,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of PAG on body weight, organ indexes, swimming time and liver pathology in EIF mice (\u003cem\u003en \u003c/em\u003e= 8). (\u003cstrong\u003eA\u003c/strong\u003e) Body weight; (\u003cstrong\u003eB\u003c/strong\u003e) Liver index; (\u003cstrong\u003eC\u003c/strong\u003e) Spleen index; (\u003cstrong\u003eD\u003c/strong\u003e) Thymus index; (\u003cstrong\u003eE\u003c/strong\u003e) Kidney index; (\u003cstrong\u003eF\u003c/strong\u003e) Swimming time. Note: Comparedto the control group: * \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, ** \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.01; compared to the positive group: # \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, ## \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.01. (\u003cstrong\u003eG\u003c/strong\u003e)H\u0026amp;E staining sections of liver tissue (\u003cem\u003en\u003c/em\u003e=8, Scale bars: 20 µm): (\u003cstrong\u003ea\u003c/strong\u003e) The control group, (\u003cstrong\u003eb\u003c/strong\u003e) The positive group, (\u003cstrong\u003ec\u003c/strong\u003e) The PAG-L group, (\u003cstrong\u003ed\u003c/strong\u003e) The PAG-M group, (\u003cstrong\u003ee\u003c/strong\u003e) The PAG-H group.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7515364/v1/41738e1cdddaf421db5e7575.png"},{"id":94688402,"identity":"593f9ed8-2f6f-406c-99a4-7c1acb36b4be","added_by":"auto","created_at":"2025-10-29 15:56:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1350563,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of PAG on relevant fatigue indexes in EIF mice (\u003cem\u003en \u003c/em\u003e= 8). \u003cstrong\u003e(A)\u003c/strong\u003e SOD; \u003cstrong\u003e(B)\u003c/strong\u003e GSH-Px; \u003cstrong\u003e(C)\u003c/strong\u003e MDA;\u003cstrong\u003e (D)\u003c/strong\u003eBUN; \u003cstrong\u003e(E)\u003c/strong\u003e LA; \u003cstrong\u003e(F)\u003c/strong\u003e LDH; \u003cstrong\u003e(G)\u003c/strong\u003e CK; \u003cstrong\u003e(H)\u003c/strong\u003e MG; \u003cstrong\u003e(I)\u003c/strong\u003eLG. Note: Compared to the control group: *\u003cem\u003e p\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; compared to the positive group: # \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, ## \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7515364/v1/c784206790c5c7e850fed03e.png"},{"id":94688396,"identity":"5ddb71d8-95b6-4751-991d-f1a07fa0bffe","added_by":"auto","created_at":"2025-10-29 15:56:30","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2227291,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of PAG on the diversityand composition of the GM (\u003cem\u003en \u003c/em\u003e= 5).\u003cstrong\u003e (A) \u003c/strong\u003eChao1 index; \u003cstrong\u003e(B)\u003c/strong\u003e Ace index;\u003cstrong\u003e (C) \u003c/strong\u003eShannon index;\u003cstrong\u003e (D) \u003c/strong\u003eSimpson index; \u003cstrong\u003e(E)\u003c/strong\u003e Beta diversity analysis of GM; \u003cstrong\u003e(F)\u003c/strong\u003e relative abundance of microbesat the phylum level in the GM community of mice from different treatment groups; \u003cstrong\u003e(G) \u003c/strong\u003erelative abundance of microbes at the genus level in the GM community of mice from different treatment groups.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7515364/v1/d525dafb1fd102ac8e40de20.png"},{"id":94688397,"identity":"9e7c3706-faa4-4c67-bd53-1661290d9a75","added_by":"auto","created_at":"2025-10-29 15:56:30","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":6550142,"visible":true,"origin":"","legend":"\u003cp\u003eLEfSe differenceanalysis on GM and content of SCFAsof the effectof PAG in mice (\u003cem\u003en \u003c/em\u003e= 5).\u003cstrong\u003e (A) \u003c/strong\u003ePhylogenetic branching map of GM;\u003cstrong\u003e (B) \u003c/strong\u003eBar graph of LDA value distribution of GM. \u003cstrong\u003e(C) \u003c/strong\u003eAcetic acid; \u003cstrong\u003e(D)\u003c/strong\u003e Propionic acid; \u003cstrong\u003e(E)\u003c/strong\u003e Butyric acid; \u003cstrong\u003e(F) \u003c/strong\u003eValeric acid. Note: Compared to the control group: * \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, ** \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.01; compared to the positive group: # \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, ## \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7515364/v1/dd6502b2a37d32968b88725c.png"},{"id":94688408,"identity":"a0c3f288-e35d-4143-a83b-1871589c2ea9","added_by":"auto","created_at":"2025-10-29 15:56:30","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":691068,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman correlation analysis between GM, SCFAs, and host fatigue-related indexes. Positive correlations are shown in red, and negative correlations are shown in blue.\u003cstrong\u003e (A) \u003c/strong\u003eCorrelation analysis between SCFAs and fatigue indexes in the feces of fatigued mice; \u003cstrong\u003e(B, C)\u003c/strong\u003e Spearman correlation analysis between fatigue-related indexes, SCFAs, and changes in GM at the phylum level; \u003cstrong\u003e(D, E)\u003c/strong\u003e Spearman correlation analysis between fatigue-related indexes, SCFAs, and changes in GM at the genus level.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7515364/v1/4716debb79a1fc6d004c2e86.png"},{"id":98243964,"identity":"407c6804-e938-461d-943c-1e7d062c4b4b","added_by":"auto","created_at":"2025-12-15 16:11:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":36721333,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7515364/v1/ef1949ba-c997-40bf-984c-1b75bac0572c.pdf"},{"id":94688394,"identity":"f21e22ea-a6a8-4c13-a65e-bf8c96806e06","added_by":"auto","created_at":"2025-10-29 15:56:30","extension":"tif","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1199282,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.tif","url":"https://assets-eu.researchsquare.com/files/rs-7515364/v1/4ab68da870ef91698c4a4743.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Anti-fatigue potential of glycoprotein from Periplaneta americana: improving oxidative stress and regulating the gut microbiota","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFatigue refers to the inability of an organism to maintain its physiological functions at a certain level, or to sustain appropriate exercise intensity, and is characterized by sustained lack of energy, decreased physical strength, and a sense of exhaustion throughout the body. It not only hinders daily activities, but also significantly reduces people\u0026apos;s overall health and quality of life. Prolonged fatigue without effective relief can lead to the development of a variety of serious diseases, including neurodegenerative diseases like Alzheimer\u0026apos;s disease, and metabolic disorders like obesity. In addition, fatigue is strongly associated with mental health problems, such as anxiety and depression \u003csup\u003e1,2\u003c/sup\u003e. However, the types of drugs currently used to relieve fatigue symptoms are limited and have obvious side effects \u003csup\u003e3-5\u003c/sup\u003e. With the development of society and fast-paced life, various enormous pressures have made fatigue-related syndromes a serious global health problem. Therefore, the exploration of novel bioactive substances with fatigue relieving properties has received extensive attention.\u003c/p\u003e\n\u003cp\u003eThe causes of fatigue are diverse and complex, and its pathophysiology and etiology have been fully unelucidated. At present, a large number of researchers have confirmed the mechanisms of relieving fatigue mainly include reducing oxidative stress damage \u003csup\u003e6\u003c/sup\u003e, regulating gut microbiota (GM) \u003csup\u003e7\u003c/sup\u003e, enhancing energy reserve \u003csup\u003e8\u003c/sup\u003e, and reducing metabolite levels \u003csup\u003e9\u003c/sup\u003e, etc. In particular, oxidative stress and imbalance of GM are regarded as factors closely related to fatigue. Sufficient evidence indicates that excessive exercise usually disrupts the balance of the body\u0026apos;s oxidation/antioxidant system, so regulating the oxidation balance by eliminating acquired 1,1-diphenyl-2-picrylhydrazyl (DPPH), hydroxyl, and 2,2\u0026prime;-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radical is a way to alleviate fatigue \u003csup\u003e6\u003c/sup\u003e. Studies have demonstrated that short-chain fatty acids (SCFAs), the metabolites of GM, are energy sources for skeletal muscle and play a regulatory role in maintaining redox homeostasis in vivo. Modulating the balance of GM has been shown to extend exercise duration, enhance antioxidant enzyme activity, decrease metabolic byproduct accumulation, and promote glycogen storage in mice experiencing exercise-induced fatigue (EIF) \u003csup\u003e10\u003c/sup\u003e. Probiotics, such as \u003cem\u003eLactobacillus, Akkermansia\u003c/em\u003e, and \u003cem\u003eBifidobacterium\u003c/em\u003e\u003cem\u003e,\u003c/em\u003e not only maintain intestinal balance but also promote the production of SCFAs to further exert anti-fatigue effects \u003csup\u003e11-13\u003c/sup\u003e. The above results clearly indicate that improving oxidative stress and regulating GM balance are effective means to alleviate fatigue. Significantly, due to the good biological activity of macromolecular substances like glycoproteins, they have attracted the attention of many researchers. Glycoproteins are a class of bioactive macromolecules formed by connecting sugar chains with proteins or peptides, widely existing in nature, which possess various pharmacological activities including anti-fatigue, antioxidation, regulating GM, anti-aging, immune regulation, and antitumor \u003csup\u003e14\u003c/sup\u003e. According to reports, glycoprotein can play an anti-fatigue role by scavenging excessive free radicals, improving antioxidant enzyme activity, increasing glycogen reserves, and reducing metabolites accumulation \u003csup\u003e15,16\u003c/sup\u003e. \u003cem\u003eTrichiurus lepturus\u0026nbsp;\u003c/em\u003eglycoprotein has been confirmed to have obvious antioxidant activity in vitro and relieve fatigue in exercise mice \u003csup\u003e16,17\u003c/sup\u003e. The glycoprotein of breast milk and edible bird\u0026apos;s nest have various biological activities like antioxidant and regulating GM \u003csup\u003e18,19\u003c/sup\u003e.\u0026nbsp;Therefore, glycoproteins have broad application prospects\u0026nbsp;in the development of anti-fatigue functional products.