Tupistra chinensis polysaccharides remitted intestinal inflammation induced by LPS via regulating gut microbiota

Abstract

Natural products are increasingly regarded as alternatives to antibiotics due to rising concerns about antimicrobial resistance (AMR). As a result, we investigated the therapeutic effects of Tupistra chinensis (TC) polysaccharides in lipopolysaccharide (LPS)-challenged mice. Thirty ICR mice were divided into three groups: control (DB), LPS- LPS-challenged (LB), and TC-treated (KB). The KB group received oral TC polysaccharides (1 g/kg/day) for 14 days, followed by the LPS challenge. Histopathological analysis revealed that TC polysaccharides restored intestinal mucosal integrity and splenic architecture to near-normal levels following LPS-induced damage. High-throughput 16 s rRNA sequencing demonstrated that LPS significantly (p < 0.05) reduced alpha(α)-diversity (Shannon and Pielou indices), with distinct clustering observed between the LPS- and TC-treated groups regarding beta(β)-diversity. At the phylum level, beneficial Verrucomicrobiota, Firmicutes, and Campylobacterota increased while pathogenic Proteobacteria decreased in the TC group. At the genus level, Paramuribaculum, Prevotella, Alloprevotella, and Duncaniella (anti-inflammatory) were elevated in the TC-treated group, while LPS-induced pathogens (Bacteroides_H, UBA 3263, and Erysipelatoclostridium) were diminished. LeFSe analysis indicated TC-associated taxa, including Campylobacterota, Helicobacter-D, and COE 1, linked to inflammation resolution. Regarding metabolic pathways, TC upregulated vitamin K2 biosynthesis pathways and energy metabolism, mitigating oxidative stress, while LPS increased pathways related to the degradation of amino acids (L-arginine, L-threonine), which TC counteracted. In conclusion, the restoration of gut microbiota diversity and metabolic homeostasis underscores TC’s potential as an antibiotic alternative for treating enteritis through microbiota-targeted mechanisms.

Introduction

An impaired intestinal barrier allows pathogens to enter and cause enteric and systemic infections (Turner 2009). To combat these infections, antibiotics are commonly used. However, excessive use of antibiotics has led to the rise of multidrug-resistant bacteria, like Salmonella and Escherichia coli (E. coli) (Xu et al. 2017; Scott et al. 2018). The World Health Organization (WHO) recognizes antimicrobial resistance (AMR) as one of the top ten global health challenges, attributing 1.27 million mortalities directly to AMR in 2019, with an additional 4.95 million deaths associated worldwide (Marston et al. 2016; Walsh et al. 2023). Among resistant pathogens, E. coli poses a significant global health threat for humans and animals, with an incidence of 45–52 cases per 100,000 people between 2010 and 2014, resulting in an estimated annual economic burden of £14.3 million (Hiruy et al. 2024; MacKinnon et al. 2020).

Lipopolysaccharide (LPS) is a key constituent of the cell wall in Gram-negative bacteria-induced sepsis-like illness, leading to the activation of the innate immune response and promoting the secretion of inflammatory cytokines (Wang et al. 2022). Previous studies have reported gut dysbiosis in mice due to LPS (Tang et al. 2021). Therefore, there is a growing interest in anti-LPS therapeutics and in developing new antimicrobial agents to address this ever-growing challenge. The recent shift from antibiotics to natural products is attracting scientists worldwide due to AMR (Matsakidou et al. 2019).

Tupistra chinensis (TC) is a perennial herb belonging to the family Asparagaceae and genus Tupistra Ker-Gawl, also known as cow root seven and bamboo root seven. It is primarily found in different regions like Sichuan, Yunnan, and Zhejiang in China. For centuries, TC extracts have been used as an anti-inflammatory medicine. Studies have shown the therapeutic effects of TC extract against acute hepatitis in mice by activating T lymphocytes (Wu et al. 2014); especially, the root extract has antifungal activity (Yao et al. 2022). Traditionally, TC is mainly used for sore throat, diphtheria, and stomach discomfort (Lu et al. 2023). It is included in key Chinese pharmacopoeias, like the Great Dictionary of Chinese Materia Medica and the National Compendium of Chinese Materia Medica (Thuy Linh et al. 2022). Modern pharmacological research has explored several beneficial properties of TC, including anti-inflammatory, antibacterial, and anti-tumor effects (Samantaray and Pradhan 2024). It is reported that the TC mainly contains saponins, polysaccharides, fatty acids, etc. (Wang et al. 2021), with extracts like n-butanol showing significant cytotoxic and anti-inflammatory effects (Xu et al. 2020a). Additionally, polysaccharides from this plant are reported to have anti-inflammatory, analgesic, and immune-modulating properties in a few studies (Xu et al. 2020a), but need further exploration in this regard.

