The experimental design is shown in Figure 1A . MFGM was obtained from Beijing Sanyuan Foods Co., Ltd. Six- to seven-week-old specific pathogen-free (SPF) C57BL/6J male mice (obtained from SPF Biotechnology Co., Ltd., Beijing, China) were maintained in a standard SPF facility with 12-h light and 12-h dark cycles at 22°C at four animals per cage. After a week of acclimation, the mice were randomly divided into four groups (n = 8) for the subsequent experiment: CON group [oral gavage of 200 μl sterile phosphate-buffered saline (PBS) for 4 weeks with regular tap water], MFGM group (oral gavage of 200 μl 50 mg/kg body weight MFGM in sterile PBS for 4 weeks with regular tap water), DSS group (oral gavage with 200 μl sterile PBS for 4 weeks with 4% DSS in drinking water for the last week), and MFGM + DSS group (oral gavage with 200 μl 50 mg/kg body weight MFGM in sterile PBS for 4 weeks with 4% DSS in drinking water for the last week). The dose of MFGM is based on our previous study in other animal models (25, 28). The animal experiment was performed in accordance with the guidelines of the local ethics committee. The disease activity index (DAI) score was evaluated to assess the severity of colitis by combining the scores of body weight loss, diarrhea of the stool, and the extent of blood in the feces (29). Body weight and DAI were recorded daily in the last week. After sacrifice, the length of gross colon was recorded, and 5-mm segments of the mid-colon and liver were fixed in formalin for sectioning and staining. Fecal samples, serum samples, and colonic and hepatic tissue from each mouse were collected and immediately stored at -80°C for a subsequent analysis.

For morphological measurements, the fixed colonic and hepatic tissue were paraffin-embedded, dehydrated, sectioned at 5 μm, and stained with hematoxylin and eosin (H&E). The histological score was consisting of the extent of inflammatory infiltration, histopathological changes, ulceration and loss of crypt, and the completeness of colonic epithelia (3). To measure the thickness of mucus, the colonic sections were stained with Alcian blue for 10–15 min and dehydrated with 100% alcohol and xylene.

Immunofluorescence staining of proliferating cell nuclear antigen (PCNA) was performed on colonic sections of mice with the PC10 antibody (Abcam, ab201672). Immunofluorescence staining of F4/80 was performed on the liver sections of mice with the anti-F4/80 antibody (Abcam, ab100790). The images were acquired with a microscope (Carl Zeiss AG, Jena, Germany).

Frozen colonic and hepatic tissues as well as serum were homogenized with radioimmunoprecipitation assay lysis buffer (Solarbio, Beijing, China) to extract total proteins. Total protein level was quantified with a bicinchoninic acid protein assay kit (Solarbio, Beijing, China). The concentrations of IL-6, IL-1β, and IL-10 were measured by ELISA kits (R&D Systems, Minneapolis, MN, USA). The levels of total superoxide dismutases (T-SOD), catalase (CAT), glutathione peroxidase (GSH-px), and malondialdehyde (MDA) were quantified using commercial kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, China) according to the manufacturer’s directions.

The contents of myeloperoxidase (MPO), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were assayed using commercial kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, China) according to the manufacturer’s directions.

Total RNA of colonic and hepatic tissues was isolated using TRIzol™ Reagent (Invitrogen, CA, USA) and purified using a PureLink™ RNA Mini Kit (Invitrogen, CA, USA) according to the manufacturer’s directions. RNA quality was evaluated by electrophoresis using an Agilent 2100 Bioanalyzer (Agilent Technologies, CA, USA). Samples with RNA integrity number >9.4 and with 260/280 nm absorbance ratio from 1.9 to 2.1 were used for the construction of the library products for RNA sequencing. The library products were prepared using the TrugSeq™ RNA Sample Prep kit (Illumina, CA, USA) according to the manufacturer’s directions. Then, sequencing of the library products was performed in Illumina HiseqTM 2500 (Illumina, CA, USA), and the quality was individually assessed using FastQC. Based on the referential genome of Mus musculus (version GRCm38.p6), mapped reads were acquired, and then differentially expressed genes were identified using the DEGseq2 package. Heat maps were generated using the “pheat-map” packages of R software (version 4.1.2; https://www.r-project.org/). Scatter plots were derived using RSEM (version 1.3.3). The data were analyzed through the free online platform of Majorbio Cloud Platform (www.majorbio.com). Gene Ontology (GO) enrichment was performed using Goatools (version 0.6.5) based on the GO database (version 2019.7.1; http://www.geneontology.org/).

