Introduction
Weaning-associated challenges, including diarrhea, growth retardation, and elevated mortality rates, pose significant economic and welfare concerns in swine production (Singer et al. Reference Singer, Finch and Wegener2003). Historically, antibiotics have been widely employed to mitigate these issues by enhancing growth performance and disease resistance. However, their prolonged use has raised global alarms due to unintended consequences such as antimicrobial resistance, drug residues, and gut microbiota dysbiosis (Nwobodo et al. Reference Nwobodo, Ugwu and Anie2022; Uddin et al. Reference Uddin, Chakraborty and Khusro2021). In response, over 40 countries have implemented regulatory restrictions on antibiotic use in livestock, driving the urgent need for safe and sustainable alternatives (Bjrnsson Reference Bjrnsson2017).
Probiotics have emerged as a promising solution, demonstrating the capacity to modulate immune responses, strengthen intestinal barrier function, and competitively exclude pathogens (Sanders et al. Reference Sanders, Merenstein and Reid2019; Slizewska et al. Reference Slizewska, Markowiak-Kopec and Slizewska2021). Among these, Lactobacillus acidophilus and Bacillus subtilis – approved by the Ministry of Agriculture and Rural Affairs as feed additives – exhibit synergistic benefits. Lactobacillus acidophilus enhances nutrient absorption and growth performance in piglets through the production of bioactive metabolites such as organic acids and antimicrobial peptides (Lee et al. Reference Lan, Koo and Kim2016; Sanchez et al. Reference Sanchez, Carrol and Broadway2019). Concurrently, B. subtilis secretes extracellular enzymes (e.g., proteases, amylases) that improve feed digestibility, while also fostering a favorable gut environment by reducing oxidative stress and suppressing Escherichia coli colonization (Ding et al. Reference Ding, Zhao and Ma2021; He et al. Reference He, Jin and Sun2023). Critically, B. subtilis enhances the survival of Lactobacillus strains via oxygen scavenging and co-metabolite production, underscoring the superiority of multi-strain probiotics over single-strain applications (Li et al. Reference Li, Jiang and Qiao2021).
Building on prior evidence that compound probiotic fermentation (FAM®, a co-culture of L. acidophilus and B. subtilis) improved feed intake and growth performance while reduced diarrhea incidence in weaned piglets (Xie et al. Reference Xie, Li and Qian2022), as detailed in Supplementary Table S1, this study investigates its mechanistic effects on nitrogen utilization and nutrient metabolism. Using a comparative approach with antibiotic-treated and control groups, we evaluated FAM’s impact on (1) apparent nutrient digestibility (AND), (2) fecal nitrogen excretion, (3) digestive enzyme activity, and (4) serum metabolomic profiles. Our findings provide novel insights into how FAM enhances nitrogen retention and metabolic efficiency, offering a viable strategy to optimize swine productivity while aligning with global antibiotic-reduction initiatives.
Materials and methods
Animals, diets, and experimental design
The experimental protocol followed the standards of the Animal Care and Use Committee of Zhejiang University (SYXK 2012-0178). One hundred eighty piglets (Duroc × Landrace × Yorkshire hybrid) weaned at 28 days old (average weight of 8.21 ± 0.67 kg) were randomly allocated to three groups with three pens per group, 20 piglets per pen. The three groups consisted of (1) the control group (C), which was fed with basal diet; (2) the FAM group (F), which was fed with basal diet supplemented with 0.1% FAM; and (3) the antibiotic group (A), which was fed with basal diet supplemented with 55 mg/kg kitasamycin and 75 mg/kg chlortetracycline. The basal diet was formulated to meet the nutrient needs for weaned piglets as recommended by the National Research Council (NRC, 1998), with the composition details provided in Table 1. FAM® was provided by Zhejiang Kangwan Dechuan Technology Co., Ltd. (Shaoxing, China), which is a co-fermentation product containing L. acidophilus (≥1 × 106 CFU/g) and B. subtilis (≥1 × 106 CFU/g).
