The animal experimental procedures were approved by the Animal Care and Use Committee of Shanxi Agricultural University (SXAU-EAW-2021MS.P.052801).

The equations should be inserted in editable format from the equation editor. Forage enzyme preparations (temperature range and enzyme activity detailed in Table 1) were purchased from SUNSON Biotechnology Co., Ltd. (Cangzhou, China). Standard gluconic acid was purchased from Solarbio (Beijing, China). Total amino acid assay kits (A026-1-1) were purchased by Jiancheng Bioengineering Technology (Nanjing, China). ELISA kits for detecting glycinin, α-conglycinin, β-conglycinin, and soybean trypsin inhibitor (STI) content were purchased from Jiangsu Meimian Industrial Co., Ltd. (Jiangsu, China). All other chemicals and solvents used were of analytical grade.

The basal diet was formulated according to the nutritional requirements for swine as recommended by the National Research Council (21). The ingredients and nutritional values are shown in Table 2. The substrates for the EHD group consisted of the solid basal diet (S-CON). These substrates were mixed with water in a ratio of 1:2.5 and treated with compound enzyme preparations. The liquid control group (L-CON) was prepared by adding the same amount of water without these enzymes. The substrates were then pre-digested at temperatures of 40, 50, and 60°C for 1 h, respectively. Each trial was performed in triplicate.

Liquid samples were collected to evaluate the bacteriostatic effect, and the remaining sample material was dried at 65°C for 48 h, cooled, ground, and prepared for conventional nutrient analysis. The dried samples were analyzed for organic matter (OM), crude protein (CP), ether extract (EE), calcium, and phosphorus according to AOAC methods (22). Dietary nitrogen content was measured before and after the pre-digestion treatment using a Kjeldahl automated apparatus (K9805, Shanghai Analytical Instrument Co., Ltd., Shanghai, China). The nitrogen content was then multiplied by a factor of 6.25 to estimate CP quantity. EE was measured by Soxhlet extraction (23). Neutral detergent fiber (NDF) and acid detergent fiber (ADF) were measured using a fiber analyzer (ANKOM A200i Fiber Analyzer, United States) following the method of McRoberts and Cherney (24). Calcium and phosphorus contents were measured using the method described by Hanson (25). Reducing sugar was quantified by the dinitro salicylic acid (DNS) method (26).

Enzymatic hydrolysis products in the supernatants were analyzed using a high-performance liquid chromatography system (HPLC) equipped with a reverse-phase column [Luna 3.5 μm C18(2) 100 Å, LC Column 250 mm × 4.6 mm, Phenomenex, Torrance, CA]. The mobile phase, consisting of methanol (65%) and water (35%), was pumped at a flow rate of 1.0 mL/min, and gluconic acid was detected at wavelengths of 325, 340, and 385 nm. Gluconic acid was used as an external standard. Physical property changes in diets before and after enzymatic pre-digestion were examined using scanning electron microscopy (KYKY-EM3200, China) and laser confocal microscopy. The relative fluorescence intensity on the surface of the substances was measured by rhodamine B staining (Solarbio, Beijing, China).

The bacteriostasis of the predigested feed was tested by bacterial culture. Set up test groups: negative control (CON): single colony + sterile water, experimental group (EHD): single colony + enzymatic solution. Take out the preserved bacteria of Escherichia coli and Salmonella from the refrigerator at −80°C, coat the activated bacteria in LB solid medium, put them in 37°C constant temperature incubators for 24 h, pick single colonies and inoculate them in LB liquid medium, incubate them at 180 r/min with shaking, and take samples for measuring their OD value (600 nm) every 15 min to draw the growth curve.

Thirty-six Duroc × Landrace × Yorkshire pigs (body weight (BW) = 25 ± 0.5 kg; age = 75 ± 3 days) were randomly assigned to three dietary treatment groups. Each group had three replicates with four pigs (two males and two females). The groups were as follows: the solid control (S-CON) group, which received the basal diet; the L-CON group, which received the S-CON mixed with water at a ratio of 1:2.5; and the EHD group, which received a basal diet mixed with water in the same ratio and supplemented with 4% forage enzyme preparations. Pigs were fed ad libitum twice daily at 8:00 and 17:00 during both the 7-day pretrial period and the 30-day trial period. Deworming, castration, and immunization were performed according to standard farm protocols prior to the commencement of the experiment.

