Preparation and Characterization of Peptides from Rana chensinensis skin via Microbial Fermentation

Preparation and Characterization of Peptides from Rana chensinensis skin via Microbial Fermentation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Preparation and Characterization of Peptides from Rana chensinensis skin via Microbial Fermentation Hui Zhang, Qingqing Li, Jianhang Li, Yani Chen, Xiaoxi Shen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8565314/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract As the main by-product of Rana chensinensis product processing, Rana chensinensis skin has important development and utilization value because it is rich in a variety of bioactive components. In this study, Bacillus subtilis was used as the fermentation strain to explore the efficient preparation process and antioxidant activity of peptides from Rana chensinensis skin. The fermentation conditions were optimized by single factor experiment and response surface analysis, and the optimal parameters were determined as follows: inoculum volume was 3%, fermentation time was 16 h, and shaking speed was 190 rpm. Under these conditions, the peptide content of the fermentation product reached 71.46 ± 0.92 mg/mL, and the DPPH scavenging rate was 81.29 ± 1.03%, which were 1.77-fold and 4.71-fold higher than those before fermentation, respectively, and the antioxidant activity was significantly improved. The molecular weight distribution of peptides in fermentation liquor was further analyzed by high performance liquid chromatography. The results showed that the proportion of peptides with molecular weight less than 10,000 Da was up to 90%, and 50.54% of small peptides were concentrated in the range of less than 3000 Da. Subsequently, small molecular peptides were obtained by ultrafiltration centrifugation, which showed higher DPPH scavenging rate, and their key role in antioxidant activity was verified. This study realized the high-value utilization of Rana chensinensis skin, not only laid an experimental foundation for its application in various fields, but also provided a scientific basis for the sustainable utilization of Rana chensinensis skin. Rana chensinensis Skin Peptide Optimization Bacillus subtilis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1 Introduction Amphibian skin secretions represent significant natural sources of bioactive peptides. Early investigations into the active compounds present in amphibian skin have confirmed that it is abundant in biogenic amines, bufogenin, alkaloids, peptides, and proteins, all of which play crucial roles in physiological regulation[ 1 , 2 ]. Given the rich structural and diverse functions of these peptides, subsequent research has gradually focused on the extraction, isolation and purification of peptides from amphibian skin and the identification of their biological activities. Andre et al.[ 3 ] characterized amphibian skin as a "treasure trop of peptides", highlighting that the variety and content of peptides found therein far exceed those present in other animal organs while also exhibiting a wide range of biological activities. This provides an essential material foundation for research across related fields. Rana chensinensis is a valuable economic amphibian species utilized for both medicinal and culinary purposes, it is primarily distributed in Northeast China and possesses high development and utilization value[ 4 ]. However, the processing of its products has remained in the primary stage for a long time, the intensive processing technology is relatively scarce, and there is a significant limitation in the utilization of resources. Most of the existing processing modes focus on the extraction of Rana chensinensis oil, which is the dried product in the female oviduct of Rana chensinensis[ 5 – 7 ]. While this oil is widely acknowledged for its nutrient richness, numerous by-products generated during extraction, including skin, bones and internal organs, are not effectively utilized. They are typically relegated to feed production or discarded outright. This practice results in considerable resource wastage. Notably, recent studies have increasingly demonstrated that peptides extracted from Rana chensinensis skin (RCS) exhibit remarkable biological activities, such as antibacterial[ 8 – 12 ], anti-tumor[ 13 – 15 ], antioxidant[ 16 ], promote wound healing[ 17 ]. This indicates significant application value and development potential across various fields such as food, medicine, cosmetics, and more. Furthermore, it offers a new direction for the efficient utilization of the entire industrial chain associated with Rana chensinensis. In recent years, there has been a relative scarcity of studies focused on the preparation of peptides from RCS. The commonly employed methods include physicochemical techniques and enzymatic hydrolysis methods. However, these approaches are often associated with challenges such as low peptide yields, complex process and high costs. For example, Wang et al.[ 4 ] soaked the dried skin of Rana chensinensis in an acetic acid solution to obtained an extract rich in polypeptides through ultrasonic treatment and vacuum concentration. This extract was confirmed to exhibit antibacterial effects against Staphylococcus aureus , Pseudomonas aeruginosa and so on. Wang et al.[ 18 ] extracted collagen hydrolysate from the skin of Rana chensinensis under acidic conditions using pepsin, achieving a yield of 15.1% (w/w). They also suggested that the skin of Rana chensinensis could serve as an alternative source of collagen hydrolysate for applications in both the food industry and pharmaceutical sectors. Additionally, Zhang et al.[ 16 ] extracted polypeptides, ARPS and ERPs, from the skin of Rana chensinensis by combining acid extraction with enzymatic digestion. The yields were 0.65% and 0.52%, respectively. These polypeptides demonstrated the ability to enhance the proliferation rate of HaCaT cells by factors of 1.66 and 2.1, respectively, while also reducing the apoptosis rate by factors of 2.6 and 3.4, respectively. Wu et al.[ 19 ] subjected the skin of Quasipaa Spinosa to enzymatic hydrolysis treatment with papain and acidic protease, achieving a hydrolysis degree of 30%. The hydrolysis product (QSPH-I-3) was obtained through the purification of ultrafiltration and gel filtration chromatography purification. The IC 50 of DPPH, ABTS and hydroxyl radical scavenging capacity were found to be 1.68+/-0.05 mg/mL, 1.20+/-0.14 mg/mL and 1.55+/-0.11 mg/mL, respectively. Previous studies have indicated that few peptides derived from RCS have been produced through microbial fermentation. However, this approach offers several advantages including high yield, low cost, small molecular weight, enhanced biological activity, straightforward fermentation processes, and greater potential for industrial application. Meanwhile, research has shown that compounds exhibiting antioxidant activity, such as low-molecular-weight peptides and amino acids, can be generated via microbial fermentation to improve overall antioxidant efficacy[ 20 – 22 ]. Therefore, RCS was selected as the focus of this study in which peptides were obtained through fermentation with Bacillus subtilis under optimized production conditions. The production conditions were optimized. This provided an efficient strategy for utilizing the by-products remaining after processing Rana chensinensis—specifically RCS. 2 Materials and Methods 2.1 Materials RCS is sourced from Fusong County, Baishan City, Jilin Province, China. Bacillus subtilis is purchased from the Shanghai Preservation Microbial Center. Additionally, 1,1-diphenyl-2-trinitrophenylhydrazine (DPPH), Gly-Gly-Tyr-Arg, Gly-Gly-Gly, cytochrome C, aprotinin and bacitracin are purchased from Sigma in the United States. All other chemical agents utilized in this study are of domestically produced analytical grade. 2.2 Preparation of Peptides from RCS The glycerol stock of Bacillus subtilis was streaked onto LB solid medium and incubated at 37°C for 24 h. Subsequently, a single colony from the plate was selected using an inoculating loop and transferred into 3 mL of LB liquid medium. This culture was shaken at 160 rpm at 37°C for 12 h to obtain the seed culture of Bacillus subtilis . The RCS medium is prepared by directly mixing 6 g of RCS powder, which is produced by crushing clean and dried RCS, with 100 mL of distilled water. The mixture is then subjected to pH adjustment and sterilization (115°C, 30 min). After cooling, the RCS medium is inoculated with the seed culture of Bacillus subtilis and subsequently incubated in a constant-temperature shaking incubator for a designated period. Subsequently, the fermentation broth is immediately boiled in a 98°C water bath for 5 min. The peptides derived from RCS are obtained as supernatant after centrifugation (8,000×g at 4°C for 10 min). 2.3 Optimization of Fermentation Conditions Single-factor experiments were conducted to evaluate the effects of various parameters on the content of peptides derived from RCS and the DPPH radical scavenging rate. The factors examined included inoculum amount (1–6%, v/v), pH values (5–9), liquid volume (20%-60%), fermentation time (0–24 h) and shaking speed (100–220 rpm). Additionally, all other experimental conditions were ensured to be consistent. Based on the above experimental results, the Box-Behnken Design (BBD) of the response surface methodology was employed to optimize the fermentation process parameters. Using the peptide content as the response value, a 3-factor and 3-level experiment was carried out to identify the optimal fermentation conditions for RCS. 2.4 Peptide Content Quantification and DPPH radical Scavenging Assay Peptide content was quantified using the biuret method with reduced glutathione as the standard substance. The DPPH radical scavenging rate was determined according to the method method described by Zhu et al.[ 23 ], with slight modifications. Anhydrous ethanol and 0.1 mmol/L DPPH ethanol ( A 0 ), peptides and 0.1 mmol/L DPPH ethanol ( A 1 ), as well as peptide and anhydrous ethanol ( A 2 ) were mixed in equal volumes, and allowed to react in the dark at room temperature for 30 min. The OD value of the mixed solution at 517 nm was measured using a concentration of 0.1 mg/mL vitamin C as a positive control. The calculation formula is presented as follows: 2.5 Determination of the Relative Molecular Weight of Peptides A Waters 2695 high performance liquid chromatography (HPLC) was performed to analyze the relative molecular weight of peptides.The chromatographic column employed was a TSKgel 2000SWxl (300×7.8 mm). The mobile phase consisted of a mixture of acetonitrile, water and trifluoroacetic acid in a volume ratio of 40 : 60 : 0.1. The flow rate was set at 0.5 mL/min, and the column temperature was maintained at 30℃. UV detection was performed at a wavelength of 220 nm. Standard substances used for constructing the molecular weight calibration curve included cytochrome (12384 Da), aprotinin (6500 Da), bacitracin (1422 Da), glycine-glycine-tyrosine-arginine (451 Da), and glycine-glycine-glycine (MW: 189 Da). 2.6 ultrafiltration The fermentation liquor of RCS was fractionated using ultrafiltration centrifuge tubes with molecular weight of 3 kDa and 10 kDa, followed by centrifugation at 10,000×g for 20 min at 4℃. Peptides were collected based on their molecular weights into three distinct categories: those greater than 10 kDa (MW > 10 kDa), those between 3 kDa and 10 kDa (3 kDa < MW < 10 kDa), and those less than 3 kDa (MW < 3 kDa). After freeze-drying, the peptides were redissolved in distilled water to a concentration of 1 mg/mL for the determination of DPPH scavenging activity, and preliminarily explore the relationship between the molecular weight of peptides and antioxidant activity. 