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. 2025 Jul 1;9:118. doi: 10.1038/s41538-025-00491-y

The effect of fermentation times of Semen Sojae Praeparatum on active ingredients and pharmacological activity

Liqiang Sui 1,#, Dongying Cao 2,#, Yali Wang 1, Zhong Wu 1, Sugui Wang 1, Wei Xu 1,✉, Lixia Chen 1,3,✉, Hua Li 1,✉
PMCID: PMC12215671  PMID: 40593753

Abstract

Semen Sojae Praeparatum (SSP) is a traditional soybean fermented food in China. One of the special processes is seven-time fermentation. In order to verify the rationality of the process, we collected samples from multiple stages of fermentation, a mouse fever model was established to observe the antipyretic and anti-inflammatory effects. The content of 22 amino acids, 6 isoflavones and polysaccharides was determined, the biological information was analyzed. Our results showed the peak value of flavonoids, amino acids and polysaccharides content occurred during the second fermentation, while the antipyretic and anti-inflammatory effects were also superior after two-time fermentation. The dominant strains in the fermentation were Aspergillus, Rhizopus arrhizus and Bacillus. Bacillus involved in the transformation of genistin, glutamate and leucine, which contributed to the anti-inflammatory effect. We speculated two-time fermented SSP to be superior, excessive fermentation is likely to negatively affect the accumulation of components and the activities of SSP.

Subject terms: Microbiology, Chemistry

Introduction

Soybean, as one of the most important food crops and nutrition sources for humans, is abundant in fat, vitamins, sugars, isoflavones and other substances with health functions. The practice of fermenting soybean food with the assistance of microorganisms1 has witnessed a long history of development and occupies a vital position in food cultures across the world due to their rich nutrients and delicious taste, such as Natto in Japan, Tianpei Douchi in Indonesia, as well as Douchi in China2. These fermented soybean foods also play an important role in promoting human health by exerting antipyretic, anti-inflammation, anti-osteoporosis, and anti-radiation activities, as well as contributing to the lowering of blood pressure, the reduction of blood lipid, and so on3,4. Nowadays, research on how fermentation techniques and methods impact the components and bioactivities of products has greatly promoted the development of healthier soybean fermented food.

Semen Sojae Praeparatum (SSP), officially recorded in the Chinese Pharmacopoeia with the Chinese name of “Dan-Douchi”, is a kind of Douchi in China fermented by the seeds of the leguminous plant Glycine max (L.) Meorr5. There are many processing methods for SSP in China, the different processing methods will affect the nutrition of SSP3. For example, the processing method in Fujian Province involves 7 rounds of fermentation, with seven days each time, with black beans as main raw materials, Mori Folium, Nelumbinis Folium, Lophatheri Herba, Eriobotryae Folium and Perillae Folium as auxiliary materials6. However, the scientific basis of SSP fermentation is only roughly understood and the patterns in the change of products are largely uncharted. The current fermentation process suffers from an extensively long production cycle and a low yield ratio of final products, which renders it unsuitable for large-scale industrial manufacturing.

The main active components in SSP include flavonoids, saponins, amino acids, proteins and sugars. Among them, isoflavones have phytoestrogen-like effects, including regulating lipid metabolism disorders and blood glucose, anti-atherosclerosis, protecting myocardial ischemia, anti-oxidation, anti-tumor, etc. Soybean oligosaccharides have been proved to possess many functions, such as improving human digestive system, reducing blood pressure and serum cholesterol7,8, removing toxins in the body9, enhancing immunity, and mitigating aging10. Amino acids produced in the fermentation of SSP are important medicinal substances that possess the effects of calming nerves, anti-anxiety, and promoting sleep11.

Our study provides the first comprehensive analysis of the changes of antipyretic and anti-inflammatory effects in the fermentation process of Fujian seven-times fermented SSP. To further elucidate the underlying biochemical basis for such phenomena, we assessed both the changing patterns of flavonoids, amino acids, and polysaccharides, and the microbial landscape during the fermentation process. Through our correlation analysis of ‘strain-composition-activity’, we explored how the diversity of microorganism populations was associated with the change in nutritional components and pharmacological activities, providing a reference for the optimization of processing techniques for SSP and other soybean fermented food.

Results

Antipyretic and anti-inflammatory effects of seven-time fermented SSP

The in vivo antipyretic and anti-inflammatory research showed that every sample was capable of mitigating the increase in body temperature of lipopolysaccharides (LPS) induced fever mice. Among them, the antipyretic effect of the second fermented SSP was superior to the rest. The expression levels of IL-1β in each sample, IL-6 in the first to fifth time fermented samples, and TNF-ɑ in the first to third time fermented samples all showed significant decreases. The results of antipyretic and anti-inflammatory effects are shown in (Fig.1; Supplementary Tables 1–3).

Fig. 1. The in vivo antipyretic and anti-inflammatory effects of SSP in different fermentation stages.

Fig. 1

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A Fresh black soybean sample; B SSP sample; C Changes of body temperature of mice (n = 10); D Changes of the expression level of TNF-ɑ; E Changes of the expression level of IL-6; F Changes of the expression level of IL-1β (*P < 0.05, **P < 0.01).