The metabolism test used metabolic cages and the total feces collection method to observe the effects on the apparent metabolic rate of nutrients and digestive enzyme activity in pigs. The cage dimensions were: length 1,200 mm, width 600 mm, height 800 mm. On day 20, three healthy pigs with similar weights were selected from each group. The entire phase included a 5-day pretrial period followed by a 5-day fecal collection period (27). Daily intake was set at 4% of body weight, fed twice daily at 8:00 and 17:00, with water provided ad libitum. Fresh feces were accurately collected without contamination over the 5-day period. Fecal samples were treated with 10% sulfuric acid (H₂SO₄), stored at −20°C, then dried, cooled, ground, and prepared for later chemical analyses.

The contents of OM, CP, EE, NDF, and ADF in feces were determined using the same methods applied to the diet analysis as described above. Nutrient digestibility was assessed using the total feces collection method as previously described (25). Intestinal digesta and mucosa was homogenized in cold saline and the supernatant was extracted after centrifugation at 2,500 r/min for 10 min, to prepare for the digestive enzyme activity assay. The activity of four enzymes was determined by colorimetry using commercial kits (Jiancheng, Nanjing, China)-α-amylase (starch-iodine colorimetry), lipase (colorimetry), cellulase (colorimetry), and trypsin (UV colorimetry).

Feed intake and refusal were recorded daily. Pigs were weighed after fasting for 12 h at the beginning and end of the experiment. At the conclusion of the trial, three pigs from each treatment group, close to the group’s average weight, were selected. Blood samples were collected from these pigs via the jugular vein into heparinized collection tubes. About 10 mL of blood was collected from the BD Serum Collection Tube and dispensed into red biochemical tubes. Immediately after blood collection, the blood was placed in an ice box at a low temperature for 15–20 min, and then centrifuged at 3,000–4,000 rpm for 5 min at 4°C, and then the supernatant was dispensed into sterile centrifugal tubes and then frozen in a refrigerator at −20°C for spare use. Subsequently, the pigs were euthanized and slaughtered using standard humane procedures.

Meat quality indicators, including pH, meat color, Warner-Bratzler shear force (WBSF), and drip loss, were measured. The pH of the longissimus dorsi (LD) muscle, located between the last and penultimate thoracic vertebrae, was measured at 45 min and 24 h post-slaughter using a pH meter (pH-STAR, SFK-Technology, Denmark). Meat color was measured directly on the LD muscle at the thoracolumbar vertebral junction using a spectrophotometric colorimeter (Konica Minolta Inc., Tokyo, Japan) within 1 to 2 h post-slaughter. Drip loss was determined using the dropper method on LD muscle samples taken from the third and fourth thoracic vertebrae within 1 to 2 h post-slaughter. Trimmed muscle cubes (3 cm³) were weighed, held at a constant temperature of 4°C for 48 h, then reweighed. To measure WBSF, LD muscles from the 13th to 16th lumbar vertebrae were refrigerated at 4°C for 72 h to mature, then heated in a thermostatic water bath until reaching an internal temperature of 70°C. After cooling to room temperature, cylindrical meat samples (3 cm in length) were prepared by shearing parallel to the muscle fibers.

Intestinal samples were collected immediately post-slaughter and kept on ice boards. The intestinal contents were manually flushed out with saline, and approximately 2 cm sections of duodenum, jejunum, and ileum were fixed in 4% paraformaldehyde. Cross-sectional slices of each specimen were prepared, subjected to hematoxylin and eosin (H&E) staining, and subsequently encased in a neutral resin for preservation. The intestinal morphology was observed using the Leica DMi8 Microsystem and Leica Application Suite 3.7.0 (Leica, Wetzlar, Germany). Three slices were selected from each cross-section of the intestinal canal, and five intact and well-oriented villus-crypt units were randomly chosen from each slice. Villus height (VH) and crypt depth (CD) were measured using ImageJ software (Image-Pro Plus 6.0, Media Cybernetics, United States), then the villus height/crypt depth (V/C) was calculated.