2.7 Statistical Analysis SPSS software (version 29.0 SPSS, IBM) was applied for statistical analysis. A one-way ANOVA with multiple comparisons (LSD) and Tukey’s post hoc test were employed to assess significant differences among the treatment groups, with significance levels set at p < 0.05 or p < 0.01. All data are presented as the mean ± SD of three independent experimental groups.The figures were generated using OriginPro 2025 and Design Expert 13 software. 3 Results 3.1 Results of Single-factor Experiments 3.1.1 Effect of Fermentation Time on the Fermentation of RCS As shown in Fig. 1 a, compared to unfermented RCS, both the peptide content and DPPH scavenging rate of fermented RCS significantly increased with the extension of fermentation time, peaking at 15 h. In contrast, a significant decrease in peptide content and DPPH scavenging rate was observed after 15 h (p < 0.01). Furthermore, results from subsequent analysis using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) were consistent (Fig. 1 b). The upper portion of the band for unfermented RCS (Lane 1) appears relatively dark, indicating a higher presence of high-molecular-weight proteins in the fermentation broth. As fermentation proceeds, bands gradually deepen in regions corresponding to low-molecular-weight peptides. Notably, Bands 6 and 7 exhibit darker low-molecular-weight regions. This observation suggests that through microbial action during fermentation, RCS can be decomposed into low-molecular-weight peptides that demonstrate strong antioxidant activity. In conclusion, further investigation will focus on varying fermentation times (12 h, 15 h and 18 h) as variables in response surface experiments. 3.1.2 Effect of Inoculum Amount on the Fermentation of RCS The inoculum amount of Bacillus subtilis was used as a variable to explore its effect on the fermentation of RCS, and the results are shown in Fig. 2 , peptide content and DPPH scavenging rate of RCS initially increased and subsequently decreased with the increase of inoculum amount ( p < 0.01). Notably, these parameters reached their peak values when the inoculum amount was set at 3%. Therefore, the inoculum amount of Bacillus subtilis (2%, 3%, 4%) during the fermentation of RCS will be further studied as a variable in the response surface experiment. 3.1.3 Effect of pH on the Fermentation of RCS The effects of different pH values on the peptide content and DPPH scavenging rate of RCS are shown in Fig. 3 . With the increase of pH, the peptide content initially rises before subsequently declining ( p < 0.01), however, alterations in pH do not have a significant effect on the clearance rate. Notably, both peptide content and DPPH scavenging rate reach their peak values at pH 7, which is therefore designated as the optimal pH for RCS fermentation. 3.1.4 Effect of Liquid Volume on the Fermentation of RCS The effect of different liquid volumes on the fermentation of RCS was investigated in this experiment, and the results was shown in Fig. 4 . With the increase of liquid volume, there was a gradual decline in dissolved oxygen content and DPPH scavenging rate of RCS exhibited significant reductions ( p < 0.01), reaching the maximum value at a 20% liquid volume.. 3.1.5 Effect of Shaking Speed on the Fermentation of RCS As shown in Fig. 5 , experimental results indicate that both peptide content and DPPH scavenging rate significantly increased (p < 0.01 ) as the shaking speed was accelerated, peaking at a speed of 180 rpm. However, when the shaking speed exceeded 180 rpm, both peptide content and DPPH scavenging rate decreased significantly ( p < 0.01 ). Therefore, further investigation into varying shaking speeds (140 rpm, 180 rpm, and 220 rpm) during RCS fermentation will be conducted as part of response surface experiments. 3.2 Response Surface Analysis for Optimization of Fermentation Conditions 3.2.1 Response Surface Experimental Design and Results Based on the results of the single-factor experiment and the central combination design of Box-Behnken, a total of 17 experimental groups of experiments were conducted. The fermentation time (A), inoculation volume (B), and shaker speed (C) were designated as independent variables, and the peptide content was taken as the response value. The variables and levels of experimental factors are shown in Table 1 . Table 1 Experimental domain of BBD Variables Symbol Levels Low level (-1) Center level (0) High level (+ 1) Fermentation time (h) A 12 15 18 Inoculum amount (%) B 2 3 4 Shaking speed (rpm) C 140 180 220 The experimental results of BBD are shown in Table 2 , and regression variance fitting was performed on the data in the table. The multiple quadratic regression model equation of peptide content (Y) was obtained as follows: Y = 71.17 + 1.19A + 1.21B + 1.55C-0.6250AB-0.5925AC-0.8925BC-2.46A 2 -4.30B 2 -3.31C 2 . The results of the response surface regression model and analysis of variance are shown in Table 3 , the F-value reflects the variance ratio of regression to residual, with larger values signifying better model fit. The lack-of-fit term represents the difference between observed values and predicted values, with smaller values indicating a better fit. In this experiment, the F-value of the model is 110.82 (P 0.05), which is not significant, suggesting that the regression equation is appropriate. In addition, R² = 0.9930 and R² Adj = 0.9841, which shows that the experiment has a high degree of fitting, and the equation fits the actual situation. By comparing F-value, the order of influence of the three factors on the peptide content is as follows: C (shaking speed) > B (inoculum amount) > A (fermentation time). This model can be used to analyze and determine the optimal process parameters for preparing peptides by fermenting RCS. Table 2 Experiment design and results of BBD Run A:Fermentation time (h) B:Inoculum amount (%) C:Shaking speed (rpm) peptide content (mg/mL) 1 15 3 180 71.56 2 12 4 180 64.88 3 15 4 140 63.76 4 15 3 180 71.16 5 15 3 180 70.92 6 18 3 220 67.03 7 15 4 220 65.69 8 15 2 220 65.13 9 15 3 180 71.40 10 18 3 140 65.73 11 15 2 140 59.63 12 12 3 220 66.24 13 18 2 180 65.17 14 12 2 180 61.12 15 15 3 180 70.81 16 18 4 180 66.43 17 12 3 140 62.57 Table 3 Response surface regression model and analysis of variance results Source Sum of Squares df Mean Square F-value P-value Significant Model 214.81 9 23.87 110.82 < 0.0001 ** A 11.40 1 11.40 52.93 0.0002 ** B 11.79 1 11.79 54.72 0.0001 ** C 19.22 1 19.22 89.24 < 0.0001 ** AB 1.56 1 1.56 7.26 0.0309 * AC 1.40 1 1.40 6.52 0.0379 * BC 3.19 1 3.19 14.79 0.0063 * A² 25.58 1 25.58 118.79 < 0.0001 ** B² 78.03 1 78.03 362.33 < 0.0001 ** C² 46.20 1 46.20 214.52 < 0.0001 ** Residual 1.51 7 0.2154 Lack of Fit 1.11 3 0.3701 3.73 0.1181 not significant Pure Error 0.3972 4 0.0993 Cor Total 216.31 16 * Indicates significant differences ( p < 0.05). ** Indicates extremely significant differences ( p < 0.01). 3.2.2 Interaction Analysis Response surface and contour maps generated based on the model equation can reveal the interaction relationships among factors, thereby identifying the optimal factors and their corresponding levels[ 24 ]. As shown in Fig. 6 , variations in independent variables resulted in a general trend of response values that initially increased before subsequently decreasing. The contour map for each factor exhibited an approximately elliptical shape, indicating significant interactions among all pairs of factors, namely AB, AC and BC. Furthermore, the response surface reached a maximum value with a relatively steep slope. 3.2.3 Determination of 0ptimal Conditions and Verification Test The Design Expert 13 software was used to obtain the optimal fermentation parameters as follows: fermentation time of 15.61 h, inoculation amount of 3.11%, shaking speed was 188.07 rpm, and the predicted value of peptide content of 71.51 mg/mL. For practical application purposes, the experimental conditions were adjusted to fermentation time of 16 h, inoculation amount of 3%, and a shaking speed of 190 rpm. Verification tests were conducted under these specified conditions. The peptide content obtained from the three parallel experiments was 71.46 ± 0.92 mg/mL, which was close to the predicted value. In addition, under optimal fermentation conditions, a DPPH scavenging rate of 81.29 ± 1.03% was achieved. In comparison to the pre-fermentation state, where the RCS exhibited a peptide content of 25.84 mg/mL and a DPPH scavenging rate of 14.22%, the peptide content was raised by 1.77-fold, while the DPPH scavenging rate was elevated by 4.71-fold. 3.3 Distribution of Relative Molecular Weight Generally, the relative molecular weight of peptide is considered to be less than 10,000 Da. The optimal fermentation conditions in the previous paper were selected to prepare the peptide of RCS, and its molecular weight was determined by HPLC. Results as shown in Fig. 7 and Table 4 , peptides with a molecular weight of less than 10,000 Da constituted 76.25% of the total content in the fermentation liquor. Among these, peptides weighing less than 3,000 Da accounted for 50.54%, while small molecular peptides under 1,000 Da represented 33.45%. Table 4 Peptide content of different molecular weights Molecular weight range / Da Peptide Content / % > 10000 23.75 10000 ~ 5000 16.47 5000 ~ 3000 9.24 3000 ~ 2000 6.50 2000ཞ1000 10.59 1000 ~ 500 7.30 500ཞ180 10.30 <180 15.85 Total (<10000) 76.25 3.4 Antioxidant activity of ultrafiltration components The DPPH scavenging rate of various molecular weight components in the fermentation liquor of RCS after ultrafiltration classification are shown in Table 5 . As the molecular weight decreases, there is a significant increase in the DPPH scavenging rate. Specifically, peptides with MW 10 kDa) have the lowest DPPH scavenging rate. Table 5 DPPH scavenging rate of peptides with various molecular weights after ultrafiltration Fermentation liquor MW > 10 kDa 3 kDa < MW < 10 kDa MW < 3 kDa DPPH scavenging rate / % 82.32 44.79 68.59 89.15 4 Discussion The results of this study indicate that key parameters such as fermentation time, inoculum amount, pH, liquid volume, and shaking speed significantly influence the microbial fermentation process, thereby influencing the formation of fermentation products and their antioxidant activity. These findings are consistent with previous studies on the synergistic regulation of multiple parameters in microbial fermentation processes[ 25 ]. Time is a critical factor influencing microbial fermentation. The growth, metabolism, and degradation of various substances by microorganisms are all affected by the duration of fermentation. It is important to note that prolonged fermentation times may increase costs and introduce additional challenges[ 26 ]. In this experiment, both peptide content and DPPH radical scavenging rate of RCS extract significantly decreased after 15 hours of fermentation. This may be attributed to the continuous consumption and limitation of nutrients in the culture medium, which not only affects the growth and fermentation process of the strain, but also even leads to the autolysis of the strain and the hydrolysis of peptides[ 27 ]. This suggests that, in the optimization of practical fermentation processes, precise control over the termination time of fermentation is essential to balance product accumulation with production costs and process stability. For instance, Can et al. investigated the fermentation time parameters (3 days for F3, 6 days for F6) of fish bone fermentation by Monascus purpureus , and found that the contents of soluble proteins, peptides and other related substances in the fermented products, as well as the antioxidant capacity (such as DPPH and ABTS⁺ radical scavenging activities), were significantly enhanced[ 28 ] . The regulation of inoculum amount is also crucial. This study observed that excessive inoculation significantly inhibits the fermentation