Ligilactobacillus salivarius alleviated intestinal damage induced by Salmonella in mice via regulating microbiota

Abstract

Background

Salmonella is a major foodborne etiological agent with serious drug resistance, and the pursuit of novel therapeutic agents for the prevention and control of Salmonella infections is of paramount significance.

Purpose

This study aimed to investigate the regulatory effects of Ligilactobacillus salivarius (L. salivarius) on intestinal damage in mice infected with Salmonella.

Methods

Thirty healthy, four-week-old ICR mice were divided into three groups: a control group, an infection model group, and a L. salivarius treatment group. Specifically, mice in the treatment group were orally administered L. salivarius for 15 days before being infected with Salmonella. Following a 24-hour post-infection period, samples were collected from the duodenum, jejunum, ileum, cecum, colon, and rectum. These samples were analyzed for bacterial load and histopathological changes, comparing the model and treatment groups. Additionally, rectal contents were subjected to 16 S rRNA and ITS sequencing.

Results

The findings revealed that L. salivarius mitigated the weight loss and organ weight reduction. It also significantly decreased Salmonella counts in the intestinal tract and alleviated the associated intestinal mucosal damage and inflammation. Notably, L. salivarius influenced gut microbiota composition by reducing the abundance of beneficial bacteria such as Coprocola and Acutalibacter, while simultaneously lowering harmful bacterial populations, including Angelakisella, UBA3263, Glomeromycota, Kickxellomycota, Nigrospora, and Fusarium.

Conclusions

Collectively, these findings suggest that L. salivarius protects against Salmonella-induced intestinal damage by reducing bacterial load, mitigating intestinal injury, and modulating gut microbiota composition.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-025-04277-w.

Introduction

Salmonella is a major etiological agent of foodborne illnesses [1], posing a significant global zoonotic threat through both direct and indirect transmission routes [2]. Taxonomically, Salmonella belongs to the family Enterobacteriaceae, comprises two main species: Salmonella enterica and Salmonella Bongori [3, 4], with S. enterica being particularly pathogenic to both humans and livestock [5]. Previous studies have demonstrated that broiler chickens and eggs act as key vectors for Salmonella transmission, threatening food safety and hygiene [6, 7]. Notably, Salmonella possesses the ability to invade host cells and persist intracellularly, exhibiting high levels of antibiotic resistance. A large-scale survey of 18,334 samples in China revealed that the majority of isolated Salmonella strains exhibited drug resistance, with over half demonstrating multidrug resistance [8]. The persistence of Salmonella as an uncontained public health threat is attributed to its broad host range, high incidence rates, and increasing antibiotic resistance [9]. Consequently, the pursuit of novel therapeutic agents for the prevention and control of Salmonella infections is of paramount significance.

Among potential biotherapeutics, L. salivarius is an important probiotic with broad-spectrum antimicrobial properties. It can effectively prevent the excessive growth of pathogenic bacteria, enhance the intestinal resistance to pathogen invasion, and improve epithelial barrier function [10–12]. As a natural resident of the host microbiota, L. salivarius helps maintain microbial balance and suppresses the proliferation of pathogenic bacteria through multiple mechanisms. Certain strains of L. salivarius have been proven to have strong antibacterial effects by secreting bacteriocins, organic acids, and other antimicrobial substances [13]. For instance, L. salivarius UCC118 produces Abp118, a bacteriocin that exhibits broad-spectrum activity against numerous foodborne pathogens such as Listeria monocytogenes and Staphylococcus aureus [14, 15]. Similarly, the L. Salivarius DPC6005 strain, isolated from pig intestine, exhibits comparable antibacterial activity [16]. In another study, Eileen et al. identified additional bacteriocins, such as sialolin L and T [17], produced by L. salivarius DPC6488, which demonstrate urogenital and gastrointestinal tract pathogens, including Enterobacter faecalis and Campylobacter species [18–22].