Table 1. Ingredients and nutrient composition of the base diets

a The premix provided per kg dry matter of diet: vitamin A 5,000 IU, vitamin B1 3.0 mg, vitamin B1 6.5 mg, vitamin B6 2.4 mg, vitamin D 2,000 IU, vitamin E 20 IU, vitamin K 1.0 mg, biotin 0.4 mg, folic acid 1.45 mg, pantothenic acid 23.0 mg, niacin 1 mg, Fe (FeSO4) 200 mg, Cu (CuSO4) 6 mg, Mn (MnSO4) 30 mg, Zn (ZnSO4) 80 mg, I (KI) 0.2 mg, Se (Na2SeO3) 0.3 mg.
b Except for the calculated digestible energy, the rest are measured values.
All piglets were housed in a single barn but allocated to three distinct pens within separate spatial regions, ensuring standardized environmental conditions across groups. Husbandry practices conformed to commercial-scale swine farm protocols, including consistent implementation of cleaning, disinfection, and biosecurity measures to maintain optimal hygiene, ventilation, and temperature control. Piglets were kept in pens with unrestricted access to food and water. The experiment period lasts 30 days following a 10-day adaptation period. The intake of feed was recorded during the experiment.
Sample collection and preparation
From 27 to 29 days, for each replicate, 200 g of feces was collected daily, mixed with 10% HCl at a volume ratio of 5:1, and stored at −20℃ for further analysis. At the beginning and end of the experiment, each piglet was weighed and recorded, with a 12-hour fasting period before weighing but free access to water. After the feeding trial, two piglets with an average weight were selected from each pen. A total of 18 piglets were slaughtered following 12 h fast. First, 5 g of liver inner lobe was cut in a 2 mL freezing tube. Blood samples were collected from carotid artery and centrifuged at 3000 × g at 4℃ for 15 min to obtain the serum. The entire gastrointestinal tract was then excised. The digesta samples from the duodenum were collected and placed into 50 mL falcon tubes. The mucosal samples were scraped from the center of the jejunum using a blade and placed into 2 mL tubes. The samples obtained above were snap frozen in liquid nitrogen and then stored at −80°C until further analysis.
Apparent nutrient digestibility
Fecal samples were dried at 65℃ and pulverized to pass a 1.0-mm screen. The ash, ether extract (EE), crude protein (CP), calcium (Ca), and phosphorus (P) contents of the diets and feces were determined in accordance with the standard procedures established by the Association of Official Agricultural Chemists (AOAC (Association of Official Analytical Chemists) 2000). We determined AND using the acid-insoluble ash method, which is characterized by its simplicity, cost-effectiveness, and reliability. The calculation formula is presented below (Van Keulen and Young Reference Van Keulen and Young1977):

where AND is the apparent nutrient digestibility (%), IF is the acid-insoluble ash content (%) in the feed, nf is the nutrient content (%) in the feces, if is the acid-insoluble ash content (%) in the feces, and NF is the nutrient content (%) in the feed.
Fecal nitrogen excretion
The nitrogen content in feces was determined using the Kjeldahl method. The Nesslerization method was used for detecting the ammonium-N. 1 g of feces was soaked in 2.0 mol/L KCl to extract ammonium-N. Then, 10 mL of the filtrate was transferred to a colorimetric tube, and 1 mL of Nessler’s reagent was added. The absorbance was determined at a wavelength of 410 nm, and the concentration of ammonium-N was calculated by standard curve.
Digestive enzymatic activity
0.1 g of digesta sample and 0.1 g of mucosal sample were weighed and homogenized with saline (1:9; wt/v) and three steel balls for 20 min (4000 × g, 4°C). The supernatant was used for the determination of the activities of trypsin, lipase, amylase, sucrase, lactase, and maltase following the instructions provided in the commercial kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, China).
Antioxidant capacity
The antioxidant capacity of total superoxide dismutase (T-SOD), total antioxidant capacity (T-AOC), malondialdehyde (MDA), and glutathione peroxidase (GSH-Px) were assessed using ELISA kits according to the instructions (Nanjing Jiancheng Bioengineering Institute, Nanjing city, China).