process, specifically manifested by a marked decrease in peptide content and DPPH radical scavenging rate when the inoculum amount exceeds 3%. Excessive inoculation can cause rapid metabolism of the strain in the early stage of fermentation, accelerate the consumption of nutrients, and may also accumulate inhibitory metabolites, thereby hindering the growth of the strain[ 27 ]. This result is consistent with microbial growth kinetics theory, which states that the inoculum amount must be matched to the nutrient supply capacity of the medium to maintain the strain in a stable logarithmic growth phase and ensure efficient fermentation. For instance, in the study by Yi et al. on optimization of Rosa roxburghii Tratt pomace fermentation process, experimental results showed that the total phenolic content increased with inoculum amount ranging from 6% to 10%, and then decreased as the inoculum amount was further increased from 10% to 14%[ 29 ]. Changes in pH can significantly influence the charge properties and dissociation states of nutrients within the medium, as well as the charge properties of cells, thereby impacting substance exchange[ 30 ]. However, the results of this study indicate that pH has no significant effect on peptide content or DPPH radical scavenging activity. This may be attributed to the strain's inherent tolerance to pH variations or the pH gradient range set in the experiment falling within its optimal growth range. This finding suggests that, in subsequent process optimization, the priority of pH control could be appropriately reduced, with greater emphasis placed on other parameters that exert more pronounced influences. In the process of liquid fermentation, liquid volume serves as a critical parameter for regulating the oxygen environment. The results of this study indicate that peptide content and DPPH radical scavenging activity decrease with increasing liquid volume, which may be attributed to the fact that an excessively high liquid volume reduces the concentration of dissolved oxygen. This reduction impedes the metabolism of aerobic bacteria and promotes the accumulation of metabolic by-products. In contrast, an excessively low liquid volume may lead to excessive foam generation during shaking, thereby increasing the risks of contaminating bacteria and bacterial autolysis. Consequently, precise regulation of liquid volume to match the dissolved oxygen with the metabolic requirements of microorganisms is essential for optimizing the fermentation process. The shaking speed of the fermentation system is directly correlated with the concentration of dissolved oxygen, and maintaining an optimal level of dissolved oxygen is crucial for ensuring the robust growth of microbial strain[ 31 ]. This study further found that when the rotation speed exceeded 180 r/min, both peptide content and DPPH radical scavenging activity decreased. This may be attributed to the insufficient dissolved oxygen concentration in the fermentation system at lower speeds, which adversely regulated the metabolic process of the strain. Conversely, excessively high rotational speeds can lead to a substantial increase in oxygen dissolution rates, ultimately causing the strain to rapidly enter a phase of growth decline[ 32 ]. Elucidating the characteristics of fermentation products and identifying the core source of their antioxidant activity are key prerequisites for achieving targeted optimization and efficient application of these products. Therefore, RCS peptides were prepared under the optimal fermentation conditions established in previous sections, followed by in-depth analysis using molecular weight determination and ultrafiltration fractionation methods. From the general properties of peptide substances, a molecular weight below 10,000 Da is a typical characteristic of peptides. Enzymatic hydrolysis during microbial fermentation is likely the central mechanism regulating the molecular weight distribution of the resulting products. This study hypothesizes that enzymes capable of promoting the hydrolysis of RCS peptides may be generated during microbial fermentation, which could degrade large-molecule RCS peptides into numerous small-molecule peptides. These low-molecular-weight peptides can effectively react with free radicals and exhibit significant antioxidant activity, thereby enhancing the free radical scavenging capacity of the fermentation broth[ 33 ]. This enzymatic hydrolysis regulatory mechanism provides a rational explanation for the formation of antioxidant activity in the fermentation system. Ultrafiltration fractionation analysis further confirms the intrinsic correlation between molecular weight characteristics and antioxidant activity, indicating that the molecular weight of peptides is a key determinant of their antioxidant potency. Specifically, low-molecular-weight peptides tend to exhibit superior DPPH radical scavenging activity. This may be attributed to the strong antioxidant activity of small molecular peptides accompanied by free radical exposure[ 33 ]. From the perspective of structure–function relationships, low-molecular-weight peptides possess simpler spatial conformations, allowing their antioxidant active sites to be more fully exposed. Consequently, they can interact with free radicals more efficiently and exert stronger scavenging effects. Notably, the activity of fermentation liquor was slightly lower than that of small molecular peptides due to the influence of macromolecular impurities in the system. In contrast, macromolecular proteins (MW > 10 kDa) have the lowest DPPH scavenging rate due to their complex structure, difficult exposure of active sites, and the existence of steric hindrance and substrate competition. This further clarifies the regulatory role of molecular weight characteristics in the antioxidant function of peptides. 5 Conclusion Owing to the advantages of high efficiency, environmental protection and low cost, biological fermentation has been widely used in the preparation of bioactive substances, especially becoming one of the mainstream technical paths for peptide preparation. With this technology as the core, the fermentation process parameters were optimized through single factor experiment and response surface analysis, and the fermentation products were finally significantly improved in both peptide content and DPPH scavenging rate. The result directly confirmed that microbial fermentation technology can effectively activate the biological activity value of RCS. Furthermore, the results of HPLC and ultrafiltration centrifugation confirmed that small molecular peptides were the key components to endow the fermentation products with excellent antioxidant properties, which provided a clear direction for the isolation and precise development of active substances from RCS. In terms of application value, the study broke the limitations of traditional utilization of RCS and established an effective path for the utilization of animal-derived by-products. It not only laid a foundation for its application in multiple fields such as food and medicine, but also provided a technical paradigm for the sustainable development of similar biological resources, with potential industrialization prospects. In addition, future research could focus on the technical bottleneck of peptide preparation and overcome practical application problems such as the maintenance of activity, and promote the deep transformation of forest frog skin resources from “waste” to “high-value products” through process optimization and technological innovation. To promote the in-depth transformation of RCS from “waste” to “high-value products” through process optimization and technological innovation. Declarations Acknowledgements This work is supported by the Science and Technology Research Project of Jilin Provincial Department of Education (JJKH20241741KJ), the Concept Validation Center of Boda College of Jilin Normal University, and the High-Level Discipline Cluster for Deep Processing of Jilin Characteristic Resource Foods. Author contributions All authors contributed to the study conception and design. H.Z., J.L. and Y.C. methodology – production and optimization of RCS, Q.L. and X. S. methodology – determination of the relative molecular mass of the peptide. The first draft of the manuscript was written by H.Z.. The article was corrected to be by X.S.. All authors read and approved the final manuscript. Funding This study was funded by the Science and Technology Research Project of Jilin Provincial Department of Education (JJKH20241741KJ). Data Availability The authors confirm that the datasets supporting the findings and conclusions of this study are available within the article. Additional data can be provided upon request. Competing Interests The authors declare no competing interests. References Erspamer V, Erspamer GF, Inselvini M, Negri L (1972) Occurrence of bombesin and alytesin in extracts of the skin of three European discoglossid frogs and pharmacological actions of bombesin on extravascular smooth muscle. Br J Pharmacol 45:333–348. https://doi.org/10.1111/j.1476-5381.1972.tb08087.x Roseghini M, Erspamer V, Falconieri Erspamer G, Cei JM (1986) Indole-, imidazole- and phenyl-alkylamines in the skin of one hundred and forty American amphibian species other than bufonids. Comp Biochem Physiol C 85:139–147. https://doi.org/10.1016/0742-8413(86)90064-2 Rinaldi AC Antimicrobial peptides from amphibian skin: an expanding scenario. https://doi.org/10.1016/S1367-5931(02)00401-5 Wang R, Zhai S, Liang Y, et al (2020) Antibacterial effects of a polypeptide-enriched extract of Rana chensinensis via the regulation of energy metabolism. Mol Biol Rep 47:4477–4483. https://doi.org/10.1007/s11033-020-05508-1 Xiao Y, Ni S, Wang S, et al (2019) Environmental influences on quality features of Oviductus Ranae in the Changbai Mountains. RSC Adv 9:36050–36057. https://doi.org/10.1039/C9RA04823E Zhang Y, Wang Y, Li M, et al (2019) Traditional Uses, Bioactive Constituents, Biological Functions, and Safety Properties of Oviductus ranae as Functional Foods in China. Oxid Med Cell Longev 2019:4739450. https://doi.org/10.1155/2019/4739450 Wang S, Gan Y, Kan H, et al (2021) Exploitation of HPLC Analytical Method for Simultaneous Determination of Six Principal Unsaturated Fatty Acids in Oviductus Ranae Based on Quantitative Analysis of Multi-Components by Single-Marker (QAMS). Molecules 26:479 Ji F, Zhao Y, Jiang F, Shang D (2022) Membrane mechanism of temporin-1CEc, an antimicrobial peptide isolated from the skin secretions of Rana chensinensis , and its systemic analogs. Bioorganic Chem 119:105544. https://doi.org/10.1016/j.bioorg.2021.105544 Ji F, Tian G, Shang D (2024) Antimicrobial peptide 2K4L inhibits the inflammatory response in macrophages and Caenorhabditis elegans and protects against LPS-induced septic shock in mice. Sci Rep 14:15093. https://doi.org/10.1038/s41598-024-64511-9 Zhang R, Gao J, Xie H, et al (2022) The Prepropalustrin-2CE2 and Preprobrevinin-2CE3 Gene from Rana chensinensis: Gene Expression, Genomic Organization and Functional Analysis of the Promoter Activity. Protein Pept Lett 29:143–155. https://doi.org/10.2174/0929866528666211125105627 Ye Z, Zhou X, Xi X, et al (2022) In Vitro & In Vivo Studies on Identifying and Designing Temporin-1CEh from the Skin Secretion of Rana chensinensis as the Optimised Antibacterial Prototype Drug. Pharmaceutics 14:604. https://doi.org/10.3390/pharmaceutics14030604 Li M, Liu Z, He J, et al (2025) Trp-containing Peptides with Therapeutic Potential for Cutibacterium acnes Infection. Probiotics Antimicrob Proteins. https://doi.org/10.1007/s12602-025-10749-2 Han Z, Wang Y, Wang W, et al (2025) Design, synthesis and activity evaluation of reduction-responsive anticancer peptide temporin-1CEa drug conjugates. Bioorganic Chem 154:108103. https://doi.org/10.1016/j.bioorg.2024.108103 Zhang J, Sun Y, Kang Y, Shang D (2021) Antimicrobial peptide temporin-1CEa isolated from frog skin secretions inhibits the proinflammatory response in lipopolysaccharide-stimulated RAW264.7 murine macrophages through the MyD88-dependent signaling pathway. Mol Immunol 132:227–235. https://doi.org/10.1016/j.molimm.2021.01.007 Wang C, Li H-B, Li S, et al (2012) Antitumor effects and cell selectivity of temporin-1CEa, an antimicrobial peptide from the skin secretions of the Chinese brown frog ( Rana chensinensis ). Biochimie 94:434–441. https://doi.org/10.1016/j.biochi.2011.08.011 Zhang X, Cheng Y, Yang Y, et al (2016) Polypeptides from the Skin of Rana Chensinensis Exert the Antioxidant and Antiapoptotic Activities on HaCaT cells. Anim Biotechnol 30:1–10. https://doi.org/10.1080/10495398.2016.1188825 Ji X, Liu G, Cui Y, et al (2020) A hybrid system of hydrogel/frog egg-like microspheres accelerates wound healing via sustained delivery of RCSPs. J Appl Polym Sci 137:49521. https://doi.org/10.1002/app.49521 Zhao Y, Wang Z, Zhang J, Su T (2018) Extraction and characterization of collagen hydrolysates from the skin of Rana chensinensis. 