Beyond its antimicrobial properties, L. salivarius contributes to gut health by colonizing the intestinal mucosa and forming biofilms that prevent the adhesion and proliferation of pathogenic bacteria [23, 24]. It competes for intestinal adhesion sites, thereby limiting pathogen colonization and supporting epithelial integrity. L. salivarius can also inhibit the growth and reproduction of other pathogenic microorganisms by competing for intestinal adhesion sites. Notably, L. salivarius exhibits strong acid and oxidative stress tolerance, allowing it to thrive in low-pH, high-oxygen environments, providing a competitive advantage against pathogenic bacteria [25, 26]. Additionally, L. salivarius interacts with other microorganisms, such as Enterococcus faecium and other Lactobacillus species, producing volatile organic acids and hydrogen peroxide to inhibit pathogenic bacterial growth [27, 28]. By influencing metabolic and biosynthetic pathways, L. salivarius secretes metabolites, including disaccharides and pyruvate, that slow down the growth rate of pathogenic bacteria, further reinforcing its protective effects [29–31].

This study aimed to establish an in vivo murine model of Salmonella infection to elucidate the prophylactic efficacy of L. salivarius against the intestinal damage caused by Salmonella. This was accomplished by assessing alterations in body weight, bacterial burden within various organs, intestinal histopathology, and gut microbiota composition. Finally, these findings seek to contribute to the development of novel strategies for the prevention and management of Salmonella-induced diarrhea and to provide a theoretical framework for the advancement and utilization of probiotic-based therapies.

Materials and methods

Experiment design

Seven days prior to the start of the experiment, 30 male Institute of Cancer Research (ICR) mice (four weeks old, approximately 20 g each) were acquired from Qinglongshan Animal Breeding Farm in Nanjing, China. The mice underwent a seven-day adaptive feeding period to acclimate to the experimental conditions. Following acclimatization, the mice were randomly assigned to three groups: the control group (C), the Salmonella infection model group (S), and the L. salivarius treatment group (T), with 10 mice per group. Mice in the treatment group received a daily oral gavage of 0.2 ml of L. salivarius (PP859184) suspension at a concentration of 1 × 10^9 CFU/ml in normal saline. The control and model groups were gavaged with an equivalent volume (0.2 ml) of normal saline.

On the fifteenth day of the experiment, mice in the model and treatment groups were orally challenged with 0.2 ml of Salmonella enterica serovar Typhimurium (ATCC 14028) at a concentration of 1 × 10^8 CFU/ml suspended in Luria-Bertani (LB) medium (Solarbio, Beijing, China). The control group received an equivalent volume (0.2 ml) of sterile LB medium. Following a 24-hour post-infection period, all mice were euthanized by cervical dislocation (Fig. 1a). Tissue samples were collected from the duodenum, jejunum, ileum, cecum, and rectum for histopathological analysis. Additionally, samples from the duodenum, jejunum, ileum, cecum, and colon were harvested to assess bacterial load. Rectal contents were collected for subsequent 16 S rRNA gene and ITS sequencing analysis.

Fig. 1.

Influence of L. salivarius on Salmonella infection. a: Experimental design; b: Body weight comparison of mice before dissection; c: Organ weight. Data are presented as mean ± SEM. C: Control group, S: Infection model group (Salmonella-infected), T: L. salivarius treatment group. ***p < 0.001, **p < 0.01, *p < 0.05

Histopathological examination

The intestinal tissues of the experimental animals were preserved with 4% paraformaldehyde and processed in hematoxylin and eosin (H&E) staining (Wuhan Pinofey Biotechnology Co., LTD., China) according to the previous study [32, 33]. The tissue sections were examined by histopathological analysis using an Olympus GX41 microscope (Olympus Co., Japan).