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePeriplaneta american\u003c/em\u003e\u003cem\u003ea\u003c/em\u003e (PA), commonly known as \u0026ldquo;cockroach\u0026rdquo;, was first recorded in the ancient book \u0026quot; \u003cem\u003eDivine Farmer\u0026apos;s Materia Medica\u003c/em\u003e\u0026quot; \u003csup\u003e20\u003c/sup\u003e. It is a famous traditional medicinal insect with a medicinal history of more than 2,000 years and has been widely raised and used commercially in China \u003csup\u003e21\u003c/sup\u003e. In ethnic minority areas of China, there has been a custom of eating insects since ancient times. PA is an insect with drug and food homology. In recent years, its medicinal and nutritional functions have attracted extensive attention and research. The adult powder of PA has been certified as a health supplement \u003csup\u003e22\u003c/sup\u003e. Modern studies have shown PA, which rich contain of bioactive substances such as amino acids, peptides, polysaccharides and nucleosides, exhibits a variety of pharmacological activities including antioxidation, regulating GM, wound repair, and immunomodulation \u003csup\u003e23-25\u003c/sup\u003e. Lu et al. confirmed PA Oligosaccharides played a preventive role in streptozotocin-induced diabetes in mice by reducing inflammation and oxidative stress, improving pancreatic function, enhancing immunity and regulating GM \u003csup\u003e26\u003c/sup\u003e. In recent years, numerous research pieces of evidence have revealed the excellent biological activity of macromolecular substances. Researchers firmly believe macromolecular substances are one of the key substances in PA that exert biological activity \u003csup\u003e20\u003c/sup\u003e. Based on this, our previous study isolated and purified PA glycoprotein (PAG) from PA, and characterized its structural composition, revealing that the total sugar and protein content of PAG are about 20.60% and 66.00%, respectively. PAG is mainly composed of 7 kinds of monosaccharides and 10 kinds of amino acids. The molecular weight of PAG was divided into 4 segments, among which the molecular weight of 66-14.5 kDa accounts for about 79.05% \u003csup\u003e27\u003c/sup\u003e. In previous research, we found that PAG can effectively eliminate DPPH, hydroxyl and ABTS free radicals to exert antioxidant activity \u003csup\u003e28\u003c/sup\u003e, and also promote the proliferation of \u003cem\u003eLactobacillus plantarum\u003c/em\u003e and \u003cem\u003eBifidobacterium\u003c/em\u003e \u003cem\u003eadolesc\u003c/em\u003e\u003cem\u003eentis\u0026nbsp;\u003c/em\u003eand the generation of SCFAs \u003csup\u003e29\u003c/sup\u003e.\u0026nbsp;Therefore, we scientifically speculate PAG can play a role in relieving fatigue through antioxidant, regulating\u0026nbsp;GM, and increasing SCFAs content.\u003c/p\u003e\n\u003cp\u003eFor this reason, we first investigated the antioxidant activity of PAG under simulated gastrointestinal digestion environment. On this basis, we first established a fatigue mouse models by swimming tests, and detected fatigue-related indexes such as swimming time, antioxidant indexes and glycogen content. Subsequently, the diversity of GM in intestinal contents and the content of SCFAs in feces were analyzed. Finally, Spearman correlation analysis was used to analyze the correlation among GM, SCFAs and fatigue-related indexes to clarify the role and potential mechanism of PAG in preventing and alleviating fatigue. In summary, this study is intended to provide scientific evidence for PAG as a potential raw material for anti-fatigue drugs/nutritional supplements.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eIn Vitro Antioxidant Activity of PAG\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ePhysical fatigue often results from the excessive accumulation of free radicals \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Therefore, we evaluated the antioxidant activity of PAG in a simulated gastrointestinal environment using several markers, such as total reducing capacity and ABTS, DPPH, and hydroxyl free radicals clearance ability, to supply data to support further research on the antioxidant and anti-fatigue effects of PAG in vivo. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, when assessed in the simulated gastric environment, no significant differences were observed in the total reducing capacity, DPPH, or hydroxyl free radicals scavenging capacity between the pepsin and gastric acid groups and the gastric blank group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). With increasing PAG concentration, the ABTS free radical scavenging rate increased gradually. At the same PAG concentration, the ABTS free radical scavenging rate of the pepsin group was significantly greater than those of the gastric acid and gastric blank groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003e After trypsin digestion, the total reduction capacity, ABTS and hydroxyl free radicals clearance rate of PAG increased with increasing concentration, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The scavenging rate of the trypsin group was higher than that of the intestinal blank group, but there was no statistically significant difference in the rate of DPPH free radical clearance between the two sets of data (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eEIF Effect of PAG\u003c/h2\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003ch2\u003eEffects of PAG on the Body Weight Change and Organ Index\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eBody weight change and organ index reflect the effects of PAG and American ginseng capsules (AGC) administration on the health of mice. During the experimental period, the weight of mice in the 5 experimental groups continued to increase (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). However, there was no significant difference in the weight change of the treatment groups compared with the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating that PAG and AGC didn't affect growth and development of mice. Moreover, the weight increase depended on food intake. We noted that intervention with PAG and AGC significantly reduced the liver weight of mice with EIF (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting that continuous high-intensity exercise might cause mild liver edema, resulting in an increased liver weight (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). PAG appeared to alleviate oxidative stress in the liver, playing a protective role to a certain degree. The indexes of the other organs were not significantly different from those of the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-E) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eEffect of PAG on Exhaustive Swimming Time\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe exhaustive swimming time of mice is one of the main indexes to study the anti-fatigue effect. The duration of weight-loaded swimming directly reflects the level of EIF mice. The longer the swimming time, the more effective the sample is at mitigating fatigue. Establishing a weight-loaded swimming model provides a reliable way to objectively evaluate the fatigue tolerance of mice and the anti-fatigue effects of samples \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. As the PAG dosage was raised, the exhaustive swimming time of the mice increased compared to the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). The PAG-M (43 min) and PAG-H (43 min) groups swam for 27 min longer than the control group (16 min, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and also surpassed the positive group (32 min). This study confirmed that PAG prolonged exercise time in mice, improved their fatigue tolerance, and had a good anti-fatigue effect.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eMorphological Analysis of Liver Tissue\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAccording to the available literature \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, EIF mice are closely related to liver metabolism, which includes oxidative stress leading to liver tissue damage during exercise. This is reflected in the microscopic observation results of the hematoxylin \u0026amp; eosin (H\u0026amp;E) staining paraffin sections of liver tissue, presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG. After free swimming for 30 min, the hepatocytes of mice in the control group had large intercellular spaces, loose cells, irregular nuclei arrangement, and different nuclei sizes. Conversely, in the PAG groups, the intercellular space gradually decreased with increasing PAG dosage, and the cellular structure tended to be normal. H\u0026amp;E staining confirmed that the hepatocytes of EIF mice were irregularly arranged, indicating that oxidative stress damage occurred in the liver tissue. After the administration of PAG, the arrangement of hepatocytes returned to normal, and oxidative stress injury of the liver tissue was alleviated to a certain extent. These findings suggest that PAG mitigated oxidative stress damage to hepatocytes in mice with EIF and played a protective role in liver function.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eEffect of PAG on Liver Speroxide Dismutase (SOD), Glutathione Peroxidase (GSH-Px) and Malondialdehyde (MDA)\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eCritical antioxidant enzymes, such as SOD and GSH-Px, play a pivotal role in the body's defense against oxidative damage, while MDA is an important final product of lipid peroxidation triggered by a large amount of free radicals. Therefore, the SOD, GSH-Px, and MDA levels were measured to assess the anti-fatigue effects of PAG. Comparing the PAG and positive groups to the control group, we observed significant increases in the activities of SOD and GSH-Px in the liver of mice and a substantial decrease in MDA levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-C). These results suggest that PAG reversed the decline in antioxidant enzyme activity and the rise in MDA levels in the livers of exercise-fatigued mice, indicating favorable antioxidant activity in vivo. Moreover, the activities of SOD and GSH-Px and the content of MDA in the mice liver changed in a dose-dependent manner with the increase of PAG concentration.