All animals were fed at the experimental base of Chongqing Academy of Animal Sciences. The preparation of Bama strain GF piglets and GF environment testing were based on Zhang et al. (2023). The GF piglets were reared in sterile isolators under GF conditions and were handfed Co60 γ-irradiated sterile 4.8%-fat cow milk powder diluted with sterile water (Anyou Group, Jiangsu, China). Once per week, the GF environments were checked for aerobic and anaerobic bacterial contamination (Sun et al., 2018). Of six GF piglets, three were assigned to the GF piglet; the other three were raised in rearing isolators in a barrier environment which the cleanliness could reach 10,000 and required independent flow of clean air with a high ventilation frequency (20 ∼ 60 times/h) (Ogden et al., 2016) and assigned to the SPF piglet. The pathogen detection report of SPF piglet was attached Supplementary Figure 1. The Ethics Committee of the Chongqing Academy of Animal Science reviewed the relevant ethical issues and approved the study (permit number XKY-No. 20210606).

At 42 days of age, all GF and SPF piglets were weighed, euthanized under isoflurane anesthesia, and exsanguinated in a sterile environment, followed by careful removal and weighing of the spleens. The mass of the MLNs in the jejunum was too slight to be weighed. A portion of the fresh spleen and MLNs were fixed with 4% (w/v) paraformaldehyde (Beyotime, China) for histomorphologic analysis. The remainder of the spleen and MLNs samples were snap-frozen in liquid nitrogen, and then stored at −80°C for further analysis.

For hematoxylin-eosin (HE) staining, fixed tissues were dehydrated and embedded in paraffin. Tissue blocks were sliced, and the tissue sections were deparaffinized and stained with HE (Beyotime, China). B- and T-cell distributions were examined by immunohistochemistry (IHC) staining using CD3⁺ and CD20⁺ pig-specific makers, respectively. IHC staining was performed following the method described by Zhang et al. (2023). Semi-quantitative evaluation of IHC staining using an Image-Pro Plus (version 6.0) followed the method introduced in a previous report (Wang et al., 2009). Briefly, after B cell and T cell zones were identified based on the structure of the splenic central arteriole and the packing density of the cell populations (van Krieken et al., 1985), parameters including area and integrated optical density (IOD) were measured. The mean optical staining densities of the B-cell and T-cell zones were calculated as: sum of IOD/sum of area.

Total RNA was isolated from the frozen spleen and MLNs using TRIzol reagent (Takara Bio, Japan), in accordance with the manufacturer’s instructions. Total RNA samples with a ratio of absorbance at 260/280 nm ranging from 1.8 to 2.0 and an RNA integrity number >8 were used for library construction. We pooled the samples from each tissue by group and prepared a total of 12 sequencing libraries: three replicates each of GF versus SPF in spleen and MLNs. All libraries were constructed and sequenced on the DNBSEQ-T7 seq platform (Novogene, China), and 150-base pair paired-end reads were obtained. High-quality data (clean data) were generated from raw data through rigorous quality control, removing poly-N and low-quality reads, including those with ≥10% N, >10 nucleotides aligned to the adapter with ≤10% mismatches allowed, and >50% of bases with Phred quality <5. The RNA-seq data have been deposited in the GSA with the accession number CRA015219.

Levels of mRNA were quantified using Kallisto software (v 0.44.0), and the transcripts per kilobase of exon model per million mapped reads (TPM) value of each sample was calculated. An mRNA with a TPM value >1 and at least three repeats within one group was considered expressed. Differentially expressed (DE) genes were identified by edgeR (v 3.10) using cutoffs of P < 0.05 and | log₂(Fold Change) | > 1(Bergen and Wu, 2009). Gene functional enrichment analysis and gene set enrichment analysis (GSEA) were performed at the Metascape¹ (Zhou et al., 2019) and Omicshare² websites, respectively. We uploaded each sample matrix to the CIBERSORTx database,³ to calculate the abundances of each immune cell type (Yao et al., 2023), selecting samples with a P value < 0.05.

Spleens from 42-day-old piglets were aseptically removed and bubbled in pre-cooled phosphate-buffered saline (PBS) (Boster Bio, China) containing 5% penicillin/streptomycin for 3–5 min, followed by removal of the connective tissues around the spleen. After three washes in pre-cooled PBS, the spleen was cut into small pieces. Steps for isolating spleen lymphocytes using the Porcine Spleen Lymphocyte Isolation Kit (TBD Sciences, China) followed the protocol described by Ren et al. (2020). Splenic lymphocytes were suspended in RPMI-1640 complete medium and counted using trypan blue staining exclusion. Experiments were conducted on splenic lymphocytes reaching a concentration of 3.75 × 10⁶ cells/ml with a viability >95%. Splenic lymphocytes were cultured in RPMI-1640 medium (Procell Life Science & Technology Co., Ltd., China) with 10% fetal bovine serum (Procell Life Science & Technology Co., Ltd., China) and 1% penicillin/streptomycin in a 37°C incubator with 5% CO₂. The cells were divided into five treatment groups: control (treated with Phosphate Buffered Saline) (Servicebio, China), SCFAs (acetic acid, propionic acid, and butyric acid), lipopolysaccharide (LPS) (Beyotime, China), and concanavalin A (ConA) (Beyotime, China). SCFAs concentrations were based on Zhang et al. (2023), LPS and ConA concentrations were based on Cho et al. (2023).