The gastrointestinal (GI) tract is not only responsible for the digestion and absorption of nutrients, but is also considered the largest immune organ in the body (Weersma et al. 2020), integral for growth, development, and overall health (Adak and Khan 2019). In this context, gut microbiota evolves alongside the host, with variations in the microbiota’s community structure reflecting the health and physiological functioning of the host (Sittipo et al. 2018). The gut microbiota consists of dynamic microorganisms such as bacteria, archaea, viruses, molds, and protozoa (Nathan et al. 2021), coexisting with the host for mutual benefits (Malago 2015). However, an imbalance in the microbiota, caused by physical, chemical, or microbial factors, disrupts metabolism and significantly affects the host’s growth and development, as seen in inflammatory bowel disease (IBD) (Marafini and Monteleone 2024). Furthermore, recent studies have indicated that the composition of the gut microbiota is closely related to the occurrence of many diseases, including enteric, metabolic, and some cardiovascular and cerebrovascular diseases (Hou et al. 2022).

Recent improvements in high-throughput genome sequencing (HST) technologies, such as genomics and transcriptomics, allow us to study gut microbiota in detail, paving the way to understand how they interact with the host and with each other (Nambu et al. 2022). So, we explored how TC polysaccharides exhibited protective effects in LPS-challenged mice, paying attention to variations in enteric architecture, spleen tissues, and gut bacteria. The prime concern was to provide new insight into the potential therapeutic effects of TC against gram-negative bacteria and other inflammatory diseases.

Materials and methods

Drugs and reagents

The root of TC was bought from Shenao Pharmacy in Bozhou, China, grown according to GAP standards, and kept in a dark, dry place at a temperature of 20–25 °C and 50–60% humidity in a sealed container to prevent external damage. The roots of TC were dried and crushed. The crushed material was then defatted three times with triploid 95% ethanol at 65 °C to remove fats. After degreasing, we soaked the plant residue in hot water to extract the filtrate, repeating the process three times. The solution was then centrifuged, followed by vacuum drying and freezing, resulting in a crude polysaccharide. This crude polysaccharide was then precipitated in an 80% ethanol solution and centrifuged at 2500 rpm for 10 min. The collected liquid contained the polysaccharide extracted from TC, which was then stored at 4 °C for future use.

Experiment design

In this experiment, thirty 4-week-old ICR mice were purchased from the Experimental Animal Center at Yangzhou University. Mice were acclimatized for 3 days under controlled conditions (26 °C, 50–60% humidity, 12-h light/dark cycle). Feed and water were provided ad libitum, with environmental parameters monitored daily. After the adaptation period, mice were randomly divided into 3 groups, with 10 mice in each group: control group (DB), LPS-challenged model group (LB), and polysaccharide treatment group (KB).

The KB group received a daily dose of 1 g/kg polysaccharide solution via oral gavage, while the mice in groups DB and LB received 0.5 ml of normal saline daily for 14 days. On day 14, one hour after administering the last dose, mice in the LB and the KB groups were intraperitoneally injected with 20 mg/kg LPS. Then, the mice in all groups were humanely euthanized 24 h post-LPS challenge by CO₂ inhalation. Blood, small intestine, spleen, liver, and fecal samples were collected and stored at −80℃ for further analysis.

Ethical approval

All the experiments were conducted after approval from the Animal Welfare Committee on the Ethics of Animal Care and Use, Nanjing Agricultural University (NJAU.No.20230413054).

Histopathological analysis

We collected jejunum and ileal tissues (0.5–1 cm/animal) from mice in all three groups and fixed them in a 4% formaldehyde solution for 48 h. The fixed samples were then sent to Wuhan Pinuofei Biological Technology (China) for hematoxylin and eosin (H&E) staining. A histopathological analysis of villus integrity and damage was conducted using an Olympus CX33 microscope (Olympus, Japan), as described in a previous study (Xu et al. 2024). Each analysis was performed in triplicate.