The content of six isoflavones in the fermentation process

The content deterination of isoflavones is carried out utilizing high performance liquid chromatography (HPLC) assays. Content analysis of six isoflavones showed that throughout the fermentation process, the contents of daidzin, glycitin, and genistin gradually decreased, while the contents of their corresponding aglycones, daidzein, glycitein, and genistein, gradually increased. The content of the three aglycones reached their peak after the second fermentation process (Fig. 2A–C; Supplementary Tables 4, 5).

Fig. 2. Change patterns of flavonoid, polysaccharide and amino acid content in fermentation processes of seven-fermented SSP sample.

Fig. 2

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A HPLC chromatogram of mixed reference substances (1-daidzin, 2-glycitin, 3-genistin, 4-daidzein, 5-glycitein, 6-genistein); B HPLC chromatogram of SSP sample; C Change patterns of the abundance of 6 isoflavones in seven-fermented SSP; D Change patterns of total flavonoid abundance in seven-fermented SSP; E Change patterns of total polysaccharide abundance in seven-fermented SSP; F MRM chromatograms of amino acid reference substances; G MRM chromatograms of seven-fermented SSP sample; H Change patterns of the content of 22 kinds of amino acid in seven-fermented SSP (histogram); I Change patterns of the content of 22 kinds of amino acid in seven-fermented SSP (line chart).

The total flavone content of SSP was determined by ultraviolet-visible (UV) spectrophotometry, the most common method for quantifying the content of flavonoids. Flavone content reached a peak after the second round of fermentation and decreased in later rounds (Fig. 2D; Supplementary Table 6). The change pattern of flavone content was consistent with the change of antipyretic and anti-inflammatory effects.

The content of total polysaccharide in the fermentation process

Polysaccharide content is commonly determined using anthrone-sulfuric acid or phenol-sulfuric acid methods. The contents of total polysaccharide measured by phenol-sulfuric acid method in this study showed an initial increase and a subsequent decrease during the whole fermentation process. During seven-time fermentation, the peak in the total content of polysaccharides was reached after the second-time fermentation (Fig. 2E; Supplementary Table 7).

The content of amino acids in the fermentation process

Herein, the content of amino acids throughout the SSP fermentation process was determined by Liquid Chromatograph Mass Spectrometry (LC-MS) analysis. The multiple reaction monitoring (MRM) chromatograms are shown in Fig. 2F, G, and the content of twenty-two amino acids in fermentation process was presented in (Fig. 2H, I; Supplementary Table 8, 9). The results showed the dynamic changes of amino acids during the whole fermentation process, with an overall increase in content followed by a gradual decrease afterwards. The content of Asp, Asn, Gln, Arg, Hyd, and Ser was relatively stable. The content of Glu reached its peak on the second day of the first round of fermentation while the content of Thr, Phe, Met, Trp, Cit and Lys reached their peaks on the seventh day of the first round of fermentation, and the content of His, GABA, Leu, Ile, Ala, Gly, Pro and Val reached their peaks on the second day of the second round of fermentation. The total amino acid content initially increased but then gradually decreased during the whole fermentation process and reached a peak during the first and second rounds of fermentation (Fig. 2H).

Diversity of fungal and bacterial species in the fermentation process of seven-fermented SSP

Internal Transcribed Spacer (ITS) analysis of 11 samples from different periods during the fermentation process of seven-fermented SSP generated a total of 66,922 effective ITS sequences. The average length of the sample sequence was 324 bp, and a total of 1,339 operational taxonomic units (OTUs) were obtained. The OTUs were clustered and annotated at a 97% similarity level. The samples were mainly distributed among 10 phyla, 15 classes, 23 orders, 39 families, 39 genera, and 49 species.

Using high-throughput Next Generation Sequencing (NGS) sequencing technology, the bacterial 16S V1-V3 regions in 11 different periods of the fermentation process of seven-fermented SSP were sequenced. After double-end splicing and effective filtration, a total of 56,868 valid sequences were obtained. The average length of the sample sequence was 460 bp, and 956 OTUs were obtained. The OTUs were clustered and annotated at 97% similarity level. The samples were mainly distributed in 8 phyla, 8 classes, 20 orders, 29 families, 72 genera, and 88 species.

Fungal and bacterial phylum level analysis in the fermentation process of seven-fermented SSP

The fungal communities in different fermentation stages of seven-fermented SSP were classified and annotated at various levels (Fig. 3A). Ten fungal phyla were detected in the samples based on prior SSP microbiome studies: Mucoromycota, Ascomycota, Basidiomycota, Mortierellomycota, Chytridiomycota, Rozellomycota, Glomeromycota, Olpidiomycota, and Blastocladiomycota. The dominant fungi in the first fermentation were Mucoromycota (56.86%) and Ascomycota (42.49%). The major fungi in the second and third fermentations were Mucoromycota (8.36%), Ascomycota (60.36%), and Basidiomycota (3.20%). Mucoromycota (5.83%), Ascomycota (37.67%), Basidiomycota (38.70%), Mortierellomycota (2.64%) and Chytridiomycota (2.11%) dominated the fourth fermentation stage, while Ascomycota (7.44%) and Basidiomycota (3.36%) dominated the fifth and Mucoromycota (95.56%) and Ascomycota (0.46%) dominated the seventh/last fermentation. Therefore, Mucoromycotina and Ascomycota were identified as the most dominant fungal phyla involved in the whole fermentation process according to the analysis of abundance value.