Serum biochemistry parameters
Blood urea nitrogen (BUN), total protein (TP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALP) in serum were measured according to the instructions provided with kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, China).
Serum metabolomic analysis
Serum metabolome analysis was conducted by liquid chromatography-tandem mass spectrometry (LC–MS/MS). LC–MS/MS analysis was conducted on the UHPLC system (Agilent 1290, USA) together with AB Sciex TripleTOF 6600 system (Q-TOF, Concord, ON, Canada).
The file format of the serum metabolome analysis was converted to common data format using MSConvert. Data from LC–MS was pretreated using XCMS 1.41.0. Further multivariate statistical analysis was performed on the SIMCA (Version 14.1, MKS Data Analytics Solutions, Concord, ON, Canada). Orthogonal projections to latent structures discriminant analyses (OPLS-DA) were used for detecting responses of dependent variables to independent variables in all groups. The Q2 predictive ability parameter and R2Y goodness-of-fit parameter were calculated to assess model quality using seven-fold cross-validation. Metabolite set enrichment analysis and pathway analysis were performed separately for each identified metabolite and biomarker pathway using the web-based tool MetaboAnalyst, yielding-related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.
Statistical analysis
Statistical analysis of the data was performed using SPSS software 26.0. All data are presented as mean. Significance was set at p < 0.05, and 0.05 ≤ p < 0.10 was viewed as a tendency toward significance. The Kolmogorov–Smirnov test was used to assess the normality of the data distribution. Comparisons between two groups were made using the unpaired Student’s t-test with Welch’s correction or the Mann–Whitney U test. For comparisons involving more than two groups, one-way ANOVA was employed to determine significant differences among groups, followed by Bonferroni or Dunnett’s T3 post-hoc multiple comparison tests.
Result
AND and fecal nitrogen excretion
As shown in Table 2, in piglets supplemented with FAM or antibiotics, the AND of CP and EE was increased significantly (p < 0.05). Additionally, FAM or antibiotics decreased fecal N (p < 0.05) and NH3-N (p < 0.01), and the antibiotic group showed higher fecal NH3-N levels (p < 0.05) compared to the FAM group (Table 3).
Table 2. Effect of FAM on apparent nutrient digestibility in weaned piglets

C: control group; F, FAM group; A, antibiotic group. CP, crude protein; EE, ether extract; CA, crude ash. Values are presented as the means, n = 6.
a-b The mean values within rows with different letters differ significantly (p < 0.05).
Table 3. Effect of FAM on fecal nitrogen excretion in weaned piglets

C: control group; F, FAM group; A, antibiotic group. N, nitrogen; NH3-N, ammonia nitrogen. Values are presented as the means, n = 6.
a-b The mean values within rows with different letters differ significantly (p < 0.05).
Digestive enzymatic activity
Based on the positive effect of FAM on the apparent digestibility of piglets, we then measured changes in the activity of intestinal digestive enzymes in piglets. Digestive enzymes are one of the key factors affecting digestibility. In the duodenum (Table 4), FAM or antibiotics supplementation enhanced (p < 0.05) the activities of trypsin, lipase, and amylase compared to the control group. Similarly, in the jejunal mucosa (Fig. 2B), the supplementation of FAM or antibiotics enhanced the activities of sucrase, lactase, and maltase (p < 0.05).
Table 4. Effect of FAM on digestive enzymatic activity in weaned piglets

C: control group; F, FAM group; A, antibiotic group. N, nitrogen; NH3-N, ammonia nitrogen. Values are presented as the means, n = 6.
a-b The mean values within rows with different letters differ significantly (p < 0.05).
Serum biochemistry parameters
To evaluate the impact of FAM on the nutritional and health status of piglets, we conducted tests on serum biochemical parameters. As shown in Table 5, the ALT levels were higher in the antibiotic group compared to control and FAM groups (p < 0.05), and the BUN levels were lower in FAM and antibiotic groups (p < 0.05). No significant differences were observed in the ALP, AST, or TP levels between groups.