Bacterial load in organs

Tissues from the duodenum, jejunum, ileum, cecum, and colon were aseptically collected in a sterile environment. Each tissue sample was placed into a sterile 4 mL centrifuge tube containing 1 mL of sterile phosphate-buffered saline (PBS) and 1 mm zirconia grinding beads. The samples were homogenized using a bead-beater homogenizer (Qiagen TissueLyser II) for 2 min at 4 °C and 70 Hz. Afterward, 100 µL of the supernatant was serially diluted in PBS, and 100 µL of the appropriately diluted bacterial suspension was evenly spread onto agar plates. The plates were then incubated at 37 °C for 16–18 h for colony counting. Each group and dilution concentration were plated in triplicate to ensure accuracy.

Intestinal flora sequencing

Genomic DNA was extracted and quantified from each sample via a Nanodrop spectrophotometer. The V3–V4 variable region of the 16 S rDNA gene in bacteria was amplified with the universal primers F: ACTCCTACGGGAGGCAGCA and R: GGACTACHVGGGTWTCTAAT. Likewise, the ITS_V1 region was amplified using the universal primers F: CTTGGTCATTTAGAGGAAGTAA and R: GCTGCGTTCTTCATCGATGC. The amplified PCR products were visualized through 2% agarose gel electrophoresis, followed by excision and purification of the target fragments. Quantification of the DNA was conducted using a Microplate Reader (BioTek FLx800) along with the Quant-iT PicoGreen dsDNA Assay Kit. Subsequently, the samples were combined based on the desired sequencing depth. Library preparation was carried out using the Illumina TruSeq Nano DNA LT Library Prep Kit, and sequencing was executed on a NovaSeq 6000 system, employing the NovaSeq 6000 SP Reagent Kit (500 cycles) for paired-end sequencing at 2 × 250 bp. The sequencing was facilitated by Bioyi Biotechnology Co., Ltd., located in Wuhan, China.

The raw sequencing data underwent rigorous quality filtering using QIIME2 software (version 1.9.1). This process involved eliminating low-quality sequences, specifically those shorter than 200 bp, sequences containing primer mismatches, and chimeric reads. Subsequently, the filtered sequences were grouped into Operational Taxonomic Units (OTUs) based on a 97% similarity threshold.

The α-diversity metric for gut microbiota was determined from the distribution of OTU relative abundances within each sample. Additionally, β-diversity indices were used to assess the comparability and variations in gut microbiota compositions across the samples. Furthermore, rarefaction curves were plotted for each sample to estimate sequencing depth and completeness. Statistical analyses were carried out using GraphPad Prism software (version 9.0c). The data were presented as mean ± SEM, and statistical significance was determined at p < 0.05.

Results

Body weight and organ weight of mice

Compared to the control group, mice in both the model and treatment groups exhibited varying degrees of weight loss. Specifically, the model group showed a significant reduction in body weight (p < 0.001), while the treatment group demonstrated a lesser degree of weight loss compared to the control group but a notable increase relative to the model group (Fig. 1b). In terms of organ weights, significant reductions were observed in the spleen (p < 0.05), kidney (p < 0.05), and liver (p < 0.001) in both the model and treatment groups compared to the control group. Although the differences in organ weights between the model and treatment groups were not statistically significant, the treatment group exhibited slightly higher organ weights than the model group (Fig. 1c).

Bacterial load in intestinal organs

Compared to the control group, the bacterial load in all intestinal segments was elevated in both the model and treatment groups. Notably, the bacterial load in the duodenum, ileum, and colon of the model group was significantly higher (p < 0.01). However, following treatment with L. salivarius, the bacterial load in the duodenum (p < 0.001) and colon of the treatment group was significantly reduced (Fig S1).