Cell proliferation was measured using a Cell Counting Kit (CCK)-8 Assay Kit (Beyotime, China) following the manufacturer’s instructions. Splenic lymphocytes were seeded in a 96-well plate (2 × 10⁵ cells/well), divided into three replicates for each of the six treatment groups. After applying each treatment, cells were cultured and assayed at 1, 3, 6, and 12 h by the addition of 10 μl/well CCK-8. Optical density (OD) was measured at 450 nm using a microplate reader (Thermo Fisher Scientific, Spain).

Total RNA was extracted from frozen spleen, MLNs samples, and splenic lymphocytes using HiPure Total RNA Mini Kits (Magen, China), in accordance with the manufacturer’s instructions. Synthesis of cDNA was carried out as described by Pistol et al. (2015), using a PrimeScript RT reagent Kit with gDNA Eraser (Takara Bio, Japan) following the manufacturer’s instructions. Primers were designed through the National Center for Biotechnology Information database and synthesized commercially by Tsingke (China). Real-time quantitative PCR (RT-qPCR) was performed on an ABI Prism 7000 detection system in a two-step protocol with SYBR Green (Applied Bio-Systems, Foster City, CA, USA). Each reaction was performed in a volume containing 1 μl cDNA, 5 ml SYBR Premix Ex Taq (2×), 0.2 μl ROX reference dye (50×), 0.4 μl of each forward and reverse primer, and 3 μl PCR-grade water. The following PCR reaction was performed in a Quant Studio 6 Flex (Thermo Fisher Scientific, USA): 95°C for 30 s, followed by 40 cycles of 95°C for 5 s and 60°C for 34 s, and ending with a melting curve analysis (65–95°C). The relative expression of mRNA was calculated using the 2^{–Δ Δ CT} method and expressed as fold-change relative to the GF or cell culture control group. GADPH was used to normalize the gene expression. The specific primer sequences in this study are listed in Supplementary Table 1.

All statistical analyses were performed using Graphpad Prism 9.5. Unless otherwise stated, numerical data are presented as the mean ± standard deviation (SD). For single comparisons between two groups, the unpaired t-test was used. P-values < 0.05 and <0.01 were considered to indicate statistical significance.

The spleen and MLNs play important roles in innate and adaptive immunity. We established GF and SPF piglets to explore the histological differences in spleen and MLNs between the two models. The spleen weight and organ index were significantly lower in the GF piglet than in the SPF piglet (P < 0.05; Figures 1A, B). Although red pulp structures and lymphatic follicles in the spleen were obvious in both piglets (Figure 1C), the red pulp area was larger in the SPF piglet (Figure 1E). The mature lymphoid regions in MLNs were as follows: the follicular region, in which many germinal centers were located; the paracortex, a lymphatic region located between the cortex and the medulla; and the sinusoid region, comprising the lymphatic cord and sinus (Figure 1D). The mean area of the germinal center was larger in the SPF piglet than in the GF piglet (Figure 1F). These results indicated that the commensal microbiota promotes the development and maturation of the spleen and MLNs in piglets.

The spleen and MLNs contain a variety of immune cells that co-participate in B cell-mediated humoral immunity and T cell-mediated cellular immunity (McCoy et al., 2017). IHC staining of porcine-specific B and T cell markers revealed that B and T cells were mainly distributed in the lymphatic follicles of the spleen and in the cortical part of the MLNs (Figures 2A, B). The proportions of T cells were slightly higher in the spleen of the SPF piglet than in the GF piglet (P = 0.0843) and were significantly higher in the MLNs of the SPF piglet than in those of the GF piglet (P < 0.05; Figure 2C). Furthermore, the proportions of B cells were significantly higher in the spleen and MLNs of the SPF piglet than in those of the GF piglet (P < 0.05; Figure 2D), indicating that B and T cell development in the spleen and MLNs are influenced by colonization of the commensal microbiota.