Table 5. Effect of FAM on serum biochemistry parameters in weaned piglets

C: control group; F, FAM group; A, antibiotic group. BUN, blood urea nitrogen; TP, total protein; AST, aspartate aminotransferase; ALP, alkaline phosphatase; ALT, alanine aminotransferase. Values are presented as the means, n = 6.
A-B The mean values within rows with different capital letters differ extremely significantly (p < 0.01).
a-b The mean values within rows with different lowercase letters differ significantly (p < 0.05).
Serum metabolomics analysis
We further conducted serum metabolomics analysis to assess the metabolic status and explored the mechanisms underlying the effects on digestion efficiency and nitrogen utilization. The untargeted LC–MS/MS approach was used to analyze the serum metabolite profiles. The total ion chromatogram (TIC) curves of quality control (QC) samples showed that the response intensity and retention time of each chromatographic peak largely overlapped, indicating that there was minimal variation due to instrument error throughout the experimental process (Fig. 1A). The QC samples were closely clustered in the principal component analysis (PCA), reflecting good repeatability (Fig. 1B). The R2X for PCA was 0.548, suggesting the reliability of the PCA model (Supplementary Table S2). The orthogonal partial least squares discriminant analysis (OPLS-DA) score plot for the serum samples of control, FAM, and antibiotic groups showed clear clustering in Fig. 1C, indicating that FAM or antibiotics significantly influenced the serum metabolome. The Q2 values of the OPLS-DA, which exceeded 0.5, indicate that model remained stable and reliable (Supplementary Table S2). Furthermore, the regression line in the response permutation testing displayed an upward trend, suggesting that the models did not overfit (Fig. 1D).

Figure 1. (A) The total ion chromatogram plot of quality control samples. (B) Principal component analysis score plot of QC and serum samples with 95% confidence interval. (C, D) Orthogonal partial least squares discriminant analysis (C) and response permutation testing of serum samples (D). The sequence of each group of images from left to right is as follows: F vs C, F vs A, and A vs C. The following pictures are in the same order. C: control group; F, FAM group; A, antibiotic group.
Serum differential metabolomics
The volcano plots further illustrated the differences between groups (Fig. 2A). For FAM and control groups, there were 34 different metabolites. For FAM and antibiotic groups, there were 22 different metabolites. For antibiotic and control groups, there were 18 different metabolites. In addition, the differential metabolites are shown in Fig. 2B. The results revealed that, compared to the control group, 24 metabolites, including decanoyl-L-carnitine, L-carnosine, and creatine, were significantly upregulated in the FAM group. In comparison, 10 metabolites, such as L-carnitine, S-methyl-5‘-thioadenosine, and hypoxanthine, were significantly downregulated. Compared to the antibiotic group, 13 metabolites, including acetylcarnitine, L-carnosine, creatine, and creatinine, were significantly upregulated in the FAM group, while 9 metabolites, such as L-pipecolic acid and D-(+)-melibiose, were significantly downregulated. Compared to the control group, 15 metabolites, including trimethoprim, arginine-glutamate, glycerophosphocholine, and indole-3-pyruvate acid, were significantly upregulated in the antibiotic group, while acetylcarnitine, 1-aminocyclohexanecarboxylic acid, and hydrocortisone were significantly downregulated. These findings suggest that both FAM and antibiotics can cause significant alterations in serum metabolites of piglets.

Figure 2. (A) Volcano plots showed the relationship between log2 (fold change) and −log10(p-value). (B) LEfSe of serum differential metabolite.
Metabolic pathway enrichment analysis of differential metabolites
To identify the significantly different metabolic pathways between groups, we further conducted metabolite enrichment analysis. The metabolic pathway enrichment analysis is shown in Fig. 3. For FAM and control groups, there were significant differences in biosynthesis of amino acids, protein digestion and absorption, ABC transporters, and other pathways. For FAM and antibiotic groups, significant differences emerged in N metabolism, the biosynthesis of amino acids and unsaturated fatty acids, ABC transporters, and other pathways. For antibiotic and control groups, there were significant differences in ABC transporters, galactose metabolism, pyrimidine metabolism, and other pathways. Moreover, compared to the control and the antibiotic groups, the FAM group exhibited enhanced amino acid metabolic activity, including biosynthesis of arginine, valine, leucine and isoleucine, and metabolism of alanine, aspartate, glutamate, histidine, arginine, and proline.