DNA extraction, PCR amplification of target fragments

The total microbial DNA was extracted from rectal samples of mice in the DB (n = 3), LB (n = 3), and KB (n = 3) groups using the FastDNA Spin Kit for Feces (Beijing Think-Far Technology Co., Ltd., China). The quality and quantity of DNA were checked via Ultramicrospectrophotometer YSNano-100 (Yeasen, China) and agarose gel electrophoresis (1.5%), following the protocol described in previous studies (Zhu et al. 2025; Stanzick et al. 2023).

High-throughput 16S rRNA sequencing

The composition and diversity of intestinal microbiota in mice were studied by metagenomic sequencing of the 16S rRNA gene V3-V4 variable region (Grigorova et al. 2021). Pyrococcus furiosus (Pfu) high-fidelity DNA polymerase was used to amplify the extracted DNA by PCR to obtain accurate amplification products. Negative and positive controls were included during amplification to ensure product purity and accuracy. For PCR amplification of the 16S rRNA gene (V3-V4), universal primers 27 F (AGAGTTTGATCCTGGCTCAG) and 1492R (GGTTACCTTGTTACGACTT) were used.

The PCR mix consisted of 12.5 μL 2 × Taq PCR MasterMix, 1μL (10 μM) of each forward and reverse primer, 9.5μL ddH₂O, and 1μL template DNA (thoroughly mixed and centrifuged), making a total volume of 25 μL. The thermal cycling reaction consisted of 35 cycles with initiation at 95 °C for 3 min (required only once at the start of the reaction), followed by denaturation at 95 °C for 15 s, primer annealing at 53 °C for 15 s, elongation at 72 °C for 30 s, and a final elongation at 72 °C for 5 min. The PCR products were analyzed by electrophoresis on a 1% agarose gel. The parallel PCR products were sent to Shanghai Shenggong Bioengineering Co., Ltd., Shanghai, China, for phylogenetic sequencing. The PCR amplification products were purified and recovered using magnetic beads (Henley et al. 2020). The purified products were quantified by Quant-iT PicoGreen dsDNA Assay Kit and analyzed with a microplate reader (BioTek, FLx800).

Bioinformatics analysis

After high-throughput sequencing, the original sequencing information was in FASTQ form. The paired-end reads were then preprocessed with the cutadapt software to check and remove the adapters. Following cutting, paired-end reads were filtered, denoised, combined, and detected, and chimera reads were removed using the Divisive Amplicon Denoising Algorithm 2 (DADA2, Version: 1.26.0) with the help of Quantitative Insights into Microbial Ecology (QIIME, Version: 2024.10)2’s default parameters. Finally, the software generated the representative readings and amplicon sequence variant (ASV) abundance graphs. After choosing exemplary sequences for each ASV using the QIIME 2 software package, all representative sequences were annotated and blasted against the Silva database Version 138, utilizing classify-sklearn with the standard parameters. According to taxonomic data, a statistical evaluation of microbial structure was carried out (Lozupone et al. 2007). Statistical Analysis of Metagenomic Profiles (STAMP; Version: 2.1.3) and Linear Discriminant Analysis Effect Size (LefSe) differential analysis were employed to assess the abundance of bacterial and fungal species. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2 (PICRUSt2) was used to predict the metabolomics based on the marker gene (16S/ITS) sequence (Douglas et al. 2020). The Analysis of Similarities (ANOSIM) and Wilcoxon tests were employed to determine variations among treatments.

The clean data were then used subsequently for alpha (α)-diversity (Chao1, Pielou, Goods coverage, Simpson’s index, and Faith PD) and beta (β)-diversity analysis: PCoA and NMDS, Unweighted Pair Group Method with Arithmetic Mean (UPGMA), Permutational Multivariate Analysis of Variance (PERMANOVA) (Hall and Beiko 2018; Mohsen et al. 2022). Additionally, R software and LEfSe (LDA score > 2) were used to analyze the species composition of intestinal flora and identify significant differences in intestinal microorganisms (Pisano et al. 2023). The MetaCyc database was used to predict the abundance of secondary functional pathways, allowing for the analysis of differential metabolic pathways among different groups.