Total protein (TP) extracts from scraped colon mucosa were obtained using a Total Protein Extraction Kit (KeyGen BioTECH, Nanjing, China). Equal amounts of protein were separated by sulfate-polyacrylamide gel electrophoresis and transferred to polyvinylidene fluoride membranes. The membranes were then blocked with 5% skim milk (Sangon Biotech Co., Ltd., Shanghai, China) and then incubated with primary antibodies overnight at 4°C. Subsequently, they were incubated with the corresponding secondary antibodies at room temperature for 1 h. Antibodies used included those against Occludin, Zonula Occludens-1 (ZO-1), and β-actin. Western blot analysis was performed using an Odyssey infrared imaging system (LI-COR Biosciences, Lincoln, NE, United States).

Total RNA was extracted from pig colon tissue using Trizol reagent (Sigma, Saint Louis, MO), and cDNA was synthesized with a reverse transcription kit (TransGen, Beijing, China). qRT-PCR was used to measure the relative mRNA expression of tight junction (TJ) proteins (Occludin and ZO-1) and inflammatory cytokines (Interleukin 4, Interleukin 6; Interleukin 10, and tumor necrosis factor) in the colon. qRT-PCR was conducted using a CFX RT-PCR detection system (BioRad, Hercules, CA, United States) and a SYBR Green RT-PCR kit (TAKARA Co., Ltd) with the following cycle parameters: 95°C for 10 min, followed by 45 two-step cycles of 95°C for 7 s and 60°C for 34 s, and a cooling step at 40°C for 60 s. Primer sequences are listed in Table 3. Relative mRNA content was standardized to β-actin, and gene expression changes were calculated using the 2^−ΔΔCt method.

Colonic contents were cooled in liquid nitrogen for 24 h then stored at −80°C. The detection of SCFA followed the method of Liu et al. (28). Briefly, colon content samples were centrifuged in ultrapure water to obtain the supernatant, which was then mixed with crotonic acid metaphosphate and stored at −20°C. Before measurement, the solution was thawed, filtered through a 0.22 μm aqueous membrane, centrifuged, and the supernatant was injected into a gas chromatograph (TRACE 1300 Gas Chromatograph Mass Spectrometer, Thermo Scientific, United States). The chromatographic conditions were as follows: injection volume 2.0 μL, injection temperature of 220°C, split ratio 6, constant flow rate of 0.8 mL/min, initial column temperature of 70°C, and detector temperature of 220°C. Gas flow rates were set to hydrogen 35 mL/min, air 350 mL/min, and tail blow 40 mL/min.

On 30th day, fecal samples were collected from the anal orifice morning after feeding. These samples were cooled in liquid nitrogen for 24 h and then stored at −80°C. They were sent to the Majorbio sequencing platform (Shanghai, China) for 16S rRNA sequencing and data analysis. The fecal samples were used for total microbial DNA extraction using the TIAN amp Bacteria DNA kit (Tiangen Biotech Inc., Beijing, China). The final DNA concentration and purification were determined using the NanoDrop 2000 UV–Vis spectrophotometer and DNA quality was checked by 1% agarose gel electrophoresis (Thermo Fisher Scientific, Waltham, Massachusetts, United States). Primers 341F (5’-CCTAYGGGRBGCASCAG-3′) and 806R (5’-GGACTACNNGGGTATCTAAT-3′) were used to amplify the V3-V4 variable regions of the 16S rRNA gene through PCR the thermocycler PCR system (Thermo Fisher Scientific, Waltham, Massachusetts, United States). The amplified products were purified with AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, California, United States) and quantified with QuantiFluor™-ST (Promega, United States) according to the manufacturer’s protocol. Purified amplicons were pooled in equimolar and paired-end sequenced (2 × 300 bp) on an Illumina MiSeq platform (Illumina, San Diego, United States). All the raw data were filtered, denoised, merged, and non-chimeric by Qiime2 DADA2 plug-in to form ASVs. Classification of ASVs on species based on sklearn algorithm. The alpha and beta diversity of fecal microorganisms were analyzed using four indices: Chao, Shannon, Simpson, and Faith. Characteristic genera unique and common to each sample subgroup were identified and calculated to find significant biological markers, which were then illustrated in linear discriminant analysis effect size (LEfSe) maps. The comparative analysis of correlations between fecal microflora abundance and SCFAs was completed using the Wekemo Bioincloud, a dynamic real-time interactive online platform for data analysis.¹