Figure 3. The KEGG pathway enrichment analysis of serum different metabolites.
Serum and liver antioxidant parameters
The results for the piglet serum and liver antioxidant ability are presented in Table 6. No significant differences were observed in serum T-AOC and T-SOD across the three groups. Compared to the control group, serum GSH-Px was significantly increased and serum MDA was significantly decreased (p < 0.05) in both FAM and antibiotic groups. Compared to the control and antibiotic groups, T-AOC in liver was significantly increased in the FAM group (p < 0.05), while T-SOD showed no significant differences between three groups. Compared to control group, GSH-Px in liver was increased (p < 0.05) and MDA in liver was decreased (p < 0.05) in both FAM and antibiotic groups, with no significant differences between FAM and antibiotic groups (p > 0.05).
Table 6. Effect of FAM on antioxidant capacity of serum and liver in weaned piglets

C: control group; F, FAM group; A, antibiotic group. MDA, malondialdehyde; SOD, superoxide dismutase; GSH-Px, glutathione peroxidase. Values are presented as the means, n = 6.
a-b The mean values within rows with different letters differ significantly (p < 0.05).
Discussion
This study confirms that compound probiotic fermentation (FAM) enhances nutrient utilization in weaned piglets through multifaceted mechanisms. Consistent with prior findings (Xie et al. Reference Xie, Li and Qian2022) demonstrating that the FAM group showed superior average daily gain (ADG), feed conversion ratio (FCR), and diarrhea incidence compared to the control group while performing comparably to the antibiotic (A) group, FAM supplementation significantly elevated the apparent digestibility of CP and EE, respectively, paralleling improvements in duodenal trypsin, amylase, and lipase activities. Concurrently, a reduction in fecal N and NH3-N concentrations was observed, further explaining FAM’s role in promoting lean muscle deposition and nitrogen recycling. Moreover, FAM caused a rise in the concentrations of L-carnosine, creatine, and acetylcarnitine in serum and had a positive effect on metabolic pathways such as amino acids biosynthesis, unsaturated fatty acids biosynthesis, and protein digestion and absorption. Notably, FAM outperformed antibiotics in safety metrics, as evidenced by elevated serum ALT levels in the antibiotic group, a marker of potential hepatotoxicity (Yin et al. Reference Yin, Cheng and Yang2023).
The synergistic utilization of multiple microbial strains holds the potential to amplify probiotic efficacies through intricate inter-strain interactions. Unlike single-strain formulations, the combined use of L. acidophilus and B. subtilis in FAM leverages complementary functional roles: Lactobacillus acidifies the intestinal environment through lactic acid production, inhibiting pathogens and stimulating endogenous enzyme activity (Gao et al. Reference Gao, Li and Chen2022), while Bacillus secretes extracellular hydrolases that break down complex nutrients (Sella et al. Reference Sella, Vandenberghe and Soccol2015). Such interactions can stimulate the biosynthetic potential of the constituent strains, thereby fostering host growth and augmenting the overall salutary impact on host health (Selegato and Castro-Gamboa Reference Selegato and Castro-Gamboa2023). This aligns with studies showing multi-strain probiotics outperform single-strain formulations in viability and metabolic output (Moussavi et al. Reference Moussavi, Barouei and Evans2023), even rivaling fecal microbiota transplantation in restoring gut health (Kurt et al. Reference Kurt, Leventhal and Spalinger2023). Hence, the observed improvement in digestion and absorption capabilities can plausibly be ascribed to the co-fermentation of diverse microbial strains. This connection bridges the gap between the observed benefits of FAM and the broader context of multi-strain probiotic strategies, highlighting the importance of strain combinations in achieving optimal results.
