Skip to main content
NCBI home page
Microbial Biotechnology logoLink to Microbial Biotechnology
. 2026 Jan 16;19(1):e70300. doi: 10.1111/1751-7915.70300

Multi‐Omics Analysis Reveals the Potential Preventive Mechanism of Lactobacillus salivarius Li01 Against L‐Arginine‐Induced Acute Pancreatitis in Mice

Jiamin Duan 1, Jing Lou 2, Feiyu Wang 2, Huiyong Jiang 2,✉, Longxian Lv 2,3,✉, Hongwei Fu 1,✉
PMCID: PMC12810401  PMID: 41543515

ABSTRACT

Acute pancreatitis (AP) pathogenesis involves gut microbiota dysbiosis. Although Lactobacillus salivarius Li01 (Li01) is a well‐characterised probiotic strain, its specific role in AP via the ‘gut‐pancreas axis’ remains unclear. Li01 pretreatment via oral gavage was assessed in an L‐arginine‐induced AP mouse model. The gut microbiota composition and abundance were analysed via 16S rRNA sequencing, complemented by untargeted faecal metabolomics and pancreatic transcriptomics analyses. Li01 pretreatment significantly alleviated histopathological damage to the pancreas and reduced serum amylase activity in AP model mice. Pancreatic transcriptomic analysis revealed that Li01 modulated the expression of 89 differentially expressed genes (DEGs), thereby impacting key immune‐related signalling pathways, including the TNF‐α signalling pathway. Furthermore, Li01 mitigated gut microbiota dysbiosis in AP mice, notably by increasing the relative abundance of bacteria such as Paramuribaculum. Faecal metabolomics analysis indicated that Li01 intervention significantly increased the levels of metabolites involved in steroid hormone biosynthesis, including 17α‐estradiol. Li01 may alleviate AP by modulating the gut microbiota composition, increasing the relative abundance of bacteria such as Paramuribaculum, and regulating faecal metabolite profiles, particularly those involved in the steroid hormone biosynthesis pathway. These modulations, in turn, appear to influence pancreatic inflammation‐related signalling pathways, including the TNF signalling pathway.

Keywords: acute pancreatitis, gut microbiota, Lactobacillus salivarius Li01, metabolomics, transcriptomics

This study reveals that Lactobacillus salivarius Li01 alleviates acute pancreatitis by increasing gut Paramuribaculum. This modulation of the microbiota and its steroid hormone metabolites suppresses the pancreatic TNF signaling pathway, uncovering a protective ‘gut‐metabolism‐immunity’ axis.

graphic file with name MBT2-19-e70300-g003.jpg

1. Introduction

The global incidence of acute pancreatitis (AP) has continued to increase, with the age‐standardised incidence rate rising by 4.7%, from 17.3 cases per 100,000 people in 1990 to 18.1 cases per 100,000 people in 2019 (Iannuzzi et al. 2022). The mortality rate of severe acute pancreatitis (SAP) can reach 20%–30% (Li et al. 2021). The primary pathological features of AP include autodigestion of the pancreas, oedema, haemorrhage, and necrosis, which can be severe in cases (Zaman and Gorelick 2024). Its pathogenesis is multifactorial and involves the abnormal activation of pancreatic enzymes, dysregulated inflammatory responses, and impaired pancreatic microcirculation (Trikudanathan et al. 2024). Recent advances in gut microbiota research have highlighted the regulatory role of the gut microbiota and its metabolites in the development of AP, offering new perspectives on its pathological mechanisms and potential therapeutic strategies.

Dysregulation of the microbiota‐gut‐pancreas axis (MGPA) may exacerbate pancreatic injury through various mechanisms, including immune modulation, metabolic alterations, and intestinal barrier disruption (Zhou et al. 2024). Compared to healthy individuals, patients with AP exhibit reduced gut microbiota diversity and significant structural changes, characterised by an enrichment of Bacteroidetes and Proteobacteria, alongside a depletion of Firmicutes and Actinobacteria (Gong et al. 2025; Zhang et al. 2018). These alterations in the gut microbiota are closely associated with AP pathophysiology (Zhang et al. 2023). Notably, the gut microbiota composition varies among AP patients with differing disease severities, suggesting its potential as a biomarker for disease progression and outcome. The ‘gut‐pancreas axis’ refers to a complex, bidirectional regulatory network that connects the gut microbiota and the pancreas. Furthermore, a clinical trial evaluating faecal microbiota transplantation (FMT) in AP patients demonstrated improved clinical outcomes and an increased abundance of beneficial bacteria (Mao et al. 2024). These findings underscore the critical role of the gut microbiota in AP pathogenesis and its potential as a therapeutic target.

The application of probiotics and their derivatives in AP treatment has become a significant research focus in recent years (Werawatganon et al. 2023). For example, Bifidobacterium spp. and their metabolite, lactic acid, effectively attenuate AP in mice by suppressing both pancreatic and systemic inflammatory responses (Li et al. 2022). Clostridium butyricum exerts protective effects against AP‐related lung injury in mice by modulating the gut microbiota composition and associated metabolic pathways (Liu et al. 2024). The membrane protein Amuc_1100 from Akkermansia muciniphila reduces serum amylase and lipase levels, thereby alleviating pancreatic injury in AP mouse models (Wang et al. 2024). Polyphosphates derived from Lactobacillus brevis mitigate AP symptoms by inhibiting the growth of intestinal pathogenic bacteria and enhancing intestinal mucosal barrier integrity in mice (Takauji et al. 2021). A randomised, double‐blind, controlled clinical trial demonstrated that the incidence of infectious complications, including infected pancreatic abscesses, was significantly lower in the Lactobacillus spp. strain‐treated group than in the control group (Oláh et al. 2002). These studies highlight the therapeutic potential of probiotics in preventing or treating the progression of AP.

Lactobacillus salivarius , a key member of the gut microbiota, is recognised as a beneficial microorganism (Gao et al. 2025; Williams and Smith 2025). Supplementing infant formula with Lactobacillus AP‐32 effectively increases the abundance of beneficial bacteria in the infant's gut and reduces faecal Proteobacteria levels (Shen et al. 2024). Daily oral administration of Lactobacillus CECT5713 to healthy adults significantly induced the upregulation of IgM, IgA, and IgG, as well as the cytokine IL‐10 (Sierra et al. 2010). However, the specific role and underlying mechanisms of L. salivarius Li01 (Li01) in the development of AP remain unclear. In this study, we established an AP mouse model via intraperitoneal injection of L‐arginine to investigate the preventive effects of Li01 on the development of AP and explore its underlying mechanisms.

2. Materials and Methods

2.1. Strain and Culture Conditions

Lactobacillus salivarius Li01 (CGMCC No. 7045), a previously isolated and characterised probiotic strain from our laboratory, was used in this study. This strain has also been deposited in the China General Microbiological Culture Collection Center (CGMCC). The strain was cultured anaerobically in Man‐Rogosa‐Sharpe (MRS) broth (Oxoid; Thermo Fisher Scientific, Waltham, MA, USA) at 37°C for 24 h, following a previously described method (Shi et al. 2017). Bacterial cells were harvested via centrifugation (6000 × g, 10 min, 4°C), washed twice with sterile physiological saline (Qidu Pharmaceutical Co. Ltd., Zibo, China) (Lv et al. 2014), and resuspended in sterile saline to a final concentration of 1 × 109 CFU/mL.