Total DNA was extracted from fecal samples using QIAamp^® Fast DNA Stool Mini Kits (Qiagen Ltd., Germany) according to the manufacturer’s instructions. Then, the V3–V4 region of the 16s rRNA gene was amplified using universal primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). The PCR cycling programs were 95°C for 3 min, 29 cycles of 95°C for 30 s, 55°C for 30 s, and 72°C for 45 s, with a final extension at 72°C for 10 min. Agarose gel electrophoresis was performed to verify the quality and size of the amplicons. After purification and quantification, the normalized PCR products were pooled in equal volumes and sequenced on an Illumina MiSeq 2 × 300-bp paired-end sequencer. Negative controls for DNA extraction, amplification, and mock community (Zymo, Irvine, CA, USA) were included in each MiSeq run for quality control.

Raw sequences were analyzed using the QIIME platform (version 1.9.1). Multiplex single-end sequencing reads (>50,000 per sample) were imported into the QIIME1.9 platform. The initial reads were quality-filtered, denoised, and assembled. Chimeric sequences were removed using data2. The subsequent clean reads were clustered as operational taxonomic units (OTUs) using Uparse (version 7.0.1090) and annotated with the SILVA 16S rRNA gene database (version 132) using MOTHUR program (version 1.30.2). Alpha-diversity was calculated based on the profiles of OTU. Beta-diversity was estimated by calculating the unweighted and weighted UniFrac distances (Bray–Curtis distance and 999 permutations) and then visualized with principal coordinate analysis (PCoA). ANOSIM was performed to compare the similarity of bacterial communities among groups using the “vegan” package of R (version 4.1.2). To identify the differential bacteria among groups, the relative abundances of the phylum and genus levels were analyzed by Kruskal–Wallis H-test and adjusted by false discovery rate. Bar plots and heat maps were done using the “ggplot2” packages of R software (version 4.1.2; https://www.r-project.org/), respectively. All the relevant scripts for analysis are shown in Additional File 1 . Differentially abundant genera were identified using linear discriminant analysis (LDA) effect size (LEfSe) analysis (http://huttenhower.sph.harvard.edu/galaxy/root?tool_id=lefse_upload) (30). Only bacterial taxa reaching the LDA threshold of 2.0 and with average relative abundances greater than 0.01% are shown.

The colonic tissues were subjected to total RNA isolation, cDNA synthesis, and RT- qPCR as we have previously described (31). The qPCR reactions were performed on LightCycler^® 96 Real-Time PCR System (Roche Molecular Systems, MA, Switzerland) as follows: 95°C for 1 min, followed by 40 cycles of 95°C for 10 s and another 10 s at the respective annealing temperature for each gene. Melting curve analysis was performed to verify the specificity of the PCR reactions. Reg3b and Reg3g expressions were assayed by real-time PCR using SYBR Green Supermix (Takara, Tokyo, Japan) with specific primers (forward: TCCCAGGCTTATGGCTCCTA, reverse: GCAGGCCAGTTCTGCATCA; forward: TTCCTGTCCTCCATGATCAAAA, reverse: CATCCACCTCTGTTGGGTTCA) (13). β-actin was used as a control (forward: AGGTGACAGCATTGCTTCTG, reverse: GCTGCC TCAACACCTCAAC) (32). Gene expression was normalized to the housekeeping gene β-actin.