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eEffect of PAG on Blood Urea Nitrogen (BUN) and Lactic Acid (LA)\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eDuring intense exercise, the body's metabolism generates harmful products BUN and LA, and the higher the accumulation, the greater the impact on exercise endurance. Therefore, they are regarded as factors leading to fatigue. In the control group, the expression of BUN in the serum and LA in the muscle increased, whereas PAG significantly reduced the levels of BUN and LA (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Moreover, their levels decreased with increasing PAG dosage (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD, E). This suggests that PAG effectively eliminated the accumulation of the exercise metabolites LA and BUN, reduced exercise injury, and improved exercise tolerance in a dose-dependent manner.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eEffect of PAG on Lactate Dehydrogenase (LDH) and Creatine Kinase (CK)\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe levels of LDH and CK in serum are considered as biomarkers of muscle fatigue, so we detected their activity. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF, G, the LDH and CK activities in the PAG and positive groups were considerably lower than those in the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In the PAG-L, PAG-M, and PAG-H groups, the LDH activity were decreased by 13.18%, 25.10%, and 33.90%, and CK activity were reduced by 12.34%, 41.97%, and 55.61%, respectively. Our results indicate that PAG effectively inhibit the activities of LDH and CK in the serum of fatigued mice, thereby alleviating muscle injury caused by strenuous exercise.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eEffect of PAG on Muscle Glycogen (MG) and Liver Glycogen (LG)\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eGlycogen storage reflects the body's tolerance to fatigue ang is an important index for fatigue evaluation. Therefore, we examined glycogen content in mice. As demonstrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH, the leg muscle MG content in the PAG and positive groups was significantly higher than that in the control group. Similarly, the amount of LG in the livers of mice in the PAG and positive groups was upregulated compared to that in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Both the MG and LG contents gradually increased with increasing PAG dosage. The research indicated that PAG increased glycogen reserves in mice, serving as an energy source to supplement exercise consumption, and enhanced exercise tolerance in mice through energy consumption.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eEffects of PAG on GM\u003c/h2\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003eAlpha Diversity Analysis of GM\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo investigate the effect of PAG on GM of fatigued mice, we performed 16S rRNA sequencing on colonic contents. Alpha Diversity analysis was used to analyze the community diversity of GM in mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-D). The Chao1 and Ace indexes reflect the flora richness, and are positively correlated with community richness. The Shannon and Simpson indexes reflect the flora diversity, and the Shannon is positively correlated with the diversity of microbiota, whereas the Simpson is negatively correlated with it \u003csup\u003e13\u003c/sup\u003e. The Chao1, Ace, and Shannon values of the positive and PAG-L groups all increased and the Simpson value decreased compared to the control group, while the PAG-M and PAG-H groups showed the opposite phenomenon to the positive group. However, no significant variations (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) existed between the groups. The findings show that, following PAG intervention, there were no appreciable changes in the general composition and richness of the GM population of EIF mice.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eBeta Diversity Analysis of GM\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eBeta diversity analysis is used to measure the differences in species diversity among different flora, revealing differences in microbiota structure among samples by comparing species composition between communities. To visually demonstrate these differences, we used principal coordinate analysis (PCoA) to reflect the differences among microbiota. In PCoA plot, the distance between samples reflects the similarity of microbial community composition and abundance. Specifically, the smaller the distance between samples, the more similar the microbial community composition and species abundance \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. In Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE, the dispersion degree of the microbiota in the positive, PAG-L, PAG-M groups compared to the control group was greater than the degree of overlap, indicating that there is a certain difference in microbial diversity of the mice GM. However, the GM of the PAG-H group was clearly separated from that of the control group, and had a certain intersection with the other treatment groups, indicating that a certain concentration of PAG effectively regulated the composition and diversity of the GM in fatigued mice, and formed a new community structure.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eImpact of PAG on the Phylum-level Structure and Composition of the GM\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo clarify the effects of PAG on the GM of exercise-fatigued mice, community structures among the different groups were compared at the phylum level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). The relative abundance of Firmicutes accounted for 82.79%, which was the major bacterial groups in the intestinal content of the control group mice. In addition, there were six phyla with relative abundances above 0.02%, namely Desulfobacterota (6.74%), Patescibacteria (4.95%), Actinobacteria (4.21%), Bacteroidetes (0.79%), Verrucomicrobiota (0.02%), and Bacteria_unclassified (0.24%). The effect of PAG on the GM at the phylum level was mainly concentrated in the Firmicutes, Actinobacteria, Verrucomicrobiota, Desulfobacterota, and Patescibacteria. Firmicutes dominated the GM of the PAG-treated mice, but there were differences in the relative abundance between the groups. Compared with the control group, the abundance of Firmicutes was upregulated by 6.49%, 4.31%, and 4.15% in the PAG-L, PAG-M, and PAG-H groups, respectively. In addition, the abundance of Desulfobacterota and Patescibacteria in the PAG group decreased to varying degrees compared to that in the control group, whereas Verrucomicrobiota and Actinobacteria increased to varying degrees.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eImpact of PAG on the Genus-level Structure and Composition of the GM\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eMoving from the phylum level to the genus level, we examined the community structure of the gut bacteria in mice. The distribution of genera is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG. The dominant bacteria in the mice intestines were \u003cem\u003eLactobacillus, Ligilactobacillus, Lactobacillaceae_\u003c/em\u003eunclassified, \u003cem\u003eLimosilactobacillus, Akkermansia, Bifidobacterium\u003c/em\u003e, and \u003cem\u003eDesulfovibrio\u003c/em\u003e. Compared to the control group, the bacterial genera that showed increases in relative abundance in the intestinal contents after the different PAG concentrations were administered included \u003cem\u003eLigilactobacillus\u003c/em\u003e, \u003cem\u003eLactobacillaceae\u003c/em\u003e_unclassified, and \u003cem\u003eAkkermansia\u003c/em\u003e. Meanwhile, the abundance of \u003cem\u003eLimosilactobacillus\u003c/em\u003e, and \u003cem\u003eDesulfovibrio\u003c/em\u003e, decreased. In addition, the relative abundance of \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003eFaecalibaculum\u003c/em\u003e increased in the PAG-H group.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eImpact of PAG on GM Structure\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo further explore the biomarkers of GM in different groups of mice, we applied LDA effect size (LEfSe) differential analysis (Linear discriminant analysis (LDA)\u0026thinsp;\u0026gt;\u0026thinsp;2) \u003csup\u003e32\u003c/sup\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA represents an evolutionary branching diagram of LEfSe analysis, showing the taxonomic rank relationships from phylum to genus major groups of sample community. The predominant GM in the control group were Firmicutes and Desulfobacterota. The dominant microbial communities in PAG-L and PAG-H comprised \u003cem\u003eDubosiella\u003c/em\u003e and \u003cem\u003eBifidobacteria\u003c/em\u003e, respectively. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB express the histogram of LDA value distribution from LEfSe analysis. This histogram shows the LDA threshold of each marker species, with higher values indicating more obvious differences in the species. In the control group intestinal contents, four phyla and 21 genera were identified. Those with LDA values greater than 4 included \u003cem\u003eLimosilactobacillus, Desulfovibrionales\u003c/em\u003e, and Desulfobacterota, and the other groups followed in descending order. The abundance of \u003cem\u003eDesulfovibrio\u003c/em\u003e significantly exceeded those of the other groups. In the positive group, a total of 12 genera were identified across three phyla (Firmicutes, Desulfobacterota, and Bacteroidetes), which were significantly different from the bacteria in the other groups. The abundance of bacteria in the PAG-H group was significantly higher than those in the other groups, with 13 genera across three phyla (Actinobacteria, Firmicutes, and Bacteria_unclassified), including five unclassified bacterial genera. In contrast, the PAG-M and PAG-L groups had only one identified for genera, all of which belonged to the Firmicutes, a prominent phylum of gut microorganisms that play a crucial role in maintaining GM balance.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eEffect of PAG on SCFAs Content\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eDysbiosis of GM profoundly affects the production of its metabolites, especially SCFAs, which play a crucial role in relieving fatigue. The effects of PAG on the SCFAs content in mice feces are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC-F. When EIF mice were administered PAG, their feces had significantly higher levels of acetic acid, propionic acid, butyric acid, and valeric acid than the control group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, the amount of SCFAs increased as the PAG concentration rose. This indicated that PAG enhanced the secretion of SCFAs by the GM, thereby promoting intestinal health in mice and ultimately exerting an anti-fatigue effect.