Intestinal histopathological changes

Following colonization in the intestinal tracts of mice, Salmonella disrupts the inflammatory regulation mechanism, leading to damage to intestinal epithelial cells and subsequent structural deterioration of the intestinal tract [34]. H&E staining of each intestinal segment revealed that the villi structure in the normal control group remained intact, with no significant damage observed. In contrast, the infected model group exhibited severe swelling and damage and damage in the duodenal and ileal villi, characterized by disorganized villous epithelial cells, swollen lamina propria cells, and signs of degeneration and necrosis. Additionally, numerous damaged and shed villous fragments and exudates accumulated in the center of the intestinal lumen, along with infiltration of inflammatory cells. In the L. salivarius treatment group, although the villi were slightly swollen and damaged compared to the normal control group, the overall structure was more intact than in the infection model group. Only minor damage was observed at the tips of the villi, and inflammatory cell infiltration was noticeably reduced. These findings suggest that pretreatment with L. salivarius can mitigate intestinal epithelial damage caused by Salmonella infection in mice to some extent (Fig. 2). After Salmonella challenge, the villus height and V/C in the duodenum, jejunum and ileum of mice were significantly reduced, while the crypt depth was significantly increased. In contrast, the villus height and V/C in the Lactobacillus salivary group were significantly increased, and the crypt depth was significantly reduced (p < 0.05), this suggests that Lactobacillus salivary treatment can significantly alleviate the damage to the small intestinal villi structure caused by Salmonella (Fig. 3).

Fig. 2.

Representative images of H&E staining of intestinal segments. a: Control group (C); b: Infection model group (Salmonella-infected, S); c: L. salivarius treatment group (T)

Fig. 3.

The height of intestinal villi in each segment of the small intestine, the depth of crypts, and the ratio of the height of intestinal villi to the depth of crypts. C: Control group, S: Infection model group (Salmonella-infected), T: L. salivarius treatment group. ***p < 0.001, **p < 0.01, *p < 0.05

Analysis of intestinal bacterial diversity

High-throughput sequencing

A total of 2,162,583 raw reads were generated through high-throughput sequencing of 16 S rRNA and ITS regions. After rigorous quality control measures, including denoising, splicing, and chimera removal using DADA2’s denoise-paired function, 1,701,811 high-quality sequences were retained. Once denoising was completed for all libraries, the Amplicon Sequence Variant (ASV) feature sequences and ASV tables were integrated, with singleton ASVs being excluded. Ultimately, a total of 1,701,520 ASVs were obtained. (C = 577819, S = 559509, T = 564192) (Table 1).

Table 1.

Microflora sequencing results for each sample

Sample ID	Input	Filtered	Denoised	Merged	Non-chimeric	Non-singleton
CS1	146,823	128,000	124,641	113,063	112,764	112,763
CS2	138,733	122,721	121,676	116,514	115,699	115,693
CS3	159,539	139,933	139,488	136,543	135,871	135,869
CS4	159,796	138,491	137,159	124,494	112,436	112,373
CS5	134,531	117,789	116,384	106,730	101,146	101,121
SS1	139,307	121,159	117,878	105,702	105,608	105,608
SS2	141,089	122,405	121,209	114,716	111,097	111,080
SS3	139,157	121,206	120,464	116,442	116,337	116,337
SS4	138,214	121,863	120,032	110,618	107,677	107,662
SS5	160,089	140,531	138,839	124,846	118,860	118,822
TS1	135,129	117,561	117,237	115,501	115,211	115,210
TS2	159,499	139,105	138,737	136,509	136,369	136,367
TS3	121,248	106,149	105,789	103,392	103,183	103,182
TS4	145,397	127,456	125,826	113,509	104,741	104,680
TS5	144,032	126,329	124,603	112,818	104,812	104,753

The rarefaction curve, with the Chao1 diversity index on the vertical axis, stabilizes as sequencing depth increases, indicating that the sequencing depth ranges from 99.98 to 100%, effectively covering all species present (Fig S2 a, c). This confirms that the sequencing results accurately reflect the true microbial composition of the test samples. Additionally, the abundance rank curve exhibits a smooth gradient, indicating a uniform distribution of species within each sample (Fig S2 b, d).