Data from this experiment were processed using SPSS Version 26.0 (IBM Corporation, Chicago, IL, United States). One-way ANOVA and Independent samples t-test were used to determine the significance of the data. The pan was considered as the experimental unit. In microbiological analysis, the alpha diversity index of intestinal microbes was analyzed using Tukey HSD. The VIP value of multivariate statistical analysis OPLS-DA and the p-value of univariate statistical analysis t-test were used to screen differential metabolites. Results are expressed as mean ± SEM, differences were considered significant at p < 0.05 (∗p < 0.05; ∗∗p < 0.01), and 0.05 < p < 0.10 was considered a tendency.

The complex enzyme pre-digestion treatment increased the reducing sugar content of the diets (Figure 1A) (P < 0.01). Given that there was no significant difference in reducing sugar content at the three temperatures tested, 40°C was selected as the enzymatic hydrolysis temperature for this experiment. Figure 1C illustrates the differences in surface structure between the basal (L-CON and S-CON) and EHD diets. The EHD surface showed more fragmented structures and larger pores compared to the smooth and flat basal diet. Additionally, the relative intensity of fluorescence on the EHD surface was reduced (Figures 1D,E) (P < 0.01).

The nutritional value of the experimental EHD is summarized in Table 4. OM and CP levels increased in the EHD group following enzymatic degradation (p < 0.01), while the EE, NDF, ADF, and ANFs (including Glycinin, α-conglycinin, β-conglycinin, and STI) levels decreased (p < 0.01). The total amino acids (TAA) concentration also rose under these conditions (p < 0.01). The gluconic acid content in the EHD group was 1.59 ± 0.03 μg/g; no gluconic acid was detected in the control groups. Furthermore, the EHD showed a lower pH value (Table 4) (p < 0.01) and inhibited the growth of pathogenic bacteria in the feed (Figure 1B).

Table 5 shows that the EHD group exhibited an increase in average daily gain (ADG) (p < 0.01) and a decrease in the feed-to-gain ratio (F/G) (p < 0.01). However, there were no differences in initial and final BW and average daily feed intake (ADFI) among the three groups.

Table 6 indicates that feeding pigs with EHD did not affect serum glucose levels. However, the concentrations of blood urea nitrogen (BUN) (p < 0.01) and total cholesterol (TCHO, p < 0.05) were lower in the EHD group. Additionally, while low-density lipoprotein cholesterol (LDL-C) levels remained unchanged, the EHD group showed increases in serum TP (p < 0.01), ALB (p < 0.05), GLB (p < 0.05), triglycerides (p < 0.05), and high-density lipoprotein cholesterol (HDL-C) (p < 0.05).

Table 7 reveals no significant differences in pH at 45 m, pH at 24 h, and meat color L* value between different groups. However, pigs fed with EHD showed an increase in meat color a* value (p < 0.05) and a decrease in meat color b* value (p < 0.01). Moreover, EHD reduced both meat drip loss and shear force (p < 0.01).

Table 8 shows that the EHD group improved the digestibility of OM by 2%, CP by 3.54%, EE by 4.55%, NDF by 4.76%, and ADF by 5.33% compared to the S-CON group (p < 0.01). Compared to the L-CON group, the EHD group also improved the digestibility of OM by 2.75%, CP by 2.63%, EE by 3.51%, NDF by 4.95%, and ADF by 4.34% (p < 0.01). Furthermore, while the EHD did not have a statistically effect on the content of proteases and lipase, it did increase the levels of amylases (p < 0.01) and cellulase (p < 0.05) compared to both the S-CON and L-CON groups.