Fig. 3. Species stack diagram of the fungal and bacterial in phylum and genus level in seven-fermented SSP.

Fig. 3

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A Fungal species stack diagram in phylum level; B Stacked diagram of bacterial species at phylum level; C Stacked diagram of fungal species at genus level; D Stacked diagram of bacterial species stack diagram at genus level; E Stacked heat map of fungal species at genus level; F Stacked heat map of bacterial species at genus level.

The bacterial communities of different fermentation stages of seven-fermented SSP were also classified and annotated at various levels. A total of eight phyla were detected (Fig. 3B). Proteobacteria (62.65%) and Firmicutes (37.13%) were the dominant phyla in the first fermentation, and Proteobacteria (33.45%), Firmicutes (63.44%), and Actinobacteria (2.39%) dominated the second fermentation. Proteobacteria (32.38%), Firmicutes (65.55%), and Actinobacteria (1.96%) dominated the third, while Proteobacteria (84.11%), Firmicutes (6.24%), and Bacteroidetes (9.56%) dominated the fourth to seventh fermentations. Therefore, Proteobacteria and Firmicutes were considered to be the dominant bacteria strains in the whole fermentation process based on the abundance value.

Analysis of the fungal and bacterial genus level in seven-fermented SSP

The top known fungi genera in terms of abundance in the different fermentation stages of seven-fermented SSP included Rhizopus (28.21%), Aspergillus (32.53%), Lecanicillium (0.05%), Meira (0.07%), Leptospora (0.07%), Diutina (0.08%), Alternaria (0.07%), Suhomyces (0.09%), Rectipilus (0.09%), Choanephora (0.12%), Penicillium (0.15%), Wickerhamomyces (0.18%), Setophaeosphaeria (0.19%), Operculomyces (0.19%), Cystobasidium (0.24%), Lichtheimia (0.17%), Wallemia (0.05%), Mortierella (0.26%), Cladosporium (0.44%), Saccharomyces (0.45%) and Candida-charosporium (1.07%). Rhizopus and Aspergillus were the dominant genera in the fermentation of Fujian seven-fermented SSP, with Rhizopus having the highest overall abundance. Rhizopus arrhizus was thus identified as the main species for further analysis (Fig. 3C).

The most abundant known bacterial genera throughout different fermentation stages of seven-fermented SSP included Paenibacillus (0.32%), Pantoea (0.13%), Vagococcus (0.38%), Rhizobium (0.40%), Kosakonia (0.09%), Ignatzschineria (0.35%), Alcaligenes (0.40%), Pseudomonas (6.08%), Cronobacter (1.57%), Enterobacter (8.60%), Acinetobacter (18.03%), Bacillus (28.19%), Staphylococcus (0.01%), Comamonas (2.81%), Stenotrophomonas (2.63%) and Delftia (2.55%) (Fig. 3D). Bacillus and Acinetobacter were the core bacteria involved in the whole process of fermentation of Fujian seven-fermented SSP. We present a detailed list of genus-level fungi and bacteria species in Fujian seven-fermented SSP in a stacked heat map (Fig. 3E, F).

LEfSe analysis of fungi and bacteria populations in seven-fermented SSP

LEfSe analysis revealed that the fungal composition of seven-fermented SSP changed considerably at different stages of fermentation, and all LDA scores were >2. As shown in Fig. 4, 10 species demonstrated substantial differences in abundance between the first and the second fermentation processes of Fujian seven-fermented SSP, such as Saccharomycetales, Agaricaleseales, Hypocreales, Arocladium, and Dothideomycetes. Meanwhile, 36 species undergone significant changes in abundance between the first and the third fermentation, while there were 20 species between the first and the fourth fermentation, only 10 species between the first and the fifth fermentation, and only 4 species between the first and the sixth fermentation, 4 species between the first and the seventh fermentation.

Fig. 4. LDA histogram and taxonomic branch graphs demonstrating fluctuations in fungal composition between different stages of fermentation of seven-fermented SSP.

Fig. 4

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Fb LDA histogram and taxonomic branch graph demonstrating fluctuations in fungal composition between the first and the second fermentation; Fc LDA histogram and taxonomic branch graph demonstrating fluctuations in fungal composition between the first and the third fermentation; Fa–Fd LDA histogram and taxonomic branch graph demonstrating fluctuations in fungal composition between the first and the fourth fermentation; Fa–Fe LDA histogram and taxonomic branch graph demonstrating fluctuations in fungal composition between the first and the fifth fermentation; Fa–Ff LDA histogram and taxonomic branch graph demonstrating fluctuations in fungal composition between the first and the sixth fermentation; Fa–Fg LDA histogram and taxonomic branch graph demonstrating fluctuations in fungal composition between the first and the seventh fermentation.