3 Biotech 8:181. https://doi.org/10.1007/s13205-018-1198-y Wu D, Cao Y, Su D, et al (2024) Preparation and identification of antioxidant peptides from Quasipaa spinosa skin through two-step enzymatic hydrolysis and molecular simulation. Food Chem 445:138801. https://doi.org/10.1016/j.foodchem.2024.138801 Dai C, Ma H, He R, et al (2017) Improvement of nutritional value and bioactivity of soybean meal by solid-state fermentation with Bacillus subtilis . LWT 86:1–7. https://doi.org/10.1016/j.lwt.2017.07.041 Lee M-K, Kim J-K, Lee S-Y (2018) Effects of fermentation on SDS-PAGE patterns, total peptide, isoflavone contents and antioxidant activity of freeze-thawed tofu fermented with Bacillus subtilis . Food Chem 249:60–65. https://doi.org/10.1016/j.foodchem.2017.12.045 Wang Y, Sun H, Han B, et al (2022) Improvement of nutritional value, molecular weight patterns (soluble peptides), free amino acid patterns, total phenolics and antioxidant activity of fermented extrusion pretreatment rapeseed meal with Bacillus subtilis YY-1 and Saccharomyces cerevisiae YY-2. LWT 160:113280. https://doi.org/10.1016/j.lwt.2022.113280 Zhu Z, Song X, Jiang Y, et al (2022) Chemical structure and antioxidant activity of a neutral polysaccharide from Asteris Radix et Rhizoma. Carbohydr Polym 286:119309. https://doi.org/10.1016/j.carbpol.2022.119309 Mulu D, Yimer F, Mekuyie M (2025) Optimization of Fermentation Parameters for Bioethanol Production Using Water Hyacinth (Eichhornia crassipes). Chem Afr 8:2833–2844. https://doi.org/10.1007/s42250-025-01287-z Jin S, Zhao H, Liu W, et al (2026) An efficient and green pretreatment of Astragalus membranaceus fermentation with magnetic cellulose-immobilized Bacillus natto using deep eutectic solvent assisted for improving thrombolytic activity and evaluation of its antioxidant activity. Prep Biochem Biotechnol 56:14–23 Heng X, Chen H, Lu C, et al (2022) Study on synergistic fermentation of bean dregs and soybean meal by multiple strains and proteases. LWT 154:112626. https://doi.org/10.1016/j.lwt.2021.112626 Liu M, Li Z, Chen Q, et al (2024) Preparation and characterization of grouper bone peptides-calcium complex by lactic acid bacteria fermentation. LWT 201:116224. https://doi.org/10.1016/j.lwt.2024.116224 Chen Y-T, Hsieh S-L, Gao W-S, et al (2021) Evaluation of Chemical Compositions, Antioxidant Capacity and Intracellular Antioxidant Action in Fish Bone Fermented with Monascus purpureus. Molecules 26:5288. https://doi.org/10.3390/molecules26175288 Yi X, Zhang S, Meng D, et al (2024) Optimization of Rosa roxburghii Tratt pomace fermentation process and the effects of mono- and mixed culture fermentation on its chemical composition. Front Nutr 11:. https://doi.org/10.3389/fnut.2024.1494678 Wang K, Tian Y, Zhou N, et al (2018) Studies on fermentation optimization, stability and application of prolyl aminopeptidase from Bacillus subtilis. Process Biochem 74:10–20. https://doi.org/10.1016/j.procbio.2018.08.035 Li J, Lu J, Ma Z, et al (2022) A Green Route for High-Yield Production of Tetramethylpyrazine From Non-Food Raw Materials. Front Bioeng Biotechnol 9:. https://doi.org/10.3389/fbioe.2021.792023 Guo L, Guo Y, Wu P, et al (2022) Enhancement of Polypeptide Yield Derived from Rapeseed Meal with Low-Intensity Alternating Magnetic Field. Foods 11:2952. https://doi.org/10.3390/foods11192952 Sheng Y, Qiu Y-T, Wang Y-M, et al (2022) Novel Antioxidant Collagen Peptides of Siberian Sturgeon (Acipenserbaerii) Cartilages: The Preparation, Characterization, and Cytoprotection of H2O2-Damaged Human Umbilical Vein Endothelial Cells (HUVECs). Mar Drugs 20:325. https://doi.org/10.3390/md20050325 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8565314","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595730194,"identity":"8a53be8d-8ea4-450d-b9bd-d0ed9441c382","order_by":0,"name":"Hui Zhang","email":"","orcid":"","institution":"Jilin Engineering Vocational College","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Zhang","suffix":""},{"id":595730198,"identity":"2696d8bb-a2a6-41b1-bba9-f77496b36aac","order_by":1,"name":"Qingqing Li","email":"","orcid":"","institution":"Liaoning Inspection Examination and Certification Center","correspondingAuthor":false,"prefix":"","firstName":"Qingqing","middleName":"","lastName":"Li","suffix":""},{"id":595730200,"identity":"45f36d7b-5dfa-498a-a9c5-2124f5e08cd9","order_by":2,"name":"Jianhang Li","email":"","orcid":"","institution":"Jilin Normal University Boda College","correspondingAuthor":false,"prefix":"","firstName":"Jianhang","middleName":"","lastName":"Li","suffix":""},{"id":595730201,"identity":"b979429a-c72b-4a9f-81c5-1dd06bbdb438","order_by":3,"name":"Yani Chen","email":"","orcid":"","institution":"Jilin Normal University Boda College","correspondingAuthor":false,"prefix":"","firstName":"Yani","middleName":"","lastName":"Chen","suffix":""},{"id":595730202,"identity":"805d7fea-2027-42af-a20f-48d20cf3d95e","order_by":4,"name":"Xiaoxi Shen","email":"data:image/png;base64,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","orcid":"","institution":"Jilin Normal University Boda College","correspondingAuthor":true,"prefix":"","firstName":"Xiaoxi","middleName":"","lastName":"Shen","suffix":""}],"badges":[],"createdAt":"2026-01-10 03:38:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8565314/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8565314/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103353856,"identity":"33b89d56-e181-4bb7-af4a-00674c1e2589","added_by":"auto","created_at":"2026-02-24 17:50:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":212910,"visible":true,"origin":"","legend":"\u003cp\u003ePeptide content and DPPH scavenging rate (a) and SDS-PAGE analysis (b) of peptides from RCS at different fermentation time. Lane M: Marker; Lanes 1–9: 0, 3, 6, 9, 12, 15, 18,21and 24 h, respectively.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8565314/v1/e792b2991883d6aeb4fc3789.png"},{"id":103506318,"identity":"c6189f1b-677a-4ba4-b6a9-70db83112e06","added_by":"auto","created_at":"2026-02-26 13:35:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":73289,"visible":true,"origin":"","legend":"\u003cp\u003ePeptide content and DPPH scavenging rate of peptides from RCS at different inoculum amounts\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8565314/v1/a265cafe841d67ca218eeb7c.png"},{"id":103507007,"identity":"fe744d4a-e8b3-4f74-8a8e-6be704bd67e3","added_by":"auto","created_at":"2026-02-26 13:40:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":67986,"visible":true,"origin":"","legend":"\u003cp\u003ePeptide content and DPPH scavenging rate of peptides from RCS at different pH values\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8565314/v1/b0fbb7b51c6787f64b644488.png"},{"id":103506734,"identity":"0df93ce4-3e21-4006-a616-e39d6a833380","added_by":"auto","created_at":"2026-02-26 13:39:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":63519,"visible":true,"origin":"","legend":"\u003cp\u003ePeptide content and DPPH scavenging rate of peptides from RCS at different liquid volumes\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8565314/v1/ec1dd833136ca63d99f4ad13.png"},{"id":103507949,"identity":"541fe64f-0299-4815-97c7-8b9e2021be82","added_by":"auto","created_at":"2026-02-26 13:46:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":71007,"visible":true,"origin":"","legend":"\u003cp\u003ePeptide content and DPPH scavenging rate of peptides from RCS at different shaking speed\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8565314/v1/243c90486f4b9b2c67ab13ea.png"},{"id":103506317,"identity":"7da901ff-ac52-4ef2-86d4-54a2372356d1","added_by":"auto","created_at":"2026-02-26 13:35:13","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":455623,"visible":true,"origin":"","legend":"\u003cp\u003eResponse surface and contour plots of peptide content: (a) Interaction between glycerol and soybean dregs. (b) Interaction between glycerol and soybean dregs. (c) Interaction between glycerol and soybean dregs.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8565314/v1/2954ad71273b0747b1ebf1ac.png"},{"id":103506768,"identity":"10287255-04ee-4c5d-997f-8869614b24a5","added_by":"auto","created_at":"2026-02-26 13:39:24","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":14096,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular weight distribution of peptide\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8565314/v1/dd51f02a5bb7409da613afa2.png"},{"id":105729117,"identity":"76105fe1-ef47-4eed-a8cc-34eb1fdd0957","added_by":"auto","created_at":"2026-03-30 11:13:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2003694,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8565314/v1/be69b8dd-cc1b-4012-b5f7-b09a50647de9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Preparation and Characterization of Peptides from Rana chensinensis skin via Microbial Fermentation","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eAmphibian skin secretions represent significant natural sources of bioactive peptides. Early investigations into the active compounds present in amphibian skin have confirmed that it is abundant in biogenic amines, bufogenin, alkaloids, peptides, and proteins, all of which play crucial roles in physiological regulation[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Given the rich structural and diverse functions of these peptides, subsequent research has gradually focused on the extraction, isolation and purification of peptides from amphibian skin and the identification of their biological activities. Andre et al.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] characterized amphibian skin as a \"treasure trop of peptides\", highlighting that the variety and content of peptides found therein far exceed those present in other animal organs while also exhibiting a wide range of biological activities. This provides an essential material foundation for research across related fields. Rana chensinensis is a valuable economic amphibian species utilized for both medicinal and culinary purposes, it is primarily distributed in Northeast China and possesses high development and utilization value[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, the processing of its products has remained in the primary stage for a long time, the intensive processing technology is relatively scarce, and there is a significant limitation in the utilization of resources. Most of the existing processing modes focus on the extraction of Rana chensinensis oil, which is the dried product in the female oviduct of Rana chensinensis[\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. While this oil is widely acknowledged for its nutrient richness, numerous by-products generated during extraction, including skin, bones and internal organs, are not effectively utilized. They are typically relegated to feed production or discarded outright. This practice results in considerable resource wastage. Notably, recent studies have increasingly demonstrated that peptides extracted from Rana chensinensis skin (RCS) exhibit remarkable biological activities, such as antibacterial[\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], anti-tumor[\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], antioxidant[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], promote wound healing[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This indicates significant application value and development potential across various fields such as food, medicine, cosmetics, and more. Furthermore, it offers a new direction for the efficient utilization of the entire industrial chain associated with Rana chensinensis.