2.2. Animal Experimentation

Male‐specific pathogen‐free (SPF) C57BL/6 mice (7 weeks old, weighing 20–25 g) were purchased from the Zhejiang Provincial Laboratory Animal Center (Hangzhou, Zhejiang, China). The mice were housed under controlled environmental conditions (temperature: 22°C ± 2°C; humidity: 55% ± 5%; 12 h light/12 h dark cycle) with ad libitum access to standard chow and water. The mice were randomly assigned to three groups (n = 8 per group): a healthy control group (Ctrl), an L‐arginine‐induced acute pancreatitis model group (AP), and an L. salivarius Li01 pretreatment group (Li01). For 7 consecutive days, the mice in the Li01 group received a daily oral gavage of Li01 suspension (0.1 mL per mouse). In contrast, the mice in the Ctrl and AP groups received an equal volume of sterile physiological saline via oral gavage daily. On Day 8, AP was induced in mice from the AP model and Li01 groups via two intraperitoneal (i.p.) injections of L‐arginine solution (total dose of 4 g/kg body weight, administered as two separate injections of 2 g/kg each, 1 h apart). Concurrently, the mice in the Ctrl group received i.p. injections of an equivalent volume of sterile physiological saline. All mice were euthanized 24 h after the final L‐arginine or saline injection. Immediately after euthanasia, blood, fresh faecal samples and pancreatic tissues were collected for subsequent analyses.

2.3. Serum Amylase Measurement

The collected blood samples were centrifuged at 3000 rpm for 15 min at 4°C, and the supernatant was collected. Serum amylase activity was measured using a commercial amylase activity assay kit (Cat. No. MAK009; Sigma‐Aldrich; Germany) according to the manufacturer's instructions.

2.4. Histopathological Analysis

Pancreatic tissue samples were immediately fixed in 4% paraformaldehyde (in PBS, pH 7.4) at 4°C overnight, dehydrated through a graded ethanol series, embedded in paraffin wax, and sectioned into 5‐μm‐thick slices via a microtome. The tissue sections were subsequently stained with haematoxylin and eosin (H&E) following standard protocols and examined under a Zeiss Axio Imager microscope (Carl Zeiss, Jena, Germany). Microscopy images were captured via standard bright‐field illumination with an attached digital camera. The degree of pancreatic histopathological damage was assessed semiquantitatively using the scoring system described by Schmidt et al. (1992).

2.5. Microbiome Analysis

Fresh faecal samples were collected directly from each mouse into sterile tubes, immediately snap‐frozen in liquid nitrogen, and stored at −80°C until DNA extraction. Total genomic DNA was extracted from approximately 100–200 mg of each faecal sample via the QIAamp DNA Stool Kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions. The V3‐V4 hypervariable regions of the bacterial 16S rRNA gene were amplified from the extracted DNA using the universal primers 338F (5′‐ACTCCTACGGGGAGGCAGCAG‐3′) and 806R (5′‐GGACTACHVGGGTWTCTAAT‐3′), with alternative sequences appended for multiplexing. The resulting PCR amplicons were purified, quantified, pooled in equimolar amounts, and then sequenced on a PacBio Sequel IIe platform (Shanghai Majorbio Biopharm Technology Co. Ltd., Shanghai, China) (Lv et al. 2016). The raw sequencing reads were processed via the DADA2 plugin (version 1.16) for quality filtering, error correction, merging of paired reads, and chimera removal to generate amplicon sequence variants (ASVs). Taxonomic classification of the representative sequence for each ASV was performed via a naïve Bayesian classifier against the SILVA 16S rRNA gene database (version 138).

2.6. Faecal Untargeted Metabolomics Analysis

For each sample, approximately 10–12 mg of mouse faeces was accurately weighed and subsequently homogenised in 400 μL of a prechilled extraction solution (80% methanol in water, v/v) containing 0.02 mg/mL L‐2‐chlorophenylalanine as an internal standard. The samples were processed as previously described (Jiang et al. 2024; Lv et al. 2021), involving vortexing, low‐temperature sonication, and centrifugation (12,000 rpm, 15 min, 4°C). The resulting clear supernatant was carefully collected and transferred to a new vial for LC–MS analysis. Metabolomic profiling was performed via an ultrahigh‐performance liquid chromatography system coupled to a Q Exactive HF‐X hybrid quadrupole‐Orbitrap mass spectrometer (UHPLC‐Q Exactive HF‐X; Thermo Fisher Scientific, Waltham, MA, USA). The samples were ionised via electrospray ionisation (ESI) in both positive (ESI+) and negative (ESI−) ion modes, and full‐scan mass spectra were acquired over a mass range of mass‐charge ratios (m/z) 70–1000. The raw LC–MS data files were converted to a compatible format and then imported into Progenesis QI software (version 3.0; Waters Corporation, Milford, MA, USA) for automated peak picking, retention time alignment, normalisation and baseline correction. This process yielded a comprehensive data matrix comprising retention times and mass‐charge ratios (m/z), which was used for subsequent statistical analysis and metabolite identification.

2.7. Pancreatic Transcriptional Analysis

Total RNA was extracted from an appropriate amount of mouse pancreatic tissue via TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's protocol. The RNA concentration and purity were determined via a NanoDrop spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). RNA integrity was assessed using an Agilent 2100 Bioanalyzer system with an RNA 6000 Nano LabChip Kit (Agilent Technologies, Santa Clara, CA, USA). Samples with an RNA integrity number (RIN) of > 7.0 were considered suitable for library construction. Transcriptome sequencing libraries were constructed from qualified RNA samples. The libraries were then purified via the AMPure XP system (Beckman Coulter, Beverly, MA, USA) and sequenced on an Illumina NovaSeq platform (Illumina, San Diego, CA, USA) (Lv et al. 2017). The raw sequencing reads were quality‐controlled and compared to the reference genome (HISAT2, version 2.0.5). Gene expression levels were quantified as fragments per kilobase of transcript per million mapped reads (FPKM). Differentially expressed genes (DEGs) were identified via the DESeq2 package (version 1.20.0) in R. The Benjamin‐Hochberg procedure was used to adjust p‐values for multiple tests. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed using the clusterProfiler package (3.8.1).

2.8. Statistical Analysis

Statistical analysis and graph generation were performed via GraphPad Prism software (version 9.5; GraphPad Software, San Diego, CA, USA). The normality of the data distribution was assessed via the Shapiro–Wilk test. For normally distributed data, comparisons among multiple groups were performed via one‐way analysis of variance (ANOVA) followed by Tukey's multiple comparisons post hoc test. For non‐normally distributed data, the Kruskal–Wallis test was followed by Dunn's multiple comparisons post hoc test. Spearman rank correlation analysis was used to assess the correlations between serum amylase levels, faecal metabolite abundances, pancreatic gene expression levels, and the relative abundances of specific gut microbiota taxa. The data are presented as the means ± standard errors (means ± SEM). A p‐value < 0.05 was considered statistically significant (*p < 0.05; **p < 0.01; ***p < 0.001).