LEfSe analysis of the bacterial composition of seven-fermented SSP also showed variations between different stages of fermentation, and the LDA scores were all greater (>2) as well. As shown in Fig. 5, the abundance of 42 species changed considerably different between the first and the second fermentation of Fujian seven-fermented SSP, among which Firmicutes phylum, Bacilli, Bordetella, Providencia, and Brevibacillus genera were the distinct microorganism populations in the second round of fermentation, while Gammaproteobacteria, Proteobacteria, Enterobacteriaceae, and Cronobacteria were the distinct in the first round of fermentation. 22 species undergone significant changes in abundance between the first and the third fermentation, 28 species between the first and the fourth fermentation, 42 species between the first and the fifth fermentation, 42 species between the first and the sixth fermentation, and up to 46 species between the first and the seventh fermentation.

Fig. 5. LDA histogram and taxonomic branch graph of bacterial differences in different stages of fermentation of seven-fermented SSP.

Fig. 5

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Fa-Fb LDA histogram and taxonomic branch graph of bacterial differences between the first and the second fermentation; Fa-Fc LDA histogram and taxonomic branch graph of bacterial differences between the first and the third fermentation; Fa-Fd LDA histogram and taxonomic branch graph of bacterial differences between the first and the fourth fermentation; Fa-Fe LDA histogram and taxonomic branch graph of bacterial differences between the first and the fifth fermentation; Fa-Ff LDA histogram and taxonomic branch graph of bacterial differences between the first and the sixth fermentation; Fa-Fg LDA histogram and taxonomic branch graph of bacterial differences between the first and the seventh fermentation.

Correlation analysis of strain-component-biological activity

We introduced the changes of body temperature of mice, the expression levels of TNF-ɑ, IL-6, and IL-1β, the contents of total flavonoids, polysaccharides, 6 isoflavones, and 22 amino acids into SPSS26.0 software for correlation analysis. The results showed that the content of genistin and glutamate was negatively correlated with the expression level of TNF-ɑ, the content of leucine was negatively correlated with the expression level of IL-1β.

Next, we introduced the contents of genistin, glutamate, leucine, and the abundance changes of Rhizopus arrhizus, Aspergillus, and Bacillus into SPSS26.0 software for correlation analysis. The results showed that the content changes of the above three components were positively correlated with the abundance of Bacillus.

We also analyzed the correlation between the content of total flavonoids, polysaccharides, 6 isoflavones, 22 amino acids, and the abundance of Rhizopus arrhizus, Aspergillus, and Bacillus. The results showed that Aspergillus was positively correlated with the content changes of total flavonoids, polysaccharides, daidzein, glycitein, genistein, citrulline, and lysine, and negatively correlated with the content changes of asparagine, glutamine, and arginase.

Discussion

The antipyretic and anti-inflammatory effects of SSP were analyzed by establishing fever mouse models, including LPS-induced fever, yeast-induced fever12, 2,4-dinitrophenol-induced fever13, etc. Through validation from preliminary experiments, the LPS-induced fever mouse model is capable of serving our experimental purpose, and was therefore adopted as a model for assessing the antipyretic effect of SSP. In preliminary experiments, we monitored the body temperature of mice for 24 h to reveal that their change in body temperature was most significantly reflected after 6 h of SSP application, hence such a timepoint was selected for indicating the antipyretic effects of SSP. The standards for identifying fever mice model was the body temperature of the mice increased more than 1 °C. In the application of fever mice model, it was relatively easier to observe the antipyretic effect of the research object by taking it in advance. We also carried out the investigation using high, medium, and low doses (3.2, 1.6, and 0.8 g/kg, respectively). The medium dose was selected for indication as it was the most robust in reflecting the differences of samples from different fermentation stages.

The analysis of antipyretic and anti-inflammatory effects showed all sample demonstrated certain extents of anti-inflammatory effects, and the effects of the first to third time fermented samples were considerably better. Therefore, we speculate that the antipyretic and anti-inflammatory effects of two-time fermented SSP could be the best.

Content analysis of six isoflavones showed that the contents of daidzin, glycitin, and genistin decreased, while the contents of their corresponding aglycones, daidzein, glycitein, and genistein increased. This phenomenon could be attributed to the action of β-glucosidase on the oxygen glycosidic bond in glycosidic isoflavones, followed by the removal of glucose residues by microbial metabolism14. Isoflavones have been proved to enhance the antioxidant capacity of animals, alleviate inflammation, and exert estrogenic effects, all of which are more conducive to human absorption after their conversion into aglycones15. Therefore, the content shifts of isoflavone-derived aglycone content in the seven-time fermentation processes is consistent with the changing patterns of antipyretic and anti-inflammatory effects.

Content analysis of total polysaccharide showed that the peak in the total content of polysaccharides was reached after the second-time fermentation. Polysaccharides are reported to have the pharmacological activities of enhancing immunity and anti-tumor16,17. Hence, we assume consistency between total polysaccharide content and the change of antipyretic and anti-inflammatory effects.

Amino acids played an important role in inflammatory bowel disease by maintaining intestinal homeostasis and bidirectionally regulating the release of pro-inflammatory and anti-inflammatory cytokines18. Therefore, the change pattern of amino acid content was consistent with the change of antipyretic and anti-inflammatory effects.