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eSpearman Correlation Analysis of GM, SCFAs, and EIF Evaluation Indexes\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo shed light on the \u0026ldquo;GM\u0026ndash;SCFAs\u0026ndash;anti-fatigue indexes\u0026rdquo; relationship, and ultimately clarify the potential pathways of PAG in alleviates fatigue. We conducted Spearman correlation analysis on GM, SCFAs, and fatigue resistance related indexes, including LDH, CK, BUN, LA, MG, LG, MDA, GSH-Px, SOD, and swimming duration, As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA, the increase in SCFAs content after PAG administration was positively correlated with MG, LG, SOD content, and swimming duration to varying degrees, while exhibiting a negative correlation with LDH, BUN, and MDA content. Furthermore, butyric acid showed a negative correlation with CK and LA levels and a positive correlation with GSH-Px content. Further Spearman analysis between SCFAs and fatigue indexes underscored the close connection between SCFAs secretion and body fatigue.\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB, C depict the phylum level analyses. Firmicutes and Verrucomicrobiota displayed positive correlations with MG, LG, GSH-Px, SOD, SCFAs, and swimming duration to varying degrees. Actinobacteria were positively correlated to varying degrees with MG, LG, GSH-Px, and SOD content, but negatively correlated with LDH, CK, BUN, LA, MDA, and SCFAs. Desulfobacterota and Patescibacteria were positively associated with LDH, CK, BUN, LA, and MDA content and negatively associated with MG, LG, GSH-Px, and SOD content and swimming duration. Based on the above results, we speculated that PAG promoted the expression of SCFAs by upregulating the abundance of Firmicutes and Verrucomicrobiota in the intestinal contents. It also upregulated the abundance of Actinobacteriota and downregulated Desulfobacterota and Patescibacteria, which together inhibited the leakage of LDH and the accumulation of BUN, LA, and MDA, and promoted glycogen storage and oxidase activity, thereby increasing the fatigue tolerance of mice.\u003c/p\u003e\u003cp\u003eAnalyses at the genus level are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD, E. The genera that were positively correlated with MG and LG content, GSH-Px and SOD activity, and swimming duration to varying degrees included \u003cem\u003eLigilactobacillus, Lactobacillaceae\u003c/em\u003e_unclassified, \u003cem\u003eAkkermansia, Bifidobacterium, Faecalibaculum\u003c/em\u003e, and \u003cem\u003eLachnospiraceae\u003c/em\u003e_NK4A136_group, which were also negatively correlated with LDH, CK, BUN, LA, and MDA content. For example, \u003cem\u003eLactobacillus, Limosilactobacillus, Desulfovibrio, Candidatus_Saccharimonas\u003c/em\u003e, \u003cem\u003eLachnospireaceae_\u003c/em\u003eUCG-006, \u003cem\u003eLachnospireaceae\u003c/em\u003e_unclassified, \u003cem\u003eTuricibacter\u003c/em\u003e, and \u003cem\u003eOscillospiraceae\u003c/em\u003e_unclassified were positively correlated with LDH, CK, BUN, LA, and MDA to varying degrees but negatively correlated with other indexes. Moreover, \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eLactobacillaceae\u003c/em\u003e_unclassified, \u003cem\u003eAkkermansia\u003c/em\u003e, and \u003cem\u003eDubosiella\u003c/em\u003e were positively correlated with SCFAs content to varying degrees. In summary, we inferred that PAG play an anti-fatigue role by regulating the richness of GM to promote the secretion of SCFAs, alleviating oxidative stress damage, reducing metabolite accumulation, and increasing energy storage.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eFatigue is a complex physiological phenomenon involving a variety of mechanisms, including oxidative stress damage, energy metabolism disorders, and GM disorders. No studies have reported on the anti-fatigue effect and potential mechanism of PA, although a large number of research has shown that PA has a variety of pharmacological effects. In this study, we aim to elucidate the anti-fatigue effects and the potential mechanisms of PAG. Firstly, the antioxidant activity and activity stability of PAG in vitro were confirmed by simulating the gastrointestinal environment. Then, a fatigue mouse model was established to investigate the effects of PAG on fatigue-related indexes, GM, and SCFAs. Finally, the possible potential anti-fatigue mechanism of PAG was elucidated using spearman correlation analysis.\u003c/p\u003e\u003cp\u003eThe antioxidant activity of glycoproteins has been reported to be related not only to the intrinsic molecular structure but also to the direct antioxidant activity of some amino acids \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. PAG is one of the key active ingredients of PA. The glycopeptide bonds in PAG are O-glycopeptide bonds, which remain stable under acidic conditions and easily dissociate into unsaturated amino acids under weakly alkaline conditions \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Therefore, PAG may maintain its original molecular structure in a simulated gastric digestion environment (pH\u0026thinsp;=\u0026thinsp;2). PAG did not show significant changes in total reducing capacity or DPPH and hydroxyl free radicals clearance ability in the simulated gastric environment. However, the increased ABTS free radical scavenging rate may be the result of the increased exposure of antioxidant amino acid residues in some peptides of PAG without structural dissociation, which neutralizes the specific charge of ABTS radical, as reported by Ma \u003csup\u003e33\u003c/sup\u003e. In addition, trypsin can hydrolyze certain peptides into smaller peptides and amino acids \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The increased radicals scavenging rate of PAG in the intestinal environment was attributed to the decomposition of PAG by trypsin into smaller molecules. This resulted in an increased content of hydrophilic peptides and amino acids, leading to stronger binding with Fe\u003csup\u003e2+\u003c/sup\u003e, ABTS and hydroxyl radicals. However, this hydrolysis had no influence on lipophilic DPPH free radical. Our results demonstrate that PAG still has vigorous antioxidant activity during simulated gastric and intestinal digestion, indicating that PAG has good activity stability in the gastrointestinal environment. This study provides experimental evidence for subsequent research on the antioxidation and anti-fatigue effects of PAG in vivo.\u003c/p\u003e\u003cp\u003eIntense exercise significantly elevates the body's levels of ROS causing an imbalance between the oxidative and antioxidant systems and a decrease in the body's overall antioxidant capacity. However, antioxidant enzymes play a crucial role in the body's defense against oxidative damage. As SOD and GSH-Px, SOD converts ROS into H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and O\u003csub\u003e2\u003c/sub\u003e, while GSH-Px and catalase break down H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e into H\u003csub\u003e2\u003c/sub\u003eO and O\u003csub\u003e2\u003c/sub\u003e, effectively terminating the chain reaction of ROS, mitigating damage to the body, and delaying EIF \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. MDA is an effective biomarker for oxidative stress triggered by excessive oxygen free radicals attacking membrane lipids, and its content is an index for evaluating the degree of fatigue \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Based on this, the activities of SOD, GSH-Px and the level of MDA were measured. The results showed that after PAG intervention, SOD and GSH-Px activities were increased in the liver of mice, while MDA level was decreased, indicating that PAG eliminated excessive free radicals, prevented lipid peroxidation, and protected the body from oxidative stress injury, which likely a pathway of its anti-fatigue effects. The antioxidant effect of PAG is consistent with our previous results \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Therefore, the good antioxidant activity of PAG was validated by both the in vitro and in vivo data.\u003c/p\u003e\u003cp\u003eDuring anaerobic exercise, BUN is a byproduct of metabolic protein production after muscle glycogen depletion and serves as an index associated with fatigue \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The levels of BUN in serum gradually increase with continuous high-intensity exercise, and this increase is inversely correlated with exercise tolerance. In simpler terms, the higher the concentration of BUN, the poorer the body's adaptation to exercise \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. LA is a common anaerobic metabolic byproduct of high-intensity exercise. Intense exercise accelerates oxygen expenditure and glycolysis, resulting in a large accumulation of LA in the body, which lowers the pH value of tissues and blood and causes a decrease in physical exercise endurance and fatigue \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. As a result, LA is frequently employed as a crucial index to gauge levels of weariness. LDH can reduce the accumulation of LA produced in muscles during exercise and promote the conversion of LA to pyruvate \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. As a critical enzyme involved in energy metabolism and ATP synthesis, CK activity surges as ATP is heavily depleted during exercise. The activity of CK in the serum has been confirmed as an index of post-exercise muscle damage \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Notably, our study revealed a dose-dependent manner decrease in LDH and CK activity in mice treated with PAG (The reduction values of the PAG-L, PAG-M and PAG-H groups were: LDH: 13.18%, 25.10% and 33.90%, CK: 12.34%, 41.97% and 55.61%), and effectively reduced BUN and LA stockpile, indicating that PAG can reduce fatigue-related metabolites pile up, lower body's damage caused by strenuous exercise, and exert an anti-fatigue effect, which is consistent with previous research results \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Glucose, mainly in the form of glycogen, is stored in the liver and skeletal muscles. When the body experiences hypoglycemia, LG is converted into glucose, and MG directly supplies energy to the muscle tissue through anaerobic glycolysis to replenish the energy consumed during exercise \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Therefore, glycogen content is often used to evaluate the anti-fatigue efficacy of tested drugs \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Our results confirmed that PAG significantly increased LG and MG content in fatigued mice, revealing the role of PAG in relieving fatigue by increasing energy storage.