3. Results

3.1. L. salivarius Li01 Pretreatment Attenuates Pancreatic Inflammation in AP Model Mice

No mortality was observed in any group throughout the study. Compared with the Ctrl group, the AP group presented an L‐arginine‐induced increase in the pancreas‐to‐body weight ratio (%), although this ratio tended to decrease following Li01 pretreatment (Figure 1B). H&E staining revealed clear pancreatic structures with no obvious inflammatory cell infiltration in the Ctrl group (Figure 1A). In contrast, the AP group exhibited typical pathological features of AP, including diffuse inflammatory cell infiltration, tissue edema, and adipocyte necrosis. Consequently, their histopathological scores were significantly higher than those of the Ctrl group (Figure 1C). The mice in the Li01 group showed only mild inflammation, and their pathology scores were not significantly different from those of the Ctrl group (p > 0.05) but were significantly lower than those of the AP group, suggesting attenuation of L‐arginine‐induced AP by Li01 pretreatment. Consistent with these histological findings, serum amylase activity was significantly elevated in the AP group compared with the Ctrl group (Figure 1D). Li01 pretreatment significantly reduced this increase in serum amylase activity in AP mice (Figure 1D). Together, these results indicate that Li01 pretreatment effectively attenuates L‐arginine‐induced pancreatic tissue injury in mice.

FIGURE 1.

FIGURE 1

Open in a new tab

L. salivarius Li01 pretreatment attenuates pancreatic inflammation in AP mice. (A) Representative histopathological changes in mouse pancreatic tissues visualised by H&E staining (50× magnification). (B) Histopathological scores of pancreatic tissues. (C) Pancreas‐to‐body weight ratio (%) calculated as (pancreas weight/body weight) × 100%. (D) Serum amylase levels in the indicated experimental groups (Ctrl, AP, Li01). Data are presented as mean ± SEM (n = 8 per group). Significance: **p < 0.01, ***p < 0.001, ****p < 0.0001, ns (not significant, p > 0.05) compared to the AP group unless otherwise indicated.

3.2. L. salivarius Li01 Pretreatment Modulates Pancreatic Inflammatory Pathways in AP Model Mice

To further investigate the molecular mechanisms underlying the protective effect of Li01, we performed transcriptomic analysis on pancreatic tissue samples from the three groups. Using screening criteria of a fold change (FC) > 2 and an adjusted p‐value < 0.05, we found that Li01 pretreatment partially reversed the AP‐induced changes in the expression of 89 pancreatic genes (Figure 2A). Specifically, Li01 pretreatment attenuated the AP‐induced upregulation of 21 pancreatic genes, including those involved in immune‐inflammatory regulation, such as Lrrc26 and Slco4a1. Conversely, Li01 reversed the AP‐induced downregulation of 68 pancreatic genes, including those implicated in inflammatory factor pathways, such as Socs3, Junb, Icam1, Fos, and Bcl3.

FIGURE 2.

FIGURE 2

Open in a new tab

L. salivarius Li01 pretreatment modulates pancreatic inflammatory pathways in AP mice. (A) Heatmap of 89 pancreatic differentially expressed genes (DEGs) altered by AP induction and reversed by Li01 pretreatment. Data are Z‐score normalised. (B) Gene Ontology (GO) enrichment analysis of the 89 Li01‐restored DEGs. (C) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the 89 Li01‐restored DEGs. Key immune‐related pathways are highlighted in red.

Gene Ontology (GO) functional enrichment analysis of these 89 DEGs revealed that they were primarily enriched in the biological process (BP) category (Figure 2B). The two most significantly enriched BP terms were ‘inflammatory response’ and ‘regulation of tumor necrosis factor production’. These results suggest that immune system activation occurs during AP and that Li01 intervention may exert protective effects by modulating these immune‐related processes.

Furthermore, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that these 89 DEGs were significantly enriched in 20 pathways. Considering the results of the GO analysis, which suggested a role for immune modulation in the protective effects of Li01, we focused on several relevant KEGG pathways (highlighted in red in Figure 2C), including the TNF signalling pathway, NOD‐like receptor signalling pathway, MAPK signalling pathway, haematopoietic cell lineage pathway, and lipid and atherosclerosis pathway.

3.3. L. salivarius Li01 Pretreatment Alters the Gut Microbiota Composition in AP Model Mice

Alpha diversity analysis (Figure 3A) revealed no significant differences in the Shannon and Simpson indices among the Ctrl, AP, and Li01 groups (p > 0.05). However, principal coordinate analysis (PCoA) based on the unweighted UniFrac distance matrix revealed significant differences in the overall microbial composition among the three groups (ANOSIM, p = 0.001; Figure 3B). These findings suggest that Li01 pretreatment ameliorated the gut microbiota dysbiosis induced in AP mice.

FIGURE 3.

FIGURE 3

Open in a new tab

L. salivarius Li01 pretreatment alters the gut microbiota composition in AP mice. (A) Alpha diversity of gut microbiota assessed by Shannon and Simpson indices. (B) Principal Coordinates Analysis (PCoA) based on unweighted UniFrac distances of gut microbiota. (C) Relative abundance of bacterial communities at the phylum level (phyla with < 1% relative abundance in each sample is grouped into ‘others’). (D–F) Relative abundances of significantly differing taxa at the phylum (D), genus (E), and species (F) levels among Ctrl, AP, and Li01 groups. Data are presented as mean ± SEM (n = 8 per group). Significance: *p < 0.05, **p < 0.01, ***p < 0.001, ns (not significant, p > 0.05).

Alterations in the composition of the gut microbiota at various taxonomic levels were further examined. At the phylum level, the AP group presented a significantly increased relative abundance of Verrucomicrobiota, whereas Campylobacterota was depleted in the AP group compared with the Ctrl group (Figure 3C,D). At the genus level, compared with the Ctrl group, the AP group presented significant reductions in the relative abundances of Ligilactobacillus, Paramuribaculum, Helicobacter, Mammaliicoccus, and Adlercreutzia (Figure 3E). At the species level, the AP group presented markedly decreased proportions of Porphyromonadaceae_bacterium_UBA7139, Ligilactobacillus_murinus, Paramuribaculum_intestinale, Mammaliicoccus_vitulinus, and Jeotgalicoccus_nanhaiensis. In contrast, significant enrichment was observed in Lachnospiraceae bacterium M18‐1 within the AP group (Figure 3F). Notably, Li01 pretreatment effectively attenuated AP‐induced microbial dysbiosis, restoring taxon abundances across the phylum, genus, and species levels to values comparable with those of the Ctrl group.

3.4. L. salivarius Li01 Pretreatment Alters the Faecal Metabolite Profile of AP Model Mice

Gut microbiota‐derived metabolites are known to directly or indirectly influence the pathogenesis of AP. Untargeted metabolomics analysis of faecal samples from the three experimental groups led to the identification of 2240 distinct metabolites across all 24 samples (Figure 4A). Orthogonal partial least squares discriminant analysis (OPLS‐DA) and partial least squares discriminant analysis (PLS‐DA) revealed clear separations in the faecal metabolite profiles among the Ctrl, AP, and Li01 groups (Figure 4B).

FIGURE 4.

FIGURE 4

Open in a new tab

L. salivarius Li01 pretreatment alters faecal metabolite profiles in AP mice. (A) Venn diagram showing the number of common and unique differential metabolites among the Ctrl, AP, and Li01 groups. (B) Partial Least Squares Discriminant Analysis (PLS‐DA) and Orthogonal PLS‐DA (OPLS‐DA) score plots illustrating separation of faecal metabolite profiles among groups. (C) HMDB Superclass classification of the 56 differential metabolites significantly altered by AP and reversed by Li01. (D) Hierarchical clustering analysis of the 56 differential metabolites across groups. (E) KEGG pathway enrichment analysis of the 56 differential metabolites. (F) Relative abundance of key differential faecal metabolites among groups. Data are presented as mean ± SEM (n = 8 per group; panel F). Significance: *p < 0.05, **p < 0.01, ***p < 0.001, **** p < 0.0001, ns (not significant, p > 0.05).