RNA sequencing (RNA-seq) was used to explore the gene expression patterns of spleen and MLNs in the presence or absence of the commensal microbiota. We obtained ∼218.10 G clean data from 12 libraries (18.175 G per library) (Supplementary Table 2), with a total of 12,434 mRNAs identified. Principal component analysis (PCA) and hierarchical clustering showed different expression patterns between the spleens and MLNs of the GF and SPF piglets (Figures 3A, B). A total of 809 (600 upregulated and 209 downregulated) and 346 (120 upregulated and 226 downregulated) DE mRNAs were obtained in the spleen and MLNs, respectively (Figure 3C and Supplementary Table 3). We had obtained some highly upregulated genes, such as TNF receptor superfamily (TNFRSF) was found in spleen and MLNs upregulated genes, namely TNFRSF19 and TNFRSF17, which function to activate signaling pathways for development, organogenesis, cell death, and survival (Zhao et al., 2018). In addition, USP1 associated with innate immunity (Zhai et al., 2024), was also found in the upregulated genes, and IRF7 expressed in lymphocytes consistented with the above results (Li et al., 2021). Gene Ontology (GO) enrichment showed that many immune-related pathways, such as cellular response to external stimulus and defense response to virus were enriched in the spleen, while adaptive immune response and antiviral innate immune response were enriched in MLNs (Figures 3D, E and Supplementary Table 4). These results indicated that colonization of the commensal microbiota enhances the expression of immune-related signaling pathways and promotes the function of the immune system.

The colonization of the commensal microbiota significantly stimulated the immune status of the spleen and MLNs. Therefore, we used the GO database to download genes and products related to inflammatory factors (Supplementary Table 5). In the spleen and MLNs, the majority of genes in the gene set of the SPF piglets was significantly upregulated (Supplementary Figure 2). However, gene set analysis only focused on specific related pathway. Therefore, we used GSEA to analyze the overall gene expression data of the spleen and MLNs, focusing on the synergistic changes of the entire gene set, and exploring the impact of the commensal microbiota on the overall immune-related signaling pathways in the spleen and MLNs. Compared with the GF piglet, the antigen processing and presentation of exogenous antigen-related signaling pathways (GO:0048002, GO:0019884, and GO:0003823) were significantly activated in the spleen of the SPF piglet (Figure 4A). The SPF piglet also showed not only activation of the innate and adaptive signaling pathways (GO:0045088 and GO:0002821), but also positive regulation of the lymphocyte-mediated immunity signaling pathway (G0:0002708) in MLNs compared with the GF piglet (Figure 4B). In addition, RT-qPCR was used to verify the vital factors regulating inflammatory signaling pathways and inflammation-related factors triggered by the antigen response shown in the results of GSEA. We detected the expression of an immune-suppressive cytokine (TGF-β)-related signaling pathway and found that the expression levels of TGF-β and SMAD3 were higher in the spleen and MLNs of the SPF piglet compared with those in the GF piglet (Figures 4C, D). Additionally, the expression levels of TLR2, NF-κB, MyD88, and proinflammatory factor genes IL-6 and TNF-α were also higher in the spleen and MLNs of the SPF piglet compared with those in the GF piglet (Figures 4C, D). These results revealed that the commensal microbiota impacts the specific immune-related signaling pathways of the spleen and MLNs, enhancing the expression of immune response pathways, including the TGF-β signaling pathway, and inflammatory signaling pathways (TLR2/MyD88/NF-κB).

The commensal microbiota regulates the function and abundance of multiple immune cell types (Scott and Mann, 2020). CIBERSORTx is a suitable tool for the assessment of cellular abundance and cell type-specific gene expression patterns from bulk tissue transcriptome profiles (Steen et al., 2020). We identified 16 and 17 immune cell types in the spleen and MLNs, respectively, using CIBERSORTx (Figures 5A, B). The abundances of plasma cells, CD8⁺ T cells, follicular helper T cells, and resting NK cells were significantly increased in the spleen and MLNs of the SPF piglet compared with those in the GF piglet (P < 0.05; Figure 5C). By contrast, the abundance of memory B cells was lower in the spleen and MLNs of the SPF piglet than in the GF piglet (Figure 5D). In addition, compared with the spleen, the abundances of resting NK cells and monocytes in MLNs were higher and lower, respectively (Figures 5E, F). These results indicated that the commensal microbiota alters the abundance of immune cells by influencing the cell type-specific gene expression patterns of spleen and MLNs. In addition, the commensal microbiota had different effects on the abundances of resting NK cells and monocytes.

To verify the immune-related pathways underlying the regulation of tissue immunity function, we established an in vitro model in splenic lymphocytes (Supplementary Figure 3). Cell proliferation was significantly increased under treatment with acetic acid, propionic acid, butyric acid, LPS, or ConA for 1 h compared with control (P < 0.01; Figure 6A). However, proliferation dropped thereafter, with no significant differences between the treatment and control groups 3, 6, and 12 h of treatment (Figure 6A). Next, we used RT-qPCR to analyze the expression of immune-related pathway genes at 1 h post-treatment, including TGF-β/SMAD3 and TLR2/MyD88/NF-κB pathway genes, as well as inflammatory factor genes IL-6 and TNF-α. The expression levels of TGF-β were significantly increased under all treatments compared with control (P < 0.05; Figure 6B), while the expression of SMAD3 showed an increasing trend under all treatments (Figure 6B). The expression levels of TLR2, MyD88, NF-κB, IL-6, and TNF-α were also significantly increased in all treatment groups compared with control (Figure 6B). These results revealed that the tendency for expression of specific immune-signal pathways in the spleen and MLNs in vivo were consistent with those in lymphocytes in vitro.