Analysis of the fungal and bacterial genus in seven-fermented SSP showed that the dominant fungal strains in the fermentation process were Rhizopus arrhizus, Aspergillus, and Bacillus. Aspergillus fungi such as Aspergillus niger has been reported to secrete cellulase, amylase, protease and lipase19, which hydrolyzed polysaccharides into oligosaccharides or monosaccharides, and degraded proteins into peptides and amino acids, promoting their absorption by the digestion system20. Meanwhile, α-L-rhamnosidase and β-glucosidase secreted by Aspergillus niger was capable of transforming flavonoid glycosides to aglycones. Hydroxylase and demethoxylase in Aspergillus niger were also involved in the transformation of flavonoids21.

A major fungal family, Rhizopus, was also rich in various enzymes, including lipases, amylases, and proteases, which were associated with the fermentation and transformation of sugars and amino acids22,23. Moreover, Bacillus such as Bacillus subtilis, secretes β-glucosidase along with proteases24. Therefore, the dominant strains such as Aspergillus, Rhizopus, and Bacillus in the seven fermentation processes were also involved in the transformation of amino acids, polysaccharides, and flavonoids. Consistently, the content variation of flavonoids, polysaccharides, and amino acids was positively correlated with the abundance of Bacillus, Rhizopus, and Aspergillus during the fermentation of seven-fermented SSP.

The dynamic changes of fungal abundance and their enzymatic profiles during the fermentation process of Fujian seven-fermented SSP lead us to the following speculation: Rhizopus arrhizus, with a particularly fast-growing rate, participated in initiating the fermentation process of Fujian seven-fermented SSP. Lipase and amylase produced by Rhizopus arrhizus could decompose the macromolecular substances in black beans to provide nutrients needed for the growth of other microorganisms. Subsequently, Aspergillus species producing β-gluconase gradually emerged in the fermentation process, further promoting the transformation of nutrients.

Correlation analysis of strain-component-biological activity showed that the content changes of genistin, glutamate, and leucine were related to the anti-inflammatory effect of SSP, which could reduce the expression levels of TNF-ɑ and IL-1β. Bacillus contributed to the transformation of genistin, glutamate, and leucine, Aspergillus contributed to the transformation of total flavonoids, polysaccharides, daidzein, glycitein, genistein, citrulline, and lysine, etc.

Therefore, we speculated that genistin, glutamate, and leucine were transformed under the action of Bacillus during the fermentation process of seven-time fermented SSP, which was related to the anti-inflammatory activity of SSP. Of course, the transformation of flavonoids, polysaccharides, and amino acid is not meaningless. In addition to antipyretic and anti-inflammatory effects, SSP also plays an important role in promoting human health by exerting anti-osteoporosis, anti-radiation activities, and anti-depression which need to be further studied.

Hou et al. fermented Douchi by Bacillus velezensis and Bacillus amyloliquefaciens, and the result showed that the content of thyroxineable acids was significantly increased, suggesting that Bacillus was closely related to the accumulation of amino acids25. The study of Jang et al. showed that Bacillus licheniformis and Bacillus velezensis were respectively shown to have high potential to increase concentrations of glutamic acid and GABA, while Bacillus subtilis has the ability to increase essential amino acid concentrations in fermented soybean foods26. Zhao et al. analyzed the fermentation microorganisms of Douchi by high-throughput sequencing, and the results showed that Aspergillus was dominant in the early stage fermentation, and Bacillus was dominant in the late stage of fermentation27. The above research results were basically consistent with the results of this study.

In this study, the change rules of active ingredients, antipyretic, and anti-inflammatory effects in the fermentation of SSP were analyzed. The results showed that the peak of active ingredients and biological activity of SSP appeared in the second fermentation process. Therefore, we speculate that the two-time fermentation process is better. The processing methods for SSP in Chinese Pharmacopoeia Commission (2020) is relatively similar to the two-time fermentation process. As a soybean fermented food, the traditional seven-time fermentation process is time-consuming and costly, and could potentially lead to large losses of active ingredients and activities. Therefore, we hypothesize that by optimizing and shortening the fermentation cycle, the manufactory expenses of SSP could be reduced, while its nutritional quality could be enhanced.

To our best knowledge, our study provides the first comprehensive analysis of the correlations between microbial strains, active components, and biological activities in seven-time fermented SSP. Rhizopus arrhizus, Aspergillus, and Bacillus were identified as the dominant fungal strains in the fermentation process. Aspergillus involved in the transformation of flavonoids, amino acids, and polysaccharides. Bacillus involved in the transformation of genistin, glutamate, and leucine, which contributed to the anti-inflammatory effect. Fermentation has the significant impact on flavonoid, polysaccharides, and amino acid content.

The peak period of transformation of flavonoids, amino acids, and polysaccharides occurred during the second fermentation stage, while the antipyretic and anti-inflammatory effects were also superior to earlier and later stages after the second fermentation step. Such findings suggest that the two-time fermentation process is better; excessive fermentation may negatively impact the accumulation of bioactive components and functional activities of SSP. Our study provides a reference for further investigation on the optimization of manufactory processes of soybean fermented food. We may improve production efficiency by reducing the number of fermentation, and enhance SSP nutritional quality by targeted microbial inoculation.