Analysis of intestinal flora diversity

In this research, the diversity of intestinal microbiota was evaluated employing various indices: richness was quantified using the Chao1 and Observed Species indices, diversity was assessed by the Shannon and Simpson indices, phylogenetic diversity was gauged by Faith’s PD index, and evenness was determined by Pielou’s Evenness index. Additionally, the Good’s Coverage index was utilized to assess the sequencing depth. The bacterial diversity analysis revealed a significant increase in the Chao1 (p = 0.013) and the Observed_species (p = 0.014) indices in the control group and treatment groups, indicating enhanced richness of intestinal flora, while the other indices showed no significant differences (Fig S3 a). However, compared with model group, the control and treatment groups exhibited significantly lower values for the Chao1 (p = 0.031), Observed_species (p = 0.031), Pielou_e (p = 0.016) and Shannon (p = 0.0074) indexes, suggesting that Salmonella infection led to significant changes in the diversity of intestinal flora of mice (Fig S3 b).

Beta diversity among groups was evaluated using Principal Coordinate Analysis (PCoA), employing the Bray-Curtis distance metric, and Non-metric Multidimensional Scaling (NMDS), based on the Jaccard similarity index. The PCoA results demonstrated a clear separation between the Salmonella-induced model group and the control and treatment groups, indicating significant alterations in intestinal microbial structure due to Salmonella infection. Similarly, NMDS analysis showed a stress value of < 0.2, confirming that the beta diversity analysis was accurate and reliable in reflecting differences between samples (Fig. 4 a, b). These findings suggest that Salmonella infection profoundly impacts the composition and structure of the intestinal microbiota in mice.

Fig. 4.

β-diversity analysis of gut microbiota. a: Bacterial β-diversity; b: Fungal β-diversity. C: Control group; S: Infection model group (Salmonella-infected); T: L. salivarius treatment group

Intestinal bacterial composition analysis

To analyze the bacterial composition at different taxonomic levels, the top 10 species with the highest relative abundance in each sample were selected, and a group average species distribution map was used to visualize the species composition across groups. At the phylum level, Bacteroidota was the predominant phylum in all groups (C = 48.48%, S = 52.61%, T = 40.26%), followed by Firmicutes_A (C = 13.72%, S = 11.73%, T = 13.72%), Firmicutes_D (C = 10.76%, S = 14.48%, T = 14.06%), and Proteobacteria (C = 11.39%, S = 8.37%, T = 12.48%) (Fig. 5 a). At the class level, Bacteroidia remained dominant across all groups (C = 48.41%, S = 52.60%, T = 40.14%), along with Clostridia_258483 (C = 13.74%, S = 11.65%, T = 13.73%), Bacilli (C = 10.77%, S = 14.49%, T = 14.08%), and Gammaproteobacteria (C = 7.41%, S = 6.68%, T = 8.46%) (Fig. 5 b).

Fig. 5.

Relative abundance of bacterial species at different taxonomic levels. a: Phylum; b: Class; c: Order; d: Family; e: Genus. C: Control group, S: Infection model group (Salmonella-infected), T: L. salivarius treatment group

At the order level, Bacteroidales (C = 46.80%, S = 51.94%, T = 38.78%) and Oscillospirales (C = 4.47%, S = 5.93%, T = 6.13%) were the dominant orders in all groups. Lachnospirales was shared as a dominant order between the control and treatment groups (C = 7.06%, T = 5.34%). Erysipelotrichales was shared as a dominant order between the model and treatment groups (S = 8.23%, T = 5.17%). Notably, Campylobacterales was uniquely dominant in the model group (4.23%) (Fig. 5 c). At the family level, Muribaculaceae (C = 21.01%, S = 30.92%, T = 17.50%) and Bacteroidaceae (C = 15.82%, S = 13.63%, T = 14.00%) were the dominant families across all groups (Fig. 5 d). At the genus level, the dominant genera in the control group were Paramuribaculum (5.40%), Bacteroides_H (8.46%), Duncaniella (6.13%), Prevotella (6.18%), and Bacteroides_H (8.46%). In the model group, the dominant genera were Paramuribaculum (12.20%), Alloprevotella (7.05%), UBA3263 (5.31%), and Faecalibaculum (5.62%). In the treatment group, the dominant genera were Paramuribaculum (8.28%), Alloprevotella (7.33%), Bacteroides_H (4.23%), and Dubosiella (4.80%) (Fig. 5 e).