\u003c/p\u003e\u003cp\u003eIn recent years, a large number of studies have confirmed that maintaining the diversity of GM is very important for the body to keep normal physiological functions, and the key role of GM in relieving fatigue has also attracted the attention of many researchers \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. In this study, PAG altered diversity and species abundance of GM in fatigued mice. Moreover, beta diversity analysis also indicated that PAG significantly adjusting the structure and composition of the GM in fatigued mice, which is consistent with previous study report \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOur research shows that, the effects of PAG on the GM at the phylum level was mainly concentrated in the Firmicutes, Actinobacteriota, Verrucomicrobiota, Desulfobacterota, and Patescibacteria. Firmicutes include a variety of butyric acid-producing bacteria. As the main energy source for colonic mucosal epithelial cells, butyric acid provides energy to the intestine, inhibits the growth of harmful bacteria, maintains electrolyte balance, and promotes repair of the intestinal mucosa \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Firmicutes play a role in synthesizing an enzyme responsible for carbohydrate degradation, indirectly influencing the body's anti-fatigue function \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Bacteroidota are also one of the main components of the human GM and are essential for preserving its equilibrium \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Actinobacteria are the dominant bacteria in the intestinal tract of mammals, and some Actinomycetes help to regulate certain bodily functions, including the immune system, intestinal homeostasis, and metabolism, by producing active metabolites \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. PAG increased the abundance of Firmicutes, Verrucomicrobiota, and Actinobacteriota, and decreased Desulfobacterota and Patescibacteria. The changes in the structural composition of these microbiota suggest that, in the intestinal content of exercise-fatigued mice, the right amount of PAG increases the number of beneficial bacteria while preventing the phylum-level development of detrimental bacteria. This helps maintain intestinal environmental balance and, in turn, indirectly contributes to anti-fatigue effects.\u003c/p\u003e\u003cp\u003eAt the genus level, our analysis found that the predominant bacteria of the mice GM include \u003cem\u003eLactobacillus, Ligilactobacillus, Lactobacillaceae_\u003c/em\u003eunclassified, \u003cem\u003eLimosilactobacillus, Akkermansia, Bifidobacterium, Faecalibaculum\u003c/em\u003e, \u003cem\u003eLachnospiraceae\u003c/em\u003e-NK4A136-group, \u003cem\u003eTuricibacter\u003c/em\u003e, and \u003cem\u003eDesulfovibrio\u003c/em\u003e. \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eAkkermansia\u003c/em\u003e, and \u003cem\u003eBifidobacterium\u003c/em\u003e are common members of the GM \u003csup\u003e44\u003c/sup\u003e. \u003cem\u003eLactobacillus\u003c/em\u003e and \u003cem\u003eBifidobacterium\u003c/em\u003e are important for intestinal homeostasis because they modulate intestinal tight junction protein expression, improve intestinal permeability, enhance intestinal barrier function, and inhibit the proliferation of harmful intestinal bacteria. Furthermore, through the inhibition of pro-inflammatory cytokines, they exhibit anti-inflammatory properties \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eLactobacillus\u003c/em\u003e also reduces the antioxidant activities of SOD and glutathione reductase in the liver, and alleviates liver oxidative stress injury \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eAkkermansia\u003c/em\u003e, accounting for 3\u0026ndash;5% of the microbial composition of the gastrointestinal tract in healthy humans, affects host functions, such as metabolism, inflammatory response, and immune regulation, and plays an important role in host health by ameliorating glucose and insulin levels to eliminate the risk of metabolic disorders \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eLigilactobacillus\u003c/em\u003e and \u003cem\u003eAkkermansia\u003c/em\u003e maintain homeostasis in the intestinal microenvironment by maintaining the integrity of the intestinal mucosa \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eFaecalibaculum\u003c/em\u003e has been reported to regulate duodenal epithelial homeostasis by remodeling the retinoic acid\u0026ndash;eosinophil\u0026ndash;interferon-γ-dependent circuit \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Butyrate-producing bacteria in the \u003cem\u003eLachnospiraceae\u003c/em\u003e_NK4A136_group preserve the integrity of the intestinal barrier in rats and have a negative correlation with intestinal permeability \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eLimosilactobacillus\u003c/em\u003e can regulate the abundance of GM, promote intestinal homeostasis, and improve the inflammatory response of the host organism, thereby promoting human health through various channels \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eTuricibacter\u003c/em\u003e is involved in the regulation of host bile acid metabolism and plays a part in the treatment of bile acid metabolism disorders caused by colitis \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. It has also been reported that some \u003cem\u003eTuricibacter\u003c/em\u003es species are pathogenic and are often associated with inflammation in the host \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. The sulfate-reducing bacteria \u003cem\u003eDesulfovibrio\u003c/em\u003e can \"breathe\" sulfate and produce hydrogen sulfide, which is toxic to the intestinal epithelium and leads to gastrointestinal diseases \u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Our results indicate that PAG alters the structure and abundance of the GM in exercise fatigue mice at the genus level, promotes the proliferation of some probiotics, and maintains the balance of the GM.\u003c/p\u003e\u003cp\u003eUsing the LEfSe differential analysis method, we identified significant differences in key species among the GM of mice in each group \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Analysis reveals that, PAG downregulated the abundance of Desulfobacterota in the intestinal contents of mice with exercise fatigue, while upregulating the relative abundance of probiotics, such as \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003eDubosiella\u003c/em\u003e. \u003cem\u003eDubosiella\u003c/em\u003e reduces MDA and increases SOD activity in aged mice, with various effects, such as decreasing oxidative stress and improving vascular endothelial function \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. We reconfirm that the various PAG concentrations encouraged the growth of helpful bacteria while suppressing the growth of harmful bacteria, thus regulating the healthy balance of the GM. Interestingly, these findings are consistent with our previous studies \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSCFAs can promote the proliferation of intestinal epithelial cells, maintain the integrity of the intestinal barrier, prevent LA from entering the blood, and eliminate excessive LA buildup in the muscles, thus alleviating EIF \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e,\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. Acetic acid, a major metabolite, serves as an essential energy source for the GM \u003csup\u003e60\u003c/sup\u003e. Propionic acid functions as an anti-inflammatory agent, is involved in immune regulation, and helps reverse fatigue-induced muscle damage \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. EIF leads to intestinal damage and mucosal dysfunction \u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e, whereas Butyric acid, the primary energy source for colonic epithelial cells, exhibits the highest utilization rate among SCFAs, maintains intestinal wall integrity, and simultaneously enables the self-apoptosis of cells with abnormal oxidative damage, thus preventing the occurrence of disease \u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. Therefore, we measured the content of SCFAs in mice feces using Gas Chromatography-Mass Spectrometer (GC-MS) targeted metabolomics, and found a significant increase in SCFAs content, which was dose-dependent on the dosage of PAG, suggesting that the PAG play a relieving fatigue a role by promoting the generation of SCFAs.\u003c/p\u003e\u003cp\u003eSpearman analysis revealed that, within a certain range of PAG concentrations, as the content of SCFAs increased, the levels of MG, LG, and SOD increased, and the swimming duration prolonged, while the levels of LDH, BUN, and MDA decreased. In addition, butyric acid also enhanced the activity of GSH-Px and decreased the levels of CK and LA. Considering this, we speculated that PAG promotes the secretion of SCFAs in the intestinal, providing the energy substances needed by colon cells, and combines with SCFAs to resist oxidative stress damage in the body, which may be one of the pathways PAG's anti fatigue effects. Spearman analysis also found \u003cem\u003eLimosilactobacillus\u003c/em\u003e, \u003cem\u003eTuricibacter\u003c/em\u003e and other bacteria genera were positively correlated with the expression of metabolites key enzymes (LDH, CK) and metabolic wastes (BUN, LA and MDA). Additionally, the LEfSe analysis revealed that the intestinal contents of the control group contained considerably higher relative abundances of \u003cem\u003eLimosilactobacillus\u003c/em\u003e and \u003cem\u003eTuricibacter\u003c/em\u003e than those of the positive and PAG groups. Therefore, we inferred that the upregulation of these bacterial abundances accelerated exercise-fatigue in the mice, while PAG reduced the accumulation of metabolic waste by reducing the bacterial abundance, providing an anti-fatigue effect. In the LEfSe analysis, it was also found that the abundance of \u003cem\u003eBifidobacterium, Faecalibaculum\u003c/em\u003e, and other bacterial genera in the intestinal contents of swimming-induced fatigue mice intervened with PAG was upregulated compared to that in the control group. These bacteria were positively correlated with the expression of MG, LG, GSH-Px, and SOD, as well as swimming duration. Accordingly, we inferred speculated that PAG effectively enhanced the fatigue tolerance in mice by increasing the population of these microorganisms, MG and LG accumulation, and GSH-PX and SOD activity. The results of Spearman analysis of the GM at the genus level further showed that PAG had a regulatory effect on the GM of swimming-induced fatigued mice, and different GM had different regulatory effects on SCFAs and anti-fatigue indexes.