The digestibility of nutrients is a crucial factor influencing the growth response in weaned piglets (Jones and Patience Reference Jones and Patience2014). In light of the recent implementation of antibiotic bans, there has been a notable increase in the use of probiotics and their fermentation products as feed additives. Lan et al. (Reference Lan, Koo and Kim2016) reported that L. acidophilus increased the digestibility of dry matter, nitrogen, crude fiber, and gross energy in weaned piglets. Yuan et al. (Reference Yuan, Chang and Yin2017) found that soybean meal fermented by B. subtilis, Hansenula anomala, and Lactobacillus casei increased the digestibility of CP, EE, Ca, and P of piglet. Similarly, Dowarah et al. (Reference Dowarah, Verma and Agarwal2018) found that the digestibility of CP and EE was better in pigs fed Pediococcus acidilactici FT28. This study demonstrated that FAM significantly enhances the ATD of CP and EE. Furthermore, the increase in serum ALT levels in the antibiotic group suggests liver damage in piglets, possibly due to hepatocellular necrosis or increased membrane permeability (Shaban et al. Reference Shaban, Jo and Hafez2022; Sookoian and Pirola Reference Sookoian and Pirola2015). These findings cumulatively suggest that FAM represents a viable, efficacious, and safer substitute for antibiotics.
Nutrient digestion is closely linked to the activity of digestive enzymes, which directly affects the efficiency and performance of the digestive system. Research indicates that digestive enzyme activity drops to about one-third of pre-weaning levels one week after weaning, typically taking up to two weeks for these activities to return to or exceed pre-weaning levels (Shi et al. Reference Shi, Wang and Kang2022). In animal experiments, B. subtilis was shown to increase protease and amylase activities (Liu et al. Reference Liu, Wang and Cai2017), while Lactobacillus lactis enhanced the activities of protease, amylase, and lipase (Kong et al. Reference Kong, Li and Chu2021). Similarly, the current study demonstrates that the activities of duodenal digestive enzymes and jejunal mucosal disaccharidases of piglets in the FAM group were elevated, corresponding to improved digestibility. The positive effects of FAM on digestive enzyme activity are likely due to reduced intestinal pH (Shi et al. Reference Shi, Wang and Kang2022). Lactobacillus acidophilus can produce lactic acid, which lowers intestinal pH and inhibits pathogenic bacteria (Deng et al. Reference Deng, Hou and Zhao2022). Meanwhile, B. subtilis forms spores with strong survival capabilities in the gastrointestinal tract, exhibiting acid resistance and thermal stability while promoting the growth of Lactobacillus (Cutting Reference Cutting2011). Therefore, the synergistic action of these two strains in FAM likely contributed to improving the intestinal environment, thereby enhancing digestive enzyme activity and AND.
Increased nitrogen utilization efficiency is one of the manifestations of improved nutrient digestibility. We observed that FAM reduced fecal N and NH3-N content, as well as serum BUN levels, of which the reduction is inversely correlated with the feed’s biological value (Bassily et al. Reference Bassily, Michael and Said1982). These results indicate an improvement in nitrogen utilization efficiency, which partly explains the enhanced digestibility of piglets. Previous studies have shown that probiotics exhibit such effect. For instance, adding a mixture containing active dry yeast to the diet of dairy cows resulted in a reduction of fecal NH3-N content over a period of 7 to 35 days (Vasil and Evgeni Reference Vasil and Evgeni2023). In another study conducted by Zhao and Kim, it was observed that feed mixed with Lactobacillus reuteri and Lactobacillus plantarum reduced fecal NH3-N in weaned piglets (Zhao and Kim Reference Zhao and Kim2015). A possible explanation for these findings may be the enhancement of intestinal flora, which aids in converting small non-protein waste in the blood into microbial proteins that can be digested and absorbed (Zheng et al. Reference Zheng, Pan and Chen2020).