To further analyze differences in bacterial composition at the genus level, multiple t-tests were employed. Specifically, in comparison to the control group, the model group exhibited a significant increase in the relative abundance of UBA3263 (p < 0.01) and Parasutterella (p < 0.05), while COE1 significantly decreased (p < 0.05). Additionally, within the treatment group, a significant decrease was observed in the relative abundance of CAG-269. When comparing the model group to the treatment group, the relative abundances of Coprocola and Acutalibacter were markedly decreased in the model group (p < 0.05), whereas the relative abundance of CAG-605 and Angelakisella were significantly increased (p < 0.05) (Fig S4).

Linear Discriminant Analysis (LDA) histograms were used to visualize the labeled species and their relationships within each group. Conversely, taxonomic lineage maps illustrated their hierarchical distribution. Notably, significant compositional differences were observed exclusively in the model group, particularly at the genus level, highlighting Faecalibaculum, UBA3263, UBA737, and Blautia_A_141781 as distinct markers (Fig. 6 ).

Fig. 6.

Linear discriminant analysis effect size (LEfSe) and LDA scores for intestinal bacterial microbiota. C: Control group; S: Infection model group (Salmonella-infected); T: L. salivarius treatment group

Intestinal fungal composition analysis

At the phylum level, Ascomycota (C = 78.75%, S = 75.38%, T = 81.41%) and Basidiomycota (C = 12.66%, S = 13.46%, T = 12.34%) were the predominant fungal phyla across all groups (Fig. 7 a). At the class level, the most abundant fungal classes included Saccharomycetes (C = 30.64%, S = 22.71%, T = 44.39%), Sordariomycetes (C = 22.08%, S = 24.19%, T = 12.99%), and Dothideomycetes (C = 15.37%, S = 11.81%, T = 9.39%) (Fig. 7 b). Shifting focus to the order level, Saccharomycetales (C = 31.12%, S = 23.15%, T = 45.27%) and Hypocreales (C = 11.29%, S = 11.95%, T = 5.64%) exhibited high relative abundances across all groups (Fig. 7 c). At the family level, Saccharomycetales_fam_Incertae_sedis (C = 20.89%, S = 12.15%, T = 34.15%) was the most dominant family in all groups (Fig. 7 d). Lastly, at the genus level, Candida (C = 22.52%, S = 11.37%, T = 35.08%) emerged as the predominant strain in all groups (Fig. 7 e).

Fig. 7.

Relative abundance of fungal species at different taxonomic levels. a: Phylum; b: Class; c: Order; d: Family; e: Genus. C: Control group, S: Infection model group (Salmonella-infected), T: L. salivarius treatment group

To analyze differences in fungal composition between groups at the phylum and genus levels, multiple t-tests were performed. At the phylum level, statistical significance was observed in the relative abundances of Glomeromycota (p < 0.01) and Kickxellomycota (p < 0.05), with both being notably more abundant in the model group compared to the treatment group (Fig S5 a). At the genus level, compared to the control group, the model group exhibited a significant increase in Pseudeurotium, Ramicandelaber, Botryderma, Thermomyces, Acremonium, and Coniochaeta (p < 0.05). Similarly, compared to the treatment group, the model group showed a significant increase in Fusarium, Xenodidymella, Wallemia, Ramicandelaber, Botryoderma, Thermomyces, Acremonium, and Nigrospora (p < 0.05). Notably, the model group exhibited a statistically significant decrease in the relative abundance of Candida compared to the treatment group (p < 0.01) (Fig S5 a).