Methods

Instruments, chemicals, and materials

Mastercycler gradient PCR instrument (Eppendorf), Miseq gene sequencer (Illumina), QTRAP 4500 triple quadrupole linear ion hydrazine mass spectrometer (ABSCIEX, USA), SIL-30AC liquid chromatograph (Tsushima, Japan), SQP analytical balance (Beijing Sartorius Scientific Instrument Company), SP-1920 UV-visible spectrophotometer (Shanghai Spectrometer Instrument Company), TC-M600D low-speed desktop air-cooled centrifuge (Ningbo Topson Scientific Instrument Company), AXD-202 electronic thermometer (Guangzhou Aixinda Electronics Company).

Daidzin (J11J12T137054), glycitin (N24GB169100), genistin (J16GB155067), daidzein (C11D11Y134057), glycitein (G26N11L132454), genistein (M22GB142479), threonine (S01F4G1), aspartic acid (S24A8I34463), asparagine (SM0503GA13), histidine (Z18A11H121745), glutamic acid (S12A10I85582). glutamine (011M01991V), phenylalanine (H20N8H48638), arginine (MKBD3032V), γ-aminobutyric acid (Z07J10H79273), leucine (BCBN3570V), hydroxyproline (Z03J10H92127), methionine (Z01A10H84569), isoleucine (SM0503D13G), alanine (S20A6G17672), tryptophan (S02D7I26049), tyrosine (BCBK5272V), glycine (S29A10I964), Citrulline (S12M11I112899). The above standards were purchased from Shanghai Yuanye Biotechnology Company, and the purity was ≥ 98%. D-anhydrous glucose (C11653106, Shanghai McLean Biochemical Technology Company). LPS (0000153963, Sigma), acetaminophen (S3044, Shanghai Yuanye Biotechnology Company), sodium chloride injection (220703A43, Fuzhou Haiwang Fuyao Pharmaceutical Company). TNF-ɑ ELISA kit (24118991017), m.IL-6 ELISA Kit (132189610170, m.IL-1β ELISA kit (11618871017), the above kits were purchased from Wuhan Boster Bioengineering Company. DL2000 Marker (Beijing Kangwei Century Biotechnology Company), agarose (SIGMA), Trans2K DNA Marker, 6×DNA Loading Buffer (Beijing All Gold Biotechnology Company), EB, Ethidium bromide stock solution, 50×TAE concentrate Solution (Shanghai Shenggong Biological Engineering Technology Service Company), Uracil-DNA Glycosylase, dUTP, 100 mM Solution, dATP, 100 mM Solution, dCTP, 100 mM Solution, dGTP, 100 mM Solution and dTTP, 100 mM Solution (Fermentas), GoldStar Taq DNA Polymerase (Beijing Kangwei Century Biotechnology Company), Qubit ® dsDNA HS Assay Kit, for use with the Qubit ® 2.0 Fluorometer (Invitrogen), Phanta ® UC Super-Fidelity DNA Polymerase for Library Amplification (Vazyme), Genome Size Selector (Gnomegen), DNA-ExitusPlus (AppliChem).

Black beans were purchased from a market, Mori Folium (Bozhou Cijitang Chinese Herbal Pieces Company, 1905012), Nelumbinis Folium (Bozhou Chinese Herbal Pieces Factory, 1804015016), Lophatheri Herba (Beijing Bencao Fangyuan Pharmaceutical Company, 20181122), Perillae Folium (Bozhou Huqiao Pharmaceutical Company, 1902150243), Eriobotryae Folium (Anhui Shunhetang Chinese Herbal Pieces Company, 190301). The above materials were identified by Associate Professor Che Surong of Fujian University of Traditional Chinese Medicine.

Sample preparation

SSP was fermented according to the Fuzhou Standard for Processing6. The black beans were steamed for 2 h. The decoction of mulberry leaves, perilla leaves, bamboo leaves, loquat leaves, and lotus leaves was mixed into black beans and fermented for 7 days. According to this method, steamed and fermented seven times to obtain SSP. A total of 12 samples were collected, the black bean sample was numbered Fa0, the samples of the second, fourth, sixth day in the first fermentation were numbered Fa1, Fa2, and Fa3, respectively. The samples of the second, fourth, sixth day in the second fermentation were numbered Fb1, Fb2, and Fb3, respectively. The samples of the sixth day from the third fermentation to the seventh fermentation were numbered Fc, Fd, Fe, Ff, Fg, respectively.

Analysis of antipyretic and anti-inflammatory effects

ICR mice (half male and half female) were fed adaptively for 3 days and fasted for 12 h before the experiment. The body temperature was measured three times continuously, and mice with basal body temperature >38 °C and body temperature fluctuation >0.5 °C were eliminated.

According to the clinical equivalent dose of human (200 mg/Kg) and mouse (1.8 mg/g), the appropriate amount of SSP was added into ultra-pure water, and after soaking for 30 min, the sample was decocted for 1 h, then filtered and concentrated to obtain the required liquid.