\u003c/p\u003e\u003cp\u003eIn this study, it was first demonstrated that PAG has good antioxidant activity under simulated gastric and intestinal environmental conditions. Further, animal experiments have proved that PAG significantly prolong exhaustive swimming time, improve liver injury, rise the activities of SOD and GSH-Px and reduce the level of MDA in the liver, decrease the accumulation of BUN and LA and the activities of LDH and CK in the serum, augment the storage of LG and MG, optimize the structure of mice GM, increase the abundance of some beneficial bacteria, and promote the secretion of SCFAs, thereby prolonging the swimming time of fatigue mice. Finally, Spearman correlation analysis was used to demonstrate varying degrees of correlation among GM, SCFAs, and fatigue related indexes.\u003c/p\u003e\u003cp\u003eIn summary, this study elucidates the potential of PAG to exert anti-fatigue effects by reducing oxidative stress damage, decreasing metabolite accumulation, increasing glycogen storage, and regulating GM. This study provides a scientific basis for PAG as an anti-fatigue drugs/nutritional supplements and for its development and utilization. Future studies are needed to further clarify its exact target of action and validate its clinical impact on EIF and the effective dose range for the human body, thereby facilitating translational application.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eMaterials and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003cstrong\u003eeagents\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePA was purchased from the GAP breeding base of Yunnan Jingxin Biotechnology Co., Ltd (Yunnan, China). PAG was isolated from PA\u003cem\u003e\u0026nbsp;\u003c/em\u003evia water extraction and alcohol precipitation. AGC were obtained from Xiamen Yongfuxing Health Products Co., Ltd. (Xiamen, China). Pepsin (porcine, activity: 1:10000), trypsin (from the porcine pancreas, activity: 1:250), and ABTS were obtained from Beijing Solarbio Science \u0026amp; Technology Co., Ltd. (Beijing, China). We acquired DPPH from Tokyo Kasei Kogyo Co., Ltd. (Tokyo, Japan). Appropriate kits for the determination of LG, MG, BUN, LA, LDH, CK, SOD, GSH-Px, MDA, and total protein were acquired from the Nanjing Jiancheng Biotechnology Institute (Nanjing, China). Acetic, propionic, butyric, and valeric acid standards were purchased from Sigma-Aldrich Co. (St. Louis, MO, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePAG Extraction from PA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording\u0026nbsp;to our previous research, the dried PA\u003cem\u003e\u0026nbsp;\u003c/em\u003ewas processed through crushing (24 mesh sieve) and three extractions using ultrapure water (1/5, g/v) with heating reflux extraction. The resulting filtrate, concentrated to one-quarter of the total volume, was defatted thrice with petroleum ether (1/3, w/v) at 30 \u0026deg;C and precipitated using 95% ethanol (1/5, v/v), followed by 12 h at 4 \u0026deg;C.\u0026nbsp;The precipitate was collected via centrifugation (4000 rpm, 10 min) and dissolved in an appropriate amount of water. Then, the free proteins were removed by employing a 3-fold volume of Sevag reagent (chloroform/n-butanol = 4/1, v/v), and the supernatant was concentrated and freeze-dried to obtain PAG.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFormulation of PAG Solution for Simulating Gastrointestinal Digestion\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;method\u0026nbsp;described in the literature was used to guide the preparation of simulated gastrointestinal fluid \u003csup\u003e65\u003c/sup\u003e, with slight modifications. To obtain the simulated gastric fluid, hydrochloric acid (4.2 mL) and pepsin (2.5 g) were added to deionized water, and the volume\u0026nbsp;was\u0026nbsp;fixed at 250 mL. The simulated intestinal fluid was prepared by mixing potassium dihydrogen phosphate (1.7 g), sodium hydroxide (adjusted to pH 6.8), deionized water (500 mL), and trypsin (10 g) and diluting it to 1000 mL with water.\u003c/p\u003e\n\u003cp\u003eSimulated gastrointestinal digestion was performed as described by Sun et al\u003cem\u003e.\u003c/em\u003e \u003csup\u003e66\u003c/sup\u003e, with\u0026nbsp;slight\u0026nbsp;modifications. A certain amount of PAG was weighed and dissolved in 0.9% normal saline to prepare PAG solutions with different concentrations for antioxidant experiments in simulated gastrointestinal environments. The PAG concentrations used to determine the total reducing capacities were 0.1, 0.2, 0.4, 0.8, and 1.6 mg/mL. The PAG concentrations used for the DPPH and hydroxyl\u0026nbsp;free\u0026nbsp;radicals\u0026nbsp;scavenging experiments were 0.025, 0.050, 0.100, 0.200, and 0.400 mg/mL. The concentration of PAG for the ABTS\u0026nbsp;free\u0026nbsp;radical scavenging experiment were as follows: 0.01, 0.02, 0.04, 0.08, and 0.16 mg/mL. To obtain the pepsin, gastric acid, and gastric blank groups, 15 mL of simulated gastric juice, 0.01 mol/L hydrochloric acid, and 0.9% saline, respectively, was added to different concentrations (injection nitrogen) of the sample solutions. After digestion for 0 and 2 h, the samples were removed and\u0026nbsp;centrifuged\u0026nbsp;at 6000 rpm for 15 min. The supernatant was removed to obtain the simulated gastric digestion sample solution and stored at \u0026ndash;80 \u0026deg;C. The 2 h pepsin group, which had varying concentrations of sample solutions and injected nitrogen, was mixed with simulated intestinal solution and phosphate buffer solution (pH \u0026asymp; 6.8) to generate sample solutions for the intestinal digestion and blank intestinal groups. After digestion for 0, 3, or 6 h, the sample solutions were removed, and the remaining steps were the same as those used for the simulated gastric digestion sample solution.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of PAG Antioxidant Capacity in Simulated Gastrointestinal Digestion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTotal Reducing Capacity Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe total reduction capacity of PAG was measured using the method described by Vasylie et al. \u003csup\u003e67\u003c/sup\u003e, with slight modifications. The phosphate buffer solution (0.025 mol/L, 1 mL) was transferred into a centrifuge tube with different concentrations of simulated gastric digestion sample solutions (0 and 2 h, 1 mL) and K\u003csub\u003e3\u003c/sub\u003eFe(CN)\u003csub\u003e6\u003c/sub\u003e (1%, 1 mL), then centrifuged for 10 min at 4000 rpm. We mixed the supernatant with distilled water and FeCl\u003csub\u003e3\u003c/sub\u003e solution (0.1%, 0.5 mL), let it sit for 10 min, and measured absorbances \u003cem\u003eA\u003csub\u003e1\u003c/sub\u003e\u003c/em\u003e and \u003cem\u003eA\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e at 700 nm. The simulated intestinal digestion sample solutions (0, 3, and 6 h) were analyzed using the same method. Total reducing power was calculated using equation (1):\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 495px;\"\u003e\n \u003cp\u003eTotal reducing capacity = \u003cem\u003eA\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e- \u003cem\u003eA\u003csub\u003e1\u003c/sub\u003e,\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ewhere \u003cem\u003eA\u003csub\u003e1\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003eis the absorbance value of the sample and \u003cem\u003eA\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003eis the absorbance value of the control (containing an equal volume of distilled water instead of FeCl\u003csub\u003e3\u003c/sub\u003e solution).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDPPH Free Radical Clearance Assay\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe scavenging rate of PAG on DPPH free radical activity was determined according to the method described by Lu et al. with slight modifications \u003csup\u003e68\u003c/sup\u003e. Various concentrations of simulated gastric digestion sample solutions (0 and 2 h, 1 mL) were mixed with DPPH (1 mL) and centrifuged at 4000 rpm for 10 min. The supernatant was then removed for the detection of absorbances \u003cem\u003eA\u003csub\u003e0\u003c/sub\u003e\u003c/em\u003e and\u003cem\u003e\u0026nbsp;A\u003csub\u003e1\u003c/sub\u003e\u003c/em\u003e at 517 nm. The simulated intestinal digestion sample solutions (0, 3, and 6 h) were analyzed using the same method. The activity of DPPH free radical scavenging was calculated by employing equation (2):\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 495px;\"\u003e\n \u003cp\u003eDPPH free radical scavenging activity (%) = (\u003cem\u003eA\u003csub\u003e0\u003c/sub\u003e\u003c/em\u003e - \u003cem\u003eA\u003csub\u003e1\u003c/sub\u003e\u003c/em\u003e) / \u003cem\u003eA\u003csub\u003e0\u003c/sub\u003e\u003c/em\u003e \u0026times; 100\u003cem\u003e,\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ewhere A\u003csub\u003e0\u003c/sub\u003e is the absorbance of the control (saline instead of the sample solution) and A\u003csub\u003e1\u003c/sub\u003e is the absorbance of the sample.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHydroxyl Free Radical Clearance Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe method described by Xiao et al\u003cem\u003e.