Based on a variable importance in projection (VIP) score > 1 and a p‐value < 0.05, Li01 pretreatment reversed the AP‐induced alterations in the levels of 56 faecal metabolites (Figure 4D). Specifically, Li01 pretreatment attenuated the AP‐induced increase in the levels of 20 metabolites, which included five amino acids or their derivatives (Ala Val Thr, Leu Val Ser, Pro‐Tyr, Ile Ile Ala, and Ile‐Leu), and two alkaloids (isoquinoline and Heteratisine) (Figure 4C). Conversely, Li01 pretreatment counteracted the AP‐induced decrease in the levels of 36 metabolites, including 13 amino acids or their derivatives (N2‐Acetyl‐L‐Ornithine, Gly‐Pro, Leu‐Leu, Ile Gly, Asp‐Thr‐Ala, Leu‐Gly‐Leu, Thr‐Phe, Val‐Ile, Ala‐Val‐Ile, etc.), three gibberellins (Gibberellin A4, Gibberellin A9, Gibberellin A14), and three steroid hormones or related compounds (17α‐Estradiol, 17β‐Estradiol 3‐Sulfate, and 19‐Hydroxyandrost‐4‐Ene‐3,17‐Dione).

KEGG pathway enrichment analysis was performed on these 56 differentially abundant metabolites. The analysis revealed significant enrichment in two metabolic pathways: steroid hormone biosynthesis and diterpenoid biosynthesis (p < 0.001; Figure 4E). These findings suggest that Li01 may ameliorate pancreatic injury by modulating these two key metabolic pathways. Specifically, 17α‐Estradiol, 17β‐Estradiol 3‐Sulfate, and 19‐Hydroxyandrost‐4‐Ene‐3,17‐Dione are key metabolites in the steroid hormone biosynthesis pathway, whereas Gibberellin A4, A9, and A14 are involved in the diterpenoid biosynthesis pathway. Notably, the faecal levels of these six metabolites were significantly lower in the AP group than in the Ctrl group, whereas their levels were significantly different restored after Li01 pretreatment (Figure 4F).

3.5. Multiple Correlation Analysis of L. salivarius Li01 Treatment for AP

To explore the interplay between Li01‐induced gut microbiota modulation and AP severity, we performed a Spearman correlation analysis to examine the relationship between the relative abundances of gut microbiota genera and serum amylase activity. At the genus level, a significant negative correlation was observed between serum amylase activity and the relative abundances of both Mammaliicoccus and Paramuribaculum (|r| > 0.6, p < 0.01) (Figure 5A). These findings suggest that these two microbial genera may contribute to the Li01‐mediated alleviation of pancreatic injury in AP.

FIGURE 5.

FIGURE 5

Open in a new tab

Gut microbiota correlates with AP severity and associated metabolites. (A) Spearman correlation analysis between Li01‐modulated genus‐level gut microbiota abundances and serum amylase activity, pancreatic pathology score, and pancreas/body weight ratio. (B) KEGG pathway enrichment analysis of pancreatic DEGs significantly correlated with the abundances of Paramuribaculum and Mammaliicoccus. Significance: *p < 0.05, **p < 0.01, ***p < 0.001, ns (not significant, p > 0.05).

To further explore how specific microbial taxa might ameliorate AP by modulating metabolites, we performed a Spearman correlation analysis between the 56 faecal metabolites whose levels were reversed by the Li01 intervention and genus‐level gut microbiota relative abundances, using screening criteria of p < 0.05 and |r| > 0.6. As shown in Figure 5B, Paramuribaculum abundance exhibited significant positive correlations with gibberellin A4, 17α‐estradiol, 17β‐estradiol 3‐sulfate, and 19‐hydroxyandrost‐4‐ene‐3,17‐dione but significant negative correlations with Ala‐Val‐Ile, gentiatibetine, Leu‐Thr‐Ile, and Leu‐Val‐Ser. Mammaliicoccus was positively correlated with gibberellin A14, 19‐hydroxyandrost‐4‐ene‐3,17‐dione, and 17α‐estradiol but negatively correlated with Leu‐Leu, 5‐hydroxyindole‐3‐acetic acid, and Ala‐Val‐Thr. Notably, 17α‐estradiol, 17β‐estradiol 3‐sulfate, and 19‐hydroxyandrost‐4‐ene‐3,17‐dione—metabolites involved in the steroid hormone biosynthesis pathway—were strongly correlated with Paramuribaculum abundance. These findings further suggest that Li01 may alleviate AP progression by reshaping the gut microbiota and its metabolic outputs.

We subsequently analysed the correlations between the genus‐level microbial abundances and the 89 key pancreatic DEGs reversed by Li01 via Spearman's method (p < 0.05, |r| > 0.8; Figure 6A). The results revealed significant associations between the abundances of Paramuribaculum and Mammaliicoccus and most of these pancreatic DEGs. KEGG pathway enrichment analysis (pathway gene number threshold ≥ 2) of these microbiota‐associated DEGs highlighted their predominant enrichment in the TNF signalling pathway (Figure 6B). By integrating the observed correlations among the abundances of Paramuribaculum and Mammaliicoccus, serum amylase levels, faecal metabolite profiles, and pancreatic transcriptomic changes, we propose that Li01 mitigates AP by increasing the abundances of Paramuribaculum and Mammaliicoccus. These microbial changes, in turn, appear to modulate the TNF signalling pathway in the pancreas and steroid hormone biosynthesis in the faeces.

FIGURE 6.

FIGURE 6

Open in a new tab

Correlation analysis between gut microbiota and pancreatitis transcriptomes. (A) Spearman correlation analysis heatmap between Li01‐modulated genus‐level gut microbiota abundances and pancreatic differentially expressed genes (DEGs). (B) Enriched plots and strings for KEGG pathway analysis of pancreatic genes associated to Paramuribaculum and Mammaliicoccus.

4. Discussion

Acute pancreatitis (AP), characterised by inflammatory injury to the pancreas, often resulting from autodigestion and triggered by various aetiologies, has an increasing global incidence and persistently high mortality rates in severe cases (Lo et al. 2025). Significant differences exist in the gut microbiota composition between patients with AP and healthy individuals. Preclinical studies suggest that certain probiotic genera, including Lactobacillus, Saccharomyces boulardii, and Bifidobacterium, hold potential as adjunct therapies for AP (Akyol et al. 2003; Du et al. 2025; Mores et al. 2023). Lactobacillus salivarius , recognised as a beneficial microorganism, contributes to gastrointestinal homeostasis and barrier integrity, potentially through interactions with signalling pathways such as the TLR4/NF‐κB/MyD88 pathway (Wei et al. 2023). However, the specific mechanisms by which L. salivarius Li01 (Li01) prevents or treats AP remain poorly understood. This study demonstrated that Li01 pretreatment significantly alleviated L‐arginine‐induced AP in mice. The underlying mechanism potentially involves an increased intestinal abundance of bacteria, such as Paramuribaculum, which subsequently modulate the TNF signalling pathway in pancreatic tissues and faecal steroid hormone biosynthesis.