All data are presented as means ± SEM and analyzed using GraphPad Prism (version 9.0, GraphPad Software, San Diego, CA, USA). Data among groups were compared using one-way ANOVA, followed by Tukey’s multiple-comparison tests. Adjusted P ≤0.05 was considered statistically significant. Heat maps (correlation between parameters from the colon and liver) were created using the “pheat-map” packages of R software (version 4.1.2). All the relevant scripts for analysis are shown in Additional File 1 .

Firstly, the alleviated effects of prophylactic MFGM in DSS-induced colitis were assessed. The body weight of mice was significantly increased in the MFGM + DSS group compared with the DSS group ( Figure 1B ), but the body weight was not impacted by MFGM in healthy mice (mice without DSS) ( Figure 1B ). Decreased DAI score was shown in the MFGM + DSS group compared with the DSS group ( Figure 1C ). The colonic length was also shortened by DSS treatment, while it was increased in the MFGM-treated group ( Figures 1D, E ). H&E staining revealed that the histological score of colons was increased in the DSS group but was significantly decreased in mice with prophylactic MFGM ( Figures 1F, G ).

DSS treatment significantly increased the colonic levels of IL-1β and IL-6 but decreased the colonic level of IL-10, MPO, and MDA, while these were reversed by MFGM ( Figures 1H–L ).

To explore how MFGM protects from colonic damage, the gene expression profiles for colonic tissues were quantified by RNA-seq analysis. The gene expression profiles of colonic tissue were significantly influenced by prophylactic MFGM ( Supplementary Figure S2 ). In total, 807 genes were significantly upregulated, but 370 genes were significantly downregulated in the MFGM + DSS group ( Figure 2A ). Genes including Ighv1-72, Ighv1-53, Ighv1-82, Ighv1-61, Igkv4-51, Igkv2-116, MUC2, MUC4, Reg3b, and Reg3g were twice upregulated in the MFGM + DSS group compared with the DSS group ( Figure 2A ).

Furthermore, the functions of the altered genes were annotated by GO pathway analysis. The enriched pathways of the comparison were mainly enriched in the parts of biological process and cellular component, consisting of cellular process, cell part, and binding shown by GO analysis ( Figure 2B ). Moreover, the differential genes from the comparison were also respectively determined by GO enrichment analysis. The upregulated pathways of the comparison were consisting of such as chemokine-mediated signaling pathway, epithelial cell proliferation, response to protozoan, and cell matrix adhesion in the MFGM + DSS group compared with the DSS group ( Figure 2C ). On the contrary, some metabolic pathways such as steroid metabolic process, intestinal lipid absorption, and lipid transport were downregulated in colitis mice with prophylactic MFGM ( Figure 2D ).

To further explore how prophylactic MFGM impacts the response to protozoan, the community of gut microbiota was explored by 16s rRNA V3–V4 sequencing. Interestingly, prophylactic MFGM significantly decreased the community richness and community diversity of the fecal microbiota in both mice with and without DSS, shown by the ACE estimator and Shannon diversity index ( Figures 3A, B ). The PCoA revealed the respective clustering of gut microbiota for the four groups (R = 0.898, P = 0.001, Figure 3C ) and a significantly separated clustering of microbiota between groups with MFGM and without MFGM in healthy mice (R = 0.858, P = 0.002) as well as between the DSS group and the MFGM + DSS group (R = 0.634, P = 0.002). At the phylum level, all fecal samples shared a similar community structure. The phyla in all groups were mainly dominated by Firmicutes and Bacteroidetes, representing more than 80% of the relative abundance in healthy mice but more than 60% of it in DSS-treated mice ( Figure 3D ). At the genus level, Lactobacillus, norank_f:Muribaculaceae, Bifidobacterium, and Dubosiella were the dominant genera in all groups ( Figure 3E ). Furthermore, differential bacteria at the genus level were identified by LEfSe. The LEfSe analysis revealed that six genera were enriched in the DSS group, while another 15 genera, such as Faccalibacumum and Roseburia, were enriched in the MFGM + DSS group ( Figure 3F ). Nine genera, including Bifidobacterium and Dubosiella, were significantly impacted by MFGM compared to the normal controls ( Supplementary Figure S3 ).