Statistical analysis of data

All experimental data were analyzed using SPSS software and one-way ANOVA. The results presented in this paper are expressed as Mean ± SD. The p-value < 0.05 was considered statistically significant.

Results

Tupistra chinensis treatment restores damaged tissue structure

H&E staining was performed using jejunum, ileum, and splenic tissues from all three groups. Intact intestinal mucosa, a well-organized tissue structure, and complete, neatly arranged villi were detected in group DB. However, LPS induction resulted in a noticeable disruption in the morphology of the jejunum and ileum, severe intestinal damage, including inflammatory cell infiltration, disrupted tissue structure, and villi characterized by obvious shortening, aggregation, and destruction. After TC polysaccharide treatment, the infected mice retained relatively intact intestinal mucosa and villi. The integrity was markedly higher compared to the LPS group, and the structure was close to normal (Fig. 1a).

Fig. 1.

Morphological alteration in enteric and splenic tissue in mice treated with TC. a: small intestine, b: spleen. It is represented in this figure that the DB group has intact intestinal and splenic architecture. In the LB group, necrotic, damaged intestinal villi, mononuclear infiltration in the intestine, anemic red pulp, and reduced white pulp in the spleen are distinctive, while in KB, near-normal restoration in the intestinal and splenic architecture can be observed

Similarly, spleen H&E staining showed that LPS exposure resulted in the reduction of the spleen’s white pulp and anemia in the red pulp when compared to group DB. The splenic structure of TC-treated mice was approximately restored to its normal architecture (Fig. 1b).

Variation in gut microbiota after TC treatment

In this research, over 190,000, 170,000, and 100,000 raw sequencing reads were obtained from groups DB, LB, and KB, respectively. After the denoising, between 9,000 and 200,000 sequences were left in the sample (Table 1). Differences in species abundance within populations were underscored by α-diversity analysis. α-diversity indices like Chao1, Faith’s PD, Goods coverage, observed species, and Simpson indicated insignificant variations among groups DB, LB, and KB (p > 0.05). However, Pielou’s evenness and Shannon indices indicated significant (p < 0.05) variation in gut microbial diversity, suggesting that LPS induction reduced gut microbial abundance in mice, whereas TC treatment partially restored it to normal (Fig. 2a). The rarefaction and rank abundance curve gradually leveled off, indicating that the sequencing depth was sufficient to perform the analysis (Fig. 2b, c).

Table 1.

The sequenced data of gut microbiome

Sample ID	Input reads	Clean reads	Denoised reads	Merged reads	Non-chimeric reads
KB1	198,942	187,736	186,736	180,951	168,731
KB2	205,068	193,638	192,569	185,912	170,061
KB3	213,498	202,202	200,154	188,259	150,554
LB1	173,609	164,726	163,499	154,978	130,572
LB2	198,801	188,369	187,209	178,458	147,402
LB3	196,546	186,366	185,294	178,363	142,633
DB1	209,886	198,953	198,465	196,056	173,525
DB2	211,718	199,694	198,834	188,224	159,535
DB3	105,640	99,520	98,153	90,110	69,725

Fig. 2.

α-diversity analysis. a: α-diversity index, b: rarefaction curve, c: Rank abundance curve. This figure illustrates that LPS reduced diversity indices like Shannon but not Chao1. Other α-diversity indices represent the significant (p = 0.05) variations in gut microbiota in the KB, LB, and DB groups. Rarefaction and the rank-abundance OTU curve’s gradual flattening indicate that sequencing depth is sufficient to satisfy the experimental requirements for sequencing

The differences in intestinal flora composition among all three groups were represented by β-diversity analysis. Principal Coordinates Analysis (PCoA) and Non-metric Multidimensional Scaling (NMDS) results showed that the microbial community structure in the LPS-induced group differed significantly (p < 0.05) compared to those in the control and treatment groups, underscoring that LPS-induction altered the normal composition of gut microbiota (Fig. 3a, b). The UPGMA bargraph PERMANOVA also indicated significant variations among the three groups (Fig. 3c, d).

Fig. 3.