The ‘gut‐pancreas axis’ concept highlights the intricate relationship between gut microbiota composition and pancreatic diseases (Lei et al. 2021). For example, elastase released from necrotic pancreatic tissue can disrupt the intestinal mucus layer, leading to alterations such as a decreased Firmicutes/Bacteroidetes ratio and an increase in Enterobacteriaceae abundance. This dysbiosis is significantly and positively correlated with serum endotoxin levels (Zhang et al. 2023). Accordingly, the present study investigated the role of the gut microbiota in mediating the ameliorative effects of Li01 on AP. Consistent with our hypothesis, Li01 pretreatment significantly altered the gut microbiota composition in AP mice. Previous studies employing metagenomic sequencing have reported altered gut microbiota compositions in AP patients, characterised by increased abundances of species such as Escherichia coli and Enterococcus faecium (Gong et al. 2025). Another study reported that gut microbiota dysbiosis resulted in significant alterations in the abundance of Lachnospiraceae and Bifidobacterium in a sodium taurocholate‐induced AP mouse model (Xiong et al. 2022). In a mouse model of severe acute pancreatitis (SAP) induced by caerulein combined with lipopolysaccharide, intervention with ganoderic acid A (GAA) significantly increased the abundance of potentially beneficial bacteria, including Akkermansia and Parvibacter (Zhang et al. 2025). These studies suggest that modulating the composition of the gut microbiota to promote beneficial bacteria while inhibiting potentially harmful bacteria may ameliorate pancreatic injury. For example, a dietary inulin intervention significantly improved gut microbial homeostasis in mice with high‐fat diet‐induced AP, as evidenced by the enrichment of beneficial taxa such as Akkermansia, Muribaculaceae, and Anaerostipes, along with the inhibition of potentially pathogenic bacteria such as Escherichia_Shigella, Enterococcus, and Klebsiella (Li et al. 2024; Wang et al. 2025). In this study, L‐arginine induced intestinal inflammation and injury, a finding also reported in another study (Xia et al. 2023). In our L. salivarius Li01‐pretreated acute pancreatitis mouse model, the relative abundances of the genera Ligilactobacillus, Paramuribaculum, Helicobacter, Mammaliicocus, and Adlercreutzia were significantly increased the relative abundances of Paramuribaculum and Helicobacter. Among these, Paramuribaculum belongs to the Bacteroidetes phylum and is a beneficial butyrate‐producing bacterium (Fang et al. 2023). Butyrate is a key factor in maintaining gut health, as it exerts anti‐inflammatory effects and enhances intestinal barrier function and mucosal immunity (Chen et al. 2025; Leonel and Alvarez‐Leite 2012; Liu et al. 2018). Furthermore, butyrate has been reported to alleviate pancreatic injury in mouse models of acute pancreatitis induced by taurocholate or creulein (Pan et al. 2019; Xiong et al. 2022; Xu et al. 2024). Therefore, L. salivarius Li01 may alleviate the severity of AP by elevating gut butyrate levels through the enrichment of butyrate‐producing microorganisms.

In recent years, the influence of gut microbiota‐derived metabolites on host physiology has been extensively investigated. Notably, alterations in the levels of these metabolites may also contribute to the pathogenesis of pancreatic inflammation. Short‐chain fatty acids (SCFAs), major products of dietary fibre fermentation by the gut microbiota, are recognised for their protective role in AP. For example, butyric acid inhibits the NF‐κB pathway by activating the GPR109a receptor, thereby reducing neutrophil infiltration and the release of proinflammatory factors (Lei et al. 2021). An imbalance in the gut microbiota can lead to elevated levels of secondary bile acids (e.g., deoxycholic acid), which may inhibit IL‐22 secretion through FXR receptors and impair pancreatic tissue repair (Qiu et al. 2024). Furthermore, microbiota‐derived lipopolysaccharide (LPS) can promote the polarisation of pancreatic macrophages toward the M1 phenotype through TLR4 signalling, thereby exacerbating the inflammatory response (Zhang et al. 2023). To investigate AP‐associated faecal metabolic changes and the effects of Li01 intervention, this study employed untargeted metabolomics. Following Li01 pretreatment, the levels of 56 differentially abundant metabolites shifted toward those observed in the Ctrl group compared with those in the AP group. KEGG pathway enrichment analysis revealed that these 56 Li01‐altered metabolites were primarily enriched in the steroid hormone biosynthesis and diterpenoid biosynthesis pathways. Steroid hormones are known to fulfil diverse and critical physiological functions. A previous study demonstrated that supplementation with Guggulsterone inhibited macrophage and neutrophil infiltration and attenuated pancreatic injury, potentially by inhibiting ERK1/2 and JNK activation in a mouse model of ceruloplasmin‐induced AP (Kim et al. 2015). In the present study, Li01 pretreatment modulated steroid hormone biosynthesis; specifically, the faecal levels of 17α‐estradiol, 17β‐estradiol 3‐sulphate and 19‐hydroxyandrost‐4‐ene‐3,17‐dione were significantly higher in the Li01 intervention group than in the AP group. Collectively, these analyses support a regulatory effect of L. salivarius Li01 on steroid hormone biosynthesis, suggesting its potential therapeutic relevance for pancreatic injury. Regarding diterpenoids, the related GA derivative GA‐13315 has been reported to exhibit low toxicity and antitumor potential in lung adenocarcinoma cells (Xie et al. 2019). In the present study, the faecal levels of Gibberellin A4, A9 and A14 were significantly reduced in AP mice, whereas their levels were significantly increased following Li01 pretreatment. These findings suggest that Li01 may ameliorate pancreatic injury partly by modulating diterpenoid biosynthesis.

Although this study demonstrated an ameliorative effect of Li01 pretreatment on AP, the precise underlying molecular mechanisms and key regulated genes require further investigation. Pancreatic transcriptomic analysis revealed 89 DEGs whose aberrant expression induced by AP was reversed by Li01 pretreatment. These findings suggest that Li01 exerts its protective effect through a complex gene regulatory network rather than solely by modulating individual genes. GO and KEGG enrichment analyses of these 89 key DEGs revealed that the Li01 intervention primarily modulated signalling pathways closely related to immune and inflammatory responses, including the TNF signalling pathway, NOD‐like receptor signalling pathway, MAPK signalling pathway, haematopoietic cell lineage pathway and lipid and atherosclerosis pathway. The TNF signalling pathway is known to play a crucial role in initiating inflammation, regulating T‐cell proliferation and activation, promoting the production of proinflammatory cytokines, and inducing regulatory T‐cell (Treg) activity (Beldi et al. 2020). Recent studies have reported high expression of the NOD‐like receptor protein 3 (NLRP3) inflammasome in cerulein‐induced AP mice, which exacerbates inflammation‐mediated tissue damage (An et al. 2025). The general importance of the MAPK signalling pathway in inflammation is underscored by findings in other contexts; for example, the Mycobacterium tuberculosis Rv0928 protein has been shown to amplify MAPK signalling by potentiating bacterium‐induced inflammatory responses (Xu et al. 2023). The haematopoietic cell lineage pathway, also identified in our analysis, regulates haematopoiesis and differentiation, acting as a key hub that connects inflammation, immune regulation, and metabolism (Lareau et al. 2022). These processes are crucial for clearing necrotic tissues, resisting infection, and regulating inflammation during AP (Sreejit and Park 2024). Abnormalities in lipid metabolism, which are relevant to identified lipids and atherosclerosis, can increase the release of inflammatory cytokines (e.g., TNF‐α, IL‐6, and IL‐1β), known contributors to pancreatitis severity (Močnik and Marčun Varda 2023). Furthermore, intestinal dysbiosis in patients with hypertriglyceridaemic pancreatitis has been shown to exacerbate the formation of neutrophil extracellular traps (NETs), thereby inducing pancreatic injury (Li et al. 2023). The modulation of these pathways by Li01, as observed in this study, may contribute to the amelioration of pancreatic injury, potentially by inhibiting the production or activity of inflammatory mediators.