In fact, liver injury was always along with acute colitis (10). Notably, the gut–liver axis consisting of the gut microbiota, intestinal mucosal barrier, and hepatic immunity might play a critical role in secondary liver injury (14, 15, 17). Therefore, the attenuated effect of MFGM in colitis-associated liver injury was further explored. H&E staining revealed that DSS induced histological damage in the liver, as shown by the infiltration of immunocytes, and even local bleeding, which were alleviated in mice with MFGM ( Figures 4A, B ). The hepatic MPO level was significantly enhanced by DSS compared to normal controls, while it was significantly attenuated in the MFGM + DSS group ( Figure 4C ). The hepatic levels of MPO, IL-6, and IL-10 were also increased in the DSS-treated mice, while they were decreased in the MFGM+DSS group ( Figures 4D, E ). Increased plasma levels of IL-6 and IL-10 were shown in mice with prophylactic MFGM compared to the DSS group ( Figures 4F, G ). Furthermore, the concentrations of AST and ALT in the plasma and liver were obviously evaluated by DSS treatment, while they were reduced in mice with prophylactic MFGM compared with the DSS group ( Figures 4H–K ).

To further assess the impact of prophylactic MFGM on hepatic function, hepatic gene expression profiles of DSS-treated mice were also quantified by RNA-seq analysis ( Supplementary Figure S1 ). In total, 248 genes were upregulated, while 1,785 genes were downregulated in the liver of the MFGM + DSS group compared with the DSS group ( Figure 5A ). Of note is that major urine proteins (MUPs), such as MUPs1–3 and MUPs7–9, were twice upregulated in the MFGM+DSS group than in the DSS group, as shown with a scatter plot ( Figure 5A ). The GO annotation analysis revealed that impacted genes were mostly enriched in cellular process, cell, and binding ( Figure 5B ). The upregulated pathways were mainly consisting of such as mitochondrion morphogenesis, circadian behavior, glutathione transferase activity, and oxidoreductase activity ( Figure 5C ). Otherwise, pathways such as microvillus membrane, pyroptosis, collagen binding, collagen metabolic process, and sister chromatid segregation were downregulated in the MFGM + DSS group compared to the DSS group ( Figure 5D ).

Since “epithelial cell proliferation” and “response to protozoan” was enriched in the colonic RNA-seq data, these two pathways were further determined in the colonic samples. Epithelial cell proliferation was accessed by PCNA staining. The results revealed that the expression of positive PCNA was significantly increased in the MFGM + DSS group compared with the DSS group ( Figure 6A ). Moreover, the decreased mucus layer of the colon upon DSS treatment was revealed by Alcian blue staining, while it was increased in the MFGM + DSS group ( Figure 6A ). To further demonstrate it, the colonic RNA expression levels of Reg3b and Reg3g were quantified by qPCR. Similarly, both significantly upregulated levels of Reg3b and Reg3g were revealed in the MFGM + DSS group compared with mice treated with DSS ( Figures 6B, C ). All these data suggested that prophylactic MFGM improved the colonic epithelial barrier. Moreover, since glutathione transferase activity was enriched in the MFGM + DSS group shown by GO analysis, the hepatic levels of CAT, T-SOD, GSH-PX, and MDA were explored. Significantly increased hepatic levels of CAT, T-SOD, and GSH-PX while decreased hepatic and plasma levels of MDA were shown in the MFGM + DSS group ( Figures 6D–H ). The correlation between the parameters of colonic tissues and hepatic tissues in DSS-treated mice was also analyzed. The results revealed that the colonic concentrations of IL-1β, IL-6, and MPO positively correlated with the hepatic levels of IL-6, AST, and ALT and negatively correlated with the hepatic levels of IL-10, GSH-PX, T-SOD, and CAT ( Figure 7 ; Additional Files 2 , 3 ). Moreover, the colonic levels of IL-10, Reg3b, and Reg3g showed a negative correlation with the hepatic levels of IL-6, AST, and ALT, but with a positive correlation with the hepatic levels of IL-10, GSH-PX, T-SOD, and CAT ( Figure 7 ; Additional Files 2 , 3 ).