\u0026nbsp;\u003c/em\u003e\u003csup\u003e69\u003c/sup\u003e, with minor modifications, was used to generate hydroxyl free radical. Various concentrations of simulated gastric digestion PAG solutions (0 and 2 h, 1 mL) were mixed with FeSO\u003csub\u003e4\u003c/sub\u003e, a salicylic acid-ethanol solution, and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (1%, 1 mL) at 37 \u0026deg;C for 30 min. The absorbances \u003cem\u003eA\u003csub\u003e0\u003c/sub\u003e\u003c/em\u003e, \u003cem\u003eA\u003csub\u003e1\u003c/sub\u003e\u003c/em\u003e, and \u003cem\u003eA\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e were measured at 510 nm, using distilled water as a reference. The measurement method for the simulated intestinal digestion samples (0, 3, and 6 h) was the same as described above. The hydroxyl free radical scavenging activity was calculated using equation (3):\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 495px;\"\u003e\n \u003cp\u003eHydroxyl free radical scavenging activity (%) = (A\u003csub\u003e0\u003c/sub\u003e - \u003cem\u003eA\u003csub\u003e1\u003c/sub\u003e\u003c/em\u003e + \u003cem\u003eA\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e) / \u003cem\u003eA\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e \u0026times; 100\u003cem\u003e,\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ewhere A\u003csub\u003e0\u003c/sub\u003e is the absorbance of the control solution (saline instead of the sample solution), A\u003csub\u003e1\u003c/sub\u003e is the absorbance of the sample, and A\u003csub\u003e2\u0026nbsp;\u003c/sub\u003eis the absorbance of the sample with an equal volume of distilled water instead of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eABTS Free Radical Clearance Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe detection of the PAG clearance rate of ABTS was conducted according to a previous method \u003csup\u003e68\u003c/sup\u003e, with minor modifications. An ABTS reserve solution was prepared by mixing equal volumes of ABTS liquid (7.4 mmol/L) and potassium sulfate (2.6 mmol/L), and adjusting its absorbance (A) at 734 nm with phosphate buffer (pH = 7.4) to achieve an A value of 0.70 \u0026plusmn; 0.02, thus obtaining the ABTS working solution. The working solution (6 mL) was separately blended with various concentrations of simulated gastric digestion PAG solutions (0 and 2 h, 1 mL) and incubated for 6 min. The \u003cem\u003eA\u003csub\u003e0\u003c/sub\u003e\u003c/em\u003e and \u003cem\u003eA\u003csub\u003e1\u003c/sub\u003e\u003c/em\u003e absorbances were then detected at 734 nm. The simulated intestinal digestion sample solutions (0, 3, and 6 h) were analyzed using the same method. ABTS free radical scavenging activity was calculated according to equation (4):\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 495px;\"\u003e\n \u003cp\u003eABTS free radical scavenging activity (%) = (A\u003csub\u003e0\u003c/sub\u003e - \u003cem\u003eA\u003csub\u003e1\u003c/sub\u003e\u003c/em\u003e + \u003cem\u003eA\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e) / \u003cem\u003eA\u003csub\u003e2\u003c/sub\u003e\u003c/em\u003e \u0026times; 100\u003cem\u003e,\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ewhere\u0026nbsp;\u003cem\u003eA\u003csub\u003e0\u003c/sub\u003e\u003c/em\u003e is the absorbance of the control (saline instead of the sample solution) and \u003cem\u003eA\u003csub\u003e1\u003c/sub\u003e\u003c/em\u003e is the absorbance of the sample.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimals\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this experiment, eighty healthy male Kunming species mouse (SPF grade, 6\u0026ndash;8 weeks old, weighing 36 \u0026plusmn; 3 g) were purchased from Hunan SJA Laboratory Animal Co., Ltd (Hunan, China; No. SCXK (Xiang) 2019\u0026ndash;0004). Mice were kept at the Laboratory Animal Center of Dali University (Use License NO.: SYXK(Dian)2024-0001) at a temperature of 23 \u0026plusmn; 1 \u0026deg;C, relative humidity of 55 \u0026plusmn; 10%, alternating light and dark for 12 hours, and free access to feed and water. The mice were kept in this environment to adapt for one week. All experimental procedure strictly according to ARRIVE guide (https://arriveguidelines.org) and Dali university experimental animal ethics committee guidelines and related regulations, and by Experimental Animal Ethics Committee of Dali University (No. 2021-PZ-071; Approval date: 28 June, 2021).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmerican Ginseng was recognized as an anti-fatigue compound \u003csup\u003e70\u003c/sup\u003e; therefore, AGC was used as a positive control drug in this study, and its dosage was determined by pre-experiments and dosage conversion between mice and humans \u003csup\u003e71\u003c/sup\u003e. To determine the optimal dose of PAG, this study referred to the dose of the positive control group, and according to the results of the acute toxicity test (no toxicity at a dose of 40g/kg) and the pre-experiment, we designed three experimental groups with varying supplementation levels to systematically evaluate the anti-fatigue and dose-dependent effects.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter one week of adaptation, based on a review of an extensive body of anti-fatigue-related literature \u003csup\u003e43,61,62\u003c/sup\u003e and rigorous calculations using PASS software and simple methods, eighty mice were randomly divided into five groups according to their body weight. With sixteen mice in each group, the sample size was sufficient to meet the statistical requirements for both the weight-loaded swimming experiment (\u003cem\u003en\u003c/em\u003e=8) and the unloaded swimming experiment (\u003cem\u003en\u003c/em\u003e=8). This design, which minimizes the sample size of experimental animals, is in line with the ethical standards for animal experimentation. The dose settings and assignments were as follows: the control group (saline), the positive group (AGC, 400 mg/kg/d), the PAG-L group (200 mg/kg/d), the PAG-M group (400 mg/kg/d), and the PAG-H group (600 mg/kg/d). The mice were administered once daily for 4 weeks by gavage, and weighed every 2 d for inter group weight comparison. During the study period, the mice were subjected to adaptive free swimming for 15\u0026ndash;30 min using an experimental water tank (25 \u0026plusmn; 2 \u0026deg;C, water depth 30 cm), twice a week.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of Exhaustive Swimming Time\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt the end of the fourth week, a weight-loaded swimming test was performed on 8 mice from each group to measure exhaustive swimming time. After the final gavage session lasting 30 min, the mice were deprived of food but could drink water for 12 h. Their tails were cleansed of grease, and they were loaded with lead skin weighing 5% of their body weight at the base of the tail. Subsequently, they were placed individually in a water tank, and timing began. The timing concluded when the mice sank to the bottom of the water due to exhaustion and remained submerged for 7 s, marking the point of exhaustion in swimming. The hair of each mouse was dried, and the mice were euthanized with an overdose of anesthetic (Isoflurane). Specifically, mice were sacrificed by the cervical dislocation method after excessive isoflurane anesthesia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of Fatigue-related Biochemical Indexes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBy the conclusion of the fourth week, the remaining 8 mice in each group were subjected to a 12 h fasting period but allowed to drink water. Following a 30 min gap post-gavage, they engaged in free swimming without bearing additional weight for 30 min. Then, the mice were allowed to rest for 30 min before being anesthetized and blood samples were collected from the eyeball of each mouse. The collected blood was allowed to stand for 2 h at room temperature. It was then centrifuged for 15 min (4000 rpm, 4 \u0026deg;C) to separate the serum. Mice were sacrificed with an overdose of anesthetic (Isoflurane) and dissected immediately. Specifically, mice were sacrificed by the cervical dislocation method after excessive isoflurane anesthesia. The livers, kidneys, spleens, thymuses, and leg muscles were removed and measured mass. The organ index was calculated according to the following formula: Organ index (%) = organ mass (g)/mouse body weight (g) \u0026times; 100%.\u003c/p\u003e\n\u003cp\u003eThe liver levels of SOD, GSH-Px, and MDA were examined to gauge the PAG antioxidant potential. The levels of BUN, LDH, and CK in the serum, as well as LA in the muscle were determined to evaluate the protective effects of PAG on muscle and exercise metabolites in mice. The expression of LG in the liver and MG in the muscle was detected to evaluate the effect of PAG on body energy in mice. The kit instructions were followed in determining the aforementioned indexes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMorphological Observation of Liver Tissue\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePartial liver samples were fixed for 18\u0026ndash;24 h in a 4% paraformaldehyde solution fixative, then dehydrated in ethanol, embedded in paraffin, sectioned, and stained with H\u0026amp;E. To evaluate the protective effect of PAG on the livers of EIF mice, a light microscope outfitted with a Charge-coupled Device camera (BX-53, Olympus, Tokyo, Japan) was used to observe and photograph the gaps and color of hepatocytes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e16S rRNA Sequencing and Bioinformatic Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenomic DNA was extracted from intestinal inclusion samples using a genomic DNA extraction kit (Omega Bio-Tek,\u003cem\u003e\u0026nbsp;\u003c/em\u003eNorcross, GA, USA), and 1% agarose gel electrophoresis was used to assess the DNA content and purity. Using the V3\u0026ndash;V4 region of the 16S rRNA gene as the designated region for high-throughput sequencing, a specific primer with barcodes was synthesized. All samples were amplified through Polymerase Chain Reaction (PCR). Using the AxyPrep DNA Gel Recovery Kit (AXYGEN, San Francisco, CA, USA), the PCR products were recovered, after being detected using 2% agarose gel electrophoresis. The recovered products were quantified using a QuantiFluor\u0026trade;-ST Blue Fluorescence Quantification System (Promega, Madison, USA). To construct sequencing libraries and obtain sequence products, we utilized the Illumina PE250 platform. The high-throughput sequencing of samples was conducted at the Shanghai Yuanxin Biomedical Technology Co. (Shanghai, China).