β-diversity analysis. a: PCoA, b: NMDS, c: UPGMA, d: PERMANOVA across three groups (DB, KB, LB). PCoA plot based on Bray–Curtis distances showing separation of microbial communities among DB (blue), KB (orange), and LB (red) groups. b NMDS plot illustrating community composition differences among the three groups, with shaded areas indicating group clustering. c UPGMA represents the relative abundance of major bacterial genera in each sample, with hierarchical clustering on the left. d PERMANOVA showing distances of KB and LB samples to the DB group centroids, indicating significant differences in community composition between groups. Each point or bar represents an individual sample

The effect of TC treatment on gut microbiome composition

In total, 15 phyla and 211 genera were identified through gut microbiota analysis. The top ten taxa at the phylum, class, order, family, and genus levels are shown in Fig. 4 (a-e). At the phylum level, Bacteroidota (72.62%, 66.64%, 64.44%) and Firmicutes_D (23.19%, 19.97%, 12.73%) were the predominant bacteria in the DB, LB, and KB groups. Notably, Firmicutes_A ranked third in the TC treatment group (12.26%), while it was significantly (p < 0.05) lower in the DB (1.09%) and LB (1.93%) groups. Other phyla, such as Verrucomicrobiota (DB = 1.68%, KB = 5.34%), Campylobacterota (DB = 0.1%, KB = 3.83%), Proteobacteria (DB = 0.24%, LB = 10.67%, KB = 0.12%), Desulfobacterota_I (DB = 0.53%, LB = 0.51%, KB = 0.79%), and Actinobacteriota (DB = 0.38%, LB = 0.38%) 0.19%, KB = 0.13%) were also present across all three groups, but at lower abundance (Fig. 5).

Fig. 4.

Relative abundance of the top 10 bacterial taxa in three sample groups (KB, LB, DB) across different taxonomic levels. Stacked bar plots represent the composition of gut microbiota at the a phylum, b class, c order, d family, and e genus level. Each bar indicates the mean relative abundance (%) of the top-most abundant taxa in each group, with all termed as “others”. Color coding corresponds to the taxa listed in the legends for each panel. These results illustrate shifts in gut microbial community structure and highlight the dominant taxa present across each taxonomic rank

Fig. 5.

Comparison of gut microbiota composition among groups KB, LB, and DB. a Heatmap showing the relative abundance of major bacterial phyla (top) and genera (bottom) across samples, with phylogenetic clustering and color-coded groups (KB: blue, LB: yellow, DB: red). b LEfSe analysis identifying significantly enriched taxa in DB versus KB groups: LDA score (top) and Cladogram (bottom) underscore the differential taxa, with green nodes indicating enrichment in KB and red in DB. The cladogram annotates the taxonomic levels

At the genus level, Phocaeicola_A_858004 and Ligilactobacillus were the main genera in the DB group, accounting for ~ 50%. In group LB, the dominant genera included Phocaeicola_A_858004, Lactobacillus, and Bacteroides_H. The TC-treated group had a higher abundance of Paramuribaculum, Duncaniella, and Alloprevotella; markedly different phyla and genera have been shown in Fig. 6a, b. These results were consistent with the trends observed in the heat map (Fig. 5a). LEfse analysis explored the marker bacteria associated with TC treatment in LPS-induced mice. Additionally, the marker taxa in the TC-treated group included Campylobacterota, Campylobacterales, Campylobacteria, Helicobacter_D, Helicobacteraceae, and COE1 (Fig. 5b).

Fig. 6.

Relative abundance of bacterial taxa in groups DB, KB, and LB. The bar plot shows the mean relative abundance with standard error bars for selected taxa at a phylum and b genus levels. The statistical difference is indicated by asterisks (*p < 0.05)

Alterations in metabolic pathways after TC treatment

A significant (p < 0.05) difference in metabolic pathways among all groups was identified in our study. Five pathways were found to be differentially expressed between the TC treatment group and the LPS induction group. Of these, PWY − 6478 (GDP-D-glycero-&alpha;-D-manno-heptose biosynthesis) and PWY − 7373 (superpathway of demethylmenaquinol-6 biosynthesis II) were significantly (p < 0.05) upregulated after TC treatment. On the other hand, AST − PWY (L-arginine degradation II), THREOCAT − PWY (superpathway of L-threonine metabolism), and PWY − 7377 (cob (II) yrinate a, c-diamide biosynthesis I) showed significant upregulation after LPS induction (Fig. 7a, b).