Ten qualified mice were intraperitoneally injected with 0.9% sodium chloride injection (10 mL/kg) as the blank group. The rest mice were intraperitoneally injected with LPS (1 μg/10 g) solution prepared from 0.9% sodium chloride injection to establish fever model28. The mice were divided into 13 groups such as model group, acetaminophen group, and samples Fa1, Fa2, Fa3, Fb1, Fb2, Fb3, Fc, Fd, Fe, Ff, Fg with 10 mice in each group. After modeling, they were fed immediately. The body temperature was measured every 1 h, the body temperature change at 6 h after modeling was used as the main observation index. After the observation of body temperature, the blood was taken, centrifuged at 3500 r/min for 15 min, the supernatant was taken, sub-packed, and stored at −80 °C. The cytokines in the serum samples of mice were determined by ELISA after thawing. The results were statistically analyzed using IBM SPSS 26.0. The data that did not conform to the normal distribution were tested by non-parametric test. The data that conformed to the normal distribution and had uniform variance were analyzed by single factor variance LSD method. The data that conformed to the normal distribution but had uneven variance were analyzed by single factor variance Games-Howell method. P < 0.05 was considered statistically significant. This study was approved by the Experimental Animal Ethics Committee of Fujian University of Traditional Chinese Medicine (FJTCM PRE IACUC 2024160), which was in line with the ethical norms of experimental animal welfare.

Content analysis of six isoflavones

Chromatographic column was UltimateXB-C18(4.6 mm × 250 mm, 5 μm), mobile phase was methanol-0.1% formic acid water. The detection wavelength was 254 nm29,30.

Daidzin, glycitin, genistin, daidzein, glycitein, and genistein were accurately weighed and dissolved in methanol to obtain a mixed reference solution with daidzin 34 μg/mL, glycitin 43 μg/mL, genistin 68 μg/mL, daidzein 76 μg/mL, glycitein 38 μg/mL, and genistein 56 μg/mL. The mixed reference solution was diluted to a mixed reference solution with different gradient concentrations. The concentration of references was taken as abscissa, and peak area were taken as ordinate to obtain the standard curve.

Samples were accurately weighed as 2 g, added into 25 mL methanol, ultrasonically extracted for 30 min, and filtered to obtain the test solution. According to the above method, the content of 6 isoflavones was determined and calculated.

Content analysis of total flavone

1.11 mg genistin was accurately weighed and dissolved in 25 mL 70% methanol to a concentration of 0.044 mg/mL. 0.2, 0.6, 0.8, 1, 1.5, 1.8, and 2 mL reference solution were taken and diluted to 10 mL. The absorbance was measured at 260 nm. The regression equation and linear correlation coefficient were obtained with the absorbance value as the ordinate and the concentration of genistin as the abscissa31,32.

1 g sample was accurately weighed, heated and refluxed twice with 25 mL of 70% methanol, 0.5 h each time, 0.5 mL of the filtrate was diluted to 25 mL. Total flavone content was calculated with the method above.

Content analysis of polysaccharide

11.5 mg anhydrous glucose was precisely weighed, dissolved in 100 mL water to obtain a concentration of 0.115 mg/mL control solution. The glucose reference solutions of 0.1, 0.2, 0.4, 0.7, 0.8, 0.9, 1.0 mL were accurately absorbed, and 1 mL distilled water was added to the total volume, 1 mL of 5% phenol solution was added, shaken well, 5 mL of concentrated sulfuric acid was added quickly, boiling water bath for 15 min, ice water bath for 15 min, absorbance was measured at 485 nm. The standard curve was drawn with the mass concentration of D-anhydrous glucose as abscissa and the absorbance value as ordinate. The regression equation and the linear correlation coefficient were obtained.

4 g sample was accurately weighed, extracted by 50 mL water reflux for 2times, 0.5 h each time. 1/5 Sevag was added into the extract, shaken for 15 min, centrifuged at 4000r for 15 min, and the supernatant was taken. The protein-removed extract was concentrated to 25 mL, and anhydrous ethanol was added to make the alcohol content reach 80%. Polysaccharide was obtained through centrifuged, collected, and precipitated after 24 h. Dried polysaccharide was dissolved in water and diluted to 100 mL, the test solution was obtained. 1 mL sample solution was precisely measured, and polysaccharide content was calculated with the method above33,34.

Content analysis of amino acid

Agilent Poroshall 120 Hilic-z column (2.1 mm × 150 mm, 2.7 μm) was used. The mobile phase was ammonium formate-acetonitrile solution. The condition was multiple reaction monitoring (MRM) in electrospray positive ion (ESI+) mode, curtain gas 30 μL/min, temperature 550 °C, spray voltage 5500V35–37.

Amino acid reference materials were prepared as described. Amino acids (1 mg; 0.2 mg for tyrosine) were placed in a 1 mL volumetric flask and dissolved in 0.1 mol/L hydrochloric acid. The solution was shaken to prepare a single standard reference stock solution with a mass concentration of approximately 1 mg/mL (0.2 mg/mL for tyrosine). The linear range, limit of detection (LOD), limit of quantitation (LOQ), recovery, and precision (relative standard deviation, RSD) of the method were evaluated. The peak area of the standard sample or the peak area ratio to the analyte concentration internal standard was drawn to establish the standard curve. Recovery was determined when the signal-to-noise ratio (S/N) ≥3 and ≥10 for the LOD and LOQ, respectively.

A total of 0.1 g of each batch of Fa0 to Fg stages of Fujian seven-fermented SSP was placed in a centrifuge tube, and 20 mL of water was added and incubated at room temperature for 60 min, followed by ultrasonication for 60 min and centrifugation at 12,000 rpm for 10 min. The supernatant was aspirated to obtain the test solution stored at 4 °C. The sample was 0.22 μm filtered before injection into the liquid chromatograph. The content of 22 amino acids in each sample was then calculated according to the above method.