\u003c/p\u003e \u003cp\u003eIn recent years, there has been a relative scarcity of studies focused on the preparation of peptides from RCS. The commonly employed methods include physicochemical techniques and enzymatic hydrolysis methods. However, these approaches are often associated with challenges such as low peptide yields, complex process and high costs. For example, Wang et al.[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] soaked the dried skin of Rana chensinensis in an acetic acid solution to obtained an extract rich in polypeptides through ultrasonic treatment and vacuum concentration. This extract was confirmed to exhibit antibacterial effects against \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e and so on. Wang et al.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] extracted collagen hydrolysate from the skin of Rana chensinensis under acidic conditions using pepsin, achieving a yield of 15.1% (w/w). They also suggested that the skin of Rana chensinensis could serve as an alternative source of collagen hydrolysate for applications in both the food industry and pharmaceutical sectors. Additionally, Zhang et al.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] extracted polypeptides, ARPS and ERPs, from the skin of Rana chensinensis by combining acid extraction with enzymatic digestion. The yields were 0.65% and 0.52%, respectively. These polypeptides demonstrated the ability to enhance the proliferation rate of HaCaT cells by factors of 1.66 and 2.1, respectively, while also reducing the apoptosis rate by factors of 2.6 and 3.4, respectively. Wu et al.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] subjected the skin of Quasipaa Spinosa to enzymatic hydrolysis treatment with papain and acidic protease, achieving a hydrolysis degree of 30%. The hydrolysis product (QSPH-I-3) was obtained through the purification of ultrafiltration and gel filtration chromatography purification. The IC\u003csub\u003e50\u003c/sub\u003e of DPPH, ABTS and hydroxyl radical scavenging capacity were found to be 1.68+/-0.05 mg/mL, 1.20+/-0.14 mg/mL and 1.55+/-0.11 mg/mL, respectively. Previous studies have indicated that few peptides derived from RCS have been produced through microbial fermentation. However, this approach offers several advantages including high yield, low cost, small molecular weight, enhanced biological activity, straightforward fermentation processes, and greater potential for industrial application. Meanwhile, research has shown that compounds exhibiting antioxidant activity, such as low-molecular-weight peptides and amino acids, can be generated via microbial fermentation to improve overall antioxidant efficacy[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Therefore, RCS was selected as the focus of this study in which peptides were obtained through fermentation with \u003cem\u003eBacillus subtilis\u003c/em\u003e under optimized production conditions. The production conditions were optimized. This provided an efficient strategy for utilizing the by-products remaining after processing Rana chensinensis\u0026mdash;specifically RCS.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Materials\u003c/h2\u003e\n \u003cp\u003eRCS is sourced from Fusong County, Baishan City, Jilin Province, China. \u003cem\u003eBacillus subtilis\u003c/em\u003e is purchased from the Shanghai Preservation Microbial Center. Additionally, 1,1-diphenyl-2-trinitrophenylhydrazine (DPPH), Gly-Gly-Tyr-Arg, Gly-Gly-Gly, cytochrome C, aprotinin and bacitracin are purchased from Sigma in the United States. All other chemical agents utilized in this study are of domestically produced analytical grade.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Preparation of Peptides from RCS\u003c/h2\u003e\n \u003cp\u003eThe glycerol stock of \u003cem\u003eBacillus subtilis\u003c/em\u003e was streaked onto LB solid medium and incubated at 37\u0026deg;C for 24 h. Subsequently, a single colony from the plate was selected using an inoculating loop and transferred into 3 mL of LB liquid medium. This culture was shaken at 160 rpm at 37\u0026deg;C for 12 h to obtain the seed culture of \u003cem\u003eBacillus subtilis\u003c/em\u003e .\u003c/p\u003e\n \u003cp\u003eThe RCS medium is prepared by directly mixing 6 g of RCS powder, which is produced by crushing clean and dried RCS, with 100 mL of distilled water. The mixture is then subjected to pH adjustment and sterilization (115\u0026deg;C, 30 min). After cooling, the RCS medium is inoculated with the seed culture of \u003cem\u003eBacillus subtilis\u003c/em\u003e and subsequently incubated in a constant-temperature shaking incubator for a designated period. Subsequently, the fermentation broth is immediately boiled in a 98\u0026deg;C water bath for 5 min. The peptides derived from RCS are obtained as supernatant after centrifugation (8,000\u0026times;g at 4\u0026deg;C for 10 min).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Optimization of Fermentation Conditions\u003c/h2\u003e\n \u003cp\u003eSingle-factor experiments were conducted to evaluate the effects of various parameters on the content of peptides derived from RCS and the DPPH radical scavenging rate. The factors examined included inoculum amount (1\u0026ndash;6%, v/v), pH values (5\u0026ndash;9), liquid volume (20%-60%), fermentation time (0\u0026ndash;24 h) and shaking speed (100\u0026ndash;220 rpm). Additionally, all other experimental conditions were ensured to be consistent. Based on the above experimental results, the Box-Behnken Design (BBD) of the response surface methodology was employed to optimize the fermentation process parameters. Using the peptide content as the response value, a 3-factor and 3-level experiment was carried out to identify the optimal fermentation conditions for RCS.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Peptide Content Quantification and DPPH radical Scavenging Assay\u003c/h2\u003e\n \u003cp\u003ePeptide content was quantified using the biuret method with reduced glutathione as the standard substance.\u003c/p\u003e\n \u003cp\u003eThe DPPH radical scavenging rate was determined according to the method method described by Zhu et al.[\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e], with slight modifications. Anhydrous ethanol and 0.1 mmol/L DPPH ethanol (\u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e), peptides and 0.1 mmol/L DPPH ethanol (\u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e), as well as peptide and anhydrous ethanol (\u003cem\u003eA\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e) were mixed in equal volumes, and allowed to react in the dark at room temperature for 30 min. The OD value of the mixed solution at 517 nm was measured using a concentration of 0.1 mg/mL vitamin C as a positive control. The calculation formula is presented as follows:\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5 Determination of the Relative Molecular Weight of Peptides\u003c/h2\u003e\n \u003cp\u003eA Waters 2695 high performance liquid chromatography (HPLC) was performed to analyze the relative molecular weight of peptides.The chromatographic column employed was a TSKgel 2000SWxl (300\u0026times;7.8 mm). The mobile phase consisted of a mixture of acetonitrile, water and trifluoroacetic acid in a volume ratio of 40 : 60 : 0.1. The flow rate was set at 0.5 mL/min, and the column temperature was maintained at 30℃. UV detection was performed at a wavelength of 220 nm. Standard substances used for constructing the molecular weight calibration curve included cytochrome (12384 Da), aprotinin (6500 Da), bacitracin (1422 Da), glycine-glycine-tyrosine-arginine (451 Da), and glycine-glycine-glycine (MW: 189 Da).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6 ultrafiltration\u003c/h2\u003e\n \u003cp\u003eThe fermentation liquor of RCS was fractionated using ultrafiltration centrifuge tubes with molecular weight of 3 kDa and 10 kDa, followed by centrifugation at 10,000\u0026times;g for 20 min at 4℃. Peptides were collected based on their molecular weights into three distinct categories: those greater than 10 kDa (MW\u0026thinsp;\u0026gt;\u0026thinsp;10 kDa), those between 3 kDa and 10 kDa (3 kDa\u0026thinsp;\u0026lt;\u0026thinsp;MW\u0026thinsp;\u0026lt;\u0026thinsp;10 kDa), and those less than 3 kDa (MW\u0026thinsp;\u0026lt;\u0026thinsp;3 kDa). After freeze-drying, the peptides were redissolved in distilled water to a concentration of 1 mg/mL for the determination of DPPH scavenging activity, and preliminarily explore the relationship between the molecular weight of peptides and antioxidant activity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.7 Statistical Analysis\u003c/h2\u003e\n \u003cp\u003eSPSS software (version 29.0 SPSS, IBM) was applied for statistical analysis. A one-way ANOVA with multiple comparisons (LSD) and Tukey\u0026rsquo;s post hoc test were employed to assess significant differences among the treatment groups, with significance levels set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 or p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. All data are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD of three independent experimental groups.The figures were generated using OriginPro 2025 and Design Expert 13 software.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Results of Single-factor Experiments\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1 Effect of Fermentation Time on the Fermentation of RCS\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, compared to unfermented RCS, both the peptide content and DPPH scavenging rate of fermented RCS significantly increased with the extension of fermentation time, peaking at 15 h. In contrast, a significant decrease in peptide content and DPPH scavenging rate was observed after 15 h (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Furthermore, results from subsequent analysis using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) were consistent (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The upper portion of the band for unfermented RCS (Lane 1) appears relatively dark, indicating a higher presence of high-molecular-weight proteins in the fermentation broth. As fermentation proceeds, bands gradually deepen in regions corresponding to low-molecular-weight peptides. Notably, Bands 6 and 7 exhibit darker low-molecular-weight regions. This observation suggests that through microbial action during fermentation, RCS can be decomposed into low-molecular-weight peptides that demonstrate strong antioxidant activity. In conclusion, further investigation will focus on varying fermentation times (12 h, 15 h and 18 h) as variables in response surface experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2 Effect of Inoculum Amount on the Fermentation of RCS\u003c/h2\u003e \u003cp\u003eThe inoculum amount of \u003cem\u003eBacillus subtilis\u003c/em\u003e was used as a variable to explore its effect on the fermentation of RCS, and the results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, peptide content and DPPH scavenging rate of RCS initially increased and subsequently decreased with the increase of inoculum amount (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Notably, these parameters reached their peak values when the inoculum amount was set at 3%. Therefore, the inoculum amount of \u003cem\u003eBacillus subtilis\u003c/em\u003e (2%, 3%, 4%) during the fermentation of RCS will be further studied as a variable in the response surface experiment.