LEfSe analysis revealed the most abundant taxa distinguishing the three groups. At the genus level, the control group was characterized by Cercospora as the key differentiating species. In contrast, the model group was distinguished by Thermomyces, Botryoderma, and Acremonium, which were particularly notable genera. For the treatment group, Rhodotorula emerged as the unique species at the genus level (Fig. 8 ).

Fig. 8.

Linear discriminant analysis effect size (LEfSe) and LDA scores for intestinal fungal microbiota. C: Control group, S: Infection model group (Salmonella-infected), T: L. salivarius treatment group

Discussion

Salmonella readily contaminates animal-derived foods, posing a significant threat to public health. Currently, antibiotics are primarily used to treat Salmonella infections; however, the improper use of antibiotics can lead to the emergence of drug-resistant bacteria, disrupt the intestinal barrier function, and cause dysbiosis of the gut microbiota [35]. L. salivarius is an intestinal probiotic bacterium that plays a pivotal role in inhibiting and regulating intestinal pathogens. Wang et al. demonstrated that L. salivarius could inhibit the growth of Salmonella pullorum [36]. Similarly, other studies have reported that L. salivarius strain CPU-01 mitigates temozolomide-induced intestinal mucosal inflammation by modulating gut microbiota, maintaining intestinal barrier integrity, and inhibiting the release of pro-inflammatory cytokines [37].

In this study, we investigated the protective efficacy of L. salivarius against a Salmonella enteritis model and elucidated its underlying mechanism. Our findings revealed that mice infected with Salmonella exhibited a notable decrease in body weight, accompanied by a significant reduction in the weight of organs such as the liver, spleen, and kidney. These observations were in concordance with the results reported by Pang et al. [34]. However, pretreatment with L. salivarius mitigated body weight loss observed in the model group. The assay assessing bacterial load in organs revealed that the intestinal bacterial load was significantly elevated in the infection model group compared to the control group. Importantly, after pretreatment with L. salivarius, the bacterial load in the treated group, while still higher than that of the control group, was notably reduced compared to the model group. Consistently, He et al. observed that oral administration of L. salivarius XP132 significantly decreased the Salmonella content in chicken intestines and effectively prevented both vertical and horizontal transmission of Salmonella [38]. In the current study, histopathological analysis revealed severe damage to the intestinal villi in the Salmonella-infected group, with extensive epithelial shedding and inflammatory infiltration. However, pretreatment with L. salivarius PP859184 alleviated these pathological changes, findings that corroborate previous studies by Pang et al. [34].

Probiotics exert beneficial effects by colonizing the gut, outcompeting pathogens, and disrupting microbial signaling. In this study, 16 S rRNA and ITS sequencing revealed notable differences in gut microbiota composition at the genus level between Salmonella-infected, control, and treatment groups, despite no significant phylum-level changes. The genus UBA3263 (Porphyromonadaceae) was significantly reduced in infected mice. This aligns with Zhang et al. [36], who reported the involvement of Porphyromonas in inflammatory diseases, suggesting Salmonella may suppress protective commensals. Acutalibacter, also decreased post-infection, has been shown to counteract colitis-associated colorectal cancer [39], indicating a loss of beneficial microbes under pathogenic stress. Angelakisella, another reduced genus, was previously found to negatively correlate with key genes in colorectal cancer [40], reinforcing its potential protective role. Coprocola, a known butyrate producer [38], showed altered abundance, which may reflect compromised gut barrier integrity. Parasutterella, linked to metabolic and inflammatory disorders [37], was also affected, supporting its role as a gut health indicator. These microbial shifts suggest that Salmonella disrupts beneficial taxa, while probiotic treatment may help restore microbial balance. Our findings correlate with prior studies and support the therapeutic potential of probiotics in modulating infection-induced dysbiosis.