Analysis of strain changes in fermentation process

Samples were thawed on ice from storage at −80 °C and then mixed for several times. Sample (2 mL) was then centrifuged at 12,000 rpm for 10 min, and the supernatant was discarded. CTAB (cetyl trimethyl ammonium bromide) solution was preheated to 65 °C, and 650 μL was added to the sample and mixed evenly. CTAB and sample were incubated in 65 °C for 0.5 h and evenly mixed once every 15 min. After cooling 650 μL chloroform/isoamyl alcohol (24:1) was added, mixed well, and centrifuged at 12,000 rpm for 15 min. The supernatant was transferred to a new Eppendorf tube, and 650 mL chloroform/isoamyl alcohol (24:1) was added and centrifuged at 12,000 rpm for 15 min. The supernatant was transferred into a new centrifuge tube, and a 1/3 volume of NaAc (3 mol/L) and 0.5 mL of isopropyl alcohol were added, mixed well, and placed at −80 °C for 0.5 h. The solution was centrifuged at 12,000 rpm for 10 min, and the upper layer was discarded. Ethanol (75%) was added into the centrifuge tube to wash it twice, and the tube was then placed upside down on absorbent paper to dry. Q water was added to dissolve the pellet, and the obtained DNA was stored at −20 °C38.

The fungal PCR reaction system (25 μL) comprised 5 μL of 5 × PCR buffer, 2 μL of five dNTP mix (2.5 mM each), 4 μL of forward primer ITS3 (5ʹ-GCATCGATGAAG AACGCAGC-3ʹ) and reverse primer ITS4 (5ʹ-TCCTCCGCT TATTGATATGC-3ʹ), 0.25 mL CW0938S model GoldStar Taq DNA Polymerase, 20 ng DNA, 0.2 mL UNG, and ddH2O to 25 mL. The reaction procedure was 50 °C, 2 min; 95 °C, 10 min; 95 °C, 15 s; 55 °C, 30 s; 72 °C, 35 cycles in 40 s; 72 °C, 5 min.

The bacterial PCR reaction system (50 mL) comprised 2 μL Phanta UC, 1 μL of 10 mM dNTP 1 μL, 10 μL 5× Buffer, 10 mM Illumina F primer, 0.5 μL Trueseq primer Index 27 F (5ʹ-AGAGTTTGATCCTGGCTCAG-3ʹ) and 518 R (5ʹ-ATTACCGCGGC TGCTGG-3ʹ), 100 ng template, and H2O to 25 mL. The reaction procedure was 95 °C, 2 min; 95 °C, 30 s; 60 °C, 30 s; 72 °C, 10 cycles in 3 min; 72 °C, 5 min.

Each typical sequence was aligned with the Green genes 2013-08 release database to find out the most similar species information with a reliability of more than 90%, so as to obtain the taxonomic information of each OUT (Operational Taxonomic Units). According to the species annotation, the number of sequences of each sample at 6 taxonomic levels (phylum, class, order, family, genus, species) was counted using QIIMEv1.8.0 software and rdp_classifier v2.2 as the algorithm. The data was further analyzed by MEGAN6 software for phylogenetic tree. Then, according to the calculation results, the VennDiagram package of R language was used to process the data and draw the sample intersection Venn diagram. Finally, the LEfSe module in Galaxy’s web platform (http://huttenhower.sph.harvard.edu/galaxy/) was used to analyze species differences between multiple groups and find species biomarkers with significant differences in abundance.

Supplementary information

Supplementary information (238.7KB, pdf)

Acknowledgements

This work was financially supported by institutional funding through China Fujian Provincial Department of Science and Technology guidance project (2021Y0036), “Select the best candidates to lead key research projects” of Fujian University of Traditional Chinese Medicine (XJB2022008, XJB2023001), Foundation of Fujian University of Traditional Chinese Medicine (X2023001-Talent). And we acknowledged the support from National-Local Joint Engineering Research Center for Molecular Biotechnology of Fujian & Taiwan TCM, at Fujian University of Traditional Chinese Medicine.

Author contributions

Liqiang Sui: methodology, formal analysis, writing-original draft, visualization, funding acquisition; Dongying Cao: methodology, formal analysis, writing-original draft; Yali Wang: writing-review and editing; Zhong Wu: formal analysis; Sugui Wang: formal analysis; Wei Xu: conceptualization, funding acquisition, supervision; Lixia Chen: conceptualization, writing-review and editing; Hua Li: conceptualization, writing-review and editing, supervision. All authors read and approved the final manuscript.

Data availability

Data is provided within the manuscript or supplementary information files. Other raw data can be obtained on request.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Liqiang Sui, Dongying Cao.

Contributor Information

Wei Xu, Email: 2000017@fjtcm.edu.cn.

Lixia Chen, Email: syzyclx@163.com.

Hua Li, Email: lihua@fjtcm.edu.cn.

Supplementary information

The online version contains supplementary material available at 10.1038/s41538-025-00491-y.

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Supplementary Materials

Supplementary information (238.7KB, pdf)

Data Availability Statement

Data is provided within the manuscript or supplementary information files. Other raw data can be obtained on request.

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