Fig. 7.

Functional profile of KB and LB groups. a Relative abundance of predicted KEGG pathways, categorized by broad functional classes. b LEfSe analysis comparing pathway enrichment between KB and LB groups, showing LDA scores for significantly different pathways

Discussion

We investigated the protective effect of TC polysaccharides on LPS-induced intestinal inflammation. LPS has been used as a potential inflammatory stimulant in intestinal models (Zhang et al. 2024). Pathological results showed that LPS exposure led to shortened and damaged intestinal villi and mononuclear infiltration, which is consistent with previous studies (He et al. 2023). Previous research indicated that TC extract has anti-inflammatory properties by inhibiting inflammatory cell proliferation (Xiang et al. 2016). We found that TC treatment alleviated intestinal and splenic lesions in mice, restoring tissue structure to near normal. Generally, when the GI barrier is disrupted, the invasion of bacteria and toxins, especially LPS, into the blood leads to associated damage (Ghosh et al. 2020a)., as disrupted splenic architecture, oxidative stress, and metabolic and immune disruptions (Ghosh et al. 2020b); however, TC treatment mitigated enteritis and reduced the splenic damage post-LPS-administration. Previous studies have indicated that intestinal inflammation disrupts the composition of the gut microbiota (Dong et al. 2019; Wu et al. 2019), consistent with our findings that LPS exposure reduced microbial diversity and altered gut microbiota in mice.

We found that Firmicutes_A and Firmicutes_D were significantly different (p < 0.05) among the three groups. Firmicutes play a crucial role in host nutrition and metabolism through the synthesis of short-chain fatty acids (SCFAs) (Ma et al. 2020). SCFAs (propionate, butyrate, acetate) are the major byproduct of gut bacteria formed after the breakdown of complex, indigestible carbohydrates, are recognized as vital energy materials, have anti-cancer and anti-inflammatory characteristics and can lower cholesterol and fat storage, regulate the pH of the intestine, and also avoid predatory harmful germs from entering and sticking (Lee et al. 2020; Moniri and Farah 2021). Proteobacteria were found to be noticeably increased in group LB in our study. This phylum includes opportunistic pathogens like Salmonella and E. coli (Bradley and Pollard 2017). Hence, LPS-challenge increased pathogenic gut microbes. Verrucomicrobiota, which was found to be highest in the KB group, has a significant anti-inflammatory effect (Wang et al. 2025). Actinobacteria were found to be noticeably increased in the DB, followed by the LB group. This increases intestinal homeostasis and carbohydrate breakdown, boosts immune reactions, and reduces inflammation (Ghosh et al. 2023). Also, as a probiotic, it prevents a range of resistant pathogenic bacteria (Binda et al. 2018). Its increase in the LPS-challenged group may indicate the compensatory mechanism after LPS-induced damage.

Through LEfse analysis, it was identified that eight phyla and twelve genera differed between the TC treatment group and the LPS-induced group. Beneficial bacteria such as Alloprevotella, Paramuribaculum, Duncaniella, CAG 485, Mailhella, Prevotella, and Odoribacter_865974 had higher abundance in the TC treatment group. Alloprevotella is often considered a probiotic (Kong et al. 2019; Xie et al. 2022). Paramuribaculum, a core bacterium in the intestinal microbiota, has been linked to the treatment of alcoholic liver disease in mice (Fang et al. 2023). Duncaniella, known for its anti-inflammatory properties, has been shown to help combat intestinal inflammation and was also found in the intestinal flora of mice fed Physalis alkekengi (Yang et al. 2023). CAG: 485, a key bacterium in the Prevotella genus, is known for balancing health and disease conditions, and it has been found to affect the efficacy of PD-1 antibody immunotherapy in Microsatellite Stable (MSS) colorectal cancer in previous studies (Xu et al. 2020b). Prevotella is generally associated with a healthy plant-based diet, acting as a probiotic, and its decline has been linked to the occurrence of various diseases (Tett et al. 2021). Mailhella, a newly isolated bacterial strain from the feces of healthy individuals (Ndongo et al. 2017), has also been found to improve antioxidant capacity (Shao et al. 2023). In previous studies, Odoribacter_865974 was found to be an important microorganism for maintaining intestinal homeostasis and has been used to counter intestinal inflammation (Lima et al. 2022; Zhou et al. 2022).