Fungi in the gut play a critical role in immune regulation and microbial homeostasis [39]. Some studies have shown that in digestive diseases such as inflammatory bowel disease (IBD), colorectal cancer, and liver cirrhosis, the intestinal fungal community becomes dysregulated [40–42]. At the phylum level, the relative abundance of Glomeromycota and Kickxellomycota was significantly elevated in the infected model group. Luan et al. found that Glomeromycota is the dominant phylum in adenomas and adjacent tissues of colorectal cancer patients through deep sequencing of fungal microbiota in biopsy samples [43]. Similarly, Lan et al. investigated the composition and changes in intestinal fungi in healthy and diarrheic horses and observed a downward trend in Kickxellomycota during equine diarrhea [44]. At the genus level, compared with the model group, the abundance of Fusarium was significantly reduced in the treatment group. The mycotoxin T-2, produced by Fusarium species, induces intestinal inflammation in livestock and poultry, posing a significant threat to grain food and feed safety [45]. Additionally, Tahliyah et al. found that fungal variants from the Thermomyces genus are strongly associated with metabolic disorders and weight gain [46]. Moreover, Qiu et al. reported changes in mucosa-associated fungal flora in patients with ulcerative colitis and found that Nigrospora was positively correlated with the expression of pro-inflammatory cytokines [47].

Finally, these findings suggest that L. salivarius effectively mitigates Salmonella-induced gut dysbiosis by restoring bacterial and fungal homeostasis, reducing pathogenic load, and preserving intestinal barrier integrity. Therefore, these results provide strong evidence for the potential application of L. salivarius as a probiotic intervention against Salmonella infections.

Conclusion

In conclusion, L. salivarius PP859184 effectively mitigates weight loss and organ weight reduction caused by infection with Salmonella enterica serovar Typhimurium (ATCC 14028), reduces the bacterial load in intestinal organs, and significantly alleviates intestinal mucosal damage and inflammation induced by this Salmonella serovar. In addition, L. salivarius PP859184 modulates gut microbiota by decreasing the abundance of intestinal probiotics such as Coprocola and Acutalibacter, while also reducing the presence of harmful microorganisms such as Angelakisella, UBA3263, Glomeromycota, Kickxellomycota, Nigrospora, and Fusarium. These findings provide a new strategy for the prevention and management of diarrhea caused by S. enterica serovar Typhimurium in mice and lay a theoretical basis for further research on the protective mechanisms of L. salivarius PP859184 against this and other Salmonella serovars. Given the diverse pathogenic mechanisms of Salmonella serovars, additional studies are needed to evaluate the efficacy of L. salivarius PP859184 against other serovars, such as S. enterica serovar Enteritidis or S. pullorum, to confirm broader applicability.

Authors’ contributions

XHL, QH and KL: conceptualization and methodology. CX, MA, LLG, MS and Qudratullah: reagents, materials, and analysis tools. XHL, QH and CX original draft writing and preparation. XHL and KL: review and editing. KL: visualization and supervision. All authors reviewed and approved the final manuscript.

Funding

This study was funded by the Innovation Capability Enhancement Project of technology-based small and medium-sized enterprises of Shandong Province (2023TSGC0235) and Jinan Municipal Strategy Project for City-University Integrated Development (JNSX2024060).

Data availability

All raw sequence data from mice were deposited in the NCBI Sequence Read Archive database under accession number: PRJNA1230988 and PRJNA1230870.

Declarations

Ethics approval and consent to participate

All procedures performed in this research were approved by the Laboratory Animal Welfare and Ethics Committee of Nanjing Agricultural University (NJAU.No20240910164). All procedures involving animals in this study were in accordance with the guidelines of the National Institutes of Health and ARRIVE guidelines (https://arriveguidelines.org).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.