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3 Effect of pH on the Fermentation of RCS\u003c/h2\u003e \u003cp\u003eThe effects of different pH values on the peptide content and DPPH scavenging rate of RCS are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. With the increase of pH, the peptide content initially rises before subsequently declining (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), however, alterations in pH do not have a significant effect on the clearance rate. Notably, both peptide content and DPPH scavenging rate reach their peak values at pH 7, which is therefore designated as the optimal pH for RCS fermentation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.1.4 Effect of Liquid Volume on the Fermentation of RCS\u003c/h2\u003e \u003cp\u003eThe effect of different liquid volumes on the fermentation of RCS was investigated in this experiment, and the results was shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. With the increase of liquid volume, there was a gradual decline in dissolved oxygen content and DPPH scavenging rate of RCS exhibited significant reductions (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), reaching the maximum value at a 20% liquid volume..\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.1.5 Effect of Shaking Speed on the Fermentation of RCS\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, experimental results indicate that both peptide content and DPPH scavenging rate significantly increased \u003cem\u003e(p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/em\u003e) as the shaking speed was accelerated, peaking at a speed of 180 rpm. However, when the shaking speed exceeded 180 rpm, both peptide content and DPPH scavenging rate decreased significantly (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/em\u003e). Therefore, further investigation into varying shaking speeds (140 rpm, 180 rpm, and 220 rpm) during RCS fermentation will be conducted as part of response surface experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Response Surface Analysis for Optimization of Fermentation Conditions\u003c/h2\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1 Response Surface Experimental Design and Results\u003c/h2\u003e \u003cp\u003eBased on the results of the single-factor experiment and the central combination design of Box-Behnken, a total of 17 experimental groups of experiments were conducted. The fermentation time (A), inoculation volume (B), and shaker speed (C) were designated as independent variables, and the peptide content was taken as the response value. The variables and levels of experimental factors are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExperimental domain of BBD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSymbol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eLevels\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow level (-1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCenter level (0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh level (+\u0026thinsp;1)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFermentation time (h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInoculum amount (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShaking speed (rpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe experimental results of BBD are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and regression variance fitting was performed on the data in the table. The multiple quadratic regression model equation of peptide content (Y) was obtained as follows: Y\u0026thinsp;=\u0026thinsp;71.17\u0026thinsp;+\u0026thinsp;1.19A\u0026thinsp;+\u0026thinsp;1.21B\u0026thinsp;+\u0026thinsp;1.55C-0.6250AB-0.5925AC-0.8925BC-2.46A\u003csup\u003e2\u003c/sup\u003e-4.30B\u003csup\u003e2\u003c/sup\u003e-3.31C\u003csup\u003e2\u003c/sup\u003e. The results of the response surface regression model and analysis of variance are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the F-value reflects the variance ratio of regression to residual, with larger values signifying better model fit. The lack-of-fit term represents the difference between observed values and predicted values, with smaller values indicating a better fit. In this experiment, the F-value of the model is 110.82 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating an extremely significant result. Furthermore, the lack-of-fit term of 0.1181 (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), which is not significant, suggesting that the regression equation is appropriate. In addition, R\u0026sup2; = 0.9930 and R\u0026sup2;\u003csub\u003eAdj\u003c/sub\u003e = 0.9841, which shows that the experiment has a high degree of fitting, and the equation fits the actual situation. By comparing F-value, the order of influence of the three factors on the peptide content is as follows: C (shaking speed)\u0026thinsp;\u0026gt;\u0026thinsp;B (inoculum amount)\u0026thinsp;\u0026gt;\u0026thinsp;A (fermentation time). This model can be used to analyze and determine the optimal process parameters for preparing peptides by fermenting RCS.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExperiment design and results of BBD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRun\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA:Fermentation time (h)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB:Inoculum amount (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC:Shaking speed (rpm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003epeptide content (mg/mL)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResponse surface regression model and analysis of variance results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSum of Squares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e214.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e110.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e118.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e362.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e214.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of Fit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003enot significant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePure Error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.3972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCor Total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e216.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e* Indicates significant differences (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). ** Indicates extremely significant differences (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2 Interaction Analysis\u003c/h2\u003e \u003cp\u003eResponse surface and contour maps generated based on the model equation can reveal the interaction relationships among factors, thereby identifying the optimal factors and their corresponding levels[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, variations in independent variables resulted in a general trend of response values that initially increased before subsequently decreasing. The contour map for each factor exhibited an approximately elliptical shape, indicating significant interactions among all pairs of factors, namely AB, AC and BC. Furthermore, the response surface reached a maximum value with a relatively steep slope.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3 Determination of 0ptimal Conditions and Verification Test\u003c/h2\u003e \u003cp\u003eThe Design Expert 13 software was used to obtain the optimal fermentation parameters as follows: fermentation time of 15.61 h, inoculation amount of 3.11%, shaking speed was 188.07 rpm, and the predicted value of peptide content of 71.51 mg/mL. For practical application purposes, the experimental conditions were adjusted to fermentation time of 16 h, inoculation amount of 3%, and a shaking speed of 190 rpm. Verification tests were conducted under these specified conditions. The peptide content obtained from the three parallel experiments was 71.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92 mg/mL, which was close to the predicted value. In addition, under optimal fermentation conditions, a DPPH scavenging rate of 81.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03% was achieved. In comparison to the pre-fermentation state, where the RCS exhibited a peptide content of 25.84 mg/mL and a DPPH scavenging rate of 14.22%, the peptide content was raised by 1.77-fold, while the DPPH scavenging rate was elevated by 4.71-fold.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Distribution of Relative Molecular Weight\u003c/h2\u003e \u003cp\u003eGenerally, the relative molecular weight of peptide is considered to be less than 10,000 Da. The optimal fermentation conditions in the previous paper were selected to prepare the peptide of RCS, and its molecular weight was determined by HPLC. Results as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, peptides with a molecular weight of less than 10,000 Da constituted 76.25% of the total content in the fermentation liquor. Among these, peptides weighing less than 3,000 Da accounted for 50.54%, while small molecular peptides under 1,000 Da represented 33.45%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePeptide content of different molecular weights\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMolecular weight range / Da\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeptide Content / %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10000\u0026thinsp;~\u0026thinsp;5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5000\u0026thinsp;~\u0026thinsp;3000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3000\u0026thinsp;~\u0026thinsp;2000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2000ཞ1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1000\u0026thinsp;~\u0026thinsp;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e500ཞ180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal (\u0026lt;10000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Antioxidant activity of ultrafiltration components\u003c/h2\u003e \u003cp\u003eThe DPPH scavenging rate of various molecular weight components in the fermentation liquor of RCS after ultrafiltration classification are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. As the molecular weight decreases, there is a significant increase in the DPPH scavenging rate. Specifically, peptides with MW\u0026thinsp;\u0026lt;\u0026thinsp;3 kDa exhibited the highest DPPH scavenging rate. The activity of fermentation liquor was slightly lower than that of small molecular peptides. In contrast, macromolecular proteins (MW\u0026thinsp;\u0026gt;\u0026thinsp;10 kDa) have the lowest DPPH scavenging rate.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDPPH scavenging rate of peptides with various molecular weights after ultrafiltration\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFermentation liquor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMW\u0026thinsp;\u0026gt;\u0026thinsp;10 kDa\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e3 kDa\u0026thinsp;\u0026lt;\u0026thinsp;MW\u0026thinsp;\u0026lt;\u0026thinsp;10 kDa\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMW\u0026thinsp;\u0026lt;\u0026thinsp;3 kDa\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDPPH scavenging rate / %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e44.