Interestingly, the LPS-induced group showed an increased abundance of Bacteroides_H, UBA3263, and Erysipelatoclostridium. Bacteroides_H, gut commensal bacteria, have been associated with an increased risk of severe malaria (Mandal et al. 2023). UBA3263 (formerly Porphyromonadaceae bacterium) has been linked to a higher risk of metabolic aging-related diseases (Künstner et al. 2022). Erysipelatoclostridium, a potential pathogen, was found to be associated with colonic diseases (Yu et al. 2023b), and its increase after LPS induction is an indicator of inflammation. Hence, we concluded that LPS exposure reduces intestinal microbial diversity and promotes the growth of notorious pathogenic bacteria in mice, while TC polysaccharides partially restore intestinal dysbiosis by increasing beneficial bacteria. This aligns with the previous studies demonstrating the anti-inflammatory and gut microbiota modulatory effects of TC (Xiang et al. 2016). The mechanism of how TC treatment helps alleviate LPS-induced enteritis is through a robust and healthy microbial shift post-TC administration (Sommer et al. 2017).

Further, we identified the changes in metabolic pathways among the three groups of mice to understand the effect of TC treatment on LPS-induced gut inflammation. The upregulation of metabolic pathways related to energy production suggests that LPS may lead to disrupted energy metabolism (Yu et al. 2023a). Vitamin K2 (VK2) is a group of menadione derivatives with strong antioxidant properties, primarily synthesized by the intestinal flora (Smajdor et al. 2023). It activates several key proteins in the human body, including coagulation factors, osteocalcin, and matrix Gla protein, exerting various biological effects such as promoting coagulation function, promoting bone metabolism, reducing cancer, regulating blood sugar, protecting nerves, and preventing vascular sclerosis (Li et al. 2019; Su et al. 2022; Jin et al. 2023). In the KB group, the super pathway of demethylmenaquinol-6 biosynthesis II was upregulated, suggesting an increase in vitamin K synthesis. Moreover, TC treatment increased the abundance of beneficial bacteria in the intestine, which could further contribute to the synthesis of VK2 and may explain why TC alleviates oxidative stress and LPS-induced intestinal inflammation.

In summary, TC treatment can alleviate LPS-induced intestinal inflammation by increasing the abundance of beneficial gut bacteria, regulating energy metabolism, and increasing VK2 synthesis. However, fine underlying details need to be further explored. A positive control group using standard anti-inflammatory drugs (e.g., dexamethasone) would strengthen comparative efficacy. We focused on evaluating TC polysaccharides as a novel natural alternative. Future studies should focus on direct comparisons with other pharmaceuticals. Also, we utilized a 14-day LPS challenge model to evaluate acute inflammation, while informative, longer-term studies are needed to assess TC’s effects on chronic IBD, including safety and sustained microbiota modulations.

Conclusion

In conclusion, TC polysaccharides alleviate LPS-induced intestinal inflammation in three primary mechanisms: restoring the structure of disrupted intestinal flora, increasing intestinal flora diversity, and beneficially modulating metabolic pathways. Additionally, TC treatment can repair intestinal and splenic damage. Our study underscores LPS-induced enteritis and suggests that these polysaccharides can relieve intestinal inflammation, providing a new approach for the treatment of enteritis as an alternative to potential antibiotics and decreasing the risk of AMR.

Author contributions

MA, MML, and KL, research idea and methodology. MA, JDC, CX, and QH, reagents, materials, and analysis tools. MA, JDC, MML, and KL wrote the original draft and prepared it. KL, MA, and MML, writing-review and editing. KL, visualization, and supervision. All authors contributed to the article and approved the submitted version.

Funding

The study was supported by the National Natural Science Foundation of China (32102692).

Data availability

The raw data in this study were deposited in the NCBI database under accession number: PRJNA1106752.

Declarations

Conflict of interest

No potential conflict of interest was reported by the authors.

Ethical approval

This study was guided and approved by the ethics committee of Nanjing Agricultural University (NJAU.No20240226021).

Consent to participate

Not Applicable.

Consent for publication

The authors declare no conflict of interest.