Our results indicate that pretreatment with L. salivarius Li01 alleviates acute pancreatitis induced by L‐arginine. This finding suggests that L. salivarius Li01 has broad therapeutic potential for the prevention and treatment of acute pancreatitis. However, this study has limitations; for instance, it was limited to a single animal model and thus requires further validation in clinical trials.

5. Conclusion

In summary, we investigated the effects of L. salivarius Li01 pretreatment on L‐arginine‐induced acute pancreatitis in mice through histomorphological and multi‐omics analyses. Overall, our findings provide evidence that Li01 may mitigate pancreatitis injury by increasing the relative abundance of gut genera such as Paramuribaculum. Furthermore, Li01 intervention induced significant alterations in both the faecal metabolome and the pancreatic transcriptome. Specifically, it regulated the steroid hormone biosynthesis pathway and diterpenoid biosynthesis pathways in faeces, while modulating multiple immune‐inflammatory pathways in the pancreas, including the TNF signalling pathway, NOD‐like receptor signalling pathway, MAPK signalling pathway, haematopoietic cell lineage, and lipid and atherosclerosis pathways. Therefore, this study supports the potential application of L. salivarius Li01 in preventing acute pancreatitis.

Author Contributions

Jiamin Duan: investigation, writing – original draft preparation, writing – review and editing, software, methodology. Jing Lou: validation, visualisation, methodology, investigation. Feiyu Wang: investigation. Huiyong Jiang: project administration, investigation, visualisation, supervision. Longxian Lv: conceptualization, writing – review and editing, supervision, funding acquisition. Hongwei Fu: methodology, formal analysis, supervision.

Funding

This work was funded by the National Key Research and Development Program (2023YFC2506000 and 2022YFC2304500), the Fundamental Research Funds for the Central Universities (2022ZFJH003 and 2025ZFJH03), the Shandong Provincial Laboratory Project (SYS202202), the Research Project of Jinan Microecological Biomedicine Shandong Laboratory (JNL‐2022009B and JNL‐2022047D) and the Central Guidance Fund for Local Science and Technology Development (2024ZY01054).

Ethics Statement

All animal experiments and procedures were approved by the Animal Ethics Committee of The First Affiliated Hospital, Zhejiang University School of Medicine (Approval No. 20241108) and were performed in strict accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals (NIH Publication No. 85‐23, revised 1996).

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgements

This work was funded by the National Key Research and Development Program (2023YFC2506000 and 2022YFC2304500), the Fundamental Research Funds for the Central Universities (2022ZFJH003 and 2025ZFJH03), the Shandong Provincial Laboratory Project (SYS202202), the Research Project of Jinan Microecological Biomedicine Shandong Laboratory (JNL‐2022009B and JNL‐2022047D) and the Central Guidance Fund for Local Science and Technology Development (2024ZY01054).

Duan, J. , Lou J., Wang F., Jiang H., Lv L., and Fu H.. 2026. “Multi‐Omics Analysis Reveals the Potential Preventive Mechanism of Lactobacillus salivarius Li01 Against L‐Arginine‐Induced Acute Pancreatitis in Mice.” Microbial Biotechnology 19, no. 1: e70300. 10.1111/1751-7915.70300.

Contributor Information

Huiyong Jiang, Email: jianghuiyong@zju.edu.cn.

Longxian Lv, Email: lvlongxian@zju.edu.cn.

Hongwei Fu, Email: fhw668@zju.edu.cn.