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e89.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe results of this study indicate that key parameters such as fermentation time, inoculum amount, pH, liquid volume, and shaking speed significantly influence the microbial fermentation process, thereby influencing the formation of fermentation products and their antioxidant activity. These findings are consistent with previous studies on the synergistic regulation of multiple parameters in microbial fermentation processes[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Time is a critical factor influencing microbial fermentation. The growth, metabolism, and degradation of various substances by microorganisms are all affected by the duration of fermentation. It is important to note that prolonged fermentation times may increase costs and introduce additional challenges[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In this experiment, both peptide content and DPPH radical scavenging rate of RCS extract significantly decreased after 15 hours of fermentation. This may be attributed to the continuous consumption and limitation of nutrients in the culture medium, which not only affects the growth and fermentation process of the strain, but also even leads to the autolysis of the strain and the hydrolysis of peptides[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This suggests that, in the optimization of practical fermentation processes, precise control over the termination time of fermentation is essential to balance product accumulation with production costs and process stability. For instance, Can et al. investigated the fermentation time parameters (3 days for F3, 6 days for F6) of fish bone fermentation by \u003cem\u003eMonascus purpureus\u003c/em\u003e, and found that the contents of soluble proteins, peptides and other related substances in the fermented products, as well as the antioxidant capacity (such as DPPH and ABTS⁺ radical scavenging activities), were significantly enhanced[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] .\u003c/p\u003e \u003cp\u003eThe regulation of inoculum amount is also crucial. This study observed that excessive inoculation significantly inhibits the fermentation process, specifically manifested by a marked decrease in peptide content and DPPH radical scavenging rate when the inoculum amount exceeds 3%. Excessive inoculation can cause rapid metabolism of the strain in the early stage of fermentation, accelerate the consumption of nutrients, and may also accumulate inhibitory metabolites, thereby hindering the growth of the strain[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This result is consistent with microbial growth kinetics theory, which states that the inoculum amount must be matched to the nutrient supply capacity of the medium to maintain the strain in a stable logarithmic growth phase and ensure efficient fermentation. For instance, in the study by Yi et al. on optimization of \u003cem\u003eRosa roxburghii\u003c/em\u003e Tratt pomace fermentation process, experimental results showed that the total phenolic content increased with inoculum amount ranging from 6% to 10%, and then decreased as the inoculum amount was further increased from 10% to 14%[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eChanges in pH can significantly influence the charge properties and dissociation states of nutrients within the medium, as well as the charge properties of cells, thereby impacting substance exchange[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. However, the results of this study indicate that pH has no significant effect on peptide content or DPPH radical scavenging activity. This may be attributed to the strain's inherent tolerance to pH variations or the pH gradient range set in the experiment falling within its optimal growth range. This finding suggests that, in subsequent process optimization, the priority of pH control could be appropriately reduced, with greater emphasis placed on other parameters that exert more pronounced influences.\u003c/p\u003e \u003cp\u003eIn the process of liquid fermentation, liquid volume serves as a critical parameter for regulating the oxygen environment. The results of this study indicate that peptide content and DPPH radical scavenging activity decrease with increasing liquid volume, which may be attributed to the fact that an excessively high liquid volume reduces the concentration of dissolved oxygen. This reduction impedes the metabolism of aerobic bacteria and promotes the accumulation of metabolic by-products. In contrast, an excessively low liquid volume may lead to excessive foam generation during shaking, thereby increasing the risks of contaminating bacteria and bacterial autolysis. Consequently, precise regulation of liquid volume to match the dissolved oxygen with the metabolic requirements of microorganisms is essential for optimizing the fermentation process.\u003c/p\u003e \u003cp\u003eThe shaking speed of the fermentation system is directly correlated with the concentration of dissolved oxygen, and maintaining an optimal level of dissolved oxygen is crucial for ensuring the robust growth of microbial strain[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This study further found that when the rotation speed exceeded 180 r/min, both peptide content and DPPH radical scavenging activity decreased. This may be attributed to the insufficient dissolved oxygen concentration in the fermentation system at lower speeds, which adversely regulated the metabolic process of the strain. Conversely, excessively high rotational speeds can lead to a substantial increase in oxygen dissolution rates, ultimately causing the strain to rapidly enter a phase of growth decline[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eElucidating the characteristics of fermentation products and identifying the core source of their antioxidant activity are key prerequisites for achieving targeted optimization and efficient application of these products. Therefore, RCS peptides were prepared under the optimal fermentation conditions established in previous sections, followed by in-depth analysis using molecular weight determination and ultrafiltration fractionation methods. From the general properties of peptide substances, a molecular weight below 10,000 Da is a typical characteristic of peptides. Enzymatic hydrolysis during microbial fermentation is likely the central mechanism regulating the molecular weight distribution of the resulting products. This study hypothesizes that enzymes capable of promoting the hydrolysis of RCS peptides may be generated during microbial fermentation, which could degrade large-molecule RCS peptides into numerous small-molecule peptides. These low-molecular-weight peptides can effectively react with free radicals and exhibit significant antioxidant activity, thereby enhancing the free radical scavenging capacity of the fermentation broth[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This enzymatic hydrolysis regulatory mechanism provides a rational explanation for the formation of antioxidant activity in the fermentation system.\u003c/p\u003e \u003cp\u003eUltrafiltration fractionation analysis further confirms the intrinsic correlation between molecular weight characteristics and antioxidant activity, indicating that the molecular weight of peptides is a key determinant of their antioxidant potency. Specifically, low-molecular-weight peptides tend to exhibit superior DPPH radical scavenging activity. This may be attributed to the strong antioxidant activity of small molecular peptides accompanied by free radical exposure[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. From the perspective of structure\u0026ndash;function relationships, low-molecular-weight peptides possess simpler spatial conformations, allowing their antioxidant active sites to be more fully exposed. Consequently, they can interact with free radicals more efficiently and exert stronger scavenging effects. Notably, the activity of fermentation liquor was slightly lower than that of small molecular peptides due to the influence of macromolecular impurities in the system. In contrast, macromolecular proteins (MW\u0026thinsp;\u0026gt;\u0026thinsp;10 kDa) have the lowest DPPH scavenging rate due to their complex structure, difficult exposure of active sites, and the existence of steric hindrance and substrate competition. This further clarifies the regulatory role of molecular weight characteristics in the antioxidant function of peptides.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eOwing to the advantages of high efficiency, environmental protection and low cost, biological fermentation has been widely used in the preparation of bioactive substances, especially becoming one of the mainstream technical paths for peptide preparation. With this technology as the core, the fermentation process parameters were optimized through single factor experiment and response surface analysis, and the fermentation products were finally significantly improved in both peptide content and DPPH scavenging rate. The result directly confirmed that microbial fermentation technology can effectively activate the biological activity value of RCS. Furthermore, the results of HPLC and ultrafiltration centrifugation confirmed that small molecular peptides were the key components to endow the fermentation products with excellent antioxidant properties, which provided a clear direction for the isolation and precise development of active substances from RCS. In terms of application value, the study broke the limitations of traditional utilization of RCS and established an effective path for the utilization of animal-derived by-products. It not only laid a foundation for its application in multiple fields such as food and medicine, but also provided a technical paradigm for the sustainable development of similar biological resources, with potential industrialization prospects. In addition, future research could focus on the technical bottleneck of peptide preparation and overcome practical application problems such as the maintenance of activity, and promote the deep transformation of forest frog skin resources from \u0026ldquo;waste\u0026rdquo; to \u0026ldquo;high-value products\u0026rdquo; through process optimization and technological innovation. To promote the in-depth transformation of RCS from \u0026ldquo;waste\u0026rdquo; to \u0026ldquo;high-value products\u0026rdquo; through process optimization and technological innovation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eThis work is supported by the Science and Technology Research Project of Jilin Provincial Department of Education (JJKH20241741KJ), the Concept Validation Center of Boda College of Jilin Normal University, and the High-Level Discipline Cluster for Deep Processing of Jilin Characteristic Resource Foods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003eAll authors contributed to the study conception and design. H.Z., J.L. and Y.C. methodology \u0026ndash; production and optimization of RCS, Q.L. and X. S. methodology \u0026ndash; determination of the relative molecular mass of the peptide. The first draft of the manuscript was written by H.Z.. The article was corrected to be by X.S.. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e This study was funded by the Science and Technology Research Project of Jilin Provincial Department of Education (JJKH20241741KJ).