\u003c/p\u003e\n\u003cp\u003ePaired-end reads were obtained from the Illumina PE250 platform and spliced according to the overlap relationship, and the sequence quality was controlled and filtered to obtain the optimized sequence. Using Usearch (v7.01090) for cluster sequences, sequences were classified into the same operational taxonomic units (OTUs) when the similarity was 97% or more. The Ribosomal Database Project Naive Bayes classifier (v2.2, http://sourceforge.net/projects/rdp-classifier/) was used to perform taxonomic analysis on representative OTU sequences, and the community composition of the samples was separately calculated at different taxonomic levels (phylum and genus). Furthermore, alpha and beta diversity index analyses were performed based on the results of the OTU cluster analysis. LEfSe was typically utilized to analyze the variations in microbiota between groups and identify the major microbiota among groups. The relative microbiota abundance of corresponding groups (LDA\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u0026gt; 2) was found to be higher than that of other groups, as indicated by an LDA score greater than 2. We employed Spearman\u0026rsquo;s correlation analysis to examine the relationships between SCFAs, GM, and EIF indexes. This analysis helped us understand how these factors related to one another and their connection to the anti-fatigue properties of PAG.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of SCFAs Content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDetermination of the SCFAs content was based on the method described by Yang\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. \u003csup\u003e72\u003c/sup\u003e, with some modifications. The mouse fecal samples (0.15 g) were precisely weighed, added to methanol (1 mL), vortexed for 3 min, ultrasonicated for 2 min, and thoroughly mixed to prepare a fecal suspension. Following a pH adjustment (pH = 2.0\u0026ndash;3.0) with concentrated sulfuric acid, the suspension underwent a 2-min vortex, was centrifuged for 20 min at 5000 rpm, and the supernatant was collected and filtered through a 0.45 \u0026mu;m microporous membrane. Acetic, propionic, butyric, and valeric acid standards were prepared appropriately, and methanol was added to prepare mixed standard solutions at concentrations of 1, 0.75, 0.75, and 0.15 mol/L, respectively. The filtrate was analyzed using a GC-MS (Agilent, Santa Clara, CA, USA) with an Agilent DB-WAXDB-WAX chromatography column (30 m \u0026times; 250 \u0026mu;m, 0.25 \u0026mu;m). Helium (0.5 mL/min) was used as the carrier gas, with a 1 \u0026mu;L injection volume and 10:1 shunt ratio. The temperature of the column was initially set to 110 \u0026deg;C and kept at that level for 2 min. After that, it was raised to 135 \u0026deg;C at a rate of 5 \u0026deg;C/min and kept at that level for 0 min. Finally, it was raised to 150 \u0026deg;C at a rate of 1 \u0026deg;C/min and kept at that level for 0 min. It was further increased to 160 \u0026deg;C at 5 \u0026deg;C/min, maintained for 0 min, and finally raised to 200 \u0026deg;C at 10 \u0026deg;C/min, with a maintenance period of 0 min. The mass spectrometry conditions were as follows: Agilent 5975C detector at 230 \u0026deg;C, inlet at 230 \u0026deg;C, ion source at 230 \u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the data were expressed as mean \u0026plusmn; standard deviation (SD) after processing with SPSS 22.0 software (SPSS Inc, Chicago, IL, USA). Data comparison between groups was performed using one-way analysis of variance. At \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, statistical significance was established; compared to the control group: * \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; compared to the positive group: # \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ## \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the raw sequencing data involved in this study have been deposited in the NCBI SRA database, with the accession number PRJNA1335858. In addition, other raw data have been uploaded to the Mendeley database (https://data.mendeley.com/datasets/5w3skwj28k/1, published on September 18, 2025), DOI: 10.17632/5 w3skwj28k. 1. The name of the dataset is the same as the title of the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful for the support of the Analytical and Testing Center of Dali University (Dali University, Dali, China), and Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R\u0026amp;D (Dali University, Dali, China).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZ.C. and X.Y.: Conceptualization, Formal analysis, Methodology, Investigation, Software, Writing\u0026mdash;original draft. J.Z.: Software, Validation. \u0026nbsp;K.L.: Visualization. R.H.: Data curation. Y.Y.: Formal analysis. J.W.: Software. Z.H.: Project administration, Funding acquisition, Writing\u0026mdash;review and editing. P.X.: Project administration, Resources, Methodology, Supervision, Funding acquisition. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Basic Research Key Projects of Science and Technology Department of Yunnan Provincial (grant number 202501AS070162); Joint Project of Basic Research of Local Universities in Yunnan Province (grant number 202401BA070001-007); and the Yunnan Expert Workstation (grant number 202405AF140044). The APC was funded by Peiyun Xiao.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Experimental Animal Ethics Committee of Dali University (approval number: 2021-PZ-071; approval date: 28 June, 2021) and reported in accordance with ARRIVE guidelines (https://arriveguidelines.org).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrespondence\u0026nbsp;\u003c/strong\u003eand requests for materials should be addressed to P.X.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLuo, C.\u003cem\u003e et al.\u003c/em\u003e Natural medicines for the treatment of fatigue: Bioactive components, pharmacology, and mechanisms. \u003cem\u003ePharmacol Res\u003c/em\u003e \u003cstrong\u003e148\u003c/strong\u003e, 104409. https://doi.org/10.1016/j.phrs.2019.104409 (2019).\u003c/li\u003e\n\u003cli\u003eHuang, S.\u003cem\u003e et al.\u003c/em\u003e Ethanol extract of propolis relieves exercise-induced fatigue via modulating the metabolites and gut microbiota in mice. \u003cem\u003eFront Nutr\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 1549913. https://doi.org/10.3389/fnut.2025.1549913 (2025).\u003c/li\u003e\n\u003cli\u003eKim, H. 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B. \u0026amp; Morsy, M. A. Dose Conversion Between Animals and Humans: A Practical Solution. \u003cem\u003eIndian Journal of Pharmaceutical Education and Research\u003c/em\u003e \u003cstrong\u003e56\u003c/strong\u003e, 600-607. https://doi.org/10.5530/ijper.56.3.108 (2022).\u003c/li\u003e\n\u003cli\u003eYang, Y.\u003cem\u003e et al.\u003c/em\u003e Bergamot polysaccharides relieve DSS-induced ulcerative colitis via regulating the gut microbiota and metabolites. \u003cem\u003eInt J Biol Macromol\u003c/em\u003e \u003cstrong\u003e253\u003c/strong\u003e, 127335. https://doi.org/10.1016/j.ijbiomac.2023.127335 (2023).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Gut microbiota, anti-fatigue, Periplaneta americana glycoprotein, antioxidant","lastPublishedDoi":"10.21203/rs.3.rs-7515364/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7515364/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFatigue, as a complex physiological phenomenon, has emerged as a growing global health concern. Glycoproteins from \u003cem\u003ePeriplaneta americana\u003c/em\u003e (PA), a medicinal insect resource, exhibit pharmacological activities (e.g., regulating the gut microbiota (GM), antioxidation and enhancing immunity) consistent with the core therapeutic targets for anti-fatigue. This study aimed to investigate the efficacy and mechanisms of PA glycoprotein (PAG) in anti-fatigue. The antioxidant capacity of PAG was evaluated by detecting antioxidant-related indexes in simulated gastrointestinal environment. The effectiveness of PAG in anti-fatigue was verified through swimming time measurement, histological staining and biochemical index monitoring. 16S rRNA sequencing, targeted metabolomics and Spearman correlation analysis were integrated to dissect the underlying mechanism of its anti-fatigue effect. PAG has excellent antioxidant activity. Secondly, PAG exerts anti-fatigue effects through multiple mechanisms: prolonged swimming time, improved liver injury, increased glutathione peroxidase and superoxide dismutase activities, decreased malondialdehyde level, promoted glycogen storage, simultaneously inhibited lactate dehydrogenase and creatine kinase activities, and reduced blood urea nitrogen and lactate accumulation in fatigued mice, altered the composition and structure of GM, and increased short-chain fatty acids (SCFAs) content. In conclusion, these findings suggest that PAG is promising candidates for anti-fatigue, and it warrants further systematic investigation for clinical translation.\u003c/p\u003e","manuscriptTitle":"Anti-fatigue potential of glycoprotein from Periplaneta americana: improving oxidative stress and regulating the gut microbiota","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 15:56:25","doi":"10.21203/rs.3.rs-7515364/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-28T07:54:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-27T18:51:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-16T11:08:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265072258057959042538044170615285039546","date":"2025-10-15T17:08:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"182419857846680621676484824819443946294","date":"2025-10-15T13:53:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-15T13:16:33+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-01T12:18:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-30T08:58:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-30T06:52:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-09-30T06:25:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1e05c659-2ec3-47f2-a1c4-8ecb3b9c2012","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":56998036,"name":"Biological sciences/Biochemistry"},{"id":56998037,"name":"Health sciences/Diseases"},{"id":56998038,"name":"Biological sciences/Microbiology"},{"id":56998039,"name":"Biological sciences/Physiology"}],"tags":[],"updatedAt":"2025-12-15T16:03:44+00:00","versionOfRecord":{"articleIdentity":"rs-7515364","link":"https://doi.org/10.1038/s41598-025-31459-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-12-10 15:58:29","publishedOnDateReadable":"December 10th, 2025"},"versionCreatedAt":"2025-10-29 15:56:25","video":"","vorDoi":"10.1038/s41598-025-31459-3","vorDoiUrl":"https://doi.org/10.1038/s41598-025-31459-3","workflowStages":[]},"version":"v1","identity":"rs-7515364","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7515364","identity":"rs-7515364","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}