Data Availability Statement

The raw sequencing reads have been deposited in the NCBI Short Read Archive (SRA) under accession number PRJNA1281822. The other datasets analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Akyol, S. , Mas M. R., Comert B., et al. 2003. “The Effect of Antibiotic and Probiotic Combination Therapy on Secondary Pancreatic Infections and Oxidative Stress Parameters in Experimental Acute Necrotizing Pancreatitis.” Pancreas 26, no. 4: 363–367. 10.1097/00006676-200305000-00009. [DOI] [PubMed] [Google Scholar]
  2. An, Y. , Tu Z., Wang A., et al. 2025. “Qingyi Decoction and Its Active Ingredients Ameliorate Acute Pancreatitis by Regulating Acinar Cells and Macrophages via NF‐κB/NLRP3/Caspase‐1 Pathways.” Phytomedicine 139: 156424. 10.1016/j.phymed.2025.156424. [DOI] [PubMed] [Google Scholar]
  3. Beldi, G. , Khosravi M., Abdelgawad M. E., et al. 2020. “TNFα/TNFR2 Signaling Pathway: An Active Immune Checkpoint for Mesenchymal Stem Cell Immunoregulatory Function.” Stem Cell Research & Therapy 11, no. 1: 281. 10.1186/s13287-020-01740-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Chen, H. , Wang F., Li S., et al. 2025. “Protective Effect of Pediococcus pentosaceus Li05 on Constipation via TGR5/TPH1/5‐HT Activation.” Microbial Biotechnology 18, no. 11: e70257. 10.1111/1751-7915.70257. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Du, B. , Yan R., Hu X., et al. 2025. “Role of Bifidobacterium animalis Subsp. Lactis BB‐12 in Mice With Acute Pancreatitis.” AMB Express 15, no. 1: 62. 10.1186/s13568-025-01867-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Fang, C. , Cheng J., Jia W., and Xu Y.. 2023. “ Akkermansia muciniphila Ameliorates Alcoholic Liver Disease in Experimental Mice by Regulating Serum Metabolism and Improving Gut Dysbiosis.” Metabolites 13, no. 10: 1057. 10.3390/metabo13101057. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Gao, Y. , Zhu A., Li J., Liu H., Li X., and Zhang H.. 2025. “ Lactiplantibacillus plantarum Attenuates Diet‐Induced Obesity and Insulin Resistance Through Gut Microbiota‐Driven PPAR/PI3K‐Axis Modulation.” Microbial Biotechnology 18, no. 11: e70227. 10.1111/1751-7915.70227. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Gong, L. , Li X., Ji L., et al. 2025. “Characterization and Comparison of Gut Microbiota in Patients With Acute Pancreatitis by Metagenomics and Culturomics.” Heliyon 11, no. 3: e42243. 10.1016/j.heliyon.2025.e42243. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Iannuzzi, J. P. , King J. A., Leong J. H., et al. 2022. “Global Incidence of Acute Pancreatitis Is Increasing Over Time: A Systematic Review and Meta‐Analysis.” Gastroenterology 162, no. 1: 122–134. 10.1053/j.gastro.2021.09.043. [DOI] [PubMed] [Google Scholar]
  10. Jiang, H. , Yu Y., Hu X., et al. 2024. “The Fecal Microbiota of Patients With Primary Biliary Cholangitis (PBC) Causes PBC‐Like Liver Lesions in Mice and Exacerbates Liver Damage in a Mouse Model of PBC.” Gut Microbes 16, no. 1: 2383353. 10.1080/19490976.2024.2383353. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Kim, D. G. , Bae G. S., Choi S. B., et al. 2015. “Guggulsterone Attenuates Cerulein‐Induced Acute Pancreatitis via Inhibition of ERK and JNK Activation.” International Immunopharmacology 26, no. 1: 194–202. 10.1016/j.intimp.2015.03.030. [DOI] [PubMed] [Google Scholar]
  12. Lareau, C. A. , Romagnani C., and Ludwig L. S.. 2022. “Editorial: Lineage Tracing, Hematopoietic Stem Cell and Immune Cell Dynamics.” Frontiers in Immunology 13: 1062415. 10.3389/fimmu.2022.1062415. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Lei, Y. , Tang L., Liu S., et al. 2021. “Parabacteroides Produces Acetate to Alleviate Heparanase‐Exacerbated Acute Pancreatitis Through Reducing Neutrophil Infiltration.” Microbiome 9, no. 1: 115. 10.1186/s40168-021-01065-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Leonel, A. J. , and Alvarez‐Leite J. I.. 2012. “Butyrate: Implications for Intestinal Function.” Current Opinion in Clinical Nutrition and Metabolic Care 15, no. 5: 474–479. 10.1097/MCO.0b013e32835665fa. [DOI] [PubMed] [Google Scholar]
  15. Li, C. L. , Jiang M., Pan C. Q., Li J., and Xu L. G.. 2021. “The Global, Regional, and National Burden of Acute Pancreatitis in 204 Countries and Territories, 1990‐2019.” BMC Gastroenterology 21, no. 1: 332. 10.1186/s12876-021-01906-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Li, G. , Liu L., Lu T., et al. 2023. “Gut Microbiota Aggravates Neutrophil Extracellular Traps‐Induced Pancreatic Injury in Hypertriglyceridemic Pancreatitis.” Nature Communications 14, no. 1: 6179. 10.1038/s41467-023-41950-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Li, H. , Xie J., Guo X., et al. 2022. “Bifidobacterium spp. and Their Metabolite Lactate Protect Against Acute Pancreatitis via Inhibition of Pancreatic and Systemic Inflammatory Responses.” Gut Microbes 14, no. 1: 2127456. 10.1080/19490976.2022.2127456. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Li, X. , Zheng P., Zou Y., et al. 2024. “Dietary Inulin Ameliorates Obesity‐Induced Severe Acute Pancreatitis via Gut‐Pancreas Axis.” Gut Microbes 16, no. 1: 2436949. 10.1080/19490976.2024.2436949. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Liu, H. , Wang J., He T., et al. 2018. “Butyrate: A Double‐Edged Sword for Health?” Advances in Nutrition 9, no. 1: 21–29. 10.1093/advances/nmx009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Liu, J. , Wen B., Huang Y., Deng G., Yan Q., and Jia L.. 2024. “Exploring the Effect of Clostridium butyricum on Lung Injury Associated With Acute Pancreatitis in Mice by Combined 16S rRNA and Metabolomics Analysis.” Anaerobe 87: 102854. 10.1016/j.anaerobe.2024.102854. [DOI] [PubMed] [Google Scholar]
  21. Lo, C. H. , Pannala R., and Samadder N. J.. 2025. “Trends in Acute Pancreatitis‐Related Mortality Among US Adults From 1999 to 2020.” Gastro Hep Advances 4, no. 5: 100615. 10.1016/j.gastha.2025.100615. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Lv, L. , Jiang H., Chen X., et al. 2021. “The Salivary Microbiota of Patients With Primary Biliary Cholangitis Is Distinctive and Pathogenic.” Frontiers in Immunology 12: 713647. 10.3389/fimmu.2021.713647. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Lv, L. X. , Fang D. Q., Shi D., et al. 2016. “Alterations and Correlations of the Gut Microbiome, Metabolism and Immunity in Patients With Primary Biliary Cirrhosis.” Environmental Microbiology 18, no. 7: 2272–2286. 10.1111/1462-2920.13401. [DOI] [PubMed] [Google Scholar]
  24. Lv, L. X. , Hu X. J., Qian G. R., et al. 2014. “Administration of Lactobacillus salivarius LI01 or Pediococcus pentosaceus LI05 Improves Acute Liver Injury Induced by D‐Galactosamine in Rats.” Applied Microbiology and Biotechnology 98, no. 12: 5619–5632. 10.1007/s00253-014-5638-2. [DOI] [PubMed] [Google Scholar]
  25. Lv, L. X. , Yan R., Shi H. Y., et al. 2017. “Integrated Transcriptomic and Proteomic Analysis of the Bile Stress Response in Probiotic Lactobacillus salivarius LI01.” Journal of Proteomics 150: 216–229. 10.1016/j.jprot.2016.08.021. [DOI] [PubMed] [Google Scholar]
  26. Mao, Y. , Huang Y., Zhang W., et al. 2024. “FMT Reduces Systemic Inflammatory Response in Severe Acute Pancreatitis by Increasing the Abundance of Intestinal Bifidobacteria and Fecal Bacteria.” Biomolecules & Biomedicine 25: 1591–1600. 10.17305/bb.2024.11445. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Močnik, M. , and Marčun Varda N.. 2023. “Lipid Biomarkers and Atherosclerosis‐Old and New in Cardiovascular Risk in Childhood.” International Journal of Molecular Sciences 24, no. 3: 2237. 10.3390/ijms24032237. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Mores, M. G. , Fikry E. M., El‐Gendy A. O., Mohamed W. R., and Badary O. A.. 2023. “Probiotics Mixture and Taurine Attenuate L‐Arginine‐Induced Acute Pancreatitis in Rats: Impact on Transient Receptor Potential Vanilloid‐1 (TRPV‐1)/IL‐33/NF‐κB Signaling and Apoptosis.” Tissue & Cell 85: 102234. 10.1016/j.tice.2023.102234. [DOI] [PubMed] [Google Scholar]