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e The authors confirm that the datasets supporting the findings and conclusions of this study are available within the article. Additional data can be provided upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eErspamer V, Erspamer GF, Inselvini M, Negri L (1972) Occurrence of bombesin and alytesin in extracts of the skin of three European discoglossid frogs and pharmacological actions of bombesin on extravascular smooth muscle. Br J Pharmacol 45:333\u0026ndash;348. https://doi.org/10.1111/j.1476-5381.1972.tb08087.x\u003c/li\u003e\n \u003cli\u003eRoseghini M, Erspamer V, Falconieri Erspamer G, Cei JM (1986) Indole-, imidazole- and phenyl-alkylamines in the skin of one hundred and forty American amphibian species other than bufonids. Comp Biochem Physiol C 85:139\u0026ndash;147. https://doi.org/10.1016/0742-8413(86)90064-2\u003c/li\u003e\n \u003cli\u003eRinaldi AC Antimicrobial peptides from amphibian skin: an expanding scenario. https://doi.org/10.1016/S1367-5931(02)00401-5\u003c/li\u003e\n \u003cli\u003eWang R, Zhai S, Liang Y, et al (2020) Antibacterial effects of a polypeptide-enriched extract of Rana chensinensis via the regulation of energy metabolism. Mol Biol Rep 47:4477\u0026ndash;4483. https://doi.org/10.1007/s11033-020-05508-1\u003c/li\u003e\n \u003cli\u003eXiao Y, Ni S, Wang S, et al (2019) Environmental influences on quality features of \u003cem\u003eOviductus Ranae\u003c/em\u003e in the Changbai Mountains. RSC Adv 9:36050\u0026ndash;36057. https://doi.org/10.1039/C9RA04823E\u003c/li\u003e\n \u003cli\u003eZhang Y, Wang Y, Li M, et al (2019) Traditional Uses, Bioactive Constituents, Biological Functions, and Safety Properties of Oviductus ranae as Functional Foods in China. Oxid Med Cell Longev 2019:4739450. https://doi.org/10.1155/2019/4739450\u003c/li\u003e\n \u003cli\u003eWang S, Gan Y, Kan H, et al (2021) Exploitation of HPLC Analytical Method for Simultaneous Determination of Six Principal Unsaturated Fatty Acids in Oviductus Ranae Based on Quantitative Analysis of Multi-Components by Single-Marker (QAMS). Molecules 26:479\u003c/li\u003e\n \u003cli\u003eJi F, Zhao Y, Jiang F, Shang D (2022) Membrane mechanism of temporin-1CEc, an antimicrobial peptide isolated from the skin secretions of \u003cem\u003eRana chensinensis\u003c/em\u003e, and its systemic analogs. Bioorganic Chem 119:105544. https://doi.org/10.1016/j.bioorg.2021.105544\u003c/li\u003e\n \u003cli\u003eJi F, Tian G, Shang D (2024) Antimicrobial peptide 2K4L inhibits the inflammatory response in macrophages and Caenorhabditis elegans and protects against LPS-induced septic shock in mice. Sci Rep 14:15093. https://doi.org/10.1038/s41598-024-64511-9\u003c/li\u003e\n \u003cli\u003eZhang R, Gao J, Xie H, et al (2022) The Prepropalustrin-2CE2 and Preprobrevinin-2CE3 Gene from Rana chensinensis: Gene Expression, Genomic Organization and Functional Analysis of the Promoter Activity. Protein Pept Lett 29:143\u0026ndash;155. https://doi.org/10.2174/0929866528666211125105627\u003c/li\u003e\n \u003cli\u003eYe Z, Zhou X, Xi X, et al (2022) In Vitro \u0026amp; In Vivo Studies on Identifying and Designing Temporin-1CEh from the Skin Secretion of Rana chensinensis as the Optimised Antibacterial Prototype Drug. Pharmaceutics 14:604. https://doi.org/10.3390/pharmaceutics14030604\u003c/li\u003e\n \u003cli\u003eLi M, Liu Z, He J, et al (2025) Trp-containing Peptides with Therapeutic Potential for Cutibacterium acnes Infection. Probiotics Antimicrob Proteins. https://doi.org/10.1007/s12602-025-10749-2\u003c/li\u003e\n \u003cli\u003eHan Z, Wang Y, Wang W, et al (2025) Design, synthesis and activity evaluation of reduction-responsive anticancer peptide temporin-1CEa drug conjugates. Bioorganic Chem 154:108103. https://doi.org/10.1016/j.bioorg.2024.108103\u003c/li\u003e\n \u003cli\u003eZhang J, Sun Y, Kang Y, Shang D (2021) Antimicrobial peptide temporin-1CEa isolated from frog skin secretions inhibits the proinflammatory response in lipopolysaccharide-stimulated RAW264.7 murine macrophages through the MyD88-dependent signaling pathway. Mol Immunol 132:227\u0026ndash;235. https://doi.org/10.1016/j.molimm.2021.01.007\u003c/li\u003e\n \u003cli\u003eWang C, Li H-B, Li S, et al (2012) Antitumor effects and cell selectivity of temporin-1CEa, an antimicrobial peptide from the skin secretions of the Chinese brown frog (\u003cem\u003eRana chensinensis\u003c/em\u003e). Biochimie 94:434\u0026ndash;441. https://doi.org/10.1016/j.biochi.2011.08.011\u003c/li\u003e\n \u003cli\u003eZhang X, Cheng Y, Yang Y, et al (2016) Polypeptides from the Skin of Rana Chensinensis Exert the Antioxidant and Antiapoptotic Activities on HaCaT cells. Anim Biotechnol 30:1\u0026ndash;10. https://doi.org/10.1080/10495398.2016.1188825\u003c/li\u003e\n \u003cli\u003eJi X, Liu G, Cui Y, et al (2020) A hybrid system of hydrogel/frog egg-like microspheres accelerates wound healing via sustained delivery of RCSPs. J Appl Polym Sci 137:49521. https://doi.org/10.1002/app.49521\u003c/li\u003e\n \u003cli\u003eZhao Y, Wang Z, Zhang J, Su T (2018) Extraction and characterization of collagen hydrolysates from the skin of Rana chensinensis. 3 Biotech 8:181. https://doi.org/10.1007/s13205-018-1198-y\u003c/li\u003e\n \u003cli\u003eWu D, Cao Y, Su D, et al (2024) Preparation and identification of antioxidant peptides from \u003cem\u003eQuasipaa spinosa\u003c/em\u003e skin through two-step enzymatic hydrolysis and molecular simulation. Food Chem 445:138801. https://doi.org/10.1016/j.foodchem.2024.138801\u003c/li\u003e\n \u003cli\u003eDai C, Ma H, He R, et al (2017) Improvement of nutritional value and bioactivity of soybean meal by solid-state fermentation with \u003cem\u003eBacillus subtilis\u003c/em\u003e. LWT 86:1\u0026ndash;7. https://doi.org/10.1016/j.lwt.2017.07.041\u003c/li\u003e\n \u003cli\u003eLee M-K, Kim J-K, Lee S-Y (2018) Effects of fermentation on SDS-PAGE patterns, total peptide, isoflavone contents and antioxidant activity of freeze-thawed tofu fermented with \u003cem\u003eBacillus subtilis\u003c/em\u003e. Food Chem 249:60\u0026ndash;65. https://doi.org/10.1016/j.foodchem.2017.12.045\u003c/li\u003e\n \u003cli\u003eWang Y, Sun H, Han B, et al (2022) Improvement of nutritional value, molecular weight patterns (soluble peptides), free amino acid patterns, total phenolics and antioxidant activity of fermented extrusion pretreatment rapeseed meal with \u003cem\u003eBacillus subtilis\u003c/em\u003e YY-1 and \u003cem\u003eSaccharomyces cerevisiae\u003c/em\u003e YY-2. LWT 160:113280. https://doi.org/10.1016/j.lwt.2022.113280\u003c/li\u003e\n \u003cli\u003eZhu Z, Song X, Jiang Y, et al (2022) Chemical structure and antioxidant activity of a neutral polysaccharide from Asteris Radix et Rhizoma. Carbohydr Polym 286:119309. https://doi.org/10.1016/j.carbpol.2022.119309\u003c/li\u003e\n \u003cli\u003eMulu D, Yimer F, Mekuyie M (2025) Optimization of Fermentation Parameters for Bioethanol Production Using Water Hyacinth (Eichhornia crassipes). Chem Afr 8:2833\u0026ndash;2844. https://doi.org/10.1007/s42250-025-01287-z\u003c/li\u003e\n \u003cli\u003eJin S, Zhao H, Liu W, et al (2026) An efficient and green pretreatment of Astragalus membranaceus fermentation with magnetic cellulose-immobilized Bacillus natto using deep eutectic solvent assisted for improving thrombolytic activity and evaluation of its antioxidant activity. Prep Biochem Biotechnol 56:14\u0026ndash;23\u003c/li\u003e\n \u003cli\u003eHeng X, Chen H, Lu C, et al (2022) Study on synergistic fermentation of bean dregs and soybean meal by multiple strains and proteases. LWT 154:112626. https://doi.org/10.1016/j.lwt.2021.112626\u003c/li\u003e\n \u003cli\u003eLiu M, Li Z, Chen Q, et al (2024) Preparation and characterization of grouper bone peptides-calcium complex by lactic acid bacteria fermentation. LWT 201:116224. https://doi.org/10.1016/j.lwt.2024.116224\u003c/li\u003e\n \u003cli\u003eChen Y-T, Hsieh S-L, Gao W-S, et al (2021) Evaluation of Chemical Compositions, Antioxidant Capacity and Intracellular Antioxidant Action in Fish Bone Fermented with Monascus purpureus. Molecules 26:5288. https://doi.org/10.3390/molecules26175288\u003c/li\u003e\n \u003cli\u003eYi X, Zhang S, Meng D, et al (2024) Optimization of Rosa roxburghii Tratt pomace fermentation process and the effects of mono- and mixed culture fermentation on its chemical composition. Front Nutr 11:. https://doi.org/10.3389/fnut.2024.1494678\u003c/li\u003e\n \u003cli\u003eWang K, Tian Y, Zhou N, et al (2018) Studies on fermentation optimization, stability and application of prolyl aminopeptidase from Bacillus subtilis. Process Biochem 74:10\u0026ndash;20. https://doi.org/10.1016/j.procbio.2018.08.035\u003c/li\u003e\n \u003cli\u003eLi J, Lu J, Ma Z, et al (2022) A Green Route for High-Yield Production of Tetramethylpyrazine From Non-Food Raw Materials. Front Bioeng Biotechnol 9:. https://doi.org/10.3389/fbioe.2021.792023\u003c/li\u003e\n \u003cli\u003eGuo L, Guo Y, Wu P, et al (2022) Enhancement of Polypeptide Yield Derived from Rapeseed Meal with Low-Intensity Alternating Magnetic Field. Foods 11:2952. https://doi.org/10.3390/foods11192952\u003c/li\u003e\n \u003cli\u003eSheng Y, Qiu Y-T, Wang Y-M, et al (2022) Novel Antioxidant Collagen Peptides of Siberian Sturgeon (Acipenserbaerii) Cartilages: The Preparation, Characterization, and Cytoprotection of H2O2-Damaged Human Umbilical Vein Endothelial Cells (HUVECs). Mar Drugs 20:325. https://doi.org/10.3390/md20050325\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Rana chensinensis, Skin, Peptide, Optimization, Bacillus subtilis","lastPublishedDoi":"10.21203/rs.3.rs-8565314/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8565314/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs the main by-product of Rana chensinensis product processing, Rana chensinensis skin has important development and utilization value because it is rich in a variety of bioactive components. In this study, \u003cem\u003eBacillus subtilis\u003c/em\u003e was used as the fermentation strain to explore the efficient preparation process and antioxidant activity of peptides from Rana chensinensis skin. The fermentation conditions were optimized by single factor experiment and response surface analysis, and the optimal parameters were determined as follows: inoculum volume was 3%, fermentation time was 16 h, and shaking speed was 190 rpm. Under these conditions, the peptide content of the fermentation product reached 71.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92 mg/mL, and the DPPH scavenging rate was 81.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03%, which were 1.77-fold and 4.71-fold higher than those before fermentation, respectively, and the antioxidant activity was significantly improved. The molecular weight distribution of peptides in fermentation liquor was further analyzed by high performance liquid chromatography. The results showed that the proportion of peptides with molecular weight less than 10,000 Da was up to 90%, and 50.54% of small peptides were concentrated in the range of less than 3000 Da. Subsequently, small molecular peptides were obtained by ultrafiltration centrifugation, which showed higher DPPH scavenging rate, and their key role in antioxidant activity was verified. This study realized the high-value utilization of Rana chensinensis skin, not only laid an experimental foundation for its application in various fields, but also provided a scientific basis for the sustainable utilization of Rana chensinensis skin.\u003c/p\u003e","manuscriptTitle":"Preparation and Characterization of Peptides from Rana chensinensis skin via Microbial Fermentation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-24 17:50:00","doi":"10.21203/rs.3.rs-8565314/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"917052ed-de7c-46ac-bfd0-31ae9440521d","owner":[],"postedDate":"February 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-28T16:09:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-24 17:50:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8565314","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8565314","identity":"rs-8565314","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}