EHD improved intestinal development, as shown in Figure 2A. The villi were more uniformly arranged across all segments of the small intestine in the EHD group, with noticeable improvements in villi height, crypt depth, and villi-to-crypt ratios. These results are quantified using Image-J measurements and presented in Table 9. Villi height in the duodenum (p < 0.01), jejunum (p < 0.01), and ileum (p < 0.05) were greater in the EHD group compared to both S-CON and L-CON groups. The villi-to-crypt ratio was also higher in all small intestine segments in the EHD group than in the S-CON group (p < 0.01), with the ileum showing an increase compared to the L-CON group (p < 0.01).

The abundance of TJ proteins Occludin and ZO-1 was elevated in the EHD group (Figures 2B,C) (P < 0.05). Additionally, pigs fed with EHD exhibited lower mRNA levels of the pro-inflammatory cytokines TNF-α and IL-6 (Figure 2C) (P < 0.05). Conversely, the mRNA level of the anti-inflammatory cytokine IL-10 was higher in the EHD group (p < 0.05).

The concentrations of acetate, propionate, and butyrate in the colon were higher in the EHD group than in both control groups (Table 10) (p < 0.01). Similarly, the isovalerate level was higher in the EHD group compared to the S-CON (p < 0.01) and L-CON (p < 0.05) groups. However, the valerate and isobutyrate contents remained unchanged. Between the two control groups, the L-CON group showed elevated levels of acetate (p < 0.01), propionate (p < 0.05), and butyrate (p < 0.05).

Four indices (Chao 1, Faith, Shannon, and Simpson 4) were used to assess the α-diversity of fecal microorganisms (Figure 3A). Although there were no significant differences among the three groups, the EHD group exhibited a trend-level decrease in Chao 1 and a trend-level increase in Shannon. Principal component analysis indicated a distinct separation of microbiota clusters among the three groups (Figure 3B), with the first and second principal components accounting for 20.73 and 16.39% of the variance, respectively.

At the phylum level, the dominant flora included Firmicutes, Bacteroidetes, and Proteobacteria (Figure 3C). Firmicutes was the predominant phylum, comprising 85.89, 82.73, and 85.57% of the microbiota in the S-CON, L-CON, and EHD groups, respectively, with no significant differences among the groups. Interestingly, the proportion of Bacteroidetes was higher in the L-CON group compared to the S-CON group (p < 0.01) and the EHD group (p < 0.05). Conversely, Proteobacteria levels were higher in L-CON group compared to the L-CON and EHD groups (p < 0.01).

At the genus level, 20 bacterial genera with relatively high abundance were identified (Figure 3D). Lactobacillus emerged as the dominant genus. The relative abundances of Lactobacillus, Prevotella, Coprococcus, and Blautia were 19.04, 4.74, 1.59, and 1.33%, respectively, all higher than in the S-CON group (p < 0.01). Oscillospira and Roseburia were lower in the EHD group compared to the S-CON group, with relative abundances of 5.29 and 4.90%, respectively (p < 0.01). Additionally, Megasphaera was lower in the EHD group compared to the L-CON group, accounting for 1.73% (p < 0.01). Phascolarctobacterium was higher in the EHD group compared to both control groups, accounting for 0.74% (p < 0.01).

Further analysis using a multi-level species tree and applying linear discriminant analysis (LDA) and LEfSe analysis revealed 27 different fecal bacterial genera among the three groups (Figures 3E,F) (P < 0.05). Notably, Lactobacillus, Gemmatobacteria, and Methanobacterium showed differences in the EHD group (p < 0.05). Interestingly, the different flora between the control groups varied, with Megasphaera and Ruminococcus being prominent in the L-CON group (p < 0.05) and Spirochaetes, Spirochaetale, and Oscillospira in the S-CON group (p < 0.05).

To explain the impacts of EHD on the gut microbiota of growing pigs, we analyzed the correlations of the significantly different SCFA content with the fecal microbiota (Figure 3G). Lactobacillus was positively correlated with Propionate, Butyrate, and Isobutyrate (p < 0.05). Acetate, propionate, butyrate, and isobutyrate were positively correlated with Phascolarctobacterium, Coprococcus, and Prevotella (p < 0.05) and negatively correlated with Pseudobutyrivibrio and Selenomonas (p < 0.05). Valerate and isovalerate were not significantly associated with most bacterial groups.