Serum metabolites reflect changes in metabolic activity, providing insights into underlying biochemical processes. In this study, FAM promoted amino acid metabolism in piglets, increasing the levels of metabolites such as L-carnosine, creatine, and acetylcarnitine. Additionally, FAM enhanced differential metabolic pathways including amino acid biosynthesis and protein digestion and absorption. Carnosine, a dipeptide constituted by β-alanine and L-histidine, is endowed with the capacity to scavenge reactive oxygen species and neutralize α,β-unsaturated aldehydes that are formed during lipid peroxidation under oxidative stress. Increased carnosine concentration through blood meal or β-alanine reduces drip loss in pork, increases lean meat yield, decreases backfat thickness, and enhances muscle antioxidant capacity (Park et al. Reference Park, Kim and Kim2014; Wang et al. Reference Wang, Long and Chadwick2022). Creatine, along with phosphocreatine and creatine kinase, functions as an intracellular energy transfer system. Creatine metabolism in fats can induce thermogenesis and combat obesity (Greenhill Reference Greenhill2017). Studies have shown that creatine supplementation promotes muscle energy metabolism, enhances protein synthesis, and improves growth and feed efficiency, while preventing rapid pH decline post-slaughter (Ying et al. Reference Ying, Tokach and DeRouchey2013; Young et al. Reference Young, Bertram and Rosenvold2005, Reference Young, Bertram and Theil2007).
The up-regulation of metabolites, amino acid biosynthesis and protein digestion and absorption aligns with the positive changes in AND, BUN, and nitrogen excretion. Furthermore, the experimental results indicate that FAM supplementation significantly enhanced the metabolic pathways of arginine, branched-chain amino acids (valine, leucine, and isoleucine), aspartate, alanine, proline, and histidine. These amino acids perform critical biological functions including, promoting urea cycle and nitric oxide production (Gao K et al., Posset R et al. 2024), regulating muscle metabolism (Zhang L et al. 2022), participating in protein and nucleotide biosynthesis (Bröer S and Bröer A 2017, Holeček M 2023), facilitating nitrogen transport (Zhang X et al. 2007), promoting collagen synthesis (Li and Wu 2017), and contributing to carnosine formation (Wang et al. Reference Wang, Long and Chadwick2022). Consequently, these metabolic modifications provide evidence for FAM’s capacity to enhance whole-body nitrogen utilization efficiency.
Weaning stress generates excess free radicals, disrupting redox balance and causing oxidative damage to lipids, proteins, and DNA. SOD and GSH-Px scavenge free radicals, while MDA, a product of lipid peroxidation, serves as a marker for oxidative damage. These indicators are critical for assessing antioxidant status in animals. Tang et al. (Reference Tang, Zhao and Yang2024) reported that combined use of Lactobacillus plantarum, Lactobacillus rhamnosus, and Bifidobacterium longum reduced serum MDA levels in weaned piglets and pregnant sows, while increasing GSH-Px and SOD levels. Similarly, Li et al. (Reference Li, Hou and Peng2019) found that Lactobacillus delbrueckii reduced serum and liver MDA levels within 4 weeks while enhancing liver GSH-Px activity. In this study, FAM significantly enhanced liver T-AOC and increased GSH-Px levels, while reducing MDA levels in both serum and liver; in line with the improvement of metabolism, it is suggested that FAM can enhance the metabolic functions, promote protein deposition, and thereby improve the antioxidant capacity.
Conclusion
In conclusion, 0.1% FAM enhances weaned piglet performance through a tripartite mechanism: (1) enzymatic nutrient hydrolysis via strain synergy, (2) nitrogen conservation through biosynthesis and metabolism of amino acids, and (3) antioxidant mitigation of weaning stress. By elevating digestibility indices (CP, EE) and reducing nitrogen waste, FAM not only improves ADG, FCR, and diarrhea incidence, but also addresses environmental concerns linked to intensive swine production. Its safety profile, contrasted with antibiotic-associated hepatotoxicity, positions FAM as a sustainable alternative in the era of antimicrobial stewardship. Future research should explore FAM’s long-term impacts on gut microbiota resilience and carcass quality to fully realize its translational potential.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/anr.2025.10010.
Author contributions
H.-x.Y.: conceptualization, reviewing, and editing; M.H.: original writing, determinations of fecal nitrogen excretion, and serum metabolomic analysis; L.-z.X. and L.-t.T.: determination of digestive enzymatic activity and antioxidant parameters; C.-s.H.: determination of serum biochemistry parameters; and A.-w.D. and X.-z.J.: determination of AND.
M.H. and L.-z.X. contributed equally to this study.