  29. Oláh, A. , Belágyi T., Issekutz A., Gamal M. E., and Bengmark S.. 2002. “Randomized Clinical Trial of Specific Lactobacillus and Fibre Supplement to Early Enteral Nutrition in Patients With Acute Pancreatitis.” British Journal of Surgery 89, no. 9: 1103–1107. 10.1046/j.1365-2168.2002.02189.x. [DOI] [PubMed] [Google Scholar]
  30. Pan, X. , Fang X., Wang F., et al. 2019. “Butyrate Ameliorates Caerulein‐Induced Acute Pancreatitis and Associated Intestinal Injury by Tissue‐Specific Mechanisms.” British Journal of Pharmacology 176, no. 23: 4446–4461. 10.1111/bph.14806. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Qiu, Y. F. , Ye J., Xie J. J., et al. 2024. “Pancreatitis Affects Gut Microbiota via Metabolites and Inflammatory Cytokines: An Exploratory Two‐Step Mendelian Randomisation Study.” Molecular Genetics and Genomics 299, no. 1: 36. 10.1007/s00438-024-02125-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Schmidt, J. , Rattner D. W., Lewandrowski K., et al. 1992. “A Better Model of Acute Pancreatitis for Evaluating Therapy.” Annals of Surgery 215, no. 1: 44–56. 10.1097/00000658-199201000-00007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Shen, S. P. , Lin H. C., Chen J. F., et al. 2024. “Assessment of the Safety and Gut Microbiota Modulation Ability of an Infant Formula Containing Bifidobacterium animalis Ssp. Lactis CP‐9 or Lactobacillus salivarius AP‐32 and the Effects of the Formula on Infant Growth Outcomes: Insights From a Four‐Month Clinical Study in Infants Under Two Months Old.” BMC Pediatrics 24, no. 1: 840. 10.1186/s12887-024-05289-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Shi, D. , Lv L., Fang D., et al. 2017. “Administration of Lactobacillus salivarius LI01 or Pediococcus Pentosaceus LI05 Prevents CCl4‐Induced Liver Cirrhosis by Protecting the Intestinal Barrier in Rats.” Scientific Reports 7, no. 1: 6927. 10.1038/s41598-017-07091-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Sierra, S. , Lara‐Villoslada F., Sempere L., Olivares M., Boza J., and Xaus J.. 2010. “Intestinal and Immunological Effects of Daily Oral Administration of Lactobacillus salivarius CECT5713 to Healthy Adults.” Anaerobe 16, no. 3: 195–200. 10.1016/j.anaerobe.2010.02.001. [DOI] [PubMed] [Google Scholar]
  36. Sreejit, G. , and Park C. Y.. 2024. “(Reg)ulation of Hematopoietic Lineage Fates.” Blood 143, no. 3: 188–190. 10.1182/blood.2023023000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Takauji, S. , Konishi H., Fujiya M., et al. 2021. “Polyphosphate, Derived From Lactobacillus brevis , Modulates the Intestinal Microbiome and Attenuates Acute Pancreatitis.” Digestive Diseases and Sciences 66, no. 11: 3872–3884. 10.1007/s10620-020-06747-9. [DOI] [PubMed] [Google Scholar]
  38. Trikudanathan, G. , Yazici C., Evans Phillips A., and Forsmark C. E.. 2024. “Diagnosis and Management of Acute Pancreatitis.” Gastroenterology 167, no. 4: 673–688. 10.1053/j.gastro.2024.02.052. [DOI] [PubMed] [Google Scholar]
  39. Wang, J. , Chen P., Deng Y., et al. 2025. “ Akkermansia muciniphila Alleviates Olanzapine‐Induced Hepatic Steatosis via the Gut Microbiota‐IGFBP2/APOA1‐Liver Axis.” Microbial Biotechnology 18, no. 12: e70281. 10.1111/1751-7915.70281. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Wang, L. J. , Jin Y. L., Pei W. L., et al. 2024. “Amuc_1100 Pretreatment Alleviates Acute Pancreatitis in a Mouse Model Through Regulating Gut Microbiota and Inhibiting Inflammatory Infiltration.” Acta Pharmacologica Sinica 45, no. 3: 570–580. 10.1038/s41401-023-01186-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Wei, Z. , He Z., Wang T., Wang X., Wang T., and Long M.. 2023. “ Lactobacillus salivarius WZ1 Inhibits the Inflammatory Injury of Mouse Jejunum Caused by Enterotoxigenic Escherichia coli K88 by Regulating the TLR4/NF‐κB/MyD88 Inflammatory Pathway and Gut Microbiota.” Microorganisms 11, no. 3: 657. 10.3390/microorganisms11030657. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Werawatganon, D. , Vivatvakin S., Somanawat K., et al. 2023. “Effects of Probiotics on Pancreatic Inflammation and Intestinal Integrity in Mice With Acute Pancreatitis.” BMC Complementary Medicine and Therapies 23, no. 1: 166. 10.1186/s12906-023-03998-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Williams, M. D. , and Smith L.. 2025. “Streptococcus Salivarius and Ligilactobacillus Salivarius: Paragons of Probiotic Potential and Reservoirs of Novel Antimicrobials.” Microorganisms 13, no. 3: 555. 10.3390/microorganisms13030555. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Xia, H. , Guo J., Shen J., Jiang S., Han S., and Li L.. 2023. “Ketogenic Diet Exacerbates L‐Arginine‐Induced Acute Pancreatitis and Reveals the Therapeutic Potential of Butyrate.” Nutrients 15, no. 20: 4427. 10.3390/nu15204427. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Xie, L. , Chen Y., Chen J., et al. 2019. “Anti‐Tumor Effects and Mechanism of GA‐13315, a Novel Gibberellin Derivative, in Human Lung Adenocarcinoma: An In Vitro and In Vivo Study.” Cellular & Molecular Biology Letters 24: 6. 10.1186/s11658-018-0126-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Xiong, Y. , Ji L., Zhao Y., Liu A., Wu D., and Qian J.. 2022. “Sodium Butyrate Attenuates Taurocholate‐Induced Acute Pancreatitis by Maintaining Colonic Barrier and Regulating Gut Microorganisms in Mice.” Frontiers in Physiology 13: 813735. 10.3389/fphys.2022.813735. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Xu, C. , Yue Y., and Xiong S.. 2023. “ Mycobacterium tuberculosis Rv0928 Protein Facilitates Macrophage Control of Mycobacterium Infection by Promoting Mitochondrial Intrinsic Apoptosis and ROS‐Mediated Inflammation.” Frontiers in Microbiology 14: 1291358. 10.3389/fmicb.2023.1291358. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Xu, Y. , Tan X., Yang Q., Fang Z., and Chen W.. 2024. “ Akkermansia muciniphila Outer Membrane Protein Regulates Recruitment of CD8+ T Cells in Lung Adenocarcinoma and Through JAK‐STAT Signalling Pathway.” Microbial Biotechnology 17, no. 7: e14522. 10.1111/1751-7915.14522. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Zaman, S. , and Gorelick F.. 2024. “Acute Pancreatitis: Pathogenesis and Emerging Therapies.” Journal of Pancreatology 7, no. 1: 10–20. 10.1097/jp9.0000000000000168. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Zhang, C. , Li G., Lu T., et al. 2023. “The Interaction of Microbiome and Pancreas in Acute Pancreatitis.” Biomolecules 14, no. 1: 59. 10.3390/biom14010059. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Zhang, L. , Wang K., Huang L., et al. 2025. “Ganoderic Acid A Alleviates Severe Acute Pancreatitis by Modulating Gut Homeostasis and Inhibiting TLR4‐NLRP3 Signaling.” Journal of Agricultural and Food Chemistry 73, no. 2: 1563–1579. 10.1021/acs.jafc.4c07635. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Zhang, X. M. , Zhang Z. Y., Zhang C. H., Wu J., Wang Y. X., and Zhang G. X.. 2018. “Intestinal Microbial Community Differs Between Acute Pancreatitis Patients and Healthy Volunteers.” Biomedical and Environmental Sciences 31, no. 1: 81–86. 10.3967/bes2018.010. [DOI] [PubMed] [Google Scholar]
  53. Zhou, R. , Wu Q., Yang Z., Cai Y., Wang D., and Wu D.. 2024. “The Role of the Gut Microbiome in the Development of Acute Pancreatitis.” International Journal of Molecular Sciences 25, no. 2: 1159. 10.3390/ijms25021159. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The raw sequencing reads have been deposited in the NCBI Short Read Archive (SRA) under accession number PRJNA1281822. The other datasets analyzed during the current study are available from the corresponding author upon reasonable request.

Articles from Microbial Biotechnology are provided here courtesy of Wiley

RESOURCES